diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..3753c66 --- /dev/null +++ b/.gitignore @@ -0,0 +1,30 @@ +.ipynb_checkpoints +**/species/*.png +*:Zone.Identifier +**/chemkin/* +**/seed/* +**/*.jld2 + +CO2RR_RMS/Cu/CO2RR_Cu.ipynb +CO2RR_RMS/Ag/CO2RR_RMS.ipynb +CO2RR_RMS/Ag/CO2RR_RMS_Diffusion_Interface.ipynb +CO2RR_RMS/Ag/CO2RR_RMS_3.ipynb +CO2RR_RMS/Ag/CO2RR_RMS_Diffusion_Interface_1.ipynb +CO2RR_RMS/Ag/CO2RR_RMS_2.ipynb +CO2RR_RMS/Ag/CO2RR_RMS_AIChE.ipynb +CO2RR_RMS/Ag/CO2RR_RMS_Diffusion_Interface_Matt.ipynb +CO2_Reduction_Ag/CO2RR_RMS.ipynb +CO2_Reduction_Ag/CO2RR_RMS_Diffusion_Interface.ipynb +CO2_Reduction_Ag/CO2RR_RMS_3.ipynb +CO2_Reduction_Ag/CO2RR_RMS_Diffusion_Interface_1.ipynb +CO2_Reduction_Ag/CO2RR_RMS_2.ipynb +CO2_Reduction_Ag/CO2RR_RMS_AIChE.ipynb +CO2_Reduction_Ag/CO2RR_RMS_4.ipynb +CO2_Reduction_Ag/CO2RR_RMS_Diffusion_Interface_Matt.ipynb +CO2_Reduction_Cu/CO2RR_Cu.ipynb +AIChE_2025/Plot_FE.ipynb +AIChE_2025/CO2RR_RMS_Diffusion.ipynb +CO2_Reduction_Cu3Sn/CO2RR_RMS_Diffusion_Interface_Cu3Sn.ipynb +CO2_Reduction_Ag/HER-Data/Validation/HER-Val-Data.ipynb +CO2_Reduction_Ag/HER-Data/Validation/CO2RR_RMS_Sensitivity.ipynb +setup.ipynb \ No newline at end of file diff --git a/AIChE_2025/CO2RR_RMS_Diffusion.ipynb b/AIChE_2025/CO2RR_RMS_Diffusion.ipynb deleted file mode 100644 index e1a33b0..0000000 --- a/AIChE_2025/CO2RR_RMS_Diffusion.ipynb +++ /dev/null @@ -1,1013 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 257, - "id": "8a590634", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\u001b[32m\u001b[1m Activating\u001b[22m\u001b[39m project at `~/mambaforge/envs/rmg_electrocat_2/julia_env`\n" - ] - } - ], - "source": [ - "using Pkg\n", - "Pkg.activate(ENV[\"PYTHON_JULIAPKG_PROJECT\"])\n", - "using ReactionMechanismSimulator" - ] - }, - { - "cell_type": "code", - "execution_count": 258, - "id": "82245f05", - "metadata": {}, - "outputs": [], - "source": [ - "using PythonPlot\n", - "using DifferentialEquations\n", - "using Sundials\n", - "using SciMLBase\n", - "using QuadGK\n", - "using CSV, DataFrames" - ] - }, - { - "cell_type": "code", - "execution_count": 259, - "id": "e941d4fb", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[00:33:06] WARNING: not removing hydrogen atom without neighbors\n", - "[00:33:06] WARNING: not removing hydrogen atom without neighbors\n", - "┌ Warning: failed to generate StokesDiffusivity model for species vacantX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2O2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species H2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(C[Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]COO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(=[Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC([Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C([Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH3X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [H][H].[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(C=[Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(C#[Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]=C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)([Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=[Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]C#CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]OC#CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n" - ] - }, - { - "data": { - "text/plain": [ - "Dict{Any, Any} with 4 entries:\n", - " \"Solvents\" => Solvent[Solvent(\"water\", RiedelViscosity{Float64}(…\n", - " Set([\"gas\", \"surface\"]) => Dict{Any, Any}(\"Reactions\"=>ElementaryReaction[pro…\n", - " \"gas\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…\n", - " \"surface\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "outdict = readinput(\"Ag_C2_042925.rms\")" - ] - }, - { - "cell_type": "code", - "execution_count": 260, - "id": "fe2767e9", - "metadata": {}, - "outputs": [], - "source": [ - "boundarylayerspcs = outdict[\"gas\"][\"Species\"]\n", - "boundarylayerrxns = outdict[\"gas\"][\"Reactions\"]\n", - "surfspcs = outdict[\"surface\"][\"Species\"]\n", - "surfrxns = outdict[\"surface\"][\"Reactions\"]\n", - "interfacerxns = outdict[Set([\"surface\", \"gas\"])][\"Reactions\"]\n", - "solv = outdict[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 261, - "id": "c54ee65e", - "metadata": {}, - "outputs": [], - "source": [ - "sitedensity = 2.294e-5; # Ag111 site density is 2.294e-9 mol/cm^2 or 2.294e-5 mol/m^2\n", - "boundarylayer = IdealDiluteSolution(boundarylayerspcs,boundarylayerrxns,solv,name=\"boundarylayeruid\",diffusionlimited=true);\n", - "surf = IdealSurface(surfspcs,surfrxns,sitedensity,name=\"surface\");" - ] - }, - { - "cell_type": "code", - "execution_count": 262, - "id": "138a067e", - "metadata": {}, - "outputs": [], - "source": [ - "phi = -(1.37 + 0.414);" - ] - }, - { - "cell_type": "code", - "execution_count": 263, - "id": "8894c84d", - "metadata": {}, - "outputs": [], - "source": [ - "# Reservoir is a 100 mL (100e-6 m^3) cell\n", - "# Proton concentration is 10^-7 mol/L (10^-4 mol/m^3)\n", - "# CO2 concentration is 0.01 mol/L (10 mol/m^3), saturation solubility ~0.03 mol/L\n", - "# AVratio in experiments is 36 m^-1 but is measured by surface area/reservoir volume\n", - "# Area of the electrode is therefore 3.6e1 m^-1 * 1e2 * 1e-6 m^3 = 3.6e-3 m^2 = 36 cm^2\n", - "# Assume boundary layer thickness d_bl = 1 mm or 1e-3 m\n", - "# Volume of the boundary layer V_bl = 3.6e-3 m^2 * 1e-3 m = 3.6e-6 m^3\n", - "# Actual AVratio is therefore 3.6e-3 m^2 / 3.6e-6 m^3 = 1e3 m^-1 (reciprocal of d_bl)\n", - "# Amount of sites is 2.943e-5 mol/m^2 * 3.6e-3 m^2 = 10.595e-8 mol\n", - "\n", - "# For earlier simulations, a 100x linear scale factor is applied,\n", - "# so volume becomes 100e-6 m^3 * (1e2)^3 = 100 m^3,\n", - "# electrode area becomes 3.6e-3 * (1e2) ^2 = 3.6e1 m^2,\n", - "# AVratio becomes 3.6e1 m^2 / 1e2 m^3 = 0.36 m^-1\n", - "# Volume of the boundary layer becomes 3.6e1 m^2 * 1e-3 m = 3.6e-2 m^3\n", - "\n", - "C_proton = 1e-7*1e3;\n", - "C_co2 = 1e-2*1e3;\n", - "C_default = 1e-12;\n", - "V_res = 1e3;\n", - "layer_thickness = 1e-5;\n", - "AVratio = 36;\n", - "A_surf = V_res*AVratio;\n", - "V_bl = A_surf*layer_thickness;\n", - "# V_bl = V_res;\n", - "sites = sitedensity*A_surf;\n", - "\n", - "# The initial conditions for individual species are moles not concentration, so we need to multiply concentration by boundary layer volume\n", - "initialcondsboundarylayer = Dict([\"proton\"=>C_proton*V_bl,\n", - " \"CO2\"=>C_co2*V_bl,\n", - " # \"H2\"=>C_default*10*V_bl,\n", - " # \"O=CO\"=>C_default*V_bl,\n", - " \"V\"=>V_bl,\"T\"=>300,\"Phi\"=>0.0,\"d\"=>0.0]);\n", - "initialcondsreservoir = Dict([\"proton\"=>C_proton,\n", - " \"CO2\"=>C_co2,\n", - " \"V\"=>V_res,\"T\"=>300]);\n", - "\n", - "\n", - "# Assume voltage is -1.0 V vs. R.H.E. which equates to -1.414 V vs. S.H.E. at pH=7\n", - "initialcondssurf = Dict([\"CO2X\"=>0.4*sites,\n", - " # \"CHO2X\"=>0.1*sites,\n", - " # \"CO2HX\"=>0.1*sites,\n", - " # \"OX\"=>0.1*sites,\n", - " # \"OCX\"=>0.1*sites,\n", - " \"vacantX\"=>0.6*sites,\n", - " # \"CH2O2X\"=>0.05*sites,\n", - " # \"CHOX\"=>0.04*sites,\n", - " # \"CH2OX\"=>0.01*sites,\n", - " \"A\"=>A_surf,\"T\"=>300,\"Phi\"=>phi]);" - ] - }, - { - "cell_type": "code", - "execution_count": 264, - "id": "ddb39b3d", - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "domainboundarylayer, y0boundarylayer, pboundarylayer = ConstantTVDomain(phase=boundarylayer, initialconds=initialcondsboundarylayer);\n", - "domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf,\n", - " initialconds=initialcondssurf);" - ] - }, - { - "cell_type": "code", - "execution_count": 265, - "id": "d3aaf802", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "9.32e-9" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Set proton diffusivity to a higher value than calculated from Stokes Einstein equation\n", - "# The values are taken from DOI: 10.1039/C8SC01253A\n", - "# Values calculated from MD is 1.015 A^2/ps, experimental values are 0.932 A^2/ps.\n", - "# 1 A^2/ps = 1e-8 m^2/s\n", - "domainboundarylayer.diffusivity[6] = 0.932e-8" - ] - }, - { - "cell_type": "code", - "execution_count": 266, - "id": "ed49d2b4", - "metadata": {}, - "outputs": [], - "source": [ - "inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainboundarylayer,\n", - " domaincat,interfacerxns,298.15,A_surf);" - ] - }, - { - "cell_type": "code", - "execution_count": 267, - "id": "dee14906", - "metadata": {}, - "outputs": [], - "source": [ - "# start with 1mm layer thickness\n", - "diffusionlayer = ConstantReservoirDiffusion(domainboundarylayer, initialcondsreservoir, A_surf, layer_thickness);" - ] - }, - { - "cell_type": "code", - "execution_count": 268, - "id": "e70ac4b0", - "metadata": {}, - "outputs": [], - "source": [ - "interfaces = [inter, diffusionlayer];" - ] - }, - { - "cell_type": "code", - "execution_count": 269, - "id": "244f0912", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.003601 seconds (8.47 k allocations: 7.894 MiB)\n" - ] - } - ], - "source": [ - "@time react,y0,p = Reactor((domainboundarylayer,domaincat), (y0boundarylayer,y0cat), (0.0, 1.8e3), interfaces, (pboundarylayer,pcat,pinter));" - ] - }, - { - "cell_type": "code", - "execution_count": 270, - "id": "962f838c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.211123 seconds (487.07 k allocations: 364.304 MiB, 6.12% gc time)\n", - "1800.0\n", - "Success\n" - ] - } - ], - "source": [ - "@time sol = solve(react.ode,Sundials.CVODE_BDF(),abstol=1e-22,reltol=1e-8);\n", - "println(sol.t[end]);\n", - "println(sol.retcode);" - ] - }, - { - "cell_type": "code", - "execution_count": 271, - "id": "6667bb5a", - "metadata": {}, - "outputs": [], - "source": [ - "ssys = SystemSimulation(sol,(domainboundarylayer,domaincat,), interfaces,p);" - ] - }, - { - "cell_type": "code", - "execution_count": 272, - "id": "d4939a87", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "get_reservoir_concentration" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "\"\"\"\n", - "diffusive flux to the reservoir\n", - "\"\"\"\n", - "function flux_to_reservoir(sim,t,reservoirinterface)\n", - " cs = concentrations(sim,t)\n", - " return reservoirinterface.A .* sim.domain.diffusivity .* (cs - reservoirinterface.c) / reservoirinterface.layer_thickness\n", - "end\n", - "\n", - "\"\"\"\n", - "Integrates the flux to the reservoir and computes the concentration assuming\n", - "there is no prior concentration of that species in the reservoir\n", - "\"\"\"\n", - "function get_reservoir_concentration(sim,t,reservoirinterface,Vres,C0)\n", - " intg,err = quadgk(x -> flux_to_reservoir(sim,x,reservoirinterface), 0, t);\n", - " intg[5] = 0;\n", - " intg[6] = 0;\n", - " return C0 + intg./Vres\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 273, - "id": "411d79d6", - "metadata": {}, - "outputs": [], - "source": [ - "# Logarithmic time scale\n", - "t_vals = 10 .^ range(-12, stop=3, length=160);\n", - "\n", - "# Compute reservoir concentrations\n", - "flux_vals = [flux_to_reservoir(ssys.sims[1], t, diffusionlayer) for t in t_vals]\n", - "\n", - "conc_vals_bl = [concentrations(ssys.sims[1], t) for t in t_vals]\n", - "flux_matrix = hcat(flux_vals...);\n", - "conc_matrix_bl = hcat(conc_vals_bl...);\n" - ] - }, - { - "cell_type": "code", - "execution_count": 274, - "id": "1b8bc2d2", - "metadata": {}, - "outputs": [], - "source": [ - "conc_0 = concentrations(ssys.sims[1], 0)\n", - "t_vals_2 = 10 .^ range(-9, stop=3, length=130);\n", - "conc_vals = [get_reservoir_concentration(ssys.sims[1], t, diffusionlayer, V_res, conc_0) for t in t_vals_2]\n", - "conc_matrix = hcat(conc_vals...);" - ] - }, - { - "cell_type": "code", - "execution_count": 275, - "id": "543fe758", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotC_Reservoir (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "function plotC_Reservoir(sim, cs, tvals, tol, exclude)\n", - " clf()\n", - " xs = cs\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " time_filtered = tvals\n", - " xs_filtered = xs\n", - "\n", - " # Custom species order and their corresponding names and color\n", - " species_order = [\"CO2\", \"proton\", \"H2\", \"O=CO\", \"C=O\", \"CO-2\", \"CCO\", \"CH4\", \"OCO\", \"COC\", \"COCO\", \"CC(=O)O\", \"OCCO\"]\n", - " color_map = Dict(\"CO2\" => \"black\", \"proton\" => \"grey\", \"H2\" => \"green\",\n", - " \"O=CO\" => \"red\", \"C=O\" => \"brown\", \"CO-2\" => \"blue\", \"CCO\" => \"magenta\",\n", - " \"CH4\" => \"brown\", \"OCO\" => \"orange\", \"COC\" => \"teal\", \"COCO\" => \"lime\", \"CC(=O)O\" => \"teal\", \"OCCO\" => \"lime\")\n", - " # Replacement map for species labels\n", - " replacement_map = Dict(\"CO-2\" => \"CH3OH\", \"O=CO\" => \"HCOOH\", \"C=O\" => \"HCHO\",\n", - " \"CCO\" => \"C2H5OH\", \"OCO\" => \"CH2(OH)2\", \"COC\" => \"CH3OCH3\", \"COCO\" => \"CH3OCH2OH\", \"CC(=O)O\" => \"CH3COOH\", \"OCCO\" => \"OHCH2CH2OH\")\n", - "\n", - " # Build a map of species names to indices\n", - " name_to_index = Dict(sim.domain.phase.species[i].name => i for i in 1:length(sim.domain.phase.species))\n", - " # Keep track of whether the species is plotted, used for later checks\n", - " plotted = falses(length(sim.domain.phase.species))\n", - "\n", - " # Plot species from the custom species dictionary\n", - " for species_name in species_order\n", - " if species_name in exclude\n", - " continue\n", - " end\n", - "\n", - " if haskey(name_to_index, species_name)\n", - " i = name_to_index[species_name]\n", - "\n", - " if (maxes[i] > tol) || (species_name == \"proton\") || (species_name == \"CCO\") # Always plot proton and ethanol\n", - " plot_label = get(replacement_map, species_name, species_name)\n", - " plot_color = color_map[species_name]\n", - "\n", - " plot(time_filtered, xs_filtered[i, :]/1000, label=plot_label, color=plot_color)\n", - " plotted[i] = true # Mark as plotted\n", - " end\n", - " end\n", - " end\n", - "\n", - " # Plot any remaining species that passed tolerance but were not in species_order\n", - " for i in 1:length(sim.domain.phase.species)\n", - " if plotted[i] || sim.domain.phase.species[i].name in exclude\n", - " continue\n", - " end\n", - "\n", - " if maxes[i] > tol\n", - " species_name = sim.domain.phase.species[i].name\n", - " plot(time_filtered, xs_filtered[i, :]/1000, label=species_name) # Default color\n", - " end\n", - " end\n", - "\n", - " xlabel(\"Time (s)\", fontsize=14)\n", - " ylabel(\"Bulk Concentration (mol/L)\", fontsize=14)\n", - " xticks(fontsize=14)\n", - " yticks(fontsize=14)\n", - " legend(loc=\"upper left\", bbox_to_anchor=(0, 0.9), fontsize=12, ncol=2)\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 276, - "id": "1a6e5f63", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "export_final_molefractions! (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "function export_final_molefractions!(conc_matrix, ssys, phi; filename=\"final_molefractions.csv\")\n", - " # species of interest\n", - " species_list = [\"O=CO\", \"H2\", \"CO\", \"CO-2\", \"C=O\", \"CC(=O)O\"]\n", - "\n", - " # map species name → index\n", - " name_to_index = Dict(ssys.sims[1].domain.phase.species[i].name => i\n", - " for i in 1:length(ssys.sims[1].domain.phase.species))\n", - "\n", - " # extract final concentrations and normalize\n", - " final_concs = [conc_matrix[name_to_index[sp], end] for sp in species_list]\n", - " molefracs = final_concs ./ sum(final_concs)\n", - "\n", - " phi_label = round(phi + 0.414; digits=2);\n", - " col_name = string(phi_label)\n", - "\n", - " # create or update CSV\n", - " if isfile(filename)\n", - " df = CSV.read(filename, DataFrame)\n", - " else\n", - " df = DataFrame(Species = species_list)\n", - " end\n", - "\n", - " # insert or update the new column labeled by φ\n", - " df[!, col_name] = molefracs;\n", - "\n", - " CSV.write(filename, df)\n", - " println(\"✅ Appended mole fractions for φ = $(phi) V to $(filename)\")\n", - " return df\n", - "end\n" - ] - }, - { - "cell_type": "code", - "execution_count": 277, - "id": "9078fcd8", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "✅ Appended mole fractions for φ = -1.784 V to final_molefractions.csv\n" - ] - }, - { - "data": { - "text/html": [ - "
6×5 DataFrame
RowSpecies-0.77-0.97-1.17-1.37
String7Float64Float64Float64Float64
1O=CO0.9927790.9497980.3042640.00858474
2H20.0001560930.03682660.6941850.991415
3CO6.64579e-195.57168e-191.81049e-191.39735e-21
4CO-21.55232e-71.38659e-50.0002328471.86322e-7
5C=O0.007018820.01270020.00129452.93285e-7
6CC(=O)O4.58797e-50.0006612082.38637e-51.49172e-10
" - ], - "text/latex": [ - "\\begin{tabular}{r|ccccc}\n", - "\t& Species & -0.77 & -0.97 & -1.17 & -1.37\\\\\n", - "\t\\hline\n", - "\t& String7 & Float64 & Float64 & Float64 & Float64\\\\\n", - "\t\\hline\n", - "\t1 & O=CO & 0.992779 & 0.949798 & 0.304264 & 0.00858474 \\\\\n", - "\t2 & H2 & 0.000156093 & 0.0368266 & 0.694185 & 0.991415 \\\\\n", - "\t3 & CO & 6.64579e-19 & 5.57168e-19 & 1.81049e-19 & 1.39735e-21 \\\\\n", - "\t4 & CO-2 & 1.55232e-7 & 1.38659e-5 & 0.000232847 & 1.86322e-7 \\\\\n", - "\t5 & C=O & 0.00701882 & 0.0127002 & 0.0012945 & 2.93285e-7 \\\\\n", - "\t6 & CC(=O)O & 4.58797e-5 & 0.000661208 & 2.38637e-5 & 1.49172e-10 \\\\\n", - "\\end{tabular}\n" - ], - "text/plain": [ - "\u001b[1m6×5 DataFrame\u001b[0m\n", - "\u001b[1m Row \u001b[0m│\u001b[1m Species \u001b[0m\u001b[1m -0.77 \u001b[0m\u001b[1m -0.97 \u001b[0m\u001b[1m -1.17 \u001b[0m\u001b[1m -1.37 \u001b[0m\n", - "\u001b[1m \u001b[0m│\u001b[90m String7 \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m Float64 \u001b[0m\n", - "─────┼─────────────────────────────────────────────────────────────\n", - " 1 │ O=CO 0.992779 0.949798 0.304264 0.00858474\n", - " 2 │ H2 0.000156093 0.0368266 0.694185 0.991415\n", - " 3 │ CO 6.64579e-19 5.57168e-19 1.81049e-19 1.39735e-21\n", - " 4 │ CO-2 1.55232e-7 1.38659e-5 0.000232847 1.86322e-7\n", - " 5 │ C=O 0.00701882 0.0127002 0.0012945 2.93285e-7\n", - " 6 │ CC(=O)O 4.58797e-5 0.000661208 2.38637e-5 1.49172e-10" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "export_final_molefractions!(conc_matrix, ssys, phi)" - ] - }, - { - "cell_type": "code", - "execution_count": 278, - "id": "d68e0335", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotC_Reservoir(ssys.sims[1], conc_matrix, t_vals_2, 1e-8, exclude_species)\n", - "\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-3, 1e3)\n", - "ylim(1e-18, 1e-1)\n", - "legend(loc=\"upper left\", bbox_to_anchor=(0, 0.9), fontsize=12, ncol=2)\n", - "title(\"Ag111@-1.0V vs. R.H.E., d = 1 mm\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 279, - "id": "53cf7fe2", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "clf()\n", - "\n", - "for i in 1:size(flux_matrix, 1)\n", - " if maximum(abs.(flux_matrix[i, :])) > 1e-10\n", - " plot(t_vals, abs.(flux_matrix[i, :]), label=ssys.sims[1].domain.phase.species[i].name)\n", - "\n", - " end\n", - "end\n", - "\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlabel(\"Time (s)\")\n", - "ylabel(\"Diffusive Flux (mol/s)\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-9, 1e1)\n", - "legend()\n", - "tight_layout()\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 280, - "id": "a88347b2", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "clf()\n", - "for i in 1:size(conc_matrix_bl, 1)\n", - " if maximum(conc_matrix_bl[i, :]) > 1e-10\n", - " plot(t_vals, conc_matrix_bl[i, :]/1e3, label=ssys.sims[1].domain.phase.species[i].name)\n", - "\n", - " end\n", - "end\n", - "\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlabel(\"Time (s)\")\n", - "ylabel(\"Boundary Layer Concentrations (mol/L)\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-18, 1)\n", - "legend()\n", - "tight_layout()\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 281, - "id": "87dcaf99", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotX (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotX(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = molefractions(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time (s)\")\n", - " ylabel(\"Concentration (mol/m^3)\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 282, - "id": "ddf6da6b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotC (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "function plotC(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = concentrations(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " # Custom species order and their corresponding names and color\n", - " species_order = [\"CO2\", \"proton\", \"H2\", \"O=CO\", \"C=O\", \"CO-2\", \"CCO\", \"CH4\", \"OCO\", \"COC\", \"COCO\", \"CC(=O)O\", \"COC=O\"]\n", - " color_map = Dict(\"CO2\" => \"black\", \"proton\" => \"grey\", \"H2\" => \"green\",\n", - " \"O=CO\" => \"red\", \"C=O\" => \"brown\", \"CO-2\" => \"blue\", \"CCO\" => \"magenta\",\n", - " \"CH4\" => \"brown\", \"OCO\" => \"orange\", \"COC\" => \"teal\", \"COCO\" => \"lime\", \"CC(=O)O\" => \"teal\", \"COC=O\" => \"lime\")\n", - " # Replacement map for species labels\n", - " replacement_map = Dict(\"CO-2\" => \"CH3OH\", \"O=CO\" => \"HCOOH\", \"C=O\" => \"HCHO\",\n", - " \"CCO\" => \"C2H5OH\", \"OCO\" => \"CH2(OH)2\", \"COC\" => \"CH3OCH3\", \"COCO\" => \"CH3OCH2OH\", \"CC(=O)O\" => \"CH3COOH\", \"COC=O\" => \"CH3OCHO\")\n", - "\n", - " # Build a map of species names to indices\n", - " name_to_index = Dict(sim.domain.phase.species[i].name => i for i in 1:length(sim.domain.phase.species))\n", - " # Keep track of whether the species is plotted, used for later checks\n", - " plotted = falses(length(sim.domain.phase.species))\n", - "\n", - " # Plot species from the custom species dictionary\n", - " for species_name in species_order\n", - " if species_name in exclude\n", - " continue\n", - " end\n", - "\n", - " if haskey(name_to_index, species_name)\n", - " i = name_to_index[species_name]\n", - "\n", - " if (maxes[i] > tol) || (species_name == \"proton\") || (species_name == \"CCO\") # Always plot proton and ethanol\n", - " plot_label = get(replacement_map, species_name, species_name)\n", - " plot_color = color_map[species_name]\n", - "\n", - " plot(time_filtered, xs_filtered[i, :]/1000, label=plot_label, color=plot_color)\n", - " plotted[i] = true # Mark as plotted\n", - " end\n", - " end\n", - " end\n", - "\n", - " # Plot any remaining species that passed tolerance but were not in species_order\n", - " for i in 1:length(sim.domain.phase.species)\n", - " if plotted[i] || sim.domain.phase.species[i].name in exclude\n", - " continue\n", - " end\n", - "\n", - " if maxes[i] > tol\n", - " species_name = sim.domain.phase.species[i].name\n", - " plot(time_filtered, xs_filtered[i, :]/1000, label=species_name) # Default color\n", - " end\n", - " end\n", - "\n", - " xlabel(\"Time (s)\", fontsize=14)\n", - " ylabel(\"Boundary Layer Concentration (mol/L)\", fontsize=14)\n", - " xticks(fontsize=14)\n", - " yticks(fontsize=14)\n", - " legend(loc=\"upper left\", bbox_to_anchor=(0, 0.9), fontsize=12, ncol=2)\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 283, - "id": "e719a85d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys.sims[1], 1e-12, 1.8e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-8, 2e3)\n", - "ylim(1e-16, 5)\n", - "title(\"Liquid-phase Mole Fractions vs. Time on Ag111@-1.0V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 284, - "id": "1ef78267", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotC(ssys.sims[1], 1e-8, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-20, 1e-1)\n", - "title(\"Cu111@-1.0V vs. R.H.E., d = 1 mm\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 285, - "id": "a1e338ce", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys.sims[2], 1e-3, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-6, 5)\n", - "title(\"Surface Mole Fractions vs. Time on Ag111@-1.0V\")\n", - "gcf()" - ] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.10.10", - "language": "julia", - "name": "julia-1.10" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.10.10" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/AIChE_2025/CO2RR_RMS_Diffusion.jl b/AIChE_2025/CO2RR_RMS_Diffusion.jl new file mode 100644 index 0000000..3465eab --- /dev/null +++ b/AIChE_2025/CO2RR_RMS_Diffusion.jl @@ -0,0 +1,441 @@ +# -*- coding: utf-8 -*- +# --- +# jupyter: +# jupytext: +# formats: ipynb,jl:percent +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.17.3 +# kernelspec: +# display_name: Julia 1.10.9 +# language: julia +# name: julia-1.10 +# --- + +# %% [markdown] +# # Simulation with Diffusion Layer +# + +# %% +using Pkg +Pkg.activate(joinpath(@__DIR__, "..")) + +# %% +using PythonPlot +using DifferentialEquations +using Sundials +using SciMLBase +using QuadGK +using CSV, DataFrames + +# %% +using ReactionMechanismSimulator + +# %% +outdict = readinput("Cu_C2_042925.rms") + +# %% +boundarylayerspcs = outdict["gas"]["Species"] +boundarylayerrxns = outdict["gas"]["Reactions"] +surfspcs = outdict["surface"]["Species"] +surfrxns = outdict["surface"]["Reactions"] +interfacerxns = outdict[Set(["surface", "gas"])]["Reactions"] +solv = outdict["Solvents"][1]; + +# %% +sitedensity = 2.294e-5; # Ag111 site density is 2.294e-9 mol/cm^2 or 2.294e-5 mol/m^2 +boundarylayer = IdealDiluteSolution(boundarylayerspcs,boundarylayerrxns,solv,name="boundarylayeruid",diffusionlimited=true); +surf = IdealSurface(surfspcs,surfrxns,sitedensity,name="surface"); + +# %% +phi = -(1.37 + 0.414); + +# %% +# Reservoir is a 100 mL (100e-6 m^3) cell +# Proton concentration is 10^-7 mol/L (10^-4 mol/m^3) +# CO2 concentration is 0.01 mol/L (10 mol/m^3), saturation solubility ~0.03 mol/L +# AVratio in experiments is 36 m^-1 but is measured by surface area/reservoir volume +# Area of the electrode is therefore 3.6e1 m^-1 * 1e2 * 1e-6 m^3 = 3.6e-3 m^2 = 36 cm^2 +# Assume boundary layer thickness d_bl = 1 mm or 1e-3 m +# Volume of the boundary layer V_bl = 3.6e-3 m^2 * 1e-3 m = 3.6e-6 m^3 +# Actual AVratio is therefore 3.6e-3 m^2 / 3.6e-6 m^3 = 1e3 m^-1 (reciprocal of d_bl) +# Amount of sites is 2.943e-5 mol/m^2 * 3.6e-3 m^2 = 10.595e-8 mol + +# For earlier simulations, a 100x linear scale factor is applied, +# so volume becomes 100e-6 m^3 * (1e2)^3 = 100 m^3, +# electrode area becomes 3.6e-3 * (1e2) ^2 = 3.6e1 m^2, +# AVratio becomes 3.6e1 m^2 / 1e2 m^3 = 0.36 m^-1 +# Volume of the boundary layer becomes 3.6e1 m^2 * 1e-3 m = 3.6e-2 m^3 + +C_proton = 1e-7*1e3; +C_co2 = 1e-2*1e3; +C_default = 1e-12; +V_res = 1e3; +layer_thickness = 1e-5; +AVratio = 36; +A_surf = V_res*AVratio; +V_bl = A_surf*layer_thickness; +# V_bl = V_res; +sites = sitedensity*A_surf; + +# The initial conditions for individual species are moles not concentration, so we need to multiply concentration by boundary layer volume +initialcondsboundarylayer = Dict(["proton"=>C_proton*V_bl, + "CO2"=>C_co2*V_bl, + # "H2"=>C_default*10*V_bl, + # "O=CO"=>C_default*V_bl, + "V"=>V_bl,"T"=>300,"Phi"=>0.0,"d"=>0.0]); +initialcondsreservoir = Dict(["proton"=>C_proton, + "CO2"=>C_co2, + "V"=>V_res,"T"=>300]); + + +# Assume voltage is -1.0 V vs. R.H.E. which equates to -1.414 V vs. S.H.E. at pH=7 +initialcondssurf = Dict(["CO2X"=>0.4*sites, + # "CHO2X"=>0.1*sites, + # "CO2HX"=>0.1*sites, + # "OX"=>0.1*sites, + # "OCX"=>0.1*sites, + "vacantX"=>0.6*sites, + # "CH2O2X"=>0.05*sites, + # "CHOX"=>0.04*sites, + # "CH2OX"=>0.01*sites, + "A"=>A_surf,"T"=>300,"Phi"=>phi]); + +# %% +domainboundarylayer, y0boundarylayer, pboundarylayer = ConstantTVDomain(phase=boundarylayer, initialconds=initialcondsboundarylayer); +domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf, + initialconds=initialcondssurf); + +# %% +# Set proton diffusivity to a higher value than calculated from Stokes Einstein equation +# The values are taken from DOI: 10.1039/C8SC01253A +# Values calculated from MD is 1.015 A^2/ps, experimental values are 0.932 A^2/ps. +# 1 A^2/ps = 1e-8 m^2/s +domainboundarylayer.diffusivity[6] = 0.932e-8 + +# %% +inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainboundarylayer, + domaincat,interfacerxns,298.15,A_surf); + +# %% +# start with 1mm layer thickness +diffusionlayer = ConstantReservoirDiffusion(domainboundarylayer, initialcondsreservoir, A_surf, layer_thickness); + +# %% +interfaces = [inter, diffusionlayer]; + +# %% +@time react,y0,p = Reactor((domainboundarylayer,domaincat), (y0boundarylayer,y0cat), (0.0, 1.8e3), interfaces, (pboundarylayer,pcat,pinter)); + +# %% +@time sol = solve(react.ode,Sundials.CVODE_BDF(),abstol=1e-22,reltol=1e-8); +println(sol.t[end]); +println(sol.retcode); + +# %% +ssys = SystemSimulation(sol,(domainboundarylayer,domaincat,), interfaces,p); + +# %% +""" +diffusive flux to the reservoir +""" +function flux_to_reservoir(sim,t,reservoirinterface) + cs = concentrations(sim,t) + return reservoirinterface.A .* sim.domain.diffusivity .* (cs - reservoirinterface.c) / reservoirinterface.layer_thickness +end + +""" +Integrates the flux to the reservoir and computes the concentration assuming +there is no prior concentration of that species in the reservoir +""" +function get_reservoir_concentration(sim,t,reservoirinterface,Vres,C0) + intg,err = quadgk(x -> flux_to_reservoir(sim,x,reservoirinterface), 0, t); + intg[5] = 0; + intg[6] = 0; + return C0 + intg./Vres +end + +# %% +# Logarithmic time scale +t_vals = 10 .^ range(-12, stop=3, length=160); + +# Compute reservoir concentrations +flux_vals = [flux_to_reservoir(ssys.sims[1], t, diffusionlayer) for t in t_vals] + +conc_vals_bl = [concentrations(ssys.sims[1], t) for t in t_vals] +flux_matrix = hcat(flux_vals...); +conc_matrix_bl = hcat(conc_vals_bl...); + + +# %% +conc_0 = concentrations(ssys.sims[1], 0) +t_vals_2 = 10 .^ range(-9, stop=3, length=130); +conc_vals = [get_reservoir_concentration(ssys.sims[1], t, diffusionlayer, V_res, conc_0) for t in t_vals_2] +conc_matrix = hcat(conc_vals...); + +# %% +function plotC_Reservoir(sim, cs, tvals, tol, exclude) + clf() + xs = cs + maxes = maximum(xs, dims=2) + + time_filtered = tvals + xs_filtered = xs + + # Custom species order and their corresponding names and color + species_order = ["CO2", "proton", "H2", "O=CO", "C=O", "CO-2", "CCO", "CH4", "OCO", "COC", "COCO", "CC(=O)O", "OCCO"] + color_map = Dict("CO2" => "black", "proton" => "grey", "H2" => "green", + "O=CO" => "red", "C=O" => "brown", "CO-2" => "blue", "CCO" => "magenta", + "CH4" => "brown", "OCO" => "orange", "COC" => "teal", "COCO" => "lime", "CC(=O)O" => "teal", "OCCO" => "lime") + # Replacement map for species labels + replacement_map = Dict("CO-2" => "CH3OH", "O=CO" => "HCOOH", "C=O" => "HCHO", + "CCO" => "C2H5OH", "OCO" => "CH2(OH)2", "COC" => "CH3OCH3", "COCO" => "CH3OCH2OH", "CC(=O)O" => "CH3COOH", "OCCO" => "OHCH2CH2OH") + + # Build a map of species names to indices + name_to_index = Dict(sim.domain.phase.species[i].name => i for i in 1:length(sim.domain.phase.species)) + # Keep track of whether the species is plotted, used for later checks + plotted = falses(length(sim.domain.phase.species)) + + # Plot species from the custom species dictionary + for species_name in species_order + if species_name in exclude + continue + end + + if haskey(name_to_index, species_name) + i = name_to_index[species_name] + + if (maxes[i] > tol) || (species_name == "proton") || (species_name == "CCO") # Always plot proton and ethanol + plot_label = get(replacement_map, species_name, species_name) + plot_color = color_map[species_name] + + plot(time_filtered, xs_filtered[i, :]/1000, label=plot_label, color=plot_color) + plotted[i] = true # Mark as plotted + end + end + end + + # Plot any remaining species that passed tolerance but were not in species_order + for i in 1:length(sim.domain.phase.species) + if plotted[i] || sim.domain.phase.species[i].name in exclude + continue + end + + if maxes[i] > tol + species_name = sim.domain.phase.species[i].name + plot(time_filtered, xs_filtered[i, :]/1000, label=species_name) # Default color + end + end + + xlabel("Time (s)", fontsize=14) + ylabel("Bulk Concentration (mol/L)", fontsize=14) + xticks(fontsize=14) + yticks(fontsize=14) + legend(loc="upper left", bbox_to_anchor=(0, 0.9), fontsize=12, ncol=2) +end + +# %% +function export_final_molefractions!(conc_matrix, ssys, phi; filename="final_molefractions.csv") + # species of interest + species_list = ["O=CO", "H2", "CO", "CO-2", "C=O", "CC(=O)O"] + + # map species name → index + name_to_index = Dict(ssys.sims[1].domain.phase.species[i].name => i + for i in 1:length(ssys.sims[1].domain.phase.species)) + + # extract final concentrations and normalize + final_concs = [conc_matrix[name_to_index[sp], end] for sp in species_list] + molefracs = final_concs ./ sum(final_concs) + + phi_label = round(phi + 0.414; digits=2); + col_name = string(phi_label) + + # create or update CSV + if isfile(filename) + df = CSV.read(filename, DataFrame) + else + df = DataFrame(Species = species_list) + end + + # insert or update the new column labeled by φ + df[!, col_name] = molefracs; + + CSV.write(filename, df) + println("✅ Appended mole fractions for φ = $(phi) V to $(filename)") + return df +end + + +# %% +export_final_molefractions!(conc_matrix, ssys, phi) + +# %% +exclude_species = ["H2O"] +plotC_Reservoir(ssys.sims[1], conc_matrix, t_vals_2, 1e-8, exclude_species) + +xscale("log") +yscale("log") +xlim(1e-3, 1e3) +ylim(1e-18, 1e-1) +legend(loc="upper left", bbox_to_anchor=(0, 0.9), fontsize=12, ncol=2) +title("Ag111@-1.0V vs. R.H.E., d = 1 mm") +gcf() + +# %% +clf() + +for i in 1:size(flux_matrix, 1) + if maximum(abs.(flux_matrix[i, :])) > 1e-10 + plot(t_vals, abs.(flux_matrix[i, :]), label=ssys.sims[1].domain.phase.species[i].name) + + end +end + +xscale("log") +yscale("log") +xlabel("Time (s)") +ylabel("Diffusive Flux (mol/s)") +xlim(1e-12, 1e3) +ylim(1e-9, 1e1) +legend() +tight_layout() +gcf() + +# %% +clf() +for i in 1:size(conc_matrix_bl, 1) + if maximum(conc_matrix_bl[i, :]) > 1e-10 + plot(t_vals, conc_matrix_bl[i, :]/1e3, label=ssys.sims[1].domain.phase.species[i].name) + + end +end + +xscale("log") +yscale("log") +xlabel("Time (s)") +ylabel("Boundary Layer Concentrations (mol/L)") +xlim(1e-12, 1e3) +ylim(1e-18, 1) +legend() +tight_layout() +gcf() + +# %% +# Helper function +function plotX(sim, tol, t_end, exclude) + clf() + xs = molefractions(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time (s)") + ylabel("Concentration (mol/m^3)") +end + +# %% +function plotC(sim, tol, t_end, exclude) + clf() + xs = concentrations(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + # Custom species order and their corresponding names and color + species_order = ["CO2", "proton", "H2", "O=CO", "C=O", "CO-2", "CCO", "CH4", "OCO", "COC", "COCO", "CC(=O)O", "COC=O"] + color_map = Dict("CO2" => "black", "proton" => "grey", "H2" => "green", + "O=CO" => "red", "C=O" => "brown", "CO-2" => "blue", "CCO" => "magenta", + "CH4" => "brown", "OCO" => "orange", "COC" => "teal", "COCO" => "lime", "CC(=O)O" => "teal", "COC=O" => "lime") + # Replacement map for species labels + replacement_map = Dict("CO-2" => "CH3OH", "O=CO" => "HCOOH", "C=O" => "HCHO", + "CCO" => "C2H5OH", "OCO" => "CH2(OH)2", "COC" => "CH3OCH3", "COCO" => "CH3OCH2OH", "CC(=O)O" => "CH3COOH", "COC=O" => "CH3OCHO") + + # Build a map of species names to indices + name_to_index = Dict(sim.domain.phase.species[i].name => i for i in 1:length(sim.domain.phase.species)) + # Keep track of whether the species is plotted, used for later checks + plotted = falses(length(sim.domain.phase.species)) + + # Plot species from the custom species dictionary + for species_name in species_order + if species_name in exclude + continue + end + + if haskey(name_to_index, species_name) + i = name_to_index[species_name] + + if (maxes[i] > tol) || (species_name == "proton") || (species_name == "CCO") # Always plot proton and ethanol + plot_label = get(replacement_map, species_name, species_name) + plot_color = color_map[species_name] + + plot(time_filtered, xs_filtered[i, :]/1000, label=plot_label, color=plot_color) + plotted[i] = true # Mark as plotted + end + end + end + + # Plot any remaining species that passed tolerance but were not in species_order + for i in 1:length(sim.domain.phase.species) + if plotted[i] || sim.domain.phase.species[i].name in exclude + continue + end + + if maxes[i] > tol + species_name = sim.domain.phase.species[i].name + plot(time_filtered, xs_filtered[i, :]/1000, label=species_name) # Default color + end + end + + xlabel("Time (s)", fontsize=14) + ylabel("Boundary Layer Concentration (mol/L)", fontsize=14) + xticks(fontsize=14) + yticks(fontsize=14) + legend(loc="upper left", bbox_to_anchor=(0, 0.9), fontsize=12, ncol=2) +end + +# %% +exclude_species = ["H2O"] +plotX(ssys.sims[1], 1e-12, 1.8e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-8, 2e3) +ylim(1e-16, 5) +title("Liquid-phase Mole Fractions vs. Time on Ag111@-1.0V") +gcf() + +# %% +exclude_species = ["H2O"] +plotC(ssys.sims[1], 1e-8, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e3) +ylim(1e-20, 1e-1) +title("Cu111@-1.0V vs. R.H.E., d = 1 mm") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys.sims[2], 1e-3, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e3) +ylim(1e-6, 5) +title("Surface Mole Fractions vs. Time on Ag111@-1.0V") +gcf() + +# %% diff --git a/AIChE_2025/Cu_C2_042925.rms b/AIChE_2025/Cu_C2_042925.rms index 6b6e1a2..30af4b9 100644 --- a/AIChE_2025/Cu_C2_042925.rms +++ b/AIChE_2025/Cu_C2_042925.rms @@ -3970,9 +3970,52 @@ Phases: type: Species name: surface Reactions: +- comment: 'Volmer. Made up by Richard. +A = kB / h / concentration to get units right. +n = 1 so that overall the A = k_B * T / H +Ea = 0.825 eV for Cu from Table 1 of Yang 2024 +assume DeltaS+ = 0 +q = 0.5' + electronchange: 1 + kinetics: + A: 2.084e10 + Ea: 79600.125 + n: 1.0 + q: 0.5 + V0: -0.250 + type: Arrheniusq + products: + - HX + radicalchange: 0 + reactants: + - proton + - vacantX + type: ElementaryReaction +- comment: 'Heyrovsky. Made up by Richard. +A = kB / h / concentration to get units right. +n = 1 so that overall the A = k_B * T / H +Ea = 0.575 eV for Cu from Table 1 of Yang 2024 +assume DeltaS+ = 0 +q = 0.5' + electronchange: 1 + kinetics: + A: 2.084e10 + Ea: 55478.875 + n: 1.0 + q: 0.5 + V0: 0.250 + type: Arrheniusq + products: + - H2 + - vacantX + radicalchange: 0 + reactants: + - HX + - proton + type: ElementaryReaction - comment: '' electronchange: 0 - kinetics: + kinetics:Surface_Proton_Electron_Reduction_Beta_Dissociation A: 0.005 Ea: 0.0 n: 0.0 diff --git a/AIChE_2025/Plot_FE.ipynb b/AIChE_2025/Plot_FE.ipynb deleted file mode 100644 index 2f23b69..0000000 --- a/AIChE_2025/Plot_FE.ipynb +++ /dev/null @@ -1,402 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "98ea2f1b", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\u001b[32m\u001b[1m Activating\u001b[22m\u001b[39m project at `~/mambaforge/envs/rmg_electrocat_2/julia_env`\n" - ] - } - ], - "source": [ - "using Pkg\n", - "Pkg.activate(ENV[\"PYTHON_JULIAPKG_PROJECT\"])\n", - "using CSV, DataFrames, PythonPlot" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "029170ce", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "PythonPlot" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt = PythonPlot" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "4d74e33a", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
12×5 DataFrame
RowSpecies-0.77-0.97-1.17-1.37
String7Float64Float64Float64Float64
1O=CO0.9927790.9497980.3042640.00858474
2H20.0001560930.03682660.6941850.991415
3CO6.65e-195.57e-191.81e-191.4e-21
4CO-21.55e-71.39e-50.0002328471.86e-7
5CCO0.00.00.00.0
6C=O0.007018820.01270020.001294512.93e-7
7O=CO0.01296670.04880.03746670.012
8H20.58920.4314650.7801330.925637
9CO0.2481330.3830890.1793670.0159759
10CO-20.00360.00.001466670.0
11CCO0.00.00.01343330.0
12C=O0.00.00.00.0
" - ], - "text/latex": [ - "\\begin{tabular}{r|ccccc}\n", - "\t& Species & -0.77 & -0.97 & -1.17 & -1.37\\\\\n", - "\t\\hline\n", - "\t& String7 & Float64 & Float64 & Float64 & Float64\\\\\n", - "\t\\hline\n", - "\t1 & O=CO & 0.992779 & 0.949798 & 0.304264 & 0.00858474 \\\\\n", - "\t2 & H2 & 0.000156093 & 0.0368266 & 0.694185 & 0.991415 \\\\\n", - "\t3 & CO & 6.65e-19 & 5.57e-19 & 1.81e-19 & 1.4e-21 \\\\\n", - "\t4 & CO-2 & 1.55e-7 & 1.39e-5 & 0.000232847 & 1.86e-7 \\\\\n", - "\t5 & CCO & 0.0 & 0.0 & 0.0 & 0.0 \\\\\n", - "\t6 & C=O & 0.00701882 & 0.0127002 & 0.00129451 & 2.93e-7 \\\\\n", - "\t7 & O=CO & 0.0129667 & 0.0488 & 0.0374667 & 0.012 \\\\\n", - "\t8 & H2 & 0.5892 & 0.431465 & 0.780133 & 0.925637 \\\\\n", - "\t9 & CO & 0.248133 & 0.383089 & 0.179367 & 0.0159759 \\\\\n", - "\t10 & CO-2 & 0.0036 & 0.0 & 0.00146667 & 0.0 \\\\\n", - "\t11 & CCO & 0.0 & 0.0 & 0.0134333 & 0.0 \\\\\n", - "\t12 & C=O & 0.0 & 0.0 & 0.0 & 0.0 \\\\\n", - "\\end{tabular}\n" - ], - "text/plain": [ - "\u001b[1m12×5 DataFrame\u001b[0m\n", - "\u001b[1m Row \u001b[0m│\u001b[1m Species \u001b[0m\u001b[1m -0.77 \u001b[0m\u001b[1m -0.97 \u001b[0m\u001b[1m -1.17 \u001b[0m\u001b[1m -1.37 \u001b[0m\n", - "\u001b[1m \u001b[0m│\u001b[90m String7 \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m Float64 \u001b[0m\u001b[90m Float64 \u001b[0m\n", - "─────┼──────────────────────────────────────────────────────────\n", - " 1 │ O=CO 0.992779 0.949798 0.304264 0.00858474\n", - " 2 │ H2 0.000156093 0.0368266 0.694185 0.991415\n", - " 3 │ CO 6.65e-19 5.57e-19 1.81e-19 1.4e-21\n", - " 4 │ CO-2 1.55e-7 1.39e-5 0.000232847 1.86e-7\n", - " 5 │ CCO 0.0 0.0 0.0 0.0\n", - " 6 │ C=O 0.00701882 0.0127002 0.00129451 2.93e-7\n", - " 7 │ O=CO 0.0129667 0.0488 0.0374667 0.012\n", - " 8 │ H2 0.5892 0.431465 0.780133 0.925637\n", - " 9 │ CO 0.248133 0.383089 0.179367 0.0159759\n", - " 10 │ CO-2 0.0036 0.0 0.00146667 0.0\n", - " 11 │ CCO 0.0 0.0 0.0134333 0.0\n", - " 12 │ C=O 0.0 0.0 0.0 0.0" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "df = CSV.read(\"final_molefractions.csv\", DataFrame)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "03cc21cd", - "metadata": {}, - "outputs": [], - "source": [ - "# Define parameters\n", - "species_order = [\n", - " \"H2\",\n", - " \"CO\",\n", - " \"O=CO\",\n", - " \"CO-2\",\n", - " \"CCO\",\n", - " \"C=O\"\n", - " ]\n", - "labels = [\n", - " \"H2\",\n", - " \"CO\",\n", - " \"Formate\",\n", - " \"Methanol\",\n", - " \"Ethanol\",\n", - " \"Formaldehyde\"\n", - " ]\n", - "colors = [\n", - " \"#440154\",\n", - " \"#FDAE61\",\n", - " \"#31688E\",\n", - " \"#35B779\",\n", - " \"#FDE725\",\n", - " \"#A5D32F\"\n", - " ];\n" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "121f625e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "6" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "potentials = names(df)[2:end] # all potential columns\n", - "n_species = length(species_order)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "e140adae", - "metadata": {}, - "outputs": [], - "source": [ - "# Split sim vs exp (first 5 rows = sim, next 5 = exp)\n", - "sim = df[1:n_species, :]\n", - "exp = df[n_species+1:end, :];" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "58df0a8e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "6×4 Matrix{Float64}:\n", - " 58.92 43.1465 78.0133 92.5637\n", - " 24.8133 38.3089 17.9367 1.59759\n", - " 1.29667 4.88 3.74667 1.2\n", - " 0.36 0.0 0.146667 0.0\n", - " 0.0 0.0 1.34333 0.0\n", - " 0.0 0.0 0.0 0.0" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sim_data = Matrix(sim[[findfirst(==(s), sim.Species) for s in species_order], potentials]).*100\n", - "exp_data = Matrix(exp[[findfirst(==(s), exp.Species) for s in species_order], potentials]).*100" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "da20e164", - "metadata": {}, - "outputs": [], - "source": [ - "plt.figure(figsize=(8,4.5))\n", - "x = collect(1:length(potentials))\n", - "bar_width = 0.3;\n", - "bar_gap = 0.1;" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "7ae4fc80", - "metadata": {}, - "outputs": [], - "source": [ - "# Left bars (simulation)\n", - "bottom_sim = zeros(length(potentials))\n", - "for (i, sp) in enumerate(species_order)\n", - " plt.bar(x .- (bar_width/2 + bar_gap/2), sim_data[i, :],\n", - " bar_width, bottom=bottom_sim,\n", - " color=colors[i], label=labels[i])\n", - " bottom_sim .+= sim_data[i, :]\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "df2ef3f8", - "metadata": {}, - "outputs": [], - "source": [ - "# Right bars (experiment)\n", - "bottom_exp = zeros(length(potentials))\n", - "for (i, sp) in enumerate(species_order)\n", - " plt.bar(x .+ (bar_width/2 + bar_gap/2), exp_data[i, :],\n", - " bar_width, bottom=bottom_exp,\n", - " color=colors[i], alpha=0.9,\n", - " label=\"_nolegend_\")\n", - " bottom_exp .+= exp_data[i, :]\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "5eacc6f7", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Python: None" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.xticks(x, potentials)\n", - "plt.xlabel(\"Applied Potential (V vs RHE)\", fontweight=\"bold\")\n", - "plt.ylabel(\"Faradaic Efficiency (%)\", fontweight=\"bold\")\n", - "plt.xticks(fontweight=\"bold\")\n", - "plt.yticks(fontweight=\"bold\")\n", - "plt.ylim(0.0, 108)\n", - "plt.title(\"Simulation vs Experimental Faradaic Efficiencies on Ag(111)\", pad = 12, fontweight=\"bold\")\n", - "plt.legend(bbox_to_anchor=(1.05, 1), loc=\"upper left\")\n", - "plt.text(1.04, 0.5,\n", - " \"Left = Simulation\\n\\nRight = Experiment\",\n", - " fontsize=9, fontweight=\"bold\",\n", - " ha=\"left\", va=\"center\",\n", - " transform=plt.gca().transAxes)\n", - "plt.tight_layout()" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "19543b5e", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.savefig(\"plt_full.png\", dpi=300)\n", - "display(\"image/png\", read(\"plt_full.png\"))" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "de683459", - "metadata": {}, - "outputs": [], - "source": [ - "selected_species = [\"O=CO\", \"CO-2\", \"CCO\"]\n", - "selected_labels = [\"Formate\", \"Methanol\", \"Ethanol\"]\n", - "selected_colors = [\"#31688E\", \"#35B779\", \"#FDE725\",];" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "2520e399", - "metadata": {}, - "outputs": [], - "source": [ - "sel_idx = [findfirst(==(s), exp.Species) for s in selected_species]\n", - "exp_sel = exp[sel_idx, :]\n", - "exp_data_sel = Matrix(exp_sel[:, potentials]).*100;" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "b69a3be7", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Python: None" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize=(6,4))\n", - "x = collect(1:length(potentials))\n", - "bar_width = 0.3\n", - "bottom_sim = zeros(length(potentials))\n", - "for (i, sp) in enumerate(selected_species)\n", - " plt.bar(x .- (bar_width/2), exp_data_sel[i, :],\n", - " bar_width, bottom=bottom_sim,\n", - " color=selected_colors[i],\n", - " label=selected_labels[i])\n", - " bottom_sim .+= exp_data_sel[i, :]\n", - "end\n", - "\n", - "plt.xticks(x, potentials)\n", - "plt.xlabel(\"Applied Potential (V vs RHE)\", fontweight=\"bold\")\n", - "plt.ylabel(\"Faradaic Efficiency (%)\", fontweight=\"bold\")\n", - "plt.xticks(fontweight=\"bold\")\n", - "plt.yticks(fontweight=\"bold\")\n", - "plt.ylim(0.0, 10)\n", - "plt.title(\"Experimental Faradaic Efficiencies on Ag(111)\", pad = 12, fontweight=\"bold\")\n", - "plt.legend(bbox_to_anchor=(1.05, 1), loc=\"upper left\")\n", - "plt.tight_layout()" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "dac9c6c7", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.savefig(\"plt_partial.png\", dpi=300)\n", - "display(\"image/png\", read(\"plt_partial.png\"))" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "59b6f2d0", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Julia 1.10.10", - "language": "julia", - "name": "julia-1.10" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.10.10" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/AIChE_2025/Plot_FE.jl b/AIChE_2025/Plot_FE.jl new file mode 100644 index 0000000..b8a41e3 --- /dev/null +++ b/AIChE_2025/Plot_FE.jl @@ -0,0 +1,152 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,jl:percent +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.17.2 +# kernelspec: +# display_name: Julia 1.10.10 +# language: julia +# name: julia-1.10 +# --- + +# %% +using Pkg +Pkg.activate(ENV["PYTHON_JULIAPKG_PROJECT"]) +using CSV, DataFrames, PythonPlot + +# %% +plt = PythonPlot + +# %% +df = CSV.read("final_molefractions.csv", DataFrame) + +# %% +# Define parameters +species_order = [ + "H2", + "CO", + "O=CO", + "CO-2", + "CCO", + "C=O" + ] +labels = [ + "H2", + "CO", + "Formate", + "Methanol", + "Ethanol", + "Formaldehyde" + ] +colors = [ + "#440154", + "#FDAE61", + "#31688E", + "#35B779", + "#FDE725", + "#A5D32F" + ]; + + +# %% +potentials = names(df)[2:end] # all potential columns +n_species = length(species_order) + +# %% +# Split sim vs exp (first 5 rows = sim, next 5 = exp) +sim = df[1:n_species, :] +exp = df[n_species+1:end, :]; + +# %% +sim_data = Matrix(sim[[findfirst(==(s), sim.Species) for s in species_order], potentials]).*100 +exp_data = Matrix(exp[[findfirst(==(s), exp.Species) for s in species_order], potentials]).*100 + +# %% +plt.figure(figsize=(8,4.5)) +x = collect(1:length(potentials)) +bar_width = 0.3; +bar_gap = 0.1; + +# %% +# Left bars (simulation) +bottom_sim = zeros(length(potentials)) +for (i, sp) in enumerate(species_order) + plt.bar(x .- (bar_width/2 + bar_gap/2), sim_data[i, :], + bar_width, bottom=bottom_sim, + color=colors[i], label=labels[i]) + bottom_sim .+= sim_data[i, :] +end + +# %% +# Right bars (experiment) +bottom_exp = zeros(length(potentials)) +for (i, sp) in enumerate(species_order) + plt.bar(x .+ (bar_width/2 + bar_gap/2), exp_data[i, :], + bar_width, bottom=bottom_exp, + color=colors[i], alpha=0.9, + label="_nolegend_") + bottom_exp .+= exp_data[i, :] +end + +# %% +plt.xticks(x, potentials) +plt.xlabel("Applied Potential (V vs RHE)", fontweight="bold") +plt.ylabel("Faradaic Efficiency (%)", fontweight="bold") +plt.xticks(fontweight="bold") +plt.yticks(fontweight="bold") +plt.ylim(0.0, 108) +plt.title("Simulation vs Experimental Faradaic Efficiencies on Ag(111)", pad = 12, fontweight="bold") +plt.legend(bbox_to_anchor=(1.05, 1), loc="upper left") +plt.text(1.04, 0.5, + "Left = Simulation\n\nRight = Experiment", + fontsize=9, fontweight="bold", + ha="left", va="center", + transform=plt.gca().transAxes) +plt.tight_layout() + +# %% +plt.savefig("plt_full.png", dpi=300) +display("image/png", read("plt_full.png")) + +# %% +selected_species = ["O=CO", "CO-2", "CCO"] +selected_labels = ["Formate", "Methanol", "Ethanol"] +selected_colors = ["#31688E", "#35B779", "#FDE725",]; + +# %% +sel_idx = [findfirst(==(s), exp.Species) for s in selected_species] +exp_sel = exp[sel_idx, :] +exp_data_sel = Matrix(exp_sel[:, potentials]).*100; + +# %% +plt.figure(figsize=(6,4)) +x = collect(1:length(potentials)) +bar_width = 0.3 +bottom_sim = zeros(length(potentials)) +for (i, sp) in enumerate(selected_species) + plt.bar(x .- (bar_width/2), exp_data_sel[i, :], + bar_width, bottom=bottom_sim, + color=selected_colors[i], + label=selected_labels[i]) + bottom_sim .+= exp_data_sel[i, :] +end + +plt.xticks(x, potentials) +plt.xlabel("Applied Potential (V vs RHE)", fontweight="bold") +plt.ylabel("Faradaic Efficiency (%)", fontweight="bold") +plt.xticks(fontweight="bold") +plt.yticks(fontweight="bold") +plt.ylim(0.0, 10) +plt.title("Experimental Faradaic Efficiencies on Ag(111)", pad = 12, fontweight="bold") +plt.legend(bbox_to_anchor=(1.05, 1), loc="upper left") +plt.tight_layout() + +# %% +plt.savefig("plt_partial.png", dpi=300) +display("image/png", read("plt_partial.png")) + +# %% diff --git a/CO2RR_RMS/Ag/CO2RR_RMS.ipynb b/CO2RR_RMS/Ag/CO2RR_RMS.ipynb deleted file mode 100644 index 41de817..0000000 --- a/CO2RR_RMS/Ag/CO2RR_RMS.ipynb +++ /dev/null @@ -1,1197 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "8a590634", - "metadata": {}, - "outputs": [], - "source": [ - "using DifferentialEquations\n", - "using ReactionMechanismSimulator\n", - "using PyPlot" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "e941d4fb", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[11:25:07] WARNING: not removing hydrogen atom without neighbors\n", - "[11:25:07] WARNING: not removing hydrogen atom without neighbors\n", - "┌ Warning: failed to generate StokesDiffusivity model for species vacantX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2O2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC([Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species H2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "[11:25:08] WARNING: not removing hydrogen atom without neighbors\n", - "[11:25:08] WARNING: not removing hydrogen atom without neighbors\n", - "┌ Warning: failed to generate StokesDiffusivity model for species vacantX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2O2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species H2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [H][H].[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n" - ] - }, - { - "data": { - "text/plain": [ - "Dict{Any, Any} with 4 entries:\n", - " \"Solvents\" => Solvent[Solvent(\"water\", RiedelViscosity{Float64}(…\n", - " Set([\"surface\", \"gas\"]) => Dict{Any, Any}(\"Reactions\"=>ElementaryReaction[vac…\n", - " \"gas\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…\n", - " \"surface\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "outdict1 = readinput(\"chem43_Ag.rms\");\n", - "outdict2 = readinput(\"chem43_Cu.rms\")\n" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "fe2767e9", - "metadata": {}, - "outputs": [], - "source": [ - "liqspcs1 = outdict1[\"gas\"][\"Species\"];\n", - "liqrxns1 = outdict1[\"gas\"][\"Reactions\"];\n", - "surfspcs1 = outdict1[\"surface\"][\"Species\"];\n", - "surfrxns1 = outdict1[\"surface\"][\"Reactions\"];\n", - "interfacerxns1 = outdict1[Set([\"surface\", \"gas\"])][\"Reactions\"];\n", - "solv1 = outdict1[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "2e3c1e9a", - "metadata": {}, - "outputs": [], - "source": [ - "liqspcs2 = outdict2[\"gas\"][\"Species\"];\n", - "liqrxns2 = outdict2[\"gas\"][\"Reactions\"];\n", - "surfspcs2 = outdict2[\"surface\"][\"Species\"];\n", - "surfrxns2 = outdict2[\"surface\"][\"Reactions\"];\n", - "interfacerxns2 = outdict2[Set([\"surface\", \"gas\"])][\"Reactions\"];\n", - "solv2 = outdict2[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "711d8a69", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "100000.0" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sitedensity1 = 2.292e-5; # Ag111\n", - "sitedensity2 = 2.943e-5; # Cu111\n", - "AVratio = 1.0e5" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "8894c84d", - "metadata": {}, - "outputs": [], - "source": [ - "initialcondsliq = Dict([\"proton\"=>10.0^-4,\"CO2\"=>10.0^-3*10^3,\n", - " \"V\"=>1.0,\"T\"=>298.15,\"Phi\"=>0.0,\"d\"=>0.0]);\n", - "initialcondssurf1 = Dict([\"CO2X\"=>0.4*sitedensity1*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity1*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity1*AVratio,\n", - " \"OX\"=>0.1*sitedensity1*AVratio,\n", - " \"OCX\"=>0.1*sitedensity1*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity1*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity1*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity1*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity1*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-1.5]);\n", - "initialcondssurf2 = Dict([\"CO2X\"=>0.4*sitedensity1*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity1*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity1*AVratio,\n", - " \"OX\"=>0.1*sitedensity1*AVratio,\n", - " \"OCX\"=>0.1*sitedensity1*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity1*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity1*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity1*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity1*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-1.0]);\n", - "initialcondssurf3 = Dict([\"CO2X\"=>0.4*sitedensity1*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity1*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity1*AVratio,\n", - " \"OX\"=>0.1*sitedensity1*AVratio,\n", - " \"OCX\"=>0.1*sitedensity1*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity1*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity1*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity1*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity1*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-2.0]);\n", - "initialcondssurf4 = Dict([\"CO2X\"=>0.4*sitedensity2*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity2*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity2*AVratio,\n", - " \"OX\"=>0.1*sitedensity2*AVratio,\n", - " \"OCX\"=>0.1*sitedensity2*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity2*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity2*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity2*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity2*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-1.5]);\n", - "initialcondssurf5 = Dict([\"CO2X\"=>0.4*sitedensity2*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity2*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity2*AVratio,\n", - " \"OX\"=>0.1*sitedensity2*AVratio,\n", - " \"OCX\"=>0.1*sitedensity2*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity2*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity2*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity2*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity2*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-1.0]);\n", - "initialcondssurf6 = Dict([\"CO2X\"=>0.4*sitedensity2*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity2*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity2*AVratio,\n", - " \"OX\"=>0.1*sitedensity2*AVratio,\n", - " \"OCX\"=>0.1*sitedensity2*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity2*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity2*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity2*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity2*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-2.0]);" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "ddb39b3d", - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "liq1 = IdealDiluteSolution(liqspcs1,liqrxns1,solv1,name=\"liquid\",diffusionlimited=true);\n", - "\n", - "liq2 = IdealDiluteSolution(liqspcs2,liqrxns2,solv2,name=\"liquid\",diffusionlimited=true);\n", - "\n", - "surf1 = IdealSurface(surfspcs1,surfrxns1,sitedensity1,name=\"surface\");\n", - "\n", - "surf2 = IdealSurface(surfspcs2,surfrxns2,sitedensity2,name=\"surface\");\n", - "\n", - "domainliq1,y0liq1,pliq1 = ConstantTVDomain(phase=liq1,\n", - " initialconds=initialcondsliq,constantspecies=[\"proton\",\"CO2\"]);\n", - "\n", - "domainliq2,y0liq2,pliq2 = ConstantTVDomain(phase=liq2,\n", - " initialconds=initialcondsliq,constantspecies=[\"proton\",\"CO2\"]);" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "29ec7f86", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat1,y0cat1,pcat1 = ConstantTAPhiDomain(phase=surf1,\n", - " initialconds=initialcondssurf1);\n", - "\n", - "inter1,pinter1 = ReactiveInternalInterfaceConstantTPhi(domainliq1,\n", - " domaincat1,interfacerxns1,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "02daf794", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat2,y0cat2,pcat2 = ConstantTAPhiDomain(phase=surf1,\n", - " initialconds=initialcondssurf2);\n", - "\n", - "inter2,pinter2 = ReactiveInternalInterfaceConstantTPhi(domainliq1,\n", - " domaincat2,interfacerxns1,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "b6bac559", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat3,y0cat3,pcat3 = ConstantTAPhiDomain(phase=surf1,\n", - " initialconds=initialcondssurf3);\n", - " \n", - "inter3,pinter3 = ReactiveInternalInterfaceConstantTPhi(domainliq1,\n", - " domaincat3,interfacerxns1,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "5ed60871", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat4,y0cat4,pcat4 = ConstantTAPhiDomain(phase=surf2,\n", - " initialconds=initialcondssurf4);\n", - " \n", - "inter4,pinter4 = ReactiveInternalInterfaceConstantTPhi(domainliq2,\n", - " domaincat4,interfacerxns2,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "5b589c3f", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat5,y0cat5,pcat5 = ConstantTAPhiDomain(phase=surf2,\n", - " initialconds=initialcondssurf5);\n", - " \n", - "inter5,pinter5 = ReactiveInternalInterfaceConstantTPhi(domainliq2,\n", - " domaincat5,interfacerxns2,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "8eaa5eaf", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat6,y0cat6,pcat6 = ConstantTAPhiDomain(phase=surf2,\n", - " initialconds=initialcondssurf6);\n", - " \n", - "inter6,pinter6 = ReactiveInternalInterfaceConstantTPhi(domainliq2,\n", - " domaincat6,interfacerxns2,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "244f0912", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 10.851519 seconds (50.44 M allocations: 3.017 GiB, 11.09% gc time, 99.93% compilation time: <1% of which was recompilation)\n", - " 4.063472 seconds (19.08 M allocations: 1.154 GiB, 9.18% gc time, 97.88% compilation time)\n" - ] - } - ], - "source": [ - "@time react1,y01,p1 = Reactor((domainliq1,domaincat1), (y0liq1,y0cat1), (0.0, 1.0e2), [inter1], (pliq1,pcat1,pinter1));\n", - "\n", - "@time sol1 = solve(react1.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6);\n", - "\n", - "ssys1 = SystemSimulation(sol1,(domainliq1,domaincat1,),(inter1,),p1);\n" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "3b06f7a9", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.000678 seconds (3.32 k allocations: 960.422 KiB)\n", - " 0.090015 seconds (571.54 k allocations: 82.069 MiB, 33.06% gc time)\n" - ] - } - ], - "source": [ - "@time react2,y02,p2 = Reactor((domainliq1,domaincat2), (y0liq1,y0cat2), (0.0, 1.0e2), [inter2], (pliq1,pcat2,pinter2));\n", - "\n", - "@time sol2 = solve(react2.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6);\n", - "\n", - "ssys2 = SystemSimulation(sol2,(domainliq1,domaincat2,),(inter2,),p2);" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "ab03df14", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.000723 seconds (3.32 k allocations: 960.422 KiB)\n", - " 0.041817 seconds (335.25 k allocations: 45.316 MiB, 27.65% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "[CVODES ERROR] CVode\n", - " At t = 8.08742 and h = 1.35613e-09, the error test failed repeatedly or with |h| = hmin.\n", - "\n" - ] - } - ], - "source": [ - "@time react3,y03,p3 = Reactor((domainliq1,domaincat3), (y0liq1,y0cat3), (0.0, 1.0e2), [inter3], (pliq1,pcat3,pinter3));\n", - "\n", - "@time sol3 = solve(react3.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6);\n", - "\n", - "ssys3 = SystemSimulation(sol3,(domainliq1,domaincat3,),(inter3,),p3);" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "9b238da8", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.000737 seconds (3.67 k allocations: 866.000 KiB)\n", - " 0.035751 seconds (282.48 k allocations: 32.996 MiB, 32.97% gc time)\n" - ] - } - ], - "source": [ - "@time react4,y04,p4 = Reactor((domainliq2,domaincat4), (y0liq2,y0cat4), (0.0, 1.0e2), [inter4], (pliq2,pcat4,pinter4));\n", - "\n", - "@time sol4 = solve(react4.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6);\n", - "\n", - "ssys4 = SystemSimulation(sol4,(domainliq2,domaincat4,),(inter4,),p4);" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "b7c78e37", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.000749 seconds (3.67 k allocations: 866.000 KiB)\n", - " 0.031855 seconds (285.34 k allocations: 33.355 MiB, 21.41% gc time)\n" - ] - } - ], - "source": [ - "@time react5,y05,p5 = Reactor((domainliq2,domaincat5), (y0liq2,y0cat5), (0.0, 1.0e2), [inter5], (pliq2,pcat5,pinter5));\n", - "\n", - "@time sol5 = solve(react5.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6);\n", - "\n", - "ssys5 = SystemSimulation(sol5,(domainliq2,domaincat5,),(inter5,),p5);" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "8498a9b3", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.000716 seconds (3.67 k allocations: 866.000 KiB)\n", - " 0.021732 seconds (259.36 k allocations: 30.961 MiB)\n" - ] - } - ], - "source": [ - "@time react6,y06,p6 = Reactor((domainliq2,domaincat6), (y0liq2,y0cat6), (0.0, 1.0e2), [inter6], (pliq2,pcat6,pinter6));\n", - "\n", - "@time sol6 = solve(react6.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6);\n", - "\n", - "ssys6 = SystemSimulation(sol6,(domainliq2,domaincat6,),(inter6,),p6);" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "39632165", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotX (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotX(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = molefractions(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Mole Fraction\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "6ef159b3", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys1.sims[1], 1e-10, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e-3)\n", - "ylim(1e-12, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V\")\n", - "gcf()\n", - "savefig(\"Ag111@-1.5V_X.png\")" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "bce46a3f", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys2.sims[1], 1e-10, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e-3)\n", - "ylim(1e-12, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.0V\")\n", - "gcf()\n", - "savefig(\"Ag111@-1.0V_X.png\")" - ] - }, - { - "cell_type": "code", - "execution_count": 52, - "id": "78344a8c", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys3.sims[1], 1e-10, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e-3)\n", - "ylim(1e-12, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-2.0V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "a5b06177", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys4.sims[1], 1e-10, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e-3)\n", - "ylim(1e-12, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Cu111@-1.5V\")\n", - "gcf()\n", - "savefig(\"Cu111@-1.5V_X.png\")" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "a15be1a0", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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UlpaWq9atb9++Oe5nZ/6XL1++4z5SU1P5999/GTRoEC4uLtZyjUbDsGHDuHbtWr6bRgvD9u3bqV+/Po0aNcpR/tRTTxXaPlJTU9m/fz+PPfYYDg4O1vLs2sJbmc3mO9bKAneMNSkpiUOHDuUoz8/7ExUVxYQJE6hcuTJ2dnZotVqqVKkCwKlTp6zrtWzZkkWLFvHhhx+yb9++XM01e/bsIS4ujhEjRuSI32w20717d/bv35/vmg4XFxcef/xxFixYgNFoZMmSJYwaNSrPX/Lbt28HyNXc3LJlS+rWrXvX/6P169ejUqkYOnRojpgrVKhAo0aN8j3CMa9jQvb/OVhqMPIyZ84cmjZtioODg/W137ZtW47X/Y8//sDBweGeTYT5debMGW7cuMGwYcNy1By4uLgwcOBA9u3bR1paWo7H5PU5ysjIICoqCoAWLVoA8MQTT/DLL79w/fr1fMWS32Nly5YtSUhIYMiQIaxZs+aetaFFrXfv3jnu161bF7AMOLi9/Nb/tfXr1+Ph4UGfPn1yfN4aN25MhQoV7vp5K4r3rbxZs2YN48ePt94fPXo0+/bt4/vvv+fnn3/m4MGD/PLLL9bl3bp1Izo62lqze3sNefZntrDcqaby9vIxY8YQExPD2rVrAUvt+tKlS3n44YepWbNmgfZZppKzunXr0rx58xyXZs2a5Vhn9OjRXL9+na1btwLw888/k5mZmeMLJDY2lgoVKuR64f38/LCzs8vRXFRcYmNjCQgIyFWePfLs9pi8vb1z3M8e5XS36vn4+HgURSnQfopS9vtwu7zK7ld8fDxmszlf+xk9ejRardZ66dKlyz3jyi4r6PtjNpvp1q0bK1eu5PXXX2fbtm38999/7Nu3L8d6ACtWrGDEiBHMnz+fNm3a4OXlxfDhw4mIiACwNgEOGjQoR/xarZZPP/0URVGsTXn5MWbMGA4dOsRHH31EdHT0HYfHZz/nO32e7vZZioyMRFEU/P39c8W8b9++fCcBeR0TbpVXbF988QXPPvssrVq14vfff2ffvn3s37+f7t2753jdo6OjCQwMfKA+Lbe61+tlNputzcnZ7vU5at++PatXr8ZoNDJ8+HAqVapEgwYN7joaL1t+jpXDhg1jwYIFXL58mYEDB+Ln50erVq2sjyluXl5eOe7rdLo7lmdkZFjvR0ZGkpCQgE6ny/V5i4iIuOvnrSjet7wEBQUBlibAsiQ+Pp7o6GjrD9SoqChWrVrFkiVLePzxx+nWrRurVq3K8eNZq9Xi6elp7Q/YpUuXHO9ZYf1gyn6f8jpWxcXF5fpcDRo0CHd3d2uXmI0bNxIZGXnHbh93U6am0siPRx99lMDAQBYuXMijjz7KwoULadWqVY7h7N7e3vz7778oipIjQYuKisJoNOLj43PH7Wd/gG4fOPCgvyi9vb0JDw/PVX7jxg2Au8aUX56enqjV6iLfT355e3tbE4xb5VXm4OCQ52CNmJiYu8bs6emJSqXK137efffdHP3dXF1d7xlXdtntB+N7OXHiBEePHmXRokWMGDHCWh4WFpZrXR8fH2bOnMnMmTO5cuUKa9euZcqUKURFRbFp0ybr8//mm29o3bp1nvvL9/BuoF27dtSuXZv333+frl275qrNzZb9nMPDw3NNe3Djxo27vi8+Pj6oVCp27dpl/eK6VV5l9yOvX8RLly6lY8eOzJ49O0d5cnJyjvu+vr7s3r0bs9lcKAnara/X7W7cuIFarcbT07PA2+3Xrx/9+vUjMzOTffv2MW3aNJ566imqVq1KmzZt7vi4/BwrwdI/bdSoUaSmprJz506mTp1K7969OXv2rLWmt6Tz8fHB29ubTZs25bn89v/1WxXV+3a75s2b4+XlxZo1a5g2bdo9+50V1XdRYcuu6c+ON3swXdOmTa3ruLq65piqSa/XEx0dbT2GzJ07N8f/Z2F9TzVs2BCA48eP5/jcG41GTp8+zZAhQ3Ks7+joyJAhQ/j+++8JDw9nwYIFuLq68vjjjxd432Wq5iw/spvoVq9eza5duzhw4ECuLLtLly6kpKTkmjhyyZIl1uV3kj1q8dixYznKs6s5b2Vvb3/Pjqa3xvTXX39Zk6RbY3Jycrrjl25BODs706pVK1auXJkjLrPZzNKlS6lUqRK1atV64P3kV6dOnTh58iRHjx7NUb5s2bJc61atWjXXa3727Nl7NsM6OzvTsmVLVq5cmeOXdHJyMuvWrcu1j1trYG6f1+1Osbq6uuY40ORH9oH39iRk7ty5d31cUFAQzz//PF27drU2pbZr1w4PDw9CQ0Nz1SJlX7JrGPLr7bffpk+fPjnmoLpd586dAUuyc6v9+/dz6tSpu/4f9e7dG0VRuH79ep7xZh80i4JKpcr1uh87dixX14EePXqQkZFxzwmN8/t/Xrt2bSpWrMiyZctQFMVanpqayu+//24dCXi/7O3t6dChA59++ikAhw8fvuv6+TlW3srZ2ZkePXrwf//3f+j1ek6ePHnfsRa33r17Exsbi8lkyvPzdrc5HIv6fcum1Wp54403OH36NB988EGe60RFRfHPP/8ABfsusiUfHx8cHR05e/YscPOH4q0zHphMJq5evWq9/+OPPxIUFGT9Pqpdu3aO96uwJrRu1aoVAQEBuf7Hf/vtN1JSUvIcIDhmzBhMJhMzZsxg48aNPPnkk/f1/pepmrMTJ07kOQqpevXq+Pr6Wu+PHj2aTz/9lKeeegpHR0cGDx6cY/3hw4fz3XffMWLECC5dukTDhg3ZvXs3H3/8MT179uSRRx65YwwtWrSgdu3avPrqqxiNRjw9PVm1alWeI3YaNmzIypUrmT17Ns2aNUOtVudqdsk2depU1q9fT6dOnXjnnXfw8vLip59+YsOGDUyfPj3PaQzux7Rp0+jatSudOnXi1VdfRafTMWvWLE6cOMHPP//8QKOEjh8/nufM+C1atMjzF/akSZNYsGABvXr14sMPP8Tf35+ffvqJ06dP51p32LBhDB06lIkTJzJw4EAuX77M9OnTc7zvd/LBBx/QvXt3unbtyiuvvILJZOLTTz/F2dm5QM19gYGB9O3bl3fffZeAgACWLl3K1q1b+fTTTwv8z1mnTh2qV6/OlClTUBQFLy8v1q1bl6u5KDExkU6dOvHUU09Rp04dXF1d2b9/P5s2bbIeOFxcXPjmm28YMWIEcXFxDBo0CD8/P6Kjozl69CjR0dG5aonuZejQoQwdOvSu69SuXZvx48fzzTffoFar6dGjB5cuXeJ///sflStXvuvotHbt2jF+/HhGjRrFgQMHaN++Pc7OzoSHh7N7924aNmzIs88+W6CY86t379588MEHTJ06lQ4dOnDmzBnef/99qlWrluP4MmTIEBYuXMiECRM4c+YMnTp1wmw28++//1K3bl2efPJJwPJ/vmPHDtatW0dAQECuWoBsarWa6dOn8/TTT9O7d2+eeeYZMjMzmTFjBgkJCXzyyScFfi7vvPMO165do0uXLlSqVImEhAS++uortFotHTp0uOfj73WsHDduHI6OjrRr146AgAAiIiKYNm0a7u7u1v5uly9fpnr16owYMYIffvihwM+hODz55JP89NNP9OzZk5deeomWLVui1Wq5du0a27dvp1+/fgwYMCDPxxbF+3Ynr732GqdOnWLq1Kn8999/PPXUU9ZJaHfu3Mm8efN47733rDMBPPLII0ybNg1PT0+qVKnCtm3brCPtb5d9bM6equbAgQPWvse39r++fPky+/fvBywjym99bPYP2Gx///23tenRZDJx+fJl67odOnTA19cXtVrNI488Yp2Fv0qVKrRq1YqJEycyb948PDw8+PjjjwkPDyclJYX58+czadIkfvrpp3y9ZvmNN6/PqUajYfr06QwbNoxnnnmGIUOGcO7cOV5//XW6du1K9+7dc+2vefPmhISEMHPmTBRFua8mTaDsj9bkDqOp2rZtqwDK008/nec2Y2NjlQkTJigBAQGKnZ2dUqVKFeXNN99UMjIycqyX1yjBs2fPKt26dVPc3NwUX19f5YUXXlA2bNiQa+RMXFycMmjQIMXDw0NRqVQ5RpFw22gkRVGU48ePK3369FHc3d0VnU6nNGrUKNeImjtNcnqvETq32rVrl9K5c2fF2dlZcXR0VFq3bp1r8rz7Ga15p0t2THm9lqGhoUrXrl0VBwcHxcvLSxkzZoyyZs2aXK+l2WxWpk+frgQHBysODg5K8+bNlb/++itfozUVRVHWrl2rhISEKDqdTgkKClI++eSTAk1CW6VKFaVXr17Kb7/9ptSvX1/R6XRK1apVc40SK8j7k/3cXV1dFU9PT+Xxxx9Xrly5kuOzkZGRoUyYMEEJCQlR3NzcFEdHR6V27drK1KlTrSNEs/39999Kr169FC8vL0Wr1SoVK1ZUevXqdc8JcfP7Xuc1EspkMimffvqpUqtWLUWr1So+Pj7K0KFDlatXr+ZY706T0C5YsEBp1aqV9bNYvXp1Zfjw4cqBAwfuGsu9JqG922TAmZmZyquvvqpUrFhRcXBwUJo2baqsXr06zxjT09OVd955R6lZs6ai0+kUb29vpXPnzsqePXus6xw5ckRp166d4uTkpADWz+OdRtOtXr1aadWqleLg4KA4OzsrXbp0Uf75558c62R/NqOjo/N83tmjxdevX6/06NFDqVixoqLT6RQ/Pz+lZ8+eBZqo9G7HysWLFyudOnVS/P39FZ1OpwQGBipPPPGEcuzYMes62Z+fgk7Ey32M1rz9/b7T6zRixAjF2dk5R5nBYFA+++wzpVGjRoqDg4Pi4uKi1KlTR3nmmWeUc+fO3TPewnzf7mXNmjVKr169FF9fX8XOzk7x9PRUOnXqpMyZM0fJzMy0rhceHq4MGjRI8fLyUtzd3ZWhQ4cqBw4cyPMYeLdjdF6x5nW5/T3u0KHDHde99XO/Y8cOxcnJSQkNDVUURVHOnDmj1K9f37pu9+7dlYEDByqA0qBBA+vkr/mR33jv9jldtmyZ9fuhQoUKyosvvphjRoPbffXVVwqg1KtXL99x3k6lKLfUwwpRCuzYsYNOnTqxffv2Ap/Ko6hUrVqVBg0asH79eluHIoQQpc4LL7zAunXrWLt2rXVwwMWLF7Gzs6Ny5cpcvXoVrVZbqAPCSrJy1+dMCCGEECXLzJkz6d+/Py1btuS5555j165duLu74+Pjw/nz59m8eTMDBgxg6tSptg61WJSpPmdCCCGEKH00Gg0zZ85k4MCBfPLJJ3Tr1i3HIK369eszfvx4JkyYYMMoi480awohhBCiRMnIyODatWukp6cTGBhY4OmISjtJzoQQQgghShDpcyaEEEIIUYJIciaEEEIIUYLIgID7ZDabuXHjBq6urg80MasQQgghio+iKCQnJxfquXELmyRn9+nGjRt3PKegEEIIIUq2q1ev5jrvb0khydl9yj4R7tWrV3Fzc7NxNEIIIYTIj6SkJCpXrnzXE9rbmiRn9ym7KdPNzU2SMyGEEKKUKcldkkpmY6sQQgghRDklyZkQQgghRAkiyZkQQgghRAkiyZkQQgghRAkiyZkQQgghRAkiyZkQQgghRAkiyZkQQgghRAkiyZkQQgghRAkiyZkQQgghRAkiyZkQQgghRAkiyZkQQgghRAlSrpOz9evXU7t2bWrWrMn8+fNtHY4QQgghRPk98bnRaGTy5Mls374dNzc3mjZtymOPPYaXl5etQxNCCCFEOVZua87+++8/6tevT8WKFXF1daVnz55s3rzZ1mEJIYQQopwrtcnZzp076dOnD4GBgahUKlavXp1rnVmzZlGtWjUcHBxo1qwZu3btsi67ceMGFStWtN6vVKkS169fL47QhRBCCCHuqNQ2a6amptKoUSNGjRrFwIEDcy1fsWIFkyZNYtasWbRr1465c+fSo0cPQkNDCQoKQlGUXI9RqVQFjuNcZDIuaTcfd/sm8tpi7t2o7rE893ZujzU/+1Hlsda9nnKesdxj33nHf/fnmGcY9xH/vV6nvNe5935uL1KrQKNWoVapUKlArVJlXe7vcySEEEJkK7XJWY8ePejRo8cdl3/xxReMGTOGsWPHAjBz5kw2b97M7NmzmTZtGhUrVsxRU3bt2jVatWp1x+1lZmaSmZlpvZ+UlATAgFl7UNs7PejTEWVMdvKmykrYspO3m4lc1rX63ss1KhV2GhV2GjVateW2VqPGTp1VplFhp1ZbyrOv77Rco8LeToO9nRoHbc5re60GB60ae7vc11qNSpJOIYQoJqU2ObsbvV7PwYMHmTJlSo7ybt26sWfPHgBatmzJiRMnuH79Om5ubmzcuJF33nnnjtucNm0a7733Xq5yb2ctGgcdALdXxuWumyNXjd3t6+RRoXfPx+S1o9zbvcc28ti3ksda93yOecZy276L6HUqScwKmE0KeT+70ketIkcy56jT4Kyzw0mnwdnecm252OFsb7l2yl7H3nLtmOd9DXaaUtu7QgghikSZTM5iYmIwmUz4+/vnKPf39yciIgIAOzs7Pv/8czp16oTZbOb111/H29v7jtt88803mTx5svV+UlISlStX5u/XO+Pm5lY0T0Q8kLyaru+VGOb5mDy2YVYU67XlYnmsyXzztvnW5ebc62YvN5nvvC1T1mMNZjNGk4LRZMZgtlwbTYq13GAyYzIrGM2W27cuu/0xmUYzmUYTGYab1xkGE5nG3NfZzAqk6U2k6U2A4f7ekDvQ2alxzkrsHLRqnHR2OGo1OOg0OGbdd9BqcNRqcNTlvu+otSR6DnZq7DRqdJqbtYR2ajVau+waR0u5LqtWMbtmUwghSpoymZxlu/3AqyhKjrK+ffvSt2/ffG3L3t4ee3v7Qo1PFK08+5vd87tYvqyzKUpWImfImcylGyxJWrreRKreSFpm1rXeRJreSGpm1nX2OpmWZal6o/V+qt6EyWxJe/VGM3qjmfi0wk368iO7j6AKSzMyqqwybjYxq7B8blSq28ss97Mfm33bWn6HdbOburP3obplH3luJ8f2b25bhQq1Ou/t3PoYyO4LefMxapUlOdWoLAmqRn2zD2X2suzmdY36ZvO6WsXN2+rsdcn5uDzWtSTC3LbPPB5rvb5lPypLzLkeq8r5XLLjtSTkN5v2JQEXpVGZTM58fHzQaDTWWrJsUVFRuWrThBB5U6lUOGg1OGg1gLZQt60oCnqTOSvBM5GWeTOZyzBYEsB0/W3X2bdvuZ+RVZamN5FhNFlrEQ0mBWNWzaHeZMZoMmPOo4XZrHBLdWrZaIIWOemy+l1q7dRos2pWdXZZZZqbZdkJXfZ9B2vNrAbHrNpcR63aUktrrbm1XDvccts5q2lfmuvFgyiTyZlOp6NZs2Zs3bqVAQMGWMu3bt1Kv379bBiZEAIsiZ9lYIIGj2IaT2M2W5p6DdlNvSYFBUuTsqJY+kZmNynnVWZJ7rKboLOWmcm1DWuzN1llWbfN5txlOddVbtvGrevl3G/24yBnM7tCVnmO2G/eJut5WJrflaxm9awmdWszeta1Yok5u6k+uwnepCg3m93NWU3w1iZ9y2uSvR2zomDKsR3Fup0c28xq2s/5uKxt5fU4a4w395ddE3s7vcmM3gSWP8XHQavGxV6Lq4MdLvZZFwc7XLOuc9/X4mJvh6uDHW4OWY9zsEMrSV65VGqTs5SUFMLCwqz3L168yJEjR/Dy8iIoKIjJkyczbNgwmjdvTps2bZg3bx5XrlxhwoQJNoxaCGErarUKe7UG+1J71BP3oiiWfpfZNaaGrIvemH2t3CzLStANxpv3Lesp6I0mMozmPGtys++n3aGm12CyJImWvpyZxKRk3iPqu3PQqnHNStZc7e1u3s5K6LJv35rQ3bqOq70WB61amndLmVJ7mDpw4ACdOnWy3s/urD9ixAgWLVrE4MGDiY2N5f333yc8PJwGDRqwceNGqlSpYquQhRBCFCGVSpXVXAmOaGwSg95oJjXTSEqmkeQMy3VKpuHm7YzbllnvG0jOup+cYSTdYKnpy07yopPvP8mzU6uykrWbtXOuDlrcshI4B53GOsXOzYsGXfZt7c37Wo3a2t/PTq3O6q+Ys0ytxjIFUPZt9S39BFU3+0iKO1MpeQ1PE/eUlJSEu7s7iYmJMlpTCCFEoTKYzNbELSnDktxZLgZrcpddnpJVnr1O9mNSMo0letqhu83xqMoaFHLr5N7WZWTdV9/t8bfOIZnz8aaMNFZP7lqiv79Lbc2ZEEIIUVZpNWo8nXV4Ouvuextms0Kq/mZNXXKGgaSMm7Vz2Qld9tQ5+qxpdizT7eS8r8+aYsdgUnL0FTTdejurf6Axqw/hPeOz9p0s3gzSnJlWrPu7H5KcCSGEEGWQWq3K6n+mJcC9ePedPWjEeGvCdvt8j7cMbske6JHXnI+3zhl56/pKPtYxZw1guTnXJKQmJzFoZvG+HgUlyZkQQgghCpXKeto5W0eSW1JSyT/loozRFUIIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQSQ5E0IIIYQoQexsHYAQQgghxO1MJjOp8Zkkx2WQHJdBepKBjFQDGWkGMlMNZKYZMepNGA1mTAaz9dpkMoNi2YaiWP4oAIqlOD0z1XZPKp8kORNCCCGEzShmhbjwVGKupRB7PYXY66nEhaeQEp9pTbIKk1FvKvyNFjJJzoQQQghRbMxmhahLSVw/G094WCIRFxLJTDPmua7GTo2Llz2uXg44uetwcNbi4KzF3kmLg7MddjoNdlo1mqyLnVaNWq0GFahUlm2orDdASU/n6rKfeK2Ynuv9kuRMCCGEEEVKn2Hkysk4Lh2P4fKJWDJSDDmW29lr8K3sgndFy8Ur0BkPPyccXbSo1KoH3r9iMBC/4hdiZs8mMyrqgbdX1CQ5E0IIIUShM5vMXD0dz9l/I7hwJBqj3mxdpnO0o3IdTwJqeBBQwx2fSi6oNYU/RlFRFFL+/puoT6ejv3gRALugyhB2rtD3VZjKbXJ29epVhg0bRlRUFHZ2dvzvf//j8ccft3VYQgghRKmWHJfByZ3XCd0TTnqS3lru5utIcCMfqjb0oUINdzRFkIzdKvPcOSI/+ZTUf/4BQOPlhe8Lz6Pu1g18fIp03w+q3CZndnZ2zJw5k8aNGxMVFUXTpk3p2bMnzs7Otg5NCCGEKFUUReHG2QSO77jGhaMxKGZLT34HFy01m/tTq5U//lXdbvb/KkKmhASiv/6G+BUrwGRCpdXiNWI43s88g8bVlaSkpCKP4UGV2+QsICCAgIAAAPz8/PDy8iIuLk6SMyGEECKfFLPCxWMxHPzjElGXk63lFWt70LBDJao28inyGjJrLIpC0voNRH7yCabYWABcu3bF77VX0QUFFUsMhaXETkK7c+dO+vTpQ2BgICqVitWrV+daZ9asWVSrVg0HBweaNWvGrl277mtfBw4cwGw2U7ly5QeMWgghhCj7zGaFcwciWfHRf/wx5zhRl5Ox06qp/3AgT/6vJf1fbkr1pn7Flpjpr1zh6pix3HjtNUyxsehqVCdo0SIqffN1qUvMoATXnKWmptKoUSNGjRrFwIEDcy1fsWIFkyZNYtasWbRr1465c+fSo0cPQkNDCcp6I5o1a0ZmZmaux27ZsoXAwEAAYmNjGT58OPPnz79rPJmZmTm2VRqqRYUQQojCpCgKF45Es2/1BRIi0wDQOmho2LESjTpXxslNV7zxGAzE/rCAmNmzUTIzUel0+EyciPfoUah0xRtLYVIpilIEU7wVLpVKxapVq+jfv7+1rFWrVjRt2pTZs2dby+rWrUv//v2ZNm1avrabmZlJ165dGTduHMOGDbvruu+++y7vvfdervLExETc3Nzy90SEEEKIUurGuQT2rAwj8qKlcsLe2Y5GnSvTsGMlHJy1xR5PZlgYN6a8ScaJEwA4t21DhalT0VWpctfHJSUl4e7uXqK/v0tszdnd6PV6Dh48yJQpU3KUd+vWjT179uRrG4qiMHLkSDp37nzPxAzgzTffZPLkydb7SUlJ0gwqhBCizIu7kcre1ee5dCwGADudmsaPBNGkaxA6x+JPIxSTibjFS4ieORNFr0ft5kaF/3sLt759i2XAQXEolclZTEwMJpMJf3//HOX+/v5ERETkaxv//PMPK1asICQkxNqf7ccff6Rhw4Z5rm9vb4+9vf0DxS2EEEKUFinxmfy3/gKn94SjKKBSq6jXLoAWvavh7G6b70P91avcePNN0g8cBMC5/cMEfPAhWn8/m8RTVEplcpbt9gxZUZR8Z80PPfQQZrP53isKIYQQ5UhmupFDmy9zbNtVjAbL92RwE19a9wvGs4LtZjRI2riR8HemYk5JQe3khN+bU/AYNKjM1JbdqlQmZz4+Pmg0mly1ZFFRUblq04QQQghxbyaDmeN/X+PAH5fITLWc6zKghjttH6tBhWB3m8VlTk8n8uNpJPz6KwCOTZsSOH06ukoVbRZTUSuVyZlOp6NZs2Zs3bqVAQMGWMu3bt1Kv379bBiZEEIIUbooZoWz+yP5d+0FkmMzAPCs4ESbAdWpGuJj05qpzLAwrr/8MpnnwkClwnvCM/g+9xwqu1KZvuRbiX12KSkphIWFWe9fvHiRI0eO4OXlRVBQEJMnT2bYsGE0b96cNm3aMG/ePK5cucKECRNsGLUQQghROiiKwtXQOPasOk/stRQAnN11tOwTTJ02FYrkXJcFkbhuPeH/+x9KRgYaHx8qTv8U57ZtbRpTcSmxydmBAwfo1KmT9X72SMkRI0awaNEiBg8eTGxsLO+//z7h4eE0aNCAjRs3UuUeQ2iFEEKI8i7yUhJ7V53n+pl4AHQOGpp2r0JI58podRqbxqaYzUR/9TWxc+cC4Ny2LYHTP8WuhJ8PszCVinnOSqLSME+KEEIIcauEyDT+XXuBsINRAKjtVDTsWInm3avi4FL8c5XdzpyWxo03ppC8dSsA3uPG4vvyy6jUhVeLVxq+v0tszZkQQgghCkdCVBoHN17izH+RlpOSq6BOqwq06FMNN29HW4cHgCE8nKvPPUdm6ClUWi0VPngfj1smny9PJDkTQgghyqiEyDQO/HGJs/9GkN1OVqWhN236V8e7oottg7tF+tGjXH3+eUzRMWi8vKj07bc4NW1i67BsRpIzIYQQooyJu5HKoc2XOftfzqSsRa9q+FctWU15ies3EP7WWyh6Pfa1alF59iy0FcvuNBn5IcmZEEIIUQYoisL1swkc2XqFyydireVVG3rTonc1/KqUrKRMMZuJ/uYbYmfPAcClUycCZ8xA42K7iW5LCknOhBBCiFLMZDJz/lAUR7ZeJfpKsqVQBcGNfWnWvUqJS8ogq+P/lDdJ3rIFAO+xYywd/zW2HSlaUkhyJoQQQpRCKfGZnNpzg9DdN0iJzwTATqumbtsAQrpUxsPPycYR5s0QEcHViRPJDD0FWi0B772Hx2MD7v3AckSSMyGEEKKUUMwK107Hc2LXdS4ejbGMvAQcXbU07FiJBh0q4uiis3GUd5Z+7BhXn3vO0vHf05NK336DU7Nmtg6rxJHkTAghhCjhkuMyOPtfBKf+CScxOt1aHlDDnQbtK1K9iR8arW1n9L+XxA0bCH/r/1AyM7GvWZNKs2eX6fNjPghJzoQQQogSyJBp4sLhKE7vi+DamXjIGnWpc9BQu3UA9R8OLFHTYdyJYjYT8+13xMyaBYBLx44EfvaZdPy/C0nOhBBCiBJCMStcP5fAmb3hhB2Oxphpsi4LrOlB7dYVqNHMD51D6fj6NqenWzr+b94MgNeY0fhNniwd/++hdLy7QgghRBkWez2Fs/sjOfdfJMlxGdZyN19H6rSuQO1WFXDzKRkz+eeXITKSaxOfI+PkSUvH/3ffxWPgY7YOq1SQ5EwIIYSwgaSYdM4diOTsf5HE3Ui1luscNNRo7k+d1hWoUN0dlUplwyjvT/rx41yb+BzG6GhLx/9vvsapeXNbh1VqSHImhBBCFJO0JD1hB6M4tz+CiAtJ1nK1nYoq9b2p2cKfaiE+2OlKb7Nf0saN3HjzrayO/zWyOv5XsnVYpYokZ0IIIUQR0qcbuXAkmnP7I7l6Ot46/QUqqFjLk1ot/Qlu7IuDs9a2gT4gxWwm5rtZxHz3HQAuHToQ+PlnaFxK/qCFkkaSMyGEEKKQGQ0mrpyI4+z+CC4dj8VkMFuX+VVxpVZLS8d+Zw97G0ZZeMypqdyYMoXkrX8C4DVqFH6vviId/++TJGdCCCFEIVDMCuHnEzi9L4Lzh6LRpxutyzz8najV0p+azf3x8C+ZM/ffL/21a1yb+ByZZ8+i0mqpIB3/H5gkZ0IIIcQDSIxO58y+cM78G0FSzM2Rls4e9tRs4U+tFv74VHYplR377yX13/+4/tJLmBIS0Pj6UOnrr3Fq0sTWYZV6kpwJIYQQBaRPNxJ2KIrTe8MJD0u0lmsdNNRo6kft1hUIrOGBSl32EjIARVGIX7aMyGmfgNGIQ/36VPruW7QVKtg6tDJBkjMhhBAiHxRFITwskZO7r3PhUDTG7H5kKqhcx5ParQMIbuKLthSPtMwPc2oq4e9MJWnDBgDcevcm4MMPUDs42DiyskOSMyGEEOIuMlINnNkXwcld14mPSLOWe1ZwonbWBLEunuUjMckMC+PaS5PQnz8PGg1+r7yC16iRZbLJ1pYkORNCCCFuoygKEecTObnrBmGHoqyjLe10amq28Kdeu0D8q7mVq6Qkce1awqe+i5Kejp2fHxW//AKnZs1sHVaZJMmZEEIIkUWfYeTMvghO7LyeY9Z+70ouNHg4kFotK6BzLF9fnaaUFCI/+pjEVasAcG7bhsAZM7Dz9rZxZGVX+fqECSGEEHlIiknn+I5rhP4Tbp0Cw06npmZzf+o/XBG/qq7lqpYsW9qhQ9x4/Q0M166BSoXPs8/i89xEmb+siElyJoQQolxSFIUb5xI49tc1Lh6NRsmauN/d15GQzpWo3ToA+3JWS5ZNMRiI/u47Yud9D2Yz2sBAAqd/KufHLCbl81MnhBCi3DIZzZw7EMnRbVeJuZpiLa9c15OQzpWpUt+7zE6BkR/px08Q/s47ZJ46BYB7//74v/1/chqmYiTJmRBCiHJBn2Hk1D/hHPnzCinxmQDYadXUbl2BkE6V8Qp0tnGEtmVOSyP6q6+J+/FHMJvRuLtT4b13ceve3dahlTuSnAkhhCjT0pP1HNt+jeM7rpGZZulP5uSmI6RzJeo/XLHUn3C8MCTv2EHk+x9guHEDsMxd5v/mFOn0byOSnAkhhCiTkmLTOfLnVU7tvmGdMNbdz5EmXYOo3boCdlrp1J55/jyRn3xK6q5dAGgDA6nw7lRc2re3cWTlmyRnQgghypTE6HQO/nGJ0/siUMyWXv6+Qa40fbQKwU18UZfj/mTZTAkJRH83i/hly8BkAq0Wr2HD8H1uImrn8t28WxJIciaEEKJMyCspq1THk6bdq1Cptme5nArjdqaUFOKWLCFu4SLMyckAuHTpgv9rr6KrWtW2wQkrSc6EEEKUanklZUH1vWjRqxoVgt1tHF3JYE5LI+6nn4ib/wOmRMuJ2u1r1cL/zSk4t2lj4+jE7SQ5E0IIUSolxaRzYKMkZXdjjIkhbulS4n9ejjkrKdNVq4bP88/h1qMHKrXaxhGKvEhyJoQQolRJT9ZzYOMlTuy8jtkkSVleMsPCiFu8hMQ1a1D0egC0QUH4PPss7n16o7KTr/+STN4dIYQQpYI+w8iRP69yZOsVDJkmwNKnrFXfYEnKAHNGBkmbNpHwy6+kHzpkLXds1AivMaNx7dJFTrtUSkhyJoQQokQzGc2c3HWdAxsvkZ5sACyjL9sMqE7lul42js62FLOZ9CNHSVq/nsT16zEnJVkWaDS4du6E18iRODZtKoMhShlJzoQQQpRIiqIQdjCKfavPkxSTAVjmKWvVN5gaTf3K7SmWFEUhIzSUpI0bSfrjD4w3wq3LtBUr4vH447g/NgCtn58NoxQPQpIzIYQQJU7kpSR2/3KOiAuWTuxO7jpa9KpG3XYBaDTlrxO7OTOTtP/+I2XH36T8/TeGa9esy9ROTrg80gX3Pn1xbtdWOvmXAZKcCSGEKDFSEzLZu/o8Z/ZFAGCnU9P00So07hqEVld++kspRiMZp8+QfugQqXv3krpvH0p6unW5yt4el06dcOvRA5cO7VE7ONgwWlHYJDkTQghhc0a9iSN/XuHgpssY9ZZTLdVuXYHW/arj4mlv4+iKnikpifQjR0g7fJj0Q4dJP3YsRzIGYOfvj0uHDrh07IBz69aonZxsFK0oapKcCSGEsBlFUbh4NIZdv5wlJS4TgArBbjz0eC38q7nZOLqioSgKhitXbiZihw+TGRYGipJjPbWrK46NG+PUrBkuHdpjX6eOdOwvJyQ5E0IIYRNJMensXHGWy8djAXDxtKfNY9Wp2dy/TCUhZr2ejJMnLYnYkcOkHT6CKSYm13raoCCcmjTBsWlTHJs0xr5GDek/Vk5JciaEEKJYmQxmDm+9woE/LmEymFFrVDTpGkSznlXLRL8yY1wc6UeOkH7oEGmHDpNx4oR1IlgrrRbH+vVxbNIEx6ZNcGrSBDsfH9sELEocSc6EEEIUm6un49j581kSItMAqFjbgw5DauNZwdnGkd0fRVEwXL9O2oEDpB88SNqBg+gvXsy1nsbTE8cmTXBq2gTHJk1waNAAtX3Z70sn7o8kZ0IIIYpcRoqBXb+e5ey/kQA4uul4aFANarYoXU2YiqKgDwsjdf9+0g8cJO3gQYyRkbnW01WvbknEGltqxnRVq5aq5ylsq9wnZ2lpadStW5fHH3+czz77zNbhCCFEmXP+UBR//3zGMru/Chp2qESrvtWwd9LaOrR8MUZHW6az+GcPqXv2YIyOzrmCnZ2libJ5M5yaNcexSWPsPD1tE6woE8p9cvbRRx/RqlUrW4chhBBlTlqSnp3Lz3D+kCWZ8QxwpvPwOlSoVrLPg6kYjaQdOkTKjr9J/ecfMs+cybFc5eCAU9OmN5OxkIaoHR1tFK0oi8p1cnbu3DlOnz5Nnz59OHHihK3DEUKIMkFRFM7+F8muX86SmWpEpVbRrHsVmveoikZbMkcfmlNTSfnnH1K2/UXKjh2YEhNzLHeoVw/ndm1xbtcOxyZNpL+YKFIlNjnbuXMnM2bM4ODBg4SHh7Nq1Sr69++fY51Zs2YxY8YMwsPDqV+/PjNnzuThhx/O9z5effVVZsyYwZ49ewo5eiGEKJ9SEzPZsfQ0l7Kmx/Cp7ELnYXXxDXK1cWS5mZKSSP5zG8mbN5O6d2+OEZUad3fLZK/t2+Pcpg12XuX7BOuieJXY5Cw1NZVGjRoxatQoBg4cmGv5ihUrmDRpErNmzaJdu3bMnTuXHj16EBoaSlBQEADNmjUjMzMz12O3bNnC/v37qVWrFrVq1cpXcpaZmZljW0lJSZYbSweC4639Jm7r8JmfDqC51snjMfdaJ8/9FMY6xRlLAfdTZLHkYz8qNag0WdeqrOusi1qT836O5bcvy1qe6zG3bU+tBY0W1HZZ19n3b12mBY3dXdbNuq+xB5k7SRSBC4ej2b70NBmpBtR2Klr0qkaTbkEl6lyY5vR0UnbsIHHDBlL/3oliMFiXaStXxrVzZ1y6dMapaVNUdiX2K1KUcSpFuW1K4hJIpVLlqjlr1aoVTZs2Zfbs2dayunXr0r9/f6ZNm3bPbb755pssXboUjUZDSkoKBoOBV155hXfeeSfP9d99913ee++9XOWJU1xxs5cROKKU0ejAzhHs7EHrAHZZF21WmXXZLfdvXU/nAjon0Dln3XYGrdPN29kXdemfs0rcmz7DyO5fz3Hqn3DAUlv2yKh6eAe62DgyC8VoJGX3bpLWbyD5r79Q0tKsy3Q1quPWsyeujzyCfc2aMqKyHEhKSsLd3Z3ExETc3ErmWShKZXKm1+txcnLi119/ZcCAAdb1XnrpJY4cOcLff/9doO0vWrSIEydO3HW0Zl41Z5UrVyZx30+4uWSf3+y2lzLPlzY/69z+kNvXKYz95PGYwlinuGK5r9etEGNRzHlcFDCb7rDsLhezyfLYXMtMN7dnMoDZkHVtvOW+MR/lhtzPqbjYOdxM1LS3JG13Su60TpZyrWPWfUfL47SON8t0WetpSsdIv7Iu4kIiWxeGkhSdDipo2i2Ilr2DS0TfssyLF0lcuYrE1atzjLDUVqqEW8+euPXqhX0tScjKm9KQnJXKOtuYmBhMJhP+/v45yv39/YmIiCiSfdrb22OfVwfQur2hhL65QgA3k8bsZM2YCcaMmxdDRgHvp4M+FQxplmt9StZ1KujTLPcVk2Xf2Y9Jiy3856W2u5nQZSdvajtLrWCOZlzdbU28upvNv9nNyqhuaYLOvp9VduuyHOtlL+OW26p83s5rH/e6Tf7Xt8ZJ3vGrNZYmdrUm67Gam2W3N83nWDeraV6txmxWc2BrOAe23EAxW0699MjIulSsbdu+WebUVJI2byFh5e+kHzhoLdd4euLWuzfuvXvhEBIiCZko0Uplcpbt9n8uRVHu6x9u5MiRhRSRECWQSmVJRjR2lgSmqCmKJQHUp4Ih9ZbELSUrebsloTOk5UzuDGmW5M+QfvO2PvWWslRLTSJYagozkywXUaxSTN5sSXiFcENdAGo5/E177Tzsf04DVLclctlJnyqPBNCS6OVeV51Vfvu6d04mMyIziN8fTdKxWMz6rM+IClzq+uPepjqujauistdCyg74d8/NxF1jf8tt3c3bOWpvb/0BIE31ouiVyuTMx8cHjUaTq5YsKioqV22aEKKYqVSW/mlaB8C7cLetKGDS507i9GlgTLc055r0tzX16nM2+5r0N29bm6iVnLezE0Dr7butp2TdVm65bc7jdh6PhzuU32l/99pHfmLKbkrPajI3m2+5nVVuzqNpPWudy5lN+TPhJTIUN3SqVDq4zaGW4+5b3yTL61sMFBMkXXMg/pwz6TE3Wza0LkY8gtNwr5qG1ukGpB6Gfwpppxr7Oydu2qymenvXrIvbLbfvUKZzzmNQkijvCpycmUwmFi1axLZt24iKisJsNudY/tdffxVacHei0+lo1qwZW7duzdHnbOvWrfTr16/I9y+EsBGVKmuAgj04ygzsxclsMvPv2gsc2nwFAN/Kzjw6shHuPh1vJnC3JnI5bueRAN6aGOb5uNvXzb6tYIiJJ+HP/cRvO4QpIdUSoFqFa7MaeHZugFNNP1RmAxj1N5Nz0623M28rz7o2Zt5cbsi4+SPAmH7zhTBlWi4ZCYXzwqrUoLslWXNwu5nAZd+2lrnlsdzdci19MMuUAidnL730EosWLaJXr140aNCgyNrtU1JSCAsLs96/ePEiR44cwcvLi6CgICZPnsywYcNo3rw5bdq0Yd68eVy5coUJEyYUSTxCCFFepcRnsOWHk4SHWSZmbdixEu0G1ij2Tv/px48Tt3AhSZu3gMnSr1Hj64PnE4PxeOIJtP5+RbNjs/lmf0trre3t11nN7vo0yEzOanJPvsMla1l24pmZaLk8CDuHW5I311tuu+eR6GUvd7dcax2zRmJn/fDR6KQ2z8YKnJwtX76cX375hZ49exZFPFYHDhygU6dO1vuTJ08GYMSIESxatIjBgwcTGxvL+++/T3h4OA0aNGDjxo1UqVKlSOMSQojy5GpoHFt+OElGqgGtg4bOw+pSo1kRJUF5UMxmUnbsIG7BQtIOHLCWOzZvhtdTT+H6yCOodLqiDUKtzhpd7EShNdUriiWhsyZsiTdvZ2T1pcy+znH7tuWGrJrD7ME3qVGFE5+dg6UJ187+tsRNe7PPn9ouq8+f3S39Au1u9hfMUX7LoBLrIJU7zQd5p4sqH+vmYzup6fd8+rZW4Kk0AgMD2bFjB7Vq1SqqmEqF0jAUVwgh7peiKBzecoV9q8+jKOAb5Eq3sfXx8HO694MLgTkjg8TVa4hbtAj9pUuWQjs73Hv1wmvUSBzq1CmWOEo8kxH0tyd0WbVzGYl5J3TW5UmWpNCQYWmqLSeSMhXcP0ku0d/fBa45e+WVV/jqq6/49ttvZSiyEEKUQfoMI38tOc35Q5ZamLrtAmj/ZC3stEU/UtEYH0/8T8uI/+knTPHxAKhdXfF8cjCeQ4eilUFfOWnsLP0vH7QPZvZgG2PGLdPt3HLflGmp6TMbbxk4Yrylv+Ht5eac65iNd5jP8dYBM+Y7r3P7nJIPsjxND2wpjFe/yBQ4Odu9ezfbt2/njz/+oH79+mi1OTshrly5stCCE0IIUbwSotL4Y85x4m6kotaoeHhwLeo/HFjkP8YNkVHELVhA/C+/oKRbmp20gYF4jRyB+2MD0bg4F+n+y71bB9uUdUlJMNHd1lHcVYGTMw8PjxwjJIUQQpQNl47HsHVBKPp0I05uOro/05CA6kX7Jaa/dp3Y+d+T+PtK63kuHerXx3vsGFy7dpXzW4pyqcCf+oULFxZFHEIIIWwku3/Z3tXnQYEKwe50f6YBzu5FV4uSeeEisfPmkbhunXXkpWOzZvhMmIDzQ+2k24wo1+77J0l0dDRnzpxBpVJRq1YtfH19CzMuIYQQxcBkMLNj2WlO77VM6l3/4UAeHlwLjV3RTJORcfo0MXPmkrx5s3UiXud27fCZ8AxOLVoUyT6FKG0KnJylpqbywgsvsGTJEusEtBqNhuHDh/PNN9/g5FQ8I3mEEEI8mPQUPX/MOU54WCIqFTz0RC1COlUqkn1lhIYS/e13pNwyUblLly74THgGx4YNi2SfQpRWBU7OJk+ezN9//826deto164dYBkk8OKLL/LKK68we/bsQg9SCCFE4Yq7kcqGWUdJislA56Dh0XENCKpfyKfbAjLOnCXm229I3vqnpUClwq1Hd7yfeQaH2rULfX9ClAUFnufMx8eH3377jY4dO+Yo3759O0888QTR0dGFGV+JJfOcCSFKqysnY9n8/Qn0GSbcfBzoNbERXoGFOxoyMyyM6O++I/mPTZYClQq3Xr3wmTgR++BqhbovIQqiNHx/F7jmLC0tLc+Ti/v5+ZGWllYoQQkhhCgaJ/6+xs4V51DMCgE13OnxTEMcXQtvhv3MixeJmTWbpPXrrX3KXHt0x/e557CvUaPQ9iNEWVbg5KxNmzZMnTqVJUuW4ODgAEB6ejrvvfcebdq0KfQAhRBCPDjFrLBvzXnricvrtK5Ax6frFNr5MfVXrxIzazaJa9ZYJiAFXLs+gs/zz0vzpRAFVODk7KuvvqJ79+5UqlSJRo0aoVKpOHLkCA4ODmzevLkoYhRCCPEATEYzfy05xdn/IgFo1bcazXpULZTpKgzXrxMzZw4Jq1aD0QiAS6dO+Dz/HI716z/w9oUojwrc5wwsNWVLly7l9OnTKIpCvXr1ePrpp3F0dCyKGEuk0tBmLYQQmelG/phznOtn4lGrVXQcWoe6bQMeeLvG2Fhi5swlfvlyyJo81vnhh/F94XkcQ0IeePtCFJXS8P19X/OcOTo6Mm7cuMKORQghRCFKic9k/bdHib2egtZeQ/dnGhBU78FGZJpSUohbsJDYRYtQsvoZO7Vuje+LL+LUtElhhC1EuZev5Gzt2rX06NEDrVbL2rVr77pu3759CyUwIYQQ9y/2RgrrvzlKSnwmTm46ej/fCN8g1/venjkzk/hlPxM7dy6mhAQAHBo0wG/yyzi3bVtIUQshIJ/Nmmq1moiICPz8/FCr79x5VKVSYco6DUdZVxqqRYUQ5dONc/FsmHUcfboRzwpO9H6+EW4+99ftRDEaSVyzhuhvv8MYHg6Arlo1fCdNwrVbVznNkih1SsP3d75qzrLPBHD7bSGEECXLxWMxbJ53ApPRTEB1d3pODMHBWVvg7SiKQvLWrUTP/Ar9hQsA2FWogO8Lz+Per5+ckFyIIlTgMdRLliwhMzMzV7ler2fJkiWFEpQQQoiCO/NvBH/MOY7JaKZqiA99X2p8X4lZ6r59XHpiMNdffAn9hQtoPDzwe+MNqm/ehMfAgZKYCVHECjxaU6PREB4ejp+fX47y2NhY/Pz8pFlTCCFs4Nj2q+xacQ6A2q0r0HlYHdSagv3+zggNJeqzz0ndswcAlZMT3iNH4DVqFBrX+++vJkRJUhq+vwv880dRlDz7GFy7dg13d/dCCUoIIUT+KIrC/g2X2L/+IgAhnSrx0OM1Uanz3xfMcOMG0V99ReLadZZZ/bVaPAcPxmfCM9j5+BRV6EKIO8h3ctakSRNUKhUqlYouXbpgd0u1tslk4uLFi3Tv3r1IghRCCJGbYlbY/es5jm2/BkDLPtVo3jP/k8uakpOJnfc9cYsXo+j1ALj16oXvy5PQVapUZHELIe4u38lZ//79AThy5AiPPvooLi4u1mU6nY6qVasycODAQg9QCCFEbiaTme1LTnPm3wgAHh5ck5BOlfP1WEWvJ37FL8TMmoUpPh4ApxYt8Hv9NRwbNiyymIUQ+ZPv5Gzq1KkAVK1alSeffBJ7e/siC0oIIcSdGQ0mNn9/kkvHYlCpVXQZUZfarSrc83GKopC8ZStRX3yO4bLlHJu64GD8Xn0Vl04dZVoMIUqIAvc5q1evHkeOHKFVq1Y5yv/99180Gg3NmzcvtOCEEELkZNCb2DjrGNdOx6OxU/Po+AZUC7l3v7C0Q4eJmjGD9MOHAdD4+OD7/PN4DJLRl0KUNAWeSuO5557j6tWrucqvX7/Oc889VyhBCSGEyE2fYWT9N0e5djoeO3sNfV5odM/ETH/lCtdefInLTz1F+uHDqBwd8Zn4LNU3bcLzycGSmAlRAhX4vzI0NJSmTZvmKm/SpAmhoaGFEpQQQoicMtMtiVnEhUR0Dhp6v9CYgOp3HiFvSkkhZvZs4pf8iGIwgFqN+2MD8H3hRbT+fnd8nBDC9gqcnNnb2xMZGUlwcHCO8vDw8BwjOIUQQhSOjFQD674+QtTlZOyd7OjzYmP8q+Y9P5NiMpGwciXRM7/CFBsLgHO7dvi98ToOtWoVZ9hCiPtU4Gyqa9euvPnmm6xZs8Y6r1lCQgJvvfUWXbt2LfQAhRCiPEtP1rP26yPEXE3BwVlL30mN8a2c94Swqf/9R+S0T8g8dQoAXdWq+E15A5cOHaSzvxClSIGTs88//5z27dtTpUoVmjRpAlim1/D39+fHH38s9ACFEKK8Sk3MZO1XR4i7kYqjm45+LzXGu6JLrvX0164RNX0GyVu2AKB2dcX3+efwHDIElU5X3GELIR5QgZOzihUrcuzYMX766SeOHj2Ko6Mjo0aNYsiQIWi1BT+HmxBCiNxS4jNZM/MwCZFpOLvr6PdyEzwrOOdYx5SSSuzcucQtWmTtV+Yx+Al8X3wRO09PG0UuhHhQ99VJzNnZmfHjxxd2LEIIIYCk2HTWfHmYpJgMXLzs6f9yE9x9nazLFUUhad06ImfMwBQdA4Bz2zb4TZki/cqEKAPuuwd/aGgoV65cQZ91yo9sffv2feCghBCivEqOy2D1F4dJjs3AzceBfi83wc3b0bo848wZIj74gPQDBwHQVgnC/403cOnUSfqVCVFGFDg5u3DhAgMGDOD48eOoVCoURQGwHhRMJlPhRiiEEOWEJTE7RHJsBu6+jvSf3AQXTwfAch7M6G++If6nZWAyWeYre/ZZvEaOQC39yoQoUwo8Ce1LL71EtWrViIyMxMnJiZMnT7Jz506aN2/Ojh07iiBEIYQo+1LiLYlZUkwGbrckZoqikLh2Led79CR+yY9gMuH66KNU37Aen/HjJDETogwqcM3Z3r17+euvv/D19UWtVqNWq3nooYeYNm0aL774IoezTg0ihBAif1LiM1n1haWPmZuPA/1ftiRmGWfOEvHB+9YmTF3Vqvi//TYuD7WzccRCiKJU4OTMZDLh4mIZyu3j48ONGzeoXbs2VapU4cyZM4UeoBBClGUp8Zms/vIQSdHplsRsclOc7U1ETvuEuKVLpQlTiHKowMlZgwYNOHbsGMHBwbRq1Yrp06ej0+mYN29errMGCCGEuLPURMt0GYlR6bh6Wzr/c2Qv5z/4AGN4OACujz6K/xuvow0MtHG0QojiUuDk7O233yY1NRWADz/8kN69e/Pwww/j7e3NihUrCj1AIYQoi1ITM1n9hWUeMxcve3oPDyLp/TdJ3rwZAG2lSlSYOhWXhx+ycaRCiOKmUrKHWz6AuLg4PD09y9Uw7qSkJNzd3UlMTMTNLe9z3AkhRF7SkvSs/uIQ8RFpuHja07nWddJmfYY5ORk0GrxHjcTnuedQOzree2NCiAIpDd/fBao5MxqNODg4cOTIERo0aGAt9/LyKvTAhBCiLEpL0rP6y8PER6Th7KKhxeUlpKzaCYBDSAgB77+HQ506No5SCGFLBUrO7OzsqFKlisxlJoQQ9yEj1cDarw4TH56Ko52Bhn9/gCo5ArWTE74vv4znU0NQaTS2DlMIYWMFnufs7bff5s033yQuLq4o4hFCiDIpM93Iuq+PEHs9FXtTCo3++Qin5AhcOncmeMN6vIYNlcRMCAHcx4CAr7/+mrCwMAIDA6lSpQrOzjlPxHvo0KFCC04IIcoCQ6aJ9V8fJupyMlp9Mo2PzMTVRaHCJ1/h2q1rueqvK4S4twInZ/379y+CMIQQomwyGkysm/4PEdeN2BnSaHzsWwIeaUGFt95C4+Fh6/CEECVQvkdrLliwgKeffhp7e/uijqlUKA2jPYQQtmVISWPtO5uISPNAY8yg6ZUfqTtlHK6dO9s6NCHKrdLw/Z3v5Eyj0RAeHo6fnx8AgYGB7Nmzh6pVqxZlfEXq4sWLjB49msjISDQaDfv27cvVTHsnpeHNFULYTsqBQ2z66l8inWujNulp53aU+v97ptTUlqUZ0riRcoPItEjiM+OJz8i6ZMaTok/BYDagN+kxmA0YzAY0Kg1atRY7tR1atRZnrTPu9u6Wi85y7efkR4BzAL5OvtipC9xwI0ShKA3f3/n+77g9h0tOTsZsNhd6QMVp5MiRfPjhhzz88MPExcVJraAQ4oGZMzOJ+vIrdv9rJtK/JSqzkU6ddNR56g1bh5aLoijEZsRyNv4s5+LPcTb+LJeTLnMt+RqxGbFFtl+1Sm1N1Kq6VaW6R3WC3YMJ9ggmwDkAtarAY9WEKFPK7U+XkydPotVqefjhhwGZq00I8eAyTp3i2muvcVzdksjAh1BhptvI2tRoW8XWoQGQbkznRMwJjkYf5WjUUY7FHCMu484j7111rgQ4B+Dp4ImXvRceDh54OnjiqnVFp9GhVWvRarRo1VrMihmj2WipSTMZSDYkk6RPIikzicTMROIz44lMjSQiLQKj2UhEagQRqREcjjqcY5+Odo7U9apLfZ/6NPRpSAPvBlRyrSSDJkS5ku/kTKVS5fjnuP1+Ydu5cyczZszg4MGDhIeHs2rVqlyDEWbNmsWMGTMIDw+nfv36zJw505ps3cu5c+dwcXGhb9++XLt2jUGDBvHWW28VwTMRQpR1islE7IIFRH39Deeq9OVGoOWUS13HNKRGC3+bxaU36TkSdYS94XvZd2Mfp+NOY1SMOdZRq9QEuQZR07MmNT1rUt29OpVcK1HRpSLu9u6FHpNZMRObHkt4ajjXU65zMfEi5xPOcyHxApeSLpFuTOdQ1CEORd0c+e9h70Fz/+a0DGhJqwqtqOZeTZI1UaYVqFmzVq1a1n+IlJQUmjRpglqds/q5sOY/S01NpVGjRowaNYqBAwfmWr5ixQomTZrErFmzaNeuHXPnzqVHjx6EhoYSFBQEQLNmzcjMzMz12C1btmAwGNi1axdHjhzBz8+P7t2706JFC7p27ZpnPJmZmTm2lZSUVCjPUwhRuumvXePGG1NIP3iQi1V7ca2SpbN/5+F1qGmDxOxq0lW2X93OnvA9HIo8RLoxPcdyPyc/Gvk2orFvYxr5NaKWZy0c7YrvNFFqlRpfJ198nXwJ8Q3JscxgNnAl6QonY09yPPo4J2NPcjruNAmZCfx55U/+vPInAD6OPrQOaE3Hyh15qOJDOGvz11dYiNIi3wMCFi9enK8Njhgx4oECyotKpcpVc9aqVSuaNm3K7NmzrWV169alf//+TJs27Z7b3Lt3L++99x6bNm0CYMaMGQC89tprea7/7rvv8t577+UqL8kdCoUQRUdRFBJXriLyo48wp6VxLbgbZ4P6AfDw4FqEdKpUbHGcijvFX1f+4q+rf3Eu/lyO5T6OPrQJaEObwDY0929OgEtAscRVWPQmPaGxoeyP2M+/Ef9yJOoImaabP5S1ai0tK7Skc1BnulbpiqeDpw2jFaVBaRgQUCgnPi9qtydner0eJycnfv31VwYMGGBd76WXXuLIkSP8/fff99ym0WikRYsW/PXXX7i7u9OvXz+eeeYZevfunef6edWcVa5cuUS/uUKIomGMiyNi6lSSt1pqcmJbDeaoY3sAWvapRote1Yp0/4qiEBoXyoYLG/jz8p+Ep4Zbl2lUGpr7N+fhSg/TJrANNT1qlqkmQL1Jz9Hoo+y6tovtV7dzKemSdZmdyo6HKj1En+A+dKjcAXuNDPISuZWG5KxUDgiIiYnBZDLh75+zycDf35+IiIh8bcPOzo6PP/6Y9u3boygK3bp1u2NiBmBvby+jOYUQJO/YQfjb/8MUEwNaLfrhb3DsYgCYoVHnyjTvWbXI9n0l6QobLm5g44WNOZISRztH2gW2o3NQZ9pXal8kfcVKCp1GR4sKLWhRoQWTm0/mQuIFtl/ZzuZLmzkVd4odV3ew4+oOXHWu9K/RnyG1h1DZrbKtwxaiQEplcpbt9l+DiqIU6Bdijx496NGjR2GHJYQog8xpaUROn07C8hUA2NesAS98wN9rE1DMZuq0rkC7QTUKvZYqMTORjRc3su78Oo7HHLeW22vs6VS5E92rdadtYNti7TdWkgS7BxPcMJgxDccQFh/Gugvr2HBhA5FpkfwY+iNLQ5fycKWHebrO07QJbFOmahFF2VUqkzMfHx80Gk2uWrKoqKhctWlCCPGg0o8e5frrr2O4fAUAr5EjUQaOYe23JzEZzVRr5EOnYXVQqQvni19RFA5EHmDluZVsvbzV2sdKrVLTJqANPYN70iWoi3SEv00Nzxq83OxlXmr6Eruv72bZ6WX8c/0fdl7byc5rO6nnXY8JIRPoWLmjJGmiRCuVyZlOp6NZs2Zs3bo1R5+zrVu30q9fPxtGJoQoSxSjkZg5c4mZPRtMJuwqVCDwk2lkVmnIqs8OYcg0UbG2B93G1ketefCJU2PSY1h7fi0rz63kctJla3lNz5o8VuMxulfrjo+jzwPvp6xTq9S0r9Se9pXacynxEsvPLGfluZWExoby4vYXqeNVh2cbPUunyp0kSRMl0n0nZ3q9nosXL1K9enXs7Ao/x0tJSSEsLMx6/+LFixw5cgQvLy+CgoKYPHkyw4YNo3nz5rRp04Z58+Zx5coVJkyYUOixCCHKH/2VK9x47XXSjx4FwK13byq88z9SDVrWfXaIjFQDflVc6flsCHZazX3vR1EU9kfsZ/mZ5Wy/st06D5mTnRM9qvVgYM2BNPBpIEnEfarqXpUpLacwPmQ8S04u4efTP3M67jQvbX+J5v7Nea3Fa9TzrmfrMIXIocCjNdPS0njhhResU2ucPXuW4OBgXnzxRQIDA5kyZUqhBLZjxw46deqUq3zEiBEsWrQIsExCO336dMLDw2nQoAFffvkl7du3L5T930tpGO0hhCi426fIULu6UmHqVNx79yItSc/Kzw6SGJWOZwUnBrzaFEcX3X3tJ82QxoaLG1h2ahlhCTd/iIb4hDCw1kAerfqoNFsWgYSMBBaHLubH0B/JNGWiQkWf6n2Y3Gwy3o7etg5PFIPS8P1d4OTspZde4p9//mHmzJl0796dY8eOERwczNq1a5k6dSqHDx++90bKgNLw5gohCsYYH0/EO1NJ3roVAKcWLQj89BO0gYFkphtZ/cUhYq6m4OJlz8DXmuHi6VDgfVxLvsaKMyv4/dzvJOuTActoyz7BfXii9hPU9qpdqM9J5C0iNYKZh2ay4cIGANzt3Xmt+Wv0rd5XainLuNLw/V3g5KxKlSqsWLGC1q1b4+rqytGjRwkODiYsLIymTZuWm5nzS8ObK4TIv5R//iF8ypsYo6NBq8X3xRfwHj0alUaDUW9i7ddHCA9LxNFVy2OvNsPD3ynf21YUhf8i/uOnUz+x4+oOFCyH3UoulRhSZwj9a/bHTSfHEVs4Fn2MD/Z9wOm40wC0DmjNu23fpaJLRRtHJopKafj+LnBnsejoaPz8/HKVp6amyq8NIUSpY87MJPqLL4hbvAQAXXAwgTOm41i/vmW5yczm+ScJD0tE56Chz4uN852YGcwGNl3cxOKTizkTf8Za3iagDU/XfZqHKj6ERn3//dXEgwvxDWFZr2UsObmE2Udnsy98H4+vfZx32rxD92rdbR2eKKcKnJy1aNGCDRs28MILLwA35xr7/vvvadOmTeFGJ4QQRSjjzBluvPoamecspzzyfGoIfq+9htrRMmeYoij8vewMl47FoNGq6fVcI3wru95zuyn6FH4/9zs/hv5IZFokYGm67Fu9L0/VeYpgj+Cie1KiwLRqLWMajqFrla68tfstjkYf5bWdr7H7+m7ebPWm9P0Txa7Aydm0adPo3r07oaGhGI1GvvrqK06ePMnevXvzddokIYSwNcVsJm7xEqK/+ALFYEDj7U3gxx/h0qFDjvX2r79I6D/hqFTQbUx9Amt63HW7UWlRLD21lN/O/EaywdKfzNvBm6frPs0TtZ8o0zP3lwVBbkEs6r6IucfmMu/YPNacX8OxmGN83elrqrpXtXV4ohy5r3NrHj9+nM8++4yDBw9iNptp2rQpb7zxBg0bNiyKGEuk0tBmLYTIzRAZyY0pU0jbuw8Al06dCPjwA+y8c47UO7HzOn8vszRFdniqNg3a37kPUlh8GItOLmLDxQ0YzZapMKq6VWVk/ZH0rt5bzvFYCh2MPMjrO18nKi0KV60r0ztM56GKD9k6LFEISsP3d6k48XlJVBreXCFETkmbNhM+dSrmxERUDg74T5mCx+AncvWXvXAkmk1zj6Mo0LxnVVr1zbsZ8mTMSeYdm8dfV/+yljX1a8qoBqNoX6k9atWDT0wrbCcmPYbJOyZzOOowKlS83OxlRtYfKf2rS7nS8P2dr2bNgozALKlPVAhRfpkSE4n44EOS1q8HwKFBAwKnT8c+uFqudcPDEtjyw0kUBeq2C6Bln9zrHIk6wpxjc/jn+j8AqFDxSJVHGFl/JCG+IUX7ZESx8XH04YduP/Dxfx/z29nf+OLgF0SmRfJ6i9cl8RZFKl/JmYeHxz1/KWSfdNxkMhVKYEIIURhSdu0i/P/exhgVBWo13uPH4fvcc6i02lzrxoWnsmHWMUwGM1UbetPxqdrWY1/2dBjzjs3jv4j/ANCoNPQK7sWYhmMIdpdO/mWRVqNlapupBLsHM33/dH469ROx6bF89NBH6DT3NwGxEPeSr+Rs+/btRR2HEEIUKlNKKlHTp5Pwyy8A6KpWJfDTT3Bs1CjP9VPiM1n39REy04z4V3Oj27gGqDVqFEVh1/VdzDs2j6PRllM52ant6Fe9H2MajKGyW+Vie07CdobVG4a3gzf/98//senSJhIzE/mq81c42jnaOjRRBkmfs/tUGtqshSiv0vbv58abb2G4dg0Az+HD8Hv5ZesUGbfLTDOw6vNDxF5PxcPficdea4q9sx3br2xn7rG5nIo7BYC9xp6BNQcyqsEoKjhXKLbnI0qOPTf28PL2l0kzptE6oDXfdP4GB7uCnylC2E5p+P6+r+QsISGBH374gVOnTqFSqahXrx6jR4/G3b38DBMvDW+uEOWNOSOD6JlfEbd4MSgK2sBAAj7+GOfWre74GKPBxLqvj3LjXAJObjr6v9aEfSk7mXdsnvWcl452jgyuPZgR9Ufg4+hTXE9HlFCHIg8x4c8JpBvTaRPQhq87fy0JWilSGr6/C5ycHThwgEcffRRHR0datmyJoigcOHCA9PR0tmzZQtOmTYsq1hKlNLy5QpQn6cePc2PKm+jPnwfAfdBA/KdMQePicsfHmM0KW+af4PyhaLQOGjyeSGRJ5DwuJ10GwEXrwpA6QxhWbxieDp7F8jxE6XBrgtYusB3fdP4GrSZ3P0ZR8pSG7+8CJ2cPP/wwNWrU4Pvvv8fOztJlzWg0MnbsWC5cuMDOnTuLJNCSpjS8uUKUB+aMDKK/+Ya4hYvAbEbj60PA++/j2qnTXR+nKAq7fjnH8e3XQK2wp8kKjun2ApaTYA+rO4whdYfIOS/FHR2MPMizfz5LujGd3sG9+eihj2QUZylQGr6/C5ycOTo6cvjwYerUqZOjPDQ0lObNm5OWllaoAZZUpeHNFaKsS9u/nxtvv43h8hUA3Hr2xP9/b2Pnee9arn//COPAGsvjttZcxHmfw3g5eDGy/kgG1x6Mkzb/JzYX5dfu67t5YdsLGBUjoxqMYnKzybYOSdxDafj+LvDpm9zc3Lhy5Uqu5Ozq1au4ut77nHNCCPGgTCkpRH3+OQk/LwfAzs+PCu++i2vnu9eWAaQaUvlpzXoMf/oC8E/VlSQHXWdKgykMrDlQ+g6JAnmo4kO82/Zd3v7nbRaeWIifox9D6w21dViilCtwcjZ48GDGjBnDZ599Rtu2bVGpVOzevZvXXnuNIUOGFEWMQghhlbJzJ+FT38UYHg6Ax+OP4/faq2ju8Qs4MTORZaeXsW33PtqfGIoGCKvyLwMe60C/6l/InFXivvWr0Y/o9Gi+OvQV0/dPJ8gtiPaV2ts6LFGKFTg5++yzz1CpVAwfPhyj0XIOOa1Wy7PPPssnn3xS6AEKIQSAMT6eqE8+IXHNWgC0lSoR8OEHOLdufdfHxWXEsTR0KT+f/hnHeC/6nnwejaLBqa6BT597BZ2dJGXiwY1pMIbrKdf57exvTNk5hWW9lsnJ0sV9u+95ztLS0jh//jyKolCjRg2cnMpX/4zS0GYtRFmgKApJ6zcQ+cknmGJjQaXCa/gwfF96CfVdjjtRaVEsOrmI387+RroxHbd0HwaFvoJO70SlOp70fr4RGjvpvC0Kj8FkYMyWMRyOOkw192r81PMnXHXS3aekKQ3f3zIJ7X0qDW+uEKVd5sWLRLz/Pml79wGgq16dwI8+xLFx4zs+5nrKdRaeWMjKcysxmA0ANHJpRvv9wzAkqPANcqX/5CboHArccCDEPcWkx/Dk+ieJTIukQ6UOfN35axnBWcKUhu/vfB+dRo8ena/1FixYcN/BCCEEgDkzk9jv5xM7dy6KwYDK3h6fZyfgNXo0al3ezZCXEi8x//h8NlzYgFGxdLlo4teEsbXHE/GzjuiEFNx8HOj9fCNJzESR8XH04atOXzFi0wj+vvY3S04uYWSDkbYOS5Qy+T5CLVq0iCpVqtCkSROksk0IUVRS9+wh4r330V+2TATr3K4dFaa+gy4oKM/1z8afZf6x+Wy+vBmzYgagdUBrxoeMp4l3UzbOPk701TgcXLT0eaExTm7Sx0wUrfo+9Xmj5Ru8v/d9vjr0Fc38m9HQt6GtwxKlSL6TswkTJrB8+XIuXLjA6NGjGTp0KF5eXkUZmxCiHDHGxBD5yackrV8PgMbXhwpvvYVr9+6oVKpc65+IOcG8Y/PYfnW7taxjpY6MCxlHiG8Iilnhz8WhXA2Nw06npvfzjfDwL199Y4XtDKo5iH039rHl8hZe2/kav/b5VfqfiXwrUJ+zzMxMVq5cyYIFC9izZw+9evVizJgxdOvWLc+DZ1lWGtqshSgNFJOJ+BUriP5yJubkZFCp8HzqKXwnvYQmj7kTD0UeYt6xefxz4x8AVKjoWqUr40LGUcfr5vyLe1aGcXjLFVRqFb0mhlClgXexPSchAJL1yTy+7nGup1yne9XuTG8/vdx9V5ZEpeH7+74HBFy+fJlFixaxZMkSDAYDoaGhuNzlHHZlTWl4c4Uo6dIOHCDiw4/IPH0aAId69ajw3ns4NmyQYz1FUdgbvpfvj33PgcgDAGhUGnoF92JMgzEEewTnWP/otqvs/vUcAF1G1KVOm4BieDZC5HYs+hgj/hiBUTEyo/0MulfrbuuQyr3S8P19371iVSoVKpUKRVEwm82FGZMQoowzREYSNX0GSRs2AKB2c8P3xRfxfHIwKrubhyVFUfj72t/MOzaP4zHHAbBT29G/Rn9GNxhNZdfKubZ97kAku3+zJGat+wdLYiZsKsQ3hPEh45l1dBYf/vshzSs0x8fRx9ZhiRKuQMnZrc2au3fvpnfv3nz77bd0794dtVqGCgsh7s6s1xO3aDExc+agpKWBSoXH44/j+/KkHOfDNJlNbL2ylfnH5nMm/gwA9hp7BtUaxMj6I6ngXCHP7V87E8+fi0JBgYYdK9H00SrF8ryEuJuxIWP56+pfnI47bRkk0Okrad4Ud5Xv5GzixIksX76coKAgRo0axfLly/H2lj4cQoj8Sd6xg8hp06wnKXds0gT/t/8Px/r1resYzAbWn1/PghMLuJR0CQAnOyeerPMkw+oNu2uNQ8y1ZP6YfQyzUaF6U18eeqKmfAGKEkGr1vJhuw95csOTbL+6nfUX1tOneh9bhyVKsHz3OVOr1QQFBdGkSZO7HvBWrlxZaMGVZKWhzVqIkkB/6RKR0z4h5e+/AcsoTP9XX8Wtb1/rsSTDmMHKcytZdHIR4amWc2a66dx4uu7TPF33adzt3e+6j6SYdH6fcZC0RD2BNT3o82Ij7LSaon1iQhTQvGPz+ObwN7jp3Fg3YB1eDjLjgS2Uhu/vfNecDR8+XH6FCiHyzZScTOzcucQtXoJiMIBWi9fwYfg8OxGNizMAKfoUVpxZwZLQJcRlxAHg7eDNiPojeKL2Ezhrne+5n4wUA+u+OUpaoh6vQGd6PttQEjNRIo1uMJotl7ZwJv4MXxz4gg8f+tDWIYkSSk7fdJ9KQ+YthC0oRiPxv/xCzDffYoqPB8D5oYfwf+st7IOrARCfEc/SU5aTkSfrkwEIdA5kdIPR9K/ZH3uNfb72Zcg0sWbmYSIvJuHiac/A15vj4pm/xwphC0ejjzJs4zAUFBY+upDmFZrbOqRypzR8f8s5TIQQhUJRFFJ37iRy+gz0588DoAsOxu+1V3Hp2BGVSkVkaiSLQxdbT0YOUM29GmMbjqVHtR5o1dp8789kMrP5+xNEXkzC3smOPi80lsRMlHiNfBsxqNYgfj37Kx/u+5Bf+/yKVpP/z70oHyQ5E0I8sIwzZ4j6dDqpe/YAoPH0xOeF5/F8/HFUWi1Xk66y4OQC1oStsZ6MvK5XXcaFjKNLUJcCnxhaURR2/HiayydisdNaZv/3Crx3E6gQJcFLTV9i25VtnE88z+LQxYxtONbWIYkSRpIzIcR9M0ZHE/311yT8vhLMZlRaLZ7Dh+HzzDNo3Nw4F3+OH078wB8X/7Ce97KpX1PGh4ynbWDb++7Hum/1eU7vi0ClVvHouAZUCL77gAEhShJ3e3debf4qb+1+i3nH5tG3el/8nPxsHZYoQSQ5E0IUmDk9nbhFi4j5fr5lvjLAtUd3/F55BV2lShyPPs73f32f47yX7Sq2Y1zDcTTzb/ZA+z7y5xUObbZMx9FpaB2qhsiEnqL06R3cm1/O/MKR6CN8fehrGRwgcpDkTAiRb4rZTNL69UR98SXGiAgAHBqF4P/GFBybNGZ/xH6+3/Ie+8L3AZbzXj5S5RHGNhxLPe96D7z/M/9G8M9vYYBl9v+6bWX2f1E6qVQqXmvxGk9vfJq159fyVN2nCuV/RJQNkpwJIfIl5Z9/iPr8czJDTwFgFxiA3yuv4NqjB7uu7+L7P4ZxNPoocMt5LxuOIdg9+G6bzbcrobH8tdiy75DOMvu/KP1CfEPoWa0nGy9uZMb+GSx4dIFMWSUASc6EEPeQfuIk0V98TuqevQConZ3xHj8e92FPsy1yF9+vf5yz8WcB0Kl1DKg5gFENRlHRpWKhxRB5KYk/5p7AbFao2cKfhwbJ7P+ibJjUdBLbrmzjQOQB/rryF12qdLF1SKIEkORMCJEn/ZUrRM/8iqSNGwEsnf2fegqP8WPYkrCPeZufzHGKpcF1BjO83vBCP6lzQmQa6789ijHTRKU6nnQZUReVWhIzUTYEuAQwov4I5h2bxxcHv6B95fYFmlJGlE2SnAkhcjDGxhIzazbxK1aA0QgqFW59euP5wkQ2Zxzm+79HcDX5KmA5xdLQukN5qu5T9zzF0v1ITcxk7ddHyEgx4BvkSo8JDdHYFWzaDSFKujENxvDb2d+4knyFNWFrGFRrkK1DEjYmyZkQAgBTSipxixYRt2AB5qwRmM4PP4znS8/zh/Y0C/6bwPWU6wB42nsyvP5wnqz9JC46lyKJJzPdyLpvjpIcm4G7ryO9n2+EzkEOWaLscdI6Ma7hOD7d/ylzjs6hT/U++T5Lhiib5EgnRDmn6PXE//orMbNmY4qNBcChQQM8X36RP7yv8cPxyUSmRQKW816OajCKx2s9jpPWqchiMhpM/DH7GLHXUnB009HnxcY4uemKbH9C2NrjtR9n0clFRKZF8suZXxhWb5itQxI2JMmZEOWUYjaTvGkTUTO/wnDFMm+YtkoQHi8+xx9VE1h4cirRYdEA+Dn6MbrhaAbWHIiDnUORxmU2K/y5IJTrZxPQOmjo80Ij3H0di3SfQtiavcaeZxs9y7t732X+8fkMrDmwSH8AiZJNkjMhyqHUvXuJ+uxzMk6eBEDj44P7hLH80cDAwjOfE3cgDoAKzhUY02AMA2oOKJZmFkVR2Ln8LOcPR6O2U9Hz2RB8K7sW+X6FKAn61ujLghMLuJJ8haWnljI+ZLytQxI2IsmZEOVI+rFjRM+ceXNaDCcnXEYNY3MrHQsvzCfhaAIAFV0qMrbhWPpV71esJ2U+sPESJ3deBxV0HVWfSrU9i23fQtiaVq1lYuOJTNk1hUUnFvFknSdx07nZOixhA+U6Ofvyyy+ZP38+iqLwyCOP8NVXX8ncSaJMyjh7luivvyblz22WAq0W58cHsKWjGwuv/0rSqSQAglyDGBcyjl7BvYp9OP+Jndf5b91FANoPrkWNZnKuQVH+9KjWg++Pfc/5xPMsP71cas/KqXKbnEVHR/Ptt99y8uRJtFot7du3Z9++fbRp08bWoQlRaPSXLxP97XckrV8PigJqNU59evLXIz58H72G5IvJAFRzr8b4kPF0r9odO3XxHxYuHI5m589nAGjesyoNO1Yq9hiEKAnUKjXjQsYxZdcUfgz9kaF1h0rfs3Ko3CZnAEajkYyMDAAMBgN+fvJLXZQNhogIYmbNJmHlSstcZYBjt0fY+Wggc5PWk3TDUlNWw6MGz4Q8Q9cqXdGoNTaJ9ca5eLb8cBJFgXoPBdKyTzWbxCFESfFo1UeZdWQWV5Kv8OvZXxlRf4StQxLFrMTO5rhz50769OlDYGAgKpWK1atX51pn1qxZVKtWDQcHB5o1a8auXbvyvX1fX19effVVgoKCCAwM5JFHHqF69eqF+AyEKH7GuDgiP/mU890eJeGXX8BoxOGhdhz5dChD2x5mRswykvRJBLsHM6PDDH7v+zvdq3W3WWIWcy2FDbOOYzKaqdbIhw5DaknXAlHu2antGNNwDACLTi4i05Rp44hEcSuxNWepqak0atSIUaNGMXDgwFzLV6xYwaRJk5g1axbt2rVj7ty59OjRg9DQUIKCggBo1qwZmZm5P9RbtmzB0dGR9evXc+nSJRwdHenRowc7d+6kffv2Rf7chChspuRk4hYuJG7RYusEsvZNm3BwQB2+Mf1JfMK/AFR1q8qzjZ7l0aqP2iwhy5YUk866b46gTzcSUMOdbmPqo9aU2N+LQhSrPsF9mH10NhGpEaw6t4on6zxp65BEMVIpiqLYOoh7UalUrFq1iv79+1vLWrVqRdOmTZk9e7a1rG7duvTv359p06bdc5u//vorO3bs4LvvvgNgxowZKIrC66+/nuf6mZmZORK9pKQkKleuTGJiIm5uMppG2IY5PZ24pUuJnf8D5sREAHT16nD8sRC+tNtOXGY8YOnoP6HRBHpW61nsSZnJZMJgMOQoy0jVs3VBKEkxGbj7OdJ1VD3sneR8goVBq9Wi0dg28RaF4+fTP/Pxvx8T4BzAhgEbinXkdFmWlJSEu7t7if7+LrE1Z3ej1+s5ePAgU6ZMyVHerVs39uzZk69tVK5cmT179pCRkYFWq2XHjh2MH3/nUTHTpk3jvffee6C4hSgs1ln958zBFB0DgDa4GqcGNuFz593EZq4EE1RyqcSERhPoFdyr2Dv6K4pCREQECQkJucrTkvRUaWOPSu2Ak7uOG5HXijW2ss7Dw4MKFSpIE3EpN6DGAOYdm0d4ajibLm2iT/U+tg5JFJNSmZzFxMRgMpnw9/fPUe7v709ERES+ttG6dWt69uxJkyZNUKvVdOnShb59+95x/TfffJPJkydb72fXnAlRnBSDgYRVq4iZMwfjjXAA7CoGEjawOZ95/UdU5lrItMxT9kzIM/Su3rvYp8TIlp2Y+fn54eTkhEqlQlEUkmMzMNibUKlVuPk4YKeVWp7CoigKaWlpREVFARAQEGDjiMSDcLBz4Kk6T/H14a9ZfHIxvYN7S8JdTpTK5Czb7R9SRVEK9MH96KOP+Oijj/K1rr29Pfb2ciJaYRuKwUDi2rXEzJqN4brl5OMaHx+uPNaS6QGHCddvhEwIcA5gfMj4Yp889nYmk8mamHl7e1ueQ1ZihkmDTmuHh78jWvtSfQgqkRwdLae6ioqKws/PT5o4S7knaj/B98e/50z8Gf6N+JfWAa1tHZIoBqXyyOjj44NGo8lVSxYVFZWrNk2I0kwxGklct56Y2bOt57/UeHtztX8LPq90nKv6LaAHfyd/xoeMZ0CNASWiX0p2HzMnp5vzM6UmZJKRail385XErChlv+4Gg0GSs1LO3d6d/jX68/Ppn1l8crEkZ+VEqTw66nQ6mjVrxtatWxkwYIC1fOvWrfTr18+GkQlROBSTiaSNG4n59jv0ly8DoPHy5Eb/1nxW6TiXDX+C3nJC8rEhYxlYcyA6jc7GUeeWXZOdlphJWpIeAFdvB+wdS+Whp9SQpq+yZVjdYSw/vZzd13cTFh9GDc8atg5JFLESe4RMSUkhLCzMev/ixYscOXIELy8vgoKCmDx5MsOGDaN58+a0adOGefPmceXKFSZMmGDDqIV4MIrJRNKmTcR8Nwv9hQsAqD08iB7Qls+DQgnTbwUD+Dj6MLbhWAbVGlQsJyR/EBkpelISLCOdXTzscXQpeUmkECVZZbfKdAnqwp9X/mRJ6BLeb/e+rUMSRazEJmcHDhygU6dO1vvZnfFHjBjBokWLGDx4MLGxsbz//vuEh4fToEEDNm7cSJUqVWwVshD3TTGbSd6yhehvv0Ufdh4Atbsb8QPa82XwGULTLc2XXg5ejG4wmsG1B+Ng52DjqO9Nn2EkI9EMgKOrDif3kp1IClFSjag/gj+v/Mn6C+t5semL+Dj62DokUYRKxTxnJVFpmCdFlHyK2Uzyn38S8+13ZJ49C4Da1ZWUgZ35qnoYh9Ms55t01bkyqv4onq77dKk4z15GRgZh587j5VwBO40WB2ctrt4O0txWTDIyMrh48aL1DCqibHh649Mciz7G+JDxvNDkBVuHU2qVhu9vmY5bCBtQzGaSNm/h4sBBXH/xJTLPnkXt4oJ+RH8+f7MmIwM2cDjtDI52jowPGc+mgZsYFzKuVCRmAInRaaQn61EUBZ2DXalLzCIiInjhhRcIDg7G3t6eypUr06dPH7Zt22ZdZ8+ePfTs2RNPT08cHBxo2LAhn3/+OSaTybrOpUuXGDNmDNWqVcPR0ZHq1aszdepU9Hq9LZ6WKOWG1xsOwG9nf0Nvks9QWVZimzWFKIssHf3/IGbunJvNl05OGAd1Z1bdG+xIWg/JoFPreLLOk4xpOAYvBy8bR10wKfGZ/LX0NNUfdkSjVePm61iqErNLly7Rrl07PDw8mD59OiEhIRgMBjZv3sxzzz3H6dOnWbVqFU888QSjRo1i+/bteHh48Oeff/L666+zb98+fvnlF1QqFadPn8ZsNjN37lxq1KjBiRMnGDduHKmpqXz22We2fqqilOkc1Bk/Jz+i0qLYcnkLvYN72zokUUSkWfM+lYZqUVFyKAYDievWEzt3rnX0pdrFBfOgHvxQL5LN8ZYzW9ip7BhYayDjGo7D37n0TQuTmWZg5WeHSEtNJ6S/B/VDauHkbKntUxSFdIPpHlsofI5aTYGSw549e3Ls2DHOnDmDs7NzjmUJCQlotVqqVKlChw4d+P3333MsX7duHX379mX58uUMHjw4z+3PmDGD2bNncyFrwEdRkGbNsmvO0Tl8d+Q7Gvk2YmnPpbYOp1QqDd/fUnMmRBEy6/UkrlpN7Lx5NyePdXdH9WRfFteJZm3UapR4BbVKTe/g3jzb6FkquVaycdT3x6g3sWHWMeJupOJZyR4nV12OE5mnG0zUe2dzsccV+v6jOOnyd6iLi4tj06ZNfPTRR7kSM7CcFmnVqlXExsby6quv5lrep08fatWqxc8//3zH5CwxMREvr9JVGypKjkG1BjH32FyORh/lZOxJ6nvXt3VIoghIciZEETBnZJDw62/E/vADxqzJkjVeXtg9PZAfa0ex8sYKzFGWUYyPVn2UiY0mEuwRbMuQH4jZrLDlh5OEhyWic9DQaWgdEtKjbB1WgYWFhaEoCnXq1LnjOmezBm7UrVs3z+V16tSxrnO78+fP88033/D5558/eLCiXPJx9KFblW5svLiR5aeX80G7D2wdkigCkpwJUYjMaWnEL19B7MIF1hOS2/n6Yj98MMtqxbDiyo8YrxsB6FCpA883eZ46XndOBEoDRVH4++czXDwag8ZOTc+JIXhWcCThYs71HLUaQt9/tNjjcyzAuTuze3nkpxn0Tj1C7nQauRs3btC9e3cef/xxxo4dm++YhLjdkDpD2HhxIxsvbOSVZq/g4eBh65BEIZPkTIhCYIyPJ/7HpcT/9BOmxEQA7AICcBr5FL/UjOWnCwvJvGSZiLVVQCteaPICjXwb2TLkQvPf+ouE7rqBSgVdx9SjYi1PMjIycq2nUqny3bxoKzVr1kSlUnHq1Cn69++f5zq1atUC4NSpU7Rt2zbX8tOnT1OvXr0cZTdu3KBTp07WCbOFeBCNfBtR16sup+JOsTJsJaMbjLZ1SKKQyVQaQjwA/bXrRHzwIWGdOhMzaxamxES0QUF4Tn2LrTP6M1A7nwXnlpJpyqSRbyN+6PYD87vNLzOJ2Ym/r3FgwyUA2g+pTfUmfrYN6AF5eXnx6KOP8t1335GamppreUJCAt26dcPLyyvPpsm1a9dy7tw5hgwZYi27fv06HTt2pGnTpixcuBC1Wg674sGoVCqG1LF8xlacXoHJXPwDbUTRKtk/Y4UooTLOnCF2/g8kbdwIWfNaOdSrh8uoYaypHMXCU3NIOpkEQF2vujzf5HkervhwqZpS4l7CDkbx93JL36oWvavRoH1FG0dUOGbNmkXbtm1p2bIl77//PiEhIRiNRrZu3crs2bM5deoUc+fO5cknn2T8+PE8//zzuLm5sW3bNl577TUGDRrEE088AVhqzDp27EhQUBCfffYZ0dHR1v1UqFDBVk9RlAE9qvXg84OfcyP1Bv/c+If2ldrbOiRRiCQ5EyKfFEUhbf9+YufPJ3XnLmu5c9s2uI4ewQbPK3x/4kvijsYBEOwezHONn+ORKo+gVpWt2pLrZ+LZuvAkKFC/fUVa9Kpq65AKTbVq1Th06BAfffQRr7zyCuHh4fj6+tKsWTNmz54NwKBBg9i+fTsff/wx7du3Jz09nRo1avB///d/TJo0yZqEb9myhbCwMMLCwqhUKecoXJnFSDwIBzsH+gT3Yemppfx+9ndJzsoYmefsPpWGeVJE4VBMJpK3bSPuhwWkHz1qKVSrcX20G+6jR7LZ/hxzjs4hMi0SgEoulZjYeCI9q/VEo85/Z/TSIvpqMqs/P4Q+w0RwE18eHdcAtTpnjaDMs2Vb8vqXD+cTztN/TX80Kg1bBm3Bz6l0dysoLqXh+1tqzoS4A1NKCom//07cj0sxXLsGgEqnw/2xAXiMHME280lmHXmTq8lXAfBz8mNCown0r9EfrVpry9CLTFJMOuu/OYo+w0RgTQ+6jq6XKzETQhSP6h7VaerXlENRh1gdtprxIeNtHZIoJJKcCXEb/bVrxP+4lITffsOc1Slc4+6Ox5An8Xz6aXann+Drw5MJSwgDwMvBi7ENx/JE7Sew19jbMvQilZakZ+1XR0hL0uNd0YWezzbErgDTVAghCt/AWgM5FHWIledWMrbh2DLXhaK8kuRMCLJOLXToEHGLFpO8bRuYLRPE6qpXx2v4cNz79uFAwnFe3j+JY9HHAHDVuTKq/iiervt0qTkh+f3SZxjZ8N1REqPTcfV2oM8LjbB3Kpu1g0KUJt2qdOOT/z7hesp19t3YR9uKuad3EaWPJGeiXDOnp5O0cSPxPy0jIzTUWu7crh1eI0fg3K4doXGneGPXS+wN3wuAg8aBp+s+zagGo3C3d7dV6MXGZDSzae5xoi4n4+Cipe+LjXH2KLs1hEKUJtkDA5adXsZv536T5KyMkORMlEuZFy+SsHwFCatWYU6yTHmh0ulw79cXr+HDsa9ZkwuJF/h256tsvbwVADu1HYNqDmJ8yHh8nXxtGX6xUcwK2xaf4uqpeOzsNfR+vhEe/mW7llCI0mZgrYEsO72M7Ve2E5Meg4+jj61DEg9IkjNRbihGIyk7dhC/7GdS9+yxlmsrVcJzyJO4P/YYdp6ehKeEM+uf/7H2/FrMihkVKnoF92Ji44lUdq1sw2dQvBRF4Z/fwji3PxK1WkWP8Q3wr1oyRzYJUZ7V8qxFiG8Ix6KPsSZsDWMajrF1SOIBSXImyjz91ask/P47iatWY4y0THeBSoVLhw54PjUE54ceQqVWE5sey/z/PmXFmRUYzAYAOlXuxPNNnqeWZy0bPgPbOLzlCkf/soxE7TyiLkH1vW0ckRDiTgbVHMSx6GP8fu53RjUYJQMDSjlJzkSZZM7IIHnLFhJ++520//6zlms8PfEYNBCPwYPRZU0KmqxPZvHJxfwY+iNpxjQAWlZoyYtNXywzp1kqqFN7wtm76jwA7QbVoHYrmc1eiJLs0aqPMn3/dK4mX+W/iP9oHdDa1iGJByDJmSgzFEUh48RJElb+TtL6DZiTky0LVCqc27XDY+BjuHTpglqnAyDDmMHy08uZf2I+iZmWk5XX867HS01fok1AmzJ1qqWCuHQ8hu1LTwPQpGsQjR8JsnFEQoh7cdI60bNaT345+wurw1ZLclbKSXImSj39pUskrt9A0vr16C9dspZrAwNxH/gYHgMGoA0MtJYbzAZWh61mztE5RKVFAVDNvRovNHmBR4IeKbdJGUDExUQ2zzuBYlao3aoCbQZUt3VIQoh86l+jP7+c/YU/L/9JcqtkXHWutg5J3CdJzkSpZIiKIvmPP0hcv4GM48et5Sp7e1y7dMFj0ECcWrdGpb7Z78KsmNl8aTPfHv6WK8lXAAhwDuDZRs/Sp3of7NTl+98hPiKVDd8ew2gwE1Tfi07D66CS2f8LTdWqVZk0aRKTJk2ydSiijGrg04Dq7tU5n3ieTZc28Xitx20dkrhP5fvbSJQqhsgoUv7aRtKWLaT9+591olg0GpzbtsW9dy9cujyCxsU5x+MURWHX9V18fehrzsSfASyz+o9rOI4naj+BTqMr7qdS4qQmZLLu66NkpBrwq+LKo+MaoNFIh+L80Ov16HTyGRK2p1Kp6F+jP58f/Jw1YWskOSvF5OgrSrTMCxeJ+f57Lg4eTFiHDkS89z5pe/eB2Yxj48b4v/02Nf/eQdD383Dv1y9XYnYo8hAjN43kuW3PcSb+DC5aF55r/BwbH9vI0HpDJTEDMtONrPvmKMlxGbj7OdL7+UboHIrgd5uigD61+C+KUqAwO3bsyPPPP8/zzz+Ph4cH3t7evP322yhZ26latSoffvghI0eOxN3dnXHjxgHw+++/U79+fezt7alatSqff/55jm1evnyZl19+GZVKlaPp/G6Py97fxx9/zOjRo3F1dSUoKIh58+bd77sgyrje1XujUWk4Gn2UC4kXbB2OuE9ScyZKFMVkIuP4cZL/2k7ytm3oz5/PsdyxUSNcHumCW/fu6Crfec6x03Gn+erQV+y+vhsAe409Q+oMYUyDMXg4eBTlUyhVjAYTG2cdI/Z6Ck5uOvq+2BhH1yJKWA1p8HHgvdcrbG/dAJ3zvde7xeLFixkzZgz//vsvBw4cYPz48VSpUsWaiM2YMYP//e9/vP322wAcPHiQJ554gnfffZfBgwezZ88eJk6ciLe3NyNHjmTlypU0atSI8ePHW7eRn8dl+/zzz/nggw946623+O2333j22Wdp3749derUefDXR5QpPo4+PFTxIf6+9jdrwtbwcrOXbR2SuA+SnAmbM0RFkbr7H1J37yLlnz2YExNvLtRqcW7VCtdHuuDSqTNaf7+7buty0mW+Pfwtmy5tAkCj0jCg5gAmhEzA39m/KJ9GqWM2K/y5MJQb5xLQOmjo/UIj3HwcbR1WiVC5cmW+/PJLVCoVtWvX5vjx43z5/+3deVzUdf7A8dcw3LeAXHKoICgoKKh5oaEpYR6ka7qVV1kqJbYe1f56bIebtVseHWqZVmbutqSulFdoBmJampp5oCKeeBAiAnLDzPf3B8lGeIAc3xl4Px+P74PmO9/jPfOxmfd8zsWLqxKrgQMHMmfOnKrjH3vsMQYNGsTf/vY3AAICAkhNTeXtt99m0qRJODk5odVqsbOzw939f9OSLFq06I7n3TR06FBiY2MBeOGFF1i8eDHJycmSnIlbivGPYefFnWw8vZEZ3Wa0+P60xkhKTDS5ipwcin7aT9HevRT9tI/SU+nVnjext8embx/sBj2Abf8ItPZ3n5U+szCTD3/5kIT0BHSKDoDodtE80/UZfO19G+V1GDNFUfg+Po3TB69iYqph6PQQWns38sguM+vKWqymdg+L0vfq1ata02Pv3r1ZuHAhOl3lv63u3btXO/748eOMHDmy2r6+ffvyzjvvoNPp0Gq1t7xPbc8LCQmpel6j0eDu7k5WVladX5doGQZ4DaCVRSuuFl9lz+U99Pfqr3ZIoo4kORONSlEUKi5fpvjwYYr2H6Bo3z5KT52qfpBGg2XnzthG9MOmXwRWIV3QmNbun2ZuSS4rj6zkixNfUKYvA6C/V3/iusUR6BTY0C+n2TjwzXmO7LwEGnhgUhBega0a/6YaTZ2bFw2VjU3NQSd/nIJFqUVft9qeZ2ZmVu2xRqNBf3NAjBB/YKY146H2D7Hm+BoS0hMkOTNCkpyJBqUrKKDkyBGKfzlM8eHKTZedXeM4i4AArHv2xLpnD6x79MC0Vd2Sg8LyQlanruazY59RWF4IQJhrGDPDZhLmFtYgr6W5St19mb1fVXYUjnikAx26S3PvH/344481Hnfo0OG2NWBBQUF8//331fbt2bOHgICAqnPMzc2rat7qcp4Q9yLGP4Y1x9eQnJFMbkmu9LU1MpKciXtys0as5ORJSk+epORkGqUnT1ZOAvvHX/6mplgGBmLVtWtVQlbXZOymUl0pX578kpVHVpJTkgNAR6eOxHWLo1+bfi16AtnaOHc4m+R/VU4nEvagLyGRLWch97rIyMhg1qxZTJ06lYMHD/L+++/XGEX5e7Nnz6ZHjx78/e9/Z+zYsfzwww8sWbKEZcuWVR3Ttm1bUlJSGDduHBYWFri4uNTqPCHuRaBTIB2dOnIi5wRbzm7h0U6Pqh2SqANJzsQd6UtKKDt/gbLz5yg7d56yc+coO3eO0rQ09AUFtzzHzNMTy9AQrEJCsQoNxTKoEyaWlvWKo0JfwcbTG1n2yzIyCzMB8LX35dmuzzKk7RBZ5LcWMs/kkbiicvb/jr3d6TWyvdohGawJEyZQXFxMz5490Wq1zJgxg6effvq2x4eFhfHll1/y8ssv8/e//x0PDw/mzZtXrVP/vHnzmDp1Kn5+fpSWlqIoSq3OE+JexfjH8I99/yAhPUGSMyOjUWrTMULUkJ+fj4ODA3l5edjXosO6oVLKyijPyqL88mUqrlyh/Eom5VeuUJ5xgdJz56i4knn7eaLMzLBo3x6LwAAsAztiERiIZcdATF1cGi4+RWH7+e0sObSEs3lnAXC1dmV66HRG+o/EzMTsLlcQUDn7//q3D1BaWIFvZ2eip3dp1ElmS0pKOHv2LO3atcOynol5U7v//vvp2rUr77zzjtqh3DNjfv9Fw7lecp2BawdSoa9g3fB10g/3N8bw/S01Z82Qotejy81Fd+0aFddy0OVcoyL7GhU519Bdy6EiJ4eKq1epuHKFiuzsu07SaWJnh3nbtr9tvpj7tsWiQwcs2rVF00gzoyuKwg+Xf+Ddn98l9VoqAI4WjkzpMoWxgWOxNJUvnNoquF7K1+8dorSwArd29jL7vxAtRCvLVkR6R7L9/HYS0hN4oecLaockakmSMwOhKApKeTlKcTH6kpKqv/riYpSSEvRFRehu3ECffwNdQfW/+oIb6PJvoLuRj/5GAbrc3P8tbVQLGnNzTD3cMfPwxMzDAzMPd8zaeGHerjIh07Zq1aR9uX65+gvvHnyXnzJ/AsDa1JoJwROYGDQRW3PbJoujOSgtKmfj+4coyCnF0c2ah54JwcxCOpoL0VLE+Mew/fx2Np/ZzKzwWZhppbXBGEhyVk/ZH35Iida0MrGqqKj8e3Or+N9/U16OUv6/5/WlJSjFJdUSsbokVLWhdXBA6+yMqbNz5V8nJ7TOTpg6u6B1dvotGXNH6+RkEB3p066n8f7P75OckQyAmYkZYwPH8lTIUzhZOqkamzGqKNex5YMj5FwuxNrBnOEzQrGyleWq7iY5OVntEIRoMH08++Bi5UJ2cTYpl1IY5DNI7ZBELUhyVk/XVqyktKGHvJuZYWJpiYmlJRorq8r/trLCxM4Orb0dJrZ2mNjZorWzr/xrb4+J7c2/dmhbOWLaqhUaM+P4hZRxI4Olh5ay5cwWFBRMNCaM9BvJ9NDpeNh6qB2eUVL0CjtWHefyqVzMLbUMl9n/hWiRTE1MGd5+OJ8e+5SE9ARJzoyEJGf15DhmDPZ2dmjMTMHMDM3NzfT3/22KxvwPjy0sMbGyRGNp9dvf3xIwS0ujSarq62rRVZYfXs76tPVUKBUADPYdzLPdnqW9g4wkrI89G06TfiALE62G6OkhuHg18uz/QgiDNdJ/JJ8e+5RdF3eRXZyNi1XDDdoSjUOSs3pye/EFgx3tYajySvP45Ogn/Pv4vynRlQDQ17MvM8JmEOwcrHJ0xu9wUgaHtl8AYOCETk0z+78QwmD5OfrRxaULR7KPsPnMZiYGT1Q7JHEXkpyJJlNUXsS/jv+LT49+yo3yGwCEtg5lZthMerj3UDm65uHMz1fZ9WXl8li9YtoTeJ/7Xc4QQrQEMf4xHMk+QkJ6AhOCJhhEP2Nxe5KciUZXritnbdpaPjr8EddKrgHQoVUH4rrFMcBrgHxINJDMM3ls++QYKBAc4UlYlCz4LoSoFNU2in/u+yfpuemk5qRKK4WBk+RMNBqdXsfms5tZdmgZlwouAeBl68Uz3Z4hum00WhOZ0qGh5P5axOalh9GV62nbxZn+4wIk6RVCVHGwcGCQzyC2nttKwqkESc4MnCRnosEpisJ3Gd+x5OclpOemA+Bi5cK0kGmM6jBK5tlpYEX5ZWx8/xAlheW4+toxZEpnTGSSWSHEH4z0H8nWc1vZcnYLc3vMxVwrU+sYKvkEFw1q75W9PL7lcZ5Leo703HTsze15Luw5tozawtiOYyUxa2DlpTo2LztMfnYJ9i6WPPRMqEwy2wAyMzOZMWMG7du3x8LCAm9vb4YPH86OHTvu+ZqfffYZPXv2xMbGBjs7O/r378+mTZsaMGoh7qyXRy/crN3IL8snKSNJ7XDEHUhyJhrE0eyjPLXtKaZsm8Lh7MNYmVrxVJen2Dp6K092eRIrU5ljq6HpdXq2fXyMrHP5WNiYMuzZUKzt5ZdwfZ07d47w8HC+++473nrrLY4cOcI333xDZGQkzzzzzD1dc86cOUydOpVHHnmEX375hX379hEREcHIkSNZsmRJA78CIW5Na6JlhN8IAL5K/0rlaMSdSLOmqJfTuad5/+f32XGhskbB1MSUMQFjeDrkaZlLpxEpisKu+FOcO5yN1tSEh6aH0MrdRu2w7khRFIoripv8vlamVnXqfxcbG4tGo2Hfvn3Y2PzvPQ0ODuaJJ56o8/1//PFHFi5cyHvvvceMGTOq9s+fP5+SkhJmzZrFyJEj8fb2rvO1hairEX4jWHFkBbsv7yarKAtXa1e1QxK30CKSs4cffpjk5GQGDRrEunXrqj23adMmZs+ejV6v54UXXmDKlCkqRWlcLhVc4oNDH7DxzEb0ih4NGob7DWd66HS87LzUDq/Z+3nbBY6mXAINDH4iCA9/R7VDuqviimLu+/d9TX7fvY/uxdrMulbH5uTk8M033zB//vxqidlNjo6OAERHR7Nr1647XqugoACAL774AltbW6ZOnVrjmNmzZ7No0SLWr1/Pc889V6sYhaiPtg5t6ebajZ+zfmbTmU080bnuPzhE42sRyVlcXBxPPPEEn332WbX9FRUVzJo1i6SkJOzt7QkLC2PUqFE4Ock6jreTXZzNisMr+DLtSyr0lbP6D/QeyIxuM/Bv5a9ydC1D2r5MfthwGoB+f+qAX5j88m0o6enpKIpCx44d73jcypUrKS6uXS1gWloafn5+mJvXbHL29PTEwcGBtLS0e4pXiHsx0m8kP2f9TEJ6ApODJ8vIbgPUIpKzyMjIWy5mvG/fPoKDg2nTpg0AQ4cOJTExkT//+c9NHKHhu1F2g0+Pfsqa42uqmqbuc7+PuLA4QlqHqBxdy3H5VC47Vh8HIHSQN6GDjKcpzMrUir2P7lXlvrWlKArAXb+sbn5mNARFUeTLUTSpqLZR/GPfPzibd5bD2YcJbR2qdkjiD1QfEJCSksLw4cPx9PREo9GQkJBQ45hly5bRrl07LC0tCQ8Pv2tzQm1dvny52oesl5cXly5dapBrNxfFFcV8cvQTHlz/ICuOrKC4opjOzp1ZMWQFK6NWSmLWhHKzitj64RH0FQrtu7Wm72jjqqnUaDRYm1k3+VaXxKdDhw5oNBqOHz9+x+Oio6OxtbW943ZTQEAAp0+fpqysrMZ1Ll++TH5+Ph06dKj9GylEPdma2/KA7wOADAwwVKrXnBUWFhIaGsrkyZMZPXp0jefj4+N57rnnWLZsGX379mX58uVER0eTmpqKj48PAOHh4ZSWltY4d9u2bXh6et723jd/Jf/e7T7IS0tLq90jPz//rq/NmJXry9lwagMf/vIhV4uvAtDeoT1x3eIY6DNQfuk3sZLCcjYvPVw1l9kDk4PQmEgZNDQnJyeioqJYunQpcXFxNfqd5ebm4ujoWKdmzXHjxvHee++xfPnyagMCABYsWICZmdktP/uEaEwx/jFsOrOJb85+w/M9nsfS1FLtkMTvqJ6cRUdHEx0dfdvnFy1axJNPPlnVUf+dd94hMTGRDz74gDfffBOAAwcO3NO927RpU62m7OLFi9x33607LL/55pu89tpr93QfY6JX9Gw9u5Wlh5aScSMDAE8bT2K7xjKs/TCZ1V8Fugo93yw/Qu6vRdg6WTA0NgQzcymHxrJs2TL69OlDz549mTdvHiEhIVRUVLB9+3Y++OADjh8/Xqdmzd69ezNz5kzmzp1LWVkZMTExlJeXs2bNGt59913eeecdGakpmlwP9x542nhyufAy3134jqHth6odkvgd1Zs176SsrIwDBw4wZMiQavuHDBnCnj176n39nj17cvToUS5dusSNGzfYsmULUVFRtzz2r3/9K3l5eVVbRkZGve9vSBRFYWfGTsZsHMOLu14k40YGTpZOvNjzRTY+vJGR/iMlMVOBoigkrznBpbRczCy1DHsmFBsHC7XDatbatWvHwYMHiYyMZPbs2XTu3JnBgwezY8cOPvjgg3u65jvvvMOyZcv4z3/+Q5cuXQgPD2fnzp0kJCTUqE0ToimYaEwY4V8551lCeoK6wYgaVK85u5Ps7Gx0Oh1ubm7V9ru5uZGZmVnr60RFRXHw4EEKCwvx8vJiw4YN9OjRA1NTUxYuXEhkZCR6vZ7nn38eZ2fnW17DwsICC4vm+aW4P3M/7x58l0NXDwFga2bL5M6TebzT47WegkA0jgPfnOfEj5loTDREPdUZ5za2dz9J1JuHhwdLlixp0Alin3jiiXuaJ02IxjLCbwQf/vIhP175kczCTNxt3NUOSfzGoJOzm/7Yv6muo5sSExNv+9yIESMYMWLEPcdmzI5fO867P7/L7ku7AbDQWvBop0d5svOTOFg4qBydOLX/V/Z+dQaA/mM74Bt86x8OQghxL7ztvOnu1p39v+7n69Nf83TI02qHJH5j0MmZi4sLWq22Ri1ZVlZWjdo0UXvn8s6x5NASEs9VJq2mGlNGdRjF1NCpMlu0gcg8k8eOVb9NmTHQm84DZGJfIUTDi/GPYf+v+/kq/Sue6vKUDPYyEAbd58zc3Jzw8HC2b99ebf/27dvp06ePSlEZr8zCTF7d8yoxX8WQeC4RDRqGthvKVzFf8bfef5PEzEDkZxez5YPD6Cr0tA1xoc+fjGvKDCGE8RjsOxgrUysu3LjAwayDaocjfqN6zVlBQQHp6elVj8+ePcuhQ4dwcnLCx8eHWbNmMX78eLp3707v3r356KOPuHDhAtOmTVMxauOSU5LDyiMriT8RT5m+cq6l+73u59luzxLoFKhydOL3SovK2bT0MMU3ynHxtmXwE0GYyJQZQohGYm1mTVTbKBLSE/jvqf8S7haudkgCA0jO9u/fT2RkZNXjWbNmATBx4kRWrVrF2LFjuXbtGvPmzePKlSt07tyZLVu24Ovrq1bIRqOgrIDVqav57NhnFFUUARDuFs5zYc/R1bWrusGJGvQ6PYkrj3H9SiE2jhY8FBuKuaXq/4sKIZq5MQFjSEhPqJrzTPocq0/1T/7777//lpPB/l5sbCyxsbFNFJHxK9WV8p8T/+HjIx9zvfQ6AJ2cOhEXFkdfz77Sp8BA7V6fTkZqDqbmJjwUG4Jtq+Y5OlgIYVi6uHSho1NHTuSc4Kv0r5gQPEHtkFo8g+5zJuqmQl/B+rT1PPTfh1iwfwHXS6/T1r4tCwYs4D/D/kO/Nv0kMTNQqd9f5vB3FwF4YHIQrX3sVI5ICNFSaDQaHgl8BIC1aWvvWmEiGp/qNWei/vSKnm3nt7H056Wcyz8HgJu1G7FdYxnhNwJTEylmQ3b5VC47vzgJQM/h7fDrJgMzhBBNa2i7oSzcv5Bz+efYl7mP+zxuvVqOaBryrW3EFEVh9+XdvHfwPY7nVE670MqiFVO6TGFsx7FYaKVZzNDlZxezdfkR9DoF/3BXug9tq3ZIQogWyMbMhmHthxF/Mp74k/GSnKlMmjWN1KGsQ0xOnMz0b6dzPOc4NmY2xIbGsmXUFiYET5DEzAiUlVSw5YPDlBSU09rHjoETO0mzs4HIyMjgySefxNPTE3Nzc3x9fZk5cybXrl2r13WTkpIYOnQozs7OWFtbExQUxOzZs6ut8avT6Vi8eDEhISFYWlri6OhIdHQ0u3fvru/LEuKOxgSMASDpQhJXi66qHE3LJsmZkTmZc5JndzzL+K3jOfDrAcxNzJkQNIGto7Yyvet0bM1leR9joOgVvv00lWuXCrG2N2fo9C6ymLmBOHPmDN27dyctLY0vvviC9PR0PvzwQ3bs2EHv3r3Jycm5p+suX76cBx54AHd3d9avX09qaioffvgheXl5LFy4EKisDR83bhzz5s0jLi6O48ePs3PnTry9vbn//vtJSEhowFcqRHWBToF0bd2VCqWCDekb1A6nRdMo0vPvnuTn5+Pg4EBeXh729vaNfr+M/AyWHFrC1rNbUVDQarTE+McwLXSarIdmhH5MOM2Bb86jNTUhZnY33Ns1r6HrJSUlnD17lnbt2mFpaal2OHUSHR3N0aNHSUtLw8rKqmp/ZmYmfn5+TJgwoc4LoF+8eBE/Pz9iY2NZvHhxjedzc3NxdHQkPj6ecePG8fXXXzN8+PBqx4wePZqdO3dy/vx5bGxs7ng/Y37/hbo2nt7I/33/f7hZu7F19FbMTMzUDqnBNfX3972QmjMDl1WUxd9/+DsjEkaw5ewWFJTKCQNHJvBqn1clMTNCaT9lcuCb8wBEju/Y7BKz21EUBX1RUZNvdfn9mZOTQ2JiIrGxsdUSMwB3d3cee+wx4uPjURSFadOmYWtre8ftwoULAKxdu5aysjKef/75W97X0dERgH//+98EBATUSMwAZs+ezbVr12qsmCJEQxrSdghOlk78WvQr28/JvzW1yIAAA5VXmsfHRz/mi+NfUKIrAaBvm77EdYsjyDlI5ejEvco6n893q08A0G2ID4H3tZzkWiku5mRY088+HnjwABpr61ode+rUKRRFoVOnTrd8vlOnTly/fp2rV68yb9485syZc8freXp6Vl3X3t4eDw+POx6flpZ2x3vfPEaIxmKhteDPHf/M0kNLWZ26muh20dIXVgWSnBmYovIiPk/9nFXHVlFQXgBA19ZdmRk2k+7u3VWOTtRHUX4ZWz88gq5cj28XZ3rF+Kkdkqijm7VwGo2G1q1b4+pau2lPFEVpsC84+aIUje2RwEdYeWQlx64d42DWQVnSSQWSnBmIMl0Za9PW8tHhj8gpqexwHNAqgJlhM4loEyEfyEZOr9OzbeVRCq6X4uhmzeAnglvcmpkaKysCDx5Q5b615e/vj0ajITU1lZiYmBrPnzhxglatWuHi4sK0adNYs2bNHa+XmpqKj48PAQEB5OXlceXKlTvWngUEBJCamnrL544fr5wup0OHDrV+PULcCydLJ4b7DWdd2jo+O/aZJGcqkAEB96ihOhTq9Do2ntnIB4c+4HLhZQC87bx5tuuzPNjuQUw00i2wOfh+7Sl+2ZGBmYWWP73YHSePO3foNnbG3CE9KiqKY8eOcerUqTsOCMjKyiI/P/+O12rbti2mpqZkZGTg7+9/1wEBX3zxBY8++qgMCBCqO5N3hpEJI9Gg4euYr2nr0FbtkBqMMQwIkJozlSiKwo4LO3j/5/c5k3cGAFcrV6aGTuXhDg83yxEyLVXavkx+2ZEBwKBJnZp9YmbslixZQp8+fYiKiuL111+nXbt2HDt2jLlz59KmTRvmz58PgKura62bNb29vVm8eDHPPvss+fn5TJgwgbZt23Lx4kVWr16Nra0tCxcuZNy4caxdu5aJEyfy9ttvM2jQIPLz81m6dClff/01a9euvWtiJkRDaO/QngFeA9h5cScrj6zk9X6vqx1SiyLVMir44fIPPLr5Uf6S/BfO5J3B3tyeWeGz2DxqM48EPiKJWTNyNeMGSZ9XDgAIj/aVpZmMQIcOHdi/fz9+fn6MHTsWPz8/nn76aSIjI/nhhx9wcnK6p+vGxsaybds2Ll26xMMPP0zHjh2ZMmUK9vb2VQMLNBoNX375JS+99BKLFy+mY8eOREREcP78eZKSkm7Z1CpEY5kaMhWATWc2cSH/gsrRtCzSrHmP7qVa9PDVw7x38D32Zu4FwMrUivFB45kUPAk7c1nourkpKSjnyzd/4sa1EnyCnXjomdAW089MmtXUJe+/aCix38ay69IuRviNYH6/+WqH0yCkWVMAkH49nfd/fp/vMr4DwMzEjEcCH2FKlym4WLmoHJ1oDHqdnsSVR7lxrQR7F8sWOQBACGH8podOZ9elXWw+s5mpIVPxsfdRO6QWQZKzRnSp4BLLDi1j4+mNKCiYaEwY3n44sV1j8bT1VDs80Yh+/OoMF09cx9TchKHTQ7C0kaZqIYTx6dK6C/29+pNyMYUlPy/hrQFvqR1SiyDJWSPILs7mo8MfsTZtLRX6CgAe8HmAZ7s9i5+jzG3V3J3a/ys/b6vsnzFwQiec28h6p0II4/Vs12fZdXEXW89tZVzHcYS5hakdUrMnyVkDyi/LZ9XRVaw5vobiimIAenn0YmbYTDq7dFY5OtEUrl0q4LvfBgB0G+xDh+5uKkckhBD108m5E6M6jGL9qfX8Y98/+OKhL9CaaNUOq1mT5KwBFFcU8+/j/+aTo5+QX1Y571EXly7MDJvJfR73qRydaCplxRVsXX6EilIdXh1b0SumvdohCSFEg5jRbQaJ5xI5nnOc/6b/lzEBY9QOqVmT5Kye1qWt4/Mzn5NdnA2Av6M/M7rNINI7Umb1b0EUReG7z4+Tl1WMbSsLhkwJxkQrM9UIIZoHZytnpodO5+39b7No/yIi2kTgbtNy1gZuavLtUU8L9i8guzibNrZteKPfG6wbvo6BPgMlMWthDidd5PTBq5hoNUQ91RkrW3O1QxJCiAb1WKfHCGkdQkF5AX/b/Td0ep3aITVbUnNWT04WTjxz3zP8qcOfMNPKiLyWKPNMHnvWpQPQZ7Q/7u0dVI5ICCEantZEy/y+8xmzcQw/XvmRpYeWEhcW1yT3Liwv5NT1U2TcyODCjQtcvHGR6yXXySvNI7c0l6KKInSKDr1ej07RYaIxwdLUEkutJZamllibWmNlZoW9uT0W5RZNEnN9SHJWT+tGrMPdWap2W6rigjISVxxFr1fwC3MlJNJL7ZCEEKLRtHVoyyt9XuGvu/7KiiMr8Hf0Z2j7oQ1+n8zCTHZd2sWhrEMczT7K2byzKNRtzvyC8oJb7tcVG36NnyRn9WRtZq12CEIlil7h209SKbheioOrFQPHd5TmbCFEszes/TDSctL49NinvPT9S5iamDKk7ZB6XVOn13E4+zApF1NIuZhC2vW0Gse4WrvS1r4t3nbeeNt542LlgqOFIw4WDlibWWOqMcVEY4JWo0Wn6CjVlVJcUUyJroSSihIKywvJL8vn12u/8hf+Uq94G5skZ0LcowPfnONCag6mZiZET+2CuZX879QcTJo0idzcXBISEqrtT05OJjIykuvXr3Po0CEWL17Mvn37yM/Pp0OHDsydO5fHHntMnaCFaGIzw2Zytfgqm85sYs7OOcTmxfJUl6fqNMVGXmke31/6npSLKey+vJu80ryq50w0JoS4hNDToychLiEEuwQ32Io6+fn5kpwJ0RxlnMhh78azAPT/c6BMNNvC7Nmzh5CQEF544QXc3NzYvHkzEyZMwN7enuHDh6sdnhCNTmui5fW+r2NrZst/Tv6HpYeW8t2F75geOp0IrwhMTWqmF+X6co5lH2PP5T3svrybo9lH0Sv6quftzO3o59mP/t796evZl1aWrZryJRkUSc6EqKOC66Vs//gYKNCprwed+nioHZJoYv/3f/9X7XFcXByJiYls2LBBkjPRYmhNtLzU6yWCXYJ566e3OJ5znLikOGzNbAltHYqbjRsmGhPyS/PJuJFBem465fryatfwd/Snv1d/+nv1J7R16C2TupZI3gUh6kCn07Pt46MU3yjH2cuW/mMD1A7JaCiKQkWZ/u4HNjBTc5Mm6QuYl5dHp06dGv0+QhiaGP8YItpE8FnqZ2w4tYHc0lx2X959y2Ptze3p5dGLvm360sezj8yVdhuSnAlRB/u+PsOV9DzMLbU8+FRnTM1lCZPaqijT89HMnU1+36ffHYCZRd3KadOmTdjaVm+q1uluP8Jr3bp1/PTTTyxfvvyeYhTC2DlbOTMrfBYzu83k5PWTHM0+Sk5JDgoK9ub2uFu7E+gUSBvbNjJwqhYkOROili6kXuNgYuWC5pHjO+HoJiN1m6vIyEg++OCDavv27t3L448/XuPY5ORkJk2axIoVKwgODm6qEIUwSFoTLUHOQQQ5B6kdilGT5EyIWijMK+XbT1MB6Ny/Df7hripHZHxMzU14+t0Bqty3rmxsbPD396+27+LFizWO27lzJ8OHD2fRokVMmDDhnmMUQojfk+RMiLtQ9Arffppa2c+sjS19/+R/95NEDRqNps7Ni4YsOTmZYcOG8c9//pOnn35a7XCEEM2IJGdC3MXBbee5eOI6puYmDJkSLP3MBMnJyTz00EPMnDmT0aNHk5mZCYC5uTlOTk4qRyeEMHay8LkQd3DldB57v/5tPrNxATh52KgckTAEq1atoqioiDfffBMPD4+qbdSoUWqHJoRoBjSKotRtsSoBVM4w7ODgQF5eHvb29mqHIxpBSWE58fP3UZBTSocebgx+IkhGGdVSSUkJZ8+epV27dlhaWqodTosj778Qt2cM399ScybELSiKQtKaExTklGLf2or7Hw2UxEwIIUSTkORMiFs4lnKJMz9fxUSrIWpKsKybKYQQoslIcibEH2RfvMH3a9MB6P2wH66+hlntLYQQonmS5EyI3ykv1ZG44hi6Cj1tuzgTOshb7ZCEEEK0MJKcCfE7u75MI/fXImwczBk4sZP0M6snGW+kDnnfhTBukpwJ8ZvTB7M4vvsKaGDwE8FY2ZqrHZLRMjMzA6CoqEjlSFqmm+/7zXIQQhgX6eUsBFBwvZSkNScACBviS5vAVipHZNy0Wi2Ojo5kZWUBYG1tLbWQTUBRFIqKisjKysLR0RGtViZMFsIYSXImWjxFr7Djs1RKiypo7WNHz+Ht1A6pWXB3dweoStBE03F0dKx6/4UQxkeSM9Hi/fJdRuXyTGYmDH4iCK2ptPY3BI1Gg4eHB66urpSXl6sdTothZmYmNWZCGLkWkZw9/PDDJCcnM2jQINatW1e1PyMjg/Hjx5OVlYWpqSl/+9vfGDNmjIqRiqaWffEGPyScBqDvmA60cpflmRqaVquVZEEIIeqgRVQRxMXFsXr16hr7TU1Neeedd0hNTeXbb7/lL3/5C4WFhSpEKNRQUaZj28ep6CsU2oa4EBzhqXZIQgghRMtIziIjI7Gzs6ux38PDg65duwLg6uqKk5MTOTk5TRydUMueDae5fqUQK3tzBo7vKB3WhRBCGATVk7OUlBSGDx+Op6cnGo2GhISEGscsW7asagHf8PBwdu3a1eBx7N+/H71ej7e3TDraEpw/eo0jSRcBGDSxE1Z2Mm2GEEIIw6B6n7PCwkJCQ0OZPHkyo0ePrvF8fHw8zz33HMuWLaNv374sX76c6OhoUlNT8fHxASA8PJzS0tIa527btg1Pz7s3VV27do0JEyawcuXK2x5TWlpa7R55eXlA5er2wrgU5ZexacUBisvKCI5oQytvMylHIYRoIW5+3hv0ZM2KAQGUDRs2VNvXs2dPZdq0adX2dezYUXnxxRfrdO2kpCRl9OjRNfaXlJQoERERyurVq+94/iuvvKIAsskmm2yyySZbM9gyMjLqlEc0JdVrzu6krKyMAwcO8OKLL1bbP2TIEPbs2VPv6yuKwqRJkxg4cCDjx4+/47F//etfmTVrVtXj3NxcfH19uXDhAg4ODvWORTSN/Px8vL29ycjIwN5eFjQ3FlJuxkvKzjg153JTFIUbN27UqmVNLQadnGVnZ6PT6XBzc6u2383NjczMzFpfJyoqioMHD1JYWIiXlxcbNmygR48e7N69m/j4eEJCQqr6un3++ed06dKlxjUsLCywsLCosd/BwaHZ/cNtCezt7aXcjJCUm/GSsjNOzbXcDL1SxaCTs5v+OIpOUZQ6jaxLTEy85f5+/fqh1+vrFZsQQgghRENSfbTmnbi4uKDVamvUkmVlZdWoTRNCCCGEaA4MOjkzNzcnPDyc7du3V9u/fft2+vTpo1JUlSwsLHjllVdu2dQpDJeUm3GScjNeUnbGScpNXRpFUXcsaUFBAenp6QB069aNRYsWERkZiZOTEz4+PsTHxzN+/Hg+/PBDevfuzUcffcSKFSs4duwYvr6+aoYuhBBCCNHgVE/OkpOTiYyMrLF/4sSJrFq1CqichPatt97iypUrdO7cmcWLF9O/f/8mjlQIIYQQovGpnpwJIYQQQoj/Meg+Z0IIIYQQLY0kZ0IIIYQQBkSSMyGEEEIIAyLJWSN5+OGHadWqFX/605+q7c/IyOD+++8nKCiIkJAQ1q5dq1KE4lZuV24AmzZtIjAwkA4dOrBy5UoVohO1tXjxYoKDgwkKCiIuLs6wFzgWVc6ePUtkZCRBQUF06dKFwsJCtUMStVRUVISvry9z5sxRO5RmQQYENJKkpCQKCgr47LPPWLduXdX+K1eu8Ouvv9K1a1eysrIICwvj5MmT2NjYqBituOl25VZRUUFQUBBJSUnY29sTFhbG3r17cXJyUjFacStXr16lV69eHDt2DDMzM/r378+CBQvo3bu32qGJuxgwYACvv/46ERER5OTkYG9vj6mpUSxk0+K99NJLnDp1Ch8fHxYsWKB2OEZPas4aSWRkJHZ2djX2e3h40LVrVwBcXV1xcnIiJyeniaMTt3O7ctu3bx/BwcG0adMGOzs7hg4dettlwYT6KioqKCkpoby8nPLyclxdXdUOSdzFzWQ6IiICACcnJ0nMjMSpU6c4ceIEQ4cOVTuUZqNFJmcpKSkMHz4cT09PNBpN1aLnv7ds2TLatWuHpaUl4eHh7Nq1q8Hj2L9/P3q9Hm9v7wa/dnOkZrldvnyZNm3aVD328vLi0qVLDXLtlqaxy7F169bMmTMHHx8fPD09eeCBB/Dz82vAV9AyNXa5nTp1CltbW0aMGEFYWBhvvPFGA0bfcjXF5+acOXN48803GyhiAUay8HlDKywsJDQ0lMmTJzN69Ogaz8fHx/Pcc8+xbNky+vbty/Lly4mOjiY1NRUfHx8AwsPDKS0trXHutm3b8PT0vGsM165dY8KECdJ3qQ7ULLdbtf5rNJp6vJqWq7HL0crKik2bNnHu3DmsrKyIjo4mJSVFJq6up8Yut/Lycnbt2sWhQ4dwdXXlwQcfpEePHgwePLjRX1tz1tjl9tNPPxEQEEBAQAB79uxp9NfTYigtHKBs2LCh2r6ePXsq06ZNq7avY8eOyosvvlinayclJSmjR4+usb+kpESJiIhQVq9eXed4RaWmLrfdu3crMTExVY/j4uKUf/3rX3ULWtTQGOX45ZdfKrGxsVWP33rrLeWf//xnvWMV/9MY5bZnzx4lKiqq6vFbb72lvPXWW/WOVfxPY5Tbiy++qHh5eSm+vr6Ks7OzYm9vr7z22msNFXKL1SKbNe+krKyMAwcOMGTIkGr7hwwZ0iC/ChRFYdKkSQwcOJDx48fX+3qiUmOXW8+ePTl69CiXLl3ixo0bbNmyhaioqHpfV1TXEOXo7e3Nnj17KCkpQafTkZycTGBgYGOEK37TEOXWo0cPfv31V65fv45eryclJYVOnTo1RrjiNw1Rbm+++SYZGRmcO3eOBQsW8NRTT/Hyyy83RrgtSots1ryT7OxsdDodbm5u1fa7ubmRmZlZ6+tERUVx8OBBCgsL8fLyYsOGDfTo0YPdu3cTHx9PSEhIVdv/559/TpcuXRryZbQ4jV1upqamLFy4kMjISPR6Pc8//zzOzs4N/TJavIYox169ejF06FC6deuGiYkJgwYNYsSIEY0RrvhNQ5Sbqakpb7zxBv3790dRFIYMGcKwYcMaI1zxm4b63BQNT5Kz2/hjfyJFUerUx+h2I/n69euHXq+vV2zi9hqr3ABGjBghX/JNpL7lOH/+fObPn9/QYYm7qG+5RUdHEx0d3dBhibuob7ndNGnSpAaKSEiz5h+4uLig1Wpr/GrIysqq8etCGA4pt+ZBytE4SbkZJyk3wyXJ2R+Ym5sTHh7O9u3bq+3fvn07ffr0USkqcTdSbs2DlKNxknIzTlJuhqtFNmsWFBSQnp5e9fjs2bMcOnQIJycnfHx8mDVrFuPHj6d79+707t2bjz76iAsXLjBt2jQVoxZSbs2DlKNxknIzTlJuRkrFkaKqSUpKUoAa28SJE6uOWbp0qeLr66uYm5srYWFhys6dO9ULWCiKIuXWXEg5GicpN+Mk5WacZG1NIYQQQggDIn3OhBBCCCEMiCRnQgghhBAGRJIzIYQQQggDIsmZEEIIIYQBkeRMCCGEEMKASHImhBBCCGFAJDkTQgghhDAgkpwJIYQQQhgQSc6EEEIIIQyIJGdCCIP16quv0rVr1ya/b3JyMhqNhtzc3Ca/txBCSHImhFCFRqO54zZp0iTmzJnDjh07mjy2Pn36cOXKFRwcHOp1nfXr13Pffffh4OCAnZ0dwcHBzJ49u4GiFEI0V6ZqByCEaJmuXLlS9d/x8fG8/PLLnDx5smqflZUVtra22NraNnls5ubmuLu71+sa3377LePGjeONN95gxIgRaDQaUlNTVUk2hRDGRWrOhBCqcHd3r9ocHBzQaDQ19v2xWXPSpEnExMTwxhtv4ObmhqOjI6+99hoVFRXMnTsXJycnvLy8+OSTT6rd69KlS4wdO5ZWrVrh7OzMyJEjOXfu3G1j+2Oz5qpVq3B0dCQxMZFOnTpha2vLgw8+WC3B/KNNmzbRr18/5s6dS2BgIAEBAcTExPD+++9XO27jxo2Eh4djaWlJ+/btq17PTbm5uTz99NO4ublhaWlJ586d2bRpU+3faCGE0ZHkTAhhVL777jsuX75MSkoKixYt4tVXX2XYsGG0atWKvXv3Mm3aNKZNm0ZGRgYARUVFREZGYmtrS0pKCt9//31VclVWVlbr+xYVFbFgwQI+//xzUlJSuHDhAnPmzLnt8e7u7hw7doyjR4/e9pjExEQef/xx4uLiSE1NZfny5axatYr58+cDoNfriY6OZs+ePaxZs4bU1FT+8Y9/oNVqax23EMIIKUIIobJPP/1UcXBwqLH/lVdeUUJDQ6seT5w4UfH19VV0Ol3VvsDAQCUiIqLqcUVFhWJjY6N88cUXiqIoyscff6wEBgYqer2+6pjS0lLFyspKSUxMvGU8SUlJCqBcv369Kj5ASU9Przpm6dKlipub221fU0FBgTJ06FAFUHx9fZWxY8cqH3/8sVJSUlJ1TEREhPLGG29UO+/zzz9XPDw8FEVRlMTERMXExEQ5efLkbe8jhGh+pM+ZEMKoBAcHY2Lyv0p/Nzc3OnfuXPVYq9Xi7OxMVlYWAAcOHCA9PR07O7tq1ykpKeH06dO1vq+1tTV+fn5Vjz08PKrucSs2NjZs3ryZ06dPk5SUxI8//sjs2bN59913+eGHH7C2tubAgQP89NNPVTVlADqdjpKSEoqKijh06BBeXl4EBATUOk4hhPGT5EwIYVTMzMyqPdZoNLfcp9frgcqmwfDwcP71r3/VuFbr1q3rdV9FUe56np+fH35+fkyZMoWXXnqJgIAA4uPjmTx5Mnq9ntdee41Ro0bVOM/S0hIrK6taxyeEaD4kORNCNGthYWHEx8fj6uqKvb29qrG0bdsWa2trCgsLq2I7efIk/v7+tzw+JCSEixcvkpaWJrVnQrQgkpwJIZq1xx57jLfffpuRI0cyb948vLy8uHDhAv/973+ZO3cuXl5ejXLfV199laKiIoYOHYqvry+5ubm89957lJeXM3jwYABefvllhg0bhre3N2PGjMHExITDhw9z5MgRXn/9dQYMGED//v0ZPXo0ixYtwt/fnxMnTqDRaHjwwQcbJW4hhPpktKYQolmztrYmJSUFHx8fRo0aRadOnXjiiScoLi5u1Jq0AQMGcObMGSZMmEDHjh2Jjo4mMzOTbdu2ERgYCEBUVBSbNm1i+/bt9OjRg169erFo0SJ8fX2rrrN+/Xp69OjBn//8Z4KCgnj++efR6XSNFrcQQn0apTadJoQQQgghRJOQmjMhhBBCCAMiyZkQQgghhAGR5EwIIYQQwoBIciaEEEIIYUAkORNCCCGEMCCSnAkhhBBCGBBJzoQQQgghDIgkZ0IIIYQQBkSSMyGEEEIIAyLJmRBCCCGEAZHkTAghhBDCgPw/r1EjGY74YocAAAAASUVORK5CYII=", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys5.sims[1], 1e-10, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e-3)\n", - "ylim(1e-12, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Cu111@-1.0V\")\n", - "gcf()\n", - "savefig(\"Cu111@-1.0V_X.png\")" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "076638f2", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys6.sims[1], 1e-10, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e-3)\n", - "ylim(1e-12, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Cu111@-2.0V\")\n", - "gcf()\n", - "savefig(\"Cu111@-2.0V_X.png\")" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "id": "87dcaf99", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys1.sims[2], 0.1, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e-3)\n", - "ylim(1e-12, 5)\n", - "title(\"Evolution of Solid-phase Mole Fractions vs. Time at phi = -1.5V on Ag111\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "4dfc055c", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Dict{String, Float64} with 17 entries:\n", - " \"O=CC=O\" => 3.45195e-29\n", - " \"proton\" => 2.7869e-5\n", - " \"O=CO\" => 0.646064\n", - " \"Ne\" => 0.0\n", - " \"COC=O\" => 1.65033e-15\n", - " \"[O]C=O\" => 2.21456e-42\n", - " \"C=O\" => 1.78999e-10\n", - " \"[CH]=O\" => 2.77632e-32\n", - " \"CO2\" => 0.27869\n", - " \"O=[C]O\" => 4.57005e-35\n", - " \"N2\" => 0.0\n", - " \"O=CCO\" => 2.01265e-6\n", - " \"Ar\" => 0.0\n", - " \"H2O\" => 0.07521\n", - " \"He\" => 0.0\n", - " \"H\" => 5.33777e-37\n", - " \"H2\" => 6.18657e-6" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "Dict([ssys1.sims[1].names[i]=>molefractions(ssys1.sims[1],1)[i] for i in 1:length(ssys1.sims[1].names)])" - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "id": "1f7d8918", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "1009×1012 Array{RGBA{N0f8},2} with eltype ColorTypes.RGBA{FixedPointNumbers.N0f8}:\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,0.933) RGBA{N0f8}(1.0,1.0,1.0,0.933)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fd1 = getfluxdiagram(ssys1,1e-3;speciesratetolerance=1e-4)" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "id": "13ecdbf2", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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peHIhHP3Ztc7OqdmPN+zYU5ij4ljYmDDI7jpJlOKxVGgxMjnin50MhgIRIhGtQWWyaou2Z1sdOpVGwXKY4xnM0AghWPcEUeqcmv3+9ba2aZ/IgNWk/XBd+Ydry80aFQLZ/w8hpFCyWR5TlsdUv7846A8P3JpuOtMriVJBWVbJDo/ZpqUxDbJ1gMV0jdeVbzWd6R1+ruXWsD/YNTk7GVi+r6LosfrtHrOBQgg2Ggyyu0UQxPBSfHLEPz44vzC3TAhY7DpPvm33PWVavVKhZBkWwwYUT2fe6Bn+0aW28cASAih12f50f/3uAg/PYJD9cRzPOD0mh9u088C26fGF7rbxF3982ZFtqtyZ5/JaWA6DbK0hAINK8aGasu3Zjudabp7uGQ7F4s+23Oz2+T+xe8eewhwVx8KGgkG2ykRRWgnFJobmR/pnF2aXNTqlp8BavbvAaNUq1RxNU7CRBaPxn1/veqG1OxSLcwzeV+T97P66YoeFQghktwEhUKq5ovLsvG3OwHy4p3389K/aNXpl5c68vG0OXsGCbK3RFFXssHz52J5Kt/OZa52D84GbU7NfDy7fV1H0+M4Kt0lPIQQbBAbZKiGQSKRnxhd72idmJoNavdJbZN9ztNxo0XA8AxsfIWQqtPKvF1tPdQ8l0hm9kn+4puzjDTusWjUC2buGMW13GWxZ+prGwp72iatvdHc0DVc3FuYW23kFC7K1puG545XFJU7rs8033+gZCsXiz7Xc7J3xf2pPze4CD89g2AgwyO40SSLLwWh/19Rgty+TFryF9gc/tsvqNLAchs1CIqRnxv/ds9ebR6cESXKb9J/ZW3tse6GaY0H2PiCE9Cb17iOlFXW5vR2Tl0/dunFlsP7AttwiO8NikK0pmqIK7eYvHWuscDueudY5OB/onJydWTr/SG3ZI7XlVo0aIVjnMMjuHFGUAvMrN1vHhntmDGZ17Z7CnEK7WssjhGATyYjitZGp75673jezAAClWbY/P7RrV76boWmQ3QkIIY1eWX+guGSHu/vG+PlXO2+2aHfu35aVY6YxBbI1peG545XFxQ7LT5s6zvaN+MPRH12+0Te78KnG6kq3E9MUrGMYZHeCKErzvlBH08jU6IIj2/iBD9e6vBaWw7DpJDPCqe6h751v9i2tYIpuKHD/2cFdJVlWCiGQ3VEIIa1B1XC4tGSHp+3K0MvPXMvb5qw/UGy0aBBCIFs7NEUVOyxfuXdfSZbtF9e7poLLFwfGxxeXPtaw476KIp2Ch/UKg+z9kSQS8K/cuDI02jfrLXI89MndVqceYxo2o2gqfaK990eX2hYiMQXLfKC88LP767KNeoRAtkoQQgaz5vADO8qqc5rP97/wb5erGvLLa71KFQeyNaVX8o/WlRc7LD++fKN5dGoisPTU6abBucUnG6tyzAaEEKw/GGTvFSFkORhrbxoe6vFluU0PP9lodxlpTMEmtRxPPHOt6+fNXSvxpFbBPVZf8fGGHSa1EmSrj6Ipp9t0/ImdowNzTad7B25O7zlW5sm30TQFsrXD0HS1J8v1oPY/2np+eaN7MRw70dE7EVj6zL7a+txsFtOwzmCQvSfJRLq3Y7L10qDRornv0bqsHDPGNGxeC+Hov12+caK9N5ZKm9XKT+2pfqS2XMNzILuLGBYXb8925Zg7mkZee761sMxVf6BYp1cBAtlaQQjsOs1/21dbZDf/6HJb3+zijYmZ2eXwR3dVPlhVYlAqYD3BIHuXRFHyjS82nemNRZKNR0qLtmezHIZNbW458t1z11+7NZjKCE699nMH6u+rKFKwDMjWglqraDxalrfNceWN7hd+eKnxnrKC0izM0CBbOzyDD5fmu036p6+0n+8fnVkKf/dc84g/+Kk9NV6LgUII1gcMsncjGk60XBzo75oq3eGp3lOo1SkBwSZGAHzB5W+dvX6mdzgjSl6r8QuHGw4U57KYBtnaoSiUlWP+4Cd299yYuHCya3xovvFIqdagAtnaoRAqdli+et++QrvpF80351cir3T2TwaXP3+gvjbXxdA0rAMYZLdHEqXJ0YWLv77JMPSDH2vIyjFTFIJNjRAYD4SeOt10cWBMkEiR3fxXRxsb8t00RYFsHeAVbHVjQXau5eKvb/7Hj64cemCHO99KUQhka8eoUnysYUee1fSvF1u7ff6Oydn/85XzTzZW31dRpOE5WGsYZLchHku1XhrsuTFeUZdbvadQqeJgsyOEDPuD/3T6atPQpERIWZbtr4421npdNIVAtm4ghGxZhgc/1tB2Zejkc807D2yr2JnHMDTI1g6H8d4ir1Ov/eGltvP9o1PB5adON00EQp/YXeXQaRGCNYRB9l8ihATmV86+3JlMpI8/sTM710pRCDY7QsjQfOAfT11pHp0iBCrcji8f21PpdlAIgWz94ZXs7sMl9izD2Zc7QouRxnvKlGoOZGuHQqjQbv7qvXtzzPrnW7sDkdhzLbemQyt/ur++zGWjEAKAlXiSYzDPYLiLMMj+OFGUhrp9l167lZ1ruf+xeo1eCVsAIWRwPvCPr19pGZsiALW5ri8dbSzNslEIgWy9omgqv9Sp0SlO/fLGq8823/NQtcGsBtmaMmtUn95T4zEZfnipbXQheGlgfCEc++8H63cX5ISTqe9faCl32Y5XbKMoBHcLBtkfkUykmy8M9N4Y33WopLzWy7AYtgBCyOB84H+9frllbBoA6r3Zf/2BPcUOC0IIZOsbQsiebXz4ycZzL3e+9NOm+x/faXHoQLamFCzzge2FWQbt9y+0NI9O9834//7kxSd2VixGYifae3tn/JVup8ekh7sFg+wPCS/Hz7/SGfCHH/hYgyvHjCgEWwAhZGBu8R9PXWkZm0YA9bnZXz62p9hhQQiBbIPQ6pXHHqm5+Nqtl59puvfReke2CSGQrSGaoirdjv/jgYP/dqnttVuDs0vh75y9TgikBKF/duHVrv7P7qtjMQ13BQbZ7yIEFmaXTr14g1eyD3+q0WjWwNZACAz5A/946krL6DRCsDPP/dfH9hTazQghkG0oChV38Hjl1dM9Lz9z/f7H6l1eM0IIZGsHIZRt1H3xnt12nfonVzsiyRS8JS2IJ7sGdud7dniccFdgkP0WQsj44PzpX7V7i+x7jpYr1RxsDQRgdCH4zVNXW8emEYKdee6//sCeQpsZIQSyDYjjmb3HyhkG//q55vuf2JXlMSMEsrWlV/LlLruKYyLJFLzNF1p5sa0n32bS8BysPgyyt0kSGer2nX25o3p3Qc2eQobFsDUQgInFpX86ffXayBQhUJeb/eVjewptZoQQyDYshsW7DpVIkvTr51oe+OguR7YRZGtqbHHph5fa/OEY/BaJkIuDY3uLvfeU5iOEYJVhkL1FFKVbrWNNZ3p3HyndXpdL0xRsDQRgKrj8z6evXhmcIIRU52R9+Vhjkd2MEALZBsew9O4jpaIgnXy2+cGPNVidepCtnXg6bdGq7Dp1IBLPiCK8bTmWeKH1VkW23a7TwCrDIAMQBPHGlaEbV4YOPbCjaHs2RSHYMuaWwt86c+3CwJhESKXb8eVje0qcVoQQyDYFhsWNR8syaeG1F1of+sRunVEFsjVSlmX72oOHJgJL10emmoYnh/yBSCIlEUIAuibnTnUPfWzXDkxTsJowbHmCILZeHOy6PvKBj9TlFtkRQrBlLISj3z3ffK5vRJRIucv25WN7ylw2hBDINhGOZ/bdu/2151tPn2i/79F6pZoD2VpACGl4rtxlL3FaH6ou7ZnxNw1NtI77ZpbCiXTmRHvfzjx3scMCqwnD1iYIYuvFwa7mkXsfrfMU2BBCsGWEYvEfXGx97dZgRpSKHZYvHdtT4XZQCIHsjhBFiERAFEGjAZaFNaVQcUceqnrpZ9cuvX7r0AM7WA6DbO3QFGXRqA4U5zbkuedWIu0TM1eHJ3tn/K929btNeiWFIJMBnod0Gt7EMBCJQCYDGg1wHLw/GLYwQRBbLw52NY/c+5E6T4ENIQRbxkoi+ePL7S939KUzQq7V+Ff37K7xZFEIgeyOEEXo7IT2dkAIHA44dAiUSlhTWoPq2IdrT/zkakfTcN3+YopCIFtrHINzzAaPSX9PWcHYYmjEHwwnkspFP/T3w+HD0N4OCIFSCW1t8CaLBY4cAbUa3gcMW5UoSu1Xhzuvj9z7aJ2nwIYQgi0jmko/c63zhbZb8XQm26j/yyO7d+W7KQqB7E6JRKClBerrwW6Hl1+GsTEoK4O1ZrHrD3+w6vX/aDPZtPklWQiBbD1ACGl4riLbUZZlByAwEYPxcZidhYkJwBgCAaitBbcbTpyAoSGoqoL3AcOWJEmkp32i7fLgsUdqcwpsCCHYMpIZ4Zc3ep653hVNpu06zZ8f3rWvOJemKJDdQckkpFKQlQUGAyiVUjgcj0Z5nscYw9pBCLxFjrp9Rede7tQbVRaHHmTrCU0hAASSBGNjcOYMjI1BYSEkk5CVBSYTaDQQDsP7g2HrIYQMdfuunOo+eLwyr9iBEIItIy2Iv7458KPLN1biSbNa+fmD9feUFTA0BbI7S6MBgwFaWsBqhZUVwWS6fv16JpOprq62WCwURcEaoSi0Y1f+4tzK2Zc7P/jxBoWKA9l6Q1FQUgIPPwyXL8ObMIaWFnC5IBCA+vpoNJrJZHQ6HUVR8O5h2GIIgYkh/9mXOxoOlxZXuBGFYMsQJOl8/+j3LrQEIjGdgv/03pr7K4s5TIPsjlMq4ehRaG2FqSly8GBAoeB5XhCE1157LS8vr7KyUqPRIIRgLTAs3vuB8hd/dKX10uCeo2UUTYFsXbHZoLoatFooKQGEQKeD1lYYG4P9+4nXu+jzXb161ePxVFZWarVaeJcwbDELs0tv/PJGVUN+RX0uRSHYMiRCmkenvnP2+txSWMWxT+yqfKS2XMEwIFsNCIHTCQ8+CIQghJhAwO/3J5PJ3NzcQCBw4sSJysrK4uJijuNgLWh0yoMPVL76i2ZXjjlvmxMQyFZJLJVOi6KW52iKgttkt4PNBghBURG8CSE4fhwIAfQbbrf78OHDbW1tJ06cqKioKC4u5nkebhuGrSS8FDv1YltOga12bxFNU7BlEEK6puaeOn1tPLDEMfjh6tKPN1SqORZkqwohQAgALBbL8ePHBwcHOzo6tFqt1+u9efPm9PT0/v371Wo1rIXsXGtNY+H5k10mu1ZvVINsdTSPTv/yRk9FtqMu15VrMWoUHIUQvCOE4E0Iwf8HIUAI3kLTtMPhuPfeeycmJlpbWwcGBmpra91uN8YYIQTvBMOWkYinz7zUoVTxe+/dzrAYtgwCMOwPfuvMtf7ZBUxRHygv+sy+Wr1SAbK7iOO48vLynJycmzdvDg8Pq1SqTCZDCIE1QlFox6786bHFpjO9Rx+uwQwNslUQT6Vbx6avDk8826IscVob8t01XpfLqFOxLELwnmGM8/PzXS7X+fPnf/7zn9fW1tbU1FgsFngnGLYGISM2ne5ZCcUefrJRqeJgK5lZWvnO2evtEzMIwd4i7+cP1ls0KpDddQghrVa7e/fugoKCS5cuBQIBjDG8k5ml8GRwiRBYDUyB7vKJm8TIGXIMIFsFQ/6AKBFBlBbC0YVw9PrIlEWr2u6y7y7w7PA47ToNz2B4r3iedzqdXq93aWkpFApZLBZ4Jxi2AEJIT/vEUI/vg5/YrTepYSsJROM/uNB6aXCcEFKdk/WFw7uyjDqQ3YZALBaKJ/Q8r2RZBYNpioI7gaIou91eV1d348YNuA0XB8a+f6FFlCRYBYQASsQ6//WNRLFG5BDI7rS0IKYFAd6WEgRfaGUmtHJhYCxLr63KcTbke+pys/VKHt4ThBDP83DbMGwB02OLV0/3HDxe6cg2wlYSTqb+/Wr7a7cGBUksdlj/8p7dBTYTAtltGV4M/f3piyyms/U6j1HvMeiz9TqnXqvhWCXDMDQN7w9CCG5DShCW40lRkmB1ID1FgilxbCXq5gGB7C4gAMl0ZnYlQk/PG5SKfJtJp+ARgrsAw2a3HIqefamjvMZbtD0bIQRbRjIjvNjW/UJrdyKdcZv0Xzi8qzLbgRAC2e2xqlXxTHpoMdwz50cI8ZhWMKxryBzNAAAgAElEQVRRqcg2aN0Gvcegdxv02XqdXatWMAysmu3Zjs/sqyEEVg+pSQ+eHdbn2OxeEwAC2Z0z7A9cHZrIiBK8jcPYplNXZDt2F3gq3Q6bTs1hDHcLhk0tncxcePWmzqCqP1BM0xRsGRlRfP3W4E+udkSSKatW9d8P7txdkENRCGS3R5AkmkJGpdK3HAYAQkgiIyQyQigeHwkEAYClab1SsTc3508baj1GPayaak9WlccJq0mSyBWlcXps8ZHdtbySBdmdc7JroGV0OiNKmKbMalW5y16f66r2ulwGrZJjEdxtGDYvSSJdzaMLc8sf/pO9vIKFLUOUyJXBie9faAlEYjol/+k9NfeUFTA0BbI/TpSkeDoTSaXmwpGRQGg8uDQaCE6GluEPQQhZ1KqHtpc8vL3UqdPAakIIECBYTRSNahoLR/tme9snavYUIoRAdodgijKrVdkmXV1udn2uy2sxqjkWIQRrBMPm5RtfbL08ePThGoNZA1uGREjH5My3z17zhVaULPN4fcXDNWU8g0H2e9KCGEmnAtH4WDA0uBAYXgxOhJZC8UQslU4JAoE/TMkwu3KyP1G3o8rl5DCG94RlWa1WixCC9UGjUzQcLrn02q38EqfBrAHZHVKebf8fHznqMRl0Sp5CCO40nue1Wi1CiOM4uA0YNqnISvzcK51l1Tm52xwIwRZBCAzOLT51umnIH2QwfXzHto837FBzLMjeQghJZITlRHJqaXk4EBwLhIYDQd9yOJxMxtMZiRB4G4WQkmEYmo4kkyIh8BYKIa/J8JHK8vtLi8wqFULw3iQiCZ7id1TsSCwnsBFjFsM6kF+S1XNjou3K0OEHdlA0BbI7IduoyzbqYHUQiegV+orSCiIRTGNCCEII/ksYNiNBEJvO9HI8U7+/mKYp2DJ8S8vfPnu9a3qOQujgtrzP7qszqBSwtUmExNLplURyIrQ84F8cWgwMLgT8kWg0lU6LIrwNIaRgGDXHWtSqXJPBazJ6jXqE0P999vJCJAoAWp47WJD7RHVFmd2GaQrelhbFSDKlU/CYouD2JKNJX7dPqVVmUhlVnQrWB5bDuw6VvPzMtbKqHKfHBLJ1jxASD8YTKwlCiNaiBSe8IwybDiEw0js72j/38JONChUHW0YgGv/Bhdam4UkgUJfn+rNDO+16DWxJEiHxdCYYjw8vBgf8i4MLgdFAMBCLR1NpQZLgbTRFqVjGoFDkmAwFZlO+xZRvNto0ajXHKhiGQmgxGnNqNaFYvNhqfqKm4khhvk7Bw1sEUQrG473zCy2T0xqO+1R9FWZZuD1as5aiqZHWkerj1QzPwLrh9Jjyih3NF/of+OguzNAgW98omrJ4LK0nWjkll1ebhxCCd4Jh01kJRS+f6q7bV2R3GWDLiCZTP23qeL17SJDEEqftL4405FqMCLYQApDMZELxxGgg1De/MLgQGFwILESjsXRalAi8jaVpDc/ZNeoCiznPbMw3G70mg0mpVHEspij4XSqW3ZHlKHfYHqvanmsy0hQSJbKcSAz4F5snfW1TvtFgiKGo/+vew0qWhdsmCqKYERmeEQUR/ghCiEQITVFwF9E0Vbu36PkfXpoaXcgtdoBsnSOQSWUomqJoShREuA0YNhchI14902swqbfX5SKEYGtIZYQTHX3/0dqdSGfcJv0XDu8qd9kRQrAFpAVxOZGYXFru9y/2zi/0+xfnw5FoKi1IEryNw1jLcw6tpthqLrJaCq1mj0GvVXAKjBFC8MfxDP7MrholyygYJpxMjQaCLZO+5snpoYXASiIpEoIQur+0qNbtQnC7CCFBX5DhmKLdRcHpoMFh4NU8/B5fYOXizdGGkhyv3UhRCO4Wo1VbUuluvTTo8lpYDoNsHcukM/5Rv6fCk0lmFsYWPJUeiqLgv4RhMyEw1OObGvF/6NN7OJ6BrUGQpLN9oz++fGMlkTRrVJ87UL8r30MhBJuXKJFoOjUXjvTNL/TMLfTM+aeXVyLJVFoU4W0spnU87zHqi62WQoup0Gp26XVajuMYjOB2UQhpeW54Mdg65WuZ9PXO+UPxhCBJ8DaLSvlQeYmG5+Dd0Jg0OquOU3Jas5ZmaPg9qYzwq6vdz1+8ebp96OOHqhrLc5UcA3cFRaHKXfnP/eDC+NB8UbkLZOsYRVH2ArtKr5IEKRVPIUDwTjBsIivLsaune+v2F1sdetgaJEJax3zfO9/sD0c1PPfJ3VVHywsYmoJNhwAkM5mleHIsGLo1O39zdn54MRCMJZKZDIH/xNK0hueydNpiq2WbzVJit2YbdFqeY2ka3quFSOyfLl5rmZxOiyL8LgqhvfneHS4HgncBIaQ2quEtOpsO/hCEUI7N4DBq+qf8//OFi72T/kf2bs8y6yiEYPXpTaryGm/b5cGcAhvHMyBbZcmMIEqSimPhXaIZWm/Tw5s44FQc3AYMm4UoSi0XBjQ6RXm1FyEEWwAh0D+7+O2z18YDSzyDH64p/XBtuYJhYBMhhETT6ZmV8K1Zf9fMXO+cfz4cjaRSgiTBW2gKqVnOodUU2yyldmuJ3eo26HQ8zzEYwR3g1GkeqSwdCQTnwhH4XTaN+oPl21QsC3cai+n76ku8DtMzZ9ubeieeu9jVO+n/xOHqumI3z2JYZQih8lpvT/v4xNB80fZskK2maCr9bPPNQCT26b01Nq0aVhmGzWJqdGGox/fBT+zmFAxsDdOh5e+eu949PU9T6HBp/qcaq7UKDjYFQZJWEsnJpeWbM/Mdvtne+YVALJbMCPA2HmOjUpFrNm532iuc9gKL2ahSKDCDENxZNEUdLMgdDy59r6k1JQjwNppChwpzyx02WB2Ypsq9jq8+evBkS98vL9/qGp3xLS4/2FD6UGO5Ta9GCMFq0hqUpdU57VeHvUV2lmNAtjri6czzLbd+fOVGMi1QFPUXh3cpWAZWE4ZNIR5LXTnVvb3W63SbYGsIROM/uNjaNDwJAPW52Z8/uNOqVcMGlxKEYDwxshhsn57pmpkbDYSWEsmMKMJbMEVpeM6p1ZQ5bGUOW7nD5tBpNByHKQpW02I0PrAQECQJfotTp32gbJuCYWDVIACTVvn4gR0lbtvPzra3DU7/9Ex736T/Y4erd+RnsZiGVYMQKq/x9rRPTI4sFJRmgWwVJDKZX97o+fGVGyvxpFmjyrMYMU3DKsOw8RFCulvHBUGsaiykKARbQCSZ+mlTx6nuIUESS522LxxuyDHpYcNKCcJiNN4772+emO6cmZtdCUeSKZEQeAuLaaNSWWgxVbmclVmOXJNBr1TwGMNdsRCNfevy9XNDo6IkMTQtEUmUCKaoe4oKttkssPpYTNcUurKt+peael6+1nO9b3LCv/ShPeXHd5YYtSoEq0VnVG2rcHc0DecU2BgWg+yOSmWEVzr6f3ixdSmWMKoUn91fd19lEUNTsMowbHyhhUh709DB45VqDQ9bQDIj/Kq994XW7kQ64zHrv3B4V5nLhhCCjSaZERZjsd75hdZJX/v0jG85HE2nCSEAgABULGtVq0rs1iqXsyLL7jboNTxHIwR3UTiZerql/dTAUEYUtTz3oYrSqaWViyPjboP+eGkRhzHcFQghu0HzqaO1JR7bM2c7bo7N/vC1lt4J/8cOVZXm2DFNwSpACJXXens7Jmangp58G8junLQg/vrW4PcutASicb2S//TemoerSxUMA6sPwwYnClLzxX5bljFvmxO2AEGSzvWNPH2lPZxImjWqz+2v35XvoRCCjSORERYi0Vtz862Tvs6ZubmVSDSdJoQAAIWQVsG7dNoKp70qO6vMYbWq1SqWQQjBXZcUhBe6ul/o6klmBCXLfLSm8k/qq/2RaEoQKrMc+RYT3F0cg/eUeb1244uXb/26pf/CzZGxueBH9lUcrS3Wq3hYBQazJq/Y2XV91JVjoTEFsjshI4qne4a/e+76QjiqVXCfbKx+tG67kmXgrsCwwU2NLkwM+R9+spFhMWx2EiEto9P/cr5lIRzV8NyTjVVHywsxTcFGkBbFxWjs1ux809hkx8zc3Eoknk4T+A0KIa2CzzHoa9xZ9Z7sIqvZqFRwGMPakQi5Ojb509bOSDLF0vT9JcWfqKnU8pyGY//2yD41y7I0DXcdQijbov/T+3eVemw/P9/ZP+X/7stNvRP+Jw7tKMgy0xQFdxRFoYqdeb96+krAv2LLMoDsfRNE6Vzf6LfOXptbjqg59qO7djyxs0LFsXC3YNjIUonMtXO9pVUeW5YBNjtCoH928Ttnr08ElngGf6im9JGacp7BsL6JkhSKJwb8i9cmpponfVOh5Wg6RQi8iUZIq+BzjPoql7PO7dpms5pUCoamYR0YWQz+67U2fyRKIbQnL+dzu+tMKiUAIITyzSZYU0qOOVxdmOc0P3ex60z70OttA8Mzi08crDpQmadWcHBHWRw6e7ax+8a41alHCIHsfRAl6dLg+LfOXJsJrShZ5iP12z/RsEPDc3AXYdjIhnp80XBiR0M+RSHY7HxLK989d73bN09T6Ehp/pON1VoFB+uVRMhKMjkWCF2fmG6emB4OBFcSSYkQAKAppFPwXpOx1p1V63YVWc0GBc/QNKwbK4nk060d3XN+AlBoMX1ud12WXgvrCYVQntP0Fw81lubYnj3fNTIb/OYvL/VMzD+6vzLHbqAQgjsEY7qiPu/MifbavUU6gwpk75UokabhyX8+fXUysMQzzIdqyv5kT41OycPdhWHDioaTrZcGahoLtXolbHbBaPwHF1qahicBoD43+3MHd1q1alh/CEAinZkILTVPTl8bn+r3Ly7FE4IkAQBCSMtzXpNhpyd7Z4670GIyKBWYomCdESVyZmj0zOCIKEkGpeLT9dVldiuC9Uij4I7vLClyWX9+rv3SrbETTd2D0wsfPVy1u9Sr5Bi4Q7K9ZqWaG+6ZqdlTCLL3RCKkdWz6m29cHVsMsQx+oGrbf9tfZ1Ap4K7DsDERQrpvjNOY3rbDgxCCTS2aTP20qeP17iFBEkudti8cbsgx6WGdyYjiQjTW6Zu7MjpxY3rGH4mmRREAEICSYZw6ba07q8Hr3u60m1UqhqZgvZpeXn6+41Y4mcIUdby0+EhRPk1RsF7RFLXNbf3rD+8vy3E8f6mrZ3L+fz5/4b56/yN7t2eZtAgheN84BVtWndPTPlFe4+UUDMjeJYmQ9omZb75xddgfZGj6vu1Fnz9Qb1YrYS1g2JiWg7Gu6yMH7q9QqjjY1FKCcKKj74XW7kQ64zbp//zwrjKXDSEE6wMhJJJK9/sXr4xNXB+fGg8txVJpAr/BYdqmUe9wOXfluHe4HA6NhmcwrG8ZUTzZO9jvXwSAYpvlsapyNcfCuqdXKx7Zu73Ybf3Z2fbmvsnnLnT2T/k/fri6tiibYzC8b/klWa2XBmemArlFDpC9G4SQW9Nz3zx1tW92AVPUPWUFf3Zol1WrhjWCYQMiEulqHtGb1LnFTtjUREk61zf64ys3VhJJs0b1uQP1u/I9FEKwDqRFcS4caZn0XRmd6PTNBuNxUSIAQFPIqFSWO2y7vZ4ad5bboFOyLIKNYSQQ+nXfYFoUlSzzSEWp12iADQLTVEWu0/WY7tXmvl9eudU+7JteWP7g7rIHG8qsejVC8H5o9Epvkb3nxkROvo2iKZDdHkJI3+zCN09d7fbN0xQ6VJL3F4cbHHoNrB0MG1BoMdLfNXX0QzUsh2HzkghpG/d973yzfyWq4blP7q46Wl7A0BSsKUJIJJUeXFi8ODLeND41HlxKZDIAgADUHJtjNDR43XtyPUVWi47nEEKwcaQE4WTvwGRoGQAqnI5DhXk0RcHGgRCYdaqPHqra5rb97OyN9uGZp99o6530f/xQVUWek8E0vFcUhUqrcl75+fXlUMxo0YDsNhACQ/7A/3PqasfkLEJoX5H3L440ZBl1sKYwbDSSRDquj1gceneeFTYvQmBwbvHbZ66PLS5xDH6ouuTDtWUKhoG1I0jSQiTaNj1zdnC00zcbjCdESQIATFFWjbom23mgIHdHlsOiVjE0DRvQwELgjYERQZI0HPfQ9hKLWgUbEIvp+uJsj03/q6vdr1zra+odn5gPPbJ3+3312wwaJYL3yJZl0BlVI70zdfuLQfZOCMDoYvCbp662jU8jBLsLPF+8p9FjNiBYYxg2moB/Zajbd/9j9QyLYfOaWVr5zrnrt3xzNEKHS/I+tadGq+BhjSQymdFA6OLI+KWR8ZFAKJ5OEwCEQMtzBRZzY66nMdeTbzYqWRbBRpXMCCd7BmZWwgigxp21J9dDIQQbE0LIYdT+ybH6Uo/9Z2fbe8bnf3Dyeu/E/EcPVW1z2zBNwbvHcrh4e3Zvx2RBmWtlKapU8VanHmR/CAGYDCz98xtN10amCIH6vOwvHW3MtRgQrD0MG4okSR1NI063MSvHDJtXMBr/wcXWq0OThEB9nuvzB3fatGq46wgh4VSqZ87/xsBI0/jk3EpEkCQAwBRl1ahqsrMOF+bvcDnMKiVNUbDBDSwsnhseEyVJp+A/WL7NqFTAnSBJUvotoigSQhBCNE2zb6EoClYTz+K923NzHcYXLt18vXXgbOfw6Fzw0f2V91QValU8vEupZEahZAe6psYG5vwzoY98Zt/BB3aA7A/xhVaeOt10eWicEFKdk/Wlo40FNhNCCNYBDBtK0B8e7Z89/sROzNCwSUWSqZ82dbx2a1CQxBKn7QuHG7xmA9xdokQWo9Hmyemzg6MdvtlQPCERAgBKlskzGffle/flefMsRhXLItgMkoLw677BuXAEAdRkZ+30ZCOE4L1KJBLBYHB8fHx4eHhyctLv9y8tLSUSCUEQMMYKhcJgMNhsNo/HU1BQ4PV6TSaTQqGAVUAh5LYaPn+8oTTH/vNzHYO+xW+fuNo74X/8QGWe00xTCG5PIpZ66WfXLpzsmveFMmmRV7CZjAiyP2R2Ofzts9fO94+JEqnIdnzpWGOJ04oQgvUBw8YhSaSredTuMjjdJtikUhnhRHvv863diXTGbdL/+aGd5dl2hBDcLRlRnFmJXB4dP9U/3O9fjKXTAIAQMigV2532o8X5Oz1uu1aNKQo2kcGFwPmhMVGSdDz/QFmxXsHDu5fJZGZmZq5fv3758uW2tjafzxeJRARB4DiOZVmaphFChBBRFNPpdCqVwhhrNBqXy1VTU7N3796GhoasrCyGYeBOU/Hs0eqifKf52Qud5zqHTzb3DfkWPnqwal9Fnopn4TYwHDZaNOHleCYtguyP84ej3z3XfLpnWJCkEqf1S8cay112hBCsGxg2jtBiZKhn5r7H6jFDw2YkSNKZ3pEfX2kPJ5JmjepzB+obCnIohOCuSAnCSCB0bmj03NDoeHApKQgAgCnKrtXsysk+XJRf4bQbFDxCCDaXlCC+0T88G44ggOpsZ70nGyEE70YmkxkeHv7Vr371yiuvDA4OZjIZs9lcWlq6bds2r9frcDiMRqNSqcQYC4KQSCRCodDc3Nz4+Hh/f//w8PDPfvazZ599trCw8IEHHnj44YcLCwsZhoE7iqJQQZb5iw/vKcuxP3uhc8i3+I8vXuqZmP/I/kq3VU8hBAArsSSmKRXPwu/BmN57rHzet/TST5uSiTQAAdnvCURj3zvf8tqtwYwoFtotXz7WWOVxUgjBeoJhgyASudkyanHosnLMsBlJhDSPTn/vfPNCOKpVcE82Vh0rL2RoClZfIiMMLiy+3j90YXjMtxwWJAkAOIzdBt2hwrwjRfn5ZqOCYWCTGguGzg2PipKk4bn7y4oNCh5uGyHE7/c///zzTz/99ODgoF6vP3jw4JEjR3bu3Jmdna3VajmOgz8ilUqFw2Gfz9fc3HzmzJnr16//wz/8w4svvvjkk08+/vjjNpsNIQR3lFbJP7CrtCjb+szZ9is94y9eudU/tfDxI9W7tnkkQv79zA2tkn/8QCXHYPg9ChX3wEd3+meWLp+6RUD2vwvFEv96ofXVzv50Rsizmr50tLHWm00hBOsMhg1iORQbvDV99JFahqFh0yGE9Pj83z5zbSK4zDP4kZryD9eW8wyGVRZLp3vnF071D18cGZ8LR0RJAgAVyxZZzfcU5+/P97r0OpamYfPKiOKZwRHf8goAVDjtOz3ZCCG4PZIkdXZ2fuMb3zh16pRSqXziiScef/zx6upqvV6PEIJ3wnGc5S2VlZWPPfZYZ2fnL37xi5MnT/7d3/3dtWvXvvrVr1ZVVVEUBXcUpqkSj+0rH9lflmN/4dLN7om5//Hs+ft2brPo1C819XAM7bUb9pTnUgjB7zGYNY9+dt/i3PJI/yzIfstyPPnjyzd+1d6bzGQ8ZsMXj+5uyHfTFIL1B8NGQAjp65jQGVXZXgtsRhPB5e+cu94748cUOlZe+MnGKg3PwWqKpdM3Z+Zf7R24Oja5GI1JhCAALc9VZjnuLSnalZNtVatoioLNzrcSPjs0mhElFcveV1JkVCrg9oiieOnSpb/927+9efNmfX39F7/4xYMHD2q1Wnj3EEIGg+HgwYO1tbXHjx9/6qmnTp48OTU19fd///cHDhygaRruKARg0Cg/sq+iKNv6zNn21sGpZ893MpiOJdMIwU/euJFt0ec6TPCHuHOtT3z+4L/9r9cJISB7SziR+ver7c+33oqnM9lG3V/es3tvoZemKFiXMGwEsUiyt3Oy8Z4ylsOw6SyEo98739w8OgUADfmezx2ot2hUsGqiqfStuflXewaujE0GojGJEISQQamocjnvKynamZNtUioQQrAFiIRcHp0YDy4BQLHN0uB1UwjBbSCENDc3f+UrXxkYGHj88cf/5m/+Jj8/n6IoeH80Gs3x48dLSkq+8Y1vPP/881/5yleeeuqpxsZGhBDcaQymqwtcbqv+hUs3n73QGUumAYAQ6J2cf+Zcx18+tEen4uH3IAqV13kf+ZO9nIIBGUA0lf759c5fNN+MpdJOvfYLhxsObsvFNAXrFYaNYKjbxzDYW2SHTWclnvzx5fazvSOiRCqy7V840pBt1MPqSGQyN2fmX+ruvzo2EYjFJUIQQmaVcleO+77Soh0uh57nEUKwZQSisTMDIylB4DC+pyjfqlbD7Zmamvr617/e19f3yU9+8mtf+5rdboc7hKKogoKCr3/96xzH/eQnP/n617/+/e9/3+v1wipACIwapUWngt8iiNLZjuHCLMuH9pQzmIbfgzG9+0hpOpWBLS+ezrzQcuun1zojyZRNq/6zQzvvKStgaBrWMQzrXjKevtk6tr0uV6HkYHNJpDPPt976VUdPKiPkWo1fONxQ7LAgBHdcUhD6/Yuv9vSfHRpbiEQlQhBCJpWyIcf9QHlxlcup5jgEWwsBaJ3y9fkXACDHqN+Xn0P/v+zBB5idV30w+P855+3v7XfuvdN7l0bSjMpoLMmW5ALGNmCDTTELToBACC35UmCf3TzZ5wvPLtkUWCB8JARCs8GmBIiNkWyr2Fazymg0XdPrnXtn7tx+33bOWaMP7doxNpKtMiPP74cRXALLsr73ve8dPnz41ltv/fznP19cXAxXWnFx8ec+97nZ2dn9+/d/97vf/dznPifLMlwF49HEfzzfWzBteIlswXzkwJna0sDWxgqEELyCJAuSLMCbW8G2f3Ky99+ePZnKG0Vu/Y/3bn/bxiZJILCyCbDiTY4sWKbT2FYGNxab0sd7hr535EzWsIq97k/s7dpWW44RgivKonQ4tvjLvsGnhkbn0mnKOEKoSNduqqm6Z31zR1mJS5ERvBllDHP/0GjOtAjGu+trK3xeuDTj4+M/+tGPAoHAZz7zmYqKCrg6ysvLP/OZz5w+ffrRRx+9//77W1tb4SpQJOFtnS1VEf/QTHwplcuZNuccAGYWU99+8oXSgLc85IU1r2Dazi9OD/zrwRPLuUJAV/9o97Z72ptlQYAVT4CVzbHp2RNjTW3lLo8KNxDK+OGhiX85cGIpm/dp6kdu2bq3tZZgDFcOZWw6mfpl39B/9g1OLacoYwjApypd1ZXv2riuvbzEJcsI3rwGF+Knp2c5QNil722oFQmBS/Pcc8+Nj4/fd999nZ2dCCG4gDGWz+dVVaWU2rataRpCCAAsy1peXgYAv98vSRL8ToxBMgmmCT4fqCpcgBDaunXrrbfe+uijjz733HMtLS0IIbjSKkK+D9zakTftxVTu/Gx8YCo2OB0bm08ks4UzI7M/OtT98bu7dEWCNz3GuUOZJBAAsBz6eM/Q1w8cX8zmfZryhzdvuW/zOlUUYTUQYGWLzSVjc8k9d21ECMGNgnPePTX31aePzi6nNEl8//aN72hvkQUBrhDGeTyb2z808rOe/qHYokUpAvAo8pbK8nvbWrZXVXhUBcGbmuXQZ86PLeXzCMG2yvKGUBAujWma3d3dnPOdO3e6XC64KJ1OP/HEE7fddtvS0tLg4ODdd98tiqJhGI8//ngsFvN4PO3t7U1NTZlMhlIKF8myrKsq6u6Go0dBkkDT4J57wOuFC3Rd37Vr12OPPdbd3W2apqIocBUghHRF0hWpKuLfvbE+WzDnltIDU7GBqYXx+cSp4ZmdbTUYIXhzG5qPHxmZekdHq1eV9/We/9rTR2PprEeVP7Rz83u2bdAkEVYJAVYwxvi5F8YrakKBsAduFBxgNJb46lNHz0cXRYHc097yYNcmXZbgSuAA6YJxeGziJ2f7umfm87YNAJokdpSX3ruhdUdNlV9VEELwpjeXTj83NkkZ9yjyrU11uizBpTEMIxqNqqpaU1ODEIKLKKWzs7Ojo6NLS0uLi4uccwCYmpoaGxt76KGH3G4357xQKBw4cCCbzcIFCKHq6urO9evFI0fgppugvh4efRT6+6GrCy5ACFVXV2uaNj8/bxiGoihwlQkE+1yqz6W2VkVMuyWVM2yHLiwsqIridrvn5+dDoZAsywBg2/b09HQqlSoqKiotLSWEwH9h2zA1Bek0RCJQXAwYw6plOfTJc8OPHD87k0f5wMoAACAASURBVEi1lIa/efiF+WTGJUsPdrW/f/tGXZZg9RBgBUsv50YH5+58YBshGG4U8XT26weOn5yYRQhubqr56C1b/boKV4LhOD2z0R+dOXd4dCJlGAAgEdIcCd27ofX2xrqQS0cIwRoAzvnxyZnpZBIAGkNFHWUlCC4V59xxHIyxIAjwcul0uqenJ51Oy7K8uLjoOE46nZYkSdM0SZI455Zl+Xw+WZbhIpfLhRgDywKPB2QZFAVME15CFEWEkOM4nHO4tmRRCPtcAPDTnz5dXFy8adOmxx9//J577iktLeWcnz59+vjx4+Xl5YuLi8Fg0DCMRCIBFwiCUFpSInV3w4kTEArBc8/BO94BlZWwak0nUgcHx7KG9bPTfY/3DOYMS5PE93Zu/OCOdrciw6oiwAo23Dvj9mqllUG4UWRN63tHzhwYGGWcd1SV/smtXSU+D7xhlLGxpeX/ONf/RP/wfDrDOBcwrgr47lnXfFdrU7nPQzCGNRelDfPgyHjBdkRCbq6vDuoaXDJJkgKBgGEYCwsL8BIIoYqKirvuuisej/f09CSTyb6+vpqaGkmSnn76ab/fX3aB3+/XNA0uQAi53W6k69DUBM8/D8XFkMlAbS28RDQaRVQi+cgzP+/xB70uj+r2qm6vqmiyKBJBJIJIRJFgguGSMcbGh6KyIhWX+wWRwO+TzWYHBgY459PT05RSAHAc59ixY52dnVu2bHEcR5Kk8fHxc+fOwQWapvl0XTp+HDo7oaMDHnsMenqgshJWJ8rY4aHxyaUkAFgOtRxKMLpjfcNDuzZ7VQVWGwFWKrNgDZyZWr+1RlZEuCHYlD7ePfjjk72G7dSGAp+8rasxEkTwhnCARD6/b3DkR2fODccXHcoQQmGX/paWhndtXNdQFBQJgTUvNxxf7JmLAkDEre+sqSIYwyVTFKW5udmyrFOnTt13332SJMEFLpdrz549gUBA0zSv1+v3+ycnJyORyL333js6OkoI8fl8sixv2rQJXmn3bhgaglwO3vY2KC+HiyzLOnXqVL6Qa2iu1l1aOpmPzyeNgm0ULMYYAoQJUlRJ1WRZFRVVUjTJ7VU9Pk13K6IkiKIgiEQQiSASjBFcZFv0V4+9MNA9tX1PS9etrRW1IVkR4dUxxmKxmMvlyuVy+Xz+/PnzmqY5jqMoCsZYEASEkCAIqqrCBYqiYITAcUBRAGOQJLBt4BwQglUols491T9iORQu4hzSBTNjmH5dRbDKCLBSzU4u5XNmfWsp3BA45yfHZ7/93KlU3gi6tI/csnVzdRlCCN4Aw3G6Z+Z/cOrs8+OTWdMCALcsb6+ueE9725aKMk0SYc0rOIw9Pz6VyBcQwObyspqgHy4HxnjHjh2hUGjfvn0PPfTQunXr4AJJkhoaGgBAVVWPx3Po0KFEIqFpWjAYLC4uhtfmcsHmzfAKY2Njv/71rz1+7e3vvWXXrq0AQClzbOrY1LGpbVOjYGVThWy6kM0UjJy1tJCeGY8XcpZl2pQyhJAgElWTNJesqJKiyS634vIoRCDRmcTY4PzUSOzg42e37Grc+Zb1dc2lmi4DglfSNG3Hjh3t7e2xWMw0zXg8bhjGunXrjhw5kk6nCSEdHR1ut7u0tBQuEF+kabBhAxw9CvE4TE3B294GCMEqxDk/Njo1FI3DSzDOnx0e12XxL+68ucitw6oiwIrEKOs9NVHTVOLxanBDmFhMfuPg8elESpXE93RuuGN9g4AxvF6M86nl5E/O9v2ybyiazjDORULWFYcfaG/b21Dr11QEa363xVz+6MQUZUyXpJ21VZokwWVqa2u74447Hn744W9961t/8zd/43a74eUQQg0NDeXl5YqiwOuVzWa/9a1vDQ0NPfDAAxs3boQLCMGEYFkR4XfhnFOH2TZ1bOrYjmU6+ayZTuWzqUI+a+SzxlIsXciZ6WR+ciQGAI5D56aW/vOHx5/f37exs/a2d3as31wtSgK83JYtWzRNU1V17969lZWVALC4uNjZ2VlUVJRIJMrKykRRLL0AXmrHDvB6IZGAO++E+npYnZJ5Y1/v+bxpw0tokriuLLKttkKRRFhtBFiRkonc9Fj8HR/oQhjB6pcqGN957tTpyTmMYE9z7Xu3bdAkEV6vrGkdGh3/3gvd5+YXbEoRQiUe99vXN79r47pKvw8jBGteXe9cdHQxAQCVfm9HeSmCy+Z2uz/ykY8cPXr0u9/9bkNDw0MPPaQoCrwExriiogLeAMMwHnnkkX//93+vrKz86Ec/6vF44BIghASRCCKBV8Eos226MLt87oVxuECSBd2tBiMeURLSybxlOqIkwMvV1tbCBevWrVtYWDh+/HhXV5eqqlu2bIHXoKqwdSusZhzgzNTc2el5uEiVxHVlkbs2Nt3SVBP2uDBCsNoIsCIN9874Anq41A+rn03p492Dvzo3TClrqyj+yC1bg24dXhfK2Mhi4pHTPU8ODC/nCxzAJUtd1ZXv37xhc3mZIgqw5jWZDj06OZ0xLYzQtqryiMcFr8uWLVv+4i/+4vOf//zf/u3fcs4/8IEPuN1uuEIymczDDz/8hS98ASH053/+59u2bYMrBBMsEyyIRHfJzRsrappKapuKa5tLImV+l1uVFBEheG0Y44aGBlVV4U0gZ1r7es+nCiYAqJLYWhp+28am3U21Ea8LIwSrkwArj2nYQz0z67dUS7IAqxznvHtq/vtHuzOGGfboH755a2NxEYLXI2UY+wZHfnDq7HBs0WGMYNxQFHzf5g13NNcHNA3Bmt8vns2dnJrjnHsUpau6UiIEXhdRFB944IFUKvXFL37xr//6r8fGxj7+8Y/X1NRgjOENYIxNTEx84xvf+Pa3v40x/qu/+qv3ve99oijCFeULuj79f9zrC7pcHkWSRbgcoVBo9+7d8OYwOB8/PjYtC6SlNHzPpuZbmmojXhdGCFYzAVae6MxyLlOoay6B1S+Wzn372VOTS0lFFN69pW1XYzVGCC4T5XwkvvSdF87sGzyfNkwA8KnKbU31H9i8sSlcRDCGNZfm3Hx0JpkCgOqgrzUSgjdA1/U/+qM/8vl8f/d3f/e1r33t2LFjH/7wh++4445IJEIIgctEKY3FYvv37//Wt7514sSJysrKv/zLv3zPe96j6zpcaZou1zaXwJXGKEMIAQJOORYwrBycA0LAObwIIeAcOAeEACF4dabjPDc8Ueb3fvjmrXuaa0u8bowRrH4CrDCc8YEzkxW1YY9fg1XOdOjPTvcdG51CAF31VfdvbVNEAS5TxjSfHh777gtnBhbilDGR4JZI+H/ZsmlPQ61HkWHNJTMd+sLUbNayMEJbK8qDugZvjKZpDz74YENDw5e//OX9+/d/5jOf2bJly913371nz57q6mq3200IgddEKc1kMhMTEwcPHvzlL3956tQphNBdd9316U9/evv27aIowlXAOM8bFkJIIJhgTAhGcAUsjC1wzlWXmoqlKtsqMcHwmhjjsaUMRkjXJEURCcZwNczPw+wsbNgAY2OAEHi9cOIE5HLQ0gLr14MgwKuwKeuoKr1/6/pir4dgBDcKAVaYTLowcT56+31bMMawmnHOT0/M/uRkr2E7lUHfH+zcHPa64HIwzicSy999ofuJ/qFkwQAAv6bes675fR0bqoN+ghCsuRxLufyZmXnOuUdVtlaWiYTAGyaK4k033dTU1PSrX/3qBz/4wQsvvHD06NFIJLJx48b29vbW1taamppQKCTLMiEEY8wYo5SaphmPx8fHxwcGBs6cOXP27NloNKqqamdn54MPPnjnnXcWFRUhhODqyObNf/3V8Vgy61IkXZF1RdQUSZMlXRE1RXIpskeXIz63W5PhcqhudeDwAAdetaEKYQS/TzZvfuN7h8enl8pL/NXlgeqKYEVpIBRwaZokSyJC8DtxzvMFW5YFgWC4FPE4dHdDfT0MDgJjkE6DxwN1dXDwIOg6NDTAq9AlaVdjNUIIbiwCrDBTIzFRFksrA7DKLaSz//78qblkRpPE92zbsLGyGMFlMBznyPjUN4+d7J6ZdxgjGLdGQh/a1rG3odYlS7Dm8g3G4jPJFABU+LzNkRBcIQihoqKiBx988I477jh27NiTTz555MiRw4cPP/nkk7Is67rudrv9fr+maYIgOI6Tz+eXl5czmUwulzNNU9O08vLyD37wg29961u7urpCoRDGGK4mUSTpvLH/1DBcgAAwxgLBhGABY0US2uvLPnj7luaKEEIILpk76GaM5ZK5YEUQIQS/j0Bwc32x7bCZueXewVnKuCSQcMhdWRaoKA1UlvorywM+t6ppsiQSuKhg2A//7ITbpdy6s7kooCOE4LVRCv398JOfwMgI1NVBMgm33QbhMAwNwewsNDTAq0AIABDccARYSajDBnum65pLFFWG1cx0nJ+e6nthbAYB7Giouqe9WSQELg0HWMzmfny275HTZxfSWQ7gVZQ7mus/uLW9PhQkCMGay+cwdmZmLmOaCKH28pKgpsEVhTGORCLveMc77rjjjvn5+b6+vp6envPnz09MTMRisbm5OUop5xwhRAhxuVyNjY1VVVWNjY1tbW3r168vLi7WNA2uPtuhBcMOujWCMWUMADgAZYwyBjb43eptHQ3337yxIuxDCMHlWI4uE4F4ijyJmURJYwlCCF6Tpkrvvqvj7tvasjlzPpaeml2aml2emF7q6Z85enKMA6iKWBzy1FQEK8uDlaX+smKf26VkcubRU2PTc8uneibvvbO9fX2FqojwGjCG8nLo7ASEQFXBMGB2FjCGTAbcbsdxOOeiKMKbhgArSTKRXZhJ7LitFSFYvTiHUxOzPz3ZZ9hOdZH/Qzs6gi4dLg1lvH8h9q9HTx4aGS/YNkaovijw0LaOtzQ3eBQZ1rxeqYJxdi7KONclqb2sVBIIXB2qqtZecNdddxUKhXw+bxhGLpfL5/OO4wiCoKqqruuqqmqapqoqxhiuMpvSbN6KJbPDM/Hh2fjQdHx0bpFxBi9BCG4uDz14a8eutlpdkeAyMcqS0WT1pmpRERcnF8M1YUES4PchBOuarGtyJOTZtK7ccVi+YKWzhbloanx6aWJ6cXI28fwLo88cGUYIPC6lrNjv1uW5hZRh2sfPTJwfj+25qenu29qqK4KEYPiddB0aG6GuDpJJQAiam+HECTh7FoqLeWPjzMzM4OBgS0tLaWmpKIrwJiDASjI6MOcNuoIRL6xmS7n8w8fOzqcymiQ+sK2traIYwSUp2M7BkbH/8fwLQ7E441wRhB21VR/t2rKhtFjAGNa8AdPJ1NhiAgDCLr21OARXH8ZYvwCuB8uhuYK1kMycn1kcno0Pz8SnY8lUzjBsG2OsyaIiigXLhgvcmnxbe8P79rbXFgcxRnD5MMZVG6qISBBCniIPEQlcPkHAHrficSvlJf6tm6ot28nlzeVkfnp+eWo2MTG9NDWb6BmYyeVNAOCcLy3nfvZkd3ff9N23bdhzU6PfpyME/1V1NZSVgaLA1q3wIlGE2lqwbXC7kSyHMJ6fnz98+HBpaWlbW1swGCSEwA1NgBXDMp3zvbON68slWYBVizK2r3f4+Og0AGyvq7x7Y7NICFyCpVz+R2fOPXzqbDybA4CwS79/0/r3dGyIuF0I1rwhHKAvGksZBgA0R0JhlwtuOIxzw7KzBSuayIzMLY7MLo7OL03HkqmcYdg2RtilSsUBd21JsKUyXFcaPNA9+stj/QhBXUnwvXvab22v92gKvG4IRFmEC0RFhDcMIZAlQZaEgE+vqw5xzg3TTqWNbz7y3K8P9sNFlLKRifg3vv/syZ7J++7ctHFduSQK8FKCAIIAL5Jl+J+8XrhI1/XOzs66urqenp59+/bV1dW1trZ6PB6EENygBFgxEvF0cilX11ICq9nIwtJjJ3pzplXsdb9v+8agS4ffh3E+El/6l6MvPDU8mrdsglBzJPSxHdtuqatWRRHWvGGm7fRHY6ZDBYzXlYQ1SYTVj3Nu2jRvWsmsMRVbHp1bGp1fmogmFlO5TMG0bIcQrClSxO+qKy1qqQw3VYSqIgGfrmiKhBHKGdbR/oktjRUP3trRVBEiGMPVtGRmB1Lzm/wVLlGBy4cQUhXJcVgmawIAIViWBEkSFFnwebSgXw/69Wgs3VBrS6IAlwNjHA6Hd+/ePTs7e+bMmZGRkV27dlVXV8MNSoAVY6R/LlTi9QZ0WLVypvXYC+dGY0siIXdtbNpcXYYQvDaHseOT0185fOzsXJQypgjC7oaaj920rTkSIgjBmishZRiDsTgAuGW5NRLGCMEqxDg3LCdvWMvZ/NxiejKWnFhITMWWo4lMpmDmDZsyJouCrkhVEX9NcaCxPNRQVlQV8ftdqqZIGCF4ifa6sj991y2dLZV+lwpXWczIfGP40MHo0Htrtr6/plMXZHhdOEBTXaSmMuj3akG/HvS7gn5d12RJJJIkSCJBCMHrIghCVVVVKBR68sknJycnq6ur4QYlwMpgGvbY4HzblhpBILA6cc6Pj03v6z3vMNZWXnzv5nWKKMBrytv2kwPnv3HkxEQiyTkPaNr9m9Z/YMvGsNuFYM0VM7WcmktlACDs1muCflgNOOemTQ3LzhlWLJmdW0rPLqam4snp2HIsmcubVsG0HcoEgjVZ9GjKuqpITXGwtiRQWxIsCXrcqqzKIkYIXkVx0BMJuDFCcJUtFNL/PHTg8dlzJrW/M3pUROSB6q2aIMHlc+vyg/dtEwWCMYKrQJblQCCAMYYblwArw1IsnUnlqxsjsGrFM7kfHu9ZyuXdivzezg1VQT+8pkS+8Mjpnu+f7F7K5RFCNUH/x27a9pbmBl0SYc2VwwEGFmIZwwSApnDIr6qw8jiUmbZjWE7OsOKpbDSRmVtKzy2l5xPphUQmUzALlm1aDuNcFIgqiV5Naa4IV4b9lWFfVdhfGfb5XKquSKJA4NIgAIQQXGUc4Fxy5uDCkEltAEhZ+W+NPi9g8q6qzSoR4TIhhGRJgDVvgAArw/m+2UhZwOPTYXWijD3VP3p6YhYB2tlYvaeljmAEr4IDzKfSX3/+xH/2DeUsi2DcXlbyqZu3b60sFzCGNVeUYdsDC3GLUpHg1uKQKgpwnXAASpnlUMtxLJtmCmYinY+nsvFkbimdiy5nY8nMUjqfN23Dsk3LYZwTjBVJUCWxNOgpCXgqQr7ykLesyFsR8vlcqiaLkiggWLkQwNaimnsrO344fiLnmACwbOa+ef6wgPA7K9sVIsKaa0uAFcA07PGhaHtXHREwrE5TidR/nOrLW3ax133/1javpsCr4JyPLS1/+fCRZ4bHLEoVQdjTUPuJnZ0NoSBGCNZcaRnTOh9fAgCXLDeHQwghuDo45w7jlDKHModSmzLLdrKGlc4Z6byRyhnLmUIyV1jO5BOZwlI6n8kbpu2YtmPalDKGEIiEyJKgiEJp0FMS8JQEPSUBd0nAUxr0hLwuTRFVSRQFAquKV1QfqrvJYfSxyZN5xwKAJTP3jfOHBUzuKd8oEwHWXEMCrACJWDqXKVTWhWF1shz6ePfgcHRRwPj2dfUbK4oR/G6M875o7J8OPn9sYtphzC3L97ev/4NtHWG3C8ENwqHModShzKGMMu4w5jjUsB3LckyHWg61bMd2qEMZZYwyThmjlHEO/wXGiGCMEBCCESCBYISA4BchghAhWCCYYCwQLBAsEEIwFggWCEYIYQQIIQBACI0sLs6nMwDgkWWvJCdzBQQIIQBAcBECQAgYhws45/Ai/hvA+G8w/huMc4cy03IM2zFtx7Qcw3YMy84Zdt6wcoaVM6y8aeUMK5M303kjUzBNmzoOtSmzHWo7lHEOAALBkkAkUZAEEvBoIa8r7HOFfHrY5w779JDPFXBpmiwqsigKBMGq55O0D9fvdDj76eSpArUBYNHIfH3oIEH4rvI2CQuw5loRYAUYGZgPlfg8Pg1Wp8H5+ONnBy1K68KBd3a0qpIIvwvj/OT07D8ceO7sbJRxHtDUh7Z1vH/zRo8iw2rjUGY5jmlT03YyeTORySezhXTeSOeMVN5M54xswcybVt6wc6ZtWLZDKWOccs4YZ5xzxhl/EXDgnAPnHF4BASCEAAAhBAgwAKAXAQKEECBACAG6ACNAvwUYIYKxQDDBL0IE4zS2lmkBAFLL+X/40SFFEAhGBGN4CYSAYOwwBhw4cIcy4MA4dyizKXUocyizHepQ5lBG2Ys45YwxThlnjDmMUcoo43ARIVgkWCREFIgoELemeDTZ71IDHs3v1gJuLeBWA24t4Na8uiJLgiIKkihghOAG5Zf1jzbschj9+XS3QW0AiBnpfx46IGL8ltL1IiawMhBCBEGAG5cA15tlOhPD0db2KiIQWIVypvWzU30zyylZEO7Z1FIfCcLvwjg/OT37fz11uC8a45wXe1wfv2nbO9taNUmElY0DWLZjWE7BtJcyuWgiM5/IxJLZpVRuMZ1LpPOZgmk51Hao7VCHMsY5ACAAjLFAMMGYEEQwJhgRhESRYIQEggWCCcaEIIIwIRgh+C8Y45TxFzmMcc4pZZyDwxj/DeCcM845AOeccc4YvwgYvwCA/wbkdOroDADMnNMbneccgL8IXooD5xzQi+A3EEIAgBAghDB6EWD0GxghjBFGiGAsEoJFJBKiSIKmSLoi6bKkKaKuSLoiuVTZqyluXfFqskdTdEUSRSIJRBIEUSAEI3jzCcqujzXe4nD2n9NnTeYAQLSQ+urgMwTh20paRUzgjeGcM84p4xy4RAhCCC4H55zatLa6FmFkm7YoiYDgxiPA9ba8lEkt56obIrA6nZ2ePzA4ShnfUBG+c0OTSAi8AuP85PTsF5863BeNAedVAd+nb+66o6leFgRYeTjnpk3zppXMFqbjqanY8nQsObeUXljOpPKGYdmG5TiUAYBAsCQIkkhkUfC7VI+meHTFq8seTXGrsqZImixpiqjJoipLskhkQZBEIgnkRRgBehEA+g0AQPByHDjnAMA5B86BAwcOHDjnQBmjjDv0RcyhzGHMoYxS5jDmUOZQRimjjFHGs6b1SP+5/qW4LJB7Nje3+kOUvYhTxuH/xynjLyIEI0AIAcEYIUAICQSLhIgECwIWCBEJlkRBFgVFFGSJyKIoCphgTDAWCBYIJhgLBBOMXgRrXiGkuP+4cbfD6K9mey3mAMBsPvmVwWcERPaUNAsIw2uijM0k08u5guE4hu0YjmPajmHbhuMYtmPYjuk4DmUdlaV7m+skQuByMMpm+2eJSBhj84n5inUVCCG44QhwvY0PRYNhjzegwyqUMcyfnxlYzOR1WXpnR2uZ3wOvwDg/OT37xacP90ZjwHlVwP/ne3bubawVMIYVg3GeN+1UtjC5sDwytzQeTUzFlqPLmWzBLJi2QxlGSBYFRRL8Li3sc0X87iKvHvRoRR496NGDHk1XJZEQUcAiIaJACMYIwXUXTWceHj4HAG5Zvq9zfUd5Kay5riKq50+a9zqc7ZvrsxkFgJlc4v8ZfErA+OZII0EYXp3D2GOnzv387IDDGOOcMsY4p4xTzhjjjHOR4D2NtY2RIpEQuEyEEG/E2/t0ryAL6/euRxjBjUiA68qx6cRwtLoxIogEVhsOcHpy7sj5Scb5hvLiW5pqMELwcpzznrno//30s73zMeC8MuD7b3t27G2sFTCG641xnjeseCo3Orc0Or84Orc0Np9YSudyhuVQJhCsSqJLlRvKiirD/tKAJ+J3FwfcxX63S5VkSZRFQjCGlS2eyy/l8gAQ0LRijxvWrAAlqveTzXspY09FBxxGOcBkdulLA08RhHeE6wnC8CpkQWivKP3x6d5kwYBXkAi5raX+s3tvqgj4EFw+BLIu26YtKILiUuAGJcB1lU7ml2Lp3XdthFUoXTB+fro/kSu4FPntHS1Fbh1ejgOMLCb+6eCRc/MLwHmF3/ffdu+8taFOwBiuEw5gWk4yWxiPJgamFgamFs7PLiYy+bxhcwBFEjyqXFsSrC0JVIb95UXe8pAv6NE0WZJFghCC1WYulS7YDgCUet26JMKalaFc83+q5VaHs4PRQYczDjCeWfzSwH4B4e2hWoww/C6UsTKfp9jjThYMeDlZEO5c1/ipPV1lPg+8LtSh8+fnQ9Uh6tD4RLy0uRQhBDccAa6rmfG47lb9RW5YbTiHF8Zmjo1OA+cdVSU7G6oxQvByM8nUlw4dOTE1wzgv9Xr+dPdNtzbWCQTDNcc5z5v2fCLdOx7tGZsfmI4tLGcyeZNxpkqi361trC2tLy2qLyuqLQmGfS6XKkmigGDVm0tlCrYNAKVejyqIsGbFqNADn2m51eH02YXzlDMOfCQd/6eB/X+O37I1WIMRgpco2PZUIvXsyMQzQ6MTiWV4OUUU7m5r/uTu7cUeN7xezGGyJpc2ltqGnUvmOOOIILgob9k2pR5VQbC6CXD9MMbHBucr68KyIsJqkywUfn6mP1UouFX57e2tAV2Fl4tnc//83PGDI+OUsaCu/fGObbc31YsEwzXEGM8UzJnF1Lnx+e7RuYHJhXgqa9qOKBCPpqyvKW6tjKyvLm6sCBV5dF2RBILhBmJTNpdOO4wRjEs9blEgsGbFQABVrqLPttxOGTsSH6WcceBDqYV/6t//F+ve0h6owghRxpfz+bMz0YPDYycmZubTGcuh8HKqKN67qfXjN3eG3Tq8AaIilreWI4TAC56wByEEF+Us6ztHz0wmlj+8Y0tDKIgQglVLgOsnlzGiM8vtXfWw2nCAk+MzJydmgcOWmvKuukqEELxE1rT+/cTpJ/qHbEo9ivyHnZvfvr5ZIgSuCc55zrAmF5ZPDs+cHJ4emVtazuZth6qSWBLwtFZF2mpKWirDpUGPW1MkgcANynDsuVQGABRBKPV6EKxZWRBArbvos623O33s+OIY45wD70/N/2P//s823+5m+pHRqcPnxwei8bRhcs4RQn5NXV8aAYCjY1MOY5ok3t/R9ke7tgZ1Dd4whBBcAGqQxgAAIABJREFUgBCCixjnTw+Ofv/EmVTBnEtmPrWna3NlKcEYVicBrp/4fBJjVFTshdUmXTCeODuULhgeVblnU4tPU+ElLEp/0TvwWHdvwXZUUXxfx8b3drSpoghXGQcomHY0kT4zMnt8cKp3IrqUzlPKXKpUHQm0VRdvqi9bVx2J+NyKJCIEN7yC7cynMwCgikKp1w1rVh4EqMET/tPW2/++79cnlyYY/43e5Oz/fvIXbFaNRguWQwFAEkip17O9pmJ3Y+2GsuKpRHJsMZEqGO/dsuHDO7b4NRWuJlUUfaqynDdOTs3+9yee+cTN2/c218qCAKuQANfP2NB8pDyg6jKsKhyge2r+hfEZ4LCpqnRrTTlC8P9hnD8/NvnNY6eSBUPA+M6Whoe2tbtlGa4mh7J4Kts9Mne0f7JnfC6WzJo21WSxvrRoc2P55oayxrKQ360pkgBvJjnTWs4XAECTpJCuw5oVCQFq8hR/tO6WeDY7bsQBgHE+ay9xVWCy6pP05kjolsaam2qrqgI+RRQAQBGF25rrdVn60PZ2r6rA1YQR2tNU65Klrxw8enZmfiS29MV9h+LZ3L2bWt2KDKuNANeJadizE4vtXfUYI1hVsob5+NnB5bzhUuS7Njb5NQUu4gD90dhXnz02m0xhhDqryj9207agrsHVwTnkDGs8uvR838SR/onx+UTetGVRKA542utKO5sr22pKiry6KBB4U0rk84bjAEBAU1VRgDUrj+k486nMqanZZ0cmFxY4DxKkU7gAuRxXNf1wbfs7m9qCuoYRgos0SfzIzi2aKOqyBFefgHFnTYVfU7968OjhkYloOvvVg0cXMtmHtneE3DqsKgJcJ6lELpMqlFUXwWpzbiZ6bHSac95WXry9tgIhBBfFMtn/8fyJvmgMAOpDwU/u6qoO+OAqcCiLLmdOn5850j95dnRuKZ0DgCKvvnN9TWdz5ab6smK/W5EEeHNbyhUshwJAQNckQYA1KwZlbClX6JtfeG5k4sTEzMxyumDbAEBMTamyLMniwAGBpRin7PN7eG0R0uDlQi4driGMUFNx6PNv3R16/uQvegbShvmDE93xTO6Pb+6sDvoQQrBKCHCdTI3G/EGXx6fBqpK37F/1DCeyeV2W7tzQGHBpcFHesh8+dfbw6ATjPOx2fWJH56ayYoQQXFGGZY9HE4d7xg6fG5tYWDYsR5PFlsrIjnXVN62rrikOaLKEEKx50VI+b1EHAIo0VRIIrLneGOepgjEaXzo2Pn10bHokvpQxTMY5AtAkqTro66ypKC/X/iN+cigV5cApZ8fiY1/q3/9nrXfUuEMIricEUObzfHpPV9itf/9491Iu/0Tv0GI296k9XRvKSghGsBoIcD0wyqZGY+U1IVESYFUZji4eGZlknLeUhnY0VGOE4ALK2NPDo4929xqOo0nig5s37G2oJRjDFcI5T+fNvsnoge7R44OT0UQGAMI+18a60l3razfVlxZ5dIFgWHMR53wpl7coQwBBXZMIgTXXCec8a1qTieSJiZmjY1OD0XgiX6CMAYBESMitbyovubmhuqOyLOJxCRjXhvx/3/fr8+kYB045ey42QjD5s9bbK/UgguvMr6kf2t4Rdru+8eyJ6eXksfHp5XzhT3Z33VxfLQkEVjwBrod8zozNJTfvaIBVxXLoU/0jsXROFoU71jWE3TpcwAH6orF/PXZyKZcnGN/aUHf/pjZFFOBKYIzHU9njg1MHukd6xqOpbEEShcby0M1ttTvX11RF/JoiIVjzX9mMJfIFzrlIcEDTMEKw5trinOcsey6ZPjk5e2x8unduIZ7N2ZQCAMG4yKU1RUI76qo6ayqqAj5dlhD81raimj9tvf3v+/aNZWIcgHJ2eGFYQPizLbdX6H643jRJfPuG5iJd++qho31zscFo/P988uDijq33bGjWZQlWNgGuh6WFNAAEIx5YVaaWkocGxyljDZHgzsZqjBFcsJTL/9uxU8OxRQSwrjj8ka4tRboGbxhlbD6Rea53fP+p4aHpeMGy3aq8vaVqz6a6zpaqYr9bIBjWvAqHsrRhAoCIiVeVYc21wjnkLWsmmTo9NffC5Oy52WgskzMdBwAwQl5VqS0KdNZU3FRbWR8O+lQFIwQvRxDuCtV9tuW2f+zfN5Fd5AAOoweigwLCn2m5rVTzwfUmErKroTro0r5y4OiRscnZZPrLB44sZLIf6NwU1DVYwQS4HibOL4RLfZouw+pBGTs0ND6dSAoE72mpK/N74QKL0p/19B8aHWech136R7u2NIWL4I2xKZ2Jpw71jD59ZmR0btF2aJHXdWt7/S0b6jbVl/pcKkYI1rwmh7GsaQKAQLBLlmHNVcY5z5rWXCrTPT13YmKmZzYay+RMxwEAhJBbkSv83i1VZV01la0l4aCuCQTDqyMI74w0UM7+sX/fdC7BAWxGn5rvJxh/uvnWYtUL1xtGaF1J5H+9c/e/PHviV33Dy/nCd46djmVyH9u1tcLvQwhWJgGuOdumsxOLDevLMMGwesTSuaf7RyyHVgS8e1tqRYIBgHN+anr2h6d78pYtC8K7N62/ua4GIwSvl+XQiWjiQPfIgbOjE9EE47w44Nm5rvr2zY1NFSFNlmDNpXEYy1oWAAgYuyQJ1lwdlPGMYUwmkt3T86emZvuj8cVszrAdAEAIdFkq83k2V5Ztr6lYXxopcumyQODSCAjfEml0OPtS//6Z/DIAWIz+erZPQOSTzXvCigeuN4SgKuD7s9t2htyuH548m8wbv+gZWMrl/mR317qSMEYIVh4BrrlsurC8mKmoDcPqwTk/Njo1HF3ECO1oqK4LB+GCaCb7b8dOzaTSCKFtVeUPbGpTRQFeF9uhEwvLvz45+MyZkZnFFAIoK/LesrHu9o7G2pKgIgmw5nI4lGZNCwAEjF2yBGuuKJvSZMEYiydOT8+dnpobji0u5woWpQCAEOiyVOb1tFeUbK0u31BWHPG4ZEGAyydgsre42WH0ywNPzxeSAGAx54nZHgHhTzTvKZJdsAIEde2jO7aE3fq/PX9yLpk+fH5iKVf41O6urtpKkWBYYQS45mJzSUWTvH4NVo90wXxmYDRv2UGXdvu6ekUUAMB0nB939x2fnOGcV/i8H9m+ucTjgstnUzq1kNx/evip08NTsSRGqLYkuGdT/Z6NddWRgCQSWHP5bMZypgUAAiEuWYI1bxjnPG/Z8WxuMBo/Oxs9OzM/uZRMFQyHMQDACHkUuczvbS8v2VxZ1lYWCbtdiijAGyNicntpq8PZVwafXiikAcCkzi9nzgoYf7xxd0DWYQXQZendHetDLv1rh44NLyz2zkW/8KsDH9u17c51jaokwkoiwDU3NRILl/oVTYLVo38u1j01DwDtlaWtZWEA4ACnZ+Z+2tNnOo4miu/t2LC5ogwhBJfDoWx2MfXU6fO/Pjk0GVsGgJriwFu2Nu/dVF9e5BUIhjWvl+k4FqUAIAtEEgRY83o5lKUMY2Y51TMb7Z6ZH5iPxzLZnGVzzgGAYOzX1MqAr6OidHNVaUtxuMilyYIAV46EhbeWrXcY+9rQM3EjAwAGtf9jqlvA5KMNN/slDVYAiZC9TXVFLu0rB46emJiZTCT/4annYpnse7ds9GkKrBgCXFuW6URnEm1baxBCsEqYtnNgYGw5V9AkcW9rnUeRASCezX33RPdcOoMQ6qqpeGdbi0QIXDLG+OxS6ukz5/edHB6bX+KcV0UCt29uuLW9sTLsEwiGNW+M6VDGOQDIRCAIwZrLQRnPWVY8kxteiPfOx3rnFsYXl5OFguVQuEASSEBTG8JF7RUlG8tL6sPBgKaKhMDVIWPhrvI2yunXhw4umlkAKFDrJ5OnBEQ+XL/TK6lwUdYxz6cXWrwlChHh2iIYbSov+d/etuefDx1/anBkKZf/1+dPxjK5D+/YUurzIFgRBLi2sulCajlXVhWE1WMqkXx+ZJJxXhcObq0pRwjZlP6yd/DIxBTnvMzr+eDWjiJdh0vDOSxn84d6xn5+pHdwOs4Yqwj5butouH1zY1XELxICa64Ei1LGOQBIAsEIwZrfh3Get+xErjAaX+qbj/XNL4zGE4lcPmfZnHMAwAi5FTns0ltKwpvKSzaUF1f6vW5FIRjB1acQ8e0Vm2zO/mX4UMLMAUDesR6deEHE+EN1OzyiAgAZ23h4/PjzsZEvtN9boQfgmkMI1RYF/vKOm8Nu/cene9OG+ePTvfFs7k9u2d4YKcIIwfUmwLW1MLusuxS3T4NVgjL+3PnJ2eWUQPAtzTURjwsA+qOxR7vPFWxbFoR3bVzXUV6CEFwKw3JOn5957HDPyeFpw7JLg95b2+vfsqWptiQoCgTWXDmWQxnnACARghGCNb8LZTxnWcl8YTKRHFqI983FhmOL8UwuZ1mUcbhAEohXVSr9vk0VJZvKS5oiRUGXpokiQgiuLYWI91a2O4x+8/yzSSsPADnHfGT8hIjIB2q3U+DfGz368PhxBGg0E6/QA3CdhN36H9/cGXa7vn30VCydfWZodCmb/+Serm3V5QLGcF0JcG1Nj8VDJT5ZEWGVWM7lDw2OWw4t93tubqoRCM4Y5g/PnJtKJBHA5orS+za0yoIAvw/jfG4x/fOjvf95bCCezPpc6m0dDffuWN9cEZZEAdZcaRZ1GOMAIAkEIwRrLrIozZlWIlcYW0wMRuODC/GxxcRyrpA1LYcxuEAg2K8pxR5Xc3FoXWlkfWmk3Of1qrJICFxXGpHeXbXZ4ezb559L2QUAyNjG98aO2Zwa1P7p5OmsYxKE+1NzuyINBGG4TtyK/L6tG8Ju/Z8PHR9dTJyZmf/bJw584pbO25rrFVGA60eAa8i2nNh8cl1HFUIIVolzMwtD0ThCsKWmvDYUYJw/Ozb5zPAY5Tyoaw9u3ljiccPvY9rOsYHJ7z11und8HiG0rbnyPbds3NxY4VIlWHN12JQxzgFAIgQjBG9iDmN5y04b5lwyPb6YGIknRuNLU8upVMHImRbjHC4gGHtVJaCrDeGiDWXF60rC1UG/T1UUSUSwguiC/J7qrQ6j3xk9krENAEjbhe+MHuGcW4wCAOWsLzmXc0yPqML1IwvCW1obArr21YNHz0zPjy0m/m7fs7FM7t0d6z2KDBc4jGGEMEJwrQhwDeUyRiqRK60Mwiph2M7h4fF0wXTJ8i1NNZokzqbSj5w+mywUCMZ3NNV31VQihODVcQ6LqezPnu/96XPnFtO5koDn7V3r7tneGvG7EEKw5qphnHHgAIDRb8CbiUVpwbKzphVNZyaXkmOLibHF5cnE8nK+kDNty3E4/JZIiFeWwm69PhxsDBc1RUK1RX6/ruqShBGClcolyO+v6XQY/f7YsaxjAoBJHXiJsUw8ZmQ8ogrXFcG4s7o88La9Xzt07MDwWCyT/frh47FM9g+6Noc9Ltuh+wbOh92urdXlCK4RAa6hpVhakgW3V4NVYjqROjE2zTmvCwc3VpbalP6id7B7NsoBaoP+B9rbXJIEr44xPjgd+7cnTxztn2AculqrP3T75g21pZJAYM1Vxjn8FkJw4+IANqWm7RRsO5k3ZpPpyURyZjk1vZyaSaaSeSNvWYZDOedwAUJIlUSXLIXdroZwsCkSaowUVQd8XlVRJREjBKuEW1Q+UNeVsguPTZ5yGIWXS1i5oVS03h2G6w0h1BAp+txbbily6T8/258xzEde6Illch/ftW0ykfzSM0eaI6H6UDCgq3BNCHANTY/FQ8VeRZNgNWCcHxudmlvOCATvbKwqcmuDC/GfnxswHUcVxXdtXNcULoJXZ9rOs73j337yxPBM3OfS3t617t03txX73QghWHP1cfgtBDcIxrlFqeVQ03Hylh3P5KLp7EI6M5fKLKQz8+nsUjaft6y8bTuUwUUIQBYFXZL8mlpd5K8rCtSFAjXBQMSjuxVZEUUEq1XBsTK2yTmHVyg4dn9q7o7SdSImcL0hgBKv+9N7uoo9ru8cO72Yze/rPz+VSGZNa3Y5lSoYh86Pv2NjC0YIrj4BrhXq0IXZ5eqGYowRrAapvPHs0ITpOCU+986GKsuhP+3pn1xOIoD28pK3tTQJGMOrSOWMnz1/7ocHuhfTufrSoj9869Zd62tVWYQ11wyH/wnB6kAZp5xRxhzKHMZsyizHSRnmcq6QyOeXc4VEvpDIFxK5fDyTS+QLBcs2bMd0HIcxeAmCsUuWNEkM6Fq5z1sZ8NYU+WuDgRKv263ImiQSjGH1m8snvzZ0YN9cH+UMXoED70/OZ2wjIOuwMnhV5QOdm4pc+jeePTGZSPbOLcAFGcP88enerVVl5X4vXH0CXCv5rJmIZ3bcsR5WiaFofGA+BgCbKktrQoHTM3P7h0YoYz5VuX/T+ohbh9+FA8SWs9/df/KXx/osm+5YV/2ROztbq4oJRvAmwzl3GLMpcyh1GHcYo4xZDjUcx3Icy6EWpQ5jlDHOgXLGOIcr5+xc1KYMAGKZ3IGhMVUSYGXgHBzGOOcOY5ZDLUothxq2k7esgu3kLStrWhnDzJhWxjAN27YcalFqUepQBq8gEuySJUUUXLJc4nWX+70Vfm+F31vh9xa5dF0SVUkUMIYbCAeYzS9/dfCZ/XP9FnPgVUzlErP5ZEDWYcVQRfGetmYB4y88eSCZN+Ci3rmFX/UNP9S1WSQYXo5Sms/nc7lcoVDI5XKO4yCEJEnSdV1VVZfLpSgKQggumQDXyvJSFiHkC+iwGtiUHhmZSuYLmiTubKhyGHu0uzeWzWGEdtVW76ytQgjBK3DOx6PL//L40UM9YwLB79yx/oO3bykJeBCCGxUHsCk1bcd0qOE4qYKRyOWX84Vk3kgVjJRhpAtmxjBzlpWz7LxpmQ6lnDHGGeeMXwDAXwQAHK4gG5jBbAAYiMb++xPPIECwMnAADhw4MOCMccY545xxxjm8BoKxKv6/7MF3lN7nXSD671N/5e11umY0RcWS1axiSa5xYseOY6WTchcC4cDCAksuC0vYs38kB9gD53KB7LLnQLiwh7M3DjaJ48SkOHGc2LFly5JVrN5mRtPnnXfe/v7K0648i1n5ukSyZ6SR/X4+jFPCCXE4y0UjbfFoezzaFo+2x2Nt8Wg24kYs7nBmEYoQvINpo18qjZ+rzXJMhFYGDLyeimierEzdmOqC5cQT4vj0rBdKuEQg5beOnLh1sG9New4WBEEwPT199uzZ0dFRz/MAgBDCOWeMGWPCBcYYAEilUgMDAytXrsxkMoQQ+FkoXC3jw4VMPuZELLgezNWaz58bU9p0pxObezufHbmwd/iCMaY9Hvv45vVx24bXMMacuDD7V9965oVTYzHX/rnbN37ijo3JiAPvIFJrX0hPiJofTFfr09VaodaYrTUKtfpsvVFqeJ4QoVShUkIpqbSBa8ZgMAQukkrXVQjLEgJACBGMKKYEI4IxxZhiTAl2GIvZVsp10q6Tijhp10lFnLTrpiNOynVczmxKLUYpxvAugxG+o331umTXicrU4fkLh0vjY435qvCV0XCJQMljlckPKmETBsuD0vrxE2cfOXQ8kBJebXiu9Mjh47+d3iUD/+jRo0eOHBFC9PT0bN++PZfLRSIR27YppbDAGCOE8DyvVqtNTEycO3fuueeey2QyW7du7e/v55zDG6NwVWitp8dL7d1pQjBcDw6PTY3MlTBC21Z2U4q/cfh41fcJxnevGdzY2YHg/09rc+jc5H979KcvDU+1pWKfu3fHPVtXuxaD65kxxpeyEYiy502Uq+Ol6ni5MlmuTlVqxUazGQpfyEBKbQy8BsHYYpRhQglmhFCMbUZdziKcW4xalHBCLEopwQiAYIwRgkU1Vas9NTIaSNmeiN3W12tRCssAQohiDAgIQpRgTggjxKLUZtRhzOHM5Sxq8Zhl2YwyghkhnBJOCMEYWhYgAIfwFZH0ikj6zvY15bB5vlY4XBo7Uho/U52ZDxuBkrDgZGWqEnq2w2C5QP3Z9Me3rN83Mj48V6oFgTEGFkitHz9+plOHtXOn4vH4rbfe2tfX57ouvB6EEF+QSCS6u7u3bdtWLpdPnjz5ox/96Lnnnrv99tt7e3sxxvB6KFwVfjOcm6lu2jkA1wMvFM+cGa0HQdyxbx5YsXdk7MXxSQPQk0zsWb/WYRReTWmz//TYXz7y9OnxQk8u+esf3HXHxgFGCVxvjDG+lI0gnKs3R+fLI8XScLE0WizPVOuNMPSECKWCV6MYO4xZjLicp10nHXHTESftOinXiTt2wrHith23rYjFOSEUY4IxwQgjhBHCGGGEAAABQggW1/Oj4/snJwMpe1KJ37hzZ9p1YHlACAEAAoQRIISg5W3gmOTtWN6Obcv21WUw2Sy/VBo/XBo7Vp6c8arTXnW0UWxz4gAgpRRC2LaNEIJrhGC0uadjfWdbsdE4Njn703Mj+0cnJspVLxQGYLpa/8aRE//53js3rl3DGIPLhjFOp9O7du3auHHjoUOHHn300fXr1+/evdtxHHgNCldFveaLUKSyMbgeTJZrL45OGAOD+Uwm7v4/Tx5ohCEj+N61q1bls/BqSpvnT45++ZGfnp2cG+zM/rs9u3eu7aUEw3VCKFUPwkK9MTxXGp4rjc6XRorlqUqtHgSekEpreAVGyOHMZSxi8Xws0hGPtcVjmaibi0bysUguFolanBPCKeGEEozgmrIZxQgBgDKaYswIgZZ3LoJwgjmJhLMm0X5/98ZCUDtZmX6pNO4pAQvm5uaef/75vr6+VatWOY4D1w4juD0ea4/Hdg/0TldrB8cmv7P/0NHpOQ/hGUQLxKKUwlsSiUR27do1ODj43e9+95FHHrn//vvj8Ti8GoWrYnayHI07bsSCZc8YODg6OV2uE4y3ruw+PDl9bGoWAPoz6fvXreaEwCWU1s+duPCXjzx9fqq4ujv37z9869ZVPRgjWMYMQCBkzQ8mK9XTs8Uzs3OnZ+bGSpWK53tCKG3gFQTjmGXFHKszEetOJbqTie5UvDuZyMciEYs7jFmUEoxgWWKEYIQAQCitjYGWdwcEyKW8l2Z6I5k721drY2BBJpNZu3bt4cOHz58/v2XLlq6uLkopXFM2o32ZlKmWz1RnP/KeXWVmPzc89vTZke193ZmIC28JQqitre0Tn/jE97///W984xsf+chH4vE4XILCVTF1YT6TT3CLwbLXDMPnzl3whMhG3d5s8mtHXvKE4IR8YN3qlZkUXEJrs//U+Jcfefr8VHFNT/63P3LblsEujBEsS76QZc8fKZZOzRTOzhbPzBYnKtWaHwRCGvgXlOC4Y8Ut3pmM92VSPalEbzrZl0lloq7LmUUpRgiuEzalGCEACKTUxkDLuw/HFF7BGBsaGmpvbz9x4sTTTz/d0dGxefPmVCqFEIIl05Dh6er0UKwtyix4PYVC4bHHHrvz1ltuuukmhND9N66ZqtQwQvAmpISxMSiXIZeDTAaKRWhvh2YTPA/a2mCB67r33nvvY4899r3vfe9DH/oQ5xxeQWHpSaHmZipD67oQguVvbL7y0vg0AAy0ZUYr5RMzswAwmMvcs3qIYgyv0MYcPDvxl998+txUcXV3/vMfvW3zYBdGCJaTUKqq74+VKiemCyenC8enZicr1ZofCqVgAQKwGI3ZVlcyPpTL9OfSfenUinQy5ToRi3FKEVyvLEoJRgDgC6m0hpZ3PYRQPB7funVrX1/foUOHfvSjH73nPe9J2zYcOQLz89DfD0NDQAgsnqpo/unR7w3E8h9esXl9stMiDC4hhHj88ceHhoa2bNmCMQaAmG3FbAve3NGj8MwzkMnAM8/ATTfBkSPwyU/C6dMwMgIf+xggBAts277nnnsefPDBgwcPbt++HSEECygsPa8ZlIv1jp40LHvGmAMjE7PVBiN4RTb59PCoJySn5L61q3pSCXiFMebYyPSXv/nT0+OFwc7sv//wLZsHujBCsAwobepBMFmpnZiaPTY1e2J6dqxUqXh+KBUswAhFLJ507L5MaiifGchlhvKZrmQ8ZlkWowjeITjBDBMAEFqFSkFLywJCSFtb25133lkoFBzbhmefheFhGBiAxx8HzqG/HxaPMTAfNo6PH3qhOPz+znX3d29aGctQRGDBqVOnqtXqnj17CCFwCSnl8PBwuVyGV4tGo/09Pdb+/bB+PezcCd/+Nhw+DBMTcOgQDA+D1vBqsVjsrrvu+ud//udVq1alUilYQGHp1coeAMSSLix79SDcd34skDIbizSVOFOYA4ChbOZ9qwcpxrDAGDg3VfyrR585Njrd15b6zQ/tvmlVD8YIrqlQqlLTO1coHp6YPjI+fXp2br7h+UIYeBlCKMJ5OuIM5jJr2nND+cxgLpOLRaKWxQiGdyKCsc0oAChtfCmhpeUSnPOuri4IQzh2DO66C1avhkIBzp2D/n5YbNqYyWb5H84/9/Ts2Qe6N97dua7dSUgh9u3bt2PHjmg0Cq9mjCmXy7Ozs/BqQgjV2QlSAudACDAGUkKzCePjMDsL6TS8Rl9fXz6fP3LkyO233w4LKCy9qbH5RDriRixY9sbmK8cmZgEgG3NPFAqekJySe9eu6kkl4BUTc5X//q1nD5yZ6EjHf+2Du25e20swgmtBG9MIwpla/cTU7OHx6SMT02OlSs0PpNYAgABsxhKO3ZtJ3tCRX9+RX92ey0UjUYsTjOGdDiNkMwoASmtfSGi5noVana5OJ5mbd2IcU1gsCAHn0GiAlOD7wBgsGanVmerMX5168iczp/es2DSoovVGY2hoCF6DMbZt2zZ4XcbAunVw6BDU6zA8DOvWwUX33gunTsHICLwGIWTTpk1PPfXUzTffbFkWAFBYYsbA9MR8ti1BGYHlzRhzcHSyWG9SggXSY5UqAKxMp+5aNUAxhgXFauNvv/v8M0dH0jHnV+67+bYb+wnGcHUpY2p+MFosHRybOnBh4tRMYa7e9IQwBi4iGKdcpyeVWN/Vtr6jbU17rj0ei9lpzuPhAAAgAElEQVQWIxjeTSjGLuMAoLRphAJarmfKqG9eOHhofuzmXP/u/ODqRHuSuRgheJsYgx074Kc/hZMnwffhhhvgZwmUPFAcKQsPLkMpaHoyhEv4SuwvjpysTvVKd8uKNLIZXBGEYNs2iESgUIC77oIVK6CzE6JRGBiAfB4Qgtfo6OgIw7BSqeTzeQCgsMREKIoz1c07B2HZqwfh/uHxQEqL06LveUIwQu5eM7QilYAFNS/4n0+8+PiB067NPnvPtru3rmKUwNWitC57/vBc6cCFiRcvTJ6aKRQbnlAKFtiMpl1nVVt2Q1fHhu72oVwm6ToWJfBuRTCOcAYAUutGGELL9YxjGmP26er0mdrMt8cPr4m3784P3Zzr73ZTLuXwdmzY4MViqlyO9vdDOg0/S136f3v26ePlSbgM2oCvBLxGXQTHTDDJ/cax7394xZa1iQ6LULhMtg1btsC/uuEGuCifh3weXk80GmWMVavVfD4PABSWWLMR1ipevisFy95EqXpsYhYAMEGV0AeAnmTifasHGCEAEAr17b3Hv/HTlxCCj9224YGd6yxGYekprecb3smZwosXJl8cmzxXmC97nlQaABBCMdvqSsZv7Gy7sat9fWdbVzIesy2MELzrUYwjnAOA1LoRhNByPSMI5+04wzTUcj5oPFs4t784+rWR+E2Z3tvyQzemerJWhGICbwGlw0LMed5tmQxcBgPgKdGQIbxNCErC++bYoReKI5/s2/axvq0u4bAECCG2bTcaDVhAYYnVyg1CcSRqwfJmDBy+MFWoNxCCwCipNcH4zqGV/ek0AGhtfnps+H8+ccAP5AduXvupOzdHbA5LSWld9vyzs8V9I+PPj4ydK8xXPF8bAwAEo6Tr9KYTm3s6t6zoXNfRlom4NqPQcgmKccTiAKC0boQhtFzn2py4RWioJSwItRxrzI83Sk9MnVgZze7MDezODw7EcjFqI4TgSvi+X6/X4VpwKR+Ktw3G8hwRWDJaa0IILKCwxKbHS8l0xHY5LG/NMDwwOhEICQgUMgYgH428b/Ugp8QYOH5h5m+/+/xsuX7z2t5fvGdbOubC0lBaVzz/3Nz888NjL4yMny3Mlz1faQ0AlOC04/ZnU1t6Om/q7VqVz6YjDiMEWl4PwTjCGQBIrRuhgJbrjTQ6UDLQwpeiHDbHG/PwGgZMTfhHSuPHy5OPXDi4Ptn53s4b3tO+JkItWBoEoQ4nURcBXAap1bRXkUbDaxANq9zcZ9buvjW/KmVFELw+c5EyiCCjDboII7hCYRh6nheLxWABhSU2N11J52KUEljeZqv1Y+MzAGAwaGQQQjv7elbnswAwNV/9yneeOz1eGOzM/sp9N3dnE7DYjDH1IBwulp47P7Z3+MKZ2blS01daAwDBOBNxV7Vld67suam3qy+TSjg2xRha3hTBKMo5RkgbUw8CbQxGCFqWHwMmVCrQIlCyIYO5oF7wawW/NuvXCn6tENTm/HpdBp4SDRnAG5BGz/rVI2WzMd2DAMGVIIQwxuDyJJj7n278QKgVXIYZr/ofDjw041XhEhSTldHsRp1KTzTve8+NjFJ4YzKQ48fH093pykwlmommO9KA4IpUKhWlVDwehwUUlpII5XyhdsOWXlj2jk7MzFTrAGAwAIKkbd+9ZijCeaXh/8MP9j934kI2Hvnc+7ev62tHCMHi8YSYKFcPjE48e/7CkYnpuXpTKAUABONMxB3MZ7b3dm/r6x7MpROOQzCClssWsy2KcahULQil0pwSaLl2tDFCq0DLUAlPifmgMRfU58NGwa8V/HrBr80F9XLY8JQIlAyUkEbDZcMIDcbyvzx06x3taxzC4LIJX3R1duWyudALmc0QQvCmMEIZKwqXxxhDEIZXYIQ6neQ9Xevv79oQD9HXjj5Ymp/P5/PwxggjWuvjPz7OHZ7pyQCCK3X+/PlkMhmPx2EBhaXkN8NqudnWmYLlLZDy4OikJwQgMAQu2tjVvrmrI5TqseeOf2ffSYuRT79ny20b+glGsBiEUrO1xqGxqb3DFw6MTkxVa76QAIARSrnOUD6zva97W2/3YD6TdGyCMbRcuZhtUYJDpap+ILTiQKBliRkAqVWoldAyULKhglLQnA8bRb8+F9SLQX0uqM/59XLY9JQItQy1DJUyYOBtsDDdlR/85aFb1yU7CcJwJWbOz3hVz4paFyYu9G/tRwjBEkCAUpZ7W37VR3q33JDotAjVWnd1dR06dOh973sfQgjeACY43ZU+9qNjq3aucmIOXCHP8w4dOrRr1y5CCCygsJQadd8YE407sLzN170jY9PGgMFgMLic3bNmKG7bz50YffDJg4GQe3at27NrncUovD3GmKofnJ4tPn12ZO+50eFiqRGEBgAhiFq8J53c0de9q7/3ho5c0nUoxtDyNsQti2ECIGpBIJWGlkViwAitQq2ElqFWTRmWw+Z80JgPGvNhoxQ2S0FjPmwUg0ZN+KGWoZahkkJrAwauEEbYwsQizCEs1Go+qBt4lSR3P9Sz6TP9N7c5CQRXLNOTOfDYARnIzfduxhjDYkMAFJM18bYP927ZlumLUrsm/bqEi4Y2r//Wt7+18sY16XQaXhGhlk0YvEJJVRgptA22NSoNr+ZFkhG4bMaYQ4cOUUqHhobgFRSW0uxkOZZwbZfD8nZutjhZrgKAIQAIVuezO/t6xgrlv//+C9Ol2tah7n/z3psSERveBl/IiXJ138jY02dHXpqYmW96SmsAsBntSMS29HTu7F+xqbsjH4tySqBlMcRsixIMADU/EFpDy2VTRkuthVFCK6Glr2RVeJXQK4fNctgshc2K8OaDRjlslsNmTfihlqFWoZKhUcYYuHIIEMPEItTC1KE8bUXyVixnx3J2LGfHcnYsb8d+Mn3qv5/6caglLMAI9UWznx3YfXfnDRFqwVvCOAMDWmk7asNiIxhvTPUoUGdr04+M7f/m2H4AIAhjhAFAaz3T7R186Z+i0RgsSDDnV1fduS7RBa/w675W+obbbygMF+rFuptwEUJwecbHx59//vk9e/bYtg2voLCUZibLqVyMcwrLmNLmyPh0zQ8BgcHACblraMAm9O+f2Hfk/GRnOv7Ze7Z1ZxPwlmhjSk3vyPj0T84M7xsZn6xUfSEBgGCcj0U3drffMtC7tberMxl3GIOWRRW3LIYxAFT9QCoFLQsMGKm1NEpoJbUWWnlKNGRQE15V+FXh1URQDptV4VeFVw6bldCrSV9oFWoptBJaSa0MvEUIgGJiYcoJtQlLcjdnxbJ2NGtF83Ysa8eyVjRtRRzCLEwtwigmCP7FeLNkExpqCQAMk22Zlb+y6raN6R6KMLwlxpips1PRVJTkyeSpyb5NfQgjWDwZK/of199bFs3/fOjrxyoT8Fo2zIoSlEoAgBG6v2vTCjcDl3BizsC2AcaZG3cNGIQQXJ6ZmZlHH310x44dvb29cAkKS0YpXSrUVgzmAcFyVveDI2PTSmuDATB0xGM7e3sef+H04/tP25x96j2bbxrqRgjBFQqkHC9Vnj1/4cenh49NzlT8wBiDAKIWX5lN7+5fcetQ31A+G7M4QghalkDE4hajANAUoSckvHMZMMoYpbU0WhmtjFZaS6NDLRsyaMigIcOGDOoiaMigIYOa8GvSrwm/Jvyq8BoiFEYJraRWwiiptTIa3h6CMMeUE8IxdQhPcTdtRdJWJGNFM1Yka0XTViRrRSPUsgjlmHJMMULwptrsuE1YVfgxZt/fveHn+3d1RZIIELxVRhtM8MD2AUJIaaqktSaYwOKhCKetSII7e3q2DDcKTRnCG+tyUx9dsTXGbLgEJhgTDACEEbg8xpixsbFvfetb69at27ZtG8YYLkFhyfjNsFysb79jDSxvk5Xa2ZkiXIQBMNre210uew8+edALxZ6d6z6wYy2jBC6bNqbc9I5Nzf749Pm958cmytVASgDghLQnYjet6LxloG/zis5c1GWEwLuMATAXgYEF5iL4FwaMMbC4DDJRiwNAKFWx2ehMxmDZMGAM/AtzEZiLNIC5CIwGYwxoozUYbYwyWmgVahkqGWjpK+Er6SsRKOEpESjhKdFUoSfDpgybKmzK0JNhU4WeElIrabTUWhqltJZGK6NhkVCEGSYMU46JRViCO2keSVuRtBXJ8EjaiqStSJpHEtyxCeOYckwYphgheEtS3E1w1yLs3/Tv/ED3hjiz4e3BBHet6YIFbtKFpUEQvrN97U9mTj5bOGPg9RGDOme0VfR1QmOM4a0KguDgwYN79+7duXPn1q1bKaXwahSWjN8Mw1AmUi4sb8fGZ+YbTQAwGBKOtT6X/6efHJ4oVjb2d37mri1x14bLEyo1Wa7uPX/hhyfPHZ+arXi+NgYhFLetVW3ZO1f17x7oXZFOupzB9cYAaKOV0cpoZYwyWmmtjVbGSKNCrUIlAy1DLQMlQy1DLQMlhVbSaKmVNFpqJY2WWkmjpVYGXqaNUUYDgAFQRmtjYFEFoZoTVQCoieDvTj3bNu/AsqGM1kbDAmW0NFpqLY1SWkujpVFS61AroWWoZaiVNkYbo43WYJTR2hhltDJaG6OM1sbA0iAIM0w4JgxTjkmEWknuJrmb5E6Su0nuJrmb5G6SuynuOIRzTDkhHFOCMCw2l/L3dqzdlOrZll3JMIHrR5zaWzMr9xeHAy3h9dyY7nkgPfj9f/7u6ZUrb7755mw2izGGKyGEGB0dffrpp4UQe/bs6evrwxjDa1BYMuX5hu1w2+GwPBhjgiDwPC8MQ6WUMQYAFKADwxd8IQGBwbAynRoemdt3aiwTc/+Pu7asaEvBz2IAGkF4aqbw5KnzT58dGZ0v+0ICACOkKx7d1td9x9DKTT2dmYhDMIblxAAoo5XWwiiplTJaaOUr0ZBhUwYNGTZl2FBBU4ZNGTZl6KnQU8JXwlOhJ4WvhKfCQElptDZaG6PBaKO1McoYbYwG8zIw2hgD5mVwdWkkhAvAAil/MnkGN0NouQQCoJhQhCkmDBOGiUNYjNkx5sSZHWN2nDkJ5iS5m+ROkrtJ7rqEM0w4JgxThglGCK6iKLU/O7DbIQwhBNcJodVIY+57k0e+P3lUGAWvJ86cT/Ruv6fjxvmh9Xv37n3wwQe7u7s3bNjQ2dnpui5CCN6YUqparQ4PDx8+fLjRaGxe4LouvAEKS2Z2qpxIuZbN4NoxxtTr9ampqePHj588eXJ4eHh6erpYLDabTSklIcSKJ4MNt5hIEijGGGhD/uTUOaPNB3eu23lDL0YI3pg2Zq7e3D86/qNT5/ePjhfqTaU1AojZ1pq23G1DfbsHevsyKZczuBa0MdIooZXQSmgltGrIoCK8qvCroVcVXl0GTRk2ZFAVfl34DRnWZdCUgTRaaq2MkkYro5XWymgD1yEEiBi4yCCjELw7IACCMMGYIEwRJohQjCnCNmFRZkWoFaV2jNlxZkepFWN2lNlxZseZE2d2hFqcUIoww4RiwhDBCMGygRFyKYfrhNBqrFn84dTxx6eOjjTmpFbwejBCt+RX3ZJfRTDO5XL333//3NzcSy+99MQTT0gps9lsV1dXe3t7JBJhjBFCjDFKqTAMy+Xy1NTUxMREtVqNx+MbNmxYtWpVLBaDN0VhycwXaolMFBMM10IYhhcuXPjxj3/85JNPHjhwYGZmpl6vSykxxpxzSilCyBijEaLjU7y9m6YzJB7d10CR7GCKyYGYViIEzuD1CKXGS9Wnz448cfLs8elC3Q8MAMG4LR7d2tt11+qBrb1dmUiEYARLSRkdaiW0DLUKlazLoCK8auhVhVcVfiX0qsKrCq8i/Gro1YTvKyGMEloJraRWymgD72jIANFwkQFQCJY9BIAuAnQRBoQRwghhQBghjBACTBDCCGGEGSYWpjZhNmE2YTZhDmUu4S7lLuUO4S7lLuERyiPUjlAeoZZFKMWEIkwRppgwTAjC0LIEhFajjbknpo8/MX18uF4QWsEb63SSH1+xLc4cWIAxzufzd9111+7du4vF4oULFyYnJ0+cOCGlhAUIIWMMADiOk8/nN2/e3NXVlUwmKaVwGSgsDSlUZb6+ZkMPXHVSytOnTz/88MPf/OY3T58+7XleJBLJ5XLbtm0bGBjo7u7OZDLRaJQxppRqNpulUmlqenrkwtiZk4dnZ4vV5MnRSuE3Hv/7u++++9Of/vTWrVsdx4FXNENxambuydPnnzo9PFwsBVICgM3oykzq1sGVt69aubotG7E4gsVhAKRWoZZCq1ArT4Zl0SwFzXLYLIXNUtgohc1S0CiFzUroeUpIo4RWQiuhlTIalgZGCCNMECIIE4QxQgRhDAgjhBEmCDFMLUwZJhRjigjFmCJCMWaIEIwxIIIxBgQACBDFGADB0jilKi/OzWljBty2LSuyGCG4phAAxRgBAgAEQDBBAAghijBFmGBCEaYYU0QoxgwRTijHlGPCMeWYcEItTC3CLEwJwgQhjDBBGCNEMSYIE4QJwtByjYRaXmgUn5g+/oOpY6ONOaEVXCJK7TWJjmmvMt6chwUc0/u6Nq5LdsFr2LbdtQAAlFJBEAghtNYIIYwx59yyLIQQXCEKS8P3wmq5metIwtU1Pz//0EMP/c3f/M2xY8cAoLe39/YFmzdvbm9vj0QilmUhhODVhBCNRmN+fv7o0aPPPPPsj370xIkTJ77yla9873vf+/SnP/25z32ur6+vFoRHJqa/f/zMs+dGZ2oNpTUCiNvWus62u9cO7hro7UzEGCHwlmhjQi0DLUMlmyqcDxrzQaMY1OfDZilolMNmKWyWwkZV+KGSoVahlkIrZTQsEoIwxZgiQhGmGBOEKSY2YS7hEWq5lLuUu4TblDmY2ZQ5hNuE2YQ5hNmEcUItTDmmnBCOKUUYI4QAYYQQIIwQAnQRBkAXAUIIABAswIBgyXxdHTt6+ilfyrWxzv9z7e02ZXBtIcCA4BXoIngZAvQyaLleNWV4rj7zo+kTP5k5OdacF1rBJRzC1ye7HujesiPb/4Opo//t1BOeCgFgbaLj/q5NHFN4U4QQ13VhMVBYGr4XSqGicQeuFmPM2bNn//RP//Thhx9uNBqrV6/+uZ/7uT179gwODrquC2+KMZZc0N/f//73v//f/ttf/cEPfvDVr371hRde+LM/+7MXXjz4oX/3Wyeb8sDoRKnpaWMIxm3x6Lbe7veuGdja25WOuBghuAzK6EDJUMtAybr0i0GjGDSKQb0Y1ItBfS5ozAf1ctj0lQy1DJQURhlj4O3BCDFEKCYME4YJxyRK7Ti3Y9SOMjtKrSizotSOMitKrSi1I8yKEO5SzjChiBCMKcIEYYIwwYgARgjBdSLjuowQX8p6IJDBFqHQ0rJ4DJiq8F4qjf9w6tjzxfOzflUZDZdwCF+b6Lyva8Ot+dU5K4YRem/H+qdmT++bOxdl9kdXbOt203AVUVga5WLDcbntMrgqjDFHjx79whe+8Pjjj0ej0V/6pV/61V/91fXr13PO4QpxzleuXPnLv/zL73//+7/61a/+9V//9U+e3Xuua4h39xkARnBvKnnb0Mq71w6ubstFLI7gdRgwoVKBloESnhKloDEb1Ap+bdqrFPzaXFAvBo2a8AMlQq1CLYVW8FYhQAxjhinDhGHCMXUpjzM7zpw4sxPcSfFIgjlx7sSZHWdOnNkWoRQThgjFmCJCEUYIwTtRwrYZwQBQ9XypNbS0LBJp9Kxf3V8cfnL6xKHShXLYNGDgEi7l6xJd7++8cXduVd6OY4RgQd6KfWTFTaer09syK2/Lr8YIwVVEYWnMTpYTqYhlMbgqzp8//wd/8Aff//73Ozs7f//3f/9Tn/pUMpmEtwFjvGLFis9//vMbN2784pe+dO70sVS2rSeV+MiOLXetGVyZTVmUwgJtTKBloISvxHzQKAS1gl8v+LWCXysEtYJfK4eer0SgZaCE0AreEowQQ4QRyjHhmMaZneJukkdSlpvibopHUtxNcjfO7BizOaEMEYoJw4QhQjGGd6u4bVFCAKAaBEIpaGl5ewyYugjO12efLZx9pnDmfH22KUO4BAKIUGtdsuv9nRt254ayVgwjBJdACO3MDn6oZ8vu3KoEd+HqorA0SnO1RCaKCYalV6vVvvzlLz/++OMdHR1/9Ed/9PGPf9yyLFgMlmXdc889iUTiP37pD1/67jfau9rv+Oj72tKReVEv1ZszfnXGrxb82oxXK/jVWb9WFZ6vZKBFqJUxBq4QAsQwsQjlmNqEJbmTtiIpHklxN8GdBHNTlpvmkSR3o8zimHJMGKYMYwQIWl5P1LI4IQBQD8JAKmhpeat8Jab9yovFkWcKZ46Wx4tBXRoNl0CAktzdlF7x3vZ127P9GR7FCMHriTHnFwdudQhHcLVRWAJSqMp8Y82mFbD0jDE//vGPv/a1r1mW9fnPf/5jH/uYZVmweDDGN99883/67d/69V//9RdfHP7iMw8lCj2zfq0m/EAJX0mhpYErgxFimFiYckwdylPcTVuRrBXL2dGsFc1Y0YwVTVmuSzgnlGPCMKUIQ8uVsyiJcg4AoVL1IICWlisktCoG9WOVib2FswdLoxPNkq8EvBpBOGfHdmQG3ttxw4ZUT5w5CBC8MQQQZw5cCxSWQOCLWtXLtsVh6dVqtQcffHBubu6BBx74zGc+Y9s2LDaM8Z133vnzP//z/9dX/upgZdwuCLg8CIBiYhFmYepSnrYieSuWs2MZO5rmkawVTVuRNI/YlHFMLMw4IQgQtCweSnDM5gAglaoFAbS0XB5ldDlsnqpOv1A8/0JxeLQxVxeBAQOvZhO2IpLZnRu6o23tUKzNpRyWNwpLIPCFCGU07sDSO3/+/N69e2Ox2Cc/+clcLgc/i9a62Wzatq21FkK4rosQgp/FsqyPfvSjD337m81ize5rg9fACFmYWoTZhMWYnbOiOTuWt2NZO5azY3krlrYiLuUWphZhFBMELVcDwyRu2wAgtK76AbS0vCkDpi6C8/XCC8Xz++bOn6nNVERTGwOvRhBOcnd9ouuW/Ood2f4OJ8kwgesBhSVQr3qMEctmsPROnDhRLBZ7enq2bduGEIKfpdlsfuc737nlllsqlcrp06c/8IEPUErhMvT19W1af+NP5soIkEWoTZhNaIK57U4ib8fanXibk2iz4zk7GqW2RahFmIUpRgharh1KcMyyAEAqXQsCaGl5PQbAk+F4c/7F+ZF9xeFj5fFi0JBGwashQBFq9UWz27P9O7MDq+LtceoghOD6QWEJFGeq0YRr2QyW3vT0tO/73d3diUQCLoPWenp6+ty5c5VKpVgs+r4/PDw8NDRk2za8Kdd1e7t6ao8/t6575S997FMrkvmcFY1zxyHMwowTggBByzLDMI7bFgAIpap+AC0tr+YrMe1XDpcuvDA3fLh0YdavBlrCa9iEdTjJzenendnB9cnurBVlmMB1iMISmJ+rxZMuZQSWnpTSGEMpRQjB5anVai+99FKj0YhEImEYnj17tre317ZteFMYY0qpLFYjRW9dvKMtlrYJswjjmCBA0LIsUYxjtoUAlNZVPzAGEIKWlkDLgl99qTy+vzh8qHRhsln2VAivwTDJ2/Ebk907sgObU73tTsImDK5nFBabMaZaamba4nBVpNNpxtjs7Kzv+3B5urq67rjjjnK5fOLEiVgsdv/991NK4WfxfX92rpC888bx3W3/4ejDcea0O4m8ncjbsZwd77ATOTsWZ45NmIUpxxQhBC3XGkIoblkEY6l1LQik1oxgaHm3EloVg/qJ6uTzc+cPzo+ON+ebMjRg4NUowkkeWRPv2JHt35pZuSKScSlHgOD6R2GxiUBWy81VN3bDVTE0NBSPxy9cuHDq1KnOzk74WRzHufXWW3O5XHIBIQRjDJehUCi8dOKYtbNNcDTjV2f86pnaDAAgQJxQhzCbsBR3c1Y8a8eyVjTNI1k7lrPiWSvqUG5hamFKMYGWqytmW5RgqXXVD6RWjGBoeZcJtZwPGqeqU/vnR14sjow152vCN2Dg1TBCceasjOS2Z/t3ZAf6o7k4czBC8A5CYbEFvmjU/XQuBlfF6tWrb7jhhqeffvrRRx/dsWOH67rwphhjAwMDsCCZTMLl0Vo/+eSTp4bPZj44CK9mwARKBEoAwLRXOQFTAIAAKCYWZhahUWplrFjOjuWsWNaO5axY1opmrGiU2hahDFMLU4oJgpYlEbcthokPsuYHQmmHQcu7hK9EMaifqEy+OD96qDQ63izVpa+NgVdDgKLMWhHJbE2v3J7tXxVrT1kRijC8E1FYbL4vjDZOhMNVkc1mP/KRj+zbt+/rX//6+973vnvvvRdjDIvt9OnTX/nKV5pBMJRK2dz1lQi11MbAGzAAQiuhVV1CMaiPNoqwgCBsEcoxtTB1qZWxIikezVrRnB3LWNEMj2asaII7FmYWoRxThgkCBC1vQ8zilGAAqAeh1Bpa3tG0MQ0ZTPuVY+WJI6Wxo5XxyWa5IQMDBl4NAXIp73ZTm9O9W9Mr1yW7s1aUYQLvaBQWW7XUsGxmWQyuCkLIhz/84e985zuPP/74H//xH7e3t2/ZsgUhBItncnLyT/7kT/bt29c/NPif1t6fHeyZ9auzfq0Y1Ka9yqxfnQ8bvhK+EqGW2hh4Y8ropgybEMKC4XoBFhCEGSYWppxQl/AUj2asSMaKpngkwZ0Uj6R4JMncOHcsTDmmDBOOKUYIWn4Wl3OKMQA0RKi0hpZ3HAPGV7ISNkcahaPliaPliTO16WJQ95WA1+MQ3uYkNqV6bs4OrE/25OyYhSm8O1BYbPOFWizhcIvB1dLZ2fl7v/d7IyMjzz///O/+7u/+4R/+4fbt2yml8LYZY0ZGRv74v/yXf3zooXg8/tu/+Vv3bNnNOQcAAyC18pXwlagKbzaozvrVgl+bC+pzfq0QVItBw1NhoESgpdAK3pQyWintKwECLhptFGEBAqCYMEw5JgzTCOFJ7qZ4JMndFI8kuG4r7mQAACAASURBVJNkbopHktxNctchnGFCMWGIMIwxwtACEOGMYAwAjVBIraHlHUEb46uwKvwJr3S6On2yMnWqOjXtV+rCl0bDayAAh/CcHbsh0XVzdmBjakWbE3cIh3cZCoutUmpE4w6hGK4WhNAtt9zypS996Qtf+MJTTz31a7/2a7/zO7/zwAMPJJNJeBt833/22Wf/7//6X/dNz0X6B3/jEx//zGc+wzmHBQiAYcIwiTE7Z8cGYnkAMABSq0CLQMmmDIthveDX5oJawa8VgtqcX5sLalXhBVqGWoZKSqPhTRkAoZXQqgkvKwBAA/4VQZhhwjFlmNiExZidYG6c2XHmxJkTZ06cOXHmxJkdZ06M2RamFBOGCUOEYkIQhncBmzJOMAAEQoZKQcv1SRntK+GpsBg0RhtzI/XCcH3ufL1Q8Kt1GYRawutBgCKUtzmJG5M9N6X71ie78nbcpRwBgnclCovKGFOveKlcDK4uSumePXssy/riF794+PDhz3/+8z/84Q9/4Rd+YevWrfF4HCEEV8LzvDNnTj300D/+v1/9x/loInPfh2Kuk9p1c4BJFADBG0IADBOGSZRCxoKeSBoWKKNDLQMlAy2qwi8G9WJQLwb1+bBeDOrFoFEM6lXhBUqEWgZaSq0M/GzKaKW0rwS8HoIwxZghQjFhmHBMY9SOMyfOnDh34syOUSdCrSizotSOUivK7Ai1OKYUYYIwxZggTBEhCGOE4LrFCHYYAwCpdTMU0LLsaWNCLQMtAyVqwi8E1UmvPNEsTzRLE83SrF+tS99ToTYG3gBBOM7sbje9IdWzMbVibbwzZ8dswuBdj8KikkLVq17/mg646hhj9913X3d391/8xV98+9vf/upXv/rEE0/cdttt9913344dOzo6OiKRCMYY3oAxxvO8YrF4+PDh5/b+gJtnJ0eGKx50vX+PisU9gL978cjpcvUXt2/e0NnOCIErQRB2CHcIB4A2OzEUa4MFyuhQy1DJQMuGDEthvRjUi0G9GDaKQX0+qM+HjUrY9JQItRRahVpKrQ0YuAzKaKV0ABLeAEaIIEwRoRhTRCjGDFGX8gjlLrFcyiPUcil3ieVS7lLuEO4QbhPmEGYTZhNuE8YxIQhjhDDCGBBGCCOMESKALsKAXgYIIwTXCME4wjkASK2bYQgt14IBMMZooxUYbbQyRhstjVZaC6M8GdZlUBXNctgsh81y2JwPG4WgVvCrFeH5SnhKhEoaMPDGECCHsjSPDsXa1iW71ie7+qP5JHc5ptDyCgqLKgxkveansjG4FgghmzZt+vM///O77777H/7hH/bt2/fQQw899thjPT09GzduXL9+/cDAQHd3dyaTcV0XY2yMCYJgfn5+ampqeHj4+PHjL7102Kbjn/6w+fB9bq2RuuN992U2ffbrJ8+9cGGiGYofnjp7enbuk5tvfODGtZmIi+DtIgg7hDuEw4KVkIUF2hihZahVqGWgZU34pbBRDpulsFEKm+WwUQqb5bBRCpt16YdaCq1CrYSW2hi4bNoYbZQABQreHAZEMCYIE4QxQgRhgjBBmCDMMLEw5YRamHJMLUI5phxTC1OGKcWYIkIxpohQjCkiFGGKCYKXEUQwQgCAEKIIw9Jo+KKqmgDgS/HjqVMTaBZaloA2RhkNCwwYZbTSWhotjZJaS6OFlqGWvpKBEoGWvhJNGTRk0FBBqKQ0WmgltBJaSqPh8iCEHMITzOmNZFbF29cmOlfH23NWPEItjBC0vAaFRRUGQgnlRi24RhBC6XT6U5/61F133fXUU0899thje/fuvXDhwsmTJx9++GHXdR3HsSyLv4wxqikRlGvmYum6xZnKzv7qb34usXGdRSnKpFBff4AS7Zv7+//p8NGvHz42XauPzJe+/PTegxNTv7B988bOdkYILAGMkEWYRRj8Lw78KwNGaBVqJbQMtWrKoBQ2y2GjHDYrwqsJvya8qvSroVcVXk36ngqlVkJrYZTUShkNV06D0VoJUPA2IEAIAQZ0ESxAgBCCBQjDRQiWgFZQb9oAtCnDrw4/z+cltCwBA8aAgf/FgAFjALQxBszLYHEgQJzQCOFJ7na76f5YfnW8fTDWlrNiUWpRTKDlTVFYVF4jxARbFoNrCmPc3t7+8Y9//L777hsdHT1w4MChQ4dOnjw5MjJSqVQ8z3PtxgfvQoN9pKvLOqZWP1G8YVpmboue/eLu5zszBv6FAbEX/Ec745/9lV3bNnV1/I99L75wYaIZih+cOntqdu6TW27cs35tOuIiuHoQII4pxxTAggUr4X/TxkijhFZCK2lUoGRN+lXhVUOvKryq8KrCqwi/Krya8GrSb8jAV0JqLY2SWkujpNFKawMGFpsBYwxoMGDgajIKacRhQSilUiG0XCcwwhamFqEO4Vkr1uUmu9xUl5vujWQ6nGSUWi61KMLQctkoLKpSse5GbW5RWAYQQtFodN2CT37yk/V6vVarzS9gaOymwb9x+Jw2aOR4erjQIwHPsB5tHwOowb8ynmn+I7ANNt9xa3/vYDb9T4ePff3wselafWS+9OWn9h6ZnPns9s3rO9ooxrAMYIQ4ohxTeAPaGGGU0EpqJY2SWvtK1KVfl0Fd+g0R1GXQkEFThU0ZNGXYkEFThU0ZNFXoKyG1VkZro5XRyhhltDJag9FGa2NgWUIIEDYAYAwYjaBlOSEIU4QJJhRhhgnHJELtJHdTPJK1ojk7lrNiOTuet2Nx5jqE2YQRhKHlraKwqEpztVjcYZzCMsM5Ty/o7e2Fi/ScLn8PwjmMzJbcTJL7c7470YidmM92R2pwKTUOjb8D0odIe2ci/iu7tm3sbP+75w8cGJtshuJ7J06fmi18esuGD6xbk3IdBMsdRshC1MIU3pQyWhmtjJZaK6Ol0cooqXWghSeFr4UnQ18LXwlPiVCJQMtQy0DJUMtQyUDLUEuhlTRKai2NllpJo6VRUittjAEjtTbwMm20MhqWjDFojqMKAAKUoG7CcaBliSBEEUaAAAAhoIhQhCkmBGGKCUPYItTCzCLMJtTCzKU8Qq0ItSLUilArzpwkcx3KOSYMUwtTigmClsVEYVHVKl4kbiOMYJlDDiJdBl4EgP54aSBenvPdumD75/rv6JpgOIT/zZjwOfC+gSKfA2TZlN420NefTT986Og3jhwv1Orn5ub//CfPvjgx9QvbNq/vaKMYw/WPIEwQhosIXD5tjDZag1HGaKMNGG2MATDGaDAvA6ONAQADYIyBBQaMgSUklf7rcP/D08cI4E/0bP34TeugZckgAAQIFiCEMCCEAAHCCCFAGCGCMEaIIIwRIggjQNByFVFYPFqbRs3vXJGG5Q85QHoAEIBJ8mBLbnp/oUMZdLA4VJIzeX4MwMC/Mr7xHga2EVm7ANBFPcnEr+3esamr43/se/HFscl6EH73+OmTM4VP37TxAzesTrsOvCthhDAi/x978AFex3nfifr3n/mmnDOn4ACnoBIAUQhSLKC6ZBVKtqoleeUWyZZLXBN7N1Hszd7i3bvx82T3au1Ycnbt3Ci21z22lSi2rGLHVrOqRVEURRIkABJEb+cAOL3MzDfzXQUJiEOTlCgRsgRi3hdvMY7rhlUfAAEYstboq4HHs1YxrBxu82KhEq41sApIkJtAGkSFSe45sZmgamZMfSSvHarcENeTcJOo5kyh9L/B2iE3YpFPYVd0tnfF6u55cd9P9x5IFYpDcwt3Pf70nsnpj55/9sZEjEkSPG8BRMQkCYAQgrsuPJ41jGHlWCYvF8xwbQCrgtwM8kFUAGyoWVgXyGVMPWfaL6R6Lqr/d1L5OxAWlglh7UT5H8n4FEjHIiJqqQl/5pILepsavv3c7hcnpwum9VDfwMDs3AfP3Xbdxu4anw7Pm42IZFkCIITgrguPZw1jWDm25Tjc9flVrAYkNQgKAmkAtXp5e3R230LMcd0XptPZrTfVKvuE9VtA4ChhivK9UHpJuxQgLPEpyhVd6zujdT9+ce99+w7OF0uDqbm/evSpFyemPnze9p5EjEkSPG8eAhgRAQJwXFcABI9njWJYOWbFJolUlWFVkEKQ6+GMAVAl55zY9D8d2ZC31UPz88M5f230D+EMw5lBNWcGxW+BtUNuQRWJqLW25j9cetH2psbv7Nz90tRM3jTv399/YDZ12znbrt3YXePT4XnzyLJEREII7rpCCCKCx7MmMaycfKak+xRFZVgVyEdyk8C/2Vw712jkBzJ16XJ558Tk9oYLJN97RPGbECaWCWG/gNKPKPDvQX4cy68q79jQ0R2v+/HufT/ff3C+WBpMzn350adenJz+8Lm9PYmYLEnwvBlkkogAAUe8DCB4PGsTw8rJLBSMoK5oDKsCaZCbAQlwAcR8pbOjs4OZOu66Oycnb926NeJ7H+yXhPk0IHCUsET5Z1C2kH4NIOFYElFbbeRPLrtoe3PDd3bu3js1kzfNn+8/2D+b+tB526/e0BnSNXjeFAIvI3g8axrDysllSv6ALssSVgcJcjNIgygD0GV+fmLq/tHOgq0OpFJH0ulzGhvg/0PwI3CmUM2dF8VvE+sC68SJ+FXlqg2dXbHo37/w0gN9/elS+eBs6n88/MSLE1MfOre3K1YnSxI8v0cCQmAJweNZsxhWTqlQMYI+rB4kNwvyQ5SxaGttstEoDGZq0+Xy8xMTvQ0Nsno+fO8XxbshylgmYO8Xpe9T8POgEE5EIlpfF/mzHRdvb2747s4X90/PZiuVf9p7oG86+aHzeq/a0BnSNXh+bwT+FYEIHs/axbBCHMctFcz6plqsInIDpDDceSyK+0vbo7OHMrW26+6cmPiDLVsiPh/53wt7vzAfBVws46LyEJQt5LsZkHEShqpet7G7Jx77+90vPdg3kC6VD8wm73j4id0TUx86r7crWidLEjxvPIElBI9nLWNYIdxyykUrGPFjFaEAyU2CH8EiXebnx6ceGO0s2kr/3NxwOh3x+SDFyPi4cIbAh1HNzYri94j1QNmMk5OIOqK1f7bjbdubGr/3/Iv7p2ezlco/7T3QN5P86Plnv717fVDTsKhk23OFUnNNSCKCZ4UJLCJ4PGsawwqxbV4pm8GwH6sI+SGvQ5VtdclGf/5QtnahXH5+crK3oUEigrqV/LeJ/F0QBVTjh0Tp2xT8AqRavKKAql6/qXtjIvaDXXseOjCYLpcPzCT/+68ff3Fi6rZze9dHawl4/NDwffsP/scrLumK1eEUOI7juq4QgohkWZYkCZ6TcFwh8C8kIoLHs3YxrBDbdhxH6D4FqwipkFtBCoSNRXFfcXt09nC21nacnRMTf7BlS42uAwrpN8DeJ8r3Aw6WOaLyKJSt5PsASMErkog6orWfv+KS3qaG7z3/4sHZVKZc+Yc9+/dPz37k/LNbIzXf2bl7//RsImj8xysuDekajsU5z+fzc3NzY4tSqVQ6na5UKo7jyLLs8/kikUgsFlu3KBqNBoNBWZbhAQRgO64QggBFlokIHs9axbBCbJMTQVFkrC6sBeSDsLHIx/j58ekHRzuLXDmYSg2n09sbGvAyKUL+jwh7APwgqomiKP0QbBOp5wKEVxPQ1Bs292ysj/1g10u/PDiYKVf2Tc/+5a8eiwWM4fk0d91fHDy0tbHh5i0bZUkC4DjO3Nzc/v37n3rqqRdeeKG/vz+dTpdKJdM0HcdBFcaYpml+vz8SifT09Jx99tkXXnhhb29vNBqVZRlrmBDCchwARKTKMjyeNYxhhRQLFUVlTGVYVUhuERQAcliyLTrbYBQOZyML5fKuyclt9fUSEV6m9JDxEZG/A24G1fgYit8CWwcpgVMgE3XHon9+5SXbmxq+v2vPwdlUplzJlCtYlC1XvrfzxZ54dEO0dmho6KGHHnrggQf6+voWFhY45zg5vqhYLKZSqcHBwQcffLC2tnbr1q033njjdddd197erigK1iRXCNtxAEhEiizD41nDGFZILl3yGZqiyFhdpAikOJwpLEn4ir11s0PZiO04z46Pv/essyI+H/6FTPpVsPeJ0k8AjmWusJ5B6R/J+ARIw6kJatpNmzduqo//zVPP/WrgsOO6WHIoNff1x55qnDzy0x/96MCBA6Zp4rVzHCeVSj3yyCNPP/30d77znVtvvfWWW25paWkhIqwxrhCW4wCQiFQmw+NZwxhWSD5b8hsaU2SsLmQQaxX2HizRGb+ofvIX4x1FWzmYTA4tLJzb1IR/RUHy3ybsA7D3AAJHiYoo3wNlM2mXAYRTI0vUGA4aqiqEQBVHiMcOH1l45Jdze/cKx8HpqVQqe/bsGRgYeOSRRz73uc/t2LFD0zSsJa4rbMcBIBGpsgyPZw1jWCGlgukzNCLC6kI65DZAAlwsIqA3mmw2SgOZ8EK5/Oz4+PaGBlmS8K9YOxkfF7kvwk2hmjOD4jfBWiG34dQ4rnh08MjDg4ddIXAsV2b+sy/QR0fKo0ewEsrl8q9//evBwcE/+7M/+8hHPhIOh7FmOEJUOAcgSaQyGR7PGsawQiolKxTxY/WRwFpBPogiliR8xfPiycFsmLvus+Pjt27dGvX78W8k0i6B72ZR+g6EhWVC2LtR/AEFbwcFcAoq3B5eSNcZfiIqmJbtOKii1kVrLrncXpjj+RyWaJoWDoej0WhTU1M0GjUMgzHGOS8UCnNzc5OTk/Pz89ls1jRNHEcIMTIy8sUvfjGdTt9+++3hcBhrg+O6RcsGwCTJUFV4PGsYw0pwHLdStupbIliFSG4VZEAUsUST+UWNhZ+PUs4Uh+bm+lOpS1pbcRT5yX8L7D5hPQMIHCVsUbkfylnkuwmQ8Wr8ivLxC895z7azxtLZfWPj37vv/vFcQYnUSj6fpGogMjo3mGefn376cUWSmpubL7jggosvvnjbtm3r1q0zDEPTNMYYEQkhOOemaRYKhdHR0ZdeeumZZ5557rnnJicnbdvGsRYWFv76r/86EAh85jOf8fl8WAO465ZMC4AsSYaqwONZwxhWAredcskKhHxYjaQ45BjcJKpsqV1oDUn7Uk62Unl2fPyClhZFknCU3ATj43BG4UygmpsWxW8T64JyFkB4RUQU1LSgpjUGA5O7nhu+5wepTJYFQ2osrsQSaiyhxhLBzduaVfaeSy668cYbOzs7A4EAEeFEgsFgNBpta2u77LLLPvrRjw4ODt5///333nvvwMAA5xxV0un0XXfd1dnZeeONN0qShDOd47pFywLAJMlQVXg8axjDSuDcqZStQMiH1UgySG4Vdh+qRPXsBY2+vrmiI8Rz4+PzpVJ9IIBlROr58N8qCl+HKKEaPySK36LQf4ZUh1MzMjLy11/96uzUlBDCKRbMmSkQSaoWb25+38c+fvOnvnzRhi5d03BqiCgUCp177rlbt269+eab77777p/85CfpdBpVpqamvvrVr/b29ra2tuJMx123aFkAmCQZqgqPZw1jWAncdrjt+PwqViPygbUCBAgsUah8UaN776CeLpePpNN9s7P1gQCqkUq+d8M+ICq/AFwsc4T5GMqbyP8RkIpXwzm/9957d+/eLYTAUUK01Cf+7//057fccksoFMLroqpqb2/vHXfcsXnz5jvuuGNiYgJLhBA7d+687777PvvZz8qyjDOayXmFOwBUWdYVBo9nDWNYCdx2IARTGFYlGXIbSIco4yhR2lhb7Kxten6ynDfNZ8bGLm1rU2UZ1aRaMj4m+BB4P6qJkij9CKyHtEsAwitKJpP3339/pVJBlfr6+i9+8Yu33HKLpmk4PeFw+OMf/7iqql/4whdSqRSWlEql++677w/+4A8SiQTOaAXT4o4DwFAVRZLg8axhDCvBtjhJxBQZqxOxNkEBiDKWObXqzIXNvbunZxzX3Tk5mSwUmsNhHIOgbCLjoyJ/B9wMqjmTKH4DbB3kVryi/fv39/f3o4qqqh/5yEfe+973apqG3yEEXBeyDNfFyyQJ/8px4DiQJDCG4+i6fssttxw4cODrX/+6bdtY0tfX19/fn0gkcEbLlCuW4wII+3RFluHxrGEMK6GYNzVdYYqEVUpqgBSFm0IV2R29sDnyo336XKk0lsm8NDPTHA7jd8mkXw37gCj/CMLGMiHsF1D8HgVvBwVxcn19fdlsFlXa2to++MEPGoaB442NIZnE1q3o60M4jI4OvCyXw86dSCZRU4MLL0RtLY4TDAZvu+22++67b3h4GEsymcyBAwcuv/xynNEy5bLtOABqfD5FluHxrGEMK6GYL2s+lTEZq5QUINYm+EFUc2e6IqInFntqdLRo20+PjV3Z0eFjDL+DAmTcBt4vrOcBgaOELSo/h9JDvpsBhhPhnE9PT9u2jSrbtm1rbW3FCSWT2LsXzc3o60NbGzo6IAR278boKN72Nuzahd/+FldfDcZwnPXr12/evHl4eBhLLMuanp52XVeSJJy50qWK5TgAIn6fymR4PGsYw0ooFkxNV2QmY5UiH1g7IAEujnILNcrMRevWPTcxYTvOrsnJyVyus7YWx5PXwfgknAk4U6jmZkXx28Q6ofQChOO4rlsul3Gsuro6VVVxQo6D/n4QYXAQjY0oFiEEpqawbh02bMDCAgYH4ThgDMfRNC0ajaKKEKJUKrmuK0kSzlBCiHS5zF2HgIjPp0gSPJ41jGElVEqmpiuSRFitZMjrQTpECUeJkuQMX9Sy/Yd+/1Q+P5nLPT8x0RGJEBF+l0TqhfB/QBT+BqKEavyIKPwdhf4r5HocR5Zlv9+PY83Pz1uWpes6jidJ6OrC298OIlgW9uxBsYhwGGNjGBjAkSOIxSDLOBHTNOfm5lCFiPx+vyzLOHPZrpsul4WAIssRv05E8HjWMIaVYJZtTVewmhFrFxSAKGGZCz68vkbf1tAwlc9XOH9qdPSdGzaENA3HI41874E9ICoPAQ6WucJ6GuWfkPEpkA/HkmW5oaFBURTbtrHkpZdeGhkZ2bp1K46XSGD7dtTXY9s2BALw+bBnD3p7oWnYvRu1tbjgAjCGEzly5Mj+vj6SGckySTLJsqr7EIzsHp7KlSuZUoU77uWb2uOhAM4gFnfSpQoAVZYiPh88nrWNYSWYFTtcZ2BVk+KQ43CTqCKc4YBiX9ra+vjwcNm2X5qZObKw0NvQgBOS6sj4uHCOwD4ACBwlKqJ0D1g36VcDMo61adOmcDg8NzeHJSMjIz/84Q87OjoMw8DvWLcOzc2QZfT2olzG448jEkEigcZGOA4kCYzhRBayue//6gmzZVN9e6+s+2TdkHUf8xm/WqDHv/8AdxzLcVqjkYu71+HMYjl8rlAEoDJWZ/jh8axtDKfNdVyzYvv9GlY1KUBym7D3o5qTJDd5blNTUzB4eGFhrlh8dnx8SyIhSxJOSNlAxidE7i/hzqOaOyeK3yB5HZRNAKHK5s2be3p6nnrqKSyxLOu73/1uT0/PBz7wAU3TUI0IsoyXSRJsG5IExuA4UFXIMk6iUqnc85Mf/8MPv8+6thut3ZKiYkmBCxRKWNRSGw76dJxZShZPFYoAdMZiAQMez9rGcNo4d82K7Q/oWNXIB7YekAAXR4mC4ENNoY3nNTcPpdO26z41Ovq+zZujfj9OTCbtCvj6Rek7ECaWCdgHRfEbFPoCpBiqxOPxm266adeuXZVKBUtmZ2f/4i/+wrKsW2+9NRQK4YRqanDddXg1mUzmBz/4wR133DE1NcVGh2o2nRvZeqEargMRjjWSSn/3iRd6GuNd9XW1AZ+hqbIkYZWbL5UKlgUg4veFdA0ez9rGcNoc7pgV2x/UsLpJYB0gP0QBR4ky+JCu49LW1gcHBnKmOTA3t392dkd7O06G/OT/APiAMJ8AXCxzhPkYSl1kfBykYwlj7N3vfvfPfvazZ599VgiBJWNjY1/4whf279//yU9+cuPGjYqi4DWyLKuvr+/uu+++55570uk0AF7Izb/wRGlqpO7sy0LrN4IpqHJ4dv5IcsGvqbUB3/p47YbGWE9jrDNRFw0afk2VJcIqlMwXKjYHEA8YusLg8axtDKfN4a5lcp9fwypHbL2QgnAKWCbAhyBK2+rrO2prX5yezlYqT4yMXNTSojGGk5HrYXwKzjj4EKqJsij9CKyT9KsACUva2tpuv/32I0eOzMzMoMr8/Pzdd9/9m9/85r3vfe8NN9zQ2dkZDAaJCK9ICJHP5wcGBu6///577713cHCQc44lwuGliSNRn3LDdVf25d3RVNoVAkDYrzdGQnP5Yq5sjs1lxuYyTxwc9mtqXcDXkajb0BDrbox2Jurqgn5DU2VJwioxmy+YnANIBAM6Y/B41jaG08YdVwhXUWSsdlIUchOcaVQRzjCJbNRouqS1dd/sLHfd346PT+fzbZEITopI7YXxMZH/MtwMqrkpUfw7ktdB2Yglsixff/31hw4d+tKXvpTNZlHFtu19+/YNDAx897vfPf/88y+++OJt27a1trYahqFpGmOMiIQQnHPTNAuFwujo6J49e5555pmdO3dOTk7ato3jRCKRP/n0Jz9127uPzOf+/uk9vzk4XKiY53e03H792zLFyuB06uBUanB6bnIhmyubo3OZ0bnM4weO+DW11vCtT9RuaIhtaIx1JGqjQSOgq7Ik4XUTAvk8TBOBAFQVpgmfD5YFIaDrOG2OELP5ou04ElEiGFBlGR7P2sZw2hzuACQzCasdBYh1CGsXqrkLwhlnasulra337N8/WyiMZbM7Jydba2qICCfFSL8O/JAo/T2EhWUC9gFR/CaF/i9IUSwxDOOP//iPK5XK1772tXQ6jWNZlnVk0U9/+tNwOFxXV9fU1BSNRgOBAGPMtu1CoTA3Nzc5OTk/P5/L5UzTxEnU1tb+6Z/+6Sc+8YlgwNgWMFqjNWe3N/3Db/dubkm01NW0Rmlba4Np83zFnM7k+ydTA9OpganUxEI2VzbH5jNj85knDg77NSVi+NvjkZ7GWE9jvCNRGw0aAV2VJQmvyeHDePRRSBL8fmzfjr4+BOgHPwAAIABJREFU3HAD9u1DuYzLL8dpM20+k8sLQGNyIhggIng8axvDaXMcF4Asy1jtSAXrBCkQNo4SRfAhqBd31tVtq6//1eHDZdt+YmTk2q6ukKbhFVCA/B8GHxLmU4DAMkeYj6C0noyPgXxYEolEPv/5z9fW1t51113j4+NCCBzHNM3kooMHD+I1IqK2trbPfe5zH/7wh0OhEBbVGL73XLB5e1ujpjCJCIs0hWkKiwaNLS31Fndy5cp0Jt8/lRqYSg1MpSYWsvmyOT6fGZ/PPNU/4teUiOFrj9f2NMZ6GuMdidpo0DB0lUkSXhnneOwxdHWhtxf33oudO5FMYnISIyNgDCuhZNvjmSwAn6I0hUPweNY8htNmVbjMJJlJWPUIcgfIgMjgKGGBD0GYIU27vK3tyZGRMud7pqeHFha2NzTglclNMD4FZwJ8GNVESZT+HqyN9GsBGUvC4fAf/dEfdXd333nnnc8880y5XMYK8fv9l1xyyec+97kdO3ZomoYqTJK6G6I4CZXJ0aARDRpbWuot7uTKlelMvn8qdXAyOTCVmkrn8mVzYj47Pp99qn/ErykRw9cajWxsil++af3WdfUSEU6Gc2SzaG5GTQ1qazE+jvFxPPwwxsawZQuyWQiBUAiShNcrUy7P5gsAgpraGA7C41nzGE5bpWSqKpNlCasfsXVCisDNoIrgQySKJGnnNzc3h8OH5udTxeKTIyNbEgkmSXglROo58P+hKHwFbhbV3DlR/DuSW6BsAQhLdF2/9tprzzrrrHvuuedHP/rRwYMHK5UKToOu65s2bfrgBz/4/ve/v6mpiYjweqlMjgaNaNDY0lJv2jxfMacz+cGpuf6p5MB0amI+lytXJuaz4/PZ5w6PGbq6dV09XoGqYv16PPMMCgWMjKCzE0R43/uwcyeyWfT3Y3wcO3YgGsXrNZnJFSwLQEMoFNJ1eDxrHsNpK5UsVVNkJuEMQGGS2wQfRjVnAu4cpNrGUOjClpahhQXuuk+MjLxv8+aGYBCvgpHvneCHRPnHEDaWCdgDovC3FPovkBtQRZKk1tbW22+//aabbnpw0f79+xcWFjjnOGWyLNfW1m7btu3GG2+87rrr2traFEXBytEUpiksGjS2tNRb3MmVzelMbnBqrn8qOTCdyhQrXfV1EhFegSThHe/As8+ivx+XXoq2NjQ0IBhEdzdME42NSCbhujgNY5ls2bIBtETCfkWBx7PmMZy2SslUNSbLEs4AkgHWAfNxQOAoNyv4ELFunbEd7e0PDAyky+XDCwu7p6au37CB8GooSMZH4YwI82nAxTJXWE+i9H0KfAYUwLEURdmwYUNnZ+dtt93W19f35JNP7tq1a2BgIJ1Ol0ol0zQ556jCGNM0ze/319bW9vT0bN++/aKLLurt7a2rq5NlGW8klcnRoD8a9G9pqbe4kytXFgqlhpoQXlU4jGuvxVHxOF7W0QHbxm9+A0VBKITXy3bc8XTWchxZonU1YY3J8HjWPIbTZlZsRWWSJOFMwMC6QDpEGUeJEvggcDUgb0kkNsViT4+NFUzzseHhHe3thqriVcnNMP4YzjT4YVQTpijfC9ZOvpsBhuPIshxfdNlll+Vyufn5+bFFqVQqnU5XKhXOOWPM5/PV1NTE4/F1i+rq6oLBoCzL+L1TmRwNGtGggdPBOWQZqgrbhq7jdSnb9lgmA0BnSkskTETweNY8htNmm1xRZRDODMQ6BYUgyljmgh+CKIGCEZ9vR3v785OTluM8Pzk5nE5vTiTw6ojUXhifEPkvwV1ANTctit+E3ELqBQDhJGRZjizq7OzEItd1HccRQhCRLMuSJOGM4fPhiitwevKmOZ7OAjBUpaUmDI/HAzCcNtt2FJXhjCHXQ26EO4sqgh8hNwM5KBFd3NrauHfvSDo9Wyg8NTq6MRaTJQmvjpF+DfiwKH0XooJqfASFryEUBevEKZMW4a3HFf9CliS8qSYy2fliCUA8GEgEA/B4PADDabMt7jc0nDEoSKxL2C+imjsv+BjJLQBaw+ELmptHMxnbcX4zMvLuTZvigQBOBRnkvw3OiKj8GnCxTAhrN4p3U/D/gBTF6uG6wuTc5E7ZstOFUjJXTOWKM5l8R33d1Vu6mCzhzXN4bqFgWQA66mqDmgaPxwMwnDbbcpQIwxmDNChdqCgQNo4SBfBBaBcD5FOUK9rbf3noULZS6U+lXpyevrqri3Bq5DgZnxbOJOw+QGAZF5VfQW4m45MgP956HFeYNq/YvGLb6WI5mS1MZ/LJXDGVK6RyxWSukC1VTNsxObe4c83Wrst72pms4k1icWdobt7ijixJHbFan8Lg8XgAhtPjOq5tcc2n4MxBYF2gAEQaRwkb/BCECdIB9DY0bIzFfjs+njfNh4eGLmltNVQVp4SgbCLj0yL/3+DMoJooi9KPIDeS/u9ACt483HVNm5u2UzStuXwxmS3M5grz+dJsNj+bLczligXTMm1etjnnjsC/ISKNyT6FRQyfriqOEHg13OLFTDEQCZSyJc3QVJ+KFVKwrMOpBQCGqnRG64gIHo8HYDg9jiu47aiagjMIya1CisJNo4rgh0jkQDqAWr//ivb23VNTluPsnJg4srCwpb4ep0oibQecCVH4OkQB1dwFUbgbUpS0ywEJbzzuuBXbNm2nZFnzhdJ0Oj+bLaTyxVSukMoVk9lCoWJVODdtzh0XSySJNMYMVdED/ojhS4QDsZARDwXioUB9JBgPGbUBf0BX8Woc7gzvHg4nwpmZTNcFXapPxQqZL5bGM1kAYV1vr43A4/EsYjg9wnU5d1SN4UwihYl1CH4I1ZxpODOQ4gBkokvb2n68b99wOj1bKDw+MrIxHmeShFNEGvneC2dClP8BwkI1Z1wU/hdJtVC2AoQVIgDOHZPzis3zZXMuX0rlislcYTZbmMnkk7nCQqFUsuyKxU2bc9fFElkiTWEhn6YrSsTwxUJGQ00wEQ7EQoFYyIiHjJBf1xWmMaYymYjwWqg+NdoafeH+F87acZZRY2DlHJlfyFVMAC2RcK3fB4/Hs4jh9LiO4NxVVIYzCfnBuoBfAS6OEnnBB0nZikWtNTUXr1s3msnYrvv48PB7zjqrMRjEqZPCZHwczpQwfwO4WCZgHxCF/0nB/wzWjtdOCFgON21u2k6hYs7lS9OZ/Gw2n8oVU7nibLYwly9WbNu0nYrNHdfFEiZJmsJCfs2vqtGgEQsZsZARDwfqw8FEOBANGQFN1RSmK0xhMmElCFhlS/WpruMKIQiEleAIMZiaL1kWAZ3ROkNT4fF4FjGcHtcVDndUleGMIoF1gwyIPI4SFdgD0C2QCkBn7Mr16x8aHEyXy4fn55+fmLhp40bCayE3UeAzwk3CPgAILHOF+Sykr1PgzyEncHJCCIs7Judli+dKlVS+mMoVZ7OFmWw+mS0kc8VMsVyx7LLNTc5dV2AJkyVdYTWG7lfVuoA/EQ7U1wTjISMWCsRCRixkBHVNU2SNMYXJeMMUM8XMTGb7ddunB6fz8/lwPIyVUDStAzNJRwifwnriUVWW4fF4FjGcHtd1OXcUjeHMQqxTSDVw8lgmBO8nUQDVYtHW+voticQTIyNFy3rkyJEr168PahpeA4KyhQJ/InJ/CWccx+Ci8s+gEAX+A6QIAFcI0+Ymdyq2nSuZyVxhOpNPZQupfDGZK85k8pli2bS5yR2Tc9cVWEQAY7LGWK3hC+paNGTEQkY8FIiFAvU1gUQ4WBfw+1VFU5iuMiZJ+P1iGus4tyMUDfnDfkVXsELmisXDc/MAwrrek4jB4/EsYTg9whXCFYzJOMNIdcTahTOOas4Y3FlItVhUo+tvX79+58REhfNdk5MHU6nzm5vx2kikXoLAH4n8nXDnscgVZHLZ5FTKPZydbUjZO1K5ykw2P5spJHOFVK6YK1cqNq/Y3OKOEAKLCFCYrCtKQFcDuhYN+htqQolwIBYyYiEjHgpEg36fqmqKrCtMliS8BeiGrhs6gFAshJUzmJyfL5YAtNVGGsMheDyeJQynx3WFEJAkwhlGCoD1wHwSEDjKzQp7kNhGLJKI3tba2haJ9KdSc8Xiw0ND2xoaNFnGKeOua9rC5FeWzZGFhQdnclqyEEgW/HNFY7ZgzOYDBStjOr8yuWtxRwiBRUSkMlljLOzXw349FjRiISMRCsTDgfqaYDxk1Bg+XVV8CtMYkyTCWsJdt28mWbJsItpUHw9qKjwezxKG0+O6AoAkEc40DEoPyA9RxFGiDD4AwUEMi5pCocvb2g7Nzzuu+8TIyPs3b+6sq8OJcNc1bW7avGha84VSKldM5orT6VwyV0jliqlssFi5umLLFS5zRxb4N0RCk0s+RUT8oZDfiAWN+kgwEQ7GgkYsZCTCgYjh01VFY7LGmCQR1ryCaR2YmXWFMFT1rPq4IsvweDxLGE6P67oASJJwxiHWJaQwnCKWCfB+iAKoBotUWX57R8fP+/un8/mxbPaJ0dH2SMR1hcl5xXbKljWXL01n8slsIZUrpvKF2WwhmS2WLMu0HZNzmztYIkl+jZGhln1KOeIrx4xSLFCMB4r1wUI86MYT7w/XvFNT/brCNCYTETwnMpsvHJlPA4j49Q2JKDweTxWG0+O6AoAkE848UhxyG5wpVBF8hNwUpBoAAuDcaQoEN0fjM+m8bfH7XzhYWbAyhXIqV0zmCvOFUtm0KzY3bc5dF0tkSdIVFtRVXVEihi8eDjTUBOOhQDSIGLsvoT0aVMsa4xrjquwSCbxM/g7pUdKuAjF4Tu7gbCpdLgNYX1cbDwTg8XiqMJwe13WJSJIIZx4KkLJBWM8CQgiyHNnksulaxcqB2YqWzBaSuUIqV0zmCkNTc1qGIHA4nRo6nHJdgSVMkjSFhfy6oSl1ASMWMmIhoz4cTNQE4qFANGQENFVTmE9hjMkEAdtw80OwXgRcVHMmRf5OgEh7B0iB50RM7rw0NV22bIloc0MiqKnweDxVGE6PEdAv2NGj6SrOFEIIizsVm1dsO5tuT86uTxWUmXxgNm+kCkaqaKQrI2U+bdrc5Nx1BRYR/oVLQpapMRyKhwINkWAiHIgFjVgoEAsZ8XAgoKmaImuMKUzGiRGUHinweTf/32H3AQLLBJxxkb8TkEh7O4jBc5x0ubxvalYAIU3b1lgvSxI8Hk8VhtMTCPnOuaQLq5PrCpNzkzsVy86WKjOZfDJXTOUKqXxxNluYzuRzpZxpXW5y2eSyKwiLCC5jlsZYreEP+rRo0B8LGQXHfmpitCK47tc+8/aLLm1r01WmKYxJEl4bCerZUuDzbv7/BT8ECCwTcMZE/isAkX4lwOA51tDc/HgmC6AxHOyOR+HxeI7FsDa4rjA5r9i8bNnpYjmVK6ZyxelMbjZbSOWKqVwxV66ULW5ybnFHCIFFRFBlRWN2QDMDqhULlOqDhXgQ8di7YpHORDgQDRq6omiKPF3Ijz2UO5hK5YT50tzstRu7dcbwOknQLiR8TuT/B/gIILBMwBkVhb8CQPqVAINnieOKPZPTuYpJwOaGRJ3fD4/HcyyGMw53XdPmpu2UbXsuX0xmC6lcMZkrpHLFmUw+mSsUKpZpOybnFneEEFhERCqTNcZq/HrIr8eCRixkJMJGQv9tXH00ZhQjvoqucJ3ZmqLLNTeS3oUqrazmyvXrD83Pc9d9YmTkfZs3b4rF8PrJpF0GYYn8X8EZBwSWCfBRUfgKSCJtB8DgWZQzK7vHpx3X9SnK9uZGTWHweDzHYnhrsLhj2jygq0SEU8Zd17R5xeIly5ovlFK54my2MJPJJ3OFVK6YyhULFatic5O/zBH4NxKRpjCfwiJ+X8ivxUOBhppgLByIBY14yKivCdYYPk1hGpM1xshMiVwSooRlRdh90K4BMSxRZPmqzs77+/vHstnJXO6RoaHuujomSXj9GGlvB4TIfwXOOCCwTICPiPyXIVzSrgQxeICxdHYwNQcgFvBvbawneDye38XwZrMdZziZfmjPgCJLH9txrk9VcBwBcO6YnFdsp2iayWwxlSsmc4VUrpjMFabT+flCsWTZpu2YNrcdB0skiTTGDE31B5WI4YuFjFjIqA8HEzWBeCgQCxkhn64rTFeYymQiwvFYj5Bq4JSwTAj7AIk8KIIqnbW1l7S2/njfPttxHh4aeldPz7qaGpwOUkh7ByBE/itwxnEMAT4i8l8GHNLeAVKwtgkhXpyYSpfKADbVJxpDQXg8nuMwvHlsxx1NpX+5d/DXewdH5zLndbSYNtdVxeZOxeamzQsVcy5fSuYKM5n8bLaQyhWTucJ8vlSyLNN2TJtz18USJkmawoI+VVeUiOGrrwkmwoF4KBALGfFwoD4cCOiapsgaYyqTiQinSK6H3AZnCtWcEbgzkCKo4lOUa7q6fnX48FypNDQ//+To6K3hsESE00EKaVcBrsjfCWcCxxBwxkT+K4BL2tUgBWtY3rSeH5u0HEeV5XOaGw1VgcfjOQ7Dm4G77sR89ld7D/1iz8BIKm07DoDRVPqnz/dZ3JkrlGYy+dlsIVMsV2zbtJ2KzR3XxRImSZrCQn49oKnRkBEPBeJhIx4KxEOBWMiIhoyApuoq09nLZMLpoSApm4T1LCBwlJsRdj+xjTjWlkTivKamXx46VOb8F4cOXdXZGTcMnCZSSLsGgMjfCWcCxxBwxkX+K4BD2rUgFWvVyEJ6//QsgGjAf05LIxHB4/Ech+H3y3HdyYXcw/sP/2LPwNDsvMUdLJnO5L/2z8/YjusKgUUEMCZrjEUM3aeq0aC/oSYYDwdiISMWDCTCgXjY8GuqrjCNMSZLeCMQg7IJ5Ico4ihRBj8AcQNIQZWQrl/b3f302FjONPfPzDw7NnZTTw8R4TSRQto1gBD5u+BM4BgCzoTI3wUhSL8OpGLtcYXYOTYxVywB2NJQ3xqpgcfjORGG103AFa4kScIVIBARXpHjiulM7rG+oQdfHDg0PWdyjt8hhCxJIb8e0LVo0B8LGfXhYH1NMBYy4qFAXcDv0xRdYZrCmCTh94jYBiFF4BSxTAj7IIkcqA5VCLigpWVbff2To6MFy3pwYOCytraIz4fTRwpp1wAk8nfBmQAEqjmTonAXIEi/HqRijcmUK88Mj9mOozF2YVtLQFPh8XhOhOH1Msvm5MHJREciNZqqa64L1gXxilK5wj/8dt9jfUNz+aLjujiOLEnvOnfTzedtrjF0XVE0RdYVJksS3nRSnFiHcCZQzRmFMwWpDseq8/mu37Bh99RU0bZfmJraNTn5js5OwkoglbRrAFnk74QzBghUc6ZE4a9BEmnXglSsJX0zswdmkgAaQsHz1jURETwez4kwvF5MZWbJfOmfX/KFfI1djXg1dUH/Ry47+6ZzNo7NZUZS6ZFUemQuM5PO5StWybK44zpC1Bi+nqaYRIS3FCkAZRPMJwEXR7lZYR8gZQuOJRFd0tq6MR7fNTmZNc0HBgcvaGkJaRpWBCmkvQOQROFO8BFAoJozKfJ3AUTatSAFa4PJ+W8Oj2TKFSI6v7W5pSYMj8dzEgyvl8zk2sbavsf6zrnxHNWn4tUoslwb8NcG/B2JOiFgcl4yrXSxMj6fGUmlR+fSI6m0EII7rspkvLXIYGeBDIg8jhIV8H0Q7wLpOFYiELiuq2v/7GyF8+fGx/fOzFzS2oqVQgrpbwdkUfgr8GFAoJozKfJfBSTSrgYpWAMmMrlnhsdcIcI+fUdnu09R4PF4ToLh9bLK1vSh6e6LuxcmFuo7631BH04ZEXSF6QqrDfg7ErUCsGxeNC0ATJbw1kOsW8hR8DyqCLuP3DTkBhxLJrpi/fqfHjiwP5mcL5UeHBzc3thoKApWDCN9B0gS+S+DHwEEqjkTIn8XIJF2FYjhjOa44omhkfFMBkBPPLqtsR4ej+fkGF4vs2TW1Nc09TTNHJ4xi6Yv6MPrRYCmME1heMuSo8Q2CD6Mas4UnCOQG3CcplDo6q6ugfl523GeHBnpm509v7kZK4mRdhkgRP7L4MOAwDIBZ1zk7wJU0ncAMs5cc8Xiw4OHTe5ojL2ju7PW8MPj8Zwcw+sVqA0EIgGSqHlTM8545IeyFZWHAY6j3Lyw95F6ESDhWEySruroeKC/f3B+frZQuL+/f3Mi4VcUrCRG2uWAEPkvg48AAssEnFFRuJPIB+1CQMKZSAjx3OjEwdkUgLbamks72mQieDyek2N4vYgIhJeRRDjzSaRsFlII7gKWcdj7IYqgII7THolc09U1nMnYjvP48PC7Nm48t6kJK4yRtgNCiPyX4YwCAssE+GG38BVJ+s9QegHCGSdTrvzi4GDRtJgk7ehsb64JwePxvCIGzymS2yE3w11AFWEPkJMEC+I4iixf1939y0OHDs3PzxYK9/f3nxWP+xQFK4yRdgXgiPxX4IwBAssE7D43f6cU+i9gXQDhDCKAFyamXhifEkBDKHjVhk5VluHxeF4Rw++LgEuQsHpJNaScJex9gMBR7rzg/cQ6cCLtkcjVnZ0j6bTtuo8ND79r48azGxux4oiR9nZAiPyX4UzgGC6sXaLwvyj4f0JuwhkkXzEf7BvIVsoS0WUdbV2xKDwez6thWDmuEFm7yMAMRZOIUMV2FubLj4e0Xr/SDhBWI9KgbAH9DKKMo0QR9j5oV4MUHEeV5eu6u3956NDQwsJMPn//wMCmeFxnDCuOFNLeAVERhTvhzOIYjjAfgxShwO2QanFGEMDuianfjo4LgUTQuH5Tt09h8Hg8r4Zh5XDh3Dv+28Hx9I0t517Qtk6VZSxyRHmq8OOJ7LcD6sbWms+GtXOIGFYhYmcJKQKnjGVC2PtJ5EB1OJGO2tqrOzu/sWsXd91Hh4Zu3LDh7MZGvBFIIf16iIoo/E+486gmLFG+H1KCjD8E+bH65SvmffsOLpTKEtGlHW2b6hPweDyngGHlCCFSleyjkwd2702/57yzbtqyqcGoIXLnSw9P5X7I3Wym8pw1n1oX/nTUuEYmH1YduYFYh3CmUI2PwBmHVIcTUWX5uu7ufz506Eg6PZ3P/+zgwZ5YzK8oeCOQRr53QeRE4e8g8qgmiqL0A8gN5LsJYFjNBLBrfPLZkTEhRCIUuGnzRkNV4PF4TgHDyhGAC0E6n87m735013NTR9537lm9daXp3N9aTgr/QpTsoSPpL1X4eGPwA4pch9VFCkLZAvNpwMVRIiPsvaRsAwgn0lVXd2139zeef9523UeOHLm+u/vClha8QchPvlvhZkTphxAVVHPnRfFvISdIvQiQsGplyuV/eqkvXa5IRJd3tG9pSMDj8ZwahpUkXiapLimuWXR37kslCw997ILfxvQhVLGcufHstyp8oiX8ab/SDhBWDRnKFkgBuDkcJSxYL8L3HpCBE1Fl+YYNGx4eGhqcm0sWCj89cGBzIhFQVbxBpBAZH4O7ICoPQNioxkdR+BuE6sE6sDoJIZ4+Mvbc6IQQoiEceteWjX5VgcfjOTUMK0cALgTJruRznCITDs1NSvuPqBd2Mp9qoYojSrPF+yt8urXms2HtHCKGVYLYBiE1wM2hiuAHyEmCteMk1kci7+zuHkmnLcf5zcjIO6emLm1rI7xhpBgF/hjunDCfBlwsE8J6EcVvUvA/QYpgFUoViv+0ty9XqciSdNWGzs31CXg8nlPGsKKEECQLWec2NAD5su+B3eelC8ErN++t8RdRRQieqTxnzafWhT8dNa6RyYdVQaojZYvgA6jmJAXvI9aOk1Bk+fru7l8dPtyXTM6VSj89cKC3oSGkaXjjyK0U+PfCnYPdDwgs46LyS7D15P8wSMOq4rjurweHdk9MCWBdJPyuzT26wuDxeE4Zw8oREAICBMnnkCSESwCKpv7Ygc1zheD1vbubIvNEAstEyR46kv5ShY83Bj+gyHV46yMdSi8qD0BUcJQowdoD7WqQipNYV1NzY0/P4YUFk/OnRkefm5h4R0cH4Y1DULaS8VmR/29wplFNFEXp+2DtpF0JSFg9RtOZe1/qK1m2Ksvv3LShOx6Fx+N5LRhWkIAr8DLJ50AWcAmLbIftGVmfKQau376rp3GCSS6qWM7cePZbFT7REv60X2kHCG9pRMoWIdXBmcQyIey9JNKgBE6CSdI1nZ2/PHRoz/R0ulL5x/37z25oqPP78QaSSbsczqQofA0ij2rOrCh8g+Q2sE6sEibnP9t3cCA5B2BjfeymzT2qLMPj8bwWDCtHAAIuAElzSBHCxlGuoJF07J+HL43Hhht8ex23gCqOKM0W76/w6daaz4a1c4gY3srkRmLdwplENWcM/AjUBE6uKRS6eePGwbm5km0/NzHx2PDwuzdtkojwxiGNfDfDGRbleyFsLBOw94nidyj455DCWA32T88+2DdgO05AU9+3bXNLpAYej+c1YlhRLgQAYkLWuVuSsYRpYtvWmvdv2/G2REPJfGgy9z3TmQUElgjBM5XnrPnUuvCno8Y1MvnwliUFofbCfBLgOMrNCXsPqRcAEk5ClqSrOjt/PTT09Oho3jT/cf/+C1tamkMhvKGkGjI+Bj4irOcAgWVcmL+Eson87wcY3toKpnXPnv2T2RwRnb+u+e3dHTIRPB7Pa8SwkoQQeBnJQtIdvIwAEnBJIXZ9a+87122XSYpot+mseSz7/xWtAQEXy0TJHjqS/lKFTzQGb1XkOrxFSaT0CikEdwHLOKyX4MtDCuPk4obxvs2b98/OZiqVfbOzvxgc/MOzz2aShDeU3IrAHyE7DWcU1dycKH2PlB4o2wHCW5jlcJkkQ1V1hd1y9tZavx8ej+e1Y1g5AhBC4GUkJJ8jqS6LmCQLa8ZXMZ1H9w1f1bEhFghIpEeNqzRWP5r5eqbyjCtsVLGcufHsNyt8oiX8Kb/SDhDegth6yC1wF1BF8AFypyCFcXJEdElr6yWtrQ8ODlY4/9mBA5e1tW2IRvHGIlLOg/Ehkf8qRAHV+Igo/m8K/QWkKN7CIn7/n195ydktjZlS+bx1TURpsDzSAAAgAElEQVTweDyvA8OKciGwKFSHDY3RvJ4ZyiadIuNZdffI9CODh96/vVciIsghbVtX3f8znv1Wsvhz7hZQxRGl2eLPK3yqteazYe0cIoa3GoqQsk3YewGBo9x5Ye0l1gMQTi6s6+/bvPn5ycnZQuHwwsLPDh7804su0hnDG4oU0m+CfVCUfwY4WOYK8ymUf07+D4EUvFUREPH7bt66yXFclcnweDyvC8PKERACgklyZ6D+hsZzL41v2rUw9NX+/589+A6z86DvRP/9vf30mTNnei+SRhr13iUXSe4FGYzBNzEtwRSzuU9Y/rg8uTdsNgsxJEuwYQEHQpZgsNyLjCwXyVbvozqjOl1TzrTT3/q7jhyNRpYljWTNeNjn/XxesQoydlJO69YL+48srqooy8rGfyBNKq3M/i+aVNIe+41udwOM85itgcxOo7enLPSXEd8akTwYV0iBMhPp58BJDOEMzD3gu0FeXB4Bs4uKVtfU/O7gQctxXmtsXFFRsaC0lDDKhCzyPcLWCZiHAMYQTnHqaZKnQ5kDEMYxkUiURLhcrusl4cYhUL4W+lz5stuLZpd6IyIJS3Jrt0Ub3kofMYOG2ac2tPe+duzolxcslAUR50hCVnHwYU0qaRn8WdJoZDi4gFPmqdP9/5Cx2ooCD8liDq7IcuIOG4qYgzFBUh2L+bBOYxg2D5HdBakSV+SV5U/V1W1taTnd13c2Hv9tff3ESCTs8WC0SRPI90WO/Tc4vRjObuXUv5JUASECl8v1fy4JN45HVP6s8qag7FEFGecEZe+9xfMP9Te352WsmGyYeOVAw4oJlVMiRThPIC3iW6VKBc0DTw5ktjlsYhjDjrYOPpWx2kpDf+GVKwHCR7E51RH/rSyECwOfAQhjQMwneTpbpzGc3cXmIZIqcTWTI5EH6ur+efv2jGVtaW5+4+TJT9fViYKA0SWQugKeek79FmziAof1LUi/Qt6HQTLGhmHg9GnEYigqQlERBAEul2uUSbhxRBJy1SCGIWBaVvnNBdOeSe0wQqbZq7Z0x188fKhyacQjKTiPIAbVGRNy/qZ18Knu5CuWk8AwNqe6ki9nrI7yrK+H1DlEEi7GbEWTb7TH/i3suSnff69AGsYAeSDPReaP4AyGcArmHmirQRquSBbFu2trtzY3b2tpiev60wcPzi4snBiJADAdJ22aAUUhItxw5CPPZ9moh7kfYAzhFKefIWUO5OkYA8zYtQsHD6KgALt24Z57UFYGl8s1yiSMMk2U7yyau6f31LG8fmtQti1h45FTKydVLyqsJhAuIE0qrcz+K00qbY/9Rre7AcZ5zNZAZqfR21MW+mrEt1okDy7gQX1vy+DPDbs3ZZ6wnJgiahgLRMoMFnJht+ICZuMAOVGIJbiaQr//4ZkzG6PRaCrV0NPz2/r6by9dCuDVxsb2WOzR+fN9ioLRIJWT7xGONcPpxXBWE6d+R4FyCCGMNtPEnj1YsQJ1dXj2WRw5grIyuFyuUSZh9FX48+4sntMa22gETbNP7Y5mnj28f3JOYbbiw8UkIas4+LAmlbQM/ixpNDIcXMAp89Tp/h9krNaiwEOymINzUubp5oEnUuZpABnrrG6dVcQ8jA2xiOQ6tlsxnN3O5lESS3A1RLSkrOyOSZN+V19vOc5rjY0lweDZePylhoYCv/+h6dN9ioJRIZC6DNrdnPp3wMQFNutvQVlInnsAAaONGcw4h5lbW1pkWc7LyxNFES6Xa3RIGH0SCTfnT9vW07Atr92KKY5FOxrb3pvYcFfZLIEEXEwgLeJbpUoFzQNPDmS2OWxiGMOOtg4+lbHaSkN/4ZUrTbuvZfAXg/pegAHYTjxpngyoMzA2yA9lLvS3wQaGcBLmHqgrQQquxqcon58x42BnZ/3ZswOZzE927DBt23QcgahpYKA4GMQoIR95P8vmfpj1GM4Z5NS/kzwNUjVGlSxj3jzs2IGmJvT22gsWdHd3NzQ0lJeXT506NSsri4jgcrluNAljIlcL3le6oLH3Zb3TtAaUwX7nhYYDs3MrSrw5uARBDKozJuT8TevgU93JVywngWFsTnUlX85YHaWhL8X0/dHkBmYL59icSRrHmU0iGWOBSJ7FQhh2Jy5w2NhPTj/EfIxAVXb2Q9Onn+jtTRpGyjRxTsIwGnp6FpeVEUaNVEHehzneBGcQw1lHOf0c+R8DaRg9RJg/H7m5iMUwb96AqrYfPlxYWBiNRjdv3nzzzTdrmpZMJkVR9Pl8oijC5XLdCBLGBIHm5dQsKZrwcmejHZMdQzh8Jrqhqv7PqpfLgoSPQJpUWpn9V5pU2h77jW53A4zzmK2BzM6UedrmlM0pXMBJ84TFSZmyMDbEUpJq2e7EcHYzW40k5uNqHOam/v497e2mbWMY07Ybo9GMaXpkGaNFIPUmGNs5/RJgYwibnHmN1CVQFgOE0aMomDQJ5wQNo6qq6vDhw7Is19TUmKa5adOm7u7urKysBQsWlJaWwuVy3QgSxkpA8txbMn//2dYTZ207KaX6xPWnDy7Mm1AXKsVlSEJWcfBhTSpuGfxZ0jjOcHABG3Y3LpE2m027VxayMDaEIJQ50LcAFoY4cZh7oC4GJFyezbyztfUnO3bs6+iwHAcXa4xGB3XdI8sYPUKQvJ9jsx7WKQxnd3LqdyTVQsjBmFAUZerUqaWlpceOHQPQ3Nx85syZtWvXKori8XjgcrluEAljqDZUsqZianvLvnhKcnShuSPxctvuCl+eT1JxGQJpEd9qVSpoHnhyILPdYRNXZDkDKfOUV67GGBFInsNCNpweXGCzsYecfgi5uDzbcc7G4/3pNOMjdMbjrYODBX4/RpU8hTyf4cT/BKdxAbO+HZk3yfsAIGJMEFFWVtb8+fMty9q6dWsoFCoqKhIEAS6X68aRMIZUQbq9ePa2sqa9nQlHF/Q++d2OhqW5tUvzJhMIl0EQg+rMCTn/b+vgU93JVywngcuznVTSOJHjvZUgYGxIlZCqYfRgOOsUzAaoubg8RRTvqa2dGIk8e+TIhhMnoqkUM+O8uK439vTMKy7G6JLIcyeMray/BzCGcILTfyBlDqQajCHxnOLi4n379h08eNDj8YTD4dzcXLhcrhtBwrUwDCN1XiwWy2QylmVJkqRpWjAY9J7j8/lkWcZllHhz7p0w8/jxrYNdsBNStDf1YtuuKaHSHDWAKyFNKq3M/itVKmgZ/IXtJHEZDDtpHneclCj4MTaELFLms7EHsDDEGWRjJykLQTIuTxbFafn5VeHwioqK3x86tLO1NWEYOEe37YZoNGNZmiRhVAm58H4e5jE4PRjOauT0C+T/JkjD2KqsrFy6dOnhw4eDweCCBQvgcrluEAlXY9t2f3//mTNnDh48eOTIkdOnT7e2tvb39+u6bts2MxORKIqqqobD4dLS0srKyrq6uunTp1dWVmZnZ4uiiGFEElYWTdlUfeat6Fm2BLNP3d97ZnP3kXtL5osk4IpE8stCmEC4opR5ynQGRcGPMSKSMp+F38GJ4gKHjd3EfaB8XI1Plm+qqppeUPDGiRN/OHy4MRo1bRtAYzQa13VNkjC6iJT50NZw6veAhSFscmY9qSugzAMIlzBtu30wpkqSR5Y0SVYlkYhwI4iiqKrqvHnzUqlUOByGy+W6QSRcXjKZbGho2Lhx46ZNm44cOdLX15dOp5kZl3HmzJm9e/cSkcfjCYfDdXV1y5YtW7VqVV1dnc/nw3lh1b92yqx9R/v6BnRrUE6mUq+075kdrqrw5eFKeFDf0xb7teUkcEWGHc1YLZpUjDEj1UCaCCOK4ewzbB4jNR8jQEDE631w2rT5paUvHD36amNjRyzWFot1xOO5Ph9GG/nI82k2dsNqxHD2WU4/Q1IthCAukTTMH2/e3tgdLQj6CwL+olCwIBgoCPgLg4GgpnpkWZMlSRBw7RzHaWhoKCgo6O3tnTJlClwu1w0i4aMkk8ldu3Y9/fTTb775Znt7u2EYGDFmTp3T1tb29ttvP/XUU6tXr37ooYfmzZvn8/kAEGhOYfmiqtL1+086umgNyqe8Z//Ysf8L1beogoTLSJmnmweeTJlncDW2E08aJ7K0hQBhbAghUhawsQuwMMSJwdgJZQlIxsiIglATDj+2cOHKysqnDx7c2dZ2PBqdUVCAMSBPIM9aTvwTOI0LHNbfhbqFtNsAARfzynKWRzsZ7T0Z7QVARKokapLkU5SI31sYDBQGA4XBwLTCgunFBbIg4FrweXC5XDeOhIs5jtPQ0PDUU0+tW7euo6PDcRx8DKZpNjU1PfXUU6+//voDDzzw5S9/edKkSaIoBhRt1aRJ7x5rjad1a0AxcjMbO+sXRibNzK7AxRzWTbuXSGoZ/PmgvhdgXI3DZtI87rAukIYxIpIyn4UwnG5c4LCxm5woxEJcC1WS5hYXT8zJea+5GYDtOKIgYNRJpN3G+iYY2wHGEGeQU38geTbEAlyMwUWhoCyKpm0DYOaMaWVMayCdaR+M1bd3KpK4oKy0riBfJILL5RoHJAyTTqfXr1//wx/+cO/evaZp4gZxHKe1tfWJJ57Ytm3bt7/97TvuuMPj8cwsKarJzdnf0mHFZScjdkr9L7fvqg7kByQPhjHt/lP9PyBQb+odZgsjkzROWE5cETUwgwjXihnvI8LISVWQJ0HvxnB2E5tHSCzENSIgpGl3lJebAwNCLIZgEIKAEbIsxGJ4XzAIy4IgQJaRSkHTIIq4AjGfvJ9l6xicflzAMA+w/gZ5P88spEwrlsl0DMaO9/Qe747ua+uwHQeXICDi9903bfJnZ08vCQWJCNeCiCoqKkKhkNfrFQQBLpfrBpFwXjwe/9WvfvX44493dHQwM2400zR37dr1rW99q62t7Ytf/GKOzze/suRg21nHEKyYLPqsbT0NSyK1NxdMIxDOY9gJ/UjaagUYI6ZbHXqyWTl6CqdPIy8P8+cjGMRIOA6OH8eBA1AULF6MggKMkBAiZQEbO8AmhjgJmDuhLgcpuFbJpLBhgxqN4n0LF2LaNBDhqkwT776LU6fgOKirQyaD7GzU1eGVV3DLLcjNxZUQKYuhLuf0K4CDcyxHSJpOf2Jjk1V7opdO9ERP9PT2JJJx3dAtCx9FEoVphQVfXDB7WXWFV5Zx7YykUegrzC3OjbZEjZQhh2S4XK4bQcI5yWTy5z//+fe///3e3l5chiAIgUAgJyentLS0pKQkEon4fD5JkkzTTKVS0Wi0ra2ttbW1t7c3Ho87joNLMHN7e/vf/d3fWZb11a9+dV5FyTO7D/Wn0tagouRlYki91L5rWlZ5nhbCeQyb4QAMQBICIW2+IkZwMWYbcDCMAAWHD2FvAgsX4tAhmCZWrYIk4ap6evDyy1i8GP39eOEFfOEL0DSMiEDKfKYwuAsXOGzsIacHYjGu1enTaGnBQw/hzBls3Yrqavh8uKrOThw8iHvugWli/XqoKvLzkZ2NM2dgGLgqIQjPZ/T0/ng6ejbpP9mffWog+0R/+MxgeMDYkTLYchycJwqCT5Fth5OGgfOyvZ67pkz6/NwZFeFsgQjXRZKlWGest7lX1uSiCUVwuVw3iATAsqx169Y9/vjjvb29uAQR+f3+yZMnr1ixYsGCBXV1dTk5OR6PR1EUSZIEQXAcx7IswzDS6XQ0Gj169OiOHTvefffdY8eOJRIJZsbFotHo448/HolEVt9zX2VuuL+53Y7LTkYkn3VooOXtrkMPlC2WSMA5BJFAOMfmjMN6nu+ugDqNIOICZjCGs2yh41VU5mLuXBChvp4NA6JIRLg8x3GorY28XixYgMFB/PKXiMehaRghsYLkKax3YTirhc1DJBbjmjBjYACBAHJzkUpB181kUmf2+XxEhCtIJCCKyM+HaeJ98Tja2xGNoq0NzLgMhzltmgPpTGv/4PEe52THyuM98fZ4IGaoGUtifMAGoEhiQFXz/L7qSM7E3JwJuTm7Wtr+bfcB23FEQZicn/vI/Fk3T6j2qwo+Btkjh0vCu1/cvfCBhYpHgcvlukEkZt63b9+PfvSj7u5unOfz+R544IHKykoARDRhwoQlS5YUFBQoioJLCIKgnOP3+3NzcydPnnz33Xd3dnZu3br1xIkTzAygqalp3bp1yWQS53R1df3whz+cMKl2TlnRgZYONgQ7Los+K2Mbr3XsnZtTU+MvwCWYzYH0NtPuK896NOxZKZCKyxEdBLLR04N4HH19UNXW9vaugYHa2lq/309EuJhlWe3t7T09PVMVRUunMTCAvj4QQVEwckIQygIYW8EGhnACxlaoK0EaRo4IJSXYsQN79qC1FTk5ven05nfeqampmTJlisfjwSUsyxoYGPAHgxozdu+GaUJVEQph5kzMnYtkEkS4RDSZ2tfWcbw7eiradzLa25NIJnTDsH2AD+cQsVeyQqpeFhisifhrim6bkFdSmhUKaqpHlgUigej5+qMMXl074c/mzpyQGxEFwsdjZsz+s/0FNQUDnQN5lXmSIsHlct0IUjwe/+Uvf3ns2DEM4/V6H3nkkZUrV+J9zPgAEUZGUZSy95WW4n1EADZv3vzaa68lk0mcd+zYsX/91b/c9RdfD2jqYDpjxWQ5N0MiNyW617fv/Yua1Zoo4xIMJ2EcO9n734uDbYWBtZKQhY8kCJgxA+vX47e/BWCvXGkSNTU1NTY2zpo1q6amRlVVnMPMfX19e/fubW1tnTx5sllerlVW4plnYFlYvBiBAK6BQMo8FiKwO3ABm5k9g2gO+WoUUcTIlZZi1SocPQq/37z55u7e3sLCwpMnTzY2Ns6dO7eyslKWZZzDzD09PXv27Ekmk7fcdJN2xx04cADvu/NOxOPwehEMYuFCBAK4xLHO7v/+xqaueMJhxnmSIPgUIaz2VYb6JmT31WT3Tcjuz/Mm/Vq2Gr6NlBIMUxUJzysrXl5dcfvkiSGPho+PEe+NK5oy7dZpbUfbkgPJUF4ILpfrRpD27dt3/Phx27YxDBEJgoD3JZPYtQsdHSgtxbx58HgwEqaJI0dw7BgCASxciEhEEAQiwjC2ba9fv/7mu+4pygoOpjN2QmZTING22H6r6+Di3ElzwjWEj8S63dky+GTGai4JfdkjlQKES+Xn48EHEYvB49ElqWHzZkVRIpHI4cOHfT5ffn5+NBp1HCcQCOzYscNxnJqamjNnzkQiEf/dd1N/P0QR4TAEAddEqiB5GtsdGKYv2fPftm2oiPTcWl09MSfHpygYCUnCjBmYPh1EguOgt/fUqVPhcDgUCm3fvr2hoWH+/Pl5eXmpVKq+vr6hoaGysnLRokVZWVmIRFBdDSIQgRnvI8LixSDCJQpDAVEQmFmTJL+qFgT9NZGcCbk5E3KECvnJLHGXTzZFcvCfdKRfgFwHCuC8omDgb267OeLzSoKAG4KQlZ8VygtJslQzv0YQBbhcrhtE2rVrl67rGIaIKisrS0tLwYzt23H6NObOxbZtEEUsWgRBwFU1N+PNN7FsGZqb8cYbeOCB4uLiysrKnp4eZgYgCPCHRMOOHj34zsTaxcfOwtEFOykJmg2gR4+92Lqj0ucLSLLp9DMcXMJyEmcTz6Wt9vKsrwXVmQQRH0IEnw8+HwAP8+LFi/fv39/U1DRx4sRgMLhhw4b29vasrKzJ5+zduzcWi82dO7eyspJkGQUFuD7kh7IE+mZwBufZ7ByPRt9s2vPysWMLS0tvra6eU1wc9ngEIlwZEYgAiKI4bdq0kpKS3bt3nz59ury83DCMF198MS8vLxaLZWVl3X777QUFBYIg4AOCgA8Q4QNE+Ch5fv8dUyYall0dCddEckqyggFN9UgSEXP6No7tB+u4wGH9XTL2Ql0BEM6RRbEg4McNJcoizpFVGS6X68aRUqkULhYKhb72ta+VlZXBNHHmDKZPx6xZ6OtDS4szfz6dg8tgZse2hZYWys3FvHmIRPDqq0iny8vLH3300cbGxoGBAQDBLPHR/ydSUqFEIu806zFFmmjYkpOQENZBYOYdvcdeOLNzdqgHrBt2FB+F2exPbzXs7rLQVyPeWwTScBlElJ2dvWLFirNnz0aj0e7u7lOnTn32s5/Nzc11HOfs2bM1NTUTJ070+Xz4uIiUuSwWwTqNi1mO0xGPv3Ds2FunT0/Lz7+1unpJeXlJMKiIIkaAiMLh8K233tre3r5r165kMqnrelNT0x133FFdXS3LMq5LQFW+tnSBLAiyKOIiROpKVjZAfw9gDHH6OP0cyTMhZMHlcv2pkXCJOXPmrF69WhRFvC8YRFcXYjFEo/D7T5w4kUina2trvV4vEeFiuq43NTWlksmpXq8cj6O/Hz09UBRIkiiKa9asmT179ttvvw1Akql6slozWQUSRu8Rv1bWl/ALSUFw2BEJQNKy3+5J54iNYTmJK3GSxvFTff8jY7UU+h+UxTAuTxTFkpKS4uLi48ePS5Lk9/tlWWbmiooKAESEkWFgd1vb3o4OfCTOcGYWrBDOi5vqgK7iHGYezGS2NDfvaW+vyMpaWVV1a3X1hJwcn6IQrk4UxbKysvz8/IaGhjfeeGPp0qW1tbX4GIjIK8v4SEKEPJ9isx7OIC5gNnbA2E7abQDB5XL9SZFwienTp+fk5OB9ooiFC/HGG/j97yGK5qJFViJx/JzZs2dXVVXJsoxzHMc5e/bsnj17BgYG6urqjPJyuakJzzyD9y1aBK8XQE5OzvTp099++21cLNuXKAj19yX8SAsRTvXAyyAAbZns+njJ8uwTIjm4Ejbs7pbBX6SttvLQ1zSpGFdERPn5+YqibN68ubCwMCsrq7q6WhAEjBzz1paWn+7cicvKBSIYxmHCxTKW1RCNnuzre+nYsQUlJbdPnLi4rMwryxgBVVXr6uo6OjpUVcUoIlIWQ1nEmQ0AY4gT4/SLpMyHkAOXy/UnRcIlVFUVBAEfKCvDZz+LZBJ+f9q2G/bsCQQCHo+nvr4+Ozvb4/F0dnaKohgIBHbv3q1pWnFx8cmTJwvy83333YfBQSgKQiEQARAEQVVVXMKjGKU50WMdJZYpFtkxQ6MBywvAZHFfrGyCt7tE68fVOE46ZRw37agmFeNqQqHQPffcc/DgwWg0WlhYSES4Rgw4zLgSwghYjtObSh3u7q7Izp6Wn++VZYwYEWG0CSHy3M/Gbji9uIBh7GFjK2l3AwSXy/WnQ8IlTp06lUgkQqEQ3keEQACBAIAA88qVK/fu3dva2jp16lRJkp5//nnTNIPB4NSpUydPnrx3715N0xYvXlxYVARRhKZhmEQicerUKVxCFJyScK8qWbolCSmhLu/sjlilzQKAXtO/J1aeq8RVwcLlCaRke5aXhx71q1MwAkRUfA6uD1F5VtayigpcFrPdBes04ADQbfFwXyRtyRiGAJ+iTM7NvbmqakVlZUVWlipJGHcIylxSl3H6ZcDBEE5w+iVSFkHIhcvl+tMh4RI7duyor69ftmwZEWEYIsrJybnlllva2toSiURra2t3d/df/uVfaprGzK2trbNmzaqqqlJVFZdg5gMHDuzcuRPnMCMZc2L9tqKqfp+vLGL5NSsTl3sGw3f7u5p0oz2jAXCYjiSKan2dk3ydhI8mCaEC//0lwUdUqRAgjD4C7pg48eaqKlwWwzjAg8/CiQLoTPu++d7qpngI5whEEa93TnHx6pqa+SUluT6fSIRxiwLkuY+N7bC7cAHD2M/6FvLcCwhwuVx/IiRRFB3HYWac197e/sQTT0yZMiUSieASoiiWl5cz8/79+xVFUVVVkiQA1dXVRITL6O3tfeKJJ9rb23FOfMD+xT9EfX7xvvvu+9KXvlTkF8rDTdF4X3+yYmrWbfAmfn16f9o2ACQsbedgZYnW7xd1fBhpUlFJ8Ev5/nslIYAx5JEkjyThCpRax66G3gYgbUsCMQBFtEuDnmUVdatqaqbk5QVUlfCnQJ5BynJOPwc4GMIJTr9E6hIIeXC5XH8ipNra2ra2tsHBQZznOM6WLVtOnDgRiURwGURUVlbGzG+99VYwGCwuLq6srMTlnTx5cuvWrY7j4BzD4CP7MllZWTXfuDc3sDJk2xPyrb3NfYmMlExPvK00e09f3+7eEwwwcDqVezRRODfULIBxHkH0q1PLQ49me5YKpOCaMBzHEQSBmQGQQLjhhBCpy9jYAdYJCMj63LyztxQ3La8oryz5nCqH8bEFAgFN0zAGyEeee9h4D3YnhjPrWd9CnvsAAS6X60+BtGTJkqampo0bNzIzzrMsS9d1XFFOTs7atWuPHTtm23YwGMQV6bpuWRaGIaL58+cvXbqUiBRJqoqEZVFM6ubpnr7F1WX3ly44Hu8YMJIAdEfaPVhZ5YlGlATOEUjL8a4sCz3qUyYRBFwj0zA7Gjqyi7JjPTFfli+7MBuEG00gZSGLhbCagor+7Zk7K4KDES0lip0CnwbC+Bgc20n2JSdWTySmZH/Sm+UlIowqeRqpN3HqD4CDIZzk9KukLoOQC5fL9adAKigoWLVq1YEDB7q7u3GeaZoHDhwgIgCKohQVFRUUFKiqimGIqPQcfJRMJtPZ2Xn27FnDMAAcOHDANE0Mk5ub+5WvfCU/Px8AAVW5YZ8qD6QyZ3r6TNueG65Zmjt5fcdehxlAhx7aHy+7KdwgkSMLWQWBB4qDf66KeQDh2omSaBnW0c1HJUWqXVoLwqgQS0lZwFazVzIX5HfgA06UjfdIngGScb2Yuae5x8yYlmHllud6s7wYbeQl7R7WN8PuwHBmPevbyHMPQHC5XOOeJAjCmjVr/vzP//wnP/lJJpPBObFY7G//9m9lWQYgimJ+fv7N50ybNi0cDvt8PkEQcAnHcZLJZF9f36FDh95666133nmnq6vLtm0ApmnGYjGc5/F4HnnkkTVr1giCgHNKw6Esr2cglTkd7UvqZtjnuad43oH+M22pXgA2CwdipRN93bV+b0noy3m+uyTBj+sliEJOac6RTUcmLJjgDXkxSsgDdXtyvrgAACAASURBVAUyf4QziAts1reQ5zMQi3G9REnMLc/d9fyurMKscHGYiDAG5CmkruTU7wEHQzjBmVdJXQohBy6Xa9yTAAQCgccee6yjo2PdunWGYQBwHGdgYADndXZ2Hjp06De/+U1paWldXV1NTU1JSUlOTo7f75ckybKsRCLR29vb1tZ24sSJo0ePtra2DgwMOI6Dj6Ioytq1ax977LFAIIDzQh6tNDvUFO3vGIgPptNhn2dSsHh1wcz/3bTZdCwAfab3QGLezcX3FfqXEsn4GGzL7mnuyavMS8VSmUTGG/JidJA8g6VJMHZhOOs0G7vJUwQQrg/DzJiiIhKRYzsYG+Qh7U7W34bdiQsY5n42dpB2B0BwuVzjm4RzSkpKvve97wmC8Oyzz6bTaVzCcZy+c+rr6wVBUFVVURRJkgRBcBzHsizDMHRddxwHV+TxeNauXfu9732vuLgYw3hkuTQcApDUjbODicpIWBGk24pm7ew9fmSwFQCDjsbDx1M5xQEJH08mkbFNe8rKKT1NPfFo3BP0EBGuinXYLRCLQV6MkBAmdTmb+8EmhnAK+tvQbgYFcV2MjNHd1F09tzo1kIq2RItri0kgjAG5jpTlnH4WcDDEiXP6FVIWQQjD5XKNbxLOq6qq+v73v19UVPTrX/+6u7sbl+c4TvocXAsiikQiX/jCF771rW8VFRXhYrIkFmUFJUFIm2bHQAznFHvCdxfPO5PsSlkGgJiZfqlt99RQeZ4WwsfgCXiq51VLiuQL+ZiZiHB1FusbOfFL0laR9/MQsjEiIilLWfgD7FZcwGzsI7MRyjxcF0EUiicV+7J9pm7ahg3CGCEvee5iYzPsLlzAMPeysYu0NQDB5XKNYxKGKSoq+u53vztjxownn3xyz549uq7jBlFVddasWd/85jfvvvvuQCCASxBQnBXUZClpmO39gw6zQCSQsCyvdktP/dae0wxm4OBA8ztdh9aWLZZIwPUSREEQBQCiLGJEHNZ3cuJJWKc42QKnj3xfgVgAEK5KqiBlAafbAMYQp5f1TSTPACm4dpIihfJDACRFwhiTp5GyhNMvAg6GODFkXoWyEEIWXC7XOCbhYn6//8EHH5w/f/4zzzyzbt26hoaGdDqNj8Hj8UyaNOnTn/70Zz7zmcrKSlEUcRnFWUGPIid0o30gnjEtryIDyFYCnypd1hDrieoxABnbeLVj79ycmmp/AcYIwzzGiR/DOo33cZLT6+D0kf8bkKoBwpWRF+rN0DfCGcQFNuvvkffTECvwp4V8pN3F+ntwenABs7GbzD1QbwEILpdrvJJwCUEQqqur//qv/3rt2rUbNmx4/fXX6+vro9GoYRgYMUVRIpHIjBkz7rjjjlWrVlVVVcmyjCuKBHwhj9YTT3YMxNKm6VVkAASamV21Mq/uhbadNjsAmhLdr7Xv/Yua1ZooYwzYrZz4Z5gHAcYHWOfMBnb6BP9jUGYBIq6IlJksTYGxHcPZTaxvI28ZIGD0MaMvnlRkKeBR8TEpM0hdxOlXAMYQZ4DTr5I8H0IQLpdrvJJwGbIsT5w4saam5nOf+1xjY+OOHTsOHDhw9OjRzs7OVCql67ppmrZtMzMRiaIoy7Kqqj6fLz8/f8qUKTNnzly4cOGkSZOys7MFQcAIeGS5IOg/2d3bE0+mdDPHhw94ROWu4rl7+0+fSXQBsNh+q+vgosikuTk1hFHGBqdfYWMb4OAiNoydTux7FPgWKctBMq5ACJN6E5v7wDqGcIb1N0lbAyEHo4yZT3REf75hZ0lO6Eur5gW9Gj4O8pN2N+tb4fTiAmZjJ5kHoC6Hy+UaryRckSAIOTk5ixcvXrRoUTKZjMVi3d3dbW1tPT09AwMDmUzGNE1ZljVNy8rKys3NLSkpycvLCwaDPp+PiHAtVFnMDfoBpAyzL5kqDYdwXnWg4PbC2f9y6k3dMQH0ZGIvtu2cGCwMyT6MKpJIXQ5zL+s7AAsXYViNHPt7+PtIuxPkxWUJpC7h9B9gncJw5mE2D5B6C0aZ7fCWY01bjpyRRNGnKQ+vnOVVFVw/gjyLlIWcWQ8whjh9nPkjKXNAPrhcrnFJwsgQkf+coqKimTNnYhSokpTr9xGgW1ZPPIlhJBJvLZi+Pdqwv/8MAAbv7j2xtafxtsJZAhFGkQB5KgW+C+FJzmwEZ3ARht3K8X+E3U3ez0HIxuWIZaQuY6sJsDHEGURmI5SFIB9GkyQKa2ZNPNTUufnw6X/ftD/oVe9fOFWVJVw3IUCeu9jYBqcfFzAbW8lsgDIHLpdrXJIwbghEeQGfJIq6ZfUkkrhYvpZ1b8mCU4nOmJkGELcyL7XtmpFdUewJY3QRpCoKfAdCLqfXwYnjQ5xeTj4Fp5d8X4FYABAuRSqpt3B6PZxuXMBs7CDrBOSZGGVFOaGv37kokdH3nGj71cbdAY+6ZtYkSRRwnQjyHMizob8NMIbY3ay/QfJUkAqXyzX+SBhPcgM+VZaSut4dSzrMAhHOE4gWRSYuzJn0Zle9wwygIdb2xtn9D1eskAUJo03II//XIEQ4+Ss4UXwIJzm9Dk4f+b8BqRogXEqaTMoczvwRYAyxuznzJklTQApGEwHVBTnfvGvJD57bdKSl63+9vsOvqUunVIoC4foIIfLczsYucBwX2KxvIs99kCbD5XKNPxLGk0jAp0piIoNoImlYtiZLGCYge+8rnX9osPlsuh+A4Vivd+yflzNhaqgMY4CC5P08hDAnfgq7FWAMxzpnNrDTL/gfgzITEPEhQgDaKuhbwHFcYLG+iTz3Q6rGKCOiqeUF37hz8T88v+lMV/+Tr23za8rs6mIiwvUgUhayXAdjB4az2zjzFvlrABkul2uckTCehL0eVZIA9KfShm1rsoRhCJgSKl1dMPN3ze+ajg2gPd33ctuuCl+eX9IwBshD2t0Qwpz4CcwjgIOL2DB2OrHvkf8xUpeDZFyESJ7Hci2M3RjObmJ9E0kVgIhRJhDNn1j69TsW/+jFd090RJ94bdt31q6cVJxHhOshREi7jc16cBpD2GT9TdLuglQBl8s1zkgYTzyKHNTUDqA/mTYtG5dQBfn2otm7+04eHWwF4LCzpefYokjtyvw6AmEMkEzqchKyOfFj1ncAFi7iwGrg+N+D+0i7E+TFcGKE1NVsHgTrGMIGZzaSdjvEIow+URCWT62KpfUnXt164EzHE69u+/anVpTnZeN6CKQu4/TzMA9iOOsUG5tJKgVEuFyu8UTCeKJIYrbPA6A/ldYtCx+l1Jtzb/H85mRP0soAGDCS61q2VQcKyrwRjBEB8nQKfBf0JOtvgHVchGG3cvwfYUfJ+xCELFwgkrqc08/BasBwViMb28nzKYDw0WywDVJwIyiSePucSfG0/tQbO7c3Nv/09e1/dc+yguwAroNYSNoqthrABoawzpkNpK6BWACXyzWeSBhPFFHM9noApAwzntHxUQQSludN2dHbuKnrCIMZODTQ/HTTe49OuC0oezBGCFIVBf4rxAinn4UTx4c4vZz8JZwo+b4CMR8gfEAsIe1mTpwELAzhJGfWk7oCQgQfxnAGWH+HxGIoC3CDeBR57aKpg8nM0+/uf7v+ZNCjfu2Oxdl+D66ZROrNnH4J1kkMZx5jYxt57gcILpdr3JAwniiSmO3zADAsuz+VwWWEFN/9JQuPDbZ1ZgYAWGy/2Vlf5c+/r2SBLIgYM2I++b8OIcLJX8OJ4kM4weln4PSS/xuQqgHC+0gm9RZOvwK7FcMZB9jYQdqdAGEIm7AOcfLf2DyI4P9HuJH8HvX/uml2Iq2/uPPIq7uPBbzaF2+Z6/eouFZiOak3s9UEWBjCSc5sIPUmCNlwuVzjhoTxRBLEbK+HiAzb7k+lcRkETM+uuK90wW9Ov5O2DQAJK/OH5i3lvtx5OTUEwpihIHkfhpDDiZ/CbgUYw7HOmTfg9FPgW5BnACLeJ9WQuoxTvwccDOEEp18mZRGEHMACBDg9nH6Z0+tgtUDMJ7EAN1q23/Ol1fNiaX3jgePrttQHPeqDy2Z4FBnXhBTSVnNmPew2DGfWw6yHuhIul2vckDCeECHs88iiYNp2fzKNy1MF6Z7ieU2J7o2d9TY7ADrS/b85806Bll3mi2AskYe0uyGEOfHPMI8CDi5isbGTY39LvsdIXQ6SQR7Sbmf9LdhduIBh7GX9PVKXsL4F5EX6OTZ2gtN4n5ANCmEU5GcFHr19YSKjbz3W9G9v7w16tbvmTVYkEddEmkDqUk49AzgY4vRz5g1S5oO8cLlc44OEcSbb61FEMWmYfak0MxMRLiNb8X++YnlrKnp0sJUBBh/sb/5983uPTrgtIHswlkgmdTkJ2Zz4Mes7AAsXcWA2cPzvwX2k3QnyQp5KylJOvwA4GMJxTj0Ncw9nNgEWnH6AcQ4JBSAPRkdZbvY37lycSBv1Zzp+sWFnQFNunlEjCgJGjjykruHMm3CiuIDZ2E7WScjT4XK5xgcJ40y2z6NIYkI3+pMp03EUUcTlVfkL/qxy5Y8aXu7ODAKw2N7YebAmUHhPyTyJRIwpAfJ0CnwX9ATrG8E6LsKwWzn+j3B6yfNZCFnkuYeNLbC7MJxZz9ZhsIkPEQtBGkYHESYW537z7iU/ePad4x3Rn76+3aepC2vLBCKMnDyVlFmceRNgDLG7WH+LpMkgGS6XaxyQMM5kez2KKALoT6YNy1ZEEZcnEC2ITPxU6cLfnH4nbRsAElb6Dy1bq/z5M7IrCIQxRZCqKPAdCDmcfh4cx4c4vZz4Bewe8n0F8nRSb+LUM4CDCxywgw8TIRaAZIwagWhWZdE371ry+PObz3T1P/HaVr9HmVZeQEQYISEIdTX07eAELrA4s4m0+yFVwOVyjQMSxpmApnpVBUBfKm1aNlRcmSrI9xTPO5PoerPzoM0OgLZU9LdNmws92flaFsaemE/+b0DM4+Sv4UTxIZzg9DNwesn/DdLuZX0r7FZcGakQCgHCaBIEWlRb/tXbF/7Pl9871tr9k1e3fmftyuqCCBFGhkhZwPIkGHsxnH2GjS0klQECXC7XJ03COKNIYtjnOd2DvmRatyyMQLbi/1zF8qZkT2OsHYDDvKf35AttOx+pvEkTFYw9IUTehyGEOfEz2K0AYzjWOfMGnH74vkLKAk63AYwrIA+JhRh9kijcMqMmntZ/9vr2vSfbn3ht21/ft6IkEsIIibmk3srmIbCBIZzhzEbS1kDIhcvl+qRJGGdUUQz7vAASGT2pmxiZGn/B58uX/1PjK/1GAoDuWK+275kYKFqZN1UgwtgjD2n3QAhz4p9hHgMcXMRiYyfsdsDCVZEXYh7GhCpLd8+fMpjK/OatPVuONAU86mN3Lc0N+TAiIqnLOf0crJMYzjrCxl7S1gAEl8v1iZIwziiSFPZ5AeiW3ZdKVSOMERBIWJJX2xjvWNey1XAsAH16/HdN71b4cqv8BfhEkEzqChLCnPgx6zsACxdxYLdgJMRckA9jxavKDy6bEU/rz2w5+Ma+4wGP+pdrFoZ8GkZCLCd1OVtnABtDnDgyG6EuBfnhcrk+URLGGVkUwj4PERmW1ZdMY8S8orq2dOHJ+NldvScYzEBDrP2Zlm1fn3h7QPLgkyFAnk6B74KeYH0jWMe1I6EQ5MEYCnm1R26eG0/pr+459uKOIyGv9vDK2T5NwVWRQuqtnFkPuxMXMJu7yTwOZTZcLtcnSsI4Q0QRv1cWBd2ye+JJXIsCT9bDlSva0r3tqV4ANjvvdB2qC5XeUTRHJAGfDIJURYHvQPBz+nmwgWslFoBUjK2coPcraxbEM/o7B0/9bvOBgEddu3iaKku4KrmWlPmcfgVgDLF7WH+H5GkgGS6X65MjYfzJC/hVSUpk9O54wnZYFAgjQ6AZWRVrSxc+dfLNlK0DiJnpZ1q2TQgU1QaL8UmyAQEQcK1IhlgISBhzRTnBr92xKJHWdx1v/dWbewIe7bY5k2RRwJWRD+qt0DfBieECm/V3yfsAxHK4XK5PjoTxJy/o02QpntG7Y0ndsryKjBGTBfG2wllHB1vf7jrkMAM4nej6ffOW/zLprizFh08GwxkAaZBqYbfAiQEWRkqDUIBPAgFV+eFv3LXkB8++c6Sl6+d/3BHwKMvqqkSBcCVEymyWamHswnB2E+vbyVsKCHC5XJ8QCeNP2Ov1q0pPPNkdT+iW5VVkXIssxf/Z8qWnEl1nEl0AHHa29BytC5XeX7pAIhGfAII8haQa4n62TiL9ImdeBxsYCdJILMQnhIjqyvK/efeSf3hu06nOvide2+bX1Nk1xQIRrkDIIfUmNg+ADQzhNOtvk7YGQjZcLtcnRML441HkSMB3JtrfHUumDSvbi2tCwKRgyafLFv30+B8TVgZA0tKfbd0+KVg0LauC8AkhBZRPos7OINjCCAlBCDkYCWak00inoWnwekGEG0EgmltT8rU7Fv/oxXdPne39yWtbv7N25eSSPCLCZYmkLuP0OlinMZx5EOYhqMvhcrk+IRLGH02WCoIBALFMpjeRLMoK4BpJJNySP/3oYNvrHftsdgC0paJPN71XPDknRw3gk+JEOfEzNrYCDkaGhAKQByPR3Y0330QqBUXBLbegpAQ3iCgIy+sqExn9n1/ZerDp7E9e3fZfP7WiIj9MuDyxjJTFbDUBDoY4A6y/Tcp8kAaXy/VJkDD+aLJUkh0kopRhtvXHppUU4NoFZe9nypaciJ9tjLUDcJh39p5Y37H3wfKliiBh7HGck//KmfVgEyNFEAtAGq7KcbBnD4hw77147z3s3o38fMgybhBZEtfMmhRL6b/YsHPX8Zafvb7jr+5dVpgdwOWQRuotnHkdTi8ucFjfRt4mSLVwuVyfBAnjj0BUkh3SJCljmq39A8xMRLh2Vf78B8uW/Ljx1UEzBSBtGy+27awNlcwNVxMIY4kznHqO038ApzFC5CP1JqiLQSquyrbR34+iIuTmoqAAJ07AcXBDaYp0/6KpsVTm3zftf+fgSb+mfOPOxeGAF5cj10GeAf1tDOd0sL6FpAmACJfLNeYkjEul4ZBHkdNJs7VvULdsTZZw7UQSludNOTLY+lLbLottAGfTA79req/MG8nXsjB2LM68ycl/gTOIkSMJnjtJWQYIuCpJQkkJjh9HXh4aG1FUBEnCjebXlM+vnBVL6y9sP7x+T0PIq31x1byAR8VHEkKk3cLGdnAaQ9hgfTN57oWQi4/EBmCBPADB5XLdaBLGpYJgIOhR+5Kptv7BtGlqsoTr4pO0B8oWHY93HB5oZoDB+/pOvdy++88qVqqijLHgsL6Dk0/A6cI14QzsKEjBSBBhzhyYJvbtQ0EBFi6EKGIUZPk8X7x1Xjytb9jXuG7rwYBXfWjZTI8q4yMQKQtZqoJ5BMNZDWzUk3YrLuLAGYB5lI3tkKeTthoul2sUSBiXAppSFAo2Rfs7BuKDqUy214PrVebNfah82Q9TfX1GHIDhWK+276kLli7KnUQgjDa7Hel1YB1iMf6TCBLxHwgQAcL7SARE/AciiAABBJIxYrosnykq0srLRUUpCQYJoyU/y//V2xYm0vqWo2f+99v7gh7tngVTFEnEpYQCUpay2QDYGOLEoL8DdQnIg/dxGnYL69vY2ALzCMgjaKsAgsvlGgUSxiWvolRGsredah5MZ5r7Bioi2bheAtHCyMTbi2Y/07LVdCwAPZnY083vlfvzij1hjDYhhwL/NzGDJIDwHwgg/CfCB4gAwn8ggPAB8mLEUun0vvr6cDisqmpRaamIUVQayfr6nYuTGWPfqfan3tjp9yi3zpggiQI+hGRSV3D6BTjduIDZ2EXWKQgRNuuhv8vmLthnwQYA0lZDrILL5RodEsYlRRKrcsOKJCYN43RP3/IJlUS4bh5Rub90QUOsdV/fGQYzuH6g+cXWnV+svsUjKhhV5IVYjjHhnIdRRoSJRZFv3LXkB8++09De87P12wMedVFtuUCED5EmkjKLMxswnHOWE//IThLWKXAcYHyANChLIQTgcrlGh4Txqjo37FeVvmT6RFdvxjI9soyPociT/VD58tZUb3dmEIDpWK+f3TclVLIib6pABNc1IqIZFYVfv2vx489vbu4ZeOK1bT5NmVFRSEQYTghAvQn6e+AUhrDB+hZcSiwiZR5AcLlco0PCeFUazsoN+PuS6eNd0Vha98gyPgYCzQ1X31k093dNm3XHAtCnx3/X/F6FL7/SnwfXtRMEWjSp/Gt3LPqnl95raO3+ySv/P3vwAWdXXeAN//c/7fZeZu6dXjMtk5mUSZ+ENEKJoYhCQJcioO5aVl0XP8vjfkRd31d57M+uC4KKIkQEDISakN4nyfTe7/R25/Z6zvm/7Gh8wksCCSlkkvP9HvzX21cXuB2E4DSUcAWUsUPy4EMQwi8E64ZCobhkOFypzFp1YYqtfXRiNBAc8PpTjHpcGBXLfyJ9UWtg4OhkJwWlQJt/8IWBQ18s2Kjn1FCcP45l1pTnByLx/3z9cG3P0P95/fA3bq3OsJvxLhqF1E/jh2l8H+RxfCiih2oFiAYKheKS4XCl0vBcUarzjaaOQDTePDy2IMtNCMGFSVGbtmRVe8KTw1EvAJHK74zWFxvTbnQvYAkDxfkTOPbmRcXBaOw3O48fbOnVq/mv3Fzq0LQivk9O1FBxhCFxnAsuh/DlUCgUlxKHKxUhpNTtNKpV3nC0eXgsmhS1Ao8LQ0AqLNm3Zix+uvudqJQAEEhGt/YfzNWnlpgyCGa3SCTCsqzL5cLlpVXxdywvD4Sntx5o2VHXaWAPP7Rsl46fqulL0wjWyowRfDiWCEvAOKBQKC4lDlewbLslzWz0hqOtIxOToXCm1YwLxjPcje4Fbf6h3eONMqUAesNjv+/d8/XizQ6VEbNTMBhsaGjw+Xx5eXnFxcUMw+AykEbAGED0AIxa/rMrSMDv215vfOWkXsPkpBodzxytmJ8xMidlUisk8cEYM1EtB+GhUCguJQ5XMLNWXZaW2jQ8NhYItY1MZFrNuBgsgv6u7JW94fGe0CgAmdIjUx1/GTz6mezVapbHrJJIJDo7O48fP24yme6+++7U1FSWZXEZ0CSNvgzGTrS3AyzA2mzLH7rBHhRbdzVO/LGmnCVyOCHIMumdspS6xvHB+GJwc6BQKC4xDlcwFcdVZLq21bWE4omTnuHVRbkCy+KCEaDImLYle+Uv2l/zJyMA4lLylcFjefrU1c4yhhBcsUQRXi8kCRaLLAhDQ0NHjx6NRqOLFy/Ozc0VBAGXDfXTxEHIIcLPBV+MdxFdqqPynuucrYNvD075MWM8qDvQlTknZZJjZJwNEYiwHIwZCoXiEuNwZStzpziN+r7J6VrPsDccTTXqcTGwhFntLO0Kjrw4cCQpiwCm4sHf9+5xa6xzjGkEVyRRxIEDqK8Hy8LpDK9c2djYmJ6ePnfuXJ1Oh/NDQZMgPEDw0Yj9EPsge2n0j4T7JogBwIQ//MaJjqlgBKeIMrO/O2tTebvbFMRZTPu4nTv6vcH/jsfjHMep1WqTyeR0OlNTU61Wq8FgUKvVUCgUFwOHK1uKST83LbVvcrp/ytc2Mp5q1OMi0XHqOzKX9YTGaqa6KCgFOoLDv+3Z9c9Fn0hRm3AF8vlQV4eNG2G3Y+tW3cTE2rVrBUEghOB8SeM0+kcwKYSfCzYdjAHgcB4oTTaA+gCJxt4GX0U0N0kyDrf3v9PQHUskcZreScuJ/jTX3HZCKM7k8Ino//v486EI/o5SCoBl2bS0tOLi4gULFixcuDAnJ0en0xFCoFAoPioOVzatICzOSd/Z0hWMxY/1Di7Pz+JZFheJS2P5TM7qkej0QGQSgEzp4cn2NM+B+3PX6jg1rjTxOGQZZjO0WqhUTCKhUqnwkVCxiUaeBY1TxgIuj/DzwM8jXCEYK4gaIPhgNIxkPWgS75J9NPIHwpcxXM7qsjwVz/3lSHN973AknsSMSILf01W5OFcyCV0qgeK9KDTlC+59+rerNRqtIAiSJMVisenp6bGxMY/H09HRUV9f/8Ybb6hUqkWLFt14443V1dUpKSkMw0ChUJw/Dlc2AlRkulJM+r7J6Zq+wYlg2G024iIhIBXm7C3ZK3/V+ZY/GQGQkMXtQyfSNLZNaQt5hsMVxWKB1YoDB2CxIBqFy4WPSESiDnIIkCGNQhql8SNg9JRxEb4M/DzCzwXrBmMAWJyRNE7FVvwNhdhEo38i+i+bdJrrKwsX5KXtbuzedrSlY2giIUoAanqt3/q5NVsTu3+LMy01CprAKYTLyMy/NZPNxvtQSuPxuM/n6+jo2L9//86dOx955JGCgoItW7bcdNNNdrudEAKFQnE+OFzx3CZjZaa7f2q6b8pXPzDqNhtx8XAMuz61YjDi/bPnUFxOAggkI3/o22tTGVY4ilnC4Mqh0eCGG+jx4/D5yMaNcLnw0cgBmmwAZPxfEmQ/ZD8V2xDbThkr4fLBzwM/j3AFYCwgapyGii2QxvF3NEmjr0JYRFTXEUIcJv3ty+YumZP1xom2F/aeGA/GgjG5acJQuuifVM5qoj9Jo9sh9YKKACFCFRgXzoQQolarU2csW7bs/vvv379///PPP/+d73zn1Vdf/cd//Mfly5erVCooFIpzxuGKpxH4FflZO5o7w/H4ga6+1XNyNAKPi0fHqT6VuWw4OrV3vEWmMoDR6PSTXTsMnKbSkkMIwRWCEKSkjC1YIMuy2+3GRyYNQOzB2dAYpGEqDSN+EIyBsmmEnwt+HuHLwLjA6EFFJOtBIzidPIHwM+CKwLoBsAyTatJmUF+o5nXWnGbOn2d0LNx8581OlxN0PlGtodHtNPYmaBCq5SAqfBiO41wu1x133LFmzZo333zziSee+OIXv/jggw/ee++9NpsNCoXi3HCYDSoyXNl2S9PQ2In+IY/XNyfVgYvKoTbdm7NmPOZv8Q9SUAr0hMae6H7760Wb8w0ugitIT09PIpFwu934iChNNoBO48NJDxW+7gAAIABJREFUkH2QfTTZArKNMjbCFYKfBy6TJk4AFO9BafIEoi8R3YMgqkgk8sILL/zwhz90uVz//uAnrdlz3q7r6hz15rsdhPDg5hB9NlGvp8l6wlfgnBFC7Hb7li1bFi9e/Mtf/vIXv/hFb2/vI488kp6eDoVCcQ44zAYOg25ZXlbryMSIP3iwqz/faWcZgouHAPkG14N563/S/mp/eAIABW30eZ7oevtLc27K0NoJrhSyLEuShI9OAliwGZDGQcOAjA9HQaOQBqk0iPg+EC1oBO9H4zT6EhEWRqXyZ5555kc/+tHy5cv/7d/+raCggGGYkszUUDROKQjB/yAq8OWELwUYnCeGYQoKCh577LH8/Pyf//znwWDwe9/7XkZGBhQKxYfhMBvwLFtdmL2trmUsENrT3rtpXrHDoMNFxRCy0Jb/QN66X3a8Ph7zA5CpfGSyQ8VwXyy8wa2x4irBEc0tRLWCJtuQrKfJBoi9oD7QBM6JCBrA2UjDYvA3294qe/zxn61fv/7b3/622+3GDAPPGmISAn4YDGBZ/A2LDybLCIUgitDrQQgkCSoV4nGwrMlkevDBBw0Gw/dnfO9737Pb7VAoFB+IwyxRmGKvzHS/1dTRPjpR6xleX1pAcJGxhKl2lvgS4ae6d/qTEQAilfZNtLAM+3D+9W6NBVcAvV4vCAIuBNGCzSRsJtRriOyH1E8TjUjWU7EF0jhoGKD4iGQpeqC7edeKFYsfffRRt9uNv0omcfAgOjpAKcrKsHgxOA4fSpbR2Ihjx0Ap0tPhdMLvx7JlOHgQbjdKStRq9Z133hmNRn/4wx9mZWV99atf1Wg0UCgUZ8dhltCrVGuKcg909gXj8bdbupblZerVKlxsKoa/0b3Anww/338gLMYBJGVp91gjgIfyN7g1VoKPUyKayE7LFrRC2BdW69Qsz+KCcGBsYGyErwSNEGmCiq1I1tNkPcR+UD9oEueJ55L33amT9VvS09Lwd+PjqKvDDTdAFPH22ygogNOJDxUK4dAhVFTA7cb27RgZAaXIy0NvL/R6zFCr1XfffXdPT89vfvObhQsXrlu3jhAChUJxFhxmCUKwKDtjTqrjRP9QTe9g68jEopx0XAI6TvWpzOUxSXxp4HBUSgBIytLuscaELD6cvyFL5yAg+JhE/BFPo8foNIamQvlV+SzP4uIgIDpwOsJlQ7WOUB/EfpqsR7KeJlshT4JGAIpzk+qIEc1u0OUgZvxVMAiWRVoaRBGAFArFdDqtVksIwQeIxRCNIjMTNht0OkxOYmQEoojOTpSW4hSj0fj5z3++pqbmv/7rvyorK+12OxQKxVlwmD0cBt3a4rzGodHJcHhHa1d5eqqK53AJGHntPdnVIpVeGTwWlRIAkrK0f7wlJiUeytswx5jGEIKPg8Fm4ASudW9r+fpylU6FS4HwIA4IDiIsAA0TaYyKLUjU0WQjJA9kPyDhQ8g0vgfCYqK5DWDxLpsNsoz6ekgSOC7G8zt27HC5XKWlpXq9Hu8jy3IoFGIJ0ZnNqKtDaioCAbhccDiwYQPefBMsi9Pk5OTcf//9//7v/753797bbruNEAKFQnEmHGYPliHVhTkv1zZ3jk3tbe/dXFFc6k7BpWEWdPfmXMcS8peBYxEpDkCi8rGpzkAy+lD+hgXWXI6wuOwo6LsIQxiOwSVHQPTg9ITLg+p6Qn00cYIG/wPSGD6UHKCRPxJ+HrhCvMtqxdq1aGgAQNetG4/HrVarx+Pp7u6urKzMy8sTBAGnhMPh5ubm3t7eJVVVurVrcfQoWlqwZAnMZgQCsFpRVgaHA6dhGGbdunW/+93vXn755Q0bNhgMBigUijPhMKtkWE1ri/J6J6eHfYG3mjsLnHaBY3FpmAXdZ3NWc4R9aeBoSIwCkClt9Q/+uO2Vz2SvWpM6V8uqcDlR+EZ8Ylycs2zORP+ExWVR69W4PIgA4iSMidIkzgXRg7FQGiGYwbIoLUVhId7FcWJ3d39/v8FgsNlsx48f7+joWLhwocvlEkWxt7f35MmTgiBUVVWlZWSAZeF2g1JwHN5FKVgW8+eDELxXSkrK+vXrn3nmmf7+/rKyMigUijPhMKsILLu+pOCNps7+qeldrd03lxcVpthxyZh43T05q7Sc6vn+A75EGAAF9YQn/k/nG8NR7+0ZS60qA8FlQkF5NZ9VkaW36H2jPhBcXjJN1kMO4IMQMEbwFUR9IxGWgXXg7wiBIAAgQF5ensViqaur6+/vT0tLo5S++eabbrc7Ho+HQqHy8vKCggK1Wk0Iwbt4Hv8/LIv3YVl26dKlTz75ZENDQ1lZGRQKxZlwmG3ynNbrinJ/f7jW4/W/1dyZY7fwLItLxsBpPpW53MRrn+ndMxqdpvgfvkT4uf4D/eGJz+SsLjS4GMLg0iOEmJwmzLBn2nGZyUEk6gERZyJTTPsIr1tucn6KCIvAWAGCs2AYxm63r169emho6MSJE6FQyGq1trS0LFq0aPXq1SaTiRCC85eTk6PX6zs7O2VZZhgGCoXifTjMNiqOu6Gs8J3WrgGv/62mzg0l+XNSHbiUNKxwk3uBmdc93fNOd2hUphRATErsGW8eik7dmbVypaNEx6lwdZNHqdiBM2DBOpvbTT/7VdtD/3jXksx1AME54DguKysrJSWlo6PD4/HceeedqampLMvio9LpdKmpqaOjo4lEQq1WQ6FQvA+HWagwxb62KO/3R+r6vdOvN3bk2K0Cx+JS4hlupbPErjY+3f3OcW9XUpYAyFRuDwz/tG17q3/g9oyl6Vo7QwiuUjTZBHkK78GBdRPVaqLe2Nxfd+BY2+e/bAIIzodarZ47d25xcTHHcYQQXACO4/R6fTgcFkURCoXiTDjMQmqeu6m8aHd7T/+U7+2WzutLC0rcTlxiLGFKTRlfL968tf/gWyMnA8koZviT4ZcGj7YGBj+ZsWyZo0jPqXH1oTEk60Bj+CsigM0i6rVEtQFcPoiaYbsASJKE80cI4XkeF4xSKooiy7KEECgUijPhMDsVpNjXlxT89uCJQa9/e0NbntOq4jhcYgQkTWN9KH99js6x1XNwIDIpUwpAlKVGn8cTnjw53bM5vSpf7+IZFlcTeZommwAKogZXQNQbiGot2EwQATOMRiOl1Ofz4eOTSCR8Pl92djbP81AoFGfCYXZScexNc+fsbuvunvDubO26vrRgXoYLl4WeU29KX5RnSH22b9+xqc6YlMQMfzKyfeh43XTvTe6F61LLU9RmhhBcFajYCdkHYRFR30BUq8C6AA6nSU9PJ4T09fXh4+Pz+cbHxzMzM3meh0KhOBMOs1ae03p9WeGT+2qGfYFX69sKU+0ansdlwRF2rjnrG8W3vDZ04tWhmpHYNKUUgETl/vDEUz07D0223Zy2cJl9jlnQERDMbhREIPqvEmExWCfA4H1SUlJcLldDQ0M0GtVoNPg4tLS0JBKJoqIiQggUCsWZcJi1eJa9oazwnZau9rHJXW3dG8sKFman43IhIA6VcUv2ynJz1p88B2u8XRExjhlxKVk33dsVHNlrab4xbf58S66B1xLMXoQICwEWIDgLi8WyZMmSHTt2DA8P5+Xl4XwkYgmWZQlDxITIq3lCCM5fPB7fu3evzWYrKyuDQqE4Cw6zWbbNckP5nN7d02OB0Lb61mKXU6cScBkJDFdpzc3WO/eMNW0bPNYTGhOphBkhMXZgorXB17fAmrfRPb/cnGXkNQQEsxKHD8QLwsq1q1/a++ae44dycnIYhsE5ohjtHI2H4yqdKhFN5C7IJSzB+evu7t69e/eGDRtSU1OhUCjOgsNsxrHM9SUFO5q7mofH9rX33Vg2Z2leJi4vAlgF/eb0qgpLzvah47vGGififplSABTUn4zsHms66e2ZZ8ne6KqcZ8kxC1oCgqsCBWJSYjzmb/J7jtimnF9evWOsft1gdVZmFs4RgT3LfvLVk2JSrLyhkmEZnL94PP7CCy/EYrFbb71VpVJBoVCcBYdZLsNqunleUffE1GQovK2upSwtxaBW4bJjCZOrT3kof8MKZ/GrgzVHJjv8yQgFBUBBfcnwvvGW2uneUlPGmpS5i2z5dpWRJQxmJ0ppWIqPxXwt/oH66b5m/8BYzBeVErBrOsZHn9v24lcf/KJarca54QSOUirLslqvxvmjlB49enTr1q2bNm2aN28eFArF2XGY5ViGWVec91ZTR93AyIGu/pOe4erCHIKPh5rl51tyC/Suk9M9rw+fqJ3uDSWjFP+DggaSkcOT7fXTfQVGV7WjZLG9MENrFxgOs0RSlgLJyFDU2+z3NPj6OwPDU4lQTErgNIzL8OyzLxdn5t18880sy+LDUEpHOkcMdgPDMsPtw9kV2YQhOB/9/f0/+tGPrFbrAw88oNVqoVAozo7D7OcyGTfNK24fm/SGo3+pbanIcJk0anx8DLym2lkyz5x9zNv51nBto98TSkYp/iYixeun+1r9g68OHV9iL1zhKM43uIy8hoDgyiNROSzGJuOBzuBIW2CoNTA4GJkKJCNJWcKZ6CzGeKr+P37wH1ardfny5QzD4ANRmbIcm1+VTxjiG/HJsswyLM7Z6OjoD37wg/b29scff7ywsBAKheIDcZj9WIZcV5T7ZlNHTd/gkZ6BY72D64rzCcHHiICYBd361HmLrPknvD1vj9Q1+PoCySgFxYyELPaFxz2RyR2j9cXG9MW2wgpLtktj0XIqAoKPVVKWwmJsKhHsC413hUY7AsN94XFfIhyVEhQUZyIwnE1lKDamL7Dmqe9b+4Nvf/exX/3vb7Nk2eKlLMvi7BiWSS9OxwydWYfzMTwy8vh//mrHkZpv/PM/b9iwgWEYKBSKD8ThqpBi1H+iorhlZNwfiW6ra1mYlWbRafBxIyAWQb82de4iW179dP+uscYT3m5vIihTihkylafiwQMTrcemOu0qY7Epfa4ps9SU6dJaDJxGYDhcFklZikqJkBgdiU57whP94Ynu0NhQdCqQjESlhEwpzkLN8naVsciYNs+SU27OcmusOlY1bvcvfeTT7/Sc+PYzP/3S+MTGDddrtVpcVLIst7a2/ugXvzwQEFM/cZdr0XKwHBQKxYfhcFVgCKkuzHmjseNQd39N3+ChHs+NZYWEEFwBCIiJ1610liyw5rYHhveMNx+b6hiOTidlEackZHE46h2OeveNt5h4jVtjKzC4cvUp2TqnS2PRcSo1K/AMS0BwYWRKE3IyLotxKelLhkei0yPR6ZHo9FB0ajAy5U9GImI8IYs4O4YQHadOVZuLjOlzzVmlpowUtVnLCQSEgvaGxn/Ts+sYHRIybVOJ5Ld+/v2G+ob77r03IyODYRhcDIFAYMeOHT/92c+GeL26arUP3E93HRkNRe9YONeu10KhUJwdh6uFXa/dXFHcODQajMa31bYszsmw67W4YhBAx6nnW3NLzRmbI4sOT7YfGG/tDo2FxRgFxSlJWZyMByfjwQZfn8BwOk5l5LUujcWltjjUJofKaBH0ZkGn59QqhucYhiUMQxgCEBDMoKAypTJkmVKJyjEpGRSjoWQ0kIz6k5HJeHAqEZiKBScTQX8iHJUSMSkpUgkfiAAqVjDz2iydo9iUXmrKzNOnWgS9muVxikTlel/fU90766f7JCqDQJuXQtfFn/rDM/v37fvc5z63du1au93OMAw+qkgk0tDQ8Jvf/Obtt98uLy//8he/VBMU32ntGg+Gn9xf0z0x9cCKhXNSHQwhUCgUZ8LhasEQsrwga0FW2t72nlrP8IHOvk9UFDOE4AqjYvg8fWq2znm9q7LJ1394sr3B1z8e80elBN4rIYuJhDidCPeHJwAwhAgMJzAcz3AcYQWG07CCllMJDMcQwhKGgACQqJyQxYQsxuVkXErGpKRIpaQsibKUpKIoSxTnhICoWM7Aa9waa6HBPceYVmhwOdVmPadmCYP3ikvJvePNv+3Z1ReeoKCYoeL4NRtvLJ17+9Ynn/nWt75VWlr6yU9+srq6Oi0tTa1W45xJkuT1emtra1955ZWdO3dqtdovfelLd955p8vlWhuJ5jutfzxaPx4IvdnU0T/le7B6UXVBjprnoFAo3ofDVcSq1WyuKK71DPujsW11rUvzMlOMelyRWMI4VMbrUuYutc8Zi/kbff21071tgcHxmD8ixWVK8T4ypTEpGZOSuGR4htOygpHXpmttOfqUHJ0zz5CaojbrObXAcDiLYDL66lDNc/0HJuMBnKLn1DelLdiSVW2vNKyrWrljx46tW7d+97vftVqtS2eUl5c7nU69Xq9SqViWxWkopYlEIhKJ+Hy+jo6OY8eOHThwoLOz02az3X333bfddlthYSHP8wCsOu0/LJ2f67A+ua+meXi8eWjs+6/t6V7kvWPhXLteC4VC8V4criKEkCW5GVU56TtbuxoGR/Z29H5yQRlDCK5galbI0jkydY61qeXeeLArNNoeGO4MDveHJwLJSESKJ2UJlwZLGBXLa1jBwGlSNeZ0jS1T58jUOdI0ViOv0XIqjrD4QBQYj/me7dv3xvDJkBjDKQ616c7M5ZvSFhl4DYCUlJS7775748aNJ0+efPvttw8ePPj6669zHOdyuXJzc10ul91u12q1giCIohiLxXw+3+joqMfj6evri0QiGo2moqLirrvuWrlyZWZmJs/zOI2K59YU5WVYTE8dOP5Oa/d4IPTk/pruCe/nVi4sTLEzhEChUJzC4epi0mo2V5Qc7x+aDkdfrW9dWZDtMhlwxSOAhhXStLY0rW2Fozgixv3JyGBkyhOZGIp4h6Peibjfl4jE5WRSFpOyJFJZpjLOAUMIR1iOYXnCcgyrYQWroLepjHaVwaEypmosLrXFrjJoOJWWFXiGwzmjlHaFRp/ueefQRFtCFjGDgOTonfflrl3pLFYxPE4hhNjt9g0bNqxatWpqaqq9vb2xsbG9vb2vr6+hoSEYDFJKcYparbbb7enp6VVVVaWlpWVlZS6XS6/XE0JwJgwhc1Id/7pxVa7D9tyx+olA6M2m9gGv78GVi1YUZKt5DgqFYgaHqwsBFmWnL83NfKOpo3lofFdb952L5rEMwezBEsbAawy8Jl1rW4LCpCzFpERMToaSUW8iNJ0IB5KRsBiPSvGIlIiI8bicBEApJCpRgCWMiuEEhhNYXsVwOk5t4NQGXmPgNUZOaxK0alZQMZzA8BzDEnxEIpVOenue6n6n2e+RqIwZLGEqLDkP5K0tN2ezhMGZqFQq94zVq1cnEolwOByLxeLxeCwWSyQSLMuqZ6hUKq1Wq9FoGIbBubHptfcum59rt/x6//GWkbHGwdHvvbb7rqp5n1xQZtNroVAoAA5XHYNGtbmi5FjvwGQo8mp9W3VBTobVhFmLZ1ie0RigcaiMOUjBKRRUorIkyxJkvIuCglKAAWEIYQjDEMKAYQjBxRaTErvGmn7Xu3sgPElBMUPF8qucpffmrMnWOwgIPgwhRDUDF4+a59aV5GdYTb/ef3x3e89YIPTEvmPdE1OfW7ko32ljCIFCcW3jcNUhwPxM1/L87FfrW9tGJna0dH522XyOYXB1ISAcYTmWxeXlT0b+Mnj0T/2HvIkgTjHymk1pi+7MWmFXGfGxYggpcjm/dePqfKftuWP1k8Hw640d/VO+h6urlhdkqTgOCsU1jMPVSK9W3VJZfKTHMxYIbW9oWzUnN89hheLCUNCR6PQf+va+PVIXFuOYQYAUtXlLdvUN7vl6To0rAAHseu19yxfkOqxP7qtpGx1vHBz97mu776oq/+SCMqtOC4XiWsXhKlWe7rquKPeF441d4943GtsfXlXFsywUH5VMaUdw+KnunUenOpKyhBkMIXn61Ptz1y5zFAkMhyuJmufWl+RnWEy/3l+zp7131B/8773Heia8969YmO+0MYRAobj2cLhKaQX+E/OKD3T2D07732jqWFucV+xyQvGRJGWpxtv5dPc7rYFBmVLM4Ag735r7QN7aMlMmQxhceRhCit3Ob924Os9p21rTMBkMb29o75/yPVRdtSw/U8VxUCiuMRyuXiUu5/qS/N8frvVM+bbXt+XarSqeg+I8RaXEjpH6Z/r2DEe8FBQz1KywJmXuP+Rel6G1ERBcqQjgMOjuX7Egz2F9cn9N++hE/eDId7fv2rJ43m3zy6w6DRSKawmHq5eK526eV7S3o7dnwvt2S9fakvz5mW4ozsd0IvTiwJEXBw77EmGcYuJ1t2YsviNzmVXQYzbQ8Pz6koIMq/nX+2v2tPeM+IO/2nOse8J7/4qFeQ4rQwgUimsDh6tavtN2Q1nhE/tqhn2Bl082F6bY9SoBinNAQYci3t/17n5ntCEqJTCDgLg0ls/krNqQWqHlVJg9WIaUuJ3funF1nsO6taZxMhR+tb6tf8r3UPWiZXlZAsdCobgGcLiqCSx7U3nRnvbe5uGxPe09a4vzVhXmEgLFB5Op3BoYeqp7Z423S5QlzGAIKTSkPZC3drGtkGdYzDYEcBp0D6xcmOOwPrX/ePvoRN3A8He37757ScWtlSUWrQYKxdWOw9Uu02q6pbKkZ9I7FY7++URTebrLqtNAcXZJWTw82fF0zzudwWGZUszgGXaRreCB3LVFxnSGEMxaGp7fWFqYZTU/ua9mX2fvsC/wn7uPdI9P3b9iQY7dyhACheLqxeFqxzLMupL8XW3dR7o9x3oH93f2bppXzBACxZmExfhbI7V/6Ns7Gp2m+BsNK6x3VXw2e5VbayUgmOVYhpSmpfzbTavzaqx/Ot44FYq8UtfaNzn98KrFS3IzBI6FQnGV4nANcBp0t80vbRke90djL55oXpidnmY2QvE+U/HgnzyHtg0e9ScjOMUi6G/PWHJ7xlKzoMPVggBOo/7BlYtyHdan9h/vGJusHRh5bPs7dy+uuLWyxKzVQKG4GnG4BjCErMjPXpqX+VZzZ8Pg6GsNbfctX8CzLBSnUFBPePK3vbv2jDXFpCRmEJB0re2zOavXppZrWAFXHY3A31BWmGk1P7m/5kBn39B04D93H+mZ8N63fEG23cIQAoXi6sLh2mDSqj+1cG79wMiIP/iX2pYluZnl6alQzJCo3OT3PNW9s9bbK1IJMxjClBjTH8hbt9CWxxEWVymWYeampz5603XPHav/84mmqVDkL7UtvZPTD6+qWpyTIXAsZsRFiWcZhhAoFLMZh2sDASoz3TfMnfP7wyc9Xt8LxxtzHVa9SsA1YzoRSsqSQ20ieI+ELB6YaP1N9zvd4TFKKWbwDLfUPuf+3LUFBhdDCK5qBEgx6h+qrspzWH+9/3jX+NRJz/Bjr77zmaWVmytKTBq1Pxp78UTTktzMErcTCsVsxuGaoea5WytLjvR4WobHd7V1ryzIXl+STwjBNYCC7htvqff1fT7/eqfahFNCYuy1oRN/7N83EfNT/I2OU210zb87uzpVYyG4VmgF/sa5czJtlif2HjvY1T84HfjFriNd4967l1Qc6xl4cn9Nx9jkt25cbdKooVDMWhyuJTl2yycXlP3vqQPT4ehzx+pL01LSzEZcA0Ji7PBk+5HJDjOvuz9vrZ5TA5iI+Z/3HHx1qCaYjOIUm8rw6czlm9OrjLwW1xiWYcrTUv/Xzdc9d6zhzyeavOHIy7XNDYOj0+GILxLb1dazMDv91soSlmGgUMxOHK4lLMOsLyk40NW/u62n1jPy0snmh6oXqTgOVztPeKI1MBiXk9uHjjvVplvSFw9Hvb/p2bV/vCUuJzGDgGTq7PfmrlntLFOzPK5JhCDVZHh4VVWOw/L0gRPd41PtoxOYEYzF/3i0viwtpSjVAYViduJwjbHptJ9ZUtE+OjE0HfhLbfOCrLSluZmE4ComUfm4t9sbDwEIitHn+vcHkpG66b4GX59EZcxgCVNmzvxc3roKSy5HGFzbtAK/qbzIptP++7adI/4gTukYm3zuaP03rl9pUKugUMxCHK4xhKAyM+22ytIn9tWM+EO/P1yb77A6jXpcvfzJSM1Ul0glzBiP+f/Qt1eUZQqKGSqGX+4ovi9vTZ4uhRACBSDJtHfCG4zFcRpJlt9u6VyYnXZTeRFDCBSK2YbDtUfFsbfOLz3pGT7U7TnaM7CtvvUfls4XOBZXqc7gSHdoFKdJyhJO0XPqm9MW3pW10qE2ESj+pnVk/IUTTeF4Au/li8T+cKSuxO3Mc9igUMw2HK5JqUb9Z5ZWdo1PjQVCf6ppLHWnLM3NIITgiidJUmKGKIqyLFNKCSEMw3AcJ8xgWRanScpSzVRnIBnBmdhVxi3ZK292LzTwGihOk2Iy3Ld8Qa1nuGFwdNgfCMeTlFLMaBkZ31rT+JW1y3QqAQrFrMLhmkQIqcrJuKWy5LcHTw75Ak8fOJ5pNaVbTLjyiKLo9/snJia6u7v7+vqGhobGx8d9Pl8oFIrH47IssywrCIJer7dYLE6nMy0tLScnJzc31+FwGI3GqWTopLdHphRnUmLKuN5VaeA1ULxXqlF/2/zSG+fOmQiGWkYm6gdG6gZG+ianA7G4KMmvN7QvyEpbX5LPEAKFYvbgcK3S8NynFpa3DI8f6Oqv6Rt89kjdP65ZqlcJuDIkEomxsbHa2tojR46cPHmys7PT5/OFw+FEIkEpxVkQQgRB0Ol0FoulsLBwwYIFhqV5HtUEzqJuunfXaOMn0hcJDAfF+6h5LsNqzrCa1xTlTkdinWOTdQMj9QMjneNTW2sailIdWTYzFIrZg8M1zGXSP7Biocfr65/y/aWuNT/FtrmihGMYfKxCoVBTU9P27dt37NjR2dnp9/tlWca5oZTGZ3i93u7u7p17d+V/aaN5TRHOIpCMPNu316E2rnQUM4SB4ix4lnUadE6DbkluZjAWG5gOtAyPTQTDGVYTQwgUilmCwzWMEDI/y/3ZpfN/tvOgLxJ9av/xNLNpcU46IQQfh2g0evz48d///vdvvfXW8PCwKIp4H0IIfwrDMIQQSqksy8lkMpFIJJNJnIaxU3YsAAAbcUlEQVSz64UCB8UHGYv5nu5+x6YylJoyCAgUH4hliFmrMWs1ZW6nKFOGELyfJCEYhCTBYIAg4NyJIoJByDKMRlAKWYZKhVgMHAeeh0JxwThc23iWvbm8qHti6oXjTX1Tvl/tOeo06HIdVlxelNK+vr6nnnrq2Wef9Xg8sizjNGq12mKxpKen5+fnZ2Zmulwuq9VqNBoFQWBZVpKkeDweCAS8Xu/IyIjH4+ns7BwaGvL5fcayDJXTiDMhIALDqVlew6pULN8eGCo0uAWGg+LcEEJ4luD9JAknTqCuDu9yu7FmDbRanAtRxJEjaGkBpcjJgU6HZBKLF2PPHuTkoKgICsUF43DNM2pU9y1fMDQd2N/Zd6J/6L/2HP2X61c6jXpcLqIoHjp06Pvf//7evXvj8ThOUavVGRkZS5YsWbp06fz58zMyMgwGg1arZVkWZyGKYjQaDQQCHo/ncG3NdqYjquLxLkrlhCjFklIkkfSG5OlodXnVhkXVaXp7itpk4DQaTuAZFooL5/fj6FEsXw6HA9u2oacHZWU4F1NTOHEC69ZBq8Wrr0KthiAgIwO9vXA4oFBcDBwUQJrZ9PnVi8eCofaRiZ2tXQ6D7vOrFhs1Klx6oii+/vrrjz76aHNzsyzLmKHT6ebPn3/rrbeuX78+Oztbp9MRQnAOOI4zzEhLS0udm9fX9ooMaoa69UjdiV0Hfb2j8cmgFI7ThKQu6rvle/MWrFvEcRwUF1E0ikQCbjdMJmi1CIVwjsJhUAqXC4IAQUAggLExxOPo7MTChVAoLgYOCoAQzE1L/afrlv7gjT1D04E/n2gyadSfWVqpFXhcSrIs7969+5FHHmlra6OUAuA4rrS09IEHHrjlllvcbjfLsvioUjXmR8vuEBiOBztuX7lNzHi66+mWkUFJkgDUnaz95je/+fOf/7y6upphGCgumCRJPp9PKwgakwlHj8LhQCAgORzeiQm9Xq/RaHAW0Wg0HA5bzWZGpcKxY9BokEjA5UJGBtauxSuvgGWhUFwMHBQzWIasLMyeClf9bOchbzjyu8Mn9Wrh9vllap7DJdPR0fHYY4+1tbVRSgHodLrbb7/9a1/7WmlpKcdxuDAaVtCwAmbkZGf/0z/9U3V19Y9//OOXX345EolQSpubmx977LEnnngiPz8figtAKZ2cnDx+/HgoFFq9apXmhhtQUwOPB2vXiqmptQcPer3ehQsXZmdncxyH0ySTyd7e3pMnT6akpCxftky44QacOAG/Hxs2gGWRSMBoRGUlnE4oFBcDB8UpAsveXF4UiMaf3HdsOhz9773HeJbdPK9YxXO4BKLR6FNPPXX06FFKKQCDwfCFL3zh61//utPpxCXAcdz8+fMff/xxp9P55JNPhkIhWZYPHjz429/+9tFHH1Wr1TgllhSnwhGLVqMVeCjORBblsd4xnVkniVIilojQyP4D+91u97p168xmMwiB2w1KQYiKkJUrV7a3tx86dKilpaWqqsrpdDIMI8vy6OhoTU2N3++vqKgoLCwUVCpkZyMrC5SCYUAp3kUIKipACBSKi4GD4jRagf/0ornBWPzZo3UTwfB/7j7CELKpvEjFc7jYWlpaXn755WQyCUAQhHvuueeb3/ymzWbDu/x+BINwuTAxAZ4Hz6O3F4kEMjPhdIIQnAtK4fOhtxeUIjsbVisISU1NfeSRRwKBwDPPPJNMJhOJxIsvvvjpT3967ty5SUmaDEWahsYOdvX3TU4/cuOqolQHFGdCGCLGxbaDbYSQzLJMm8N2ww032Gw2hmHwV4SAEMzQaDTz5s3Lzc2tra19/fXXc3Jy8vLyuru7e3p6CgsL16xZo9frCSH4K0JACN5FCP6KECgUFwkHxXsZ1Kr7ls9PStLWmoaxQOgXuw6Lkry5sljD87h4ZFneu3fvwMAAZpSXl3/5y1+22Wz4q95etLfj5ptRUwONBsEgAgFotWhsxCc+Absd5yISwZtvQpbBMGhtxSc+AaMRgNPp/MpXvnL8+PH6+noAff39b+7eE9AYj/QMHO0d6JucDsUTdr1WlGQozoIwxJ5lbz/Urrfobek2TsXhAxFCjEbjypUr58yZs3///l27dlVVVW3atMlutzMMA4XicuGgeB+zVvO5lYtkSl843jgeCP1y9+GYKH5yQZleJeAiiUQidXV1iUQCAMdxmzZtys/Px98lEmhrg8GApiZkZGBiArfdBrMZzz8Pjwd2Oz4MpZSMjWF0FFu2gOPw7LMYHYXRiBlFRUU33nRTa1c3a7Zqswu29k785c9v+CIxmVLMSIjSif6hyVAY1ySbXluc6uRYBmdBKfWN+jQGDRiEfCFzihnngGGY1NTU6urqYDC4YsUKi8UCheLy4qA4E6tO83B1lcCyzx2rnwpFfrXnqD8S/czS+VadBhdDLBYbGRnBDL1eP2/ePI7j8HeEgGHAsmAYEIJ3SRJkGbIMhqGUAiCE4EwopX6/f3x8PE0UdZRCliFJoBSEYAaldCwUJbnFaZu3MPZUTmcIs2w4HMVpArH4L3YdZhkG16Tqguxvb1pjYFU4i2Qs6Rv1FSwtiIfi3kGv0W5kWAbnhmVZnucZhoFCcdlxUJyFRad5YOVCFc/94UitLxJ75nDtdCT2uZUL08wmQnCBKKWiKGIGwzCCIOB0goA5c7B8OZJJ6HQwm/HOO1CpoNPRjAyPxzM9PZ2fn6/X6/FekUiko6OjtbXVbrc7y8poZiZ54w0QgpQUuFyYIVE67AtMSERwuqHREpbF+1BKw/EErlWRRILig/AqPm9hHq/iqUxFUSQMgUIxG3BQnJ1Jo7532XyjWvXr/cfHg6GXTjaPBUJfvG5JqdvJEIILIAiC1WrFjEgk0tvbSyklhOCv8vLgdkOjwdKl4DjwPIaGkEzC5YLJpEom+/v729vby8vLc3NzVSoVgGQy2dfXV1dXRylNSUnx+/2eiYmy9evJ6CgohdsNnQ4zOIZZkOXeE5p4/qXf8e4sbXa+MTOXqDWSTHGKVuCvLy10GHS4JuU5rCqOxdkRhggaAQBhiMAJUChmCQ6KD6RTCXcsnGvSqn+151jf1PS+jt6JYPjhVVUrC7LVPIePSqfTFRcXMwwjy3IsFnvrrbfuuOMOh8OBv9LrodfjXTYb/qqgADMIkJKSsmHDhu7u7vr6+vb29srKSpZl6+rqfD6fy+UKh8ODg4P5+fk5OTmMwQCTCe8zPjb2zltvBD29GOgLN5+86StfK1pZfbRnoHdyOhiLy5TqVMKdVeVlaSm4JhGAEAKF4qrDQfFh1Dx349w5Dr3ul7uP1A+MtAyPff+13VsWz7t9QZlNp8VHwnHcihUrbDbbxMQEgL179/7pT3968MEHBUHAhyGEaDSa0tLSzMzM1tbWt99+e2JioqyszOFwDAwMuN3ujRs32mw2lmVxJrFY7Lnnnjt06BDeRalVr/v0muqV1UvvqprXPDx+uLu/pm8wlhQZQhhCoFAoriIcFOeAY5jFuRk2vfbX+2t2tnaPBUL/vfdYx9jkfcsXFKU6WYbg/C1atKi6uvqll16ilPr9/scff9zhcGzevFmlUuEcEEKMRuOiRYvy8vIaGho8Ho/JZFqzZo3b7eY4DmcRi8VeeOGFn/70p6FQCADDMGvWrKmsrORYJsWoTzHql+dnjgVCnWOTKUY9FJcAy7Jms5llWSgUlx0HxblhCClMsX9z46osm2VrTcNkMPxmU0fPhPezS+evKc4zqlU4T1ar9Qtf+MLJkyd7e3sB9Pf3/+u//uvk5ORdd91lsVhwbhiGsdvty5cvLy8vNxqNgiDg7Lxe77PPPvujH/1oYGAAM3Jzcx9++GGTyYRTVByXaTVnWs1QXAKxUAxxVC2sSgQToiByAgeF4jLioDgfdr32/hULCpy2pw+eaBoaax2Z+H/e2Huif+ieJZX5ThvLEJwzQsiKFSu+8pWvfOc735menqaU9vX1PfrooydOnHj44YfLy8vVajXOjWoGzi4Wi9XW1v7qV7965ZVXfD4fZtjt9q997WuLFy8mhEBxWcRCMU+9R2vWJiIJ3WIdJ3BQKC4jDorzpOH5dSX5OXbL7w7X7mjp9EdjL9e2tIyM31U1b21xnlmrIThXKpXq3nvv9fv9P/vZz7xeL4Dp6enf/e53+/fvv/XWW2+77bbi4mKDwUAIwUdCKQ0EAs3NzS+++OK2bdv6+vokScIMu93+jW9845577hEEAYrLxWA38Cq+80jn/JvmCxoBCsXlxUFx/hhCClLs/3L9yooM1x+O1HWNT7UMj//wzX2Huz1bFs8rS0tVcSzOjclk+upXv2oymX7yk594PB5KqSRJnZ2dP/7xj59//vnly5evWbOmqqoqLS3NaDTyPI9zkEgkgsHgwMDA0aNHd+3adfjw4ZGREVEUMYMQkpOT841vfOOee+4xGAxQnIVMqT8amwiGM61mNc/hYpBFWUyKglqQRAkUIFAoLicOio/KpFHfWllS4nI+X9Owo6XTF4m92dTRODh607yizfOKM6xmliE4B0aj8eGHHy4oKPjJT35y8ODBaDQKQBRFz4xt27Y5nc6ioqLS0tKCgoKMjAy3220ymQRBYFmWEEIplSQpkUj4fL7h4WGPx9PZ2dnc3Nze3j4+Ph6NRnEarVZbXV39ta99bdWqVYIgQPE+lNJwIunx+o71DB7q7p8Ihv/XzdfNz0rDBaOUTg1NMSxTtLLIO+i1uq0aowYKxWXEQXEBWIYpcTv/5fqVVTnpzx2tbxoeG5j2P7X/+KGu/tvml64pyrPrtYQQfBi1Wr1x48aysrKtW7c+99xzLS0t8XgcMyKRSN+Mt956S6VSabVatVqt0Wj0er1KpWJZVpKkeDweDAZjMyKRSDwep5TivdRqdUlJyd133/2pT30qLS2NEALFaSgQSyRHAsHa/uGDXf0Ng6MToXBClDiGOdwzMC/DxTIMLpjBajDYDGq92mA3sAILheLy4qC4YAa16sa5c+ampb5S37q9vm1w2t8wONo97n2ntfv2BWVLcjOMGjXBh2AYJjMz86tf/eqmTZtee+217du3NzQ0+Hw+WZYxg1Iam4HzwTCMxWIpLS3dvHnzzTffnJuby3EcFKeJJcWxQKhxaPRwt6duYGTEH4wmkgBYhrHrdUUuR67DKlOwuFCEEJ1FhxkmpwkKxWXHQXExMIRk2cwPV1etLMjeWtOwt6PXF44e6OxrHBpdkpt5S2XJ/Ey3Qa3Ch+F5vqioqKCgYMuWLcePH9+7d+/Ro0e7u7v9fn80GqWU4hwQQjQajdlszs/PX7JkyapVqyorK51OJ8uyUJwSTSbHAqGGwdHjfUN1nuFhfzAST1CAIcSs1eQ7rYtzMqpyMgpSbCaNmiEECsXsx0Fx8QgcW5HhynNY1xbl/flk04m+IV8k9lZzZ03f4PL8rE3ziuelp+rVKoIPwbKsy+XatGnT9ddf7/V6e3t7W1pa2tvb+/v7BwcHJycnI5GIKIqyLFNKCSEMw3Acp9VqHQ5Henp6dnb2nDlzSkpKsrOzLRaLIAhQzKCUhhPJMX+wcWjsRP9Q3cDIsC8QTSQpQAgxqFUZVvOi7LQleZklLqdFp+EYBgrFVYSD4mIzqFVri/MqMt37Onr/UtvSNDw2FYq8Wt92qMuzNC/jxrlz5memGTQqgg8nCELqjKVLl4qiGIlEotFoLBYLBoOhUCiRSEiSxLKsIAgGg0Gv16vVao1Go9VqOY6D4hSZ0mAsPjQdqB0YPtk/3Dw8NhEMRxNJChBC9GpVhsU0P8u9ODejxJVi12sFjoVCcTXioLgECCF2vfaWypKleZm723pebWhtG5mYDIW3N7Qf7PIszk2/oWzOgqw0i1ZNCMG54TjOOAOKc5MQJV801jfprfWM1HqGO8YmveFIXJQAMIQY1Kp0i2l+lrsqJ6PE7bTrdSqOhUJxVeOguGQYQlwmw6cXlVcXZu9p73m9saNtdMIbjrzZ1HGoy1OR4dpYVrg4N8Nh0HEMA8XFIFMajifGAqGWkfHGwdHGobFBr98fjYmyDIBliEWrybZbKjNclVlpxS6HXa9TcSwUimsDB8UlxjIk3WK6q6piTVHevo6+1xrbW0fG/dHY3o7e4/1D+U7bmjm51XNysm0WNc9Bcf4oEE+Kvkisd9LbODTaNDTWPjo5GQpHk0lK8S6BZVOM+nynrSLDVZHpLkyxW7RqnmWhUFxjOCguC5YhbrPxU4vmXleUe6jb82ZTR/3ASCAWqx8YaRkef6m2eWle5nVzckvcKRatmmUYKD4QBeJJMRCNDUz720YmWkcn2kYmhv2BYDQuyjIAhhCdSuU06IpSHfMyUudluDKtZqNaxTIMFIprFQfFZcQQkmLU31JRvKow50T/0M7WrprewfFguH/KN+D1v9XUWZBiX5KbsSQ3I89pM/x/7cFbaxznGQDg9zvOaWfPJ63lleVV4jhx7dSpLra2C8EmNCFggn3hi/yu/ADfFQKBIAhEYFm0jSBtbarIpZJV2ZIsSyvvzGp3Z3bO8zVdCCSQpE1pY6/1PY/CEUIgfUMABFE88IOnR4P1g2dre531g+5+fzDwgzBOYIxTUjGMZjF/4WT9/PTUa/VKOaPrnCGEQJKOPQrSzw4hVDS0a6/P/brV3Oh0l9a3fv/w8Xa31xt5Xz7avbe997s/rZ6frs+fmn6z2WgWc6aqYITgWErSdBRGfc/fsfsPO92Hh9bDTne/Pxx4QRDHMEYJLuhaxTRem6r84kT93InadCGX0xRGCEiS9C0UpOcEARgK/2Wzce5E7cbFc18+2v3Dw+3VvQPLcTsDZ/Fvm8sbj4qGfqZWvjjTePNk41Qpn9NVhVJ4qaVCeFHkBuHhwN3q2lvP7K1n9qNuz3JGThBGSQJjFOO8rlbMzKu10tmp6mv1ymy5kNc1jTGEQJKk70VBet4YITOlfLOY++25Vx917ZWt3ZV/7Gx2rL7nH/SHB/3hH/+xnVPVE4Xs643qG43a2alqPZvJqFyhFCZfnKReFLlBeDh0t62jbau3bR09tnqHA9cJAi+KhRAwxggp6Fo5o8/VymenKmfrldlyMa+rOmcIIZAk6d+hIL0YEEKmqpyfnnqjUbt58dzmoXVv5+lftvceHlo917PckeWOvnpyoDCa19TpYm6uWpqrlOaqpelizlS4xhkjBF54UZJ4UeyH0ZHn7/eHT+z+bq//pNff6w0sd+QGoR/FqRAwhhHSOcsofCpnzlVLr9TKr1RLzWI+r6saZxghkCTpp6AgvWAIxqWMXsrovzo1PfD9bevor7v7X+0drB90D4eOG4QHA+dg4Pz58R6nJKPwoqFPF3LNYu5kMd8s5hr5bFZTVUZVShklCJ6PJBVhEodxEsSJ4wddxz0cup2Bc9Af7veH+/2h7XpeGHlhFCYJfAMjpDJqKLxk6KfKhdOV4ulycbZSqJpGRlEURhFIkvTfoyC9qAhGBV0r6NqF6foojGzX2zy01p52/r7/7FHX7o08Jwht17Ndb/PQAgBOiMaZzlnR0GvZTD2bqWUzJVMv6nrR0PK6pnFKMaEEU4wpwRRjjBD8dKkQSZrGaZqkIk7SOE2jJPHCaOAHfc8/Gvm2O7Ldke16ljPqOqPeyPOjyI/iIE6SNIVvYYTkNFXnrGIazWK+WcrPlPIzpULNNDKqonOGEQJJkv5HKEgvPISQoXBD4SeLud+8esoNo6ORt20dbR5am4fWY6vX6TtOEI7CqO/5fc/f7w8fPO0AAEaIU8Ip4YQqjGRV1VSVjMJNlWcURVeYSqnCqEKpQikjmGKMEGCECUYAEKepECIVIk5FlCRhnARxHMRJEMWjMByFkRuEbhi5QTDwglEYRUkSJWmYJFGcxGkK34UR4pSYqqJzVjL0qbw5lTOnC7npQvZEIZvXNJ0zjTOMEEiS9P9BQZooBOOsqmRVpVnMX5475cfxKAiPPO9Jb7BjHz2x+0/7w4P+0HY9L4yCOA7jxI9igAAA9mAA34UA8NcQIhj9CwACBAgQQgAghAABAoQQkAqRCpEKkaapgB9DMGKE6ArnhKiMFgytahpVM1MxjWo2U89m6rlMVlVVRjXGKMEgSdLPhYI0sRACjVGN0VJGb1VKABAliR/FfhQP/eBw6B4OHMsd2a7Xcz17NDoa+UM/8MIoStI4TZJUJGmaCpEIkaRCiDQFAQIEgBACANDXABACBOhrBCOGMEYUY0wwohhTjDklhsKzqpLV1JymZlUlr6sFQysaesnQ87qqMaYwqlLKCEEIJEl6jihILxFGCCPEVJWKaZyuFGEsSUWUJGGchEkSp2kYxU4QukHohmEQJ0EUB3Hsx0mcJEkqUiFSIZI0BQCKMUKIYEQQooQolHBKFUoURnXGDIXrnKmMUkIYwQwTSjAjhGAEkiS9kChILzuCEcFUZRQkSTreKEjSpBkOhw8ePLh48SLnHH5AEATLy8u7u7s3btzIZrOrq6tra2utVmt+fh5jfO/evZ2dnWvXrmWzWRiL43h1dXVjY2NmZmZ+fp5Smqbp6urq2tpaq9Wan5+nlIIkTTgKkjRp1tfXP/roo+vXr7/33nuaprmua1lWmqYAoOt6uVzGGDPGzpw5s7S01O/3oyhaWFi4dOnSnTt3qtWq7/tLS0uqqn722WfXr19XVRUAkiRhjJ0+fXphYWF2drZer1uWtbCwcOnSpTt37lSr1Var5bru8vJyEATtdrter4MkTRoKkjRpisXi7OzshQsXOOcA0Ol0VlZWoigCgGazefnyZc45xrharWYyGQCwLItz3m63NzY2dnZ2stnszZs3q9Xq/fv3Xdd1HMf3/VqtVi6XP/30U4yxoigAYFkW57zdbm9sbOzt7bVarf39/fv377fbbd/3QZImEAVJmjSapuXz+VqtRgiB/4CiKGEYOo7jeZ5pmm+99RaMXb58OY7jlZWVTqdz9epVznm73f7444+73S5CiFIahqHjOJ7n6boOANVqdX5+fmdnRwgxMzODEAJJmigUJGnSGIZBKV1cXHz33Xc1TavValeuXEnTFAB0XaeUAkAURV988cXW1tbi4uL777/faDRu377NOZ+bm4NvoZReuXIFABzH+fzzz23bLpfLhJBPPvnknXfeaTQat2/f5pzPzc0BgO/7vV7Ptu1KpQKSNIEoSNKkMU3zww8/9H2fcw4Axhh8FyHk/PnzrVaLUloqlW7dumXbdi6XM00Tvo9hGG+//bbrurlcTtf1Dz74wDTNW7du2bady+VM0wSAcrl89erVMAxLpRJCCCRp0lCQpEmDECoUCvCjMMaVMRhjjOm6Dj8MIVQYg7F8Pg8A+hh8A2NcLpdBkiYWBUmSJOl4oCBJkiQdDxQkSZKk44GCJEmSdDxQkCRJko4HevfuXZAkSZJednfv3v0nPnQ+moLOC54AAAAASUVORK5CYII=", - "text/plain": [ - "1020×1012 Array{RGB{N0f8},2} with eltype ColorTypes.RGB{FixedPointNumbers.N0f8}:\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fd2 = getfluxdiagram(ssys2,1e-3;speciesratetolerance=1e-4)" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "id": "379c4050", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "1056×916 Array{RGBA{N0f8},2} with eltype ColorTypes.RGBA{FixedPointNumbers.N0f8}:\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " ⋮ ⋱ ⋮\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,0.933) … RGBA{N0f8}(1.0,1.0,1.0,0.933)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fd3 = getfluxdiagram(ssys3,1e-3;speciesratetolerance=1e-4)" - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "id": "007de25f", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "930×750 Array{RGB{N0f8},2} with eltype ColorTypes.RGB{FixedPointNumbers.N0f8}:\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fd4 = getfluxdiagram(ssys4,1e-3;speciesratetolerance=1e-4)" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "id": "977f11cd", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "952×750 Array{RGBA{N0f8},2} with eltype ColorTypes.RGBA{FixedPointNumbers.N0f8}:\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,0.733) RGBA{N0f8}(1.0,1.0,1.0,0.733)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fd5 = getfluxdiagram(ssys5,1e-3;speciesratetolerance=1e-4)" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "id": "6eaab3dd", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "883×753 Array{RGB{N0f8},2} with eltype ColorTypes.RGB{FixedPointNumbers.N0f8}:\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fd6 = getfluxdiagram(ssys6,1e-3;speciesratetolerance=1e-4)" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "d82e3be4", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plot_composition_comparison (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# function plot_composition_comparison(solutions, t, tol, exclude, x_labels)\n", - "# # Prepare data storage\n", - "# species_dict = Dict{String, Vector{Float64}}() # To collect mole fractions for each species\n", - "\n", - "# # Iterate through each solution\n", - "# for (idx, bsol) in enumerate(solutions)\n", - "# # Get mole fractions and species at the specified time\n", - "# mole_fractions = molefractions(bsol, t)\n", - "# species = bsol.domain.phase.species\n", - "\n", - "# # Filter species based on threshold and exclusion list\n", - "# for (i, mf) in enumerate(mole_fractions)\n", - "# species_name = species[i].name\n", - "# if mf > tol && !(species_name in exclude)\n", - "# # Initialize vector for each species if not already present\n", - "# if !haskey(species_dict, species_name)\n", - "# species_dict[species_name] = zeros(length(solutions))\n", - "# end\n", - "# # Assign the mole fraction for the current solution\n", - "# species_dict[species_name][idx] = mf\n", - "# end\n", - "# end\n", - "# end\n", - "\n", - "# # Convert species data to arrays for plotting\n", - "# species_names = collect(keys(species_dict))\n", - "# num_solutions = length(solutions)\n", - "\n", - "# # Sort species for each solution based on mole fractions (descending order)\n", - "# sorted_species = sort(species_names, by=name -> -maximum(species_dict[name]))\n", - "\n", - "# # Plotting each solution individually\n", - "# clf() # Clear the current figure\n", - "# bar_positions = 1:num_solutions\n", - "# width = 0.35 # Width of each bar\n", - "# color_cycle = get_cmap(\"tab20\", length(sorted_species))\n", - "\n", - "# # Initialize bottom values for stacked bars\n", - "# bottoms = zeros(num_solutions)\n", - "\n", - "# # Plot each species, stacking from the highest mole fraction down\n", - "# for (color_idx, species_name) in enumerate(sorted_species)\n", - "# # Get the mole fractions for the current species across solutions\n", - "# current_data = species_dict[species_name]\n", - "\n", - "# # Plot bars for the current species\n", - "# bar(bar_positions, current_data, width, bottom=bottoms, color=color_cycle(color_idx), label=species_name)\n", - "\n", - "# # Update the bottom values for stacking\n", - "# bottoms .+= current_data\n", - "# end\n", - "\n", - "# # Formatting the plot\n", - "# xticks(bar_positions, x_labels)\n", - "# ylabel(\"Mole Fraction\")\n", - "# legend(title=\"Species\", loc=\"upper right\", bbox_to_anchor=(1.2, 1))\n", - "# title(\"Liquid Phase Composition at t = $t\")\n", - "# tight_layout() # Adjust layout for better appearance\n", - "# end\n" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "id": "b1829469", - "metadata": {}, - "outputs": [ - { - "ename": "MethodError", - "evalue": "MethodError: no method matching plot_composition_comparison(::Vector{Simulation{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, SparseArrays.SparseMatrixCSC{Float64, Int64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Sundials.CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}, Vector{String}, ReactionMechanismSimulator.var\"#F#675\"{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, SparseArrays.SparseMatrixCSC{Float64, Int64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Sundials.CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Matrix{Float64}, Matrix{Float64}}}, Matrix{Float64}, Vector{Species}, Vector{ElementaryReaction}, Vector{Float64}}}, ::Float64, ::Float64, ::Vector{String})\n\nClosest candidates are:\n plot_composition_comparison(::Any, ::Any, ::Any, ::Any, !Matched::Any)\n @ Main ~/Work/Electrocat/CO2_RR_RMG/CO2_Reduction_Ag/jl_notebook_cell_df34fa98e69747e1a8f8a730347b8e2f_X26sdnNjb2RlLXJlbW90ZQ==.jl:1\n", - "output_type": "error", - "traceback": [ - "MethodError: no method matching plot_composition_comparison(::Vector{Simulation{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, SparseArrays.SparseMatrixCSC{Float64, Int64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Sundials.CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}, Vector{String}, ReactionMechanismSimulator.var\"#F#675\"{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, SparseArrays.SparseMatrixCSC{Float64, Int64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Sundials.CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Matrix{Float64}, Matrix{Float64}}}, Matrix{Float64}, Vector{Species}, Vector{ElementaryReaction}, Vector{Float64}}}, ::Float64, ::Float64, ::Vector{String})\n", - "\n", - "Closest candidates are:\n", - " plot_composition_comparison(::Any, ::Any, ::Any, ::Any, !Matched::Any)\n", - " @ Main ~/Work/Electrocat/CO2_RR_RMG/CO2_Reduction_Ag/jl_notebook_cell_df34fa98e69747e1a8f8a730347b8e2f_X26sdnNjb2RlLXJlbW90ZQ==.jl:1\n", - "\n", - "\n", - "Stacktrace:\n", - " [1] top-level scope\n", - " @ ~/Work/Electrocat/CO2_RR_RMG/CO2_Reduction_Ag/jl_notebook_cell_df34fa98e69747e1a8f8a730347b8e2f_X30sdnNjb2RlLXJlbW90ZQ==.jl:3" - ] - } - ], - "source": [ - "# sims_collection = [ssys1.sims[1], ssys2.sims[1], ssys3.sims[1]]\n", - "# x_labels = [\"Ag111@-2.0V\", \"Ag111@-1.5V\", \"Ag111@-1.0V\"]\n", - "# plot_composition_comparison(sims_collection, 1e-3, 1e-3, [\"H2O\"])" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "id": "51c99d48", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.9.1", - "language": "julia", - "name": "julia-1.9" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.9.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/CO2RR_RMS/Ag/CO2RR_RMS.jl b/CO2RR_RMS/Ag/CO2RR_RMS.jl new file mode 100644 index 0000000..7976657 --- /dev/null +++ b/CO2RR_RMS/Ag/CO2RR_RMS.jl @@ -0,0 +1,397 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,jl:percent +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.17.2 +# kernelspec: +# display_name: Julia 1.9.1 +# language: julia +# name: julia-1.9 +# --- + +# %% +using DifferentialEquations +using ReactionMechanismSimulator +using PyPlot + +# %% +outdict1 = readinput("chem43_Ag.rms"); +outdict2 = readinput("chem43_Cu.rms") + + +# %% +liqspcs1 = outdict1["gas"]["Species"]; +liqrxns1 = outdict1["gas"]["Reactions"]; +surfspcs1 = outdict1["surface"]["Species"]; +surfrxns1 = outdict1["surface"]["Reactions"]; +interfacerxns1 = outdict1[Set(["surface", "gas"])]["Reactions"]; +solv1 = outdict1["Solvents"][1]; + +# %% +liqspcs2 = outdict2["gas"]["Species"]; +liqrxns2 = outdict2["gas"]["Reactions"]; +surfspcs2 = outdict2["surface"]["Species"]; +surfrxns2 = outdict2["surface"]["Reactions"]; +interfacerxns2 = outdict2[Set(["surface", "gas"])]["Reactions"]; +solv2 = outdict2["Solvents"][1]; + +# %% +sitedensity1 = 2.292e-5; # Ag111 +sitedensity2 = 2.943e-5; # Cu111 +AVratio = 1.0e5 + +# %% +initialcondsliq = Dict(["proton"=>10.0^-4,"CO2"=>10.0^-3*10^3, + "V"=>1.0,"T"=>298.15,"Phi"=>0.0,"d"=>0.0]); +initialcondssurf1 = Dict(["CO2X"=>0.4*sitedensity1*AVratio, + "CHO2X"=>0.1*sitedensity1*AVratio, + "CO2HX"=>0.1*sitedensity1*AVratio, + "OX"=>0.1*sitedensity1*AVratio, + "OCX"=>0.1*sitedensity1*AVratio, + "vacantX"=>0.1*sitedensity1*AVratio, + "CH2O2X"=>0.05*sitedensity1*AVratio, + "CHOX"=>0.04*sitedensity1*AVratio, + "CH2OX"=>0.01*sitedensity1*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-1.5]); +initialcondssurf2 = Dict(["CO2X"=>0.4*sitedensity1*AVratio, + "CHO2X"=>0.1*sitedensity1*AVratio, + "CO2HX"=>0.1*sitedensity1*AVratio, + "OX"=>0.1*sitedensity1*AVratio, + "OCX"=>0.1*sitedensity1*AVratio, + "vacantX"=>0.1*sitedensity1*AVratio, + "CH2O2X"=>0.05*sitedensity1*AVratio, + "CHOX"=>0.04*sitedensity1*AVratio, + "CH2OX"=>0.01*sitedensity1*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-1.0]); +initialcondssurf3 = Dict(["CO2X"=>0.4*sitedensity1*AVratio, + "CHO2X"=>0.1*sitedensity1*AVratio, + "CO2HX"=>0.1*sitedensity1*AVratio, + "OX"=>0.1*sitedensity1*AVratio, + "OCX"=>0.1*sitedensity1*AVratio, + "vacantX"=>0.1*sitedensity1*AVratio, + "CH2O2X"=>0.05*sitedensity1*AVratio, + "CHOX"=>0.04*sitedensity1*AVratio, + "CH2OX"=>0.01*sitedensity1*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-2.0]); +initialcondssurf4 = Dict(["CO2X"=>0.4*sitedensity2*AVratio, + "CHO2X"=>0.1*sitedensity2*AVratio, + "CO2HX"=>0.1*sitedensity2*AVratio, + "OX"=>0.1*sitedensity2*AVratio, + "OCX"=>0.1*sitedensity2*AVratio, + "vacantX"=>0.1*sitedensity2*AVratio, + "CH2O2X"=>0.05*sitedensity2*AVratio, + "CHOX"=>0.04*sitedensity2*AVratio, + "CH2OX"=>0.01*sitedensity2*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-1.5]); +initialcondssurf5 = Dict(["CO2X"=>0.4*sitedensity2*AVratio, + "CHO2X"=>0.1*sitedensity2*AVratio, + "CO2HX"=>0.1*sitedensity2*AVratio, + "OX"=>0.1*sitedensity2*AVratio, + "OCX"=>0.1*sitedensity2*AVratio, + "vacantX"=>0.1*sitedensity2*AVratio, + "CH2O2X"=>0.05*sitedensity2*AVratio, + "CHOX"=>0.04*sitedensity2*AVratio, + "CH2OX"=>0.01*sitedensity2*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-1.0]); +initialcondssurf6 = Dict(["CO2X"=>0.4*sitedensity2*AVratio, + "CHO2X"=>0.1*sitedensity2*AVratio, + "CO2HX"=>0.1*sitedensity2*AVratio, + "OX"=>0.1*sitedensity2*AVratio, + "OCX"=>0.1*sitedensity2*AVratio, + "vacantX"=>0.1*sitedensity2*AVratio, + "CH2O2X"=>0.05*sitedensity2*AVratio, + "CHOX"=>0.04*sitedensity2*AVratio, + "CH2OX"=>0.01*sitedensity2*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-2.0]); + +# %% +liq1 = IdealDiluteSolution(liqspcs1,liqrxns1,solv1,name="liquid",diffusionlimited=true); + +liq2 = IdealDiluteSolution(liqspcs2,liqrxns2,solv2,name="liquid",diffusionlimited=true); + +surf1 = IdealSurface(surfspcs1,surfrxns1,sitedensity1,name="surface"); + +surf2 = IdealSurface(surfspcs2,surfrxns2,sitedensity2,name="surface"); + +domainliq1,y0liq1,pliq1 = ConstantTVDomain(phase=liq1, + initialconds=initialcondsliq,constantspecies=["proton","CO2"]); + +domainliq2,y0liq2,pliq2 = ConstantTVDomain(phase=liq2, + initialconds=initialcondsliq,constantspecies=["proton","CO2"]); + +# %% +domaincat1,y0cat1,pcat1 = ConstantTAPhiDomain(phase=surf1, + initialconds=initialcondssurf1); + +inter1,pinter1 = ReactiveInternalInterfaceConstantTPhi(domainliq1, + domaincat1,interfacerxns1,298.15,AVratio*1.0); + +# %% +domaincat2,y0cat2,pcat2 = ConstantTAPhiDomain(phase=surf1, + initialconds=initialcondssurf2); + +inter2,pinter2 = ReactiveInternalInterfaceConstantTPhi(domainliq1, + domaincat2,interfacerxns1,298.15,AVratio*1.0); + +# %% +domaincat3,y0cat3,pcat3 = ConstantTAPhiDomain(phase=surf1, + initialconds=initialcondssurf3); + +inter3,pinter3 = ReactiveInternalInterfaceConstantTPhi(domainliq1, + domaincat3,interfacerxns1,298.15,AVratio*1.0); + +# %% +domaincat4,y0cat4,pcat4 = ConstantTAPhiDomain(phase=surf2, + initialconds=initialcondssurf4); + +inter4,pinter4 = ReactiveInternalInterfaceConstantTPhi(domainliq2, + domaincat4,interfacerxns2,298.15,AVratio*1.0); + +# %% +domaincat5,y0cat5,pcat5 = ConstantTAPhiDomain(phase=surf2, + initialconds=initialcondssurf5); + +inter5,pinter5 = ReactiveInternalInterfaceConstantTPhi(domainliq2, + domaincat5,interfacerxns2,298.15,AVratio*1.0); + +# %% +domaincat6,y0cat6,pcat6 = ConstantTAPhiDomain(phase=surf2, + initialconds=initialcondssurf6); + +inter6,pinter6 = ReactiveInternalInterfaceConstantTPhi(domainliq2, + domaincat6,interfacerxns2,298.15,AVratio*1.0); + +# %% +@time react1,y01,p1 = Reactor((domainliq1,domaincat1), (y0liq1,y0cat1), (0.0, 1.0e2), [inter1], (pliq1,pcat1,pinter1)); + +@time sol1 = solve(react1.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +ssys1 = SystemSimulation(sol1,(domainliq1,domaincat1,),(inter1,),p1); + + +# %% +@time react2,y02,p2 = Reactor((domainliq1,domaincat2), (y0liq1,y0cat2), (0.0, 1.0e2), [inter2], (pliq1,pcat2,pinter2)); + +@time sol2 = solve(react2.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +ssys2 = SystemSimulation(sol2,(domainliq1,domaincat2,),(inter2,),p2); + +# %% +@time react3,y03,p3 = Reactor((domainliq1,domaincat3), (y0liq1,y0cat3), (0.0, 1.0e2), [inter3], (pliq1,pcat3,pinter3)); + +@time sol3 = solve(react3.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +ssys3 = SystemSimulation(sol3,(domainliq1,domaincat3,),(inter3,),p3); + +# %% +@time react4,y04,p4 = Reactor((domainliq2,domaincat4), (y0liq2,y0cat4), (0.0, 1.0e2), [inter4], (pliq2,pcat4,pinter4)); + +@time sol4 = solve(react4.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +ssys4 = SystemSimulation(sol4,(domainliq2,domaincat4,),(inter4,),p4); + +# %% +@time react5,y05,p5 = Reactor((domainliq2,domaincat5), (y0liq2,y0cat5), (0.0, 1.0e2), [inter5], (pliq2,pcat5,pinter5)); + +@time sol5 = solve(react5.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +ssys5 = SystemSimulation(sol5,(domainliq2,domaincat5,),(inter5,),p5); + +# %% +@time react6,y06,p6 = Reactor((domainliq2,domaincat6), (y0liq2,y0cat6), (0.0, 1.0e2), [inter6], (pliq2,pcat6,pinter6)); + +@time sol6 = solve(react6.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +ssys6 = SystemSimulation(sol6,(domainliq2,domaincat6,),(inter6,),p6); + +# %% +# Helper function +function plotX(sim, tol, t_end, exclude) + clf() + xs = molefractions(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Mole Fraction") +end + +# %% +exclude_species = ["H2O"] +plotX(ssys1.sims[1], 1e-10, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e-3) +ylim(1e-12, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V") +gcf() +savefig("Ag111@-1.5V_X.png") + +# %% +exclude_species = ["H2O"] +plotX(ssys2.sims[1], 1e-10, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e-3) +ylim(1e-12, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.0V") +gcf() +savefig("Ag111@-1.0V_X.png") + +# %% +exclude_species = ["H2O"] +plotX(ssys3.sims[1], 1e-10, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e-3) +ylim(1e-12, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-2.0V") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys4.sims[1], 1e-10, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e-3) +ylim(1e-12, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Cu111@-1.5V") +gcf() +savefig("Cu111@-1.5V_X.png") + +# %% +exclude_species = ["H2O"] +plotX(ssys5.sims[1], 1e-10, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e-3) +ylim(1e-12, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Cu111@-1.0V") +gcf() +savefig("Cu111@-1.0V_X.png") + +# %% +exclude_species = ["H2O"] +plotX(ssys6.sims[1], 1e-10, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e-3) +ylim(1e-12, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Cu111@-2.0V") +gcf() +savefig("Cu111@-2.0V_X.png") + +# %% +exclude_species = ["H2O"] +plotX(ssys1.sims[2], 0.1, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e-3) +ylim(1e-12, 5) +title("Evolution of Solid-phase Mole Fractions vs. Time at phi = -1.5V on Ag111") +gcf() + +# %% +Dict([ssys1.sims[1].names[i]=>molefractions(ssys1.sims[1],1)[i] for i in 1:length(ssys1.sims[1].names)]) + +# %% +fd1 = getfluxdiagram(ssys1,1e-3;speciesratetolerance=1e-4) + +# %% +fd2 = getfluxdiagram(ssys2,1e-3;speciesratetolerance=1e-4) + +# %% +fd3 = getfluxdiagram(ssys3,1e-3;speciesratetolerance=1e-4) + +# %% +fd4 = getfluxdiagram(ssys4,1e-3;speciesratetolerance=1e-4) + +# %% +fd5 = getfluxdiagram(ssys5,1e-3;speciesratetolerance=1e-4) + +# %% +fd6 = getfluxdiagram(ssys6,1e-3;speciesratetolerance=1e-4) + +# %% +# function plot_composition_comparison(solutions, t, tol, exclude, x_labels) +# # Prepare data storage +# species_dict = Dict{String, Vector{Float64}}() # To collect mole fractions for each species + +# # Iterate through each solution +# for (idx, bsol) in enumerate(solutions) +# # Get mole fractions and species at the specified time +# mole_fractions = molefractions(bsol, t) +# species = bsol.domain.phase.species + +# # Filter species based on threshold and exclusion list +# for (i, mf) in enumerate(mole_fractions) +# species_name = species[i].name +# if mf > tol && !(species_name in exclude) +# # Initialize vector for each species if not already present +# if !haskey(species_dict, species_name) +# species_dict[species_name] = zeros(length(solutions)) +# end +# # Assign the mole fraction for the current solution +# species_dict[species_name][idx] = mf +# end +# end +# end + +# # Convert species data to arrays for plotting +# species_names = collect(keys(species_dict)) +# num_solutions = length(solutions) + +# # Sort species for each solution based on mole fractions (descending order) +# sorted_species = sort(species_names, by=name -> -maximum(species_dict[name])) + +# # Plotting each solution individually +# clf() # Clear the current figure +# bar_positions = 1:num_solutions +# width = 0.35 # Width of each bar +# color_cycle = get_cmap("tab20", length(sorted_species)) + +# # Initialize bottom values for stacked bars +# bottoms = zeros(num_solutions) + +# # Plot each species, stacking from the highest mole fraction down +# for (color_idx, species_name) in enumerate(sorted_species) +# # Get the mole fractions for the current species across solutions +# current_data = species_dict[species_name] + +# # Plot bars for the current species +# bar(bar_positions, current_data, width, bottom=bottoms, color=color_cycle(color_idx), label=species_name) + +# # Update the bottom values for stacking +# bottoms .+= current_data +# end + +# # Formatting the plot +# xticks(bar_positions, x_labels) +# ylabel("Mole Fraction") +# legend(title="Species", loc="upper right", bbox_to_anchor=(1.2, 1)) +# title("Liquid Phase Composition at t = $t") +# tight_layout() # Adjust layout for better appearance +# end + + +# %% +# sims_collection = [ssys1.sims[1], ssys2.sims[1], ssys3.sims[1]] +# x_labels = ["Ag111@-2.0V", "Ag111@-1.5V", "Ag111@-1.0V"] +# plot_composition_comparison(sims_collection, 1e-3, 1e-3, ["H2O"]) + +# %% diff --git a/CO2RR_RMS/Ag/CO2RR_RMS_2.ipynb b/CO2RR_RMS/Ag/CO2RR_RMS_2.ipynb deleted file mode 100644 index f6c86d7..0000000 --- a/CO2RR_RMS/Ag/CO2RR_RMS_2.ipynb +++ /dev/null @@ -1,695 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 133, - "id": "8a590634", - "metadata": {}, - "outputs": [], - "source": [ - "using DifferentialEquations\n", - "using ReactionMechanismSimulator\n", - "using PyPlot" - ] - }, - { - "cell_type": "code", - "execution_count": 134, - "id": "e941d4fb", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Dict{Any, Any} with 4 entries:\n", - " \"Solvents\" => Solvent[Solvent(\"water\", RiedelViscosity{Float64}(…\n", - " Set([\"surface\", \"gas\"]) => Dict{Any, Any}(\"Reactions\"=>ElementaryReaction[vac…\n", - " \"gas\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…\n", - " \"surface\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "outdict = readinput(\"chem300.rms\")" - ] - }, - { - "cell_type": "code", - "execution_count": 135, - "id": "fe2767e9", - "metadata": {}, - "outputs": [], - "source": [ - "liqspcs = outdict[\"gas\"][\"Species\"]\n", - "liqrxns = outdict[\"gas\"][\"Reactions\"]\n", - "surfspcs = outdict[\"surface\"][\"Species\"]\n", - "surfrxns = outdict[\"surface\"][\"Reactions\"]\n", - "interfacerxns = outdict[Set([\"surface\", \"gas\"])][\"Reactions\"]\n", - "solv = outdict[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 136, - "id": "c54ee65e", - "metadata": {}, - "outputs": [], - "source": [ - "sitedensity = 2.292e-5; # Ag111\n", - "liq = IdealDiluteSolution(liqspcs,liqrxns,solv,name=\"liquid\",diffusionlimited=true);\n", - "surf = IdealSurface(surfspcs,surfrxns,sitedensity,name=\"surface\");" - ] - }, - { - "cell_type": "code", - "execution_count": 137, - "id": "8894c84d", - "metadata": {}, - "outputs": [], - "source": [ - "initialcondsliq = Dict([\"proton\"=>10.0^-4,\n", - " \"CO2\"=>10.0^-3*10^6,\n", - " \"V\"=>1.0,\"T\"=>300,\"Phi\"=>0.0,\"d\"=>0.0]);\n", - "AVratio = 1e5;\n", - "initialcondssurf = Dict([\"CO2X\"=>0.4*sitedensity*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity*AVratio,\n", - " \"OX\"=>0.1*sitedensity*AVratio,\n", - " \"OCX\"=>0.1*sitedensity*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>300,\"Phi\"=>-1.5]);" - ] - }, - { - "cell_type": "code", - "execution_count": 138, - "id": "ddb39b3d", - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "domainliq,y0liq,pliq = ConstantTVDomain(phase=liq,\n", - " initialconds=initialcondsliq,constantspecies=[\"proton\",\"CO2\"]);\n", - "domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf,\n", - " initialconds=initialcondssurf);" - ] - }, - { - "cell_type": "code", - "execution_count": 139, - "id": "ed49d2b4", - "metadata": {}, - "outputs": [], - "source": [ - "inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainliq,\n", - " domaincat,interfacerxns,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 140, - "id": "244f0912", - "metadata": {}, - "outputs": [], - "source": [ - "@time react,y0,p = Reactor((domainliq,domaincat), (y0liq,y0cat), (0.0, 1.0e3), [inter], (pliq,pcat,pinter));\n" - ] - }, - { - "cell_type": "code", - "execution_count": 141, - "id": "962f838c", - "metadata": {}, - "outputs": [], - "source": [ - "@time sol = solve(react.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-8);" - ] - }, - { - "cell_type": "code", - "execution_count": 142, - "id": "56b6f906", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "retcode: Success\n", - "Interpolation: 3rd order Hermite\n", - "t: 7135-element Vector{Float64}:\n", - " 0.0\n", - " 4.786910423176204e-20\n", - " 9.573820846352407e-20\n", - " 1.4360731269528611e-19\n", - " 3.136209658750193e-19\n", - " 4.836346190547525e-19\n", - " 6.536482722344857e-19\n", - " 9.290855160451293e-19\n", - " 1.393701587359254e-18\n", - " 2.1962591531694716e-18\n", - " ⋮\n", - " 879.5546091455969\n", - " 894.8998163040148\n", - " 910.2450234624328\n", - " 925.5902306208507\n", - " 940.9354377792686\n", - " 956.2806449376865\n", - " 971.6258520961044\n", - " 986.9710592545223\n", - " 1000.0\n", - "u: 7135-element Vector{Vector{Float64}}:\n", - " [0.0, 0.0, 0.0, 0.0, 1000.0, 0.0001, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]\n", - " [0.0, 0.0, 0.0, 0.0, 1000.0, 0.0001, 3.612374328324481e-148, 4.385132164362883e-19, 1.633795305695168e-19, 2.7428996724663614e-14 … 1.1203467421629118e-45, 1.8994249591181796e-72, 1.2800354014369318e-87, -3.879530191351059e-178, 1.3708129609046892e-77, 1.3213726871771316e-91, 1.5496805651867354e-69, 1.0657739381929874e-102, 7.799295861017468e-45, 1.5199781543354013e-65]\n", - " [0.0, 0.0, 0.0, 0.0, 1000.0, 0.0001, 3.2510159530929195e-147, 8.770264328726898e-19, 3.26901310954359e-19, 5.4857993449194225e-14 … 5.601733429675485e-45, 9.500781840630999e-72, 6.405079675989712e-87, 1.5792657431109165e-170, 9.579979641605759e-77, 9.249204609701657e-91, 7.747910452426376e-69, 5.3288687302123504e-102, 3.900398940032122e-44, 9.121693519206351e-65]\n", - " [0.0, 0.0, 0.0, 0.0, 1000.0, 0.0001, 1.914390693681754e-146, 1.3155396493092048e-18, 4.905653411229998e-19, 8.228699017359486e-14 … 1.5684852403090184e-44, 2.851514493402545e-71, 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3.008904767648952e-17]\n", - " [0.0, 0.0, 0.0, 0.0, 1000.0, 0.0001, 8.662001320737534e-59, 0.0006520781082836139, 1478.8029142762553, 620.9199458002881 … 1.6349225099682997e-30, 7.817281395042703e-18, 8.634034542102559e-16, 1.182646490629931e-70, 3.7649709371881814e-19, 7.801481961734099e-37, 6.350172148918026e-21, 8.274974497752408e-28, 4.009308604716525e-6, 3.007906462317097e-17]\n", - " [0.0, 0.0, 0.0, 0.0, 1000.0, 0.0001, 8.946827697111488e-59, 0.0006525467920031325, 1491.9399043216488, 626.2664659162169 … 1.6269066676192027e-30, 7.73620747200259e-18, 8.561602493564738e-16, 1.1836665222347363e-70, 3.733177555052834e-19, 7.736656031780808e-37, 6.307719612670948e-21, 8.294648908547076e-28, 4.0350703196569055e-6, 3.0070696513014354e-17]" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sol" - ] - }, - { - "cell_type": "code", - "execution_count": 143, - "id": "4714593e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ReturnCode.Success = 1" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sol.retcode" - ] - }, - { - "cell_type": "code", - "execution_count": 144, - "id": "6667bb5a", - "metadata": {}, - "outputs": [], - "source": [ - "ssys = SystemSimulation(sol,(domainliq,domaincat,),(inter,),p);" - ] - }, - { - "cell_type": "code", - "execution_count": 145, - "id": "87dcaf99", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotX (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotX(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = molefractions(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Mole Fraction\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 146, - "id": "ddf6da6b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotC (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotC(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = concentrations(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Concentration\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 147, - "id": "e719a85d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys.sims[1], 1e-3, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-9, 1e3)\n", - "ylim(1e-6, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 148, - "id": "1ef78267", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotC(ssys.sims[1], 1, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-9, 1e3)\n", - "ylim(1e-3, 1e4)\n", - "title(\"Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 149, - "id": "1f7d8918", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "1186×1435 Array{RGBA{N0f8},2} with eltype ColorTypes.RGBA{FixedPointNumbers.N0f8}:\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " ⋮ ⋱ \n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,0.8) … RGBA{N0f8}(1.0,1.0,1.0,0.569)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "getfluxdiagram(ssys,1e3;speciesratetolerance=1e-6)" - ] - }, - { - "cell_type": "code", - "execution_count": 150, - "id": "36206466", - "metadata": {}, - "outputs": [], - "source": [ - "println(ssys.names)" - ] - }, - { - "cell_type": "code", - "execution_count": 151, - "id": "44de0eb2", - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "for (i,rxn) in enumerate(inter.reactions)\n", - " str = getrxnstr(rxn)\n", - " kf = inter.kfs[i]\n", - " krev = inter.krevs[i]\n", - " Kc = kf/krev\n", - " println(str)\n", - " println(\"kf = $kf\")\n", - " println(\"krev = $krev\")\n", - " println(\"Kc = $Kc\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 152, - "id": "dd1b08a5", - "metadata": {}, - "outputs": [], - "source": [ - "for (i,rxn) in enumerate(inter.reactions)\n", - " str = getrxnstr(rxn)\n", - " kf = inter.kfs[i]\n", - " krev = inter.krevs[i]\n", - " Kc = kf/krev\n", - " println(str)\n", - " println(\"kf = $kf\")\n", - " println(\"krev = $krev\")\n", - " println(\"Kc = $Kc\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 203, - "id": "11333da0", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "10962-element SparseArrays.SparseVector{Float64, Int64} with 18 stored entries:\n", - " [11 ] = -6.62794e-112\n", - " [10253] = 5.62284\n", - " [10254] = 8950.06\n", - " [10255] = -8.57104e-20\n", - " [10256] = -7.59582e-24\n", - " [10265] = 8.69249e-8\n", - " [10268] = 5.42172e-14\n", - " ⋮\n", - " [10310] = 7.39712e-51\n", - " [10352] = 7.94894e-27\n", - " [10540] = 1.733e-29\n", - " [10555] = 6.69799e-34\n", - " [10835] = 1.03174e-24\n", - " [10865] = 5.4537e-26\n", - " [10867] = 1.78878e-45\n", - " [10908] = 1.48135e-12" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "rops(ssys, \"O=CO\", 1e-12)" - ] - }, - { - "cell_type": "code", - "execution_count": 190, - "id": "ef575a57", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotROP (generic function with 2 methods)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "function plotROP(bsol,name,t;N=0,tol=0.01)\n", - " clf()\n", - " rop = rops(bsol,name,t)\n", - " inds = rop.nzind[reverse(sortperm(abs.(rop.nzval)))]\n", - " if N == 0\n", - " N = length(inds)\n", - " elseif N > length(inds)\n", - " N = length(inds)\n", - " end\n", - " inds = inds[1:N]\n", - " mval = abs(rop[inds[1]])\n", - " minval = mval*tol\n", - " k = 1\n", - " while k < length(inds) && abs(rop[inds[k]]) >= minval\n", - " k += 1\n", - " end\n", - " inds = inds[1:k]\n", - " xs = Array{Float64,1}(1:length(inds))\n", - " barh(xs,reverse(rop[inds]))\n", - " yticks(xs,reverse(getrxnstr.(bsol.domain.phase.reactions[inds])))\n", - " xlabel(\"Production/Loss Rate mol/s\")\n", - " return\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 199, - "id": "e004c9af", - "metadata": {}, - "outputs": [ - { - "ename": "UndefVarError", - "evalue": "UndefVarError: `getphasespecies` not defined", - "output_type": "error", - "traceback": [ - "UndefVarError: `getphasespecies` not defined\n", - "\n", - "Stacktrace:\n", - " [1] plotROP(bsol::Simulation{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, SparseArrays.SparseMatrixCSC{Float64, Int64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Sundials.CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}, Vector{String}, ReactionMechanismSimulator.var\"#F#675\"{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, SparseArrays.SparseMatrixCSC{Float64, Int64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Sundials.CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Matrix{Float64}, Matrix{Float64}}}, Matrix{Float64}, Vector{Species}, Vector{ElementaryReaction}, Vector{Float64}}, name::String, t::Int64; N::Int64, tol::Float64)\n", - " @ Main ~/Work/Electrocat/CO2_RR_RMG/CO2_Reduction_Ag/jl_notebook_cell_df34fa98e69747e1a8f8a730347b8e2f_X30sdnNjb2RlLXJlbW90ZQ==.jl:3\n", - " [2] top-level scope\n", - " @ ~/Work/Electrocat/CO2_RR_RMG/CO2_Reduction_Ag/jl_notebook_cell_df34fa98e69747e1a8f8a730347b8e2f_X32sdnNjb2RlLXJlbW90ZQ==.jl:1" - ] - } - ], - "source": [ - "plotROP(ssys.sims[2], \"CH2O2X\",1;N=15,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 206, - "id": "b5b12ce0", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "10962-element SparseArrays.SparseVector{Float64, Int64} with 528 stored entries:\n", - " [47 ] = 2.35221e10\n", - " [48 ] = 1.82944e6\n", - " [49 ] = 1.82944e6\n", - " [50 ] = 0.93615\n", - " [53 ] = 1.82944e6\n", - " [54 ] = 1.82944e6\n", - " [56 ] = 21.6762\n", - " ⋮\n", - " [10084] = 5.29789e-29\n", - " [10087] = 6.68217e-37\n", - " [10088] = 1.51366e-30\n", - " [10242] = 1.87538e5\n", - " [10243] = 5.37857e5\n", - " [10253] = -5.62284\n", - " [10264] = -6.26487e-6\n", - " [10266] = -4.38995e-6" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "rops(ssys, \"CH2O2X\", 1e-12)" - ] - }, - { - "cell_type": "code", - "execution_count": 207, - "id": "16031f6f", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "10962-element SparseArrays.SparseVector{Float64, Int64} with 18 stored entries:\n", - " [11 ] = -6.62794e-112\n", - " [10253] = 5.62284\n", - " [10254] = 8950.06\n", - " [10255] = -8.57104e-20\n", - " [10256] = -7.59582e-24\n", - " [10265] = 8.69249e-8\n", - " [10268] = 5.42172e-14\n", - " ⋮\n", - " [10310] = 7.39712e-51\n", - " [10352] = 7.94894e-27\n", - " [10540] = 1.733e-29\n", - " [10555] = 6.69799e-34\n", - " [10835] = 1.03174e-24\n", - " [10865] = 5.4537e-26\n", - " [10867] = 1.78878e-45\n", - " [10908] = 1.48135e-12" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "rops(ssys, \"O=CO\", 1e-12)" - ] - }, - { - "cell_type": "code", - "execution_count": 194, - "id": "36b9ee55", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}(IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}\n", - " name: String \"liquid\"\n", - " species: Array{Species}((108,))\n", - " reactions: Array{ElementaryReaction}((43,))\n", - " solvent: Solvent\n", - " stoichmatrix: SparseArrays.SparseMatrixCSC{Float64, Int64}\n", - " Nrp: Array{Float64}((43,)) [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]\n", - " rxnarray: Array{Int64}((8, 43)) [7 7 … 7 15; 33 34 … 106 106; … ; 0 0 … 0 0; 0 0 … 0 0]\n", - " veckinetics: Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}\n", - " veckineticsinds: Array{Int64}((1,)) [43]\n", - " vecthermo: ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}\n", - " otherreactions: Array{ElementaryReaction}((0,))\n", - " electronchange: Array{Float64}((43,)) [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]\n", - " spcdict: Dict{String, Int64}\n", - " reversibility: Array{Bool}((43,)) Bool[1, 1, 1, 1, 1, 1, 1, 1, 1, 1 … 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]\n", - " forwardability: Array{Bool}((43,)) Bool[1, 1, 1, 1, 1, 1, 1, 1, 1, 1 … 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]\n", - " diffusionlimited: Bool true\n", - ", [1, 108], [1, 151], [6, 5], 300.0, 1.0, 0.0, 0.0, [8.30171982998078e6, 8.30171982998078e6, 7.945759617446088e6, 7.653861670370603e6, 7.990621761684466e6, 8.365589466005936e6, 7.486079195303395e6, 8.270053435737545e6, 7.325293273850048e6, 6.575646985634498e6 … 1.6449236157225358e-7, 975439.053875451, 421244.0828356318, 2.176624091649817e6, 1.105301411839168e6, 2.8662557808254304e-8, 3.1372973385333555e-9, 13.337843555354022, 1047.7426603355002, 3.854912483633202e-17], [2.5056634928273256e-132, 1.1613793480197979e-83, 1.0469602316081974e-111, 4.674409174722625e-63, 2.502310768518533e-105, 9.12325565337589e-115, 4.7546927811598384e-60, 1.8292328198366333e-69, 2.8349643752073253e-57, 4.807881163872417e-54 … 9.023066186355352e-17, 1.563105995258598e-44, 1.2753070140440015e-41, 1.5114569550525903e-45, 1.450059162715292e-42, 9.416249033124735e-16, 1.94720339830407e-13, 1.3370990092106833e-28, 2.48776775159488e-34, 4.535122728660089e-5], [5.536169735269627e9, 5.536169735269627e9, 5.536169735269627e9, 2.0078948710112387e8, 5.536169735269627e9, 5.536169735269627e9, 1.1607394475819142e8, 6.403973080115937e8, 5.828649368272015e7, 3.0562704051882233e7 … 1.6449236157225734e-7, 1.1153325173493526e6, 445367.8774444417, 3.034988664382294e6, 1.290665553097012e6, 2.8662557808254476e-8, 3.137297338533386e-9, 13.337865786615048, 1047.8737022624825, 3.8549124836554075e-17], Integer[], [-40043.126583650024, -32840.77588912651, -38671.7008403984, -51458.45101465355, -457938.94362207263, -12274.741585447891, 186629.03260505645, -188530.14716098696, -483402.40421594173, -325852.7281740505 … -601433.0819126703, -530752.7596515524, -297771.61210395163, -179638.08529880646, -280902.1348595971, 40897.63410455966, -175190.9596661942, -17841.765925695272, -462309.04129866365, -510468.6853220258], [7 7 … 7 15; 33 34 … 106 106; … ; 0 0 … 0 0; 0 0 … 0 0], 0.0008764544014047555, [1.2791698254820209e-9, 1.8057956542205799e-9, 1.6715781069123858e-9, 1.2139156476242518e-9, 1.122671285175347e-9, 1.6586845884779859e-9, 1.6586845884779859e-9, 1.14440221020022e-9, 1.0706139020926982e-9, 1.3343544679270026e-9 … 8.493536585469772e-10, 8.493536585469772e-10, 8.493536585469772e-10, 9.077994650831605e-10, 8.493536585469772e-10, 8.905894704051347e-10, 8.689951179730577e-10, 8.795273391843891e-10, 8.493536585469772e-10, 8.493536585469772e-10], [0.0 0.0 … 0.0 0.0; 0.0 0.0 … 0.0 0.0; … ; 0.0 0.0 … 0.0 0.0; 0.0 0.0 … 0.0 0.0], false, false, Bool[0], [0.0], [-40043.126583650024, -32840.77588912651, -38671.7008403984, -51458.45101465355, -457938.94362207263, -12274.741585447891, 186629.03260505645, -188530.14716098696, -483402.40421594173, -325852.7281740505 … 1.6449236157225734e-7, 1.1153325173493526e6, 445367.8774444417, 3.034988664382294e6, 1.290665553097012e6, 2.8662557808254476e-8, 3.137297338533386e-9, 13.337865786615048, 1047.8737022624825, 3.8549124836554075e-17], Dict{String, Int64}())" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "ssys.sims[1].domain" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "733fcc2d", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.9.1", - "language": "julia", - "name": "julia-1.9" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.9.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/CO2RR_RMS/Ag/CO2RR_RMS_2.jl b/CO2RR_RMS/Ag/CO2RR_RMS_2.jl new file mode 100644 index 0000000..ad797a8 --- /dev/null +++ b/CO2RR_RMS/Ag/CO2RR_RMS_2.jl @@ -0,0 +1,215 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,jl:percent +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.17.2 +# kernelspec: +# display_name: Julia 1.9.1 +# language: julia +# name: julia-1.9 +# --- + +# %% +using DifferentialEquations +using ReactionMechanismSimulator +using PyPlot + +# %% +outdict = readinput("chem300.rms") + +# %% +liqspcs = outdict["gas"]["Species"] +liqrxns = outdict["gas"]["Reactions"] +surfspcs = outdict["surface"]["Species"] +surfrxns = outdict["surface"]["Reactions"] +interfacerxns = outdict[Set(["surface", "gas"])]["Reactions"] +solv = outdict["Solvents"][1]; + +# %% +sitedensity = 2.292e-5; # Ag111 +liq = IdealDiluteSolution(liqspcs,liqrxns,solv,name="liquid",diffusionlimited=true); +surf = IdealSurface(surfspcs,surfrxns,sitedensity,name="surface"); + +# %% +initialcondsliq = Dict(["proton"=>10.0^-4, + "CO2"=>10.0^-3*10^6, + "V"=>1.0,"T"=>300,"Phi"=>0.0,"d"=>0.0]); +AVratio = 1e5; +initialcondssurf = Dict(["CO2X"=>0.4*sitedensity*AVratio, + "CHO2X"=>0.1*sitedensity*AVratio, + "CO2HX"=>0.1*sitedensity*AVratio, + "OX"=>0.1*sitedensity*AVratio, + "OCX"=>0.1*sitedensity*AVratio, + "vacantX"=>0.1*sitedensity*AVratio, + "CH2O2X"=>0.05*sitedensity*AVratio, + "CHOX"=>0.04*sitedensity*AVratio, + "CH2OX"=>0.01*sitedensity*AVratio, + "A"=>1.0*AVratio,"T"=>300,"Phi"=>-1.5]); + +# %% +domainliq,y0liq,pliq = ConstantTVDomain(phase=liq, + initialconds=initialcondsliq,constantspecies=["proton","CO2"]); +domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf, + initialconds=initialcondssurf); + +# %% +inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainliq, + domaincat,interfacerxns,298.15,AVratio*1.0); + +# %% +@time react,y0,p = Reactor((domainliq,domaincat), (y0liq,y0cat), (0.0, 1.0e3), [inter], (pliq,pcat,pinter)); + + +# %% +@time sol = solve(react.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-8); + +# %% +sol + +# %% +sol.retcode + +# %% +ssys = SystemSimulation(sol,(domainliq,domaincat,),(inter,),p); + +# %% +# Helper function +function plotX(sim, tol, t_end, exclude) + clf() + xs = molefractions(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Mole Fraction") +end + +# %% +# Helper function +function plotC(sim, tol, t_end, exclude) + clf() + xs = concentrations(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Concentration") +end + +# %% +exclude_species = ["H2O"] +plotX(ssys.sims[1], 1e-3, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-9, 1e3) +ylim(1e-6, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V") +gcf() + +# %% +exclude_species = ["H2O"] +plotC(ssys.sims[1], 1, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-9, 1e3) +ylim(1e-3, 1e4) +title("Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V") +gcf() + +# %% +getfluxdiagram(ssys,1e3;speciesratetolerance=1e-6) + +# %% +println(ssys.names) + +# %% +for (i,rxn) in enumerate(inter.reactions) + str = getrxnstr(rxn) + kf = inter.kfs[i] + krev = inter.krevs[i] + Kc = kf/krev + println(str) + println("kf = $kf") + println("krev = $krev") + println("Kc = $Kc") +end + +# %% +for (i,rxn) in enumerate(inter.reactions) + str = getrxnstr(rxn) + kf = inter.kfs[i] + krev = inter.krevs[i] + Kc = kf/krev + println(str) + println("kf = $kf") + println("krev = $krev") + println("Kc = $Kc") +end + +# %% +rops(ssys, "O=CO", 1e-12) + +# %% +function plotROP(bsol,name,t;N=0,tol=0.01) + clf() + rop = rops(bsol,name,t) + inds = rop.nzind[reverse(sortperm(abs.(rop.nzval)))] + if N == 0 + N = length(inds) + elseif N > length(inds) + N = length(inds) + end + inds = inds[1:N] + mval = abs(rop[inds[1]]) + minval = mval*tol + k = 1 + while k < length(inds) && abs(rop[inds[k]]) >= minval + k += 1 + end + inds = inds[1:k] + xs = Array{Float64,1}(1:length(inds)) + barh(xs,reverse(rop[inds])) + yticks(xs,reverse(getrxnstr.(bsol.domain.phase.reactions[inds]))) + xlabel("Production/Loss Rate mol/s") + return +end + +# %% +plotROP(ssys.sims[2], "CH2O2X",1;N=15,tol=0.0) + +# %% +rops(ssys, "CH2O2X", 1e-12) + +# %% +rops(ssys, "O=CO", 1e-12) + +# %% +ssys.sims[1].domain + +# %% diff --git a/CO2RR_RMS/Ag/CO2RR_RMS_3.ipynb b/CO2RR_RMS/Ag/CO2RR_RMS_3.ipynb deleted file mode 100644 index dc564d4..0000000 --- a/CO2RR_RMS/Ag/CO2RR_RMS_3.ipynb +++ /dev/null @@ -1,3861 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "8a590634", - "metadata": {}, - "outputs": [], - "source": [ - "using DifferentialEquations\n", - "using ReactionMechanismSimulator\n", - "using PyPlot" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "e941d4fb", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[12:23:54] WARNING: not removing hydrogen atom without neighbors\n", - "[12:23:54] WARNING: not removing hydrogen atom without neighbors\n", - "┌ Warning: failed to generate StokesDiffusivity model for species vacantX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2O2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species H2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [H][H].[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(=O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH3X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(C#[Pt])CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)C(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C([Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C([Pt])CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC([Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=[Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC([Pt])=C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=C=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC(=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCOC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCC(=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC([Pt])=C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=COC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCOO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C=CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])CCO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)C(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)C(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC([Pt])OC=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=[Pt])OC=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC([Pt])=CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C([Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(C=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n" - ] - }, - { - "data": { - "text/plain": [ - "Dict{Any, Any} with 4 entries:\n", - " \"Solvents\" => Solvent[Solvent(\"water\", RiedelViscosity{Float64}(…\n", - " Set([\"surface\", \"gas\"]) => Dict{Any, Any}(\"Reactions\"=>ElementaryReaction[vac…\n", - " \"gas\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…\n", - " \"surface\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "outdict = readinput(\"chem300.rms\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "fe2767e9", - "metadata": {}, - "outputs": [], - "source": [ - "liqspcs = outdict[\"gas\"][\"Species\"]\n", - "liqrxns = outdict[\"gas\"][\"Reactions\"]\n", - "surfspcs = outdict[\"surface\"][\"Species\"]\n", - "surfrxns = outdict[\"surface\"][\"Reactions\"]\n", - "interfacerxns = outdict[Set([\"surface\", \"gas\"])][\"Reactions\"]\n", - "solv = outdict[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "c54ee65e", - "metadata": {}, - "outputs": [], - "source": [ - "sitedensity = 2.292e-5; # Ag111\n", - "liq = IdealDiluteSolution(liqspcs,liqrxns,solv,name=\"liquid\",diffusionlimited=true);\n", - "surf = IdealSurface(surfspcs,surfrxns,sitedensity,name=\"surface\");" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "8894c84d", - "metadata": {}, - "outputs": [], - "source": [ - "# Reservoir is a 100 mL (100e-6 m^3) cell\n", - "# Proton concentration is 10^-7 mol/L (10^-4 mol/m^3)\n", - "# CO2 concentration is 0.01 mol/L (10 mol/m^3), saturation solubility ~0.03 mol/L\n", - "# AVratio in experiments is 36 m^-1 but is measured by surface area/reservoir volume\n", - "# Area of the electrode is therefore 3.6e1 m^-1 * 1e2*1e-6 m^3 = 3.6e-3 m^2 = 36 cm^2\n", - "# Assume boundary layer thickness d_bl = 1 mm or 1e-3 m\n", - "# Volume of the boundary layer V_bl = 3.6e-3 m^2 * 1e-3 m = 3.6e-6 m^3\n", - "# Actual AVratio is therefore 3.6e-3 m^2 / 3.6e-6 m^3 = 1e3 m^-1 (reciprocal of d_bl)\n", - "# Amount of sites is 2.292e-5 mol/m^2 * 1e3 m^-1 = 2.292e-2 mol/m^-3\n", - "\n", - "C_proton = 1e-7*1e3;\n", - "C_co2 = 1e-2*1e3;\n", - "C_default = 1e-12;\n", - "V_res = 100.0e-6;\n", - "AVratio = 1e3;\n", - "A_surf = 100.0e-6*36;\n", - "V_bl = A_surf/AVratio;\n", - "sites = sitedensity;\n", - "\n", - "initialcondsliq = Dict([\"proton\"=>C_proton,\n", - " \"CO2\"=>C_co2,\n", - " \"V\"=>V_res,\"T\"=>300,\"Phi\"=>0.0,\"d\"=>0.0]);\n", - "\n", - "initialcondssurf = Dict([\"CO2X\"=>0.4*sites,\n", - " \"CHO2X\"=>0.1*sites,\n", - " \"CO2HX\"=>0.1*sites,\n", - " \"OX\"=>0.1*sites,\n", - " \"OCX\"=>0.1*sites,\n", - " \"vacantX\"=>0.1*sites,\n", - " \"CH2O2X\"=>0.05*sites,\n", - " \"CHOX\"=>0.04*sites,\n", - " \"CH2OX\"=>0.01*sites,\n", - " \"A\"=>A_surf,\"T\"=>300,\"Phi\"=>-1.565]);" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "ddb39b3d", - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "domainliq,y0liq,pliq = ConstantTVDomain(phase=liq,\n", - " initialconds=initialcondsliq,constantspecies=[\"proton\",\"CO2\"]);\n", - "domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf,\n", - " initialconds=initialcondssurf);" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "ed49d2b4", - "metadata": {}, - "outputs": [], - "source": [ - "inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainliq,\n", - " domaincat,interfacerxns,298.15,A_surf);" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "244f0912", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 11.991855 seconds (50.60 M allocations: 3.156 GiB, 9.36% gc time, 99.15% compilation time: <1% of which was recompilation)\n" - ] - } - ], - "source": [ - "@time react,y0,p = Reactor((domainliq,domaincat), (y0liq,y0cat), (0.0, 1.0e3), [inter], (pliq,pcat,pinter));\n" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "962f838c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 11.159277 seconds (22.91 M allocations: 13.650 GiB, 8.66% gc time, 38.09% compilation time)\n" - ] - } - ], - "source": [ - "@time sol = solve(react.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-22,reltol=1e-8);" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "56b6f906", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "1000.0" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sol.t[end]" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "4714593e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ReturnCode.Success = 1" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sol.retcode" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "6667bb5a", - "metadata": {}, - "outputs": [], - "source": [ - "ssys = SystemSimulation(sol,(domainliq,domaincat,),(inter,),p);" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "87dcaf99", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotX (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotX(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = molefractions(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Mole Fraction\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "ddf6da6b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotC (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotC(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = concentrations(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Concentration\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "e719a85d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys.sims[1], 1e-7, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-12, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "1ef78267", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotC(ssys.sims[1], 1e-3, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-6, 1e6)\n", - "title(\"Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "9ca4df51", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys.sims[2], 1e-2, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-6, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "1f7d8918", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "1527×1516 Array{RGBA{N0f8},2} with eltype ColorTypes.RGBA{FixedPointNumbers.N0f8}:\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " ⋮ ⋱ ⋮\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,0.867) RGBA{N0f8}(1.0,1.0,1.0,0.867)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "getfluxdiagram(ssys,1e3;speciesratetolerance=1e-6)" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "36206466", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[\"Ar\", \"He\", \"Ne\", \"N2\", \"CO2\", \"proton\", \"H\", \"C=O\", \"O=CO\", \"H2O\", \"O=CC=O\", \"H2\", \"OO\", \"CO\", \"O2\", \"O=C=C=O\", \"C=C=O\", \"O=C=CO\", \"CH4\", \"COC=O\", \"COO\", \"CO-2\", \"COOC\", \"O=CCO\", \"OCO\", \"COCO\", \"OCCO\", \"OC=CO\", \"O=O\", \"C=CO\", \"C=C\", \"O=C=C=C=O\", \"C#COO[CH2]\", \"C#COC[O]\", \"CC=O\", \"O=C=CC=O\", \"C=C(O)O\", \"CC(=O)O\", \"[OH]\", \"CC(=O)C=O\", \"COC(C)=O\", \"CC(=O)CO\", \"O=CCC=O\", \"COC=C=O\", \"O=C=CCO\", \"[CH2]OOC=C\", \"C=COC[O]\", \"C=CC=O\", \"C=COC=O\", \"O=CC=CO\", \"COC\", \"CCO\", \"CC(O)O\", \"CCOC=O\", \"COCC=O\", \"CCOO\", \"CC(C)=O\", \"C=C=C=O\", \"CC=C=O\", \"CC\", \"O=C=C=CO\", \"[CH2]OCC=O\", \"[O]CCC=O\", \"[CH2]COC=O\", \"[CH3]\", \"O=CCCO\", \"CCC=O\", \"CC(O)=C=O\", \"[CH]=O\", \"C[O]\", \"CC(O)C=O\", \"[CH2]O\", \"C=C(O)C=O\", \"OC=CCO\", \"C=CCO\", \"[CH]=C\", \"C[CH2]\", \"C=C=CO\", \"C=C=C\", \"C=C=C(O)O\", \"C=CC(=O)O\", \"CC=CO\", \"C=CC\", \"CC=C(O)O\", \"CCC(=O)O\", \"C=COO\", \"C#C\", \"C=COC\", \"C=CC(O)O\", \"C=COCO\", \"C=CCOO\", \"C=COOC\", \"CC(O)=CO\", \"C=C(C)O\", \"C#CC=O\", \"OC=C=CO\", \"CCOC\", \"CCCO\", \"CCC(O)O\", \"CCOCO\", \"CCCOO\", \"CCC\", \"CCOOC\", \"C=C=COO\", \"CC=COO\", \"C=CCO[O]\", \"COCOC\", \"COCCO\", \"vacantX\", \"CO2X\", \"CHO2X\", \"CO2HX\", \"OCX\", \"OX\", \"CH2O2X\", \"CHOX\", \"CH2OX\", \"HOX\", \"HX\", \"CO[Pt]\", \"OC[Pt]\", \"OC(O)[Pt]\", \"OCO[Pt]\", \"H2OX\", \"OC=[Pt]\", \"O=CC(=O)[Pt]\", \"OC#[Pt]\", \"O=CC=O.[Pt]\", \"[H][H].[Pt]\", \"O=COC[Pt]\", \"OO[Pt]\", \"CX\", \"CHX\", \"CH2X\", \"O=COC#[Pt]\", \"O=CCO[Pt]\", \"O=O.[Pt]\", \"O=CC#[Pt]\", \"OC(O)=[Pt]\", \"O=C(O)C#[Pt]\", \"O=C=C=O.[Pt]\", \"OOC[Pt]\", \"C=C=O.[Pt]\", \"COC(=O)[Pt]\", \"CC(=O)[Pt]\", \"O=COCC#[Pt]\", \"O=C([Pt])CO\", \"O=CCC(=O)[Pt]\", \"OCC#[Pt]\", \"OC(O)C#[Pt]\", \"OCOC#[Pt]\", \"O=CCOC#[Pt]\", \"O=C=C[Pt]\", \"COC#[Pt]\", \"O=CC(=O)C#[Pt]\", \"O=COC=[Pt]\", \"O=C=CC#[Pt]\", \"CC#[Pt]\", \"O=C=CO[Pt]\", \"COC(=O)C#[Pt]\", \"O=C=CC(=O)[Pt]\", \"O=CCC#[Pt]\", \"CH3X\", \"O=C=CO.[Pt]\", \"O=C=C=[Pt]\", \"CC(=O)C#[Pt]\", \"O=C(C#[Pt])CO\", \"COC=O.[Pt]\", \"CC(=O)C(=O)[Pt]\", \"OOC#[Pt]\", \"O=CC[Pt]\", \"O=CC=[Pt]\", \"C.[Pt]\", \"O=C=CC=O.[Pt]\", \"CC(=O)O[Pt]\", \"CC(=O)OC#[Pt]\", \"O=C=C([Pt])C=O\", \"O=C=COC#[Pt]\", \"COO[Pt]\", \"CO.[Pt]\", \"O=C=C(O)[Pt]\", \"O=C=C(O)C#[Pt]\", \"COOC#[Pt]\", \"O=CC(O)[Pt]\", \"O=CC(O)C#[Pt]\", \"O=CC(O)=[Pt]\", \"OCO.[Pt]\", \"O=C=C=C=O.[Pt]\", \"O=CCO.[Pt]\", \"OCC=[Pt]\", \"O=C=CCO.[Pt]\", \"O=C=CC(O)[Pt]\", \"O=C=CC=[Pt]\", \"O=C=C([Pt])CO\", \"O=C=CC[Pt]\", \"O=C=CC(O)=[Pt]\", \"O=C=CCO[Pt]\", \"O=CC([Pt])C=O\", \"O=CC(=[Pt])C=O\", \"O=CCC=O.[Pt]\", \"O=CCC=[Pt]\", \"OOCC#[Pt]\", \"C=C=[Pt]\", \"O=C(O)C=[Pt]\", \"CC=O.[Pt]\", \"CC=[Pt]\", \"CC=C=O.[Pt]\", \"O=C(O)C[Pt]\", \"O=C(O)CC#[Pt]\", \"CC([Pt])=C=O\", \"CC(=C=O)O[Pt]\", \"C=C.[Pt]\", \"C=C[Pt]\", \"C=CC#[Pt]\", \"CC(=O)O.[Pt]\", \"C=CC(=O)[Pt]\", \"O=CC=CO[Pt]\", \"C=CO[Pt]\", \"C=COC(=O)[Pt]\", \"C=COC#[Pt]\", \"CC(O)=[Pt]\", \"O=CC=C[Pt]\", \"C=CC(=O)O[Pt]\", \"OC=C=[Pt]\", \"CC[Pt]\", \"CCC#[Pt]\", \"CCO[Pt]\", \"CCOC(=O)[Pt]\", \"CCC(=O)[Pt]\", \"CCOC#[Pt]\", \"CCC(=O)O[Pt]\", \"CC(O)=C=O.[Pt]\", \"OOC=[Pt]\", \"OO.[Pt]\", \"COCO[Pt]\", \"COCC(=O)[Pt]\", \"COCOC#[Pt]\", \"COCC#[Pt]\", \"COC[Pt]\", \"COC=[Pt]\", \"COC=C=O.[Pt]\", \"O=C=COC[Pt]\", \"COC([Pt])=C=O\", \"O=C=COC=[Pt]\", \"CCOO[Pt]\", \"O=C=C=CO.[Pt]\", \"O=C=C=C(O)[Pt]\", \"O=C=C=C[Pt]\", \"OC=CO.[Pt]\", \"OC=C(O)[Pt]\", \"OC=C[Pt]\", \"OC=CO[Pt]\", \"OC=COC#[Pt]\", \"O=C([Pt])C=CO\", \"OC=C(O)C#[Pt]\", \"OC=CC#[Pt]\", \"OCC[Pt]\", \"OCCC#[Pt]\", \"O=C([Pt])CCO\", \"OCCO[Pt]\", \"OCCOC#[Pt]\", \"O=C=C=C=[Pt]\", \"C=CO.[Pt]\", \"C=C(O)[Pt]\", \"C=C(O)O[Pt]\", \"C=C(O)OC#[Pt]\", \"C=C(O)C#[Pt]\", \"C=C(O)C(=O)[Pt]\", \"C=COO[Pt]\", \"O=CC=C=[Pt]\", \"C=C=C=O.[Pt]\", \"O=C=C=CO[Pt]\", \"CC(O)[Pt]\", \"CC(O)C#[Pt]\", \"CC(O)O[Pt]\", \"CC(O)C(=O)[Pt]\", \"CC(O)OC#[Pt]\", \"O=C=C(O)C[Pt]\", \"O=C=C(O)C=[Pt]\", \"CC([Pt])OC=O\", \"CC(=[Pt])OC=O\", \"O=CC=CO.[Pt]\", \"O=CC=C(O)[Pt]\", \"O=CC([Pt])=CO\", \"OC=CC=[Pt]\", \"OCC(O)[Pt]\", \"OCC(O)C#[Pt]\", \"OCC(O)=[Pt]\", \"COC(O)[Pt]\", \"COC(O)C#[Pt]\", \"COC(O)=[Pt]\", \"O=CCCO[Pt]\", \"O=CCC[Pt]\", \"C=COOC#[Pt]\", \"C=CC=O.[Pt]\", \"C=C([Pt])C=O\", \"C=C(C=O)O[Pt]\", \"C=CC=[Pt]\", \"CC(O)O.[Pt]\", \"OC(O)C[Pt]\"]\n" - ] - } - ], - "source": [ - "println(ssys.names)" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "44de0eb2", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "vacantX+CO2<=>CO2X\n", - "kf = 20654.615923781494\n", - "krev = 11189.298481041604\n", - "Kc = 1.8459259048971917\n", - "proton+CO2X<=>CHO2X\n", - "kf = 1.261250440525981e10\n", - "krev = 23.133946094360056\n", - "Kc = 5.45194682905165e8\n", - "proton+CO2X<=>CO2HX\n", - "kf = 2.5e10\n", - "krev = 1.8241783944488439e-10\n", - "Kc = 1.3704799966975535e20\n", - "proton+CHO2X<=>CH2O2X\n", - "kf = 2.5e10\n", - "krev = 2.56122922738614e-35\n", - "Kc = 9.760938120136059e44\n", - "proton+CO2HX<=>CH2O2X\n", - "kf = 2.5e10\n", - "krev = 6.438275231125871e-24\n", - "Kc = 3.883027534942493e33\n", - "proton+OCX<=>CHOX\n", - "kf = 2.5e10\n", - "krev = 7.32332564140934e-20\n", - "Kc = 3.4137496028633335e29\n", - "proton+CHOX<=>CH2OX\n", - "kf = 2.5e10\n", - "krev = 1.9481188918832043e-19\n", - "Kc = 1.2832892337404028e29\n", - "vacantX+vacantX+CO2<=>OX+OCX\n", - "kf = 3.0109478093923404e-24\n", - "krev = 3.037156297092479e15\n", - "Kc = 9.913707148607306e-40\n", - "OX+proton<=>HOX\n", - "kf = 2.5e10\n", - "krev = 1.3369541151001713e-23\n", - "Kc = 1.8699220652106578e33\n", - "vacantX+C=O<=>CH2OX\n", - "kf = 500114.13488002896\n", - "krev = 399.6803280141717\n", - "Kc = 1251.2853393732605\n", - "proton+CHO2X<=>OX+C=O\n", - "kf = 0.00019467779835038066\n", - "krev = 5.644771409631564e-12\n", - "Kc = 3.44881633325675e7\n", - "HX+CO2<=>CHO2X\n", - "kf = 6.542996392927688e-8\n", - "krev = 15.579156394796986\n", - "Kc = 4.199839983064083e-9\n", - "HX+CO2<=>CO2HX\n", - "kf = 6.542996392927688e-8\n", - "krev = 6.197590078701277e-11\n", - "Kc = 1055.7323588427441\n", - "vacantX+vacantX+C=O<=>HX+CHOX\n", - "kf = 2.0718885766149262e-11\n", - "krev = 0.008867505326838887\n", - "Kc = 2.336495440655708e-9\n", - "vacantX+O=CO<=>CH2O2X\n", - "kf = 403943.82249737746\n", - "krev = 29.756334575496034\n", - "Kc = 13575.053119278344\n", - "vacantX+vacantX+O=CO<=>HOX+CHOX\n", - "kf = 8.486192390111145e-15\n", - "krev = 9.7037034735699e11\n", - "Kc = 8.745312975839684e-27\n", - "vacantX+vacantX+O=CO<=>HX+CHO2X\n", - "kf = 1.2668346793097018e-21\n", - "krev = 380.13410282264914\n", - "Kc = 3.332599390328158e-24\n", - "vacantX+vacantX+O=CO<=>HX+CO2HX\n", - "kf = 9.840171155787102e-15\n", - "krev = 0.011746228705195169\n", - "Kc = 8.377302539184302e-13\n", - "proton+CH2OX<=>CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.3777858241445543e-5\n", - "Kc = 1.8145055321295748e15\n", - "HX+C=O<=>CO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.180104845075902e-9\n", - "Kc = 9.475050217848336\n", - "proton+CO2HX<=>H2O+OCX\n", - "kf = 2.5e10\n", - "krev = 1.1320032163576973e-16\n", - "Kc = 2.2084742904211277e26\n", - "vacantX+vacantX+H2O<=>HX+HOX\n", - "kf = 1.7047654949014593e-31\n", - "krev = 21441.30602897437\n", - "Kc = 7.950847269274322e-36\n", - "proton+CH2OX<=>OC[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.217752261552598e-12\n", - "Kc = 4.020745592356135e21\n", - "HX+C=O<=>OC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.886422105564557e-15\n", - "Kc = 2.099567387708916e7\n", - "vacantX+vacantX+O=CC=O<=>CHOX+CHOX\n", - "kf = 3.132095071630788e8\n", - "krev = 159.05427897483804\n", - "Kc = 1.9691988746346629e6\n", - "proton+CH2O2X<=>OC(O)[Pt]\n", - "kf = 1.1745297739181835\n", - "krev = 0.062358932005321215\n", - "Kc = 18.83498860785426\n", - "HX+O=CO<=>OC(O)[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 29981.045237801853\n", - "Kc = 1.0670229661561413e-12\n", - "proton+CH2O2X<=>OCO[Pt]\n", - "kf = 0.8230230555301419\n", - "krev = 0.06173768521179192\n", - "Kc = 13.33096718328118\n", - "HOX+C=O<=>OCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.962949149852605e-13\n", - "Kc = 201771.41789913058\n", - "HX+O=CO<=>OCO[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 42359.465576793365\n", - "Kc = 7.552140562327293e-13\n", - "vacantX+H2O<=>H2OX\n", - "kf = 4.842414926683719e6\n", - "krev = 2.0721934488233277e8\n", - "Kc = 0.023368546645263413\n", - "proton+HOX<=>H2OX\n", - "kf = 2.5e10\n", - "krev = 3.54967493567135e-41\n", - "Kc = 7.042898421140005e50\n", - "vacantX+vacantX+H2<=>HX+HX\n", - "kf = 3.8736093818093735e10\n", - "krev = 4.9917087254698525e28\n", - "Kc = 7.760086965901168e-19\n", - "proton+CHOX<=>OC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 66.60040554908542\n", - "Kc = 3.7537308960640866e8\n", - "vacantX+vacantX+O=CO<=>OX+OC=[Pt]\n", - "kf = 1.3995006080437096e-36\n", - "krev = 7.971831424002446e14\n", - "Kc = 1.755557203367275e-51\n", - "proton+OC=[Pt]<=>OC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.8187457787854978e-32\n", - "Kc = 1.3745736370420184e42\n", - "proton+OC(O)[Pt]<=>H2O+OC=[Pt]\n", - "kf = 5.0e10\n", - "krev = 1.2921671348706252e-19\n", - "Kc = 3.869468480562007e29\n", - "proton+O=CC(=O)[Pt]<=>OCX+C=O\n", - "kf = 5.62164531143393e9\n", - "krev = 1.7656310757388884e-16\n", - "Kc = 3.183929751055929e25\n", - "vacantX+vacantX+O=CC=O<=>HX+O=CC(=O)[Pt]\n", - "kf = 1.43713660093583e-9\n", - "krev = 0.00032277677938391324\n", - "Kc = 4.452416322137251e-6\n", - "proton+OCX<=>OC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.6472201079836807e8\n", - "Kc = 94.43869032500609\n", - "proton+OC#[Pt]<=>OC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.842447691504493e-26\n", - "Kc = 1.356890625187067e36\n", - "vacantX+O=CC=O<=>O=CC=O.[Pt]\n", - "kf = 359723.7676387533\n", - "krev = 0.32068189796600394\n", - "Kc = 1.121746409511672e6\n", - "proton+O=CC(=O)[Pt]<=>O=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.141025971459258e-19\n", - "Kc = 6.037151221051202e28\n", - "vacantX+vacantX+OO<=>HOX+HOX\n", - "kf = 4.0912386971316826e8\n", - "krev = 1.7763617117679594e-6\n", - "Kc = 2.3031563166601894e14\n", - "OCX<=>vacantX+CO\n", - "kf = 2.010168305725754e-19\n", - "krev = 2.61760793808642e-25\n", - "Kc = 767940.9419866255\n", - "vacantX+vacantX+O2<=>OX+OX\n", - "kf = 1.0945721587141857e10\n", - "krev = 4.219325007995329e-16\n", - "Kc = 2.594187830138819e25\n", - "proton+HX<=>[H][H].[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 3.360026623164089e-25\n", - "Kc = 7.440417235878283e34\n", - "vacantX+H2<=>[H][H].[Pt]\n", - "kf = 2338.960705505517\n", - "krev = 9707.159813448116\n", - "Kc = 0.24095211683495363\n", - "CHOX+C=O<=>O=COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 7.563806299311394e-5\n", - "Kc = 0.0005236345532350701\n", - "proton+OO[Pt]<=>OX+H2O\n", - "kf = 4214.261766679054\n", - "krev = 4.2823372333046466e-70\n", - "Kc = 9.841031981096316e72\n", - "vacantX+vacantX+OO<=>HX+OO[Pt]\n", - "kf = 4.980245005159166e-22\n", - "krev = 5.509834949091977\n", - "Kc = 9.038827934364735e-23\n", - "proton+OC#[Pt]<=>H2O+CX\n", - "kf = 0.008001673217280904\n", - "krev = 6.379946532921906e-11\n", - "Kc = 1.2541912657089739e8\n", - "vacantX+vacantX+O=C=C=O<=>OCX+OCX\n", - "kf = 74.64023007210145\n", - "krev = 2.953439666185894e-39\n", - "Kc = 2.52723056870475e40\n", - "HX+O=C=C=O<=>O=CC(=O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 5.0006650398424424e-61\n", - "Kc = 1.1597065597154312e53\n", - "proton+OC=[Pt]<=>H2O+CHX\n", - "kf = 2.5e10\n", - "krev = 1.8308117216940032e-14\n", - "Kc = 1.3655145258119792e24\n", - "proton+CX<=>CHX\n", - "kf = 2.5e10\n", - "krev = 1.69224256390576e-42\n", - "Kc = 1.477329582249666e52\n", - "H2+CX<=>CH2X\n", - "kf = 4.832014059685671\n", - "krev = 1.8278921581756875e-33\n", - "Kc = 2.643489681857502e33\n", - "vacantX+vacantX+C=O<=>OX+CH2X\n", - "kf = 4.5608316796485725e-28\n", - "krev = 3.884151005592286e17\n", - "Kc = 1.1742158513101117e-45\n", - "proton+OC[Pt]<=>H2O+CH2X\n", - "kf = 1.7597873266199853e6\n", - "krev = 1.3379256192080917e-10\n", - "Kc = 1.3153102843352312e16\n", - "proton+O=COC[Pt]<=>CH2X+O=CO\n", - "kf = 483827.72865357465\n", - "krev = 1.0090738757247668e-12\n", - "Kc = 4.7947701381731405e17\n", - "proton+CHX<=>CH2X\n", - "kf = 2.5e10\n", - "krev = 1.888165712127775e-24\n", - "Kc = 1.3240363300436955e34\n", - "proton+O=COC#[Pt]<=>CX+O=CO\n", - "kf = 1.5104207848670912e10\n", - "krev = 2.568997423330478e-30\n", - "Kc = 5.879417282205616e39\n", - "vacantX+vacantX+C=C=O<=>OCX+CH2X\n", - "kf = 2.4823885573387985e-14\n", - "krev = 9.351132511056354e15\n", - "Kc = 2.6546394828687704e-30\n", - "CHOX+C=O<=>O=CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.4949222028864902e7\n", - "Kc = 2.6494156850764662e-15\n", - "HX+O=CC=O<=>O=CCO[Pt]\n", - "kf = 5.6976884072695144e-8\n", - "krev = 2.551666729065355e-8\n", - "Kc = 2.23292812590636\n", - "proton+O=CC=O.[Pt]<=>O=CCO[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 0.10482305575728416\n", - "Kc = 4.769942990001556e11\n", - "O=O.[Pt]+proton<=>OO[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.970670439308934e-38\n", - "Kc = 2.5073539590114812e47\n", - "proton+O=CC#[Pt]<=>CX+C=O\n", - "kf = 1.3997507903442241e-14\n", - "krev = 1.1422410075505664e-6\n", - "Kc = 1.2254426001968397e-8\n", - "proton+CO2HX<=>OC(O)=[Pt]\n", - "kf = 2.956659508366566e-12\n", - "krev = 1.0085447542339824e12\n", - "Kc = 2.93160962461426e-24\n", - "proton+OC(O)=[Pt]<=>OC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0020982771188749e-48\n", - "Kc = 2.4947652910727788e58\n", - "proton+OC(O)=[Pt]<=>H2O+OC#[Pt]\n", - "kf = 1.4395474778874738e7\n", - "krev = 2.0234376577289587e-45\n", - "Kc = 7.114365359312209e51\n", - "proton+O=C(O)C#[Pt]<=>CX+O=CO\n", - "kf = 2.9703240042391747e-7\n", - "krev = 2.6091607384758988e-11\n", - "Kc = 11384.212403771811\n", - "proton+O=C=C=O.[Pt]<=>O=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 7.45107152375986e-58\n", - "Kc = 3.355222120775567e67\n", - "vacantX+O=C=C=O<=>O=C=C=O.[Pt]\n", - "kf = 366139.2749661925\n", - "krev = 442.06521987276346\n", - "Kc = 828.2471873077366\n", - "HOX+C=O<=>OOC[Pt]\n", - "kf = 1.5395975576095126e-29\n", - "krev = 2.622153295712258e16\n", - "Kc = 5.871500953537159e-46\n", - "proton+OOC[Pt]<=>OO+CH2X\n", - "kf = 3793.8445642184756\n", - "krev = 2.336579913888904e-16\n", - "Kc = 1.6236742178888983e19\n", - "vacantX+vacantX+O=C=CO<=>OCX+OC=[Pt]\n", - "kf = 73.33238091278024\n", - "krev = 14511.198914062346\n", - "Kc = 0.005053502563576338\n", - "vacantX+C=C=O<=>C=C=O.[Pt]\n", - "kf = 422670.5724931744\n", - "krev = 9.80980243728561e-11\n", - "Kc = 4.3086552985681545e15\n", - "proton+CO[Pt]<=>OX+CH4\n", - "kf = 1.3228476854746191e8\n", - "krev = 1.372992444355147e-26\n", - "Kc = 9.634777605028415e33\n", - "HX+C=C=O<=>CC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.3310785577331067e-33\n", - "Kc = 2.514767798332947e25\n", - "proton+C=C=O.[Pt]<=>CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.7875192879981122e-17\n", - "Kc = 1.3985863071719982e27\n", - "proton+CC(=O)[Pt]<=>OCX+CH4\n", - "kf = 2.4493635841444016e10\n", - "krev = 2.984491331023716e-15\n", - "Kc = 8.20697168285706e24\n", - "vacantX+vacantX+COC=O<=>CHOX+CO[Pt]\n", - "kf = 5.858305523872122e-8\n", - "krev = 9.372228401924443e12\n", - "Kc = 6.250707166578664e-21\n", - "vacantX+vacantX+COC=O<=>HX+O=COC[Pt]\n", - "kf = 8.724708246600757e-23\n", - "krev = 252.56605644619947\n", - "Kc = 3.454426287270814e-25\n", - "vacantX+vacantX+COC=O<=>HX+COC(=O)[Pt]\n", - "kf = 7.165711269221808e-16\n", - "krev = 0.1859922027934253\n", - "Kc = 3.852694447186316e-15\n", - "proton+O=COCC#[Pt]<=>CX+COC=O\n", - "kf = 198.60286788625663\n", - "krev = 1.4871109577323497e-12\n", - "Kc = 1.3354946169524573e14\n", - "HOX+C=C=O<=>O=C([Pt])CO\n", - "kf = 3.3473534940386794e-8\n", - "krev = 9.042590347389556e-30\n", - "Kc = 3.70176394754519e21\n", - "HX+O=C=CO<=>O=C([Pt])CO\n", - "kf = 2.8488442036348548e-8\n", - "krev = 1.614840618256874e-45\n", - "Kc = 1.7641643214981894e37\n", - "vacantX+vacantX+COO<=>HOX+CO[Pt]\n", - "kf = 3.442529358831723e8\n", - "krev = 2.6586367586035048e-11\n", - "Kc = 1.294847574679578e19\n", - "vacantX+vacantX+COO<=>HX+OOC[Pt]\n", - "kf = 1.3336211820914592e-23\n", - "krev = 16620.58178963317\n", - "Kc = 8.023913957833202e-28\n", - "CHOX+C=C=O<=>O=CCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 2.6714659015861004e-16\n", - "Kc = 1.2530025152300434e8\n", - "vacantX+vacantX+CO-2<=>HX+CO[Pt]\n", - "kf = 3.6896065237788346e-26\n", - "krev = 1200.2597905170037\n", - "Kc = 3.0740066050113714e-29\n", - "vacantX+vacantX+CO-2<=>HX+OC[Pt]\n", - "kf = 1.1691860289045307e-22\n", - "krev = 1.716447494000275\n", - "Kc = 6.811662069427353e-23\n", - "proton+OCO[Pt]<=>OX+CO-2\n", - "kf = 1.5840660497455784e10\n", - "krev = 3.3768630610350926e-16\n", - "Kc = 4.690939552816876e25\n", - "proton+COC(=O)[Pt]<=>OCX+CO-2\n", - "kf = 2.5e10\n", - "krev = 2.816084072156505e-18\n", - "Kc = 8.877575867561178e27\n", - "proton+O=C([Pt])CO<=>OCX+CO-2\n", - "kf = 4.826147915772383e9\n", - "krev = 8.348957621002498e-16\n", - "Kc = 5.780539481517796e24\n", - "proton+OCC#[Pt]<=>CX+CO-2\n", - "kf = 4.5216611658649225e-8\n", - "krev = 1.1645539021172344e-8\n", - "Kc = 3.88274098574935\n", - "vacantX+vacantX+COOC<=>CO[Pt]+CO[Pt]\n", - "kf = 3.028654941635431e8\n", - "krev = 1.0392777770118965e-11\n", - "Kc = 2.914191959673513e19\n", - "vacantX+vacantX+C=C=O<=>HX+O=C=C[Pt]\n", - "kf = 3.6584912239485734e-16\n", - "krev = 0.32395775785233605\n", - "Kc = 1.1293111942132156e-15\n", - "vacantX+vacantX+O=C=CO<=>HOX+O=C=C[Pt]\n", - "kf = 3.132095071630788e8\n", - "krev = 5.819571251914923e7\n", - "Kc = 5.382003133994065\n", - "proton+O=C=C[Pt]<=>C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.7345052298033786e-38\n", - "Kc = 9.142421717656614e47\n", - "vacantX+vacantX+O=CCO<=>CHOX+OC[Pt]\n", - "kf = 9001.813049524091\n", - "krev = 8.180569891408677e12\n", - "Kc = 1.1003894800749632e-9\n", - "vacantX+vacantX+O=CCO<=>HX+O=CCO[Pt]\n", - "kf = 3.705974451661604e-28\n", - "krev = 2668.9209237076484\n", - "Kc = 1.3885665996103351e-31\n", - "vacantX+vacantX+O=CCO<=>HX+O=C([Pt])CO\n", - "kf = 1.2718474027465153e-10\n", - "krev = 0.0002705673832361486\n", - "Kc = 4.7006678614933393e-7\n", - "proton+O=CCOC#[Pt]<=>CX+O=CCO\n", - "kf = 9.43258107937277e-21\n", - "krev = 1.0340669543802994e-19\n", - "Kc = 0.09121828175067806\n", - "proton+COC#[Pt]<=>CX+CO-2\n", - "kf = 8.741799158602462e-20\n", - "krev = 6.708704383765949e-27\n", - "Kc = 1.3030532661054935e7\n", - "proton+O=CC(=O)C#[Pt]<=>CX+O=CC=O\n", - "kf = 1.4635483332046594e-9\n", - "krev = 1.1604647201701089e-10\n", - "Kc = 12.61174344869461\n", - "vacantX+vacantX+OCO<=>HOX+OC[Pt]\n", - "kf = 1.653107374238179e-12\n", - "krev = 3.492310477620836e11\n", - "Kc = 4.7335635958815765e-24\n", - "vacantX+vacantX+OCO<=>HX+OC(O)[Pt]\n", - "kf = 4.0412190145177725e-23\n", - "krev = 628.7683045605482\n", - "Kc = 6.427198993979533e-26\n", - "vacantX+vacantX+OCO<=>HX+OCO[Pt]\n", - "kf = 1.1281154422531313e-23\n", - "krev = 247.99076039714222\n", - "Kc = 4.5490220702034325e-26\n", - "proton+OC(O)C#[Pt]<=>CX+OCO\n", - "kf = 1.358310992477003\n", - "krev = 1.7481928254289914e-9\n", - "Kc = 7.76980074920331e8\n", - "proton+OCOC#[Pt]<=>CX+OCO\n", - "kf = 5.614995538406639e-16\n", - "krev = 1.2199952082641124e-19\n", - "Kc = 4602.47343626539\n", - "proton+O=COC=[Pt]<=>O=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.9109835082233935e-55\n", - "Kc = 8.588162704933284e64\n", - "proton+O=COC=[Pt]<=>CHX+O=CO\n", - "kf = 9.956705803590705e7\n", - "krev = 3.2014558811425525e-41\n", - "Kc = 3.1100556038389953e48\n", - "proton+O=COC#[Pt]<=>O=COC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.951513757763877e-34\n", - "Kc = 2.7928237252963904e43\n", - "proton+O=C=CC#[Pt]<=>CX+C=C=O\n", - "kf = 3.066944545408356e-13\n", - "krev = 1.160517266652194e-9\n", - "Kc = 0.00026427392625150115\n", - "vacantX+vacantX+COCO<=>CO[Pt]+OC[Pt]\n", - "kf = 3.0636862331912886e-9\n", - "krev = 3.008499680951675e11\n", - "Kc = 1.0183435459837431e-20\n", - "proton+CC#[Pt]<=>CX+CH4\n", - "kf = 7.746906363095054e-6\n", - "krev = 2.4945491275097783e-8\n", - "Kc = 310.55336925067985\n", - "HX+O=C=C=O<=>O=C=CO[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.1302052975227224e-55\n", - "Kc = 2.7224155607861307e47\n", - "proton+O=C=CO[Pt]<=>OX+C=C=O\n", - "kf = 11.618913103766713\n", - "krev = 1.9367160067253906e-15\n", - "Kc = 5.999285937338862e15\n", - "proton+O=C=C=O.[Pt]<=>O=C=CO[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 6.348080467566609e-52\n", - "Kc = 7.876396692741726e61\n", - "vacantX+vacantX+O=C=CO<=>HX+O=C=CO[Pt]\n", - "kf = 0.0007071288662616175\n", - "krev = 2.8988454126647536e-5\n", - "Kc = 24.393465866522067\n", - "vacantX+vacantX+OCCO<=>OC[Pt]+OC[Pt]\n", - "kf = 2.961131444342359e-9\n", - "krev = 1.299206322752899e13\n", - "Kc = 2.2791849088819035e-22\n", - "proton+COC(=O)C#[Pt]<=>CX+COC=O\n", - "kf = 6.155268088618495e-8\n", - "krev = 2.628916041505465e-12\n", - "Kc = 23413.711170074657\n", - "proton+O=C=CC(=O)[Pt]<=>OCX+C=C=O\n", - "kf = 5.247478794257851e9\n", - "krev = 1.3474399984398267e-18\n", - "Kc = 3.8944062817890216e27\n", - "vacantX+vacantX+OC=CO<=>OC=[Pt]+OC=[Pt]\n", - "kf = 1.351949923589269e-23\n", - "krev = 7.975137957191956e11\n", - "Kc = 1.6952056890377485e-35\n", - "vacantX+OX+CH4<=>HOX+CH3X\n", - "kf = 1181.9069662995785\n", - "krev = 1.0235810933777192e20\n", - "Kc = 1.1546783874244874e-17\n", - "vacantX+HOX+CH4<=>H2OX+CH3X\n", - "kf = 5.28370763875636e9\n", - "krev = 1.2149259925984929e9\n", - "Kc = 4.348995470461149\n", - "HX+CH3X<=>vacantX+vacantX+CH4\n", - "kf = 5.733311120080377e8\n", - "krev = 8.483521653048543e-25\n", - "Kc = 6.758173497465076e32\n", - "proton+CH2X<=>CH3X\n", - "kf = 2.5e10\n", - "krev = 2.173171843464259e-37\n", - "Kc = 1.1503922285385142e47\n", - "CO2+CH3X<=>COC(=O)[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.00447183609125585\n", - "Kc = 1.463156578060128e-5\n", - "vacantX+vacantX+COC=O<=>CHO2X+CH3X\n", - "kf = 0.05589950368763065\n", - "krev = 5.054770535995559e16\n", - "Kc = 1.1058761874463802e-18\n", - "vacantX+vacantX+COO<=>OO[Pt]+CH3X\n", - "kf = 9.385776922831516e-7\n", - "krev = 3.9782610412247473e11\n", - "Kc = 2.359266228528335e-18\n", - "vacantX+vacantX+CO-2<=>HOX+CH3X\n", - "kf = 9.872876935778847e-16\n", - "krev = 6.917821124819518e13\n", - "Kc = 1.427165686657795e-29\n", - "vacantX+vacantX+COCO<=>CH3X+OCO[Pt]\n", - "kf = 3.9072411322938125e-9\n", - "krev = 8.599564777209447e13\n", - "Kc = 4.543533578174534e-23\n", - "O=O+HX<=>OO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 8.854082166234876e-41\n", - "Kc = 8.666474551788235e32\n", - "vacantX+O=O<=>O=O.[Pt]\n", - "kf = 484458.3574999593\n", - "krev = 584.920039726471\n", - "Kc = 828.247152767255\n", - "vacantX+O=C=CO<=>O=C=CO.[Pt]\n", - "kf = 359723.7676387533\n", - "krev = 0.4900054095759742\n", - "Kc = 734122.0333670193\n", - "proton+O=C=CO.[Pt]<=>O=C([Pt])CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 4.341462963320168e-39\n", - "Kc = 5.75842756490569e48\n", - "proton+O=C=CO[Pt]<=>O=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.466667008678269e-12\n", - "Kc = 7.21153775006839e21\n", - "vacantX+vacantX+O=C=C=O<=>OX+O=C=C=[Pt]\n", - "kf = 149.2804601441562\n", - "krev = 1.2008902564793325e-12\n", - "Kc = 1.2430816166483347e14\n", - "proton+O=C=C=[Pt]<=>O=CC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.00020479408231265106\n", - "Kc = 1.2207383981844497e14\n", - "proton+O=C=C=[Pt]<=>O=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.684891887988982e-24\n", - "Kc = 1.483774726332084e34\n", - "vacantX+vacantX+C=CO<=>CH2X+OC=[Pt]\n", - "kf = 3.7510196251812924e-36\n", - "krev = 6.624293894020312e13\n", - "Kc = 5.662519938264367e-50\n", - "proton+O=C(C#[Pt])CO<=>CX+O=CCO\n", - "kf = 5.165048053585714e-15\n", - "krev = 8.402553010210027e-8\n", - "Kc = 6.146998474522697e-8\n", - "vacantX+vacantX+C=C<=>CH2X+CH2X\n", - "kf = 9.387035392806688e-46\n", - "krev = 5.259242712748897e15\n", - "Kc = 1.784864457776713e-61\n", - "proton+O=COC[Pt]<=>COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.784315307539344e-38\n", - "Kc = 2.845981630297715e47\n", - "proton+COC(=O)[Pt]<=>COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.797077718056667e-28\n", - "Kc = 2.551781329030731e37\n", - "vacantX+COC=O<=>COC=O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.8619443782965007\n", - "Kc = 410274.8449265323\n", - "HX+O=C=C=C=O<=>O=C=CC(=O)[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 3.561089909521239e-25\n", - "Kc = 1.4777843564830474e17\n", - "vacantX+vacantX+O=C=C=C=O<=>OCX+O=C=C=[Pt]\n", - "kf = 135.4631249389026\n", - "krev = 3.092595390223456e6\n", - "Kc = 4.3802407960361956e-5\n", - "CH3X+O=C=C=O<=>CC(=O)C(=O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 3.5093718907449027e-71\n", - "Kc = 1.6525190917893694e63\n", - "proton+OOC#[Pt]<=>OO+CX\n", - "kf = 9.668954158629247e-50\n", - "krev = 0.3093699479013615\n", - "Kc = 3.1253695532547536e-49\n", - "proton+O=CC[Pt]<=>CH2X+C=O\n", - "kf = 2.40480804579921e-10\n", - "krev = 5.6263034661071036e-8\n", - "Kc = 0.004274223849256963\n", - "HX+C=C=O<=>O=CC[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 3.6888123831707493e-19\n", - "Kc = 9.074339235332521e10\n", - "proton+C=C=O.[Pt]<=>O=CC[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 0.004953744650468719\n", - "Kc = 5.046687256605871e12\n", - "vacantX+vacantX+O=CCO<=>HOX+O=CC[Pt]\n", - "kf = 3.3834985622063113e-5\n", - "krev = 2.9362980773683545e12\n", - "Kc = 1.1523007790948657e-17\n", - "vacantX+vacantX+O=CC=O<=>OX+O=CC=[Pt]\n", - "kf = 6.170227811474367e-18\n", - "krev = 2.1467268001769245e15\n", - "Kc = 2.874249210922341e-33\n", - "proton+O=CC=[Pt]<=>CHX+C=O\n", - "kf = 85.93041334500542\n", - "krev = 1.3446130336912793e-10\n", - "Kc = 6.390716971492252e11\n", - "proton+O=CC#[Pt]<=>O=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.825091661818015e-23\n", - "Kc = 2.832831766287838e32\n", - "proton+O=C=C[Pt]<=>O=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.0107266618178345\n", - "Kc = 2.3306412026931045e12\n", - "proton+O=CC=[Pt]<=>O=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.262838419245673e-38\n", - "Kc = 1.979667360368492e48\n", - "proton+O=CCO[Pt]<=>OX+CC=O\n", - "kf = 2.6580189250488807e7\n", - "krev = 4.498498104855556e-30\n", - "Kc = 5.908680770988628e36\n", - "vacantX+vacantX+CC=O<=>HX+CC(=O)[Pt]\n", - "kf = 4.3209399543319175e-11\n", - "krev = 0.0003615296985530135\n", - "Kc = 1.195182573278502e-7\n", - "proton+O=CCC(=O)[Pt]<=>OCX+CC=O\n", - "kf = 1.7980345225965273e9\n", - "krev = 6.3657815059751266e-21\n", - "Kc = 2.824530689450831e29\n", - "proton+O=CCC#[Pt]<=>CX+CC=O\n", - "kf = 28.689968799429533\n", - "krev = 4.385785098300487e-12\n", - "Kc = 6.541581075312385e12\n", - "vacantX+vacantX+CC=O<=>CHOX+CH3X\n", - "kf = 6.063283190982672e-6\n", - "krev = 7.026751658283665e14\n", - "Kc = 8.628856526948432e-21\n", - "proton+CC(=O)C#[Pt]<=>CX+CC=O\n", - "kf = 2.014113930200813e-15\n", - "krev = 4.3640354911232775e-9\n", - "Kc = 4.6152556144367916e-7\n", - "proton+CC(=O)C(=O)[Pt]<=>OCX+CC=O\n", - "kf = 8.358498811557002e9\n", - "krev = 1.381501911050158e-17\n", - "Kc = 6.0502984069006705e26\n", - "vacantX+vacantX+CC=O<=>HX+O=CC[Pt]\n", - "kf = 3.2094062904328744e-20\n", - "krev = 74.41720028073364\n", - "Kc = 4.312721089110603e-22\n", - "vacantX+CH4<=>C.[Pt]\n", - "kf = 11983.404197457203\n", - "krev = 27576.843954134933\n", - "Kc = 0.4345458899280744\n", - "proton+CH3X<=>C.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.552563854510203e-40\n", - "Kc = 7.037171187862234e49\n", - "HX+O=C=CC=O<=>O=CCC(=O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 3.8194581898791103e-32\n", - "Kc = 6.789235995427004e23\n", - "vacantX+vacantX+O=C=CC=O<=>CHOX+O=C=C[Pt]\n", - "kf = 2.850945414803626e8\n", - "krev = 4.6591458607721776e7\n", - "Kc = 6.119030182779314\n", - "vacantX+vacantX+O=C=CC=O<=>HX+O=C=CC(=O)[Pt]\n", - "kf = 1.1776167531898308e-10\n", - "krev = 0.0005032011998508361\n", - "Kc = 2.3402502886298994e-7\n", - "vacantX+vacantX+O=C=CC=O<=>OCX+O=CC=[Pt]\n", - "kf = 0.006845452357086415\n", - "krev = 1.638610749190394e14\n", - "Kc = 4.177595173514284e-17\n", - "vacantX+vacantX+C=C(O)O<=>CH2X+OC(O)=[Pt]\n", - "kf = 1.3631835715271243e-51\n", - "krev = 1.0974745099569602e16\n", - "Kc = 1.242109551665655e-67\n", - "proton+O=C=CC=O.[Pt]<=>O=CCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.7237756465594025e-25\n", - "Kc = 1.4503047452781423e35\n", - "proton+O=C=CC(=O)[Pt]<=>O=C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.176578896888088e-20\n", - "Kc = 1.1485914907905776e30\n", - "vacantX+O=C=CC=O<=>O=C=CC=O.[Pt]\n", - "kf = 327433.4917974331\n", - "krev = 0.29189612518083846\n", - "Kc = 1.1217466199476891e6\n", - "vacantX+vacantX+CC(=O)O<=>HOX+CC(=O)[Pt]\n", - "kf = 3.661873055903852e-12\n", - "krev = 2.1682718089028445e11\n", - "Kc = 1.6888441019563762e-23\n", - "vacantX+vacantX+CC(=O)O<=>CO2HX+CH3X\n", - "kf = 1.1977509649486271e-8\n", - "krev = 1.0254845667743408e14\n", - "Kc = 1.1679853639496008e-22\n", - "CO2+CH3X<=>CC(=O)O[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 3.3286101924403974e-7\n", - "Kc = 0.19656841788766613\n", - "proton+CC(=O)O[Pt]<=>OX+CC=O\n", - "kf = 0.0016211563581664359\n", - "krev = 8.125014520720125e-15\n", - "Kc = 1.995265798026847e11\n", - "vacantX+vacantX+CC(=O)O<=>HX+CC(=O)O[Pt]\n", - "kf = 2.4753542791841756e-22\n", - "krev = 11382.562807978633\n", - "Kc = 2.1746897609465158e-26\n", - "proton+CC(=O)OC#[Pt]<=>CX+CC(=O)O\n", - "kf = 2.5e10\n", - "krev = 4.5470286185254115e-27\n", - "Kc = 5.498096030921272e36\n", - "vacantX+vacantX+CC(=O)C=O<=>CHOX+CC(=O)[Pt]\n", - "kf = 2.810784197367395e8\n", - "krev = 8.682228189641076\n", - "Kc = 3.237399589106622e7\n", - "vacantX+vacantX+CC(=O)C=O<=>CH3X+O=CC(=O)[Pt]\n", - "kf = 0.010756441693245073\n", - "krev = 2.0353876594794328e15\n", - "Kc = 5.284714016589902e-18\n", - "vacantX+vacantX+CC(=O)C=O<=>HX+CC(=O)C(=O)[Pt]\n", - "kf = 2.426386880233808e-11\n", - "krev = 0.0003222108693910823\n", - "Kc = 7.530431499158364e-8\n", - "proton+O=C=C([Pt])C=O<=>C=O+O=C=C=[Pt]\n", - "kf = 3.2500134642798374e6\n", - "krev = 3.1747345047681616e-16\n", - "Kc = 1.0237118913088997e22\n", - "HX+O=C=C=C=O<=>O=C=C([Pt])C=O\n", - "kf = 5.262522960320117e-8\n", - "krev = 8.417963556232881e-20\n", - "Kc = 6.251539253129229e11\n", - "vacantX+vacantX+O=C=CC=O<=>HX+O=C=C([Pt])C=O\n", - "kf = 3.109950102720783e-13\n", - "krev = 0.31413419650430946\n", - "Kc = 9.900068624582613e-13\n", - "proton+O=C=C([Pt])C=O<=>O=C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.207681994828816e-26\n", - "Kc = 2.715124177186007e35\n", - "proton+O=C=COC#[Pt]<=>CX+O=C=CO\n", - "kf = 8.139655510252454e-22\n", - "krev = 2.052818179183715e-20\n", - "Kc = 0.039651127375972074\n", - "vacantX+vacantX+COC(C)=O<=>CO[Pt]+CC(=O)[Pt]\n", - "kf = 6.614441053978493e-6\n", - "krev = 7.629970776987544e11\n", - "Kc = 8.669025409544227e-18\n", - "vacantX+vacantX+COC(C)=O<=>CH3X+COC(=O)[Pt]\n", - "kf = 1.5563360867242215e-10\n", - "krev = 4.0343976517667425e14\n", - "Kc = 3.857666549162974e-25\n", - "vacantX+vacantX+COC(C)=O<=>CH3X+CC(=O)O[Pt]\n", - "kf = 0.0003463783354588583\n", - "krev = 6.683486846094463e16\n", - "Kc = 5.182599194629471e-21\n", - "vacantX+vacantX+COO<=>HX+COO[Pt]\n", - "kf = 1.175900379595729e-21\n", - "krev = 0.27982743013843664\n", - "Kc = 4.2022341377111815e-21\n", - "proton+COO[Pt]<=>OX+CO-2\n", - "kf = 31692.92485485011\n", - "krev = 1.0296413078769447e-65\n", - "Kc = 3.0780549121712023e69\n", - "vacantX+vacantX+COOC<=>CH3X+COO[Pt]\n", - "kf = 1.8186835430204133e-8\n", - "krev = 4.141977957602716e12\n", - "Kc = 4.39085760869917e-21\n", - "O=O+CH3X<=>COO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 4.970959816815508e-38\n", - "Kc = 1.543639067721808e30\n", - "proton+CO[Pt]<=>CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.994652282073202e-35\n", - "Kc = 3.574159084944541e44\n", - "proton+OC[Pt]<=>CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.5499383625577767e-28\n", - "Kc = 1.6129673672147772e38\n", - "vacantX+CO-2<=>CO.[Pt]\n", - "kf = 484125.61468448705\n", - "krev = 1.0558750276780043e7\n", - "Kc = 0.04585065485913965\n", - "vacantX+vacantX+CC(=O)CO<=>OC[Pt]+CC(=O)[Pt]\n", - "kf = 4.324183911493771e7\n", - "krev = 7.8667392573421875e12\n", - "Kc = 5.496793232924203e-6\n", - "vacantX+vacantX+CC(=O)CO<=>CH3X+O=C([Pt])CO\n", - "kf = 0.43146252134138535\n", - "krev = 2.5450806210309695e15\n", - "Kc = 1.695280368629765e-16\n", - "HX+O=C=C=O<=>O=C=C(O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 7.390785994602033e-44\n", - "Kc = 7.846667531546056e35\n", - "proton+O=C=C=O.[Pt]<=>O=C=C(O)[Pt]\n", - "kf = 5.0e10\n", - "krev = 2.202478055371417e-40\n", - "Kc = 2.2701701784523888e50\n", - "vacantX+vacantX+O=C=CO<=>HX+O=C=C(O)[Pt]\n", - "kf = 2.8707175642480555e-12\n", - "krev = 0.04083063397693327\n", - "Kc = 7.030793511239207e-11\n", - "proton+O=C=C(O)[Pt]<=>O=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.991782243495115e-24\n", - "Kc = 2.5020561288028055e33\n", - "proton+O=C=C(O)[Pt]<=>H2O+O=C=C=[Pt]\n", - "kf = 3.009739193825949e8\n", - "krev = 8.07800980988232e-39\n", - "Kc = 3.725842459542389e46\n", - "vacantX+vacantX+O=CCC=O<=>HX+O=CCC(=O)[Pt]\n", - "kf = 3.286584099620913e-11\n", - "krev = 0.0009472638388816695\n", - "Kc = 3.469555117295539e-8\n", - "vacantX+vacantX+O=CCC=O<=>CHOX+O=CC[Pt]\n", - "kf = 5.621568394735124e8\n", - "krev = 2.2372815421494465e13\n", - "Kc = 2.51267812692642e-5\n", - "proton+O=C=C(O)C#[Pt]<=>CX+O=C=CO\n", - "kf = 7.546044157424521e-29\n", - "krev = 0.006685610947353043\n", - "Kc = 1.1286992642627731e-26\n", - "proton+COOC#[Pt]<=>CX+COO\n", - "kf = 1.7959387444220673e-57\n", - "krev = 9.424056367534934e8\n", - "Kc = 1.90569609771109e-66\n", - "vacantX+vacantX+COC=C=O<=>CO[Pt]+O=C=C[Pt]\n", - "kf = 1.4053920986837533e8\n", - "krev = 2.5815645207863396e8\n", - "Kc = 0.5443954963619013\n", - "vacantX+vacantX+COC=C=O<=>CH3X+O=C=CO[Pt]\n", - "kf = 1.4053920986837533e8\n", - "krev = 1.2268284001067661e8\n", - "Kc = 1.1455490421981163\n", - "HX+O=CC=O<=>O=CC(O)[Pt]\n", - "kf = 5.6976884072695144e-8\n", - "krev = 1.248882373151946e-25\n", - "Kc = 4.562229822244678e17\n", - "proton+O=CC(O)[Pt]<=>C=O+OC=[Pt]\n", - "kf = 3.658011462340569e-7\n", - "krev = 5.27514552652793e-13\n", - "Kc = 693442.7579191831\n", - "proton+O=CC=O.[Pt]<=>O=CC(O)[Pt]\n", - "kf = 5.0e10\n", - "krev = 5.1304374957754005e-19\n", - "Kc = 9.745757557941584e28\n", - "HX+O=C=CO<=>O=CC(O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 2.6755933088589045e-38\n", - "Kc = 1.0647523277182356e30\n", - "vacantX+vacantX+O=CCO<=>HX+O=CC(O)[Pt]\n", - "kf = 5.743984385098034e-15\n", - "krev = 0.20246227896672986\n", - "Kc = 2.8370639777506056e-14\n", - "proton+O=C=CO.[Pt]<=>O=CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 7.193272898880144e-32\n", - "Kc = 3.4754694214217865e41\n", - "proton+O=CC(O)[Pt]<=>H2O+O=CC=[Pt]\n", - "kf = 112236.45929355851\n", - "krev = 7.574894709403204e-14\n", - "Kc = 1.481690024737006e18\n", - "proton+O=CC(O)C#[Pt]<=>CX+O=CCO\n", - "kf = 51.23050028548895\n", - "krev = 1.6828072651358383e-10\n", - "Kc = 3.044347463127547e11\n", - "vacantX+vacantX+O=C=CCO<=>OC[Pt]+O=C=C[Pt]\n", - "kf = 4067.906517801298\n", - "krev = 9.581534474143486e11\n", - "Kc = 4.245568941779481e-9\n", - "proton+O=CC(=O)[Pt]<=>O=CC(O)=[Pt]\n", - "kf = 4290.071779320444\n", - "krev = 8.318634576211465e10\n", - "Kc = 5.1571826361848204e-8\n", - "proton+O=CC(O)=[Pt]<=>OC#[Pt]+C=O\n", - "kf = 8.434006634376515e7\n", - "krev = 1.4465485601072513e-27\n", - "Kc = 5.830434502489978e34\n", - "proton+O=CC(O)=[Pt]<=>H2O+O=CC#[Pt]\n", - "kf = 2.6750529390132133e7\n", - "krev = 4.4829166254907855e-44\n", - "Kc = 5.967215459244351e50\n", - "proton+O=C=C(O)[Pt]<=>O=CC(O)=[Pt]\n", - "kf = 1.5878148518961966e10\n", - "krev = 2.0831689134324427\n", - "Kc = 7.622112838079702e9\n", - "proton+O=CC(O)=[Pt]<=>O=CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.1913152578475854e-55\n", - "Kc = 1.140867335745939e65\n", - "proton+OC(O)[Pt]<=>OCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.2127166260183894e-35\n", - "Kc = 2.061487363464324e45\n", - "proton+OCO[Pt]<=>OCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.583326425442653e-36\n", - "Kc = 2.912623703311006e45\n", - "vacantX+OCO<=>OCO.[Pt]\n", - "kf = 395377.4080430906\n", - "krev = 715.0601225795458\n", - "Kc = 552.9289014422803\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.847308186650777e-22\n", - "Kc = 4.275471584869465e31\n", - "vacantX+O=C=C=C=O<=>O=C=C=C=O.[Pt]\n", - "kf = 332249.5811031886\n", - "krev = 401.14766551623046\n", - "Kc = 828.2475748067037\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.3822292744050985e-16\n", - "Kc = 1.8086724440675597e26\n", - "proton+O=CCO[Pt]<=>O=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.291023506579326e-41\n", - "Kc = 4.724983733093001e50\n", - "proton+O=C([Pt])CO<=>O=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.7911524127660506e-16\n", - "Kc = 1.395749452800215e26\n", - "vacantX+O=CCO<=>O=CCO.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 1291.5767888759226\n", - "Kc = 273.8002875141987\n", - "proton+O=CC(O)[Pt]<=>O=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.081040851779133e-23\n", - "Kc = 2.3125860561935302e33\n", - "proton+OCC#[Pt]<=>OCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0254431194560544e-15\n", - "Kc = 2.43797042719066e25\n", - "proton+OCC=[Pt]<=>CHX+CO-2\n", - "kf = 5.952059546394487e9\n", - "krev = 2.5297632908193934e-18\n", - "Kc = 2.352812837467733e27\n", - "vacantX+vacantX+O=CCO<=>OX+OCC=[Pt]\n", - "kf = 3.3881471741726223e-34\n", - "krev = 2.264159139077055e16\n", - "Kc = 1.4964262518904662e-50\n", - "vacantX+vacantX+O=C=CCO<=>OCX+OCC=[Pt]\n", - "kf = 1.8009876630720204e-13\n", - "krev = 6.668943472119082e14\n", - "Kc = 2.7005591974222413e-28\n", - "vacantX+vacantX+C=CC=O<=>CH2X+O=CC=[Pt]\n", - "kf = 3.2830355290077765e-39\n", - "krev = 2.9277080237249806e14\n", - "Kc = 1.121367124864694e-53\n", - "vacantX+vacantX+C=COC=O<=>CH2X+O=COC=[Pt]\n", - "kf = 1.0242943870290668e-63\n", - "krev = 2.920849603333263e13\n", - "Kc = 3.5068371403311754e-77\n", - "vacantX+O=C=CCO<=>O=C=CCO.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 1179.037991138623\n", - "Kc = 273.8002884035305\n", - "vacantX+vacantX+O=CC=CO<=>OC=[Pt]+O=CC=[Pt]\n", - "kf = 6.284377773759944e-35\n", - "krev = 2.1623088290446475e12\n", - "Kc = 2.90632757418676e-47\n", - "vacantX+vacantX+COC<=>CH3X+CO[Pt]\n", - "kf = 3.3416169046706564e-11\n", - "krev = 3.110510590664853e12\n", - "Kc = 1.0742985137872191e-23\n", - "proton+O=C=CC(O)[Pt]<=>OC=[Pt]+C=C=O\n", - "kf = 1.9258714668753756e-6\n", - "krev = 8.017560533946666e-15\n", - "Kc = 2.4020666370040616e8\n", - "HX+O=C=CC=O<=>O=C=CC(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 3.0624966294759025e-24\n", - "Kc = 8.467340919226885e15\n", - "proton+O=C=CC=O.[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3821481595346329e-17\n", - "Kc = 1.8087785905975132e27\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=CC(O)[Pt]\n", - "kf = 2.2665619116480148e-11\n", - "krev = 0.03466826587817799\n", - "Kc = 6.537857761944495e-10\n", - "proton+O=C=CC(O)[Pt]<=>O=C=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.4911991256645053e-19\n", - "Kc = 1.0035327863777839e29\n", - "proton+O=C=CC=[Pt]<=>CHX+C=C=O\n", - "kf = 44288.19970436381\n", - "krev = 5.70447672901406e-14\n", - "Kc = 7.763762008021797e17\n", - "proton+O=C=CC#[Pt]<=>O=C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.971420643860761e-21\n", - "Kc = 5.028743651147818e30\n", - "vacantX+vacantX+O=C=CC=O<=>OX+O=C=CC=[Pt]\n", - "kf = 3.709849833927781e-21\n", - "krev = 2.4389911159903437e17\n", - "Kc = 1.5210591828750508e-38\n", - "proton+O=C=CC(O)[Pt]<=>H2O+O=C=CC=[Pt]\n", - "kf = 1146.5026649283363\n", - "krev = 2.7137254458366483e-12\n", - "Kc = 4.224829253406167e14\n", - "vacantX+vacantX+CCO<=>CH3X+OC[Pt]\n", - "kf = 1.5510087911871897e-15\n", - "krev = 9.749013808701775e13\n", - "Kc = 1.5909391674086975e-29\n", - "proton+O=C=C([Pt])CO<=>CO-2+O=C=C=[Pt]\n", - "kf = 6.328347966205425e7\n", - "krev = 3.440673057239973e-28\n", - "Kc = 1.839276170948331e35\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=C([Pt])CO\n", - "kf = 4.040764431615523e-20\n", - "krev = 30.812673220085827\n", - "Kc = 1.3113969056672023e-21\n", - "proton+O=C=C([Pt])CO<=>O=C=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.996974458229339e-31\n", - "Kc = 5.003027373659754e40\n", - "proton+O=C=CC[Pt]<=>CH2X+C=C=O\n", - "kf = 1.4688383778113973e-5\n", - "krev = 6.005179601514828e-13\n", - "Kc = 2.4459524531803805e7\n", - "vacantX+vacantX+O=C=CCO<=>HOX+O=C=CC[Pt]\n", - "kf = 8.032715739528718e-6\n", - "krev = 4.997427676480693e14\n", - "Kc = 1.6073700830795308e-20\n", - "proton+O=C=CC=[Pt]<=>O=C=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.94861556912504e-35\n", - "Kc = 4.2026585361738475e44\n", - "vacantX+vacantX+CC(O)O<=>CH3X+OC(O)[Pt]\n", - "kf = 1.0212279299691738e-21\n", - "krev = 4.839386960246169e15\n", - "Kc = 2.1102423475497943e-37\n", - "proton+O=C=CC(O)=[Pt]<=>OC#[Pt]+C=C=O\n", - "kf = 3.6869178226184714e8\n", - "krev = 2.308527988845987e-24\n", - "Kc = 1.5970860394296235e32\n", - "proton+O=C=CC(O)=[Pt]<=>H2O+O=C=CC#[Pt]\n", - "kf = 1.4173063898477724e9\n", - "krev = 1.8699327016499725e-35\n", - "Kc = 7.579451327832192e43\n", - "proton+O=C=CC(=O)[Pt]<=>O=C=CC(O)=[Pt]\n", - "kf = 1.3966647556161785e8\n", - "krev = 6.064978625986838e10\n", - "Kc = 0.002302835412530289\n", - "proton+O=C=CC(O)=[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.77109812553911e-50\n", - "Kc = 9.021694240847683e59\n", - "C=O+O=C=C[Pt]<=>O=C=CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 80798.59947863563\n", - "Kc = 4.901904683810505e-13\n", - "HX+O=C=CC=O<=>O=C=CCO[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 2.019947796444839e-5\n", - "Kc = 0.0012837560986177624\n", - "proton+O=C=CC=O.[Pt]<=>O=C=CCO[Pt]\n", - "kf = 1.6613607573018702e7\n", - "krev = 0.060581924478631026\n", - "Kc = 2.7423373747195494e8\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=CCO[Pt]\n", - "kf = 7.342900678318069e-26\n", - "krev = 740.7927312780465\n", - "Kc = 9.912220204496055e-29\n", - "proton+O=C=CCO[Pt]<=>O=C=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.776973315413755e-38\n", - "Kc = 6.619056559911473e47\n", - "vacantX+vacantX+CCOC=O<=>CH3X+O=COC[Pt]\n", - "kf = 1.714178070740009e-17\n", - "krev = 1.2983121019578911e14\n", - "Kc = 1.3203127877765141e-31\n", - "proton+O=CC([Pt])C=O<=>C=O+O=CC=[Pt]\n", - "kf = 2.47423293715182e-8\n", - "krev = 2.0280451926860074e-14\n", - "Kc = 1.2200087779478263e6\n", - "HX+O=C=CC=O<=>O=CC([Pt])C=O\n", - "kf = 2.5931203025755725e-8\n", - "krev = 5.183135272095574e-24\n", - "Kc = 5.002995612590211e15\n", - "proton+O=C=CC=O.[Pt]<=>O=CC([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.3392224526862137e-17\n", - "Kc = 1.0687311919091573e27\n", - "vacantX+vacantX+O=CCC=O<=>HX+O=CC([Pt])C=O\n", - "kf = 6.269624738894468e-15\n", - "krev = 24.522149705338403\n", - "Kc = 2.556719053684591e-16\n", - "proton+O=CC(=[Pt])C=O<=>C=O+O=CC#[Pt]\n", - "kf = 10.261874494662171\n", - "krev = 1.4436321327419983e-16\n", - "Kc = 7.108372182857295e16\n", - "proton+O=C=C([Pt])C=O<=>O=CC(=[Pt])C=O\n", - "kf = 2.5e10\n", - "krev = 1.4220334551977674e-9\n", - "Kc = 1.7580458398233084e19\n", - "proton+O=CC(=[Pt])C=O<=>O=CC([Pt])C=O\n", - "kf = 2.5e10\n", - "krev = 1.5146490668535414e-33\n", - "Kc = 1.6505473477056826e43\n", - "vacantX+vacantX+COCC=O<=>CH3X+O=CCO[Pt]\n", - "kf = 1.7650043109029407e-12\n", - "krev = 1.4735149295451475e13\n", - "Kc = 1.1978190892492496e-25\n", - "vacantX+vacantX+COCC=O<=>CO[Pt]+O=CC[Pt]\n", - "kf = 10.947009513309483\n", - "krev = 5.112987413682155e11\n", - "Kc = 2.1410202348661592e-11\n", - "proton+O=CCC(=O)[Pt]<=>O=CCC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.854503933624113e-15\n", - "Kc = 1.3480693972508561e25\n", - "vacantX+O=CCC=O<=>O=CCC=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 165389.8266532618\n", - "Kc = 1.951879075907524\n", - "proton+O=CC([Pt])C=O<=>O=CCC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3665860267196657e-23\n", - "Kc = 1.82937623473362e33\n", - "proton+O=CCC#[Pt]<=>O=CCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.6973664629136586e-26\n", - "Kc = 1.4728699162045183e36\n", - "proton+O=CCC=[Pt]<=>CHX+CC=O\n", - "kf = 2.5899695928987517e9\n", - "krev = 3.947289091334359e-20\n", - "Kc = 6.561388165322411e28\n", - "vacantX+vacantX+O=CCC=O<=>OX+O=CCC=[Pt]\n", - "kf = 1.2771337705277995e-31\n", - "krev = 6.599290845791489e16\n", - "Kc = 1.935259106426951e-48\n", - "vacantX+vacantX+CCOO<=>CH3X+OOC[Pt]\n", - "kf = 1.1728434846364774e-18\n", - "krev = 2.6840450809869076e16\n", - "Kc = 4.3696862356918e-35\n", - "proton+OOCC#[Pt]<=>CX+COO\n", - "kf = 60.315441044159115\n", - "krev = 2.977663267988303e-11\n", - "Kc = 2.025596436393158e12\n", - "vacantX+vacantX+C=C=O<=>OX+C=C=[Pt]\n", - "kf = 5.2796000958546504e-37\n", - "krev = 1.4614931014553018e17\n", - "Kc = 3.612470076387919e-54\n", - "proton+C=C=[Pt]<=>CC#[Pt]\n", - "kf = 640420.8302433634\n", - "krev = 6.912282754789268e-38\n", - "Kc = 9.264968650184908e42\n", - "vacantX+vacantX+CC(C)=O<=>CH3X+CC(=O)[Pt]\n", - "kf = 0.0015322757193851075\n", - "krev = 1.9084257758101816e14\n", - "Kc = 8.029003479239911e-18\n", - "vacantX+vacantX+C=C=C=O<=>CH2X+O=C=C=[Pt]\n", - "kf = 0.014873013888318402\n", - "krev = 6.520037160662236e15\n", - "Kc = 2.2811240981957472e-18\n", - "HOX+C=C=C=O<=>O=C=C([Pt])CO\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.9529365102554657e-31\n", - "Kc = 9.99708792916859e22\n", - "HX+C=C=C=O<=>O=C=CC[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.4091973858076736e-32\n", - "Kc = 1.225336127134283e24\n", - "vacantX+vacantX+C=C=C=O<=>OCX+C=C=[Pt]\n", - "kf = 0.8504584217531632\n", - "krev = 1.347597642765549e15\n", - "Kc = 6.310922450174717e-16\n", - "proton+O=C(O)C=[Pt]<=>CHX+O=CO\n", - "kf = 1.9246790704611034e10\n", - "krev = 1.3703711705958087e-14\n", - "Kc = 1.4044947177517558e24\n", - "proton+O=C(O)C#[Pt]<=>O=C(O)C=[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.0877559710435657e-22\n", - "Kc = 1.197457957095615e32\n", - "vacantX+vacantX+CC=C=O<=>CH3X+O=C=C[Pt]\n", - "kf = 0.0008567749561878586\n", - "krev = 1.2359860589695025e13\n", - "Kc = 6.931914401220598e-17\n", - "vacantX+vacantX+CC=C=O<=>HX+O=C=CC[Pt]\n", - "kf = 2.2773385768535307e-19\n", - "krev = 181.8091471864856\n", - "Kc = 1.2525984594810374e-21\n", - "proton+O=C=CCO[Pt]<=>OX+CC=C=O\n", - "kf = 9.282700634499574e8\n", - "krev = 2.335062558409911e-22\n", - "Kc = 3.9753541510342836e30\n", - "proton+CC(=O)[Pt]<=>CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.929137588754279e-20\n", - "Kc = 3.1529280101605185e29\n", - "proton+O=CC[Pt]<=>CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.8611661232372836e-34\n", - "Kc = 8.737696073275746e43\n", - "vacantX+CC=O<=>CC=O.[Pt]\n", - "kf = 412885.969273148\n", - "krev = 2.625517699834265\n", - "Kc = 157258.8786200951\n", - "proton+CC=[Pt]<=>CHX+CH4\n", - "kf = 9.167962734759869e9\n", - "krev = 2.1931338884767277e-17\n", - "Kc = 4.180302344024973e26\n", - "proton+CC#[Pt]<=>CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.2778968953461142e-18\n", - "Kc = 1.0975035810916887e28\n", - "vacantX+vacantX+CC=O<=>OX+CC=[Pt]\n", - "kf = 6.186864182993887e-31\n", - "krev = 2.034915252803989e19\n", - "Kc = 3.04035471475717e-50\n", - "vacantX+vacantX+CC=C=O<=>OCX+CC=[Pt]\n", - "kf = 5.619880038277716e-8\n", - "krev = 4.919193785592355e16\n", - "Kc = 1.14243924578405e-24\n", - "vacantX+vacantX+CC<=>CH3X+CH3X\n", - "kf = 1.6866972609475142e-22\n", - "krev = 6.547125244410207e13\n", - "Kc = 2.576241018739606e-36\n", - "proton+O=C=CC[Pt]<=>CC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.695228716286645e-29\n", - "Kc = 3.734002385786408e38\n", - "vacantX+CC=C=O<=>CC=C=O.[Pt]\n", - "kf = 365995.57053717994\n", - "krev = 187509.1639624155\n", - "Kc = 1.9518809790573244\n", - "proton+O=C(O)C[Pt]<=>CH2X+O=CO\n", - "kf = 1.2304284092395222e-6\n", - "krev = 5.4089377263725185e-12\n", - "Kc = 227480.60182691432\n", - "HOX+C=C=O<=>O=C(O)C[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.348252838458729e-29\n", - "Kc = 4.5553052781738184e20\n", - "vacantX+vacantX+CC(=O)O<=>HX+O=C(O)C[Pt]\n", - "kf = 1.1112170024966995e-23\n", - "krev = 36323.66987445037\n", - "Kc = 3.0592090676342045e-28\n", - "proton+O=C(O)C=[Pt]<=>O=C(O)C[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.0581893054844326e-43\n", - "Kc = 8.174771900211022e52\n", - "vacantX+vacantX+O=C=C=CO<=>OC=[Pt]+O=C=C=[Pt]\n", - "kf = 0.004371453552681894\n", - "krev = 1.2572855491392857e13\n", - "Kc = 3.476897953431907e-16\n", - "HX+O=C=C=CO<=>O=C=CC(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.3635197599529065e-33\n", - "Kc = 1.9017841755847633e25\n", - "HX+O=C=C=CO<=>O=C=C([Pt])CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 6.797711819853139e-22\n", - "Kc = 3.814695843684052e13\n", - "proton+O=C(O)CC#[Pt]<=>CX+CC(=O)O\n", - "kf = 30.70857292238805\n", - "krev = 6.812632242540305e-12\n", - "Kc = 4.507592928711706e12\n", - "proton+CC([Pt])=C=O<=>CH4+O=C=C=[Pt]\n", - "kf = 1.2085081921964822e7\n", - "krev = 8.741841358749037e-32\n", - "Kc = 1.382441230172839e38\n", - "HX+C=C=C=O<=>CC([Pt])=C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.301177455844525e-32\n", - "Kc = 1.2828548214436644e24\n", - "vacantX+vacantX+CC=C=O<=>HX+CC([Pt])=C=O\n", - "kf = 4.581183222917958e-20\n", - "krev = 34.93361388628861\n", - "Kc = 1.3113968791863429e-21\n", - "proton+CC([Pt])=C=O<=>CC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.009510491985357e-29\n", - "Kc = 3.566582863180658e38\n", - "CH3X+O=C=C=O<=>CC(=C=O)O[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.951682102619952e-64\n", - "Kc = 1.9647454732667077e56\n", - "proton+CC(=C=O)O[Pt]<=>OX+CC=C=O\n", - "kf = 0.0004690094743464506\n", - "krev = 3.463167447939826e-12\n", - "Kc = 1.354278940873782e8\n", - "vacantX+C=C<=>C=C.[Pt]\n", - "kf = 36.21750369826068\n", - "krev = 0.32335117013731834\n", - "Kc = 112.00671914340097\n", - "vacantX+vacantX+C=CO<=>HOX+C=C[Pt]\n", - "kf = 1.7018617233469498e-12\n", - "krev = 4.164837143763027e13\n", - "Kc = 4.086262354568991e-26\n", - "vacantX+vacantX+C=C<=>HX+C=C[Pt]\n", - "kf = 6.071347272542775e-23\n", - "krev = 1180.067101472276\n", - "Kc = 5.144916983930861e-26\n", - "vacantX+vacantX+C=CC=O<=>CHOX+C=C[Pt]\n", - "kf = 0.3274906030624493\n", - "krev = 2.9425898600264806e14\n", - "Kc = 1.1129332276687114e-15\n", - "vacantX+vacantX+C=COC=O<=>CHO2X+C=C[Pt]\n", - "kf = 0.2513917911405871\n", - "krev = 1.0405847657707406e16\n", - "Kc = 2.4158703779829617e-17\n", - "proton+C=C=[Pt]<=>C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.879405731717126e-43\n", - "Kc = 3.634034824365549e52\n", - "proton+C=C[Pt]<=>CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.934683922364635e-9\n", - "Kc = 2.798084433342053e18\n", - "proton+C=C[Pt]<=>C=C.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.7922688198063605e-35\n", - "Kc = 5.2167357341632115e44\n", - "proton+C=CC#[Pt]<=>CX+C=C\n", - "kf = 2.651203806309735e-13\n", - "krev = 8.915037810885974e-9\n", - "Kc = 2.9738559303387396e-5\n", - "vacantX+CC(=O)O<=>CC(=O)O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 181176.05501028927\n", - "Kc = 1.9518809818483447\n", - "proton+CC(=O)O[Pt]<=>CC(=O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.1623872922305787e-33\n", - "Kc = 2.1507461555284137e43\n", - "proton+O=C(O)C[Pt]<=>CC(=O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.635169212801562e-35\n", - "Kc = 1.5288937563328442e45\n", - "proton+C=CC(=O)[Pt]<=>OCX+C=C\n", - "kf = 1.730712607477889e9\n", - "krev = 2.0451102595690132e-14\n", - "Kc = 8.462686055091326e22\n", - "vacantX+vacantX+C=CC=O<=>HX+C=CC(=O)[Pt]\n", - "kf = 3.052485738368744e-11\n", - "krev = 0.0007099643372969683\n", - "Kc = 4.29949164769375e-8\n", - "HX+C=C=C=O<=>C=CC(=O)[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 5.604440911093213e-48\n", - "Kc = 5.267388203494818e39\n", - "HX+O=C=CC=O<=>O=CC=CO[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 5.6159867257682645e-34\n", - "Kc = 4.61739037002591e25\n", - "proton+O=C=CC=O.[Pt]<=>O=CC=CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.5345744521912456e-27\n", - "Kc = 9.863588729219e36\n", - "proton+O=CC=CO[Pt]<=>OX+C=CC=O\n", - "kf = 8.941635476659212e-8\n", - "krev = 6.459819116097008e-12\n", - "Kc = 13841.92856790347\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC=CO[Pt]\n", - "kf = 4.135805741920728e-10\n", - "krev = 0.028732529553568358\n", - "Kc = 1.4394158141245496e-8\n", - "HX+C=C=O<=>C=CO[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.272169613200064e-8\n", - "Kc = 0.46029640012283785\n", - "proton+C=C=O.[Pt]<=>C=CO[Pt]\n", - "kf = 1.6114496098941418\n", - "krev = 0.0629488455612356\n", - "Kc = 25.59935127525969\n", - "vacantX+vacantX+C=CO<=>HX+C=CO[Pt]\n", - "kf = 1.5839272910037507e-20\n", - "krev = 3600.161649580889\n", - "Kc = 4.399600476795654e-24\n", - "proton+C=CO[Pt]<=>OX+C=C\n", - "kf = 1.6348034459622817e9\n", - "krev = 2.949090847686672e-16\n", - "Kc = 5.543415006169292e24\n", - "vacantX+vacantX+C=COC=O<=>CHOX+C=CO[Pt]\n", - "kf = 0.024290856013790354\n", - "krev = 3.5586883050271985e15\n", - "Kc = 6.825789148062155e-18\n", - "vacantX+vacantX+O=CCCO<=>OC[Pt]+O=CC[Pt]\n", - "kf = 2.162232232095232e-5\n", - "krev = 5.66671683371172e13\n", - "Kc = 3.815670158833332e-19\n", - "proton+C=COC(=O)[Pt]<=>OCX+C=CO\n", - "kf = 2.0873777730813181e9\n", - "krev = 3.584260915239524e-17\n", - "Kc = 5.823732765118261e25\n", - "vacantX+vacantX+C=COC=O<=>HX+C=COC(=O)[Pt]\n", - "kf = 3.5117597357119104e-15\n", - "krev = 0.7837038908782975\n", - "Kc = 4.480977798612533e-15\n", - "CO2+C=C[Pt]<=>C=COC(=O)[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.08399332498323721\n", - "Kc = 7.789900440580834e-7\n", - "proton+C=COC#[Pt]<=>CX+C=CO\n", - "kf = 8.774713368997763e-21\n", - "krev = 2.5786202129581154e-12\n", - "Kc = 3.40287155312867e-9\n", - "vacantX+vacantX+CCC=O<=>CH3X+O=CC[Pt]\n", - "kf = 1.2257627381394946e-12\n", - "krev = 3.270257576074817e14\n", - "Kc = 3.748214657790771e-27\n", - "proton+CC(O)=[Pt]<=>OC#[Pt]+CH4\n", - "kf = 1.7151214452372642e9\n", - "krev = 7.710973221755691e-11\n", - "Kc = 2.2242606684176146e19\n", - "proton+CC(=O)[Pt]<=>CC(O)=[Pt]\n", - "kf = 2.5e10\n", - "krev = 717.4519170245923\n", - "Kc = 3.484554073488254e7\n", - "proton+CC(O)=[Pt]<=>H2O+CC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.7830871092055596e-15\n", - "Kc = 8.982830583098897e24\n", - "vacantX+vacantX+CC(=O)O<=>OX+CC(O)=[Pt]\n", - "kf = 1.1829749543892744e-33\n", - "krev = 3.758913107590896e15\n", - "Kc = 3.1471197139415875e-49\n", - "vacantX+vacantX+CC(O)=C=O<=>CH3X+O=C=C(O)[Pt]\n", - "kf = 1.049990631922765e-6\n", - "krev = 1.7955210884029898e15\n", - "Kc = 5.847832357439309e-22\n", - "vacantX+vacantX+CC(O)=C=O<=>HOX+CC([Pt])=C=O\n", - "kf = 0.0029164033711847528\n", - "krev = 3.4437539939134434e12\n", - "Kc = 8.468675103794464e-16\n", - "vacantX+vacantX+CC(O)=C=O<=>HX+CC(=C=O)O[Pt]\n", - "kf = 1.7528367761452354e-6\n", - "krev = 1.1970864565480504e-5\n", - "Kc = 0.14642524494009906\n", - "vacantX+vacantX+CC(O)=C=O<=>OCX+CC(O)=[Pt]\n", - "kf = 65.80946386077328\n", - "krev = 1217.699742052305\n", - "Kc = 0.054044081301896585\n", - "vacantX+vacantX+C=CC=O<=>HX+O=CC=C[Pt]\n", - "kf = 6.342176392543457e-21\n", - "krev = 776.2437464870187\n", - "Kc = 8.170341366672147e-24\n", - "vacantX+vacantX+O=CC=CO<=>HOX+O=CC=C[Pt]\n", - "kf = 4.672349699632388e-15\n", - "krev = 8.81363422062413e13\n", - "Kc = 5.301274800693419e-29\n", - "proton+O=CC=C[Pt]<=>O=CCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.06003726626598783\n", - "Kc = 4.16408033790888e11\n", - "proton+C=CC(=O)O[Pt]<=>OX+C=CC=O\n", - "kf = 1104.9105411729577\n", - "krev = 5.275136351485499e-16\n", - "Kc = 2.094562998095415e18\n", - "CO2+C=C[Pt]<=>C=CC(=O)O[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 450683.30306117237\n", - "Kc = 1.4517947189269602e-13\n", - "vacantX+vacantX+O=C=CO<=>OX+OC=C=[Pt]\n", - "kf = 7.548264554696059e-34\n", - "krev = 5.749061160710156e15\n", - "Kc = 1.3129560364189368e-49\n", - "proton+OC=C=[Pt]<=>OCC#[Pt]\n", - "kf = 19.409739369999222\n", - "krev = 1.9266253459058526e-51\n", - "Kc = 1.0074475253450605e52\n", - "vacantX+vacantX+O=C=C=CO<=>OCX+OC=C=[Pt]\n", - "kf = 1.463392220587488e-22\n", - "krev = 7.968303762369095e13\n", - "Kc = 1.8365166090912173e-36\n", - "proton+CC[Pt]<=>CH2X+CH4\n", - "kf = 362.55746820802517\n", - "krev = 6.769901434571724e-13\n", - "Kc = 5.355432006093324e14\n", - "HX+C=C<=>CC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 3.1627439012977165e-12\n", - "Kc = 25911.109388377805\n", - "vacantX+vacantX+CCO<=>HOX+CC[Pt]\n", - "kf = 2.1035625708276702e-15\n", - "krev = 1.0019023766861524e15\n", - "Kc = 2.099568400850909e-30\n", - "vacantX+vacantX+CCOC=O<=>CHO2X+CC[Pt]\n", - "kf = 0.08561452397466171\n", - "krev = 3.215769317238553e17\n", - "Kc = 2.6623341268826044e-19\n", - "vacantX+vacantX+CCOO<=>OO[Pt]+CC[Pt]\n", - "kf = 1.262172875849309e-6\n", - "krev = 1.5596341944506717e13\n", - "Kc = 8.092749443044025e-20\n", - "proton+CC=[Pt]<=>CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.4189501752164648e-36\n", - "Kc = 1.0335061985211343e46\n", - "vacantX+vacantX+CC<=>HX+CC[Pt]\n", - "kf = 8.697106954471648e-14\n", - "krev = 5.359609736165605e16\n", - "Kc = 1.6227127314485718e-30\n", - "proton+C=C.[Pt]<=>CC[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 9.019759137961467e-10\n", - "Kc = 5.543385276172725e19\n", - "vacantX+vacantX+CCC=O<=>CHOX+CC[Pt]\n", - "kf = 0.0004422945453165714\n", - "krev = 9.363325052982716e15\n", - "Kc = 4.723691026572629e-20\n", - "vacantX+vacantX+CC(O)C=O<=>CH3X+O=CC(O)[Pt]\n", - "kf = 9.477814531468979e-7\n", - "krev = 7.52142668687151e15\n", - "Kc = 1.2601086105129898e-22\n", - "proton+CCC#[Pt]<=>CX+CC\n", - "kf = 9.109252134386601e-9\n", - "krev = 5.157188742108513e-9\n", - "Kc = 1.7663212633676635\n", - "C=O+CH3X<=>CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.1808191230067762e-17\n", - "Kc = 3.354171909251678e9\n", - "HX+CC=O<=>CCO[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 2.639709061724686e-6\n", - "Kc = 0.012387213631168494\n", - "vacantX+vacantX+CCO<=>HX+CCO[Pt]\n", - "kf = 5.372480262216755e-24\n", - "krev = 2113.809062877283\n", - "Kc = 2.5416109508508876e-27\n", - "vacantX+vacantX+CCOC=O<=>CHOX+CCO[Pt]\n", - "kf = 4.80530366959931e-5\n", - "krev = 5.681813674074216e13\n", - "Kc = 8.457341168235823e-19\n", - "vacantX+vacantX+CCOO<=>HOX+CCO[Pt]\n", - "kf = 3.028654941635431e8\n", - "krev = 1.2132864881112858e-12\n", - "Kc = 2.496240559268171e20\n", - "proton+CC=O.[Pt]<=>CCO[Pt]\n", - "kf = 1.1580476897317786e9\n", - "krev = 0.0613528665806741\n", - "Kc = 1.8875201017853645e10\n", - "proton+CCO[Pt]<=>OX+CC\n", - "kf = 3.7072077338819857e9\n", - "krev = 2.3715094123172698e-19\n", - "Kc = 1.5632270800306741e28\n", - "proton+CCOC(=O)[Pt]<=>OCX+CCO\n", - "kf = 2.5e10\n", - "krev = 2.894100326311791e-18\n", - "Kc = 8.638263080485437e27\n", - "vacantX+vacantX+CCOC=O<=>HX+CCOC(=O)[Pt]\n", - "kf = 2.5742212027881315e-15\n", - "krev = 0.39729482671494754\n", - "Kc = 6.479372570927264e-15\n", - "CO2+CC[Pt]<=>CCOC(=O)[Pt]\n", - "kf = 3.860701485876577e-7\n", - "krev = 0.0037771400241392917\n", - "Kc = 0.00010221229451921966\n", - "CH3X+C=C=O<=>CCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.9339597186194493e-34\n", - "Kc = 1.7308289628845924e26\n", - "HX+CC=C=O<=>CCC(=O)[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 2.728234417234893e-33\n", - "Kc = 1.0624138213938816e25\n", - "proton+CCC(=O)[Pt]<=>OCX+CC\n", - "kf = 8.103432310812494e9\n", - "krev = 1.1832000102689138e-17\n", - "Kc = 6.848742596757393e26\n", - "proton+CC=C=O.[Pt]<=>CCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.9167545205392434e-32\n", - "Kc = 1.304288041692825e42\n", - "vacantX+vacantX+CCC=O<=>HX+CCC(=O)[Pt]\n", - "kf = 1.3037608552158366e-12\n", - "krev = 0.18236199715464047\n", - "Kc = 7.149301255514685e-12\n", - "vacantX+vacantX+C=C(O)C=O<=>CH2X+O=CC(O)=[Pt]\n", - "kf = 3.506980389191063e-59\n", - "krev = 1.6121784785918364e12\n", - "Kc = 2.1753053001019147e-71\n", - "proton+CCOC#[Pt]<=>CX+CCO\n", - "kf = 4.005811658122279e-20\n", - "krev = 7.196820611537062e-21\n", - "Kc = 5.566085184478061\n", - "proton+CCC(=O)O[Pt]<=>OX+CCC=O\n", - "kf = 1.3729406999742848e-5\n", - "krev = 3.285934583037464e-14\n", - "Kc = 4.1782350356627035e8\n", - "CO2+CC[Pt]<=>CCC(=O)O[Pt]\n", - "kf = 3.860701485876577e-7\n", - "krev = 2.2515045234693432e-8\n", - "Kc = 17.147207325738\n", - "vacantX+vacantX+OC=CCO<=>OC=[Pt]+OCC=[Pt]\n", - "kf = 3.6700973989487563e-44\n", - "krev = 3.0504263460080312e13\n", - "Kc = 1.203142440646588e-57\n", - "proton+CC(=C=O)O[Pt]<=>CC(O)=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.826538005480996e-9\n", - "Kc = 3.194260346336052e18\n", - "vacantX+CC(O)=C=O<=>CC(O)=C=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 165389.73964983693\n", - "Kc = 1.9518801026953096\n", - "proton+OOC=[Pt]<=>OO+CHX\n", - "kf = 7.013498875844368e9\n", - "krev = 5.546553589282952e-32\n", - "Kc = 1.2644787006828613e41\n", - "proton+OOC=[Pt]<=>OOC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.4245295584877718e-46\n", - "Kc = 1.0311278702493116e56\n", - "proton+OOC#[Pt]<=>OOC=[Pt]\n", - "kf = 2.046777417123334e-39\n", - "krev = 0.05605358109847477\n", - "Kc = 3.651465931369418e-38\n", - "vacantX+vacantX+C=CCO<=>CH2X+OCC=[Pt]\n", - "kf = 3.3256293066300124e-48\n", - "krev = 2.638642223210571e15\n", - "Kc = 1.2603562837645906e-63\n", - "vacantX+vacantX+C=CCO<=>OC[Pt]+C=C[Pt]\n", - "kf = 1.4930923415267688e-9\n", - "krev = 1.1121057711212152e14\n", - "Kc = 1.3425812366942817e-23\n", - "vacantX+OO<=>OO.[Pt]\n", - "kf = 469882.2241291155\n", - "krev = 15.560302693769444\n", - "Kc = 30197.498941795184\n", - "proton+OO[Pt]<=>OO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.1228276832814337e-34\n", - "Kc = 8.005564999260629e43\n", - "C=O+CO[Pt]<=>COCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 9.545218685674386e-14\n", - "Kc = 414937.62088874576\n", - "HX+COC=O<=>COCO[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 0.02522938529859348\n", - "Kc = 1.1100614687459063e-6\n", - "vacantX+vacantX+COCO<=>HX+COCO[Pt]\n", - "kf = 1.0488506310161173e-19\n", - "krev = 521.1543106644776\n", - "Kc = 2.0125529225284944e-22\n", - "proton+COC=O.[Pt]<=>COCO[Pt]\n", - "kf = 40509.63551266486\n", - "krev = 0.062481732764519744\n", - "Kc = 648343.663344565\n", - "proton+COCO[Pt]<=>OX+COC\n", - "kf = 1.2438206829010542e6\n", - "krev = 4.104607965767337e-14\n", - "Kc = 3.0303032427812573e19\n", - "CO[Pt]+C=C=O<=>COCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.680149232421768e-23\n", - "Kc = 1.9922953446306685e15\n", - "HX+COC=C=O<=>COCC(=O)[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 2.661991446097411e-38\n", - "Kc = 9.604054388173769e29\n", - "proton+COCC(=O)[Pt]<=>OCX+COC\n", - "kf = 2.133056617543625e10\n", - "krev = 1.4949600582197844e-15\n", - "Kc = 1.4268318446472028e25\n", - "vacantX+vacantX+COCC=O<=>HX+COCC(=O)[Pt]\n", - "kf = 2.290241001822749e-10\n", - "krev = 0.0004872161822843353\n", - "Kc = 4.7006669423105973e-7\n", - "proton+COCOC#[Pt]<=>CX+COCO\n", - "kf = 8.0026324253333e-15\n", - "krev = 1.5013306397629497e-20\n", - "Kc = 533035.9757792503\n", - "proton+COCC#[Pt]<=>CX+COC\n", - "kf = 349.9926882380769\n", - "krev = 2.8556101370374304e-11\n", - "Kc = 1.2256319015633516e13\n", - "proton+COC[Pt]<=>CH2X+CO-2\n", - "kf = 67.62022471726577\n", - "krev = 2.0667958594987744e-13\n", - "Kc = 3.2717418320000206e14\n", - "vacantX+vacantX+COCO<=>HOX+COC[Pt]\n", - "kf = 8.90444501639475e-13\n", - "krev = 8.409201083164982e12\n", - "Kc = 1.0588931015362724e-25\n", - "C=O+CH3X<=>COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 8.422687202008296e-11\n", - "Kc = 470.23832623775377\n", - "vacantX+vacantX+COC<=>HX+COC[Pt]\n", - "kf = 2.786306429788959e-20\n", - "krev = 52.25975865319748\n", - "Kc = 5.3316481009398625e-22\n", - "vacantX+vacantX+COCC=O<=>CHOX+COC[Pt]\n", - "kf = 1.4060776479118306e6\n", - "krev = 6.613786245273692e13\n", - "Kc = 2.1259798786461146e-8\n", - "vacantX+vacantX+C=C=CO<=>OC=[Pt]+C=C=[Pt]\n", - "kf = 1.5975335437882445e-34\n", - "krev = 2.2957840869759923e8\n", - "Kc = 6.958553083676594e-43\n", - "vacantX+vacantX+C=C=CO<=>CH2X+OC=C=[Pt]\n", - "kf = 9.363402027600756e-56\n", - "krev = 7.047835211144391e9\n", - "Kc = 1.328550079149818e-65\n", - "vacantX+vacantX+COC=O<=>OX+COC=[Pt]\n", - "kf = 1.1797200153280936e-59\n", - "krev = 4.3408253155831816e16\n", - "Kc = 2.7177320660497494e-76\n", - "proton+COC=[Pt]<=>CHX+CO-2\n", - "kf = 1.170091764009404e8\n", - "krev = 7.175511087628678e-41\n", - "Kc = 1.6306737592904886e48\n", - "proton+COC#[Pt]<=>COC=[Pt]\n", - "kf = 5.422856290186217e9\n", - "krev = 0.04593625803044687\n", - "Kc = 1.1805176395935234e11\n", - "vacantX+vacantX+COC=C=O<=>OCX+COC=[Pt]\n", - "kf = 2.7777170398864307e-21\n", - "krev = 2.5089215324603047e13\n", - "Kc = 1.107135876490541e-34\n", - "proton+COC=[Pt]<=>COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.788367054366857e-58\n", - "Kc = 6.599149354121444e67\n", - "vacantX+COC=C=O<=>COC=C=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 1179.0380002145982\n", - "Kc = 273.8002862958761\n", - "proton+COC=C=O.[Pt]<=>COCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.9743095348548656e-35\n", - "Kc = 8.405312126069586e44\n", - "vacantX+vacantX+C=C=C<=>CH2X+C=C=[Pt]\n", - "kf = 4.78083312177258e-41\n", - "krev = 4.774618642094983e15\n", - "Kc = 1.0013015656628172e-56\n", - "proton+O=C=COC[Pt]<=>CH2X+O=C=CO\n", - "kf = 0.012182154063050232\n", - "krev = 6.385446948420047e-11\n", - "Kc = 1.907799745492282e8\n", - "C=O+O=C=C[Pt]<=>O=C=COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.852140732586457e13\n", - "Kc = 2.1384283940268284e-21\n", - "vacantX+vacantX+COC=C=O<=>HX+O=C=COC[Pt]\n", - "kf = 3.256466928453685e-21\n", - "krev = 26.50445975246776\n", - "Kc = 1.2286486722863626e-22\n", - "proton+O=C=COC[Pt]<=>COC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.6816688786445984e-32\n", - "Kc = 5.3399761170716994e41\n", - "CH3X+O=C=C=O<=>COC([Pt])=C=O\n", - "kf = 5.799304049644909e-8\n", - "krev = 3.1615249923835833e-35\n", - "Kc = 1.8343375629216876e27\n", - "proton+COC([Pt])=C=O<=>CO-2+O=C=C=[Pt]\n", - "kf = 7.659649079510863e7\n", - "krev = 8.626594375179062e-42\n", - "Kc = 8.879111207024697e48\n", - "vacantX+vacantX+COC=C=O<=>HX+COC([Pt])=C=O\n", - "kf = 2.779636780044878e-20\n", - "krev = 3.601218910546807\n", - "Kc = 7.718599866018197e-21\n", - "proton+COC([Pt])=C=O<=>COC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.9411116126633072e-30\n", - "Kc = 8.50018744353649e39\n", - "vacantX+vacantX+C=C=C(O)O<=>OC(O)=[Pt]+C=C=[Pt]\n", - "kf = 2.937512138355157e-45\n", - "krev = 8.778136400287878e10\n", - "Kc = 3.34639609639561e-56\n", - "proton+O=C=COC=[Pt]<=>CHX+O=C=CO\n", - "kf = 5.134624572033371e9\n", - "krev = 1.1666048580433202e-32\n", - "Kc = 4.401339953825826e41\n", - "proton+O=C=COC#[Pt]<=>O=C=COC=[Pt]\n", - "kf = 6.445871807934021e7\n", - "krev = 0.04843213836104689\n", - "Kc = 1.3309079520466354e9\n", - "proton+O=C=COC=[Pt]<=>O=C=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.184421341762987e-58\n", - "Kc = 3.0545836970087866e67\n", - "proton+CCOO[Pt]<=>OX+CCO\n", - "kf = 41310.52002690171\n", - "krev = 3.87392784405959e-65\n", - "Kc = 1.066372986018535e69\n", - "vacantX+vacantX+CCOO<=>HX+CCOO[Pt]\n", - "kf = 1.893449523720139e-21\n", - "krev = 0.6694879211592951\n", - "Kc = 2.8282056537202555e-21\n", - "O=O+CC[Pt]<=>CCOO[Pt]\n", - "kf = 4.5276782379965965e-7\n", - "krev = 1.4949208469184493e-38\n", - "Kc = 3.0287076719344122e31\n", - "vacantX+vacantX+C=CC(=O)O<=>CH2X+O=C(O)C=[Pt]\n", - "kf = 4.72289540105198e-39\n", - "krev = 9.498795808374404e14\n", - "Kc = 4.9720990916429044e-54\n", - "vacantX+vacantX+C=CC(=O)O<=>CO2HX+C=C[Pt]\n", - "kf = 5.354197885861111e7\n", - "krev = 1.376967106369583e14\n", - "Kc = 3.888399266107105e-7\n", - "vacantX+vacantX+C=CC(=O)O<=>HOX+C=CC(=O)[Pt]\n", - "kf = 0.03947248649742643\n", - "krev = 2.5171232142616846e11\n", - "Kc = 1.5681586929785789e-13\n", - "vacantX+vacantX+C=CC(=O)O<=>HX+C=CC(=O)O[Pt]\n", - "kf = 2.4490000178339845e-20\n", - "krev = 458.0011375503109\n", - "Kc = 5.3471483300955e-23\n", - "proton+O=C=C=CO.[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 4.027299565349673e-27\n", - "Kc = 6.207633575385482e36\n", - "proton+O=C=C=CO.[Pt]<=>O=C=C([Pt])CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.0077759532001373e-15\n", - "Kc = 1.2451588515219141e25\n", - "vacantX+O=C=C=CO<=>O=C=C=CO.[Pt]\n", - "kf = 327433.4917974331\n", - "krev = 0.4460204906723957\n", - "Kc = 734122.0832787583\n", - "HX+O=C=C=C=O<=>O=C=C=C(O)[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 1.3048903398306852e-5\n", - "Kc = 0.004032923533638046\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C=C(O)[Pt]\n", - "kf = 2.525763395783184e8\n", - "krev = 0.0002164709972378142\n", - "Kc = 1.1667906685016052e12\n", - "proton+O=C=C=C(O)[Pt]<=>O=C=CC(O)=[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.962688775287127e-7\n", - "Kc = 8.438280864508672e16\n", - "vacantX+vacantX+O=C=C=CO<=>HX+O=C=C=C(O)[Pt]\n", - "kf = 8.233814429551885e-18\n", - "krev = 0.5740049812746953\n", - "Kc = 1.434449995759099e-17\n", - "proton+O=C=C=C(O)[Pt]<=>O=C=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.038562361337769e-30\n", - "Kc = 1.226354438507057e40\n", - "vacantX+vacantX+CC=CO<=>OC=[Pt]+CC=[Pt]\n", - "kf = 1.6816353348966163e-33\n", - "krev = 8.021148128032321e14\n", - "Kc = 2.0965020319468163e-48\n", - "proton+O=C=C=C[Pt]<=>O=C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.58869731898989e-12\n", - "Kc = 3.2943730589228036e21\n", - "vacantX+vacantX+C=C=C=O<=>HX+O=C=C=C[Pt]\n", - "kf = 3.6772489817592154e-10\n", - "krev = 0.00723599763490509\n", - "Kc = 5.081882509221477e-8\n", - "vacantX+vacantX+O=C=C=CO<=>HOX+O=C=C=C[Pt]\n", - "kf = 0.00020826365169953766\n", - "krev = 1.0739954827079557e13\n", - "Kc = 1.939148302322696e-17\n", - "vacantX+OC=CO<=>OC=CO.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.48171019889246675\n", - "Kc = 734122.0861712244\n", - "vacantX+vacantX+C=CC<=>CH2X+CC=[Pt]\n", - "kf = 3.8695500910369183e-44\n", - "krev = 2.1644248520711738e17\n", - "Kc = 1.787795999169979e-61\n", - "vacantX+vacantX+C=CC<=>CH3X+C=C[Pt]\n", - "kf = 1.1726078415532691e-17\n", - "krev = 1.59532697721828e15\n", - "Kc = 7.350266486422159e-33\n", - "HX+O=C=CO<=>OC=C(O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 2.762063581333058e-24\n", - "Kc = 1.0314187634521844e16\n", - "vacantX+vacantX+OC=CO<=>HX+OC=C(O)[Pt]\n", - "kf = 6.089904416870865e-20\n", - "krev = 3.928023437111271\n", - "Kc = 1.550373747604081e-20\n", - "proton+O=C=CO.[Pt]<=>OC=C(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.425746296644915e-18\n", - "Kc = 3.366664979019745e27\n", - "proton+OC=C(O)[Pt]<=>H2O+OC=C=[Pt]\n", - "kf = 0.00012851134417551585\n", - "krev = 4.292558419234693e-8\n", - "Kc = 2993.8170113111178\n", - "proton+OC=C(O)[Pt]<=>OC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.203306887492305e-33\n", - "Kc = 1.134658096968678e43\n", - "vacantX+vacantX+OC=CO<=>HOX+OC=C[Pt]\n", - "kf = 1.882970379851619e-8\n", - "krev = 6.2613640604613945e13\n", - "Kc = 3.0072846134950095e-22\n", - "vacantX+vacantX+C=CO<=>HX+OC=C[Pt]\n", - "kf = 5.986889507133711e-22\n", - "krev = 1492.047811549125\n", - "Kc = 4.0125319448830507e-25\n", - "proton+OC=C[Pt]<=>OCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.00476271801815967\n", - "Kc = 5.249103538080149e12\n", - "vacantX+vacantX+O=CC=CO<=>CHOX+OC=C[Pt]\n", - "kf = 3.6404040231768274e-5\n", - "krev = 5.1339082800935775e14\n", - "Kc = 7.090901949480236e-20\n", - "proton+OC=C=[Pt]<=>OC=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.342865976660395e-55\n", - "Kc = 4.679136648609417e64\n", - "vacantX+vacantX+OC=CCO<=>OC[Pt]+OC=C[Pt]\n", - "kf = 1.39754480380523e-13\n", - "krev = 4.435737343310229e14\n", - "Kc = 3.1506482364492156e-28\n", - "vacantX+vacantX+CC=CO<=>CH3X+OC=C[Pt]\n", - "kf = 3.0518560755450534e-15\n", - "krev = 1.440283576497463e15\n", - "Kc = 2.1189272205454667e-30\n", - "vacantX+vacantX+CC=C(O)O<=>OC(O)=[Pt]+CC=[Pt]\n", - "kf = 3.314404876424973e-50\n", - "krev = 3.298291971460818e17\n", - "Kc = 1.0048852269912959e-67\n", - "HX+O=C=CO<=>OC=CO[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 5.830973747204281e-42\n", - "Kc = 4.885709192226705e33\n", - "vacantX+vacantX+OC=CO<=>HX+OC=CO[Pt]\n", - "kf = 6.3392542923960805e-6\n", - "krev = 0.0008631955285686626\n", - "Kc = 0.007343937824733329\n", - "proton+O=C=CO.[Pt]<=>OC=CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.5676442787837238e-35\n", - "Kc = 1.5947495448008493e45\n", - "proton+OC=CO[Pt]<=>OX+C=CO\n", - "kf = 5.525662090235594e-6\n", - "krev = 1.7632525745938843e-12\n", - "Kc = 3.13378932199108e6\n", - "proton+OC=CO[Pt]<=>OC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0436805199750088e-15\n", - "Kc = 2.395369035018363e25\n", - "proton+OC=COC#[Pt]<=>CX+OC=CO\n", - "kf = 5.4927107814658986e-27\n", - "krev = 1.4096865507205276e-11\n", - "Kc = 3.896405749674231e-16\n", - "vacantX+vacantX+CCC(=O)O<=>CH3X+O=C(O)C[Pt]\n", - "kf = 8.997747599742267e-17\n", - "krev = 6.572577910715489e15\n", - "Kc = 1.368983026442782e-32\n", - "vacantX+vacantX+CCC(=O)O<=>CO2HX+CC[Pt]\n", - "kf = 3.388822996448631e-6\n", - "krev = 1.0293603282987281e15\n", - "Kc = 3.292163981148853e-21\n", - "vacantX+vacantX+CCC(=O)O<=>HOX+CCC(=O)[Pt]\n", - "kf = 2.1491486919570496e-14\n", - "krev = 4.131728096070369e12\n", - "Kc = 5.201573390081201e-27\n", - "vacantX+vacantX+CCC(=O)O<=>HX+CCC(=O)O[Pt]\n", - "kf = 2.415446383235281e-20\n", - "krev = 451.7273406124814\n", - "Kc = 5.347133472063615e-23\n", - "proton+O=C([Pt])C=CO<=>OCX+C=CO\n", - "kf = 54746.53245856064\n", - "krev = 5.6414195578847066e-14\n", - "Kc = 9.704389453190798e17\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=C([Pt])C=CO\n", - "kf = 2.859565189776071e-11\n", - "krev = 0.000933578065584948\n", - "Kc = 3.06301668300697e-8\n", - "HX+O=C=C=CO<=>O=C([Pt])C=CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.1750295723598082e-43\n", - "Kc = 2.206855353748942e35\n", - "proton+O=C=C=CO.[Pt]<=>O=C([Pt])C=CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 3.470573896340974e-37\n", - "Kc = 7.203419591888677e46\n", - "proton+OC=C(O)C#[Pt]<=>CX+OC=CO\n", - "kf = 7.0039209824279205e-22\n", - "krev = 5.0078848497132504e-5\n", - "Kc = 1.3985786799448798e-17\n", - "vacantX+vacantX+C=COO<=>OO[Pt]+C=C[Pt]\n", - "kf = 0.00256837059370255\n", - "krev = 1.2695573429161084e13\n", - "Kc = 2.0230441799526235e-16\n", - "vacantX+vacantX+C=COO<=>HOX+C=CO[Pt]\n", - "kf = 3.07907263663438e8\n", - "krev = 5.547742278067932e-15\n", - "Kc = 5.5501364019864025e22\n", - "vacantX+vacantX+C=COO<=>CH2X+OOC=[Pt]\n", - "kf = 7.483948884590266e-53\n", - "krev = 2.8103204909201245e17\n", - "Kc = 2.6630232775123643e-70\n", - "proton+OC=CC#[Pt]<=>CX+C=CO\n", - "kf = 2.5870543921215902e-17\n", - "krev = 9.180054098363543e-7\n", - "Kc = 2.8181254319435484e-11\n", - "proton+OCC[Pt]<=>CH2X+CO-2\n", - "kf = 0.0009719098494518383\n", - "krev = 2.4333643684295238e-11\n", - "Kc = 3.9940991249045946e7\n", - "vacantX+vacantX+OCCO<=>HOX+OCC[Pt]\n", - "kf = 2.110093084979835e-12\n", - "krev = 2.4085316622580622e14\n", - "Kc = 8.760910716040024e-27\n", - "HX+C=CO<=>OCC[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 1.1429411507382647e-15\n", - "Kc = 2.8609207088741057e7\n", - "HOX+C=C<=>OCC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 2.2750559854988554e-15\n", - "Kc = 3.602118089238167e7\n", - "proton+OCC=[Pt]<=>OCC[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.205321264143215e-44\n", - "Kc = 7.799530199879206e53\n", - "vacantX+vacantX+CCO<=>HX+OCC[Pt]\n", - "kf = 4.51610258482867e-23\n", - "krev = 15472.547765874588\n", - "Kc = 2.918784063985339e-27\n", - "vacantX+vacantX+O=CCCO<=>CHOX+OCC[Pt]\n", - "kf = 2.0496526220764064\n", - "krev = 1.4633869198921762e15\n", - "Kc = 1.4006224835106677e-15\n", - "HX+C#C<=>C=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 2.375601900047824e-24\n", - "Kc = 3.580716650609497e16\n", - "CHOX+C#C<=>O=CC=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 3.2359557228060194e-16\n", - "Kc = 2.6287001452988416e8\n", - "HOX+C#C<=>OC=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 2.419253665005007e-25\n", - "Kc = 3.516108046777805e17\n", - "proton+OCCC#[Pt]<=>CX+CCO\n", - "kf = 8.933815405796665\n", - "krev = 3.951155569707063e-11\n", - "Kc = 2.261063946530208e11\n", - "OC[Pt]+C=C=O<=>O=C([Pt])CCO\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.869121889511259e-30\n", - "Kc = 1.7908695590280368e22\n", - "HX+O=C=CCO<=>O=C([Pt])CCO\n", - "kf = 2.5565910629172877e-8\n", - "krev = 3.7973012083800085e-37\n", - "Kc = 6.732652804247709e28\n", - "proton+O=C=CCO.[Pt]<=>O=C([Pt])CCO\n", - "kf = 2.4999999999999992e10\n", - "krev = 4.2428195230680025e-34\n", - "Kc = 5.892308137095206e43\n", - "proton+O=C([Pt])CCO<=>OCX+CCO\n", - "kf = 2.3445540187631004e10\n", - "krev = 2.187390305996352e-14\n", - "Kc = 1.071849871664838e24\n", - "vacantX+vacantX+O=CCCO<=>HX+O=C([Pt])CCO\n", - "kf = 4.786286134347495e-11\n", - "krev = 0.0006355926831038164\n", - "Kc = 7.530429883135883e-8\n", - "vacantX+vacantX+C=COC<=>CO[Pt]+C=C[Pt]\n", - "kf = 1.9108708710628152e-14\n", - "krev = 5.750545812867103e12\n", - "Kc = 3.322938262290088e-27\n", - "vacantX+vacantX+C=COC<=>CH3X+C=CO[Pt]\n", - "kf = 8.809048609670953e-10\n", - "krev = 5.30334818480063e15\n", - "Kc = 1.6610353125441853e-25\n", - "vacantX+vacantX+C=COC<=>CH2X+COC=[Pt]\n", - "kf = 2.00333233616492e-67\n", - "krev = 2.0086736136424638e14\n", - "Kc = 9.973408932933319e-82\n", - "C=O+OC[Pt]<=>OCCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.726586049973397e-6\n", - "Kc = 0.00837955829095468\n", - "HX+O=CCO<=>OCCO[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 7.096612291679358e-6\n", - "Kc = 0.003946413774492056\n", - "vacantX+vacantX+OCCO<=>HX+OCCO[Pt]\n", - "kf = 1.0265256602604584e-26\n", - "krev = 112849.3186381155\n", - "Kc = 9.09642763154215e-32\n", - "proton+O=CCO.[Pt]<=>OCCO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 0.007238326313310335\n", - "Kc = 3.4538371051368965e12\n", - "proton+OCCO[Pt]<=>OX+CCO\n", - "kf = 2.3230275128452018e8\n", - "krev = 2.2926363593815933e-25\n", - "Kc = 1.0132559851191603e33\n", - "proton+OCCOC#[Pt]<=>CX+OCCO\n", - "kf = 1.5472794442733612e-19\n", - "krev = 3.5192149065236613e-20\n", - "Kc = 4.396660861503879\n", - "vacantX+vacantX+C=CC(O)O<=>OC(O)[Pt]+C=C[Pt]\n", - "kf = 1.3588265576828814e-16\n", - "krev = 6.093754170226661e16\n", - "Kc = 2.2298676968656565e-33\n", - "proton+O=C=C=C=[Pt]<=>O=C=CC#[Pt]\n", - "kf = 0.0005127174187861217\n", - "krev = 3.5554302477417527e-65\n", - "Kc = 1.442068562902553e61\n", - "vacantX+vacantX+O=C=C=C=O<=>OX+O=C=C=C=[Pt]\n", - "kf = 6.451439297868635e-57\n", - "krev = 8.482832416110645e14\n", - "Kc = 7.60528910793525e-72\n", - "proton+O=C=C=C(O)[Pt]<=>H2O+O=C=C=C=[Pt]\n", - "kf = 3.943864438612498e-9\n", - "krev = 8.892341705178332e-9\n", - "Kc = 0.44351247054708254\n", - "proton+O=C=C=C=[Pt]<=>O=C=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.135709816788667e-60\n", - "Kc = 2.2012665234056e70\n", - "vacantX+C=CO<=>C=CO.[Pt]\n", - "kf = 412885.969273148\n", - "krev = 1.1342794009872417\n", - "Kc = 364007.288604364\n", - "proton+C=CO[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.2609853382616259e-36\n", - "Kc = 1.9825765805068438e46\n", - "proton+OC=C[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.1500462322636142e-37\n", - "Kc = 2.1738256514082024e47\n", - "proton+C=CO.[Pt]<=>OCC[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.3274284903031463e-9\n", - "Kc = 1.8833406230636737e19\n", - "vacantX+vacantX+C=COCO<=>OCO[Pt]+C=C[Pt]\n", - "kf = 1.4197397308458187e-12\n", - "krev = 3.0290185667479297e13\n", - "Kc = 4.6871278586123213e-26\n", - "vacantX+vacantX+C=COCO<=>OC[Pt]+C=CO[Pt]\n", - "kf = 1.0263854075463885e-7\n", - "krev = 1.9545487277553856e14\n", - "Kc = 5.251265384031101e-22\n", - "HX+C=C=O<=>C=C(O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 3.2362559658776053e-12\n", - "Kc = 10343.290300064218\n", - "proton+C=C=O.[Pt]<=>C=C(O)[Pt]\n", - "kf = 34965.030581361505\n", - "krev = 0.0607832359351523\n", - "Kc = 575241.3481023712\n", - "vacantX+vacantX+C=CO<=>HX+C=C(O)[Pt]\n", - "kf = 4.00965787691315e-19\n", - "krev = 4.055766485027893\n", - "Kc = 9.886313454472895e-20\n", - "vacantX+vacantX+C=C(O)O<=>HOX+C=C(O)[Pt]\n", - "kf = 3.9452234947489745e-7\n", - "krev = 1.361002505571871e12\n", - "Kc = 2.8987628447394044e-19\n", - "proton+C=C(O)[Pt]<=>H2O+C=C=[Pt]\n", - "kf = 34.38614313418425\n", - "krev = 4.186275701952701e-10\n", - "Kc = 8.21401780062998e10\n", - "proton+C=C(O)[Pt]<=>CC(O)=[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.95089409807226e-19\n", - "Kc = 8.472008540168157e28\n", - "vacantX+vacantX+C=C(O)C=O<=>CHOX+C=C(O)[Pt]\n", - "kf = 2.8052009086647103\n", - "krev = 2.294429327232502e13\n", - "Kc = 1.2226137782366527e-13\n", - "proton+C=C(O)[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.8335519057468456e-32\n", - "Kc = 8.822848788933935e41\n", - "HOX+C=C=O<=>C=C(O)O[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.6625343699967689e-31\n", - "Kc = 2.0134040862236038e23\n", - "proton+C=C(O)O[Pt]<=>OX+C=CO\n", - "kf = 1.8612642008505013e-7\n", - "krev = 1.1664654332247029e-8\n", - "Kc = 15.95644541051698\n", - "vacantX+vacantX+C=C(O)O<=>HX+C=C(O)O[Pt]\n", - "kf = 8.7276566297004e-6\n", - "krev = 1.546723677424112e-6\n", - "Kc = 5.6426734503963205\n", - "vacantX+vacantX+C=CCOO<=>OOC[Pt]+C=C[Pt]\n", - "kf = 2.5331825038162864e-12\n", - "krev = 1.769892843246248e17\n", - "Kc = 1.4312632052740838e-29\n", - "proton+C=C(O)OC#[Pt]<=>CX+C=C(O)O\n", - "kf = 2.623787352399973e-20\n", - "krev = 1.2487485387244388e-5\n", - "Kc = 2.1011334716596324e-15\n", - "proton+C=C(O)C#[Pt]<=>CX+C=CO\n", - "kf = 9.014573555163225e-18\n", - "krev = 4.234728239402636e-6\n", - "Kc = 2.1287253976030464e-12\n", - "vacantX+vacantX+C=COOC<=>COO[Pt]+C=C[Pt]\n", - "kf = 0.0009962735751002543\n", - "krev = 4.495422962203487e13\n", - "Kc = 2.21619541359445e-17\n", - "vacantX+vacantX+C=COOC<=>CO[Pt]+C=CO[Pt]\n", - "kf = 2.772273774659678e8\n", - "krev = 3.7705323383409334e-17\n", - "Kc = 7.352473141443741e24\n", - "proton+C=C(O)C(=O)[Pt]<=>OCX+C=CO\n", - "kf = 240578.16834993917\n", - "krev = 3.542554287396912e-14\n", - "Kc = 6.791093342050583e18\n", - "HOX+C=C=C=O<=>C=C(O)C(=O)[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 3.5720015577500406e-52\n", - "Kc = 8.264488540948707e43\n", - "vacantX+vacantX+C=C(O)C=O<=>HX+C=C(O)C(=O)[Pt]\n", - "kf = 2.8595651897765786e-11\n", - "krev = 0.000933577098423846\n", - "Kc = 3.063019856211522e-8\n", - "proton+C=COO[Pt]<=>OX+C=CO\n", - "kf = 10729.177497927041\n", - "krev = 4.5794499634895865e-68\n", - "Kc = 2.3428965451019583e71\n", - "O=O+C=C[Pt]<=>C=COO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 1.0833501613715598e-32\n", - "Kc = 7.082998693235901e24\n", - "vacantX+vacantX+C=COO<=>HX+C=COO[Pt]\n", - "kf = 4.552726448583842e-23\n", - "krev = 27.53540659037694\n", - "Kc = 1.6534081069915729e-24\n", - "vacantX+vacantX+C=COOC<=>CH3X+C=COO[Pt]\n", - "kf = 2.287071149777874e-9\n", - "krev = 2.2490557638427473e13\n", - "Kc = 1.0169028205286352e-22\n", - "vacantX+vacantX+CC(O)=CO<=>OC=[Pt]+CC(O)=[Pt]\n", - "kf = 7.128045206079291e-31\n", - "krev = 1.6024698052635947e11\n", - "Kc = 4.4481619451835966e-42\n", - "vacantX+vacantX+CC(O)=CO<=>CH3X+OC=C(O)[Pt]\n", - "kf = 1.2021042471738558e-26\n", - "krev = 3.79937896614338e12\n", - "Kc = 3.163949313521812e-39\n", - "proton+O=CC=C=[Pt]<=>O=CCC#[Pt]\n", - "kf = 3.756297566489362e6\n", - "krev = 1.394497962930394e-35\n", - "Kc = 2.693655829081234e41\n", - "vacantX+vacantX+O=C=CC=O<=>OX+O=CC=C=[Pt]\n", - "kf = 1.1758489216219413e-43\n", - "krev = 2.1453863988577092e16\n", - "Kc = 5.480825842132732e-60\n", - "proton+O=CC=C=[Pt]<=>O=CC=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.623932218117028e-56\n", - "Kc = 9.527685138886843e65\n", - "proton+C=C=C=O.[Pt]<=>O=C=CC[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.250573762851411e-26\n", - "Kc = 3.9996328254824715e35\n", - "vacantX+C=C=C=O<=>C=C=C=O.[Pt]\n", - "kf = 372758.92921022984\n", - "krev = 0.5077615475124772\n", - "Kc = 734122.012658058\n", - "proton+C=C=C=O.[Pt]<=>CC([Pt])=C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.97032003849065e-26\n", - "Kc = 4.18738021392907e35\n", - "proton+C=C=C=O.[Pt]<=>C=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.4540515244078705e-41\n", - "Kc = 1.7193338461771962e51\n", - "proton+O=C=C=C[Pt]<=>C=C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.222095880127153e-21\n", - "Kc = 3.4615990170930613e30\n", - "vacantX+vacantX+C=C(C)O<=>CH2X+CC(O)=[Pt]\n", - "kf = 1.2526307828427685e-31\n", - "krev = 1.8291181793687947e14\n", - "Kc = 6.848276929132241e-46\n", - "vacantX+vacantX+C=C(C)O<=>CH3X+C=C(O)[Pt]\n", - "kf = 6.412809230790006e-14\n", - "krev = 6.896161957802356e13\n", - "Kc = 9.299098933624258e-28\n", - "HX+O=C=C=C=O<=>O=C=C=CO[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 6.474039280394542e-15\n", - "Kc = 8.128654665807662e6\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C=CO[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 2.126073974360248e-11\n", - "Kc = 2.351752601413851e21\n", - "proton+O=C=C=CO[Pt]<=>OX+C=C=C=O\n", - "kf = 1.874455781059316e-11\n", - "krev = 4.625195948234001e-11\n", - "Kc = 0.40527056627190544\n", - "vacantX+vacantX+O=C=C=CO<=>HX+O=C=C=CO[Pt]\n", - "kf = 4.194899212644372e-10\n", - "krev = 0.014508998351933198\n", - "Kc = 2.891239705796395e-8\n", - "proton+O=C=C=CO[Pt]<=>O=C=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.108872710284178e-21\n", - "Kc = 6.084393886777513e30\n", - "proton+CC(O)[Pt]<=>OC=[Pt]+CH4\n", - "kf = 14505.158568543793\n", - "krev = 8.791660588386561e-14\n", - "Kc = 1.649876996810425e17\n", - "HX+C=CO<=>CC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 1.2254518112062234e-21\n", - "Kc = 2.668292606261641e13\n", - "HX+CC=O<=>CC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 2.4645381117653586e-12\n", - "Kc = 13267.654460532101\n", - "vacantX+vacantX+CCO<=>HX+CC(O)[Pt]\n", - "kf = 1.7361137032745595e-19\n", - "krev = 63.774720976875884\n", - "Kc = 2.72225997492652e-21\n", - "vacantX+vacantX+CC(O)O<=>HOX+CC(O)[Pt]\n", - "kf = 7.380915652046712e-14\n", - "krev = 2.775462823415347e13\n", - "Kc = 2.6593458899096773e-27\n", - "proton+CC=O.[Pt]<=>CC(O)[Pt]\n", - "kf = 2.154785154775262e9\n", - "krev = 1.0658396310796219e-7\n", - "Kc = 2.0216785827269468e16\n", - "proton+CC(O)[Pt]<=>H2O+CC=[Pt]\n", - "kf = 723833.2544114416\n", - "krev = 1.343069025839796e-9\n", - "Kc = 5.3893972721084994e14\n", - "proton+CC(O)=[Pt]<=>CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3666617888820996e-28\n", - "Kc = 1.8292748215671905e38\n", - "vacantX+vacantX+CC(O)C=O<=>CHOX+CC(O)[Pt]\n", - "kf = 753631.9525109725\n", - "krev = 9.011518944421836e14\n", - "Kc = 8.362984721654206e-10\n", - "proton+C=CO.[Pt]<=>CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.4232575724813062e-15\n", - "Kc = 1.7565337773973695e25\n", - "HX+C#CC=O<=>O=CC=C[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 1.9866745274914506e-30\n", - "Kc = 1.4859387148609413e22\n", - "proton+CC(O)C#[Pt]<=>CX+CCO\n", - "kf = 332.5520669610812\n", - "krev = 2.804408762154108e-12\n", - "Kc = 1.1858188130379505e14\n", - "O=CO+CH3X<=>CC(O)O[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 7.324156308451427e-7\n", - "Kc = 0.043678018970166745\n", - "HOX+CC=O<=>CC(O)O[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 7.587328136505701e-13\n", - "Kc = 43096.38318446866\n", - "HX+CC(=O)O<=>CC(O)O[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 4598.938099177113\n", - "Kc = 6.089703295881323e-12\n", - "proton+CC(O)O[Pt]<=>OX+CCO\n", - "kf = 4.0498182587176275e8\n", - "krev = 1.1661892804129953e-13\n", - "Kc = 3.4726937785634773e21\n", - "vacantX+vacantX+CC(O)O<=>HX+CC(O)O[Pt]\n", - "kf = 4.052122584605618e-24\n", - "krev = 469.09529347560436\n", - "Kc = 8.638165082797514e-27\n", - "proton+CC(=O)O.[Pt]<=>CC(O)O[Pt]\n", - "kf = 44577.580288635516\n", - "krev = 0.059626670260686736\n", - "Kc = 747611.4311556076\n", - "vacantX+vacantX+OC=C=CO<=>OC=[Pt]+OC=C=[Pt]\n", - "kf = 3.0449395213240036e-51\n", - "krev = 1.4315520101841116e12\n", - "Kc = 2.1270198355785863e-63\n", - "CH3X+O=C=CO<=>CC(O)C(=O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 4.477216581188038e-53\n", - "Kc = 6.362980552705156e44\n", - "proton+CC(O)C(=O)[Pt]<=>OCX+CCO\n", - "kf = 2.337144947972358e10\n", - "krev = 3.405958225337868e-14\n", - "Kc = 6.861930750018272e23\n", - "HOX+CC=C=O<=>CC(O)C(=O)[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 3.536759710167166e-36\n", - "Kc = 8.195394062368554e27\n", - "HX+CC(O)=C=O<=>CC(O)C(=O)[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 4.830700359768998e-42\n", - "Kc = 5.292381792522405e33\n", - "vacantX+vacantX+CC(O)C=O<=>HX+CC(O)C(=O)[Pt]\n", - "kf = 4.786286134353719e-11\n", - "krev = 0.0006355923790078162\n", - "Kc = 7.530433486042254e-8\n", - "proton+CC(O)=C=O.[Pt]<=>CC(O)C(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 3.8477677166331543e-41\n", - "Kc = 6.4972737028614895e50\n", - "proton+CC(O)OC#[Pt]<=>CX+CC(O)O\n", - "kf = 6.806815423841785e-14\n", - "krev = 1.2617237138429e-15\n", - "Kc = 53.948541579756\n", - "vacantX+vacantX+CCOC<=>CO[Pt]+CC[Pt]\n", - "kf = 2.3627317133785774e-11\n", - "krev = 3.856091265609508e13\n", - "Kc = 6.127271246016828e-25\n", - "vacantX+vacantX+CCOC<=>CH3X+CCO[Pt]\n", - "kf = 6.326940367296449e-9\n", - "krev = 1.8372911814097844e13\n", - "Kc = 3.443624195943553e-22\n", - "vacantX+vacantX+CCOC<=>CH3X+COC[Pt]\n", - "kf = 1.3389399016858639e-14\n", - "krev = 2.773400746132106e14\n", - "Kc = 4.8277909478217395e-29\n", - "proton+O=C=C(O)C[Pt]<=>CH2X+O=C=CO\n", - "kf = 1.0267021441542508e-19\n", - "krev = 7.62301030392619e-8\n", - "Kc = 1.3468460663439657e-12\n", - "HOX+C=C=C=O<=>O=C=C(O)C[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 6.322264310888409e-36\n", - "Kc = 4.669334354059592e27\n", - "vacantX+vacantX+CC(O)=C=O<=>HX+O=C=C(O)C[Pt]\n", - "kf = 6.004181315465852e-13\n", - "krev = 0.19478740167193392\n", - "Kc = 3.082427951669201e-12\n", - "proton+O=C=C(O)C[Pt]<=>CC(O)=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.6475806151299193e-19\n", - "Kc = 1.517376434902315e29\n", - "proton+O=C=C(O)C=[Pt]<=>CHX+O=C=CO\n", - "kf = 0.00044142923419071626\n", - "krev = 7.030454489095277e-11\n", - "Kc = 6.278815044964784e6\n", - "proton+O=C=C(O)C#[Pt]<=>O=C=C(O)C=[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.413737039087288e-10\n", - "Kc = 2.655693471805739e19\n", - "proton+O=C=C(O)C=[Pt]<=>O=C=C(O)C[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.050236459862395e-43\n", - "Kc = 6.172479125045791e52\n", - "vacantX+vacantX+CCCO<=>OC[Pt]+CC[Pt]\n", - "kf = 4.648157058598011e-13\n", - "krev = 1.3999921584371802e15\n", - "Kc = 3.3201307811515004e-28\n", - "vacantX+vacantX+CCCO<=>CH3X+OCC[Pt]\n", - "kf = 1.2211065235504926e-16\n", - "krev = 1.2627143633797795e15\n", - "Kc = 9.670488900451568e-32\n", - "proton+CC([Pt])OC=O<=>CH4+O=COC=[Pt]\n", - "kf = 2.608059424001873e-13\n", - "krev = 1.9949354850991522e-8\n", - "Kc = 1.3073402340488457e-5\n", - "CHOX+CC=O<=>CC([Pt])OC=O\n", - "kf = 3.269864007171502e-8\n", - "krev = 0.48922244404245907\n", - "Kc = 6.68379802887317e-8\n", - "HX+C=COC=O<=>CC([Pt])OC=O\n", - "kf = 2.5565910629172877e-8\n", - "krev = 1.2259112200812889e-16\n", - "Kc = 2.0854618352769157e8\n", - "vacantX+vacantX+CCOC=O<=>HX+CC([Pt])OC=O\n", - "kf = 6.519502059052115e-22\n", - "krev = 142.86665816232104\n", - "Kc = 4.563347489828482e-24\n", - "proton+CC([Pt])OC=O<=>O=CO+CC=[Pt]\n", - "kf = 1.9656544562502943e6\n", - "krev = 2.020961723539808e-11\n", - "Kc = 9.726331940653283e16\n", - "proton+CC(=[Pt])OC=O<=>CH4+O=COC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.558494385695921e-8\n", - "Kc = 1.6041122912891756e18\n", - "proton+CC(=[Pt])OC=O<=>O=CO+CC#[Pt]\n", - "kf = 1.7807391551733809e6\n", - "krev = 5.863642747435994e-50\n", - "Kc = 3.036916183121913e55\n", - "proton+CC(=[Pt])OC=O<=>CC([Pt])OC=O\n", - "kf = 2.5e10\n", - "krev = 7.29542074748508e-57\n", - "Kc = 3.426807152777055e66\n", - "vacantX+vacantX+CCC(O)O<=>OC(O)[Pt]+CC[Pt]\n", - "kf = 3.712816041087776e-19\n", - "krev = 9.367983662004229e16\n", - "Kc = 3.9633032838716965e-36\n", - "vacantX+O=CC=CO<=>O=CC=CO.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 0.8868529608572997\n", - "Kc = 364007.2889878057\n", - "proton+O=CC=CO[Pt]<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.125561502536909e-21\n", - "Kc = 6.059781192118184e30\n", - "proton+O=C([Pt])C=CO<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.779022423570751e-21\n", - "Kc = 2.8476974763018754e30\n", - "HX+O=C=CC=O<=>O=CC=C(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.0473065138531246e-21\n", - "Kc = 2.475989854235963e13\n", - "proton+O=C=CC=O.[Pt]<=>O=CC=C(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.726642820300639e-15\n", - "Kc = 5.289166317502677e24\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC=C(O)[Pt]\n", - "kf = 2.77963678004065e-20\n", - "krev = 3.601218827022036\n", - "Kc = 7.718600045027592e-21\n", - "proton+O=CC=C(O)[Pt]<=>H2O+O=CC=C=[Pt]\n", - "kf = 5.7812366209281336e-11\n", - "krev = 1.1104870752509939e-6\n", - "Kc = 5.206036837143242e-5\n", - "proton+O=CC=C(O)[Pt]<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.2122557558958284e-33\n", - "Kc = 1.1300682542410892e43\n", - "vacantX+vacantX+CCOCO<=>OCO[Pt]+CC[Pt]\n", - "kf = 2.4512530384253315e-9\n", - "krev = 3.614837695546209e14\n", - "Kc = 6.781087409389048e-24\n", - "vacantX+vacantX+CCOCO<=>OC[Pt]+CCO[Pt]\n", - "kf = 1.0293700832173347e-6\n", - "krev = 1.2050997101819434e12\n", - "Kc = 8.541783509863451e-19\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC([Pt])=CO\n", - "kf = 4.3007284274917255e-15\n", - "krev = 1.9561961334382385\n", - "Kc = 2.1985159636997663e-15\n", - "HX+O=C=C=CO<=>O=CC([Pt])=CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.6370748462102965e-36\n", - "Kc = 1.5839961798805036e28\n", - "proton+O=CC([Pt])=CO<=>C=O+OC=C=[Pt]\n", - "kf = 1.0573125829484168e-30\n", - "krev = 6.241600179982588e-5\n", - "Kc = 1.693976788739721e-26\n", - "proton+O=C=C=CO.[Pt]<=>O=CC([Pt])=CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 4.8352733933355844e-30\n", - "Kc = 5.1703384620313873e39\n", - "HOX+C#CC=O<=>O=CC([Pt])=CO\n", - "kf = 2.952076594227614e-8\n", - "krev = 4.790462195255654e-44\n", - "Kc = 6.162404531970363e35\n", - "proton+O=CC([Pt])=CO<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.301245778704317e-28\n", - "Kc = 3.9674694303291534e37\n", - "proton+OC=CC=[Pt]<=>CHX+C=CO\n", - "kf = 90.55362122505268\n", - "krev = 1.3557377052656083e-12\n", - "Kc = 6.679287658176619e13\n", - "vacantX+vacantX+O=CC=CO<=>OX+OC=CC=[Pt]\n", - "kf = 8.803023976547135e-28\n", - "krev = 1.526615583505237e17\n", - "Kc = 5.766365856383213e-45\n", - "proton+OC=CC#[Pt]<=>OC=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.010813267435613e-18\n", - "Kc = 6.233149821004808e27\n", - "vacantX+vacantX+CCCOO<=>OOC[Pt]+CC[Pt]\n", - "kf = 5.56726706794292e-16\n", - "krev = 4.282042054393877e17\n", - "Kc = 1.3001430152303739e-33\n", - "proton+OCC(O)[Pt]<=>OC=[Pt]+CO-2\n", - "kf = 39.90218353825371\n", - "krev = 4.2391805941373414e-15\n", - "Kc = 9.412711407821884e15\n", - "HX+O=CCO<=>OCC(O)[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 4.347223516290618e-14\n", - "Kc = 644231.1603064304\n", - "vacantX+vacantX+OCCO<=>HX+OCC(O)[Pt]\n", - "kf = 7.314142036323851e-21\n", - "krev = 492.5535033039904\n", - "Kc = 1.4849436634317805e-23\n", - "HX+OC=CO<=>OCC(O)[Pt]\n", - "kf = 5.6012337000223925e-8\n", - "krev = 1.5412075197181771e-21\n", - "Kc = 3.634315060340885e13\n", - "HOX+C=CO<=>OCC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 6.743155058263278e-19\n", - "Kc = 4.8491603395127426e10\n", - "proton+O=CCO.[Pt]<=>OCC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.4340343074260776e-11\n", - "Kc = 5.6382062624392066e20\n", - "proton+OCC(O)[Pt]<=>H2O+OCC=[Pt]\n", - "kf = 177.91844230207138\n", - "krev = 3.2568464308064616e-11\n", - "Kc = 5.462905484862396e12\n", - "proton+OC=CO.[Pt]<=>OCC(O)[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 4.214854511364257e-15\n", - "Kc = 1.1862805671035147e25\n", - "proton+OCC(O)C#[Pt]<=>CX+OCCO\n", - "kf = 1284.511081678092\n", - "krev = 1.3713436394246532e-11\n", - "Kc = 9.366806719700164e13\n", - "vacantX+vacantX+CCC<=>CH3X+CC[Pt]\n", - "kf = 7.798842461270165e-20\n", - "krev = 4.754727023110295e15\n", - "Kc = 1.640229275700578e-35\n", - "proton+O=C([Pt])CO<=>OCC(O)=[Pt]\n", - "kf = 1.4296361342291135e-8\n", - "krev = 1.0085447542339824e12\n", - "Kc = 1.4175237422309153e-20\n", - "proton+OCC(O)=[Pt]<=>H2O+OCC#[Pt]\n", - "kf = 3.958447319557353e6\n", - "krev = 3.182083208820376e-48\n", - "Kc = 1.243979826984091e54\n", - "proton+OCC(O)=[Pt]<=>OC#[Pt]+CO-2\n", - "kf = 93517.82837499859\n", - "krev = 2.428322855670937e-42\n", - "Kc = 3.851128286199816e46\n", - "proton+OC=C(O)[Pt]<=>OCC(O)=[Pt]\n", - "kf = 1.5352733872797546e10\n", - "krev = 6.332152612110587e8\n", - "Kc = 24.245678860352488\n", - "proton+OCC(O)=[Pt]<=>OCC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.5032071422509527e-57\n", - "Kc = 5.551598940550537e66\n", - "HX+COC=O<=>COC(O)[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 224.3395816271696\n", - "Kc = 1.2483828443014824e-10\n", - "proton+COC(O)[Pt]<=>OC=[Pt]+CO-2\n", - "kf = 1.3782616260030866e8\n", - "krev = 2.2541975021300877e-19\n", - "Kc = 6.114200839548035e26\n", - "vacantX+vacantX+COCO<=>HX+COC(O)[Pt]\n", - "kf = 6.183244140051347e-23\n", - "krev = 2731.92216309053\n", - "Kc = 2.2633310068601865e-26\n", - "O=CO+CH3X<=>COC(O)[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 8.503469161971292e7\n", - "Kc = 3.7620485485108396e-16\n", - "proton+COC=O.[Pt]<=>COC(O)[Pt]\n", - "kf = 4.472471246879653\n", - "krev = 0.06133968239651949\n", - "Kc = 72.91317907334695\n", - "proton+COC(O)[Pt]<=>H2O+COC=[Pt]\n", - "kf = 1.2470163051273544e-7\n", - "krev = 2.43558443499695e-10\n", - "Kc = 511.9987988135242\n", - "vacantX+vacantX+CCOOC<=>COO[Pt]+CC[Pt]\n", - "kf = 1.4778859852656565e-10\n", - "krev = 2.404289853338368e13\n", - "Kc = 6.146871115450596e-24\n", - "vacantX+vacantX+CCOOC<=>CO[Pt]+CCO[Pt]\n", - "kf = 2.735304068777078e8\n", - "krev = 1.1929824589169815e-11\n", - "Kc = 2.2928284052560617e19\n", - "vacantX+vacantX+CCOOC<=>CH3X+CCOO[Pt]\n", - "kf = 1.542530561493995e-10\n", - "krev = 1.2789927244807063e12\n", - "Kc = 1.2060510837700736e-22\n", - "proton+COC(O)C#[Pt]<=>CX+COCO\n", - "kf = 9.593083466645867\n", - "krev = 2.0011561623178948e-10\n", - "Kc = 4.793770544890615e10\n", - "proton+COC(=O)[Pt]<=>COC(O)=[Pt]\n", - "kf = 2.1359376692019918e-7\n", - "krev = 1.0085447542339824e12\n", - "Kc = 2.1178412363309503e-19\n", - "proton+COC(O)=[Pt]<=>OC#[Pt]+CO-2\n", - "kf = 9.373860566892e7\n", - "krev = 2.3679228112414644e-41\n", - "Kc = 3.958685022328677e48\n", - "proton+COC(O)=[Pt]<=>H2O+COC#[Pt]\n", - "kf = 5.3217458625295416e7\n", - "krev = 1.3966950062652271e-42\n", - "Kc = 3.8102419201454223e49\n", - "proton+COC(O)=[Pt]<=>COC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.8456659619748266e-48\n", - "Kc = 8.785289747307718e57\n", - "vacantX+vacantX+C=C=COO<=>OOC=[Pt]+C=C=[Pt]\n", - "kf = 1.9145907695639512e-44\n", - "krev = 1.1771971588384226e12\n", - "Kc = 1.626397715275781e-56\n", - "C=O+O=CC[Pt]<=>O=CCCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 0.0025285011306884937\n", - "Kc = 1.5664103465194285e-5\n", - "HX+O=CCC=O<=>O=CCCO[Pt]\n", - "kf = 5.113182125834635e-8\n", - "krev = 3.03538509820146e-7\n", - "Kc = 0.16845250142607343\n", - "proton+O=CCC=O.[Pt]<=>O=CCCO[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 2.4177551440971664e-6\n", - "Kc = 2.0680340654872596e16\n", - "vacantX+vacantX+O=CCCO<=>HX+O=CCCO[Pt]\n", - "kf = 2.5157725911236352e-27\n", - "krev = 8837.406478086354\n", - "Kc = 2.84673178421957e-31\n", - "proton+O=CCCO[Pt]<=>OX+CCC=O\n", - "kf = 1.892400800322357e8\n", - "krev = 8.225252574797967e-26\n", - "Kc = 2.3007205956454646e33\n", - "CHOX+C=C<=>O=CCC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 0.4688595936220698\n", - "Kc = 1.7478623517301195e-7\n", - "proton+O=CCC[Pt]<=>CH2X+CC=O\n", - "kf = 0.4088202013457029\n", - "krev = 3.0029053456382804e-14\n", - "Kc = 1.3614155435818654e13\n", - "HX+C=CC=O<=>O=CCC[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 7.666152073113618e-12\n", - "Kc = 3780.924152337611\n", - "proton+O=CCC=[Pt]<=>O=CCC[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.9177352178840055e-40\n", - "Kc = 6.381237783982416e49\n", - "vacantX+vacantX+O=CCCO<=>HOX+O=CCC[Pt]\n", - "kf = 8.901266563864654e-15\n", - "krev = 1.309728963703428e15\n", - "Kc = 6.79626610584771e-30\n", - "vacantX+vacantX+CCC=O<=>HX+O=CCC[Pt]\n", - "kf = 1.6716561102658422e-25\n", - "krev = 524619.2678123232\n", - "Kc = 3.186417680076247e-31\n", - "vacantX+vacantX+CC=COO<=>OOC=[Pt]+CC=[Pt]\n", - "kf = 3.7147962989308654e-50\n", - "krev = 4.0636001726377395e18\n", - "Kc = 9.141638303749602e-69\n", - "proton+C=COOC#[Pt]<=>CX+C=COO\n", - "kf = 3.6540765247849917e-59\n", - "krev = 2.915247620280042e8\n", - "Kc = 1.253436071558812e-67\n", - "vacantX+C=CC=O<=>C=CC=O.[Pt]\n", - "kf = 365995.57053717994\n", - "krev = 1.0054621985249468\n", - "Kc = 364007.290452202\n", - "proton+C=CC(=O)[Pt]<=>C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.2322927799450702e-20\n", - "Kc = 2.0287386574734604e30\n", - "proton+O=CC=C[Pt]<=>C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.3417309535272846e-36\n", - "Kc = 1.0675863494199959e46\n", - "proton+C=CC=O.[Pt]<=>O=CCC[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.004428421127728e-5\n", - "Kc = 2.48897775830866e15\n", - "vacantX+vacantX+C=CC=O<=>HX+C=C([Pt])C=O\n", - "kf = 1.2784478936507186e-21\n", - "krev = 132.59733776930153\n", - "Kc = 9.641580405445367e-24\n", - "proton+C=C([Pt])C=O<=>C=O+C=C=[Pt]\n", - "kf = 5.880300754395758e-11\n", - "krev = 7.532973079877229e-10\n", - "Kc = 0.07806082262664338\n", - "HX+C=C=C=O<=>C=C([Pt])C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.4992009477647154e-32\n", - "Kc = 1.1812081765045545e24\n", - "vacantX+vacantX+C=C(O)C=O<=>HOX+C=C([Pt])C=O\n", - "kf = 1.107119853181277e-14\n", - "krev = 2.5289157654010746e13\n", - "Kc = 4.377843929513773e-28\n", - "proton+C=C=C=O.[Pt]<=>C=C([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.484084684889564e-26\n", - "Kc = 3.855594307437055e35\n", - "HX+C#CC=O<=>C=C([Pt])C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 1.683521621093348e-30\n", - "Kc = 1.753512730243651e22\n", - "proton+C=C([Pt])C=O<=>C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.7634080711060838e-36\n", - "Kc = 9.046799950176552e45\n", - "CHOX+C=C=O<=>C=C(C=O)O[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.906984656058423e-6\n", - "Kc = 0.017553122325364576\n", - "proton+C=C(C=O)O[Pt]<=>OX+C=CC=O\n", - "kf = 3312.686160774717\n", - "krev = 4.929585897381066e-13\n", - "Kc = 6.7200090022463e15\n", - "vacantX+vacantX+C=C(O)C=O<=>HX+C=C(C=O)O[Pt]\n", - "kf = 8.336773502217888e-19\n", - "krev = 4.018028855986407\n", - "Kc = 2.0748416203624424e-19\n", - "vacantX+vacantX+COCOC<=>CH3X+COCO[Pt]\n", - "kf = 0.24675966205104702\n", - "krev = 5.277017405064255e15\n", - "Kc = 4.6761199198288865e-17\n", - "vacantX+vacantX+COCOC<=>CO[Pt]+COC[Pt]\n", - "kf = 4.1241018831024145e-7\n", - "krev = 7.782310155024181e12\n", - "Kc = 5.2993286067375974e-20\n", - "proton+C=CC=[Pt]<=>CHX+C=C\n", - "kf = 3.268705758712953e8\n", - "krev = 6.199277832920159e-14\n", - "Kc = 5.272720221305576e21\n", - "vacantX+vacantX+C=CC=O<=>OX+C=CC=[Pt]\n", - "kf = 1.438969400016978e-30\n", - "krev = 1.6093339940290013e17\n", - "Kc = 8.941396909254915e-48\n", - "proton+C=CC#[Pt]<=>C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.000387979468591e-16\n", - "Kc = 8.332255751947066e25\n", - "vacantX+CC(O)O<=>CC(O)O.[Pt]\n", - "kf = 347843.58123444836\n", - "krev = 178209.4487483253\n", - "Kc = 1.9518806868971765\n", - "proton+CC(O)O[Pt]<=>CC(O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.617161959393997e-34\n", - "Kc = 5.414581558945629e43\n", - "vacantX+vacantX+COCCO<=>OC[Pt]+COC[Pt]\n", - "kf = 1.3358759661274015e-7\n", - "krev = 3.1165281946439875e14\n", - "Kc = 4.286423490161954e-22\n", - "vacantX+vacantX+COCCO<=>CO[Pt]+OCC[Pt]\n", - "kf = 6.192873660096324e-8\n", - "krev = 3.90827625278604e13\n", - "Kc = 1.584553716150872e-21\n", - "vacantX+vacantX+COCCO<=>CH3X+OCCO[Pt]\n", - "kf = 4.52195120819324e-12\n", - "krev = 5.920081591014324e14\n", - "Kc = 7.638325821483257e-27\n", - "proton+OC(O)C[Pt]<=>CH2X+OCO\n", - "kf = 5.501847802305245e-5\n", - "krev = 1.7947847097140223e-10\n", - "Kc = 306546.3936998828\n", - "HOX+C=CO<=>OC(O)C[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 6.095879365149742e-19\n", - "Kc = 5.364056293281289e10\n", - "HX+C=C(O)O<=>OC(O)C[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 1.7806643358524245e-19\n", - "Kc = 1.572793251160735e11\n", - "vacantX+vacantX+CC(O)O<=>HX+OC(O)C[Pt]\n", - "kf = 2.610914590914038e-25\n", - "krev = 48838.0104312493\n", - "Kc = 5.3460707507516085e-30\n", - "vacantX+vacantX+CCC(O)O<=>CH3X+OC(O)C[Pt]\n", - "kf = 2.73273606062798e-19\n", - "krev = 1.7143250273592365e15\n", - "Kc = 1.594059479396106e-34\n", - "proton+OC(O)C[Pt]<=>CC(O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.8575136346671286e-37\n", - "Kc = 8.748864641169856e46\n" - ] - } - ], - "source": [ - "for (i,rxn) in enumerate(inter.reactions)\n", - " str = getrxnstr(rxn)\n", - " kf = inter.kfs[i]\n", - " krev = inter.krevs[i]\n", - " Kc = kf/krev\n", - " println(str)\n", - " println(\"kf = $kf\")\n", - " println(\"krev = $krev\")\n", - " println(\"Kc = $Kc\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "dd1b08a5", - "metadata": {}, - "outputs": [ - { - "ename": "ErrorException", - "evalue": "type IdealSurface has no field kfs", - "output_type": "error", - "traceback": [ - "type IdealSurface has no field kfs\n", - "\n", - "Stacktrace:\n", - " [1] getproperty(x::IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, f::Symbol)\n", - " @ Base ./Base.jl:37\n", - " [2] top-level scope\n", - " @ ~/Work/Electrocat/CO2_RR_RMG/CO2_Reduction_Ag/jl_notebook_cell_df34fa98e69747e1a8f8a730347b8e2f_X26sdnNjb2RlLXJlbW90ZQ==.jl:3" - ] - } - ], - "source": [ - "for (i,rxn) in enumerate(domaincat.phase.reactions)\n", - " str = getrxnstr(rxn)\n", - " kf = domaincat.kfs[i]\n", - " krev = domaincat.krevs[i]\n", - " Kc = kf/krev\n", - " println(str)\n", - " println(\"kf = $kf\")\n", - " println(\"krev = $krev\")\n", - " println(\"Kc = $Kc\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "ef575a57", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "10195-element Vector{Float64}:\n", - " 0.0012344778691559958\n", - " 72.36206903962457\n", - " 1.961996133737021e-23\n", - " 4.18e17\n", - " 1.1335512974672508e13\n", - " 1.1335512974672508e13\n", - " 2.0225157751676203e6\n", - " 1.273973662253391e10\n", - " 2273.061514562824\n", - " 1.1335512974672508e13\n", - " ⋮\n", - " 6671.450650656444\n", - " 8.288339109768252e-5\n", - " 8.288339109768252e-5\n", - " 8.36e17\n", - " 8.195615541166058e-6\n", - " 2.762779703256084e-5\n", - " 8.288339109768252e-5\n", - " 3.6704623828488594e12\n", - " 1.8347921409001655e12" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "domaincat.kfs" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "09d93523", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.9.1", - "language": "julia", - "name": "julia-1.9" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.9.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/CO2RR_RMS/Ag/CO2RR_RMS_3.jl b/CO2RR_RMS/Ag/CO2RR_RMS_3.jl new file mode 100644 index 0000000..4ed5052 --- /dev/null +++ b/CO2RR_RMS/Ag/CO2RR_RMS_3.jl @@ -0,0 +1,207 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,jl:percent +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.17.2 +# kernelspec: +# display_name: Julia 1.9.1 +# language: julia +# name: julia-1.9 +# --- + +# %% +using DifferentialEquations +using ReactionMechanismSimulator +using PyPlot + +# %% +outdict = readinput("chem300.rms") + +# %% +liqspcs = outdict["gas"]["Species"] +liqrxns = outdict["gas"]["Reactions"] +surfspcs = outdict["surface"]["Species"] +surfrxns = outdict["surface"]["Reactions"] +interfacerxns = outdict[Set(["surface", "gas"])]["Reactions"] +solv = outdict["Solvents"][1]; + +# %% +sitedensity = 2.292e-5; # Ag111 +liq = IdealDiluteSolution(liqspcs,liqrxns,solv,name="liquid",diffusionlimited=true); +surf = IdealSurface(surfspcs,surfrxns,sitedensity,name="surface"); + +# %% +# Reservoir is a 100 mL (100e-6 m^3) cell +# Proton concentration is 10^-7 mol/L (10^-4 mol/m^3) +# CO2 concentration is 0.01 mol/L (10 mol/m^3), saturation solubility ~0.03 mol/L +# AVratio in experiments is 36 m^-1 but is measured by surface area/reservoir volume +# Area of the electrode is therefore 3.6e1 m^-1 * 1e2*1e-6 m^3 = 3.6e-3 m^2 = 36 cm^2 +# Assume boundary layer thickness d_bl = 1 mm or 1e-3 m +# Volume of the boundary layer V_bl = 3.6e-3 m^2 * 1e-3 m = 3.6e-6 m^3 +# Actual AVratio is therefore 3.6e-3 m^2 / 3.6e-6 m^3 = 1e3 m^-1 (reciprocal of d_bl) +# Amount of sites is 2.292e-5 mol/m^2 * 1e3 m^-1 = 2.292e-2 mol/m^-3 + +C_proton = 1e-7*1e3; +C_co2 = 1e-2*1e3; +C_default = 1e-12; +V_res = 100.0e-6; +AVratio = 1e3; +A_surf = 100.0e-6*36; +V_bl = A_surf/AVratio; +sites = sitedensity; + +initialcondsliq = Dict(["proton"=>C_proton, + "CO2"=>C_co2, + "V"=>V_res,"T"=>300,"Phi"=>0.0,"d"=>0.0]); + +initialcondssurf = Dict(["CO2X"=>0.4*sites, + "CHO2X"=>0.1*sites, + "CO2HX"=>0.1*sites, + "OX"=>0.1*sites, + "OCX"=>0.1*sites, + "vacantX"=>0.1*sites, + "CH2O2X"=>0.05*sites, + "CHOX"=>0.04*sites, + "CH2OX"=>0.01*sites, + "A"=>A_surf,"T"=>300,"Phi"=>-1.565]); + +# %% +domainliq,y0liq,pliq = ConstantTVDomain(phase=liq, + initialconds=initialcondsliq,constantspecies=["proton","CO2"]); +domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf, + initialconds=initialcondssurf); + +# %% +inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainliq, + domaincat,interfacerxns,298.15,A_surf); + +# %% +@time react,y0,p = Reactor((domainliq,domaincat), (y0liq,y0cat), (0.0, 1.0e3), [inter], (pliq,pcat,pinter)); + + +# %% +@time sol = solve(react.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-22,reltol=1e-8); + +# %% +sol.t[end] + +# %% +sol.retcode + +# %% +ssys = SystemSimulation(sol,(domainliq,domaincat,),(inter,),p); + +# %% +# Helper function +function plotX(sim, tol, t_end, exclude) + clf() + xs = molefractions(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Mole Fraction") +end + +# %% +# Helper function +function plotC(sim, tol, t_end, exclude) + clf() + xs = concentrations(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Concentration") +end + +# %% +exclude_species = ["H2O"] +plotX(ssys.sims[1], 1e-7, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e3) +ylim(1e-12, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V") +gcf() + +# %% +exclude_species = ["H2O"] +plotC(ssys.sims[1], 1e-3, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e3) +ylim(1e-6, 1e6) +title("Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys.sims[2], 1e-2, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e3) +ylim(1e-6, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V") +gcf() + +# %% +getfluxdiagram(ssys,1e3;speciesratetolerance=1e-6) + +# %% +println(ssys.names) + +# %% +for (i,rxn) in enumerate(inter.reactions) + str = getrxnstr(rxn) + kf = inter.kfs[i] + krev = inter.krevs[i] + Kc = kf/krev + println(str) + println("kf = $kf") + println("krev = $krev") + println("Kc = $Kc") +end + +# %% +for (i,rxn) in enumerate(domaincat.phase.reactions) + str = getrxnstr(rxn) + kf = domaincat.kfs[i] + krev = domaincat.krevs[i] + Kc = kf/krev + println(str) + println("kf = $kf") + println("krev = $krev") + println("Kc = $Kc") +end + +# %% +domaincat.kfs + +# %% diff --git a/CO2RR_RMS/Ag/CO2RR_RMS_AIChE.ipynb b/CO2RR_RMS/Ag/CO2RR_RMS_AIChE.ipynb deleted file mode 100644 index 1b2ed55..0000000 --- a/CO2RR_RMS/Ag/CO2RR_RMS_AIChE.ipynb +++ /dev/null @@ -1,1212 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 82, - "id": "8a590634", - "metadata": {}, - "outputs": [], - "source": [ - "using DifferentialEquations\n", - "using ReactionMechanismSimulator\n", - "using PyPlot" - ] - }, - { - "cell_type": "code", - "execution_count": 83, - "id": "e941d4fb", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[17:10:35] WARNING: not removing hydrogen atom without neighbors\n", - "[17:10:36] WARNING: not removing hydrogen atom without neighbors\n", - "┌ Warning: failed to generate StokesDiffusivity model for species vacantX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2O2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC([Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species H2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "[17:10:36] WARNING: not removing hydrogen atom without neighbors\n", - "[17:10:36] WARNING: not removing hydrogen atom without neighbors\n", - "┌ Warning: failed to generate StokesDiffusivity model for species vacantX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2O2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species H2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [H][H].[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n" - ] - }, - { - "data": { - "text/plain": [ - "Dict{Any, Any} with 4 entries:\n", - " \"Solvents\" => Solvent[Solvent(\"water\", RiedelViscosity{Float64}(…\n", - " Set([\"surface\", \"gas\"]) => Dict{Any, Any}(\"Reactions\"=>ElementaryReaction[vac…\n", - " \"gas\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…\n", - " \"surface\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "outdict1 = readinput(\"chem43_Ag.rms\");\n", - "outdict2 = readinput(\"chem43_Cu.rms\")\n" - ] - }, - { - "cell_type": "code", - "execution_count": 84, - "id": "fe2767e9", - "metadata": {}, - "outputs": [], - "source": [ - "liqspcs1 = outdict1[\"gas\"][\"Species\"];\n", - "liqrxns1 = outdict1[\"gas\"][\"Reactions\"];\n", - "surfspcs1 = outdict1[\"surface\"][\"Species\"];\n", - "surfrxns1 = outdict1[\"surface\"][\"Reactions\"];\n", - "interfacerxns1 = outdict1[Set([\"surface\", \"gas\"])][\"Reactions\"];\n", - "solv1 = outdict1[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 85, - "id": "2e3c1e9a", - "metadata": {}, - "outputs": [], - "source": [ - "liqspcs2 = outdict2[\"gas\"][\"Species\"];\n", - "liqrxns2 = outdict2[\"gas\"][\"Reactions\"];\n", - "surfspcs2 = outdict2[\"surface\"][\"Species\"];\n", - "surfrxns2 = outdict2[\"surface\"][\"Reactions\"];\n", - "interfacerxns2 = outdict2[Set([\"surface\", \"gas\"])][\"Reactions\"];\n", - "solv2 = outdict2[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 86, - "id": "711d8a69", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "100000.0" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sitedensity1 = 2.292e-5; # Ag111\n", - "sitedensity2 = 2.943e-5; # Cu111\n", - "AVratio = 1.0e5" - ] - }, - { - "cell_type": "code", - "execution_count": 87, - "id": "8894c84d", - "metadata": {}, - "outputs": [], - "source": [ - "initialcondsliq = Dict([\"proton\"=>10.0^-4,\"CO2\"=>10.0^-3*10^3,\n", - " \"V\"=>1.0,\"T\"=>298.15,\"Phi\"=>0.0,\"d\"=>0.0]);\n", - "initialcondssurf1 = Dict([\"CO2X\"=>0.4*sitedensity1*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity1*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity1*AVratio,\n", - " \"OX\"=>0.1*sitedensity1*AVratio,\n", - " \"OCX\"=>0.1*sitedensity1*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity1*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity1*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity1*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity1*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-1.5]);\n", - "initialcondssurf2 = Dict([\"CO2X\"=>0.4*sitedensity1*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity1*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity1*AVratio,\n", - " \"OX\"=>0.1*sitedensity1*AVratio,\n", - " \"OCX\"=>0.1*sitedensity1*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity1*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity1*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity1*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity1*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-1.0]);\n", - "initialcondssurf3 = Dict([\"CO2X\"=>0.4*sitedensity1*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity1*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity1*AVratio,\n", - " \"OX\"=>0.1*sitedensity1*AVratio,\n", - " \"OCX\"=>0.1*sitedensity1*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity1*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity1*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity1*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity1*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-2.0]);\n", - "initialcondssurf4 = Dict([\"CO2X\"=>0.4*sitedensity2*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity2*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity2*AVratio,\n", - " \"OX\"=>0.1*sitedensity2*AVratio,\n", - " \"OCX\"=>0.1*sitedensity2*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity2*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity2*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity2*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity2*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-1.5]);\n", - "initialcondssurf5 = Dict([\"CO2X\"=>0.4*sitedensity2*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity2*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity2*AVratio,\n", - " \"OX\"=>0.1*sitedensity2*AVratio,\n", - " \"OCX\"=>0.1*sitedensity2*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity2*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity2*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity2*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity2*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-1.0]);\n", - "initialcondssurf6 = Dict([\"CO2X\"=>0.4*sitedensity2*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity2*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity2*AVratio,\n", - " \"OX\"=>0.1*sitedensity2*AVratio,\n", - " \"OCX\"=>0.1*sitedensity2*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity2*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity2*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity2*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity2*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-2.0]);" - ] - }, - { - "cell_type": "code", - "execution_count": 88, - "id": "ddb39b3d", - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "liq1 = IdealDiluteSolution(liqspcs1,liqrxns1,solv1,name=\"liquid\",diffusionlimited=true);\n", - "\n", - "liq2 = IdealDiluteSolution(liqspcs2,liqrxns2,solv2,name=\"liquid\",diffusionlimited=true);\n", - "\n", - "surf1 = IdealSurface(surfspcs1,surfrxns1,sitedensity1,name=\"surface\");\n", - "\n", - "surf2 = IdealSurface(surfspcs2,surfrxns2,sitedensity2,name=\"surface\");\n", - "\n", - "domainliq1,y0liq1,pliq1 = ConstantTVDomain(phase=liq1,\n", - " initialconds=initialcondsliq,constantspecies=[\"proton\",\"CO2\"]);\n", - "\n", - "domainliq2,y0liq2,pliq2 = ConstantTVDomain(phase=liq2,\n", - " initialconds=initialcondsliq,constantspecies=[\"proton\",\"CO2\"]);" - ] - }, - { - "cell_type": "code", - "execution_count": 89, - "id": "29ec7f86", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat1,y0cat1,pcat1 = ConstantTAPhiDomain(phase=surf1,\n", - " initialconds=initialcondssurf1);\n", - "\n", - "inter1,pinter1 = ReactiveInternalInterfaceConstantTPhi(domainliq1,\n", - " domaincat1,interfacerxns1,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 90, - "id": "02daf794", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat2,y0cat2,pcat2 = ConstantTAPhiDomain(phase=surf1,\n", - " initialconds=initialcondssurf2);\n", - "\n", - "inter2,pinter2 = ReactiveInternalInterfaceConstantTPhi(domainliq1,\n", - " domaincat2,interfacerxns1,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 91, - "id": "b6bac559", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat3,y0cat3,pcat3 = ConstantTAPhiDomain(phase=surf1,\n", - " initialconds=initialcondssurf3);\n", - " \n", - "inter3,pinter3 = ReactiveInternalInterfaceConstantTPhi(domainliq1,\n", - " domaincat3,interfacerxns1,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 92, - "id": "5ed60871", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat4,y0cat4,pcat4 = ConstantTAPhiDomain(phase=surf2,\n", - " initialconds=initialcondssurf4);\n", - " \n", - "inter4,pinter4 = ReactiveInternalInterfaceConstantTPhi(domainliq2,\n", - " domaincat4,interfacerxns2,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 93, - "id": "5b589c3f", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat5,y0cat5,pcat5 = ConstantTAPhiDomain(phase=surf2,\n", - " initialconds=initialcondssurf5);\n", - " \n", - "inter5,pinter5 = ReactiveInternalInterfaceConstantTPhi(domainliq2,\n", - " domaincat5,interfacerxns2,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 94, - "id": "8eaa5eaf", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat6,y0cat6,pcat6 = ConstantTAPhiDomain(phase=surf2,\n", - " initialconds=initialcondssurf6);\n", - " \n", - "inter6,pinter6 = ReactiveInternalInterfaceConstantTPhi(domainliq2,\n", - " domaincat6,interfacerxns2,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 95, - "id": "244f0912", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.001202 seconds (3.31 k allocations: 960.234 KiB)\n", - " 0.105116 seconds (462.72 k allocations: 65.158 MiB, 18.36% gc time)\n" - ] - } - ], - "source": [ - "@time react1,y01,p1 = Reactor((domainliq1,domaincat1), (y0liq1,y0cat1), (0.0, 1.0e2), [inter1], (pliq1,pcat1,pinter1));\n", - "\n", - "@time sol1 = solve(react1.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6);\n", - "\n", - "ssys1 = SystemSimulation(sol1,(domainliq1,domaincat1,),(inter1,),p1);\n" - ] - }, - { - "cell_type": "code", - "execution_count": 96, - "id": "3b06f7a9", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.001183 seconds (3.31 k allocations: 960.234 KiB)\n", - " 0.033939 seconds (133.51 k allocations: 19.993 MiB, 23.54% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "[CVODES ERROR] CVode\n", - " At t = 1.71566e-13 and h = 2.74651e-20, the error test failed repeatedly or with |h| = hmin.\n", - "\n" - ] - } - ], - "source": [ - "@time react2,y02,p2 = Reactor((domainliq1,domaincat2), (y0liq1,y0cat2), (0.0, 1.0e2), [inter2], (pliq1,pcat2,pinter2));\n", - "\n", - "@time sol2 = solve(react2.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-12,reltol=1e-6);\n", - "\n", - "ssys2 = SystemSimulation(sol2,(domainliq1,domaincat2,),(inter2,),p2);" - ] - }, - { - "cell_type": "code", - "execution_count": 97, - "id": "ab03df14", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.001498 seconds (3.31 k allocations: 960.234 KiB)\n", - " 0.074664 seconds (341.64 k allocations: 46.424 MiB, 11.17% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "[CVODES ERROR] CVode\n", - " At t = 15.6322 and h = 5.60371e-09, the error test failed repeatedly or with |h| = hmin.\n", - "\n" - ] - } - ], - "source": [ - "@time react3,y03,p3 = Reactor((domainliq1,domaincat3), (y0liq1,y0cat3), (0.0, 1.0e2), [inter3], (pliq1,pcat3,pinter3));\n", - "\n", - "@time sol3 = solve(react3.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6);\n", - "\n", - "ssys3 = SystemSimulation(sol3,(domainliq1,domaincat3,),(inter3,),p3);" - ] - }, - { - "cell_type": "code", - "execution_count": 98, - "id": "9b238da8", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.001587 seconds (3.66 k allocations: 865.812 KiB)\n", - " 0.056727 seconds (266.76 k allocations: 31.517 MiB, 15.80% gc time)\n" - ] - } - ], - "source": [ - "@time react4,y04,p4 = Reactor((domainliq2,domaincat4), (y0liq2,y0cat4), (0.0, 1.0e2), [inter4], (pliq2,pcat4,pinter4));\n", - "\n", - "@time sol4 = solve(react4.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6);\n", - "\n", - "ssys4 = SystemSimulation(sol4,(domainliq2,domaincat4,),(inter4,),p4);" - ] - }, - { - "cell_type": "code", - "execution_count": 99, - "id": "b7c78e37", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.001386 seconds (3.66 k allocations: 865.812 KiB)\n", - " 0.047519 seconds (288.60 k allocations: 33.380 MiB)\n" - ] - } - ], - "source": [ - "@time react5,y05,p5 = Reactor((domainliq2,domaincat5), (y0liq2,y0cat5), (0.0, 1.0e2), [inter5], (pliq2,pcat5,pinter5));\n", - "\n", - "@time sol5 = solve(react5.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6);\n", - "\n", - "ssys5 = SystemSimulation(sol5,(domainliq2,domaincat5,),(inter5,),p5);" - ] - }, - { - "cell_type": "code", - "execution_count": 100, - "id": "8498a9b3", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.001202 seconds (3.66 k allocations: 865.812 KiB)\n", - " 0.053374 seconds (254.13 k allocations: 30.542 MiB, 19.28% gc time)\n" - ] - } - ], - "source": [ - "@time react6,y06,p6 = Reactor((domainliq2,domaincat6), (y0liq2,y0cat6), (0.0, 1.0e2), [inter6], (pliq2,pcat6,pinter6));\n", - "\n", - "@time sol6 = solve(react6.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6);\n", - "\n", - "ssys6 = SystemSimulation(sol6,(domainliq2,domaincat6,),(inter6,),p6);" - ] - }, - { - "cell_type": "code", - "execution_count": 101, - "id": "39632165", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotX1 (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotX1(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = molefractions(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Mole Fraction\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 130, - "id": "63bd3256", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotX (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "function plotX(bsol, tol, t_end, exclude)\n", - " # Species order and corresponding colors for the main species\n", - " species_order = [\"CO2\", \"proton\", \"H2\", \"O=CO\", \"C=O\", \"O=CC=O\", \"O=CCO\"]\n", - " color_map = Dict(\"CO2\" => \"blue\", \"proton\" => \"orange\", \"H2\" => \"purple\",\n", - " \"O=CO\" => \"red\", \"C=O\" => \"green\", \"O=CC=O\" => \"magenta\",\n", - " \"O=CCO\" => \"brown\")\n", - " # Replacement map for species labels\n", - " replacement_map = Dict(\"C=O\" => \"CH2=O\", \"O=CO\" => \"HCOOH\",\n", - " \"O=CC=O\" => \"O=CH-CH=O\", \"O=CCO\" => \"O=CH-CH2OH\")\n", - "\n", - " clf()\n", - " \n", - " xs = molefractions(bsol)\n", - " maxes = maximum(xs, dims=2)\n", - " spnames = []\n", - " plotted_species = Set{String}()\n", - "\n", - " # Filter data to the specified time range\n", - " if t_end !== nothing\n", - " t_mask = bsol.sol.t .<= t_end\n", - " ts = bsol.sol.t[t_mask]\n", - " xs = xs[:, t_mask]\n", - " else\n", - " ts = bsol.sol.t\n", - " end\n", - "\n", - " # Plot species in the specified order with custom colors and labels\n", - " for sp in species_order\n", - " # Find the species index in the phase\n", - " species_index = findfirst(x -> x.name == sp, bsol.domain.phase.species)\n", - " if species_index === nothing || maxes[species_index] <= tol || sp in exclude\n", - " continue\n", - " end\n", - "\n", - " # Apply replacement for display name if available\n", - " display_name = get(replacement_map, sp, sp)\n", - "\n", - " # Plot the species with the specified color\n", - " plot(ts, xs[species_index, :], label=display_name, color=color_map[sp])\n", - " push!(spnames, display_name)\n", - " push!(plotted_species, sp)\n", - " end\n", - "\n", - " # Plot any remaining species that are above the tolerance and not already plotted\n", - " for i = 1:length(bsol.domain.phase.species)\n", - " sp = bsol.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(sp in exclude) && !(sp in plotted_species)\n", - " plot(ts, xs[i, :], label=sp)\n", - " push!(spnames, sp)\n", - " end\n", - " end\n", - "\n", - " # Configure the legend and labels\n", - " xlabel(\"Time in sec\", fontsize=16)\n", - " ylabel(\"Mole Fraction\", fontsize=16)\n", - " xticks(fontsize=14)\n", - " yticks(fontsize=14)\n", - " legend(spnames, loc=\"upper left\", bbox_to_anchor=(0, 0.93), fontsize=12, ncol=2)\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 132, - "id": "6ef159b3", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys1.sims[1], 1e-12, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1)\n", - "ylim(1e-12, 5)\n", - "title(\"Ag111@-1.5 V\", fontsize=16, fontweight=\"bold\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 133, - "id": "bce46a3f", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys2.sims[1], 1e-10, 10, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 10)\n", - "ylim(1e-12, 5)\n", - "title(\"Ag111@-1.0 V\", fontsize=16, fontweight=\"bold\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 134, - "id": "78344a8c", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys3.sims[1], 1e-12, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1)\n", - "ylim(1e-12, 5)\n", - "title(\"Ag111@-2.0 V\", fontsize=16, fontweight=\"bold\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 135, - "id": "a5b06177", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys4.sims[1], 1e-12, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1)\n", - "ylim(1e-12, 5)\n", - "title(\"Cu111@-1.5 V\", fontsize=16, fontweight=\"bold\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 136, - "id": "a15be1a0", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys5.sims[1], 1e-12, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1)\n", - "ylim(1e-12, 5)\n", - "title(\"Cu111@-1.0 V\", fontsize=16, fontweight=\"bold\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 137, - "id": "076638f2", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys6.sims[1], 1e-12, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1)\n", - "ylim(1e-12, 5)\n", - "title(\"Cu111@-2.0 V\", fontsize=16, fontweight=\"bold\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 109, - "id": "87dcaf99", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys1.sims[2], 0.1, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1)\n", - "ylim(1e-12, 5)\n", - "title(\"Solid-phase Mole Fractions on Ag111@-1.5 V\", fontsize=16, fontweight=\"bold\")\n", - "legend(loc=\"lower left\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 110, - "id": "4dfc055c", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Dict{String, Float64} with 17 entries:\n", - " \"O=CC=O\" => 3.45197e-29\n", - " \"proton\" => 2.7869e-5\n", - " \"O=CO\" => 0.646063\n", - " \"Ne\" => 0.0\n", - " \"COC=O\" => 1.65034e-15\n", - " \"[O]C=O\" => 2.21457e-42\n", - " \"C=O\" => 1.79e-10\n", - " \"[CH]=O\" => 2.77632e-32\n", - " \"CO2\" => 0.27869\n", - " \"O=[C]O\" => 4.57006e-35\n", - " \"N2\" => 0.0\n", - " \"O=CCO\" => 2.01266e-6\n", - " \"Ar\" => 0.0\n", - " \"H2O\" => 0.0752102\n", - " \"He\" => 0.0\n", - " \"H\" => 5.33777e-37\n", - " \"H2\" => 6.18658e-6" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "Dict([ssys1.sims[1].names[i]=>molefractions(ssys1.sims[1],1)[i] for i in 1:length(ssys1.sims[1].names)])" - ] - }, - { - "cell_type": "code", - "execution_count": 121, - "id": "1f7d8918", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "842×1012 Array{RGBA{N0f8},2} with eltype ColorTypes.RGBA{FixedPointNumbers.N0f8}:\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,0.733) RGBA{N0f8}(1.0,1.0,1.0,0.733)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fd1 = getfluxdiagram(ssys1,1;speciesratetolerance=1e-4)" - ] - }, - { - "cell_type": "code", - "execution_count": 122, - "id": "379c4050", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "1322×1036 Array{RGB{N0f8},2} with eltype ColorTypes.RGB{FixedPointNumbers.N0f8}:\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " ⋮ ⋱ ⋮\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fd3 = getfluxdiagram(ssys3,1;speciesratetolerance=1e-4)" - ] - }, - { - "cell_type": "code", - "execution_count": 123, - "id": "007de25f", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "879×750 Array{RGB{N0f8},2} with eltype ColorTypes.RGB{FixedPointNumbers.N0f8}:\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fd4 = getfluxdiagram(ssys4,1;speciesratetolerance=1e-4)" - ] - }, - { - "cell_type": "code", - "execution_count": 124, - "id": "977f11cd", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "884×750 Array{RGB{N0f8},2} with eltype ColorTypes.RGB{FixedPointNumbers.N0f8}:\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fd5 = getfluxdiagram(ssys5,1;speciesratetolerance=1e-4)" - ] - }, - { - "cell_type": "code", - "execution_count": 125, - "id": "6eaab3dd", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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1hAkTVFVFHZCXfEvJOxfhrxBTIknYRgr7FMh28Myi6icRXdph/JNGgVUUWAVTN2GfLGxXAxKMMcYalgSrO013/xJ6JSKi5ijOWVAzYcyJEyemT5/+5ptvBoNBNBp79+6dMmXKU0899fjjj99www0wLnyQfB+QbwF0N2LK1E3Ybha20RA21BK2sVTzPMiP2AntIveDVP2MsI8T9olQUsEYY6yhSLC6ouoZCG5BRNQcxTkXaksYoOv6O++888ADD5SVlaFR2rt374033jhkyJA//elPXbp0wVlQiAIr4V1AwQ0AIXaEWViGCvsUmHvhPyjJwjqKfB8gWhQH9Cr8kH6Sal4kz6vCOlIk3A7ZAYwxxmJPgtUJBT4nz+uIiJqrON+BmgMD9u7dO2XKlM2bN6PRW7VqVa9evR5++OFHHnlEVVX8B/0k+RaRdy60Y4gptbWw3yhsN0JJxRkI+yTyfYBoEKaLKLQdZ0FB8i0m34fCPECkPAfFCcYYY7EkwepAKyX3gwDBOCVFSX0Tag4MmDNnzt133+3xeBAnAoHA9OnTV6xYMW/evAsuuAD/RBTcAO8C8v8V0BBDijD3Q8JkYRkCCJydqQtM3REqRD2Ze0PNQWg7zo1IOyyUFDDGGIsxCRYxIvdD0CthnLAoKa9AtsG5+Hy+2267bf78+YhDmzZtuvjiixfMf/3yAQHyzkb4G8SU0kLYxgr7LVBbwjBhH0/u36A+zL2U5Gf0shEwRtgnAgoYY4zFmASLEPk+oOAGREAIx//A3AvnUllZee211/79739HfCroYbljktqn7a+oSkFMmboJ+2RhuxqQiJCwjqLqP0J3oW5M+UrqG+R5CxSAESJB2K8HY4yx2JNgEdFPUvUfEQmR9ICwjca5HD58eMSIEXv27EF8+tvClpdfakdMiURhu1bYx0O2R50Jq7COJu8c1IGpq5I6E8JCvgUwRtjGQiSBMcZY7EmwSFDVH6C7YZiwjREJd+JcysrKhg8fvm/fPkSbxWLJyspq2bJlcnJyYmKioig2m83j8YTD4aqqquPHjx87dqy8vBz1tvfr4OWX2hEjsq2w3yJsN0LYUU8UQngf6sDUWUl9C0oy+ZdBK4UhQtgngDHGWIOQYIZRYDX5P4Jxsr1wPIZzqampGTly5L59+xANOTk5l112WUFBQbdu3bp06ZKXl4dz8fv9e/fu3b17d2Fh4bp16zZv3hwMBhGhl99y3/2TFCEQTcIkLMNgv1mYByA6wuS6l4KbECnZUUmdDSUZAHnmwBhhuRSyLRhjjDUICWYQ+anqdzBO2JSU/4Ow4ayI6JZbbtm8eTPqQVXVSy+9dMyYMVdddVX79u0RIavVml8Ltbxe77p16z788MPFixeXlJTAmL1fBz/f4Bs8wIaoUDOF7SZhHw8lDVGjketXFPgUkZJtFecsKCn4h9AuhLbDIPtkMMYYaygSzBjyzoZWCsOE4zHIdjiXF198cdmyZairCy+88M4777z11lszMjIQJXa7fXitF154Yc2aNa+88sqiRYuCwSDO5ZXZrsEDbKgXRZj7wX6zsF4BqIgmjVzTyL8CkZJtFOfbUFqgFnlnwyC1jbBcAsYYYw1Fghmhu8jzGgwTtjHCNgbnsnPnzoceegh10qtXr9/97nfXXHONoiiIDUVRBtcqLS199tlnX3nlFY/HgzNbtMJztDSckyVRB4pDWK8TCVOg5iH6NHL/mvzLECm1teJ8B0o6TtHLyf8RjBEJkwEFjDHGGooEM4A8L0OvgkFKukh6GOdCRLfffrvf70eEWrduPWPGjDFjxggh0CCysrKeffbZBx988NFHH33jjTd0XcePCYfpzXlVj/7SiYiYugnbzcI2GsKGmCCqmk6+DxEpNUdxvgUlA98j77ugIIwQCcJ2HRhjjDUgCXZOWgl558Iw4XgMSjLOZcGCBZs3b0YkFEW5//77H3vssYSEBDS4jIyMmTNn3lZr7969+DGvznE/9LNUk0ngnIRFWK8S9lth6oIYIqp6jLwLESk1W3G+A7Ul/oVC5J0PY4T9JohEMMYYa0AS7Fyo5kVQEMYI6whhHY5zCQQCDz/8MCKRlZU1Z86c4cOH47zq16/fl19+ee+9977xxhv4gaOl4eUrPdddlYizUNsI+w3CdjOUZMQWUdXj5J2HSKlZivNtqLk4DfmXQz8JQ4Sw3QLGGGMNS4KdnXac/EthkEgSSY/AgPfee+/gwYMwrHPnzh999FHr1q3RCNjt9tdff7179+7333+/ruv4dy/Pdl93VSJ+QNOg2gaLxFuFuT8gEHtU/Qx55yJSSgsldRbUVvh35H0HxgjLEMg2YIwx1rAk2FmR921QCMaIpPugZsKAWbNmwbAePXqsWrXK6XSiMbnvvvuSk5Nvu+02IsJpPl3j3fdtsOOFZnyv9IQ2Z2HVy2+53pz98tChA9AgqPo58ryOSClpinMO5IX4D6FtCO2EQQmTwRhjrMFJsLMgD/nmwyA1V9jGwYADBw6sWrUKxrRu3frjjz92Op1ofG699daTJ08++OCDOA0RZs5xP/f7dADrNvteeM314ceeUIgAvPnmm0OHDkXsUc3z5HkVkVKcinM2ZDv8AHnmwCDZTpj7gzHGWIOTYGdG3vegV8EYkfQAhBkG/OUvfyEiGCClnDdvXnZ2NhqradOmrV+/fvHixTjN7AVVeS1NM+e4930bxGkWL14cCoVMJhNiiWpepJqXESnFoaS+DtkBP6SfIP8nMEbYJwECjDHGGpwEOyONvHNgkKmrsI6EMevWrYMxv/jFL/r374/GbebMmatWrXK73fhepVt/YPpJ/IDX6922bVufPn0QM+R5k2peRKREkpI6C6Zu+DHkfRcIwwjFIWzXgTHG2Pkgwc6AghuhHYExIvGXgIABRLR+/XoYkJqa+sgjj6AeiouLfT5fbm5uQkICAJfLVVRUdMEFFyQnJyN60tPTp02b9uijj8KA9evX9+nTB7FBnreo+ilESiQqzjdh6o4fRUHyLoQxwnYjhA2MMcbOBwl2Jr7FMEh2EJZLYcyhQ4dOnDgBA8aPH5+SkoJ6WLRo0bfffnvPPfd07NgRwK5du/74xz8+8sgj/fr1Q1Tdeeedjz/+eDAYxLl88cUXiA3yzqHqJxApYVNSX4WpJ86A/Euhl8EQVdgngDHG2HkiwX4U+cj/NxgjEqYCAsaUlpbCmOuuuw5xIj09feDAgatWrcK5lJaWIgbI9x5V/Q8iJWwidSbMF+PMyDsXxgjr5VBzwRhj7DyRYD+G/J+AvDBCyRDWq2FYeXk5jLn44osRPy6++OJVq1bhXMrLyxFt5PuA3L8FCBERVpH6qjD3xVkEv0RoFwyyTwJjjMWtioqK7du3f/XVVz6fLyUlpXv37l26dNm2bVsoFOrVq1dKSgqA4uLiDRs2DBo0KDs7G42PBPtRvsUwRiRMhDDBsPLychhgtVqTk5NRb7t373711VdbtGgB4NChQ8ePH0dsZGdnw4CysjJEFfkWkfsRQEdEhEmkvCDM/XBW5J0Dg2QHYe4LxhiLTydOnFiyZMn69esdDkdSUpLb7a6oqLDZbJ9++qnP52vTpk1KSgqAgwcPzp49u23bttnZ2Wh8JNgP6ZUU3ARDVGG7HpFQFAUG6LqOaFAUxWQymc1mAFJKIQRiQ9M0GKCqKqKH/B+R+2FAR0SESaS8KCyDcXbacfKvhDEiYQogwBhjcUjX9c2bN3/88ccDBgwYO3Zsenp6VVXVgQMHHA4H4ooE+wEKfA5oMEBYBkJJRyTS0tJgQDAYLC8vT0tLQ/106NBh/Pjx7dq1A7Bhw4aioiIAxcXFixYtcrlcrVq1uvnmm+12O+rt6NGjMMDpdCJKyP8Jue4HNERGipT/E5bLcS7kfQcIwwglWVivBmOMxafq6uqtW7fabLYbbrihVatWABISErKyshBvJNgPBVbDINu1iFBaWhqM2bhx46hRo1A/qqpardaEhAQAVqtVURQAiqL07t2biObOnVtQUNC1a1dVVVE/mzZtggEtWrRANJB/Jbl+CWiIjCpSnhGWYTgn8pNvAYwRtnEQNjDGWHyqqqoqKytr0aJFTk4OvieEQK1Nmza53e7k5GQAhw8fLi0tRWMlwf6TRsF1MELYhGUoIpSTkwNj3n///VGjRiEGMjMzs7OzFUWZP3++x+MhItTP4cOHN27cCANatmyJeqPAGnL/AggjMqpI/qOwjoIB5F8K3QVDVGEfB8YYi1uKogghdF0nIvxAQkJCRkZGWloaAJ/PJ6VEYyXB/kNwG3Q3DBCWoRB2RCg3N7dly5YlJSU4l/fee+/JJ5/MyspCXU2YMCEUCjmdTtTKz8//05/+lJ6ebjKZAOzfv9/tdrdp00ZVVdTPSy+9pGkaDOjbty/qh4LryHUPKIjIKCL5SWEbDWPIMwfGCOsVUFuCMcbiVnJyck5OztatW4uKitq3b49aRIRanTp1uvnmm9u0aQNg7dq1+/fvB1BcXLxkyRKXy5WXl3f99dcnJiaiEZBg/46Ca2GQZTDqZODAgQsXLsS5eDye3/3udzNnzkRdtWjRAqdJqIVaLpfrmWeeueuuu1q0aCGEQD0UFxe/8MILMGbgwIGoBwqup8qfggKIjBCOx4TtOhhDwY0I74Mxwj4JjDEWz+x2+8UXX7xly5ZZs2ZNnDgxNze3rKyssLCwffv2AKSUNpstISEBgNVqVRQFtTp16qRp2pIlS/Lz87t06SKlxPkmwf5DcCsMUYVlEOpk4MCBCxcuhAGvv/76mDFjrrrqKkRVKBSaPn366NGjCwoKpJSoB03TJk+e7PP5YEBycnK3bt1QZ8GtVHk3yI/ICOH4nbCPg3Hed2CQqTPMvcEYY/FMUZSCgoLx48d//PHH06dPVxQlKSmpcy2cQWZmZk5Ojqqqy5cvr6qqIiI0AhLs32gU2gkjzD2hpKBObrjhhgceeCAcDuNciGjKlClr167t0KEDoudvf/vbhg0bduzY8eKLLz744IODBw+WUqJOHnzwwc8//xzG3HDDDaqqom5C2/TKqSAvIiSSpgn7BBinHSX/pzBG2KeAMcbin8PhGDZsWIcOHY4ePRoKhex2e25ubk5Ozvjx4zVNy8rKQq1u3bpNnz69ffv2FosFQFFRUU1NTU5OjqqqaAQk2OlC+0BeGCDMl6GucnJyRowYsWzZMhhw8uTJK6+88vPPP2/VqhWiZGQt1NuTTz45Y8YMGDZ16lTUTWiHXjEV5EGERNKvRMLtiAR55wEajFCcwjoKjDEW/4jIbrd3roXTdOjQAadJq4Va1dXVr7322jXXXJOdna0oChoBCXYaCm2DMcJ8MerhtttuW7ZsGYwpKioaMGDAihUrevTogcaBiH71q1/NmDEDhnXp0qV///6og9BevfJ2UA0iJJLuFwl3IiIUJN8HMEbYx0FYwBhj8c/v9y9ZsiQYDE6aNGn+/Pmapo0dO9Zms+EMwuHwyy+/3K5du8suu8xqtaJxkGCnC+2AIRKmrqiHa6+99qKLLtq+fTuMKSkpueSSS1566aVJkybhfCsrK7v11luXL1+OSDzyyCOog/BXeuUU6G5ESCTeKxL+CxEi/wroZTBECts4MMZYk6Dr+pEjR3w+H4DDhw+HQiFN03BmGzduXL58eXZ29pYtWyZOnFhQUGAymXC+SbDTUHgfjDB1hrChHhRFeeKJJ0aOHAnDqqurJ0+e/Mknn8yYMSMjIwPnyYcffnj33XcfPXoUkSgoKBg3bhwiFT6gV9wG3YUIiYSpIvFniBx558IYYb0CahYYY6xZ6tat28svv6woihAiKytLVVU0AhLs/9MRPggDhCkf9XbVVVcNHTr0008/RSTmzp27fPnyxx9//K677jKbzWhAe/funTZt2vLlyxG5p59+WlEURCRcpFdMgl6GCImEn4ikh1AHod0I7YAxwj4ZjDHWXKXUQiMjwf5FOwzywwhTN0TDzJkz8/Pzq6qqEAmXy3Xvvfc+88wzv/71r3/yk5/YbDbE2K5du5544okFCxbouo7I3XHHHZdffjkiohXpFROhn0SEhH2KSPoN6oS8c2CQ7ARzLzDGGGtMJNhgT4/lAAAgAElEQVT3KPw1jBGyHaKhbdu2f/7znydOnIjIHT58+J577nnkkUcmT548derUHj16INo8Hs+iRYteffXVtWvXoq46d+78v//7v4iIVqJX3Ar9BCIkbDcKx8OoG72S/CtgjEiYBMYYY42MBPuX8LcwRIG8EFEyYcKETz/9dNasWagTl8v1Qq327dtff/31I0eO7NOnj8ViQT0UFxevWrVq8eLFn3zyic/nQz0kJCTMnz/fbrfDOO2oXjEJ2lFESNhuEMn/DQjUCfkWggIwQnEI69VgjDHWyEiwfwkXwwg1B8KG6HnllVeOHj36ySefoB6+/vrrp2pZrdY+ffr07t27a9eu3bt3b926dUZGBs7M7/cfPXp07969u3btKiwsXLduXVFREaLBZDK9//77PXr0gHFaqV4xCdoRREjYxojkPwAK6kgj7wIYI2w3QNjAGGOskZFg/6KXwgAhL0RUmc3m999/f+jQoV988QXqze/3r6mF75nN5qysrPT0dJPJlJiYCCAcDldXVwcCgWPHjpWXlyMGhBCzZs0aMWIEjNPL9MpboR1GhIR1pEh+AlBQVxRYBe0IDBHCNg6MMcYaHwn2PdKOwgg1D9GWmJj40UcfjR49et26dYi2YDBYXAsNRUo5c+bMCRMmwDi9XK+YjPABREhYrxQpzwEq6sMzF8YIy2WQbcAYY+dJmEL7q/eW+A4PzxwF9u8k2L9ox2CEmo0YcDqdn3766eTJkxcuXIh4lpCQsGDBglGjRsE4vUKvmILwN4iQsA4XKc8DKupDK6LgehhknwjGGGtwXs3zVdWuQve2ne6tPs2rCGVA2mUJMhHsNBLsFN0N8sIINRuxYbFY3n333VatWj333HNEhDjUpk2b999/v6CgAMbpVXrlVIT3I0LCMkgkPw9I1A953gEIRqithOUSMMZYQ6kIlu2p2lno3ra3qjBMYXxPJ31vdWHv1P6IErvd/stf/lJRFADTpk3TdV0IgXgjwU7RT8AYoWQhZlRVfeaZZ6688spJkyaVlpYirowZM+aNN95ITU2FcVStV96K0G5ESFguESkvQZhRT+Ql3yIYI+wTAAWMMRZjx/xHCt3bCt3bDtR8TSD8mF3u7b1T+yMaiEjXdNIJEoqi0D9opJOuSlUoAvFDgp2iu2GQmokYGzZs2JYtW+66665ly5YhHqSkpDz99NN33HEHIkI1esVPENqFCAnzAJHyZwgL6o18i0HVMEJYhW0sGGMsNsIU3l+9Z6d7607XVleoAueyp2qnTroiFNSbrumFKwsPbDnQZ2yflp1ahvyhdfPXBbyBvmP7pmanIn5IsFqkV8IgxYnYy8nJWbp06YcffnjfffcdOnQIjcBzv09/7Jny6hodpxFCTJ48+emnn87IyEBEyKdX3oXQTkTKXCBS/wxhRTSQ910YI2yjoSSDMcaiSif9oOfrra4vNldsqAlXwbCacHWR99u2Ce1Rb6pU2/ZuW3a4bM/qPalZqYd2HHIfd3cb2i01OxVxRYKdQi4YIiHsaCjXXnvt8OHDZ8yY8fzzz1dUVOC8umqo/ZK+1hE3l1S6ddQaMmTIH/7whwEDBiBS5NMr70RwMyJl6qWkvgFhRzRQcCPC+2GMsN0CxhiLEgIdqNm/1fXFlsqNVSE36mSXe3vbhPaIBkcLR7s+7XZ8smPTXzZ5Kj2ZF2S27t4a8UaCnaK7YISSCgg0ILvd/uijj957770vvPDC888/X1FRgfPEkah0vND8ycLcq8aV9My/bPr06YMGDUIdkJ8q70JwEyJlukhxvgFhR7R458Egcy+YuoIxxurtmP/IpvJ1myrWukOVqJ9d7u2jc25ElOR1ySv9unTtvLXterdr37+9yWpCvJFgp+hVMEJJwfngcDgeffTRadOmLVmyZObMmStXrkSDS3aoAAp6WA7tHJqQMx9KKuqAQuT6OQU3IlKmLkrqaxAJiBb9JPn/BmOEfRIYY6wejvmPbK384ouKdScDxxElJb5iV6gixeRENBCRxW6xJdkSWyQmpCQgDkmwU8gHI0QSzh+LxXJjrR07dsybN++DDz745ptvEHsWi2XEiOF22z7UssmDesUExTkbSjoiQiFy/YwCnyNSspOSOhtKMqKHvAuBMIxQ0oXlCjDGWOSO+Y9srfxic8X6E4FSRBuBdrt3DGwxBPVGOpV+U1qytySjTUZNRc2BLQc6XdJJNamIKxLsFPLBACGsaAR61nrqqad27tz54Ycfrl69euPGjV6vF1F1wQUXDBo06Morrxw1apQjkfQTF+Nfwt/oFZMU5xwoGTAqTK77KLAKkZIdFOdsKMmIJo1878EYYR8HYQJjjBlWFjjxRcW6LZUbj/lLEBtZ1pweyQVtE9sjGjwuz7ebvzXbzAPGDfhq3VdFO4rS26Snt0kXQiB+SLDvBGCEsKEx6VHrt7/9bSgU2rx584YNG3bv3l1YWLh3716Px4MItWrVqmvXrt27d+/Zs+egQYNyc3PxL1oJ/kP4gF4xSUmdAzUT56aRaxoFViJS8gLFOQtKKqKKAqugHYUhqrDdBMYYM8Cv+Xa4t2wqX7uvejeBEG0CIs/epntyfq/UvtnWloiScDB8cNtB13FXj+E9nC2dHfp3+OIvX3z7xbeOFg5rkhXxQ4KdQj4YIaxolEwm04BaqKXr+rFjx44cOVJaWnr48GGXy1VTUxMMBj0eDwBFUZKTk1VVTUlJyczMzKmVl5eXlJSEM6Fq/FD4oF5xi+J8G2pLnI1GrgfJvxyRUtsozrehpCPqvPNhjLBeATUTjDF2ZgQ6ULN/U8W6LyrWBfUAos2kmC9M6NA9Ob9Xat9kUwoiR6DDnpN7qoqHZl5kUiT+nb/GH/AE8rrm5XXLA9Air0X7fu1PFp2srqi2JlkRPyTYKRSAEcKKeKAoSstaiBa9Bj9KO6JXTFCcb0PNw4/Tyf0b8i9FpNTWivNtKBmIOu0wBdbCIPt4MMbYGRzzH9lQ/vfNFevdoUpEm8OU3D05v0dyr05J3UyKGRHyhP3f1hwrdBcVug7udhe7Q55WCRkjsnvjBxKdib1H98Zp2vdt375ve8QbCXYKaTBCSDRLRDU4E+2oXjFJcc6G2hr/iajqMfItRqTUHMX5FtRMxAB55wE6jJBthbkPGGPs3wV0/5bKTevLVh/wfI1oS7dk5qf06ZHS64KEdgIChmmkF3tP7qs6sstdtNN18JDnBIFwmn5pndCkSbDICDRPVI2z0I7q5eMV52zIdvj/iKp+T975iJSarTjfhtoSsUBB8i2CMcI+HhBgjLHvFXsPbqpYu6l8rVfzIKpSzWkXpfTuldKnbWIHAQFjygJV+6qP7HIV7XQd3F9dEtBDOLO+aR3RpEmw7xDYWeg1ODv9pF4xWXHOhmyPfyKq+m/yvotIqZmK822oeYgN8n8EvRxGCKuwXgvGGAN8mndL5ca/l3122FuEqEqUSRelXNzXObBtYgcBgXPxaYGvq4/urz5S6Cra7jpYGayGMRbF1CPlAjRpEiwyAs0TVeOc9DK9YrLinA3ZgaqfI+87iJSSpqS+BbUVYoa882CMsF4NJRmMsebtoOebNSdXbnVtCukhRE+idOSnXNzb2a9dYicBgTPTST/oOb7HXbyn6tAed/Eh7wmdCJHLT73QopjQpEmw7xDYWZAHRujlesUEYRlGvg8QKcWpOOdAXojYCe9DaCuMEfbxYIw1V2EK7XRt/ezExwc8XyN6bKq9R3KvXql9ujh6qkLFGZQHqvZUFe+pKt7jLv6q6ohPC6De+qZ1QlMnwZgReg0M0t3k+wCRUpKV1Dcg2yOWyPsuDDJ1gakbGGPNz8nA8XVlq9eVr/KEaxAlJsXcKalrX+clPVIKpJA4q+N+112bX6gIViOq+qZ1RFMnwSIj0DxRNWJHcSips2DqipgiL/mWwhhhnwjGWHOik76ravuakyv3VhUSCNGgCLWro0df5yXdk/NNihnGZFpTZuTfce/WV6pCXkRJts2Za2+Bpk6CfYfAzoJqEDkCBM5FJCmps2Dqhhgj32JQDYxQHMI6Coyx5sGv+daXr1514q/lwZOIklxb635pl/ROHeAwJSNybROz/9jztvu3vebTAoiGfmmd0AxIsMgINE96DSIncC7CpqS+ClN3xB75FsIYYR0DYQNjrKkrD578+8nP1pZ95tU8iIYEmZif0ufSFpfn2dugfromt36y560Pbn8jqIdRb/3SOqEZkGDMAKIaRJ2wK6lvwFyABhDcitAeGCPsN4Ex1qQd8Hz96fGPdri/1ElHvalC7Z7ca0DaZV0c3RWhIkp6pbZ7rNvE3xbO0UhHPZgUmZ96IZoBCfYdAUM0NE96DaJL2ETqKzAXoEGQ710YI8z9INuDMdYUEWiXe9tfjy/7tmY/oiHDknWxc8CAtMtSzWmIgUvSu/6my81P7JmvE6Gueqa0tapmNAMS7BRhghEURvNE1YgiYRYpLwpzPzQMvZL8n8Ag+y1gjDU5QT24vnz1yuMrKoJlqDeTYspP6TMgbXD7pE4CArF0RVYvT9j//L5FqKu+aR3RPEiw70gYEkbzRDWIFmESKS8KyyA0FPJ9AArACCVdWIeDMdaEeDXPmpMrPzvxSU24CvWWY8u7pMWQPs6BdjUBDWVM7oCasO+1bz9GnfRN64jmQYKdIiSMoBCaIQqBAogORaS8ICxD0HCIfAthjLDfCEgwxpqE6nDVmpMrPzvxsU/zon6kkD1SCi5pMaRjUlcBgQY3qc3QTWVf7XQXIUIZ1pQ2CZloHiTYd0wwJIRmiGoQRXo1GhAFNyFcBENUYbsJjLH4Vx48+dmJj9eWrQrpQdRPsimlr/PSwRnDU0xOnCcEenH/0p3uIkSuX1onNBsS7BRhghEURjNENYgandy/ASBs16FheOfDGGEZDDUHjLF4dsx/5KNjH251bdJJRz0IiI5JXQelD+2R3EsRKs4fnfQ/7n3vo2Nfok76pnVEsyHBviNhSBjNkF6NaNLI/WsgLGw3INb0SgqshEH2W8AYi1ul/qMrji3aUrmRQKgHi2LtnzbosvThmdZsnG8hPfz73e+uOVGIOpFC7ZXaDs2GBDtFSBhBITQ/RNWIMp3cj4D8wj4RsUS+D0BBGKHmCsslYIzFofLgyU9Kl64vX62TjnpINqVc0uLywelXJMhENAI+LfCbHW9trfwGddU9pU2CtKLZkGDfMcEAQkig+aEaRB9R1X8DmrBPQawQ+RbCGGG/CVDAGIsr5cGTn5QuXV/+uU4a6iHP3ubyjBG9U/urQkXjUB32Pbj9jd3uQ6iHPmkd0ZxIsFOEhBEURjOk1yAmiKr+B+QTCf+FGKDgRoSLYIgqbGPBGIsfFcGyj0uXrC//XCcNdSUguiVfNCTjyk5J3dCYVASrf7Xt9W9qjqJ++qZ1RHMiwb5jgiFhNENUg5ih6hmAEAl3Ieq8C2CMsA6FkgHGWDxwh1wrjv1lffnnGmmoK7NiGdhi8OUZI9LM6WhkSv2V92+becRbhrNShPLTC0ctPbqx2HsSPybN4rgwMRvNiQQ7RUgYQWE0Q1SDWKLq56BXi6RfIYr0SgqshEG2m8EYa/SCemD1yb9+XLrEr/lQV1bV1j9t0JWZox2mZDQ+xZ4T929/7YTfhbNShfJQ55tGZBcMyexxz5aXjvtd+IF+aR0FBJoTCfYdFYZoaIb0GsQYeWZCSJH4C0QJ+d4HBWGEmissA8EYa8Q00jaUf77s2AdVITfqymFKvrTF0MszRthUOxql/dUlv9r+mivowVmZFPlYtwmXpncDkGFNmZF/58+2vFwZrMa/65PWCc2MBPuOCkPCaIaoBrFHNX8GhUTSNEQBke89GCPsNwEKGGONEoG2VX7x4dGFJwPHUVctLBlD0q+8pMXlJsWExmqn6+BDO970hP04K5tqeaLHlAJne3wvz57+XP7t9215pTrsw/cUoRSktkMzI8FOESqMoDCaIapBgyDPayCPcEwHBOqBghsRLoIhqrCNBWOsUdpfvWdRyfxD3gOoq1xb6xFZo/NT+wgINGJbK7/5zY63fFoAZ5UkbU9fNLVrcmv8u3aJOU9fNPWX22b6tSBqdUtu7TDZ0cxIsO9IGKKhGdKr0VDI+y6gC8djgII68y6AMcI6DEoGGGONzMnA8fePzC10b0VdtbS1GpU9tmdKgYBA47b25O7Hdr0T1MM4K6c5aUb+HW0Ts/Fjuia3fqLHlId2zArpYQB90jqi+ZFg31FhBIXR/BDVoAGRdz5AwvF7QEEd6JUUWAmDbDeDMdaYBPXg344v++vxpSE9hDrJtra8IuuaPs6BAgKN3l9Ltz65Z4FGOs4qy5r6fK87W9pa4Mx6OztM7zZheuHbGul90zqi+ZFgpwgJQzQ0Q1SDhiOhpFJwG3yLhW0sIke+90FBGKHmCssAMMYajUL31gWH51QEy1AnWdacK7NGX5w6QBEK4sGiI+v/b/9inQhn1TohY0b+nemWZJzLoPRuD3W+8eVvlrdPbInmR4J9R4UhYTRDejWiQlggHFAzhZIOJRnCASUZigNKhlAyoDigJENpASioOyLvezBG2G8GFDDGGoEjvkMLD8/5pmYf6iTNnH5l1jUD0gYrQkGcmHto1avfrMC5dEzKfTb/9mRTAowZkd27bWK2IgSaHwl2ipAwgjQ0Q1SDsxMWCAeUZCgOoWRCSYeSDMUBkQzFIZQMqBlQnIBEjFFwI7QiGKIK2xgwxs43T7hmydH31pWv0klH5JzmtKuzb+jjHKgIBXGCQH/+evmC4s9xLj1T2j7V8ycJ0opIdEhqiWZJgn1HhSFhxKfly5cnJydfdNFFiYmJAA4dOrRx48aBAwfm5ubinNSWQnaE4oSSCiUVSiqUVCipQkmDSIGSCmFBI+FdAGOEdRiUDDDGzh8CrS1bteToQk+4BpGzqwlXZo0enH6FSTEhfuikP/vVX5Yd3YRz6d+i8+PdJ1kUE5gxEuw7CgzREZ8WLVrUpk2bCy+8MDExEcCBAwdmz56dl5eXm5uLc1HS/oK4oFdSYCUMst0Mxtj5czJw/N3iN/ZV70HkpJD90gaNzrkhUToQV0K69ofd7646sRPnMjTzoke6jpNCBTNMgn0nDEMkWGNFvvdAQRih5grLADDGzgeNtE9PrFh29IMwhREhAZGf2mdMy3Fp5nTEG78W+m3h7E3l+3Auo1v2u7/jWEUIsEhIsFNIgxFCgjVSRN73YYyw3wwoYIw1uG9r9r9b/MYxfwki1ymp29jcW3JtrRGHPGH/Qzve3Ok6iHO5Pm/gvR2uFRBgEZJg3wnDEBVxa/Xq1aWlpQkJCQCKi4tLS0vRhFBwA7QiGKIK2xgwxhqWT/MuKpm/rmwVgRChLGvOjbmTOzu6IT5VhbzTtr++t+owzmVC6yF3tRsJVicS7DsaDJGIW4mJiZmZmQ6HA4DH45FSoinxLoAxwjoMSgYYYw2o0L11XvFbrlAFImRRrMMyR16ZNVoKifhUHqi6f/trB2tKcVYC4mcdrrkx71KwupJgp5AGI4RE3OrZs+eECRMyMzMBrFmz5ptvvkGToVdS4FMYZLsZjLGG4tO8Cw7P/qJiHSIkIPo4B45peYvDlIy4dcxXcf+2mSW+cpyVIpRpnW4YlXMxWD1IsO+EYYiKuGUymWw2W0JCAgCr1aooCpoK8r0PCsIINU9YBoAx1iD2VhW+fWimK1SJCLWyX3BT3uS2Ce0Rz4o8xx/Y9trJgBtnZVLU33WdcFlGd7D6kWDf0WCEkGCNDpH3PRgj7DcBChhjMRbSg4uPLlh94q8EQiQSZOLIrDGDM64QEIhnX1Udmbb9dXfIg7Oyqub/6THlYmcHsHqTYKdQCIZIxKef//zndrs9NTUVtbp37z59+vT27dsj/lFwE7QiGKIK2xgwxmLsgOfr2UWvnAwcRyQExKD0Ydfm3GRVbYhz2ysP/GbnLE/Yj7NKlLanL7qtW3IbsGiQaEAnTpwoLS09ceKEz+fz1wJgrWWz2TJrZWRk4PzQYYiK+NSzZ0+cpkUtNA3e92CMsA6HkgHGWMzopK08sWLp0fc10hCJHFvu+FZT2ya0R/xbX7Z3euHbAT2Es0o1Jz170e3tk3LAokQiZr799ttNmzYVFhburnXkyJFgMIjTWCwWAIFAAKcxm825ubndunXr2rVrt27d+vXr17ZtWzQACsMIIRHPPvnkk2PHjl1xxRU5OTloGvQqCvwNBtlvBmMsZo75j7xV9MphbxEiYVJMV2VdNzzzalWoiH8rj297YveCMGk4q0xryoz8O/Ps6WDRIxFV5eXlS5cuXbly5erVq0tKSsxmc8eOHbt27Tp16tRWrVrl5uZmZWVlZmba7XaLxYLvBQIBj8dz/Pjx0tLSkpKSQ4cOFRYWLlu27Nlnnw2FQrm5uYMHDx42bNg111zjdDoRI+SHISbEs+PHjxcVFfn9fjQV5F8M8sMINU+Y+4MxFhubKtbOK54V1AOIRLvEjuNbTc2y5qBJ+LBkw/P7FulEOKtW9vTn8u/MtKaARZVENFRVVc2bN2/hwoVr1qyRUl566aU//elPL7vssj59+pjNZpyLpZbT6ezcuTNOEwgEvvjii88//3zNmjV33XXX7bffPnjw4JtuumncuHFJSUmILqqGAUJJBGtMyPs+jBH2GwEFjLFoC+mhhUfmrCtbhUjYVPvV2dcPzrhCQKBJmHto1cxvPiIQzuqChMzn8u9sYXGARZtE/RQWFr700ktz587VNO2aa6555513Ro4cmZSUhGiwWCyX1gJQXV29YsWKv/zlL/fdd98DDzwwYcKEu+++u3v37ogWqoERIhGs8QjtQPir/8cefIBHVSV+A/6dO3dqMsnMJJPeqIHQg3RBCYo0KaFLJ4C66O7+Laxlrbt2ENcCi3RRFCQB1IBiQRBERUBp0glJSM+UZCZT7z2fD/u4n9nI5A6kzXDeF5LIiDoTDMM0tBJn0aqLrxc5CuGPnvo+ExNmhsnDESzWXti19uLnqE+HsMTF3eeFyTVgGgGPa3Xs2LFXXnnlvffea9u27d///vd58+ZFRESg0Wi12slXWK3WTZs2vfnmmytWrBg5cuTTTz/ds2dPXD+xGlKQUDAtBq3ZDGmI8lZwUWAYpkH9YNr/fv5al+iEZGqZZlz8lJsjMxAsKOgbZz7eUvAN6tND3+aFbnM0MiWYxsHDf5cvX37wwQc3b96cnp6+bdu2UaNGEULQVMLDwxcsWDB//vyPPvromWee6dWr19SpUxcvXhwbG4vrQKkNUnBaMC0EraHOHZBIMxEMwzQcL/VsvfzB7rLP4I8O2s4zkufrFREIFiIVX/rlw53FP6I+AyLTnukyQ8HxYBoND3+Iovj6668/+eSTRqNx69ato0ePJoSgORBCxowZM3r06G3btj344IMdOnR49tln77//fo7jcG3EKkhBQsG0DNTxCagdUnBGorwFDMM0EJO7YtXFN/Ls5yGZnJOPjM28PXoUAUGw8IjeZ05s3Ft2DPW5PSb9sbTJMsKBaUw8JCsqKpoxY8b+/fsXLVr06KOPqtVqNDdCyLhx44YNG/b8888vWrTo448/3rBhQ2xsLK6BWAkpiBZMy0AdmyEN0UwEZGAYpiGcqPp5zcW3HEINJEvWtJ6Vck+MKg5BxCm4Hzu6/kfTGdRnXEL/v7QfyxECppHxkObLL7+cOnWqXq//9ttv09PT0ZKo1ep//OMfY8eOnTp1ardu3TZt2jR48GD4hTpAbZBCZgTTEnjPwHMUkhCizgTDMA1hX8VXHxSsF6kAaTgiuy1qxKi48TzhEUSqvY5FP60+Yb2E+kxLHnx32xFgmgQPCTZu3DhnzpzMzMyVK1eGhoaiRerZs+ehQ4fmzZs3fPjwdevWTZkyBdKJlZCIiwDTAtCaTZCGKPpDlgSGYa6PQIXNBeu/qfgKkhkUkfNa3Z8S0gbBxeSufujIqnO2IvhEQO5tN3JK0i1gmgqP+ixbtuy+++576KGHXnrpJUIIWjCtVvv+++8//PDD06ZNs1gs99xzDyQSKyAN4SLBNDvqos6PIJFmIhiGuT41gn3lhddPV5+AZF3Ce8xMvjuED0VwKXGaHzjydmFNBXziCPdgauad8X3ANCEePr3//vv333//888//8gjjyAQcBy3ZMkSg8GwcOFCg8EwadIkSEDFCkjERSCQzZw5E4GPOj+FaIUUnI4obwPDMNeh3FW6/PySEmcRpOGIbHjMmBGx4wgIgku+veyBn1aWOS3wiSeyJzpNHRzdDUzT4nF1e/funT179gMPPPDII48goDz++OMVFRUzZ86Mj48fMGAA6uUthCQycOEIQJRSwSMQQjieI4RQSgWPQAjheI4QgkBDHR9CGqLOBFGAYZhrdd52esWFf9m8VZBGJ9dntbqvTWgqgs6Z6ssP/bTS4rbDJznHP9152kBjZzBNjsdVmEym6dOnjxw58uWXX0YAWrJkyYULF+66666ffvpJr9fDN+EypJBFAxwCkNftzX0tN8wY1vPOnmGRYc5q5ydLP4nvEN/tjm4huhAEFiEf7oOQhqgngGGYa7W/YvcHBesEKkCajmFd5qTcG8qHIegctVz8289r7F4nfFLLlM93ndXT0A5Mc+BxFffeey+ldNWqVYQQBCCO41avXt29e/c//elP77//PnwTCiCFLBGBSa6U953Q94sVX0SnRLfp0+bQJ4fkKnnbPm1DdCEINLRmE0AhhaIn+LZgGOaa7Cr9eNvlTZCGgNwePWp03ESOcAg6h83nHv15nUNwwSctr365e1an8GQwzYTHH9m7d+/mzZt37txpMBgQsCIjI99+++2RI0cuXLjw5ptvxtVRoQASEFkiAlZMm5jUAamn9p+yWWx5R/L6ZPaJiI9A4BGoYxukIepJYBjGfxT0w4INX5fvgjRqmWZeq/s7hnVBMNpXfuLp4++6RS98Mii0r/aY3zo0Fkzz4W5ppPEAACAASURBVFEHpfShhx664447hg0bhgA3YsSIIUOGPPzwwwcOHIAPwmVIIUtAIOs2tNulny7tfWdv73G9YzvEyuQyBBrq/AJiOaQgWqIaBoZh/CRS4b381Qcq90IaozL63jYPxqjiEIx2lRx+4eQmgYrwKUalX5q+IF4dCaZZ8ahj3759Bw8e/PHHHxEUnnvuub59+3777bf9+/fHHxJKQGsghSwBAU6j18hVckO8QaFWIBA5PoQ0RH0niBoMw/jDLbpXXvjXiaqfIU17bcf5rf4SwociGG0t/PZfZ7aJlMKn5JCoV3ssMCrDwTQ3HnWsWbOm5xUICn369OnevfuaNWv69++PP0K9pyEN4ZMQsERBPL3/tM1ka9Wj1dnvz+rj9XHt4zgZhwAilFDXfkhD1BPBMIw/HELNsvNLzttOQ5r+EbdOSZrNEx7B6L1Lu1ec24H6pGoTFveYFy4PAdMC8KjN6/VmZ2c/99xzCCKzZ89+6qmnVqxYIZPJUJf3DCSSpSBgVRZWntxzssPNHVqlt9q9dve5H86FRYZpI7WEEAQI6vgQECAF3wHyTmAYRrJqb9W/zr5Q5CiABBzhMuOnZkQNRzCioMvO5m7K34P6dNO1frHbnBBeBaZl4FHbzz//XF1dPWTIEASRjIyMv/71r8eOHevevTvq8p6GFFwUOB0Ck9PmPJx72JBgSO6WHGYM6zmq5/739xeeKGzXt51cJUdgEKkjG9IQzRQwDCOZzVv1r7MvFDkKIIGSU81p9aeu4ekIRiIVXzmVnVv0A+rTL7Ljs11mKDk5mBaDR23fffedXq/v0KEDgkinTp3Cw8MPHDjQvXt31EE9pyEBkaciYFWVVxGOpN2SFmYMA5CQltC2T1ub2ea0OeUqOQIBdX0DoQhSEBVRjQLDMNLYvFWvnX2+yFEICfSKiIVtHo5TJyAYeUThnyc27i47ivoMie7+eKcpPJGBaUl41Jafn9+mTRuO4xBEOI5r3bp1fn4+6qIeCBchBd8eASuqVdTQe4bid3qO6onA4vgQ0hDVcHBhYBhGApu36rWzLxQ5CiFBjCruvrZ/MygiEIycgueJY+u/rzyN+oyO7/tAaiZHCJgWhkdtlZWVERERCDqRkZGVlZWoy3sC1A0p+FQwzUWspM6vIA1RTwbDMBLUCPY3z71S5CiABEmaVve1fTiUD0Mwsnudf/t5zVHLRdRnfOKAP7cfQ0DAtDw8anM4HCqVCkFHo9HU1NSgDuo+AmkI3x7M1VAHiBqNhjq2AV5IwbeGogcYhqlPjWB//eyL+TUXIUF7bcd7Wj+gkqkRjKo8NQ//tOqXqgLUZ1ry4LvbjgDTUvGozWAwFBQUIOhUVlYmJyejLs9PkIIowLcF80eoYxutXswZNoBvhcZBHdmQhqgnAwQMw/jkEGpeO/N8oeMSJOiuu2luq4U8kSMYVbqqHvhp5UVbCXwiIPe1v3Ni4kAwLRiP2iIjI8vLyxF0ysrKIiIiUAf1HIYU8s4gCjB10JoNtOqfABXNsznDRsji0eA8R+A9BymInKjHgGEYn9yie9n5xYWOS5Cgf8QtdyVlcYRDMCp2mB448vZlRyV84gi3qOOEEbG9wLRsPGrr3Lnz2bNnq6qqwsLCECyqqqrOnz/ftWtX/A/hMoRSSEDk6WDqoPa3afVi/IdQLJrmcBHvgTOiQdGaLZCGKG8HZwDDMFcnUGHVxdfP285AggGRt96VlEVAEIzy7KUPHllZ7rLCJzkne7LTtFuiuoBp8XjU1r9/f0EQfvjhh9tuuw3B4rvvvhMEoV+/fqiNun+ARPLuYGqhtPpFal+L3xPyRNMczvAeuHA0FOqgzp2QSD0BDMNcHQV9L3/1cetPkKB/xK13JWUREASjU1WFD/+0yuqxwyeVTPFc11m9DO3BBAIetcXGxnbq1Gnr1q233XYbgkVOTk6XLl2io6PxP1x7IQ1R9ADz/wnU+gR1bEFd3jOiOYszrAcJQUOgzh2gNkghiyHKfmAY5uqyCzd+V7kXEvSPuHVachYBQTD6yXzh0aNr7V4nfArl1S93n9s5PAVMgOBRx6xZs5577rlXXnlFo9Eg8Dkcjk2bNj355JP4XyJ1H4AUsiRwRjD/QT3U+iB1foqr8RwVTVmcYS2IGteNOrZAGqKeCMjAMMxV5BbnfFW2ExL0j7hlWnIWAUEw+rbil6eObXCJHvikV2gXd5/XThsHJnDwqGPmzJlPPPHE2rVrFy5ciMC3cuVKp9M5ffp0/A/PcYgmSEAU6WD+gzqo5T7q+ga+eQ5T85+IfgWIAtfDmwf3YUhCiHoMGIa5ir3lX+QW50CCAZG33pWURUAQjL4oPfL8iU1eKsCnaJXu1R4LEjVGMAGFRx3R0dELFy585plnZsyYERYWhkBWXV393HPP/fnPfzYajaiNuvZAIuVAML8Sq0TLArgPQwLq3g/rX4nuDUCGa0UdWwAKCYiiH2RJYBjmjxy3/rS58B1I0C9i0F1JWQQEwWj75QNLT28VKYVPSRrjqz0WRKl0YAINjz/y+OOPr1279qmnnlq6dCkC2d///nev1/vII4+gDuraB0k4orgZjGgWzXPgOQnJqPMLWB8l4S8CHK6FQB3bIJFmAhiG+SNFjsK1ectEKqI+XcPTpyVlERAEo/cu7X773E4KCp9ahUQv6bEgUhkGJgDx+CMGg+G1116bPXv2kCFDRo0ahcD06aefvvHGG++8845er8f/EIrh+RlSyDuD04MhoYSLpPAPdWwDeBL+HEDgJ+raA7EMUhAtUd4GhmHqsHosb51/xSHUoD7ttWlZre7niAzBaO2FXWsvfo76dAhLXNx9XphcAyYw8biKmTNn7tq1Kysr68CBA61bt0agOXfu3MyZM2fMmDF9+nTUQZ07ARESEOUgML8icqJ7g5qz4P4R/qCOLeBCifYx+MuxBdIQ9WgQFRiGqc0tuldcWGp2V6I+Ceqku1v/Vc7JEXQo6BtnPt5S8A3q00Pf5oVuczQyJZiAxePqli9fPnjw4DvuuGPfvn3R0dEIHMXFxXfccUdKSsqyZcvwR6gzF9IQ5c1g/oOoOf0K0TQLnuPwB7WvAwknoQshnVhBnV9DGqKeAIZhaqOgay6+lWc/j/oYldH3tf2bWqZB0BGp+NIvH+4s/hH1GRCZ9kyXGQqOBxPIeFydVqvdsWPHzTffPHTo0J07d8bFxSEQXL58ediwYTzP5+bmhoSEoC6hAJ7jkIILh7wbmP8iWk6/WjRNg/cc/EFt/wJRkpB5kIY6tgFeSMGnQt4JDMPUtqXw3aPWQ6iPTq7/c7tHwuThCEZPHtuwt/w46jMs9qZHOk7kCAcmwPHwKSoq6osvvhg2bFj//v137tzZsWNHtGwnTpwYPny4Vqv94osvjEYj/gh17gAoJCDKoYAMzO9xes6wTqycCqEA/qDVr4CEEs0USEAdOZCGaCaBYZja9lV8tbvsM9RHIwu5v90jEQojgtSgqC77Kk6IlOLqxiX0/0v7sRwhYAIfj/okJSXt379/zJgxffv2Xb58+V133YWWKjs7e/78+ampqR9//HFkZCSugjo+hkSq4WDq4qI4wwbRdBeEIviB0qqnwYUQ1Z3wzXMY3nOQgsiJahQYhvmdC/azmwveQX1kRDa/9Z9jVfEIXkNj0u1e59LTW3EV05IH3912BJhgwUMCvV6/a9euhx56aNq0aV9//fWSJUu0Wi1akurq6gceeGD16tULFy5cvHixUqnE1XgOw3sGUnAGouwH5g/J4jjDOrFyGsRy+EGklkXQ8UQ1HFdHa7IhDVEOBacHwzC/sXosqy687qVe1GdS4qxUbScEu3EJ/as9NasufIbaCMi97UZOSboFTBDhIY1KpXrzzTeHDBkyf/78HTt2vPrqq5MmTULL8MEHHzz44IMulysnJ2fs2LHwidZ8AGmIajggA3M1shTOsFo0zYBohR8Ean0YXBhRDMAfog7q3AGJNBPAMMxvvNSz4sJSi8eM+gyLGTMwMgM3hpmtbqsRXBsvfY3fcIR7MDXzzvg+YIILD3+MGzdu4MCBjzzyyJQpU5YvX/7ss88OHDgQzWfPnj1PPvnkvn375s6d++KLL0ZERMA3sYo6P4M0RDUCjG98B06/SjTNBrVDOuqm5j9Bv4Io+qIO6twBaocUshii6AuGYX6zqWB9nv086pOu73Nn3ATcSO5uO8LmdX50+TsAPJE90Wnq4OhuYIIODz9FRkauWrVq3rx5jz322KBBgzIyMhYtWnT77bdzHIemIoriZ5999tJLL+3ZsycjI+PAgQO9e/eGBNSRA+qAFJwRip5g6iXvxulXi+Y5oA5IRx3UfDfRr4KiF2qjji2QhqgnAjIwDHPF1+W79ld8jfoka1rPTL6bgOBGQkAeSM2s8br2lB97uvO0gcbOYIIRj2vSt2/fr776au/evf/4xz+GDx/eqlWr+fPnT58+PSEhAY2psLBww4YNK1euzMvLGzJkyN69ewcOHAjJqONDSEPUmQAHRgpFOtG9RS33gLohHXWI5rs5wzrIu+K/vHlwH4YkhKjHgmGYK87ZTmUXvof6RCiMC9s+pOAUuPFwhDzWafJU263ttHFgghSP6zBo0KDPP//81KlTK1asePnllx977LE+ffpkZmaOGjWqY8eOaCCU0l9++SU3NzcnJ+f777/X6/WzZs1asGBBhw4d4A/q2gfvWUjCEc0kMJIR5c0IX0otfwYESEdtomkOZ1gPeWdcQR1bAAoJiKIfZIlgGAao9latvviWQAX4JOcUC1r/JZQPQ5PJz8ehQ+jZE0lJ+FV1NY4ehd2OoUPxq+pqHDuG48dht0OnQ5cu6NoVCgUaDU9k7bRxYIIXj+vWoUOHpUuXvvDCC1988UVOTs5LL720aNGiqKiogQMHDhgwoMsV0dHR8EdJScnx48ePHj26f//+b775pry8PDIycvTo0U888cSQIUOUSiX8R+0rIA1RDoAsEYw/iOp2hL9ArY8AIqSj1aI5izNsAN8eEKhjGyTSTADDMAAFXZe3zOoxwycCMjN5QaImBU3p/HmsXw+9HklJ+FVVFb74AiUlGDoUVis+/xw7diAkBCoVzp7FwYMYMQLDh0MmA8NcEx4NRKVSjbrC6/UeOXJk7969e/bsefHFF8vKygBERka2atUqNjY2Pj4+OjpapVKp1WqVSgXA6XQ6HA6n01laWlpYWFhcXHzx4sXKykoAUVFRffv2feSRRwYOHNijRw+e53HNPEfh/h4SqaeA8R9RjwW106pn4BfRLJpmcoZ3qXAJYhmk4MKI8jYwDAPsKN76S9Vx1GdozJ099X3RQogiTp3C5s1ITcXcuTAakZeHjRuxYQPat0f79mCYa8KjofE83+uKBx98EEBZWdnx48dPnjx56dKlkpKSX375Ze/evY4rnE4nAJVKpb7CaDQmJCSkpqbOmjUrLS2tS5cuRqMRDYTalkMizkhUg8FcE6KZBuqh1c/DL6JJNM0kfHtIQ1SjQVRgmBvemeqTO0u2oT4dwzrfGTsBLYfDgWPHYDJhxgy0aoVfpaVh2DAsXYr9+9G+PRjmmvBoZFFRURlXoBl5z1PXbkhDNBMBHsy1IiGzQc3Uthx+ESuouwLSEPUEMMwNr8pjXZu3TKQifIpQGOem3McRDs2iuBjr1uHrr/Gr6mocP47WrWG3o6gIoaFo1Qr/wXGIiEBUFPLzwTDXiscNgNr/DYiQhCfqSWCuDwn9P1A3ta9GY+BTIU8Dw9zYRCquzVtm9Vjgk5JT3dvmwRA+FM2F46BUQq3Gr9xu8Dx+RQgIAaWgFP9FKSgFx4FhrhWPoOe9SB2fQBqiHgVZHJjrRrSLQKtpzWY0NKKZDIa54X1SnH26+gTqMz15Xpw6Ac3IaMTYsRg4EL8qKsL69TCZEBKCxETs3o0zZ9C5M34liigvR3ExBg0Cw1wrHsGOVr8MCJCEkJB5YBoGIWH/AEBrNqMBEQVRjQTD3NjO2U7vKv0Y9RlkvK2nvi+aF8dBrUZoKH4VEgKFAr9SqdClC6KjsWoV7rkHcXE4cwZbt0KrxYABAARBcLvdoiiGhISAYSTjEdw8P1HXV5CGqIaAbw+mwRAS9gyokzo+QgMhyqHg9GCYG5hDqFmXt1ykInyKVyeNj78LLRPHoX17zJyJ7dvx3HMgBKKIyEgsWICkJAAOh2Pv3r379u0bNWpU7969eZ4Hw0jAI6iJ1S8CFNKQkPlgGpiMhL8EKlBnLhqEZgIY5sb2fv5ak7sCPqlkqnmt7pdzCjSvtDQ88ABSU/Efej0yM+F04ldaLW65BQkJuHgRDgdCQ9G6Ndq2hUwGQKFQJCQkhIaGrl+/ft++fWPGjElNTQXD1IdH8KLOXXAfhjRE0RfyHmAanozoXoHZSV1f4jrJYomiDxjmBvZd5d4fzQdQnxnJd0erYtHsoqMRHY3/0mjQpQv+S6NBly7o0gV1KBSKtLS0yMjIw4cPHzhw4JVXXhkwYMCoUaOMRiMY5up4BC2B2l6FdKH3gGksPNG9DstC6voa14GoJwAyMMyNqsJVtrlwA+ozOOqOHrpeCHA8z8fFxUVERHTo0OHQoUPffffd999/P2LEiCFDhoSEhIBh/giPIEXta+C9AIkUNxFFfzCNh8iJ7k1Y/kRde3GNOKLOBMPcqAQqrMl7yyk44FOypvW4+KkIFkqlsk2bNnFxcWlpad9///3HH3/81VdfTZkypXfv3hzHgWFq4xGUhMvU9iYk47QPgWlsREF0b1DzAri/h/+Iog9k8WCYG9XOkq159vPwScmp5rT6E094BBFCiEaj6dSpU2JiYufOnffv3798+fJdu3ZNnTq1Xbt2YJjf4RGMqPXvoA5IQ1TDIE8H0wSImtO/LZqz4P4R/qImUBeIEgxz4ymoyfus5GPUZ1LizChlDIIRx3E6ne6mm25q06bN0aNHd+3a9fjjj99xxx2jRo3SXCGTycDc8HgEHerIoe79kEpGQh8A02SImtOvEE2z4TkGf1DPaVgWEt0yEAUY5kbipZ71l1YIVIBP3XW9+kUMQlDjed5oNA4cONBqte7ZsycvL+/dd98FMGLEiI4dO4K54fEIMsJlWv0CJCOaSeBTwDQlouX0a0XzbHiOwx/UtRfWB4juX4AMDHPD+Lgou8hRAJ90csO0pCzcGBQKRWhoaFxc3JQpUwoKCnJzc6urq8EwAI+gIoiWByFaIRHRkND7wDQ9LowLf1msGAlQ+IM6d8GyiOheBmRgmBvARfu5L8t2wCcCMivlnhA+FDcSpVIZExNjt9sBUErBMACPIEKrF8NzGJKRkCxwRjDNgbp2AxT+o86PYRGIbgkgA8MENY/oeffSSpGK8OmOmDtTtWlgmBsej2BBXXupfQ2k41NIyAIwzYQ6cnCtqHMHLCC6JYAMDBO8PiraXOy8DJ8SNSkjY8eDYRiAR3AQLlHrQwCFVIQL+yeIEkyzcB+G9zyuA3XugAVEtwSQgWGC0Xnbma/KPoVPPOFnJd8tIzIwDAPwCALUJpr/BNECyYhmEhS9wTQT6tiC60adO2AB0S0BZGCY4OKlno35qykofBoZOz5OnQiGYa7gEfAEar4f3rOQjjOS0IfANBdaQ5070RCocwcsILolgAwME0Q+Ldle7LwMnxI1KbdFjwDDML/hEeBo1T+oez/8QcKeBhcOpplQZy6oHQ2EOnfAAqJbAsjAMEGhyFGwq+QT+MQTfnbKPTIiA8Mwv+ERyKh9Ja3ZCH8QzRSiuh1M86E12WhQ1LkDFhDdEkAGhglwFHRj/hov9cKnMfGTY1UJYBjmd3gELOrYSqsXwy98e6J9DEwz8ubBcwQNjTp3wAKiWwLIwDCBbHfZpxfsZ+FTm9D2GVHDwDBMbTwCE3V+Qa2PARTSETWn+xeICkzzoY7NAEUjoM4dsCpI+AuADAwTmEzuio+LsuETT/hpSfMICBiGqY1HAKLub6n1r4AAf5CwZ8C3AdOcBOrYDomIBrQG/qCObaBuolsCyMAwAWhj/hqX6IRPI2IzY1RxYBimDh4BiJBwSjSgbkhG1BOJeiyYZkVduyGWQwounNOtEC13Q7TCH9S5AxYQ3RJABoYJKIfM35+sOgqf4tVJt0ePBMMwf4RHIJJ34gzvi6ZZEMsghaInCXsKTLOryYY0RDUainROv1Y0z4FohT+ocwcshOgWAzIwTIBwCs7swnfhE0e46cnzZUSGG55MJlMoFAA4jpPL5RzHgWEAHgGKb8MZNojmmRBK4ZssgdO9BaIA07zECuraA2mIegJ+Je/M6d8WTVmgNviDOnNhAdEtBmRgmEDwSfEWi8cMnzKihidrWoEBOnbsOG/evNDQ0JSUlMmTJycnJ4NhAB6Bi2/FGT4QTTMgFOJqSCin/zc4A5jmRh3bAS+kkHeGvCP+Q96DM6wWTVmgNviDOnNhAdEtBmRgmJatyFGwp/xz+BShMI6KzcQNj1IqeARdqK5f3368nFcoFLowndvpFjyCTC4Dc2PjEdBk8ZzhXdE0C8Il/AEZ0b0Kvj2YFoA6tkEaoh6P35P34AyrRVMWqA3+oM5cWEB0iwEZGKaloqAb89cIVMDVEZBpyVkKTokbHhXppZ8vHdx+MH1kers+7bwe7+n9p4/vPj5o+qC41DgwNzYegU4Wx0VsFE2z4D2HWggJf5YobwXTEniOwXsaUhAlUY3C/5D34AyrRVMWqA3+oM5cWEB0iwEZGKZF+rbi6wv2s/Cpl6F/B21nMAAn42JTY1ultzq662hUSlS1qfrcD+fa3NQmLjUOzA2PRxDgjJzhHdE0G94z+A3RLiLqiWBaBurIgTREeTu4cNQl78EZVoumLFAb/EGdubCA6BYDMjBMC2P32rYVbYJPapkmM/4uML/RhGlap7euyK/Y9/6+EF0IJ+O6DukKhgF4BAcukjO8J5rnwnMMAAm9l4RkgWkhqIc6cyGRZjyuRt6DM6wWTVmgNviDOnNhAdEtBmRgmJYktzjH7rXBpzFxk8Lk4WB+JyIhom2vtrmv5UYkRGTMy1CGKsEwAI+gwYVz+rWiOYvI00jo/4FpMajrc4gWSCGLIYq+8EHegzOsEk3zQG3wB3XmwgKiWwzIwDAtQ4mz6JuKL+FTkqbVzZEZCBwUFBSEEDQmSinHcyG6EGWoMiwyDAxzBY9gwoVxhnUgajAtiiMH0hB1JiCDb/J0zrBKNM0DtcEf1JkLC4huMSADw7QAWwrfFaiAqyMgUxJnc4RDi2Tz1hQ7KivdVZWuqmJnZbGjsthZWeN1run9CAFBo6EiNRWZzh88r4/Va3San3f93G9iP7lKDuaGxyPIkBAwLYpYRl37IQ1RjYEU8nTOsEo0ZYHa4Q/qzIVVScKfBzgwTLM6bv3pZNVR+DTIeFtKSBs0N4/orXBZi52VxY7KYmdlsaOy2FlZ5Ci3e52oY0LirRzh0JicNufFIxdrLDUZ8zJMl01HPj1y6dilNje1IYSAubHxYJjGRB1bAQFSKG4C3woSydM5w2rRlAVqhz+oIwcACX8e4MAwzUSgQs7ljfApTB4+Om4impBXFMpdlmJnZbGjstJtNbmrih2Vxc7KEoeJgkKajKieaExej7fwVGHB8YK0W9IikyJVWlVlQeWJr04Yk43hUeFgbmw8GKYxUcdWSEPUmfCLPJ3TrxLN80Dt8Ad15AAg4c8BMjBMc9hT/nmJswg+3Rk7US3ToHHYvDXFjspiZ2Wxo7LYWVnsqCx2VpY6zSIVcR0SNVHttAloTB6nx1ntjGkb065POwCh+tC2fdp63V5ToSk8KhzMjY0HwzQezxF4L0AKoiaq4fCXoidnWC2askDt8Ad15IC6iG4xIAPDNC2717azZBt8SlAn94sYhMbhEtwP/bTsvO0yGlpGdE80MrVW3WVIF/yOMdloTDaCYQAeDNNoqCMH0hDVMJAQXAN5OmdYLZqyQO3wB3XmwiIS3RKAB8M0oY+Lt9i9Nvg0MXE6Rzg0DqVM8UznuQsPvWr12NFwCEhGVDpaMJvbHapQgAlePBimkVAnde6EROpMXDN5OmdYLZqyQO3wB3XuhNlJdG+AKMAwTaLEWbSvYjd86qHr3S60IxpTtMrwdOe5D/+0zEsFNJCOYclx6ki0VFtPnnzpm2/WZGamGY1gghQPhmkc1LkLYhWkkMUTRS9cD3k6p18tmrNA7fAHde2GZSHRvQmiBMM0vi2F74pUwNXxhB8bPxmNr3N46wVtRi87txUNJCM6HS3V5+fO/W3XLkEUp23evGrcuJ5xcWCCEQ+GaSSOHEhD1JkAh+ukSOf0q0VzFqgd/qCuPbAsJLq3QJRgmMZ0zHr4ZNVR+DQkeoRRGY0mMS5h0EV78c7i73DdZIQbZOyOFml/fv6fc3MFUQRQ5XLN2rJl2ejRg1JSwAQdHgzTGIQS6v4ekhCiHosGoUjn9KtFcxaoHf6grr2w3Et0y0BUYJjGIVAh5/L78ClMHn5H9J1oQve1G3/RXnSqKh/Xp6c+Va/QouU5Ulx8z/btbkHAbxxe74Lt25cOHz68fXswwYVHk3M73P+e9++MrIzOGZ0BuGvcy+ctv/2e29MGpYEJFtSRDQiQgCj6QJaIhqJI5/SrRXMWqB3+oK591JzF6VeCaMAwjeDr8l2lzmL4NCZuskqmRhNScPyTnebcd+hVk7sa1yEjOh0tj0Dp3z77rMbjQW0eQfjLjh1Or3dcWhqYIMKjySnUilEPjsr5Z05yl+SQiJDPln0W1yEubVAamOBBqWMbJFJnomEp0jn9atGcBWqHX9wHRXMWp18FEgKGaVA1gn1n8Tb4lKhJ6RsxEE3OqNQ92WnOQz+/5RUFXBOVTNE/sgtaHhkhq8eNm5mdnW+xoDZBFB/+9FOzwzG3Z08wwYJHc2id3rrTrZ12vLGj621dL/x4Yd6yeWCCiftHCJcgBdEQ1VA0OEU6p39bNM8DdcAv7kOiOYvTbT+TdwAAIABJREFUrwIJBcM0nM9LP6kR7PBpYsJ0AoLm0Cm81cK2mf868yGuSf/IzmqZEi1SYnj4psmTZ2Vnn6moQG0UeG7PnoqamkUDB4IJCjyaSUZWxvKs5XlH8u586M4QQwiYIEIdOZCGqEaCaNAYFL04/VrRPA/UBr+4D4ummZx+LbhwMExDsHosu8t2waee+j5tQzug+bQKiVXJ5E7BA/8NieqJFiwqJOT9SZOytm79qbgYdaw4eNDh9T45eDABE/B4NBOvxxtmDDN5TBEJEWCCCXVQ56eQhqjHo/Eo0jnDO6J5DkQr/OI5Lppncfp14HRgmOu2s2SbW3Th6uScfGz8FDSf3KIDb57L9ooC/BcuD003pKJl06lUGyZMWLB9+4H8fNTxzpEj1S7XS0OHyjgOTCDj0Ry8Hu93W77ThGuSuyZ/tearsX8bqw5TgwkK1PkpqB1SyFKg6IFGJe/M6deI5rkQrfCL56Rons3p14LTg2GuQ6W7/NuKr+HTkKgREQojmoNXFN44m72j+ACu1S1R3XkiQ4unkctXjh37p48+2puXhzq2njzpFoRXhw/nOQ5MwOLRHC4cunDu+3OZj2dqI7Sbntp0eMfhfpP6cRwHJvBRRzakIZpMgKCxybtw+ndE82yIZvjFc1I03cUZ1oOLAsNcq4+LtnipF1cXyocNjb4TzcHqsT17Yt1Ry3lch4yodAQINc+/PWbMAzt37jhzBnXknj5td7vfuvNOFc+DCUw8mpy52Lxv477emb2NKUYAg+cO3vmvnYmdEpO6JIEJdMJluA9CEo6oxqBpyDtyho2iaSbEcvjFe140Tef06yGLBcP4r8hReND0LXwaHjNGJVOhyZ2quvTMibUVLiuuQ4wqIi08BYFDLpO9NnKkVqncdOwY6vj64sU5OTkrx44NVSjABCAeTc7r8rbr065zRmdckdQ5qdfYXh6nB0zgo45sgEICouwPWSyaDN+GM2wQTTMhlsEv3jzRNJUzvANZEhjGT9uLNlNQXJ1BETHQmIEm92XpoaWnN7lED65PRnQ6AUFAkRHy3O23axWKVYcOoY4fCgunffjh2sxMg1oNJtDwaHLGFKMxxYjfSR+ZDiYYUOrYDonUmWhifGvOsEE0z4RQCr8IRWLlVM6wDnw7MIxkefbzx61H4NPI2PE8kaMJCVRce3HHpvwv0RAGR6UjABHg0VtuMWg0L3/zDeo4Xlo6ddOm9ePHx2i1YAIKD4ZpINT9PYQCSEG0RDkETY9vxRk+EE3TIVyGX8Ry0TSLM6wD3x4MI822ok0UFFcXpYzpYxiAJlTlsf/z5DtHzGcggUERBsDkrsJVtA2NTwmJQcC6u1cvjVz+7O7dIqWo7ZzJNHnTpncmTEjW6cAEDh4M01AcOZCGqEeBqNEsZPGc4V3RNBNCAfwiVoimaZx+NeRdwTD1OVl19Ez1Sfg0Jn4yR2RoKhdsRU8dX1PirIQEncNbP9FptsVd/Zcj/3IKbvyRIdE3IcDN6N5dq1Qu+uwzQRRRW2FV1eRNm9ZlZnYwGsEECB4M0yBoDXXugjREnYlmJIvnDBtE00wI+fCLaBXNczn9Ssh7gGGujoJuL9oMn5I0rbrrbkJT+brsyOLTH7gENyQYGdfvvrbjeU5mUGj/1mHasyfWUVDURkBuieqOwDe2Y8dQheLPubkurxe1ldvtd3344epx43rExoIJBDwYpiFQZy5oDaTgW0HeDc1LFscZNoimWRDy4BexSjTNJvoVRNEXDHMVh80/FNTkwacxcZMJCBqfSMU1F3dszv+KgqI+co6/v9344bF98ZubjV0nJWVsyv8StXXTtzUqdQgKt7Vps3rs2AXbt9d4PKjN6nTO3LLl32PGDEhKAtPi8WCYhkAd2ZCGqCegJZDFchEbRdMseM/CL9RBzXdD9xZR3gyGqUOk4ifFW+BTe21ax7DOaHw1XucLv7z7XeUJSGBQhD3deW7HsGTUltVqZJ69+PvKk/idjKh0BJF+SUnvTpw4NyfH4nSithqPZ97Wra+PHHl727ZgWjYeDHP9hDy4j0ASGVGPQQvBRXKG9aJpNrxn4BfqoJZ7oXudKAeDYWr70Xyg1FkMn0bHTUTjK6gpe+r46oKaMkjQTpvwdKe5USo96iCEPNZxxv2HX8uvKcUVco4faOyG4NItJmbDhAmzsrNNDgdqcwvCwk8+eXHo0My0NDAtGA+GuW60JgegkIAoB4KLQsvBRXKG90RzFjxH4RfqouaF0L1KVMPAML+hoLtKP4ZP3XQ9W4e0QyP7rvLEi7+8a/c6IcGQ6Jv+L3WSkpPjKjS86unOc+8/vNTudQLoE5EWyqsRdNKioj6YPHlWdnZxdTVqE0Txb5995haEKV26gGmpeDDM9RKpczskUmeipeHCOcNa0TQPniPwj5da/g/hDqIeByZ45ddcdIvutqGpkOCw+YciRyGujoCMjB2PxkRBN+d/tfpCLgVFfWSEm9NqxOSkIahPoiZqUYdpTx9fQ0GHRPVEkGpjMGyaPHlmdnae2YzaREr//vnn1S7X/JtuAtMi8WgJPMfAtwYJAROAqGs/hGJIwYUTZQZaIKLlDGtE891w/wD/CNT6KKibaCaDCVJe6n31zD8SNSkZUcN66ftxRIaroKCflmyHT70NAxLUSWg0NYLr5V/e219xDBKEy0P+njaru74dpOkf2Xl6ytDswj29IjoieMWHhW2aPHl2dvYv5eWojQIv7t1rdjgWDRwIpuXh0exotWi5D0TL6VdBFgPgqPlyO22UmpeDCQiOHEhDVKNBFGiZSAinX0ktC6lrH/wj0qonQW0kJAtMMIpVxQMoqMlbn/fvT4qyM6KGDYgcrOAUqOOo5fBlRz6ujiOyEbHj0GiKHBVPHV+dZy+BBG1C45/pPDdaZYA/ZqTckRISo+TkCGqRGs3GSZPm5uQcKS5GHSsOHrS53U9nZHCEgGlJeDQ3WvVPCMVAsWiayulXg2+9o+DEgfJP3uw7KTFED6aFo9XU9SWkIepMtGRETXQrYP0rdX4O/1Ba/RJEM9E+BKZlc3sFp8dT5XS5PF6nxwug2umiFP9R4/Z4BQG1EULUJMxBqwBUuss/LNzwSVFOJ02/fvqMaHWknJdpVUpc8WnJdvjU29DfqIxG4zhoOvX8yXdsXgckGBzV48HUKUqZAn4iIIOM3XEDCFMq35kw4d6PPtp36RLqeO/nn6tdrsXDhsk4DkyLwaNZUdfX1LEV/yFcFk2TOd3yEkfVaWvphN2rlvYe3z+qNZgWjDo+AXVCCr495J3QwhE50b0O6yPUsR1+ova3Qe0k7AmAA9OE3F7BZK+x1DgrbTXmGoe1xmm2Oyw1DkuNs9JeY3O6q50ul8fr8HhtTpdIKfzXbRDVR+G/HKL9R9sXP1i/LC80XDoVU1OtUvCy6Hhbm14XcHWEcB35QZYap06jQoOioJvzv1pzcYdIRdSHI9zcViMmJw0BUx+NXL5y7Ni/7tjx2dmzqOOjU6fsbvcbo0YpeR5My8CjGdFqWvUkfk+0iubZJfY5AKxux/z97/21U8b89gPAtFTUkQ1piHo8AoOMhL8IyKgjB36iNe+B2kj4i4AMTIPyCEKJ1VZWZSuyVJVabaVVtiJLdam1urTKVmmrQSOzV6n1UdWojZPR6OTKqKRKU0l4/qnYyNaF8KkkXzfrw08ByGUyQ4g6UhsSGaoxhGqM2pCIUI1RGxITro3TaSO1IRwhkMwpuF859f7e8p8ggVauebzjzJ6GVDDSKGSyN0aNenTXruwTJ1DHlxcuzNm6deWYMSEKBZgWgEfzoVX/gFCC/0HdpTXlgAaAQOmS41+etpb+M320SsaDaWm8F+E5CklkRD0KAUNGwl8A0dCad+En6tgO0U50r4EowFwTSlFsrbpUYcmrMOdVmC9WmC9VWIosVkGkaCY1VSpcBSGIiLVGxFrhGyX5v8TgCo8glFbZSqts+CO8jIvShsbotHE6bUy4NjosNE4flqgPT4wIV/I8ait3WZ46vuZsdQEkSNREPdM5K1ETBcYfMkJeuuMOrVK57vBh1PF9QcH0LVvWZmbqVCowzY1HM6Gu3dSxDXWIlJR51PidTwqOX6iueKvv5FhNOJiWhDo+hDRENRicEYGEkLAnQHhqXwc/UdcXsCwkujdAVGAkuGyuOlNSfrqk4nRJRV65Ka/C4vJ60ZLYrWpcn/LLOnuVGhJ4BbHIUlVkqTqMWghBlDY0MSI8Ua9LjAhPNOi8mqoNZdutHjsk6BvR6dGO0zW8Coz/CPDErbdGhYS8/M03qONoScmUTZvWjx8fHRoKplnxaBZiFa16En+kwqMSKEFtJy0l43evfK33hN7GFDAthUAd2yGROhOBhxDtYyAh1PYW/ERde6g5i9OvAAkFU5tHEC5VWE4UlZ64XHa+rPJ0cbnJ7kDLZq9W43pQkn86BteHUpRW2UqrbD9evAwgJMGm62AGR1EfAjIpKSOr1UhCCJjrcHevXgBe+eYbiv91trJy8qZNGyZMSAwPB9N8eDQHWv0shFL8kRK3Bn/E5KrJ2v/eE92HT0pJB9MCUNc3EMshBRdBlLciMJHQv4CoafVi+Mt9UDTN5PSrwelxY7M6nMcKSk4WlZ0qLj9dXJ5vsggiRaNRK+R6jdoQqtZr1DqNWh+iVsn5UKVCrZCr5HyoUqFRKhS8LFSp0CgVPMfhinC1Er9RK+RymQyAw+3xCAKueP7sg1VeK65JRVF4tVmDBkI4quto0sTbIYGSyOcnjx+d3IcQMNfv7l69tErlU19+KVKK2gqs1rs2b14/YUJrvR5MM+HR5KjrK+r4CFdR5tbgKjyi8OThT05ZSh7rOoznODDNy5EDaYh6NMAjYJGQBQCh1a/AX57jomkGZ1gLzogbiUcQfikqP1ZYcrSg5FhhSV6FGQ0qXK2KDg+NDddGh2ujw0JjdVqjNiQyVBOuUetDVEqeRwNRK+RqyHFFrDqhqtqKa9I3NfqpAcNCaazJXmOyOcqrbZU2h8leU1ZlM9sdlbaasmq7w+2BBDKlENGjXB7mhgTeGnnpkchHP/v2n8of20ZFpMZGtouObB8TmRoTGaZWgbkmd3XtqlUoHvr0U68oorai6uopmzatGz8+zWgE0xx4NDHRQq1P4OpKXCHwaeOFH09ZS1/vMzFSFQqmuYhW6voK0hD1OAQ4EjIfJJRWPQOI8Iv3jFg5mTOshywRQe1SpeVoQfHRgpJjhSWnisvdXgHXTcZxCfqw5Eh9q0h9SqQ+KUIXHR4apwtTyXk0uTh1wunqE7gm52ynz9meaxPafmj0qIykHgQEdVQ7XSXW6iJLdYmluqTKVmypKrZUl1htpVXVbq+AK5Q6l6FbOacUIYGrQl15NIJ6OQB2l/vnguKfC4rxm1idtlN8dFpcVKf46LS4qIhQDRjJ7uzQIUShuP+TT5xeL2qrrKmZtnnzqnHjesbFgWlyPJoWrXoWYjmurtStRn0OVxaM373yzb6Tu+jjwDQH6vwI1A0p5J3Ad0DgI5qp4EKp5W+AF34RCkXTDE6/DnwKgojbKxwvLPkx7/KhvMtHC0qsDieuj1ohbxcd0SHWmBypT4nUt4rUJ+jDeRmHliFGFY/rc952Zrnt1QR10m3RI3vq+8qIDL+jVSm1KmW76EjURilKq2wFJstnJd/vdX1LIaJelFTnaavP6iiuqthSXWyp/uLEOVwRHR6aFhfdKT4qLS6qc3x0pDYEjE8ZrVuvycxcsG2bze1GbVUu16wtW5aNHj0oJQVM0+LRhKjrS+r8BD6VujSQoNRRPWPvun+mjx6V2BlMk6OOrZCGqDMRLIjqTuhU1Pp/oG74RSgSTXdxhjXgOyCQ1bg9P+UXHcq7fPBi4bGCUpfXi+sQrw9rH2NMjYnsEGtMjTUmGsI5QtBSxani0RAKHfnr8pZvL9qcETVsQMRglUwFnwhBpFb9fsmOPa4DkIAKnOm4wVmqgT9KrbZSq233L+dxRZwurFtSbNfEmC4JMWlxUSo5D6aOPgkJ706cOCcnx+xwoDaH17tg+/alw4cPb98eTBPi0WREC7U+ifqUujWQxil4HzqY80NF3lPdR8gIB6bJeM/CcxxSEDlRjUIQIarbwa2i5ntAa+AXsUI0Ted0K6DoiYBidTgPXyr68WLhobzLJy6XCaKIa6LgZe2jIzvEGVNjjKkxxtTYSK1KicARq05AwzG7K7ML38stzu4Xccvt0SN1cgOuwuqxPXti3VHLeUhgkIeNixjuSJdfKDedK608W1pR4/bAf0WWqiJL1c6jpwHwMq5DjLFrYkzXxNhuSbHJETowv+kSHf3BpEkzs7NLbTbU5hGEv+Tm2tzuiZ07g2kqPJoKrXoGYjnqU+rWwB+bLx6+XGNd2nt8mFwFpklQRw6kIcoh4PQILkTRlxjeEc1ZEK3wi1glmucS3RtEOQgtm93l/uFCwbfn8g9eLDxXWilSCv8RgpQIfZfEmC4JMV0TYzrGRvEyDgFLIwsJk4dXeaxoOE7Bubvss2/Kv+xl6H9n3ESdXI/azlYXPn1iTZnTDAm66to8kTZbpwjFbyhFodlyurjibGnl6ZLyMyUVBSaLIFL4wyuIxy+XHr9cuvG7nwFEhGrSk+N6psT3SI5Li4uScRxubG0jIjZNnjwzOzvfYkFtAqWP7tpV7XLN7dkTTJPg0SSocxd15qI+FKTMrYaf9peen7B71bK+k9uGGcE0OoE6PoJE6kwEJXlXTr9ONGdBNMEv1EHNdyP8eaIehxZGEMWfC0oOnLt04Fz+zwUlgijCf4YQddfE2C4JMV0SY7omRIepVQgisaqEKo8VDU3BKZM1rcPlOtT2Zemhpac3uUQPJBgZ1+++duN5IsPvEIJEgy7RoLutU1tc4fR4z5VVnioqP1lUdrKo9ExJhdPjhT8qbTWfnzj3+YlzANQKedfEmJ7J8T2S43okx2kUctyQEsPDN02ePCs7+0xFBWqjwHN79lTU1CwaOBBM4+PRBEQzrXoKEpg9SqfIw3/5NtOkr1e/dNOY2+M6gmlM1LUPYjmk4CKJciCClbwTZ9gommdDKIF/BGp9BKKVhMxGC3ChzPTtuUsHzuX/cLHQ7nLDTzKOpMYYe6bEd0uK7ZoYk6APR/CKVcWfrj6BhkNAehsGjIufGiYPx+8IVFx7ccem/C8hgYLj/9J+4tCY3pBAJec7x0d3jo/GFYIonisznSwqPXm57OTlslMl5Q63B5I53J7vzxd8f74AAC/juibE9GmT2Kd1UvekWAUvw40kKiTk/UmTsrZu/am4GHWsOHjQ4fU+OXgwAdO4eDQ+WvUMxEpIUOZW41rVeN1//u7DhR1vWdjxFgKm0Ti2QhqiHgvIEMT41v+PPfiAj6pM9Ab8f885c86cycykTNqkN5IQUkggQAARAUEFpYOI3dVd1/Vu1XvvuqtuvbvrFl0/P9uqa0VUQBEFlN5LCpCekA6ZtDNJZibT57wfP/dzf3CTkBlIIJB5HiZknWy8H54m+IZS8+8hdxHNz3A1GPtsh2qbDp1uOny6ud1kgY8ULJsVEzE5MSYvPiovIVot8BgbIpVRGD7hQuTq2PvHazNxIZOr77cV75R018ALoULgs5kPpmnicElYhkmLDE2LDF2aNwGAR6b1ndKplrYTzYZTLYb6TqNHpvCO2yMXN7UWN7W+vOuoUsFNjIualhw7NTk2MzqCZRiMAUFK5bsrVjzy2WeHm5vRzzslJWaH44/z57MMA78Rw2GEUfs2av8S3ml3qnAZKPB/KvdW9bb/cfKSAI6H37CjZurYBe8QcQmue2w0o/tANj4Adw18RPteA7US7S8ABlfE6XZpT1X94brmY/VnPLIMXygVXEZUeF5CdEFyXG58lFLBYeyJEmMwHBQMPz9i0YLI2zmiwIXqLa3PlL3ZZpfghQmBiU9PeCCE12CYsAwZFxE6LiJ0+eRMAFanq6q1o7y1o/xse1Hj2bPdJnjH7nIfqWs+UtcMQOQVE+P0BclxBSlx46PCGUJw/VIpFK8vWfL9zZv3NTain00VFU6P56+33soxDPxGBocRJXdT06/htTZnAC7bjtaq5bte/78Fq5M0ofAbVtT2Bagd3lBkgkvFWMCEMSHvy90PwXUKPqLW90DNJPAPAIuRYbY7DtY27atu2F/TKFms8IXIKyYlRE9Ljp2UED0hKoJjGYxtemUMLltWYN6q2Ht0fBj62dNR8ufqDx0eJ7ywMKrgBynLOYbFiFHxiryE6LyEaHyjxdhb3HS2pKm1qLG1vlOiFN6wOV2HTzcfPt2M7QgJEPOTYqclxU5Njk0IDcb1SOS41xYv/unWrV/U1KCfL6qr+5zOl26/Xclx8BsBHEYSNT0DuQtea3eIuGw8w2YG620eF/yGG7VtgneIuBRjBxPIhLwldz8MZzF8RG2fQTaToOdBlBg+NW1d+6ob9tU0lDQZPLIMr7EMmRAdUZASX5AclxuvV7As/L4VwKm1ikCTqxeXJITXrYq9NztwEvqRqfxmw5cfNe+ioBiKguEeH7f8Vv00XFmxIYGxIYGLczMA9FjtJc2txY1nS5pay862O90eeMHYZ9teWrO9tAZARKC6IDnuhtSEGePitaIS1xEFy/5t4UK1IKwvLUU/exoaHti48fUlS9Q8D7/hxmHEUPuX1L4NvmhzqnAZIpTMysQb1iRN1gkB8Bt2nka4TsArHFEuxJhCNEzwW7TnB9SxHz6ijl20+ztM8CsgalwGp9tzrL5lR0XdvuqGtl4zfBGvCypIiS9IiZuaFKMVlfAbRKQy2uTqhY8Ywt4YNu92/Uolq0Q/Vrf9fyrfOyKVwwshvPaZzAcytAm4qoJUypvSk25KTwLgcLtPNBuO1rUcrWs5dabNI8vwQnuv5dPiik+LK1iGmRinn5WWOCstMS0yFNcFlpDf3Xyzhuf/UVSEfo6dObP244/fWrYsRBThN6w4jBBZoqZfwUftThV8xxA6M8iwJrL6hqBWVi0QYRb8RgC1bQIovECUs8GEYKwhIgl6Gb0/pvav4SvnMdl4LxP8Bphg+Mhsd+yvadxZUbe/usHicMJrwQHitOS4guS46ePiooK08POCXhldY66AL1LUaXfGPhAlxmAgLdaOZ8reaLF2wAvjNDHPTngwXBmM0UTguKlJsVOTYnEzrE5XYcOZo3UtR+pbqg2dMqUYikeWixrPFjWe/dv2A5GBmllpCbNSEwtS4kRegWsZAf77xhtDVKo/7d+Pfsra29esX//28uWRGg38hg+HkUFNv4LcDR+1OwLgiwDWtTS87h59VazSgm/QvtfhaSGBz4EI8BtOlNo+h5eUyzA2EZ4E/R29T1Pbx/CVq0w2rmGC3wKrhxeMfbb9NQ3bS2sPnW5yuj3wWnK47qbxSQXJcVOSYliGgZ8v9MpoeE3NaZdFr5mqm0lAMJAjUvkfKt/rc9vhhbkRk3+ctkpgFBjFVLxiVlrirLREAH0O56mWtsN1zYdPN1e0tlOKIbX1mj86VvrRsVKWYXJiI2enJxWkxE2IjsA167v5+SqF4te7d8uU4kKnjcbV69e/s2JFfFAQ/IYJhxFA7VuofRt81+EU4YtbQpt+nliIC1H7Nsg9JPglEA38hgl1HoXnDLzBBBFhFsYulgT+Fkwg7fsHfOWul41rmOC3wCViEC3G3j1V9dtLa040G2RK4R2RV0xNip2dnnRjemKEVg2/SxWpjIYXCMiUkBnLY9aqOQ0GQkE/at71Rv0XFBRDYQnzQOJtq+Pm4poSIPAFKXEFKXFYAMliLWw4c7iu+fDp5hZjL4bikeXiptbiplZsR2xIYEFK3I3pSdNT4gSOw7XmnokTNYLw5PbtHlnGhc6YTKvXr//nsmXpYWHwGw4chp3cRU2/hu/Mbt7iUcAXX3QmPJFQomUduBB1HqHSWibkH2DC4TcsbBvhHaK8HYTHmEaI5kkwgdT8V4DCJ55W2biGCf4HFJk4T5Whc1tpzddltQ1d3fBaSoRuVmrirLTESQlRLMPA77JFiTEYSowYd2fcA0kB4zAIq8fxp8r3D3aVwgtaRcAvM+6bGDwO1zKdWrUgK3VBViqAFmPvsfqWg7VNB2ubzHYHhtJi7G05VvrRsVKRVxSkxM3LSLlpfFKgqMS1Y8n48Wqe/48vvnC43bhQZ1/fXR9//MbSpbl6PfwuG4fhRk2/gtwD37U7VfCRXeY+70hYq69Gf+4quWsZE/IPcOnwu0zURu1fwTtEXAo/gAR8F0wY7X0K8MAnslE23k2C/k6EWZWtHdvLareV1jRLPfAOz7FTkmLnjE+alZYYFaSF37BScxo1p7W4TRgIzwi36ZfMC7+NISwG0Wrreqbsjca+NnghWR39q8wHI5QhuI7EhgTGhgQun5zpkeXiptb9NY37qhtq2rowFJvTtauibldFHcswU5Ji5mWkzM1IDteqcS2Yl5z8xpIlj3z2mdXlwoV67fZ7P/nklcWLZ8TFwe/ycBhW1P45tW/HJWl3qtCPgshzQlpuCD77y9MFFAT9fNiWepe+hoCADQcbQ9gYsLFgYwgbDTYGbAT8Lhu1bwO1whtcChSZ8PsGEZeBaGnvj0Ed8Am1uo3f+8uhRe8U6eEdpYKblhy3IGvcnPHJGqUAvxGjV0bXWkzoJysw987Y+4N5HQZ33Fj1+4p3LG4bvHBTeO5P0+4UWB7XKZZh8hNj8hNjfrJgpmSxHqht3FPVcLCm0eJw4qI8snz4dPPh082/2bwrOVx3S9a4W7PTksJCMLoVxMW9t3Llgxs39tjtuJDV5frOpk0vLFw4PyUFfpeBwzCSO6npN7hUbQ4VzhPO2+4Iq79LXx3JWwFs7kw61huJfupsgUXk7Snhk0AU8Bshtk3wDhGXwe88RDkPzOu0+1HQPviCJe4npn/G0Gn/LJ6IwYUEiDNTExZkpc5Iiec5Fn4jTy9G11oqcZ4wIWJ17H0Z2mxbY73PAAAgAElEQVQMjoJ+1LzrzYYvZSpjKAxhHky8bVXcHAKCsUGnVi3OzVicm+GR5ZPNhj3VDbsr6+s6JAylrkN6aaf00s4jyeG6m8YnzU5LzI2PJgSjU05k5LsrVty3YYPRZsOFnB7PD7Zs+cP8+csyMuB3qTgMH2r6FeQeXKo2pwoAQ+jUwPZVEbXzQppZQvENolq9Jjn9WHEdBrKu6cyUiGnwGyGes9R5DF5hifJ2+F2I8NNIyDty90OQe+ALQujPZh7Wqy1/2D+DUoLzJIWFzM1InpuRkhUTSQj8riS9MhrfYgk7N/y2hfplCkaBwTll99+q1+9oL4QXNArVU+PvnRSShjGJZZi8hOi8hOifLJjZJPXsrarfV91Y2HjG6fbgouo6pLoO6R97j8eGBN08IWXehJTs2EiGEIwyGeHhH65efd+GDQazGRfyyPJ/bt/udLvvzM6G3yXhMEyo7VNq/wqXwUnZB6IqVkfUxolm/C+K7PnxyyMqX2i3mdHPV2er2m3mCFEDvxFAbZ8BMrxAhBlgI+DXnyKLCflA7n4Annb4aO3EUo3S8fTOm9weJiMqfEFW6rwJKYmhwfC7SvTKaHwjVZNxZ+z9kcooXFSno+eZsjdrzS3wQqwq/FeZD8WqwuEHxOuC7p2Rd++MPJvTdfh0887Kut2VdT1WOy6qxdjz5v7CN/cXhmvVczOSb81Ky0uIYgjBqJEcErJ+9ep7N2xo7O7GhWRKf7Fjh9npfHjyZPj5jsOwkDup+XcYAgdWT9hYsOFgwsHGgoulvU/A04lv/DiuBINxN7OEWZGQ+1LlPvTjofKGppLvp8+C3wig9s/gJXEZ/AbDpTAhH8rGB+BphI/uSK/JiQ5ggp+PD9XD72rTizGBiqAl0XdODZkJLzxf/VGtuQVemBmW/WT6XSIrwO9CIq+Yk5E8JyPZI9OTza3bymq/Lq9t77XgojpMlnVHTq47cjJCq745c9wtmeNy46MJwWgQrdWuX736/g0bKjs7cSEK/GHfvm6b7ckbboCfjzgMB2p6FnIv/o0JBBtL2FiwsWBjwcUSNhZsFMDiQpRNgqcTQ/I0AlidOOnV6gNuWUY/H9YXPZI6k2MY+A0vVzHcDfAG0RBhDvwGYXe591b17a64574JL6eFdsFH8ZoSkP+A/BqYYPhdVRpO++yEPwuMEt75afqdjxX9tcvRi8ERkFVxcx5KXEgIgd/gWIbkJUTnJUT/fNHs0+3S9rKaraU19R1GXFS7yfLeoZL3DpVEBWnnZCQvycvIiArH1RaqUn2watWDGzeWGAzo59Xjxy1O57Nz5jCEYCD7GhvH6XR6jQZ+5+Fw+TyNYJNJ4Gyw0YSNARsFcPAOYeMojmIo1N1EgHCl5qbItK9bK9FPh928u63m5qh0+A0ratsE7xDxNhAl/C7k8nj2Vzd+frJqb1W93eUGsLvyjpcWf5mnb4OvXCdl41om+A2wevhdVQKjhNdCeO0vJ9z/sxMvuWQ3BqJihSfHr50RmgU/X6RE6FIiCh6bW1Db3rWjvG5HxenK1g5cVGuP6b1DJe8dKkmLDL0tJ/227LToYC2uHq0gvLNixaObNx9oakI/7588aXY4nrvlFo5hcKESg+Gxzz+/e+LE/7zhBvidh8PlYxOI5ie4NFw8vOFpAihA1iRN+rq1EgNZV194c1Q6/IYRdVD7VniHiEvhd55TLW2bSyq+PFXdY7XjPGan8MimRS8s/GpGfDN85T4tSyuZkDfBpcLv2pGhTfhR6srnqtahn2gx7FeZD8YHRMLvUo2LCB0XEfronKlnunt3lJ/eUVF3oqlVphSDq27rqm478PxXB3Ji9bdlpy3ISg3TBOBqUCkUry9Z8qMvv9xeW4t+NldV9TmdLy5aJHAcvlXV2fnQpk1Wl+vDU6cenzZNpVDA71scri42Ad6gNsidYMILwpMSNboGs4R+DnfUN1qkBLUOfsOEOnZCNsEbbDwUufADDD3mzSUVm0sqG7q6MQi7W/GDz2/9/fydt6aehq/kDtl4NxP8KhS58Lt2zI+cUmlq2tJ6COeZEjL+vzPuUXMi/IZDTHDg/TMn3T9zUpe5b1dl3dbSmsKGMx6ZYhCU4kSz4USz4Y9f7p2cGLMwO31+ZopWVOLK4ln2xUWL/vurrzaUl6OfnfX1D2za9PrixQE8D6Cxu/u+DRt67XYAJodjQ3n5PRMnwu9bHK4qwsVTeMfdBD6cAKsTJ/3h1FfohwLrG4r+M2s+/IaLbSO8Q8SlAMEYZne591bVf1ZSub+mwSNTDCVAqTpu/PEk975wbj18JffIxvtJ0AtEmA2/i+vpAaVQq6FQ4ByHA2YzVCqoVDjH4YDZDLsd5/A8NBoolSAEI+Oxccuare2neuoAEJBVcXMeSlxICIHfcAvVBKyakr1qSnaP1f5VWe3mkoqS5lZKMRiPTI/WtRyta/nt57ump8Qvzh0/NyOFYxlcKSwhf1ywQCMI/ywuRj9HW1ru/uSTt5Yts7lc927Y0GW14lv/LClZm5PDEAK/b3C4utg4gAAUQ6GeJoJ8AMviJz5fvtvucaGfDY0nfphxk5JVwO/yyV3UcRBeIUS8A2OSR6aH65o3l1TsKD9td7kxFI1SuHlCyqKJ6fmJsSxDgJupNYWafg9Q+ITaaPejCPw1EVfC7yL+8hc4HHjkEaSk4JwTJ/D881ixAsuXw2bD7t1Yvx6nTsHjQWIi1qzB/PkIDgYhGAEcYX+Rcd9jRX+1uG0/S18zKywHfiMsSKVcNSVr1ZSss92mL09Vf3mqutrQicE53Z49VfV7qup1atWinPQlkyakRYbiiiDAL2fPDg8I+NP+/ejnVFvbynXr3LJ81mTCeRq7u3c3NMxNSoLfNzhcXUQEGw5PO4bkbsI3tArlwtgJGxpPoB+Ty/7lmfJl8RPhd9mo7TPAAy8QfirYGIwxzVLPxqLyz4or2k0WDEXguBvTE2+fOP6G1ASeY3EeoroPJID2/hLwwDce2vsLyN0k4BH4+YpSfP01XnkF+fn4xS+gUmHDBrz2GpxOrFwJUcTICOY1v8p8kCVskjoKfldQdLD24RvzH74xv65D+vJU9Zcnq5ukHgxOsljfPlj89sHidH3YkryMRTnpIWoVRt538/MBPLd/P8X/Vt/djYG8WVQ0NykJft/gcNWx8fC0Y0ieJnxrbdKUDY0nMJB19YXL4ifCD6D2LZB7iXIRmED4jto+hZfEpRgzHG73nsr6j46XHqlrphRDmhAdcUfu+EU56cEBIgZBxBVgQmjPj0Ft8A2l5j/D3UQCfw2w8POe1YrNm5GaigceQEICzvne93DmDA4cQF4eMjMxYsZpYuF39SSH6x6fN/3xedNPt0vby2o2l1S2GHsxuCpD5x++2Pvc1n1TkmLvyB2/IDNVqeAwkr6bn68RhGd27pQphReOtLRUdnaODwuDH8DhaiNsPMUxDIV6mgj+v4ygyKzgqNLuVvRT2t1a1t2aGRyFMY9wmXLXAmr+PeFnQlxChHkgCnjJVQZ3NbxBRKKcjzHgZIthY2H51lPVFocTQ4kNCbwjd/wdueNjQ4LgBSLMISHvyN2PQO6Gj6jtY8jdJOgvICL8+pMkVFbCYsE5tbWwWHBOSwsMBtx+O2Ji8C88j+xsbN2KtjZkZsLvepcSoUuJKHh0zrTixtYvT1VvL6vp7rNhEB6ZHj7dfPh08x+27L0tJ21xbkZ2bCRGzF3Z2Rqe/9m2bW5ZhhfeKi7+04IF8AM4XHVcHLzhbgQoQPCNNUmTS4s2YyDrGgp/F3wH/LgEKCbCVUIdu+HYTZlAoryFKJeAzwMILoraNsE7RLkAJADXL6PF+tmJyo2F5XUdEoaiUQq3ZqfeMXF8bnw0IfCNIocJ+UDufhAeA3xEHTuo8R4m+FUwOvj9L4cPo7wcoohzzGb09eEchwOUQhDAMPg3UYQsw+2G35jBEDI5MXpyYvTPF83eV93waUnF3qoGl8eDQfTa7OuOnFx35GRSWMiyyROW5GaEqFUYAbenpwfw/ONbttjdbgzl86qqJ2bODAsIwJjH4apjE+ANaoPcBSYM37gtJvOPpV/3Om3o54uWsiczbw7kRYx5RFxOXSX4F7mXWtdT63pwSUS5kIhLwcZgYG5q/wJeEpfheiRTeqi26aPjpXuq6t0eGRfFsczMcQmLc8fPHp8kcBwuGZfM6D6WjQ/BXQ1fuU7J0iom+A1wCfA737x5uPtuJCTgnJISvPYazgkOhlKJri709UGjwTmyDIMBCgXUaviNPRzLzMlInpOR3GO1f3Gy6rOSirIz7Rhcfafxz1v3v/DVoTkZySsmZxakxDGEYFjdlJQ0NSZmb2MjhuL0eN4/efJH06djzONwtREunsI77ibwYfiGkuWWxee8VXsE/dg97k3NJ+9PmYYxj4iLqPn3oFacz11PLS9Sy0vgJxLlUiIuAgnAeah9D2QjvMFGEj4f1xejxbqxqPzj46Utxl4MJTE0eOmkCUsnTdCpVRgWTDgT8p7c8z04i+ArT4tsXMUEvwJFHvz+TalESAjCw3FOUBB4Hufo9cjKQmkpjh3D1KlgWTQ34/hxREcjNhaALMtut5v9BvzGkiCVcm3BxLUFE+s7jVtPVX9aXHG224RBuDye7aU120trIrTq23PH3zk1OypIi+FAgad37Njb2AjvvH/y5KNTpggch7GNw1XHxgMEoBgK9TQSTMa31iTlv336qEwp+vmgvvDe5KkMIRjjiIooF1DbJgxAhrOYOoup+XdEuAniYiLcCLA4x74R3iHiUoDF9aL8bPvHx0s3l1TaXW5clFLB3ZietCo/a1pyHCEYZkwgE/wm7fkhdeyBr+Qe2fgACXqeCDfB7yIUCixdildfxSefoLkZgoCjR+HxYMECxMQAsFgsJ0+e5Hk+LS0tMDCQEAK/MSYpLOSxuQWPzpl2oql184nKz09U2ZwuDKLdZPnH3uNv7iucmhy7Kj9r3oQUlmFwGZ7bv/+DU6fgNaPN9llV1arMTIxtHK46IoIJg9yBIbmbcJ64gOBpYYmHOurRT7PFeKSzYXp4EsY8Ii6ntk24CGqn9q2wb6VsBBEWEOUC6tgH7xDlYlz7zHbH1lM1Hxw5UdPWhaFMiI5YmZ+1aGK6ildg5BCRBL8M0zPU+hF8RW20+/vQ/pKo7oJfejpcLgQE4F+Cg5GXB70e50yciB/+EF9+iV274HIhNRX33YfMTLAsAJvNtn///sbGxqnfSEpKUqlU8Bt7GELyEqLzEqJ/duusnRWnN5dUHqlrphQDkik9fLr58OnmME3A4ryMlflZsSGB8N3Lx469evw4fPRWcfHKzEyCMY3DaMDFw9mBIXmacaE1SZMPddRjIOvqi6aHJ8GPzwcbD08ThuRpp9Z3qPUdeEmRCy4J17ITzYb1R09tK61xuN24qHCtenHu+KWTJiSEBuMKYYn2N2AiqOVF+MxDTc/CXU+0TwEEY9natThfaiqeeAL/lp6O9HQMJCIi4rHHHtu9e/eOHTvKysqmTZs2ZcqU6OhonufhNyapBX5xbsbi3IwWY8/GoopNReUdJgsG0Wnu+8fe42/uK5yeErciP2tuRjLLMPDOeydP/vnAAfiupqvrYFPTzPh4jGEcRgHCJlAcx1Cop5HgAnP0aVGqwFZrL/rZZahus5kiRS3GOkLEZdTyNww3Ii7FtcnicG45Ubn+6Knqti5cFMuQG1ITV03JuiE1kWUIrjRC1I+DCaKm3wEyfESt74CaSODvAQ5+vgsMDFyyZEl+fv6WLVt2795dWVmZn5+fl5cXHh7Osiz8xqrYkKAf3jz9B3On7a1q+KSwbH9Ng0emGIhM6YHapgO1TeFa9cr8rJX5meFaNS6qqafn+UOHcKneLC6eGR+PMYzDaMDFwRvuJoACBN9iCVken/ti5R7046Hyx43Fj4+fjTGPiEup5e+AB8OICER5K641dR3S+mOlGwvLrE4XLipUE7AkL2P1lOzoYC2uKqK6B0ww7f0vUCd8RG2fQu4iQS+CBMDvkkRHRz/88MPV1dWbN2/esmVLWVnZ1KlTc3JygoKCCCHwG6tYhpmTkTwnI7nT3PdZccXHx0tbjL0YRIfJ8tLOw6/sPnJDauI903OnJccRggHFBwUdfuSR3Q0NG8rL9zY2ujwe+GJfQ0Od0ZgcEoKxisNowMbDG9QKuQtMGM6zOjHv5ep9bllGPx81FD+aNotjGIxxbCQRZlDHPgwfIswFE4hrhMPt3lNZ/9Hx0sOnm3FRhGBactyq/Ky5GSkcy2B0IMpFYEJpzw8gm+Aj6jhApdVM8D/ARsLvkjAMM378+KSkpMLCwq1bt27YsKG8vHzatGnp6ekBAQHwG9vCNAHfuTH/wVmTj9a1fHS8dFdFncvjwUA8Mt1TVb+nqj4hNHjZpAmrpmRpRSX6UbDs/JSU+SkpvXb71pqajRUVRa2t8A4F3iou/u28eRirOIwChEug8I67EXwYzhOqVM/Tp287W4F+Ou2WnYaqBdEZ8BNXwLEPw4eyEYRaQVQY3Rq6ujcVlX9yvLTHasdFaZTCrdmp90zPTQ7XYfQh/DQSsk7ufhieVvjKXSMbVzLB/wCXBr9LJQjCjBkzMjMz9+/fv3v37tra2tzc3ClTpiQkJIiiCL+xjSGkICWuICXOZLNvK619/3BJbbuEQTR2df91+4FX9xxbmJO2ZtrEtMhQDCRQqbwzO/vO7Ow6o3FLdfWmioqW3l4MZVNFxc9mzgxSKjEmcRgN2HiAABRDoe56wufjQmuSJm87W4GBrKsvWhCdgTGPCHMpEwLZiOHS95Zs/YAIcyAuJsKNAIvRxCPLOyvq3jtcUthwFkPJT4xZNSX75gkpPMdiNOPGMSEfyt3fgbsGvvK0y8a7maCXwE+B32UIDAxctGhRTk7Ojh07Dh48eOrUqXvvvTcnJwd+ft/QispVU7JW5mcdbzjzyfHSr8prnW4PBtLncH50rPSjY6X5iTFrpuXMy0jhWAYDSQ4J+WFBwePTph1uadlUUbG9ttbqcmEQdrd73alTj06ZgjGJw2hARLDh8LRjSJ569DM1LGGcNrzW1IF+jnQ2nDZ1pmjDMMYRBVHeTq1vYxhRB7VvhX0rZSOJ8g4iLgGXgqvNbHd8Wlzx9oHi1h4TLkqjFG7NTr1r2sTUyFBcK9hIRvcR7fkP6tgHX8m9cvcDRPs7Ii6B3+WJjY299957w8LC3n333ebm5pycHPj5nYcQTEmKmZIU81+WGzcWla8/dupstwmDON5w5njDGZ1adefU7DXTJoYEiBgIQ8iMuLgZcXG/njt3W23txoqKoy0tMqXo590TJx6ePJljGIw9HEYHwiZSTzuG5K7DQFYn5v325DYMZH1D0VM5t2DMI6qV1Po2RoKnjfa9RvteA5dCxCVEXAYmFFdcQ1f3uiMnNxSW2ZwuXNSE6IiV+Vm3T0wXeQWuOURFgl6G6efU9hl8RV2090m4yoj2KYDA7zKwLBv7DaVSCT+/QYSoVd+5Mf/BWZOP1rW8e6hkb3U9pRiQZLG+tPPI63uP35KV+sANk9MiQzEIlUKxLCNjWUZGu8Wytabmk/Lyys5OnKfdYvmiunrx+PEYeziMElwynEcwFOquJxjA0viJfyvf1ed2op9Pm0/+ZMJckVNgjONSoZgAVzlGjvs0Nf+Zmv9G+KkQlxDlAhARI0ym9Ghdy7uHSvZW11OKiwgQ+IU5aaunZI+PCsc1jShI4J/AxlHLi/Adtb4DuZME/hFECT8/v5HHEFKQEleQEtcs9XxSWPbJ8dIeqx0Dcbo9m0sqN5dU5sVH3TM9d96EcSxDMIgItfr+vLz78/JqJWlTRcUn5eWS1YpvvFFUtHj8eIw9HEYJLgne8LSC2kBEXCiA4xfGZn7UUIx+zC7H52dKVyXkYcwj4nLqKseI81DnITgPUfNviTAH4hLCFwAEw83icH55svrtA0UNXd24qKTwkCW5GaumZGlFJa4ThKgfBxtJe58GPPARtW+lnjYm+GUwIfC7qipNLQc6y4J4dZAiIITXBPPqIF4dpAhgCAO/606cLugnC2Y+Nnfansr6tw8Wn2g2YBDFTa3FTa2xIUEr8zNXT83WKAUMbpxO9+QNN/x4+vR9TU2fVlR8XVdX3tFx/OzZ/OhojDEcRgkuCV6R4WkCl45+7krK/6ihGAP5oO74qoQ8jHlEeTs1/xHUgStDNlHbp7B9SrkEolxCxMVgozEc6juN7x06sbmkwup0YXAcyyzIHHf39NycWD2uR0RcCSaY9vwU1AZfuUpkaRUT/Dq4RIxiVo+j3W5stxunhIxnCIPrTqWp+d3GXeiHZ7hQIVDHazQKMVQI1PEajULUCYE6XqNRqDScGCpo4XdtEjhuQVbqgqzUE82GdUdObi+rcbo9GEiLseev2w+8vvf48smZdxXkxAQHYnAKlp2blDQ3KanbZvu8qur4mTP50dEYYziMDoRNpvAKddcTLh39pAdGTAyJOWE8g36qettPGs/khMRgjGMCiTCP2r/AFeZupJbnqfVdJvhlKCbiUsmU7q9pfO9QyaHTTZTiIkLUqlX5WXdOzQ7XqnFdI8I8EvKu3P1dyBJ85WmWjauYoJfAT8HV5pLdXY5eg10y2CSDXTLYJMnZa3Sa2mxGCgrg/WlPhyuDcd3pdlowEKfsbrVJrTYJg+AZTqNQaTgxVNDqeK1GIeoErY7XahRiqKDV8dpgXs0SBn5XVZ/bHsApMYiJcfqJcfonb5v14dFTHx49KVmsGIjZ7vjngaLWHtPzdy2CF4JF8d7cXIxJHEYJNgJEDWrBkNx1GMSapMknjGcwkHX1hTkhMfBTrYD9C1xhRCSq+4j6YRANLkmfw/nFyep3D5XUdUi4qPFR4aunZN+RO16p4DBGKLIZ3Udy90NwN8JXcq/c/SDR/o6Ii3FFuGR3l6PXYJcMNslglww2SXL2Gp2mNpuRgmJw7XZjuDIY151upwWXxCm7JYdJcpga+9oxCJ7hQoVAHa/RKMRQIVDHazQKUScE6niNRqEKFbQaToTfSPpu4YsPJc6/KSIHg9OpVY/NnfbI7PxdFXX/PFB8ssWAgdw/cxL8hsJhtCDgEuAqw5Dc9RjErTET/lT6teToQz9fnil/Mmt+iKDC2Eb4AspGwdOKK4Ql4lKi/iHYCFySZqnnvcMnPi0qtzicGBzLMPMmpNxTMDEvIRpjEBvLhHwkd38PrmL4ijpp75PwNBP1DwCCYeKS3V2OXoNdMtgkg12SHL1Gp8lgl9psRgoK37XZjVlIxnWn22nBiHHK7lab1GqTMAie4TQKlYYTQwWtjtdqFKJO0Op4rUYhhgpaHa8N5tUsYeB3SShoq1V6puy9Q12VP01frmQVGJyCZRdkpS7ISj3ecOa9QyW7Kus8MsW3cmL1E+P0uLj6epSWYtIkxMTgnJ4elJSA5zFjBs4xGnHiBKqr4XAgLAx5eUhJgUKBkVNfj8JCGAxgGCQkYMYMBAWBYbB+PVJTkZkJhQLn1NTg0CHcdRd4HpeNw6hBuGTqKsNQqKeeYGA8wy6Nz/lHzSH045Q9m5pOPJQ6HWMdQ8Rl1PJ/MPIIP51o/wtcOi5J+dn2dw+VfHGyyiNTDE6jFBbnZdw/My8qSIuxjAliQt6iPT+mjl3wGaWWF+E5S7S/AVHAFy7Z3eXoNdglg02SnL1Gp8lgkwx2qc1mpKAYPm12I65H3U4Lrh6n7JYcJslhauxrxyB4hgsVAnW8RqMQQ4VAHa/RKESdEKjjNRqFKkzQqjkRfgMxuaxu6gGwva2o2nzmmcy1yWo9hpKfGJOfGHOmu/ejY6UfHyvttdkBPHDDJAypuhrvv4/QUMTE4BxJwpdfQq3GjBno6MCWLTh4EGo1FAqUl+PECSxfjilTwDAYCVVVeOMNmEzQaEApjh5FVRUeegjBwXj9dSxbhrQ0KBQ4p6wMzz+PFSvA87hsHEYPNgnecDcAMsBgIKsTJ71Ze1imFP182FD0wLgChhCMbURcRi0vARQjR5FJNE8SfhrOY3E41QKPociU7q6sf2t/YXFTKy4qNTL07oLcRRPTlQoOfucQkQS/BNOvqXUdfEdtG+FpJUEvgglEP27Z0+noMdglg02SnL1Gp8lgkwx2qc1mpKAYee12I65H3U4zRjen7G61Sa02CYPgGU6jUGk4MVTQ6nitRiHqBK2O12oUYqig1fHaYF7NEgZjT7fTgm819rV/9/jfv5dy24rYG+CFmODAnyyY+d3ZUz4trthVWTc3IwWXTJZx7Bi2bcO0aVi1ClotysvxxhvYtAmxsYiOxrBzu/HWW2huxsMPIz8fbjd27cKf/4y0NCxYgJHEYfTgkuANaofHADYaA4kNCJ4Znryv/TT6aenrPthRd0NECsY4NobwU6nzCEYCG0UCHiWqlQCD87x1oOhEU+sLa2/H4Jxuz9bS6tf3Hq/vMGJwDCFTk2Pvnp47Oy2JEPhdiCXaX4FLoqb/AWT4iDqPyNIKo+q5FqdKcvQanSaDXTLYJINdarMZKSiunna7EdejbqcF1zin7JYcJslhauxrxyA0nKgTtBpO1CjEUCFQx2s0ClEnBOp4jUahChO0ak7EdafbacF5nLL77zWbS7rr/3P8Sq1CBS8ECPzagolrCybicpjNKCqCIGDFCsTE4JwpU1BTg6++QmUloqMx7NrasHMnfvQjFBQgIADnLFmCzZuxYwdmzsRI4jBqEC6JwivUXUfYaAxiTdLkfe2nMZB19UU3RKTAT1wO5xEMLyaQBDxMVPeBCLjQW/uLntu6jxDUtneNiwhFP919tg2FZe8dPtFhsmBwaoFfMmnCvTNyY4ID4Tc4oroPjJ72PgFqg4+Ip4ntvuefZydV2oIxmrTZu3Hdccguq8eBMcDstpndNgyOZziNQhXKa3WCRsOpNApRJ2h1vFajEEMFrY7XhvBqhjC4pvQ4Lehnf2dZtRdZNZ8AACAASURBVPnMLyesyQlKwrBracGbb+Lrr3FOdzfKyjBrFnp70dmJ0FBEReFfWBbR0eA4dHRgJJw5A5sNqakQRfyLQoHMTBw+DJcL52zbhtZWcBzOqaqC04lhwmH0YBMAFvBgSO46CLMwiBsjx0Wrgs5ae9DPnraas9aeaFUQxjaiXEBNvwY1Y1gQJVHdSwIeAaNFP2/uL/zz1v0AKMWb+4r+Z+UCnKdZ6nn7YPGmonK7y43BJYYG3zMjd3Fuhsgr4OcFopxPWL3c/T3InfBREOd4Lu7I823ZO3qjMWp0Oro9VGYJg+uIW/Ysj53R7bQYneYeZ1+Py9Lj7MOY5JTdksMkOUwwY0AsYYJ4dZAiIJjXhPDqIF4drFCHCJpARUAwr9bxmkA+QGAUGE26XRYMpMPe88PiV9fE3fhQ8gKOsBhGDAOehyjiHKsVLIt/IQSUglL8G6U4hxCMBEJAKSjF+WQZhOBfFAoolVAocI5CAUIwTDiMHkQBLhbuRgzJU4/BMYSsSsz7W/ku9CNT+nFjyY8ybsIYY7PZ7Ha7zWaz2+34RpRmHu/ZhMvFEOUConkSbDQG8sa+wr9s249vfXGq6gfzCqKDtQDKz7a/e6jki5PVHlnG4PLio+6ZnjtvwjiWIfAbnJt6OuzdHfbuNrux3W5ssxvb7EaXa+YPI3YmCyb4SEHkn+lPxPPmNzvTKAhGAQoYnaYwIQjXkQBO+cPUJbiQ2W3rcpjMLqvkNEuOXrPLZnbbJIepy2Eyu22djt4+tx1jj4fKksMkOUyAAYPgGU6jUIXyWp2g0XAqjULUCVodr9UoxFBBq+O1IbyaIQyulG6nBYOQqfx+0+6S7rqnM++KEnUYLpGRWL4c06bhnIYGOJ04JzgYkZEoL0dzM5KTcY7Hg6YmuFyIjMRIiI+HWo2yMkyYALUa57hcKC5GYiJ4HufccAPWroUo4pzNm3HqFIYJh9GEsEnU3YihUHcdwcWsTMh7qXKvU/agn48air6fPotnWFynJEk6efJkRUVFWVlZQ0PD2bNne3t7eZ4PDg4GEBwcDMButyfFWt76Ky4HEWYRzRPg0jCI/7vryP/ZcRjncXvktw4UzRgX/96hksOnmzE4hpBZaYkPz87PjYuC33nc1NPrtBidJoNdMtgkg10y2CSDXeqwd3uojH5+1lTw86jifHUnfESAVbq6KL7vOcNEu8ziClJzKr2o0yt1elGnV+r0oi6E1+pFncAoMJqEhYXNmjUrLi4Ow0rDiRpOxOAcssvssklOU5fDZHbZLG6r5DB3OUxmt1VymLucpm6nRaYyxh6n7JYcJslhghmD0XCiTtBqODFU0OoErYYTNQpRJwTqeI1GoQoXAgM4JYZJj7MPF1Vhan742AtPjl95Y3gWhgXLQhShVuMclQoKBc4JCMDkyTh5Eh98gLvvRlAQiouxezcSE5GRAcDtdjscDo7jBEHAZaCUSpKk1Wr5sDDcdhs+/RTh4Zg5Ey4XPvsMjY34zncQEIBzeB4BAVCpcI5SCUIwTDiMKlwyHLswJHctLipEUN0cPf6LljL0Y3RYv26tWhgzAdcRSZK++uqrvXv37t+/n2GYnJyczMzMhQsXpqSkREdHa7VaDETuuh3ualwCLpVofkaE2RjcSzsPv7TzCPr58MjJDw6fwOCUCm7ZpAn3zcyLDQnC2GZxWw02yWCXDDbJYJcMNslglzrs3R4qw2tWmXvmbP73I8oXBTXBdzM1bVGKg8+endzuUmG4qTmVXtTplTq9qNMrdXpRF8Jr9coQgeVxLQgLC5s9e7YgCLiyBEYhCIpQQZumwWDMbluXw2R2WSWnWXL0ml02s9smOUxdDpPZbet09Pa57RiTzG6b2W3D4HiG0yhUobxWJ2g0nCpU0OoEjZpTaRRiqKDV8doQXs0QBl7odpoxFLPb9svSdxZETvpp+jIly2MkMAzy89HTg5078fTTIASyjORkLF+OsDAAPT09GzduNJvNixYtSklJYVkWvjMYDJ9//nl3d/fatWujo6PJ/feDYfDJJ/j4Y5zjduPhhzF1KhQKjCQOowqXDG/IvZA7wYRhcGsSJ3/RUoaBfFhfuDBmAq59HR0dH3/88aZNm5qbm2+99dZbbrnld7/7nU6ng3eIuJSa/wCfsHoS8H2iWgkwGNzfvz70yu6jGIhMKQYhCOQ7M6feNW1icICIscTithpsksEuGWySwS4ZbJLBLnXYuz1UxnDwUPJiW2aLM+B7YZWEUPgoSWl+Pv7Qr85OrrIF4ZKoOZVe1OmVOr2o0yt1OkGr47Wxqggly+Ma5HF5jn92HAQZszK0YVqPy3P448MMx2TMytDoNBgdNJyo4UQMziG7zC6b5DR1OUxml01ymiSHyeyymd1WyWHucpq6nRaZyhh7nLJbcpgkhwlmDEbDiTpBq+HEUEGrE7QaTtQJWp2g1XCiRqEKFwIDOCUAo9MC72xvK6o0tzwzYe04TRQuWU4O/uM/kJqKfwkPx113geNwTkgIbr0VKSloaYHTiaAgpKYiJgYMA0ClUqWkpOzYseOFF16YOnXqggULIiMj4TWz2bx79+5t27YJgjBnzhytVotzEhLwne+gqgpdXWAYREYiOxsaDQjBz3+O2FjwPP4lPx+//z0EAcOBw2hCuHEUXqHu04QPw+Amh8alBUZU97ajn+NdTTWmjlRtOK5Ze/fufeWVVwoLC++8887nnnsuNzcXviPiUmr5C6gLXug149TpKZn5f9KponBRL+449Mruo/AFr5LFuN70cQGPFRTg+mVxWw02yWCXDDbJYJcMNklymtpskkN2YeR9akzscolPRp0QiAc+CuEcf447/Hxb9o7eaAxOzan0ok6v1OlFnY7X6gStXqmLVUUoWR7XEYZlIsdFFm0uCggMGH/j+Prj9W2n29JnpotaEdcOgVEIgiJU0KZpMCA39fQ4+3pcFslh7nFZepx9Rqe522npcVp6XBbJYe5x9blkN8Yks9tmdtswuABOqeM17Y4eeK25r+PRwhe/P27R0pjpBASXICoKUVH4N40Gubn4N60WkyZh0iT0o1KpZsyYERsbe+zYsaNHj5aUlNx2220FBQUajQYX5XK5jh07tmHDhr6+vsmTJ0+ZMiU1NVWpVBJCcE5UFKKi0N+cOThfbCxiYzFMOIwqXDJAAIohuWvAF+Ci7kyc9KsTX2IgH9YXPj3xNlxrKKVbtmz5zW9+Exoa+uijj7733nssy+KSMcFEmE3tX+PiiIKIaxzyqr3HP3zo8Vm33377k08+qdfrMZC/bT/w+t7j8FpMuNoW0SJEWgihnS47BSUguMZZ3FaDTTLYJYNNMtglg02SnKY2u9HhceKqOmCO7Gqe9mx0YTDngI8URH5Cf2Kc0PNKR0YAF6AXdXqlTi/qdLxWJ2j1Sl2MKlxkBYwBhCEx42PaatsaTzQShtQdr4tIjIjPjucUHK4jHGFDBW2ooE1RYzAO2WV22SSnqcthMrtsktMkOUxml01ymrocJrPb1u00y5Ri7Olz2/vcdvjIKbufr/70YGfFUxPuDOE1uIIEQRg3bpxer58wYcKRI0c+/vjjvXv3Llu2LCsri+d5DKS2tnbdunUNDQ1ZWVlTp07NzMzUarWEEFxVHEYVogIbBc9ZDMldi6Esjsv+S9lOi9uBfj5rPvWTCXPVCgHXjv379//kJz+JjY197bXXJk6ciGEhLof9awyKEOUtRPME2JhILZ5++uknn3zy9ddfnzVr1pIlS55++mmNRoPzvPD1odf3Hoc3CGamJASPsxS7i5X4/xyyq8dpCeY1uEZY3FaDTTLYJYNNMtglyWGSnKZma7vD48RoVWUL+lHTjN/EHovjLfDdkpDGOyLjuODfgqgxhnE8l3lT5p639+x9e29cVlzSpCRRI2LsERiFIChCBW2aBoMxu21dDpPZZZWcZsnRa3bZJKe5y9FrdtnMbluHvcfqccDvPMeNNQ8fe+EXE9bkBifjylKr1Tk5OXFxcVlZWfv373/++edzcnJWrFgRFxfHMAy+1dbWtmnTpqNHjyYmJq5duzY7O1un07Esi1GAwyhDuHHUcxZDoa7TBENQcfztcVnr6gvRT5/b+XlL6ZqkybgWdHZ2PvHEE1VVVS+//PLkyZMxfIhwI2XCIXegH8JPJ5onocjAeZRK5eOPP/7www//5S9/mTRp0m9/+9tVq1bhG899ue+tA0XwEkWnuqnB3YQLtduNwbwGo4zFbTXYJINdMtgkg12SHCbJaWqxtts9TlyD2lzijxunPx1TnKPqgu8Y5z5ZWsMEvwI2GmNYQHBAYESg0+4MTwrXxeoIQ+A3EA0najgRg3PILrPLJjlNXQ6T2WWTnCbJYTK7bJLT1OUwmd22bqdZphRjSaej90fFry6PnfH9cYs4wuIKIoSEhIRMmzYtMTHx1KlTe/bsefbZZ+fNm3fLLbeEhobabLadO3du3LhRFMU77rhj8uTJer1eoVBg1OAw2nDj4NiDIblrAQoQXNTapPwP6wspBvB+/fE1SZMx6m3btu3xxx//6U9/+uabbzIMg2HGEnEJ7XsN5+PGEc3PiHATBqFUKp966qm1a9c+9thjGzZsePXV1149eOLtg8XwRV2VK0JHwFCcp81uTNfG4yqxuK0Gm2SwSwabJDlNksNksEtnrB02jwPXBTWn0os6Ha/VCdpabnEE82mk/DUugbtalpYxQS+Bn4yxynDa0NHQoQ3Ttte1dzR2RKdHw++SCIxCEBShgjZNg8GY3bYuh8nsskpOs+ToNbtsktPc5eg1u2yS09zp6HHJHlxfKOgnLQfKepueyVwbLepwZbEsGxUVpdPp0tPTDx8+/NVXXx08eDApKam6upoQMnv27MmTJycmJiqVSkIIRhMOow03Dt6gZng6wEbgolK0YZNC4wq7mtHPaVNnkdQ8SReH0crj8fzXf/3Xvn37tm3blpycjJFBxBW073WA4hw2kgQ8RlQrABZDSUhI2LJly9///mLBIz8mKVnwkdvGWdtUqqg+nKfdbsTIs7itBptksEuSwyQ5TQabZLBLZ6wdNo8D1wU1p9IJWh2v1Ys6vVKnF3V6pS5aDFNxSlxgHu17jZr/Bsjwldwtdz9AAn9PlLdj7HHYHKe+OhUUETRt2bTCLYV1hXVBkUEBQQHwGxkaTtRwIgbnkF1ml01ymrocJrPLJjlNksNkdtkkp6nLYTK7bd1Os0wprjVVppbvHHv+ifQVcyJycMUJgpCQkBAaGpqTk/PBBx+sX79+4cKFS5YsSUlJCQgIYBgGow+HUYZwKRReoe5awkZgKGsSJxd2NWMg6+oLJ+niMCpZrdY1a9ZERUXt37+f53mMHC4BfC7cdSTgYaK6D0SAD4glKYu0e3BJzI1ald4KQvGtNrsRw8fithpsksEuSQ6T5DQZbJLBLp21dlg9DlwX1JxKJ2h1vFYv6vRKnV7U6ZW6KDEsgFPCK4QEfBdcOu35MagFvqIO2vNTqE4S7c8BBmNJ+e5yu8WePiNdn6bPtGYWbyluPtmcdkMawzDwuxoERiEIilBBm6bBgFyyu9dlNbttZpdVcpolR6/ZZZOc5i5Hr9llk5zmTkePS/Zg9Olz258te++4sfqHqUuULI8rTq1Wjx8/fv78+WfPnp0+fXp2djbLshitOIw2XDLAADKG5K6FMBNDmR89XncqQHL0oZ/tZyv/O7tPJwRglDGZTLfeeuttt9321FNPYeQxmqfBRoMJhC8oxW8/37XuyElcKrdFYe9UKsNt+Fab3QjfWdxWg02SnCbJYTLYJYNNMtils9YOq8eB6wLPcDohUK/U6UWdXqnTizq9UqcXQ9WciMtGhBtJyPtyz6PwtMJ31PoOZAMJ/BNIAMaGttNtdcfrkiYlRWdEMyyTmJtoqDHUFdUFRf0/9uADvuk68R//6/3JJ7PNaNIVOuiihZZCC5S9ZMiuDBHBdThAUXGCeC7UU8+teHqKGwfDhSjrAMumyCqldEEHdI+0TdI2+/P+++P+fh/1OtKmLSTt5/lUaftpwXNLQob1FSt8xQq0zsLZjDaTzmqothiMNpPOatBZDEabSWc1VFsMRrup1mrkKMVVJxEIZQJJo8MiEYhwLRBC5HK5UqmUyWQCgQBujIW7IVIIguAoglP2i2gHISO4MSzxo5zDaMbGOX4oPLMsZizcidlsnjt37qJFi1auXImrQxiLDqIUL2zbt/l4OtqBIYQRORixXSB2MBIHI3awYrtA7GAkDlZiRxMV5hq0rt7eWGbS6awGncVQZtaVmXRlZl2JqarRbkaPIGJYjViplWi0Uo1WotFKNVqJRiv19Wal6FbCAYzmJ67uAVhPoOOoeQ+1z2NU/wYbiV4gICJg/t/nE4YQhgBgBMzoRaMppQzDgOfJxIxQLBb6ihUxcrTIxtn1tkaj3WS0NeqsRp1Fb7SZdFZjtUVvtJl0VmOVpc7GOdB1pALxrD5Jt/S9TiNWgNcOLNwPYftRRxGcofYLBO1yc/jQT3KPOChFMxsLTt0VPUZACNwDpfT2228fM2bMypUr4a4oxfM/793y+zk04SUWqWXiy7nZY4YkxEWE+Su8AxTevnKv8+bcr0t/tcOOdqgw11DQBrup2mKosRrKTLoys67MpCsz60pNVQ12M3oEEcNqxEqtRKOVarQSjVaq0Uo0WqnGm5XhWmF8GJ/PqeFpatoKF9gLOd1ConqNiKegpyMMETACNMEIGPB6ASHD+ooVvmIFWmewNdZa6+ts9Z/k7T5blw9XebGSG0PGLgwZpxDKwGs3Fm6I7QfLb3DKfgGgAIEzWplyfGC/lLJcNFPWqD9UcWFiYDTcwwcffEApffHFF+HGDuTki1j2kWljAxTeAQpvP7lXoEouEwkBpKWl3XzzzW+kpqpUKjvn+NfFH7aXHkO7WTn7DYfWmBxW9AgygThAog6QqLVSTYBEHShRB0jUgRIfb1YGN0RERPkahHHU8ArAoaNoPa29H173EPljAAGP1ysphDKFUNYX/iKGhUsUQtmC4DE3ho6Ts1LwOoiFG2Kj0B60AY5yCLRoh8URw1LKctGSjfmnJgZGww1kZmauW7cuNTUV7m1i/4iJ/SPQkoSEhBUrVtx3330fbvj4hfNfpNfloYNMDis8jYhhNWKlVqLRSjVaiUYr1ahFCo1IGShVExB4FCK7A4IwWvcIaD06jNKG9XAUE+UrIFLweL1Yna0eHaQUes0PHn1T6HgvVgKeS1i4H8L2o2gXar9ABFq0w7iAqL7e6kv1NWjmYPmFy/U1od5qXGuPPPLI22+/7ePjA0/24IMP/pC6c+nRl43UhJ5FyLC+YqVWotFKNVqJRivVqEUKjUgZKFUTEPQURDyBaDZytcvhKEXHUfMOas9jfD6AIAQ8Xm9VY61Hu/mIvG8KHb8geKxEIASvE1i4ITYSEAAOOGW/APF4tAMBFoYNeSNjL5qhwHeFZx4bOBnX1O7duzmOmzlzJjzcvspTXsvijNQEjyVkWF+xUivRaKUarUSjFik0YqVWogmUqgkIegM2htH8xNU9AOsJuMCew+nmE9U7RDQGPF7vQ0H11ga0Q4BEtaTvdbP6DBcxLHidxsINETEEIXAUwil7LtrtxrDE97L2Wxx2NPN94ZkHBkwQC1hcO6+//vo//vEPeDIH5T4v2LH58j54CCHD+oqVWolGK9WoRQqNSKmVarQSTaBETQhBL8f4MD6fU8PT1LQVLuD0tOZuyB8hXsvA4/UyRpvJTh1oU6DE56bQcclBo0QMC14XYeGWiDCKOgrhDLVnE7SXSiSdHhT78+V0NFNrbdxdkpUcGo9rpLCwsLKycuTIkfBYNVbji+e/yNDnw/2wjMBPrNJKNFqpRi1SaERKrVSjlWgCJWpCCHitISKifA3COGp4BeDQYQ5qfAO2LKJ8GUQKHq/XqLXWo3V9pJolfSfO6jNcQBjwuhQL98RGA3vhlD0PsAMs2mdxxLCfL6ejJRsLTiaHxuMa2bJly2233QaPlW24/Pz5z6otelxTLCPwE6u0Eo1apNCIlVqJRivVaCWaQImaEAKeS4jsDgjCaN0joPXoOGreTh35jOoDCILA4/UOtdZ6tCTcK2Bx3+umBiYKCANeN2DhntgYtAe1wp4PNhrtk6AOjlVpM+vK0MwZXVFmXVmsSotr4eDBg88//zy6x1tvvVVWVnbfffdFREQA2L9//z//+c9169ZFR0ejK+yrOPl2zhYLZ8PVwjICP7FKK9GoRQqNWKmVaLRSjVaiCZD4MIQBr6sR8QSi/oaruw+OUrjAlsXpFjCqdRANB4/XC9RajfirCG/tzaETrg9MZAgDXrdh4ZYI25+iXag9h7DRaLebw4c+e+ZXtGRTwakXEmfjWjh37tzgwYPRPTiOczgclFJcwXGc3W6nlKIrUEqtnD1QqrnUUI6uxhKBn0SlFik0IqVWqtFKNFqpRivRBEh8GMKAdzUJBzCarbTuIWo9BhdwNVzNHUT+CPFaBh6vp6u11eNPUd59bgufPNE/noCA181YuCc2FEQKaoJTtlxI0H7JofFvZOw12Mxo5teijFUDp8qFYlxd9fX1Xl5eLMviWrBYLJRSiUQClxBCZmhHTteO+F2X9V1Rytm6i+i0W/teP1QdEyBR+4qUhBDw3ASjIurPYHiFNm6AKxzU+AbseUSxFkQKHq/nqrM2ABioDLsl7LrRvgMICDwcwzAikYhhGLg3Fm5KADYKtnNwyp6NjpAIhMmhg77O+x3NNNqt2y6n3xKZhKtLp9P5+vqiO+n1+oKCArvdDqCoqMhqteJPW7ZssVgsd999NzqBgIzQxI7QxOYai74rSjlUddZBObgqRBYwUBkBnjsSEMXTEA2m+qdAzeg4avqJ2tIZ1b/ARoLH66H6SNXvDrk30ScSPUVISMjChQtDQ0Ph3li4K8L2p7ZzcIbacwg6ZnHEsG/yfqdowbf5J5ZEJhFcVWazWSKRoDulpqZmZWVJpVIAtbW1JpMJf/riiy/0ev3dd9+NrhAtD3kq9vYKc80vpUe3FR0yUSs6rsJcA54bI5I5RBDJ1a2AoxQusOdxuoVE+TKRTAeP1xNN1w5Dj0AptTRYQKBSqpKSkiil5nozYYhQImQYBu6HhdsSRsME5xzl4OrAqNBukXLf4X5hx6sK0UyesfpEVeFwvzBcRWq1uqamBt1p4sSJS5cuDQsLA3D48OF3330Xf3rrrbccDge6VIBEfXfE7MCLzFfpvwrGBFRZ6tARFZYa8NycMJbR/ETrHqLWVLiA1tO6hyC7jSjWACx4PJ5bctgdRzcftZqsQ+cM9Q31NelNe9bvUQepE2ckequ94X5YuC02Bu1D7TlENAIdsThi2PGqQrRkY8HJ4X5huIp8fHx0Oh26k1gs9vHx8fX1BaBQKAQCAf40ePBgdA99VW14teLFEU/9Vnn6+6KUwoZytE+5qQY898f4EPXnML5NG9bDFZQ2bqD2LEb1Dhg/8Hg898MK2cHTBh/48kDB6QKZUnZu7zlCSNTwKG+1N9wSC3dF2AEU7WPPgWgEOmJqn/4BUnmFyYhm9pRmV5qN/hI5rhaWZb29vauqqvz8/NCDnDp1KikpSciw0wKHXx+YdEKX9V3x/rTaC3Am23ChylLuJw4Ez90JiPxxsFHU8AyoBS6wnuCqk4nqbSIaCR6P5340wZro0dG5x3ItDZbS3NL4SfF+ff3grli4LUYJQQAcFXDKloMOEhDmxrDE97MOohk7x31feGZF//G4ikaPHn3s2LHk5GR0gxEjRhgMBpVKhSv69u27ePFitVqNbnb06NGHHnoIVxCQ4ZrY4ZrYvPqS74v27688Y6cOtKKR43xFAeB5CCKdS9i+XO0D4KrgAk5Ha5ZC/gjxugcg4PF4biZmdMzl9MupP6QOmTkkOC6YFbFwVyzcGGFjqKMCzlB7DkGHLQof+lHOYTvHoZktBaeXx4wVEAZXy9SpU7dt25acnIxuMG7cODQReQW6WUlJicFg6Nu3L/6kt9UWNRaUm4uDZPqRviTHWF9j8XJQgmYohc5q8BUrwfMUwkTG9yeu9gHY0uAKBzW+AWsaUb0KIgePx3MnnIOTeEvEXmK5n1wkE8GNsXBnbH9YDsIpey7gAAToCH+J/LrA6D2l2Wim3GRIKcud0qc/rpbk5ORVq1YZjUa5XI4e4fMvPr/13sUZ+tNFjflFpoLLDXlGux5N+ImhFjXqrVKdRWajAvxVhbnGV6wEz4Mw/oz6a2p4npq+g0uoZS/VLWBU/wIbDR6P5x44B5d/Kr+uvK5vfN+SzBK/UL/QQaECVgC3xMKdCWPQHtQMexHYMHTQ4ohhe0qz0ZKNBaem9OmPq0UkEs2fP//zzz9fuXIlPJONs5aai4obC0tMBZcbCsonXxSImY/zM9E6AeHU4gYfUaPeJtFZvCwciz+Vm2vilOHgeRYiIsqXIBxEjS+A2uACeyGnu5EoniPSBeDxeG6gtqw291hu8IDgmDExqT+k5p3KU2lVqkAVIQTuh4UbI2wMRbtQezZhw9BBo/wjwrw1hfU6NHO0Iq+wXhfmrcHVsmbNmlGjRt1xxx1KpRKewORoLDMVFZnyixoLys3FpaYiB7XjTwIxg/YhhKpEJpXI1OgQ1lqUBpuQglaYa8DzTES2iLARXN1D4KrhAmqm+idhO0/kT4IIwePxrh1LoyXjtwyxlzh8SLgyQDlo6qBjm49dOntJppSJZWK4HxbujI0EEYFa4ZQ9F5iODiLAovChr577D5qhwOaC00/ET8XV4ufnt3Tp0rVr17799ttwb9nG9E2XP661VqNLyQS2aX2HDlFd/11RSrVFD57nEiUxvlu5uodgPQWX0MavqS2DUb0LgRY8Hu8aaahrIIREj4xWB6sBaPtp+43sZzKazEazWCaG+2Hh1gQQRMCeDafs2XDJgrCEdzNTzA4bmvmh8MxDsRMlAiGultWrCzeDrwAAIABJREFUV48bN2779u2zZs2CG4v2jpMJvGpRjS5FQMb7TfMXa58YcIuFs4Hn0Rh/Rv01Nb5NGz4GKFxgS+OqZxPlS0QyHTwe71pQ91GPv208moifEg83xsK9EWF/as+GM9SWSeAKhVAyMzjux0tpaMZgM+8szpzXdzCuFqFQuGHDhlmzZg0aNCgkJATuiiGCm0PveTv3WY5y6DqxykR/sRZXiBkheB5PQOSPQ5RA654ANcIF1EjrHoLsNiJ/AkQIHo/HaxMLN8fGoD0cpeBqwfig426NHP7jpTS0ZGP+yXl9B+Mqio6Ofvvtt6dNm7Z//35/f3+4q1BZ5DjfaQeqdqLrTPCbDl6PQ8RTiOYHru4B2HPhCkobN1DbaUb1DgSh4PF4vNaxcHPC/mgfas8molHouFhV4ECfPhm1pWgmvbYko7Z0oE8fXEWzZ8+uqqqaM2fOjh07NBoN3NXsPosy9Kd01kp0hUBJcLR8IHg9EhvGaL6nhuep6Qe4xpbBVc8lyheJZBZ4PB6vFSzcG2HjKNrHdh6iUXDJ4vBhT9VuQ0s2FZz6h08fXF1Lly4VCARjx4795ZdfoqKicLVQ00/g6ohoGISxgABtEjHiG0OWfpT3KrrCBL/pBAS8nopIiPIVCOOo8RVQG1xA62ndI5CdJPI1IGLweDxeMyzcHKOCoA8cpXDKlglXzQoZ+FrGHr3VhGZ+LTq3auAUpUiKq+v222/39/efMWPGhx9+OHnyZHSPanN9Qb0uQR0sZAT4g+U3at5NARAphAOIcBjEo4lwCIgELYlVJMTLk84ZT6BzWCIMkYWD19MR2a1EOJCrWwlHOVxCG7+httOM8i2wkeDxer2UirTc+uLlkbPBu4KF2yNsLHWUwhlqzyRwkUTAzgsd/MXFVDRjdti3Xk6/I2oErrrp06f/+uuvS5YsmT59+tq1a4VCIbravrKcdzNTBquD/zXyJgFhqKMS/0VNsJ6m1tNoWE8hgHAAEQ6BaCgRjQajxJ8yMjI+WvHNmDf6UyGHTrBT25s5T0fLB473mx6nTCQg4PVUwgRG8zPVP0Yth+EaWxanm0fkjxHZHeDxerF9FWdeyfzWQTmO0vui5oAHsHB/wgGw7IVT9kLQRhAZXLIkYtiGvOMcpWjmm/wTt0eNILgGYmJijhw5smbNmqSkpPfee2/cuHHoUkcq82ssjSlluY/8/sPbw28kXAVa4IAtg9oy0LiBQgA2nIiGWriB735w7Iuvdq9fv56JsGwp+hSdQ0FzjOdyjOf8xIHj/K4fpZkkYsTg9UiMD/H5FA0fU+NbAAcXUDM1vATrcaJ4GYwKPF7vs730+Js531FKAWy5vN+LldweNhW9Hgv3J4xFu3CwZUM0BC4J9VaP9As/WpmPZi7X1xyrzB/tH4FrQSKRvPPOO6dOnbr//vujoqLWrl0bFRWFruCgNLWqEFf8pyTrqdPb/hGkY/D/UEoIoWiBA/aL1H5RhM2r7sTjdwcz4l+ocOhJr9D8hsvoClWW8h+LN+ws+364evxE/1lqkS94PRAhXsvARlP9KnB6uISa91LrWaL8JxGPA4/Xm2wrOfpO7o+UUvzp8/xdAsLc0ncyejcWbo+wcRTtQu2ZRDQErlocMexoZT5asjH/1Gj/CFw7Q4cOPXr06DfffHPDDTckJSU9+eSTMTEx6JxztSUGqwl/2nrprMw66OnwEwDO5QZU6rynjL6INhGumJqKYdq6yEv8esNAO7qMydF4oGrXwardscrECX7TY+Tx4PU4RDyRaH7m6lbClg7XcFW09m7IbiPyJ0CE4PF6gS2X93948VcKir/6JG+HgDA3h16HXoyF+xMEgvEFVw2nbJnohEna6ECpotxkQDO/leWUmwyBUgWuHYZhbrvttiVLlmzcuHHJkiUqlWr58uVz584ViURwyeGKPPzVt2UxLLg14afCQ2ofe2lGYZHqrptOEULhjL/AMtm7bHe9Fl2Kgp7Xnz6vPx0sDRvjOyVJPU7IiMDrSQR9GPU31PgP2rgZLqK0cQO1pTGqtyAIBY/Xo2289Nv6vO1oxfqL26UC8Q1Bo9FbsfAERNifWg7DGWo/T+A6AWEWhg15L2s/mnFQ7vvCMw8MmIBrTSAQ3HrF77///tFHH61atWrixInz58+fNm2aRCJBRxytzEczG8oGKFjbipD0oADDpl8HFRT7PLViv0xqgzNT5GVpZp8KuwTdoNhUuLnokx1lW0ZoJo7zm6YSqsHrMYiYKF6EaBw1/B2cAa6xpXPVc4j8USK7HSDg8Xqiz/N3bSjcg9ZR0Hdzf/QXq0b5xqJXYuER2DhYDsMp+0VQK4gIrropfMi/cw7aOQ7NbC44dW/MOJZh4B6GX2E2m/fu3fvDDz889NBDYWFhEyZMGDt2bEJCgp+fH9pUb7Ok15agJf8qGiRiHNER1cXlyuNpIY/+Y9YLj+7119SjTSzoQuWl93UxFN3FaDfsrdiWUrkjXjnsOv+ZYV79wOspiOR6Iozj6h6BLQ2uoSZqeAmWg0TxMgQB4PF6ls/yd31VuAfODFJGJPhEordi4RGEA9Ae1Ab7BQjj4Co/ifcUbf9dJZlopspcv68se1pQLNyJRCKZfQWArKysgwcPfvXVV6tXr9bpdNHR0VFRUVqtNigoSKvVisViHx8fQohUKm1sbDymL7JzHFrx9qWEeX6luOLiZfX9z81Zu/K3uOgKtClSVD9cVn280RfdyUHtaXWpaXWpkd79x/tNH6QcxhABeD2AIIjRfEuN79CGjwEKl1DLIaqbReTPEmkyeLwegYJ+cGHb90UH4cxwTf8X4v8mZoTorVh4AiKMpWgXas8kwjh0wuKIYbtKMtGSjfmnpgXFwl0NuGL58uUA7Hb7xYsX8/LyysrKSkpKTp8+XV9fbzabTSaT2WxWqVSlSUGIUqMVFGQ7E6zB/69WL338lekPLz06bfwFtClZUZJpVho5IbpfXn12Xn22QqgarZk83m+6F+sNnsdjifxxiBKpfg04PVzDGaj+cVj2EcULYJTg8TwZBX0vd+tPxYfhzEjNgOfj/yZiWLRPat7lzw6enB4fMzkuUimVoEdg4REEfUHkoEY4ZcuEFJ0xwi8sSuF30VCFZlKrCi4aqqIUfnB7LMv2vwKtuH73e7qGWrTO6kvBUHAEV9jsgtc/HldY4nPPopMMw6EVMmKfqyj+qi4czgz1FkWpbjxQfbDcXIxOMNjqdpX/sK9yW4Jq5OSAOVpJCHgejognE802Tv8IrKfhKmreSa0nifIlIp4IHs8zcZR7I/u7nWW/w5mJ/oOfiruFJQK027YzWYcvXDp84dLan5nRUX1nDY6ZkzAAHo6FZyAQ9of1BJyhtkyCzloUPvSls7vQki2Fp/8+aBo8XFFD7eWGWrSJsrCpIaxGU9/tGFhYrHrq/v3eMitaMURac9KkybIo0KZJQWuDZeGj/GbnGjMOVO3K1J+hoHCVjbOdqDl0ouZQhFfMBP/pg5TDGcLAndTU1JSVlRUXFxsMBpPJZDabLRYLIUQkEkmlUolE4uPj0+cKlUoFnkDLqL+mxndpw8cAB9dwVbR2OWS3EPkqECl4PI/CUe7VrE3/KT8FZyYFJP49domAMGg3i92+LzMPV9gd3MGcAgBzEgbAw7HwEISNpdYTcMqeDTgAATphbujgt87vM9ltaOanS2mPxE6SskJ4ssMVeWgHmz8VVhP81Yn04AeeS37x0T0hWj1asVB56dWqOAtl0IpI7/7BsnAABCRGHh8jj6+ylB+q2n1Ml2LlLOiE/Iac/IIcX3HAKM2kMb5TpAIZroWSkpLU1NTz589nZGScP38+Pz/fbDajfaRSab9+/WJjY+Pj4+Pi4kaOHBkQEIDeiCXyxyAeS/Wr4CiHiyht/JpaDjDK1yAaCh7PQ9g5x4vnvz5YlQ5nZvYZ8VjMQoYQdERKVr7RbEETswf3h+dj4SmEsWgPaoK9EGwkOkEuFM8Jjt9SeBrNGG2WX4szFoYlwpMdrcxHO1j9OVkmg2aKyxUrn5/97IO/JcaVoSU+Aus0eek2QzBaMcFvBv7KTxw4P/iOmdqbjtfs31+5s8ZahU6otlT8UrrxP+Vbh6pHT/SbGSDpg+6n0+l27NiRkpJy8ODBvLw8uMpkMqVfsWnTJlzRv3//8ePHT5w4ccaMGSqVCr0JEY0gvtup/llq3g6XOYq4mluJ113E+yEQIXg892bnHM+f33C4KgPOzAka9XD0AoYQdNCvZ7PRhETIToqNhOdj4SGIMI6iXajtPGEj0TlLIpO2FJ5GS77NO7EwLBEey0G51KoCtIPNn6IVxgbxmten37v4+LxpmWjJBFnlGZNPkc0LzahFvvHKoWiJRCCd4DdjvN/08/ozB6t25RjPoRMsnOlo9b5j1b9FyweO95sep0wkIOhq5eXl33///U8//XTgwAGHw4FukH3F+vXrRSLRpEmT5s+fv2DBArVajV6CyInqbZgmUMNzoCa4yEEb1lPLfkb1Btj+4PHclcVhffrcFydrcuDMDUFjHoqZR0DQQQaT+XBuIZqYEhslEwnh+Vh4CjYSRAJqhlP2DCAZndNfGTBYHXy2phjNZOnLz9aUDFYHwTOdrSkx2ixoB5sPpSyIHS1yOMj7X48sKlfef2uqQEDxVwyhi5SX3tLFchT/Y5zfNIYI0DoCMlA5ZKBySLGp8Ej13hM1h2ycFa6ioDnGcznGc/7iPmP9pozSTBIxYnSFU6dOvfvuu5s2bbLZbLgqrFbrrisefPDB5OTkZcuWTZkyBb0Dkc4lwkGc/lHYMuEyey6nW0i8HyRedwMMeDw3Y3ZYn0r/7HTtBTizuO+kZZGz4JLdGResdgeamJXQHz0CC48hANsPtnNwhtrSCbrA4ohhZ2uK0ZKNBScHq4PgmY5W5qOdGFj9qLiMoHXb9g6QSuz3LDqBZoKEpvFetfvrfdCEiBGP1ExE+wRLwxaF3D1Te9Nx3f5DVbvrbDXohEpL6Y/FG3aWfT9cPX6S/2yVSAOXOByOTZs2vfTSS1lZWbhGLBbLd1ckJiY+88wzc+fOJYSgx2MjGPUWWv8GbfgSoHANtVDjG9RyiFH+E4Ig8Hhuw+Sw/D3907TaPDizuO+kZZGz4KrtZ7PRhFIqGR0Vih6BhecgwjhqOwenbFmAAxCgc2YGx71+bo/O0oBmdhRlrB44VS2WwQMdrshDu9n8qbiMoBUKb8tdN52cOTEXLRImzgp7+VzuOp21En8arh4vE3ijI+SsYkpA8nX+M8/pT6ZU7ihsuIBOMDkaD1TtOly9J16ZNMF/eoRXDNqNUvrtt9+++OKLOTk5cA9nzpyZP3/+4MGD165dO3fuXPR4RETkf4f4OqpfA0cZXGY9zlXPJN73E6+7AQY83rVWbzc9kfZxpuESnLkzYvptYVPhqkpD/anCEjQxY1CMUCBAj8DCgwjjgU1wippgvwg2Bp0jYgRz+w7+NPcomrFyjq2Xz97ZbxQ8jcFmPldbinaz+XEAg2YIoZNH5917y+8quRnNESHxfoh43S0Cc2PI0o/yXsUVBGS83zS4REDYBNXIBNXIosaCA1U7T9cedVAHXOWgjrS61LS61BBZ+AS/6UN8xgiIAG1KT09fsWLFkSNH4H7Onj07b96866677l//+ldsbCx6OiIaRXy3U+OrtHEzXEZN1PgGtaQwipfBhoPHu3aMdtPqtI+yDUVoEwFZ0S/5xpDx6ITtZ3McHEUTswfHoKdg4TmIcBBFu1BbOmFj0Gk3hw/9/MIxjlI0syn/5N+iRjKEwKMcrypwUA7tZgugaAmJsi2986RKZEZzgj6M6n0I43BFrCIh0WfUmdpjAGIU8QGSIHROiCz81r4rkvssOVK991D17gZ7PTqhqLHg60v/3la6cbRm8ni/aV6sHM2Yzeannnpq3bp1drsdbiwlJWXIkCFPPPHEM888w7IsejbiTRQvQjSWGp4FVwuXWU9xuhuI9wPE6y5AAB7vqquz1j+W9mF+fRnaREAejJ47L3gsOufXs9loQquSJ/YNQk/BwoOwUSBSUBOcsp2DdCE6LcTLZ4x/5KGKi2jmckPtkcq8cQFR8CiHK/LREXY55aSUMRFcQUWgAGOF44Lojj0zv5663Vdkwv+gVgj80cSC4DtyDOmNjoYJfjPQRRRC1QztjVMDbzhTe+y3yl9LTUXoBIOtblf5D3srtiX6jJzkP7uPNBR/ys7OXrx4cVpaGjyBxWJ54YUXdu7cuXHjxsjISPR0RDKNiIZR/TPUshcuo2ZqfIOa9zLKl8FGgce7imqsxsfOfFjYUI42MYR5vP/CGdrh6Jz8qpqs0ko0MSdhACHoMVh4EgGEA2A9DWeo7RxB11gcMfRQxUW0ZGP+qXEBUfAoRyvz0SEEVn8quURAYIrmDKMcolLi8x+WAKZ98uV9Jn8zeJeEsaMprpqre5RRfwEIcIWcVSYHLdlX8csAxWB0KZYIk9Tjk9Tj8+tzDlTtStf/zlEOrrJT24maQydqDkV4xUzwnz5ImfTN19/ee++9jY2N8CgnTpwYNmzYl19+mZycjB6P0RCfD2DaSg3PgzbAZbY0rjqZeN1JvB8CEYLH636V5tpHz3xYYqpGmxjCPDFg0fWBw9Bpv6Zl469mDopBD8LCoxDhIGo9DadsOaBmEAk6bWJgdJBMVdJYh2YOlOeWNNYFyVTwEJfqa4oaatFBNl8qqKf6cQ6rlgNgiqSqcBspEAqryIKKyxLGjuasx6nxLSJfhT+N1FwXIA4iIOgeEd4xEd4x1ZaKY7rfjlTvNTka0Qn5DTn5BTmsWXww5QQntMMD1dXVzZ8/f926dStWrEAvQKRziSiJ06+B9ThcZ6cN66nlAKN8BcKB4PG6U7m55tEzH5aZdGgTSwTPDLx1vN8gdIWd6TloIibQNzrQFz0IC88ijEe72GHPhjABncYQclP4kLfP/4ZmHJR+V3jm4djr4CGOVOaj4xoGOozDHBLWPkZROUZVNlpVpoy23fnEAouV3fTj4OtHXPT1aUQztOFjsOFEeiOuICAR3jHoZr7igDl9Fk8JuOG4bv/B6t06SyU6wS6xjH5w0LA7Y7O25R988wzlKDpOLpfHxcUNHDhwwIABQVcEBAQolUqhUCiTySilJpPJYrHo9fqKiori4uKSkpLMzMyMjIysrKyGhgZ0gsPhuP/++8vKyl588UX0BoIgRr2BNm6hxpdBTXCZPYfTLSRedxHvlSAi8HjdoLix6tEz/66y6NEmlhE8F3f7WL+B6Appl8su6erQxKzB/dGzsPAoRBhP0S7Udo4IE9AVFoYNeT/rgJVzoJktBadW9B8vYgTwBEcq8tBx8QHVK0PShiiqxIwD/yXD4jnpX/wwpNEk/Gjj8KdW7EdLqOF5wkZBmICrSyqQTfSfOcF/Rq4x40DVrkz9GQoKV4m8WFWYnHIU7SaTyaZMmTJp0qQJEyYMGjSIYRi0TiKRAAgMDIyJiUETdrv99OnTBw4c+O2331JSUiwWC1zyj3/8QyQSPfPMM+gVCJEtIqKhnH4VbOfhOgdtWE/NuxnlSxANB4/XpS43Vj565t86iwFtEjLs2oG3j/aNQxfZfjYbTRCCGYNi0LOw8CyCvmBU4OrglO0cuohaLJsaNGB7UQaaqbE07inNnhUcB7fnoNzv1YXoODtHRqnK8Vc3z0lPORZxqVSVcizi+jEXkwYXozlq4WrvZzTfQ6DFVUdAYuTxMfL4Skvp4ao9x3QpVs4Cl6R9m4t2EIlEc+fOXbRo0fTp02UyGTqHZdnhV6xatcpgMOzYsWPjxo3bt293OBzooGeffTYgIGDZsmXoJdgoRvM9bfiUGt8B7HCZ4xJXczuRLSTyJ0Fk4PG6wsX6klVn1tfZ6tEmsUD0UvzSoepodBEHx+08l4smhvQNCvJRoGdh4WEIYeOo9QicobZ0gi6zOHzY9qIMtGRT/slZwXFwe2d0xUabBa2QMHZfkaXY7IVmshrVOptEIzSjCVbArVx69PGXZ1BK/vXVyI9jfxIJHWiOq+Lq7mPUG0GkuEb8xX3mB98xQ7vw95oDKZU7aq3V6Ii6y8bLx8rRpsDAwJUrV955550BAQHoBgqF4uYrioqK1q9f/8EHH9TU1KAjVqxYERkZOXnyZPQWAuK1jIhGcPrVsBfAdRxt3EwtR4jyJSIaBR6vcy4Yix9PW2+wNaBNUoH4pUF3JvpEoesczC2sqW9EE3MS+qPHYeFxhPGwHoFT9gJwBjAKdIVhvqHRCv9cQyWaOVF9KddQGa3wh3s7WpmPZpQiaYI6KNm/ZoL0g/MNmjsypqIZjpLjdYEz/QpxBRHGUFsOgMH9y68blf/b0ciSCsWmXwfdPu8MWmTLpPrVRLUOILh2pALZBL8Z43ynZRrSDlbtyjGeQ/ukfZtLOYpWBAQErFmzZvny5VKpFN0vJCTkxRdfXLVq1bp169588826ujq0j8PhuP3228+ePevr64veQziY0Wylxtdo47cAhcscxbTmb5AtIvLVIN7g8VySbShafXa90daINnmz0lcT7olV9EWX2nrqPJoQCgTXD4xGj8PC4wgHoV0otWcS0Uh0kZsjhr2QtgMt2Zx/6pmEGXBvRyrz/CTeOkujRCBIUIdM6zNggrZfoFQBgBpfow32RO8qb4Gt3iFEM4f12pl+hSASIn+MyO5A3UPUvBPAfUt+/z0tpL5RtHHboOtG5odo9WgJNe9G/b+J9wpcawxhBiqHDFQOKWosOKrbd6LmoI2zoXXWBlv29kK0hGGYe++996WXXlKpVLi6FArF008/fc8996xevfqrr76ilKIdSktL77zzzm3btqFXIVKieA6SqVT/NBzFcB2ljZuo+TeieIZIpoHH66D0uvwnz37S6LCgTXJW+lrC8v6KEHSpukbzgZwCNDGxf7hKJkGPw8LTEGE8RfvYzkE0El1kbuigtzL21dstaGbr5bOPxE3yForhxt4beZMXKy5uqI1WBhD8FVcJgGW4JGVFSk0wmjlc14cKBwlUb0AQBoAoX6H2XNjzfJSmpQtPvfflKJtd8N5XI19bvRutoPXvgg0jkplwDyGy8EWyu2cE3nikeu/h6j31dgNacv6nfGuDDc2EhoZ+8803Y8eOxbUTEBDw5ZdfLlmy5I477qioqEA7/PLLL1u3bp07dy56GSIaTXy30/r3acOngAMu4ypp3YMQTySK5yAIAo/XPmm1eX9P/9TksKBNKpH3mwn3Rnhr0dW2ncm02h1oYt7QOPRELDyOIACMP7hKOGU7h64jY0VzQuM35p9EMw1266/FGTeHD4Ub85fIAcQoA9CcoxJXjFGVptQEo5lqqzSPXRct6IP/IjJG9S6nWwhqSp6cve9IZOZF/9Pngg4cj5gwIh8to1T/JBGEQjgQbkMhVM3Q3jg18IZjZSmfpv5LGe6FJihH0zdfQDMzZ878+uuvfXx84AamTZuWlpa2cOHCw4cPox3WrFkze/ZslmXR2xApkT9OJJM4/VOw56ETqGU/rT5OvO4m3vcBLHi8Nh3XZT977nMrZ0eb1CL5m4n3hnkFohv8dDoTTWi8ZWP7haEnYuGBiDCeWvbBGWpLJ+hKt0Qkbcw/iZZszD95c/hQeCbKleOKscoytOJw5aVoZR/8HzaaKN+gdQ8Swj1wR+oDz83mOOb9r4cPiy/2klnRImriau9i1JvAhsOdsES4/9PjXz77S58Ev8GLoyMnBTMCAiD/QIm+pB5/ddddd3344Ycsy8JtBAYG7tmz55Zbbvnxxx/hTE5Ozqeffrp8+XL0TsIhjGYrbVhP6/8N2OEyaqL171HzHkb5IoSDweO14lh15nMZX9o4O9rkL/F5K/HeIKkvukFmaWVOWRWauCExlhUw6IlYeCJhPCz74JSjFJwOjAZdJErhN1QTekp3Gc3k6CtO64qGaELgiRyVuCJUagyR1BeZvdHM4Yq8O/uNQhNEMhXeD9D6ddFh1XMm5/y8Z0BNnezLHxNX3HocreFqudq7Gc0mMH5wG3a7/cMPPwRQmlZVmlalCPKKXxAVNy/y7MZc/NVtt9328ccfE0LgZiQSyZYtWxYtWvTDDz/AmXfeeWf58uXotYiYeD9IJFM5/ZOwnUdn2LM53SIiW0jkT4B4g8f7q/2VaS+d/9ZOHWhTgMTn7cT7tFINusdPp87jr+YNjUUPxcITCePRPtSWQcQT0HUWRww7pbuMlmzMPzlEEwKPQ+tBG/Gn0crSzeZoNHNKd9nssEkEQjRBvO+HPZ+af71r4cnDJ/vqamVb9wyYOvZivzAdWuMo4mruZDTfgsjhHnbu3FlaWoo/GUoajqw7+/sn522NdjQxffr0zz77jBACtyQQCL7++uvi4uLjx4+jTdnZ2ampqSNHjkRvxvZnNN/Thk9p/TpQK1zH0cbN1Pwbka8i0rng8f60r+LMK5nfOiiHNgXL/N5KvM9PrET3sDkcO9Jz0MSgkMBIfw16KBYeiAjjKQhA4ZQtHeIJ6DrTgga8ku6lszSgmV0lmWsGXa8Re8GzOCrRxBifss0V0WjG4rCfrL48NiASf0GI8mXquCxD+r2Lf3/pg4kcx7zz2Zj31v7KMBxaY8+htfcTn09ARHADX3zxBZqxNdrRRGBg4JdffsmyLNyYRCLZuHFjYmKiXq9Hmz7//PORI0eitxMQr2VEfB2nfxK2dHQGV0X1q2HeSRTPQhAEXq/3a2nqWznfU0rRplCZ/1uJ92nECnSb3zLzahtMaGL+0Dj0XCw8EaOCIBiOIjhlO4MuJWQEC8IS1+ccRjM2zvFDYdqymDHwKJSrxJ8clJwzagAKEDRzpDJvbEAk/geRMD7/5nTzrxuV/58jUSfOBucU+O7YHz17UjZaR62p0D9BVG8CDK4ph8Oxb98+OPPmm2/6+/vD7YWHhz///PMPP/ww2rR7927w/ovtx2i20MbvqPFlUBM6gVpSaHUq8b6PUmclAAAgAElEQVSfeN0FCMDrrbaVHH0n90dKKdoU5R30euIyldAb3en7kxloQiJkZwyKQc/FwjMRYTx1FMEZak0jcAACdJ3F4UM/zT3ioBTNbCw4eVf0aAEh8CCOcvwXG/7GpWlfltSjFYcq8p6IRwsYP0b1b67mlgduS70nc57VJvh487BRQy5pVCa0jpq3wxhI5E/gmsrIyNDr9WhTQkLC4sWL4SHuu+++t99++9KlS2jdpUuXSkpKgoKCwPt/GCJbRMSjqf4pak1FZ1ATNb5BzdsZxYsQDgKv99l8ef+HF3+BM/3kwW8kLFMIvdCdSmoNxy5eRhNTYqPkEjF6LhYeSjgY5h1witbDngc2Gl1HK1OOC+i3vzwXzZQ16g9VXJwY2A8ehKsEQKRziWJtYO1ZYA9acdFQVWYyaKUKNCccSJT/DKIPL5qV/tXWxIZG0cebktbcexBtog2fgvEnXktx7Rw9ehTOLF++nBCCjvruO+zciRUrMGwY/pCdjQ8+QL9+ePBBNHf6ND74ALt3w2LB8OF4+GGMGwexGB0nEonuuuuuZ599Fm06evTowoULwfs/ghCi/hKNW6jxn6AN6AxbFqe7icgWEvkaEC/weo2Nl35bn7cdzsTIQ15PWCYXytDNvj+ZwVGKJhYkDUSPxsIzEVEiRbtQaxpho9GlFkcM3V+ei5Zsyj85MbAfPAi1E58PiHgKgCTfvmjT0Yr8BWEJaAmRzIBX5pIbPtl/PKKoTLn3SNT08RcSYsvQJmp8FYwPkc7FNXLhwgW0iRAyf/58uIDjYLeDUvwXpXA44HDgf1CKQ4fw2msID8euXZDLsWED1q7Fo48iORksi45bsGDBs88+izZduHABvP9FiGwREY+lhmeo5TA6haONm6nlIJH/nUimgdcLfFGw+8uC/8CZQaqIVwbfLROI0c0cHPfTqfNoIkStGh4egh6NhYdiY0HEoBY4ZTsD3IQuNT6wX19v9aX6GjRzsOJicUNdsJcKHoJ43wswuGKASqsQSgw2M1pxpDJvQVgCWkHkj4q4igdvS1392jQA73w+5uNXfhKyDrSFo/onQVgimY1rQafToU0RERH+/v7oPhYLfv4ZffrgwQcRHY0/rF4NnQ579iAuDjEx6LgBAwaoVKq6ujq0rrq6GrwWCYKIz2cw76SGF8Dp0BmOMlr3IEQjieJZsFHg9Vyf5u/8unAvnBmsinxl8F1SgRjdb392QaWhHk3cNDyeEPRsLDwUEYGNg+00nKG2MwRdjAALw4a8kbEXzXCUbi449djAyfAYDP4kIGSIJmR/+QW04nBFnoNSASFoGSHKl4cOWzZhRP6B4xHF5YrvdgxcknwWTjho3Wr4SIl4Mq66qqoqtCkkJAQua2zEpUtQKPCHggIYDGiupASXL2PkSISH479EIiQmYtcuVFQgJgYdRwgJDg6uq6tD66qrq8FrHZHMIKLRtP492vg1wKETqDWVVicT2RIifxREBl7PQkHfv/DzD0WH4MwITf/n4/8mZoS4Kr47cQ5NCAWCeUNi0dOx8FhElEBtp+GUvQBcHRgVutSCsIT3svZbHHY0833hmQcGTBALWHigJN+++8svoBUGmzmzrizepw9axRLVeyv+tvREuq3RJPzm58ETRxT0CTDACTutWwnV+0Q8EVeX2WxGmyQSCVyWlYVXX4VCgT80NMBgwNCh+B8WCyiFWAyBAP9HJgPHwW6Hq2QyGdrU2NgIXtsYJVE8TSTTOcOzsF9Ep9hp4wZq2U28HyPSueD1FBR0Xe5PW4uPwJlRvrFrB94hYlhcFeX6+iMXCtHEpNhItbcMPR0LzyVMRLtQaksn4vHoUj4i2fSg2J8vp6OZWmvj7pKs5NB4eKDhfmFo0+GKvHifPmgD8fKLeH/pwlXvb+hvsbLvfDnqtdW74RS10bqV8Pk3EY3BVaRWq9GmmpoauGzQINx1FxIS8IfcXHz2Gf5gMqGoCNXVkEoREgIfH3h5obISBgNUKvyB41BSArEY3t5wlU6nQ5s0Gg147SEaxvhuow2f0fr3QC3oDEcF1a+G6SeieA5sBHgejqPc69lbdpWdgDMT/ROeilvCEgGulh9OnnNwFE0sTBqIXoCFxyKiRIr2sZ2BeDy62uKIYT9fTkdLNhacTA6NhweKVWnlQrHRZkErjlTm3dd/HNrG+M1f/HzKsQ8yL/icPhe092jUlNEX4RQ109rlUK0j4km4WjQaDdqUlZXlcDgEAgFcIBRCqYSvL/5QVQWxGH/Q63HiBHJyUF+P8eMxdSqGDEFqKvbvx8SJEAqRk4PUVAwYgJAQuKS+vv7SpUtok5+fH3jtxRKvZUQyjerXUusRdA61HqPVs4lsCZE/CiIDzzNxlHs1a9N/yk/BmckBiU/GLhEQBlcLR+mPp86jiWAf5cjIUPQCLDwX4w9BHzhK4ZT1DLpBgjo4VqXNrCtDM2d0RZl1ZbEqLTyNgJAhmtAD5RfQijO6YqPNIheK0SbC9n304eR7HzpgtzMffDViWHyxSm6GU9RK6x6Eah0RT8ZV4e/vjzYZjcbTp08nJSWhq6hUmDcPEgm+/RYVFWhsxOzZqKnB9u04fx5CIfLy4OeH2bMREACXHDp0yG63o01+fn7gdYigL1F/DvNOangeXA06xU4bN1DLf4j3o0Q6FzxPY+ccL5z/6lDVOTgzq8+IR2MWMoTgKjqYU1BWZ0QTNyYNZAhBL8DCkxFhAnWUwhlqO0vgAAToajeHD332zK9oyeaC088nzoIHGu7b90D5BbTCQbnjVQVT+vSHMxHRYxbckLf5h1JDvfjjTUmr7jmE9qA2WrcSyneJZAq637Bhw+DMhg0bkpKS0FEDBoBhoNXivzQaTJsGjQYSCf5gMMBggLc3ZDL4+eGee5CaitxcmM0YMQLjxiE8HAwDl3zxxRdwJikpCbyOI5IZRDSa1r9BG7cAFJ3hKKf61TDvJIqnIQgBz0PYOcfajA1HqjPgzJygUQ9HL2AIwdX1bepZNCFgmLlDYtE7sPBookSYd8Ap2gD7RbAx6GrJofFvZOw12Mxo5peic48PnCIXiuFpkvz6ok1HKvOn9OmPdvjb0sUHj7xXVm79z6GoKaMvJsaVoT2ojeofAl4nkpnoZmPGjCGEUErRui+++OLvf/+7VqtFhwwahEGD8H/8/ZGcjP+yWHD4MCwWjBsHLy/8ITgYN96IrpCbm/vTTz+hTWKxeMiQIeC5hlESxYtEkswZnoU9D51DLSm0+hjxuod4LQMRg+feLA7r0+e+OFmTA2duCp14b9RsAoKr67Ku7uiFS2hi0oAIf4U3egcWnowIh1C0C7WeIWwMuppEIEwOHfR13u9optFu3XY5/ZbIJHiaOJXWmxXX2y1oxaGKi2gfsVj48EPznnhyM6Xk3S9Gr395q0joQHtQG617FAoDkd2M7uTr69uvX7/c3Fy0rr6+/umnn/7000/RJTgOx44hKwtjxqB/f3S1VatW2Ww2tGno0KESiQS8zhAlMb6/0IbPaP06UCs6g5pp/XvU9DNRPE3EE8FzV2aH9an0z07XXoAzi/tOWhY5C9fCxtSzHKVoYsnIBPQaLDyacACIFNQEp2xngJvRDRZHDPsm73eKFnybf2JJZBKBhxEQZphv6P7yC2hFcUPdpfqavt5qtEPSsPBJ18X+lpJZXK785ufBS288jfbiqOFZOIqJ/HF0p4ULF7700kto02effZacnHzDDTeg8y5dwrZtuHgRNTWorMS4cfDxQRf55JNPtm3bBmduuukm8LoAS7yWEck0qn+OWo+ikxyXae0yiEYTxdNgo8BzMw128xNnPz6vL4Qzi/tOWhY5C9eC2WbfejoTTUT4q4dHhKDXYOHZWAhjYT0FZ6jtDEG3iJT7JvmF/V5ViGbyjNUnqy8l+faFpxnpH76//AJad7gir6+3Gu3z4P1TT50u0OtNm38ddN3IgrDgWrQbbVgPUCJ/HCDoHkuXLn355ZcppWjT0qVLDx48OHDgQHSSry+WLkV9PUQiaDSQydBFjhw5snLlSjgjFotvvfVW8LqKoC9Rfw7TD9T4OrhadA61HqW6uUT2N+K9AkQGnnuot5tWp63PMlyGM3dGTL8tbCqukV/SsvQmM5pYMjKBEPQeLDwcESZS6yk4Zb8ErhaMD7rB4vBhv1cVoiUb808m+faFpxnlF442Haq4eEtkEtpHqZTefdfEN9/aaXcwb34ydt1zvxJC0W604WM4ionyNRAxukFkZOTEiRNTUlLQptra2mnTph04cCAqKgqdIZcjPh5dLS0tbc6cOSaTCc7MnTtXo9GA15UIkd5IxFNp/Xu08RvAgc6gVtqwnpp+It4riWwhwIDXpY5Wn2+wm6cGDkX7GO2m1WkfZRuK0CYCsqJf8o0h43HtbD6ejia8xKLkxAHoTVh4OmEi2oVS21kinohucH1Qf3+JvNJsRDP/Kc2qNBv9JXJ4lGhlgEbspbM0oBXHqwutnEPECNA+M6cP/u23zDNpl7Ly/LanxMyelI2OoOad4GqJz/sgcnSD5557LiUlBc6UlpaOHDly27Zto0ePhjtJSUmZN2+eXq+HMwzDrFmzBrzuwCiJ4mkinccZnoctDZ3EVVHDM9S0mVE8A2EieF3nVM2FrSVHGMJMDkiEM7VW4+NpH+XXl6FNBOTB6Lnzgsfi2jldWJJZWokmbkgc4C0WoTdh4eGIaAhF+9jOQDwR3UBAmBv/P/bgBKCqOu8b+Pd/zrkbl31HUAFBRBZFXMAFd9OWyTIzW7RFbTFbbKqZqaZ5xmamTctqzMrKzNIW02ZySy0FxQUURVzZZUfZ7+Wu5/xeH+eZeW+DN1C4cIHz+YQmrDqbihaskrSp6Pijg8ahW2HAKL/QbaWnYIfBasm8VDzaPxxtwxiefvKGBQ9/YjZbP9w4Oinhgq9XM64FmQ9RzV2c10fg+6CjjR8//qabbtq6dStaU1NTM23atHffffeBBx6AEyCilStXPv/882azGW0wb968oUOHQuY4ihjO5ysyfE9Nr0KqRTtZcqSau5jmVub2LDg/yDrCsbpciaS/nv6SZ2yC/1DYV2tueiZrdZG+Er+KY9xvB82eETQSXerLQyfwS3NGxaOXEdDdcT7gQyCWolXmLDjMnWHDPji3XyQJLXxdeHRR1BiecehWkvzDtpWegn37q/JH+4ejzUJCvOfelfTZuv3NBry/4c6XHluLa2XNlWrncJ7vQxGLjvbaa6/9+OOPFosFrdHr9Q8++OCPP/64cuVKf39/dJ3S0tJHHnlk69ataButVrts2TLIHI4xzUymmki6d6l5PSChXYgMW8i4k2kXMO3DYEp0GjKR4Xvmcid6kHqzrlhfBUAi6S+nv1RxymTfwbiaamPd0qzVZYZL+FUc456PvmtaYCK61KUm/a5TebAxakDfyABf9DICuj+mSCCxFK0hSzaDCPBwgECN+8SggbvLz6KFCkPj3srcyUFR6FaS/cLwq9Kq8p+Lm4prcc/c5L37zhYXX9p3kJsy/v7kmLW4VmKVVDuXuS9jmpnoUDExMcuWLfvd736Httm4cePOnTtfeeWVRYsWCYKAzmU0GleuXLls2TK9Xo82W7lyZUhICGSdg/Ng7i8yzUyp8X9gOYF2IgPp3iXDP5n775lqIjoFNX9GzeuZyyyAR09xtC6XQLjCKol/zFn7StyDo3wG4ZcqjbVLs1ZXGGrwqwSOfynm3hS/eHS1r46ctIgibMwdNQS9j4AeQJkA4z/RKmqG5QwUsXCMuWGJu8vP4mo2FGRODopCt9JX6xWi9SzV18OO3MbqiuaGIBcPtJkg8EufvOGpZ74gwrufeCa8/YBa/BTXikzU8DysBcztKYBDx3n22Wd37dq1Z88etE1dXd3ixYuXL1/+4osv3nvvvQqFAo5nNBrXrFnz6quvlpWV4VrceeedDz30EGSdTBHL+XxFhn9Q098g1aGdxCKqexjK0cz9RQgRcCipkfQfQWog8xGmTEZPkVWXCxtWSXw557NX4xcM9RqAfytprn4ma/VFUwN+lcDxL8fMG+sXi65mtopfHcmGDX9310nRA9D7COj+mGIooU3InMEUsXCM0QEDQl19inQ1aOFAVX6RribU1QfdSpJf2Lf6LNi3v7pgdmgCrkVcXN8bZwzduu14dXXj2k0jH73XjXTv4JoR6VfDmss83wTTooNwHPf5558nJSVduHABbVZQUPDggw+++OKLDz300IIFC/r16wfHyM3N/eijj9auXXvx4kVco8GDB3/44YeQdQ2OaWYy1UTSvUvN6wEJ7UPmdLr0G+ZyN3N7CswVjkH6DyA14DLDZiiT0VMcq8vFL5lE8++z17w2ZGG8ZziAYn3VM8dX15ga8atUvPKVuPuHe0fBCWzNPnupSQ8bc0fFCzyH3kdAD6CIBtOADGiVJQN4AI7BgDlhw147uQstEPBV4bHn46aiW0n2C/u2KAv27a/Knx2agGv0yKKJhw7n1dToNn2XOWH8fdH9vahxGSDhGpFpD9Xcxnm+CyEKHSQoKGjHjh3jxo2rqanBtSgvL1+2bNlf/vKX0aNH33777TNnzgwLC0NHOH/+/ObNm7/77ruMjAwiwrXr27fvzp07PTw8IOtCnAdzf5Gpb5Qa/wTrWbSXlZrXkXE7c3uaaW4HOHQssYqa1+MKMu5g7i+BuaH7qzLWVRhq0YJRNP8h++M3hz4icNyzWR/WW3T4VWpe+Zf4B4d5RcI5rDuQBRtqhXDnyHj0SgJ6Ap4phpL5IFpD5qMMBDA4xqzQhJWn9xpFC1rYVJT15OAJal6B7iPJP4wBBLsOVheIJPGMw7XQalWPPjz5lb9+T0Qr3t6x+u/3857uVP88YMW1shZJNXcw9z8yzWx0kOjo6K1bt06ZMkWn0+EaSZK0/4qlS5eGhoampKSMGTMmPj4+JibGzc0NbVNfX5+Tk5Odnb1///7U1NSysjK0g6+v744dO0JCQiBzBsphnO8Wav6Gml4HNaGdpIvU8AdqXs/cfs+Uo9BxSLcSZMC/kJGMO5hmNrq/o7XnYYfeanwm632OMZ3ViF+l4VV/jX9oqNcAOIdD+RfOVVyEjd8kRHtpNeiVBPQMyuEwH0SrpDpY8yFEwDHcFeoZIYM3F59AC40W447S0zP7D0H34aPSRrr7n2+shh2NFuOJ2rJhPn1xjSZNjN7z06mDh/IKCqq/25J55x23wEtL9U+BjLhWZKKGF2A+ztxfAlOjI4waNWrv3r033XRTVVUVrlfRFevWrcMVfa8IDAwMDg52cXHRarVKpRKA0Wg0GAx6vb6kpKSqqurChQvl5eXoIKGhodu3bx80aBBkToRjLnOYehI1vUGG7wFCO1lOU+19UE9lbs+B74/2sxaQYTNskGEz08xG93esLg/2NYsmtMZV0Lw2dOFg9/5wGp/tPwYbjOG+0QnorQT0DMoRaBsyZzIhAg4zN3z45uITuJoNhZkz+w9Bt5LkH3a+sRr27a/KH+bTF9fuySXTjp+4YDCYP12bNm7MwKCgScx7nVT3CKRaXDsyfEOWbM5zOYSB6AiJiYkHDx6cMWPGuXPn0BFKrkAniouL27ZtW0hICGROiPNjHq8zl3lS4zJYstBuZNxFxp+ZyyzmuhScF9qBmt4ARNgyZ8JaCCEM3RmBjtfloR3cBM3rQx8e5N4XTqPoUl3a+SLYGBMZOsDfB72VgB6BKYYSU4AsaJUlE7gLDhPvFRzr1SenrhwtnKgty6krj/Xqg+4j2S9sXd5h2JdWlffE4Am4dv7+7vPvG7P6w59NJsvKd3989a93QjGU8/lGqlsAayGug/WcVDOLuS5h2gUAh3YLCws7cuTIww8/vHHjRnQ3991336pVq1xdXSFzZopYzmcjGb6npjcgXUR7Wan5KzLuYNqFzOUBMAWug+U4mX5CC2T8B3N9Et1Zsb6qxtyI6+WldFue8EiYNhDO5LMDxyQi2Jg/Zhh6MQE9A1NDiIUlC60h8xEGx5obNvyFun/gajYWHn3Fqw+6j5F+oQLHWSUJdpyqr6gx6X1UWly7O2aN3PPzmdzcyiMZBT/vPTNxQjT4vpz311L9IzAfxXUgEzW9CdMB5vEa+EC0m7u7+4YNG2bMmPHoo482NzejO3Bzc1u1atW9994LWffAmGYmU99A+jWk/wBkRjtJDdT0Jhk2MdenmHoGrpHU9CpAaIEMm5jr4wCPbutYXR6ul7fSbXnCI6HaQDiTRoPxH1lnYCMiwGd0RH/0YgJ6CqYcTpYstEqshFgGPhgOc1Pf2NdzdjWYDWjhh5KTz8ZO8VBq0E1oBeVQ75DMSxdgh0SUXl1wS984XDuOY0ufmr54yWeSRO+t2j18eJibqxqcB+f1CTU8S8YfcV3IfJBqbmFuLzDNTHSEefPmjR49esmSJTt27IBzu/nmm999993Q0FDIuhemYa5LmOYWavwbmX5G+1kLqf5JKL9i7r+HEIW2IeNumI/hqsRKMh9hymR0W1l1ubgu/mqvFQmPBGt84WQ2Hs42mC2wMX/MMMbQmwnoMZTDof8IbUDmDKYJhsOoeeG2fkPW5h1CC0bRuuVC9vyIUeg+RvuHZ166gMsIYGhpf1X+LX3jcF2iBgbeNnP4pu8y6ur0H63Zu/Sp6biMaZjnu9B/RE0rAAnXQWqghudg/IG5/w/4YLRbRETE9u3bv/7662eeeaa0tBTOJzIy8u23377xxhsh6774UOb1Aczp1PgKrHloNzKn06VbmeY3zO05cL5ohUi6t/ArDJuhTEb3JJF0oi4f185f5fV2wqNBGh84GYsobjh0Aja8tZqbhgxC7yagp2DK4QQeENEqSyY0M+FId4cP/yzvEOEqvijImBcxiqHbGOM/4J3Te3EZw1WlVeVJRBxjuC4LHkxJT8+tqKzfuu34pAnRQ4f2x/9iTLsIfF9q+B3IgOtCplS6dCNzXcy0DwE82u3OO++89dZbP/roo9dee620tBTOYcCAAS+88MJ9990nCAJk3R9TjmY+31PzWtKtAunRXhIZtpBxD3N9lLnMA1PCDjJ8B2su7CPjDub+EpgbuqHzTWVNVgOunVpQuAhqOJ9/Zp2tatTBxl2jhqgVAno3AT0Gc4MQAes5tIbMmQyO1c/VO9k/PL26AC1c0NUeqi5M9g9DNxHr1cdDqWkwG2BHran5TENljGcQrotKpXhyybTfvfA1Ed56Z+eaDx5SKHhcwdQzGN9fqn8UYgWuDxmo6U0y7uLcX4IiHu2mUqkef/zxhQsXrl27dtWqVdnZ2eg6I0eOXLx48d133y0IAmQ9CVMw7UKmmUm6d6j5G0BCO1ETNb1OzZ8z7WPMZTbA4b+QiXTv4deRkYw7mGY2uqGsulxclwv66mePf7gi4RFXQQOnIRF9sj8TNpQCf9eoePR6AnoQphxB1nNolbUQUg04HzjS3PDE9OoCXM2Gwsxk/zB0EzxjSX5hO8tOw760yrwYzyBcr5Ejw8enDNqXerakpPbLDQfnzxuL/1AM5nw2SfVPw3wY181yQqqZzTQzmdtvwfmh3VQq1cNXHDx48IMPPvjuu++amprQWby8vO68886HH344ISEBsh6M82Puy5hmjtT4CizH0H5iBTW+RIavmNvzTDkKNqj5M4gVaA0ZNjPNbHRDx+rycL1ym0qfO/7hm0MfdhHUcA57TucXVNfCxsxhg33dtOj1BPQkyuFoXo/WEZkzmfoGONKkoKhAjXuloREt7Ck/V2VoCtC4oZsY4x++s+w07Ntfnf/IoHFoh8cXTzl6rEinM36x4WBKSlRYqB/+g/PlvNdS09uk/xAgXCciw2Yy7mSujzKX+8FU6AjJV6xevXrXrl2bNm364Ycfampq4BgBAQG33nrrrFmzJk6cqFAoIOslFLGcz5dk2ExNKyBdRPtZcqj2PqgmM7dnIYTjMqmR9B+hLcxHIRaD749uxSJZTzYUoh3ONF74Xfaa14csUvNKOIFP0zJhg+fYA+OGQwYI6EGYcgShbcyZUN8AR+IZd0downtn9qEFkaRvio49Hj0e3cSYgHD8qqya0iaLyU2hwvXy8XZ9eNHE5Su2W63iG8u3vbdyHscx/H88c3sGykRqeBZSA64bNVPTcmr+gmkfYpq5YEp0BLVafcsVkiTl5OTs27cvNTU1IyOjuLgY7cAYCwsLS0pKGjduXEpKSnR0NGMMst6IY5pZTH0j6deQ/iOQEe1Gpj1k2stc7mCuT5B+LaQGtAmRYQtzfRLdypnGCybRjPY5WV/4h+yP/zZkgYpToEsdzi85fqECNqbGRPb38YQMENCTcH7g+0MsRmvIksngcHPCElefS7NKElr4qvDoI1HjBI5DdxDs4tnf1btYVws7RJIOXSyY2ica7XDj9CF79505erTo7NmKzVsyZ90+Ar/EVBOYzxap/klYstEeYiU1/oX065jrEqa5BeDRQTiOi79iyZIlABoaGk6dOpWTk1NYWFhWVlZeXl5RUVFfX28wGIxGo8FgAODi4qJSqVxcXDw9PYODg4OCgoKDg8PDw+Pi4gYPHuzq6gqZ7F+YhrkuYZrZpFtBhu8BQnuJ1PwVNX8PWNFmZNjMXJcAHLqPo3W56AhZdXl/PLn2lbgHFJyArrMmNQO/9FDKcMiuENCzMOUIMhSjVZazoCYwNziSn9p1ctCgnWWn0cJFo+6ninPTgqPRTYzxDy/W1cK+tKr8qX2i0Q6M4ZmnZzy08GODwbzmk9TkpMg+fTzxX/hgzmcjNa0k/RpARHuIJdTwHOk/YNqFTH0LmAIdzcPDY/QVkMk6Ch/IPF5nLvdJTX+B+Rg6gBHXRCwn82GmTEbnEEUYjTCZQASeh1oNlQqMwWCAKEKthiDgMqsVBgOUSqhUaOFYbS46yJGasy+e/PSVuAcUnICucK7iYnpeMWyMiewfExwA2RUCehjlcBi+RetEMmcxVQocbG544s6y07iaDYWZ07dxMAAAACAASURBVIKj0U2M9g//siAT9qVW5qHdAgM85s8bu/qDn0wmy5tvbV/++lzG0ILA3J5h6slS/bMQi9FO1nxq+B01vclc5jKXeeA8IJM5P0Uc572BjDuo6Q2Ipehkhs1QJqMTWK04exaffYadO9HYiLAwzJ2LWbPg7Y1PP8XJk1i8GLGxuOzECbz1Fm69FbNn45eMovls0wV0nCM1Z5edWv9y7Dyeceh0H+w9QgRbC1JGQPZvAnoWphxOaBtzBlQpcLAkv7AId7+8xoto4WB1YV7jxQh3P3QHyf7hAsdZJQl2VBoa8xovRrj7oX1mzxqRmnbu9Omy48eLd/6YPf2GeFyVYijnu5maXqPmr9B+0iXSvUv6T5hmFtMuAB8ImczZMaaewVQTSf8p6T8ANaOzkHEnc38ZTAuHIsL583jrLTQ1Yc0a9OuHH3/E+vWoq8MTT6DNTtQXWCURHcdDoRVJym0qHeTeD52rpLZh16lc2IgNCRg1oC9k/yagh+H7gfOHVI3WkCWToTPcGTrsr9k7cTXfFB37ffwN6A60gnKIV8jRmguwL60qP8LdD+3DGFv61PRHHltrtYp/f3/P8MQwX183XBVzZe7LoBxDjX+GdAntR3pqXkeGDUx9K9M+BGEAZDInx9TM9VHmcgfp3qHmbwERnYAMZNzONHfAoaxWZGaitBR//jNGjsRld98NnQ579+L4cbRZVl0u2ocx1t8lINYjNMYjNMajf18Xf3SRj1MzRIlgY0HKCMhsCOhxmHIEGbeiVZaTIAOYBg52W/+hb53+yWC1oIXNxSeeGjxJIyjQHST7hx2tuQD79lfnPxCZhHYLD/O7a86o9V+k6/Wmv7+/5+WXZsI+pp7OlMnU9DcybAYI7UcWMnxLhk1MNQ4u9zJVCsBBJnNmnB9zX8Zc5lPTq2RKheORYTPT3AGHqq9HXh58fTFkCP5FEBAZicOHUViIywwGVFXB0xOXVVfDaMTVHKvLw7XT8KpB7n3jPMIGe/SP8Qh1FTToapUNTVuOnYaNMF+vKTERkNkQ0PMoh8O4Fa0iM1mOMeUYOJibQnVzSOw3RVloodFi3Fqac0doArqDcQED3juzD/ZlXio2ihY1r0C73XfPmLT954uLL+1LPZu2/9y4sVH4FZwH83iVaWZJjS/AWoSOQWRKhSmV+L7MZQ7TzAbnBZnMmQkRzGsNzOnU+AqseXAocybEC+D7wXHMZphM0GigVOI/NBpwHIxGXLZ/P9LToVbjMoMBRJgzB7/UZGnO05WhbXyU7gPdQ+I8wmI9wqLd+wkcD2fy0b4Ms1WEjQdThnOMQWZDQI/DlCMIbWM6BOUYON7dA0Z8U5SFq/kiP+OO0AR0B7FewZ5KTb3ZADtMovXwxaLxgZFoN4WCf/aZG5946nNJopXv/jh0aH83VzV+nXIE5/M96d4h/WeAFR1FLKGmN0n3HlPfzFzugSIGMpkTY8rRzOd7al5P+lWQGuAoRIYtzPUJOI5GAzc3FBWhqQkeHriMCA0NsFrh7g6jESkpmD8fAwfisuxsrFmDFrLq84gIdvCMC3Hxi/MIi/MMi/cMD1R7w1lVNeo2ZebARqCH2y1DoyH7JQE9jxABzhNSPVpD5nSGZ+B40R6BQ7xDTtSWooUzDZUnasuGeAfD6fGMjQkYsLUkBwQwXNX+qvzxgZHoCIOj+/zmlmFbvj9aW6v/8MOfn1k6A61iGub2PNPMpqa/kikVHYiMZPiWDN9CkcBc7mbqG8DUkMmcE1Mw7QNMczvpP6Lmz0AmOAAZvmOujwMcHMTDA9HROHAAe/di2jQoFGhowPHjIEJkJKqroVLBxwdBQbisvBwqFVo4VpuHX3IR1NHu/WI9QuM8wmI9w1ScAt3Bmn0ZZqsIG4smjFAKPGS/JKAH4phyFBl3olWW05AawHnA8eaGDz9RW4qr2VCYOcQ7GN3BuICIrSU5YLAnrSofHWfRggmHj+RXVNRv23FiwvjoxMRQtIUQzrzWwJxOjX+BNRcdy5JFDVnU+GemngzNTKYcDZnMOXEezO23zOUe0q+i5m8ACR1LLCfzEaZMgoPwPBITkZGBzz6D2YygIKSn4+BB3HYbYmJw4ADa4FhdLoAgjU+cR2icZ3isR2h/bQADQ7dysUm/KTMHNvzctLclxkDWgoAeSZkE4060TiRLBlNNgePdGBLz+skfa03NaGFbSc5zsVO9VS5weikBERxjEhHsKNLVlOjr+mq90BHUasWTj0/73QtfE+Gtd3Z8/OFDKpUCbcOUo5nPFmpeR/oPINWjY1ETGbbAsIWESKaZxTS/AecLmcwJ8UHMfRnTzKGm18l8CB3L8B2USXCc0FA8/ji+/hqrV6OhARERWLgQ06ZBEODlhaAgqFT4F7UaffrA3R02JJIWR94a49HfVdCgO/toX4bRYoWNhyeOUgkCZC0I6ImYMpnQNqbDUE2B4yk5fma/IZ/kHkQLZknccuHEg5HJcHreKpdBHoGn6ytgX2pV3j3hI9BBRo4Mnzo5ZteeU+Xl9Ws+SV386GS0HVMw7UPMZS41ryf9h5Aa0eGsudT0KjW9wZSj4DKHqacCAmQyZ6OIZd7rYE6nhmUQ89FByLiTub8MpoXjhIRg6VIsXYr/MncubMXE4PXX8Usc40b5DEI3d6lJ/23GSdjwc9PenhgD2dUI6JGEcPABEKvQGjIfZOgkd4UPX5t3SCJCCxsLMu+PSOIYg9NLCYw4XV8B+9Iq8+4JH4GOs/ixKZnHiurq9N9tzkwZOzAuri+uCXNh2kVMM4ea15H+U5AOHU8kczrM6cR5MNVEqKcz1XiAh0zmTJhyNNTjSZ+PjkIGMm5nmjvgSGazub6+nuM4X19f9D5rUjONFitsLJowUq0QILsaAT0UUyaR4Xu0ypoL6SI4PzheP63XGP8BaVV5aOGCvi69umBswAA4vXEBA1afTYN9hy4WGkWrmhfQQdzdNc88Pf3FP24iojdWbP9o9YMqlYBrxXkw1yXMZS7p15JhI6RGOILUQIYtMGwhPoCpb2Tqm6CIh0zmJMQKav4CHYoM3zHNHXCkqqqqjRs3arXaxx57DL1Mja756yPZsOHrpp01PBYyOwT0VMokGL5H64jMR5j6JnSKueGJaVV5uJoNBZljAwbA6Q317uuh1DSYDbDDKFozLxWPDRiAjjM6OXJ8yqB9qWdLS2s/+3z/ogUTcH04X+b2W+b6GBm+If0nECvgIGIV6T8l/afg+zDVFKaeAWUiZLIuRbp3QCZ0LPNRiBfA94PMAT5OzTRarLCxcPwItUKAzA4BPRRTJhPaxnwQ6pvQKcYHDgx28SxrrkcLeyvPlzc39HHxgHPjGUv2C9tRdhr2pVbljQ0YgA711BM3nMi+UF/f/NXXh8ckR8bEBOO6MRfmMp9p7ibjD6T/GNbzcByxnJrXUfM6CAOYagpTT4EiHmCQyTqZNZcMW9DxiAybmeuTkHW0i036jYdPwIavm3b2iDjI7BPQU/F9wPeDeAGtIdMhhk7CMzY7NOHt0z+jBZHom6JjTw6eCKc3LiBiR9lp2JdamfeH+BvQoTw8NI8/NuWVv/6DiN5Yvu3D1Q8olQLagymY5jamuQ3mo6T/kEw/w6Gs+WTNJ/0H4LyZKgXq6Uw5FkwJmaxTUNNyQIQDkGEzc10CcJB1qPd/Omy0WGHjoZThaoUAmX0Cei6mSqbmC2iVeAFiGfhgdIo7wxJXnU01SyJa+KYo67FBKQqOh3NLCYxgAMGuIl3NBV1tP1dvdKhJEwfvSz2Xtv/chZKa9V+kP/hACjqEMpEpP2CWbGpeR8btIAscSqolwxYYthBzY6oUqKcy1TgwN8hkjmM+Sqaf4CBiOZmPMGUSZB2npLbh28yTsOHrpp0zMh6yXyWgB1MmofkrtAGZDzHNLHQKb5XL1D6DtpaeQguXjLpd5WdvDImBc/NTu0Z5BJxtqIJ9qVV597qOREd7csm04yeKm5qMG746NGbMwKiBgegoinjm8SZz+z0ZNlHzlxDL4WjURMatMG4l8FBEM9VEppoIRQzAIJN1KEn3BhzK8B2USZB1nHd3pVtFCTYenjBSrRAg+1UCei6mTCIwgNAq8yFoZqGz3BU+fGvpKVzNhoLMG0Ni4PRSAiPONlTBvtTKvHsHjERH8/bWLn50yquv/yCK0hvLt63++3xB4NGBOB+mXcS0C8h8CPrPyLQXIDicCEsOWXJI9y44b6YcBeVopp4Ezg8yWbuRaTfMx+BIZNzJ3F8G00LWEc5XXtqWfQ42gr3cZ4+Ig6w1AnowzgdCJKzn0RoypTN0nhG+/Qe6+59vrEYLGZeKcxurI9394dzGBUR8eO4A7DtyqcgoWtS8Ah1t2tTYtP3nDqTnFhRUf7nx0Lx7x6DjcUw5GsrRzJpPzV+QYQtIh84h1ZJxO4zbqfFPUMQx1VgoRzHFUDAVZLLrIVLTCjgUH8QUiZAugtdC1hHe2rlfIoKNJVNGKwUestYI6NGYMpms59Eq6SKsBRDC0VnmhCcuO74dV7Ox8OhLQ2bAuSV493VTqJosJthhFK1HLhWnBETAAZ564obs7JImnfHz9QeSkyIiIwLgIMIA5v5H5vZbMm4jwyaYjwGETiLCcpwsx4H3iKmYIgHKkUyZBMUQMAVksrah5k2w5qGD8RDCmDIRikSmHA4+BLKOc6yobN+5QtiIDPC5eeggyNpAQM+mSkLzZ2gDMh9kQjg6y8x+Q97K+UlnNaGFLcUnnh48yVWhghMTOG5swIDtpadhX2plXkpABBzAx8d10aKJy1dsF0XpjTe3rXpvviBwcBzmwjR3MM0dsBaRYRMZt0CsQmciE5kPwXyI8A6YhikSoEpiipFQxIIpIZPZQ0bSv4cOwXkyRQKUCUwxDIo4MA1kjrFyVzp+6akbxnKMQdYGAno0phxJ4AERrTIfgss96CxaQXlz39iNhUfRgt5q3lqaMycsEc5tQuDA7aWnYd++ytwXh0yHY9w4fUhq6tmMzMK8/Kqvvzl899xkdAIhlLk9w9yeJvMhGLaQcSfIgE5GBjKnw5xOuIyHIpophkERy5QjwfeBTGaDmj+DWInrxvdlykQoYpgiEYrBAAeZg+09W5BRWAobcSGBE6LCIWsbAT0bc4MiBpZstIbMhxgkgENnuXfAyI2FR3E1XxZkzglLhHObEBjJMyYSwY4SfV2xrra/qzccgDEsfWr6Q4s+bm42f/b5/tHJkaGhvugkHFOOhnI0c/sDGf9Jhn/Akg0QuoAISw5ZcgAQAL4/UyZAMYwph0EYAPCQ9WZSA+nX4JowDRTRTIiFMpEpk8B5QdaJJKJ3dqXjl5ZOH8sYZG0koKdjymSyZKNVUgMsZ6CIQWeJcPcb5tP3WE0JWjjXUHWspmSYT184MQ+lZoh3yLGaEti3rzJ3XsQoOEZAgMeiBRPffmenxSK+9sYP770zj+c5dCbOk7ncx1zug1hOpl1k3A7zMXQhsZgMxTBsIQBMASGKKYZBEcsUMRAGABxkvQnpV0NqQKs4P6aIhTKRKRKhiANTQtZFtmWfO1txETbGDgwdFd4XsjYT0OOpkqH/AG1A5nSmiEEnmhs+/FhNCa5mQ0HmMJ++cG4TAgceqymBfalVefMiRsFhbrk54UD6+YzMwnPnK7/ccPC+e8egS/B9mMt85jIf1jwybiXDVohF6FpkgSWHLDkACADTQjGYKWKhiGXCYAihAA9ZDyZWUfMXuDoeQhhTJkKRyBQxECLh3ERRNJvNarUaPZrJan175wHYYAxPTRsD2bUQ0NMxRQIxJciMVpnSoF2ITjQ9ePCr2T/WmPRoYUfZ6d/FT/NRaeHEJgZFrji1B/ZlXCo2ihY1r4BjMIZnn7nxwYUf63TGdesPjBo1YGBkILqQEMFcn2SuT8KSQ8atZNwBsQzOgPQwZ5A5AwABYCoIkUyIgjAQikFMGATOC7IehHRvgYz4D6ZliiFQJkIRwxTDwbmjO5AkqaGh4fjx43l5eYmJiejRPtt/rLy+ETZmxEUN7uMP2bUQ0OMxDRRDYT6C1pDlKCM9mBadRcHxs0KHfnjuAFqwSOJ3xccXDhwDJxbp7h+i9SzV18MOk2g9dLFoQmAkHMbX1+2RRRPfXLFdFKU33tz2/t/nCwKPLqeIZYpY5vY8LGfItJtMu2E5A+dBJlhyyJKDKwgA58cUgyBEQQhjwgDwA8B5QNZNWfPJ8D04P6YcDuUwpkiEYjDAoVsxGAy5ubnp6elZWVmenp7x8fHouS416T/alwEbCp5fMnU0ZNdIQC/AlMlkPoJWkYXMh5hqMjrR3LDhH59PF4nQwoaCzAcjR/OMwYlNCBy4Pv8ICGC4qrTKvAmBkXCkG2cMSdt//vCR/PyC6nXrDzx4fwqchyKaKaKZ6xKIZWTcRaY9MGcCIpyNdJFMF2FKA0C4gvOBEMGEMPDhEAYwIRx8EMBB5vyYivNPB+eF7slsNpeVlWVmZmZkZOj1+unTp0+ePNnd3R091zu70/UmM2zckzy0v48nZNdIQC/AVONItxJtYdoP1WR0oiAXj3EBkXsrz6OF8uaGtKq8CYGRcGITAiPX5x8Bgz37qnJfwgw42G+Xznhw4ZqmJuOGjYfGJEdGRQXB2fDBTHs/094PqZ5MP8H0E5nSQTo4LakG5hoyH8YVBIApwYcwvj/4fhD6g+/H+H7gg8EUkDkVPgQdi4xgajieJEm1tbWZmZkHDhyoqqoaMWLETTfd1KdPH/Ro5youbj56CjbcNeqHJ46E7NoJ6A0UseC8IdWiNWTax9DZ5oYn7q08j6vZWJA5ITASTmykX6hWUOqtZthRqq8vbKoJc/OBI/n4uD6+eOrfXv2nKEqvvv7DB+8/oFQKcE6cJ9PcDs3tDFaYj5EpjcypsJwFCE6OzLAWkLUA/0a4jAcfxPgQ8EHgQ8AHgu/DuD7gg8DUkHUbVogXIVWQeBFSJcQqSBdJrIB0EWIl+BDOdysciYj0ev3JkycPHz6cl5fn5+f32GOPxcfHcxyHnu6N7WmiRLCxZEqyh0YN2bUT0CtwTDmajD+gVWIpxCLwoehE4wIiQrSepfp6tJBalVeqrw/ResJZKTl+tP+AXeVnYN++qtwwNx842NTJMQcOnE9NO1d8oWbtuv2LFkyAsxOgHMmUIxmegXSRTGkwpZH5AKR6dCcixFISS2GDcAXnAz6I8YHgAsH5gg8E58v4QHC+4Lwh61QipBpItSRWQ6qFVAupClIdpFoSqyDVQroEEOwRK+BIZrO5oKAgPT39+PHjPM/ffvvtY8aMUalU6AV+PpOfnlcMG2G+XnNGxkN2XQT0EqpxMP6ANiBTGnMJRSfiGJsTlrg8Zw9akIi+Ljq6NGYynNiEwMhd5WdgX2pl3v0RSXC8p568IftkSX1981dfH04eNSAuri+6C86PaW6H5nYGEZaTZDoI8yGyZIGM6L6kGkg1ZMmBDcIVTAnOF1wg47zBeYH3BecN5gXeh3G+4LzAeQMCZK0iM6gBUj2kBqJ6SA2QGiDVgxogNZBUA6kGUi2kWrQH6UBNYG64bqKI/Hzk5KCpCRoNwsMRHw+lUpKkixcvHjhwIDMzs6GhITk5ecaMGT4+PugdRElasfMAfum5m8YLPAfZdRHQOzDVWAIDCK0ypcHlPnSuO0IT3juzzyRa0cI3hVmLB41X8QKc1YSgSI4xiQh2ZF4qbraaXQQlHMzTw2XpU9P/+KfviOjVN7Z+/OFDarUC3QwPxVCmGAo8ysgMywkyHyLzYViOg8zoMcgMsRxiOeG/Ef6NuYFzB+fBmAc4D3DuYJ7g3ME8wLmDuYCpGHMFcwFTgbmCuYAp0K1RM0gP0kPSETWB9JCaQXpQEyQdSA9qBukgNZBUD2qAVA8yoHOIFRDccH0kCSdP4sMP0dwMQYAkgeNwyy24+WarKBYUFOzatSsqKmrBggXh4eHoTb48dCK/ugY2Rg3oOz4qDLLrJaCX4PygGATLGbSGzIcZmcGU6EReSpcbgqP/ceEkWqgzN/9YfuaWvnFwVj4qbaxnn+y6MthhlsTDF4smBg2E440dM3DC+EF7952tqKj/+NPUxY9ORvfFlFCOYMoRDEtARrIch/kwmQ/DkgMyosejJohNEMsIdhH+Cw/OFUwDqMG5gmkYU4G5gWnAVGBu+F8MnBv+Dw/min9hPJgW/8IUYC74FVIjQGiJdCAJ/8sK0gMEqQmXURMgQWoGrCAjyESwgAyACEkHWEHNkBrgxEisZMJAXAciGAx4+23odHjhBQwciIoKrF+PlSsRHc3CwoKCgubPnz9ixAie59GbNBqM7/90CDZ4jv3+pgmQtYOAXoMpU8hyBq0iA1kymXI0OtfcsOH/uHASV7OhIPOWvnFwYhODBmbXlYEAhqtKrcqbGDQQneKpJ27IPllSW6v/bnPm2DGRQ+L7oQdgaqZMgjKJ4TIR1gIyH4PlKJkzIJZB9n9ESA1AAy4TcRlB1kHECly3khJs24YtW5CQgMsGDMD8+UhLw48/Kh5/PPQK9D7v7j5Y32yEjdsTYwcG+kLWDgJ6D9VY6D9AW5jSoByNzpXg03ewZ9Dp+gq0cKym5HR95WDPQDiryX2iVp7+GQz27K3MfRmdxN1d8/ST0196eRMRvf7mtjUfPKjRKNGj8BAimRAJzGEAxDIyH4UliyxZsJwDRMhkHU6qwPWRJOTmQpKQmIh/YQyurhg0CGfPorc6XV698fAJ2NCqlEumJEPWPgJ6DaZMJOYK0qE1ZEpjbs+j080JG/Zy1lZczdeFR/+UcBOc1UB3//6u3sW6WthR0dyQ33RpgJsvOsWY0ZFTp8Tu2p1TUVG/avVPzzw9HT0YH8w0wdD8huEyK6yFZDkFSw5Zc2A5CbJAJms/sQLXTRTBcWAM/8EYeB5WK3oliejP3+8RJYKNheNH+LppIWsfAb2IwJRJZNqNVlnPQ6wAH4TOdUvfuDdzdjdZTGjhHyUnfxs7xVWhgrOaFBT1ae5B2JdamTvAzRed5YnHp57IvlBd3bh12/ERw8NSxkWhVxAgRDIhEpqZDAAZYDlNlpOw5pAlB9ZiQIRMdh3ESlwfxhAaCknCmTMYMgSXEUGvR34+Jk5Er/RtRk52SSVs9PPxnD92GGTtJqBXUY2FaTfagMz7mWY2OpeLoPxNv/gv8jPQQrPV/H1J9j3hI+CspvSJ+jT3IOxLrcp7IDIZnUWrVb3wu1ueeuZLInp75c642BAvLy16G6aBMpEpEwEwXGaFtZAsp2DNgzWXLDmQLkImawMSKxiuC2MID8fo0Vi1Cr/9LUJCUFuLf/4TDQ2YNAm9T4PBuHLXAfzSC7dMVAkCZO0moDdhqvGEtjHth2Y2Ot3d4SO+zM8gXMWX+Rl3h49gcFIJ3n191a6XjDrYkXnpgt5q1gpKdJa4uL633zZ803cZ9Q3Ny9/a8cqfZ6G3EyBEMiESVzAAUjVZzsF6FtZcsubDWgjSQSZrSaoECGC4VoxBq8XTT2P1arz/Pry9odejpAT33ov4ePQ+b25Pq9MbYGN63MBxA0Mh6wgCehU+GEIorEVoDZkPMIgAj841wM13uG//jEvFaCG/6VLmpeIRvv3hlDjGJgZGflOUBTssknjoYuHkoCh0okULJmRlFRUUXkw/mLtt+4kbZwyBzBbnz1T+UI0DwHCF1ABrHlnzIJbAmkvWPIilAEHWy5ERUj04L1wHnse4cdBqsX8/amvh4YGUFEyYAEFAL5NTWrX56CnY0KqUz980HrIOIqCXYcoUshahVVIjLCegGIZONzd8eMalYlzNxoLMEb794awm94n6pigL9qVW5k0OikInUij455+7efGSdVar+N6q3fHx/UKCvSD7FZwHlIlMmYgrGABqgrWYxAsQS2C9QGIxxAsQqwCCrFcRK8B54foIAkaOxMiR6MVEiV7eslsigo3HJicFuLtC1kEE9DaqcWhehzYg036mGIZON61PtL/ardrYhBZ2lp953tjkr3aDUxrtP0ArKPVWM+xIrcxFp4uMCJg/b+zHn+wzGi2vvfHDyhX3chyDrO2YGxSxTBGLKxiuIBPEEhIvQCyBWAaxnMQKiBWQLkHW3TEVuEDwfowLAu8LLgi8P+MCIYShfYxG4/79+6dMmYJe6ctDx8+UV8NGRIDPfckJkHUcAb0MU44ipgYZ0RoypTLXJ9DpBI6bFTr0/bNpaMEqSd8VHX9k0Dg4JSXHjwuI2FF2GnZUGBpzG6sj3f3Rue6+KykjoyD7ZMmpU2Ubvzp099xkyNqJqSBEMCEC/8ZwBZkglpNUAbEcYgXEckiXSKyEVAPpEmROgvMG5wPOm3F+4LzB+YD3B+fH+EBw/uA84Rg6nW7FihVTpkxB71Oja35v90HYYAwv3jJJ4DnIOo6A3oapmSKRzAfQKksOpBpwPuh0d4YlfnjugEgSWviq8OjCqLE8Y3BKk/tE7Sg7Dfv2VuZGuvujczHGnn/upoUPf9LcbF67Li1xWGhUVBBkjsBUEMIYwmCD4QqyQKqBVEFiDaRKSJcgXYJYS1QLqRZiDagJsnZiCjBPcB7gPBjzBOcBzhNcADgvcN6M9wfnA84b4NEVrFZrdnY2eqVXt+5tMppg4zdDB48MD4GsQwnohVQpMB9A6yQy7WeaW9HpgjTuE4MG7i4/ixYqDI17K89PDoqCU5oQOFDB8RZJhB37KnMXDhyDThcU6Pnow5OWv7XDapVeff2H1aseUKkEyDoTU4APBB/IFLDF8G9kAdVBqiXxEqgeUgOkRlA9pEZQA0kNkBpAjZAaQc3oLXhwrmCuYFowF8a04NzBtODcwXmCeYDzAOfFmAc4D3BeYC6QOZ995wq3njgHG64q5dLpYyHraAJ6H6YaS01oE9PP0NyKrjA3LHF3+VlczYaCzMlBUXBKbgrVCN/+6dUFsCOrpqTebPBUatDpbrpxaEZmYWraueILNZ+sTX304UmQORWmE+wDlwAAIABJREFUAPMH588EtMTwS6QDmUDNkHSAiagZkh4wQmoG6UFGUDNIDzKB9CA9kQmkx7+QDiTiX0gHSPgXqREgXD8BnBb/hwNzBRg4dwCMuQIcOBdAAaYGUwJKMA0YD6YFODA3cK5gLoxpwVzAeYC5gLmAaSDr5pqMpj9t2Y1fevqGsX5uWsg6moBeSIgE3wdiOVpDplRGFjAFOt3ogAGhrj5Fuhq0cKAqv0hXE+rqA6c0pc+g9OoC2CES7a/Kv7lvLLrCU0/ecDKntK5O/+2mjKRRAxKG9oesm2KuYK6AD3hcxtAKhmtCkBphD1ODqSCTtc0b21OrGnSwEd838M6R8ZA5gIBeiSnHkOEbtIp0ZDnClGPQ6RgwJ2zYayd3oQUCvi489lzcVDilKX2ilh3fRrBrb+X5m/vGoit4ergsfWr6Sy9vIqLXXt/60YcPurmqIZP9NwbOAzJZux3OL9mUmQMbCp5fdvtUnmOQOYCA3kk1EYZv0BbGn6Acg64wKzRh5em9RtGCFr4tynpi8AQ1r4Dz8Ve7xXkFZ9eVwY60qnyRJJ5x6ApjRkfOmB6/fUd29cXG5Su2/+mPt0Emk8kcwGix/nHzbiLYenTSqMgAX8gcQ0CvxFRjiGlABrSGTHsYXgQYOp27Qj0jZPDm4hNoodFi3FF6emb/IXBK04Kjs+vKYEeD2XC8tjTRpx+6yOJHp5w8WVJaVpeadu6fPxy/5eahkMlkso62fEdaSW09bEQF+i5IGQGZwwjonZiGKZPI9DNaJZbDeg7CIHSFueHDNxefwNVsKMyc2X8InNL04MHLc3YT7NpXmZvo0w9dxMVF+eILtz7+xOdWq/j393fHDO4THu4PmUzmYG5ubq+88gp6h+MXKjYcOgEbPMctmzVN4DnIHEZAr6WaBNPPaAMy7mGug9AV4r2CY7365NSVo4UTtWWn6itiPIPgfEK0noM9g07VV8COnytyl8ZMRtcZGBm48KHx73/wk9lsfeVv/3j/vfkqlQIymcyRtFrt/fffj17AbBVf+m6XRAQbD6UMjw0OgMyRBPRWTD2RGhlAaA2ZfmKui9FF7gpLfLGuHFezsSBz2bBb4JSmhww+VV8BO3Ibq8ua64NdPNF17pg18viJCwcP5RUVXVq1+qenn7wBMpnMAYjIpDcd+vZQ1JiooMggItLV6I7vPD5o7CC//n7oid7bczC/ugY2wny9Hp00CjIHE9Brcf5QxMJyEq2y5ECsAh+ArnBz37g3cnY3mA1o4Z8lJ5+Nm+quUMP5zAiOWZGzh2DXvsq8u8OHo+swhmd/e+PCRZ/U1Or++UPWkPh+kyZGQyaTOQDjmGgRD35z8Oanbyai0/tOV+ZVDpk2BD1RTlnVp2lHYYNjbNmsaSpBgMzBBPRiTDWJLCfROiLTXuYyB11BzQsz+8V/lncYLRhF65biE/MiRsH5hGg9B3sGnaqvgB37KnPvDh+OLuXp4fLCH37z2+c2SBK9/c7OwYP7BAZ4QCaTdSjGmFKtHHLDkJ2rdmbvyvYP9T+ffn703NHufu7ocYwW6/NfbRclCTbuSR46rH8fyBxPQC/G1JNJtxJtYfoJLnPQRe4JH7Eu7zDhKr4oyLgvYhSDM5oeMvhUfQXsOHSx0GC1aAQFutTQIf3m3Dlqw8ZDOp1x2Svfr3zrXkHgIJPJOhTjmFeQV8KMhP1f7vfq4xUSE9I/rj96ole37i28VAcbwV7uT04bA1mnENCbCYPAh0AsRWvIfJCRAUyDrtDP1TvJP+xgdSFaKNbVHr5YmOQXBuczIzhmRc4ewtWZROuhi4UTgwaiqz14f0r2yZJTp8rOnC3//IsDD8wfB5lMZpcI8Lh2nMD1je0riVJlXuWkByYJKgE9zk+n878+chI2GMOy26e6KBWQdQoBvRtTTaDm9WgVGcl8gKmmoIvMDRt+sLoQV7Oh4GiSXxicT4jWc7Bn0Kn6CtixtzJ3YtBAdDWe51564daFiz5p0hnXf5E+JL7vsIRQyGSyFsi0l3RvcZ7vg++DaySJUmVuJYHc/dzLc8t9+vmgZ6nVNb+8ZTd+af6YxKQB/SDrLAJ6OdUkNK9HWxh/hmoKusjkPlEBGrcqQxNa2F1+tsrQFKBxg/OZHjL4VH0F7Pi54vyfEm5i6Hr+fu5Ln57+P8u2ENGrr2/9aPWDHh4ayGQyW5ZTVP8kyCDVzOa8PoAiFm1GRPo6fcb3GUOnDXXxcDm+43hwdLB3H2/0FET4w6Yfa3TNsBER4PPktNGQdSIBvRtTJRHnDqkRrSHTTwwSwKEr8IybHTrsvTP70IJI0jdFxx6PHg/nMyM4ZkXOHsLVVRubzjZURnsEwgmMTxl044wh27afuHSp6dXXf/jrK7MZg0wm+z9ilVT/KMiAy6SLUu09zHM5U01B24gWMWt7lspFFT8tXrJKpWdKM7/PnLJoCsdz6BE+Tz+Weq4QNpQC/8acG1WCAFknEtDbCUw5lozb0CqpBpYTUCSgi8wJS1x9Ls0qSWjhq8Kjj0SNEzgOTiZE6znYM+hUfQXs2FeRG+0RCOewZPGUU6dKiy/UHD6S/+2mI7PvGAmZTHYZ6aW6hRAr8R9koLrFcH2cuS5BayRJKj1dmns4d/ri6VpPrWgVh0wdsm/dvrwjeQOTB6L7y6uqefvHA/ilZ2ekRAX6Qta5BMhUE2HchjYg409MkYAu4qd2nRQU9WPZGbRw0aj7ufLc1D7RcD7TQwafqq+AHXsrcx8ZNA7OQaVSvPTCrY8tWWc2Wz/6eG90dJ/YmBDIZL2dSPVLYT2L/0akexdSFXP/EyDAPsaYd7D3pIcmBQ0MAsALfEBEQMq8FFcvV3R/Zqv47NfbjRYrbIyJ7H930lDIOp2AXo+pJhB4QERryPQTc3sGXWdu2PAfy87gajYUHJ3aJxrOZ0ZwzIqcPYSry64rqzHpfVRaOIfwcP8lj09dvmK71Sr96c+bP3j/AR9vV8hkvRg1vkKmn2EH/T/24AMgqjNhG/b9nHOmw8wgIL0I0gSUooioWLEEY4k9SjR14ya7iUk2vWx2UzY9JqaaZqyrMbFgV6yIBaUIqCAiSlWBkTJ9zvP7s6/76QoyI6CDnuvSroKlgqgXgDiiFYQQpatS6arEVSKJyCfcB3eFT7bsO1V5EddwUsjemzKaEAhuPw4CRgVxXxgPoU3mIlhKwfrhDhnQvUdPpevp+ou4QcaFMyUNNT0cnWFnvBXqMLVHgaYSLeEp3VddPNG3N+xG8tg++fnlW7bm1tY2vfv+ho8/mMEwBALBPYk2/US1y3BT1LCf1sxknL4D64V7zN5TJUszsnC9dx5IcnVUQHAncBAARDKcGg/BClS/iyjm4s6Z5h/zXu5W3IACK0syX+k9GvYn2Tu8QFOJVuypKpzo2xv25Nm/jiouri46XZ2dXbp4yf6H5wyGQHDvoYbdtOEjWMNcyNdMY5y+gygC94xKTcMrv22lFNea0b/PsLBACO4QDgKASIfThvdhBWrYSRRzcedM9OvzWUGazmzCDf4ozXm213AZJ4KdGecT+Un+Tp5StGR/dbGZ5zmGgd0Qi7k335j45J9/aWoyLF12IDzMKy4uAALBPcWURzXPABZYib/I185iXDaD9cQ9wGi2PLNsQ12TDtfwdVa/MHYwBHcOB8EVrB+4QJiL0SbjEfAXwbjiDlGKpOO8I1afzcIN6k36jWV5U/yjYWfcZI6xzr5HLpWiJQ0mw7Gac3Gu/rAnXp5Or7w07o231lBK331//bffzPVwV0MguEdYqnnNn0F1sAWRp4D1RGss1bRpISSjiGQwur73UnfllVfjGmKO/XRmslwsguDO4SBoRiQjqLkYbeOpfgeRz8Sd82Bgv9Vns9CSZcVHpvhHw/7c7xt55FIpWrG7qijO1R92JmFA0OQH+v225khDo/4f76z74rPZIhELgeCuR5v4usdhqYItiHQ0cXwOLaI6ql1CG78G1RK+FpLB6OJSs0+uOnwc13t13LBent0huKM4CJoRyXDa9D2sod8M+UzcOWEq9z7dvHJqy3GDksZL5VqNl1wNOzPGq9c72ZuNvAUt2V1V9GJkEuzPnx4fdupU5fG8slOnKr/5Lu2vTydBILjLWajmeZhPwiaiCKL6EGDwv3iqW08bPgJ/Ec2oPo3wF8B0R5d1qurSm39sx/XGRYVOi4uE4E7jIPgPcR8wLuAvoS3UeITwtWC64c6Z2aNvTm05ruHr0G2qf/QU/2gnsRz2RymSDnEP2l5xEi0503DpXGOtr0M32BmWZd56Y9IT836qrW1au+5oWKhH0sgICAR3L1r/DjWkwSasF+P0PYgM16PGg7ThfZhO4DoWqvudKJ5E19SgN/x16Qa9yYxrBLu7/GNSEgR2gIPg/7BEmkS1K9A2C9VvI/IZuHPu84n4MG97rUHLEBLv2iMlMG6oRzCBXbvfJ3J7xUm0Yk/16RSHONifbt0Ur78y/oWXVvI8/WzB1uAgdz8/FwgEdyPa9DPVLoNNiAPj9B0YF1zLfJY2fkb1m9ESql1FFE8ADLoaSvH6mm3nazW4hkIi/nRmslTEQWAHOAj+SzoG2hWwhn4L5DNw54gZdm7PATqLcVqPWA+ZEl3BEPcgpUhab9KjJburilIC42CXoqL8HkoZ9MvifXq96c23f/9m4Vy5XAyB4O5CDbtpw4ewDUucvgQXjP/iL9OmRVT7M6gJrbGUUWMGEQ9EV7Noz+Ht+adxDULw7uRRAa7dILAPHARXEXEcZZzB16At1HiI8DVgnHHnPBEyEF2KhOWSvELXnM1GSw5dLGkyGxWcGHYpZVZCQUH54SNnyspqDx46PXxYLwgEdxNTPtU8A1hgC6J8g4gH4v+YqXYZbfwSfD3apF0F8UB0KYeKz3+54wCu98jgvqMigiCwGxwE/w9LpCOp9t9om4XqdxL5NAhscb9P5Jqz2WiJmecPXDiT5BkKu0QIee2V8fOfX5Yye+CQxFAIBHcT/gKvmQeqgy2I4nEifxDNqCGN1r8HyzlYh+q3E/4iGFd0EedrLz+/cqOFp7hGXID3s6MGQmBPOHQmk8lUVFSUn59fUlJSUVFRWVlZUVHR0Izn+cuXLwNQq9WEEKVS6eDg4Onp6eHh4enp2aNHj/Dw8KCgIJFIhNtJOgbaf8Mahi2QT4PAFnEu/m5Sx2p9A1qyu6owyTMU9srRUfr9t48wDIFAcDehTXztY7BUwRZEOoo4Po8rTHl8w/swHoFtzFS3ligeR1dwWad/8pc/apt0uIaLo+LDaWNZhoHAnnDoaMXFxfv27du7d+/hw4cLCwtNJhNuqq6uDq0QiUQhISFxcXGJiYmDBw8OCAhAJyPieMp0A1+LtlBDBuFrwXSDwGoMIff5RPxclIGW7Kg4+U7MeAL7xTAEAsFdxUI1z8N8EjYRRRDVR7BU08ZPqW49QGE7ql1NFI8BBPbNbOHnL99YcqkO12AZ5rOZyd2VDhDYGQ4dwWg07t69e+3atRs2bCgrK0MHMZlMec1++uknAL6+vuPGjZs0adKQIUNEIhE6BUskI6huNdpmoYadRDYVAlvc7xP5c1EGWnLZqC/QVIarPSAQCG4LWv8uNaTBJqwno15AtUto49egWtwyy1lqPETE8bBvb63dcbD4HK73yrihsf5eENgfDu1z6NCh77///vfff9doNOhk586d+7qZk5PT5MmTn3jiiX79+qHDScdAtxrW0G+FbCoEtuildvdz6FbaWIuWbCrLD1d7QCAQdD7a9DPVLoVNiILIpvM1M8BfRPtpV0EcDzv2/e7DfxzNx/VmJ0Q/GN8HArvE4ZYYDIZffvnlm2++ycnJwW1XV1f3Q7Po6Ognn3xyzpw5EokEHYRIEijjBL4ObaGGA4S/DEYFgS0e8Iv6LD8NLdlclv+3iJEQCASdjBr20IYPYRsWrDNt/AwdhBq2Er4WTDfYpW15RV9sP4DrDQr2f+m+RAjsFQcbGQyGxYsX//Of/ywrK8OdlpWV9ac//enNN9+cP3/+X/7yF7lcjg7AEskIqvsNbTNTww4imwyBLSb49l5QkMZT3KhCe7lKV+8uU0IgEHQeUwHVPANYYBsLzOfQgaiJ6tYRxcOwP/nl1a/8tpWnFNcI7O78yYz7WIaBwF5xsBqldOnSpS+99FJlZSXsSXV19csvv/zFF1988MEHs2bNIoSgnaRjoPsN1tBvhmwyBLZwlyl7qT3z6irQkpVnjj4bPgwCgaCT8Bd4zZOgWtgBqvs3UcwFCOxJdX3j00vW64wmXMPFUfH93EmOUgkEdoyDdXJycp5++un9+/fDXlVUVKSkpHz//fcLFy7s3bs32oFIEiijAn8ZbaGGA4S/DEYFgS3m9hzwwpE1aMmG88efDR8GgUDQGWgTX/sYLFWwE+YzMGZC3A92o8lgfPKXP6rrG3ENqYj7OmWCh9oRAvvGoS2U0i+++OLFF180Go2we/v27YuNjX3ttdfefPNNhmFwizgiGUF1v6NtZmpII7JJENhitFfoq0c5I2/GDcq1mhqD1lkih93ieTQ1oaEBFgtYFgoFHB3BMOgkej0aGqDXgxBIpVCpwHEgBBcuQCaDQgGGwRVaLS5fhrs7CIFA0DIL1bwA80nYE6pbRcT9YB9MFsuzy1NPVV3CNQjBO5NHRXi7QWD3ONxUeXn5Qw89lJaWho6jUCjEYrFKpWIYBgClVKPRGI3GpqYmdASz2fz222/v379/yZIlHh4euDXSMdD9DmvoN0M2CbdTXR3y81FSApMJLi6IiICvLzgOneTMGWRno6YGYjH8/BAfD6kU7SNi2DhX//3Vp9GSRYX7X44cBfvE86isxOLF2LwZNTVwckJiIh57DAEBIAQdrqkJGzdi1SoUFoJhEBqKJ59EfDwkEsyejYkT8fDDkMlwxcaN+Pvfcfw4CIFA0BJa/y417ISdofotxPF1MCrcaRaevrhqS3pRKa737KhB9/UOgaAr4NC6nJyc5OTk8vJy3CqVStW3b99evXqFh4cHBwd7eHh4eXk5OjqiJY2NjWVlZZWVlYWFhXl5eQUFBUePHr18+TJuyc6dO+Pi4jZt2hQZGQnbEckgyqjAX0ZbqGE/4S+DUeH2uHQJmzZh3z5cwTDQ63H0KCZPRkQEGAYd7uRJfPMNGhogFoPnsXUrzp5FSgpYFu3zVFji/urTaMnGsvyXI0fBDlGKhgZ88QXS0/HPfyIqCidO4Msv8dpr+PprdOuGjkUp/vgDixZhyhQsWACLBd99h5dewldfISoKAoEtaNMvVLsUdogaqH4dkT+EO4pS/GPdzq3HC3G9STHhjw/pB0EXwaEV27Ztmzp1an19PWwkkUiGDx8+evToxMTE3r17sywL6zg4OIQ2GzZsGJpZLJbc3Ny9e/du3bo1LS3NYDDAFmVlZYMHD16zZs2IESNgM45IhlHdWrTNTA27iGwibgOex8GDSE1F376YMQOOjsjMxE8/Yf16eHjA1RUdy2zGwoUoLcUrr6BPHzQ0YPVqvP8+oqPRpw/aJ7qbt4NI0mgy4AYXdQ1nG2v8HZxhbyhFeTlWr8bXX2PYMFwRHw+RCM8/j+3bMX06OlZjI1auRFISZsyAqyuuePNNZGVh3ToEBkIgsBo17KENH8BeUe0qIn8Id9SC7emrjxzH9eIDff8+aQQEXQeHlmzZsmXChAlGoxFWY1l27NixKSkpY8eOdXR0REdgWTa62TPPPNPQ0LBp06Zff/11y5YtPM/DOpcvX05OTk5NTR05ciRsJR0D3VpYQ78Zsom4DRobcfgw5HJMmwZfX1wxfDhOncLhwygqgqsrOlZVFf74Az/8gLg4cBwUCvzpT1ixAr/9hj590G6D3QI3lxWgJd+fSn8vdjzsjcmE/HxQiiFD8B8MA1dXhIQgNxfTp6NjlZTgwgXExqJbN/yHRIKBA5GdDb0eV5SXIzcXEgmuOHsWlEIguJGpgGqeASywW+ZCmLIgisYd8tO+zO93H8b1Irzcvpx9v4hlIeg6ONzgwIEDkydPNhqNsI6Tk9NTTz31xBNP+Pj4oNM4OjpOb1ZaWvr9999//fXXGo0GVjAYDJMmTdqxY0f//v1hCyIeRIkjaAPaQg37CF8Hxgmdra4O1dVwc4O3N/6DZeHvj0OHcPEiOlxxMfR6xMSAZfEfYjH690d2NjrCU6FDNpcVoCVbywv+GXM/SwjsCqXQaiEWQyzGf7EsZDLodABoM4Zh0CH0ejAMJBIwDP7LwQF6PXgeV6xdi/R0sCyuuHABPA+B4H/wF3jNk6Ba2EQSD74epgLcLlS7iqiicScsy8j+ePM+XM/PWf3NnIkKiRiCLoXD9YqKipKTk7VaLazg5OT0t7/97amnnlIqlbhd/Pz83n333RdffHHhwoUff/yxRqNBWxobG5OTkw8fPhwQEADrETGRDq++vK27WIc2mKl+C5HPRGejFJSCYUAI/othcAWlACwWCyGEYRi0j06nk0qlhOfBMGAYXIvjwPPoCD2VrkqRtN6kxw2azMZDF0sSugfArrAsPDxgMKCiAj4+uIJSaLWorkZsLACNRlNaWtqjRw+VSoX2c3EBx6GqCno9ZDJcwfM4exaurhCJcMXcuZg+HVIprtiwAZ98AoHgWlTL1z0OSxVsQSRDidM3AAtzEdVvobo/YClDJ6P6jcTxZTAq3F5/HM1/P3U3ruemdPjx0cnODnIIuhoO1zCZTCkpKRqNBq0YMmSIv78/AELIgAEDZsyYoVQqcSeoVKrXXnvtmWeeWbdu3Y4dOyilAEpLS3fv3o2W1NTUTJ8+PT09XSwWwzpnGi59UeDPmGM/DtqPtlB9KpHPRGdTqeDsjIsXUVUFLy9cYbGgrAxXdOsGICMjw2w2R0dHq1Qq3JKmpqbDhw9LpdLY2Fixnx9YFvn5GDwYLIsrTCZkZaFPH3SQ4Z7Ba0tz0ZLFRQcTugfArnAcwsLg7Y1ly/Doo1CpUF+PI0dQXY2EBABnz579/PPPhw4dOnDgQB8fH5lMBttRSg0GA3eFjw9698bu3QgJQa9eoBSFhTh8GHPmQC7HFQoFXF0hk+EKpRKEQCD4fyxU8zxMJ2ATUQRRLwBYXMEFEYcg4vAUjFlUv5nqU8HXopNQPdWnEvks3Ebrs0688ft2nlJcQy2X/vDIA55qJQRdEIdrvPTSS4cOHULr/vznP0+bNg12w8HBYVYzNPvtt992796NVmRmZr766qsff/wx2lKta/jq5J41Z7MtlL/PlYM1jJmwVID1RKdSKhEdjdWrkZqKCROgUKCgABkZ8PFBYCCAsrKyjIyMvLy8xMTE4OBgqVQKq5nN5vz8/F27dhUXF0+aNAlX+Phg+HD8+COcnBAcDJ0O27bhzBm89RY6yKyAuLWluWjJvgvFNYYmZ4kC9oMQuLhg3jwsXgyWhb8/ysuRno7Ro9G/P4CePXtOmTJl/fr1ubm5iYmJMTExXl5eHMfBalqt9syZM+Xl5X369HFzcyNz5mDBAixfjuho8Dx27kRICMaOhUIBgeCmaP171LATNmHdGPU3IDJch4E4lohjieOL1LAX+vXUsAvUgI5Gtf8m8lm4XTbmnHptzVaeUlzDUSpZ9PADgd2dIeiaOFyVmZm5YMEC3NU+++yzBx98MCYmBq3Qmo3Lzhz59uS+JrMRzQjrDqtQqk8liifQqVgWAweishKHDqG0FBIJKiuhVGLcOHh4ABgxYoRIJDpy5MjSpUsjIyMHDx7s7e3NcRzacu7cubS0tOPHj1NKhw0bFhcXJxKJQAjmz8eCBfjpJ7i6wmjEyZN47DHEx6ODRDh5OogkjSYDbsBTurrk2JOhg2FXZDJMngy1Ghs34tAhODvjgQcwfryFYWouXKisrBw6dGjfvn03bNiwdu3anJycQYMGRUZGurq6MgyDmzKZTGVlZZmZmXv37lWpVIGBgW5ubujfHy+9hHXrsHEjCEGfPpg5E56eIAQDBsDfHyyL//D0xNChEAiaUe1iql0CmxAF4/QDWDe0hoiJdCSkIwltpPod0G+mhr2ABR3FfBKm4xBFovNtyD7x6m/bLDzFNaQi7uuHJoR7uUHQZXG46rnnnuN5HjfVo0cP2LHAwEDcFM/zzz333O7du3EDM8//Xpq9oGBXjaEJ12K9YB2qSyWKJ9DZvLwwYwb8/ZGfD4MB0dFISEBoqN5ozMrK4jhu9OjR0dHRO3bsOHbsWGFhYd++fRMSElxcXAghaElNTU16enpmZqZGo+nVq1dycnL37t1zcnIsFktsbKy4Xz+8+CL27kVVFcRiTJuGsWMhEqGDEGCER8i6c7loydLiI48FD+QYBnZFKkVyMpKTcQ3eZCouLl6+fHlsbGx8fPzs2bMHDx68Zs2aZcuWRUREDBo0KDQ0VKVSoSU8z1dXV2dlZR08eLCysjI+Pj45OdnNzY0Qgiv69EGfPrjR22/jWgMHYuBACAQANeyl9f+CbVii/hRcCKxBHIhsImQT0fg1bfwcHYfq/k1Ekehkyw/mvLshjVJcSyrivps7KdbfC4KujEOztWvX7tu3Dzf17LPP9uvXD//j/HlkZ6OiAoTA2xtxcejWDQyDzqDX48QJHD+OxkYolQgNRe/eEItxVXR09NNPP71w4UK0bs+ePampqePGjcM1dlUWvn9827nGWtyIcQHjAv4S2mQ+CXMhuGB0Njc3TJiACRNwDd5kKikpyczMDAkJGTZs2OzZswsKCnbu3JmWlubk5NS/f3+JRIIbUErT0tL279/v5eU1ZcqU0NDQ8+fP//zzzydPnhw4cGB0dDSu6N0bvXuj04zziVh3LhctuWRo3FV1KskzDHaP47jQ0NBBgwalpaUVFhb269cvJiZm/vz5WVlZqampS5YsiY6Ojo+PDwwMlEqluIZGo8nLyztw4EBhYWFgYODzzz8fFBTEsiwEgltjKqCavwIW2IIoXyeSYbAR1W/B/6EAQbtRXSpxfBnXf1S4AAAgAElEQVTEAZ3mp32Zn2zZRymuJWLZzx8c16+HNwRdHIdmCxYswE3Nnj37008/xf8oKcGvv+L8eUgkuGLfPpw8idmz4eoKQtCxdDpkZGDFChACiQQGA9LTMW4cxowBy+KqBQsWXLp0aeXKlWjdggULxo0bh2Y5tWUfHt9xtOYcWkWIdCzVLoEVqC6VOD6HO0EmkyUmJloslry8vLNnz0ZFRSUmJj755JOZmZnOzs6EEADnz5/PzMwsKSnhed7V1bVfv36BgYEqleqBBx6IjY3VarXr1q07evSoXq+Pjo5OTEwUi8XofP1de0hZTm8xoyXLijOTPMNg9wghTk5OU6dOTUhIWL9+fWpqan5+fkJCQu/evcPDw3c1O3nyZL9+/fr37+/t7c2yrFarLSoqOnToUG5urlKpfPTRR6Ojo6VSKQSCW8Zf4DXzQLWwBVE8QuSzYCvTCZhP4v8QdAiqpbpUIp+BzvHVzoNf7czA9aQi7vMHxyWG9ICg6+MAnDlzZs+ePWhdr169vvvuO0IIrmWxYOVK5OYiJQWJieB57NiBhQvh74+xYyGToQNRiqoqLFoEJyf89a/w9kZpKZYvx08/ITgYQUG4imGYH374IScn58SJE2jFzp07T58+je6qT/J37qosRFuI7H6qXQIrUP164jgfILjtCCHe3t4zZ84sKiravn37gQMHTp06NXDgwL59+6pUKgDFxcWLFy+urKx0dHR0cHDQNHN2dk5KStLr9YcOHdq9e/fFixeDg4PHjBkTGBjIcRxuCzHDDnEP3lpegJYcvFhSVH8hSNkdXQHDMD4+Po899lhBQcGmTZtWr16dm5s7aNCgUaNGxcbGbty4MS0t7eTJk4MHD3Z1dc3NzT1y5AiAMWPGDBo0SK1WQyBoD6rl6x6HpRK2IJKhxPFvsB3V/4FOQHWriHwGOsGXOw58k3YI15OJRQtnjx/Q0xeCuwIH4Mcff6SUohUMwyxZskQul+N/XLqEnTsxcSKGDYNKhSsmT8bWrdi9GwMHQiZDBzKZUFiIvDwsXYrQUFwRFoaJE/GPf2DfPgQF4RoKheLXX3/t378/z/NoCevk8NddS0tdOAvlYQ1RH7C+sJxDmywVMGZBHIM7hOO4sLAwX1/frKysvXv3rlu3jmXZAQMGsCy7evXqgoKCadOmJSYmKpXKqqqq4uJisVhMCElNTc3IyHBycpo+fXq/fv2kUikhBLfRcI/greUFaMXKM0ffiBqLrkMikURHRwcGBh48eDAtLW3FihXh4eEDBgx46KGHTp48uXTp0q+//trLywtAr169xowZ4+PjQwiBQNAuFqp5AaYTsIkonKgXACxsZqG6jbAOkQykxmOgOljDlAdTPkTh6DgWnv5zfdqqw7m4nqNU8u3cidG+nhDcLTgAO3bsQOvmzp0bExODG5WXo6EBwcFwdMR/iESIjMT+/dDp0LGMRpSWQixGWBj+g2Hg5AQvL5w5gxv07ds3JSVl8eLFuB4jEavvi3OenHhGxoDysBYhsnG08WtYgerXEXEM7iiFQjFo0KCQkJD09HSpVGqxWOrq6vbs2TNq1KikpCQnJycAAQEBPXr0QDNK6dChQwcNGuTk5EQIwW031D2IIQxPebTkj3M5z4YPdxRJ0KUolcqkpKTevXunpaUdPnz49OnTMTExPXv29PX1rays9Pb2HjNmTEhIiEgkgkDQbrT+PWrYAZuwboz6GxAZbEcNu8FfhDVYN+L0A+GbqCEN+s3UsBew4KaobhURvY0OojOanluxcc+pElxPKZMuenhSpLc7BHcRrqmpKSsrC6174YUX0CJKcSNCcJXZbGZZlhCCduB5Xq/XywFQCkJgtZdffnnx4sW4irCsani084xhnNoBtrhs1OVrKmEZxDf9G9bQ7mcspSBitMVTrnISy9FpXF1dx48fbzQaOY6rqqpqbGzs2bOnSqXCVYQQNEtOTpZKpSzL4ra7eLFh154TaWkFXC9q9ESLtGbj+nO5swL7oashhLi7u0+bNi02Nnbbtm27m50/f37w4MHz5s1TKBQQCDoC1f5KtUtgE6JgnBaBdcet0f0B6xDpRIAFoySyiZBNJJZqathC9ZthPIZWUN164vgiiALtdqmhad6v6/LLq3E9Zwf5D49MDnF3geDuwh05csRkMqEV8fHxYWFhaJGnJxwcUFyM+HgolbjCbEZ+Pjw9IZUCWLJkSWRkZO/evcViMWzH8/ylS5cOHjzo7e0dExEBX1/o9Th1CpGRuILnodGgogJ9+6IloaGhcXFxhw8fBiGO8WEus0aKPZxhu/3Vxfuri/H/GwtrLYYV/hEzbpp/DDoTwzBSqRRX0Wa4gUKhwO3V0KDfs/fkzrSC3OPnKaUApHLW6GlGK34tPvRgYD+CLonjuJCQEB8fn+zs7LS0tLq6Ond3d4VCAYGgI1DDXlr/PmzDEvUn4EJxa/jL1LAb1iGySbgW60bkc4h8DszFVL+J6jbAchb/gzZR/WYim4L2OXOh9k+L/yivq8f13FWOPz062d/FCYK7DldaWorWjRgxAq1xdcWQIUhLg7c3Bg0Cpdi1CydO4JlnoFQCqK6uzszMjIyMHDNmjI+PD8uysA6lVKvVpqenp6WlEUJSUlIgEiE4GGFhWLQITz8NLy+cP4/168EwGDQIrRgxYsRxTYXrQ6NkYX64t3l4eDg6Op4+fbq+vt7JyQnNKKUACCG4XfR6U/qBorRdBUcyS8xmC64hPUvqE9Ca0sbajAtnEroHoMuSy+UJCQnOzs7Lli2DQNBRTAVU81fAAlsQ5etEMhy3iupTQY2whqgPuAC0iAskDn8hDn+BKY/q1lL9JvCXcBXVriKyKWiH7HOVTy1ZV9ekw/V6ujl/N2eSh9oRgrsRV1NTg9ZFRUWhNRyHmTNhMGDDBuzeDUpx4QKSk5GYCJkMQEpKSlpaWm5u7oIFCwYMGJCUlKRWqwkhuCmz2ZyXl5eamlpVVeXl5TV06NCQkBAQAg8PPPooVq7EggWQy6HVwmjEQw8hKAgtKWmoORXj6tv3cQgAFxeXoUOHpqene3p6Dh06VKlUVlRUFBUV9e/fv1u3buhkZrPlSGbJzrSCAxlFer0JLeEuE1EdMTlRtOLTAztrRfXoIB4e6tgYf9x2XDMIBB2Cv8Br5oFqYQuieJjIZ6EdqO53WIfIJqFNoggiiiDKV2DMpvq1VJcK2gRTNkwnIArDLUnNOfnGmu0GsxnX6x/g88Xs+x2lEgjuUlxNTQ1a5+LigpsICsLjj+PoUZSVgRAkJiIhAS4u9Q0NGzdujIqKmj59emxsbFpa2v79+48ePTpixIjExESJREIIwQ14nj937lxqamphYaFKpRo7duygQYMApKWlKZXK/v37Y+hQODsjOxsNDVAqER6OmBiwLK53Sd/4xYnda85mWxgegmYsy06ZMsVgMOzcuTM9PV0ulzMM4+npGRsbi05DKXJyz+1MK9i772RDgx5tkZQwJicLWpFvqfzo181sA0FHGJIYGhvjD4Gg66I6vm4eLJWwBZEMJY4voj3MhTAdhzWIiEjvg7VYiGOJOJY4vk6N6dCto/q1RBQGG1GKr9Myvk47SCn+x6iIoA+mjZFwHAR3L45hGLSO53ncnL8//P1xPYZhzp8/v3fv3r59+44bN+7RRx89evTovn371q1bFxwc7OvrSwjB9SilJpNp1apVFRUVCQkJQ4YM6dat29GjRzdu3GgwGCZNmoQrpFL064d+/XBTMk7sInEQs6zOzENwVUBAwMMPP5yVlXXu3DlKqYuLS3R0tFqtRqchBO7uKk9PtVotb2jQoy3SUqYxxoJWUILGSF51gIVAIABPNc/DdBw2EYUT9QKARTtQ7SpYh0hGgFHDVkRCJMMhGQ6qg42aDMaXVm9JKyjGDWYnRL+cPIQhBIK7Gufs7IzWXbhwAbZTKBSTJ0/es2fPiRMnjh8/PnTo0KSkpIiIiIyMDAcHB0IIgNzc3LS0tPLycolE4u/vn5SU5OnpGRkZOXbs2LCwsDNnzixbtqykpMTT03PEiBFRUVGwmoIT/7XX0JSecc+u++EgagnLQNDMuxluI3c31czp8TOnx586VblzV8Gu3SdqahrRClEVYbSEl1O0whxN3rp/kgMjQbs5OSkgEHRZtP5datgBmzDdGfU3IDK0BzVS/QZYSTYJ7UFksMW5Gs1TS9YXX6jB9ViGvDJu2IPxfSC4B3DOzs5oXVZW1owZM2AjQkhgYKCfn19eXt6uXbu2b9+emZmZnJyclJTEcRyAAwcOfPLJJz4+Pu7u7gqForKycsOGDU899dTo0aPr6uqWLVt24MABJyenpKSkhISE7t27w3ZOYrnroXNnVyx2mTnccUAvEALBnRMS4hES4jHvT8Nzcs7tTCvYu+9UQ6Me1yOAtJRowyhaYeDNBQ4X5oUOhkBwD6Paf1PtEtiEKJhuP4B1R/tQw1bwdbAG40wkg3G77Cs8+8LKTQ16A64nF4s+mj52WFggBPcGLjAwEK3bunXrBx98gFvCcVxUVFRAQMDRo0f379//448/uru7+/n5mc3mDz74QK1WP/bYY/7+/hzHlZWVVVRUEEIMBsP3339fXV09YMCAhISEoKAgQghu1bZt24wVlyo+WSUL83N9aJQs2BuCO4oQEhXlFxXl98xfRx0+ciZtV0H6gdMGgwlXSc8y2jAerVtafPjhoHgpK4JAcE+ihr20/u+wDUvUn4ALRftpV8M6RDYe4ND5KMWPe48s2J5u4Smu59NNtTBlfJCbCwT3DC42NlYqler1erQkJyfn2LFjMTExuFVKpXLYsGGhoaEHDx5Es7Nnz6alpe3cuTM8PJwQAiCwGQCGYfz9/UeOHBkVFSUSidAOhw4dOn78OJrpTpSee2WRQ98Q17mjxR7OsMUwj+BXe4/G/0P52hRYKmEFonqXiOPRim4SBe5VHMcmDAhKGBCk0xnTDxSl7SrIPFpiNvOSMoaYQTm0psbQtKY0e1ZAPwgE9yBzIdXMByywBVG+TiTD0X6WMmo8DOsQ2VR0vkaD8fU127blFeEGfXt4fT5zXDcHOQT3Ek4ikfTr12/fvn1oxbvvvrtmzRq0j4eHx4QJE4xGIyGktLQUQK9evXAVIQTNRCLRhAkT5HI52u29997D9RozTzVlnVYNj3aeMYxTO8A6ck7so3DCNSgdTRsXwgqEbCCKsRC0TiYTjxwRPnJEeEOjPiPj9J69JzeVndT582jdz0UZM3rEsoSBQHBP4S/ydY+DNsAWRPEwkc9CR6DaVQAPa4hjwPVEJ8svr35uxcbztZdxg2lxka/fP5xjGQjuMRyAUaNG7du3D634/fffd+/ePXToULQPwzBSqRSASCSyNMMNCCFyuRztlpaWtn79etyAWiya7Zn1e3OnL3jjlAfXZDbCdkT2AG38CqBoC9XvIvxFMK4QtMXRQToqKWJUUkTQ8YP/KtqG1pU1aTaV5d/vEwmB4N5BdXzdPFgqYQsiGUocX0THsFDd77AOkU1FJ1t1+Pi7G3aZLBZcT8yxb4wfPrlvBAT3JA7A3Llz//73v1ssFrTioYceysrKcnZ2RkcICgqSSqXp6eljx45FM0opAEIIOkJdXd0jjzyC1jEW/uP7H+G6OS4s2LOmNNtCediE9YY4BsajaJuF6tYSxeMQWO3+4MiPTm+3UIrWLTqVPs4nkkAguEfwVPM8TLmwiSicqBcALDoCNewGfwHWIHIiHYtO02gwvvH79q3HC3EDV0fFgln3R/l6QHCv4gB4e3uPHj1606ZNaMX58+dnz569fv16kUiEdnNzc5s1a9ZHH30klUqjo6NFIlFeXt6pU6fmzJmDdjMajdOnTy8tLUXr7rvvPk9PTwD/iBn3cNCABQW7tpQXwBZE9gA1HoUVqO43ongMIBBYx1mi6N3NO6vmPFpXWH9hb1XREPcgCAT3AFr/HjXsgE2Y7oz6GxAZOor2N1iHyMaDyNE5TlRceG7FxtIaDW7QP8Dno+ljXRwVENzDODR77rnnNm3ahNZt2bJl7ty5S5cuJYSgfTiOmz9//qJmJpNJLper1epBgwah3SilKSkp27dvx00999xzuKqHo/Pn/afk1JZ9eHzH0ZpzsA6RJtP6d0G1aJO5BMZjEMdCYLXhHsFZNedxUz8UHhjiHoSuRqVSxcfHOzs7QyCwDtWuotpfYROiYLr9ANYdHYW/SA17YB0im4pOQCmWZmR9smWf0WzB9QjBrAHRL92XyDIMBPc2Ds1GjBiRnJy8ceNGtG758uV//vOfBw4ciHYLCAh4+umnCwsL6+vrOY7r1q1bSEgI2u3AgQOrVq3CTU2cOHHIkCG4Xp9u3suGzN1VWfiv49tKG2vRJiIn0jFU9zusQHWriTgWd5TFbMnZliNXyv2j/KUOUovJcjT1aDevbr6RvmKZGHZmuEfIJ3k7cVNHLpVm1ZyPdvZBl6JWqxMSEliWhUBgBWrYS+vfgm1Yov4EXCg6DtWtAcywBhcMUSQ6WtXlhldWbz105jxu4KSQ/WvqmMHB/hAIAA5XffTRR1u3bjWbzWhdeXk5OohXM3SoyspK3JRIJPrXv/6FVgzzCB7s1vP30uwFBbtqDE24KSKbSnW/wwpUv5koXwdxwJ1DCOHEXP7ufLlS7h3ufebombM5Z519nBmWgf0JdHTxd3A+21iDm/qh8MBXA6ajK+At/KkDp6qKqiKTIl18XCxmS/aW7MbaxogREWo3NQSCFpmLqGY+YIEtiPI1IhmOjkSpdg2sQ+TT0dG25RW99ceOyzo9bhDh7fbZzHFeTkoIBM04XBUWFvbWW2+98cYbuHv9/e9/DwkJQes4hpnWI+Z+n8ilZw5/e3Jfk9mI1ohjwQXCXIw2UR3VbSLyabhzGJYJiguqLKwsOlQEguM7jvtF+nkGe3JiDnZpmEfwz0UZuKm0ylMnLleFqdxh9whDnL2dS46VnNx3sv/k/hWnKs7lnfMJ93FwcoDgLkKNGUQ8AB2Cv8jXPQbaAFsQxcNEPhsdihoPwVIKaxAJkY5Hx2nQG95Zv2tD9gncgBDMHRg7f/QgjmUgEFzF4Rqvvvrqnj17duzYgVa8//77v/zyC5r16dNn3rx5vr6+uHMqKiq+++67I0eOoFlVVRVaN2zYsJdeeglWkHGix4MHTvDtvfDEHr3FhFYQ2QO04SNYgepWE/k03FEypax3Uu/05el7l+xVdVcFxAZIHaSwVyM9Q34uysBNUWBhwZ6vBkyH3SOEOPs4+0f5Fx4sPL7jeG1ZrVwpD4oL4sQcBHcR2rgQbCpRvQ1waA+q4+vmwVIJWxDJEOL4IjqcdjWsQ6RjwKjQQQ6dOf/6mm3ldfW4gYuj4r3JowYF+0MguB6HazAMs3jx4ri4uPLycrQkuxmabd68+bPPPnvsscdefPFFX19f3F6lpaUffPDBjz/+aDQaYQUfH58VK1awLAurdZc6/iN6XJPZiFYQ2UTa8BlgRptMOTCfAheCO8qth5tcLT+bczZyZKTKXUUYAnsV3c3HVepwUd+Im9pZeSq3rry3kxfsHsuxPWJ61JyrObDygEeIR7/x/RROCgjuLgQs1a2GpYI4fQHiiFvEU83zMOXCJqJeRL0AYNGx+MvUsA1Wkk1BR9CbzF+nHfxpbyZPKW4wKNj/vcmjXBwVEAhuwOF6np6e27ZtS0xMrKmpQVsMBsNXX321aNGiWbNmPfnkk3Fxceh8hw4d+vbbb5cvX240GmEdV1fXbdu2ubm5wXYKTozWMK5EMpQadsAKVLuSKN/CHXXp/CXtZa3SVVlbXmtoNIilYtgrhpBhHsGrSo6hLQsL9nw/8EF0BVIHqcpDRSlVuirderoRhkBwt2EAUGM6rZnJOH0H1gu2o/XvU8MO2ITpzqi/BZGjo1HdGlADrMH6EHEc2u3o2fLX1mw7V6PBDaQibv7oQSkJ0RAIWsHhBr169dq0adPIkSMbGhpgBaPR+HOzqKiolJSUSZMm9ejRAx2tpKTk999///XXX3Nzc2ELpVK5adOm0NBQdAb5FBh2wApUt5Y4vgCiwB1i1BtztuWo3FShg0Lz0vLKCsp69u8pkohgr5I8Q1eVHENb9lafzrx0rq+LL+xebXltxckKqYO0sbax/ER5QGwABHcZwuA/zIV8zTTG6VuIImELql1FtYthE6JgnBaBdUfHo1S3EtYh8mkAQTs0GoxfbD+wPCObpxQ3iPB2+3DaWH8XJwgErePQkri4uF27do0bN66qqgpWy272/PPPR0VFjR49evDgwQMHDlSr1bhVGo1mf7OtW7dmZ2fDdp6enqmpqdHR0egcRDKEMt3BX0CbaBPVbSTyabhDig4VNVxqiB4b7RXm1VjbeDL9pIufi4uvCyEEdmmAa4BSJK036dGWhSf2/DI4BfbNZDCdPnTaqDWOfmp00aGiwoOFLr4uSlclOll9va76Qr2fr7NYzEHQ6Rj8F3+Rr32QqD4g0vtgHWrYS+vfgm1Yov4YojB0AmrYD/NZWIUlskloh/Si0jf/2F6pacANWIZ5fEi/Pw+P51gGAsFNcWhFbGxsRkbGfffdd+LECdgou9kHH3zAMExQUFBERER4eHhwcLCXl5e7u7ubm5uTkxOuV1tbW92srKyssLCwoKAgLy+vqKiI53ncqvDw8E2bNvn6+qITsUQ2iTZ9BytQ3TIin4Y7oeZ8zan0U76Rvu5B7mKZOHxYeHVxdVFGkVwlV6gVsEscwyS690w9n4e2HLxYsrf6dKJbT9ix83nnK4sqA/sFevfyZlgmc31m0cGi6PuiGZZBZ3J0lH6xcPvuPSc83NU9erj6+jr7+7n4+bn4+jhLJBwEHYzFtaiBaubDoZg4/AVtMhdRzXzAAlsQ5WtEMgKdRLsC1iHSYWC645Zc1uk/27p/9ZHjlOJGPd2c3508KtLbHQKBFTi0zt/fPyMjY968eStWrMAt4Xn+VLM1a9bgBk5OTgDq6urQCWbPnv3VV18plUp0MiKfSpsWATzaZDoB03GIInHbydXyfuP7qT3UUoUUgKOzY/zUeFCIZWLYsSTP0NTzebDCB7nbBo4MYAkDu6Sp0pw+fFrRTRE8IJhhGc9QT98S3/N55139XX0jfdGZCCEvv5h8+bL26LGz5RV1SMd/MAzxcFf7+7v4+jr7+7v6+zr7+rpIJBwE7cLgf1Ha+CUsVUT1NsChNfxFvu5x0AbYgijmEvlsdBJLJTXsgpVkU2E7SrE+u+DDTXvrmnS4AcswDw+OfXrEADHHQiCwDoebUqlUy5cvnzRp0hNPPKHRaNCh6urq0AkcHR0//vjjJ554ArcH60skCdSwH1ag2pVEFYnbTuYo84nwwTXcAtxg9wa79ZSynN5iRluKGy79UZozxT8adknlphr5xEgAhCEAGIaJGhsVNSaKEILOx3Hs2289MP+F5UVFVbiK52l5RV15RV36gSI0I4R4eKj8/Vz9/Jz9/Vz8/FwCA7qzLAOB9QiDllDdalgqiNMXII64EdXzdfNgqYAtiGQIcXwJnYbqVgIWWIP1JJJE2Ki0RvP22p0Hi8+hJT3dnN+bPDrC2w0CgS04WGHq1KkJCQmvvPLKkiVLYN/GjRv35Zdf+vv743aSzYBhP6xA9RuI44tgVOhqiuovFGiqxnqHixkWt4ucEyd0D0yrPAUrfFGwO9k7QsaJYH/IFSzBNRiGwW0kl4vff2fqX55dUlmpQSsopRUVmooKzYGMIgABAd0XffswBLZh0ApqTKc1Mxmn78B64To8vfwcTLmwiagXUS8AWHQWM9WugXWIfCbAwmp6k/nHvUcW7TliNFtwA5ZhHh4c+/SIAWKOhUBgIw7W8fLy+vXXX+fMmfPss8/m5eXB/kRGRn7++efDhw/HbUekIyjrBks12kT1VL+eyFPQ1Sg4yUuZa9/N2TLBt/fcoHgvuRq3RZJnaFrlKVjhgr7hp6KMp8ISIWhJt26KD/81/S/PLNFotLDCE48NJYRAYBsWN2Eu5GumMU7fQhSJq2jDv6h+B2zCdGfU34DI0Wmofgv4C7AGERHZZFht76mSdzfsPl+rQUvCPLu/80BSmGd3CAS3hIMtRowYkZOTs2bNmnfeeSc3Nxf2ISoq6vXXX580aRLDMLgzWCKbShsXwgpUu5zIZwMEXYqHXKUUSetN+iXFh5edORLv2iMlMG6oRzBB5xrmEcwSxkJ5WGFR4f6Jfr295GoIWuLl6fT+u9Oee2G5TmfETcXG+Mf1C4DAZgxujr/I1z5IVP8i0mQAVLuKNv0CmxA547QIrAc6E9Uuh3WIdCwYF1jhfK3m063pW48XoiVSEffn4fEPD45lGQYCwa3iYCOGYaZOnTplypQNGzZ8++23W7du5XkedwLLsmPGjJk3b959991HCMEdRWRTaeM3gAVtMhfDeATiOHQpBAhSdj9acw4AT+mBC2cOXDjj59Btin/09B6xSpEUnUMtlvVz8Tt4sQRW0FvMHx7fsaD/FAhaERLs/s4/Jr/86iqTyYJWEEKeeGwoBLeAMGgTNVDNc3A4A1EfWv8WbMMS9ScQhaFTmU/DeBTWIbIH0Ra9yfzj3iM/7Mk0mM1oydDQgNfHD/NUKyEQtA+HW0IIGd+stLT0p59+WrFiRVFREW6XkJCQmTNnPvLIIz4+PrATrAeRDKWGnbAC1S4h4jh0NcGq7kdrzuEapY21n+Tt/PbkvmSfiNmBccHK7ugESZ6hBy+WwDpbywv2VZ8e7NYTglZER/m99Lfkd9/fQClFS9zdVd2cHSC4FQysQmnjl4AIsMAWRPkqkYxAJ6PapQCFNbgQiGNwU7tOnnl3/a4KTT1a0l3p8ErykNGRwRAIOgKH9vHz83u7WV5e3tq1a9evX5+VlWU2m9HROI6LiYkZP378pEmTevXqBTsknwHDTliB6ncQSzlYL3QpwcruaEmT2biq5NiqkmMxzj4P9eyf5BnKEhq8AC8AACAASURBVAYdZ4RnyDs5myms9X7utvgRPUQMC0Erhg/rdfFiw3eLdqEllZWalDnfTZoQO+vBAXK5BAIbsLCBCbYg8jlEnoLORpuobj2sQ+Sz0LqTlRffT919pKQMLWEZZvaAqL8kJcjFIggEHYRDB4lo9vrrrzc0NGRkZOzfv//QoUP5+fnl5eW4Vd7e3r169erfv/+gQYMSEhIcHBxgx4hkMGW9YSlD2yxUu5I4Po8uJUTlhps6VnP+WM15D5lyRkDfKf7RzhIFOoK7TBnh5Hm8rgLWOdNw6ZfTBx8PHghB66ZP619T2/jbmiO4nkIhaWoy6PWmFf8+uG173pyHBo0d05tlGQiswuBWUIDgpogkkShfRuejurWgjbAGURDZ/WjJhfrGr9MOrsnMs/AULenbw+u1ccNCPFwhEHQoDh3N0dFxVDM002g0+fn5Z86cqaqqKi8vr6qqqqmpsVgs9fX1FosFAMuySqWSZVlnZ2d3d3cvLy93d/eAgIDw8HC1Wo2uhCHyabThU1iB6lYRh6dBJOg6gpTdCUDRhkpd/Wf5aV+d2DPGu9esgLg+3bzQbkmeocfrKmC1Lwt2D/cICXR0gaB18/40or5et217Hq5ydJD+8tPj6QeKfvp5r+aytqa28dPPt6xec/iRuYlDEkMhaBNhcCsIbk7Ui6i/AFh0PqpdAesQ2QMgClxPZzQty8j+bvfhJoMRLemudJg/euD4qF6EQCDocBw6mVqtHtgM9wAim0IbvwQ1oU18HdVvJLIH0HU4iiSecnW5VgMrGHnL+nPH15873kvtMaNH7HjfSCkrwq1K8gz7ND8NVjPylteOrl8+5GGGEAhaQQheeG5sTU3j0WNn0eyhlIFOTopxyVFDhoSuXHlwzR+ZRqP5/Pnat/+5tleY55+eGB4Z4Q3BzbDocKwbo/4ORI7bwHgE5kJYh8in4xo8pRuyT3y6Zf/Fhia0hGOZGf37PJOUoJCIIRB0Dg6CDsS4EOl9VLcOVqDaX4nsAXQpwaru5VoNbFGgqXwzK/Wz/LQp/tEzAmK95GrYroejc5Cye1H9BVgtu7ZsZcnRBwP6QtA6jmPffuuB+S8sLyqq8vBQTxgfg2aODtLHHxs6YULM0mUHNm7KoZQWnKh4Zv7SAfE9/zxvhJenEwQtI+hYRM6ovwfrhtuCapfDOkQcDy4YV+05VfLJln2nq2vQiiEhPV4ZN9TXWQ2BoDNxEHQoIp9DdetgDVMBTMcgikHXEaJy21VZCNvVGbWLCtN/KjowxD14VkDfBLdAAtuM9gorqr8AW3ySt2OYe5CHXAVB6+Ry8QfvT/vrs0sfnjOY41hco7ur8rlnx4xLjvr2+13Z2aUAMg6ePpJ5Zszo3o/MTVSr5RD8LxYdiSHqjyEKw+3BX6SGbbCSfAaaHT1b/tm29GNny9GKwO7OL96XODjYHwJB5+Mg6FiiCIh6w5QLK9CmJUQdg64jWNkd7WChNK3yVFrlqR6OzrMC+s0KjCOw1hivXgtP7EFLGBAeFDdoMhv/lvnH4sFzWEIgaJ1aJf/kw5kuLo5oSXCQ+6cfzTx67Oy336UVn7lgNvOpG7N3phVMmxI3Y3q8RMJB8F+ERcchyteIZCRuF6pdAWqCNRhXIh11urrmq7SDW48XohVOCtmTw/o/GN+HZRgIBLcFB0FHI/IUevlvsALVbyGWl8C6o4sIUbmhI1zUNXrKVQQ26Kl0DXR0KW64hBvIOFGT2YiWZF76/9iDD7iqy4Zv4L/r/P9nH85hbxAVkOUCB27FbWqmqaXlSrPSlvV03+XT3S6zMjXLHJXdluNOLTFnKk40FVwMEXGAqGw4cPa43l6ft+dTL0f5o4DnwPX95q/KOfJMVB8wd+Xj44a7SogPW/n19EOHc75emVJUVGUwmL9fe2THrrNPTu41YnhHkYiA+b8IGgiRjyOKJ9FkqJnqN0CYGtEji345sPlUhs1O4YhMzD/Rs/PT/buppBIwTBPiwTQ0IhtOqz+GvRR1s1HDeqJ6GS4iTOUp5XiTzYr70MbNe1nihDZu3qinoUExX104hFp0VrOfXF1k0MKRL7IPJvq27uQZDOb+EEL69Y1K7N52yy9p69Yf0+lMJSXVixbv2vzzqadn9u+RGA4GHBoINe0n5nRI4tEkqHEr7KUQwE5F41abCrXn4YiIkIc7xzw/uKe/RgWGaXI8mAZHJEQxkdZ8CQGofh1RPgMihyvgiKitm09W5U3cq6SAdgu7jFGJpai/IUHRX104BEcSvEJ2Xs+kcMBG7a+e3PJz0mw3sRTMfZNKxY9PTHxoeMeN//l905aTFovt2rXS+W9uSogPe3rWgIhwP7RoIjQUe4W9YjrRfEJkQ9D4qG4thNmXF1aoVcCR3pFh84b2jgrwAcM8IDyYRkAUk2jNCsCKOtmrqOFnopgEFxGp8c2qvIn6I8DMyF4vxyaJCME9idL4tXHzvlxdilrOlhdOaJ2w8UoaHLmuq3zt1M9fJk4UEQKmIajV8lkz+w8f1uGb7w4dOnyBUqSlX33muTV9+7R7elb/AH93tEyEQwOiBlr5AtxeJcqZaEzUnArrBQiz4XwcaukQ4v/ykN7d24aAYR4oHkxjEPkQ2RBq3AEBqG4NUTwGiOAK2ql9UX8qXrqw65ikgHa4P4MDo1bkHEEthfrKMa06nCq9llddCkdSbl5cmn3gpZgBYBpOcLDnW2+Oyb5wY8XKlHPnCyilBw9dOJqaO3pU52lTeqtUMrQ4IjQwO61eCNs1on4b4NBIdN9BmEtlnieuB+Iv2vp6zR2YOCQukhAwzAPHg2kcRDGFGndACNtVatpPpIPgCtpp/FBPYSqvZYkTwtU+uG9Dg6JX5ByBIyk3cxd3f/TRlNUmmxWOrLhwOFLtOyI4FkyDio4KXLxoclr61S+X7716tdRqtW35+dRvezMem5j46NiuYjGHFkSERkD1G2ErJO5LQNzQ4KxXqekwhFl7tgOlBLeFeGqeH9RzRMd2IkLAMM6BB9NIJPEQx8GSAQGo7jsiHQRXEKn2RT3184sIV/ugIcS4B4QqPfJ1Fahl5/XMebFJ82IHfnRuNxyhwPz05GClewePIDANLSE+bOXyGbt2n1vz78Pl5brqauOq1Qe2JqfPmNZ38KA4QtAyiNA4qOkILXtM5LESXBAaFNV/B9ghQLlBvv1CBIAAd7fZ/buNTYjjOREYxpnwYBoNUU6nla9ACPNJWM5C3BFOz1um8pIqy0w6CPbvvOMdvYJGBMeiIQwJil59MRW1FOgqLlQVTQnvfrQo71DRJThisFpmHV33Q9+pEWpfMA2N50UjH+o0aGDsz1vTflyXqtebi4u1Cxb++vPWtNmzBnTqGIpmj4jQeKy59rKxIvevIElAQ7FXUcMvEOY/52PdlR7T+yRM6NZeyvNgGOfDg2k0RDaCcp/BdgMCUN33xH0RXEGkxvdY8RUIRoH56cnhap9ItS/u25Cg6NUXU+HInsLsKI3fJ10fGX/gm/yacjhSZTZMO7z2h77TWrt5gWkEMpn48YmJQwbFfb/2yI6dZ+12mpNzc96r6xLiw56dndSmjS+aMw6Nyl5hr5hBNAuJbCgaAjVsADVAAKtdFBQ4a/dDfcUcB4ZxVjyYRsQRxRO0eiEEoMadxPYquEA4vXZqv2PFV1AfBqvl2dQNm5JmekgUuD/tPYICFZob+irUsqsw64WY/hqJfFnihMcOfKu3muFImUk38+iP3/Z+opXKE0zj8PJSzXtp2LixXdd8f/jgoQsA0tKvznrmu0EDY5+e1d/LU4XmSYTGRg208kW4vUqUM3F/LDaTufJ7OQchOMWoh7sMAMM4Nx5MYyKKibTmS1Ad6maj+n8Tt3/C6UVqfFF/hfrKV05sWdVrMkcI7gMBhgbFfJd7DLVcri7NqSpqp/GLVPsu7DLmhd9/slMKRwr1lRMOfLOi5+OdPIPBNJpWoV5vvTkmM7Pw61X7MzMLKaW/7c04dDhn7JiEyZN6KBRSNDciNAU7rV4I62WieRfgUX/VRtMv6VnXCte+0acUwnDKqWAYp8eDaVTEjSjGU90aCED1/yGqOSBucG7tNH5whAATW3fZVZhZaTbAkdTiy4sz978SNxD3Z2hQ9He5x+DIjuuZ7TR+AAYFRj0X1XdZ9kHcQZXZMOPID4u7P9rXLxxMY4qNDVr6+ZOHDl9YufrAzZuVJpNl/cbjO3adfWJyrzGj4zlOhGaDcGgq1LAJtpvEYymIGwQrKK9am3p686kMg9myfuIJCCTpBnEcGMbp8WAaGVFMpbq1gA11ojVUv4kop8O5tXXz4QixUYq/UPKSBV3GDA6MGhIUNevojzZK4cjqi0ej3f1HBMfiPnT0DA6Qq28atKhl5/XMl2OTcNuc6H4lxpqNV9JwB3qrefbRdTMje70cmyQiBEyjIQT9+kb16hmxa/f5b787VFmlr6oyfPnV3uRt6TOm9e3XNwrNhAhNiJqP0rLHRB4rwQWhLpmFRWtTT28/e8FmpwDiA2+19yuGMEQ5DQzjCngwjY0LIrIh1LgTAlD9v4lyCsDBick4PlTleaW6DH8KU3ktS5wQrvYB0NO3zQsxAz7P3A9HKPBG2tYwlWeMewDuFQGGBcd+l3sMteTrKs5X3GjvEQiAAG91GlFjMW6/nok7oMCqi0cvaosXdhmjkcjBNCae50Y+1Klfv6gNG45v/vmU2WwtKCh/571fYqIDZz+d1D4uGC5PhCbFgZpozVKifhdECkesNvvujNzvj6RlFBbhL57sdBYCccFEOgAM4wp4MI2PKGdS404IYSukxj1ENhzOrZ3a70p1GW7r7x/xSdexbmIp/vR0u94Xqm7tvJ4FR4w26/PHf9qUNNNDosC9GhEc+13uMTiy43pme49A3CYi5OMuj+is5gO3cnFnB2/ljktZtajbuA4eQWAamZtKNmtm/4cfjv/hx9QdO8/a7TQr+8aLL//QIzH8uWcHBgV6wIVxaCwicP6EC9PT1vO3e705qp2XWzi4YBAx7kBrMG46lfFD6plbVdX4u0C36qQ2VyAMUU4DODCMK+DBNAFxe0jiYU6HAFS3msiGw7lFanx3FWYRYGZkr5djk0SE4C8I8EH86Eva0lxtMRwp1Fe+cmLLql6TOUJwT9p7BIaqPPNrylHLruuZr7UfTPD/8CLR4u7jXz6xKeXmRdzZdV3lpIPfzY3qN6tdb44QMI3M10c976VhY8d0WbEq5fcTeQCOHb908tTlYUM7TJ/ax8NDCVdERGgQIg24EMKHgw8HF0K4EPBtQeS3qmrmrN2afaM4vq3XlF6tcQeZhUU/nTy/7cwFg9kCR57ofJ4TUQhBVEQ+FgzjIngwTYIoZlBzOoSwnIclHeJ4OLF2Gj8lL1nQZczgwCg4ouAly3s89mjKqkqzAY6kFl9enLn/lbiBuFfDg2JW5BxBLTcN2tNlBfFeIfiTjOOXJU5898yOjVfScGdWu31xVkrKrdxPuj4SqvQA0/jCwrw/+mB8WvrVr1fsz7tcbLXaf91+Zt/+rAmPdntsYqJUysPFENSXSAMuhHAh4MPBhxMuBHxrECVqOVtwc+7a5LIaPYDNpzKm9IrH35ms1gPZl9emnk6/dgN35iYxPRp7AcIQxXgQFRjGRfBgmgSRDaJcKGz5EIDq1hD3eDixjh5BmwbMau3mhTsLVrov6jZu1tEfbZTCkdUXj0a7+48IjsU9GREcuyLnCBzZcT0z3isEf8ER8k7nh4KV7p9l7MNdnS2/Pnbfyhdi+j/RtpuIEDCNLyE+bOXX0w8dzlmxMuVWUZXBYP5+7ZHtO89OeaLXiOEdRSICl8HhLkQacCGECwEXAi6E8OEQtwNRQYBd5y++sWm30WLFbblFZVk3imMCfXHbtbLKzacyNp08X6k34q7iWwX+a9BFhdgEQTiieBIM4zp4ME1ERJRTqPZ9CECNvxFbPrhQOCtvmcpbpkJdevq2eSFmwOeZ++EIBd5I2xqm8oxxD0D9tdP4hat9LmlLUMuuwqzXOwzlCMHfzYrs5S1VvXNmu9FmxZ3VWE0fntv9240L78ePaqXyBNP4CCH9+kYldm+75Ze0deuP6XSm0tLqRYt3bf751LQpvfv1jYJrEOF/iNTgQgkXAi4EXAj4EMJHQOSD+qMUy/alfp3yO6X4q5/TMtv5+xy6eOWH1NPH8/IpxV3wnGhgTPj03gkdgj3sJUmwQwgiGwIuGAzjOngwTYXIx9OaZbBXom42qltL1PPh+p5u1/tC1a2d17PgiNFmff74T5uSZnpIFKi/YUExy7QHUUupseZU6bXuPmGo5ZFWHaPc/V44/lOBrgJ3dbL02sP7vn4uqu/0iB5iEQem8Uml4scnJg4f1uHfa4/+uv201Wq/dq30nfd+SUgIe+dfYxUKCZwbkXQlXhvBhUHkgYZgtFjf2LR71/mLqGXTyYzd53NLa3S4Kw+l/NEucZN6dPJTqwBQ/VrYSyAMUU4Fw7gUHkyTIXIin0B1KyEANWwiquchUsPFEeCD+NGXtKW52mI4UqivfOXEllW9JnOEoJ4eCo5bln0Qjuy4ntndJwyORGv8f056+vW05N9uZOOujDbrosz9m66dmd9haD//CDBNwl2jeGHu4Inju3275vDefRmUwmqxKxQS1MligdEIqxV/EIshk4HjQAgag80GkwlmM+x2cBxkMkgk4AJh9YLZCqkVPI8/WK0wGiEWQypFPZVW6+asTT5//RYcMVmtphor7qxTaMBj3TsObR8h5Xn8P1aq+wYCieMgjgfDuBQeTBMiiiep/jtQC+pEddTwH6KcCden4CXLezz2aMqqSrMBjqQWX16StX9e7EDUU2s3ryiN34WqItSypzD7zY7DeZEIjqjE0qWJ49fkHvs8c7/ZbsNd5deUz05dPygw6h/tB4coPcA0CT8/zev/GPnwqM4rVqU88/QA1Mlsxp49+PZbnD4NkQgJCXj5ZcTHQyIBIWhYNhvy8rBmDX79FZWVCAvDxImYOBFeXli3DkeP4vnn0bEj/pCRgSVLkJSEJ59EfVy8Vfrcv7feqNSinqQ8P7R9xLTeCVEBPvg7avgVthsQhihngGFcDQ+mKXF+RDacGpIhANV/T5TTAB6uL1jpvqjbuFlHf7RRCkdW5RyN0viPCI5FPY0Ijr1QVYRaKsz64yVXevu1xR0QYHpEjz5+4a+c3JJTVYS67L1x4cCti2NbdXoxZoCXVAmmScTEBC35/AnUiVJs345PP8Xo0Vi8GDYbli3DSy9h+XJ07AiOQwOiFFeu4PPPUViIFSvQpg3278eaNSgtxWuvoSGkXLj8Xxt26M0W1Edrb49HEmIndGuvlsvgAKW6VRCICyGy4WAYV8ODaVpEMZ0akiGErYgadxHZSDQLPX3bPB/df3FWChyhwPz05HC1T6TaF/UxLDj288z9FA7suJ7Z268t7ipc7bOx/1MLz+9Zf/kURR2sdvt/rqTvKMicGdlzaniinBeDcRJGI374AUlJmDoV/v74wwcfYOxY/PILwsLg6YkGZLPh3DlkZ+P999GjB/4wfjyMRmzdipMncd/Wpp5euOOgzU4hjJjjkmLaTujaPrFtKCG4E2rcC2suhCHKWQAHhnE1PJgmJo6FpBvMJyAA1X1LZCPRXMyO6pOjLdp5PQuOGKyWZ1M3bEqa6SFRQLBQpUecR+D5ihuoZU9h9r86jZBxPO5KxvH/6jRiRHDcf6dvu1pThrrUWE2Ls1K+v/T75LZdp4UnqsRSMA/c5cu4dQtTp8LbG/9DJkPv3jh7FjodPD3RgLRa5ORAo0GXLvgfPI+2beHujkuXQAhMJpSW4tYt/KGsDCYThLHa7O8m79t0MgOCeShk216a6qlSoC5UtxoCibyJfAwYxgXxYJocUU6n5hMQwpIB80lIuqJZIMAH8aMvaUtztcVwpFBf+cqJLat6TeYIgWAjgmPPV9xALTVW04FbF4cFxUCALt6hPyc9vThr/w95J2yUoi4VZv2y7IPrLp+cHtFjUpuuSl4C5gHS6UAIFApwHP6Xuzv0ethsACilAAghuH8WC4xGyOWQSvG/ZDLwPAwGKBRITcWRI5DJ8AejEYRg+HDUpcpgfGndr7/nFaA+KvTG/PIqT5UCd0XNx2A5DWGIcgaIDAzjgngwTY5IkyjfBtbLEIDqvyOSrmguFLxkeY/HHk1ZVWk2wJHU4stLsvbPix0IwYYFx36SsddOKWpJzj8/LCgGwsh58esdho4Ijn3r9PYLVUUQoNyk/yxj36qco4+1SXiibTdfmRuYB8LdHYSgvBwWCyQS/IFS3LwJjQZiMYDCwkJ3d3elUkkIwX2SSuHmhpoaaLXQaPAHSlFdDZMJajWsVvTsiWnTEBODP2Rm4ptvUJf8ssrn/r31ckk56u/ntMxOoQG4u5qvIRBxI4qJYBjXxIN5AAhRPEm170AAatxPbAXgQtBcBCvdP+s69unUdTZK4ciqnKNRGv8RwbEQJkCuTvAKPVl6DbUcKsqtMOs9JAoI1tEzeHPS0xuunFqSmaK1GCGA1mJcmXP0u9zjo0LaTw3v3k7jB6aJhYWhbVscPYpOndCmDShFaSmOHsWwYVAqAcydO3fAgAGPPPKIn5+fRCIhhKCe6G12u513c0NMDHbuREoKhg2DWIyaGmRkwGBAVBQyMiCVwtsbAQH4Q1ERZDLc1e95BS+u+1VrMOKe7DyX8/rI/jIxjzuxnKfmYxCGKJ8EcQPDuCYezINA5GNpzRLYK1E3O9X/SNz+iWakl1/b56P7L85KgSMUmJ+eHK72iVT7QphRoe1Pll5DLVa7fef1rEltuqA+OEImt+k6PCj288x9m6+dsVMKASx225ZrZ7ZcO5PgFTqpTZchQdFiEQemaUgkmDIFCxbg++8xYgQoxZo1EIsxejTUagBvvvnmggUL9u7dO2vWrO7du3t5eXEcRwiBMHa7Xa/XFxcXm0ymqKgo0r49unfHqlWw2xEaitRU7N6NoUPRuTMyMlAfP508/17yfqvNjntVYzLvycgd3Tkad0B1X0MgIieKKWAYl8WDeSCInMgfo7qvIQA1bCKqF0HkaEZmR/XJ0RbtvJ4FRwxWy7OpGzYlzfSQKCDA8KDYD8/uMtqsqGVbwflJbbqg/jylivfiR01q2/WzjH1HivIgWFpZflpZvtc55dhWnR4O7RCu9gHTBJKSIJPhu+8wZw4IQY8eWLIEERFWu72spCQ6Onr9+vXbtm377LPPIiIiZs2aFRkZ6e7uTgjBXVFKzWbzjRs39uzZs3v37iFDhkRFRSEkBHPnYsMGLF6M8nK0aYMpUzB6NHgebm7w9oZEgv8hkcDHByoVarHZ6We7Dq85kob6k4l5Cc8DUEjEYk70e17B6M7RcMh6mRr3QRgiHw+RJxjGZfFgHhCifILqvwG1oE52LTVsI4oJaEYI8EH86Eva0lxtMRwp1Fe+cmLLql6TOUJQFzextK9/xJ7CbNRyuqzgWk15K5Un7km0xn91r8nHiq98krE3q/ImBCsz6VZdPLrq4tFwtc/DoR3GhHb0kanANKqePdGzJ/6uvLh4/vz5/W576KGHBg4c+PXXX8+dO3f48OFPPvlkYGCgUqmEI5RSm81WUlKSlpa2ceNGo9E4d+7c/v37E0Lwh8BAzJuHefPw/3n0UTz6KP5XTAwWLoQj18oqwrw93h4zSCmV8CICwE0uJSCEwE0mBcCJREqpBICYEykkYgASnpeJedQH1a0A7BCEJ8rpYBhXxoN5UES+RPYQNfwCAaj+e6IYDxA0IwpesixxwviU1VqLEY6kFl9ekrV/XuxACDA6pP2ewmw48mtBxpzovrgPPXxbbxowc1dh1lcXDl3SlqA+LmlLPsvYtzhzfw/fNqNDOgwOjJLzYjBNxcfHZ+LEiYsWLfrtt9+mT58eGxv7yiuvTJgwYcGCBU/dNnDgQF9fX4lEgr+w2+1arfbChQsbN248e/bs5MmTJ02aJJfL0XDa+Hi28fFEo7LdpMZfIQyRjwYXBIZxZTyYB4coplHDLxDCmgvzSUi6oXlppfL8vNu4p1PX2SiFI6tyjkZrAoYHx6Au/fwj3CXySrMBtWwtOPdcdF+C+yIiZERw7LCgmN2F2V9dOJSrLUZ92Cg9UpR3pChPzosHB0YNDozq5dtWwUvANDJCyODBg3v37r1+/fo333yze/fuU6ZMCQsLW758+fHjx997773k5OTZs2d36tTJy8uL4zhKqV6vLygo2Llz57Zt2/r27bt+/Xo/Pz+4IKpbDWqBIIQonwLDuDgezAMkjoEkAeY0CED1PxBJNzQ7vfzaPh/df3FWChyhwPz05LZq70i1L+5KLOKGBcVsuJKGWvJrys+VF3b0DMJ9ExEyPDhmaFD0bzeyv7l47FxFIerJYLUk559Pzj8vEXFdfcKS/CP7+UcEK93BNCa5XD5jxowhQ4Z89dVXL7300iOPPDJq1KjOnTtv3br1xx9/fOutt3r06DF16tTWrVtXVlYeOnRo48aN/v7+S5cujYuLg4uyl1HDJghDZIPAR4BhXBwP5oEiiiepOQ0CUONvxHYTXACandlRfS5UFe0qzIIjeqv52dQNm5JmekgUuKtRoe03XEmDI9sKznf0DEIDEREyNChmaFBMWln+2ksnfruRbaMU9WS2244W5R0tynvv7M4QpUd//4gBAZHdvMN4kQhM4wgODv7www9Pnjz5ySefHDhwYNq0aQkJCZMnTx4yZMjSpUunTZv21FNPZWVlXblyZfbs2aNGjeI4Di6L6laDGiAMUc4Cw7g+HswDRWRDKecP2y3UzUb164nbPDQ7BPgwYXRedWmuthiOFOorXzmxZVWvyRwhuLN4r9AQpUeBrgK17Lie8c/2Q3iRCA0qwSs0wSv0cnXpj3knt+afq7GacE8KdBVr806szTuhkcgTvEK7erfq4h0a4+7PERGYhta1a9d1mKcHfwAAIABJREFU69YlJycvWrQoOjr6iSeeaNeu3WuvvVZZWblx48ZJkyYtXLhQpVLBpdkrqH49hCGSnhB3AsO4Ph7MA8YR+URaswQCUMNGopoDIkWzo+AlyxInjE9ZrbUY4Uhq8eUlWSnzYpNwZwQYGRK3/MJh1FJu0h8pvtTfPxKNoI2b95udhr8SN/DXgox1l09eqCrCvaoyG/bfzNl/MweAnBdHa/wTvEJ7+LZO8AqVcjyYBsLz/NixYwcOHPj111+/9tprw4cP79y5s7e397p160JCQuD6qG4lqB4CqZ4BwzQLPJgHjSgep7rloGbUyV5BjTuJfAyao1Yqz8+7jXs6dZ2NUjiyKudItMZ/eHAM7mxMaMflFw7DkZ+vnevvH4lGo+AlE1rHT2gdf7qsILng/I7rmVVmA+6DwWpJLytILytYdfGolOPbewTGuAfEuAfEuPu3dfPmiAjM/dFoNK+99trDDz+8aNGioqKiL774As2DvYLq10MgcXsiSQTDNAs8mAdO5Elkw6ghGQJQ/fdEPgbNVC+/tnOj+y/JSoEjFJifntxW7R2p9sUdtFJ5xnkEZlTcQC37b+aUm/SeUgUaWWevkM5eIW90GHqo6FJy/vkDty6abFbcH5PNeqo0/1RpPm6Tcnw7tV+0u3+se0C0u3+k2lfK8WDqjxASFRW1YsWKyspKNBdUtxJUD2GI8lkwTHPBg3ECRPEkNSRDCEsmLGcg7oRm6pmoPjlVRbsKs+CI3mp+NnXDpqSZHhIF7mB0SPuMihuoxWK3JRecmxaeiCYhFnEDA9oNDGhXbTHtu5mz63rW4aJcG6VoCCab9VxF4bmKQvzJR6aKUPsGK91DlB4hSo9wN5/Wbt4cIWAEIIR4eHigebCXUf06CMRHEFkSGKa54ME4A3FHiDvAcg4CUP0PRNMJzRQBPkwYnVddmqsthiOF+spXTmxZ1WsyRwgcGR3a4dOMvWa7DbVsvnpmWngimpabWDomtMOY0A439VU7rmceuJWbXpZvoxQNqsRYU2KswV9IRFwrlVeo0iNQofGTq/3l6gCF2k+m9pO7iUUcmGaK6laDGiAMUc0BRGCY5oIH4xyI4gla9RoEoMadxO0fEPmgmVLwkmWJE8anrNZajHAktfjykqyUebFJcMRdIh8Q0G53YRZqydUWn6so7OARhAchQKF5KrLnU5E9q8yGw0V5KTdzDhflaS1GNA6z3ZarLc7VFuPvCOAtU/nJ1X4yN41E7i6Re0gVHhKFu0TuLlG4S+TuErlGIheLODQ+G6U6q6nKbKixmmosJp3VFOce6C1Tgbk39gqqXw+B+HAiGwaGaUZ4MM6ByEbQ6o9hL0OdqIXqfyKq59B8tVJ5ft5t3NOp62yUwpFVOUeiNf7Dg2PgyLiwTrsLs+DI5qtnOngE4YHSSOQjQ+JGhsTZqD2tNP/ArdyUWxevVJehSVCgxFhTYqzJwN2ICFHxUgUvkXC8Gy9V8BIJx7vxUgAKXsKLRPiTRizHX5jtVoPNgr/Qmo02SnVWk8Vu01vNJrvVZLMabBa91ay3mvF3S7o/OjQoBsw9obqvQfUQhqjmAiIwTDPCg3ESREIUE2jNcghADRuJajbAofnq5dd2bnT/JVkpcIQC89OTw9XeEWpf1NLbt22AQnNTX4VathdkvN5hiIwTwwlwRNTNJ6ybT9hr7QcX6CpOleafKL2aVpqfr6vAg2anVGsxai1GNK0qixHMvbEXU/16CMRHENkwMEzzwoNxGkQxmdasAqyok+0mNR0k0iQ0a89E9cmpKtpVmAVH9FbzM6kbNifNcpfI8XciQsaEdlh+4TBqqbGadhdmPxzaAU4mROkRovR4pFVHAKXGmlNl+Wml+ellBdlVt+yUosWoMhvA3BNa8wWoEcIQ1VxABIZpXngwzkPkS2SDqHEXhNCvgzQJzRoBPkwYfam65JK2BI4U6ivnndi8qtdkjhD83bhWnVfkHLFTilo2XzvzcGgHODFvmWpYUMywoBgAFWZ9Wml+RuXN7MpbmZU3S401aNa0ZiOYe2ArpIYtEIiPILKhYJhmhwfjTIjiSWrcBQGo6TCxXQPXCs2agpd8mThxfMpqrcUIR1KLLy/JSpkXm4S/C1a6d/Vu9XvJVdRysuRqfk15qMoTrsBDohgUGDUoMAq3aS3GXG1xZsXNzMqbmZU387QlFM1KlcUApv5ozWJQC4QhqrmACAzT7PBgnIqkK/hIWC+ibpTqfyJur6K5a6Xy/LzbuKdT19kohSOrco5Ea/yHB8fg78a16vx7yVXUQoEt+WdfihkAF6QWyxK8QhO8QnFbldlwUVt8tab8Wk3Z1ZryK9Wl+boKi90Gl1VlNoKpL2suNfwKgfgIIhsKhmmOeDBOhigep9p3IAA1/ERUL4BI0Nz18ms7N7r/kqwUOEKB+enJ4WrvCLUv/mJIUPT7Z3dqLUbU8tOV9Oei+kpEHFycRiLv6t2qq3cr/MlG6Q195dWasqs15fk15TcN2iKD9pZBW2qsoXABVWYDmHqiNUsAG4QhqhcAERimOeLBOBkiH0OrPwOtQZ3sFdS0h8hGogV4JqpPTlXRrsIsOKK3mp9J3bA5aZa7RI4/yTh+RHDshitpqKXMpNtTmD0yJA7NDkdIiNIjROnRxw9/ZbHbio3Vtwzam3ptkUF7y6CtMOsrzYZKs6HCpK8063VWM5yAzmoCUy+WDGr8DQKJ44hsCBimmeLBOBuiJPKRVL8BAlD9OiIbiRaAAB8mjL5UXXJJWwJHCvWV805sXtVrMkcI/jQurPOGK2lw5Ie8EyND4tBiiEVckMI9SOEOLzhksdsqzYZKs77SbNBZTUabVWsxmmxWo81SbTGabFaDzVJjMdkpBWC0Wcx2G26joFqzEbcpeIlYxOFPhBA3XgpAxvESjlfyEp5wKrFURIhGLJeIOKVYquKlaonMjZeqxDKVWCoRcWhCdps9PyPfK9jLzcuNUmo1W29evOkV4qV0V8JF0JrPAQphiOolgIBhmikejPMhislUvwFCmE/BehF8JFoABS/5MnHi+JTVWosRjqQWX16alfJybBL+1N4jMMY9IKvyJmo5U349s/JmrHsAmNvEIs5HpvKRqdCS2Cy21I2pge0C+0zqQ0Tkeub1lDUpQ58bqnRXwhVQ8+/UdBgCSeKJtC8YpvniwTghvh3EnWA5AwGofj1Rv4WWoZXK8/Nu455OXWejFI6szDkSpfEfHhyDPz3RtusbaclwZG3eiQUJD4NpwXgp329Kv22fbmvdqbXGX3Pyl5NRvaKCooLgGiit/hiCEdXLYJhmjQfjlIhiEq06AwGo4Rfi9iqIEi1DL7+2c6L7Lc06AEcoMD89OVztHaH2xW0jQ9p/lrGvzKRDLTsKMv4rbpCXVAmmpSKEBEQExCXFHVl3JLR9qNVijX8oHi6CGn+FJQPCEGlvIukOhmnWeDBOichG0OoFsJejTlRHDduJYgJajGej+l6sKt5VmAVH9FbzM6kbNifNcpfIAUhE3LiwTitzjqIWs922+erpp9v1BtOCERGJfyg+fUd60eWiR15/RKaSwSVQC61eAsGI6kUwTHPHg3FORELkY6juWwhA9T8QxQS0GAT4MGH0peqSS9oSOFKor5x3YvOqXpM5QgA83rrLNxeP2agdtfx4+eSMiJ68SASmBTNUGxRqhclgksglcBFU/wNs+RCGyAZD3BEM09zxYJwVUUyiujWAHXWyXoDlLMQd0WIoeMmXiRPHp6zWWoxwJLX48tKslJdjkwAEKDRJAe1+u5GNWooM1ftv5gwJigbTIlFKLSZLWnKau7+7Z5DnsU3HRrw4QqFWwMnRaqr7GkKJiOpFMEwLwINxWlwokSRScyoEoPr1RNMRLUkrlefn3cY9nbrORikcWZlzJErjPzw4BsATbbv+diMbjnx/6fchQdFgWqqrZ65eO3dtzD/HSBSS5E+Ssw9mxz8UT0QETozWrIS9AsIQ+cPgI8EwLQAPxpkpJsGcCgGocQdxex0iDVqSXn5t50T3W5p1AI5QYH56crjaO0Lt290nLFztc0lbglrSyvJPll7r6t0KjLPSWoxqsQyNQFuiPfafY51HdPYJ87FZbd3GdDu+6XhIXIhva184LVsR1f8bAhEpUb0IhmkZeDBOjMgGUs4PtiLUiRqpYQtRTkcL82xU34tVxbsKs+CI3mp+JnXD5qRZ7hL5E227vX16OxxZkXOkq3crMM5HazF+mrH3aNHl5EHPKHkJGlpNeY1vmG/HIR0BcDzXOqF16bXSyluVvq194axozSJQA4QhiifBBYJhWgYejFPjiHwCrfkCAlD9OqKcBhC0JAT4MGH0peqSS9oSOFKor5x3YvOqXpMfDumwKGOf1mJELUeK8jIqbsR5BIJxJgdu5b51+tciQzWARZn73uw4HA0tKCooKCoIf5LIJL0m9YIzs2RRw1YIJNIQ5WwwTIvBg3FuRPEYrVkOWFEn2zVqPk4kPdDCKHjJl4kTx6es1lqMcCS1+PLSrJSXY5Mmt+26/MJhOLIi5+gXiePBOAetxfhpxt7/XEnHn9ZfPjUsKKardyu0bPbq9wE7hCHK5yDSgGFaDB6MkxP5EFl/atwLIfTrIemBlqeVynNRt3GzU9fZKIUjK3OORGn8p4Ynfn/pd73VjFr23sjO1RZHqH3BPGi7CrPePbOj3KTHX9gpfT1t67aBz8p5MVoqatwB8ykIxAUSxWQwTEvCg3F+8kkw7oUA1PgbsRWB80PL09uv7ZzofkuzDsARCsxPT97Yf8bE1vHf5R5HLRRYdfHowi6PgHlwyky6d87s2FOYDUeu6yqXZh/4R/vBaJmohVYvgmBE9TKIBAzTkvBgnB6R9qJ8GKxXUTcbNWwiqjlokZ6N6ptTVby7MAuO6K3mZ49tWNlz0vrLp4w2K2rZXpAxN6pfqMoTzIOwqzDr7dPbK80G3Nn3l44PCmyX4BWKlofqv4UtHwLxUUQ+CgzTwvBgXAAh8gm0eiEEoIaNRPUMwKHlIcBHCaPzqksuaUvgyHVd5ftndz0c2nHjlTTUYqN09cXUd+NHgmlatwzat09vP3ArF3WxU7o4M2Vt36loaeyltOZrCEbU/wBEYJgWhgfjCoj8UVqzBNSEOtluUVMKkQ5Ci6TgJcsSJ0xI+UZrMcKR1OLLT7TtxotEVrsdtWzJPzMzsmeoyhNMU9lVmPXW6e1VZgMEGBYU869OI9Dy0OrPQXUQhkgHEEkvMEzLw4NxCSJ3IhtGDVshhH4DpIPQUoWpvBZ1Gzc7dZ2NUjjyY96JBO9Wp0qvoRar3b4k+8BnXceCaXyF+so3039NLb4MAbykyrc6jRgSFI0WyJJFDVsgFE/c/gGGaZF4MC6CKB6nhq0QgJoOE9tVcGFoqXr7tX0uqt8X2QfgCAUyKm6ICLFTilp2FGQ8FdEzxt0fTKOhwE9X0j8+v0dnNUOAYUExb3d+yF0ix91YAR7NELVXfwDYIAxRTAbfBgzTIvFgXIU4HnwUrBdQN0r1PxG3/0IL9lx034va4t2FWXDEaLMoeLHeakEtFFialfJ1z8fBNI4CXcWb6b8eL7kCAXxkqrc7PzQwoB3qQsunwnqFaN6BdDCaEWrYAvNJCCTSENUcMExLxYNxHUTxGNW+DQGo4SeiegFEipaKAB8ljM6rLrmkLYEjequFgFBQ1HLgVu6JkqvdfMLANCg7pZuunl5wfo/eakZdCDA6tMMbHYZqJHLUyXyKmk8CoBVzCB9CNJ9C3BnNAK2h1YsgGFG9AJE7GKal4sG4DiIfQ6s/Ba1BneyV1LiTyMegBVPwkmWJEyakfKO1GOEIBcUdLM5KWddvOpiGk19TPj9928nSaxAgSOH+XvzInr5tIIxd+w7+RK0FtGwi4aOJxxJwYXBltHoR7CUQiG9DFI+DYVowHowLIQoiH0X16yEA1f9I5GPQsoWpvBZ1Gzc7dZ2NUtRHelnBgVu5/f0jwNw3G7V/m3tsWfZBk82KuhBgfOv4f7QfouQlEIaa9sGag7+j1mxaMhSSriL3pRB5whVZL1L9eghG3F4HeDBMC8aDcSlEMYnq10MIy1lYMiCOQ8vW26/tc1H9vsg+gHpalLGvr1+4iBAw9yFXW/xGWvL5ihsQIETp8X78qO4+YagHO9W+D8cozCfsxT0hHynSLAB4uBJq174L2CAMkfQg0n5gmJaNB+Na+HaQxMOcDgGofh3RfIgW77novhe1xbsLs+AQBQhqu6gtTi44Pya0A5h7YqP2b3OPfZF1wGy3oS4iQh4N6/x6+6FyXoz6oIafYSvE3dhhSLYbd0P5jEg1By6CGrbCfAJC8UT9JhimxePBuBoin0TN6RCAGn8lbv+ASIOWjQAfJYzOqy65pC1BbQR38nnmvqGB0XJeDKaecqqKXk9Lzqq8CQFCVZ4fxI/q6t0K9Wal1QshBDWhZgm13SSa9+H87FpavRCCEeVU8OFgmBaPB+NqiGw4rV4AeynqRI3UsJkoZ6DFU/CSZYkTJqR8o7UYIViRoXp17tHno/uDEcxqt3936djSrAMWuw114YhoRkSPudH9pByP+qO6tbBXQDCieAyugNZ8AnspBBL5ENUcMAwD8GBcDhET+TiqWwEBqH4dUU4DRGjxwlRei7qNm526zkYpBPvmYuq4Vp0DFRowApwtvz4/fdslbQkEiFD7fpgwur1HIO4NNVLdUghGZEMhjoPzs5yl+p8gGFG/AaICwzAAD8YFEcXjVLcasKFOtnxqOkqkfcAAvf3aPhfV74vsAxDMaLN+lrnvs65jwdyV0Wb9Mvvgt7mpNkpRF46IZkT0eD6mv0TE4V5R3Zew6yAQ4YjbP+H8qMVe9QZgh0CSLkQ2AgzD3MaDcUVcIJH2p6Z9EEK/DtI+YG57LrrvRW3x7sIsCLajIGNSmy4JXqFg7uB0WcH89G2Xq0shQDuN30cJo2PcA3A/7Fqq+w6CEfnj4ILg9KhuFay5EIoTqd8CCBiGuY0H46IUk2DaBwGoKYXYroMLBgMQ4KOE0XnVJZe0JRCGAh+e3f3TgJkiQsD8ndFm+TL70De5qXZKURdeJJoe3uOFmP5iEYf7Q6sXgpohEJES1YtwfrarVLccghHlFPDtwDDMn3gwrolIe1M+DNarqJud6jcSt1fA3KbgJcsSJ0xI+UZrMUKYzMqbvxZkjA5tD+YvTpXmz09PvlZTDgE6egZ/ED8qXO2D+2cvoYbNEIyo5kCkgdOjVW+DmiCQyJuo5oJhmL/gwbgqQuSP0+qPIAA1/ERUc0GkYG4LU3l93GXMnOMb7ZRCmEWZ+wYFtlPwEjBAjcW0JCvlx8sn7ZSiLjKOnxPdb0ZET44QNASqfQuwQSCiIYoZcHrU8DM1p0Iwon4dxA0Mw/wFD8ZlEfk4WrMY1IA62cupMZnIx4P504CAyOei+i7LPghhbhm0X1049GrcILR4h4su/ev09pv6KggQ7xXyQfzo1m5eaCi2AmraB8GI+nUQCZycvZRWL4BgRNqbyEaBYZi/48G4LpGayB6ihk0QgOq+J/JHAQLmT3Oi++VqS3YXZkGY73KPjw7tEKn2RUultRg/zdj705V0irrJOPGc6L5PRfQUEYKGQyv/C5RCIC6AyMfA6VHtO7BXQCAiI+q3wTBMLTwYV0YUk6hhE4SwXqTmY0TSE8yfCPBhwui86pJL2hIIYKP2d8/sWNt3GkFLdOBW7tunt98yaCFAF+/QD+JHt1J5omFZsqjlNAQjmo8AEZwbNWylxt0QjKieBxcKhmFq4cG4NHEcxB1hOQshdGsg6QnmL5S8ZFnihAkp32gtRghwqjR/e0HGyJA4uKwvsg8MC4qJUPtCMK3F+GnG3v9cSYcAKl76WvvB41vHEzQ8WvUqQCGQOJZIesLJ2Uto9fsQjm9HlNPBMIwjPBgXRxSTadVZCEBNh4j1KvgwMH8RpvL6uMuYOcc32imFAAvO7+nnH+EmlsIFlRhrvrl47PCtvPX9Z3CEQIBdhVnvntlRbtJDgD5+4e/GjwyQq9EYTKnUeglCEZFmAZwe1b4FexWEEok07wI8GIZxhAfj4oh8JK35DLYi1M1O9d8T9Vtg/m5AQORzUX2XZR+EAKXGmmXZB17vMBQuaFn2QaPNcq6icE3usacie+Kuyky6d8/s3F2YBQHUYtmrcYMmtI5Ho6Ha1yGctA/4dnBu1LCZGvdCMKKYBHFnMAxzBzwYl8cT+WO0ZgkEoIYtRPUiRO5g/m5OdL9cbcnuwiwI8EPeiTGtOkZr/OFSrtWUb752GrctyUrp5x8RrvbBHewqzHrn9I4Ksx4C9PePeKfzSD+5GxoNNWymtpsQSiRSvwcnZyui1QsgnMiHqF4CwzB3xoNxfUTxONWtADWiTtRADT8R5Swwf0eADxNG51WXXNKWoC68iLtYVRyt8YdL+Txzv9Vux21mu+2/07f92G86Rwj+rtRY8/aZHXtvXIAAarHs1bhBE1rHo3FRWv0RBCOKMeAC4NQo1b4BexUEI+p3IFKDYZg748E0AyJPIhtFDT9BAKr/N1FOB3gwf6fkJcsSJ4xPWV1tMeHOuvmEvd1pRBs3b7iUjIobuwuz8Bdnyq+vu3zyybbd8Be7CrPeOr29ymyAAMOCYv7VaYSnVIFGRnXLYddCICImbv8N50b1/6GmwxCMyEcT2SAwDHNXPJhmgSinUsMmgKJOtiJq3ENkI8DUEqby+rjLmLnH/2OnFHcwNbx7GzdvuJpFmfsp/n+fZezr5xceqvIEcENf9d/p21KLL0MAL6nyrU4jhgRFoylYac1yCEaUM0BUcGa2Qlq9AMKJfIjbm2AYpi48mOaBjySSHtScCgGo7nsiGwHGkaSAds9F9V2WfRCOxLj7R2n84GpOlFxNLb6MWow2y3+f/nVNnymbrqR/fH6PzmqGAMOCYt7qPMJDokCTsGvfBTVBIJGKqF6EU6NU+yaoDoIR9dsQacAwTF14MM2GcirMqRDCchrmNEgSwDgyJ7pfrrZkd2EW/m5kSNz78aNknBguhQILM/biDk6UXB3521eXq0shgI9M9VanEYMCo9BkqAH6TRCMuL0G8HBiVL+Omo5AMCIfS2SDwTCMADyY5oJI+1O+DayXIQDVLSeS1WAcIcCHCaPzqksuaUtwG0dEL8UOmBXZCy5o1/WsjIobuLPL2lIQ1GlYUMw7nR/SSORoQvbK1wArBBL5EfljcGa267T6Ewgn8iVur4NhGGF4MM0HIYonqfYdCEBNh4glA+I4MI4oecmyxAnjU1ZXW0weEsWibuN6+LaGC7JR+5KsFNwdwd0FKdzfix/Z07cNmpitFKbfIJhI8yGcms1e9V+geghFiOZDiDRgGEYYHkwzQuRjac1i2KsgANWtJO5LwdxBmMprYZdHvsg++EXi+CCFO5pMURHOn0dBAex2+Pmhc2f4+4PjcE9+unr6ak0Z7hUBxreO/0f7IUpegiZnr5oH2CEMEUdC2gdOjNZ8BXMaBCOK8UTaFwzDCMaDaU6InMjHU91qCECNe4g1F3wEmDsYEBDZzz9CRAiazI0b2LwZZ8+C40AI9HqcO4eJE9GmDQhBPRlt1q8vHMa9ClF6vBc/MtGnNR4Iax7Mv0MoQtSfwplZztGa5RCOCyRu/wTDMPXBg2leiOIJqlsDWFE3O9WtJpqPwdyZiBA0GZsNu3bh4EEMH46HHoJEgiNHsHIl3N0xaRLc3VFP/750/JZBi/oTEfJoWOd/th+i4CV4QOxVLwMUAkm6QhwFp0Wr7ZUvAlYIRYj6PRAVGIapDx5MM8MFEvkoavgZAlDDNqJ6AVwQGGdQWYnDhxERgYcegr8//jBiBE6exOnT6NsX7u6oD63F+E3uMdRfqMrzg/hRXb1b4QEyn4DlAoQiIvfP4MRo1duwFUIwophEpH3AMEw98WCaHaJ8hhq2AnbUzUp1q4n6LTDOoLgY5eXo3h0+PvgfPI/ISOTmorIS9bQi50iV2YB6kor4Nb2fCFS440Gi9qp/QjjZIIj84KyoYQs1boNwXDBxexUMw9QfD6b54VsT2RBq3AUBqOEnonoWIl8wDxyl+AMh+CtCUH+3DNof806g/kx268Lzexd3fxQPDjX8DNt1CMWLNAvgtGz5VPse6kEk0iwAUYJhmPrjwTRHRPUcNe4GKOpEzVS3hri9BuaB8/GBRoPr11FeDh8f/MFqRV4elEqo1aiPL7MPGm1W3JNdhVl7CrOHBEXjgaAWWr0AwsnHgLjBSVntlS+B6iAYUTwJSTcwDHNPeDDNEh9FpH2p6SAEoPr1RDkbIg2YB8vTE4mJOHAAv/2GwYMhkeDkSaSno39/BAVBsCvVZVuuncV9eOv09i7erTylCjQ5qlsNeyWEEovU/4KzotWfw5IB4fhw4vYKGIa5VzyYZooon6WmgxCC6qj+W6J6GcyDxXEYMQKVlUhJwdmz4DjcuoWYGAwdCg8PCLYoc5+N2nEfKsz6j87t/qTrI2hi9jKq+wqCEeU0EBmck/kE1X0L4YhE5L4IRAaGYe4VD6a5ksRD0hXmkxCA6tYQxZMQeYN5sMLCMGUKTpxAXh6sVkRHo1cvhIZCJIIwZ8sL9964gPu2reD8iODYAQGRaEK05jNQE4SSEdXzcE72CnvlPMAGwYjbP8FHgWGY+8CDab6I8hlqPgkhqIHqVhG318E8cMHBCA7GvVqUuY+iYbx9ZnuCd6haLEPTsOZS/RYIRlTPgcjglGjVfNiLIRiR9iWKyWAY5v7wYJovIu1Dxe1hOQ8BqH4dUUwDFwDmgdq1a5eHh0fnzp1PnjxJKW3fvr1Go4EwR4ryfi+5igZSZKj++PyeD+JHo0lQ7fuAHQIRN6J8Ck6J6n+kpr0QTuRNNAsAAoZh7g8Pplkjymdo5RwIQU1Ut5yo3wXzQO3fv79NmzZxcXEnTpyglLZu3Vqj0UAAO6WLMvehgSh4iZdUmactzde7NO2zAAAgAElEQVRVhCo90MioaS81H4NgRPUiiBhOyJJNqz9GPYiI+ycQeYNhmPvGg2nWiGwg5SNgzYUAVL+JKGeACwPjgnZcz8yqvAUBpByvFss0ErmvzM1HplKLZRqJ3Ffm5iNTqSUyjVjuK3dTi2VoMtRCtQshnEhDFI/DCVGdveolUCMEI8oZRNILDMM0BB5MMyciqjm08iUIYqXVnxD3L8G4GqvdvjQrBYCU49VimUYiV4tlvjI3H5lKI5GrxTJfuZuPTKURy33lbmqxDM6E6tfCdhWCEbfXQMRwOpRW/RPWKxBOHEtUL4NhmAbCg2nuiGw4Fa+EJQsCUONvxHzq/7QHJ/BN1/f/wF/vbz652xxtoRUEAaFVRNDKrT8qAp3oRFBUFB2oTFARN/HAWxmHA/FiKCpI0TnBC7wPGOAxLYIcojAqOhC5KW2SJmma5Pv+86h/9sBpMWnTI837+YSpO0RSiXD0ubOuyjTbrcqI5KJ72P8UYqe1IOtFaHrYv4ArP0DsyKo5Z4GMEEIkiIJo/ojSbuaysYiN7puiZb4OaBDJw2IwHm93IQlxxaPQPYgZpd0MGNDUhDdwxSzEgxz3QnWAECJxFEQKIHN/Np6O8HrEIryZK98hywUQor5FvuPAYsTOkEXWYWhq9FK9/CZwGDEjy+/IOhxCiIRSEKmB0v/Mh/6A2LBvFpkHgSwQoj6xbxoQRczIfgPIiKZFZ89tiO5D7Aw55JgCIUSiKYjUQKbeMJ3JVf9CLKK72f8MpU2AEPWGQx9x6BPETssk63A0MVwxm0OfIg4aOWdCc0IIkWgKImWQ4w4+OBTQEQP2P0vWYTC0gRD1Isq+GYgH2f8IsqAp4dAnXPEU4kFpE8jUC0KIeqAgUoc6iaxDOfg6YsEh9k4n95MQoh5w4O+IfIvYaW6yXY4mJbqHPbcCOmJG5n6UNg5CiPqhIFIJpf2ZK98DBxEDDi1H6CMyF0CIxNI9XDEH8SD71SArmpCI7vkz9DLEznAcOWcCGoQQ9UNBpBRDNtmv5oonERv2TqWsXiALhEgcrpgNvRyxo3SyXoGmhL1/RdU6xEFprkehuSGEqDcKIsWQ/ToOvAL9AGIR3c4Vcyh9IoRIlMj3HPgH4kH2P0BzoMngyvc5sBDxIMedMOZDCFGfFESqIRul/4k9dyM27J9HlsEwdoZoKH6/f+fOnT6fLy0tDc0O+6YDEcSOrGT7A5qOyPfsuQvxIMt5ZLsKQoh6piBSD1kv5sDLCG9ETKK69x4t8xXAAFHPIpGIy+VatmxZJBLJzMzs0KGDzWZDM8Khjzn0EeJBtqugudFE6B69bCy4ArEztCPnFAgh6p+CSEWa5rhfLx0O6IhF+Gv2P0/2qyHq044dO5YsWbJhw4YePXqcddZZxx9/fHo1NBscZt9UxIUsZL8aTYXOnlsR3YHYkUVzPQ5KgxCi/imI1GTsQrbhHHgZseGKx8jSH4Z2EPXg4MGDH3zwwccff5yZmTly5MgzzjgjJydHKYXmhQMLEfkP4kHWi6Blomlg3yMc+gjxIMeDMJ4MIUSDUBCpitJu48oPoZcjFhzUy2/RMl8GFETiVFZWfvHFF6+99lowGDzzzDP79OnTtm1bi8WC5kc/yBVPIT4a2UejaeDKD9n/LOJBthFkHQYhRENREClLc1LaLey9DzEKf80Vz1DaDRCJoOv65s2bX3nllR9//PH000/v1atXbm6uw+EgIjRH7JsB9iEeZBkIQzs0BZF/s+c2gBE7lUfpd0EI0YAURAoj26Vc+Saq1iI2XDGbzP8H46kQdbNnz5433nijuLj4hBNOuPzyy7t165aZmalpGpqr8HoOvoE4kf1aNAW6Ry+7ERxE7DSH5p4DskAI0YAURErTNMcUvXQIuAoxieqeO7TMJSAzxLH9+CPefRcffQS/H+3b44ILcOaZMJsDgcCKFSveeOONtLS0oUOH5ufn5+TkmEwmNGe67v0LwIiLqTuMp6PxRdlzC6I7EQcixzQY2kII0bAURIpTHch+PVc8jhhFtrFvOjkegDiG7dtRVISSEvTvD7cbGzfi2WdRVoahQ0OhUDAY7NOnT9++fdu2bWuz2dDcceBVhL9GnMg+Bk0A+2Zw6BPEg+zXkaUQQogGpyBSHqWN49CHCG9BbDjwDxhPJ+uFEL8qGkVxMTZuxIgROPdcWCzo0QNz5+KDD3DKKWknnnj22WcbjUan00lEaPZ0D1c8gnip9mQ+G42Ng2+wfwHiQeazKP1PEEI0BgUhYNAck/XSEUAUsWHvA2TqBkM7iF8qK8PXX8PpxIABcDpxWJs26N4dS5Zg61bjSSe1aNECKYMrZkM/hDiRfQygoXGFN7P3PsTF0I6cjwEGCCEag4IQhxm7Udp1XPEUYsR+vWy8lvkqyALxP/x+eDxwuZCRgZ9oGrKyoBTKy5FSIts48A/ES8sgyxA0Lv2gXn49OIjYkU1zz4HmgBCikSgIUY3SbuLQxwh/gxhFStg3hRxTIP6HUlAKlZWIRGAy4SehEJhhNCKVsHcyEEGcyHoJyIxGxGG9fAKiexAHIufDUJ0ghGg8CkL8f0pzPqyXDgNXIjYceBnqFLJdDnG0jAy0bYtPPsG//42uXXFYJILvvkMohDZtkDK48j2uKkbcDGQbgUbFvsmoWot4UNp4sgyEEKJRKQjxX+pESvsz+6YjZuz9C1QHMvWC+C+LBb17Y80aPP00rr8e2dlYtQrvvYeePdG1K1IEV7JvBuJH5v4wtEbjYf/THFiMeJB5AKXdCCFEY1MQ4ihkH4XQSq4qRqwiXP4nynwNhlYQPyHCaafhuuvwyisYPx6hEDIzMWAALroIDgdSA/ufQXQXasF+JRoPVy5j36OIi2pPrhmABiFEY1MQ4mc0cj3CBy+EfgAx0kv18uu1jEUgK8RPrFb07o1OnVBejmgUFguysuBygQipILqb/fNRC4Z2ZOqDxhLezJ5bAR2xI7vmmgNKhxCiCVAQ4n9oWeSaxYeuBqKIUXgLl/+J3E8CBoifWCxo3RqtWyP1sG8qOIj4kf0qgNAo9AN6+fXgIOKgkesRqI4QQjQNCkL8Apl6I20sVzyJmHFoJbwPkmMyxFE+//xzn89XWFiIlMFVn3PlMtQC2cg6FI2CK/Wy6xHdg3hQ2s1k7g8hRJOhIMSvobSbuOpLVK1GzDiwCIa2ZB8DccS6dev27t1bWFiIFMFh9k5GrZD1AlA6GgGzZxLCXyEeZBlIaeMghGhKFIT4dQbN9Yh+8ELoBxEz9s2E4TiynA9RLRQKBYNBpAwOPIfId6gVsl6KxsC+R7jyXcRF5ZLzYYAghGhKFISoidZCc83Wy/4ADiNWzJ47oGWQqQ9Eqonu4oonUTsqF8ZT0eA4uIT9TyMumktzzwHZIIRoYhSEOAbTGeT4C3smIXZcxWXjyD0Pph4QqYS9fwEHUStkHY6GV/Ule+9FXMiouf4GwwkQQjQ9CkIcE1kvQngTB15E7Diol43VMhbCeCpEauDKDzm0ArVDRrIOQQOL/qiXjwdXIQ5Ejqkw9YQQoklSEOK3kONuRL7jqmLEjiv0sqs19/MwdoZo9jjIvumoLTIPhJaBhqR79bI/Qi9FPCjterIOhRCiqVIQ4rcpcj3GpcMR/RGx07162Rgt40Wo9hDNGlc8hugu1Jp1OBpUhMsnIPId4kGW31HaBAghmjAFIWKhZWjuefqhEdDLETv9oH7oSi2jCKoTRHMV+Tf7n0etGY4jc180HGbPXVz1GeJi7ELOGYAGIUQTpiBEjFQHzf2sfugP4CBipx/QD12huefD2BWpZ9y4cbquoznTdc8DQBS1RZYhgAENhX2zOLgUcdFaaq6nQFYIIZo2BSFiZ+xGrke57EYgitjpHv3Q1VrGPBhPR4qx2Wxo1jjwCsLrUAdkvQANhQMvs/8ZxIVsWsY8GLIhhGjyFISIB5nPgeM+9t6PuLBPPzSa3HPJ1AcpIBqJblq+acemHb0u6pVzYk40HF33zroDOw70HNYzq20Wmg29nCseQV2oXKhcNAgOrWLv/YiPRq6HoU6CECIZKAgRJ7JdjuiP7H8WceEgl42F6xEyD0Rzpxm0E7qdsO+7fd/885uMVhm7tuzatXVX+9PbZxyfgWaEfdOgl6EOyDoEDSP8NZffDEQRD0q/ncwDIYRIEgpCxI/SbwUHOPAi4sKVXHYTHPeQbSSaNSJyZbs6dO/w9T+/Xvvm2orSCrvDntsnV9M0NBtVazn4BuqEyHI+GkD0R73sOnAQ8SDrxWS/BkKI5KEgRG0QOe4Dwhx4GfGJsvdBRP5DjrsADc0XadSuW7uDOw5+9vJnbU5p0/eyvpY0C5oNDuve+wDGLzBAiI2pOwytUd/0cr3sWugHERdTD3JMhhAiqSgIUUtEjgehB7jybcSJA89D30/OmSAzmi9lVo6WDrPd7MpxZZ+YTURoLtg/D5Ft+DWEWJHlAtQ3Dunl4xD5D+KiOmiuJ0FGCCGSioIQtWcg1wyUBTn0T8SJK9+HXk6uJ6C50EyV7izdsXGH2Wb2lfq+W/PdSWedhOYhupP9c1FXBrIUon7p7LkNVesQFy1Dcz8NzQkhRLJREKJOFLkeR/kEDq1AnLiqmEsv1txPQeWi2QmHwt+u/rYqWHXBLReUFJeUFJfkdMxx5biQ/Ng7GRxE3ZCpB7QM1Cf2PcSV7yMuZNXcc2E4AUKIJKQgRB2Ridxz4JnEwTcQr+hOvfRScs4kyyA0Lzs27thTsievb15Opxxo+OL1LzZ/tLn38N6aQUMy48p3OPQR6s7yO9Qn9hexvwjxMZDrcRhPgxAiOSkIkQAGcj4EGDj4OuLFAS4fD/sfKf0WQEOzULanbNuabelZ6bl9cwHknJjTIb/Dti+2bd+wvcMZHZC89HL2TkUCEJkHoN5w5TvsewhxIsc9ZD4bQoikpSBEYhjIOQ1k5MBixI3Z/wyiO8k5DWRH8nMf5z73xnNxlC4DunQZ0AVJjn3ToB9E3RlPhyEH9YOrPmfPHYCOeJB9LNlGQgiRzBSESBiNHJMBCwcWIn5c+R5Htmiu2VB5EE0Phz7m4FIkAlkKUU/Cm7jsenAV4kGW8yn9FgghkpyCEIlE5Lgb6nj2Tgd0xCuyXS8dTum3km0URJPCQfY+gAQhyyDUh+h2vew6cABxMfUk518BghAiySkIkWhkGwVysfcucBjx4hB7pyL8NTkmg6wQTQP7ZiD6IxLCeAoMbZBw0X36odHQSxEX1VFzzQGZIIRIfgpC1AOyXghDCy4bD65A/Dj4Boe/0VyPQeVCNLqqdRx4CQlC5kIkHPv0sj8iuhtx0Vpo7mehOSGEaBYUhKgfZOpLmf/QD42Bvh+1ENmml15MaRPJPgogiMbClbr3LkBHgpBlEBKLK/Wy6xD5N+JCds39LAytIYRoLhSEqD/qJC1zsV42DpGtqAUOsW8aQh+R8yEYsiEaA1c8isj3SBTVHqojEinKnltQ9SXio8j1BIydIYRoRhSEqFeG1lrmy+y5nSs/QK1w1b/44HnkuJ+sQyAaWNU69j+PxCHLYCQSs+dOrlyO+BA5/0Lm/4MQonlREKK+kZVcT6Dib1zxN4BRC+xjz62o+pQc94LSIRoGB3XP7UAUiUPmQiQO+/7KwaWIE6XfQtaLIYRodhSEaAhEaTfB2IXLJ4IrUCscXMqhf5HjfrIUQtQ/9v0V0R+QQIbWMHZGgrD/WfY/hziRbSTZx0II0RwpCNFQyNyfMl/Sy65H9EfUjn6Ay8fD8nty3AMtA6LecNVnHHgJCUXmgUgQDr7GvocRJ7IOIcd9EEI0UwpCNCSVp2UuYc/tHFqJ2uLKt7nqM3LcQ5bfQ9QH9rHnLoCRWJYBSASuXM6eewBGPMjUlxzTAYIQoplSEKKBaU5yz4V/HvseAaKoHf0Ql98C89vkeBCGbIiEYs/9iO5GYmlOMvVAnXHVZ+z5ExBFXIxdyf0kyAghRPOlIEQjILL/kUy99PIJiO5GbXFoBR/8nOxjyD4OZIRIBA6+xpVvI9HI3B8woI7C67nsenAV4qI6au55IBuEEM2aghCNxdhVy1zCnts49DFqjYNcMZsr3ybH/WTqC1FH0R3snYI4GIAoYmEegDqK/Fsvuw4cRFwM2Zr7WWguCCGaOwUhGpHmJvcz8D/DvieACGot8h8+dDWsF1L67dCyIGqHq/TyP4H9iJ2WBt2D30QmMp+Fuohs1w9dA92DuGguzV0EQ2sIIVKAghCNTCP7ODKdpXtuReR71B5zcCmHVlDan8k2AjBAxIkrZiH8DWJGxtM5vB4xIFNfkB21Ft2tl42GfhBxIavmngt1IoQQqUFBiKbA2EXLXMK+GRz4B8CoNd3L3gc5sIgcd5KpL0TMuHI5+4sQO80BUzeE1yMW5gGoNX2/fugqRHcjPopcs2HMhxAiZSgI0USQlRz3wzyAPZOg70ddRLbyodEw9SXHXVC5EL8p8h/23AEwYkbp97D/WcREI8s5qB29TD80GtGdiA+RcyqZ+0EIkUoUhGhKyHwWZb3J3nu5chnqhqs+44NDyTaS0sZDc0LUhCv08uvBPsSMLIVk7MaRbxELY1doLVALXKGXXYvINsSJHHeTdRiEEClGQYimRssg1xxUvsPev0A/hDqJcGAhVy6ltPFkGwkoiP/FXH47It8jdobjyDGVA39HbMgyALXAlXrZOIS/Rpwo7Way/QFCiNSjIESTRJbzydSXvVO48i3Uke5h71T2/53SbybLeYAGcQT7HuXQcsTBoDkfhubk0IeIDZkHIF4c5vLxqPoCcSL7NZR2I4QQKUlBiCZLc5NrFkIXsvdeRPegjqI7uPwWVk9R2niyDIYAOPAC++ciHpR2A0w9EN2O8BbEQrWH6oj4RNlzG4c+RpzIehGl3wEhRKpSEKJpI3M/ynqHfY9x4O+AjjqKfMvlN7OxSEufCFNPpDAOLmXvFMTFdAal3QCAKz9AbMgyGPGJcvltXPku4kSWQnJOBQhCiFSlIETTR2nkuIcs5+reBxApQd2F1+uHriTzOZR+C1QuUg8HFrP3AYARO82pOWcBBgAcfBuxIctgxEFnzySufBtxIvNZ5HwEMEAIkcIUhEgWpu5a1lL2P88Vs8F+1BmHVnBoFVnOpbQboTohRUS2c8UsrvwA8SFyPgRDKxwW2YbIVsTC0A4qD7Fi9t7PwTcQL1M+ueaATBBCpDYFIZKJIvs1ZL2AfTM5uBQJoHPlu1z5HpnPprQJMJ6CZkwvY/98DiwAhxEnShtP5gGoxsE3EBuynItYMXsf5MBixMvYVXPPB1khhEh5CkIkHa0FOWfAejF7H0RkGxKAObSSQ6vIfDal3QRjFzQzHODA37liLrgC8SPzOZR2I/4/5sq3ERuy/A6xYd8MDvwD8VK5mnseyA4hhAAUhEhOZOpFmUs5sIAr5oL9SADm0EoOrSLzOWQfA9MZaAY4yIGX2P8M9EOoHdWOXDMBDT+pWofoLsTCcAKMpyAG7JvF/vmIl6GtlrEAmgtCCFFNQYjkRSayjyXrZVzxNw68CESRAMyhf3LonzCeQrZRZL0AMCAZcYCDr3DFM9APoNbIprnmgNJxBFe+idiQ9QLEgCseZf/TiJchW8sogtYCQghxhIIQyU5zkeMesl3C3mlc9TkSJfwNe27niifJfg1ZLwRZkSx0LwcWcuB56B7UBZnIPQeqE/6LK7nyXcSGLBfgt3DFbK54CvHSMjX38zAcDyGEOIqCEM2DyqOMhQitYN9fEfkPEiW6nb33ccXDZL2IrJdDtUdTFv2BAy9y4BVwBerKQM5HyXQmjsKV70P3IBbGLlDtcUzsX8AVsxEvzaG550G1hxBC/JyCEM0Imc8hcz8OvMgVT0IvQ6LoXvYXsX8hmXrBdgVZBgIKTQhz6F8IvMChjwAdCUDknEaWQfg5Dr6K2JBlCI6J/QvYNx3x0hyauwjGUyCEEL+gIERzo8g2iqwXs/859j8HDiBhmKuKUVXMWhZZziPrEBi7onHpBzj4NgcXI/I9EobIcQ9Zh+F/RLajag1iopFlMGrG/iL2TUe8KE1zz4exC4QQ4tcoCNEsURqlTSDbSK54ioMvgcNIIP0gB57nwPMwtCPrBWS5AKodGhIHuPJDVL7Foc+AKBKIjOSYStah+AUOvgIwYkCmPjBkowbsL2LfNMSLrJp7LozdIIQQNVAQohnTMslxD9mv5oonOPgmEEViRbdzxWyumA3Vjsz9Ye5Hxh4gE+qJfoBDHyP0CYdWgoNIOMNxmvNhmHrgV0Q5uBQxsl2CGrC/iH3TEC+ykPtpmHpCCCFqpiBEs2doTc6/kn0M+x7l0D8BRsJFtnNkAfwLmKxk6gPT6TCeRsZTQTbUkX6Iw1+j6gsOfYzIVoBRLzSyXkSOO0Hp+DVc+R70A4iF5iLzQPwa9hexbxriRUZyzSZTbwghxDEpCJEiVCdyP0nhr7liDodWAIz6wEEOrUBoBQCGAaoTGbtAnQBDGzK0hToBlI4aMfSDiO7m6G5Ef0D4aw5vQnQ36hmZz6K0W2HsjJqxfyFiQ9ZhIBN+gf1F7JuGeJGRXLPJXAAhhPgtCkKkFGMXcj9F4c3s/xtX/hNg1KMoIv/myL9RjVGNjKA0UBo0J8gErgJHwH4gCv0guAoNydiF0m8lU18cW3gDwhsRG7IOxy+wv4h90xA3AzlnkvkcCCFEDBSESEHGzuR6kiIl7J/HwTcBHQ2Gw+AyoAzRnWhEhlZkv55slwAafgv7FyJGpnyoTvg59hexbxriZiDXTLKcByGEiI2CEClL5ZJzBtnHsH8+V74NDiMVGFqT/TqyDgcZEQt9P1d+gNiQ9VL8HPuL2DcNcdPI+RBZfg8hhIiZghApTuWS86+UfhsHXuLA89A9aK4Mx5N9FFkvB5kQM/a/AEQQC81JlsE4CvuL2DcNcdPIOZWsF0IIIeKhIIQ4TMuitJvIPpoDizmwENF9aE7UiWQfR9bfAwbEhQMcXIzYkHUEyIoj2F/EvmmIG5HjPrJeDCGEiJOCEOK/KJ3sY8g+miuXIfASV60GGEnN1JNsV5FlEKAhfhx4EXo5YmIg2xU4gv3Pse8hxI3IcT/ZroAQQsRPQQjxvxRZBsMymKLbOfAqB1+GXo7kQiaynEf2a6BOQq1xiP1FiA1ZzoXhOFRj/zPsexhxI3LcT7YrIIQQtaIghKiJoR2l30ppN3Lluxxciqo1gI4mztCGbJeT9RJoTtQNB16CfgCxIfsoVGP/M+x7GHEjctxPtisghBC1pSCEODaykvVisl6M6D4Ovc+V76FqHZoazUHmc2AdSqY+AKHuuIoD8xEjYxcYTwPAFY9zxRzEjchxP9mugBBC1IGCECJGhmyyjSLbKERKOPg2h1YishWNi8xk7g/rEDIVgIxIHA6+gug+xIbs1wDMvofYvwBxI3LcT7YrIIQQdaMghIiXyqX0Wyj9FugHOfQpQis59Am4Ag3G0IbMfWHqS+Z+IDsSjsPsfxYxMrQhy7nsncqB5xE3Isd9ZLsCQghRZwpCiFrTssg6FNahxFUcXo/wBlRt5PBG6AeQYARDWzJ2gak7mf8PhraoTxx8CdHdiA2ljWXvVA68iLgROe4j20gIIUQiKAgh6o5MZOoFUy/YQQCiuzi8EZESRH7g6A5Ef4DuQVy0TBiOI0MbGE+B8VRSp0BzoGFwgCvmIkaGHFSt5eBSxI3IcR/ZRkIIIRJEQQiRcIbWZGgNnAeAUE33IPojswe6F1wBvQJcAa6ElgZoIDugQBYYWpB2HAytQGY0EvY/C/0gYkNaSw4uRdyIHPeRbSSEECJxFIQQDUBzQnMSmjy9lP1FiBGZOfwV4qaR8y9kvQRCCJFQCkIIcQRXzAb7ESMOIW4Gck4l60UQQohEUxBCiJ9Et3PgZdQjAzmnk3UohBCiHigIIUQ19j0KRFBfDOT8K1mHQAgh6oeCEEIcVvUlV76PekJGcj5GlkEQQoh6oyCEEIjq3gcARn0gE7keJ/MACCFEfVIQQqQ89r+AyFbUB7KS+0kynQkhhKhnCkKIFKcfZP/fUB/ISu65ZOoDIYSofwpCiNTGvhnQvUg4spL7GTL1ghBCNAgFIUQqC6/j4BtIOErXMubDeBqEEKKhKAghUldU904GGImluTT3czB2gRBCNCAFIUSq4sCLCG9GYmlZWsYCqDwIIUTDUhBCpKboLvY9gsQytNIyimBoByGEaHAKQohkw5UfkKUQINQBe+8DB5BAhuO1jIUwtIEQQjQGBSFEsuHAAoSWkfOvgAG1wsHXOPQJEkidqLmLYMiGEEI0EgUhRNLR/Vz1JjhCrocBhXjpB9j3EBLIeIrmfg6aG0II0XgUhBBJhwMAuPJdlAXJ9QTIjHiwdzJ0DxLFeKrmfg6aE0II0agUhBBJhwOoxqGVKL+RXH8DWRAbDq3gyg+QKKZemnsuyA4hhGhsCkKIpMN+HMGhj7nsWs39DMiO36R72HMvEoTMZ5PrCZAFQgjRBCgIIZJMFFyJo1Wt0Q/9QXM/B82JY2LfVOgHkAhkOY9cDwMKQgjRNCgIIZILB/BL4U162WjN/Rw0N2rAlR9wcCkSgawXkXMqYIAQQjQZCkKI5KL78avC3+iHrtAyFkJriV+K7mPvPUgEsl9H6RMBghBCNCUKQojkwgHUJPKdfugqzb0Qhhz8TFT3TITuQV0Rpd9G9jEQQoimR0EIkVw4gGOI/Ec/NELLeB6GtjiCfY+h6gvUlYGck8l6CYQQoklSEEIkFeYKHFt0t156uZaxEKojAA59xP5nUUdkIucjZCmEEEI0VQpCiOTCAfwm/YB+6A9axgKQjT23AjrqgmzkfpJMfSGEEE2YghAiuXAAsdAP6odGgpzQPagLLUtzz4OxM4QQomlTEEIkF92PGOlewIu6MLTS3EVQ7SCEEE2eghAiuXAADUN11NzPwZADIYRIBgpCiOTCfjQA46maezCy15IAABcfSURBVB40N4QQIkkoCCGSCwdQz8jUm9xPgewQQojkoSCESC4cQH0iyyByPgoyQQghkoqCECK5cAD1hmxXkOM+QIMQQiQbBSFEcuEK1A+yX0fpt0IIIZKTghAiuegBJB5R+h1kvwZCCJG0FIQQSYXZjwQzkHMKWS+GEEIkMwUhRH0KBoMHDhzYu3fvgQMHSktLKysrmbm8vBxHuN1uAFarNTMzM7taVlaWxWJBTTiABCIruR4n89kQQogkpyCESBBd10tKStavX79169Zvv/1227Zt3377bVlZGeKXlZXVsWPH3NzcTp065ebm5ufnd+zYET9hPxKHTGeTuQBCCJH8FIQQdeD3+z/++OOPPvpozZo1a9eu9Xq9SISD1YqLi3FERkZG9+7de/bsec84j9GAROHQe/A6yPEgoEEIIZKZghAifps3b16yZMny5cs/++yzqqoq1L9Dhw59WO2uP3aEgZA4HFgMDpFzOmCAEEIkLQUhRMy+++67xYsXL1q0aNOmTWgMJiOZTYRE4+BS6F5yPQEyQQghkpOCEOK3RKPRt956a86cOf/85z+ZGY0nza6hfnBoBcpvJNdskAVCCJGEFIQQNQsEAk8++eTs2bN/+OEHNAHpaYR6w6GPuGyM5n4GZIMQQiQbBSHEr6mqqioqKnrwwQd3796NJiPNrqFeVX2hl43R3M+A0iCEEElFQQjxC6+//vqf//znH374AU1Mml1Dfataqx8arbnnQ3NCCCGSh4IQ4ii7du26+eabX3vtNTRJdruGBhD+Si/7g+ZeAC0DQgiRJBSEEEcUFRXdeOONgUAA9cBms7Vo0SIjI0PTNLPZbLPZAFRUVITD4UgkUlZWduDAgWAwiGNKsxMaRniLfuhKLaMIWksIIUQyUBBCAIFA4MYbbywqKkIidOzY8bTTTuvYsWOnTp06duzYtm3bli1b2mw2/JaKiop9+/b98MMP27Zt+7ba+vXrd+zYgSPS7RoaTGSbXnqZlvE8DG0ghBBNnoIQKW/Xrl2DBw/etGkTastkMvXp02fAgAG9evXq0aOH2+1GraRVO/HEE/v3748j9u/fv3bt2uLi4uXLlzsd/0ZDiu7SD12lZRTB0A5CCNG0KQiR2r799tvCwsLt27cjfhkZGRdddNGwYcMKCgrsdjvqR8uWLc+rNnny5GDpHIQfRwMgI7QMaFmkZXHgNUr/E2CAEEI0YQpCpLBNmzYNGjRo3759iIfRaBw6dOioUaMKCwuNRiMakMUc5TDqjmEizQnNSVpLGFqCHDC0hNYSmoO0ljC0hJYFaBBCiOShIESq2rNnz/nnn79v3z7ErEWLFtdff/3YsWNbtWqFRsF+xKAyxLv3Rvbsj5SX67v3Rfbsi5Z5orv3Rvbui5Z5orv3Ro5rfdK//vWOy+WCEEI0FwpCpKRgMDhs2LCdO3ciNunp6TfccMOdd97pdDrRiDiAwzQntBbQHKRlQ2sBzekP2t985/Pnn1/67feeH3dHqsKMYyrzbB46dOiHH35oMpkghBDNgoIQKen6669fvXo1YqBp2tixY6dOnep2u9HYKP0uckwGCD+XloYrRl8zYPCUiRMnvvjii4jBRx99dPfdd8+cORNCCNEsKAiRet57772FCxfit2ia1rVr12eeeaZHjx5oIsiKmmVnZ//973+/9tprx44d+9133+m6jmN69NFHL7300h49ekAIIZKfghApxuv1jh07FjF48sknx44di2TTv3//kpKS6dOn33XXXTimaDQ6atSo9evXm81mCCFEklMQIsU8/vjjO3fuxDER0cMPPzx27FgkrUmTJvl8vunTp+OYtmzZsnDhwuuuuw5CCJHkFIRIJZWVlXPmzMExaZo2f/780aNHI5kR0bRp0zIyMm677TYc06xZs8aMGaNpGoQQIpkpCJFKFi5cuG/fPhzTjBkzRo8ejf/h88Hng9sNqxWHVVWhrAwGA7KycFgohPJy+HzQdZjNcLmQng5NQ/0JBlFWBr8fzLBakZkJqxVE+Llbb711//79M2fORM1KSkrefPPNoUOHQgghkpmCEKnkhRdewDFdeeWVEydOxC8tW4ZXX8WECejdG4ft2IG5c+Fy4d57EQziiy/wyivYuBFVVWjRAoWFGDYMxx8PItQHnw/LlmHpUmzbBl1H69YYPhyFhcjIABF+7qGHHtq0adP777+Pmi1cuHDo0KEQQohkpiBEyvB6vatXr0bNcnJyHn/8ccSFGevX4+mnkZmJuXPRsiVWrcLf/47yctx8M5xOJJyu4/33UVSEggJMngyTCa+/jmefxWFDh8Jqxc9pmvbMM8906dLF6/WiBitXroxEIkopCCFE0lIQImWsXLkyEomgZnfddVdGRgbiEgziX/9CJIJx43DKKThs2DCUlmLlSmzYgIICJFxFBd56C126YORItG6Nw8aOxXff4ZNPkJ+PvDz8Qps2bSZMmDBlyhTUwOPxrFmzpk+fPhBCiKSlIETKKC4uRs3S09OvueYaHEN5Odauhd+Pw3btwu7dcLlQWoqdO5GTg06d8BOlcOKJ+Pxz/PAD6sOPP2L/fvTvj+xs/MRoRNeu+PBDHDqEGowfP3769OnRaBQ1KC4u7tOnD4QQImkpCJEy9uzZg5r179/fbrfjGHbvxuuvIzMTh1VUYO9edO6MaBTRKCwWGAz4L6MRmoZIBAkVDoc1TTOEwzjMaISm4b9MJug6olHUIDs7u0ePHsXFxajBnj17IIQQyUxBiJSxf/9+1Oy0007DseXmYswYnHEGDvv+eyxciMPS0+F2Y9cuHDiAnBwcpuvYtw9VVcjMRIJUVVVt377d5/O1b98+IysLNhv27IHPB6cTh0Wj+OEH2GxIS0PN8vPzi4uLUYO9e/dCCCGSmYIQKaO0tBQ1y8zMxLEpBYcDmZk47NAhmM04zOVCt27YsgXvvIMhQ2C34z//wWefweFA584AdF0Ph8OaphmNRsQvGo3u3r177dq1a9as6dSpU+vWrZGdje7dsWEDPv0UZ54JpfDNN1izBr16oVUr1CwrKws1O3jwIIQQIpkpCJEyHA4Haub1elELBgP69MHOnfj4Y+zeDZsNO3ciGMSwYWjfHkBFRcXq1at9Pl/Pnj1btWqlaRpiVlpa+uWXX65evXrv3r0nn3xyQUFBy5YtoWm46CKUl+Ott7BpEwwGlJTg+ONx7rnIykLNysvLUTOn0wkhhEhmCkKkjOzsbNSspKQEx9CxIwYPRk4OfuJy4f/+D1YrDjv+eIwcifbtsXEj9u9Hu3Y46yx07QqDAQAzl5aWfvrpp5s3b+7Vq1d+fn5mZiZ+i8/n++qrr1avXr1jx47s7OxrrrnmpJNO2r1799q1azt06JB10km4/np8/DFKSqDr6N4d55yD9u2haajZ1q1bUbOWLVtCCCGSmYIQKSM7Oxs1W758eTQaNRgM+FVdu6JrV/xXixYYOhT/lZ2NYcMwbBh+wel0DhkypH379qtWrXrrrbc2btzYr1+/U045xW6349dUVVWVlJSsWrVq69atGRkZw4YNy8/P9/v977333rp169q0aXPcccfhsPbt0b49YhYMBj/55BPULCcnB0IIkcwUhEgZXbt2Rc327NmzdOnSiy++GIlms9l69eqVm5v7xRdfFBcXL1q0qGPHjmeffXanTp2MRiOO0HV9x44dq1at2rJli9FoLCgoOOuss8xmc3Fx8eeff15eXt6xY8eCgoLs7GzEb8GCBYFAADU77bTTIIQQyUxBiJQxaNAgImJm1GDKlCkXXnihUgr1wO12FxYWnnrqqZ999tm6devmz5/ftWvXc8455/jjjyeiAwcOfPrpp6tXrw6Hw6eeempBQUGLFi02b968YsWK3bt3t23bdvDgwaeccordbkf8/H7/zJkzUTOTydSvXz8IIUQyUxAiZbRq1apz587ffPMNarBhw4aZM2feeeedqB9E1KpVq6FDh3br1u3TTz/9+uuvt2zZ0rt3b6XUmjVrKioqOnXq1Ldv344dO/7444/z58/ftm1bdnb273//++7du7vdbiJCrdx7773bt29Hzfr27Wu32yGEEMlMQYhUMnz48G+++QY1u//++7t37z5o0CDUG6VUp06djj/++JKSkk8++eTDDz/cuXNnu3btLrroou7du3u93sWLF2/YsMHhcJx99tm9e/fOyckxGAyorUWLFj322GM4puHDh0MIIZKcghCp5IYbbpgxY0YwGEQNwuHwJZdcsmLFivz8fNQnq9XarVu3tm3bbtq06dNPP1VK2Wy2VatWrVixAkD37t379OnTtm1bk8mEOlixYsXVV1/NzKhZZmbm1VdfDSGESHIKQqSSli1bjho1au7cuaiZx+MpKChYsmTJwIEDUc/cbvdZZ52Vm5u7fv36JUuWBAKBrl279uzZ88QTT7Tb7aibt99++9JLL62srMQxjR8/3mazQQghkpyCEClm0qRJL7zwgt/vR80qKiouuOCCd999t3///qhnmqbl5OT07NkzPT3dbDbn5uY6HA4iQt28+uqrl19+eSQSwTG1bNnypptughBCJD8FIVLMCSecMHXq1D/96U84psrKyiuvvHLChAk33nhjWloa6llGRkafPn00TSMi1E1ZWdkjjzzy9NNPRyIR/JbHH388MzMTQgiR/BSESD033XTTq6+++umnn+KYdu/ePWnSpEcffXTGjBlXXXUVEaHeEJHBYEDdMPMLL7xwyy23lJaWIgbnn3/+iBEjIIQQzYKCEKlH07QXXnihd+/e+/btw2/Zt2/fqFGj5s2bN2XKlH79+qGpevfdd++7774vv/wSsWnfvv1zzz0HIYRoLhSESEnt2rVbunTpOeecEwwGEYNPPvmkoKBg4MCBt99++8CBA4kITUM0Gn377bcfeuih4uJixMzlcr3zzjstW7aEEEI0FwpCpKrevXu/8MILI0aMiEQiiM3yanl5eTfccMPIkSMzMzPRePbu3btw4cKnnnpqx44diIfVan3ttddOPvlkCCFEM6IgRAq7+OKLX3vttcsuu6yyshIx27p1680333zrrbcOGDDgsssuu+CCCzIzM9FQ9u3bt2TJkpdffvnjjz+ORqOIk9PpfPPNN/v16wchhGheFIRIbUOGDHn//fcvvPBCj8eDeITD4ferGQyGM844Y9CgQQMHDuzevXtaWhoSzePxrF69evny5cuWLdu4cSMzo1ays7Pfe++9008/HUII0ewoCJHyCgoKVq9efckll2zatAnxi0ajX1SbOnWqwWA46aSTunfv3q1bt9zc3E6dOrVv395oNCIeoVDo+++/Lykp+fbbbzds2LB27dqSkhJmRt307dt30aJFbdq0gRBCNEcKQgggLy9v9erVN9100/z581EH0Wj0m2o4QimVnZ2dlZV13HHHtWjRwmq1pqenK6UsFouu61VVVeFwuKKiwu/379+/f9++fQcOHNi3b5+u60gcIpo4ceK0adOMRiOEEKKZUhBCVLNarfPmzTv//PMnTJjw448/IkEikciuahs3bkRj6NSp01NPPTVgwAAIIUSzpiCEOMqwYcN+97vfzZgxY9q0aeFwGMnMaDTecsstDzzwgMVigRBCNHcKQoifs9lsDzzwwKWXXvrggw+++uqruq4j2Silrrzyyvvuu699+/YQQojUoCCE+DWdO3devHjxV1999cADD7zxxhu6riMZGI3Gyy677N57783NzYUQQqQSBSFEzbp27fr6669///33Tz311HPPPXfo0CE0VTk5Odddd93YsWNbtWoFIYRIPQpCiN/SoUOHmTNnTp48+dVXX120aNGyZcvC4TCaBovFct55511++eVDhgwxmUwQQohUpSCEiI3Var2q2qFDh15//fUlS5Z89NFHfr8fjcHpdA4YMGDYsGEXXnhheno6hBAi5SkIIeKUkZExplpVVdVnn322bNmyVatWbdiwIRAIoD6lpaXl5+efc845gwYN6tmzp1IKQgghjlAQQtSWyWQ6uxqASCSyefPmNWvWrFu3rqSkZNu2bT/88IOu66gtg8FwwgkndOrUKS8vLz8/v0ePHnl5eQaDAUIIIX6NghAiEZRSXatde+21qBYKhb777rtdu3bt37//wIED+/fvLy0traysDAaDuq57PB4ALpeLiOx2u8lkanFETk5O69at27dvbzKZIIQQIjYKQoj6YTabO1eDEEKI+qcghBBCCJH8FIQQKaN79+7jx48fPXo06mb8+PFz5swBYDAYIpEIjohGo5MmTSoqKgoEAoWFhXPnzs3OzsZRrrvuumeffXby5Mn33nsvjhKNRidNmlRUVBQIBAoLC+fOnZudnY2fi0ajkyZNKioqCgQChYWFc+fOzc7OhhBCHKEghBBx+lu1t99+e+jQoTjK9OnTFy9evHz58pYtW1577bUjRoxYuXIljnjooYdee+21OXPm3HbbbR06dBg5ciSOmD59+uLFi5cvX96yZctrr712xIgRK1euxM9Nnz598eLFy5cvb9my5bXXXjtixIiVK1dCCCGOUBBCpIYRI0Z8+eWXV1fr1atXcXExEm3u3Ll33HFHt27dAMyaNatz585bt27Ny8sD8PLLL8+cOXPZsmX5+fm5ubnDhw9v06ZNv379UG3u3Ll33HFHt27dAMyaNatz585bt27Ny8vDUebOnXvHHXd069YNwKxZszp37rx169a8vDwc5Yknnnj00Uf379+fn5//+OOP5+fnQwiRMhSEEKlh0aJF27ZtGz9+/OjRo/ELo0ePXrhwIX7h7rvvnjJlCmJQWlq6a9euHj16oNrJJ59ss9k2btyYl5f3+eefT5gw4f3338/PzwcwcODARYsWjRgxYuXKlXl5eaWlpbt27erRoweqnXzyyTabbePGjXl5eTiitLR0165dPXr0QLWTTz7ZZrNt3LgxLy8PR5SUlNx6660rV64844wzNmzY8NJLL+Xn50MIkTIUhBACKKqGOvB6vQCcTieOcLlcXq8XQJ8+ffbu3YujnHvuubt370Y1r9cLwOl04giXy+X1enEUr9cLwOl04giXy+X1enEUo9FoMpkcDofFYuldDUKIVKIghBCJ4HA4AHg8HhxRXl7ucDjwWxwOBwCPx4MjysvLHQ4HjuJwOAB4PB4cUV5e7nA4cJT27du/9NJLt91228GDB7t27XrzzTd369YNQoiUoSCESBmapqEGo0ePXrhwIX7h7rvvnjJlCmKQmZnZunXrNWvW9O7dG8CWLVsCgUC3bt3wWzIzM1u3br1mzZrevXsD2LJlSyAQ6NatG46SmZnZunXrNWvW9O7dG8CWLVsCgUC3bt3wcxdU03X9H//4R79+/fbs2WOz2SCESA0KQoiUcdxxx3311VeRSEQphZ8rqoa6GTdu3MyZM/v165ednT1x4sSCgoK8vDzEYNy4cTNnzuzXr192dvbEiRMLCgry8vIAjBkzZvv27cuXLwcwbty4mTNn9uvXLzs7e+LEiQUFBXl5eTjKsmXLVq5cec0117Rp0yYajQaDQV3XIYRIGQpCiJRx++23jxkzZvbs2WeccUZxcTFqa968eX/84x9RjYgAHDhwICsr68477ywvLx8wYEAgECgsLFywYAFic+edd5aXlw8YMCAQCBQWFi5YsAC/cOedd5aXlw8YMCAQCBQWFi5YsAA/V1BQsH79+sGDB+/atSs3N/fll19OS0uDECJlKAghUsaZZ565ZcsW1NmYavgFg8HwcDXEyWAwPFwNPzdv3jwcYTAYHq6GGphMpturQQiRkhSEEEIIIZKfghBCCCFE8lMQQgghhEh+CkIIIYQQyU9BCCGEECL5KQghhBBCJD8FIYQQQojkpyCEEEIIkfwUhBBCCCGSn4IQQgghRPJTEEIIIYRIfgpCCCGEEMlPQQghhBAi+f0/zJVRDhUtLqUAAAAASUVORK5CYII=", - "text/plain": [ - "956×753 Array{RGB{N0f8},2} with eltype ColorTypes.RGB{FixedPointNumbers.N0f8}:\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fd6 = getfluxdiagram(ssys6,1;speciesratetolerance=1e-4)" - ] - }, - { - "cell_type": "code", - "execution_count": 116, - "id": "d82e3be4", - "metadata": {}, - "outputs": [], - "source": [ - "# function plot_composition_comparison(solutions, t, tol, exclude, x_labels)\n", - "# # Prepare data storage\n", - "# species_dict = Dict{String, Vector{Float64}}() # To collect mole fractions for each species\n", - "\n", - "# # Iterate through each solution\n", - "# for (idx, bsol) in enumerate(solutions)\n", - "# # Get mole fractions and species at the specified time\n", - "# mole_fractions = molefractions(bsol, t)\n", - "# species = bsol.domain.phase.species\n", - "\n", - "# # Filter species based on threshold and exclusion list\n", - "# for (i, mf) in enumerate(mole_fractions)\n", - "# species_name = species[i].name\n", - "# if mf > tol && !(species_name in exclude)\n", - "# # Initialize vector for each species if not already present\n", - "# if !haskey(species_dict, species_name)\n", - "# species_dict[species_name] = zeros(length(solutions))\n", - "# end\n", - "# # Assign the mole fraction for the current solution\n", - "# species_dict[species_name][idx] = mf\n", - "# end\n", - "# end\n", - "# end\n", - "\n", - "# # Convert species data to arrays for plotting\n", - "# species_names = collect(keys(species_dict))\n", - "# num_solutions = length(solutions)\n", - "\n", - "# # Sort species for each solution based on mole fractions (descending order)\n", - "# sorted_species = sort(species_names, by=name -> -maximum(species_dict[name]))\n", - "\n", - "# # Plotting each solution individually\n", - "# clf() # Clear the current figure\n", - "# bar_positions = 1:num_solutions\n", - "# width = 0.35 # Width of each bar\n", - "# color_cycle = get_cmap(\"tab20\", length(sorted_species))\n", - "\n", - "# # Initialize bottom values for stacked bars\n", - "# bottoms = zeros(num_solutions)\n", - "\n", - "# # Plot each species, stacking from the highest mole fraction down\n", - "# for (color_idx, species_name) in enumerate(sorted_species)\n", - "# # Get the mole fractions for the current species across solutions\n", - "# current_data = species_dict[species_name]\n", - "\n", - "# # Plot bars for the current species\n", - "# bar(bar_positions, current_data, width, bottom=bottoms, color=color_cycle(color_idx), label=species_name)\n", - "\n", - "# # Update the bottom values for stacking\n", - "# bottoms .+= current_data\n", - "# end\n", - "\n", - "# # Formatting the plot\n", - "# xticks(bar_positions, x_labels)\n", - "# ylabel(\"Mole Fraction\")\n", - "# legend(title=\"Species\", loc=\"upper right\", bbox_to_anchor=(1.2, 1))\n", - "# title(\"Liquid Phase Composition at t = $t\")\n", - "# tight_layout() # Adjust layout for better appearance\n", - "# end\n" - ] - }, - { - "cell_type": "code", - "execution_count": 117, - "id": "b1829469", - "metadata": {}, - "outputs": [], - "source": [ - "# sims_collection = [ssys1.sims[1], ssys2.sims[1], ssys3.sims[1]]\n", - "# x_labels = [\"Ag111@-2.0V\", \"Ag111@-1.5V\", \"Ag111@-1.0V\"]\n", - "# plot_composition_comparison(sims_collection, 1e-3, 1e-3, [\"H2O\"])" - ] - }, - { - "cell_type": "code", - "execution_count": 118, - "id": "51c99d48", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.9.1", - "language": "julia", - "name": "julia-1.9" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.9.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/CO2RR_RMS/Ag/CO2RR_RMS_AIChE.jl b/CO2RR_RMS/Ag/CO2RR_RMS_AIChE.jl new file mode 100644 index 0000000..61098d9 --- /dev/null +++ b/CO2RR_RMS/Ag/CO2RR_RMS_AIChE.jl @@ -0,0 +1,451 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,jl:percent +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.17.2 +# kernelspec: +# display_name: Julia 1.9.1 +# language: julia +# name: julia-1.9 +# --- + +# %% +using DifferentialEquations +using ReactionMechanismSimulator +using PyPlot + +# %% +outdict1 = readinput("chem43_Ag.rms"); +outdict2 = readinput("chem43_Cu.rms") + + +# %% +liqspcs1 = outdict1["gas"]["Species"]; +liqrxns1 = outdict1["gas"]["Reactions"]; +surfspcs1 = outdict1["surface"]["Species"]; +surfrxns1 = outdict1["surface"]["Reactions"]; +interfacerxns1 = outdict1[Set(["surface", "gas"])]["Reactions"]; +solv1 = outdict1["Solvents"][1]; + +# %% +liqspcs2 = outdict2["gas"]["Species"]; +liqrxns2 = outdict2["gas"]["Reactions"]; +surfspcs2 = outdict2["surface"]["Species"]; +surfrxns2 = outdict2["surface"]["Reactions"]; +interfacerxns2 = outdict2[Set(["surface", "gas"])]["Reactions"]; +solv2 = outdict2["Solvents"][1]; + +# %% +sitedensity1 = 2.292e-5; # Ag111 +sitedensity2 = 2.943e-5; # Cu111 +AVratio = 1.0e5 + +# %% +initialcondsliq = Dict(["proton"=>10.0^-4,"CO2"=>10.0^-3*10^3, + "V"=>1.0,"T"=>298.15,"Phi"=>0.0,"d"=>0.0]); +initialcondssurf1 = Dict(["CO2X"=>0.4*sitedensity1*AVratio, + "CHO2X"=>0.1*sitedensity1*AVratio, + "CO2HX"=>0.1*sitedensity1*AVratio, + "OX"=>0.1*sitedensity1*AVratio, + "OCX"=>0.1*sitedensity1*AVratio, + "vacantX"=>0.1*sitedensity1*AVratio, + "CH2O2X"=>0.05*sitedensity1*AVratio, + "CHOX"=>0.04*sitedensity1*AVratio, + "CH2OX"=>0.01*sitedensity1*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-1.5]); +initialcondssurf2 = Dict(["CO2X"=>0.4*sitedensity1*AVratio, + "CHO2X"=>0.1*sitedensity1*AVratio, + "CO2HX"=>0.1*sitedensity1*AVratio, + "OX"=>0.1*sitedensity1*AVratio, + "OCX"=>0.1*sitedensity1*AVratio, + "vacantX"=>0.1*sitedensity1*AVratio, + "CH2O2X"=>0.05*sitedensity1*AVratio, + "CHOX"=>0.04*sitedensity1*AVratio, + "CH2OX"=>0.01*sitedensity1*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-1.0]); +initialcondssurf3 = Dict(["CO2X"=>0.4*sitedensity1*AVratio, + "CHO2X"=>0.1*sitedensity1*AVratio, + "CO2HX"=>0.1*sitedensity1*AVratio, + "OX"=>0.1*sitedensity1*AVratio, + "OCX"=>0.1*sitedensity1*AVratio, + "vacantX"=>0.1*sitedensity1*AVratio, + "CH2O2X"=>0.05*sitedensity1*AVratio, + "CHOX"=>0.04*sitedensity1*AVratio, + "CH2OX"=>0.01*sitedensity1*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-2.0]); +initialcondssurf4 = Dict(["CO2X"=>0.4*sitedensity2*AVratio, + "CHO2X"=>0.1*sitedensity2*AVratio, + "CO2HX"=>0.1*sitedensity2*AVratio, + "OX"=>0.1*sitedensity2*AVratio, + "OCX"=>0.1*sitedensity2*AVratio, + "vacantX"=>0.1*sitedensity2*AVratio, + "CH2O2X"=>0.05*sitedensity2*AVratio, + "CHOX"=>0.04*sitedensity2*AVratio, + "CH2OX"=>0.01*sitedensity2*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-1.5]); +initialcondssurf5 = Dict(["CO2X"=>0.4*sitedensity2*AVratio, + "CHO2X"=>0.1*sitedensity2*AVratio, + "CO2HX"=>0.1*sitedensity2*AVratio, + "OX"=>0.1*sitedensity2*AVratio, + "OCX"=>0.1*sitedensity2*AVratio, + "vacantX"=>0.1*sitedensity2*AVratio, + "CH2O2X"=>0.05*sitedensity2*AVratio, + "CHOX"=>0.04*sitedensity2*AVratio, + "CH2OX"=>0.01*sitedensity2*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-1.0]); +initialcondssurf6 = Dict(["CO2X"=>0.4*sitedensity2*AVratio, + "CHO2X"=>0.1*sitedensity2*AVratio, + "CO2HX"=>0.1*sitedensity2*AVratio, + "OX"=>0.1*sitedensity2*AVratio, + "OCX"=>0.1*sitedensity2*AVratio, + "vacantX"=>0.1*sitedensity2*AVratio, + "CH2O2X"=>0.05*sitedensity2*AVratio, + "CHOX"=>0.04*sitedensity2*AVratio, + "CH2OX"=>0.01*sitedensity2*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-2.0]); + +# %% +liq1 = IdealDiluteSolution(liqspcs1,liqrxns1,solv1,name="liquid",diffusionlimited=true); + +liq2 = IdealDiluteSolution(liqspcs2,liqrxns2,solv2,name="liquid",diffusionlimited=true); + +surf1 = IdealSurface(surfspcs1,surfrxns1,sitedensity1,name="surface"); + +surf2 = IdealSurface(surfspcs2,surfrxns2,sitedensity2,name="surface"); + +domainliq1,y0liq1,pliq1 = ConstantTVDomain(phase=liq1, + initialconds=initialcondsliq,constantspecies=["proton","CO2"]); + +domainliq2,y0liq2,pliq2 = ConstantTVDomain(phase=liq2, + initialconds=initialcondsliq,constantspecies=["proton","CO2"]); + +# %% +domaincat1,y0cat1,pcat1 = ConstantTAPhiDomain(phase=surf1, + initialconds=initialcondssurf1); + +inter1,pinter1 = ReactiveInternalInterfaceConstantTPhi(domainliq1, + domaincat1,interfacerxns1,298.15,AVratio*1.0); + +# %% +domaincat2,y0cat2,pcat2 = ConstantTAPhiDomain(phase=surf1, + initialconds=initialcondssurf2); + +inter2,pinter2 = ReactiveInternalInterfaceConstantTPhi(domainliq1, + domaincat2,interfacerxns1,298.15,AVratio*1.0); + +# %% +domaincat3,y0cat3,pcat3 = ConstantTAPhiDomain(phase=surf1, + initialconds=initialcondssurf3); + +inter3,pinter3 = ReactiveInternalInterfaceConstantTPhi(domainliq1, + domaincat3,interfacerxns1,298.15,AVratio*1.0); + +# %% +domaincat4,y0cat4,pcat4 = ConstantTAPhiDomain(phase=surf2, + initialconds=initialcondssurf4); + +inter4,pinter4 = ReactiveInternalInterfaceConstantTPhi(domainliq2, + domaincat4,interfacerxns2,298.15,AVratio*1.0); + +# %% +domaincat5,y0cat5,pcat5 = ConstantTAPhiDomain(phase=surf2, + initialconds=initialcondssurf5); + +inter5,pinter5 = ReactiveInternalInterfaceConstantTPhi(domainliq2, + domaincat5,interfacerxns2,298.15,AVratio*1.0); + +# %% +domaincat6,y0cat6,pcat6 = ConstantTAPhiDomain(phase=surf2, + initialconds=initialcondssurf6); + +inter6,pinter6 = ReactiveInternalInterfaceConstantTPhi(domainliq2, + domaincat6,interfacerxns2,298.15,AVratio*1.0); + +# %% +@time react1,y01,p1 = Reactor((domainliq1,domaincat1), (y0liq1,y0cat1), (0.0, 1.0e2), [inter1], (pliq1,pcat1,pinter1)); + +@time sol1 = solve(react1.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +ssys1 = SystemSimulation(sol1,(domainliq1,domaincat1,),(inter1,),p1); + + +# %% +@time react2,y02,p2 = Reactor((domainliq1,domaincat2), (y0liq1,y0cat2), (0.0, 1.0e2), [inter2], (pliq1,pcat2,pinter2)); + +@time sol2 = solve(react2.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-12,reltol=1e-6); + +ssys2 = SystemSimulation(sol2,(domainliq1,domaincat2,),(inter2,),p2); + +# %% +@time react3,y03,p3 = Reactor((domainliq1,domaincat3), (y0liq1,y0cat3), (0.0, 1.0e2), [inter3], (pliq1,pcat3,pinter3)); + +@time sol3 = solve(react3.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +ssys3 = SystemSimulation(sol3,(domainliq1,domaincat3,),(inter3,),p3); + +# %% +@time react4,y04,p4 = Reactor((domainliq2,domaincat4), (y0liq2,y0cat4), (0.0, 1.0e2), [inter4], (pliq2,pcat4,pinter4)); + +@time sol4 = solve(react4.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +ssys4 = SystemSimulation(sol4,(domainliq2,domaincat4,),(inter4,),p4); + +# %% +@time react5,y05,p5 = Reactor((domainliq2,domaincat5), (y0liq2,y0cat5), (0.0, 1.0e2), [inter5], (pliq2,pcat5,pinter5)); + +@time sol5 = solve(react5.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +ssys5 = SystemSimulation(sol5,(domainliq2,domaincat5,),(inter5,),p5); + +# %% +@time react6,y06,p6 = Reactor((domainliq2,domaincat6), (y0liq2,y0cat6), (0.0, 1.0e2), [inter6], (pliq2,pcat6,pinter6)); + +@time sol6 = solve(react6.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +ssys6 = SystemSimulation(sol6,(domainliq2,domaincat6,),(inter6,),p6); + +# %% +# Helper function +function plotX1(sim, tol, t_end, exclude) + clf() + xs = molefractions(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Mole Fraction") +end + +# %% +function plotX(bsol, tol, t_end, exclude) + # Species order and corresponding colors for the main species + species_order = ["CO2", "proton", "H2", "O=CO", "C=O", "O=CC=O", "O=CCO"] + color_map = Dict("CO2" => "blue", "proton" => "orange", "H2" => "purple", + "O=CO" => "red", "C=O" => "green", "O=CC=O" => "magenta", + "O=CCO" => "brown") + # Replacement map for species labels + replacement_map = Dict("C=O" => "CH2=O", "O=CO" => "HCOOH", + "O=CC=O" => "O=CH-CH=O", "O=CCO" => "O=CH-CH2OH") + + clf() + + xs = molefractions(bsol) + maxes = maximum(xs, dims=2) + spnames = [] + plotted_species = Set{String}() + + # Filter data to the specified time range + if t_end !== nothing + t_mask = bsol.sol.t .<= t_end + ts = bsol.sol.t[t_mask] + xs = xs[:, t_mask] + else + ts = bsol.sol.t + end + + # Plot species in the specified order with custom colors and labels + for sp in species_order + # Find the species index in the phase + species_index = findfirst(x -> x.name == sp, bsol.domain.phase.species) + if species_index === nothing || maxes[species_index] <= tol || sp in exclude + continue + end + + # Apply replacement for display name if available + display_name = get(replacement_map, sp, sp) + + # Plot the species with the specified color + plot(ts, xs[species_index, :], label=display_name, color=color_map[sp]) + push!(spnames, display_name) + push!(plotted_species, sp) + end + + # Plot any remaining species that are above the tolerance and not already plotted + for i = 1:length(bsol.domain.phase.species) + sp = bsol.domain.phase.species[i].name + if maxes[i] > tol && !(sp in exclude) && !(sp in plotted_species) + plot(ts, xs[i, :], label=sp) + push!(spnames, sp) + end + end + + # Configure the legend and labels + xlabel("Time in sec", fontsize=16) + ylabel("Mole Fraction", fontsize=16) + xticks(fontsize=14) + yticks(fontsize=14) + legend(spnames, loc="upper left", bbox_to_anchor=(0, 0.93), fontsize=12, ncol=2) +end + +# %% +exclude_species = ["H2O"] +plotX(ssys1.sims[1], 1e-12, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1) +ylim(1e-12, 5) +title("Ag111@-1.5 V", fontsize=16, fontweight="bold") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys2.sims[1], 1e-10, 10, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 10) +ylim(1e-12, 5) +title("Ag111@-1.0 V", fontsize=16, fontweight="bold") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys3.sims[1], 1e-12, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1) +ylim(1e-12, 5) +title("Ag111@-2.0 V", fontsize=16, fontweight="bold") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys4.sims[1], 1e-12, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1) +ylim(1e-12, 5) +title("Cu111@-1.5 V", fontsize=16, fontweight="bold") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys5.sims[1], 1e-12, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1) +ylim(1e-12, 5) +title("Cu111@-1.0 V", fontsize=16, fontweight="bold") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys6.sims[1], 1e-12, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1) +ylim(1e-12, 5) +title("Cu111@-2.0 V", fontsize=16, fontweight="bold") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys1.sims[2], 0.1, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1) +ylim(1e-12, 5) +title("Solid-phase Mole Fractions on Ag111@-1.5 V", fontsize=16, fontweight="bold") +legend(loc="lower left") +gcf() + +# %% +Dict([ssys1.sims[1].names[i]=>molefractions(ssys1.sims[1],1)[i] for i in 1:length(ssys1.sims[1].names)]) + +# %% +fd1 = getfluxdiagram(ssys1,1;speciesratetolerance=1e-4) + +# %% +fd3 = getfluxdiagram(ssys3,1;speciesratetolerance=1e-4) + +# %% +fd4 = getfluxdiagram(ssys4,1;speciesratetolerance=1e-4) + +# %% +fd5 = getfluxdiagram(ssys5,1;speciesratetolerance=1e-4) + +# %% +fd6 = getfluxdiagram(ssys6,1;speciesratetolerance=1e-4) + +# %% +# function plot_composition_comparison(solutions, t, tol, exclude, x_labels) +# # Prepare data storage +# species_dict = Dict{String, Vector{Float64}}() # To collect mole fractions for each species + +# # Iterate through each solution +# for (idx, bsol) in enumerate(solutions) +# # Get mole fractions and species at the specified time +# mole_fractions = molefractions(bsol, t) +# species = bsol.domain.phase.species + +# # Filter species based on threshold and exclusion list +# for (i, mf) in enumerate(mole_fractions) +# species_name = species[i].name +# if mf > tol && !(species_name in exclude) +# # Initialize vector for each species if not already present +# if !haskey(species_dict, species_name) +# species_dict[species_name] = zeros(length(solutions)) +# end +# # Assign the mole fraction for the current solution +# species_dict[species_name][idx] = mf +# end +# end +# end + +# # Convert species data to arrays for plotting +# species_names = collect(keys(species_dict)) +# num_solutions = length(solutions) + +# # Sort species for each solution based on mole fractions (descending order) +# sorted_species = sort(species_names, by=name -> -maximum(species_dict[name])) + +# # Plotting each solution individually +# clf() # Clear the current figure +# bar_positions = 1:num_solutions +# width = 0.35 # Width of each bar +# color_cycle = get_cmap("tab20", length(sorted_species)) + +# # Initialize bottom values for stacked bars +# bottoms = zeros(num_solutions) + +# # Plot each species, stacking from the highest mole fraction down +# for (color_idx, species_name) in enumerate(sorted_species) +# # Get the mole fractions for the current species across solutions +# current_data = species_dict[species_name] + +# # Plot bars for the current species +# bar(bar_positions, current_data, width, bottom=bottoms, color=color_cycle(color_idx), label=species_name) + +# # Update the bottom values for stacking +# bottoms .+= current_data +# end + +# # Formatting the plot +# xticks(bar_positions, x_labels) +# ylabel("Mole Fraction") +# legend(title="Species", loc="upper right", bbox_to_anchor=(1.2, 1)) +# title("Liquid Phase Composition at t = $t") +# tight_layout() # Adjust layout for better appearance +# end + + +# %% +# sims_collection = [ssys1.sims[1], ssys2.sims[1], ssys3.sims[1]] +# x_labels = ["Ag111@-2.0V", "Ag111@-1.5V", "Ag111@-1.0V"] +# plot_composition_comparison(sims_collection, 1e-3, 1e-3, ["H2O"]) + +# %% diff --git a/CO2RR_RMS/Ag/CO2RR_RMS_Diffusion_Interface.ipynb b/CO2RR_RMS/Ag/CO2RR_RMS_Diffusion_Interface.ipynb deleted file mode 100644 index b089263..0000000 --- a/CO2RR_RMS/Ag/CO2RR_RMS_Diffusion_Interface.ipynb +++ /dev/null @@ -1,6894 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "8a590634", - "metadata": {}, - "outputs": [], - "source": [ - "using DifferentialEquations\n", - "using ReactionMechanismSimulator\n", - "using PyPlot" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "e941d4fb", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[14:28:08] WARNING: not removing hydrogen atom without neighbors\n", - "[14:28:08] WARNING: not removing hydrogen atom without neighbors\n", - "┌ Warning: failed to generate StokesDiffusivity model for species vacantX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2O2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species H2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [H][H].[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(=O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH3X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(C#[Pt])CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)C(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C([Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C([Pt])CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC([Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=[Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC([Pt])=C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=C=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC(=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCOC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCC(=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC([Pt])=C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=COC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCOO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C=CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])CCO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)C(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)C(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC([Pt])OC=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=[Pt])OC=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC([Pt])=CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C([Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(C=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n" - ] - }, - { - "data": { - "text/plain": [ - "Dict{Any, Any} with 4 entries:\n", - " \"Solvents\" => Solvent[Solvent(\"water\", RiedelViscosity{Float64}(…\n", - " Set([\"surface\", \"gas\"]) => Dict{Any, Any}(\"Reactions\"=>ElementaryReaction[vac…\n", - " \"gas\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…\n", - " \"surface\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "outdict = readinput(\"chem300.rms\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "fe2767e9", - "metadata": {}, - "outputs": [], - "source": [ - "boundarylayerspcs = outdict[\"gas\"][\"Species\"]\n", - "boundarylayerrxns = outdict[\"gas\"][\"Reactions\"]\n", - "surfspcs = outdict[\"surface\"][\"Species\"]\n", - "surfrxns = outdict[\"surface\"][\"Reactions\"]\n", - "interfacerxns = outdict[Set([\"surface\", \"gas\"])][\"Reactions\"]\n", - "solv = outdict[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "c54ee65e", - "metadata": {}, - "outputs": [], - "source": [ - "sitedensity = 2.292e-5; # Ag111\n", - "boundarylayer = IdealDiluteSolution(boundarylayerspcs,boundarylayerrxns,solv,name=\"boundarylayeruid\",diffusionlimited=true);\n", - "surf = IdealSurface(surfspcs,surfrxns,sitedensity,name=\"surface\");" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "8894c84d", - "metadata": {}, - "outputs": [], - "source": [ - "initialcondsboundarylayer = Dict([\"proton\"=>10.0^-4,\n", - " \"CO2\"=>10.0^-3*10^6,\n", - " \"V\"=>1.0e-3,\"T\"=>300,\"Phi\"=>0.0,\"d\"=>0.0]);\n", - "initialcondsreservoir = Dict([\"proton\"=>10.0^-4,\n", - " \"CO2\"=>10.0^-3*10^6,\n", - " \"V\"=>1.0,\"T\"=>300]);\n", - "AVratio = 1e5;\n", - "initialcondssurf = Dict([\"CO2X\"=>0.4*sitedensity*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity*AVratio,\n", - " \"OX\"=>0.1*sitedensity*AVratio,\n", - " \"OCX\"=>0.1*sitedensity*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>300,\"Phi\"=>-1.0]);" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "ddb39b3d", - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "domainboundarylayer, y0boundarylayer, pboundarylayer = ConstantTVDomain(phase=boundarylayer, initialconds=initialcondsboundarylayer);\n", - "domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf,\n", - " initialconds=initialcondssurf);" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "ed49d2b4", - "metadata": {}, - "outputs": [], - "source": [ - "inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainboundarylayer,\n", - " domaincat,interfacerxns,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "dee14906", - "metadata": {}, - "outputs": [], - "source": [ - "# start with 1mm layer thickness\n", - "diffusionlayer = ConstantReservoirDiffusion(domainboundarylayer, initialcondsreservoir, AVratio*1.0, 1e-3);" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "e70ac4b0", - "metadata": {}, - "outputs": [], - "source": [ - "interfaces = [inter, diffusionlayer];" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "244f0912", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 17.594306 seconds (76.53 M allocations: 4.854 GiB, 7.88% gc time, 99.49% compilation time: <1% of which was recompilation)\n" - ] - } - ], - "source": [ - "@time react,y0,p = Reactor((domainboundarylayer,domaincat), (y0boundarylayer,y0cat), (0.0, 1.0e2), interfaces, (pboundarylayer,pcat,pinter));\n" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "962f838c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 14.018329 seconds (45.39 M allocations: 14.701 GiB, 8.17% gc time, 63.16% compilation time)\n" - ] - } - ], - "source": [ - "@time sol = solve(react.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-8);" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "56b6f906", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "retcode: Success\n", - "Interpolation: 3rd order Hermite\n", - "t: 7378-element Vector{Float64}:\n", - " 0.0\n", - " 5.637182922368118e-20\n", - " 1.1274365844736235e-19\n", - " 2.8910211211279163e-19\n", - " 4.654605657782209e-19\n", - " 6.418190194436502e-19\n", - " 9.195383720242527e-19\n", - " 1.3841882991386121e-18\n", - " 2.1843751517941395e-18\n", - " 3.563281809146959e-18\n", - " ⋮\n", - " 34.585534778618225\n", - " 37.972824443061896\n", - " 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SystemSimulation(sol,(domainboundarylayer,domaincat,), interfaces,p);" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "87dcaf99", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotX (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotX(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = molefractions(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Mole Fraction\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "ddf6da6b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotC (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotC(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = concentrations(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Concentration\")\n", - "end" - ] 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3.3559e-91 1.9748e-90 3.87397e-29 3.86904e-29\n", - " 0.0 -2.93082e-188 3.21592e-180 … -1.60967e-81 -1.50788e-81\n", - " 0.0 9.11712e-79 4.55875e-78 9.86869e-27 9.85295e-27\n", - " 0.0 4.97228e-96 3.90346e-95 2.11012e-43 2.10736e-43\n", - " 0.0 1.68005e-98 9.82947e-98 2.73081e-48 -3.29903e-48\n", - " 0.0 8.91927e-103 4.45963e-102 7.2535e-39 7.24499e-39\n", - " 0.0 5.27893e-50 3.0284e-49 … 6.33888e-19 6.33473e-19\n", - " 0.0 1.99529e-66 1.39664e-65 3.5683e-24 3.5682e-24" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "concentrations(ssys.sims[2])" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "e719a85d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys.sims[1], 1e-6, 1e2, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e2)\n", - "ylim(1e-9, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "1ef78267", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotC(ssys.sims[1], 1e-6, 1e2, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 10)\n", - "ylim(1e-6, 1e8)\n", - "title(\"Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "1ee8224d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotC(ssys.sims[2], 1e-6, 1e2, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 10)\n", - "ylim(1e-6, 1e-4)\n", - "title(\"Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "1f7d8918", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "1406×1462 Array{RGB{N0f8},2} with eltype ColorTypes.RGB{FixedPointNumbers.N0f8}:\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "getfluxdiagram(ssys,1e2;speciesratetolerance=1e-6)" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "36206466", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[\"Ar\", \"He\", \"Ne\", \"N2\", \"CO2\", \"proton\", \"H\", \"C=O\", \"O=CO\", \"H2O\", \"O=CC=O\", \"H2\", \"OO\", \"CO\", \"O2\", \"O=C=C=O\", \"C=C=O\", \"O=C=CO\", \"CH4\", \"COC=O\", \"COO\", \"CO-2\", \"COOC\", \"O=CCO\", \"OCO\", \"COCO\", \"OCCO\", \"OC=CO\", \"O=O\", \"C=CO\", \"C=C\", \"O=C=C=C=O\", \"C#COO[CH2]\", \"C#COC[O]\", \"CC=O\", \"O=C=CC=O\", \"C=C(O)O\", \"CC(=O)O\", \"[OH]\", \"CC(=O)C=O\", \"COC(C)=O\", \"CC(=O)CO\", \"O=CCC=O\", \"COC=C=O\", \"O=C=CCO\", \"[CH2]OOC=C\", \"C=COC[O]\", \"C=CC=O\", \"C=COC=O\", \"O=CC=CO\", \"COC\", \"CCO\", \"CC(O)O\", \"CCOC=O\", \"COCC=O\", \"CCOO\", \"CC(C)=O\", \"C=C=C=O\", \"CC=C=O\", \"CC\", \"O=C=C=CO\", \"[CH2]OCC=O\", \"[O]CCC=O\", \"[CH2]COC=O\", \"[CH3]\", \"O=CCCO\", \"CCC=O\", \"CC(O)=C=O\", \"[CH]=O\", \"C[O]\", \"CC(O)C=O\", \"[CH2]O\", \"C=C(O)C=O\", \"OC=CCO\", \"C=CCO\", \"[CH]=C\", \"C[CH2]\", \"C=C=CO\", \"C=C=C\", \"C=C=C(O)O\", \"C=CC(=O)O\", \"CC=CO\", \"C=CC\", \"CC=C(O)O\", \"CCC(=O)O\", \"C=COO\", \"C#C\", \"C=COC\", \"C=CC(O)O\", \"C=COCO\", \"C=CCOO\", \"C=COOC\", \"CC(O)=CO\", \"C=C(C)O\", \"C#CC=O\", \"OC=C=CO\", \"CCOC\", \"CCCO\", \"CCC(O)O\", \"CCOCO\", \"CCCOO\", \"CCC\", \"CCOOC\", \"C=C=COO\", \"CC=COO\", \"C=CCO[O]\", \"COCOC\", \"COCCO\", \"vacantX\", \"CO2X\", \"CHO2X\", \"CO2HX\", \"OCX\", \"OX\", \"CH2O2X\", \"CHOX\", \"CH2OX\", \"HOX\", \"HX\", \"CO[Pt]\", \"OC[Pt]\", \"OC(O)[Pt]\", \"OCO[Pt]\", \"H2OX\", \"OC=[Pt]\", \"O=CC(=O)[Pt]\", \"OC#[Pt]\", \"O=CC=O.[Pt]\", \"[H][H].[Pt]\", \"O=COC[Pt]\", \"OO[Pt]\", \"CX\", \"CHX\", \"CH2X\", \"O=COC#[Pt]\", \"O=CCO[Pt]\", \"O=O.[Pt]\", \"O=CC#[Pt]\", \"OC(O)=[Pt]\", \"O=C(O)C#[Pt]\", \"O=C=C=O.[Pt]\", \"OOC[Pt]\", \"C=C=O.[Pt]\", \"COC(=O)[Pt]\", \"CC(=O)[Pt]\", \"O=COCC#[Pt]\", \"O=C([Pt])CO\", \"O=CCC(=O)[Pt]\", \"OCC#[Pt]\", \"OC(O)C#[Pt]\", \"OCOC#[Pt]\", \"O=CCOC#[Pt]\", \"O=C=C[Pt]\", \"COC#[Pt]\", \"O=CC(=O)C#[Pt]\", \"O=COC=[Pt]\", \"O=C=CC#[Pt]\", \"CC#[Pt]\", \"O=C=CO[Pt]\", \"COC(=O)C#[Pt]\", \"O=C=CC(=O)[Pt]\", \"O=CCC#[Pt]\", \"CH3X\", \"O=C=CO.[Pt]\", \"O=C=C=[Pt]\", \"CC(=O)C#[Pt]\", \"O=C(C#[Pt])CO\", \"COC=O.[Pt]\", \"CC(=O)C(=O)[Pt]\", \"OOC#[Pt]\", \"O=CC[Pt]\", \"O=CC=[Pt]\", \"C.[Pt]\", \"O=C=CC=O.[Pt]\", \"CC(=O)O[Pt]\", \"CC(=O)OC#[Pt]\", \"O=C=C([Pt])C=O\", \"O=C=COC#[Pt]\", \"COO[Pt]\", \"CO.[Pt]\", \"O=C=C(O)[Pt]\", \"O=C=C(O)C#[Pt]\", \"COOC#[Pt]\", \"O=CC(O)[Pt]\", \"O=CC(O)C#[Pt]\", \"O=CC(O)=[Pt]\", \"OCO.[Pt]\", \"O=C=C=C=O.[Pt]\", \"O=CCO.[Pt]\", \"OCC=[Pt]\", \"O=C=CCO.[Pt]\", \"O=C=CC(O)[Pt]\", \"O=C=CC=[Pt]\", \"O=C=C([Pt])CO\", \"O=C=CC[Pt]\", \"O=C=CC(O)=[Pt]\", \"O=C=CCO[Pt]\", \"O=CC([Pt])C=O\", \"O=CC(=[Pt])C=O\", \"O=CCC=O.[Pt]\", \"O=CCC=[Pt]\", \"OOCC#[Pt]\", \"C=C=[Pt]\", \"O=C(O)C=[Pt]\", \"CC=O.[Pt]\", \"CC=[Pt]\", \"CC=C=O.[Pt]\", \"O=C(O)C[Pt]\", \"O=C(O)CC#[Pt]\", \"CC([Pt])=C=O\", \"CC(=C=O)O[Pt]\", \"C=C.[Pt]\", \"C=C[Pt]\", \"C=CC#[Pt]\", \"CC(=O)O.[Pt]\", \"C=CC(=O)[Pt]\", \"O=CC=CO[Pt]\", \"C=CO[Pt]\", \"C=COC(=O)[Pt]\", \"C=COC#[Pt]\", \"CC(O)=[Pt]\", \"O=CC=C[Pt]\", \"C=CC(=O)O[Pt]\", \"OC=C=[Pt]\", \"CC[Pt]\", \"CCC#[Pt]\", \"CCO[Pt]\", \"CCOC(=O)[Pt]\", \"CCC(=O)[Pt]\", \"CCOC#[Pt]\", \"CCC(=O)O[Pt]\", \"CC(O)=C=O.[Pt]\", \"OOC=[Pt]\", \"OO.[Pt]\", \"COCO[Pt]\", \"COCC(=O)[Pt]\", \"COCOC#[Pt]\", \"COCC#[Pt]\", \"COC[Pt]\", \"COC=[Pt]\", \"COC=C=O.[Pt]\", \"O=C=COC[Pt]\", \"COC([Pt])=C=O\", \"O=C=COC=[Pt]\", \"CCOO[Pt]\", \"O=C=C=CO.[Pt]\", \"O=C=C=C(O)[Pt]\", \"O=C=C=C[Pt]\", \"OC=CO.[Pt]\", \"OC=C(O)[Pt]\", \"OC=C[Pt]\", \"OC=CO[Pt]\", \"OC=COC#[Pt]\", \"O=C([Pt])C=CO\", \"OC=C(O)C#[Pt]\", \"OC=CC#[Pt]\", \"OCC[Pt]\", \"OCCC#[Pt]\", \"O=C([Pt])CCO\", \"OCCO[Pt]\", \"OCCOC#[Pt]\", \"O=C=C=C=[Pt]\", \"C=CO.[Pt]\", \"C=C(O)[Pt]\", \"C=C(O)O[Pt]\", \"C=C(O)OC#[Pt]\", \"C=C(O)C#[Pt]\", \"C=C(O)C(=O)[Pt]\", \"C=COO[Pt]\", \"O=CC=C=[Pt]\", \"C=C=C=O.[Pt]\", \"O=C=C=CO[Pt]\", \"CC(O)[Pt]\", \"CC(O)C#[Pt]\", \"CC(O)O[Pt]\", \"CC(O)C(=O)[Pt]\", \"CC(O)OC#[Pt]\", \"O=C=C(O)C[Pt]\", \"O=C=C(O)C=[Pt]\", \"CC([Pt])OC=O\", \"CC(=[Pt])OC=O\", \"O=CC=CO.[Pt]\", \"O=CC=C(O)[Pt]\", \"O=CC([Pt])=CO\", \"OC=CC=[Pt]\", \"OCC(O)[Pt]\", \"OCC(O)C#[Pt]\", \"OCC(O)=[Pt]\", \"COC(O)[Pt]\", \"COC(O)C#[Pt]\", \"COC(O)=[Pt]\", \"O=CCCO[Pt]\", \"O=CCC[Pt]\", \"C=COOC#[Pt]\", \"C=CC=O.[Pt]\", \"C=C([Pt])C=O\", \"C=C(C=O)O[Pt]\", \"C=CC=[Pt]\", \"CC(O)O.[Pt]\", \"OC(O)C[Pt]\"]\n" - ] - } - ], - "source": [ - "println(ssys.names)" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "64238bc0", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"CH2O2X\",1;N=15,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "e8bb3c43", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"CHO2X\",1;N=10,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "0bb84a7f", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"CO2HX\",1;N=10,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "1044d2b9", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"OX\",1;N=10,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "7086e403", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"OCX\",1.0e-6)" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "44de0eb2", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "vacantX+CO2<=>CO2X\n", - "kf = 20654.615923781494\n", - "krev = 11189.298481041604\n", - "Kc = 1.8459259048971917\n", - "proton+CO2X<=>CHO2X\n", - "kf = 5.164749496653815e7\n", - "krev = 3.369038128826839e8\n", - "Kc = 0.1533004168893831\n", - "proton+CO2X<=>CO2HX\n", - "kf = 463658.8965294065\n", - "krev = 1.20318988446587e-5\n", - "Kc = 3.853580407511801e10\n", - "proton+CHO2X<=>CH2O2X\n", - "kf = 2.5e10\n", - "krev = 9.108706843764319e-26\n", - "Kc = 2.7446266993557504e35\n", - "proton+CO2HX<=>CH2O2X\n", - "kf = 1.9190551016885178e10\n", - "krev = 1.757621070775451e-14\n", - "Kc = 1.0918480289052538e24\n", - "proton+OCX<=>CHOX\n", - "kf = 2.5e10\n", - "krev = 2.604453583293511e-10\n", - "Kc = 9.59894242706594e19\n", - "proton+CHOX<=>CH2OX\n", - "kf = 1.7890196451453958e9\n", - "krev = 4.957912234830633e-11\n", - "Kc = 3.608413300616868e19\n", - "vacantX+vacantX+CO2<=>OX+OCX\n", - "kf = 3.0109478093923404e-24\n", - "krev = 3.037156297092479e15\n", - "Kc = 9.913707148607306e-40\n", - "OX+proton<=>HOX\n", - "kf = 2.5e10\n", - "krev = 4.7547181516587526e-14\n", - "Kc = 5.25793521352646e23\n", - "vacantX+C=O<=>CH2OX\n", - "kf = 500114.13488002896\n", - "krev = 399.6803280141717\n", - "Kc = 1251.2853393732605\n", - "proton+CHO2X<=>OX+C=O\n", - "kf = 7.971946163368602e-7\n", - "krev = 8.220582009654122e-5\n", - "Kc = 0.009697544716428197\n", - "HX+CO2<=>CHO2X\n", - "kf = 6.542996392927688e-8\n", - "krev = 15.579156394796986\n", - "Kc = 4.199839983064083e-9\n", - "HX+CO2<=>CO2HX\n", - "kf = 6.542996392927688e-8\n", - "krev = 6.197590078701277e-11\n", - "Kc = 1055.7323588427441\n", - "vacantX+vacantX+C=O<=>HX+CHOX\n", - "kf = 2.0718885766149262e-11\n", - "krev = 0.008867505326838887\n", - "Kc = 2.336495440655708e-9\n", - "vacantX+O=CO<=>CH2O2X\n", - "kf = 403943.82249737746\n", - "krev = 29.756334575496034\n", - "Kc = 13575.053119278344\n", - "vacantX+vacantX+O=CO<=>HOX+CHOX\n", - "kf = 8.486192390111145e-15\n", - "krev = 9.7037034735699e11\n", - "Kc = 8.745312975839684e-27\n", - "vacantX+vacantX+O=CO<=>HX+CHO2X\n", - "kf = 1.2668346793097018e-21\n", - "krev = 380.13410282264914\n", - "Kc = 3.332599390328158e-24\n", - "vacantX+vacantX+O=CO<=>HX+CO2HX\n", - "kf = 9.840171155787102e-15\n", - "krev = 0.011746228705195169\n", - "Kc = 8.377302539184302e-13\n", - "proton+CH2OX<=>CO[Pt]\n", - "kf = 4.612846333154699e7\n", - "krev = 90.4105198560361\n", - "Kc = 510211.23874742666\n", - "HX+C=O<=>CO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.180104845075902e-9\n", - "Kc = 9.475050217848336\n", - "proton+CO2HX<=>H2O+OCX\n", - "kf = 2.5e10\n", - "krev = 4.0258346788129556e-7\n", - "Kc = 6.20989235637749e16\n", - "vacantX+vacantX+H2O<=>HX+HOX\n", - "kf = 1.7047654949014593e-31\n", - "krev = 21441.30602897437\n", - "Kc = 7.950847269274322e-36\n", - "proton+CH2OX<=>OC[Pt]\n", - "kf = 1.2443063594454413e6\n", - "krev = 1.1005987164187474e-6\n", - "Kc = 1.1305722429827158e12\n", - "HX+C=O<=>OC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.886422105564557e-15\n", - "Kc = 2.099567387708916e7\n", - "vacantX+vacantX+O=CC=O<=>CHOX+CHOX\n", - "kf = 3.132095071630788e8\n", - "krev = 159.05427897483804\n", - "Kc = 1.9691988746346629e6\n", - "proton+CH2O2X<=>OC(O)[Pt]\n", - "kf = 1.9695177200694968e-5\n", - "krev = 3718.799864740736\n", - "Kc = 5.296111088803661e-9\n", - "HX+O=CO<=>OC(O)[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 29981.045237801853\n", - "Kc = 1.0670229661561413e-12\n", - "proton+CH2O2X<=>OCO[Pt]\n", - "kf = 1.3800914441571782e-5\n", - "krev = 3681.751563599994\n", - "Kc = 3.748464339097702e-9\n", - "HOX+C=O<=>OCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.962949149852605e-13\n", - "Kc = 201771.41789913058\n", - "HX+O=CO<=>OCO[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 42359.465576793365\n", - "Kc = 7.552140562327293e-13\n", - "vacantX+H2O<=>H2OX\n", - "kf = 4.842414926683719e6\n", - "krev = 2.0721934488233277e8\n", - "Kc = 0.023368546645263413\n", - "proton+HOX<=>H2OX\n", - "kf = 2.5e10\n", - "krev = 1.2623996335027457e-31\n", - "Kc = 1.9803554545269617e41\n", - "vacantX+vacantX+H2<=>HX+HX\n", - "kf = 3.8736093818093735e10\n", - "krev = 4.9917087254698525e28\n", - "Kc = 7.760086965901168e-19\n", - "proton+CHOX<=>OC=[Pt]\n", - "kf = 3.6460821201937575e9\n", - "krev = 3.454391742229775e10\n", - "Kc = 0.10554917890812951\n", - "vacantX+vacantX+O=CO<=>OX+OC=[Pt]\n", - "kf = 1.3995006080437096e-36\n", - "krev = 7.971831424002446e14\n", - "Kc = 1.755557203367275e-51\n", - "proton+OC=[Pt]<=>OC[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.468152848309303e-23\n", - "Kc = 3.8650910988497585e32\n", - "proton+OC(O)[Pt]<=>H2O+OC=[Pt]\n", - "kf = 6.989877198043828e9\n", - "krev = 6.424310280494338e-11\n", - "Kc = 1.0880354299303816e20\n", - "proton+O=CC(=O)[Pt]<=>OCX+C=O\n", - "kf = 2.302032083373261e7\n", - "krev = 2.5713202543754838e-9\n", - "Kc = 8.952724109165363e15\n", - "vacantX+vacantX+O=CC=O<=>HX+O=CC(=O)[Pt]\n", - "kf = 1.43713660093583e-9\n", - "krev = 0.00032277677938391324\n", - "Kc = 4.452416322137251e-6\n", - "proton+OCX<=>OC#[Pt]\n", - "kf = 26781.620683797883\n", - "krev = 1.0085447542339806e12\n", - "Kc = 2.6554717151981333e-8\n", - "proton+OC#[Pt]<=>OC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.552445879282663e-17\n", - "Kc = 3.815369170624406e26\n", - "vacantX+O=CC=O<=>O=CC=O.[Pt]\n", - "kf = 359723.7676387533\n", - "krev = 0.32068189796600394\n", - "Kc = 1.121746409511672e6\n", - "proton+O=CC(=O)[Pt]<=>O=CC=O.[Pt]\n", - "kf = 1.508798479649927e9\n", - "krev = 8.88806985342612e-11\n", - "Kc = 1.6975547048252826e19\n", - "vacantX+vacantX+OO<=>HOX+HOX\n", - "kf = 4.0912386971316826e8\n", - "krev = 1.7763617117679594e-6\n", - "Kc = 2.3031563166601894e14\n", - "OCX<=>vacantX+CO\n", - "kf = 2.010168305725754e-19\n", - "krev = 2.61760793808642e-25\n", - "Kc = 767940.9419866255\n", - "vacantX+vacantX+O2<=>OX+OX\n", - "kf = 1.0945721587141857e10\n", - "krev = 4.219325007995329e-16\n", - "Kc = 2.594187830138819e25\n", - "proton+HX<=>[H][H].[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.1949534688419614e-15\n", - "Kc = 2.0921316730623565e25\n", - "vacantX+H2<=>[H][H].[Pt]\n", - "kf = 2338.960705505517\n", - "krev = 9707.159813448116\n", - "Kc = 0.24095211683495363\n", - "CHOX+C=O<=>O=COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 7.563806299311394e-5\n", - "Kc = 0.0005236345532350701\n", - "proton+OO[Pt]<=>OX+H2O\n", - "kf = 17.257164508221003\n", - "krev = 6.236444643145301e-63\n", - "Kc = 2.767147869610126e63\n", - "vacantX+vacantX+OO<=>HX+OO[Pt]\n", - "kf = 4.980245005159166e-22\n", - "krev = 5.509834949091977\n", - "Kc = 9.038827934364735e-23\n", - "proton+OC#[Pt]<=>H2O+CX\n", - "kf = 3.276640102032806e-5\n", - "krev = 0.0009291230748795855\n", - "Kc = 0.03526594259277716\n", - "vacantX+vacantX+O=C=C=O<=>OCX+OCX\n", - "kf = 74.64023007210145\n", - "krev = 2.953439666185894e-39\n", - "Kc = 2.52723056870475e40\n", - "HX+O=C=C=O<=>O=CC(=O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 5.0006650398424424e-61\n", - "Kc = 1.1597065597154312e53\n", - "proton+OC=[Pt]<=>H2O+CHX\n", - "kf = 2.5e10\n", - "krev = 6.511063937864271e-5\n", - "Kc = 3.839618261865876e14\n", - "proton+CX<=>CHX\n", - "kf = 2.5e10\n", - "krev = 6.018259224258551e-33\n", - "Kc = 4.1540251206244773e42\n", - "H2+CX<=>CH2X\n", - "kf = 4.832014059685671\n", - "krev = 1.8278921581756875e-33\n", - "Kc = 2.643489681857502e33\n", - "vacantX+vacantX+C=O<=>OX+CH2X\n", - "kf = 4.5608316796485725e-28\n", - "krev = 3.884151005592286e17\n", - "Kc = 1.1742158513101117e-45\n", - "proton+OC[Pt]<=>H2O+CH2X\n", - "kf = 7206.229958253159\n", - "krev = 0.0019484451144913943\n", - "Kc = 3.6984516036184127e6\n", - "proton+O=COC[Pt]<=>CH2X+O=CO\n", - "kf = 1981.2472905766488\n", - "krev = 1.4695324127813272e-5\n", - "Kc = 1.3482161219069803e8\n", - "proton+CHX<=>CH2X\n", - "kf = 2.5e10\n", - "krev = 6.715036577093663e-15\n", - "Kc = 3.722987911231938e24\n", - "proton+O=COC#[Pt]<=>CX+O=CO\n", - "kf = 6.185088018779624e7\n", - "krev = 3.741277098492221e-23\n", - "Kc = 1.6532023306352497e30\n", - "vacantX+vacantX+C=C=O<=>OCX+CH2X\n", - "kf = 2.4823885573387985e-14\n", - "krev = 9.351132511056354e15\n", - "Kc = 2.6546394828687704e-30\n", - "CHOX+C=O<=>O=CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.4949222028864902e7\n", - "Kc = 2.6494156850764662e-15\n", - "HX+O=CC=O<=>O=CCO[Pt]\n", - "kf = 5.6976884072695144e-8\n", - "krev = 2.551666729065355e-8\n", - "Kc = 2.23292812590636\n", - "proton+O=CC=O.[Pt]<=>O=CCO[Pt]\n", - "kf = 957581.7759153218\n", - "krev = 7139.55197608848\n", - "Kc = 134.12351070801344\n", - "O=O.[Pt]+proton<=>OO[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.545950245153839e-28\n", - "Kc = 7.050296330064662e37\n", - "proton+O=CC#[Pt]<=>CX+C=O\n", - "kf = 5.731900626219973e-17\n", - "krev = 16.634660991475336\n", - "Kc = 3.4457574032662074e-18\n", - "proton+CO2HX<=>OC(O)=[Pt]\n", - "kf = 8.313674902647437e-22\n", - "krev = 1.0085447542339753e12\n", - "Kc = 8.243238455949296e-34\n", - "proton+OC(O)=[Pt]<=>OC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.563843227039955e-39\n", - "Kc = 7.014898918762039e48\n", - "proton+OC(O)=[Pt]<=>H2O+OC#[Pt]\n", - "kf = 58948.65819613129\n", - "krev = 2.9467686111082447e-38\n", - "Kc = 2.0004508658710534e42\n", - "proton+O=C(O)C#[Pt]<=>CX+O=CO\n", - "kf = 1.2163309452954808e-9\n", - "krev = 0.00037997676558546045\n", - "Kc = 3.201066632117316e-6\n", - "proton+O=C=C=O.[Pt]<=>O=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.649884885591097e-48\n", - "Kc = 9.434372087609898e57\n", - "vacantX+O=C=C=O<=>O=C=C=O.[Pt]\n", - "kf = 366139.2749661925\n", - "krev = 442.06521987276346\n", - "Kc = 828.2471873077366\n", - "HOX+C=O<=>OOC[Pt]\n", - "kf = 1.5395975576095126e-29\n", - "krev = 2.622153295712258e16\n", - "Kc = 5.871500953537159e-46\n", - "proton+OOC[Pt]<=>OO+CH2X\n", - "kf = 15.535579749933543\n", - "krev = 3.4028033042152773e-9\n", - "Kc = 4.5655238816444645e9\n", - "vacantX+vacantX+O=C=CO<=>OCX+OC=[Pt]\n", - "kf = 73.33238091278024\n", - "krev = 14511.198914062346\n", - "Kc = 0.005053502563576338\n", - "vacantX+C=C=O<=>C=C=O.[Pt]\n", - "kf = 422670.5724931744\n", - "krev = 9.80980243728561e-11\n", - "Kc = 4.3086552985681545e15\n", - "proton+CO[Pt]<=>OX+CH4\n", - "kf = 541698.6744405399\n", - "krev = 1.9995135619129721e-19\n", - "Kc = 2.7091522896313173e24\n", - "HX+C=C=O<=>CC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.3310785577331067e-33\n", - "Kc = 2.514767798332947e25\n", - "proton+C=C=O.[Pt]<=>CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.357099551204697e-8\n", - "Kc = 3.9326110592781875e17\n", - "proton+CC(=O)[Pt]<=>OCX+CH4\n", - "kf = 1.0030005882936613e8\n", - "krev = 4.3463683404291294e-8\n", - "Kc = 2.3076750743003805e15\n", - "vacantX+vacantX+COC=O<=>CHOX+CO[Pt]\n", - "kf = 5.858305523872122e-8\n", - "krev = 9.372228401924443e12\n", - "Kc = 6.250707166578664e-21\n", - "vacantX+vacantX+COC=O<=>HX+O=COC[Pt]\n", - "kf = 8.724708246600757e-23\n", - "krev = 252.56605644619947\n", - "Kc = 3.454426287270814e-25\n", - "vacantX+vacantX+COC=O<=>HX+COC(=O)[Pt]\n", - "kf = 7.165711269221808e-16\n", - "krev = 0.1859922027934253\n", - "Kc = 3.852694447186316e-15\n", - "proton+O=COCC#[Pt]<=>CX+COC=O\n", - "kf = 0.8132675549526747\n", - "krev = 2.165706403032533e-5\n", - "Kc = 37552.06863746147\n", - "HOX+C=C=O<=>O=C([Pt])CO\n", - "kf = 3.3473534940386794e-8\n", - "krev = 9.042590347389556e-30\n", - "Kc = 3.70176394754519e21\n", - "HX+O=C=CO<=>O=C([Pt])CO\n", - "kf = 2.8488442036348548e-8\n", - "krev = 1.614840618256874e-45\n", - "Kc = 1.7641643214981894e37\n", - "vacantX+vacantX+COO<=>HOX+CO[Pt]\n", - "kf = 3.442529358831723e8\n", - "krev = 2.6586367586035048e-11\n", - "Kc = 1.294847574679578e19\n", - "vacantX+vacantX+COO<=>HX+OOC[Pt]\n", - "kf = 1.3336211820914592e-23\n", - "krev = 16620.58178963317\n", - "Kc = 8.023913957833202e-28\n", - "CHOX+C=C=O<=>O=CCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 2.6714659015861004e-16\n", - "Kc = 1.2530025152300434e8\n", - "vacantX+vacantX+CO-2<=>HX+CO[Pt]\n", - "kf = 3.6896065237788346e-26\n", - "krev = 1200.2597905170037\n", - "Kc = 3.0740066050113714e-29\n", - "vacantX+vacantX+CO-2<=>HX+OC[Pt]\n", - "kf = 1.1691860289045307e-22\n", - "krev = 1.716447494000275\n", - "Kc = 6.811662069427353e-23\n", - "proton+OCO[Pt]<=>OX+CO-2\n", - "kf = 6.4866612293733e7\n", - "krev = 4.917786339628338e-9\n", - "Kc = 1.319020547335029e16\n", - "proton+COC(=O)[Pt]<=>OCX+CO-2\n", - "kf = 5.096893185474306e9\n", - "krev = 2.041829224680708e-9\n", - "Kc = 2.49623872744369e18\n", - "proton+O=C([Pt])CO<=>OCX+CO-2\n", - "kf = 1.9762803815844387e7\n", - "krev = 1.2158736968776066e-8\n", - "Kc = 1.6253994034574272e15\n", - "proton+OCC#[Pt]<=>CX+CO-2\n", - "kf = 1.8515947729382765e-10\n", - "krev = 0.16959607683462066\n", - "Kc = 1.091767455649245e-9\n", - "vacantX+vacantX+COOC<=>CO[Pt]+CO[Pt]\n", - "kf = 3.028654941635431e8\n", - "krev = 1.0392777770118965e-11\n", - "Kc = 2.914191959673513e19\n", - "vacantX+vacantX+C=C=O<=>HX+O=C=C[Pt]\n", - "kf = 3.6584912239485734e-16\n", - "krev = 0.32395775785233605\n", - "Kc = 1.1293111942132156e-15\n", - "vacantX+vacantX+O=C=CO<=>HOX+O=C=C[Pt]\n", - "kf = 3.132095071630788e8\n", - "krev = 5.819571251914923e7\n", - "Kc = 5.382003133994065\n", - "proton+O=C=C[Pt]<=>C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.724942318590629e-29\n", - "Kc = 2.570709334924167e38\n", - "vacantX+vacantX+O=CCO<=>CHOX+OC[Pt]\n", - "kf = 9001.813049524091\n", - "krev = 8.180569891408677e12\n", - "Kc = 1.1003894800749632e-9\n", - "vacantX+vacantX+O=CCO<=>HX+O=CCO[Pt]\n", - "kf = 3.705974451661604e-28\n", - "krev = 2668.9209237076484\n", - "Kc = 1.3885665996103351e-31\n", - "vacantX+vacantX+O=CCO<=>HX+O=C([Pt])CO\n", - "kf = 1.2718474027465153e-10\n", - "krev = 0.0002705673832361486\n", - "Kc = 4.7006678614933393e-7\n", - "proton+O=CCOC#[Pt]<=>CX+O=CCO\n", - "kf = 3.8625888100004036e-23\n", - "krev = 1.5059302822169408e-12\n", - "Kc = 2.564918745318097e-11\n", - "proton+COC#[Pt]<=>CX+CO-2\n", - "kf = 3.5797175052253717e-22\n", - "krev = 9.770006712968626e-20\n", - "Kc = 0.0036639867406372244\n", - "proton+O=CC(=O)C#[Pt]<=>CX+O=CC=O\n", - "kf = 5.9931479699583235e-12\n", - "krev = 0.0016900056192162703\n", - "Kc = 3.546229611199523e-9\n", - "vacantX+vacantX+OCO<=>HOX+OC[Pt]\n", - "kf = 1.653107374238179e-12\n", - "krev = 3.492310477620836e11\n", - "Kc = 4.7335635958815765e-24\n", - "vacantX+vacantX+OCO<=>HX+OC(O)[Pt]\n", - "kf = 4.0412190145177725e-23\n", - "krev = 628.7683045605482\n", - "Kc = 6.427198993979533e-26\n", - "vacantX+vacantX+OCO<=>HX+OCO[Pt]\n", - "kf = 1.1281154422531313e-23\n", - "krev = 247.99076039714222\n", - "Kc = 4.5490220702034325e-26\n", - "proton+OC(O)C#[Pt]<=>CX+OCO\n", - "kf = 0.005562206988621036\n", - "krev = 0.025459246171787766\n", - "Kc = 0.21847492856189518\n", - "proton+OCOC#[Pt]<=>CX+OCO\n", - "kf = 2.2993090387825977e-18\n", - "krev = 1.7767009384663083e-12\n", - "Kc = 1.2941452266960681e-6\n", - "proton+O=COC=[Pt]<=>O=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.03525663068036e-45\n", - "Kc = 2.4148601669491608e55\n", - "proton+O=COC=[Pt]<=>CHX+O=CO\n", - "kf = 407721.49317133107\n", - "krev = 4.66233771243883e-34\n", - "Kc = 8.745001291595743e38\n", - "proton+O=COC#[Pt]<=>O=COC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.1834993039887084e-24\n", - "Kc = 7.852993706854812e33\n", - "proton+O=C=CC#[Pt]<=>CX+C=C=O\n", - "kf = 1.255896512556004e-15\n", - "krev = 0.016900821436021087\n", - "Kc = 7.430979123176135e-14\n", - "vacantX+vacantX+COCO<=>CO[Pt]+OC[Pt]\n", - "kf = 3.0636862331912886e-9\n", - "krev = 3.008499680951675e11\n", - "Kc = 1.0183435459837431e-20\n", - "proton+CC#[Pt]<=>CX+CH4\n", - "kf = 3.172314510568854e-8\n", - "krev = 0.363285670785801\n", - "Kc = 8.732286367659409e-8\n", - "HX+O=C=C=O<=>O=C=CO[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.1302052975227224e-55\n", - "Kc = 2.7224155607861307e47\n", - "proton+O=C=CO[Pt]<=>OX+C=C=O\n", - "kf = 0.047578794564636824\n", - "krev = 2.8204743128358057e-8\n", - "Kc = 1.6869075654441754e6\n", - "proton+O=C=C=O.[Pt]<=>O=C=CO[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 2.257619247094878e-42\n", - "Kc = 2.2147224366704162e52\n", - "vacantX+vacantX+O=C=CO<=>HX+O=C=CO[Pt]\n", - "kf = 0.0007071288662616175\n", - "krev = 2.8988454126647536e-5\n", - "Kc = 24.393465866522067\n", - "vacantX+vacantX+OCCO<=>OC[Pt]+OC[Pt]\n", - "kf = 2.961131444342359e-9\n", - "krev = 1.299206322752899e13\n", - "Kc = 2.2791849088819035e-22\n", - "proton+COC(=O)C#[Pt]<=>CX+COC=O\n", - "kf = 2.520547604265173e-10\n", - "krev = 3.828537658551766e-5\n", - "Kc = 6.583577932517004e-6\n", - "proton+O=C=CC(=O)[Pt]<=>OCX+C=C=O\n", - "kf = 2.14881300259784e7\n", - "krev = 1.9623010758881652e-11\n", - "Kc = 1.0950475587061772e18\n", - "vacantX+vacantX+OC=CO<=>OC=[Pt]+OC=[Pt]\n", - "kf = 1.351949923589269e-23\n", - "krev = 7.975137957191956e11\n", - "Kc = 1.6952056890377485e-35\n", - "vacantX+OX+CH4<=>HOX+CH3X\n", - "kf = 1181.9069662995785\n", - "krev = 1.0235810933777192e20\n", - "Kc = 1.1546783874244874e-17\n", - "vacantX+HOX+CH4<=>H2OX+CH3X\n", - "kf = 5.28370763875636e9\n", - "krev = 1.2149259925984929e9\n", - "Kc = 4.348995470461149\n", - "HX+CH3X<=>vacantX+vacantX+CH4\n", - "kf = 5.733311120080377e8\n", - "krev = 8.483521653048543e-25\n", - "Kc = 6.758173497465076e32\n", - "proton+CH2X<=>CH3X\n", - "kf = 2.5e10\n", - "krev = 7.728626954425352e-28\n", - "Kc = 3.2347272222377345e37\n", - "CO2+CH3X<=>COC(=O)[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.00447183609125585\n", - "Kc = 1.463156578060128e-5\n", - "vacantX+vacantX+COC=O<=>CHO2X+CH3X\n", - "kf = 0.05589950368763065\n", - "krev = 5.054770535995559e16\n", - "Kc = 1.1058761874463802e-18\n", - "vacantX+vacantX+COO<=>OO[Pt]+CH3X\n", - "kf = 9.385776922831516e-7\n", - "krev = 3.9782610412247473e11\n", - "Kc = 2.359266228528335e-18\n", - "vacantX+vacantX+CO-2<=>HOX+CH3X\n", - "kf = 9.872876935778847e-16\n", - "krev = 6.917821124819518e13\n", - "Kc = 1.427165686657795e-29\n", - "vacantX+vacantX+COCO<=>CH3X+OCO[Pt]\n", - "kf = 3.9072411322938125e-9\n", - "krev = 8.599564777209447e13\n", - "Kc = 4.543533578174534e-23\n", - "O=O+HX<=>OO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 8.854082166234876e-41\n", - "Kc = 8.666474551788235e32\n", - "vacantX+O=O<=>O=O.[Pt]\n", - "kf = 484458.3574999593\n", - "krev = 584.920039726471\n", - "Kc = 828.247152767255\n", - "vacantX+O=C=CO<=>O=C=CO.[Pt]\n", - "kf = 359723.7676387533\n", - "krev = 0.4900054095759742\n", - "Kc = 734122.0333670193\n", - "proton+O=C=CO.[Pt]<=>O=C([Pt])CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.543989619636675e-29\n", - "Kc = 1.6191818702694958e39\n", - "proton+O=C=CO[Pt]<=>O=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.012328788524416852\n", - "Kc = 2.0277742578265605e12\n", - "vacantX+vacantX+O=C=C=O<=>OX+O=C=C=[Pt]\n", - "kf = 149.2804601441562\n", - "krev = 1.2008902564793325e-12\n", - "Kc = 1.2430816166483347e14\n", - "proton+O=C=C=[Pt]<=>O=CC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 728325.7738813914\n", - "Kc = 34325.299057824195\n", - "proton+O=C=C=[Pt]<=>O=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.992117420427329e-15\n", - "Kc = 4.1721478812771864e24\n", - "vacantX+vacantX+C=CO<=>CH2X+OC=[Pt]\n", - "kf = 3.7510196251812924e-36\n", - "krev = 6.624293894020312e13\n", - "Kc = 5.662519938264367e-50\n", - "proton+O=C(C#[Pt])CO<=>CX+O=CCO\n", - "kf = 2.1150580786972557e-17\n", - "krev = 1.2236788896896236\n", - "Kc = 1.728442074565594e-17\n", - "vacantX+vacantX+C=C<=>CH2X+CH2X\n", - "kf = 9.387035392806688e-46\n", - "krev = 5.259242712748897e15\n", - "Kc = 1.784864457776713e-61\n", - "proton+O=COC[Pt]<=>COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.124037165592671e-28\n", - "Kc = 8.002465615756261e37\n", - "proton+COC(=O)[Pt]<=>COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.484214060387906e-18\n", - "Kc = 7.175219308200797e27\n", - "vacantX+COC=O<=>COC=O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.8619443782965007\n", - "Kc = 410274.8449265323\n", - "HX+O=C=C=C=O<=>O=C=CC(=O)[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 3.561089909521239e-25\n", - "Kc = 1.4777843564830474e17\n", - "vacantX+vacantX+O=C=C=C=O<=>OCX+O=C=C=[Pt]\n", - "kf = 135.4631249389026\n", - "krev = 3.092595390223456e6\n", - "Kc = 4.3802407960361956e-5\n", - "CH3X+O=C=C=O<=>CC(=O)C(=O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 3.5093718907449027e-71\n", - "Kc = 1.6525190917893694e63\n", - "proton+OOC#[Pt]<=>OO+CX\n", - "kf = 3.959382254258936e-52\n", - "krev = 4.505410128222608e6\n", - "Kc = 8.78806177812034e-59\n", - "proton+O=CC[Pt]<=>CH2X+C=O\n", - "kf = 9.847553463617368e-13\n", - "krev = 0.8193686811731042\n", - "Kc = 1.2018464568987987e-12\n", - "HX+C=C=O<=>O=CC[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 3.6888123831707493e-19\n", - "Kc = 9.074339235332521e10\n", - "proton+C=C=O.[Pt]<=>O=CC[Pt]\n", - "kf = 4.477750650627013e6\n", - "krev = 3155.453532604055\n", - "Kc = 1419.0513675324908\n", - "vacantX+vacantX+O=CCO<=>HOX+O=CC[Pt]\n", - "kf = 3.3834985622063113e-5\n", - "krev = 2.9362980773683545e12\n", - "Kc = 1.1523007790948657e-17\n", - "vacantX+vacantX+O=CC=O<=>OX+O=CC=[Pt]\n", - "kf = 6.170227811474367e-18\n", - "krev = 2.1467268001769245e15\n", - "Kc = 2.874249210922341e-33\n", - "proton+O=CC=[Pt]<=>CHX+C=O\n", - "kf = 0.3518802014338951\n", - "krev = 0.0019581841163396926\n", - "Kc = 179.69719930710195\n", - "proton+O=CC#[Pt]<=>O=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.1385387905668107e-13\n", - "Kc = 7.9654902068249e22\n", - "proton+O=C=C[Pt]<=>O=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.814809579170971e7\n", - "Kc = 655.3407052478085\n", - "proton+O=CC=[Pt]<=>O=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.4911345025101916e-29\n", - "Kc = 5.566522219725765e38\n", - "proton+O=CCO[Pt]<=>OX+CC=O\n", - "kf = 108844.3774855493\n", - "krev = 6.551243603618761e-23\n", - "Kc = 1.6614307766761425e27\n", - "vacantX+vacantX+CC=O<=>HX+CC(=O)[Pt]\n", - "kf = 4.3209399543319175e-11\n", - "krev = 0.0003615296985530135\n", - "Kc = 1.195182573278502e-7\n", - "proton+O=CCC(=O)[Pt]<=>OCX+CC=O\n", - "kf = 7.362850070977087e6\n", - "krev = 9.270601965584902e-14\n", - "Kc = 7.94214884676321e19\n", - "proton+O=CCC#[Pt]<=>CX+CC=O\n", - "kf = 0.11748380587607415\n", - "krev = 6.387097627333538e-5\n", - "Kc = 1839.3926745898334\n", - "vacantX+vacantX+CC=O<=>CHOX+CH3X\n", - "kf = 6.063283190982672e-6\n", - "krev = 7.026751658283665e14\n", - "Kc = 8.628856526948432e-21\n", - "proton+CC(=O)C#[Pt]<=>CX+CC=O\n", - "kf = 8.247683071468342e-18\n", - "krev = 0.06355423283679383\n", - "Kc = 1.2977393799478706e-16\n", - "proton+CC(=O)C(=O)[Pt]<=>OCX+CC=O\n", - "kf = 3.422758172577326e7\n", - "krev = 2.0119060511296993e-10\n", - "Kc = 1.7012514926606157e17\n", - "vacantX+vacantX+CC=O<=>HX+O=CC[Pt]\n", - "kf = 3.2094062904328744e-20\n", - "krev = 74.41720028073364\n", - "Kc = 4.312721089110603e-22\n", - "vacantX+CH4<=>C.[Pt]\n", - "kf = 11983.404197457203\n", - "krev = 27576.843954134933\n", - "Kc = 0.4345458899280744\n", - "proton+CH3X<=>C.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.2634270430964172e-30\n", - "Kc = 1.9787450440137642e40\n", - "HX+O=C=CC=O<=>O=CCC(=O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 3.8194581898791103e-32\n", - "Kc = 6.789235995427004e23\n", - "vacantX+vacantX+O=C=CC=O<=>CHOX+O=C=C[Pt]\n", - "kf = 2.850945414803626e8\n", - "krev = 4.6591458607721776e7\n", - "Kc = 6.119030182779314\n", - "vacantX+vacantX+O=C=CC=O<=>HX+O=C=CC(=O)[Pt]\n", - "kf = 1.1776167531898308e-10\n", - "krev = 0.0005032011998508361\n", - "Kc = 2.3402502886298994e-7\n", - "vacantX+vacantX+O=C=CC=O<=>OCX+O=CC=[Pt]\n", - "kf = 0.006845452357086415\n", - "krev = 1.638610749190394e14\n", - "Kc = 4.177595173514284e-17\n", - "vacantX+vacantX+C=C(O)O<=>CH2X+OC(O)=[Pt]\n", - "kf = 1.3631835715271243e-51\n", - "krev = 1.0974745099569602e16\n", - "Kc = 1.242109551665655e-67\n", - "proton+O=C=CC=O.[Pt]<=>O=CCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.130402878837127e-16\n", - "Kc = 4.078035407151288e25\n", - "proton+O=C=CC(=O)[Pt]<=>O=C=CC=O.[Pt]\n", - "kf = 2.964275004938465e9\n", - "krev = 9.178277268525813e-12\n", - "Kc = 3.229663822756335e20\n", - "vacantX+O=C=CC=O<=>O=C=CC=O.[Pt]\n", - "kf = 327433.4917974331\n", - "krev = 0.29189612518083846\n", - "Kc = 1.1217466199476891e6\n", - "vacantX+vacantX+CC(=O)O<=>HOX+CC(=O)[Pt]\n", - "kf = 3.661873055903852e-12\n", - "krev = 2.1682718089028445e11\n", - "Kc = 1.6888441019563762e-23\n", - "vacantX+vacantX+CC(=O)O<=>CO2HX+CH3X\n", - "kf = 1.1977509649486271e-8\n", - "krev = 1.0254845667743408e14\n", - "Kc = 1.1679853639496008e-22\n", - "CO2+CH3X<=>CC(=O)O[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 3.3286101924403974e-7\n", - "Kc = 0.19656841788766613\n", - "proton+CC(=O)O[Pt]<=>OX+CC=O\n", - "kf = 6.638543952734307e-6\n", - "krev = 1.1832604608796647e-7\n", - "Kc = 56.10382643732599\n", - "vacantX+vacantX+CC(=O)O<=>HX+CC(=O)O[Pt]\n", - "kf = 2.4753542791841756e-22\n", - "krev = 11382.562807978633\n", - "Kc = 2.1746897609465158e-26\n", - "proton+CC(=O)OC#[Pt]<=>CX+CC(=O)O\n", - "kf = 3.5372794201475537e8\n", - "krev = 2.288049006228874e-19\n", - "Kc = 1.5459806195224992e27\n", - "vacantX+vacantX+CC(=O)C=O<=>CHOX+CC(=O)[Pt]\n", - "kf = 2.810784197367395e8\n", - "krev = 8.682228189641076\n", - "Kc = 3.237399589106622e7\n", - "vacantX+vacantX+CC(=O)C=O<=>CH3X+O=CC(=O)[Pt]\n", - "kf = 0.010756441693245073\n", - "krev = 2.0353876594794328e15\n", - "Kc = 5.284714016589902e-18\n", - "vacantX+vacantX+CC(=O)C=O<=>HX+CC(=O)C(=O)[Pt]\n", - "kf = 2.426386880233808e-11\n", - "krev = 0.0003222108693910823\n", - "Kc = 7.530431499158364e-8\n", - "proton+O=C=C([Pt])C=O<=>C=O+O=C=C=[Pt]\n", - "kf = 13308.622034460761\n", - "krev = 4.6234228919871786e-9\n", - "Kc = 2.8785214645897607e12\n", - "HX+O=C=C=C=O<=>O=C=C([Pt])C=O\n", - "kf = 5.262522960320117e-8\n", - "krev = 8.417963556232881e-20\n", - "Kc = 6.251539253129229e11\n", - "vacantX+vacantX+O=C=CC=O<=>HX+O=C=C([Pt])C=O\n", - "kf = 3.109950102720783e-13\n", - "krev = 0.31413419650430946\n", - "Kc = 9.900068624582613e-13\n", - "proton+O=C=C([Pt])C=O<=>O=C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.274602487927107e-16\n", - "Kc = 7.6345144463093386e25\n", - "proton+O=C=COC#[Pt]<=>CX+O=C=CO\n", - "kf = 3.333143073629419e-24\n", - "krev = 2.9895559923107984e-13\n", - "Kc = 1.1149291340260339e-11\n", - "vacantX+vacantX+COC(C)=O<=>CO[Pt]+CC(=O)[Pt]\n", - "kf = 6.614441053978493e-6\n", - "krev = 7.629970776987544e11\n", - "Kc = 8.669025409544227e-18\n", - "vacantX+vacantX+COC(C)=O<=>CH3X+COC(=O)[Pt]\n", - "kf = 1.5563360867242215e-10\n", - "krev = 4.0343976517667425e14\n", - "Kc = 3.857666549162974e-25\n", - "vacantX+vacantX+COC(C)=O<=>CH3X+CC(=O)O[Pt]\n", - "kf = 0.0003463783354588583\n", - "krev = 6.683486846094463e16\n", - "Kc = 5.182599194629471e-21\n", - "vacantX+vacantX+COO<=>HX+COO[Pt]\n", - "kf = 1.175900379595729e-21\n", - "krev = 0.27982743013843664\n", - "Kc = 4.2022341377111815e-21\n", - "proton+COO[Pt]<=>OX+CO-2\n", - "kf = 129.78074174016686\n", - "krev = 1.499485133709293e-58\n", - "Kc = 8.65502023478731e59\n", - "vacantX+vacantX+COOC<=>CH3X+COO[Pt]\n", - "kf = 1.8186835430204133e-8\n", - "krev = 4.141977957602716e12\n", - "Kc = 4.39085760869917e-21\n", - "O=O+CH3X<=>COO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 4.970959816815508e-38\n", - "Kc = 1.543639067721808e30\n", - "proton+CO[Pt]<=>CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.487564815762018e-25\n", - "Kc = 1.0049989387851077e35\n", - "proton+OC[Pt]<=>CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.512171272873819e-19\n", - "Kc = 4.535417853038886e28\n", - "vacantX+CO-2<=>CO.[Pt]\n", - "kf = 484125.61468448705\n", - "krev = 1.0558750276780043e7\n", - "Kc = 0.04585065485913965\n", - "vacantX+vacantX+CC(=O)CO<=>OC[Pt]+CC(=O)[Pt]\n", - "kf = 4.324183911493771e7\n", - "krev = 7.8667392573421875e12\n", - "Kc = 5.496793232924203e-6\n", - "vacantX+vacantX+CC(=O)CO<=>CH3X+O=C([Pt])CO\n", - "kf = 0.43146252134138535\n", - "krev = 2.5450806210309695e15\n", - "Kc = 1.695280368629765e-16\n", - "HX+O=C=C=O<=>O=C=C(O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 7.390785994602033e-44\n", - "Kc = 7.846667531546056e35\n", - "proton+O=C=C=O.[Pt]<=>O=C=C(O)[Pt]\n", - "kf = 5.0e10\n", - "krev = 7.832851008293297e-31\n", - "Kc = 6.383371769367348e40\n", - "vacantX+vacantX+O=C=CO<=>HX+O=C=C(O)[Pt]\n", - "kf = 2.8707175642480555e-12\n", - "krev = 0.04083063397693327\n", - "Kc = 7.030793511239207e-11\n", - "proton+O=C=C(O)[Pt]<=>O=C=CO.[Pt]\n", - "kf = 1.7351014576291664e10\n", - "krev = 2.4662443446341767e-14\n", - "Kc = 7.03539964077054e23\n", - "proton+O=C=C(O)[Pt]<=>H2O+O=C=C=[Pt]\n", - "kf = 1.2324712433709262e6\n", - "krev = 1.176415080398485e-31\n", - "Kc = 1.0476499867321094e37\n", - "vacantX+vacantX+O=CCC=O<=>HX+O=CCC(=O)[Pt]\n", - "kf = 3.286584099620913e-11\n", - "krev = 0.0009472638388816695\n", - "Kc = 3.469555117295539e-8\n", - "vacantX+vacantX+O=CCC=O<=>CHOX+O=CC[Pt]\n", - "kf = 5.621568394735124e8\n", - "krev = 2.2372815421494465e13\n", - "Kc = 2.51267812692642e-5\n", - "proton+O=C=C(O)C#[Pt]<=>CX+O=C=CO\n", - "kf = 3.0900625689798e-31\n", - "krev = 97363.75326657317\n", - "Kc = 3.1737299203323514e-36\n", - "proton+COOC#[Pt]<=>CX+COO\n", - "kf = 1.3396315820930446e-65\n", - "krev = 2.5e10\n", - "Kc = 5.3585263283721787e-76\n", - "vacantX+vacantX+COC=C=O<=>CO[Pt]+O=C=C[Pt]\n", - "kf = 1.4053920986837533e8\n", - "krev = 2.5815645207863396e8\n", - "Kc = 0.5443954963619013\n", - "vacantX+vacantX+COC=C=O<=>CH3X+O=C=CO[Pt]\n", - "kf = 1.4053920986837533e8\n", - "krev = 1.2268284001067661e8\n", - "Kc = 1.1455490421981163\n", - "HX+O=CC=O<=>O=CC(O)[Pt]\n", - "kf = 5.6976884072695144e-8\n", - "krev = 1.248882373151946e-25\n", - "Kc = 4.562229822244678e17\n", - "proton+O=CC(O)[Pt]<=>C=O+OC=[Pt]\n", - "kf = 1.4979350850413518e-9\n", - "krev = 7.682289195925664e-6\n", - "Kc = 0.00019498551106820976\n", - "proton+O=CC=O.[Pt]<=>O=CC(O)[Pt]\n", - "kf = 3.43386635836783e8\n", - "krev = 1.2530721027853126e-11\n", - "Kc = 2.7403581571523903e19\n", - "HX+O=C=CO<=>O=CC(O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 2.6755933088589045e-38\n", - "Kc = 1.0647523277182356e30\n", - "vacantX+vacantX+O=CCO<=>HX+O=CC(O)[Pt]\n", - "kf = 5.743984385098034e-15\n", - "krev = 0.20246227896672986\n", - "Kc = 2.8370639777506056e-14\n", - "proton+O=C=CO.[Pt]<=>O=CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.5582018736355307e-22\n", - "Kc = 9.77248912904274e31\n", - "proton+O=CC(O)[Pt]<=>H2O+O=CC=[Pt]\n", - "kf = 459.6019775429135\n", - "krev = 1.1031455244918085e-6\n", - "Kc = 4.166286018833649e8\n", - "proton+O=CC(O)C#[Pt]<=>CX+O=CCO\n", - "kf = 0.2097860124056399\n", - "krev = 0.0024507024511013467\n", - "Kc = 85.60240036947854\n", - "vacantX+vacantX+O=C=CCO<=>OC[Pt]+O=C=C[Pt]\n", - "kf = 4067.906517801298\n", - "krev = 9.581534474143486e11\n", - "Kc = 4.245568941779481e-9\n", - "proton+O=CC(=O)[Pt]<=>O=CC(O)=[Pt]\n", - "kf = 1.4625119078213113e-5\n", - "krev = 1.0085447542339824e12\n", - "Kc = 1.4501209804339615e-17\n", - "proton+O=CC(O)=[Pt]<=>OC#[Pt]+C=O\n", - "kf = 345367.8200620121\n", - "krev = 2.1066346546856475e-20\n", - "Kc = 1.6394291211996983e25\n", - "proton+O=CC(O)=[Pt]<=>H2O+O=CC#[Pt]\n", - "kf = 109541.91076063467\n", - "krev = 6.52855201530546e-37\n", - "Kc = 1.6778898368861259e41\n", - "proton+O=C=C(O)[Pt]<=>O=CC(O)=[Pt]\n", - "kf = 266253.7431100425\n", - "krev = 124230.61178859882\n", - "Kc = 2.1432217009695007\n", - "proton+O=CC(O)=[Pt]<=>O=CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.793151847783197e-46\n", - "Kc = 3.207944678649035e55\n", - "proton+OC(O)[Pt]<=>OCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.3128823116835e-26\n", - "Kc = 5.796587570283467e35\n", - "proton+OCO[Pt]<=>OCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.052557862362137e-26\n", - "Kc = 8.189852945376913e35\n", - "vacantX+OCO<=>OCO.[Pt]\n", - "kf = 395377.4080430906\n", - "krev = 715.0601225795458\n", - "Kc = 552.9289014422803\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.079525546868e-12\n", - "Kc = 1.2021973010936467e22\n", - "vacantX+O=C=C=C=O<=>O=C=C=C=O.[Pt]\n", - "kf = 332249.5811031886\n", - "krev = 401.14766551623046\n", - "Kc = 828.2475748067037\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 4.91573386591171e-7\n", - "Kc = 5.08571063485824e16\n", - "proton+O=CCO[Pt]<=>O=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.8816895227328687e-31\n", - "Kc = 1.3285932507978942e41\n", - "proton+O=C([Pt])CO<=>O=CCO.[Pt]\n", - "kf = 3.74256001789537e8\n", - "krev = 9.536073355505413e-9\n", - "Kc = 3.9246342581191416e16\n", - "vacantX+O=CCO<=>O=CCO.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 1291.5767888759226\n", - "Kc = 273.8002875141987\n", - "proton+O=CC(O)[Pt]<=>O=CCO.[Pt]\n", - "kf = 1.712472301799593e10\n", - "krev = 2.6335036754646568e-14\n", - "Kc = 6.5026387384762e23\n", - "proton+OCC#[Pt]<=>OCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.6468663797080987e-6\n", - "Kc = 6.855200437039605e15\n", - "proton+OCC=[Pt]<=>CHX+CO-2\n", - "kf = 2.437334851076409e7\n", - "krev = 3.684139726492616e-11\n", - "Kc = 6.615750302708541e17\n", - "vacantX+vacantX+O=CCO<=>OX+OCC=[Pt]\n", - "kf = 3.3881471741726223e-34\n", - "krev = 2.264159139077055e16\n", - "Kc = 1.4964262518904662e-50\n", - "vacantX+vacantX+O=C=CCO<=>OCX+OCC=[Pt]\n", - "kf = 1.8009876630720204e-13\n", - "krev = 6.668943472119082e14\n", - "Kc = 2.7005591974222413e-28\n", - "vacantX+vacantX+C=CC=O<=>CH2X+O=CC=[Pt]\n", - "kf = 3.2830355290077765e-39\n", - "krev = 2.9277080237249806e14\n", - "Kc = 1.121367124864694e-53\n", - "vacantX+vacantX+C=COC=O<=>CH2X+O=COC=[Pt]\n", - "kf = 1.0242943870290668e-63\n", - "krev = 2.920849603333263e13\n", - "Kc = 3.5068371403311754e-77\n", - "vacantX+O=C=CCO<=>O=C=CCO.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 1179.037991138623\n", - "Kc = 273.8002884035305\n", - "vacantX+vacantX+O=CC=CO<=>OC=[Pt]+O=CC=[Pt]\n", - "kf = 6.284377773759944e-35\n", - "krev = 2.1623088290446475e12\n", - "Kc = 2.90632757418676e-47\n", - "vacantX+vacantX+COC<=>CH3X+CO[Pt]\n", - "kf = 3.3416169046706564e-11\n", - "krev = 3.110510590664853e12\n", - "Kc = 1.0742985137872191e-23\n", - "proton+O=C=CC(O)[Pt]<=>OC=[Pt]+C=C=O\n", - "kf = 7.886335155622577e-9\n", - "krev = 1.1676117437495351e-7\n", - "Kc = 0.0675424446340125\n", - "HX+O=C=CC=O<=>O=C=CC(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 3.0624966294759025e-24\n", - "Kc = 8.467340919226885e15\n", - "proton+O=C=CC=O.[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 5.4417257022505686e7\n", - "krev = 1.0699402207865258e-10\n", - "Kc = 5.086009102686402e17\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=CC(O)[Pt]\n", - "kf = 2.2665619116480148e-11\n", - "krev = 0.03466826587817799\n", - "Kc = 6.537857761944495e-10\n", - "proton+O=C=CC(O)[Pt]<=>O=C=CCO.[Pt]\n", - "kf = 1.693513701515947e9\n", - "krev = 6.001577582317764e-11\n", - "Kc = 2.8217809039168078e19\n", - "proton+O=C=CC=[Pt]<=>CHX+C=C=O\n", - "kf = 181.35768264661723\n", - "krev = 8.307531938850336e-7\n", - "Kc = 2.183051283841528e8\n", - "proton+O=C=CC#[Pt]<=>O=C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.768026569342988e-11\n", - "Kc = 1.4140058997693788e21\n", - "vacantX+vacantX+O=C=CC=O<=>OX+O=C=CC=[Pt]\n", - "kf = 3.709849833927781e-21\n", - "krev = 2.4389911159903437e17\n", - "Kc = 1.5210591828750508e-38\n", - "proton+O=C=CC(O)[Pt]<=>H2O+O=C=CC=[Pt]\n", - "kf = 4.694863820330143\n", - "krev = 3.9520471176425216e-5\n", - "Kc = 118795.74510565875\n", - "vacantX+vacantX+CCO<=>CH3X+OC[Pt]\n", - "kf = 1.5510087911871897e-15\n", - "krev = 9.749013808701775e13\n", - "Kc = 1.5909391674086975e-29\n", - "proton+O=C=C([Pt])CO<=>CO-2+O=C=C=[Pt]\n", - "kf = 259142.28390262663\n", - "krev = 5.010713983419634e-21\n", - "Kc = 5.171763640074528e25\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=C([Pt])CO\n", - "kf = 4.040764431615523e-20\n", - "krev = 30.812673220085827\n", - "Kc = 1.3113969056672023e-21\n", - "proton+O=C=C([Pt])CO<=>O=C=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.777114479215893e-21\n", - "Kc = 1.4067748753603438e31\n", - "proton+O=C=CC[Pt]<=>CH2X+C=C=O\n", - "kf = 6.0148104045883e-8\n", - "krev = 8.74545093406659e-6\n", - "Kc = 0.006877644674854341\n", - "vacantX+vacantX+O=C=CCO<=>HOX+O=C=CC[Pt]\n", - "kf = 8.032715739528718e-6\n", - "krev = 4.997427676480693e14\n", - "Kc = 1.6073700830795308e-20\n", - "proton+O=C=CC=[Pt]<=>O=C=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.1155543114237032e-25\n", - "Kc = 1.1817233840324226e35\n", - "vacantX+vacantX+CC(O)O<=>CH3X+OC(O)[Pt]\n", - "kf = 1.0212279299691738e-21\n", - "krev = 4.839386960246169e15\n", - "Kc = 2.1102423475497943e-37\n", - "proton+O=C=CC(O)=[Pt]<=>OC#[Pt]+C=C=O\n", - "kf = 1.5097720767202745e6\n", - "krev = 3.361950781834918e-17\n", - "Kc = 4.490761985207459e22\n", - "proton+O=C=CC(O)=[Pt]<=>H2O+O=C=CC#[Pt]\n", - "kf = 5.803789817126122e6\n", - "krev = 2.7232165859221153e-28\n", - "Kc = 2.1312259359498893e34\n", - "proton+O=C=CC(=O)[Pt]<=>O=C=CC(O)=[Pt]\n", - "kf = 0.6530550593549805\n", - "krev = 1.0085447542339824e12\n", - "Kc = 6.475221417923034e-13\n", - "proton+O=C=CC(O)=[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.85508059604632e-41\n", - "Kc = 2.5367626125786886e50\n", - "C=O+O=C=C[Pt]<=>O=C=CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 80798.59947863563\n", - "Kc = 4.901904683810505e-13\n", - "HX+O=C=CC=O<=>O=C=CCO[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 2.019947796444839e-5\n", - "Kc = 0.0012837560986177624\n", - "proton+O=C=CC=O.[Pt]<=>O=C=CCO[Pt]\n", - "kf = 278.5863350248319\n", - "krev = 3612.827309769227\n", - "Kc = 0.07711033800910536\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=CCO[Pt]\n", - "kf = 7.342900678318069e-26\n", - "krev = 740.7927312780465\n", - "Kc = 9.912220204496055e-29\n", - "proton+O=C=CCO[Pt]<=>O=C=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3432355963676785e-28\n", - "Kc = 1.861177597407629e38\n", - "vacantX+vacantX+CCOC=O<=>CH3X+O=COC[Pt]\n", - "kf = 1.714178070740009e-17\n", - "krev = 1.2983121019578911e14\n", - "Kc = 1.3203127877765141e-31\n", - "proton+O=CC([Pt])C=O<=>C=O+O=CC=[Pt]\n", - "kf = 1.0131844482393167e-10\n", - "krev = 2.9534786470384583e-7\n", - "Kc = 0.00034304783251277847\n", - "HX+O=C=CC=O<=>O=CC([Pt])C=O\n", - "kf = 2.5931203025755725e-8\n", - "krev = 5.183135272095574e-24\n", - "Kc = 5.002995612590211e15\n", - "proton+O=C=CC=O.[Pt]<=>O=CC([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 8.319166178505196e-8\n", - "Kc = 3.005108861101275e17\n", - "vacantX+vacantX+O=CCC=O<=>HX+O=CC([Pt])C=O\n", - "kf = 6.269624738894468e-15\n", - "krev = 24.522149705338403\n", - "Kc = 2.556719053684591e-16\n", - "proton+O=CC(=[Pt])C=O<=>C=O+O=CC#[Pt]\n", - "kf = 0.04202179791424184\n", - "krev = 2.102387409121332e-9\n", - "Kc = 1.9987656761987723e7\n", - "proton+O=C=C([Pt])C=O<=>O=CC(=[Pt])C=O\n", - "kf = 2.5e10\n", - "krev = 5.057292696382588\n", - "Kc = 4.943356357025204e9\n", - "proton+O=CC(=[Pt])C=O<=>O=CC([Pt])C=O\n", - "kf = 2.5e10\n", - "krev = 5.3866690937421086e-24\n", - "Kc = 4.641087017771969e33\n", - "vacantX+vacantX+COCC=O<=>CH3X+O=CCO[Pt]\n", - "kf = 1.7650043109029407e-12\n", - "krev = 1.4735149295451475e13\n", - "Kc = 1.1978190892492496e-25\n", - "vacantX+vacantX+COCC=O<=>CO[Pt]+O=CC[Pt]\n", - "kf = 10.947009513309483\n", - "krev = 5.112987413682155e11\n", - "Kc = 2.1410202348661592e-11\n", - "proton+O=CCC(=O)[Pt]<=>O=CCC=O.[Pt]\n", - "kf = 2.1814901321970692e8\n", - "krev = 5.7550523540318155e-8\n", - "Kc = 3.7905652251256815e15\n", - "vacantX+O=CCC=O<=>O=CCC=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 165389.8266532618\n", - "Kc = 1.951879075907524\n", - "proton+O=CC([Pt])C=O<=>O=CCC=O.[Pt]\n", - "kf = 1.6062704929440186e10\n", - "krev = 3.122654421781107e-14\n", - "Kc = 5.1439265316711864e23\n", - "proton+O=CCC#[Pt]<=>O=CCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.03648176110191e-17\n", - "Kc = 4.141485220927174e26\n", - "proton+O=CCC=[Pt]<=>CHX+CC=O\n", - "kf = 1.0605779567215914e7\n", - "krev = 5.748508015003e-13\n", - "Kc = 1.8449621257439228e19\n", - "vacantX+vacantX+O=CCC=O<=>OX+O=CCC=[Pt]\n", - "kf = 1.2771337705277995e-31\n", - "krev = 6.599290845791489e16\n", - "Kc = 1.935259106426951e-48\n", - "vacantX+vacantX+CCOO<=>CH3X+OOC[Pt]\n", - "kf = 1.1728434846364774e-18\n", - "krev = 2.6840450809869076e16\n", - "Kc = 4.3696862356918e-35\n", - "proton+OOCC#[Pt]<=>CX+COO\n", - "kf = 0.24698833297799483\n", - "krev = 0.0004336424509567548\n", - "Kc = 569.5667765760919\n", - "vacantX+vacantX+C=C=O<=>OX+C=C=[Pt]\n", - "kf = 5.2796000958546504e-37\n", - "krev = 1.4614931014553018e17\n", - "Kc = 3.612470076387919e-54\n", - "proton+C=C=[Pt]<=>CC#[Pt]\n", - "kf = 10.738937415423795\n", - "krev = 4.122167482176662e-33\n", - "Kc = 2.60516766042539e33\n", - "vacantX+vacantX+CC(C)=O<=>CH3X+CC(=O)[Pt]\n", - "kf = 0.0015322757193851075\n", - "krev = 1.9084257758101816e14\n", - "Kc = 8.029003479239911e-18\n", - "vacantX+vacantX+C=C=C=O<=>CH2X+O=C=C=[Pt]\n", - "kf = 0.014873013888318402\n", - "krev = 6.520037160662236e15\n", - "Kc = 2.2811240981957472e-18\n", - "HOX+C=C=C=O<=>O=C=C([Pt])CO\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.9529365102554657e-31\n", - "Kc = 9.99708792916859e22\n", - "HX+C=C=C=O<=>O=C=CC[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.4091973858076736e-32\n", - "Kc = 1.225336127134283e24\n", - "vacantX+vacantX+C=C=C=O<=>OCX+C=C=[Pt]\n", - "kf = 0.8504584217531632\n", - "krev = 1.347597642765549e15\n", - "Kc = 6.310922450174717e-16\n", - "proton+O=C(O)C=[Pt]<=>CHX+O=CO\n", - "kf = 7.88145235948431e7\n", - "krev = 1.995696153847229e-7\n", - "Kc = 3.949224607308452e14\n", - "proton+O=C(O)C#[Pt]<=>O=C(O)C=[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.424855572557093e-13\n", - "Kc = 3.3670688615684534e22\n", - "vacantX+vacantX+CC=C=O<=>CH3X+O=C=C[Pt]\n", - "kf = 0.0008567749561878586\n", - "krev = 1.2359860589695025e13\n", - "Kc = 6.931914401220598e-17\n", - "vacantX+vacantX+CC=C=O<=>HX+O=C=CC[Pt]\n", - "kf = 2.2773385768535307e-19\n", - "krev = 181.8091471864856\n", - "Kc = 1.2525984594810374e-21\n", - "proton+O=C=CCO[Pt]<=>OX+CC=C=O\n", - "kf = 3.801213612232799e6\n", - "krev = 3.4005935521726275e-15\n", - "Kc = 1.1178088630451637e21\n", - "proton+CC(=O)[Pt]<=>CC=O.[Pt]\n", - "kf = 2.2108223076011086e9\n", - "krev = 2.493722128340101e-11\n", - "Kc = 8.865551949337277e19\n", - "proton+O=CC[Pt]<=>CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0175396707648368e-24\n", - "Kc = 2.456906665978799e34\n", - "vacantX+CC=O<=>CC=O.[Pt]\n", - "kf = 412885.969273148\n", - "krev = 2.625517699834265\n", - "Kc = 157258.8786200951\n", - "proton+CC=[Pt]<=>CHX+CH4\n", - "kf = 3.754229088708618e7\n", - "krev = 3.193900280463504e-10\n", - "Kc = 1.1754371642948722e17\n", - "proton+CC#[Pt]<=>CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.101069134371629e-9\n", - "Kc = 3.086012424450092e18\n", - "vacantX+vacantX+CC=O<=>OX+CC=[Pt]\n", - "kf = 6.186864182993887e-31\n", - "krev = 2.034915252803989e19\n", - "Kc = 3.04035471475717e-50\n", - "vacantX+vacantX+CC=C=O<=>OCX+CC=[Pt]\n", - "kf = 5.619880038277716e-8\n", - "krev = 4.919193785592355e16\n", - "Kc = 1.14243924578405e-24\n", - "vacantX+vacantX+CC<=>CH3X+CH3X\n", - "kf = 1.6866972609475142e-22\n", - "krev = 6.547125244410207e13\n", - "Kc = 2.576241018739606e-36\n", - "proton+O=C=CC[Pt]<=>CC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.381078389100095e-19\n", - "Kc = 1.0499444333476355e29\n", - "vacantX+CC=C=O<=>CC=C=O.[Pt]\n", - "kf = 365995.57053717994\n", - "krev = 187509.1639624155\n", - "Kc = 1.9518809790573244\n", - "proton+O=C(O)C[Pt]<=>CH2X+O=CO\n", - "kf = 5.038535015011119e-9\n", - "krev = 7.877133180076684e-5\n", - "Kc = 6.396407042799381e-5\n", - "HOX+C=C=O<=>O=C(O)C[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.348252838458729e-29\n", - "Kc = 4.5553052781738184e20\n", - "vacantX+vacantX+CC(=O)O<=>HX+O=C(O)C[Pt]\n", - "kf = 1.1112170024966995e-23\n", - "krev = 36323.66987445037\n", - "Kc = 3.0592090676342045e-28\n", - "proton+O=C(O)C=[Pt]<=>O=C(O)C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0876086200539217e-33\n", - "Kc = 2.2986209872776243e43\n", - "vacantX+vacantX+O=C=C=CO<=>OC=[Pt]+O=C=C=[Pt]\n", - "kf = 0.004371453552681894\n", - "krev = 1.2572855491392857e13\n", - "Kc = 3.476897953431907e-16\n", - "HX+O=C=C=CO<=>O=C=CC(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.3635197599529065e-33\n", - "Kc = 1.9017841755847633e25\n", - "HX+O=C=C=CO<=>O=C=C([Pt])CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 6.797711819853139e-22\n", - "Kc = 3.814695843684052e13\n", - "proton+O=C(O)CC#[Pt]<=>CX+CC(=O)O\n", - "kf = 0.12574987603391333\n", - "krev = 9.921358720719502e-5\n", - "Kc = 1267.4662772882168\n", - "proton+CC([Pt])=C=O<=>CH4+O=C=C=[Pt]\n", - "kf = 49487.72961177987\n", - "krev = 1.2730900614037961e-24\n", - "Kc = 3.8872135689451003e28\n", - "HX+C=C=C=O<=>CC([Pt])=C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.301177455844525e-32\n", - "Kc = 1.2828548214436644e24\n", - "vacantX+vacantX+CC=C=O<=>HX+CC([Pt])=C=O\n", - "kf = 4.581183222917958e-20\n", - "krev = 34.93361388628861\n", - "Kc = 1.3113968791863429e-21\n", - "proton+CC([Pt])=C=O<=>CC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.492848961236613e-19\n", - "Kc = 1.0028686209532082e29\n", - "CH3X+O=C=C=O<=>CC(=C=O)O[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.951682102619952e-64\n", - "Kc = 1.9647454732667077e56\n", - "proton+CC(=C=O)O[Pt]<=>OX+CC=C=O\n", - "kf = 1.920567374031219e-6\n", - "krev = 5.0434729686975995e-5\n", - "Kc = 0.03808025513274787\n", - "vacantX+C=C<=>C=C.[Pt]\n", - "kf = 36.21750369826068\n", - "krev = 0.32335117013731834\n", - "Kc = 112.00671914340097\n", - "vacantX+vacantX+C=CO<=>HOX+C=C[Pt]\n", - "kf = 1.7018617233469498e-12\n", - "krev = 4.164837143763027e13\n", - "Kc = 4.086262354568991e-26\n", - "vacantX+vacantX+C=C<=>HX+C=C[Pt]\n", - "kf = 6.071347272542775e-23\n", - "krev = 1180.067101472276\n", - "Kc = 5.144916983930861e-26\n", - "vacantX+vacantX+C=CC=O<=>CHOX+C=C[Pt]\n", - "kf = 0.3274906030624493\n", - "krev = 2.9425898600264806e14\n", - "Kc = 1.1129332276687114e-15\n", - "vacantX+vacantX+C=COC=O<=>CHO2X+C=C[Pt]\n", - "kf = 0.2513917911405871\n", - "krev = 1.0405847657707406e16\n", - "Kc = 2.4158703779829617e-17\n", - "proton+C=C=[Pt]<=>C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.446578752089028e-33\n", - "Kc = 1.0218350820979533e43\n", - "proton+C=C[Pt]<=>CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 31.775139733809926\n", - "Kc = 7.867786014296917e8\n", - "proton+C=C[Pt]<=>C=C.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.7043133558442046e-25\n", - "Kc = 1.4668664019015827e35\n", - "proton+C=CC#[Pt]<=>CX+C=C\n", - "kf = 1.0856530221273585e-15\n", - "krev = 0.12983129718682296\n", - "Kc = 8.36202861444987e-15\n", - "vacantX+CC(=O)O<=>CC(=O)O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 181176.05501028927\n", - "Kc = 1.9518809818483447\n", - "proton+CC(=O)O[Pt]<=>CC(=O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.133892027559991e-24\n", - "Kc = 6.04756965913213e33\n", - "proton+O=C(O)C[Pt]<=>CC(=O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.815284645396005e-26\n", - "Kc = 4.2990157016290936e35\n", - "proton+C=CC(=O)[Pt]<=>OCX+C=C\n", - "kf = 7.087170621400232e6\n", - "krev = 2.9783308105065206e-7\n", - "Kc = 2.3795780496911715e13\n", - "vacantX+vacantX+C=CC=O<=>HX+C=CC(=O)[Pt]\n", - "kf = 3.052485738368744e-11\n", - "krev = 0.0007099643372969683\n", - "Kc = 4.29949164769375e-8\n", - "HX+C=C=C=O<=>C=CC(=O)[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 5.604440911093213e-48\n", - "Kc = 5.267388203494818e39\n", - "HX+O=C=CC=O<=>O=CC=CO[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 5.6159867257682645e-34\n", - "Kc = 4.61739037002591e25\n", - "proton+O=C=CC=O.[Pt]<=>O=CC=CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 9.013912308921113e-18\n", - "Kc = 2.7734904826239954e27\n", - "proton+O=CC=CO[Pt]<=>OX+C=CC=O\n", - "kf = 3.6615493516163485e-10\n", - "krev = 9.407550626549198e-5\n", - "Kc = 3.892138875429521e-6\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC=CO[Pt]\n", - "kf = 4.135805741920728e-10\n", - "krev = 0.028732529553568358\n", - "Kc = 1.4394158141245496e-8\n", - "HX+C=C=O<=>C=CO[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.272169613200064e-8\n", - "Kc = 0.46029640012283785\n", - "proton+C=C=O.[Pt]<=>C=CO[Pt]\n", - "kf = 2.7021695253394946e-5\n", - "krev = 3753.979595717479\n", - "Kc = 7.19814654406251e-9\n", - "vacantX+vacantX+C=CO<=>HX+C=CO[Pt]\n", - "kf = 1.5839272910037507e-20\n", - "krev = 3600.161649580889\n", - "Kc = 4.399600476795654e-24\n", - "proton+C=CO[Pt]<=>OX+C=C\n", - "kf = 6.694428008398142e6\n", - "krev = 4.294813980591457e-9\n", - "Kc = 1.5587236231070068e15\n", - "vacantX+vacantX+C=COC=O<=>CHOX+C=CO[Pt]\n", - "kf = 0.024290856013790354\n", - "krev = 3.5586883050271985e15\n", - "Kc = 6.825789148062155e-18\n", - "vacantX+vacantX+O=CCCO<=>OC[Pt]+O=CC[Pt]\n", - "kf = 2.162232232095232e-5\n", - "krev = 5.66671683371172e13\n", - "Kc = 3.815670158833332e-19\n", - "proton+C=COC(=O)[Pt]<=>OCX+C=CO\n", - "kf = 8.547694380469097e6\n", - "krev = 5.219823560516419e-10\n", - "Kc = 1.637544695020963e16\n", - "vacantX+vacantX+C=COC=O<=>HX+C=COC(=O)[Pt]\n", - "kf = 3.5117597357119104e-15\n", - "krev = 0.7837038908782975\n", - "Kc = 4.480977798612533e-15\n", - "CO2+C=C[Pt]<=>C=COC(=O)[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.08399332498323721\n", - "Kc = 7.789900440580834e-7\n", - "proton+C=COC#[Pt]<=>CX+C=CO\n", - "kf = 3.59319568894763e-23\n", - "krev = 3.7552909398960855e-5\n", - "Kc = 9.568355012853036e-19\n", - "vacantX+vacantX+CCC=O<=>CH3X+O=CC[Pt]\n", - "kf = 1.2257627381394946e-12\n", - "krev = 3.270257576074817e14\n", - "Kc = 3.748214657790771e-27\n", - "proton+CC(O)=[Pt]<=>OC#[Pt]+CH4\n", - "kf = 7.023325690411809e6\n", - "krev = 0.001122962882704699\n", - "Kc = 6.254281239906934e9\n", - "proton+CC(=O)[Pt]<=>CC(O)=[Pt]\n", - "kf = 9.881755573608883e9\n", - "krev = 1.0085447542339819e12\n", - "Kc = 0.009798033782957261\n", - "proton+CC(O)=[Pt]<=>H2O+CC#[Pt]\n", - "kf = 7.254296675241664e9\n", - "krev = 2.8720393080667615e-6\n", - "Kc = 2.5258347456688205e15\n", - "vacantX+vacantX+CC(=O)O<=>OX+CC(O)=[Pt]\n", - "kf = 1.1829749543892744e-33\n", - "krev = 3.758913107590896e15\n", - "Kc = 3.1471197139415875e-49\n", - "vacantX+vacantX+CC(O)=C=O<=>CH3X+O=C=C(O)[Pt]\n", - "kf = 1.049990631922765e-6\n", - "krev = 1.7955210884029898e15\n", - "Kc = 5.847832357439309e-22\n", - "vacantX+vacantX+CC(O)=C=O<=>HOX+CC([Pt])=C=O\n", - "kf = 0.0029164033711847528\n", - "krev = 3.4437539939134434e12\n", - "Kc = 8.468675103794464e-16\n", - "vacantX+vacantX+CC(O)=C=O<=>HX+CC(=C=O)O[Pt]\n", - "kf = 1.7528367761452354e-6\n", - "krev = 1.1970864565480504e-5\n", - "Kc = 0.14642524494009906\n", - "vacantX+vacantX+CC(O)=C=O<=>OCX+CC(O)=[Pt]\n", - "kf = 65.80946386077328\n", - "krev = 1217.699742052305\n", - "Kc = 0.054044081301896585\n", - "vacantX+vacantX+C=CC=O<=>HX+O=CC=C[Pt]\n", - "kf = 6.342176392543457e-21\n", - "krev = 776.2437464870187\n", - "Kc = 8.170341366672147e-24\n", - "vacantX+vacantX+O=CC=CO<=>HOX+O=CC=C[Pt]\n", - "kf = 4.672349699632388e-15\n", - "krev = 8.81363422062413e13\n", - "Kc = 5.301274800693419e-29\n", - "proton+O=CC=C[Pt]<=>O=CCC=[Pt]\n", - "kf = 1.2673656466904085e10\n", - "krev = 1.0824082827935274e8\n", - "Kc = 117.08757839689983\n", - "proton+C=CC(=O)O[Pt]<=>OX+C=CC=O\n", - "kf = 4.524546416801015\n", - "krev = 7.68227583414659e-9\n", - "Kc = 5.889591202505473e8\n", - "CO2+C=C[Pt]<=>C=CC(=O)O[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 450683.30306117237\n", - "Kc = 1.4517947189269602e-13\n", - "vacantX+vacantX+O=C=CO<=>OX+OC=C=[Pt]\n", - "kf = 7.548264554696059e-34\n", - "krev = 5.749061160710156e15\n", - "Kc = 1.3129560364189368e-49\n", - "proton+OC=C=[Pt]<=>OCC#[Pt]\n", - "kf = 0.00032547344886471076\n", - "krev = 1.1489507349403094e-46\n", - "Kc = 2.832788551909668e42\n", - "vacantX+vacantX+O=C=C=CO<=>OCX+OC=C=[Pt]\n", - "kf = 1.463392220587488e-22\n", - "krev = 7.968303762369095e13\n", - "Kc = 1.8365166090912173e-36\n", - "proton+CC[Pt]<=>CH2X+CH4\n", - "kf = 1.4846524062695914\n", - "krev = 9.859129077434927e-6\n", - "Kc = 150586.56749586415\n", - "HX+C=C<=>CC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 3.1627439012977165e-12\n", - "Kc = 25911.109388377805\n", - "vacantX+vacantX+CCO<=>HOX+CC[Pt]\n", - "kf = 2.1035625708276702e-15\n", - "krev = 1.0019023766861524e15\n", - "Kc = 2.099568400850909e-30\n", - "vacantX+vacantX+CCOC=O<=>CHO2X+CC[Pt]\n", - "kf = 0.08561452397466171\n", - "krev = 3.215769317238553e17\n", - "Kc = 2.6623341268826044e-19\n", - "vacantX+vacantX+CCOO<=>OO[Pt]+CC[Pt]\n", - "kf = 1.262172875849309e-6\n", - "krev = 1.5596341944506717e13\n", - "Kc = 8.092749443044025e-20\n", - "proton+CC=[Pt]<=>CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.602708332438123e-27\n", - "Kc = 2.9060615603731233e36\n", - "vacantX+vacantX+CC<=>HX+CC[Pt]\n", - "kf = 8.697106954471648e-14\n", - "krev = 5.359609736165605e16\n", - "Kc = 1.6227127314485718e-30\n", - "proton+C=C.[Pt]<=>CC[Pt]\n", - "kf = 5.504599623053448e9\n", - "krev = 0.3531497863658743\n", - "Kc = 1.558715263486103e10\n", - "vacantX+vacantX+CCC=O<=>CHOX+CC[Pt]\n", - "kf = 0.0004422945453165714\n", - "krev = 9.363325052982716e15\n", - "Kc = 4.723691026572629e-20\n", - "vacantX+vacantX+CC(O)C=O<=>CH3X+O=CC(O)[Pt]\n", - "kf = 9.477814531468979e-7\n", - "krev = 7.52142668687151e15\n", - "Kc = 1.2601086105129898e-22\n", - "proton+CCC#[Pt]<=>CX+CC\n", - "kf = 3.73018742862406e-11\n", - "krev = 0.075105066117345\n", - "Kc = 4.966625583946592e-10\n", - "C=O+CH3X<=>CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.1808191230067762e-17\n", - "Kc = 3.354171909251678e9\n", - "HX+CC=O<=>CCO[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 2.639709061724686e-6\n", - "Kc = 0.012387213631168494\n", - "vacantX+vacantX+CCO<=>HX+CCO[Pt]\n", - "kf = 5.372480262216755e-24\n", - "krev = 2113.809062877283\n", - "Kc = 2.5416109508508876e-27\n", - "vacantX+vacantX+CCOC=O<=>CHOX+CCO[Pt]\n", - "kf = 4.80530366959931e-5\n", - "krev = 5.681813674074216e13\n", - "Kc = 8.457341168235823e-19\n", - "vacantX+vacantX+CCOO<=>HOX+CCO[Pt]\n", - "kf = 3.028654941635431e8\n", - "krev = 1.2132864881112858e-12\n", - "Kc = 2.496240559268171e20\n", - "proton+CC=O.[Pt]<=>CCO[Pt]\n", - "kf = 19418.796323941955\n", - "krev = 3658.802750537776\n", - "Kc = 5.30741820424393\n", - "proton+CCO[Pt]<=>OX+CC\n", - "kf = 1.5180806810718186e7\n", - "krev = 3.4536717602694347e-12\n", - "Kc = 4.395555763392486e18\n", - "proton+CCOC(=O)[Pt]<=>OCX+CCO\n", - "kf = 1.100364657251968e9\n", - "krev = 4.5302115405928314e-10\n", - "Kc = 2.4289476272623954e18\n", - "vacantX+vacantX+CCOC=O<=>HX+CCOC(=O)[Pt]\n", - "kf = 2.5742212027881315e-15\n", - "krev = 0.39729482671494754\n", - "Kc = 6.479372570927264e-15\n", - "CO2+CC[Pt]<=>CCOC(=O)[Pt]\n", - "kf = 3.860701485876577e-7\n", - "krev = 0.0037771400241392917\n", - "Kc = 0.00010221229451921966\n", - "CH3X+C=C=O<=>CCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.9339597186194493e-34\n", - "Kc = 1.7308289628845924e26\n", - "HX+CC=C=O<=>CCC(=O)[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 2.728234417234893e-33\n", - "Kc = 1.0624138213938816e25\n", - "proton+CCC(=O)[Pt]<=>OCX+CC\n", - "kf = 3.3183098775357734e7\n", - "krev = 1.723115430616528e-10\n", - "Kc = 1.9257618024745373e17\n", - "proton+CC=C=O.[Pt]<=>CCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.816709270833084e-23\n", - "Kc = 3.667458740974689e32\n", - "vacantX+vacantX+CCC=O<=>HX+CCC(=O)[Pt]\n", - "kf = 1.3037608552158366e-12\n", - "krev = 0.18236199715464047\n", - "Kc = 7.149301255514685e-12\n", - "vacantX+vacantX+C=C(O)C=O<=>CH2X+O=CC(O)=[Pt]\n", - "kf = 3.506980389191063e-59\n", - "krev = 1.6121784785918364e12\n", - "Kc = 2.1753053001019147e-71\n", - "proton+CCOC#[Pt]<=>CX+CCO\n", - "kf = 1.6403573057503937e-22\n", - "krev = 1.0480859144262605e-13\n", - "Kc = 1.5650981309565184e-9\n", - "proton+CCC(=O)O[Pt]<=>OX+CCC=O\n", - "kf = 5.622114816602621e-8\n", - "krev = 4.785365563630673e-7\n", - "Kc = 0.11748558687619057\n", - "CO2+CC[Pt]<=>CCC(=O)O[Pt]\n", - "kf = 3.860701485876577e-7\n", - "krev = 2.2515045234693432e-8\n", - "Kc = 17.147207325738\n", - "vacantX+vacantX+OC=CCO<=>OC=[Pt]+OCC=[Pt]\n", - "kf = 3.6700973989487563e-44\n", - "krev = 3.0504263460080312e13\n", - "Kc = 1.203142440646588e-57\n", - "proton+CC(=C=O)O[Pt]<=>CC(O)=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 27.83415070046663\n", - "Kc = 8.981772165076653e8\n", - "vacantX+CC(O)=C=O<=>CC(O)=C=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 165389.73964983693\n", - "Kc = 1.9518801026953096\n", - "proton+OOC=[Pt]<=>OO+CHX\n", - "kf = 2.8719882764673755e7\n", - "krev = 8.077545633440945e-25\n", - "Kc = 3.555520955000709e31\n", - "proton+OOC=[Pt]<=>OOC[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.62255074484058e-37\n", - "Kc = 2.899374064566577e46\n", - "proton+OOC#[Pt]<=>OOC=[Pt]\n", - "kf = 3.432151727081939e-44\n", - "krev = 3342.777740155216\n", - "Kc = 1.0267364431242663e-47\n", - "vacantX+vacantX+C=CCO<=>CH2X+OCC=[Pt]\n", - "kf = 3.3256293066300124e-48\n", - "krev = 2.638642223210571e15\n", - "Kc = 1.2603562837645906e-63\n", - "vacantX+vacantX+C=CCO<=>OC[Pt]+C=C[Pt]\n", - "kf = 1.4930923415267688e-9\n", - "krev = 1.1121057711212152e14\n", - "Kc = 1.3425812366942817e-23\n", - "vacantX+OO<=>OO.[Pt]\n", - "kf = 469882.2241291155\n", - "krev = 15.560302693769444\n", - "Kc = 30197.498941795184\n", - "proton+OO[Pt]<=>OO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.110596489625074e-24\n", - "Kc = 2.251042591395165e34\n", - "C=O+CO[Pt]<=>COCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 9.545218685674386e-14\n", - "Kc = 414937.62088874576\n", - "HX+COC=O<=>COCO[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 0.02522938529859348\n", - "Kc = 1.1100614687459063e-6\n", - "vacantX+vacantX+COCO<=>HX+COCO[Pt]\n", - "kf = 1.0488506310161173e-19\n", - "krev = 521.1543106644776\n", - "Kc = 2.0125529225284944e-22\n", - "proton+COC=O.[Pt]<=>COCO[Pt]\n", - "kf = 0.6792883990466445\n", - "krev = 3726.123137157573\n", - "Kc = 0.00018230433457033608\n", - "proton+COCO[Pt]<=>OX+COC\n", - "kf = 5093.375621150868\n", - "krev = 5.977614318003391e-7\n", - "Kc = 8.520749834613165e9\n", - "CO[Pt]+C=C=O<=>COCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.680149232421768e-23\n", - "Kc = 1.9922953446306685e15\n", - "HX+COC=C=O<=>COCC(=O)[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 2.661991446097411e-38\n", - "Kc = 9.604054388173769e29\n", - "proton+COCC(=O)[Pt]<=>OCX+COC\n", - "kf = 8.734746675052269e7\n", - "krev = 2.1771371890779743e-8\n", - "Kc = 4.012033196103488e15\n", - "vacantX+vacantX+COCC=O<=>HX+COCC(=O)[Pt]\n", - "kf = 2.290241001822749e-10\n", - "krev = 0.0004872161822843353\n", - "Kc = 4.7006669423105973e-7\n", - "proton+COCOC#[Pt]<=>CX+COCO\n", - "kf = 3.2770328923262016e-17\n", - "krev = 2.1864147814239428e-13\n", - "Kc = 0.0001498815741719407\n", - "proton+COCC#[Pt]<=>CX+COC\n", - "kf = 1.433200340176918\n", - "krev = 0.00041586763423335837\n", - "Kc = 3446.289689792732\n", - "proton+COC[Pt]<=>CH2X+CO-2\n", - "kf = 0.2769010105768301\n", - "krev = 3.0099119392563808e-6\n", - "Kc = 91996.38267332179\n", - "vacantX+vacantX+COCO<=>HOX+COC[Pt]\n", - "kf = 8.90444501639475e-13\n", - "krev = 8.409201083164982e12\n", - "Kc = 1.0588931015362724e-25\n", - "C=O+CH3X<=>COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 8.422687202008296e-11\n", - "Kc = 470.23832623775377\n", - "vacantX+vacantX+COC<=>HX+COC[Pt]\n", - "kf = 2.786306429788959e-20\n", - "krev = 52.25975865319748\n", - "Kc = 5.3316481009398625e-22\n", - "vacantX+vacantX+COCC=O<=>CHOX+COC[Pt]\n", - "kf = 1.4060776479118306e6\n", - "krev = 6.613786245273692e13\n", - "Kc = 2.1259798786461146e-8\n", - "vacantX+vacantX+C=C=CO<=>OC=[Pt]+C=C=[Pt]\n", - "kf = 1.5975335437882445e-34\n", - "krev = 2.2957840869759923e8\n", - "Kc = 6.958553083676594e-43\n", - "vacantX+vacantX+C=C=CO<=>CH2X+OC=C=[Pt]\n", - "kf = 9.363402027600756e-56\n", - "krev = 7.047835211144391e9\n", - "Kc = 1.328550079149818e-65\n", - "vacantX+vacantX+COC=O<=>OX+COC=[Pt]\n", - "kf = 1.1797200153280936e-59\n", - "krev = 4.3408253155831816e16\n", - "Kc = 2.7177320660497494e-76\n", - "proton+COC=[Pt]<=>CHX+CO-2\n", - "kf = 479145.9852086257\n", - "krev = 1.0449825701778588e-33\n", - "Kc = 4.5852055228736854e38\n", - "proton+COC#[Pt]<=>COC=[Pt]\n", - "kf = 90933.51053402986\n", - "krev = 2739.427130274527\n", - "Kc = 33.194352764155155\n", - "vacantX+vacantX+COC=C=O<=>OCX+COC=[Pt]\n", - "kf = 2.7777170398864307e-21\n", - "krev = 2.5089215324603047e13\n", - "Kc = 1.107135876490541e-34\n", - "proton+COC=[Pt]<=>COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3472876439887766e-48\n", - "Kc = 1.8555799952254487e58\n", - "vacantX+COC=C=O<=>COC=C=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 1179.0380002145982\n", - "Kc = 273.8002862958761\n", - "proton+COC=C=O.[Pt]<=>COCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.0577777781824875e-25\n", - "Kc = 2.3634453772469967e35\n", - "vacantX+vacantX+C=C=C<=>CH2X+C=C=[Pt]\n", - "kf = 4.78083312177258e-41\n", - "krev = 4.774618642094983e15\n", - "Kc = 1.0013015656628172e-56\n", - "proton+O=C=COC[Pt]<=>CH2X+O=C=CO\n", - "kf = 4.988523456059943e-5\n", - "krev = 0.0009299241102698363\n", - "Kc = 0.05364441464596958\n", - "C=O+O=C=C[Pt]<=>O=C=COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.852140732586457e13\n", - "Kc = 2.1384283940268284e-21\n", - "vacantX+vacantX+COC=C=O<=>HX+O=C=COC[Pt]\n", - "kf = 3.256466928453685e-21\n", - "krev = 26.50445975246776\n", - "Kc = 1.2286486722863626e-22\n", - "proton+O=C=COC[Pt]<=>COC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.6649798034152577e-22\n", - "Kc = 1.5015197150571575e32\n", - "CH3X+O=C=C=O<=>COC([Pt])=C=O\n", - "kf = 5.799304049644909e-8\n", - "krev = 3.1615249923835833e-35\n", - "Kc = 1.8343375629216876e27\n", - "proton+COC([Pt])=C=O<=>CO-2+O=C=C=[Pt]\n", - "kf = 313658.31445379555\n", - "krev = 1.256306436150439e-34\n", - "Kc = 2.496670441448219e39\n", - "vacantX+vacantX+COC=C=O<=>HX+COC([Pt])=C=O\n", - "kf = 2.779636780044878e-20\n", - "krev = 3.601218910546807\n", - "Kc = 7.718599866018197e-21\n", - "proton+COC([Pt])=C=O<=>COC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0459713323621888e-20\n", - "Kc = 2.390122867281724e30\n", - "vacantX+vacantX+C=C=C(O)O<=>OC(O)=[Pt]+C=C=[Pt]\n", - "kf = 2.937512138355157e-45\n", - "krev = 8.778136400287878e10\n", - "Kc = 3.34639609639561e-56\n", - "proton+O=C=COC=[Pt]<=>CHX+O=C=CO\n", - "kf = 2.102599834403735e7\n", - "krev = 1.6989476123058672e-25\n", - "Kc = 1.237589563782969e32\n", - "proton+O=C=COC#[Pt]<=>O=C=COC=[Pt]\n", - "kf = 1080.8801129554665\n", - "krev = 2888.2699525834805\n", - "Kc = 0.37423098626520285\n", - "proton+O=C=COC=[Pt]<=>O=C=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.9106920181466426e-48\n", - "Kc = 8.589022763019266e57\n", - "proton+CCOO[Pt]<=>OX+CCO\n", - "kf = 169.16425212622386\n", - "krev = 5.6416707126946964e-58\n", - "Kc = 2.9984779463568512e59\n", - "vacantX+vacantX+CCOO<=>HX+CCOO[Pt]\n", - "kf = 1.893449523720139e-21\n", - "krev = 0.6694879211592951\n", - "Kc = 2.8282056537202555e-21\n", - "O=O+CC[Pt]<=>CCOO[Pt]\n", - "kf = 4.5276782379965965e-7\n", - "krev = 1.4949208469184493e-38\n", - "Kc = 3.0287076719344122e31\n", - "vacantX+vacantX+C=CC(=O)O<=>CH2X+O=C(O)C=[Pt]\n", - "kf = 4.72289540105198e-39\n", - "krev = 9.498795808374404e14\n", - "Kc = 4.9720990916429044e-54\n", - "vacantX+vacantX+C=CC(=O)O<=>CO2HX+C=C[Pt]\n", - "kf = 5.354197885861111e7\n", - "krev = 1.376967106369583e14\n", - "Kc = 3.888399266107105e-7\n", - "vacantX+vacantX+C=CC(=O)O<=>HOX+C=CC(=O)[Pt]\n", - "kf = 0.03947248649742643\n", - "krev = 2.5171232142616846e11\n", - "Kc = 1.5681586929785789e-13\n", - "vacantX+vacantX+C=CC(=O)O<=>HX+C=CC(=O)O[Pt]\n", - "kf = 2.4490000178339845e-20\n", - "krev = 458.0011375503109\n", - "Kc = 5.3471483300955e-23\n", - "proton+O=C=C=CO.[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.4322611471299928e-17\n", - "Kc = 1.7454917387164855e27\n", - "proton+O=C=C=CO.[Pt]<=>O=C=C([Pt])CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 7.140416160377535e-6\n", - "Kc = 3.5011964903006675e15\n", - "vacantX+O=C=C=CO<=>O=C=C=CO.[Pt]\n", - "kf = 327433.4917974331\n", - "krev = 0.4460204906723957\n", - "Kc = 734122.0832787583\n", - "HX+O=C=C=C=O<=>O=C=C=C(O)[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 1.3048903398306852e-5\n", - "Kc = 0.004032923533638046\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C=C(O)[Pt]\n", - "kf = 4235.342411204313\n", - "krev = 12.909334546967292\n", - "Kc = 328.0837130523738\n", - "proton+O=C=C=C(O)[Pt]<=>O=C=CC(O)=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1053.6449933824201\n", - "Kc = 2.3727156828928486e7\n", - "vacantX+vacantX+O=C=C=CO<=>HX+O=C=C=C(O)[Pt]\n", - "kf = 8.233814429551885e-18\n", - "krev = 0.5740049812746953\n", - "Kc = 1.434449995759099e-17\n", - "proton+O=C=C=C(O)[Pt]<=>O=C=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.249904355928212e-21\n", - "Kc = 3.4483213533096645e30\n", - "vacantX+vacantX+CC=CO<=>OC=[Pt]+CC=[Pt]\n", - "kf = 1.6816353348966163e-33\n", - "krev = 8.021148128032321e14\n", - "Kc = 2.0965020319468163e-48\n", - "proton+O=C=C=C[Pt]<=>O=C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.0269882986128818\n", - "Kc = 9.263273820479827e11\n", - "vacantX+vacantX+C=C=C=O<=>HX+O=C=C=C[Pt]\n", - "kf = 3.6772489817592154e-10\n", - "krev = 0.00723599763490509\n", - "Kc = 5.081882509221477e-8\n", - "vacantX+vacantX+O=C=C=CO<=>HOX+O=C=C=C[Pt]\n", - "kf = 0.00020826365169953766\n", - "krev = 1.0739954827079557e13\n", - "Kc = 1.939148302322696e-17\n", - "vacantX+OC=CO<=>OC=CO.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.48171019889246675\n", - "Kc = 734122.0861712244\n", - "vacantX+vacantX+C=CC<=>CH2X+CC=[Pt]\n", - "kf = 3.8695500910369183e-44\n", - "krev = 2.1644248520711738e17\n", - "Kc = 1.787795999169979e-61\n", - "vacantX+vacantX+C=CC<=>CH3X+C=C[Pt]\n", - "kf = 1.1726078415532691e-17\n", - "krev = 1.59532697721828e15\n", - "Kc = 7.350266486422159e-33\n", - "HX+O=C=CO<=>OC=C(O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 2.762063581333058e-24\n", - "Kc = 1.0314187634521844e16\n", - "vacantX+vacantX+OC=CO<=>HX+OC=C(O)[Pt]\n", - "kf = 6.089904416870865e-20\n", - "krev = 3.928023437111271\n", - "Kc = 1.550373747604081e-20\n", - "proton+O=C=CO.[Pt]<=>OC=C(O)[Pt]\n", - "kf = 6.4368819183992445e7\n", - "krev = 6.799608634080986e-11\n", - "Kc = 9.466547657075904e17\n", - "proton+OC=C(O)[Pt]<=>H2O+OC=C=[Pt]\n", - "kf = 5.262467142275111e-7\n", - "krev = 0.6251329939834178\n", - "Kc = 8.418156125054411e-7\n", - "proton+OC=C(O)[Pt]<=>OC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.835798651062412e-24\n", - "Kc = 3.190485247679302e33\n", - "vacantX+vacantX+OC=CO<=>HOX+OC=C[Pt]\n", - "kf = 1.882970379851619e-8\n", - "krev = 6.2613640604613945e13\n", - "Kc = 3.0072846134950095e-22\n", - "vacantX+vacantX+C=CO<=>HX+OC=C[Pt]\n", - "kf = 5.986889507133711e-22\n", - "krev = 1492.047811549125\n", - "Kc = 4.0125319448830507e-25\n", - "proton+OC=C[Pt]<=>OCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.693803965028289e7\n", - "Kc = 1475.967733939179\n", - "vacantX+vacantX+O=CC=CO<=>CHOX+OC=C[Pt]\n", - "kf = 3.6404040231768274e-5\n", - "krev = 5.1339082800935775e14\n", - "Kc = 7.090901949480236e-20\n", - "proton+OC=C=[Pt]<=>OC=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.9001266800545872e-45\n", - "Kc = 1.3157017509633512e55\n", - "vacantX+vacantX+OC=CCO<=>OC[Pt]+OC=C[Pt]\n", - "kf = 1.39754480380523e-13\n", - "krev = 4.435737343310229e14\n", - "Kc = 3.1506482364492156e-28\n", - "vacantX+vacantX+CC=CO<=>CH3X+OC=C[Pt]\n", - "kf = 3.0518560755450534e-15\n", - "krev = 1.440283576497463e15\n", - "Kc = 2.1189272205454667e-30\n", - "vacantX+vacantX+CC=C(O)O<=>OC(O)=[Pt]+CC=[Pt]\n", - "kf = 3.314404876424973e-50\n", - "krev = 3.298291971460818e17\n", - "Kc = 1.0048852269912959e-67\n", - "HX+O=C=CO<=>OC=CO[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 5.830973747204281e-42\n", - "Kc = 4.885709192226705e33\n", - "vacantX+vacantX+OC=CO<=>HX+OC=CO[Pt]\n", - "kf = 6.3392542923960805e-6\n", - "krev = 0.0008631955285686626\n", - "Kc = 0.007343937824733329\n", - "proton+O=C=CO.[Pt]<=>OC=CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.575140256117379e-26\n", - "Kc = 4.4841921192150256e35\n", - "proton+OC=CO[Pt]<=>OX+C=CO\n", - "kf = 2.262727495050209e-8\n", - "krev = 2.5678564004292932e-5\n", - "Kc = 0.0008811736881672694\n", - "proton+OC=CO[Pt]<=>OC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.711725523568878e-6\n", - "Kc = 6.73541182968781e15\n", - "proton+OC=COC#[Pt]<=>CX+OC=CO\n", - "kf = 2.2492341197526439e-29\n", - "krev = 0.00020529518482061674\n", - "Kc = 1.0956097785332785e-25\n", - "vacantX+vacantX+CCC(=O)O<=>CH3X+O=C(O)C[Pt]\n", - "kf = 8.997747599742267e-17\n", - "krev = 6.572577910715489e15\n", - "Kc = 1.368983026442782e-32\n", - "vacantX+vacantX+CCC(=O)O<=>CO2HX+CC[Pt]\n", - "kf = 3.388822996448631e-6\n", - "krev = 1.0293603282987281e15\n", - "Kc = 3.292163981148853e-21\n", - "vacantX+vacantX+CCC(=O)O<=>HOX+CCC(=O)[Pt]\n", - "kf = 2.1491486919570496e-14\n", - "krev = 4.131728096070369e12\n", - "Kc = 5.201573390081201e-27\n", - "vacantX+vacantX+CCC(=O)O<=>HX+CCC(=O)O[Pt]\n", - "kf = 2.415446383235281e-20\n", - "krev = 451.7273406124814\n", - "Kc = 5.347133472063615e-23\n", - "proton+O=C([Pt])C=CO<=>OCX+C=CO\n", - "kf = 224.18396606543615\n", - "krev = 8.215700647740584e-7\n", - "Kc = 2.728726078001508e8\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=C([Pt])C=CO\n", - "kf = 2.859565189776071e-11\n", - "krev = 0.000933578065584948\n", - "Kc = 3.06301668300697e-8\n", - "HX+O=C=C=CO<=>O=C([Pt])C=CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.1750295723598082e-43\n", - "Kc = 2.206855353748942e35\n", - "proton+O=C=C=CO.[Pt]<=>O=C([Pt])C=CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.234268290529092e-27\n", - "Kc = 2.0254915557527025e37\n", - "proton+OC=C(O)C#[Pt]<=>CX+OC=CO\n", - "kf = 2.8680661830740045e-24\n", - "krev = 729.307267106125\n", - "Kc = 3.932589612680575e-27\n", - "vacantX+vacantX+C=COO<=>OO[Pt]+C=C[Pt]\n", - "kf = 0.00256837059370255\n", - "krev = 1.2695573429161084e13\n", - "Kc = 2.0230441799526235e-16\n", - "vacantX+vacantX+C=COO<=>HOX+C=CO[Pt]\n", - "kf = 3.07907263663438e8\n", - "krev = 5.547742278067932e-15\n", - "Kc = 5.5501364019864025e22\n", - "vacantX+vacantX+C=COO<=>CH2X+OOC=[Pt]\n", - "kf = 7.483948884590266e-53\n", - "krev = 2.8103204909201245e17\n", - "Kc = 2.6630232775123643e-70\n", - "proton+OC=CC#[Pt]<=>CX+C=CO\n", - "kf = 1.0593841984272302e-19\n", - "krev = 13.369077699035607\n", - "Kc = 7.924138241066921e-21\n", - "proton+OCC[Pt]<=>CH2X+CO-2\n", - "kf = 3.9799160772985795e-6\n", - "krev = 0.00035437522440524626\n", - "Kc = 0.011230796633647675\n", - "vacantX+vacantX+OCCO<=>HOX+OCC[Pt]\n", - "kf = 2.110093084979835e-12\n", - "krev = 2.4085316622580622e14\n", - "Kc = 8.760910716040024e-27\n", - "HX+C=CO<=>OCC[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 1.1429411507382647e-15\n", - "Kc = 2.8609207088741057e7\n", - "HOX+C=C<=>OCC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 2.2750559854988554e-15\n", - "Kc = 3.602118089238167e7\n", - "proton+OCC=[Pt]<=>OCC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.1399343496076094e-34\n", - "Kc = 2.1931087530264836e44\n", - "vacantX+vacantX+CCO<=>HX+OCC[Pt]\n", - "kf = 4.51610258482867e-23\n", - "krev = 15472.547765874588\n", - "Kc = 2.918784063985339e-27\n", - "vacantX+vacantX+O=CCCO<=>CHOX+OCC[Pt]\n", - "kf = 2.0496526220764064\n", - "krev = 1.4633869198921762e15\n", - "Kc = 1.4006224835106677e-15\n", - "HX+C#C<=>C=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 2.375601900047824e-24\n", - "Kc = 3.580716650609497e16\n", - "CHOX+C#C<=>O=CC=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 3.2359557228060194e-16\n", - "Kc = 2.6287001452988416e8\n", - "HOX+C#C<=>OC=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 2.419253665005007e-25\n", - "Kc = 3.516108046777805e17\n", - "proton+OCCC#[Pt]<=>CX+CCO\n", - "kf = 0.036583470766554806\n", - "krev = 0.0005754138836916786\n", - "Kc = 63.577664361948486\n", - "OC[Pt]+C=C=O<=>O=C([Pt])CCO\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.869121889511259e-30\n", - "Kc = 1.7908695590280368e22\n", - "HX+O=C=CCO<=>O=C([Pt])CCO\n", - "kf = 2.5565910629172877e-8\n", - "krev = 3.7973012083800085e-37\n", - "Kc = 6.732652804247709e28\n", - "proton+O=C=CCO.[Pt]<=>O=C([Pt])CCO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.5089082544191712e-24\n", - "Kc = 1.6568270421201532e34\n", - "proton+O=C([Pt])CCO<=>OCX+CCO\n", - "kf = 9.600816617542319e7\n", - "krev = 3.185535798116408e-7\n", - "Kc = 3.0138781121904944e14\n", - "vacantX+vacantX+O=CCCO<=>HX+O=C([Pt])CCO\n", - "kf = 4.786286134347495e-11\n", - "krev = 0.0006355926831038164\n", - "Kc = 7.530429883135883e-8\n", - "vacantX+vacantX+C=COC<=>CO[Pt]+C=C[Pt]\n", - "kf = 1.9108708710628152e-14\n", - "krev = 5.750545812867103e12\n", - "Kc = 3.322938262290088e-27\n", - "vacantX+vacantX+C=COC<=>CH3X+C=CO[Pt]\n", - "kf = 8.809048609670953e-10\n", - "krev = 5.30334818480063e15\n", - "Kc = 1.6610353125441853e-25\n", - "vacantX+vacantX+C=COC<=>CH2X+COC=[Pt]\n", - "kf = 2.00333233616492e-67\n", - "krev = 2.0086736136424638e14\n", - "Kc = 9.973408932933319e-82\n", - "C=O+OC[Pt]<=>OCCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.726586049973397e-6\n", - "Kc = 0.00837955829095468\n", - "HX+O=CCO<=>OCCO[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 7.096612291679358e-6\n", - "Kc = 0.003946413774492056\n", - "vacantX+vacantX+OCCO<=>HX+OCCO[Pt]\n", - "kf = 1.0265256602604584e-26\n", - "krev = 112849.3186381155\n", - "Kc = 9.09642763154215e-32\n", - "proton+O=CCO.[Pt]<=>OCCO[Pt]\n", - "kf = 3.478307222117794e6\n", - "krev = 3581.5775849412535\n", - "Kc = 971.1662360023528\n", - "proton+OCCO[Pt]<=>OX+CCO\n", - "kf = 951266.6788585404\n", - "krev = 3.3388075163598663e-18\n", - "Kc = 2.8491210535420697e23\n", - "proton+OCCOC#[Pt]<=>CX+OCCO\n", - "kf = 6.336022152476698e-22\n", - "krev = 5.125095889500872e-13\n", - "Kc = 1.2362738744959868e-9\n", - "vacantX+vacantX+C=CC(O)O<=>OC(O)[Pt]+C=C[Pt]\n", - "kf = 1.3588265576828814e-16\n", - "krev = 6.093754170226661e16\n", - "Kc = 2.2298676968656565e-33\n", - "proton+O=C=C=C=[Pt]<=>O=C=CC#[Pt]\n", - "kf = 8.597534639917141e-9\n", - "krev = 2.1202950562509243e-60\n", - "Kc = 4.0548765204023916e51\n", - "vacantX+vacantX+O=C=C=C=O<=>OX+O=C=C=C=[Pt]\n", - "kf = 6.451439297868635e-57\n", - "krev = 8.482832416110645e14\n", - "Kc = 7.60528910793525e-72\n", - "proton+O=C=C=C(O)[Pt]<=>H2O+O=C=C=C=[Pt]\n", - "kf = 1.6149902683641734e-11\n", - "krev = 0.12950076972214764\n", - "Kc = 1.2470893198775887e-10\n", - "proton+O=C=C=C=[Pt]<=>O=C=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.039016761990757e-51\n", - "Kc = 6.189625216528679e60\n", - "vacantX+C=CO<=>C=CO.[Pt]\n", - "kf = 412885.969273148\n", - "krev = 1.1342794009872417\n", - "Kc = 364007.288604364\n", - "proton+C=CO[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.484544240591893e-27\n", - "Kc = 5.574702502366298e36\n", - "proton+OC=C[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.090002516938126e-28\n", - "Kc = 6.112465676112982e37\n", - "proton+C=CO.[Pt]<=>OCC[Pt]\n", - "kf = 1.7684909297990441e9\n", - "krev = 0.3339506079512917\n", - "Kc = 5.295666148501179e9\n", - "vacantX+vacantX+C=COCO<=>OCO[Pt]+C=C[Pt]\n", - "kf = 1.4197397308458187e-12\n", - "krev = 3.0290185667479297e13\n", - "Kc = 4.6871278586123213e-26\n", - "vacantX+vacantX+C=COCO<=>OC[Pt]+C=CO[Pt]\n", - "kf = 1.0263854075463885e-7\n", - "krev = 1.9545487277553856e14\n", - "Kc = 5.251265384031101e-22\n", - "HX+C=C=O<=>C=C(O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 3.2362559658776053e-12\n", - "Kc = 10343.290300064218\n", - "proton+C=C=O.[Pt]<=>C=C(O)[Pt]\n", - "kf = 0.5863133386822127\n", - "krev = 3624.832599039063\n", - "Kc = 0.00016174908017480404\n", - "vacantX+vacantX+C=CO<=>HX+C=C(O)[Pt]\n", - "kf = 4.00965787691315e-19\n", - "krev = 4.055766485027893\n", - "Kc = 9.886313454472895e-20\n", - "vacantX+vacantX+C=C(O)O<=>HOX+C=C(O)[Pt]\n", - "kf = 3.9452234947489745e-7\n", - "krev = 1.361002505571871e12\n", - "Kc = 2.8987628447394044e-19\n", - "proton+C=C(O)[Pt]<=>H2O+C=C=[Pt]\n", - "kf = 0.1408093188614318\n", - "krev = 0.006096548509334685\n", - "Kc = 23.09656334987455\n", - "proton+C=C(O)[Pt]<=>CC(O)=[Pt]\n", - "kf = 1.124057689749841e8\n", - "krev = 4.718570974473911e-12\n", - "Kc = 2.382199390092179e19\n", - "vacantX+vacantX+C=C(O)C=O<=>CHOX+C=C(O)[Pt]\n", - "kf = 2.8052009086647103\n", - "krev = 2.294429327232502e13\n", - "Kc = 1.2226137782366527e-13\n", - "proton+C=C(O)[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0077190030498644e-22\n", - "Kc = 2.4808503088993487e32\n", - "HOX+C=C=O<=>C=C(O)O[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.6625343699967689e-31\n", - "Kc = 2.0134040862236038e23\n", - "proton+C=C(O)O[Pt]<=>OX+C=CO\n", - "kf = 7.621772041144703e-10\n", - "krev = 0.16987445654378072\n", - "Kc = 4.4867087119601115e-9\n", - "vacantX+vacantX+C=C(O)O<=>HX+C=C(O)O[Pt]\n", - "kf = 8.7276566297004e-6\n", - "krev = 1.546723677424112e-6\n", - "Kc = 5.6426734503963205\n", - "vacantX+vacantX+C=CCOO<=>OOC[Pt]+C=C[Pt]\n", - "kf = 2.5331825038162864e-12\n", - "krev = 1.769892843246248e17\n", - "Kc = 1.4312632052740838e-29\n", - "proton+C=C(O)OC#[Pt]<=>CX+C=C(O)O\n", - "kf = 1.0744261387122509e-22\n", - "krev = 181.85749301564874\n", - "Kc = 5.908066370516815e-25\n", - "proton+C=C(O)C#[Pt]<=>CX+C=CO\n", - "kf = 3.691417083839596e-20\n", - "krev = 61.67110810051338\n", - "Kc = 5.985650651555046e-22\n", - "vacantX+vacantX+C=COOC<=>COO[Pt]+C=C[Pt]\n", - "kf = 0.0009962735751002543\n", - "krev = 4.495422962203487e13\n", - "Kc = 2.21619541359445e-17\n", - "vacantX+vacantX+C=COOC<=>CO[Pt]+C=CO[Pt]\n", - "kf = 2.772273774659678e8\n", - "krev = 3.7705323383409334e-17\n", - "Kc = 7.352473141443741e24\n", - "proton+C=C(O)C(=O)[Pt]<=>OCX+C=CO\n", - "kf = 985.1540455146012\n", - "krev = 5.159085449148215e-7\n", - "Kc = 1.9095517126533618e9\n", - "HOX+C=C=C=O<=>C=C(O)C(=O)[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 3.5720015577500406e-52\n", - "Kc = 8.264488540948707e43\n", - "vacantX+vacantX+C=C(O)C=O<=>HX+C=C(O)C(=O)[Pt]\n", - "kf = 2.8595651897765786e-11\n", - "krev = 0.000933577098423846\n", - "Kc = 3.063019856211522e-8\n", - "proton+C=COO[Pt]<=>OX+C=CO\n", - "kf = 43.93537738533433\n", - "krev = 6.669135249611683e-61\n", - "Kc = 6.587867203306832e61\n", - "O=O+C=C[Pt]<=>C=COO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 1.0833501613715598e-32\n", - "Kc = 7.082998693235901e24\n", - "vacantX+vacantX+C=COO<=>HX+C=COO[Pt]\n", - "kf = 4.552726448583842e-23\n", - "krev = 27.53540659037694\n", - "Kc = 1.6534081069915729e-24\n", - "vacantX+vacantX+C=COOC<=>CH3X+C=COO[Pt]\n", - "kf = 2.287071149777874e-9\n", - "krev = 2.2490557638427473e13\n", - "Kc = 1.0169028205286352e-22\n", - "vacantX+vacantX+CC(O)=CO<=>OC=[Pt]+CC(O)=[Pt]\n", - "kf = 7.128045206079291e-31\n", - "krev = 1.6024698052635947e11\n", - "Kc = 4.4481619451835966e-42\n", - "vacantX+vacantX+CC(O)=CO<=>CH3X+OC=C(O)[Pt]\n", - "kf = 1.2021042471738558e-26\n", - "krev = 3.79937896614338e12\n", - "Kc = 3.163949313521812e-39\n", - "proton+O=CC=C=[Pt]<=>O=CCC#[Pt]\n", - "kf = 62.9877146015209\n", - "krev = 8.316144406521062e-31\n", - "Kc = 7.574148730766316e31\n", - "vacantX+vacantX+O=C=CC=O<=>OX+O=CC=C=[Pt]\n", - "kf = 1.1758489216219413e-43\n", - "krev = 2.1453863988577092e16\n", - "Kc = 5.480825842132732e-60\n", - "proton+O=CC=C=[Pt]<=>O=CC=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.331702565774384e-47\n", - "Kc = 2.6790395240083815e56\n", - "proton+C=C=C=O.[Pt]<=>O=C=CC[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.2229421483387703e-16\n", - "Kc = 1.1246356554390213e26\n", - "vacantX+C=C=C=O<=>C=C=C=O.[Pt]\n", - "kf = 372758.92921022984\n", - "krev = 0.5077615475124772\n", - "Kc = 734122.012658058\n", - "proton+C=C=C=O.[Pt]<=>CC([Pt])=C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.123273247571115e-16\n", - "Kc = 1.1774273531962195e26\n", - "proton+C=C=C=O.[Pt]<=>C=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.171161147913428e-32\n", - "Kc = 4.834504144216726e41\n", - "proton+O=C=C=C[Pt]<=>C=C=C=O.[Pt]\n", - "kf = 3.820491632517615e9\n", - "krev = 3.925100397444825e-12\n", - "Kc = 9.733487670798667e20\n", - "vacantX+vacantX+C=C(C)O<=>CH2X+CC(O)=[Pt]\n", - "kf = 1.2526307828427685e-31\n", - "krev = 1.8291181793687947e14\n", - "Kc = 6.848276929132241e-46\n", - "vacantX+vacantX+C=C(C)O<=>CH3X+C=C(O)[Pt]\n", - "kf = 6.412809230790006e-14\n", - "krev = 6.896161957802356e13\n", - "Kc = 9.299098933624258e-28\n", - "HX+O=C=C=C=O<=>O=C=C=CO[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 6.474039280394542e-15\n", - "Kc = 8.128654665807662e6\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C=CO[Pt]\n", - "kf = 2.4048564698523636e10\n", - "krev = 0.03636685994081414\n", - "Kc = 6.612769080877996e11\n", - "proton+O=C=C=CO[Pt]<=>OX+C=C=C=O\n", - "kf = 7.675790818902377e-14\n", - "krev = 0.0006735755949001122\n", - "Kc = 1.1395589265731426e-10\n", - "vacantX+vacantX+O=C=C=CO<=>HX+O=C=C=CO[Pt]\n", - "kf = 4.194899212644372e-10\n", - "krev = 0.014508998351933198\n", - "Kc = 2.891239705796395e-8\n", - "proton+O=C=C=CO[Pt]<=>O=C=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4612716650323904e-11\n", - "Kc = 1.71083862078759e21\n", - "proton+CC(O)[Pt]<=>OC=[Pt]+CH4\n", - "kf = 59.397807135376084\n", - "krev = 1.2803453253139382e-6\n", - "Kc = 4.639202093451769e7\n", - "HX+C=CO<=>CC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 1.2254518112062234e-21\n", - "Kc = 2.668292606261641e13\n", - "HX+CC=O<=>CC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 2.4645381117653586e-12\n", - "Kc = 13267.654460532101\n", - "vacantX+vacantX+CCO<=>HX+CC(O)[Pt]\n", - "kf = 1.7361137032745595e-19\n", - "krev = 63.774720976875884\n", - "Kc = 2.72225997492652e-21\n", - "vacantX+vacantX+CC(O)O<=>HOX+CC(O)[Pt]\n", - "kf = 7.380915652046712e-14\n", - "krev = 2.775462823415347e13\n", - "Kc = 2.6593458899096773e-27\n", - "proton+CC=O.[Pt]<=>CC(O)[Pt]\n", - "kf = 36132.65188770086\n", - "krev = 0.006356177292382113\n", - "Kc = 5.68465135971048e6\n", - "proton+CC(O)[Pt]<=>H2O+CC=[Pt]\n", - "kf = 2964.0563969386994\n", - "krev = 0.019559355499681682\n", - "Kc = 151541.61889367664\n", - "proton+CC(O)=[Pt]<=>CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.860369956892034e-19\n", - "Kc = 5.143641373338227e28\n", - "vacantX+vacantX+CC(O)C=O<=>CHOX+CC(O)[Pt]\n", - "kf = 753631.9525109725\n", - "krev = 9.011518944421836e14\n", - "Kc = 8.362984721654206e-10\n", - "proton+C=CO.[Pt]<=>CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.061646123775542e-6\n", - "Kc = 4.939104668453628e15\n", - "HX+C#CC=O<=>O=CC=C[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 1.9866745274914506e-30\n", - "Kc = 1.4859387148609413e22\n", - "proton+CC(O)C#[Pt]<=>CX+CCO\n", - "kf = 1.3617819786307934\n", - "krev = 4.084110860281074e-5\n", - "Kc = 33343.413663777814\n", - "O=CO+CH3X<=>CC(O)O[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 7.324156308451427e-7\n", - "Kc = 0.043678018970166745\n", - "HOX+CC=O<=>CC(O)O[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 7.587328136505701e-13\n", - "Kc = 43096.38318446866\n", - "HX+CC(=O)O<=>CC(O)O[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 4598.938099177113\n", - "Kc = 6.089703295881323e-12\n", - "proton+CC(O)O[Pt]<=>OX+CCO\n", - "kf = 1.6583777607664147e6\n", - "krev = 1.6983423991371652e-6\n", - "Kc = 9.764684445309413e11\n", - "vacantX+vacantX+CC(O)O<=>HX+CC(O)O[Pt]\n", - "kf = 4.052122584605618e-24\n", - "krev = 469.09529347560436\n", - "Kc = 8.638165082797514e-27\n", - "proton+CC(=O)O.[Pt]<=>CC(O)O[Pt]\n", - "kf = 0.7475019896975738\n", - "krev = 3555.8603422114556\n", - "Kc = 0.00021021691454639312\n", - "vacantX+vacantX+OC=C=CO<=>OC=[Pt]+OC=C=[Pt]\n", - "kf = 3.0449395213240036e-51\n", - "krev = 1.4315520101841116e12\n", - "Kc = 2.1270198355785863e-63\n", - "CH3X+O=C=CO<=>CC(O)C(=O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 4.477216581188038e-53\n", - "Kc = 6.362980552705156e44\n", - "proton+CC(O)C(=O)[Pt]<=>OCX+CCO\n", - "kf = 9.570476890072168e7\n", - "krev = 4.96015815008412e-7\n", - "Kc = 1.929470109720163e14\n", - "HOX+CC=C=O<=>CC(O)C(=O)[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 3.536759710167166e-36\n", - "Kc = 8.195394062368554e27\n", - "HX+CC(O)=C=O<=>CC(O)C(=O)[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 4.830700359768998e-42\n", - "Kc = 5.292381792522405e33\n", - "vacantX+vacantX+CC(O)C=O<=>HX+CC(O)C(=O)[Pt]\n", - "kf = 4.786286134353719e-11\n", - "krev = 0.0006355923790078162\n", - "Kc = 7.530433486042254e-8\n", - "proton+CC(O)=C=O.[Pt]<=>CC(O)C(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.368412782384192e-31\n", - "Kc = 1.8269341182594315e41\n", - "proton+CC(O)OC#[Pt]<=>CX+CC(O)O\n", - "kf = 2.7873525673015004e-16\n", - "krev = 1.8374709107747412e-8\n", - "Kc = 1.516950581887719e-8\n", - "vacantX+vacantX+CCOC<=>CO[Pt]+CC[Pt]\n", - "kf = 2.3627317133785774e-11\n", - "krev = 3.856091265609508e13\n", - "Kc = 6.127271246016828e-25\n", - "vacantX+vacantX+CCOC<=>CH3X+CCO[Pt]\n", - "kf = 6.326940367296449e-9\n", - "krev = 1.8372911814097844e13\n", - "Kc = 3.443624195943553e-22\n", - "vacantX+vacantX+CCOC<=>CH3X+COC[Pt]\n", - "kf = 1.3389399016858639e-14\n", - "krev = 2.773400746132106e14\n", - "Kc = 4.8277909478217395e-29\n", - "proton+O=C=C(O)C[Pt]<=>CH2X+O=C=CO\n", - "kf = 4.2042874371743854e-22\n", - "krev = 1.1101526849597185\n", - "Kc = 3.787125405481442e-22\n", - "HOX+C=C=C=O<=>O=C=C(O)C[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 6.322264310888409e-36\n", - "Kc = 4.669334354059592e27\n", - "vacantX+vacantX+CC(O)=C=O<=>HX+O=C=C(O)C[Pt]\n", - "kf = 6.004181315465852e-13\n", - "krev = 0.19478740167193392\n", - "Kc = 3.082427951669201e-12\n", - "proton+O=C=C(O)C[Pt]<=>CC(O)=C=O.[Pt]\n", - "kf = 1.859235052213257e9\n", - "krev = 4.357618832801525e-11\n", - "Kc = 4.266630753057283e19\n", - "proton+O=C=C(O)C=[Pt]<=>CHX+O=C=CO\n", - "kf = 1.807627844430322e-6\n", - "krev = 0.0010238577171457239\n", - "Kc = 0.0017655068806528764\n", - "proton+O=C=C(O)C#[Pt]<=>O=C=C(O)C=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.347883511420028\n", - "Kc = 7.467404380923659e9\n", - "proton+O=C=C(O)C=[Pt]<=>O=C=C(O)C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4404183806094484e-33\n", - "Kc = 1.735606844271341e43\n", - "vacantX+vacantX+CCCO<=>OC[Pt]+CC[Pt]\n", - "kf = 4.648157058598011e-13\n", - "krev = 1.3999921584371802e15\n", - "Kc = 3.3201307811515004e-28\n", - "vacantX+vacantX+CCCO<=>CH3X+OCC[Pt]\n", - "kf = 1.2211065235504926e-16\n", - "krev = 1.2627143633797795e15\n", - "Kc = 9.670488900451568e-32\n", - "proton+CC([Pt])OC=O<=>CH4+O=COC=[Pt]\n", - "kf = 1.0679856406424377e-15\n", - "krev = 0.2905260385078575\n", - "Kc = 3.6760410396521245e-15\n", - "CHOX+CC=O<=>CC([Pt])OC=O\n", - "kf = 3.269864007171502e-8\n", - "krev = 0.48922244404245907\n", - "Kc = 6.68379802887317e-8\n", - "HX+C=COC=O<=>CC([Pt])OC=O\n", - "kf = 2.5565910629172877e-8\n", - "krev = 1.2259112200812889e-16\n", - "Kc = 2.0854618352769157e8\n", - "vacantX+vacantX+CCOC=O<=>HX+CC([Pt])OC=O\n", - "kf = 6.519502059052115e-22\n", - "krev = 142.86665816232104\n", - "Kc = 4.563347489828482e-24\n", - "proton+CC([Pt])OC=O<=>O=CO+CC=[Pt]\n", - "kf = 8049.244255788158\n", - "krev = 0.00029431628636694825\n", - "Kc = 2.7348959703006394e7\n", - "proton+CC(=[Pt])OC=O<=>CH4+O=COC#[Pt]\n", - "kf = 4.771264023974434e9\n", - "krev = 10.578082715743388\n", - "Kc = 4.510518732164335e8\n", - "proton+CC(=[Pt])OC=O<=>O=CO+CC#[Pt]\n", - "kf = 7292.02651577905\n", - "krev = 8.53932827082491e-43\n", - "Kc = 8.539344412712957e45\n", - "proton+CC(=[Pt])OC=O<=>CC([Pt])OC=O\n", - "kf = 2.5e10\n", - "krev = 2.5945295399651927e-47\n", - "Kc = 9.635658262860014e56\n", - "vacantX+vacantX+CCC(O)O<=>OC(O)[Pt]+CC[Pt]\n", - "kf = 3.712816041087776e-19\n", - "krev = 9.367983662004229e16\n", - "Kc = 3.9633032838716965e-36\n", - "vacantX+O=CC=CO<=>O=CC=CO.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 0.8868529608572997\n", - "Kc = 364007.2889878057\n", - "proton+O=CC=CO[Pt]<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.467206835324098e-11\n", - "Kc = 1.703917907012588e21\n", - "proton+O=C([Pt])C=CO<=>O=CC=CO.[Pt]\n", - "kf = 3.672999120067293e9\n", - "krev = 4.587068754429701e-12\n", - "Kc = 8.00729031262133e20\n", - "HX+O=C=CC=O<=>O=CC=C(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.0473065138531246e-21\n", - "Kc = 2.475989854235963e13\n", - "proton+O=C=CC=O.[Pt]<=>O=CC=C(O)[Pt]\n", - "kf = 9.946079261837086e6\n", - "krev = 6.687641252513296e-9\n", - "Kc = 1.4872327755468685e15\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC=C(O)[Pt]\n", - "kf = 2.77963678004065e-20\n", - "krev = 3.601218827022036\n", - "Kc = 7.718600045027592e-21\n", - "proton+O=CC=C(O)[Pt]<=>H2O+O=CC=C=[Pt]\n", - "kf = 2.367383825493301e-13\n", - "krev = 16.1722227709439\n", - "Kc = 1.463858035487058e-14\n", - "proton+O=CC=C(O)[Pt]<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.867624236214861e-24\n", - "Kc = 3.177579311035777e33\n", - "vacantX+vacantX+CCOCO<=>OCO[Pt]+CC[Pt]\n", - "kf = 2.4512530384253315e-9\n", - "krev = 3.614837695546209e14\n", - "Kc = 6.781087409389048e-24\n", - "vacantX+vacantX+CCOCO<=>OC[Pt]+CCO[Pt]\n", - "kf = 1.0293700832173347e-6\n", - "krev = 1.2050997101819434e12\n", - "Kc = 8.541783509863451e-19\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC([Pt])=CO\n", - "kf = 4.3007284274917255e-15\n", - "krev = 1.9561961334382385\n", - "Kc = 2.1985159636997663e-15\n", - "HX+O=C=C=CO<=>O=CC([Pt])=CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.6370748462102965e-36\n", - "Kc = 1.5839961798805036e28\n", - "proton+O=CC([Pt])=CO<=>C=O+OC=C=[Pt]\n", - "kf = 4.3296354594819855e-33\n", - "krev = 908.9754469679581\n", - "Kc = 4.76320397203711e-36\n", - "proton+O=C=C=CO.[Pt]<=>O=CC([Pt])=CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.7196074204687593e-20\n", - "Kc = 1.4538201977044896e30\n", - "HOX+C#CC=O<=>O=CC([Pt])=CO\n", - "kf = 2.952076594227614e-8\n", - "krev = 4.790462195255654e-44\n", - "Kc = 6.162404531970363e35\n", - "proton+O=CC([Pt])=CO<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.2409630475480663e-18\n", - "Kc = 1.1155918000233681e28\n", - "proton+OC=CC=[Pt]<=>CHX+C=CO\n", - "kf = 0.3708119772368373\n", - "krev = 1.9743851754031655e-5\n", - "Kc = 18781.136621992628\n", - "vacantX+vacantX+O=CC=CO<=>OX+OC=CC=[Pt]\n", - "kf = 8.803023976547135e-28\n", - "krev = 1.526615583505237e17\n", - "Kc = 5.766365856383213e-45\n", - "proton+OC=CC#[Pt]<=>OC=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4263979915391943e-8\n", - "Kc = 1.7526665172195773e18\n", - "vacantX+vacantX+CCCOO<=>OOC[Pt]+CC[Pt]\n", - "kf = 5.56726706794292e-16\n", - "krev = 4.282042054393877e17\n", - "Kc = 1.3001430152303739e-33\n", - "proton+OCC(O)[Pt]<=>OC=[Pt]+CO-2\n", - "kf = 0.16339719354915763\n", - "krev = 6.17359485423602e-8\n", - "Kc = 2.6467106670766133e6\n", - "HX+O=CCO<=>OCC(O)[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 4.347223516290618e-14\n", - "Kc = 644231.1603064304\n", - "vacantX+vacantX+OCCO<=>HX+OCC(O)[Pt]\n", - "kf = 7.314142036323851e-21\n", - "krev = 492.5535033039904\n", - "Kc = 1.4849436634317805e-23\n", - "HX+OC=CO<=>OCC(O)[Pt]\n", - "kf = 5.6012337000223925e-8\n", - "krev = 1.5412075197181771e-21\n", - "Kc = 3.634315060340885e13\n", - "HOX+C=CO<=>OCC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 6.743155058263278e-19\n", - "Kc = 4.8491603395127426e10\n", - "proton+O=CCO.[Pt]<=>OCC(O)[Pt]\n", - "kf = 698182.0065765544\n", - "krev = 4.403884986144656e-6\n", - "Kc = 1.5853774764171848e11\n", - "proton+OCC(O)[Pt]<=>H2O+OCC=[Pt]\n", - "kf = 0.7285659975205578\n", - "krev = 0.0004743003964980969\n", - "Kc = 1536.0855755124403\n", - "proton+OC=CO.[Pt]<=>OCC(O)[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 1.4989628309182922e-5\n", - "Kc = 3.3356397482764175e15\n", - "proton+OCC(O)C#[Pt]<=>CX+OCCO\n", - "kf = 5.26000051169577\n", - "krev = 0.00019971123776726528\n", - "Kc = 26338.02969978857\n", - "vacantX+vacantX+CCC<=>CH3X+CC[Pt]\n", - "kf = 7.798842461270165e-20\n", - "krev = 4.754727023110295e15\n", - "Kc = 1.640229275700578e-35\n", - "proton+O=C([Pt])CO<=>OCC(O)=[Pt]\n", - "kf = 4.019918430047713e-18\n", - "krev = 1.0085447542339827e12\n", - "Kc = 3.9858602339377106e-30\n", - "proton+OCC(O)=[Pt]<=>H2O+OCC#[Pt]\n", - "kf = 16209.61875952926\n", - "krev = 4.634124941714537e-41\n", - "Kc = 3.4978812533984058e44\n", - "proton+OCC(O)=[Pt]<=>OC#[Pt]+CO-2\n", - "kf = 382.95023851607715\n", - "krev = 3.536410198453644e-35\n", - "Kc = 1.0828784474253827e37\n", - "proton+OC=C(O)[Pt]<=>OCC(O)=[Pt]\n", - "kf = 6875.768524790738\n", - "krev = 1.0085447542339824e12\n", - "Kc = 6.8175145385720384e-9\n", - "proton+OCC(O)=[Pt]<=>OCC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.6015120113778689e-47\n", - "Kc = 1.5610248204439706e57\n", - "HX+COC=O<=>COC(O)[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 224.3395816271696\n", - "Kc = 1.2483828443014824e-10\n", - "proton+COC(O)[Pt]<=>OC=[Pt]+CO-2\n", - "kf = 564390.3708916149\n", - "krev = 3.282828318007529e-12\n", - "Kc = 1.7192198806002883e17\n", - "vacantX+vacantX+COCO<=>HX+COC(O)[Pt]\n", - "kf = 6.183244140051347e-23\n", - "krev = 2731.92216309053\n", - "Kc = 2.2633310068601865e-26\n", - "O=CO+CH3X<=>COC(O)[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 8.503469161971292e7\n", - "Kc = 3.7620485485108396e-16\n", - "proton+COC=O.[Pt]<=>COC(O)[Pt]\n", - "kf = 7.49969185016536e-5\n", - "krev = 3658.0165064396892\n", - "Kc = 2.0502072193940793e-8\n", - "proton+COC(O)[Pt]<=>H2O+COC=[Pt]\n", - "kf = 5.10646151413012e-10\n", - "krev = 0.003546985366877098\n", - "Kc = 1.439662413557134e-7\n", - "vacantX+vacantX+CCOOC<=>COO[Pt]+CC[Pt]\n", - "kf = 1.4778859852656565e-10\n", - "krev = 2.404289853338368e13\n", - "Kc = 6.146871115450596e-24\n", - "vacantX+vacantX+CCOOC<=>CO[Pt]+CCO[Pt]\n", - "kf = 2.735304068777078e8\n", - "krev = 1.1929824589169815e-11\n", - "Kc = 2.2928284052560617e19\n", - "vacantX+vacantX+CCOOC<=>CH3X+CCOO[Pt]\n", - "kf = 1.542530561493995e-10\n", - "krev = 1.2789927244807063e12\n", - "Kc = 1.2060510837700736e-22\n", - "proton+COC(O)C#[Pt]<=>CX+COCO\n", - "kf = 0.03928313633337953\n", - "krev = 0.002914319669063903\n", - "Kc = 13.479350515448948\n", - "proton+COC(=O)[Pt]<=>COC(O)=[Pt]\n", - "kf = 6.005930457604258e-17\n", - "krev = 1.0085447542339825e12\n", - "Kc = 5.955046052632466e-29\n", - "proton+COC(O)=[Pt]<=>OC#[Pt]+CO-2\n", - "kf = 383854.3090963643\n", - "krev = 3.448448528690976e-34\n", - "Kc = 1.113121758677009e39\n", - "proton+COC(O)=[Pt]<=>H2O+COC#[Pt]\n", - "kf = 217922.49486435574\n", - "krev = 2.0340320286285714e-35\n", - "Kc = 1.0713818258372662e40\n", - "proton+COC(O)=[Pt]<=>COC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0120272229346644e-38\n", - "Kc = 2.4702892801149458e48\n", - "vacantX+vacantX+C=C=COO<=>OOC=[Pt]+C=C=[Pt]\n", - "kf = 1.9145907695639512e-44\n", - "krev = 1.1771971588384226e12\n", - "Kc = 1.626397715275781e-56\n", - "C=O+O=CC[Pt]<=>O=CCCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 0.0025285011306884937\n", - "Kc = 1.5664103465194285e-5\n", - "HX+O=CCC=O<=>O=CCCO[Pt]\n", - "kf = 5.113182125834635e-8\n", - "krev = 3.03538509820146e-7\n", - "Kc = 0.16845250142607343\n", - "proton+O=CCC=O.[Pt]<=>O=CCCO[Pt]\n", - "kf = 2.3901708430508703e8\n", - "krev = 41.103568870106145\n", - "Kc = 5.814995896351951e6\n", - "vacantX+vacantX+O=CCCO<=>HX+O=CCCO[Pt]\n", - "kf = 2.5157725911236352e-27\n", - "krev = 8837.406478086354\n", - "Kc = 2.84673178421957e-31\n", - "proton+O=CCCO[Pt]<=>OX+CCC=O\n", - "kf = 774927.4661784222\n", - "krev = 1.1978583087682196e-18\n", - "Kc = 6.469274875884902e23\n", - "CHOX+C=C<=>O=CCC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 0.4688595936220698\n", - "Kc = 1.7478623517301195e-7\n", - "proton+O=CCC[Pt]<=>CH2X+CC=O\n", - "kf = 0.0016740956920828355\n", - "krev = 4.373185000711893e-7\n", - "Kc = 3828.0925499614495\n", - "HX+C=CC=O<=>O=CCC[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 7.666152073113618e-12\n", - "Kc = 3780.924152337611\n", - "proton+O=CCC=[Pt]<=>O=CCC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3932958912707058e-30\n", - "Kc = 1.794306590339518e40\n", - "vacantX+vacantX+O=CCCO<=>HOX+O=CCC[Pt]\n", - "kf = 8.901266563864654e-15\n", - "krev = 1.309728963703428e15\n", - "Kc = 6.79626610584771e-30\n", - "vacantX+vacantX+CCC=O<=>HX+O=CCC[Pt]\n", - "kf = 1.6716561102658422e-25\n", - "krev = 524619.2678123232\n", - "Kc = 3.186417680076247e-31\n", - "vacantX+vacantX+CC=COO<=>OOC=[Pt]+CC=[Pt]\n", - "kf = 3.7147962989308654e-50\n", - "krev = 4.0636001726377395e18\n", - "Kc = 9.141638303749602e-69\n", - "proton+C=COOC#[Pt]<=>CX+C=COO\n", - "kf = 8.811176921711816e-67\n", - "krev = 2.5e10\n", - "Kc = 3.5244707686847265e-77\n", - "vacantX+C=CC=O<=>C=CC=O.[Pt]\n", - "kf = 365995.57053717994\n", - "krev = 1.0054621985249468\n", - "Kc = 364007.290452202\n", - "proton+C=CC(=O)[Pt]<=>C=CC=O.[Pt]\n", - "kf = 3.399604827397095e9\n", - "krev = 5.959510760846119e-12\n", - "Kc = 5.704503211458966e20\n", - "proton+O=CC=C[Pt]<=>C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.32808736312024e-27\n", - "Kc = 3.00188973889839e36\n", - "proton+C=CC=O.[Pt]<=>O=CCC[Pt]\n", - "kf = 5.197601136262071e7\n", - "krev = 74.26603000820454\n", - "Kc = 699862.5260684955\n", - "vacantX+vacantX+C=CC=O<=>HX+C=C([Pt])C=O\n", - "kf = 1.2784478936507186e-21\n", - "krev = 132.59733776930153\n", - "Kc = 9.641580405445367e-24\n", - "proton+C=C([Pt])C=O<=>C=O+C=C=[Pt]\n", - "kf = 2.4079500300331376e-13\n", - "krev = 0.010970404022735962\n", - "Kc = 2.194951092997765e-11\n", - "HX+C=C=C=O<=>C=C([Pt])C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.4992009477647154e-32\n", - "Kc = 1.1812081765045545e24\n", - "vacantX+vacantX+C=C(O)C=O<=>HOX+C=C([Pt])C=O\n", - "kf = 1.107119853181277e-14\n", - "krev = 2.5289157654010746e13\n", - "Kc = 4.377843929513773e-28\n", - "proton+C=C=C=O.[Pt]<=>C=C([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.305987527913534e-16\n", - "Kc = 1.0841342243780513e26\n", - "HX+C#CC=O<=>C=C([Pt])C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 1.683521621093348e-30\n", - "Kc = 1.753512730243651e22\n", - "proton+C=C([Pt])C=O<=>C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.827731832923639e-27\n", - "Kc = 2.5438219545478565e36\n", - "CHOX+C=C=O<=>C=C(C=O)O[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.906984656058423e-6\n", - "Kc = 0.017553122325364576\n", - "proton+C=C(C=O)O[Pt]<=>OX+C=CC=O\n", - "kf = 13.565263195704604\n", - "krev = 7.179044500174065e-6\n", - "Kc = 1.8895638821260543e6\n", - "vacantX+vacantX+C=C(O)C=O<=>HX+C=C(C=O)O[Pt]\n", - "kf = 8.336773502217888e-19\n", - "krev = 4.018028855986407\n", - "Kc = 2.0748416203624424e-19\n", - "vacantX+vacantX+COCOC<=>CH3X+COCO[Pt]\n", - "kf = 0.24675966205104702\n", - "krev = 5.277017405064255e15\n", - "Kc = 4.6761199198288865e-17\n", - "vacantX+vacantX+COCOC<=>CO[Pt]+COC[Pt]\n", - "kf = 4.1241018831024145e-7\n", - "krev = 7.782310155024181e12\n", - "Kc = 5.2993286067375974e-20\n", - "proton+C=CC=[Pt]<=>CHX+C=C\n", - "kf = 1.3385165927063483e6\n", - "krev = 9.028119675350497e-7\n", - "Kc = 1.4826083845132273e12\n", - "vacantX+vacantX+C=CC=O<=>OX+C=CC=[Pt]\n", - "kf = 1.438969400016978e-30\n", - "krev = 1.6093339940290013e17\n", - "Kc = 8.941396909254915e-48\n", - "proton+C=CC#[Pt]<=>C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.067052266556579e-6\n", - "Kc = 2.342903040792558e16\n", - "vacantX+CC(O)O<=>CC(O)O.[Pt]\n", - "kf = 347843.58123444836\n", - "krev = 178209.4487483253\n", - "Kc = 1.9518806868971765\n", - "proton+CC(O)O[Pt]<=>CC(O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.64203868551119e-24\n", - "Kc = 1.5224976257010135e34\n", - "vacantX+vacantX+COCCO<=>OC[Pt]+COC[Pt]\n", - "kf = 1.3358759661274015e-7\n", - "krev = 3.1165281946439875e14\n", - "Kc = 4.286423490161954e-22\n", - "vacantX+vacantX+COCCO<=>CO[Pt]+OCC[Pt]\n", - "kf = 6.192873660096324e-8\n", - "krev = 3.90827625278604e13\n", - "Kc = 1.584553716150872e-21\n", - "vacantX+vacantX+COCCO<=>CH3X+OCCO[Pt]\n", - "kf = 4.52195120819324e-12\n", - "krev = 5.920081591014324e14\n", - "Kc = 7.638325821483257e-27\n", - "proton+OC(O)C[Pt]<=>CH2X+OCO\n", - "kf = 2.252975678309519e-7\n", - "krev = 0.002613777215265548\n", - "Kc = 8.619616335895816e-5\n", - "HOX+C=CO<=>OC(O)C[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 6.095879365149742e-19\n", - "Kc = 5.364056293281289e10\n", - "HX+C=C(O)O<=>OC(O)C[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 1.7806643358524245e-19\n", - "Kc = 1.572793251160735e11\n", - "vacantX+vacantX+CC(O)O<=>HX+OC(O)C[Pt]\n", - "kf = 2.610914590914038e-25\n", - "krev = 48838.0104312493\n", - "Kc = 5.3460707507516085e-30\n", - "vacantX+vacantX+CCC(O)O<=>CH3X+OC(O)C[Pt]\n", - "kf = 2.73273606062798e-19\n", - "krev = 1.7143250273592365e15\n", - "Kc = 1.594059479396106e-34\n", - "proton+OC(O)C[Pt]<=>CC(O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0162407066861682e-27\n", - "Kc = 2.4600470966688416e37\n" - ] - } - ], - "source": [ - "for (i,rxn) in enumerate(inter.reactions)\n", - " str = getrxnstr(rxn)\n", - " kf = inter.kfs[i]\n", - " krev = inter.krevs[i]\n", - " Kc = kf/krev\n", - " println(str)\n", - " println(\"kf = $kf\")\n", - " println(\"krev = $krev\")\n", - " println(\"Kc = $Kc\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "dd1b08a5", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "vacantX+CO2<=>CO2X\n", - "kf = 20654.615923781494\n", - "krev = 11189.298481041604\n", - "Kc = 1.8459259048971917\n", - "proton+CO2X<=>CHO2X\n", - "kf = 5.164749496653815e7\n", - "krev = 3.369038128826839e8\n", - "Kc = 0.1533004168893831\n", - "proton+CO2X<=>CO2HX\n", - "kf = 463658.8965294065\n", - "krev = 1.20318988446587e-5\n", - "Kc = 3.853580407511801e10\n", - "proton+CHO2X<=>CH2O2X\n", - "kf = 2.5e10\n", - "krev = 9.108706843764319e-26\n", - "Kc = 2.7446266993557504e35\n", - "proton+CO2HX<=>CH2O2X\n", - "kf = 1.9190551016885178e10\n", - "krev = 1.757621070775451e-14\n", - "Kc = 1.0918480289052538e24\n", - "proton+OCX<=>CHOX\n", - "kf = 2.5e10\n", - "krev = 2.604453583293511e-10\n", - "Kc = 9.59894242706594e19\n", - "proton+CHOX<=>CH2OX\n", - "kf = 1.7890196451453958e9\n", - "krev = 4.957912234830633e-11\n", - "Kc = 3.608413300616868e19\n", - "vacantX+vacantX+CO2<=>OX+OCX\n", - "kf = 3.0109478093923404e-24\n", - "krev = 3.037156297092479e15\n", - "Kc = 9.913707148607306e-40\n", - "OX+proton<=>HOX\n", - "kf = 2.5e10\n", - "krev = 4.7547181516587526e-14\n", - "Kc = 5.25793521352646e23\n", - "vacantX+C=O<=>CH2OX\n", - "kf = 500114.13488002896\n", - "krev = 399.6803280141717\n", - "Kc = 1251.2853393732605\n", - "proton+CHO2X<=>OX+C=O\n", - "kf = 7.971946163368602e-7\n", - "krev = 8.220582009654122e-5\n", - "Kc = 0.009697544716428197\n", - "HX+CO2<=>CHO2X\n", - "kf = 6.542996392927688e-8\n", - "krev = 15.579156394796986\n", - "Kc = 4.199839983064083e-9\n", - "HX+CO2<=>CO2HX\n", - "kf = 6.542996392927688e-8\n", - "krev = 6.197590078701277e-11\n", - "Kc = 1055.7323588427441\n", - "vacantX+vacantX+C=O<=>HX+CHOX\n", - "kf = 2.0718885766149262e-11\n", - "krev = 0.008867505326838887\n", - "Kc = 2.336495440655708e-9\n", - "vacantX+O=CO<=>CH2O2X\n", - "kf = 403943.82249737746\n", - "krev = 29.756334575496034\n", - "Kc = 13575.053119278344\n", - "vacantX+vacantX+O=CO<=>HOX+CHOX\n", - "kf = 8.486192390111145e-15\n", - "krev = 9.7037034735699e11\n", - "Kc = 8.745312975839684e-27\n", - "vacantX+vacantX+O=CO<=>HX+CHO2X\n", - "kf = 1.2668346793097018e-21\n", - "krev = 380.13410282264914\n", - "Kc = 3.332599390328158e-24\n", - "vacantX+vacantX+O=CO<=>HX+CO2HX\n", - "kf = 9.840171155787102e-15\n", - "krev = 0.011746228705195169\n", - "Kc = 8.377302539184302e-13\n", - "proton+CH2OX<=>CO[Pt]\n", - "kf = 4.612846333154699e7\n", - "krev = 90.4105198560361\n", - "Kc = 510211.23874742666\n", - "HX+C=O<=>CO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.180104845075902e-9\n", - "Kc = 9.475050217848336\n", - "proton+CO2HX<=>H2O+OCX\n", - "kf = 2.5e10\n", - "krev = 4.0258346788129556e-7\n", - "Kc = 6.20989235637749e16\n", - "vacantX+vacantX+H2O<=>HX+HOX\n", - "kf = 1.7047654949014593e-31\n", - "krev = 21441.30602897437\n", - "Kc = 7.950847269274322e-36\n", - "proton+CH2OX<=>OC[Pt]\n", - "kf = 1.2443063594454413e6\n", - "krev = 1.1005987164187474e-6\n", - "Kc = 1.1305722429827158e12\n", - "HX+C=O<=>OC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.886422105564557e-15\n", - "Kc = 2.099567387708916e7\n", - "vacantX+vacantX+O=CC=O<=>CHOX+CHOX\n", - "kf = 3.132095071630788e8\n", - "krev = 159.05427897483804\n", - "Kc = 1.9691988746346629e6\n", - "proton+CH2O2X<=>OC(O)[Pt]\n", - "kf = 1.9695177200694968e-5\n", - "krev = 3718.799864740736\n", - "Kc = 5.296111088803661e-9\n", - "HX+O=CO<=>OC(O)[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 29981.045237801853\n", - "Kc = 1.0670229661561413e-12\n", - "proton+CH2O2X<=>OCO[Pt]\n", - "kf = 1.3800914441571782e-5\n", - "krev = 3681.751563599994\n", - "Kc = 3.748464339097702e-9\n", - "HOX+C=O<=>OCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.962949149852605e-13\n", - "Kc = 201771.41789913058\n", - "HX+O=CO<=>OCO[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 42359.465576793365\n", - "Kc = 7.552140562327293e-13\n", - "vacantX+H2O<=>H2OX\n", - "kf = 4.842414926683719e6\n", - "krev = 2.0721934488233277e8\n", - "Kc = 0.023368546645263413\n", - "proton+HOX<=>H2OX\n", - "kf = 2.5e10\n", - "krev = 1.2623996335027457e-31\n", - "Kc = 1.9803554545269617e41\n", - "vacantX+vacantX+H2<=>HX+HX\n", - "kf = 3.8736093818093735e10\n", - "krev = 4.9917087254698525e28\n", - "Kc = 7.760086965901168e-19\n", - "proton+CHOX<=>OC=[Pt]\n", - "kf = 3.6460821201937575e9\n", - "krev = 3.454391742229775e10\n", - "Kc = 0.10554917890812951\n", - "vacantX+vacantX+O=CO<=>OX+OC=[Pt]\n", - "kf = 1.3995006080437096e-36\n", - "krev = 7.971831424002446e14\n", - "Kc = 1.755557203367275e-51\n", - "proton+OC=[Pt]<=>OC[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.468152848309303e-23\n", - "Kc = 3.8650910988497585e32\n", - "proton+OC(O)[Pt]<=>H2O+OC=[Pt]\n", - "kf = 6.989877198043828e9\n", - "krev = 6.424310280494338e-11\n", - "Kc = 1.0880354299303816e20\n", - "proton+O=CC(=O)[Pt]<=>OCX+C=O\n", - "kf = 2.302032083373261e7\n", - "krev = 2.5713202543754838e-9\n", - "Kc = 8.952724109165363e15\n", - "vacantX+vacantX+O=CC=O<=>HX+O=CC(=O)[Pt]\n", - "kf = 1.43713660093583e-9\n", - "krev = 0.00032277677938391324\n", - "Kc = 4.452416322137251e-6\n", - "proton+OCX<=>OC#[Pt]\n", - "kf = 26781.620683797883\n", - "krev = 1.0085447542339806e12\n", - "Kc = 2.6554717151981333e-8\n", - "proton+OC#[Pt]<=>OC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.552445879282663e-17\n", - "Kc = 3.815369170624406e26\n", - "vacantX+O=CC=O<=>O=CC=O.[Pt]\n", - "kf = 359723.7676387533\n", - "krev = 0.32068189796600394\n", - "Kc = 1.121746409511672e6\n", - "proton+O=CC(=O)[Pt]<=>O=CC=O.[Pt]\n", - "kf = 1.508798479649927e9\n", - "krev = 8.88806985342612e-11\n", - "Kc = 1.6975547048252826e19\n", - "vacantX+vacantX+OO<=>HOX+HOX\n", - "kf = 4.0912386971316826e8\n", - "krev = 1.7763617117679594e-6\n", - "Kc = 2.3031563166601894e14\n", - "OCX<=>vacantX+CO\n", - "kf = 2.010168305725754e-19\n", - "krev = 2.61760793808642e-25\n", - "Kc = 767940.9419866255\n", - "vacantX+vacantX+O2<=>OX+OX\n", - "kf = 1.0945721587141857e10\n", - "krev = 4.219325007995329e-16\n", - "Kc = 2.594187830138819e25\n", - "proton+HX<=>[H][H].[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.1949534688419614e-15\n", - "Kc = 2.0921316730623565e25\n", - "vacantX+H2<=>[H][H].[Pt]\n", - "kf = 2338.960705505517\n", - "krev = 9707.159813448116\n", - "Kc = 0.24095211683495363\n", - "CHOX+C=O<=>O=COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 7.563806299311394e-5\n", - "Kc = 0.0005236345532350701\n", - "proton+OO[Pt]<=>OX+H2O\n", - "kf = 17.257164508221003\n", - "krev = 6.236444643145301e-63\n", - "Kc = 2.767147869610126e63\n", - "vacantX+vacantX+OO<=>HX+OO[Pt]\n", - "kf = 4.980245005159166e-22\n", - "krev = 5.509834949091977\n", - "Kc = 9.038827934364735e-23\n", - "proton+OC#[Pt]<=>H2O+CX\n", - "kf = 3.276640102032806e-5\n", - "krev = 0.0009291230748795855\n", - "Kc = 0.03526594259277716\n", - "vacantX+vacantX+O=C=C=O<=>OCX+OCX\n", - "kf = 74.64023007210145\n", - "krev = 2.953439666185894e-39\n", - "Kc = 2.52723056870475e40\n", - "HX+O=C=C=O<=>O=CC(=O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 5.0006650398424424e-61\n", - "Kc = 1.1597065597154312e53\n", - "proton+OC=[Pt]<=>H2O+CHX\n", - "kf = 2.5e10\n", - "krev = 6.511063937864271e-5\n", - "Kc = 3.839618261865876e14\n", - "proton+CX<=>CHX\n", - "kf = 2.5e10\n", - "krev = 6.018259224258551e-33\n", - "Kc = 4.1540251206244773e42\n", - "H2+CX<=>CH2X\n", - "kf = 4.832014059685671\n", - "krev = 1.8278921581756875e-33\n", - "Kc = 2.643489681857502e33\n", - "vacantX+vacantX+C=O<=>OX+CH2X\n", - "kf = 4.5608316796485725e-28\n", - "krev = 3.884151005592286e17\n", - "Kc = 1.1742158513101117e-45\n", - "proton+OC[Pt]<=>H2O+CH2X\n", - "kf = 7206.229958253159\n", - "krev = 0.0019484451144913943\n", - "Kc = 3.6984516036184127e6\n", - "proton+O=COC[Pt]<=>CH2X+O=CO\n", - "kf = 1981.2472905766488\n", - "krev = 1.4695324127813272e-5\n", - "Kc = 1.3482161219069803e8\n", - "proton+CHX<=>CH2X\n", - "kf = 2.5e10\n", - "krev = 6.715036577093663e-15\n", - "Kc = 3.722987911231938e24\n", - "proton+O=COC#[Pt]<=>CX+O=CO\n", - "kf = 6.185088018779624e7\n", - "krev = 3.741277098492221e-23\n", - "Kc = 1.6532023306352497e30\n", - "vacantX+vacantX+C=C=O<=>OCX+CH2X\n", - "kf = 2.4823885573387985e-14\n", - "krev = 9.351132511056354e15\n", - "Kc = 2.6546394828687704e-30\n", - "CHOX+C=O<=>O=CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.4949222028864902e7\n", - "Kc = 2.6494156850764662e-15\n", - "HX+O=CC=O<=>O=CCO[Pt]\n", - "kf = 5.6976884072695144e-8\n", - "krev = 2.551666729065355e-8\n", - "Kc = 2.23292812590636\n", - "proton+O=CC=O.[Pt]<=>O=CCO[Pt]\n", - "kf = 957581.7759153218\n", - "krev = 7139.55197608848\n", - "Kc = 134.12351070801344\n", - "O=O.[Pt]+proton<=>OO[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.545950245153839e-28\n", - "Kc = 7.050296330064662e37\n", - "proton+O=CC#[Pt]<=>CX+C=O\n", - "kf = 5.731900626219973e-17\n", - "krev = 16.634660991475336\n", - "Kc = 3.4457574032662074e-18\n", - "proton+CO2HX<=>OC(O)=[Pt]\n", - "kf = 8.313674902647437e-22\n", - "krev = 1.0085447542339753e12\n", - "Kc = 8.243238455949296e-34\n", - "proton+OC(O)=[Pt]<=>OC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.563843227039955e-39\n", - "Kc = 7.014898918762039e48\n", - "proton+OC(O)=[Pt]<=>H2O+OC#[Pt]\n", - "kf = 58948.65819613129\n", - "krev = 2.9467686111082447e-38\n", - "Kc = 2.0004508658710534e42\n", - "proton+O=C(O)C#[Pt]<=>CX+O=CO\n", - "kf = 1.2163309452954808e-9\n", - "krev = 0.00037997676558546045\n", - "Kc = 3.201066632117316e-6\n", - "proton+O=C=C=O.[Pt]<=>O=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.649884885591097e-48\n", - "Kc = 9.434372087609898e57\n", - "vacantX+O=C=C=O<=>O=C=C=O.[Pt]\n", - "kf = 366139.2749661925\n", - "krev = 442.06521987276346\n", - "Kc = 828.2471873077366\n", - "HOX+C=O<=>OOC[Pt]\n", - "kf = 1.5395975576095126e-29\n", - "krev = 2.622153295712258e16\n", - "Kc = 5.871500953537159e-46\n", - "proton+OOC[Pt]<=>OO+CH2X\n", - "kf = 15.535579749933543\n", - "krev = 3.4028033042152773e-9\n", - "Kc = 4.5655238816444645e9\n", - "vacantX+vacantX+O=C=CO<=>OCX+OC=[Pt]\n", - "kf = 73.33238091278024\n", - "krev = 14511.198914062346\n", - "Kc = 0.005053502563576338\n", - "vacantX+C=C=O<=>C=C=O.[Pt]\n", - "kf = 422670.5724931744\n", - "krev = 9.80980243728561e-11\n", - "Kc = 4.3086552985681545e15\n", - "proton+CO[Pt]<=>OX+CH4\n", - "kf = 541698.6744405399\n", - "krev = 1.9995135619129721e-19\n", - "Kc = 2.7091522896313173e24\n", - "HX+C=C=O<=>CC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.3310785577331067e-33\n", - "Kc = 2.514767798332947e25\n", - "proton+C=C=O.[Pt]<=>CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.357099551204697e-8\n", - "Kc = 3.9326110592781875e17\n", - "proton+CC(=O)[Pt]<=>OCX+CH4\n", - "kf = 1.0030005882936613e8\n", - "krev = 4.3463683404291294e-8\n", - "Kc = 2.3076750743003805e15\n", - "vacantX+vacantX+COC=O<=>CHOX+CO[Pt]\n", - "kf = 5.858305523872122e-8\n", - "krev = 9.372228401924443e12\n", - "Kc = 6.250707166578664e-21\n", - "vacantX+vacantX+COC=O<=>HX+O=COC[Pt]\n", - "kf = 8.724708246600757e-23\n", - "krev = 252.56605644619947\n", - "Kc = 3.454426287270814e-25\n", - "vacantX+vacantX+COC=O<=>HX+COC(=O)[Pt]\n", - "kf = 7.165711269221808e-16\n", - "krev = 0.1859922027934253\n", - "Kc = 3.852694447186316e-15\n", - "proton+O=COCC#[Pt]<=>CX+COC=O\n", - "kf = 0.8132675549526747\n", - "krev = 2.165706403032533e-5\n", - "Kc = 37552.06863746147\n", - "HOX+C=C=O<=>O=C([Pt])CO\n", - "kf = 3.3473534940386794e-8\n", - "krev = 9.042590347389556e-30\n", - "Kc = 3.70176394754519e21\n", - "HX+O=C=CO<=>O=C([Pt])CO\n", - "kf = 2.8488442036348548e-8\n", - "krev = 1.614840618256874e-45\n", - "Kc = 1.7641643214981894e37\n", - "vacantX+vacantX+COO<=>HOX+CO[Pt]\n", - "kf = 3.442529358831723e8\n", - "krev = 2.6586367586035048e-11\n", - "Kc = 1.294847574679578e19\n", - "vacantX+vacantX+COO<=>HX+OOC[Pt]\n", - "kf = 1.3336211820914592e-23\n", - "krev = 16620.58178963317\n", - "Kc = 8.023913957833202e-28\n", - "CHOX+C=C=O<=>O=CCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 2.6714659015861004e-16\n", - "Kc = 1.2530025152300434e8\n", - "vacantX+vacantX+CO-2<=>HX+CO[Pt]\n", - "kf = 3.6896065237788346e-26\n", - "krev = 1200.2597905170037\n", - "Kc = 3.0740066050113714e-29\n", - "vacantX+vacantX+CO-2<=>HX+OC[Pt]\n", - "kf = 1.1691860289045307e-22\n", - "krev = 1.716447494000275\n", - "Kc = 6.811662069427353e-23\n", - "proton+OCO[Pt]<=>OX+CO-2\n", - "kf = 6.4866612293733e7\n", - "krev = 4.917786339628338e-9\n", - "Kc = 1.319020547335029e16\n", - "proton+COC(=O)[Pt]<=>OCX+CO-2\n", - "kf = 5.096893185474306e9\n", - "krev = 2.041829224680708e-9\n", - "Kc = 2.49623872744369e18\n", - "proton+O=C([Pt])CO<=>OCX+CO-2\n", - "kf = 1.9762803815844387e7\n", - "krev = 1.2158736968776066e-8\n", - "Kc = 1.6253994034574272e15\n", - "proton+OCC#[Pt]<=>CX+CO-2\n", - "kf = 1.8515947729382765e-10\n", - "krev = 0.16959607683462066\n", - "Kc = 1.091767455649245e-9\n", - "vacantX+vacantX+COOC<=>CO[Pt]+CO[Pt]\n", - "kf = 3.028654941635431e8\n", - "krev = 1.0392777770118965e-11\n", - "Kc = 2.914191959673513e19\n", - "vacantX+vacantX+C=C=O<=>HX+O=C=C[Pt]\n", - "kf = 3.6584912239485734e-16\n", - "krev = 0.32395775785233605\n", - "Kc = 1.1293111942132156e-15\n", - "vacantX+vacantX+O=C=CO<=>HOX+O=C=C[Pt]\n", - "kf = 3.132095071630788e8\n", - "krev = 5.819571251914923e7\n", - "Kc = 5.382003133994065\n", - "proton+O=C=C[Pt]<=>C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.724942318590629e-29\n", - "Kc = 2.570709334924167e38\n", - "vacantX+vacantX+O=CCO<=>CHOX+OC[Pt]\n", - "kf = 9001.813049524091\n", - "krev = 8.180569891408677e12\n", - "Kc = 1.1003894800749632e-9\n", - "vacantX+vacantX+O=CCO<=>HX+O=CCO[Pt]\n", - "kf = 3.705974451661604e-28\n", - "krev = 2668.9209237076484\n", - "Kc = 1.3885665996103351e-31\n", - "vacantX+vacantX+O=CCO<=>HX+O=C([Pt])CO\n", - "kf = 1.2718474027465153e-10\n", - "krev = 0.0002705673832361486\n", - "Kc = 4.7006678614933393e-7\n", - "proton+O=CCOC#[Pt]<=>CX+O=CCO\n", - "kf = 3.8625888100004036e-23\n", - "krev = 1.5059302822169408e-12\n", - "Kc = 2.564918745318097e-11\n", - "proton+COC#[Pt]<=>CX+CO-2\n", - "kf = 3.5797175052253717e-22\n", - "krev = 9.770006712968626e-20\n", - "Kc = 0.0036639867406372244\n", - "proton+O=CC(=O)C#[Pt]<=>CX+O=CC=O\n", - "kf = 5.9931479699583235e-12\n", - "krev = 0.0016900056192162703\n", - "Kc = 3.546229611199523e-9\n", - "vacantX+vacantX+OCO<=>HOX+OC[Pt]\n", - "kf = 1.653107374238179e-12\n", - "krev = 3.492310477620836e11\n", - "Kc = 4.7335635958815765e-24\n", - "vacantX+vacantX+OCO<=>HX+OC(O)[Pt]\n", - "kf = 4.0412190145177725e-23\n", - "krev = 628.7683045605482\n", - "Kc = 6.427198993979533e-26\n", - "vacantX+vacantX+OCO<=>HX+OCO[Pt]\n", - "kf = 1.1281154422531313e-23\n", - "krev = 247.99076039714222\n", - "Kc = 4.5490220702034325e-26\n", - "proton+OC(O)C#[Pt]<=>CX+OCO\n", - "kf = 0.005562206988621036\n", - "krev = 0.025459246171787766\n", - "Kc = 0.21847492856189518\n", - "proton+OCOC#[Pt]<=>CX+OCO\n", - "kf = 2.2993090387825977e-18\n", - "krev = 1.7767009384663083e-12\n", - "Kc = 1.2941452266960681e-6\n", - "proton+O=COC=[Pt]<=>O=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.03525663068036e-45\n", - "Kc = 2.4148601669491608e55\n", - "proton+O=COC=[Pt]<=>CHX+O=CO\n", - "kf = 407721.49317133107\n", - "krev = 4.66233771243883e-34\n", - "Kc = 8.745001291595743e38\n", - "proton+O=COC#[Pt]<=>O=COC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.1834993039887084e-24\n", - "Kc = 7.852993706854812e33\n", - "proton+O=C=CC#[Pt]<=>CX+C=C=O\n", - "kf = 1.255896512556004e-15\n", - "krev = 0.016900821436021087\n", - "Kc = 7.430979123176135e-14\n", - "vacantX+vacantX+COCO<=>CO[Pt]+OC[Pt]\n", - "kf = 3.0636862331912886e-9\n", - "krev = 3.008499680951675e11\n", - "Kc = 1.0183435459837431e-20\n", - "proton+CC#[Pt]<=>CX+CH4\n", - "kf = 3.172314510568854e-8\n", - "krev = 0.363285670785801\n", - "Kc = 8.732286367659409e-8\n", - "HX+O=C=C=O<=>O=C=CO[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.1302052975227224e-55\n", - "Kc = 2.7224155607861307e47\n", - "proton+O=C=CO[Pt]<=>OX+C=C=O\n", - "kf = 0.047578794564636824\n", - "krev = 2.8204743128358057e-8\n", - "Kc = 1.6869075654441754e6\n", - "proton+O=C=C=O.[Pt]<=>O=C=CO[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 2.257619247094878e-42\n", - "Kc = 2.2147224366704162e52\n", - "vacantX+vacantX+O=C=CO<=>HX+O=C=CO[Pt]\n", - "kf = 0.0007071288662616175\n", - "krev = 2.8988454126647536e-5\n", - "Kc = 24.393465866522067\n", - "vacantX+vacantX+OCCO<=>OC[Pt]+OC[Pt]\n", - "kf = 2.961131444342359e-9\n", - "krev = 1.299206322752899e13\n", - "Kc = 2.2791849088819035e-22\n", - "proton+COC(=O)C#[Pt]<=>CX+COC=O\n", - "kf = 2.520547604265173e-10\n", - "krev = 3.828537658551766e-5\n", - "Kc = 6.583577932517004e-6\n", - "proton+O=C=CC(=O)[Pt]<=>OCX+C=C=O\n", - "kf = 2.14881300259784e7\n", - "krev = 1.9623010758881652e-11\n", - "Kc = 1.0950475587061772e18\n", - "vacantX+vacantX+OC=CO<=>OC=[Pt]+OC=[Pt]\n", - "kf = 1.351949923589269e-23\n", - "krev = 7.975137957191956e11\n", - "Kc = 1.6952056890377485e-35\n", - "vacantX+OX+CH4<=>HOX+CH3X\n", - "kf = 1181.9069662995785\n", - "krev = 1.0235810933777192e20\n", - "Kc = 1.1546783874244874e-17\n", - "vacantX+HOX+CH4<=>H2OX+CH3X\n", - "kf = 5.28370763875636e9\n", - "krev = 1.2149259925984929e9\n", - "Kc = 4.348995470461149\n", - "HX+CH3X<=>vacantX+vacantX+CH4\n", - "kf = 5.733311120080377e8\n", - "krev = 8.483521653048543e-25\n", - "Kc = 6.758173497465076e32\n", - "proton+CH2X<=>CH3X\n", - "kf = 2.5e10\n", - "krev = 7.728626954425352e-28\n", - "Kc = 3.2347272222377345e37\n", - "CO2+CH3X<=>COC(=O)[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.00447183609125585\n", - "Kc = 1.463156578060128e-5\n", - "vacantX+vacantX+COC=O<=>CHO2X+CH3X\n", - "kf = 0.05589950368763065\n", - "krev = 5.054770535995559e16\n", - "Kc = 1.1058761874463802e-18\n", - "vacantX+vacantX+COO<=>OO[Pt]+CH3X\n", - "kf = 9.385776922831516e-7\n", - "krev = 3.9782610412247473e11\n", - "Kc = 2.359266228528335e-18\n", - "vacantX+vacantX+CO-2<=>HOX+CH3X\n", - "kf = 9.872876935778847e-16\n", - "krev = 6.917821124819518e13\n", - "Kc = 1.427165686657795e-29\n", - "vacantX+vacantX+COCO<=>CH3X+OCO[Pt]\n", - "kf = 3.9072411322938125e-9\n", - "krev = 8.599564777209447e13\n", - "Kc = 4.543533578174534e-23\n", - "O=O+HX<=>OO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 8.854082166234876e-41\n", - "Kc = 8.666474551788235e32\n", - "vacantX+O=O<=>O=O.[Pt]\n", - "kf = 484458.3574999593\n", - "krev = 584.920039726471\n", - "Kc = 828.247152767255\n", - "vacantX+O=C=CO<=>O=C=CO.[Pt]\n", - "kf = 359723.7676387533\n", - "krev = 0.4900054095759742\n", - "Kc = 734122.0333670193\n", - "proton+O=C=CO.[Pt]<=>O=C([Pt])CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.543989619636675e-29\n", - "Kc = 1.6191818702694958e39\n", - "proton+O=C=CO[Pt]<=>O=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.012328788524416852\n", - "Kc = 2.0277742578265605e12\n", - "vacantX+vacantX+O=C=C=O<=>OX+O=C=C=[Pt]\n", - "kf = 149.2804601441562\n", - "krev = 1.2008902564793325e-12\n", - "Kc = 1.2430816166483347e14\n", - "proton+O=C=C=[Pt]<=>O=CC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 728325.7738813914\n", - "Kc = 34325.299057824195\n", - "proton+O=C=C=[Pt]<=>O=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.992117420427329e-15\n", - "Kc = 4.1721478812771864e24\n", - "vacantX+vacantX+C=CO<=>CH2X+OC=[Pt]\n", - "kf = 3.7510196251812924e-36\n", - "krev = 6.624293894020312e13\n", - "Kc = 5.662519938264367e-50\n", - "proton+O=C(C#[Pt])CO<=>CX+O=CCO\n", - "kf = 2.1150580786972557e-17\n", - "krev = 1.2236788896896236\n", - "Kc = 1.728442074565594e-17\n", - "vacantX+vacantX+C=C<=>CH2X+CH2X\n", - "kf = 9.387035392806688e-46\n", - "krev = 5.259242712748897e15\n", - "Kc = 1.784864457776713e-61\n", - "proton+O=COC[Pt]<=>COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.124037165592671e-28\n", - "Kc = 8.002465615756261e37\n", - "proton+COC(=O)[Pt]<=>COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.484214060387906e-18\n", - "Kc = 7.175219308200797e27\n", - "vacantX+COC=O<=>COC=O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.8619443782965007\n", - "Kc = 410274.8449265323\n", - "HX+O=C=C=C=O<=>O=C=CC(=O)[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 3.561089909521239e-25\n", - "Kc = 1.4777843564830474e17\n", - "vacantX+vacantX+O=C=C=C=O<=>OCX+O=C=C=[Pt]\n", - "kf = 135.4631249389026\n", - "krev = 3.092595390223456e6\n", - "Kc = 4.3802407960361956e-5\n", - "CH3X+O=C=C=O<=>CC(=O)C(=O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 3.5093718907449027e-71\n", - "Kc = 1.6525190917893694e63\n", - "proton+OOC#[Pt]<=>OO+CX\n", - "kf = 3.959382254258936e-52\n", - "krev = 4.505410128222608e6\n", - "Kc = 8.78806177812034e-59\n", - "proton+O=CC[Pt]<=>CH2X+C=O\n", - "kf = 9.847553463617368e-13\n", - "krev = 0.8193686811731042\n", - "Kc = 1.2018464568987987e-12\n", - "HX+C=C=O<=>O=CC[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 3.6888123831707493e-19\n", - "Kc = 9.074339235332521e10\n", - "proton+C=C=O.[Pt]<=>O=CC[Pt]\n", - "kf = 4.477750650627013e6\n", - "krev = 3155.453532604055\n", - "Kc = 1419.0513675324908\n", - "vacantX+vacantX+O=CCO<=>HOX+O=CC[Pt]\n", - "kf = 3.3834985622063113e-5\n", - "krev = 2.9362980773683545e12\n", - "Kc = 1.1523007790948657e-17\n", - "vacantX+vacantX+O=CC=O<=>OX+O=CC=[Pt]\n", - "kf = 6.170227811474367e-18\n", - "krev = 2.1467268001769245e15\n", - "Kc = 2.874249210922341e-33\n", - "proton+O=CC=[Pt]<=>CHX+C=O\n", - "kf = 0.3518802014338951\n", - "krev = 0.0019581841163396926\n", - "Kc = 179.69719930710195\n", - "proton+O=CC#[Pt]<=>O=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.1385387905668107e-13\n", - "Kc = 7.9654902068249e22\n", - "proton+O=C=C[Pt]<=>O=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.814809579170971e7\n", - "Kc = 655.3407052478085\n", - "proton+O=CC=[Pt]<=>O=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.4911345025101916e-29\n", - "Kc = 5.566522219725765e38\n", - "proton+O=CCO[Pt]<=>OX+CC=O\n", - "kf = 108844.3774855493\n", - "krev = 6.551243603618761e-23\n", - "Kc = 1.6614307766761425e27\n", - "vacantX+vacantX+CC=O<=>HX+CC(=O)[Pt]\n", - "kf = 4.3209399543319175e-11\n", - "krev = 0.0003615296985530135\n", - "Kc = 1.195182573278502e-7\n", - "proton+O=CCC(=O)[Pt]<=>OCX+CC=O\n", - "kf = 7.362850070977087e6\n", - "krev = 9.270601965584902e-14\n", - "Kc = 7.94214884676321e19\n", - "proton+O=CCC#[Pt]<=>CX+CC=O\n", - "kf = 0.11748380587607415\n", - "krev = 6.387097627333538e-5\n", - "Kc = 1839.3926745898334\n", - "vacantX+vacantX+CC=O<=>CHOX+CH3X\n", - "kf = 6.063283190982672e-6\n", - "krev = 7.026751658283665e14\n", - "Kc = 8.628856526948432e-21\n", - "proton+CC(=O)C#[Pt]<=>CX+CC=O\n", - "kf = 8.247683071468342e-18\n", - "krev = 0.06355423283679383\n", - "Kc = 1.2977393799478706e-16\n", - "proton+CC(=O)C(=O)[Pt]<=>OCX+CC=O\n", - "kf = 3.422758172577326e7\n", - "krev = 2.0119060511296993e-10\n", - "Kc = 1.7012514926606157e17\n", - "vacantX+vacantX+CC=O<=>HX+O=CC[Pt]\n", - "kf = 3.2094062904328744e-20\n", - "krev = 74.41720028073364\n", - "Kc = 4.312721089110603e-22\n", - "vacantX+CH4<=>C.[Pt]\n", - "kf = 11983.404197457203\n", - "krev = 27576.843954134933\n", - "Kc = 0.4345458899280744\n", - "proton+CH3X<=>C.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.2634270430964172e-30\n", - "Kc = 1.9787450440137642e40\n", - "HX+O=C=CC=O<=>O=CCC(=O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 3.8194581898791103e-32\n", - "Kc = 6.789235995427004e23\n", - "vacantX+vacantX+O=C=CC=O<=>CHOX+O=C=C[Pt]\n", - "kf = 2.850945414803626e8\n", - "krev = 4.6591458607721776e7\n", - "Kc = 6.119030182779314\n", - "vacantX+vacantX+O=C=CC=O<=>HX+O=C=CC(=O)[Pt]\n", - "kf = 1.1776167531898308e-10\n", - "krev = 0.0005032011998508361\n", - "Kc = 2.3402502886298994e-7\n", - "vacantX+vacantX+O=C=CC=O<=>OCX+O=CC=[Pt]\n", - "kf = 0.006845452357086415\n", - "krev = 1.638610749190394e14\n", - "Kc = 4.177595173514284e-17\n", - "vacantX+vacantX+C=C(O)O<=>CH2X+OC(O)=[Pt]\n", - "kf = 1.3631835715271243e-51\n", - "krev = 1.0974745099569602e16\n", - "Kc = 1.242109551665655e-67\n", - "proton+O=C=CC=O.[Pt]<=>O=CCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.130402878837127e-16\n", - "Kc = 4.078035407151288e25\n", - "proton+O=C=CC(=O)[Pt]<=>O=C=CC=O.[Pt]\n", - "kf = 2.964275004938465e9\n", - "krev = 9.178277268525813e-12\n", - "Kc = 3.229663822756335e20\n", - "vacantX+O=C=CC=O<=>O=C=CC=O.[Pt]\n", - "kf = 327433.4917974331\n", - "krev = 0.29189612518083846\n", - "Kc = 1.1217466199476891e6\n", - "vacantX+vacantX+CC(=O)O<=>HOX+CC(=O)[Pt]\n", - "kf = 3.661873055903852e-12\n", - "krev = 2.1682718089028445e11\n", - "Kc = 1.6888441019563762e-23\n", - "vacantX+vacantX+CC(=O)O<=>CO2HX+CH3X\n", - "kf = 1.1977509649486271e-8\n", - "krev = 1.0254845667743408e14\n", - "Kc = 1.1679853639496008e-22\n", - "CO2+CH3X<=>CC(=O)O[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 3.3286101924403974e-7\n", - "Kc = 0.19656841788766613\n", - "proton+CC(=O)O[Pt]<=>OX+CC=O\n", - "kf = 6.638543952734307e-6\n", - "krev = 1.1832604608796647e-7\n", - "Kc = 56.10382643732599\n", - "vacantX+vacantX+CC(=O)O<=>HX+CC(=O)O[Pt]\n", - "kf = 2.4753542791841756e-22\n", - "krev = 11382.562807978633\n", - "Kc = 2.1746897609465158e-26\n", - "proton+CC(=O)OC#[Pt]<=>CX+CC(=O)O\n", - "kf = 3.5372794201475537e8\n", - "krev = 2.288049006228874e-19\n", - "Kc = 1.5459806195224992e27\n", - "vacantX+vacantX+CC(=O)C=O<=>CHOX+CC(=O)[Pt]\n", - "kf = 2.810784197367395e8\n", - "krev = 8.682228189641076\n", - "Kc = 3.237399589106622e7\n", - "vacantX+vacantX+CC(=O)C=O<=>CH3X+O=CC(=O)[Pt]\n", - "kf = 0.010756441693245073\n", - "krev = 2.0353876594794328e15\n", - "Kc = 5.284714016589902e-18\n", - "vacantX+vacantX+CC(=O)C=O<=>HX+CC(=O)C(=O)[Pt]\n", - "kf = 2.426386880233808e-11\n", - "krev = 0.0003222108693910823\n", - "Kc = 7.530431499158364e-8\n", - "proton+O=C=C([Pt])C=O<=>C=O+O=C=C=[Pt]\n", - "kf = 13308.622034460761\n", - "krev = 4.6234228919871786e-9\n", - "Kc = 2.8785214645897607e12\n", - "HX+O=C=C=C=O<=>O=C=C([Pt])C=O\n", - "kf = 5.262522960320117e-8\n", - "krev = 8.417963556232881e-20\n", - "Kc = 6.251539253129229e11\n", - "vacantX+vacantX+O=C=CC=O<=>HX+O=C=C([Pt])C=O\n", - "kf = 3.109950102720783e-13\n", - "krev = 0.31413419650430946\n", - "Kc = 9.900068624582613e-13\n", - "proton+O=C=C([Pt])C=O<=>O=C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.274602487927107e-16\n", - "Kc = 7.6345144463093386e25\n", - "proton+O=C=COC#[Pt]<=>CX+O=C=CO\n", - "kf = 3.333143073629419e-24\n", - "krev = 2.9895559923107984e-13\n", - "Kc = 1.1149291340260339e-11\n", - "vacantX+vacantX+COC(C)=O<=>CO[Pt]+CC(=O)[Pt]\n", - "kf = 6.614441053978493e-6\n", - "krev = 7.629970776987544e11\n", - "Kc = 8.669025409544227e-18\n", - "vacantX+vacantX+COC(C)=O<=>CH3X+COC(=O)[Pt]\n", - "kf = 1.5563360867242215e-10\n", - "krev = 4.0343976517667425e14\n", - "Kc = 3.857666549162974e-25\n", - "vacantX+vacantX+COC(C)=O<=>CH3X+CC(=O)O[Pt]\n", - "kf = 0.0003463783354588583\n", - "krev = 6.683486846094463e16\n", - "Kc = 5.182599194629471e-21\n", - "vacantX+vacantX+COO<=>HX+COO[Pt]\n", - "kf = 1.175900379595729e-21\n", - "krev = 0.27982743013843664\n", - "Kc = 4.2022341377111815e-21\n", - "proton+COO[Pt]<=>OX+CO-2\n", - "kf = 129.78074174016686\n", - "krev = 1.499485133709293e-58\n", - "Kc = 8.65502023478731e59\n", - "vacantX+vacantX+COOC<=>CH3X+COO[Pt]\n", - "kf = 1.8186835430204133e-8\n", - "krev = 4.141977957602716e12\n", - "Kc = 4.39085760869917e-21\n", - "O=O+CH3X<=>COO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 4.970959816815508e-38\n", - "Kc = 1.543639067721808e30\n", - "proton+CO[Pt]<=>CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.487564815762018e-25\n", - "Kc = 1.0049989387851077e35\n", - "proton+OC[Pt]<=>CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.512171272873819e-19\n", - "Kc = 4.535417853038886e28\n", - "vacantX+CO-2<=>CO.[Pt]\n", - "kf = 484125.61468448705\n", - "krev = 1.0558750276780043e7\n", - "Kc = 0.04585065485913965\n", - "vacantX+vacantX+CC(=O)CO<=>OC[Pt]+CC(=O)[Pt]\n", - "kf = 4.324183911493771e7\n", - "krev = 7.8667392573421875e12\n", - "Kc = 5.496793232924203e-6\n", - "vacantX+vacantX+CC(=O)CO<=>CH3X+O=C([Pt])CO\n", - "kf = 0.43146252134138535\n", - "krev = 2.5450806210309695e15\n", - "Kc = 1.695280368629765e-16\n", - "HX+O=C=C=O<=>O=C=C(O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 7.390785994602033e-44\n", - "Kc = 7.846667531546056e35\n", - "proton+O=C=C=O.[Pt]<=>O=C=C(O)[Pt]\n", - "kf = 5.0e10\n", - "krev = 7.832851008293297e-31\n", - "Kc = 6.383371769367348e40\n", - "vacantX+vacantX+O=C=CO<=>HX+O=C=C(O)[Pt]\n", - "kf = 2.8707175642480555e-12\n", - "krev = 0.04083063397693327\n", - "Kc = 7.030793511239207e-11\n", - "proton+O=C=C(O)[Pt]<=>O=C=CO.[Pt]\n", - "kf = 1.7351014576291664e10\n", - "krev = 2.4662443446341767e-14\n", - "Kc = 7.03539964077054e23\n", - "proton+O=C=C(O)[Pt]<=>H2O+O=C=C=[Pt]\n", - "kf = 1.2324712433709262e6\n", - "krev = 1.176415080398485e-31\n", - "Kc = 1.0476499867321094e37\n", - "vacantX+vacantX+O=CCC=O<=>HX+O=CCC(=O)[Pt]\n", - "kf = 3.286584099620913e-11\n", - "krev = 0.0009472638388816695\n", - "Kc = 3.469555117295539e-8\n", - "vacantX+vacantX+O=CCC=O<=>CHOX+O=CC[Pt]\n", - "kf = 5.621568394735124e8\n", - "krev = 2.2372815421494465e13\n", - "Kc = 2.51267812692642e-5\n", - "proton+O=C=C(O)C#[Pt]<=>CX+O=C=CO\n", - "kf = 3.0900625689798e-31\n", - "krev = 97363.75326657317\n", - "Kc = 3.1737299203323514e-36\n", - "proton+COOC#[Pt]<=>CX+COO\n", - "kf = 1.3396315820930446e-65\n", - "krev = 2.5e10\n", - "Kc = 5.3585263283721787e-76\n", - "vacantX+vacantX+COC=C=O<=>CO[Pt]+O=C=C[Pt]\n", - "kf = 1.4053920986837533e8\n", - "krev = 2.5815645207863396e8\n", - "Kc = 0.5443954963619013\n", - "vacantX+vacantX+COC=C=O<=>CH3X+O=C=CO[Pt]\n", - "kf = 1.4053920986837533e8\n", - "krev = 1.2268284001067661e8\n", - "Kc = 1.1455490421981163\n", - "HX+O=CC=O<=>O=CC(O)[Pt]\n", - "kf = 5.6976884072695144e-8\n", - "krev = 1.248882373151946e-25\n", - "Kc = 4.562229822244678e17\n", - "proton+O=CC(O)[Pt]<=>C=O+OC=[Pt]\n", - "kf = 1.4979350850413518e-9\n", - "krev = 7.682289195925664e-6\n", - "Kc = 0.00019498551106820976\n", - "proton+O=CC=O.[Pt]<=>O=CC(O)[Pt]\n", - "kf = 3.43386635836783e8\n", - "krev = 1.2530721027853126e-11\n", - "Kc = 2.7403581571523903e19\n", - "HX+O=C=CO<=>O=CC(O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 2.6755933088589045e-38\n", - "Kc = 1.0647523277182356e30\n", - "vacantX+vacantX+O=CCO<=>HX+O=CC(O)[Pt]\n", - "kf = 5.743984385098034e-15\n", - "krev = 0.20246227896672986\n", - "Kc = 2.8370639777506056e-14\n", - "proton+O=C=CO.[Pt]<=>O=CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.5582018736355307e-22\n", - "Kc = 9.77248912904274e31\n", - "proton+O=CC(O)[Pt]<=>H2O+O=CC=[Pt]\n", - "kf = 459.6019775429135\n", - "krev = 1.1031455244918085e-6\n", - "Kc = 4.166286018833649e8\n", - "proton+O=CC(O)C#[Pt]<=>CX+O=CCO\n", - "kf = 0.2097860124056399\n", - "krev = 0.0024507024511013467\n", - "Kc = 85.60240036947854\n", - "vacantX+vacantX+O=C=CCO<=>OC[Pt]+O=C=C[Pt]\n", - "kf = 4067.906517801298\n", - "krev = 9.581534474143486e11\n", - "Kc = 4.245568941779481e-9\n", - "proton+O=CC(=O)[Pt]<=>O=CC(O)=[Pt]\n", - "kf = 1.4625119078213113e-5\n", - "krev = 1.0085447542339824e12\n", - "Kc = 1.4501209804339615e-17\n", - "proton+O=CC(O)=[Pt]<=>OC#[Pt]+C=O\n", - "kf = 345367.8200620121\n", - "krev = 2.1066346546856475e-20\n", - "Kc = 1.6394291211996983e25\n", - "proton+O=CC(O)=[Pt]<=>H2O+O=CC#[Pt]\n", - "kf = 109541.91076063467\n", - "krev = 6.52855201530546e-37\n", - "Kc = 1.6778898368861259e41\n", - "proton+O=C=C(O)[Pt]<=>O=CC(O)=[Pt]\n", - "kf = 266253.7431100425\n", - "krev = 124230.61178859882\n", - "Kc = 2.1432217009695007\n", - "proton+O=CC(O)=[Pt]<=>O=CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.793151847783197e-46\n", - "Kc = 3.207944678649035e55\n", - "proton+OC(O)[Pt]<=>OCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.3128823116835e-26\n", - "Kc = 5.796587570283467e35\n", - "proton+OCO[Pt]<=>OCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.052557862362137e-26\n", - "Kc = 8.189852945376913e35\n", - "vacantX+OCO<=>OCO.[Pt]\n", - "kf = 395377.4080430906\n", - "krev = 715.0601225795458\n", - "Kc = 552.9289014422803\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.079525546868e-12\n", - "Kc = 1.2021973010936467e22\n", - "vacantX+O=C=C=C=O<=>O=C=C=C=O.[Pt]\n", - "kf = 332249.5811031886\n", - "krev = 401.14766551623046\n", - "Kc = 828.2475748067037\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 4.91573386591171e-7\n", - "Kc = 5.08571063485824e16\n", - "proton+O=CCO[Pt]<=>O=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.8816895227328687e-31\n", - "Kc = 1.3285932507978942e41\n", - "proton+O=C([Pt])CO<=>O=CCO.[Pt]\n", - "kf = 3.74256001789537e8\n", - "krev = 9.536073355505413e-9\n", - "Kc = 3.9246342581191416e16\n", - "vacantX+O=CCO<=>O=CCO.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 1291.5767888759226\n", - "Kc = 273.8002875141987\n", - "proton+O=CC(O)[Pt]<=>O=CCO.[Pt]\n", - "kf = 1.712472301799593e10\n", - "krev = 2.6335036754646568e-14\n", - "Kc = 6.5026387384762e23\n", - "proton+OCC#[Pt]<=>OCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.6468663797080987e-6\n", - "Kc = 6.855200437039605e15\n", - "proton+OCC=[Pt]<=>CHX+CO-2\n", - "kf = 2.437334851076409e7\n", - "krev = 3.684139726492616e-11\n", - "Kc = 6.615750302708541e17\n", - "vacantX+vacantX+O=CCO<=>OX+OCC=[Pt]\n", - "kf = 3.3881471741726223e-34\n", - "krev = 2.264159139077055e16\n", - "Kc = 1.4964262518904662e-50\n", - "vacantX+vacantX+O=C=CCO<=>OCX+OCC=[Pt]\n", - "kf = 1.8009876630720204e-13\n", - "krev = 6.668943472119082e14\n", - "Kc = 2.7005591974222413e-28\n", - "vacantX+vacantX+C=CC=O<=>CH2X+O=CC=[Pt]\n", - "kf = 3.2830355290077765e-39\n", - "krev = 2.9277080237249806e14\n", - "Kc = 1.121367124864694e-53\n", - "vacantX+vacantX+C=COC=O<=>CH2X+O=COC=[Pt]\n", - "kf = 1.0242943870290668e-63\n", - "krev = 2.920849603333263e13\n", - "Kc = 3.5068371403311754e-77\n", - "vacantX+O=C=CCO<=>O=C=CCO.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 1179.037991138623\n", - "Kc = 273.8002884035305\n", - "vacantX+vacantX+O=CC=CO<=>OC=[Pt]+O=CC=[Pt]\n", - "kf = 6.284377773759944e-35\n", - "krev = 2.1623088290446475e12\n", - "Kc = 2.90632757418676e-47\n", - "vacantX+vacantX+COC<=>CH3X+CO[Pt]\n", - "kf = 3.3416169046706564e-11\n", - "krev = 3.110510590664853e12\n", - "Kc = 1.0742985137872191e-23\n", - "proton+O=C=CC(O)[Pt]<=>OC=[Pt]+C=C=O\n", - "kf = 7.886335155622577e-9\n", - "krev = 1.1676117437495351e-7\n", - "Kc = 0.0675424446340125\n", - "HX+O=C=CC=O<=>O=C=CC(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 3.0624966294759025e-24\n", - "Kc = 8.467340919226885e15\n", - "proton+O=C=CC=O.[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 5.4417257022505686e7\n", - "krev = 1.0699402207865258e-10\n", - "Kc = 5.086009102686402e17\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=CC(O)[Pt]\n", - "kf = 2.2665619116480148e-11\n", - "krev = 0.03466826587817799\n", - "Kc = 6.537857761944495e-10\n", - "proton+O=C=CC(O)[Pt]<=>O=C=CCO.[Pt]\n", - "kf = 1.693513701515947e9\n", - "krev = 6.001577582317764e-11\n", - "Kc = 2.8217809039168078e19\n", - "proton+O=C=CC=[Pt]<=>CHX+C=C=O\n", - "kf = 181.35768264661723\n", - "krev = 8.307531938850336e-7\n", - "Kc = 2.183051283841528e8\n", - "proton+O=C=CC#[Pt]<=>O=C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.768026569342988e-11\n", - "Kc = 1.4140058997693788e21\n", - "vacantX+vacantX+O=C=CC=O<=>OX+O=C=CC=[Pt]\n", - "kf = 3.709849833927781e-21\n", - "krev = 2.4389911159903437e17\n", - "Kc = 1.5210591828750508e-38\n", - "proton+O=C=CC(O)[Pt]<=>H2O+O=C=CC=[Pt]\n", - "kf = 4.694863820330143\n", - "krev = 3.9520471176425216e-5\n", - "Kc = 118795.74510565875\n", - "vacantX+vacantX+CCO<=>CH3X+OC[Pt]\n", - "kf = 1.5510087911871897e-15\n", - "krev = 9.749013808701775e13\n", - "Kc = 1.5909391674086975e-29\n", - "proton+O=C=C([Pt])CO<=>CO-2+O=C=C=[Pt]\n", - "kf = 259142.28390262663\n", - "krev = 5.010713983419634e-21\n", - "Kc = 5.171763640074528e25\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=C([Pt])CO\n", - "kf = 4.040764431615523e-20\n", - "krev = 30.812673220085827\n", - "Kc = 1.3113969056672023e-21\n", - "proton+O=C=C([Pt])CO<=>O=C=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.777114479215893e-21\n", - "Kc = 1.4067748753603438e31\n", - "proton+O=C=CC[Pt]<=>CH2X+C=C=O\n", - "kf = 6.0148104045883e-8\n", - "krev = 8.74545093406659e-6\n", - "Kc = 0.006877644674854341\n", - "vacantX+vacantX+O=C=CCO<=>HOX+O=C=CC[Pt]\n", - "kf = 8.032715739528718e-6\n", - "krev = 4.997427676480693e14\n", - "Kc = 1.6073700830795308e-20\n", - "proton+O=C=CC=[Pt]<=>O=C=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.1155543114237032e-25\n", - "Kc = 1.1817233840324226e35\n", - "vacantX+vacantX+CC(O)O<=>CH3X+OC(O)[Pt]\n", - "kf = 1.0212279299691738e-21\n", - "krev = 4.839386960246169e15\n", - "Kc = 2.1102423475497943e-37\n", - "proton+O=C=CC(O)=[Pt]<=>OC#[Pt]+C=C=O\n", - "kf = 1.5097720767202745e6\n", - "krev = 3.361950781834918e-17\n", - "Kc = 4.490761985207459e22\n", - "proton+O=C=CC(O)=[Pt]<=>H2O+O=C=CC#[Pt]\n", - "kf = 5.803789817126122e6\n", - "krev = 2.7232165859221153e-28\n", - "Kc = 2.1312259359498893e34\n", - "proton+O=C=CC(=O)[Pt]<=>O=C=CC(O)=[Pt]\n", - "kf = 0.6530550593549805\n", - "krev = 1.0085447542339824e12\n", - "Kc = 6.475221417923034e-13\n", - "proton+O=C=CC(O)=[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.85508059604632e-41\n", - "Kc = 2.5367626125786886e50\n", - "C=O+O=C=C[Pt]<=>O=C=CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 80798.59947863563\n", - "Kc = 4.901904683810505e-13\n", - "HX+O=C=CC=O<=>O=C=CCO[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 2.019947796444839e-5\n", - "Kc = 0.0012837560986177624\n", - "proton+O=C=CC=O.[Pt]<=>O=C=CCO[Pt]\n", - "kf = 278.5863350248319\n", - "krev = 3612.827309769227\n", - "Kc = 0.07711033800910536\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=CCO[Pt]\n", - "kf = 7.342900678318069e-26\n", - "krev = 740.7927312780465\n", - "Kc = 9.912220204496055e-29\n", - "proton+O=C=CCO[Pt]<=>O=C=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3432355963676785e-28\n", - "Kc = 1.861177597407629e38\n", - "vacantX+vacantX+CCOC=O<=>CH3X+O=COC[Pt]\n", - "kf = 1.714178070740009e-17\n", - "krev = 1.2983121019578911e14\n", - "Kc = 1.3203127877765141e-31\n", - "proton+O=CC([Pt])C=O<=>C=O+O=CC=[Pt]\n", - "kf = 1.0131844482393167e-10\n", - "krev = 2.9534786470384583e-7\n", - "Kc = 0.00034304783251277847\n", - "HX+O=C=CC=O<=>O=CC([Pt])C=O\n", - "kf = 2.5931203025755725e-8\n", - "krev = 5.183135272095574e-24\n", - "Kc = 5.002995612590211e15\n", - "proton+O=C=CC=O.[Pt]<=>O=CC([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 8.319166178505196e-8\n", - "Kc = 3.005108861101275e17\n", - "vacantX+vacantX+O=CCC=O<=>HX+O=CC([Pt])C=O\n", - "kf = 6.269624738894468e-15\n", - "krev = 24.522149705338403\n", - "Kc = 2.556719053684591e-16\n", - "proton+O=CC(=[Pt])C=O<=>C=O+O=CC#[Pt]\n", - "kf = 0.04202179791424184\n", - "krev = 2.102387409121332e-9\n", - "Kc = 1.9987656761987723e7\n", - "proton+O=C=C([Pt])C=O<=>O=CC(=[Pt])C=O\n", - "kf = 2.5e10\n", - "krev = 5.057292696382588\n", - "Kc = 4.943356357025204e9\n", - "proton+O=CC(=[Pt])C=O<=>O=CC([Pt])C=O\n", - "kf = 2.5e10\n", - "krev = 5.3866690937421086e-24\n", - "Kc = 4.641087017771969e33\n", - "vacantX+vacantX+COCC=O<=>CH3X+O=CCO[Pt]\n", - "kf = 1.7650043109029407e-12\n", - "krev = 1.4735149295451475e13\n", - "Kc = 1.1978190892492496e-25\n", - "vacantX+vacantX+COCC=O<=>CO[Pt]+O=CC[Pt]\n", - "kf = 10.947009513309483\n", - "krev = 5.112987413682155e11\n", - "Kc = 2.1410202348661592e-11\n", - "proton+O=CCC(=O)[Pt]<=>O=CCC=O.[Pt]\n", - "kf = 2.1814901321970692e8\n", - "krev = 5.7550523540318155e-8\n", - "Kc = 3.7905652251256815e15\n", - "vacantX+O=CCC=O<=>O=CCC=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 165389.8266532618\n", - "Kc = 1.951879075907524\n", - "proton+O=CC([Pt])C=O<=>O=CCC=O.[Pt]\n", - "kf = 1.6062704929440186e10\n", - "krev = 3.122654421781107e-14\n", - "Kc = 5.1439265316711864e23\n", - "proton+O=CCC#[Pt]<=>O=CCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.03648176110191e-17\n", - "Kc = 4.141485220927174e26\n", - "proton+O=CCC=[Pt]<=>CHX+CC=O\n", - "kf = 1.0605779567215914e7\n", - "krev = 5.748508015003e-13\n", - "Kc = 1.8449621257439228e19\n", - "vacantX+vacantX+O=CCC=O<=>OX+O=CCC=[Pt]\n", - "kf = 1.2771337705277995e-31\n", - "krev = 6.599290845791489e16\n", - "Kc = 1.935259106426951e-48\n", - "vacantX+vacantX+CCOO<=>CH3X+OOC[Pt]\n", - "kf = 1.1728434846364774e-18\n", - "krev = 2.6840450809869076e16\n", - "Kc = 4.3696862356918e-35\n", - "proton+OOCC#[Pt]<=>CX+COO\n", - "kf = 0.24698833297799483\n", - "krev = 0.0004336424509567548\n", - "Kc = 569.5667765760919\n", - "vacantX+vacantX+C=C=O<=>OX+C=C=[Pt]\n", - "kf = 5.2796000958546504e-37\n", - "krev = 1.4614931014553018e17\n", - "Kc = 3.612470076387919e-54\n", - "proton+C=C=[Pt]<=>CC#[Pt]\n", - "kf = 10.738937415423795\n", - "krev = 4.122167482176662e-33\n", - "Kc = 2.60516766042539e33\n", - "vacantX+vacantX+CC(C)=O<=>CH3X+CC(=O)[Pt]\n", - "kf = 0.0015322757193851075\n", - "krev = 1.9084257758101816e14\n", - "Kc = 8.029003479239911e-18\n", - "vacantX+vacantX+C=C=C=O<=>CH2X+O=C=C=[Pt]\n", - "kf = 0.014873013888318402\n", - "krev = 6.520037160662236e15\n", - "Kc = 2.2811240981957472e-18\n", - "HOX+C=C=C=O<=>O=C=C([Pt])CO\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.9529365102554657e-31\n", - "Kc = 9.99708792916859e22\n", - "HX+C=C=C=O<=>O=C=CC[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.4091973858076736e-32\n", - "Kc = 1.225336127134283e24\n", - "vacantX+vacantX+C=C=C=O<=>OCX+C=C=[Pt]\n", - "kf = 0.8504584217531632\n", - "krev = 1.347597642765549e15\n", - "Kc = 6.310922450174717e-16\n", - "proton+O=C(O)C=[Pt]<=>CHX+O=CO\n", - "kf = 7.88145235948431e7\n", - "krev = 1.995696153847229e-7\n", - "Kc = 3.949224607308452e14\n", - "proton+O=C(O)C#[Pt]<=>O=C(O)C=[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.424855572557093e-13\n", - "Kc = 3.3670688615684534e22\n", - "vacantX+vacantX+CC=C=O<=>CH3X+O=C=C[Pt]\n", - "kf = 0.0008567749561878586\n", - "krev = 1.2359860589695025e13\n", - "Kc = 6.931914401220598e-17\n", - "vacantX+vacantX+CC=C=O<=>HX+O=C=CC[Pt]\n", - "kf = 2.2773385768535307e-19\n", - "krev = 181.8091471864856\n", - "Kc = 1.2525984594810374e-21\n", - "proton+O=C=CCO[Pt]<=>OX+CC=C=O\n", - "kf = 3.801213612232799e6\n", - "krev = 3.4005935521726275e-15\n", - "Kc = 1.1178088630451637e21\n", - "proton+CC(=O)[Pt]<=>CC=O.[Pt]\n", - "kf = 2.2108223076011086e9\n", - "krev = 2.493722128340101e-11\n", - "Kc = 8.865551949337277e19\n", - "proton+O=CC[Pt]<=>CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0175396707648368e-24\n", - "Kc = 2.456906665978799e34\n", - "vacantX+CC=O<=>CC=O.[Pt]\n", - "kf = 412885.969273148\n", - "krev = 2.625517699834265\n", - "Kc = 157258.8786200951\n", - "proton+CC=[Pt]<=>CHX+CH4\n", - "kf = 3.754229088708618e7\n", - "krev = 3.193900280463504e-10\n", - "Kc = 1.1754371642948722e17\n", - "proton+CC#[Pt]<=>CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.101069134371629e-9\n", - "Kc = 3.086012424450092e18\n", - "vacantX+vacantX+CC=O<=>OX+CC=[Pt]\n", - "kf = 6.186864182993887e-31\n", - "krev = 2.034915252803989e19\n", - "Kc = 3.04035471475717e-50\n", - "vacantX+vacantX+CC=C=O<=>OCX+CC=[Pt]\n", - "kf = 5.619880038277716e-8\n", - "krev = 4.919193785592355e16\n", - "Kc = 1.14243924578405e-24\n", - "vacantX+vacantX+CC<=>CH3X+CH3X\n", - "kf = 1.6866972609475142e-22\n", - "krev = 6.547125244410207e13\n", - "Kc = 2.576241018739606e-36\n", - "proton+O=C=CC[Pt]<=>CC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.381078389100095e-19\n", - "Kc = 1.0499444333476355e29\n", - "vacantX+CC=C=O<=>CC=C=O.[Pt]\n", - "kf = 365995.57053717994\n", - "krev = 187509.1639624155\n", - "Kc = 1.9518809790573244\n", - "proton+O=C(O)C[Pt]<=>CH2X+O=CO\n", - "kf = 5.038535015011119e-9\n", - "krev = 7.877133180076684e-5\n", - "Kc = 6.396407042799381e-5\n", - "HOX+C=C=O<=>O=C(O)C[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.348252838458729e-29\n", - "Kc = 4.5553052781738184e20\n", - "vacantX+vacantX+CC(=O)O<=>HX+O=C(O)C[Pt]\n", - "kf = 1.1112170024966995e-23\n", - "krev = 36323.66987445037\n", - "Kc = 3.0592090676342045e-28\n", - "proton+O=C(O)C=[Pt]<=>O=C(O)C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0876086200539217e-33\n", - "Kc = 2.2986209872776243e43\n", - "vacantX+vacantX+O=C=C=CO<=>OC=[Pt]+O=C=C=[Pt]\n", - "kf = 0.004371453552681894\n", - "krev = 1.2572855491392857e13\n", - "Kc = 3.476897953431907e-16\n", - "HX+O=C=C=CO<=>O=C=CC(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.3635197599529065e-33\n", - "Kc = 1.9017841755847633e25\n", - "HX+O=C=C=CO<=>O=C=C([Pt])CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 6.797711819853139e-22\n", - "Kc = 3.814695843684052e13\n", - "proton+O=C(O)CC#[Pt]<=>CX+CC(=O)O\n", - "kf = 0.12574987603391333\n", - "krev = 9.921358720719502e-5\n", - "Kc = 1267.4662772882168\n", - "proton+CC([Pt])=C=O<=>CH4+O=C=C=[Pt]\n", - "kf = 49487.72961177987\n", - "krev = 1.2730900614037961e-24\n", - "Kc = 3.8872135689451003e28\n", - "HX+C=C=C=O<=>CC([Pt])=C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.301177455844525e-32\n", - "Kc = 1.2828548214436644e24\n", - "vacantX+vacantX+CC=C=O<=>HX+CC([Pt])=C=O\n", - "kf = 4.581183222917958e-20\n", - "krev = 34.93361388628861\n", - "Kc = 1.3113968791863429e-21\n", - "proton+CC([Pt])=C=O<=>CC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.492848961236613e-19\n", - "Kc = 1.0028686209532082e29\n", - "CH3X+O=C=C=O<=>CC(=C=O)O[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.951682102619952e-64\n", - "Kc = 1.9647454732667077e56\n", - "proton+CC(=C=O)O[Pt]<=>OX+CC=C=O\n", - "kf = 1.920567374031219e-6\n", - "krev = 5.0434729686975995e-5\n", - "Kc = 0.03808025513274787\n", - "vacantX+C=C<=>C=C.[Pt]\n", - "kf = 36.21750369826068\n", - "krev = 0.32335117013731834\n", - "Kc = 112.00671914340097\n", - "vacantX+vacantX+C=CO<=>HOX+C=C[Pt]\n", - "kf = 1.7018617233469498e-12\n", - "krev = 4.164837143763027e13\n", - "Kc = 4.086262354568991e-26\n", - "vacantX+vacantX+C=C<=>HX+C=C[Pt]\n", - "kf = 6.071347272542775e-23\n", - "krev = 1180.067101472276\n", - "Kc = 5.144916983930861e-26\n", - "vacantX+vacantX+C=CC=O<=>CHOX+C=C[Pt]\n", - "kf = 0.3274906030624493\n", - "krev = 2.9425898600264806e14\n", - "Kc = 1.1129332276687114e-15\n", - "vacantX+vacantX+C=COC=O<=>CHO2X+C=C[Pt]\n", - "kf = 0.2513917911405871\n", - "krev = 1.0405847657707406e16\n", - "Kc = 2.4158703779829617e-17\n", - "proton+C=C=[Pt]<=>C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.446578752089028e-33\n", - "Kc = 1.0218350820979533e43\n", - "proton+C=C[Pt]<=>CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 31.775139733809926\n", - "Kc = 7.867786014296917e8\n", - "proton+C=C[Pt]<=>C=C.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.7043133558442046e-25\n", - "Kc = 1.4668664019015827e35\n", - "proton+C=CC#[Pt]<=>CX+C=C\n", - "kf = 1.0856530221273585e-15\n", - "krev = 0.12983129718682296\n", - "Kc = 8.36202861444987e-15\n", - "vacantX+CC(=O)O<=>CC(=O)O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 181176.05501028927\n", - "Kc = 1.9518809818483447\n", - "proton+CC(=O)O[Pt]<=>CC(=O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.133892027559991e-24\n", - "Kc = 6.04756965913213e33\n", - "proton+O=C(O)C[Pt]<=>CC(=O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.815284645396005e-26\n", - "Kc = 4.2990157016290936e35\n", - "proton+C=CC(=O)[Pt]<=>OCX+C=C\n", - "kf = 7.087170621400232e6\n", - "krev = 2.9783308105065206e-7\n", - "Kc = 2.3795780496911715e13\n", - "vacantX+vacantX+C=CC=O<=>HX+C=CC(=O)[Pt]\n", - "kf = 3.052485738368744e-11\n", - "krev = 0.0007099643372969683\n", - "Kc = 4.29949164769375e-8\n", - "HX+C=C=C=O<=>C=CC(=O)[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 5.604440911093213e-48\n", - "Kc = 5.267388203494818e39\n", - "HX+O=C=CC=O<=>O=CC=CO[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 5.6159867257682645e-34\n", - "Kc = 4.61739037002591e25\n", - "proton+O=C=CC=O.[Pt]<=>O=CC=CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 9.013912308921113e-18\n", - "Kc = 2.7734904826239954e27\n", - "proton+O=CC=CO[Pt]<=>OX+C=CC=O\n", - "kf = 3.6615493516163485e-10\n", - "krev = 9.407550626549198e-5\n", - "Kc = 3.892138875429521e-6\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC=CO[Pt]\n", - "kf = 4.135805741920728e-10\n", - "krev = 0.028732529553568358\n", - "Kc = 1.4394158141245496e-8\n", - "HX+C=C=O<=>C=CO[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.272169613200064e-8\n", - "Kc = 0.46029640012283785\n", - "proton+C=C=O.[Pt]<=>C=CO[Pt]\n", - "kf = 2.7021695253394946e-5\n", - "krev = 3753.979595717479\n", - "Kc = 7.19814654406251e-9\n", - "vacantX+vacantX+C=CO<=>HX+C=CO[Pt]\n", - "kf = 1.5839272910037507e-20\n", - "krev = 3600.161649580889\n", - "Kc = 4.399600476795654e-24\n", - "proton+C=CO[Pt]<=>OX+C=C\n", - "kf = 6.694428008398142e6\n", - "krev = 4.294813980591457e-9\n", - "Kc = 1.5587236231070068e15\n", - "vacantX+vacantX+C=COC=O<=>CHOX+C=CO[Pt]\n", - "kf = 0.024290856013790354\n", - "krev = 3.5586883050271985e15\n", - "Kc = 6.825789148062155e-18\n", - "vacantX+vacantX+O=CCCO<=>OC[Pt]+O=CC[Pt]\n", - "kf = 2.162232232095232e-5\n", - "krev = 5.66671683371172e13\n", - "Kc = 3.815670158833332e-19\n", - "proton+C=COC(=O)[Pt]<=>OCX+C=CO\n", - "kf = 8.547694380469097e6\n", - "krev = 5.219823560516419e-10\n", - "Kc = 1.637544695020963e16\n", - "vacantX+vacantX+C=COC=O<=>HX+C=COC(=O)[Pt]\n", - "kf = 3.5117597357119104e-15\n", - "krev = 0.7837038908782975\n", - "Kc = 4.480977798612533e-15\n", - "CO2+C=C[Pt]<=>C=COC(=O)[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.08399332498323721\n", - "Kc = 7.789900440580834e-7\n", - "proton+C=COC#[Pt]<=>CX+C=CO\n", - "kf = 3.59319568894763e-23\n", - "krev = 3.7552909398960855e-5\n", - "Kc = 9.568355012853036e-19\n", - "vacantX+vacantX+CCC=O<=>CH3X+O=CC[Pt]\n", - "kf = 1.2257627381394946e-12\n", - "krev = 3.270257576074817e14\n", - "Kc = 3.748214657790771e-27\n", - "proton+CC(O)=[Pt]<=>OC#[Pt]+CH4\n", - "kf = 7.023325690411809e6\n", - "krev = 0.001122962882704699\n", - "Kc = 6.254281239906934e9\n", - "proton+CC(=O)[Pt]<=>CC(O)=[Pt]\n", - "kf = 9.881755573608883e9\n", - "krev = 1.0085447542339819e12\n", - "Kc = 0.009798033782957261\n", - "proton+CC(O)=[Pt]<=>H2O+CC#[Pt]\n", - "kf = 7.254296675241664e9\n", - "krev = 2.8720393080667615e-6\n", - "Kc = 2.5258347456688205e15\n", - "vacantX+vacantX+CC(=O)O<=>OX+CC(O)=[Pt]\n", - "kf = 1.1829749543892744e-33\n", - "krev = 3.758913107590896e15\n", - "Kc = 3.1471197139415875e-49\n", - "vacantX+vacantX+CC(O)=C=O<=>CH3X+O=C=C(O)[Pt]\n", - "kf = 1.049990631922765e-6\n", - "krev = 1.7955210884029898e15\n", - "Kc = 5.847832357439309e-22\n", - "vacantX+vacantX+CC(O)=C=O<=>HOX+CC([Pt])=C=O\n", - "kf = 0.0029164033711847528\n", - "krev = 3.4437539939134434e12\n", - "Kc = 8.468675103794464e-16\n", - "vacantX+vacantX+CC(O)=C=O<=>HX+CC(=C=O)O[Pt]\n", - "kf = 1.7528367761452354e-6\n", - "krev = 1.1970864565480504e-5\n", - "Kc = 0.14642524494009906\n", - "vacantX+vacantX+CC(O)=C=O<=>OCX+CC(O)=[Pt]\n", - "kf = 65.80946386077328\n", - "krev = 1217.699742052305\n", - "Kc = 0.054044081301896585\n", - "vacantX+vacantX+C=CC=O<=>HX+O=CC=C[Pt]\n", - "kf = 6.342176392543457e-21\n", - "krev = 776.2437464870187\n", - "Kc = 8.170341366672147e-24\n", - "vacantX+vacantX+O=CC=CO<=>HOX+O=CC=C[Pt]\n", - "kf = 4.672349699632388e-15\n", - "krev = 8.81363422062413e13\n", - "Kc = 5.301274800693419e-29\n", - "proton+O=CC=C[Pt]<=>O=CCC=[Pt]\n", - "kf = 1.2673656466904085e10\n", - "krev = 1.0824082827935274e8\n", - "Kc = 117.08757839689983\n", - "proton+C=CC(=O)O[Pt]<=>OX+C=CC=O\n", - "kf = 4.524546416801015\n", - "krev = 7.68227583414659e-9\n", - "Kc = 5.889591202505473e8\n", - "CO2+C=C[Pt]<=>C=CC(=O)O[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 450683.30306117237\n", - "Kc = 1.4517947189269602e-13\n", - "vacantX+vacantX+O=C=CO<=>OX+OC=C=[Pt]\n", - "kf = 7.548264554696059e-34\n", - "krev = 5.749061160710156e15\n", - "Kc = 1.3129560364189368e-49\n", - "proton+OC=C=[Pt]<=>OCC#[Pt]\n", - "kf = 0.00032547344886471076\n", - "krev = 1.1489507349403094e-46\n", - "Kc = 2.832788551909668e42\n", - "vacantX+vacantX+O=C=C=CO<=>OCX+OC=C=[Pt]\n", - "kf = 1.463392220587488e-22\n", - "krev = 7.968303762369095e13\n", - "Kc = 1.8365166090912173e-36\n", - "proton+CC[Pt]<=>CH2X+CH4\n", - "kf = 1.4846524062695914\n", - "krev = 9.859129077434927e-6\n", - "Kc = 150586.56749586415\n", - "HX+C=C<=>CC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 3.1627439012977165e-12\n", - "Kc = 25911.109388377805\n", - "vacantX+vacantX+CCO<=>HOX+CC[Pt]\n", - "kf = 2.1035625708276702e-15\n", - "krev = 1.0019023766861524e15\n", - "Kc = 2.099568400850909e-30\n", - "vacantX+vacantX+CCOC=O<=>CHO2X+CC[Pt]\n", - "kf = 0.08561452397466171\n", - "krev = 3.215769317238553e17\n", - "Kc = 2.6623341268826044e-19\n", - "vacantX+vacantX+CCOO<=>OO[Pt]+CC[Pt]\n", - "kf = 1.262172875849309e-6\n", - "krev = 1.5596341944506717e13\n", - "Kc = 8.092749443044025e-20\n", - "proton+CC=[Pt]<=>CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.602708332438123e-27\n", - "Kc = 2.9060615603731233e36\n", - "vacantX+vacantX+CC<=>HX+CC[Pt]\n", - "kf = 8.697106954471648e-14\n", - "krev = 5.359609736165605e16\n", - "Kc = 1.6227127314485718e-30\n", - "proton+C=C.[Pt]<=>CC[Pt]\n", - "kf = 5.504599623053448e9\n", - "krev = 0.3531497863658743\n", - "Kc = 1.558715263486103e10\n", - "vacantX+vacantX+CCC=O<=>CHOX+CC[Pt]\n", - "kf = 0.0004422945453165714\n", - "krev = 9.363325052982716e15\n", - "Kc = 4.723691026572629e-20\n", - "vacantX+vacantX+CC(O)C=O<=>CH3X+O=CC(O)[Pt]\n", - "kf = 9.477814531468979e-7\n", - "krev = 7.52142668687151e15\n", - "Kc = 1.2601086105129898e-22\n", - "proton+CCC#[Pt]<=>CX+CC\n", - "kf = 3.73018742862406e-11\n", - "krev = 0.075105066117345\n", - "Kc = 4.966625583946592e-10\n", - "C=O+CH3X<=>CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.1808191230067762e-17\n", - "Kc = 3.354171909251678e9\n", - "HX+CC=O<=>CCO[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 2.639709061724686e-6\n", - "Kc = 0.012387213631168494\n", - "vacantX+vacantX+CCO<=>HX+CCO[Pt]\n", - "kf = 5.372480262216755e-24\n", - "krev = 2113.809062877283\n", - "Kc = 2.5416109508508876e-27\n", - "vacantX+vacantX+CCOC=O<=>CHOX+CCO[Pt]\n", - "kf = 4.80530366959931e-5\n", - "krev = 5.681813674074216e13\n", - "Kc = 8.457341168235823e-19\n", - "vacantX+vacantX+CCOO<=>HOX+CCO[Pt]\n", - "kf = 3.028654941635431e8\n", - "krev = 1.2132864881112858e-12\n", - "Kc = 2.496240559268171e20\n", - "proton+CC=O.[Pt]<=>CCO[Pt]\n", - "kf = 19418.796323941955\n", - "krev = 3658.802750537776\n", - "Kc = 5.30741820424393\n", - "proton+CCO[Pt]<=>OX+CC\n", - "kf = 1.5180806810718186e7\n", - "krev = 3.4536717602694347e-12\n", - "Kc = 4.395555763392486e18\n", - "proton+CCOC(=O)[Pt]<=>OCX+CCO\n", - "kf = 1.100364657251968e9\n", - "krev = 4.5302115405928314e-10\n", - "Kc = 2.4289476272623954e18\n", - "vacantX+vacantX+CCOC=O<=>HX+CCOC(=O)[Pt]\n", - "kf = 2.5742212027881315e-15\n", - "krev = 0.39729482671494754\n", - "Kc = 6.479372570927264e-15\n", - "CO2+CC[Pt]<=>CCOC(=O)[Pt]\n", - "kf = 3.860701485876577e-7\n", - "krev = 0.0037771400241392917\n", - "Kc = 0.00010221229451921966\n", - "CH3X+C=C=O<=>CCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.9339597186194493e-34\n", - "Kc = 1.7308289628845924e26\n", - "HX+CC=C=O<=>CCC(=O)[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 2.728234417234893e-33\n", - "Kc = 1.0624138213938816e25\n", - "proton+CCC(=O)[Pt]<=>OCX+CC\n", - "kf = 3.3183098775357734e7\n", - "krev = 1.723115430616528e-10\n", - "Kc = 1.9257618024745373e17\n", - "proton+CC=C=O.[Pt]<=>CCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.816709270833084e-23\n", - "Kc = 3.667458740974689e32\n", - "vacantX+vacantX+CCC=O<=>HX+CCC(=O)[Pt]\n", - "kf = 1.3037608552158366e-12\n", - "krev = 0.18236199715464047\n", - "Kc = 7.149301255514685e-12\n", - "vacantX+vacantX+C=C(O)C=O<=>CH2X+O=CC(O)=[Pt]\n", - "kf = 3.506980389191063e-59\n", - "krev = 1.6121784785918364e12\n", - "Kc = 2.1753053001019147e-71\n", - "proton+CCOC#[Pt]<=>CX+CCO\n", - "kf = 1.6403573057503937e-22\n", - "krev = 1.0480859144262605e-13\n", - "Kc = 1.5650981309565184e-9\n", - "proton+CCC(=O)O[Pt]<=>OX+CCC=O\n", - "kf = 5.622114816602621e-8\n", - "krev = 4.785365563630673e-7\n", - "Kc = 0.11748558687619057\n", - "CO2+CC[Pt]<=>CCC(=O)O[Pt]\n", - "kf = 3.860701485876577e-7\n", - "krev = 2.2515045234693432e-8\n", - "Kc = 17.147207325738\n", - "vacantX+vacantX+OC=CCO<=>OC=[Pt]+OCC=[Pt]\n", - "kf = 3.6700973989487563e-44\n", - "krev = 3.0504263460080312e13\n", - "Kc = 1.203142440646588e-57\n", - "proton+CC(=C=O)O[Pt]<=>CC(O)=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 27.83415070046663\n", - "Kc = 8.981772165076653e8\n", - "vacantX+CC(O)=C=O<=>CC(O)=C=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 165389.73964983693\n", - "Kc = 1.9518801026953096\n", - "proton+OOC=[Pt]<=>OO+CHX\n", - "kf = 2.8719882764673755e7\n", - "krev = 8.077545633440945e-25\n", - "Kc = 3.555520955000709e31\n", - "proton+OOC=[Pt]<=>OOC[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.62255074484058e-37\n", - "Kc = 2.899374064566577e46\n", - "proton+OOC#[Pt]<=>OOC=[Pt]\n", - "kf = 3.432151727081939e-44\n", - "krev = 3342.777740155216\n", - "Kc = 1.0267364431242663e-47\n", - "vacantX+vacantX+C=CCO<=>CH2X+OCC=[Pt]\n", - "kf = 3.3256293066300124e-48\n", - "krev = 2.638642223210571e15\n", - "Kc = 1.2603562837645906e-63\n", - "vacantX+vacantX+C=CCO<=>OC[Pt]+C=C[Pt]\n", - "kf = 1.4930923415267688e-9\n", - "krev = 1.1121057711212152e14\n", - "Kc = 1.3425812366942817e-23\n", - "vacantX+OO<=>OO.[Pt]\n", - "kf = 469882.2241291155\n", - "krev = 15.560302693769444\n", - "Kc = 30197.498941795184\n", - "proton+OO[Pt]<=>OO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.110596489625074e-24\n", - "Kc = 2.251042591395165e34\n", - "C=O+CO[Pt]<=>COCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 9.545218685674386e-14\n", - "Kc = 414937.62088874576\n", - "HX+COC=O<=>COCO[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 0.02522938529859348\n", - "Kc = 1.1100614687459063e-6\n", - "vacantX+vacantX+COCO<=>HX+COCO[Pt]\n", - "kf = 1.0488506310161173e-19\n", - "krev = 521.1543106644776\n", - "Kc = 2.0125529225284944e-22\n", - "proton+COC=O.[Pt]<=>COCO[Pt]\n", - "kf = 0.6792883990466445\n", - "krev = 3726.123137157573\n", - "Kc = 0.00018230433457033608\n", - "proton+COCO[Pt]<=>OX+COC\n", - "kf = 5093.375621150868\n", - "krev = 5.977614318003391e-7\n", - "Kc = 8.520749834613165e9\n", - "CO[Pt]+C=C=O<=>COCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.680149232421768e-23\n", - "Kc = 1.9922953446306685e15\n", - "HX+COC=C=O<=>COCC(=O)[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 2.661991446097411e-38\n", - "Kc = 9.604054388173769e29\n", - "proton+COCC(=O)[Pt]<=>OCX+COC\n", - "kf = 8.734746675052269e7\n", - "krev = 2.1771371890779743e-8\n", - "Kc = 4.012033196103488e15\n", - "vacantX+vacantX+COCC=O<=>HX+COCC(=O)[Pt]\n", - "kf = 2.290241001822749e-10\n", - "krev = 0.0004872161822843353\n", - "Kc = 4.7006669423105973e-7\n", - "proton+COCOC#[Pt]<=>CX+COCO\n", - "kf = 3.2770328923262016e-17\n", - "krev = 2.1864147814239428e-13\n", - "Kc = 0.0001498815741719407\n", - "proton+COCC#[Pt]<=>CX+COC\n", - "kf = 1.433200340176918\n", - "krev = 0.00041586763423335837\n", - "Kc = 3446.289689792732\n", - "proton+COC[Pt]<=>CH2X+CO-2\n", - "kf = 0.2769010105768301\n", - "krev = 3.0099119392563808e-6\n", - "Kc = 91996.38267332179\n", - "vacantX+vacantX+COCO<=>HOX+COC[Pt]\n", - "kf = 8.90444501639475e-13\n", - "krev = 8.409201083164982e12\n", - "Kc = 1.0588931015362724e-25\n", - "C=O+CH3X<=>COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 8.422687202008296e-11\n", - "Kc = 470.23832623775377\n", - "vacantX+vacantX+COC<=>HX+COC[Pt]\n", - "kf = 2.786306429788959e-20\n", - "krev = 52.25975865319748\n", - "Kc = 5.3316481009398625e-22\n", - "vacantX+vacantX+COCC=O<=>CHOX+COC[Pt]\n", - "kf = 1.4060776479118306e6\n", - "krev = 6.613786245273692e13\n", - "Kc = 2.1259798786461146e-8\n", - "vacantX+vacantX+C=C=CO<=>OC=[Pt]+C=C=[Pt]\n", - "kf = 1.5975335437882445e-34\n", - "krev = 2.2957840869759923e8\n", - "Kc = 6.958553083676594e-43\n", - "vacantX+vacantX+C=C=CO<=>CH2X+OC=C=[Pt]\n", - "kf = 9.363402027600756e-56\n", - "krev = 7.047835211144391e9\n", - "Kc = 1.328550079149818e-65\n", - "vacantX+vacantX+COC=O<=>OX+COC=[Pt]\n", - "kf = 1.1797200153280936e-59\n", - "krev = 4.3408253155831816e16\n", - "Kc = 2.7177320660497494e-76\n", - "proton+COC=[Pt]<=>CHX+CO-2\n", - "kf = 479145.9852086257\n", - "krev = 1.0449825701778588e-33\n", - "Kc = 4.5852055228736854e38\n", - "proton+COC#[Pt]<=>COC=[Pt]\n", - "kf = 90933.51053402986\n", - "krev = 2739.427130274527\n", - "Kc = 33.194352764155155\n", - "vacantX+vacantX+COC=C=O<=>OCX+COC=[Pt]\n", - "kf = 2.7777170398864307e-21\n", - "krev = 2.5089215324603047e13\n", - "Kc = 1.107135876490541e-34\n", - "proton+COC=[Pt]<=>COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3472876439887766e-48\n", - "Kc = 1.8555799952254487e58\n", - "vacantX+COC=C=O<=>COC=C=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 1179.0380002145982\n", - "Kc = 273.8002862958761\n", - "proton+COC=C=O.[Pt]<=>COCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.0577777781824875e-25\n", - "Kc = 2.3634453772469967e35\n", - "vacantX+vacantX+C=C=C<=>CH2X+C=C=[Pt]\n", - "kf = 4.78083312177258e-41\n", - "krev = 4.774618642094983e15\n", - "Kc = 1.0013015656628172e-56\n", - "proton+O=C=COC[Pt]<=>CH2X+O=C=CO\n", - "kf = 4.988523456059943e-5\n", - "krev = 0.0009299241102698363\n", - "Kc = 0.05364441464596958\n", - "C=O+O=C=C[Pt]<=>O=C=COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.852140732586457e13\n", - "Kc = 2.1384283940268284e-21\n", - "vacantX+vacantX+COC=C=O<=>HX+O=C=COC[Pt]\n", - "kf = 3.256466928453685e-21\n", - "krev = 26.50445975246776\n", - "Kc = 1.2286486722863626e-22\n", - "proton+O=C=COC[Pt]<=>COC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.6649798034152577e-22\n", - "Kc = 1.5015197150571575e32\n", - "CH3X+O=C=C=O<=>COC([Pt])=C=O\n", - "kf = 5.799304049644909e-8\n", - "krev = 3.1615249923835833e-35\n", - "Kc = 1.8343375629216876e27\n", - "proton+COC([Pt])=C=O<=>CO-2+O=C=C=[Pt]\n", - "kf = 313658.31445379555\n", - "krev = 1.256306436150439e-34\n", - "Kc = 2.496670441448219e39\n", - "vacantX+vacantX+COC=C=O<=>HX+COC([Pt])=C=O\n", - "kf = 2.779636780044878e-20\n", - "krev = 3.601218910546807\n", - "Kc = 7.718599866018197e-21\n", - "proton+COC([Pt])=C=O<=>COC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0459713323621888e-20\n", - "Kc = 2.390122867281724e30\n", - "vacantX+vacantX+C=C=C(O)O<=>OC(O)=[Pt]+C=C=[Pt]\n", - "kf = 2.937512138355157e-45\n", - "krev = 8.778136400287878e10\n", - "Kc = 3.34639609639561e-56\n", - "proton+O=C=COC=[Pt]<=>CHX+O=C=CO\n", - "kf = 2.102599834403735e7\n", - "krev = 1.6989476123058672e-25\n", - "Kc = 1.237589563782969e32\n", - "proton+O=C=COC#[Pt]<=>O=C=COC=[Pt]\n", - "kf = 1080.8801129554665\n", - "krev = 2888.2699525834805\n", - "Kc = 0.37423098626520285\n", - "proton+O=C=COC=[Pt]<=>O=C=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.9106920181466426e-48\n", - "Kc = 8.589022763019266e57\n", - "proton+CCOO[Pt]<=>OX+CCO\n", - "kf = 169.16425212622386\n", - "krev = 5.6416707126946964e-58\n", - "Kc = 2.9984779463568512e59\n", - "vacantX+vacantX+CCOO<=>HX+CCOO[Pt]\n", - "kf = 1.893449523720139e-21\n", - "krev = 0.6694879211592951\n", - "Kc = 2.8282056537202555e-21\n", - "O=O+CC[Pt]<=>CCOO[Pt]\n", - "kf = 4.5276782379965965e-7\n", - "krev = 1.4949208469184493e-38\n", - "Kc = 3.0287076719344122e31\n", - "vacantX+vacantX+C=CC(=O)O<=>CH2X+O=C(O)C=[Pt]\n", - "kf = 4.72289540105198e-39\n", - "krev = 9.498795808374404e14\n", - "Kc = 4.9720990916429044e-54\n", - "vacantX+vacantX+C=CC(=O)O<=>CO2HX+C=C[Pt]\n", - "kf = 5.354197885861111e7\n", - "krev = 1.376967106369583e14\n", - "Kc = 3.888399266107105e-7\n", - "vacantX+vacantX+C=CC(=O)O<=>HOX+C=CC(=O)[Pt]\n", - "kf = 0.03947248649742643\n", - "krev = 2.5171232142616846e11\n", - "Kc = 1.5681586929785789e-13\n", - "vacantX+vacantX+C=CC(=O)O<=>HX+C=CC(=O)O[Pt]\n", - "kf = 2.4490000178339845e-20\n", - "krev = 458.0011375503109\n", - "Kc = 5.3471483300955e-23\n", - "proton+O=C=C=CO.[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.4322611471299928e-17\n", - "Kc = 1.7454917387164855e27\n", - "proton+O=C=C=CO.[Pt]<=>O=C=C([Pt])CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 7.140416160377535e-6\n", - "Kc = 3.5011964903006675e15\n", - "vacantX+O=C=C=CO<=>O=C=C=CO.[Pt]\n", - "kf = 327433.4917974331\n", - "krev = 0.4460204906723957\n", - "Kc = 734122.0832787583\n", - "HX+O=C=C=C=O<=>O=C=C=C(O)[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 1.3048903398306852e-5\n", - "Kc = 0.004032923533638046\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C=C(O)[Pt]\n", - "kf = 4235.342411204313\n", - "krev = 12.909334546967292\n", - "Kc = 328.0837130523738\n", - "proton+O=C=C=C(O)[Pt]<=>O=C=CC(O)=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1053.6449933824201\n", - "Kc = 2.3727156828928486e7\n", - "vacantX+vacantX+O=C=C=CO<=>HX+O=C=C=C(O)[Pt]\n", - "kf = 8.233814429551885e-18\n", - "krev = 0.5740049812746953\n", - "Kc = 1.434449995759099e-17\n", - "proton+O=C=C=C(O)[Pt]<=>O=C=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.249904355928212e-21\n", - "Kc = 3.4483213533096645e30\n", - "vacantX+vacantX+CC=CO<=>OC=[Pt]+CC=[Pt]\n", - "kf = 1.6816353348966163e-33\n", - "krev = 8.021148128032321e14\n", - "Kc = 2.0965020319468163e-48\n", - "proton+O=C=C=C[Pt]<=>O=C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.0269882986128818\n", - "Kc = 9.263273820479827e11\n", - "vacantX+vacantX+C=C=C=O<=>HX+O=C=C=C[Pt]\n", - "kf = 3.6772489817592154e-10\n", - "krev = 0.00723599763490509\n", - "Kc = 5.081882509221477e-8\n", - "vacantX+vacantX+O=C=C=CO<=>HOX+O=C=C=C[Pt]\n", - "kf = 0.00020826365169953766\n", - "krev = 1.0739954827079557e13\n", - "Kc = 1.939148302322696e-17\n", - "vacantX+OC=CO<=>OC=CO.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.48171019889246675\n", - "Kc = 734122.0861712244\n", - "vacantX+vacantX+C=CC<=>CH2X+CC=[Pt]\n", - "kf = 3.8695500910369183e-44\n", - "krev = 2.1644248520711738e17\n", - "Kc = 1.787795999169979e-61\n", - "vacantX+vacantX+C=CC<=>CH3X+C=C[Pt]\n", - "kf = 1.1726078415532691e-17\n", - "krev = 1.59532697721828e15\n", - "Kc = 7.350266486422159e-33\n", - "HX+O=C=CO<=>OC=C(O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 2.762063581333058e-24\n", - "Kc = 1.0314187634521844e16\n", - "vacantX+vacantX+OC=CO<=>HX+OC=C(O)[Pt]\n", - "kf = 6.089904416870865e-20\n", - "krev = 3.928023437111271\n", - "Kc = 1.550373747604081e-20\n", - "proton+O=C=CO.[Pt]<=>OC=C(O)[Pt]\n", - "kf = 6.4368819183992445e7\n", - "krev = 6.799608634080986e-11\n", - "Kc = 9.466547657075904e17\n", - "proton+OC=C(O)[Pt]<=>H2O+OC=C=[Pt]\n", - "kf = 5.262467142275111e-7\n", - "krev = 0.6251329939834178\n", - "Kc = 8.418156125054411e-7\n", - "proton+OC=C(O)[Pt]<=>OC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.835798651062412e-24\n", - "Kc = 3.190485247679302e33\n", - "vacantX+vacantX+OC=CO<=>HOX+OC=C[Pt]\n", - "kf = 1.882970379851619e-8\n", - "krev = 6.2613640604613945e13\n", - "Kc = 3.0072846134950095e-22\n", - "vacantX+vacantX+C=CO<=>HX+OC=C[Pt]\n", - "kf = 5.986889507133711e-22\n", - "krev = 1492.047811549125\n", - "Kc = 4.0125319448830507e-25\n", - "proton+OC=C[Pt]<=>OCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.693803965028289e7\n", - "Kc = 1475.967733939179\n", - "vacantX+vacantX+O=CC=CO<=>CHOX+OC=C[Pt]\n", - "kf = 3.6404040231768274e-5\n", - "krev = 5.1339082800935775e14\n", - "Kc = 7.090901949480236e-20\n", - "proton+OC=C=[Pt]<=>OC=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.9001266800545872e-45\n", - "Kc = 1.3157017509633512e55\n", - "vacantX+vacantX+OC=CCO<=>OC[Pt]+OC=C[Pt]\n", - "kf = 1.39754480380523e-13\n", - "krev = 4.435737343310229e14\n", - "Kc = 3.1506482364492156e-28\n", - "vacantX+vacantX+CC=CO<=>CH3X+OC=C[Pt]\n", - "kf = 3.0518560755450534e-15\n", - "krev = 1.440283576497463e15\n", - "Kc = 2.1189272205454667e-30\n", - "vacantX+vacantX+CC=C(O)O<=>OC(O)=[Pt]+CC=[Pt]\n", - "kf = 3.314404876424973e-50\n", - "krev = 3.298291971460818e17\n", - "Kc = 1.0048852269912959e-67\n", - "HX+O=C=CO<=>OC=CO[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 5.830973747204281e-42\n", - "Kc = 4.885709192226705e33\n", - "vacantX+vacantX+OC=CO<=>HX+OC=CO[Pt]\n", - "kf = 6.3392542923960805e-6\n", - "krev = 0.0008631955285686626\n", - "Kc = 0.007343937824733329\n", - "proton+O=C=CO.[Pt]<=>OC=CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.575140256117379e-26\n", - "Kc = 4.4841921192150256e35\n", - "proton+OC=CO[Pt]<=>OX+C=CO\n", - "kf = 2.262727495050209e-8\n", - "krev = 2.5678564004292932e-5\n", - "Kc = 0.0008811736881672694\n", - "proton+OC=CO[Pt]<=>OC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.711725523568878e-6\n", - "Kc = 6.73541182968781e15\n", - "proton+OC=COC#[Pt]<=>CX+OC=CO\n", - "kf = 2.2492341197526439e-29\n", - "krev = 0.00020529518482061674\n", - "Kc = 1.0956097785332785e-25\n", - "vacantX+vacantX+CCC(=O)O<=>CH3X+O=C(O)C[Pt]\n", - "kf = 8.997747599742267e-17\n", - "krev = 6.572577910715489e15\n", - "Kc = 1.368983026442782e-32\n", - "vacantX+vacantX+CCC(=O)O<=>CO2HX+CC[Pt]\n", - "kf = 3.388822996448631e-6\n", - "krev = 1.0293603282987281e15\n", - "Kc = 3.292163981148853e-21\n", - "vacantX+vacantX+CCC(=O)O<=>HOX+CCC(=O)[Pt]\n", - "kf = 2.1491486919570496e-14\n", - "krev = 4.131728096070369e12\n", - "Kc = 5.201573390081201e-27\n", - "vacantX+vacantX+CCC(=O)O<=>HX+CCC(=O)O[Pt]\n", - "kf = 2.415446383235281e-20\n", - "krev = 451.7273406124814\n", - "Kc = 5.347133472063615e-23\n", - "proton+O=C([Pt])C=CO<=>OCX+C=CO\n", - "kf = 224.18396606543615\n", - "krev = 8.215700647740584e-7\n", - "Kc = 2.728726078001508e8\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=C([Pt])C=CO\n", - "kf = 2.859565189776071e-11\n", - "krev = 0.000933578065584948\n", - "Kc = 3.06301668300697e-8\n", - "HX+O=C=C=CO<=>O=C([Pt])C=CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.1750295723598082e-43\n", - "Kc = 2.206855353748942e35\n", - "proton+O=C=C=CO.[Pt]<=>O=C([Pt])C=CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.234268290529092e-27\n", - "Kc = 2.0254915557527025e37\n", - "proton+OC=C(O)C#[Pt]<=>CX+OC=CO\n", - "kf = 2.8680661830740045e-24\n", - "krev = 729.307267106125\n", - "Kc = 3.932589612680575e-27\n", - "vacantX+vacantX+C=COO<=>OO[Pt]+C=C[Pt]\n", - "kf = 0.00256837059370255\n", - "krev = 1.2695573429161084e13\n", - "Kc = 2.0230441799526235e-16\n", - "vacantX+vacantX+C=COO<=>HOX+C=CO[Pt]\n", - "kf = 3.07907263663438e8\n", - "krev = 5.547742278067932e-15\n", - "Kc = 5.5501364019864025e22\n", - "vacantX+vacantX+C=COO<=>CH2X+OOC=[Pt]\n", - "kf = 7.483948884590266e-53\n", - "krev = 2.8103204909201245e17\n", - "Kc = 2.6630232775123643e-70\n", - "proton+OC=CC#[Pt]<=>CX+C=CO\n", - "kf = 1.0593841984272302e-19\n", - "krev = 13.369077699035607\n", - "Kc = 7.924138241066921e-21\n", - "proton+OCC[Pt]<=>CH2X+CO-2\n", - "kf = 3.9799160772985795e-6\n", - "krev = 0.00035437522440524626\n", - "Kc = 0.011230796633647675\n", - "vacantX+vacantX+OCCO<=>HOX+OCC[Pt]\n", - "kf = 2.110093084979835e-12\n", - "krev = 2.4085316622580622e14\n", - "Kc = 8.760910716040024e-27\n", - "HX+C=CO<=>OCC[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 1.1429411507382647e-15\n", - "Kc = 2.8609207088741057e7\n", - "HOX+C=C<=>OCC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 2.2750559854988554e-15\n", - "Kc = 3.602118089238167e7\n", - "proton+OCC=[Pt]<=>OCC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.1399343496076094e-34\n", - "Kc = 2.1931087530264836e44\n", - "vacantX+vacantX+CCO<=>HX+OCC[Pt]\n", - "kf = 4.51610258482867e-23\n", - "krev = 15472.547765874588\n", - "Kc = 2.918784063985339e-27\n", - "vacantX+vacantX+O=CCCO<=>CHOX+OCC[Pt]\n", - "kf = 2.0496526220764064\n", - "krev = 1.4633869198921762e15\n", - "Kc = 1.4006224835106677e-15\n", - "HX+C#C<=>C=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 2.375601900047824e-24\n", - "Kc = 3.580716650609497e16\n", - "CHOX+C#C<=>O=CC=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 3.2359557228060194e-16\n", - "Kc = 2.6287001452988416e8\n", - "HOX+C#C<=>OC=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 2.419253665005007e-25\n", - "Kc = 3.516108046777805e17\n", - "proton+OCCC#[Pt]<=>CX+CCO\n", - "kf = 0.036583470766554806\n", - "krev = 0.0005754138836916786\n", - "Kc = 63.577664361948486\n", - "OC[Pt]+C=C=O<=>O=C([Pt])CCO\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.869121889511259e-30\n", - "Kc = 1.7908695590280368e22\n", - "HX+O=C=CCO<=>O=C([Pt])CCO\n", - "kf = 2.5565910629172877e-8\n", - "krev = 3.7973012083800085e-37\n", - "Kc = 6.732652804247709e28\n", - "proton+O=C=CCO.[Pt]<=>O=C([Pt])CCO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.5089082544191712e-24\n", - "Kc = 1.6568270421201532e34\n", - "proton+O=C([Pt])CCO<=>OCX+CCO\n", - "kf = 9.600816617542319e7\n", - "krev = 3.185535798116408e-7\n", - "Kc = 3.0138781121904944e14\n", - "vacantX+vacantX+O=CCCO<=>HX+O=C([Pt])CCO\n", - "kf = 4.786286134347495e-11\n", - "krev = 0.0006355926831038164\n", - "Kc = 7.530429883135883e-8\n", - "vacantX+vacantX+C=COC<=>CO[Pt]+C=C[Pt]\n", - "kf = 1.9108708710628152e-14\n", - "krev = 5.750545812867103e12\n", - "Kc = 3.322938262290088e-27\n", - "vacantX+vacantX+C=COC<=>CH3X+C=CO[Pt]\n", - "kf = 8.809048609670953e-10\n", - "krev = 5.30334818480063e15\n", - "Kc = 1.6610353125441853e-25\n", - "vacantX+vacantX+C=COC<=>CH2X+COC=[Pt]\n", - "kf = 2.00333233616492e-67\n", - "krev = 2.0086736136424638e14\n", - "Kc = 9.973408932933319e-82\n", - "C=O+OC[Pt]<=>OCCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.726586049973397e-6\n", - "Kc = 0.00837955829095468\n", - "HX+O=CCO<=>OCCO[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 7.096612291679358e-6\n", - "Kc = 0.003946413774492056\n", - "vacantX+vacantX+OCCO<=>HX+OCCO[Pt]\n", - "kf = 1.0265256602604584e-26\n", - "krev = 112849.3186381155\n", - "Kc = 9.09642763154215e-32\n", - "proton+O=CCO.[Pt]<=>OCCO[Pt]\n", - "kf = 3.478307222117794e6\n", - "krev = 3581.5775849412535\n", - "Kc = 971.1662360023528\n", - "proton+OCCO[Pt]<=>OX+CCO\n", - "kf = 951266.6788585404\n", - "krev = 3.3388075163598663e-18\n", - "Kc = 2.8491210535420697e23\n", - "proton+OCCOC#[Pt]<=>CX+OCCO\n", - "kf = 6.336022152476698e-22\n", - "krev = 5.125095889500872e-13\n", - "Kc = 1.2362738744959868e-9\n", - "vacantX+vacantX+C=CC(O)O<=>OC(O)[Pt]+C=C[Pt]\n", - "kf = 1.3588265576828814e-16\n", - "krev = 6.093754170226661e16\n", - "Kc = 2.2298676968656565e-33\n", - "proton+O=C=C=C=[Pt]<=>O=C=CC#[Pt]\n", - "kf = 8.597534639917141e-9\n", - "krev = 2.1202950562509243e-60\n", - "Kc = 4.0548765204023916e51\n", - "vacantX+vacantX+O=C=C=C=O<=>OX+O=C=C=C=[Pt]\n", - "kf = 6.451439297868635e-57\n", - "krev = 8.482832416110645e14\n", - "Kc = 7.60528910793525e-72\n", - "proton+O=C=C=C(O)[Pt]<=>H2O+O=C=C=C=[Pt]\n", - "kf = 1.6149902683641734e-11\n", - "krev = 0.12950076972214764\n", - "Kc = 1.2470893198775887e-10\n", - "proton+O=C=C=C=[Pt]<=>O=C=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.039016761990757e-51\n", - "Kc = 6.189625216528679e60\n", - "vacantX+C=CO<=>C=CO.[Pt]\n", - "kf = 412885.969273148\n", - "krev = 1.1342794009872417\n", - "Kc = 364007.288604364\n", - "proton+C=CO[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.484544240591893e-27\n", - "Kc = 5.574702502366298e36\n", - "proton+OC=C[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.090002516938126e-28\n", - "Kc = 6.112465676112982e37\n", - "proton+C=CO.[Pt]<=>OCC[Pt]\n", - "kf = 1.7684909297990441e9\n", - "krev = 0.3339506079512917\n", - "Kc = 5.295666148501179e9\n", - "vacantX+vacantX+C=COCO<=>OCO[Pt]+C=C[Pt]\n", - "kf = 1.4197397308458187e-12\n", - "krev = 3.0290185667479297e13\n", - "Kc = 4.6871278586123213e-26\n", - "vacantX+vacantX+C=COCO<=>OC[Pt]+C=CO[Pt]\n", - "kf = 1.0263854075463885e-7\n", - "krev = 1.9545487277553856e14\n", - "Kc = 5.251265384031101e-22\n", - "HX+C=C=O<=>C=C(O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 3.2362559658776053e-12\n", - "Kc = 10343.290300064218\n", - "proton+C=C=O.[Pt]<=>C=C(O)[Pt]\n", - "kf = 0.5863133386822127\n", - "krev = 3624.832599039063\n", - "Kc = 0.00016174908017480404\n", - "vacantX+vacantX+C=CO<=>HX+C=C(O)[Pt]\n", - "kf = 4.00965787691315e-19\n", - "krev = 4.055766485027893\n", - "Kc = 9.886313454472895e-20\n", - "vacantX+vacantX+C=C(O)O<=>HOX+C=C(O)[Pt]\n", - "kf = 3.9452234947489745e-7\n", - "krev = 1.361002505571871e12\n", - "Kc = 2.8987628447394044e-19\n", - "proton+C=C(O)[Pt]<=>H2O+C=C=[Pt]\n", - "kf = 0.1408093188614318\n", - "krev = 0.006096548509334685\n", - "Kc = 23.09656334987455\n", - "proton+C=C(O)[Pt]<=>CC(O)=[Pt]\n", - "kf = 1.124057689749841e8\n", - "krev = 4.718570974473911e-12\n", - "Kc = 2.382199390092179e19\n", - "vacantX+vacantX+C=C(O)C=O<=>CHOX+C=C(O)[Pt]\n", - "kf = 2.8052009086647103\n", - "krev = 2.294429327232502e13\n", - "Kc = 1.2226137782366527e-13\n", - "proton+C=C(O)[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0077190030498644e-22\n", - "Kc = 2.4808503088993487e32\n", - "HOX+C=C=O<=>C=C(O)O[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.6625343699967689e-31\n", - "Kc = 2.0134040862236038e23\n", - "proton+C=C(O)O[Pt]<=>OX+C=CO\n", - "kf = 7.621772041144703e-10\n", - "krev = 0.16987445654378072\n", - "Kc = 4.4867087119601115e-9\n", - "vacantX+vacantX+C=C(O)O<=>HX+C=C(O)O[Pt]\n", - "kf = 8.7276566297004e-6\n", - "krev = 1.546723677424112e-6\n", - "Kc = 5.6426734503963205\n", - "vacantX+vacantX+C=CCOO<=>OOC[Pt]+C=C[Pt]\n", - "kf = 2.5331825038162864e-12\n", - "krev = 1.769892843246248e17\n", - "Kc = 1.4312632052740838e-29\n", - "proton+C=C(O)OC#[Pt]<=>CX+C=C(O)O\n", - "kf = 1.0744261387122509e-22\n", - "krev = 181.85749301564874\n", - "Kc = 5.908066370516815e-25\n", - "proton+C=C(O)C#[Pt]<=>CX+C=CO\n", - "kf = 3.691417083839596e-20\n", - "krev = 61.67110810051338\n", - "Kc = 5.985650651555046e-22\n", - "vacantX+vacantX+C=COOC<=>COO[Pt]+C=C[Pt]\n", - "kf = 0.0009962735751002543\n", - "krev = 4.495422962203487e13\n", - "Kc = 2.21619541359445e-17\n", - "vacantX+vacantX+C=COOC<=>CO[Pt]+C=CO[Pt]\n", - "kf = 2.772273774659678e8\n", - "krev = 3.7705323383409334e-17\n", - "Kc = 7.352473141443741e24\n", - "proton+C=C(O)C(=O)[Pt]<=>OCX+C=CO\n", - "kf = 985.1540455146012\n", - "krev = 5.159085449148215e-7\n", - "Kc = 1.9095517126533618e9\n", - "HOX+C=C=C=O<=>C=C(O)C(=O)[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 3.5720015577500406e-52\n", - "Kc = 8.264488540948707e43\n", - "vacantX+vacantX+C=C(O)C=O<=>HX+C=C(O)C(=O)[Pt]\n", - "kf = 2.8595651897765786e-11\n", - "krev = 0.000933577098423846\n", - "Kc = 3.063019856211522e-8\n", - "proton+C=COO[Pt]<=>OX+C=CO\n", - "kf = 43.93537738533433\n", - "krev = 6.669135249611683e-61\n", - "Kc = 6.587867203306832e61\n", - "O=O+C=C[Pt]<=>C=COO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 1.0833501613715598e-32\n", - "Kc = 7.082998693235901e24\n", - "vacantX+vacantX+C=COO<=>HX+C=COO[Pt]\n", - "kf = 4.552726448583842e-23\n", - "krev = 27.53540659037694\n", - "Kc = 1.6534081069915729e-24\n", - "vacantX+vacantX+C=COOC<=>CH3X+C=COO[Pt]\n", - "kf = 2.287071149777874e-9\n", - "krev = 2.2490557638427473e13\n", - "Kc = 1.0169028205286352e-22\n", - "vacantX+vacantX+CC(O)=CO<=>OC=[Pt]+CC(O)=[Pt]\n", - "kf = 7.128045206079291e-31\n", - "krev = 1.6024698052635947e11\n", - "Kc = 4.4481619451835966e-42\n", - "vacantX+vacantX+CC(O)=CO<=>CH3X+OC=C(O)[Pt]\n", - "kf = 1.2021042471738558e-26\n", - "krev = 3.79937896614338e12\n", - "Kc = 3.163949313521812e-39\n", - "proton+O=CC=C=[Pt]<=>O=CCC#[Pt]\n", - "kf = 62.9877146015209\n", - "krev = 8.316144406521062e-31\n", - "Kc = 7.574148730766316e31\n", - "vacantX+vacantX+O=C=CC=O<=>OX+O=CC=C=[Pt]\n", - "kf = 1.1758489216219413e-43\n", - "krev = 2.1453863988577092e16\n", - "Kc = 5.480825842132732e-60\n", - "proton+O=CC=C=[Pt]<=>O=CC=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.331702565774384e-47\n", - "Kc = 2.6790395240083815e56\n", - "proton+C=C=C=O.[Pt]<=>O=C=CC[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.2229421483387703e-16\n", - "Kc = 1.1246356554390213e26\n", - "vacantX+C=C=C=O<=>C=C=C=O.[Pt]\n", - "kf = 372758.92921022984\n", - "krev = 0.5077615475124772\n", - "Kc = 734122.012658058\n", - "proton+C=C=C=O.[Pt]<=>CC([Pt])=C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.123273247571115e-16\n", - "Kc = 1.1774273531962195e26\n", - "proton+C=C=C=O.[Pt]<=>C=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.171161147913428e-32\n", - "Kc = 4.834504144216726e41\n", - "proton+O=C=C=C[Pt]<=>C=C=C=O.[Pt]\n", - "kf = 3.820491632517615e9\n", - "krev = 3.925100397444825e-12\n", - "Kc = 9.733487670798667e20\n", - "vacantX+vacantX+C=C(C)O<=>CH2X+CC(O)=[Pt]\n", - "kf = 1.2526307828427685e-31\n", - "krev = 1.8291181793687947e14\n", - "Kc = 6.848276929132241e-46\n", - "vacantX+vacantX+C=C(C)O<=>CH3X+C=C(O)[Pt]\n", - "kf = 6.412809230790006e-14\n", - "krev = 6.896161957802356e13\n", - "Kc = 9.299098933624258e-28\n", - "HX+O=C=C=C=O<=>O=C=C=CO[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 6.474039280394542e-15\n", - "Kc = 8.128654665807662e6\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C=CO[Pt]\n", - "kf = 2.4048564698523636e10\n", - "krev = 0.03636685994081414\n", - "Kc = 6.612769080877996e11\n", - "proton+O=C=C=CO[Pt]<=>OX+C=C=C=O\n", - "kf = 7.675790818902377e-14\n", - "krev = 0.0006735755949001122\n", - "Kc = 1.1395589265731426e-10\n", - "vacantX+vacantX+O=C=C=CO<=>HX+O=C=C=CO[Pt]\n", - "kf = 4.194899212644372e-10\n", - "krev = 0.014508998351933198\n", - "Kc = 2.891239705796395e-8\n", - "proton+O=C=C=CO[Pt]<=>O=C=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4612716650323904e-11\n", - "Kc = 1.71083862078759e21\n", - "proton+CC(O)[Pt]<=>OC=[Pt]+CH4\n", - "kf = 59.397807135376084\n", - "krev = 1.2803453253139382e-6\n", - "Kc = 4.639202093451769e7\n", - "HX+C=CO<=>CC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 1.2254518112062234e-21\n", - "Kc = 2.668292606261641e13\n", - "HX+CC=O<=>CC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 2.4645381117653586e-12\n", - "Kc = 13267.654460532101\n", - "vacantX+vacantX+CCO<=>HX+CC(O)[Pt]\n", - "kf = 1.7361137032745595e-19\n", - "krev = 63.774720976875884\n", - "Kc = 2.72225997492652e-21\n", - "vacantX+vacantX+CC(O)O<=>HOX+CC(O)[Pt]\n", - "kf = 7.380915652046712e-14\n", - "krev = 2.775462823415347e13\n", - "Kc = 2.6593458899096773e-27\n", - "proton+CC=O.[Pt]<=>CC(O)[Pt]\n", - "kf = 36132.65188770086\n", - "krev = 0.006356177292382113\n", - "Kc = 5.68465135971048e6\n", - "proton+CC(O)[Pt]<=>H2O+CC=[Pt]\n", - "kf = 2964.0563969386994\n", - "krev = 0.019559355499681682\n", - "Kc = 151541.61889367664\n", - "proton+CC(O)=[Pt]<=>CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.860369956892034e-19\n", - "Kc = 5.143641373338227e28\n", - "vacantX+vacantX+CC(O)C=O<=>CHOX+CC(O)[Pt]\n", - "kf = 753631.9525109725\n", - "krev = 9.011518944421836e14\n", - "Kc = 8.362984721654206e-10\n", - "proton+C=CO.[Pt]<=>CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.061646123775542e-6\n", - "Kc = 4.939104668453628e15\n", - "HX+C#CC=O<=>O=CC=C[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 1.9866745274914506e-30\n", - "Kc = 1.4859387148609413e22\n", - "proton+CC(O)C#[Pt]<=>CX+CCO\n", - "kf = 1.3617819786307934\n", - "krev = 4.084110860281074e-5\n", - "Kc = 33343.413663777814\n", - "O=CO+CH3X<=>CC(O)O[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 7.324156308451427e-7\n", - "Kc = 0.043678018970166745\n", - "HOX+CC=O<=>CC(O)O[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 7.587328136505701e-13\n", - "Kc = 43096.38318446866\n", - "HX+CC(=O)O<=>CC(O)O[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 4598.938099177113\n", - "Kc = 6.089703295881323e-12\n", - "proton+CC(O)O[Pt]<=>OX+CCO\n", - "kf = 1.6583777607664147e6\n", - "krev = 1.6983423991371652e-6\n", - "Kc = 9.764684445309413e11\n", - "vacantX+vacantX+CC(O)O<=>HX+CC(O)O[Pt]\n", - "kf = 4.052122584605618e-24\n", - "krev = 469.09529347560436\n", - "Kc = 8.638165082797514e-27\n", - "proton+CC(=O)O.[Pt]<=>CC(O)O[Pt]\n", - "kf = 0.7475019896975738\n", - "krev = 3555.8603422114556\n", - "Kc = 0.00021021691454639312\n", - "vacantX+vacantX+OC=C=CO<=>OC=[Pt]+OC=C=[Pt]\n", - "kf = 3.0449395213240036e-51\n", - "krev = 1.4315520101841116e12\n", - "Kc = 2.1270198355785863e-63\n", - "CH3X+O=C=CO<=>CC(O)C(=O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 4.477216581188038e-53\n", - "Kc = 6.362980552705156e44\n", - "proton+CC(O)C(=O)[Pt]<=>OCX+CCO\n", - "kf = 9.570476890072168e7\n", - "krev = 4.96015815008412e-7\n", - "Kc = 1.929470109720163e14\n", - "HOX+CC=C=O<=>CC(O)C(=O)[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 3.536759710167166e-36\n", - "Kc = 8.195394062368554e27\n", - "HX+CC(O)=C=O<=>CC(O)C(=O)[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 4.830700359768998e-42\n", - "Kc = 5.292381792522405e33\n", - "vacantX+vacantX+CC(O)C=O<=>HX+CC(O)C(=O)[Pt]\n", - "kf = 4.786286134353719e-11\n", - "krev = 0.0006355923790078162\n", - "Kc = 7.530433486042254e-8\n", - "proton+CC(O)=C=O.[Pt]<=>CC(O)C(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.368412782384192e-31\n", - "Kc = 1.8269341182594315e41\n", - "proton+CC(O)OC#[Pt]<=>CX+CC(O)O\n", - "kf = 2.7873525673015004e-16\n", - "krev = 1.8374709107747412e-8\n", - "Kc = 1.516950581887719e-8\n", - "vacantX+vacantX+CCOC<=>CO[Pt]+CC[Pt]\n", - "kf = 2.3627317133785774e-11\n", - "krev = 3.856091265609508e13\n", - "Kc = 6.127271246016828e-25\n", - "vacantX+vacantX+CCOC<=>CH3X+CCO[Pt]\n", - "kf = 6.326940367296449e-9\n", - "krev = 1.8372911814097844e13\n", - "Kc = 3.443624195943553e-22\n", - "vacantX+vacantX+CCOC<=>CH3X+COC[Pt]\n", - "kf = 1.3389399016858639e-14\n", - "krev = 2.773400746132106e14\n", - "Kc = 4.8277909478217395e-29\n", - "proton+O=C=C(O)C[Pt]<=>CH2X+O=C=CO\n", - "kf = 4.2042874371743854e-22\n", - "krev = 1.1101526849597185\n", - "Kc = 3.787125405481442e-22\n", - "HOX+C=C=C=O<=>O=C=C(O)C[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 6.322264310888409e-36\n", - "Kc = 4.669334354059592e27\n", - "vacantX+vacantX+CC(O)=C=O<=>HX+O=C=C(O)C[Pt]\n", - "kf = 6.004181315465852e-13\n", - "krev = 0.19478740167193392\n", - "Kc = 3.082427951669201e-12\n", - "proton+O=C=C(O)C[Pt]<=>CC(O)=C=O.[Pt]\n", - "kf = 1.859235052213257e9\n", - "krev = 4.357618832801525e-11\n", - "Kc = 4.266630753057283e19\n", - "proton+O=C=C(O)C=[Pt]<=>CHX+O=C=CO\n", - "kf = 1.807627844430322e-6\n", - "krev = 0.0010238577171457239\n", - "Kc = 0.0017655068806528764\n", - "proton+O=C=C(O)C#[Pt]<=>O=C=C(O)C=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.347883511420028\n", - "Kc = 7.467404380923659e9\n", - "proton+O=C=C(O)C=[Pt]<=>O=C=C(O)C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4404183806094484e-33\n", - "Kc = 1.735606844271341e43\n", - "vacantX+vacantX+CCCO<=>OC[Pt]+CC[Pt]\n", - "kf = 4.648157058598011e-13\n", - "krev = 1.3999921584371802e15\n", - "Kc = 3.3201307811515004e-28\n", - "vacantX+vacantX+CCCO<=>CH3X+OCC[Pt]\n", - "kf = 1.2211065235504926e-16\n", - "krev = 1.2627143633797795e15\n", - "Kc = 9.670488900451568e-32\n", - "proton+CC([Pt])OC=O<=>CH4+O=COC=[Pt]\n", - "kf = 1.0679856406424377e-15\n", - "krev = 0.2905260385078575\n", - "Kc = 3.6760410396521245e-15\n", - "CHOX+CC=O<=>CC([Pt])OC=O\n", - "kf = 3.269864007171502e-8\n", - "krev = 0.48922244404245907\n", - "Kc = 6.68379802887317e-8\n", - "HX+C=COC=O<=>CC([Pt])OC=O\n", - "kf = 2.5565910629172877e-8\n", - "krev = 1.2259112200812889e-16\n", - "Kc = 2.0854618352769157e8\n", - "vacantX+vacantX+CCOC=O<=>HX+CC([Pt])OC=O\n", - "kf = 6.519502059052115e-22\n", - "krev = 142.86665816232104\n", - "Kc = 4.563347489828482e-24\n", - "proton+CC([Pt])OC=O<=>O=CO+CC=[Pt]\n", - "kf = 8049.244255788158\n", - "krev = 0.00029431628636694825\n", - "Kc = 2.7348959703006394e7\n", - "proton+CC(=[Pt])OC=O<=>CH4+O=COC#[Pt]\n", - "kf = 4.771264023974434e9\n", - "krev = 10.578082715743388\n", - "Kc = 4.510518732164335e8\n", - "proton+CC(=[Pt])OC=O<=>O=CO+CC#[Pt]\n", - "kf = 7292.02651577905\n", - "krev = 8.53932827082491e-43\n", - "Kc = 8.539344412712957e45\n", - "proton+CC(=[Pt])OC=O<=>CC([Pt])OC=O\n", - "kf = 2.5e10\n", - "krev = 2.5945295399651927e-47\n", - "Kc = 9.635658262860014e56\n", - "vacantX+vacantX+CCC(O)O<=>OC(O)[Pt]+CC[Pt]\n", - "kf = 3.712816041087776e-19\n", - "krev = 9.367983662004229e16\n", - "Kc = 3.9633032838716965e-36\n", - "vacantX+O=CC=CO<=>O=CC=CO.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 0.8868529608572997\n", - "Kc = 364007.2889878057\n", - "proton+O=CC=CO[Pt]<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.467206835324098e-11\n", - "Kc = 1.703917907012588e21\n", - "proton+O=C([Pt])C=CO<=>O=CC=CO.[Pt]\n", - "kf = 3.672999120067293e9\n", - "krev = 4.587068754429701e-12\n", - "Kc = 8.00729031262133e20\n", - "HX+O=C=CC=O<=>O=CC=C(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.0473065138531246e-21\n", - "Kc = 2.475989854235963e13\n", - "proton+O=C=CC=O.[Pt]<=>O=CC=C(O)[Pt]\n", - "kf = 9.946079261837086e6\n", - "krev = 6.687641252513296e-9\n", - "Kc = 1.4872327755468685e15\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC=C(O)[Pt]\n", - "kf = 2.77963678004065e-20\n", - "krev = 3.601218827022036\n", - "Kc = 7.718600045027592e-21\n", - "proton+O=CC=C(O)[Pt]<=>H2O+O=CC=C=[Pt]\n", - "kf = 2.367383825493301e-13\n", - "krev = 16.1722227709439\n", - "Kc = 1.463858035487058e-14\n", - "proton+O=CC=C(O)[Pt]<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.867624236214861e-24\n", - "Kc = 3.177579311035777e33\n", - "vacantX+vacantX+CCOCO<=>OCO[Pt]+CC[Pt]\n", - "kf = 2.4512530384253315e-9\n", - "krev = 3.614837695546209e14\n", - "Kc = 6.781087409389048e-24\n", - "vacantX+vacantX+CCOCO<=>OC[Pt]+CCO[Pt]\n", - "kf = 1.0293700832173347e-6\n", - "krev = 1.2050997101819434e12\n", - "Kc = 8.541783509863451e-19\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC([Pt])=CO\n", - "kf = 4.3007284274917255e-15\n", - "krev = 1.9561961334382385\n", - "Kc = 2.1985159636997663e-15\n", - "HX+O=C=C=CO<=>O=CC([Pt])=CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.6370748462102965e-36\n", - "Kc = 1.5839961798805036e28\n", - "proton+O=CC([Pt])=CO<=>C=O+OC=C=[Pt]\n", - "kf = 4.3296354594819855e-33\n", - "krev = 908.9754469679581\n", - "Kc = 4.76320397203711e-36\n", - "proton+O=C=C=CO.[Pt]<=>O=CC([Pt])=CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.7196074204687593e-20\n", - "Kc = 1.4538201977044896e30\n", - "HOX+C#CC=O<=>O=CC([Pt])=CO\n", - "kf = 2.952076594227614e-8\n", - "krev = 4.790462195255654e-44\n", - "Kc = 6.162404531970363e35\n", - "proton+O=CC([Pt])=CO<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.2409630475480663e-18\n", - "Kc = 1.1155918000233681e28\n", - "proton+OC=CC=[Pt]<=>CHX+C=CO\n", - "kf = 0.3708119772368373\n", - "krev = 1.9743851754031655e-5\n", - "Kc = 18781.136621992628\n", - "vacantX+vacantX+O=CC=CO<=>OX+OC=CC=[Pt]\n", - "kf = 8.803023976547135e-28\n", - "krev = 1.526615583505237e17\n", - "Kc = 5.766365856383213e-45\n", - "proton+OC=CC#[Pt]<=>OC=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4263979915391943e-8\n", - "Kc = 1.7526665172195773e18\n", - "vacantX+vacantX+CCCOO<=>OOC[Pt]+CC[Pt]\n", - "kf = 5.56726706794292e-16\n", - "krev = 4.282042054393877e17\n", - "Kc = 1.3001430152303739e-33\n", - "proton+OCC(O)[Pt]<=>OC=[Pt]+CO-2\n", - "kf = 0.16339719354915763\n", - "krev = 6.17359485423602e-8\n", - "Kc = 2.6467106670766133e6\n", - "HX+O=CCO<=>OCC(O)[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 4.347223516290618e-14\n", - "Kc = 644231.1603064304\n", - "vacantX+vacantX+OCCO<=>HX+OCC(O)[Pt]\n", - "kf = 7.314142036323851e-21\n", - "krev = 492.5535033039904\n", - "Kc = 1.4849436634317805e-23\n", - "HX+OC=CO<=>OCC(O)[Pt]\n", - "kf = 5.6012337000223925e-8\n", - "krev = 1.5412075197181771e-21\n", - "Kc = 3.634315060340885e13\n", - "HOX+C=CO<=>OCC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 6.743155058263278e-19\n", - "Kc = 4.8491603395127426e10\n", - "proton+O=CCO.[Pt]<=>OCC(O)[Pt]\n", - "kf = 698182.0065765544\n", - "krev = 4.403884986144656e-6\n", - "Kc = 1.5853774764171848e11\n", - "proton+OCC(O)[Pt]<=>H2O+OCC=[Pt]\n", - "kf = 0.7285659975205578\n", - "krev = 0.0004743003964980969\n", - "Kc = 1536.0855755124403\n", - "proton+OC=CO.[Pt]<=>OCC(O)[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 1.4989628309182922e-5\n", - "Kc = 3.3356397482764175e15\n", - "proton+OCC(O)C#[Pt]<=>CX+OCCO\n", - "kf = 5.26000051169577\n", - "krev = 0.00019971123776726528\n", - "Kc = 26338.02969978857\n", - "vacantX+vacantX+CCC<=>CH3X+CC[Pt]\n", - "kf = 7.798842461270165e-20\n", - "krev = 4.754727023110295e15\n", - "Kc = 1.640229275700578e-35\n", - "proton+O=C([Pt])CO<=>OCC(O)=[Pt]\n", - "kf = 4.019918430047713e-18\n", - "krev = 1.0085447542339827e12\n", - "Kc = 3.9858602339377106e-30\n", - "proton+OCC(O)=[Pt]<=>H2O+OCC#[Pt]\n", - "kf = 16209.61875952926\n", - "krev = 4.634124941714537e-41\n", - "Kc = 3.4978812533984058e44\n", - "proton+OCC(O)=[Pt]<=>OC#[Pt]+CO-2\n", - "kf = 382.95023851607715\n", - "krev = 3.536410198453644e-35\n", - "Kc = 1.0828784474253827e37\n", - "proton+OC=C(O)[Pt]<=>OCC(O)=[Pt]\n", - "kf = 6875.768524790738\n", - "krev = 1.0085447542339824e12\n", - "Kc = 6.8175145385720384e-9\n", - "proton+OCC(O)=[Pt]<=>OCC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.6015120113778689e-47\n", - "Kc = 1.5610248204439706e57\n", - "HX+COC=O<=>COC(O)[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 224.3395816271696\n", - "Kc = 1.2483828443014824e-10\n", - "proton+COC(O)[Pt]<=>OC=[Pt]+CO-2\n", - "kf = 564390.3708916149\n", - "krev = 3.282828318007529e-12\n", - "Kc = 1.7192198806002883e17\n", - "vacantX+vacantX+COCO<=>HX+COC(O)[Pt]\n", - "kf = 6.183244140051347e-23\n", - "krev = 2731.92216309053\n", - "Kc = 2.2633310068601865e-26\n", - "O=CO+CH3X<=>COC(O)[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 8.503469161971292e7\n", - "Kc = 3.7620485485108396e-16\n", - "proton+COC=O.[Pt]<=>COC(O)[Pt]\n", - "kf = 7.49969185016536e-5\n", - "krev = 3658.0165064396892\n", - "Kc = 2.0502072193940793e-8\n", - "proton+COC(O)[Pt]<=>H2O+COC=[Pt]\n", - "kf = 5.10646151413012e-10\n", - "krev = 0.003546985366877098\n", - "Kc = 1.439662413557134e-7\n", - "vacantX+vacantX+CCOOC<=>COO[Pt]+CC[Pt]\n", - "kf = 1.4778859852656565e-10\n", - "krev = 2.404289853338368e13\n", - "Kc = 6.146871115450596e-24\n", - "vacantX+vacantX+CCOOC<=>CO[Pt]+CCO[Pt]\n", - "kf = 2.735304068777078e8\n", - "krev = 1.1929824589169815e-11\n", - "Kc = 2.2928284052560617e19\n", - "vacantX+vacantX+CCOOC<=>CH3X+CCOO[Pt]\n", - "kf = 1.542530561493995e-10\n", - "krev = 1.2789927244807063e12\n", - "Kc = 1.2060510837700736e-22\n", - "proton+COC(O)C#[Pt]<=>CX+COCO\n", - "kf = 0.03928313633337953\n", - "krev = 0.002914319669063903\n", - "Kc = 13.479350515448948\n", - "proton+COC(=O)[Pt]<=>COC(O)=[Pt]\n", - "kf = 6.005930457604258e-17\n", - "krev = 1.0085447542339825e12\n", - "Kc = 5.955046052632466e-29\n", - "proton+COC(O)=[Pt]<=>OC#[Pt]+CO-2\n", - "kf = 383854.3090963643\n", - "krev = 3.448448528690976e-34\n", - "Kc = 1.113121758677009e39\n", - "proton+COC(O)=[Pt]<=>H2O+COC#[Pt]\n", - "kf = 217922.49486435574\n", - "krev = 2.0340320286285714e-35\n", - "Kc = 1.0713818258372662e40\n", - "proton+COC(O)=[Pt]<=>COC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0120272229346644e-38\n", - "Kc = 2.4702892801149458e48\n", - "vacantX+vacantX+C=C=COO<=>OOC=[Pt]+C=C=[Pt]\n", - "kf = 1.9145907695639512e-44\n", - "krev = 1.1771971588384226e12\n", - "Kc = 1.626397715275781e-56\n", - "C=O+O=CC[Pt]<=>O=CCCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 0.0025285011306884937\n", - "Kc = 1.5664103465194285e-5\n", - "HX+O=CCC=O<=>O=CCCO[Pt]\n", - "kf = 5.113182125834635e-8\n", - "krev = 3.03538509820146e-7\n", - "Kc = 0.16845250142607343\n", - "proton+O=CCC=O.[Pt]<=>O=CCCO[Pt]\n", - "kf = 2.3901708430508703e8\n", - "krev = 41.103568870106145\n", - "Kc = 5.814995896351951e6\n", - "vacantX+vacantX+O=CCCO<=>HX+O=CCCO[Pt]\n", - "kf = 2.5157725911236352e-27\n", - "krev = 8837.406478086354\n", - "Kc = 2.84673178421957e-31\n", - "proton+O=CCCO[Pt]<=>OX+CCC=O\n", - "kf = 774927.4661784222\n", - "krev = 1.1978583087682196e-18\n", - "Kc = 6.469274875884902e23\n", - "CHOX+C=C<=>O=CCC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 0.4688595936220698\n", - "Kc = 1.7478623517301195e-7\n", - "proton+O=CCC[Pt]<=>CH2X+CC=O\n", - "kf = 0.0016740956920828355\n", - "krev = 4.373185000711893e-7\n", - "Kc = 3828.0925499614495\n", - "HX+C=CC=O<=>O=CCC[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 7.666152073113618e-12\n", - "Kc = 3780.924152337611\n", - "proton+O=CCC=[Pt]<=>O=CCC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3932958912707058e-30\n", - "Kc = 1.794306590339518e40\n", - "vacantX+vacantX+O=CCCO<=>HOX+O=CCC[Pt]\n", - "kf = 8.901266563864654e-15\n", - "krev = 1.309728963703428e15\n", - "Kc = 6.79626610584771e-30\n", - "vacantX+vacantX+CCC=O<=>HX+O=CCC[Pt]\n", - "kf = 1.6716561102658422e-25\n", - "krev = 524619.2678123232\n", - "Kc = 3.186417680076247e-31\n", - "vacantX+vacantX+CC=COO<=>OOC=[Pt]+CC=[Pt]\n", - "kf = 3.7147962989308654e-50\n", - "krev = 4.0636001726377395e18\n", - "Kc = 9.141638303749602e-69\n", - "proton+C=COOC#[Pt]<=>CX+C=COO\n", - "kf = 8.811176921711816e-67\n", - "krev = 2.5e10\n", - "Kc = 3.5244707686847265e-77\n", - "vacantX+C=CC=O<=>C=CC=O.[Pt]\n", - "kf = 365995.57053717994\n", - "krev = 1.0054621985249468\n", - "Kc = 364007.290452202\n", - "proton+C=CC(=O)[Pt]<=>C=CC=O.[Pt]\n", - "kf = 3.399604827397095e9\n", - "krev = 5.959510760846119e-12\n", - "Kc = 5.704503211458966e20\n", - "proton+O=CC=C[Pt]<=>C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.32808736312024e-27\n", - "Kc = 3.00188973889839e36\n", - "proton+C=CC=O.[Pt]<=>O=CCC[Pt]\n", - "kf = 5.197601136262071e7\n", - "krev = 74.26603000820454\n", - "Kc = 699862.5260684955\n", - "vacantX+vacantX+C=CC=O<=>HX+C=C([Pt])C=O\n", - "kf = 1.2784478936507186e-21\n", - "krev = 132.59733776930153\n", - "Kc = 9.641580405445367e-24\n", - "proton+C=C([Pt])C=O<=>C=O+C=C=[Pt]\n", - "kf = 2.4079500300331376e-13\n", - "krev = 0.010970404022735962\n", - "Kc = 2.194951092997765e-11\n", - "HX+C=C=C=O<=>C=C([Pt])C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.4992009477647154e-32\n", - "Kc = 1.1812081765045545e24\n", - "vacantX+vacantX+C=C(O)C=O<=>HOX+C=C([Pt])C=O\n", - "kf = 1.107119853181277e-14\n", - "krev = 2.5289157654010746e13\n", - "Kc = 4.377843929513773e-28\n", - "proton+C=C=C=O.[Pt]<=>C=C([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.305987527913534e-16\n", - "Kc = 1.0841342243780513e26\n", - "HX+C#CC=O<=>C=C([Pt])C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 1.683521621093348e-30\n", - "Kc = 1.753512730243651e22\n", - "proton+C=C([Pt])C=O<=>C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.827731832923639e-27\n", - "Kc = 2.5438219545478565e36\n", - "CHOX+C=C=O<=>C=C(C=O)O[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.906984656058423e-6\n", - "Kc = 0.017553122325364576\n", - "proton+C=C(C=O)O[Pt]<=>OX+C=CC=O\n", - "kf = 13.565263195704604\n", - "krev = 7.179044500174065e-6\n", - "Kc = 1.8895638821260543e6\n", - "vacantX+vacantX+C=C(O)C=O<=>HX+C=C(C=O)O[Pt]\n", - "kf = 8.336773502217888e-19\n", - "krev = 4.018028855986407\n", - "Kc = 2.0748416203624424e-19\n", - "vacantX+vacantX+COCOC<=>CH3X+COCO[Pt]\n", - "kf = 0.24675966205104702\n", - "krev = 5.277017405064255e15\n", - "Kc = 4.6761199198288865e-17\n", - "vacantX+vacantX+COCOC<=>CO[Pt]+COC[Pt]\n", - "kf = 4.1241018831024145e-7\n", - "krev = 7.782310155024181e12\n", - "Kc = 5.2993286067375974e-20\n", - "proton+C=CC=[Pt]<=>CHX+C=C\n", - "kf = 1.3385165927063483e6\n", - "krev = 9.028119675350497e-7\n", - "Kc = 1.4826083845132273e12\n", - "vacantX+vacantX+C=CC=O<=>OX+C=CC=[Pt]\n", - "kf = 1.438969400016978e-30\n", - "krev = 1.6093339940290013e17\n", - "Kc = 8.941396909254915e-48\n", - "proton+C=CC#[Pt]<=>C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.067052266556579e-6\n", - "Kc = 2.342903040792558e16\n", - "vacantX+CC(O)O<=>CC(O)O.[Pt]\n", - "kf = 347843.58123444836\n", - "krev = 178209.4487483253\n", - "Kc = 1.9518806868971765\n", - "proton+CC(O)O[Pt]<=>CC(O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.64203868551119e-24\n", - "Kc = 1.5224976257010135e34\n", - "vacantX+vacantX+COCCO<=>OC[Pt]+COC[Pt]\n", - "kf = 1.3358759661274015e-7\n", - "krev = 3.1165281946439875e14\n", - "Kc = 4.286423490161954e-22\n", - "vacantX+vacantX+COCCO<=>CO[Pt]+OCC[Pt]\n", - "kf = 6.192873660096324e-8\n", - "krev = 3.90827625278604e13\n", - "Kc = 1.584553716150872e-21\n", - "vacantX+vacantX+COCCO<=>CH3X+OCCO[Pt]\n", - "kf = 4.52195120819324e-12\n", - "krev = 5.920081591014324e14\n", - "Kc = 7.638325821483257e-27\n", - "proton+OC(O)C[Pt]<=>CH2X+OCO\n", - "kf = 2.252975678309519e-7\n", - "krev = 0.002613777215265548\n", - "Kc = 8.619616335895816e-5\n", - "HOX+C=CO<=>OC(O)C[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 6.095879365149742e-19\n", - "Kc = 5.364056293281289e10\n", - "HX+C=C(O)O<=>OC(O)C[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 1.7806643358524245e-19\n", - "Kc = 1.572793251160735e11\n", - "vacantX+vacantX+CC(O)O<=>HX+OC(O)C[Pt]\n", - "kf = 2.610914590914038e-25\n", - "krev = 48838.0104312493\n", - "Kc = 5.3460707507516085e-30\n", - "vacantX+vacantX+CCC(O)O<=>CH3X+OC(O)C[Pt]\n", - "kf = 2.73273606062798e-19\n", - "krev = 1.7143250273592365e15\n", - "Kc = 1.594059479396106e-34\n", - "proton+OC(O)C[Pt]<=>CC(O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0162407066861682e-27\n", - "Kc = 2.4600470966688416e37\n" - ] - } - ], - "source": [ - "for (i,rxn) in enumerate(inter.reactions)\n", - " str = getrxnstr(rxn)\n", - " kf = inter.kfs[i]\n", - " krev = inter.krevs[i]\n", - " Kc = kf/krev\n", - " println(str)\n", - " println(\"kf = $kf\")\n", - " println(\"krev = $krev\")\n", - " println(\"Kc = $Kc\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "id": "11333da0", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "ef575a57", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.9.1", - "language": "julia", - "name": "julia-1.9" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.9.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/CO2RR_RMS/Ag/CO2RR_RMS_Diffusion_Interface.jl b/CO2RR_RMS/Ag/CO2RR_RMS_Diffusion_Interface.jl new file mode 100644 index 0000000..fe10d60 --- /dev/null +++ b/CO2RR_RMS/Ag/CO2RR_RMS_Diffusion_Interface.jl @@ -0,0 +1,217 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,jl:percent +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.17.2 +# kernelspec: +# display_name: Julia 1.9.1 +# language: julia +# name: julia-1.9 +# --- + +# %% +using DifferentialEquations +using ReactionMechanismSimulator +using PyPlot + +# %% +outdict = readinput("chem300.rms") + +# %% +boundarylayerspcs = outdict["gas"]["Species"] +boundarylayerrxns = outdict["gas"]["Reactions"] +surfspcs = outdict["surface"]["Species"] +surfrxns = outdict["surface"]["Reactions"] +interfacerxns = outdict[Set(["surface", "gas"])]["Reactions"] +solv = outdict["Solvents"][1]; + +# %% +sitedensity = 2.292e-5; # Ag111 +boundarylayer = IdealDiluteSolution(boundarylayerspcs,boundarylayerrxns,solv,name="boundarylayeruid",diffusionlimited=true); +surf = IdealSurface(surfspcs,surfrxns,sitedensity,name="surface"); + +# %% +initialcondsboundarylayer = Dict(["proton"=>10.0^-4, + "CO2"=>10.0^-3*10^6, + "V"=>1.0e-3,"T"=>300,"Phi"=>0.0,"d"=>0.0]); +initialcondsreservoir = Dict(["proton"=>10.0^-4, + "CO2"=>10.0^-3*10^6, + "V"=>1.0,"T"=>300]); +AVratio = 1e5; +initialcondssurf = Dict(["CO2X"=>0.4*sitedensity*AVratio, + "CHO2X"=>0.1*sitedensity*AVratio, + "CO2HX"=>0.1*sitedensity*AVratio, + "OX"=>0.1*sitedensity*AVratio, + "OCX"=>0.1*sitedensity*AVratio, + "vacantX"=>0.1*sitedensity*AVratio, + "CH2O2X"=>0.05*sitedensity*AVratio, + "CHOX"=>0.04*sitedensity*AVratio, + "CH2OX"=>0.01*sitedensity*AVratio, + "A"=>1.0*AVratio,"T"=>300,"Phi"=>-1.0]); + +# %% +domainboundarylayer, y0boundarylayer, pboundarylayer = ConstantTVDomain(phase=boundarylayer, initialconds=initialcondsboundarylayer); +domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf, + initialconds=initialcondssurf); + +# %% +inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainboundarylayer, + domaincat,interfacerxns,298.15,AVratio*1.0); + +# %% +# start with 1mm layer thickness +diffusionlayer = ConstantReservoirDiffusion(domainboundarylayer, initialcondsreservoir, AVratio*1.0, 1e-3); + +# %% +interfaces = [inter, diffusionlayer]; + +# %% +@time react,y0,p = Reactor((domainboundarylayer,domaincat), (y0boundarylayer,y0cat), (0.0, 1.0e2), interfaces, (pboundarylayer,pcat,pinter)); + + +# %% +@time sol = solve(react.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-8); + +# %% +sol + +# %% +sol.retcode + +# %% +ssys = SystemSimulation(sol,(domainboundarylayer,domaincat,), interfaces,p); + +# %% +# Helper function +function plotX(sim, tol, t_end, exclude) + clf() + xs = molefractions(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Mole Fraction") +end + +# %% +# Helper function +function plotC(sim, tol, t_end, exclude) + clf() + xs = concentrations(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Concentration") +end + +# %% +concentrations(ssys.sims[1]) + +# %% +concentrations(ssys.sims[2]) + +# %% +exclude_species = ["H2O"] +plotX(ssys.sims[1], 1e-6, 1e2, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e2) +ylim(1e-9, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V") +gcf() + +# %% +exclude_species = ["H2O"] +plotC(ssys.sims[1], 1e-6, 1e2, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 10) +ylim(1e-6, 1e8) +title("Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V") +gcf() + +# %% +exclude_species = ["H2O"] +plotC(ssys.sims[2], 1e-6, 1e2, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 10) +ylim(1e-6, 1e-4) +title("Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V") +gcf() + +# %% +getfluxdiagram(ssys,1e2;speciesratetolerance=1e-6) + +# %% +println(ssys.names) + +# %% +plotrops(ssys,"CH2O2X",1;N=15,tol=0.0) + +# %% +plotrops(ssys,"CHO2X",1;N=10,tol=0.0) + +# %% +plotrops(ssys,"CO2HX",1;N=10,tol=0.0) + +# %% +plotrops(ssys,"OX",1;N=10,tol=0.0) + +# %% +plotrops(ssys,"OCX",1.0e-6) + +# %% +for (i,rxn) in enumerate(inter.reactions) + str = getrxnstr(rxn) + kf = inter.kfs[i] + krev = inter.krevs[i] + Kc = kf/krev + println(str) + println("kf = $kf") + println("krev = $krev") + println("Kc = $Kc") +end + +# %% +for (i,rxn) in enumerate(inter.reactions) + str = getrxnstr(rxn) + kf = inter.kfs[i] + krev = inter.krevs[i] + Kc = kf/krev + println(str) + println("kf = $kf") + println("krev = $krev") + println("Kc = $Kc") +end + +# %% + +# %% diff --git a/CO2RR_RMS/Ag/CO2RR_RMS_Diffusion_Interface_1.ipynb b/CO2RR_RMS/Ag/CO2RR_RMS_Diffusion_Interface_1.ipynb deleted file mode 100644 index 237e1c9..0000000 --- a/CO2RR_RMS/Ag/CO2RR_RMS_Diffusion_Interface_1.ipynb +++ /dev/null @@ -1,7206 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 39, - "id": "8a590634", - "metadata": {}, - "outputs": [], - "source": [ - "using ReactionMechanismSimulator\n", - "using PyPlot\n", - "using Sundials\n", - "using SciMLBase\n", - "using QuadGK" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "id": "e941d4fb", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[11:59:23] WARNING: not removing hydrogen atom without neighbors\n", - "[11:59:23] WARNING: not removing hydrogen atom without neighbors\n", - "┌ Warning: failed to generate StokesDiffusivity model for species vacantX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2O2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species H2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [H][H].[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(=O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH3X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(C#[Pt])CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)C(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C([Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C([Pt])CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC([Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=[Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC([Pt])=C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=C=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC(=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCOC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCC(=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC([Pt])=C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=COC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCOO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C=CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])CCO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)C(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)C(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC([Pt])OC=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=[Pt])OC=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC([Pt])=CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C([Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(C=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n" - ] - }, - { - "data": { - "text/plain": [ - "Dict{Any, Any} with 4 entries:\n", - " \"Solvents\" => Solvent[Solvent(\"water\", RiedelViscosity{Float64}(…\n", - " Set([\"surface\", \"gas\"]) => Dict{Any, Any}(\"Reactions\"=>ElementaryReaction[vac…\n", - " \"gas\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…\n", - " \"surface\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "outdict = readinput(\"chem300.rms\")" - ] - }, - { - "cell_type": "code", - "execution_count": 41, - "id": "fe2767e9", - "metadata": {}, - "outputs": [], - "source": [ - "boundarylayerspcs = outdict[\"gas\"][\"Species\"]\n", - "boundarylayerrxns = outdict[\"gas\"][\"Reactions\"]\n", - "surfspcs = outdict[\"surface\"][\"Species\"]\n", - "surfrxns = outdict[\"surface\"][\"Reactions\"]\n", - "interfacerxns = outdict[Set([\"surface\", \"gas\"])][\"Reactions\"]\n", - "solv = outdict[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "id": "c54ee65e", - "metadata": {}, - "outputs": [], - "source": [ - "sitedensity = 2.292e-5; # Ag111 site density is 2.292e-9 mol/cm^2 or 2.292e-5 mol/m^2\n", - "boundarylayer = IdealDiluteSolution(boundarylayerspcs,boundarylayerrxns,solv,name=\"boundarylayeruid\",diffusionlimited=true);\n", - "surf = IdealSurface(surfspcs,surfrxns,sitedensity,name=\"surface\");" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8894c84d", - "metadata": {}, - "outputs": [], - "source": [ - "# Reservoir is a 100 mL (100e-6 m^3) cell\n", - "# Proton concentration is 10^-7 mol/L (10^-4 mol/m^3)\n", - "# CO2 concentration is 0.01 mol/L (10 mol/m^3), saturation solubility ~0.03 mol/L\n", - "# AVratio in experiments is 36 m^-1 but is measured by surface area/reservoir volume\n", - "# Area of the electrode is therefore 3.6e1 m^-1 * 1e2*1e-6 m^3 = 3.6e-3 m^2 = 36 cm^2\n", - "# Assume boundary layer thickness d_bl = 1 mm or 1e-3 m\n", - "# Volume of the boundary layer V_bl = 3.6e-3 m^2 * 1e-3 m = 3.6e-6 m^3\n", - "# Actual AVratio is therefore 3.6e-3 m^2 / 3.6e-6 m^3 = 1e3 m^-1 (reciprocal of d_bl)\n", - "# Amount of sites is 2.292e-5 mol/m^2 * 1e3 m^-1 = 2.292e-2 mol/m^-3\n", - "\n", - "C_proton = 1e-7*1e3;\n", - "C_co2 = 1e-2*1e3;\n", - "C_default = 1e-12;\n", - "V_res = 1000.0e-6;\n", - "AVratio = 1e3;\n", - "A_surf = 100.0e-6*36;\n", - "V_bl = A_surf/AVratio;\n", - "sites = sitedensity;\n", - "\n", - "initialcondsboundarylayer = Dict([\"proton\"=>C_proton,\n", - " \"CO2\"=>C_co2,\n", - " \"V\"=>V_bl,\"T\"=>300,\"Phi\"=>0.0,\"d\"=>0.0]);\n", - "initialcondsreservoir = Dict([\"proton\"=>C_proton,\n", - " \"CO2\"=>C_co2,\n", - " \"V\"=>V_res,\"T\"=>300]);\n", - "\n", - "\n", - "# Assume voltage is -0.5 V vs. R.H.E. which equates to -0.914 V vs. S.H.E. at pH=7\n", - "initialcondssurf = Dict([\"CO2X\"=>0.4*sites,\n", - " \"CHO2X\"=>0.1*sites,\n", - " \"CO2HX\"=>0.1*sites,\n", - " \"OX\"=>0.1*sites,\n", - " \"OCX\"=>0.1*sites,\n", - " \"vacantX\"=>0.1*sites,\n", - " \"CH2O2X\"=>0.05*sites,\n", - " \"CHOX\"=>0.04*sites,\n", - " \"CH2OX\"=>0.01*sites,\n", - " \"A\"=>A_surf,\"T\"=>300,\"Phi\"=>-1.5]);" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "id": "ddb39b3d", - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "domainboundarylayer, y0boundarylayer, pboundarylayer = ConstantTVDomain(phase=boundarylayer, initialconds=initialcondsboundarylayer);\n", - "domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf,\n", - " initialconds=initialcondssurf);" - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "id": "ed49d2b4", - "metadata": {}, - "outputs": [], - "source": [ - "inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainboundarylayer,\n", - " domaincat,interfacerxns,298.15,A_surf);" - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "id": "dee14906", - "metadata": {}, - "outputs": [], - "source": [ - "# start with 1mm layer thickness\n", - "diffusionlayer = ConstantReservoirDiffusion(domainboundarylayer, initialcondsreservoir, A_surf, 1/AVratio);" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "id": "e70ac4b0", - "metadata": {}, - "outputs": [], - "source": [ - "interfaces = [inter, diffusionlayer];" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "id": "244f0912", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.052389 seconds (61.60 k allocations: 139.747 MiB, 11.79% gc time)\n" - ] - } - ], - "source": [ - "@time react,y0,p = Reactor((domainboundarylayer,domaincat), (y0boundarylayer,y0cat), (0.0, 1e3), interfaces, (pboundarylayer,pcat,pinter));" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "id": "962f838c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 5.124899 seconds (4.22 M allocations: 11.919 GiB, 13.75% gc time)\n" - ] - } - ], - "source": [ - "@time sol = solve(react.ode,Sundials.CVODE_BDF(),abstol=1e-22,reltol=1e-8);" - ] - }, - { - "cell_type": "code", - "execution_count": 50, - "id": "56b6f906", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "1000.0" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sol.t[end]" - ] - }, - { - "cell_type": "code", - "execution_count": 51, - "id": "4714593e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ReturnCode.Success = 1" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sol.retcode" - ] - }, - { - "cell_type": "code", - "execution_count": 52, - "id": "6667bb5a", - "metadata": {}, - "outputs": [], - "source": [ - "ssys = SystemSimulation(sol,(domainboundarylayer,domaincat,), interfaces,p);" - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "id": "abcf6608", - "metadata": {}, - "outputs": [], - "source": [ - "plotmolefractions(ssys.sims[1], 1e-8,tol=1e-25)\n", - "yscale(\"log\")\n", - "xscale(\"log\")" - ] - }, - { - "cell_type": "code", - "execution_count": 54, - "id": "afae3194", - "metadata": {}, - "outputs": [], - "source": [ - "plotmolefractions(ssys.sims[2], 1e-8,tol=3e-2)\n", - "xscale(\"log\")" - ] - }, - { - "cell_type": "code", - "execution_count": 77, - "id": "d55a5466", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "108-element Vector{Float64}:\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 2777.7746704748874\n", - " 0.027777731869113156\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " -1.4202635493838582e-27\n", - " ⋮\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "concentrations(ssys.sims[1], 1e3)" - ] - }, - { - "cell_type": "code", - "execution_count": 56, - "id": "d4939a87", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "get_reservoir_concentration" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "\"\"\"\n", - "diffusive flux to the reservoir\n", - "\"\"\"\n", - "function flux_to_reservoir(sim,t,reservoirinterface)\n", - " cs = concentrations(sim,t)\n", - " return reservoirinterface.A .* sim.domain.diffusivity .* (cs - reservoirinterface.c) / reservoirinterface.layer_thickness\n", - "end\n", - "\n", - "\"\"\"\n", - "Integrates the flux to the reservoir and computes the concentration assuming\n", - "there is no prior concentration of that species in the reservoir\n", - "\"\"\"\n", - "function get_reservoir_concentration(sim,t,reservoirinterface,Vres)\n", - " intg,err = quadgk(x -> flux_to_reservoir(sim,x,reservoirinterface), 0, t)\n", - " return intg./Vres\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 57, - "id": "4d4dfc9c", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "108-element Vector{Float64}:\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 1.1186295429633826e-8\n", - " 1.6527130498265213e-13\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " ⋮\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "flux_to_reservoir(ssys.sims[1],1e2,diffusionlayer)" - ] - }, - { - "cell_type": "code", - "execution_count": 58, - "id": "782dc215", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "108-element Vector{Float64}:\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 1.1186296057560477e-6\n", - " 1.6527131868930116e-11\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " ⋮\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "res_cs = get_reservoir_concentration(ssys.sims[1],1e2,diffusionlayer,1.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 59, - "id": "e8885c97", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "108-element Vector{Float64}:\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " ⋮\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 1.6527131868930116e-11\n", - " 1.1186296057560477e-6" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sort(res_cs)" - ] - }, - { - "cell_type": "code", - "execution_count": 60, - "id": "9606a8ed", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "108-element Vector{String}:\n", - " \"Ar\"\n", - " \"He\"\n", - " \"Ne\"\n", - " \"N2\"\n", - " \"CO2\"\n", - " \"proton\"\n", - " \"H\"\n", - " \"C=O\"\n", - " \"O=CO\"\n", - " \"H2O\"\n", - " ⋮\n", - " \"CCOCO\"\n", - " \"CCCOO\"\n", - " \"CCC\"\n", - " \"CCOOC\"\n", - " \"C=C=COO\"\n", - " \"CC=COO\"\n", - " \"C=CCO[O]\"\n", - " \"COCOC\"\n", - " \"COCCO\"" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "getfield.(ssys.sims[1].domain.phase.species,:name)" - ] - }, - { - "cell_type": "code", - "execution_count": 61, - "id": "9be02a3e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "192-element Vector{String}:\n", - " \"vacantX\"\n", - " \"CO2X\"\n", - " \"CHO2X\"\n", - " \"CO2HX\"\n", - " \"OCX\"\n", - " \"OX\"\n", - " \"CH2O2X\"\n", - " \"CHOX\"\n", - " \"CH2OX\"\n", - " \"HOX\"\n", - " ⋮\n", - " \"O=CCCO[Pt]\"\n", - " \"O=CCC[Pt]\"\n", - " \"C=COOC#[Pt]\"\n", - " \"C=CC=O.[Pt]\"\n", - " \"C=C([Pt])C=O\"\n", - " \"C=C(C=O)O[Pt]\"\n", - " \"C=CC=[Pt]\"\n", - " \"CC(O)O.[Pt]\"\n", - " \"OC(O)C[Pt]\"" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "getfield.(ssys.sims[2].domain.phase.species,:name)" - ] - }, - { - "cell_type": "code", - "execution_count": 62, - "id": "87dcaf99", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotX (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotX(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = molefractions(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Mole Fraction\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 63, - "id": "ddf6da6b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotC (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotC(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = concentrations(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Concentration\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 64, - "id": "e719a85d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys.sims[1], 1e-25, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1)\n", - "ylim(1e-25, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 65, - "id": "1ef78267", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotC(ssys.sims[1], 1e-25, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1)\n", - "ylim(1e-25, 1e8)\n", - "title(\"Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 66, - "id": "a1e338ce", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys.sims[2], 1e-2, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e-8)\n", - "ylim(1e-6, 5)\n", - "title(\"Surface Mole Fractions vs. Time on Ag111@-0.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 67, - "id": "1ee8224d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotC(ssys.sims[2], 1e-4, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1)\n", - "ylim(1e-6, 1)\n", - "title(\"Surface Concentrations vs. Time on Ag111@-0.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 68, - "id": "1f7d8918", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "1465×1370 Array{RGBA{N0f8},2} with eltype ColorTypes.RGBA{FixedPointNumbers.N0f8}:\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,0.667) RGBA{N0f8}(1.0,1.0,1.0,0.667)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "getfluxdiagram(ssys,1e-8;speciesratetolerance=1e-8)" - ] - }, - { - "cell_type": "code", - "execution_count": 69, - "id": "64238bc0", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"CH2O2X\",1e-8;N=15,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 70, - "id": "e8bb3c43", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"CHO2X\",1;N=10,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 71, - "id": "0bb84a7f", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"CO2HX\",1;N=10,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 72, - "id": "1044d2b9", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"OX\",1;N=10,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 73, - "id": "7086e403", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"OCX\",1.0e-6)" - ] - }, - { - "cell_type": "code", - "execution_count": 86, - "id": "64834b04", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "OX+OCX<=>vacantX+CO2X\n", - "kf = 20654.615923781494\n", - "krev = 11189.298481041604\n", - "Kc = 1.8459259048971917\n", - "CHO2X<=>CO2HX\n", - "kf = 6.700453386611787e9\n", - "krev = 154.2911945001599\n", - "Kc = 4.342732200835248e7\n", - "vacantX+CHO2X<=>OX+CHOX\n", - "kf = 7.803841747257553e9\n", - "krev = 7.148654626970559e-10\n", - "Kc = 1.0916518078541791e19\n", - "CHO2X+CHO2X<=>CO2X+CH2O2X\n", - "kf = 2.5e10\n", - "krev = 3.2154148400024995e-34\n", - "Kc = 7.775046531781437e43\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "kf = 2.5e10\n", - "krev = 8.082730550170151e-23\n", - "Kc = 3.0930141546625875e32\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "kf = 2.5e10\n", - "krev = 9.19383930722573e-19\n", - "Kc = 2.71921219901589e28\n", - "CO2HX+CO2HX<=>CO2X+CH2O2X\n", - "kf = 2.5e10\n", - "krev = 2.4457047139990357e-18\n", - "Kc = 1.0222002622353312e28\n", - "CHOX+CHO2X<=>CO2X+CH2OX\n", - "kf = 3.0109478093923404e-24\n", - "krev = 3.037156297092479e15\n", - "Kc = 9.913707148607306e-40\n", - "CHOX+CO2HX<=>CO2X+CH2OX\n", - "kf = 2.5e10\n", - "krev = 1.678437078622112e-22\n", - "Kc = 1.4894809176000438e32\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "kf = 500114.13488002896\n", - "krev = 399.6803280141717\n", - "Kc = 1251.2853393732605\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "kf = 0.00010342351299484538\n", - "krev = 3.7647642123828275e-11\n", - "Kc = 2.747144499904435e6\n", - "CHO2X+CH2O2X<=>CO2HX+CH2O2X\n", - "kf = 6.542996392927688e-8\n", - "krev = 15.579156394796986\n", - "Kc = 4.199839983064083e-9\n", - "CHOX+CHO2X<=>OCX+CH2O2X\n", - "kf = 6.542996392927688e-8\n", - "krev = 6.197590078701277e-11\n", - "Kc = 1055.7323588427441\n", - "CHO2X+CH2OX<=>CHOX+CH2O2X\n", - "kf = 2.0718885766149262e-11\n", - "krev = 0.008867505326838887\n", - "Kc = 2.336495440655708e-9\n", - "OCX+CH2O2X<=>CHOX+CO2HX\n", - "kf = 403943.82249737746\n", - "krev = 29.756334575496034\n", - "Kc = 13575.053119278344\n", - "OCX+CH2O2X<=>CHOX+CO2HX\n", - "kf = 8.486192390111145e-15\n", - "krev = 9.7037034735699e11\n", - "Kc = 8.745312975839684e-27\n", - "CO2HX+CH2OX<=>CHOX+CH2O2X\n", - "kf = 1.2668346793097018e-21\n", - "krev = 380.13410282264914\n", - "Kc = 3.332599390328158e-24\n", - "OCX+CH2O2X<=>CHOX+CO2HX\n", - "kf = 9.840171155787102e-15\n", - "krev = 0.011746228705195169\n", - "Kc = 8.377302539184302e-13\n", - "OCX+CH2O2X<=>CHOX+CO2HX\n", - "kf = 2.4999999999999992e10\n", - "krev = 0.0001729697966089756\n", - "Kc = 1.4453390412729847e14\n", - "OCX+CH2OX<=>CHOX+CHOX\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.180104845075902e-9\n", - "Kc = 9.475050217848336\n", - "HOX+OCX<=>vacantX+CO2HX\n", - "kf = 2.5e10\n", - "krev = 1.421137905927188e-15\n", - "Kc = 1.7591536961847018e25\n", - "vacantX+CH2O2X<=>HOX+CHOX\n", - "kf = 1.7047654949014593e-31\n", - "krev = 21441.30602897437\n", - "Kc = 7.950847269274322e-36\n", - "OX+CH2O2X<=>HOX+CHO2X\n", - "kf = 2.094291727583087e10\n", - "krev = 6.539117564188543e-11\n", - "Kc = 3.202713067971846e20\n", - "OX+CH2O2X<=>HOX+CHO2X\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.886422105564557e-15\n", - "Kc = 2.099567387708916e7\n", - "OX+CH2O2X<=>HOX+CO2HX\n", - "kf = 3.132095071630788e8\n", - "krev = 159.05427897483804\n", - "Kc = 1.9691988746346629e6\n", - "OX+CHOX<=>HOX+OCX\n", - "kf = 0.33148947903056336\n", - "krev = 0.22094946278291003\n", - "Kc = 1.5002954741567418\n", - "OX+CH2OX<=>HOX+CHOX\n", - "kf = 3.1990463818100786e-8\n", - "krev = 29981.045237801853\n", - "Kc = 1.0670229661561413e-12\n", - "OX+CH2O2X<=>HOX+CHO2X\n", - "kf = 0.23228315702691824\n", - "krev = 0.21874826816857254\n", - "Kc = 1.061874267493242\n", - "OX+CH2O2X<=>HOX+CHO2X\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.962949149852605e-13\n", - "Kc = 201771.41789913058\n", - "HOX+OCX<=>HX+CO2X\n", - "kf = 3.1990463818100786e-8\n", - "krev = 42359.465576793365\n", - "Kc = 7.552140562327293e-13\n", - "vacantX+HOX<=>OX+HX\n", - "kf = 4.842414926683719e6\n", - "krev = 2.0721934488233277e8\n", - "Kc = 0.023368546645263413\n", - "HX+CHO2X<=>vacantX+CH2O2X\n", - "kf = 2.5e10\n", - "krev = 4.456327978496074e-40\n", - "Kc = 5.610000009118949e49\n", - "HX+CO2HX<=>vacantX+CH2O2X\n", - "kf = 3.8736093818093735e10\n", - "krev = 4.9917087254698525e28\n", - "Kc = 7.760086965901168e-19\n", - "HX+OCX<=>vacantX+CHOX\n", - "kf = 2.5e10\n", - "krev = 836.113886499964\n", - "Kc = 2.990023297502197e7\n", - "HX+CHOX<=>vacantX+CH2OX\n", - "kf = 1.3995006080437096e-36\n", - "krev = 7.971831424002446e14\n", - "Kc = 1.755557203367275e-51\n", - "OX+CH2OX<=>HX+CHO2X\n", - "kf = 2.5e10\n", - "krev = 2.2832873000074666e-31\n", - "Kc = 1.0949125850224037e41\n", - "CHO2X+CO[Pt]<=>CH2OX+CH2O2X\n", - "kf = 5.0e10\n", - "krev = 1.6222106700956051e-18\n", - "Kc = 3.0822137298020145e28\n", - "CO2HX+CO[Pt]<=>CH2OX+CH2O2X\n", - "kf = 2.986526002688191e9\n", - "krev = 1.177582616520277e-15\n", - "Kc = 2.5361498724508097e24\n", - "CHOX+CO[Pt]<=>CH2OX+CH2OX\n", - "kf = 1.43713660093583e-9\n", - "krev = 0.00032277677938391324\n", - "Kc = 4.452416322137251e-6\n", - "CHO2X+OC[Pt]<=>CH2OX+CH2O2X\n", - "kf = 2.5e10\n", - "krev = 3.3233693919112797e9\n", - "Kc = 7.522486083204378\n", - "CO2HX+OC[Pt]<=>CH2OX+CH2O2X\n", - "kf = 2.5e10\n", - "krev = 2.3130431223595305e-25\n", - "Kc = 1.0808272339729469e35\n", - "CHOX+OC[Pt]<=>CH2OX+CH2OX\n", - "kf = 359723.7676387533\n", - "krev = 0.32068189796600394\n", - "Kc = 1.121746409511672e6\n", - "CO[Pt]<=>OC[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.1987210746671435e-18\n", - "Kc = 4.808875036943709e27\n", - "CHO2X+OC(O)[Pt]<=>CH2O2X+CH2O2X\n", - "kf = 4.0912386971316826e8\n", - "krev = 1.7763617117679594e-6\n", - "Kc = 2.3031563166601894e14\n", - "CO2HX+OC(O)[Pt]<=>CH2O2X+CH2O2X\n", - "kf = 2.010168305725754e-19\n", - "krev = 2.61760793808642e-25\n", - "Kc = 767940.9419866255\n", - "CHOX+OC(O)[Pt]<=>CH2OX+CH2O2X\n", - "kf = 1.0945721587141857e10\n", - "krev = 4.219325007995329e-16\n", - "Kc = 2.594187830138819e25\n", - "CHO2X+OCO[Pt]<=>CH2O2X+CH2O2X\n", - "kf = 2.4999999999999992e10\n", - "krev = 4.2182399573625954e-24\n", - "Kc = 5.926642451045138e33\n", - "CO2HX+OCO[Pt]<=>CH2O2X+CH2O2X\n", - "kf = 2338.960705505517\n", - "krev = 9707.159813448116\n", - "Kc = 0.24095211683495363\n", - "CHOX+OCO[Pt]<=>CH2OX+CH2O2X\n", - "kf = 3.9606703322965305e-8\n", - "krev = 7.563806299311394e-5\n", - "Kc = 0.0005236345532350701\n", - "CHOX+OCO[Pt]<=>CH2OX+CH2O2X\n", - "kf = 2238.846752341849\n", - "krev = 2.856092619409056e-69\n", - "Kc = 7.83884506100184e71\n", - "vacantX+OCO[Pt]<=>OX+OC[Pt]\n", - "kf = 4.980245005159166e-22\n", - "krev = 5.509834949091977\n", - "Kc = 9.038827934364735e-23\n", - "OC(O)[Pt]<=>OCO[Pt]\n", - "kf = 0.004250927229403503\n", - "krev = 4.255087166696794e-10\n", - "Kc = 9.990223614393027e6\n", - "CHOX+OCO[Pt]<=>CH2OX+CH2O2X\n", - "kf = 74.64023007210145\n", - "krev = 2.953439666185894e-39\n", - "Kc = 2.52723056870475e40\n", - "CHOX+OCO[Pt]<=>CH2OX+CH2O2X\n", - "kf = 5.799304049644909e-8\n", - "krev = 5.0006650398424424e-61\n", - "Kc = 1.1597065597154312e53\n", - "vacantX+H2OX<=>HX+HOX\n", - "kf = 2.5e10\n", - "krev = 2.298435109298346e-13\n", - "Kc = 1.087696576634346e23\n", - "OX+H2OX<=>HOX+HOX\n", - "kf = 2.5e10\n", - "krev = 2.124472809651395e-41\n", - "Kc = 1.1767625307523824e51\n", - "HOX+CHO2X<=>H2OX+CO2X\n", - "kf = 4.832014059685671\n", - "krev = 1.8278921581756875e-33\n", - "Kc = 2.643489681857502e33\n", - "HOX+CO2HX<=>H2OX+CO2X\n", - "kf = 4.5608316796485725e-28\n", - "krev = 3.884151005592286e17\n", - "Kc = 1.1742158513101117e-45\n", - "HOX+CH2O2X<=>H2OX+CHO2X\n", - "kf = 934895.4476836504\n", - "krev = 8.923256806166294e-10\n", - "Kc = 1.0477065358441816e15\n", - "HOX+CH2O2X<=>H2OX+CO2HX\n", - "kf = 257035.79866672424\n", - "krev = 6.729989470427483e-12\n", - "Kc = 3.819260041879346e16\n", - "HOX+CHOX<=>H2OX+OCX\n", - "kf = 2.5e10\n", - "krev = 2.370438376324263e-23\n", - "Kc = 1.0546572418712873e33\n", - "HOX+CH2OX<=>H2OX+CHOX\n", - "kf = 8.024182777649594e9\n", - "krev = 1.713385513637571e-29\n", - "Kc = 4.683232532189445e38\n", - "H2OX+OCX<=>HX+CO2HX\n", - "kf = 2.4823885573387985e-14\n", - "krev = 9.351132511056354e15\n", - "Kc = 2.6546394828687704e-30\n", - "HOX+CO[Pt]<=>H2OX+CH2OX\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.4949222028864902e7\n", - "Kc = 2.6494156850764662e-15\n", - "HOX+OC[Pt]<=>H2OX+CH2OX\n", - "kf = 5.6976884072695144e-8\n", - "krev = 2.551666729065355e-8\n", - "Kc = 2.23292812590636\n", - "HOX+OC(O)[Pt]<=>H2OX+CH2O2X\n", - "kf = 1.6117056515547888e10\n", - "krev = 0.4241906612356468\n", - "Kc = 3.79948405007307e10\n", - "HOX+OCO[Pt]<=>H2OX+CH2O2X\n", - "kf = 2.5e10\n", - "krev = 1.2517365237178077e-36\n", - "Kc = 1.9972254165554745e46\n", - "vacantX+CH2O2X<=>OX+OC=[Pt]\n", - "kf = 7.436243130002853e-15\n", - "krev = 7.618143862840909e-6\n", - "Kc = 9.761226965369721e-10\n", - "vacantX+OC[Pt]<=>HX+OC=[Pt]\n", - "kf = 2.355118429524867e-13\n", - "krev = 1.0085447542339824e12\n", - "Kc = 2.3351650183472963e-25\n", - "OC=[Pt]+CH2O2X<=>CHO2X+OC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.2580528275000757e-47\n", - "Kc = 1.987197950159092e57\n", - "OC=[Pt]+CH2O2X<=>CO2HX+OC[Pt]\n", - "kf = 7.647664939071944e6\n", - "krev = 1.3495259820101604e-44\n", - "Kc = 5.666926788382771e50\n", - "CHOX+OC=[Pt]<=>OCX+OC[Pt]\n", - "kf = 1.577998856851828e-7\n", - "krev = 1.7401723222676178e-10\n", - "Kc = 906.8060884887184\n", - "HOX+OC=[Pt]<=>OX+OC[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 9.354213865452181e-57\n", - "Kc = 2.6725923054135235e66\n", - "CH2OX+OC=[Pt]<=>CHOX+OC[Pt]\n", - "kf = 366139.2749661925\n", - "krev = 442.06521987276346\n", - "Kc = 828.2471873077366\n", - "H2OX+OC=[Pt]<=>HOX+OC[Pt]\n", - "kf = 1.5395975576095126e-29\n", - "krev = 2.622153295712258e16\n", - "Kc = 5.871500953537159e-46\n", - "vacantX+OC(O)[Pt]<=>HOX+OC=[Pt]\n", - "kf = 2015.4980994888942\n", - "krev = 1.5583753177625496e-15\n", - "Kc = 1.293332919557955e18\n", - "OCX+OC(O)[Pt]<=>CO2HX+OC=[Pt]\n", - "kf = 73.33238091278024\n", - "krev = 14511.198914062346\n", - "Kc = 0.005053502563576338\n", - "OC=[Pt]+CH2O2X<=>CHOX+OC(O)[Pt]\n", - "kf = 422670.5724931744\n", - "krev = 9.80980243728561e-11\n", - "Kc = 4.3086552985681545e15\n", - "H2OX+OC=[Pt]<=>HX+OC(O)[Pt]\n", - "kf = 7.027691701271914e7\n", - "krev = 9.157133997597336e-26\n", - "Kc = 7.674553744780683e32\n", - "OX+O=CC(=O)[Pt]<=>OCX+CHO2X\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.3310785577331067e-33\n", - "Kc = 2.514767798332947e25\n", - "OCX+CH2O2X<=>HOX+O=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.244084982305732e-16\n", - "Kc = 1.1140398067417758e26\n", - "vacantX+O=CC(=O)[Pt]<=>OCX+CHOX\n", - "kf = 1.3012361379695292e10\n", - "krev = 1.990497991828919e-14\n", - "Kc = 6.537239139708557e23\n", - "OCX+CH2OX<=>HX+O=CC(=O)[Pt]\n", - "kf = 5.858305523872122e-8\n", - "krev = 9.372228401924443e12\n", - "Kc = 6.250707166578664e-21\n", - "vacantX+OC=[Pt]<=>HX+OC#[Pt]\n", - "kf = 8.724708246600757e-23\n", - "krev = 252.56605644619947\n", - "Kc = 3.454426287270814e-25\n", - "OC#[Pt]+CH2O2X<=>CHO2X+OC=[Pt]\n", - "kf = 7.165711269221808e-16\n", - "krev = 0.1859922027934253\n", - "Kc = 3.852694447186316e-15\n", - "OC#[Pt]+CH2O2X<=>CO2HX+OC=[Pt]\n", - "kf = 105.5087249891725\n", - "krev = 9.918244171872598e-12\n", - "Kc = 1.063784306585105e13\n", - "CHOX+OC#[Pt]<=>OCX+OC=[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 9.042590347389556e-30\n", - "Kc = 3.70176394754519e21\n", - "HOX+OC#[Pt]<=>OX+OC=[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 1.614840618256874e-45\n", - "Kc = 1.7641643214981894e37\n", - "OC#[Pt]+CH2OX<=>CHOX+OC=[Pt]\n", - "kf = 3.442529358831723e8\n", - "krev = 2.6586367586035048e-11\n", - "Kc = 1.294847574679578e19\n", - "H2OX+OC#[Pt]<=>HOX+OC=[Pt]\n", - "kf = 1.3336211820914592e-23\n", - "krev = 16620.58178963317\n", - "Kc = 8.023913957833202e-28\n", - "OC=[Pt]+OC=[Pt]<=>OC#[Pt]+OC[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 2.6714659015861004e-16\n", - "Kc = 1.2530025152300434e8\n", - "OX+O=CC=O.[Pt]<=>CHOX+CHO2X\n", - "kf = 3.6896065237788346e-26\n", - "krev = 1200.2597905170037\n", - "Kc = 3.0740066050113714e-29\n", - "HOX+O=CC=O.[Pt]<=>CHOX+CH2O2X\n", - "kf = 1.1691860289045307e-22\n", - "krev = 1.716447494000275\n", - "Kc = 6.811662069427353e-23\n", - "vacantX+O=CC=O.[Pt]<=>CHOX+CHOX\n", - "kf = 8.415426775358086e9\n", - "krev = 2.2521891994794312e-15\n", - "Kc = 3.736554094701821e24\n", - "CHO2X+O=CC(=O)[Pt]<=>CO2X+O=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.535364355320737e-17\n", - "Kc = 7.071406929352247e26\n", - "CO2HX+O=CC(=O)[Pt]<=>CO2X+O=CC=O.[Pt]\n", - "kf = 2.563914200342384e9\n", - "krev = 5.568313503115363e-15\n", - "Kc = 4.6044717110628266e23\n", - "CHO2X+O=CC=O.[Pt]<=>CH2O2X+O=CC(=O)[Pt]\n", - "kf = 2.4021541557833424e-8\n", - "krev = 7.766959077565021e-8\n", - "Kc = 0.30927859047461714\n", - "CO2HX+O=CC=O.[Pt]<=>CH2O2X+O=CC(=O)[Pt]\n", - "kf = 3.028654941635431e8\n", - "krev = 1.0392777770118965e-11\n", - "Kc = 2.914191959673513e19\n", - "OCX+O=CC=O.[Pt]<=>CHOX+O=CC(=O)[Pt]\n", - "kf = 3.6584912239485734e-16\n", - "krev = 0.32395775785233605\n", - "Kc = 1.1293111942132156e-15\n", - "OCX+O=CC=O.[Pt]<=>CHOX+O=CC(=O)[Pt]\n", - "kf = 3.132095071630788e8\n", - "krev = 5.819571251914923e7\n", - "Kc = 5.382003133994065\n", - "CHOX+O=CC=O.[Pt]<=>CH2OX+O=CC(=O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.432948758337896e-37\n", - "Kc = 7.282369111767359e46\n", - "OX+O=CC=O.[Pt]<=>HOX+O=CC(=O)[Pt]\n", - "kf = 9001.813049524091\n", - "krev = 8.180569891408677e12\n", - "Kc = 1.1003894800749632e-9\n", - "vacantX+O=CC=O.[Pt]<=>HX+O=CC(=O)[Pt]\n", - "kf = 3.705974451661604e-28\n", - "krev = 2668.9209237076484\n", - "Kc = 1.3885665996103351e-31\n", - "CO[Pt]+O=CC(=O)[Pt]<=>CH2OX+O=CC=O.[Pt]\n", - "kf = 1.2718474027465153e-10\n", - "krev = 0.0002705673832361486\n", - "Kc = 4.7006678614933393e-7\n", - "OC[Pt]+O=CC(=O)[Pt]<=>CH2OX+O=CC=O.[Pt]\n", - "kf = 5.011103886030472e-21\n", - "krev = 6.896680096586553e-19\n", - "Kc = 0.007265965386027795\n", - "OC=[Pt]+O=CC=O.[Pt]<=>OC[Pt]+O=CC(=O)[Pt]\n", - "kf = 4.64412268136931e-20\n", - "krev = 4.4743512788423464e-26\n", - "Kc = 1.0379432440474117e6\n", - "OC(O)[Pt]+O=CC(=O)[Pt]<=>CH2O2X+O=CC=O.[Pt]\n", - "kf = 7.775170632726667e-10\n", - "krev = 7.739686395050031e-10\n", - "Kc = 1.004584712592403\n", - "OCO[Pt]+O=CC(=O)[Pt]<=>CH2O2X+O=CC=O.[Pt]\n", - "kf = 1.653107374238179e-12\n", - "krev = 3.492310477620836e11\n", - "Kc = 4.7335635958815765e-24\n", - "HOX+O=CC=O.[Pt]<=>H2OX+O=CC(=O)[Pt]\n", - "kf = 4.0412190145177725e-23\n", - "krev = 628.7683045605482\n", - "Kc = 6.427198993979533e-26\n", - "OC#[Pt]+O=CC=O.[Pt]<=>OC=[Pt]+O=CC(=O)[Pt]\n", - "kf = 1.1281154422531313e-23\n", - "krev = 247.99076039714222\n", - "Kc = 4.5490220702034325e-26\n", - "OCX+O=CC=O.[Pt]<=>CHOX+O=CC(=O)[Pt]\n", - "kf = 0.7216092218623162\n", - "krev = 1.1659522251493753e-8\n", - "Kc = 6.1890119191621915e7\n", - "OCX+O=CC=O.[Pt]<=>CHOX+O=CC(=O)[Pt]\n", - "kf = 2.9829932789111093e-16\n", - "krev = 8.136723289652317e-19\n", - "Kc = 366.6086669930953\n", - "[H][H].[Pt]+OCX<=>HX+CHOX\n", - "kf = 2.5e10\n", - "krev = 3.654502873565959e-54\n", - "Kc = 6.840875726444761e63\n", - "OX+[H][H].[Pt]<=>HX+HOX\n", - "kf = 5.289547656637059e7\n", - "krev = 2.1352018805017766e-40\n", - "Kc = 2.4773056379071775e47\n", - "[H][H].[Pt]+OC=[Pt]<=>HX+OC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.12378969712814e-32\n", - "Kc = 2.2246155187120725e42\n", - "[H][H].[Pt]+OC#[Pt]<=>HX+OC=[Pt]\n", - "kf = 1.6293289822172011e-13\n", - "krev = 7.740036852315493e-9\n", - "Kc = 2.1050661816032238e-5\n", - "HOX+O=COC[Pt]<=>CH2OX+CH2O2X\n", - "kf = 3.0636862331912886e-9\n", - "krev = 3.008499680951675e11\n", - "Kc = 1.0183435459837431e-20\n", - "CHOX+O=COC[Pt]<=>CH2OX+O=CC=O.[Pt]\n", - "kf = 4.11558111763413e-6\n", - "krev = 1.6637324348077724e-7\n", - "Kc = 24.73703722744123\n", - "OO[Pt]+OCX<=>OX+CO2HX\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.1302052975227224e-55\n", - "Kc = 2.7224155607861307e47\n", - "OX+CH2O2X<=>OO[Pt]+CHOX\n", - "kf = 6.172603247806586\n", - "krev = 1.291687223902065e-14\n", - "Kc = 4.778713556645498e14\n", - "vacantX+OO[Pt]<=>OX+HOX\n", - "kf = 4.9999999999999985e10\n", - "krev = 7.969498365351247e-51\n", - "Kc = 6.273920604260804e60\n", - "OO[Pt]+OC=[Pt]<=>OX+OC(O)[Pt]\n", - "kf = 0.0007071288662616175\n", - "krev = 2.8988454126647536e-5\n", - "Kc = 24.393465866522067\n", - "OX+H2OX<=>HX+OO[Pt]\n", - "kf = 2.961131444342359e-9\n", - "krev = 1.299206322752899e13\n", - "Kc = 2.2791849088819035e-22\n", - "vacantX+OCX<=>OX+CX\n", - "kf = 3.270015659434578e-8\n", - "krev = 1.7533480653497175e-11\n", - "Kc = 1865.0122722679996\n", - "vacantX+OC#[Pt]<=>HOX+CX\n", - "kf = 2.7877482479606147e9\n", - "krev = 8.98671268743291e-18\n", - "Kc = 3.1020778619739604e26\n", - "CX+CO2HX<=>OCX+OC#[Pt]\n", - "kf = 1.351949923589269e-23\n", - "krev = 7.975137957191956e11\n", - "Kc = 1.6952056890377485e-35\n", - "OO[Pt]+CX<=>OX+OC#[Pt]\n", - "kf = 1181.9069662995785\n", - "krev = 1.0235810933777192e20\n", - "Kc = 1.1546783874244874e-17\n", - "CX+CH2O2X<=>CHOX+OC#[Pt]\n", - "kf = 5.28370763875636e9\n", - "krev = 1.2149259925984929e9\n", - "Kc = 4.348995470461149\n", - "H2OX+CX<=>HX+OC#[Pt]\n", - "kf = 5.733311120080377e8\n", - "krev = 8.483521653048543e-25\n", - "Kc = 6.758173497465076e32\n", - "CX+OC(O)[Pt]<=>OC#[Pt]+OC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.728240377953911e-36\n", - "Kc = 9.163415438763194e45\n", - "vacantX+CHX<=>HX+CX\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.00447183609125585\n", - "Kc = 1.463156578060128e-5\n", - "vacantX+OC=[Pt]<=>HOX+CHX\n", - "kf = 0.05589950368763065\n", - "krev = 5.054770535995559e16\n", - "Kc = 1.1058761874463802e-18\n", - "CHX+CO2HX<=>OCX+OC=[Pt]\n", - "kf = 9.385776922831516e-7\n", - "krev = 3.9782610412247473e11\n", - "Kc = 2.359266228528335e-18\n", - "OO[Pt]+CHX<=>OX+OC=[Pt]\n", - "kf = 9.872876935778847e-16\n", - "krev = 6.917821124819518e13\n", - "Kc = 1.427165686657795e-29\n", - "CHX+CH2O2X<=>CHOX+OC=[Pt]\n", - "kf = 3.9072411322938125e-9\n", - "krev = 8.599564777209447e13\n", - "Kc = 4.543533578174534e-23\n", - "H2OX+CHX<=>HX+OC=[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 8.854082166234876e-41\n", - "Kc = 8.666474551788235e32\n", - "CHX+OC(O)[Pt]<=>OC=[Pt]+OC=[Pt]\n", - "kf = 484458.3574999593\n", - "krev = 584.920039726471\n", - "Kc = 828.247152767255\n", - "CX+CH2O2X<=>CHX+CHO2X\n", - "kf = 359723.7676387533\n", - "krev = 0.4900054095759742\n", - "Kc = 734122.0333670193\n", - "CX+CH2O2X<=>CHX+CO2HX\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.450353404652874e-38\n", - "Kc = 4.586858528963997e47\n", - "CX+CHOX<=>OCX+CHX\n", - "kf = 2.5e10\n", - "krev = 4.352118282059013e-11\n", - "Kc = 5.7443291702477246e20\n", - "CX+CH2OX<=>CHX+CHOX\n", - "kf = 149.2804601441562\n", - "krev = 1.2008902564793325e-12\n", - "Kc = 1.2430816166483347e14\n", - "HOX+CX<=>OX+CHX\n", - "kf = 2.5e10\n", - "krev = 0.002571023024303106\n", - "Kc = 9.723755782691377e12\n", - "CX+OC[Pt]<=>CHX+OC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.1152446342994757e-23\n", - "Kc = 1.181896391302251e33\n", - "H2OX+CX<=>HOX+CHX\n", - "kf = 3.7510196251812924e-36\n", - "krev = 6.624293894020312e13\n", - "Kc = 5.662519938264367e-50\n", - "CX+OC=[Pt]<=>CHX+OC#[Pt]\n", - "kf = 2.7439565220867836e-15\n", - "krev = 5.60405879527954e-7\n", - "Kc = 4.896373543400539e-9\n", - "CX+OC=[Pt]<=>CHX+OC#[Pt]\n", - "kf = 9.387035392806688e-46\n", - "krev = 5.259242712748897e15\n", - "Kc = 1.784864457776713e-61\n", - "CX+O=CC=O.[Pt]<=>CHX+O=CC(=O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.1027992925080103e-36\n", - "Kc = 2.266958291489692e46\n", - "[H][H].[Pt]+CX<=>HX+CHX\n", - "kf = 2.5e10\n", - "krev = 1.2299433704122521e-26\n", - "Kc = 2.032613907388314e36\n", - "CX+OC=[Pt]<=>CHX+OC#[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.8619443782965007\n", - "Kc = 410274.8449265323\n", - "CX+OC=[Pt]<=>CHX+OC#[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 3.561089909521239e-25\n", - "Kc = 1.4777843564830474e17\n", - "vacantX+CH2X<=>HX+CHX\n", - "kf = 135.4631249389026\n", - "krev = 3.092595390223456e6\n", - "Kc = 4.3802407960361956e-5\n", - "vacantX+CH2OX<=>OX+CH2X\n", - "kf = 5.799304049644909e-8\n", - "krev = 3.5093718907449027e-71\n", - "Kc = 1.6525190917893694e63\n", - "vacantX+OC[Pt]<=>HOX+CH2X\n", - "kf = 5.136678216751685e-50\n", - "krev = 2.063334055048756\n", - "Kc = 2.489503919243124e-50\n", - "CO2HX+CH2X<=>OCX+OC[Pt]\n", - "kf = 1.277565794776397e-10\n", - "krev = 3.752447070055582e-7\n", - "Kc = 0.0003404620427484067\n", - "OO[Pt]+CH2X<=>OX+OC[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 3.6888123831707493e-19\n", - "Kc = 9.074339235332521e10\n", - "CH2X+CH2O2X<=>CHOX+OC[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 0.06219023230090054\n", - "Kc = 4.0199238811394476e11\n", - "H2OX+CH2X<=>HX+OC[Pt]\n", - "kf = 3.3834985622063113e-5\n", - "krev = 2.9362980773683545e12\n", - "Kc = 1.1523007790948657e-17\n", - "CH2X+OC(O)[Pt]<=>OC=[Pt]+OC[Pt]\n", - "kf = 6.170227811474367e-18\n", - "krev = 2.1467268001769245e15\n", - "Kc = 2.874249210922341e-33\n", - "vacantX+O=COC[Pt]<=>CHO2X+CH2X\n", - "kf = 45.65094374677705\n", - "krev = 8.967858326569276e-10\n", - "Kc = 5.0905067948638275e10\n", - "CH2X+CH2O2X<=>HX+O=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.1079184319144836e-21\n", - "Kc = 2.2564838060144904e31\n", - "CX+OC[Pt]<=>OC#[Pt]+CH2X\n", - "kf = 2.5e10\n", - "krev = 0.13466450883801714\n", - "Kc = 1.8564653906005447e11\n", - "CHX+CH2O2X<=>CHO2X+CH2X\n", - "kf = 2.5e10\n", - "krev = 1.585390854652908e-37\n", - "Kc = 1.576898209462252e47\n", - "CHX+CH2O2X<=>CO2HX+CH2X\n", - "kf = 1.4120852874068921e7\n", - "krev = 3.000260496950355e-29\n", - "Kc = 4.706542278052925e35\n", - "CHX+CHOX<=>OCX+CH2X\n", - "kf = 4.3209399543319175e-11\n", - "krev = 0.0003615296985530135\n", - "Kc = 1.195182573278502e-7\n", - "CHX+CH2OX<=>CHOX+CH2X\n", - "kf = 9.552144537727627e8\n", - "krev = 4.245639842324063e-20\n", - "Kc = 2.2498716076912407e28\n", - "HOX+CHX<=>OX+CH2X\n", - "kf = 15.24168336652918\n", - "krev = 2.925086878294221e-11\n", - "Kc = 5.2106771527474915e11\n", - "CH2X+OC=[Pt]<=>CHX+OC[Pt]\n", - "kf = 6.063283190982672e-6\n", - "krev = 7.026751658283665e14\n", - "Kc = 8.628856526948432e-21\n", - "CH2X+OC=[Pt]<=>CHX+OC[Pt]\n", - "kf = 1.0700076742100442e-15\n", - "krev = 2.910581039741659e-8\n", - "Kc = 3.67626827633364e-8\n", - "H2OX+CHX<=>HOX+CH2X\n", - "kf = 4.440492535767249e9\n", - "krev = 9.213887643325446e-17\n", - "Kc = 4.819347389138122e25\n", - "OC#[Pt]+CH2X<=>CHX+OC=[Pt]\n", - "kf = 3.2094062904328744e-20\n", - "krev = 74.41720028073364\n", - "Kc = 4.312721089110603e-22\n", - "CHX+O=CC=O.[Pt]<=>CH2X+O=CC(=O)[Pt]\n", - "kf = 11983.404197457203\n", - "krev = 27576.843954134933\n", - "Kc = 0.4345458899280744\n", - "[H][H].[Pt]+CHX<=>HX+CH2X\n", - "kf = 2.5e10\n", - "krev = 4.459954780972869e-39\n", - "Kc = 5.605437998307831e48\n", - "CX+CH2X<=>CHX+CHX\n", - "kf = 2.5931203025755725e-8\n", - "krev = 3.8194581898791103e-32\n", - "Kc = 6.789235995427004e23\n", - "CH2X+OC=[Pt]<=>CHX+OC[Pt]\n", - "kf = 2.850945414803626e8\n", - "krev = 4.6591458607721776e7\n", - "Kc = 6.119030182779314\n", - "CH2X+OC=[Pt]<=>CHX+OC[Pt]\n", - "kf = 1.1776167531898308e-10\n", - "krev = 0.0005032011998508361\n", - "Kc = 2.3402502886298994e-7\n", - "vacantX+O=COC#[Pt]<=>CX+CHO2X\n", - "kf = 0.006845452357086415\n", - "krev = 1.638610749190394e14\n", - "Kc = 4.177595173514284e-17\n", - "CX+CH2O2X<=>HX+O=COC#[Pt]\n", - "kf = 1.3631835715271243e-51\n", - "krev = 1.0974745099569602e16\n", - "Kc = 1.242109551665655e-67\n", - "CH2X+O=COC#[Pt]<=>CX+O=COC[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.1640600284881483e-24\n", - "Kc = 1.1552359764005922e34\n", - "HOX+O=CCO[Pt]<=>CH2OX+CH2O2X\n", - "kf = 2.5e10\n", - "krev = 2.732517656232023e-19\n", - "Kc = 9.149071715230376e28\n", - "CHO2X+O=CCO[Pt]<=>CH2O2X+O=CC=O.[Pt]\n", - "kf = 327433.4917974331\n", - "krev = 0.29189612518083846\n", - "Kc = 1.1217466199476891e6\n", - "CO2HX+O=CCO[Pt]<=>CH2O2X+O=CC=O.[Pt]\n", - "kf = 3.661873055903852e-12\n", - "krev = 2.1682718089028445e11\n", - "Kc = 1.6888441019563762e-23\n", - "CHOX+O=CCO[Pt]<=>CH2OX+O=CC=O.[Pt]\n", - "kf = 1.1977509649486271e-8\n", - "krev = 1.0254845667743408e14\n", - "Kc = 1.1679853639496008e-22\n", - "CHOX+O=CCO[Pt]<=>CH2OX+O=CC=O.[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 3.3286101924403974e-7\n", - "Kc = 0.19656841788766613\n", - "HOX+O=CCO[Pt]<=>H2OX+O=CC=O.[Pt]\n", - "kf = 0.000861247081568792\n", - "krev = 5.418955290289518e-14\n", - "Kc = 1.5893230990705927e10\n", - "O=CC(=O)[Pt]+O=CCO[Pt]<=>O=CC=O.[Pt]+O=CC=O.[Pt]\n", - "kf = 2.4753542791841756e-22\n", - "krev = 11382.562807978633\n", - "Kc = 2.1746897609465158e-26\n", - "O=COC[Pt]<=>O=CCO[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.708424354052639e-26\n", - "Kc = 4.379492211760938e35\n", - "CHOX+O=CCO[Pt]<=>CH2OX+O=CC=O.[Pt]\n", - "kf = 2.810784197367395e8\n", - "krev = 8.682228189641076\n", - "Kc = 3.237399589106622e7\n", - "CHOX+O=CCO[Pt]<=>CH2OX+O=CC=O.[Pt]\n", - "kf = 0.010756441693245073\n", - "krev = 2.0353876594794328e15\n", - "Kc = 5.284714016589902e-18\n", - "vacantX+O=O.[Pt]<=>OX+OX\n", - "kf = 2.426386880233808e-11\n", - "krev = 0.0003222108693910823\n", - "Kc = 7.530431499158364e-8\n", - "OO[Pt]+CHO2X<=>O=O.[Pt]+CH2O2X\n", - "kf = 1.7265852223755207e6\n", - "krev = 2.1173801346453913e-15\n", - "Kc = 8.15434694094115e20\n", - "OO[Pt]+CO2HX<=>O=O.[Pt]+CH2O2X\n", - "kf = 5.262522960320117e-8\n", - "krev = 8.417963556232881e-20\n", - "Kc = 6.251539253129229e11\n", - "OO[Pt]+CHOX<=>O=O.[Pt]+CH2OX\n", - "kf = 3.109950102720783e-13\n", - "krev = 0.31413419650430946\n", - "Kc = 9.900068624582613e-13\n", - "HOX+OO[Pt]<=>O=O.[Pt]+H2OX\n", - "kf = 2.5e10\n", - "krev = 1.1559495343730438e-24\n", - "Kc = 2.162724172345407e34\n", - "OO[Pt]+O=CC(=O)[Pt]<=>O=O.[Pt]+O=CC=O.[Pt]\n", - "kf = 4.324230983561045e-22\n", - "krev = 1.3691212371032431e-19\n", - "Kc = 0.003158398881248938\n", - "CX+CHO2X<=>OX+O=CC#[Pt]\n", - "kf = 6.614441053978493e-6\n", - "krev = 7.629970776987544e11\n", - "Kc = 8.669025409544227e-18\n", - "CX+CH2O2X<=>HOX+O=CC#[Pt]\n", - "kf = 1.5563360867242215e-10\n", - "krev = 4.0343976517667425e14\n", - "Kc = 3.857666549162974e-25\n", - "vacantX+O=CC#[Pt]<=>CX+CHOX\n", - "kf = 0.0003463783354588583\n", - "krev = 6.683486846094463e16\n", - "Kc = 5.182599194629471e-21\n", - "CX+CH2OX<=>HX+O=CC#[Pt]\n", - "kf = 1.175900379595729e-21\n", - "krev = 0.27982743013843664\n", - "Kc = 4.2022341377111815e-21\n", - "CX+O=CC(=O)[Pt]<=>OCX+O=CC#[Pt]\n", - "kf = 16837.01815689783\n", - "krev = 6.867163373297897e-65\n", - "Kc = 2.4518155811417657e68\n", - "CX+O=CC=O.[Pt]<=>CHOX+O=CC#[Pt]\n", - "kf = 1.8186835430204133e-8\n", - "krev = 4.141977957602716e12\n", - "Kc = 4.39085760869917e-21\n", - "vacantX+OC(O)[Pt]<=>HX+OC(O)=[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 4.970959816815508e-38\n", - "Kc = 1.543639067721808e30\n", - "CH2O2X+OC(O)=[Pt]<=>CHO2X+OC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.781216654859147e-34\n", - "Kc = 2.846985899860024e43\n", - "CH2O2X+OC(O)=[Pt]<=>CO2HX+OC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.945821466805435e-27\n", - "Kc = 1.2848044091652411e37\n", - "CHOX+OC(O)=[Pt]<=>OCX+OC(O)[Pt]\n", - "kf = 484125.61468448705\n", - "krev = 1.0558750276780043e7\n", - "Kc = 0.04585065485913965\n", - "HOX+OC(O)=[Pt]<=>OX+OC(O)[Pt]\n", - "kf = 4.324183911493771e7\n", - "krev = 7.8667392573421875e12\n", - "Kc = 5.496793232924203e-6\n", - "CH2OX+OC(O)=[Pt]<=>CHOX+OC(O)[Pt]\n", - "kf = 0.43146252134138535\n", - "krev = 2.5450806210309695e15\n", - "Kc = 1.695280368629765e-16\n", - "H2OX+OC(O)=[Pt]<=>HOX+OC(O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 7.390785994602033e-44\n", - "Kc = 7.846667531546056e35\n", - "[H][H].[Pt]+OC(O)=[Pt]<=>HX+OC(O)[Pt]\n", - "kf = 5.0e10\n", - "krev = 2.765031941810381e-39\n", - "Kc = 1.8082973742163328e49\n", - "OC(O)=[Pt]+OC[Pt]<=>OC=[Pt]+OC(O)[Pt]\n", - "kf = 2.8707175642480555e-12\n", - "krev = 0.04083063397693327\n", - "Kc = 7.030793511239207e-11\n", - "OC(O)=[Pt]+O=CC=O.[Pt]<=>OC(O)[Pt]+O=CC(=O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.2543869389072832e-22\n", - "Kc = 1.9930054454949844e32\n", - "OCX+OC(O)=[Pt]<=>OC#[Pt]+CO2HX\n", - "kf = 1.5989383651417568e8\n", - "krev = 5.387605632290379e-38\n", - "Kc = 2.967808845470406e45\n", - "OC#[Pt]+CH2O2X<=>CHOX+OC(O)=[Pt]\n", - "kf = 3.286584099620913e-11\n", - "krev = 0.0009472638388816695\n", - "Kc = 3.469555117295539e-8\n", - "vacantX+OC(O)=[Pt]<=>HOX+OC#[Pt]\n", - "kf = 5.621568394735124e8\n", - "krev = 2.2372815421494465e13\n", - "Kc = 2.51267812692642e-5\n", - "CH2X+OC(O)=[Pt]<=>OC#[Pt]+OC[Pt]\n", - "kf = 4.008872108623533e-29\n", - "krev = 0.04458949177209046\n", - "Kc = 8.990620770279273e-28\n", - "OC=[Pt]+OC(O)=[Pt]<=>OC#[Pt]+OC(O)[Pt]\n", - "kf = 9.541010615775616e-58\n", - "krev = 6.285347549669836e9\n", - "Kc = 1.5179766179002778e-67\n", - "OC=[Pt]+OC(O)=[Pt]<=>OC#[Pt]+OC(O)[Pt]\n", - "kf = 1.4053920986837533e8\n", - "krev = 2.5815645207863396e8\n", - "Kc = 0.5443954963619013\n", - "H2OX+OC#[Pt]<=>HX+OC(O)=[Pt]\n", - "kf = 1.4053920986837533e8\n", - "krev = 1.2268284001067661e8\n", - "Kc = 1.1455490421981163\n", - "CHX+OC(O)=[Pt]<=>OC#[Pt]+OC=[Pt]\n", - "kf = 5.6976884072695144e-8\n", - "krev = 1.248882373151946e-25\n", - "Kc = 4.562229822244678e17\n", - "CX+OC(O)=[Pt]<=>OC#[Pt]+OC#[Pt]\n", - "kf = 1.9433361133957645e-7\n", - "krev = 3.518243282535333e-12\n", - "Kc = 55235.97879210185\n", - "OO[Pt]+OC#[Pt]<=>OX+OC(O)=[Pt]\n", - "kf = 5.0e10\n", - "krev = 6.440846716581066e-18\n", - "Kc = 7.762954499643958e27\n", - "CHX+OC(O)=[Pt]<=>CX+OC(O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 2.6755933088589045e-38\n", - "Kc = 1.0647523277182356e30\n", - "CH2X+OC(O)=[Pt]<=>CHX+OC(O)[Pt]\n", - "kf = 5.743984385098034e-15\n", - "krev = 0.20246227896672986\n", - "Kc = 2.8370639777506056e-14\n", - "OC=[Pt]+OC(O)=[Pt]<=>OC#[Pt]+OC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 9.030568673797047e-31\n", - "Kc = 2.7683749388385245e40\n", - "OC=[Pt]+OC(O)=[Pt]<=>OC#[Pt]+OC(O)[Pt]\n", - "kf = 59626.15667838481\n", - "krev = 5.052054449161558e-13\n", - "Kc = 1.1802358283822616e17\n", - "vacantX+O=C(O)C#[Pt]<=>CX+CO2HX\n", - "kf = 27.216448700907318\n", - "krev = 1.122343511964246e-9\n", - "Kc = 2.4249660118117508e10\n", - "CX+CH2O2X<=>HX+O=C(O)C#[Pt]\n", - "kf = 4067.906517801298\n", - "krev = 9.581534474143486e11\n", - "Kc = 4.245568941779481e-9\n", - "vacantX+O=C=C=O.[Pt]<=>OCX+OCX\n", - "kf = 1210.7940477205082\n", - "krev = 2.947449197084421e11\n", - "Kc = 4.107938650539627e-9\n", - "CHO2X+O=CC(=O)[Pt]<=>CH2O2X+O=C=C=O.[Pt]\n", - "kf = 4.4806064283670194e7\n", - "krev = 9.647714416341851e-27\n", - "Kc = 4.6442154431701585e33\n", - "CO2HX+O=CC(=O)[Pt]<=>CH2O2X+O=C=C=O.[Pt]\n", - "kf = 1.4211346889283953e7\n", - "krev = 2.9898684736722955e-43\n", - "Kc = 4.753167911707138e49\n", - "CHOX+O=CC(=O)[Pt]<=>CH2OX+O=C=C=O.[Pt]\n", - "kf = 4.481316095514531e9\n", - "krev = 7.381060539485826\n", - "Kc = 6.07137154822294e8\n", - "HOX+O=CC(=O)[Pt]<=>H2OX+O=C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.751017958044156e-54\n", - "Kc = 9.087545185555175e63\n", - "O=CC(=O)[Pt]+O=CC(=O)[Pt]<=>O=C=C=O.[Pt]+O=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.522467022601021e-34\n", - "Kc = 1.6420716921204226e44\n", - "CHOX+OOC[Pt]<=>CH2OX+CH2O2X\n", - "kf = 2.5e10\n", - "krev = 1.0775667741820985e-34\n", - "Kc = 2.3200418386114085e44\n", - "OCO[Pt]<=>OOC[Pt]\n", - "kf = 395377.4080430906\n", - "krev = 715.0601225795458\n", - "Kc = 552.9289014422803\n", - "vacantX+OOC[Pt]<=>OO[Pt]+CH2X\n", - "kf = 2.4999999999999992e10\n", - "krev = 7.340819523839582e-21\n", - "Kc = 3.405614307613962e30\n", - "vacantX+C=C=O.[Pt]<=>OCX+CH2X\n", - "kf = 332249.5811031886\n", - "krev = 401.14766551623046\n", - "Kc = 828.2475748067037\n", - "vacantX+COC(=O)[Pt]<=>OCX+CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.735276356245465e-15\n", - "Kc = 1.4406927121447852e25\n", - "OCX+CO[Pt]<=>OX+CC(=O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.64244938326729e-40\n", - "Kc = 3.7636718863039337e49\n", - "CHO2X+CC(=O)[Pt]<=>CH2O2X+C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.2486460747567866e-15\n", - "Kc = 1.1117801187411852e25\n", - "CO2HX+CC(=O)[Pt]<=>CH2O2X+C=C=O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 1291.5767888759226\n", - "Kc = 273.8002875141987\n", - "CHOX+CC(=O)[Pt]<=>CH2OX+C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3571588049567083e-22\n", - "Kc = 1.842083616795123e32\n", - "HOX+CC(=O)[Pt]<=>H2OX+C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.287360377049269e-14\n", - "Kc = 1.9419581684890723e24\n", - "O=CC(=O)[Pt]+CC(=O)[Pt]<=>C=C=O.[Pt]+O=CC=O.[Pt]\n", - "kf = 3.162060147889592e9\n", - "krev = 1.6872184207187113e-17\n", - "Kc = 1.8741261410260308e26\n", - "vacantX+O=COCC#[Pt]<=>CX+O=COC[Pt]\n", - "kf = 3.3881471741726223e-34\n", - "krev = 2.264159139077055e16\n", - "Kc = 1.4964262518904662e-50\n", - "vacantX+O=C([Pt])CO<=>OCX+OC[Pt]\n", - "kf = 1.8009876630720204e-13\n", - "krev = 6.668943472119082e14\n", - "Kc = 2.7005591974222413e-28\n", - "OCX+OCO[Pt]<=>OX+O=C([Pt])CO\n", - "kf = 3.2830355290077765e-39\n", - "krev = 2.9277080237249806e14\n", - "Kc = 1.121367124864694e-53\n", - "CHOX+O=C([Pt])CO<=>CH2O2X+C=C=O.[Pt]\n", - "kf = 1.0242943870290668e-63\n", - "krev = 2.920849603333263e13\n", - "Kc = 3.5068371403311754e-77\n", - "OCX+O=CCO[Pt]<=>OX+O=CCC(=O)[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 1179.037991138623\n", - "Kc = 273.8002884035305\n", - "HOX+O=CCC(=O)[Pt]<=>CH2O2X+C=C=O.[Pt]\n", - "kf = 6.284377773759944e-35\n", - "krev = 2.1623088290446475e12\n", - "Kc = 2.90632757418676e-47\n", - "CHOX+O=CCC(=O)[Pt]<=>C=C=O.[Pt]+O=CC=O.[Pt]\n", - "kf = 3.3416169046706564e-11\n", - "krev = 3.110510590664853e12\n", - "Kc = 1.0742985137872191e-23\n", - "vacantX+OCC#[Pt]<=>CX+OC[Pt]\n", - "kf = 1.0231284428350907e-6\n", - "krev = 5.347289159896318e-14\n", - "Kc = 1.9133591100858454e7\n", - "CX+OCO[Pt]<=>OX+OCC#[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 3.0624966294759025e-24\n", - "Kc = 8.467340919226885e15\n", - "CX+O=C([Pt])CO<=>OCX+OCC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.7351745231274126e-16\n", - "Kc = 1.4407772628508256e26\n", - "vacantX+OC(O)C#[Pt]<=>CX+OC(O)[Pt]\n", - "kf = 2.2665619116480148e-11\n", - "krev = 0.03466826587817799\n", - "Kc = 6.537857761944495e-10\n", - "vacantX+OCOC#[Pt]<=>CX+OCO[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.127497746946197e-18\n", - "Kc = 7.993610874511712e27\n", - "vacantX+O=CCOC#[Pt]<=>CX+O=CCO[Pt]\n", - "kf = 23528.318259479824\n", - "krev = 3.804584505072925e-13\n", - "Kc = 6.184201777646898e16\n", - "vacantX+C=C=O.[Pt]<=>HX+O=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.241214001168533e-20\n", - "Kc = 4.0056309550224184e29\n", - "CHO2X+O=C=C[Pt]<=>CO2X+C=C=O.[Pt]\n", - "kf = 3.709849833927781e-21\n", - "krev = 2.4389911159903437e17\n", - "Kc = 1.5210591828750508e-38\n", - "CO2HX+O=C=C[Pt]<=>CO2X+C=C=O.[Pt]\n", - "kf = 609.0850331655664\n", - "krev = 1.809911455986725e-11\n", - "Kc = 3.3652753075343477e13\n", - "CH2O2X+O=C=C[Pt]<=>CHO2X+C=C=O.[Pt]\n", - "kf = 1.5510087911871897e-15\n", - "krev = 9.749013808701775e13\n", - "Kc = 1.5909391674086975e-29\n", - "CH2O2X+O=C=C[Pt]<=>CO2HX+C=C=O.[Pt]\n", - "kf = 3.3619651735570975e7\n", - "krev = 2.294747094683907e-27\n", - "Kc = 1.465070020720604e34\n", - "OCX+C=C=O.[Pt]<=>CHOX+O=C=C[Pt]\n", - "kf = 4.040764431615523e-20\n", - "krev = 30.812673220085827\n", - "Kc = 1.3113969056672023e-21\n", - "OX+C=C=O.[Pt]<=>HOX+O=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.2732947353179126e-30\n", - "Kc = 3.985146729875919e39\n", - "OCO[Pt]+O=C=C[Pt]<=>CH2O2X+C=C=O.[Pt]\n", - "kf = 7.803274248124281e-6\n", - "krev = 4.005137429327759e-12\n", - "Kc = 1.9483162277989595e6\n", - "OC(O)[Pt]+O=C=C[Pt]<=>CH2O2X+C=C=O.[Pt]\n", - "kf = 8.032715739528718e-6\n", - "krev = 4.997427676480693e14\n", - "Kc = 1.6073700830795308e-20\n", - "CH2OX+O=C=C[Pt]<=>CHOX+C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.4680026972653605e-34\n", - "Kc = 3.347615287974457e43\n", - "CO[Pt]+O=C=C[Pt]<=>CH2OX+C=C=O.[Pt]\n", - "kf = 1.0212279299691738e-21\n", - "krev = 4.839386960246169e15\n", - "Kc = 2.1102423475497943e-37\n", - "OC[Pt]+O=C=C[Pt]<=>CH2OX+C=C=O.[Pt]\n", - "kf = 1.958692755771878e8\n", - "krev = 1.5396661662617642e-23\n", - "Kc = 1.272154184258975e31\n", - "HOX+C=C=O.[Pt]<=>H2OX+O=C=C[Pt]\n", - "kf = 7.529508093382038e8\n", - "krev = 1.2471462888159226e-34\n", - "Kc = 6.037389647794065e42\n", - "OC=[Pt]+C=C=O.[Pt]<=>OC[Pt]+O=C=C[Pt]\n", - "kf = 3.941830019983858e7\n", - "krev = 2.1489363690309378e11\n", - "Kc = 0.0001834316770282698\n", - "O=C=C[Pt]+O=CC=O.[Pt]<=>O=CC(=O)[Pt]+C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.4788881606878414e-49\n", - "Kc = 7.186203995433136e58\n", - "OC#[Pt]+C=C=O.[Pt]<=>OC=[Pt]+O=C=C[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 80798.59947863563\n", - "Kc = 4.901904683810505e-13\n", - "O=C=C[Pt]+O=CCO[Pt]<=>C=C=O.[Pt]+O=CC=O.[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 2.019947796444839e-5\n", - "Kc = 0.0012837560986177624\n", - "CX+C=C=O.[Pt]<=>CHX+O=C=C[Pt]\n", - "kf = 4.688885919704075e6\n", - "krev = 0.21465318980713355\n", - "Kc = 2.1844007647485003e7\n", - "CHX+C=C=O.[Pt]<=>CH2X+O=C=C[Pt]\n", - "kf = 7.342900678318069e-26\n", - "krev = 740.7927312780465\n", - "Kc = 9.912220204496055e-29\n", - "OO[Pt]+O=C=C[Pt]<=>O=O.[Pt]+C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.741682594755e-37\n", - "Kc = 5.272390021983691e46\n", - "OC(O)=[Pt]+C=C=O.[Pt]<=>OC(O)[Pt]+O=C=C[Pt]\n", - "kf = 1.714178070740009e-17\n", - "krev = 1.2983121019578911e14\n", - "Kc = 1.3203127877765141e-31\n", - "O=C=C[Pt]+O=CC(=O)[Pt]<=>O=C=C=O.[Pt]+C=C=O.[Pt]\n", - "kf = 1.3144481008935517e-8\n", - "krev = 1.352598964325052e-13\n", - "Kc = 97179.44014170248\n", - "O=C=C[Pt]+CC(=O)[Pt]<=>C=C=O.[Pt]+C=C=O.[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 5.183135272095574e-24\n", - "Kc = 5.002995612590211e15\n", - "vacantX+COC#[Pt]<=>CX+CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.9367034031976796e-16\n", - "Kc = 8.512946854891207e25\n", - "CX+COC(=O)[Pt]<=>OCX+COC#[Pt]\n", - "kf = 6.269624738894468e-15\n", - "krev = 24.522149705338403\n", - "Kc = 2.556719053684591e-16\n", - "vacantX+O=CC(=O)C#[Pt]<=>CX+O=CC(=O)[Pt]\n", - "kf = 5.451669985706379\n", - "krev = 9.628263387104526e-16\n", - "Kc = 5.662152941316492e15\n", - "CX+O=CC=O.[Pt]<=>HX+O=CC(=O)C#[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.785247265622252e-8\n", - "Kc = 1.4003662395352387e18\n", - "vacantX+O=COC[Pt]<=>HX+O=COC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.9015186281967622e-32\n", - "Kc = 1.3147386320221257e42\n", - "CH2O2X+O=COC=[Pt]<=>CHO2X+O=COC[Pt]\n", - "kf = 1.7650043109029407e-12\n", - "krev = 1.4735149295451475e13\n", - "Kc = 1.1978190892492496e-25\n", - "CH2O2X+O=COC=[Pt]<=>CO2HX+O=COC[Pt]\n", - "kf = 10.947009513309483\n", - "krev = 5.112987413682155e11\n", - "Kc = 2.1410202348661592e-11\n", - "CHOX+O=COC=[Pt]<=>OCX+O=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.3281787530995323e-14\n", - "Kc = 1.0738007108224487e24\n", - "HOX+O=COC=[Pt]<=>OX+O=COC[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 165389.8266532618\n", - "Kc = 1.951879075907524\n", - "CH2OX+O=COC=[Pt]<=>CHOX+O=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.715637531959152e-22\n", - "Kc = 1.4571842556656794e32\n", - "H2OX+O=COC=[Pt]<=>HOX+O=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.130905447828635e-25\n", - "Kc = 1.1732101968895276e35\n", - "[H][H].[Pt]+O=COC=[Pt]<=>HX+O=COC[Pt]\n", - "kf = 1.3759337537057946e9\n", - "krev = 2.6326332155148577e-19\n", - "Kc = 5.226454431999965e27\n", - "OC[Pt]+O=COC=[Pt]<=>OC=[Pt]+O=COC[Pt]\n", - "kf = 1.2771337705277995e-31\n", - "krev = 6.599290845791489e16\n", - "Kc = 1.935259106426951e-48\n", - "O=CC=O.[Pt]+O=COC=[Pt]<=>O=CC(=O)[Pt]+O=COC[Pt]\n", - "kf = 1.1728434846364774e-18\n", - "krev = 2.6840450809869076e16\n", - "Kc = 4.3696862356918e-35\n", - "OC=[Pt]+O=COC=[Pt]<=>OC#[Pt]+O=COC[Pt]\n", - "kf = 32.04286700116282\n", - "krev = 1.9859440346373588e-10\n", - "Kc = 1.61348287979394e11\n", - "CHX+O=COC=[Pt]<=>CX+O=COC[Pt]\n", - "kf = 5.2796000958546504e-37\n", - "krev = 1.4614931014553018e17\n", - "Kc = 3.612470076387919e-54\n", - "vacantX+O=COC=[Pt]<=>CHX+CHO2X\n", - "kf = 180747.02922982755\n", - "krev = 2.4491522098934374e-37\n", - "Kc = 7.379983510199714e41\n", - "CHX+CH2O2X<=>HX+O=COC=[Pt]\n", - "kf = 0.0015322757193851075\n", - "krev = 1.9084257758101816e14\n", - "Kc = 8.029003479239911e-18\n", - "CH2X+O=COC=[Pt]<=>CHX+O=COC[Pt]\n", - "kf = 0.014873013888318402\n", - "krev = 6.520037160662236e15\n", - "Kc = 2.2811240981957472e-18\n", - "CH2X+O=COC=[Pt]<=>CHX+O=COC[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.9529365102554657e-31\n", - "Kc = 9.99708792916859e22\n", - "CH2O2X+O=COC#[Pt]<=>CHO2X+O=COC=[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.4091973858076736e-32\n", - "Kc = 1.225336127134283e24\n", - "CH2O2X+O=COC#[Pt]<=>CO2HX+O=COC=[Pt]\n", - "kf = 0.8504584217531632\n", - "krev = 1.347597642765549e15\n", - "Kc = 6.310922450174717e-16\n", - "CHOX+O=COC#[Pt]<=>OCX+O=COC=[Pt]\n", - "kf = 1.0224949765277231e10\n", - "krev = 9.139651486927123e-14\n", - "Kc = 1.1187461337997911e23\n", - "CH2OX+O=COC#[Pt]<=>CHOX+O=COC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.6210077020119595e-21\n", - "Kc = 9.538316114374366e30\n", - "HOX+O=COC#[Pt]<=>OX+O=COC=[Pt]\n", - "kf = 0.0008567749561878586\n", - "krev = 1.2359860589695025e13\n", - "Kc = 6.931914401220598e-17\n", - "vacantX+O=COC=[Pt]<=>HX+O=COC#[Pt]\n", - "kf = 2.2773385768535307e-19\n", - "krev = 181.8091471864856\n", - "Kc = 1.2525984594810374e-21\n", - "OC[Pt]+O=COC#[Pt]<=>OC=[Pt]+O=COC=[Pt]\n", - "kf = 4.9314791816760385e8\n", - "krev = 1.5573633218480681e-21\n", - "Kc = 3.1665566489802946e29\n", - "OC(O)=[Pt]+O=COC=[Pt]<=>OC(O)[Pt]+O=COC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.95438690090272e-19\n", - "Kc = 2.511455526983069e28\n", - "H2OX+O=COC#[Pt]<=>HOX+O=COC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.5919612012855e-33\n", - "Kc = 6.95998609090013e42\n", - "OC=[Pt]+O=COC#[Pt]<=>OC#[Pt]+O=COC=[Pt]\n", - "kf = 412885.969273148\n", - "krev = 2.625517699834265\n", - "Kc = 157258.8786200951\n", - "O=COC#[Pt]+O=CC=O.[Pt]<=>O=CC(=O)[Pt]+O=COC=[Pt]\n", - "kf = 4.870524122777267e9\n", - "krev = 1.4627043997234466e-16\n", - "Kc = 3.3298075289157106e25\n", - "[H][H].[Pt]+O=COC#[Pt]<=>HX+O=COC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.8597141571613083e-17\n", - "Kc = 8.742132474112804e26\n", - "O=COC=[Pt]+O=COC=[Pt]<=>O=COC#[Pt]+O=COC[Pt]\n", - "kf = 6.186864182993887e-31\n", - "krev = 2.034915252803989e19\n", - "Kc = 3.04035471475717e-50\n", - "CX+O=COC=[Pt]<=>CHX+O=COC#[Pt]\n", - "kf = 5.619880038277716e-8\n", - "krev = 4.919193785592355e16\n", - "Kc = 1.14243924578405e-24\n", - "CX+O=COC=[Pt]<=>CHX+O=COC#[Pt]\n", - "kf = 1.6866972609475142e-22\n", - "krev = 6.547125244410207e13\n", - "Kc = 2.576241018739606e-36\n", - "CH2X+O=COC#[Pt]<=>CHX+O=COC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.405314737692951e-28\n", - "Kc = 2.974308610704312e37\n", - "OC(O)[Pt]+O=COC=[Pt]<=>OC(O)=[Pt]+O=COC[Pt]\n", - "kf = 365995.57053717994\n", - "krev = 187509.1639624155\n", - "Kc = 1.9518809790573244\n", - "O=COC#[Pt]+C=C=O.[Pt]<=>O=C=C[Pt]+O=COC=[Pt]\n", - "kf = 6.536709868845801e-7\n", - "krev = 3.607475609111285e-11\n", - "Kc = 18119.90038778431\n", - "C=C=O.[Pt]+O=COC=[Pt]<=>O=C=C[Pt]+O=COC[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.348252838458729e-29\n", - "Kc = 4.5553052781738184e20\n", - "CX+O=COC=[Pt]<=>CHX+O=COC#[Pt]\n", - "kf = 1.1112170024966995e-23\n", - "krev = 36323.66987445037\n", - "Kc = 3.0592090676342045e-28\n", - "CX+O=COC=[Pt]<=>CHX+O=COC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.839307771146613e-42\n", - "Kc = 6.511590497610387e51\n", - "CH2X+O=COC=[Pt]<=>CHX+O=COC[Pt]\n", - "kf = 0.004371453552681894\n", - "krev = 1.2572855491392857e13\n", - "Kc = 3.476897953431907e-16\n", - "CH2X+O=COC=[Pt]<=>CHX+O=COC[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.3635197599529065e-33\n", - "Kc = 1.9017841755847633e25\n", - "CX+C=C=O.[Pt]<=>HX+O=C=CC#[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 6.797711819853139e-22\n", - "Kc = 3.814695843684052e13\n", - "vacantX+O=C=CC#[Pt]<=>CX+O=C=C[Pt]\n", - "kf = 16.31407647715237\n", - "krev = 4.543665668210859e-11\n", - "Kc = 3.5905098808857336e11\n", - "CX+CO[Pt]<=>OX+CC#[Pt]\n", - "kf = 6.42025766569729e6\n", - "krev = 5.830346192866458e-31\n", - "Kc = 1.1011794931753108e37\n", - "CX+CC(=O)[Pt]<=>OCX+CC#[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.301177455844525e-32\n", - "Kc = 1.2828548214436644e24\n", - "CHO2X+O=C=CO[Pt]<=>CH2O2X+O=C=C=O.[Pt]\n", - "kf = 4.581183222917958e-20\n", - "krev = 34.93361388628861\n", - "Kc = 1.3113968791863429e-21\n", - "CO2HX+O=C=CO[Pt]<=>CH2O2X+O=C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.799869928114263e-28\n", - "Kc = 2.8409510827118884e37\n", - "CHOX+O=C=CO[Pt]<=>CH2OX+O=C=C=O.[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.951682102619952e-64\n", - "Kc = 1.9647454732667077e56\n", - "HOX+O=C=CO[Pt]<=>H2OX+O=C=C=O.[Pt]\n", - "kf = 0.00024916353007790583\n", - "krev = 2.3097496644853503e-11\n", - "Kc = 1.0787469045197308e7\n", - "O=C=CO[Pt]+O=CC(=O)[Pt]<=>O=C=C=O.[Pt]+O=CC=O.[Pt]\n", - "kf = 36.21750369826068\n", - "krev = 0.32335117013731834\n", - "Kc = 112.00671914340097\n", - "OX+C=C=O.[Pt]<=>HX+O=C=CO[Pt]\n", - "kf = 1.7018617233469498e-12\n", - "krev = 4.164837143763027e13\n", - "Kc = 4.086262354568991e-26\n", - "O=C=C[Pt]+O=C=CO[Pt]<=>O=C=C=O.[Pt]+C=C=O.[Pt]\n", - "kf = 6.071347272542775e-23\n", - "krev = 1180.067101472276\n", - "Kc = 5.144916983930861e-26\n", - "vacantX+O=C=CO[Pt]<=>OX+O=C=C[Pt]\n", - "kf = 0.3274906030624493\n", - "krev = 2.9425898600264806e14\n", - "Kc = 1.1129332276687114e-15\n", - "CX+O=C=CO[Pt]<=>OX+O=C=CC#[Pt]\n", - "kf = 0.2513917911405871\n", - "krev = 1.0405847657707406e16\n", - "Kc = 2.4158703779829617e-17\n", - "vacantX+COC(=O)C#[Pt]<=>CX+COC(=O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.636533990647995e-42\n", - "Kc = 2.8946797438730698e51\n", - "OCX+C=C=O.[Pt]<=>HX+O=C=CC(=O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.121676848269518e-7\n", - "Kc = 2.228805920222842e17\n", - "vacantX+O=C=CC(=O)[Pt]<=>OCX+O=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.016303466992672e-34\n", - "Kc = 4.155375495461265e43\n", - "CX+O=C=CC(=O)[Pt]<=>OCX+O=C=CC#[Pt]\n", - "kf = 1.4084647229282898e-13\n", - "krev = 5.945859073264746e-8\n", - "Kc = 2.3688161888353193e-6\n", - "OX+O=C=CC(=O)[Pt]<=>OCX+O=C=CO[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 181176.05501028927\n", - "Kc = 1.9518809818483447\n", - "CX+O=CCO[Pt]<=>OX+O=CCC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4592826402667932e-32\n", - "Kc = 1.7131705202379013e42\n", - "CX+O=CCC(=O)[Pt]<=>OCX+O=CCC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.0528218624629457e-34\n", - "Kc = 1.2178358218576924e44\n", - "HX+CH2X<=>vacantX+CH3X\n", - "kf = 9.194493638543996e8\n", - "krev = 1.3639804620724132e-13\n", - "Kc = 6.74092767030842e21\n", - "vacantX+CO[Pt]<=>OX+CH3X\n", - "kf = 3.052485738368744e-11\n", - "krev = 0.0007099643372969683\n", - "Kc = 4.29949164769375e-8\n", - "CH2X+CH2O2X<=>CHO2X+CH3X\n", - "kf = 2.952076594227614e-8\n", - "krev = 5.604440911093213e-48\n", - "Kc = 5.267388203494818e39\n", - "CH2X+CH2O2X<=>CO2HX+CH3X\n", - "kf = 2.5931203025755725e-8\n", - "krev = 5.6159867257682645e-34\n", - "Kc = 4.61739037002591e25\n", - "CHOX+CH2X<=>OCX+CH3X\n", - "kf = 2.4999999999999992e10\n", - "krev = 3.181951939141392e-26\n", - "Kc = 7.856812572331283e35\n", - "CH2X+CH2OX<=>CHOX+CH3X\n", - "kf = 4.75028668267054e-8\n", - "krev = 4.308357958526409e-11\n", - "Kc = 1102.5747462022132\n", - "HOX+CH2X<=>OX+CH3X\n", - "kf = 4.135805741920728e-10\n", - "krev = 0.028732529553568358\n", - "Kc = 1.4394158141245496e-8\n", - "CH2X+OC[Pt]<=>OC=[Pt]+CH3X\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.272169613200064e-8\n", - "Kc = 0.46029640012283785\n", - "OC(O)=[Pt]+CH3X<=>CH2X+OC(O)[Pt]\n", - "kf = 0.4548020863581974\n", - "krev = 0.22303963782401687\n", - "Kc = 2.0391087915819077\n", - "H2OX+CH2X<=>HOX+CH3X\n", - "kf = 1.5839272910037507e-20\n", - "krev = 3600.161649580889\n", - "Kc = 4.399600476795654e-24\n", - "CH2X+OC=[Pt]<=>OC#[Pt]+CH3X\n", - "kf = 8.684971623379145e8\n", - "krev = 1.9668877403064286e-15\n", - "Kc = 4.415590908114604e23\n", - "CH2X+O=CC=O.[Pt]<=>CH3X+O=CC(=O)[Pt]\n", - "kf = 0.024290856013790354\n", - "krev = 3.5586883050271985e15\n", - "Kc = 6.825789148062155e-18\n", - "[H][H].[Pt]+CH2X<=>HX+CH3X\n", - "kf = 2.162232232095232e-5\n", - "krev = 5.66671683371172e13\n", - "Kc = 3.815670158833332e-19\n", - "CH3X+O=COC=[Pt]<=>CH2X+O=COC[Pt]\n", - "kf = 1.1089294417172325e9\n", - "krev = 2.3905126075631446e-16\n", - "Kc = 4.638877193990873e24\n", - "CX+CH3X<=>CHX+CH2X\n", - "kf = 3.5117597357119104e-15\n", - "krev = 0.7837038908782975\n", - "Kc = 4.480977798612533e-15\n", - "CH2X+CH2X<=>CHX+CH3X\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.08399332498323721\n", - "Kc = 7.789900440580834e-7\n", - "CH2X+C=C=O.[Pt]<=>CH3X+O=C=C[Pt]\n", - "kf = 4.6616085133202476e-21\n", - "krev = 1.7198034057689652e-11\n", - "Kc = 2.7105473205153534e-10\n", - "vacantX+CC(=O)[Pt]<=>OCX+CH3X\n", - "kf = 1.2257627381394946e-12\n", - "krev = 3.270257576074817e14\n", - "Kc = 3.748214657790771e-27\n", - "CH2X+O=COC=[Pt]<=>CH3X+O=COC#[Pt]\n", - "kf = 9.111664842232262e8\n", - "krev = 5.142811625352043e-10\n", - "Kc = 1.7717282891162747e18\n", - "vacantX+CC#[Pt]<=>CX+CH3X\n", - "kf = 2.5e10\n", - "krev = 9007.024893837408\n", - "Kc = 2.7756112917046514e6\n", - "vacantX+O=C=CO.[Pt]<=>OCX+OC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.493939353913987e-14\n", - "Kc = 7.155247263234393e23\n", - "CHO2X+O=C([Pt])CO<=>CH2O2X+O=C=CO.[Pt]\n", - "kf = 1.1829749543892744e-33\n", - "krev = 3.758913107590896e15\n", - "Kc = 3.1471197139415875e-49\n", - "CO2HX+O=C([Pt])CO<=>CH2O2X+O=C=CO.[Pt]\n", - "kf = 1.049990631922765e-6\n", - "krev = 1.7955210884029898e15\n", - "Kc = 5.847832357439309e-22\n", - "CHOX+O=C([Pt])CO<=>CH2OX+O=C=CO.[Pt]\n", - "kf = 0.0029164033711847528\n", - "krev = 3.4437539939134434e12\n", - "Kc = 8.468675103794464e-16\n", - "HOX+O=C([Pt])CO<=>H2OX+O=C=CO.[Pt]\n", - "kf = 1.7528367761452354e-6\n", - "krev = 1.1970864565480504e-5\n", - "Kc = 0.14642524494009906\n", - "O=CC(=O)[Pt]+O=C([Pt])CO<=>O=C=CO.[Pt]+O=CC=O.[Pt]\n", - "kf = 65.80946386077328\n", - "krev = 1217.699742052305\n", - "Kc = 0.054044081301896585\n", - "OCX+O=C=CO.[Pt]<=>CO2HX+O=C=C[Pt]\n", - "kf = 6.342176392543457e-21\n", - "krev = 776.2437464870187\n", - "Kc = 8.170341366672147e-24\n", - "CHOX+O=C=CO.[Pt]<=>CH2O2X+O=C=C[Pt]\n", - "kf = 4.672349699632388e-15\n", - "krev = 8.81363422062413e13\n", - "Kc = 5.301274800693419e-29\n", - "vacantX+O=C=CO.[Pt]<=>HOX+O=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.7537190144509203\n", - "Kc = 3.316885937687581e10\n", - "CH2X+O=C=CO.[Pt]<=>OC[Pt]+O=C=C[Pt]\n", - "kf = 586.9890181697751\n", - "krev = 3.5182371632669316e-15\n", - "Kc = 1.668417991539588e17\n", - "OC=[Pt]+O=C=CO.[Pt]<=>OC(O)[Pt]+O=C=C[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 450683.30306117237\n", - "Kc = 1.4517947189269602e-13\n", - "OCO[Pt]+O=C=C[Pt]<=>CH2OX+O=C=CO.[Pt]\n", - "kf = 7.548264554696059e-34\n", - "krev = 5.749061160710156e15\n", - "Kc = 1.3129560364189368e-49\n", - "CHX+O=C=CO.[Pt]<=>OC=[Pt]+O=C=C[Pt]\n", - "kf = 5.478042817438384\n", - "krev = 6.82639714107839e-51\n", - "Kc = 8.02479361253951e50\n", - "CX+O=C=CO.[Pt]<=>OC#[Pt]+O=C=C[Pt]\n", - "kf = 1.463392220587488e-22\n", - "krev = 7.968303762369095e13\n", - "Kc = 1.8365166090912173e-36\n", - "OX+O=C=CO.[Pt]<=>OO[Pt]+O=C=C[Pt]\n", - "kf = 192.6103918491207\n", - "krev = 4.515166477555994e-12\n", - "Kc = 4.265853602664468e13\n", - "OC#[Pt]+O=C=CO.[Pt]<=>OC(O)=[Pt]+O=C=C[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 3.1627439012977165e-12\n", - "Kc = 25911.109388377805\n", - "OOC[Pt]+O=C=C[Pt]<=>CH2OX+O=C=CO.[Pt]\n", - "kf = 2.1035625708276702e-15\n", - "krev = 1.0019023766861524e15\n", - "Kc = 2.099568400850909e-30\n", - "O=C=C[Pt]+O=C([Pt])CO<=>C=C=O.[Pt]+O=C=CO.[Pt]\n", - "kf = 0.08561452397466171\n", - "krev = 3.215769317238553e17\n", - "Kc = 2.6623341268826044e-19\n", - "O=C=C[Pt]+O=C([Pt])CO<=>C=C=O.[Pt]+O=C=CO.[Pt]\n", - "kf = 1.262172875849309e-6\n", - "krev = 1.5596341944506717e13\n", - "Kc = 8.092749443044025e-20\n", - "CX+O=C=CO.[Pt]<=>HOX+O=C=CC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.036795069902944e-35\n", - "Kc = 8.232363206780035e44\n", - "CHO2X+O=C=CO[Pt]<=>CO2X+O=C=CO.[Pt]\n", - "kf = 8.697106954471648e-14\n", - "krev = 5.359609736165605e16\n", - "Kc = 1.6227127314485718e-30\n", - "CO2HX+O=C=CO[Pt]<=>CO2X+O=C=CO.[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 1.1323573491720412e-8\n", - "Kc = 4.415567226773338e18\n", - "CHO2X+O=C=CO.[Pt]<=>CH2O2X+O=C=CO[Pt]\n", - "kf = 0.0004422945453165714\n", - "krev = 9.363325052982716e15\n", - "Kc = 4.723691026572629e-20\n", - "CO2HX+O=C=CO.[Pt]<=>CH2O2X+O=C=CO[Pt]\n", - "kf = 9.477814531468979e-7\n", - "krev = 7.52142668687151e15\n", - "Kc = 1.2601086105129898e-22\n", - "OCX+O=C=CO.[Pt]<=>CHOX+O=C=CO[Pt]\n", - "kf = 4.839333835070635e-9\n", - "krev = 3.439572341169614e-8\n", - "Kc = 0.14069580038037627\n", - "CHOX+O=C=CO.[Pt]<=>CH2OX+O=C=CO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.1808191230067762e-17\n", - "Kc = 3.354171909251678e9\n", - "OX+O=C=CO.[Pt]<=>HOX+O=C=CO[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 2.639709061724686e-6\n", - "Kc = 0.012387213631168494\n", - "OX+O=C=CO.[Pt]<=>HOX+O=C=CO[Pt]\n", - "kf = 5.372480262216755e-24\n", - "krev = 2113.809062877283\n", - "Kc = 2.5416109508508876e-27\n", - "vacantX+O=C=CO.[Pt]<=>HX+O=C=CO[Pt]\n", - "kf = 4.80530366959931e-5\n", - "krev = 5.681813674074216e13\n", - "Kc = 8.457341168235823e-19\n", - "CO[Pt]+O=C=CO[Pt]<=>CH2OX+O=C=CO.[Pt]\n", - "kf = 3.028654941635431e8\n", - "krev = 1.2132864881112858e-12\n", - "Kc = 2.496240559268171e20\n", - "OC[Pt]+O=C=CO[Pt]<=>CH2OX+O=C=CO.[Pt]\n", - "kf = 3.2683771317360777e8\n", - "krev = 0.21738478314597703\n", - "Kc = 1.5034985818401628e9\n", - "OC=[Pt]+O=C=CO.[Pt]<=>OC[Pt]+O=C=CO[Pt]\n", - "kf = 1.9694718683312347e9\n", - "krev = 1.5816714472418169e-18\n", - "Kc = 1.245183929801401e27\n", - "OC(O)[Pt]+O=C=CO[Pt]<=>CH2O2X+O=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.6333074127753494e-17\n", - "Kc = 6.880783033138235e26\n", - "OC(O)=[Pt]+O=C=CO.[Pt]<=>OC(O)[Pt]+O=C=CO[Pt]\n", - "kf = 2.5742212027881315e-15\n", - "krev = 0.39729482671494754\n", - "Kc = 6.479372570927264e-15\n", - "OCO[Pt]+O=C=CO[Pt]<=>CH2O2X+O=C=CO.[Pt]\n", - "kf = 3.860701485876577e-7\n", - "krev = 0.0037771400241392917\n", - "Kc = 0.00010221229451921966\n", - "HOX+O=C=CO.[Pt]<=>H2OX+O=C=CO[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.9339597186194493e-34\n", - "Kc = 1.7308289628845924e26\n", - "OC#[Pt]+O=C=CO.[Pt]<=>OC=[Pt]+O=C=CO[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 2.728234417234893e-33\n", - "Kc = 1.0624138213938816e25\n", - "O=C=CO[Pt]+O=CC(=O)[Pt]<=>O=C=C=O.[Pt]+O=C=CO.[Pt]\n", - "kf = 4.304987235328105e9\n", - "krev = 7.891318764743676e-17\n", - "Kc = 5.45534575863498e25\n", - "O=CC(=O)[Pt]+O=C=CO.[Pt]<=>O=C=CO[Pt]+O=CC=O.[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.406329298480467e-31\n", - "Kc = 1.038926800907375e41\n", - "O=C=CO.[Pt]+O=COC=[Pt]<=>O=C=CO[Pt]+O=COC[Pt]\n", - "kf = 1.3037608552158366e-12\n", - "krev = 0.18236199715464047\n", - "Kc = 7.149301255514685e-12\n", - "OO[Pt]+O=C=CO[Pt]<=>O=O.[Pt]+O=C=CO.[Pt]\n", - "kf = 3.506980389191063e-59\n", - "krev = 1.6121784785918364e12\n", - "Kc = 2.1753053001019147e-71\n", - "CX+O=C=CO.[Pt]<=>CHX+O=C=CO[Pt]\n", - "kf = 2.1281066335723717e-20\n", - "krev = 4.7998990065431355e-20\n", - "Kc = 0.4433648771924941\n", - "CHX+O=C=CO.[Pt]<=>CH2X+O=C=CO[Pt]\n", - "kf = 7.2938132405514685e-6\n", - "krev = 2.191544710090903e-13\n", - "Kc = 3.3281608205241356e7\n", - "O=C=CO[Pt]+O=CCO[Pt]<=>O=C=CO.[Pt]+O=CC=O.[Pt]\n", - "kf = 3.860701485876577e-7\n", - "krev = 2.2515045234693432e-8\n", - "Kc = 17.147207325738\n", - "O=C=C[Pt]+O=C=CO.[Pt]<=>O=C=CO[Pt]+C=C=O.[Pt]\n", - "kf = 3.6700973989487563e-44\n", - "krev = 3.0504263460080312e13\n", - "Kc = 1.203142440646588e-57\n", - "O=C=CO[Pt]+CC(=O)[Pt]<=>C=C=O.[Pt]+O=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.82558147454442e-8\n", - "Kc = 2.5443786777167984e17\n", - "O=C=CO[Pt]+O=C([Pt])CO<=>O=C=CO.[Pt]+O=C=CO.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 165389.73964983693\n", - "Kc = 1.9518801026953096\n", - "O=COC#[Pt]+O=C=CO.[Pt]<=>O=C=CO[Pt]+O=COC=[Pt]\n", - "kf = 3.7259548765787992e9\n", - "krev = 3.6992581168771994e-31\n", - "Kc = 1.0072167874903892e40\n", - "O=C=CO[Pt]+O=C=CO[Pt]<=>O=C=C=O.[Pt]+O=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.043799531501529e-45\n", - "Kc = 8.21341870292861e54\n", - "OCX+O=C=CO.[Pt]<=>HOX+O=C=CC(=O)[Pt]\n", - "kf = 5.776653727817663e-40\n", - "krev = 0.19860841474496846\n", - "Kc = 2.9085644408548448e-39\n", - "CH2X+O=C=CO.[Pt]<=>CH3X+O=C=CO[Pt]\n", - "kf = 3.3256293066300124e-48\n", - "krev = 2.638642223210571e15\n", - "Kc = 1.2603562837645906e-63\n", - "OX+O=C=CO.[Pt]<=>HOX+O=C=CO[Pt]\n", - "kf = 1.4930923415267688e-9\n", - "krev = 1.1121057711212152e14\n", - "Kc = 1.3425812366942817e-23\n", - "OX+O=C=CO.[Pt]<=>HOX+O=C=CO[Pt]\n", - "kf = 469882.2241291155\n", - "krev = 15.560302693769444\n", - "Kc = 30197.498941795184\n", - "O=C=C[Pt]+O=C([Pt])CO<=>C=C=O.[Pt]+O=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.920455993640651e-33\n", - "Kc = 6.376809238658043e42\n", - "O=C=C[Pt]+O=C([Pt])CO<=>C=C=O.[Pt]+O=C=CO.[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 9.545218685674386e-14\n", - "Kc = 414937.62088874576\n", - "vacantX+O=C=C=O.[Pt]<=>OX+O=C=C=[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 0.02522938529859348\n", - "Kc = 1.1100614687459063e-6\n", - "vacantX+O=C=C[Pt]<=>HX+O=C=C=[Pt]\n", - "kf = 1.0488506310161173e-19\n", - "krev = 521.1543106644776\n", - "Kc = 2.0125529225284944e-22\n", - "CH2O2X+O=C=C=[Pt]<=>CHO2X+O=C=C[Pt]\n", - "kf = 11433.101373849615\n", - "krev = 0.22138456904438245\n", - "Kc = 51643.62368705808\n", - "CH2O2X+O=C=C=[Pt]<=>CO2HX+O=C=C[Pt]\n", - "kf = 660785.6964241413\n", - "krev = 2.737556590691246e-13\n", - "Kc = 2.413779129429028e18\n", - "CHOX+O=C=C=[Pt]<=>OCX+O=C=C[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.680149232421768e-23\n", - "Kc = 1.9922953446306685e15\n", - "HOX+O=C=C=[Pt]<=>OX+O=C=C[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 2.661991446097411e-38\n", - "Kc = 9.604054388173769e29\n", - "CH2OX+O=C=C=[Pt]<=>CHOX+O=C=C[Pt]\n", - "kf = 1.133196546666376e10\n", - "krev = 9.97059352398989e-15\n", - "Kc = 1.1365387064870632e24\n", - "H2OX+O=C=C=[Pt]<=>HOX+O=C=C[Pt]\n", - "kf = 2.290241001822749e-10\n", - "krev = 0.0004872161822843353\n", - "Kc = 4.7006669423105973e-7\n", - "[H][H].[Pt]+O=C=C=[Pt]<=>HX+O=C=C[Pt]\n", - "kf = 4.25143681327651e-15\n", - "krev = 1.001308193612447e-19\n", - "Kc = 42458.82377071624\n", - "OC=[Pt]+O=C=C[Pt]<=>OC[Pt]+O=C=C=[Pt]\n", - "kf = 185.93529229739633\n", - "krev = 1.904541046621029e-10\n", - "Kc = 9.762734839833265e11\n", - "O=C=C=[Pt]+O=CC=O.[Pt]<=>O=C=C[Pt]+O=CC(=O)[Pt]\n", - "kf = 35.92356832171279\n", - "krev = 1.3784436111735967e-12\n", - "Kc = 2.6060963270835383e13\n", - "OC#[Pt]+O=C=C[Pt]<=>OC=[Pt]+O=C=C=[Pt]\n", - "kf = 8.90444501639475e-13\n", - "krev = 8.409201083164982e12\n", - "Kc = 1.0588931015362724e-25\n", - "CX+O=C=C[Pt]<=>CHX+O=C=C=[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 8.422687202008296e-11\n", - "Kc = 470.23832623775377\n", - "CH2X+O=C=C=[Pt]<=>CHX+O=C=C[Pt]\n", - "kf = 2.786306429788959e-20\n", - "krev = 52.25975865319748\n", - "Kc = 5.3316481009398625e-22\n", - "CH2X+O=C=C[Pt]<=>CH3X+O=C=C=[Pt]\n", - "kf = 1.4060776479118306e6\n", - "krev = 6.613786245273692e13\n", - "Kc = 2.1259798786461146e-8\n", - "O=C=C[Pt]+O=COC#[Pt]<=>O=C=C=[Pt]+O=COC=[Pt]\n", - "kf = 1.5975335437882445e-34\n", - "krev = 2.2957840869759923e8\n", - "Kc = 6.958553083676594e-43\n", - "OC(O)=[Pt]+O=C=C[Pt]<=>OC(O)[Pt]+O=C=C=[Pt]\n", - "kf = 9.363402027600756e-56\n", - "krev = 7.047835211144391e9\n", - "Kc = 1.328550079149818e-65\n", - "O=C=C=[Pt]+C=C=O.[Pt]<=>O=C=C[Pt]+O=C=C[Pt]\n", - "kf = 1.1797200153280936e-59\n", - "krev = 4.3408253155831816e16\n", - "Kc = 2.7177320660497494e-76\n", - "O=C=C[Pt]+O=COC=[Pt]<=>O=C=C=[Pt]+O=COC[Pt]\n", - "kf = 6.2161685505804725e7\n", - "krev = 4.785686680273161e-40\n", - "Kc = 1.298908383660767e47\n", - "O=C=C=[Pt]+O=C=CO.[Pt]<=>O=C=C[Pt]+O=C=CO[Pt]\n", - "kf = 1.5305016921747763e9\n", - "krev = 0.1627608300478634\n", - "Kc = 9.403378513888744e9\n", - "vacantX+CC(=O)C#[Pt]<=>CX+CC(=O)[Pt]\n", - "kf = 2.7777170398864307e-21\n", - "krev = 2.5089215324603047e13\n", - "Kc = 1.107135876490541e-34\n", - "vacantX+O=C(C#[Pt])CO<=>CX+O=C([Pt])CO\n", - "kf = 2.5e10\n", - "krev = 4.755986506689556e-57\n", - "Kc = 5.256532995801423e66\n", - "CHO2X+CO[Pt]<=>OX+COC=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 1179.0380002145982\n", - "Kc = 273.8002862958761\n", - "CHO2X+CO[Pt]<=>OX+COC=O.[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 3.7340035459822127e-34\n", - "Kc = 6.695226636005739e43\n", - "HOX+COC=O.[Pt]<=>CH2O2X+CO[Pt]\n", - "kf = 4.78083312177258e-41\n", - "krev = 4.774618642094983e15\n", - "Kc = 1.0013015656628172e-56\n", - "vacantX+COC=O.[Pt]<=>CHOX+CO[Pt]\n", - "kf = 0.006471827705681551\n", - "krev = 4.258755653145197e-10\n", - "Kc = 1.5196522723490711e7\n", - "OCX+COC=O.[Pt]<=>CO[Pt]+O=CC(=O)[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.852140732586457e13\n", - "Kc = 2.1384283940268284e-21\n", - "CO[Pt]+O=CC=O.[Pt]<=>CHOX+COC=O.[Pt]\n", - "kf = 3.256466928453685e-21\n", - "krev = 26.50445975246776\n", - "Kc = 1.2286486722863626e-22\n", - "CHO2X+O=COC[Pt]<=>CO2X+COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.877454242443708e-31\n", - "Kc = 4.253542259753193e40\n", - "CO2HX+O=COC[Pt]<=>CO2X+COC=O.[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 3.1615249923835833e-35\n", - "Kc = 1.8343375629216876e27\n", - "CH2O2X+O=COC[Pt]<=>CHO2X+COC=O.[Pt]\n", - "kf = 4.069225267716308e7\n", - "krev = 5.753482545458429e-41\n", - "Kc = 7.072629899483041e47\n", - "CH2O2X+O=COC[Pt]<=>CO2HX+COC=O.[Pt]\n", - "kf = 2.779636780044878e-20\n", - "krev = 3.601218910546807\n", - "Kc = 7.718599866018197e-21\n", - "OCX+COC=O.[Pt]<=>CHOX+O=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.6923262566046736e-29\n", - "Kc = 6.770799290902607e38\n", - "CH2OX+O=COC[Pt]<=>CHOX+COC=O.[Pt]\n", - "kf = 2.937512138355157e-45\n", - "krev = 8.778136400287878e10\n", - "Kc = 3.34639609639561e-56\n", - "OX+COC=O.[Pt]<=>HOX+O=COC[Pt]\n", - "kf = 2.72779390176573e9\n", - "krev = 7.780637869692039e-32\n", - "Kc = 3.505874386457851e40\n", - "vacantX+COC=O.[Pt]<=>HX+O=COC[Pt]\n", - "kf = 1.8192290523055587e7\n", - "krev = 0.1716042050140899\n", - "Kc = 1.0601308121535759e8\n", - "CO[Pt]+O=COC[Pt]<=>CH2OX+COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0274874875606104e-56\n", - "Kc = 2.433119653783159e66\n", - "CO[Pt]+O=COC[Pt]<=>CH2OX+COC=O.[Pt]\n", - "kf = 21946.411665990272\n", - "krev = 2.5837051406163863e-64\n", - "Kc = 8.494162635274467e67\n", - "OC[Pt]+O=COC[Pt]<=>CH2OX+COC=O.[Pt]\n", - "kf = 1.893449523720139e-21\n", - "krev = 0.6694879211592951\n", - "Kc = 2.8282056537202555e-21\n", - "OC=[Pt]+COC=O.[Pt]<=>OC[Pt]+O=COC[Pt]\n", - "kf = 4.5276782379965965e-7\n", - "krev = 1.4949208469184493e-38\n", - "Kc = 3.0287076719344122e31\n", - "OC(O)[Pt]+O=COC[Pt]<=>CH2O2X+COC=O.[Pt]\n", - "kf = 4.72289540105198e-39\n", - "krev = 9.498795808374404e14\n", - "Kc = 4.9720990916429044e-54\n", - "OC(O)=[Pt]+COC=O.[Pt]<=>OC(O)[Pt]+O=COC[Pt]\n", - "kf = 5.354197885861111e7\n", - "krev = 1.376967106369583e14\n", - "Kc = 3.888399266107105e-7\n", - "OCO[Pt]+O=COC[Pt]<=>CH2O2X+COC=O.[Pt]\n", - "kf = 0.03947248649742643\n", - "krev = 2.5171232142616846e11\n", - "Kc = 1.5681586929785789e-13\n", - "HOX+COC=O.[Pt]<=>H2OX+O=COC[Pt]\n", - "kf = 2.4490000178339845e-20\n", - "krev = 458.0011375503109\n", - "Kc = 5.3471483300955e-23\n", - "OC#[Pt]+COC=O.[Pt]<=>OC=[Pt]+O=COC[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.055946827834815e-26\n", - "Kc = 4.944672254535185e35\n", - "O=CC(=O)[Pt]+O=COC[Pt]<=>O=C=C=O.[Pt]+COC=O.[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.5205992990749725e-14\n", - "Kc = 9.918276185022613e23\n", - "O=CC=O.[Pt]+O=COC[Pt]<=>O=CC(=O)[Pt]+COC=O.[Pt]\n", - "kf = 327433.4917974331\n", - "krev = 0.4460204906723957\n", - "Kc = 734122.0832787583\n", - "O=COC=[Pt]+COC=O.[Pt]<=>O=COC[Pt]+O=COC[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 1.3048903398306852e-5\n", - "Kc = 0.004032923533638046\n", - "OO[Pt]+O=COC[Pt]<=>O=O.[Pt]+COC=O.[Pt]\n", - "kf = 7.128503770743534e7\n", - "krev = 0.0007669975897549733\n", - "Kc = 9.294036729660156e10\n", - "CX+COC=O.[Pt]<=>CHX+O=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.719414628142839e-6\n", - "Kc = 6.721487787577715e15\n", - "CHX+COC=O.[Pt]<=>CH2X+O=COC[Pt]\n", - "kf = 8.233814429551885e-18\n", - "krev = 0.5740049812746953\n", - "Kc = 1.434449995759099e-17\n", - "CO[Pt]+O=CCO[Pt]<=>CH2OX+COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.559249128827655e-29\n", - "Kc = 9.768490186593142e38\n", - "O=CCO[Pt]+O=COC[Pt]<=>O=CC=O.[Pt]+COC=O.[Pt]\n", - "kf = 1.6816353348966163e-33\n", - "krev = 8.021148128032321e14\n", - "Kc = 2.0965020319468163e-48\n", - "CX+COC=O.[Pt]<=>CO[Pt]+O=CC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.526991850186384e-11\n", - "Kc = 2.6241231642820084e20\n", - "O=C=C[Pt]+COC=O.[Pt]<=>C=C=O.[Pt]+O=COC[Pt]\n", - "kf = 3.6772489817592154e-10\n", - "krev = 0.00723599763490509\n", - "Kc = 5.081882509221477e-8\n", - "CHO2X+COC(=O)[Pt]<=>CO2X+COC=O.[Pt]\n", - "kf = 0.00020826365169953766\n", - "krev = 1.0739954827079557e13\n", - "Kc = 1.939148302322696e-17\n", - "CHO2X+COC(=O)[Pt]<=>CO2X+COC=O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.48171019889246675\n", - "Kc = 734122.0861712244\n", - "CO2HX+COC(=O)[Pt]<=>CO2X+COC=O.[Pt]\n", - "kf = 3.8695500910369183e-44\n", - "krev = 2.1644248520711738e17\n", - "Kc = 1.787795999169979e-61\n", - "CHO2X+COC=O.[Pt]<=>CH2O2X+COC(=O)[Pt]\n", - "kf = 1.1726078415532691e-17\n", - "krev = 1.59532697721828e15\n", - "Kc = 7.350266486422159e-33\n", - "CH2O2X+COC(=O)[Pt]<=>CO2HX+COC=O.[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 2.762063581333058e-24\n", - "Kc = 1.0314187634521844e16\n", - "OCX+COC=O.[Pt]<=>CHOX+COC(=O)[Pt]\n", - "kf = 6.089904416870865e-20\n", - "krev = 3.928023437111271\n", - "Kc = 1.550373747604081e-20\n", - "OCX+COC=O.[Pt]<=>CHOX+COC(=O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.322420103995465e-17\n", - "Kc = 2.681707080469945e26\n", - "CH2OX+COC(=O)[Pt]<=>CHOX+COC=O.[Pt]\n", - "kf = 6.827226723819953e-5\n", - "krev = 2.862909610249775e-7\n", - "Kc = 238.47161291356\n", - "OX+COC=O.[Pt]<=>HOX+COC(=O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.7660724730806307e-32\n", - "Kc = 9.038085676821402e41\n", - "vacantX+COC=O.[Pt]<=>HX+COC(=O)[Pt]\n", - "kf = 1.882970379851619e-8\n", - "krev = 6.2613640604613945e13\n", - "Kc = 3.0072846134950095e-22\n", - "CO[Pt]+COC(=O)[Pt]<=>CH2OX+COC=O.[Pt]\n", - "kf = 5.986889507133711e-22\n", - "krev = 1492.047811549125\n", - "Kc = 4.0125319448830507e-25\n", - "OC[Pt]+COC(=O)[Pt]<=>CH2OX+COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.05979204840625116\n", - "Kc = 4.181157974408231e11\n", - "OC=[Pt]+COC=O.[Pt]<=>OC[Pt]+COC(=O)[Pt]\n", - "kf = 3.6404040231768274e-5\n", - "krev = 5.1339082800935775e14\n", - "Kc = 7.090901949480236e-20\n", - "OC(O)[Pt]+COC(=O)[Pt]<=>CH2O2X+COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.7075333850654e-54\n", - "Kc = 3.727152526093054e63\n", - "OC(O)=[Pt]+COC=O.[Pt]<=>OC(O)[Pt]+COC(=O)[Pt]\n", - "kf = 1.39754480380523e-13\n", - "krev = 4.435737343310229e14\n", - "Kc = 3.1506482364492156e-28\n", - "OCO[Pt]+COC(=O)[Pt]<=>CH2O2X+COC=O.[Pt]\n", - "kf = 3.0518560755450534e-15\n", - "krev = 1.440283576497463e15\n", - "Kc = 2.1189272205454667e-30\n", - "HOX+COC=O.[Pt]<=>H2OX+COC(=O)[Pt]\n", - "kf = 3.314404876424973e-50\n", - "krev = 3.298291971460818e17\n", - "Kc = 1.0048852269912959e-67\n", - "OC#[Pt]+COC=O.[Pt]<=>OC=[Pt]+COC(=O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 5.830973747204281e-42\n", - "Kc = 4.885709192226705e33\n", - "O=CC(=O)[Pt]+COC(=O)[Pt]<=>O=C=C=O.[Pt]+COC=O.[Pt]\n", - "kf = 6.3392542923960805e-6\n", - "krev = 0.0008631955285686626\n", - "Kc = 0.007343937824733329\n", - "O=CC=O.[Pt]+COC(=O)[Pt]<=>O=CC(=O)[Pt]+COC=O.[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.9680498035664946e-34\n", - "Kc = 1.2702930563390754e44\n", - "O=COC=[Pt]+COC=O.[Pt]<=>COC(=O)[Pt]+O=COC[Pt]\n", - "kf = 2.9355344566104805e-6\n", - "krev = 1.175996281956839e-11\n", - "Kc = 249621.0661249539\n", - "OO[Pt]+COC(=O)[Pt]<=>O=O.[Pt]+COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3102559490834589e-14\n", - "Kc = 1.9080241549361273e24\n", - "CX+COC=O.[Pt]<=>CHX+COC(=O)[Pt]\n", - "kf = 2.9180289159703806e-27\n", - "krev = 9.401864294760527e-11\n", - "Kc = 3.103670532233209e-17\n", - "CHX+COC=O.[Pt]<=>CH2X+COC(=O)[Pt]\n", - "kf = 8.997747599742267e-17\n", - "krev = 6.572577910715489e15\n", - "Kc = 1.368983026442782e-32\n", - "COC(=O)[Pt]+O=CCO[Pt]<=>O=CC=O.[Pt]+COC=O.[Pt]\n", - "kf = 3.388822996448631e-6\n", - "krev = 1.0293603282987281e15\n", - "Kc = 3.292163981148853e-21\n", - "O=C=C[Pt]+COC=O.[Pt]<=>C=C=O.[Pt]+COC(=O)[Pt]\n", - "kf = 2.1491486919570496e-14\n", - "krev = 4.131728096070369e12\n", - "Kc = 5.201573390081201e-27\n", - "OCX+COC=O.[Pt]<=>CHO2X+CC(=O)[Pt]\n", - "kf = 2.415446383235281e-20\n", - "krev = 451.7273406124814\n", - "Kc = 5.347133472063615e-23\n", - "CC(=O)[Pt]+O=COC[Pt]<=>C=C=O.[Pt]+COC=O.[Pt]\n", - "kf = 29084.357636714656\n", - "krev = 3.7625287044080875e-13\n", - "Kc = 7.730002857556974e16\n", - "CC(=O)[Pt]+COC(=O)[Pt]<=>C=C=O.[Pt]+COC=O.[Pt]\n", - "kf = 2.859565189776071e-11\n", - "krev = 0.000933578065584948\n", - "Kc = 3.06301668300697e-8\n", - "CX+COC=O.[Pt]<=>HX+O=COCC#[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.1750295723598082e-43\n", - "Kc = 2.206855353748942e35\n", - "O=C([Pt])CO+O=COC[Pt]<=>O=C=CO.[Pt]+COC=O.[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 4.3570230615432705e-36\n", - "Kc = 5.737862675242513e45\n", - "COC(=O)[Pt]+O=C([Pt])CO<=>O=C=CO.[Pt]+COC=O.[Pt]\n", - "kf = 3.720866574817531e-22\n", - "krev = 0.000333999453543238\n", - "Kc = 1.114033731296463e-18\n", - "CO[Pt]+O=CCC(=O)[Pt]<=>C=C=O.[Pt]+COC=O.[Pt]\n", - "kf = 0.00256837059370255\n", - "krev = 1.2695573429161084e13\n", - "Kc = 2.0230441799526235e-16\n", - "O=C=C=[Pt]+COC=O.[Pt]<=>O=C=C[Pt]+O=COC[Pt]\n", - "kf = 3.07907263663438e8\n", - "krev = 5.547742278067932e-15\n", - "Kc = 5.5501364019864025e22\n", - "O=C=C=[Pt]+COC=O.[Pt]<=>O=C=C[Pt]+COC(=O)[Pt]\n", - "kf = 7.483948884590266e-53\n", - "krev = 2.8103204909201245e17\n", - "Kc = 2.6630232775123643e-70\n", - "CX+COC=O.[Pt]<=>CHOX+COC#[Pt]\n", - "kf = 1.3743850393273974e-17\n", - "krev = 6.122610931292474e-6\n", - "Kc = 2.2447695186753714e-12\n", - "O=COC#[Pt]+COC=O.[Pt]<=>O=COC=[Pt]+O=COC[Pt]\n", - "kf = 0.0005163317635413589\n", - "krev = 1.6229254340255067e-10\n", - "Kc = 3.1814879027476255e6\n", - "O=COC#[Pt]+COC=O.[Pt]<=>O=COC=[Pt]+COC(=O)[Pt]\n", - "kf = 2.110093084979835e-12\n", - "krev = 2.4085316622580622e14\n", - "Kc = 8.760910716040024e-27\n", - "CX+COC=O.[Pt]<=>CHO2X+CC#[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 1.1429411507382647e-15\n", - "Kc = 2.8609207088741057e7\n", - "O=C=CO[Pt]+O=COC[Pt]<=>O=C=C=O.[Pt]+COC=O.[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 2.2750559854988554e-15\n", - "Kc = 3.602118089238167e7\n", - "O=C=CO[Pt]+COC(=O)[Pt]<=>O=C=C=O.[Pt]+COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.024019970371648e-43\n", - "Kc = 6.212692825600234e52\n", - "CX+COC=O.[Pt]<=>HX+COC(=O)C#[Pt]\n", - "kf = 4.51610258482867e-23\n", - "krev = 15472.547765874588\n", - "Kc = 2.918784063985339e-27\n", - "vacantX+COC=O.[Pt]<=>CHO2X+CH3X\n", - "kf = 2.0496526220764064\n", - "krev = 1.4633869198921762e15\n", - "Kc = 1.4006224835106677e-15\n", - "CH2X+COC=O.[Pt]<=>CH3X+O=COC[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 2.375601900047824e-24\n", - "Kc = 3.580716650609497e16\n", - "CH2X+COC=O.[Pt]<=>CH3X+O=COC[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 3.2359557228060194e-16\n", - "Kc = 2.6287001452988416e8\n", - "CX+COC=O.[Pt]<=>CH3X+O=COC#[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 2.419253665005007e-25\n", - "Kc = 3.516108046777805e17\n", - "CH2X+COC=O.[Pt]<=>CH3X+COC(=O)[Pt]\n", - "kf = 4.746132232562072\n", - "krev = 2.6352119522517757e-10\n", - "Kc = 1.8010438319796345e10\n", - "CHX+COC=O.[Pt]<=>CH3X+O=COC=[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.869121889511259e-30\n", - "Kc = 1.7908695590280368e22\n", - "O=C=CO.[Pt]+O=COC[Pt]<=>O=C=CO[Pt]+COC=O.[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 3.7973012083800085e-37\n", - "Kc = 6.732652804247709e28\n", - "O=C=CO.[Pt]+COC(=O)[Pt]<=>O=C=CO[Pt]+COC=O.[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.3265145938724705e-33\n", - "Kc = 4.69350070471215e42\n", - "CHO2X+COC(=O)[Pt]<=>CO2X+COC=O.[Pt]\n", - "kf = 1.245555554261223e10\n", - "krev = 1.4588737337488966e-13\n", - "Kc = 8.537788606697952e22\n", - "CHO2X+COC(=O)[Pt]<=>CO2X+COC=O.[Pt]\n", - "kf = 4.786286134347495e-11\n", - "krev = 0.0006355926831038164\n", - "Kc = 7.530429883135883e-8\n", - "OCX+COC=O.[Pt]<=>CHOX+COC(=O)[Pt]\n", - "kf = 1.9108708710628152e-14\n", - "krev = 5.750545812867103e12\n", - "Kc = 3.322938262290088e-27\n", - "OCX+COC=O.[Pt]<=>CHOX+COC(=O)[Pt]\n", - "kf = 8.809048609670953e-10\n", - "krev = 5.30334818480063e15\n", - "Kc = 1.6610353125441853e-25\n", - "CHO2X+CO[Pt]<=>OX+COC=O.[Pt]\n", - "kf = 2.00333233616492e-67\n", - "krev = 2.0086736136424638e14\n", - "Kc = 9.973408932933319e-82\n", - "CHO2X+CO[Pt]<=>OX+COC=O.[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.726586049973397e-6\n", - "Kc = 0.00837955829095468\n", - "CO[Pt]+O=COC[Pt]<=>CH2OX+COC=O.[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 7.096612291679358e-6\n", - "Kc = 0.003946413774492056\n", - "CO[Pt]+O=COC[Pt]<=>CH2OX+COC=O.[Pt]\n", - "kf = 1.0265256602604584e-26\n", - "krev = 112849.3186381155\n", - "Kc = 9.09642763154215e-32\n", - "O=COC[Pt]+COC=O.[Pt]<=>COC(=O)[Pt]+COC=O.[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 0.09087129568777781\n", - "Kc = 2.751143780968724e11\n", - "CH2X+COC=O.[Pt]<=>CH3X+O=COC[Pt]\n", - "kf = 1.2341194948677085e8\n", - "krev = 1.5290672892581859e-24\n", - "Kc = 8.071060727918856e31\n", - "CH2X+COC=O.[Pt]<=>CH3X+O=COC[Pt]\n", - "kf = 8.219996171491995e-20\n", - "krev = 2.347130357335255e-19\n", - "Kc = 0.3502147269240011\n", - "vacantX+CC(=O)C(=O)[Pt]<=>OCX+CC(=O)[Pt]\n", - "kf = 1.3588265576828814e-16\n", - "krev = 6.093754170226661e16\n", - "Kc = 2.2298676968656565e-33\n", - "CX+CC(=O)C(=O)[Pt]<=>OCX+CC(=O)C#[Pt]\n", - "kf = 0.00014470508438140734\n", - "krev = 1.2597560252212088e-64\n", - "Kc = 1.1486754695695751e60\n", - "CHO2X+CC(=O)C(=O)[Pt]<=>O=C=C=O.[Pt]+COC=O.[Pt]\n", - "kf = 6.451439297868635e-57\n", - "krev = 8.482832416110645e14\n", - "Kc = 7.60528910793525e-72\n", - "vacantX+OOC#[Pt]<=>OO[Pt]+CX\n", - "kf = 2.095196876444184e-9\n", - "krev = 5.9307219702134525e-8\n", - "Kc = 0.03532785530947383\n", - "CX+OOC[Pt]<=>OOC#[Pt]+CH2X\n", - "kf = 2.5e10\n", - "krev = 1.4257912410930978e-59\n", - "Kc = 1.7534123705819296e69\n", - "CHO2X+CH2X<=>OX+O=CC[Pt]\n", - "kf = 412885.969273148\n", - "krev = 1.1342794009872417\n", - "Kc = 364007.288604364\n", - "CH2X+CH2O2X<=>HOX+O=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.583064462297258e-35\n", - "Kc = 1.5792155402011454e45\n", - "vacantX+O=CC[Pt]<=>CHOX+CH2X\n", - "kf = 2.5e10\n", - "krev = 1.4437894439004186e-36\n", - "Kc = 1.731554424754771e46\n", - "CH2X+CH2OX<=>HX+O=CC[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.6664784319671228e-8\n", - "Kc = 1.5001694303651932e18\n", - "CH2X+O=CC(=O)[Pt]<=>OCX+O=CC[Pt]\n", - "kf = 1.4197397308458187e-12\n", - "krev = 3.0290185667479297e13\n", - "Kc = 4.6871278586123213e-26\n", - "CH2X+O=CC=O.[Pt]<=>CHOX+O=CC[Pt]\n", - "kf = 1.0263854075463885e-7\n", - "krev = 1.9545487277553856e14\n", - "Kc = 5.251265384031101e-22\n", - "vacantX+O=CCO[Pt]<=>OX+O=CC[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 3.2362559658776053e-12\n", - "Kc = 10343.290300064218\n", - "CX+O=CC[Pt]<=>CH2X+O=CC#[Pt]\n", - "kf = 9868.238361499898\n", - "krev = 0.2153664742836313\n", - "Kc = 45820.68028148021\n", - "CHO2X+O=CC[Pt]<=>CH2O2X+C=C=O.[Pt]\n", - "kf = 4.00965787691315e-19\n", - "krev = 4.055766485027893\n", - "Kc = 9.886313454472895e-20\n", - "CO2HX+O=CC[Pt]<=>CH2O2X+C=C=O.[Pt]\n", - "kf = 3.9452234947489745e-7\n", - "krev = 1.361002505571871e12\n", - "Kc = 2.8987628447394044e-19\n", - "CHOX+O=CC[Pt]<=>CH2OX+C=C=O.[Pt]\n", - "kf = 18.267803269894422\n", - "krev = 2.792024654707504e-9\n", - "Kc = 6.542851704082885e9\n", - "HOX+O=CC[Pt]<=>H2OX+C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.704607370852364e-18\n", - "Kc = 6.748353468359037e27\n", - "O=CC(=O)[Pt]+O=CC[Pt]<=>C=C=O.[Pt]+O=CC=O.[Pt]\n", - "kf = 2.8052009086647103\n", - "krev = 2.294429327232502e13\n", - "Kc = 1.2226137782366527e-13\n", - "O=C=C[Pt]+O=CC[Pt]<=>C=C=O.[Pt]+C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.5572937987101485e-31\n", - "Kc = 7.027814235941051e40\n", - "CC(=O)[Pt]<=>O=CC[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.6625343699967689e-31\n", - "Kc = 2.0134040862236038e23\n", - "vacantX+O=CCC(=O)[Pt]<=>OCX+O=CC[Pt]\n", - "kf = 9.888055232525487e-8\n", - "krev = 7.779707979835849e-8\n", - "Kc = 1.2710059629685642\n", - "vacantX+O=CCC#[Pt]<=>CX+O=CC[Pt]\n", - "kf = 8.7276566297004e-6\n", - "krev = 1.546723677424112e-6\n", - "Kc = 5.6426734503963205\n", - "O=C=CO[Pt]+O=CC[Pt]<=>C=C=O.[Pt]+O=C=CO.[Pt]\n", - "kf = 2.5331825038162864e-12\n", - "krev = 1.769892843246248e17\n", - "Kc = 1.4312632052740838e-29\n", - "CH2X+COC=O.[Pt]<=>CO[Pt]+O=CC[Pt]\n", - "kf = 1.393899600447792e-20\n", - "krev = 8.328492808111743e-5\n", - "Kc = 1.6736516829193498e-16\n", - "O=CC[Pt]+O=COC[Pt]<=>C=C=O.[Pt]+COC=O.[Pt]\n", - "kf = 4.789035386292112e-18\n", - "krev = 2.8243399365414766e-5\n", - "Kc = 1.695629950322654e-13\n", - "O=CC[Pt]+COC(=O)[Pt]<=>C=C=O.[Pt]+COC=O.[Pt]\n", - "kf = 0.0009962735751002543\n", - "krev = 4.495422962203487e13\n", - "Kc = 2.21619541359445e-17\n", - "vacantX+O=CC=O.[Pt]<=>OX+O=CC=[Pt]\n", - "kf = 2.772273774659678e8\n", - "krev = 3.7705323383409334e-17\n", - "Kc = 7.352473141443741e24\n", - "OX+O=CC=[Pt]<=>CHX+CHO2X\n", - "kf = 127808.30444689187\n", - "krev = 2.3626964909258914e-13\n", - "Kc = 5.40942541446813e17\n", - "CHX+CH2O2X<=>HOX+O=CC=[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 3.5720015577500406e-52\n", - "Kc = 8.264488540948707e43\n", - "vacantX+O=CC=[Pt]<=>CHX+CHOX\n", - "kf = 2.8595651897765786e-11\n", - "krev = 0.000933577098423846\n", - "Kc = 3.063019856211522e-8\n", - "CHX+CH2OX<=>HX+O=CC=[Pt]\n", - "kf = 5699.926944847187\n", - "krev = 3.054251108472864e-67\n", - "Kc = 1.866227347527155e70\n", - "CHX+O=CC(=O)[Pt]<=>OCX+O=CC=[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 1.0833501613715598e-32\n", - "Kc = 7.082998693235901e24\n", - "CHX+O=CC=O.[Pt]<=>CHOX+O=CC=[Pt]\n", - "kf = 4.552726448583842e-23\n", - "krev = 27.53540659037694\n", - "Kc = 1.6534081069915729e-24\n", - "CH2O2X+O=CC#[Pt]<=>CHO2X+O=CC=[Pt]\n", - "kf = 2.287071149777874e-9\n", - "krev = 2.2490557638427473e13\n", - "Kc = 1.0169028205286352e-22\n", - "CH2O2X+O=CC#[Pt]<=>CO2HX+O=CC=[Pt]\n", - "kf = 7.128045206079291e-31\n", - "krev = 1.6024698052635947e11\n", - "Kc = 4.4481619451835966e-42\n", - "CHOX+O=CC#[Pt]<=>OCX+O=CC=[Pt]\n", - "kf = 1.2021042471738558e-26\n", - "krev = 3.79937896614338e12\n", - "Kc = 3.163949313521812e-39\n", - "CH2OX+O=CC#[Pt]<=>CHOX+O=CC=[Pt]\n", - "kf = 1.060146069558954e6\n", - "krev = 4.940969414534533e-35\n", - "Kc = 2.1456236228469465e40\n", - "HOX+O=CC#[Pt]<=>OX+O=CC=[Pt]\n", - "kf = 1.1758489216219413e-43\n", - "krev = 2.1453863988577092e16\n", - "Kc = 5.480825842132732e-60\n", - "vacantX+O=CC=[Pt]<=>HX+O=CC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.294133341553474e-55\n", - "Kc = 7.589249556063902e64\n", - "OC=[Pt]+O=CC=[Pt]<=>OC[Pt]+O=CC#[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 7.847086633519948e-25\n", - "Kc = 3.1858957556564916e34\n", - "OC(O)=[Pt]+O=CC=[Pt]<=>OC(O)[Pt]+O=CC#[Pt]\n", - "kf = 372758.92921022984\n", - "krev = 0.5077615475124772\n", - "Kc = 734122.012658058\n", - "H2OX+O=CC#[Pt]<=>HOX+O=CC=[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 7.495250892056493e-25\n", - "Kc = 3.3354453853566298e34\n", - "OC#[Pt]+O=CC=[Pt]<=>OC=[Pt]+O=CC#[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.8254433456081984e-40\n", - "Kc = 1.3695303149312766e50\n", - "O=CC#[Pt]+O=CC=O.[Pt]<=>O=CC(=O)[Pt]+O=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.066753580889227e-20\n", - "Kc = 2.7573265090930278e29\n", - "[H][H].[Pt]+O=CC#[Pt]<=>HX+O=CC=[Pt]\n", - "kf = 1.2526307828427685e-31\n", - "krev = 1.8291181793687947e14\n", - "Kc = 6.848276929132241e-46\n", - "O=CC=[Pt]+O=COC=[Pt]<=>O=CC#[Pt]+O=COC[Pt]\n", - "kf = 6.412809230790006e-14\n", - "krev = 6.896161957802356e13\n", - "Kc = 9.299098933624258e-28\n", - "CX+O=CC=[Pt]<=>CHX+O=CC#[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 6.474039280394542e-15\n", - "Kc = 8.128654665807662e6\n", - "CX+O=CC=[Pt]<=>CHX+O=CC#[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 2.6691128365256186e-10\n", - "Kc = 1.8732816131177477e20\n", - "CHX+O=CC=[Pt]<=>CH2X+O=CC#[Pt]\n", - "kf = 9.958136134339127e-12\n", - "krev = 3.084761262689636e-10\n", - "Kc = 0.03228170767956455\n", - "O=CC#[Pt]+C=C=O.[Pt]<=>O=C=C[Pt]+O=CC=[Pt]\n", - "kf = 4.194899212644372e-10\n", - "krev = 0.014508998351933198\n", - "Kc = 2.891239705796395e-8\n", - "O=C=C=[Pt]+O=CC=[Pt]<=>O=C=C[Pt]+O=CC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.1583552721722075e-20\n", - "Kc = 4.846506043286232e29\n", - "O=COC#[Pt]+O=CC=[Pt]<=>O=CC#[Pt]+O=COC=[Pt]\n", - "kf = 7705.934977783516\n", - "krev = 5.863572986161853e-13\n", - "Kc = 1.3142046659894356e16\n", - "CH2X+O=CC=[Pt]<=>CH3X+O=CC#[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 1.2254518112062234e-21\n", - "Kc = 2.668292606261641e13\n", - "O=CC#[Pt]+O=C=CO.[Pt]<=>O=C=CO[Pt]+O=CC=[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 2.4645381117653586e-12\n", - "Kc = 13267.654460532101\n", - "CHX+COC=O.[Pt]<=>CO[Pt]+O=CC=[Pt]\n", - "kf = 1.7361137032745595e-19\n", - "krev = 63.774720976875884\n", - "Kc = 2.72225997492652e-21\n", - "O=CC#[Pt]+COC=O.[Pt]<=>O=CC=[Pt]+O=COC[Pt]\n", - "kf = 7.380915652046712e-14\n", - "krev = 2.775462823415347e13\n", - "Kc = 2.6593458899096773e-27\n", - "O=CC#[Pt]+COC=O.[Pt]<=>O=CC=[Pt]+COC(=O)[Pt]\n", - "kf = 6.081485750645586e8\n", - "krev = 3.776470929291763e-7\n", - "Kc = 1.6103621249869132e15\n", - "vacantX+O=CC[Pt]<=>HX+O=CC=[Pt]\n", - "kf = 384539.88399328274\n", - "krev = 8.957560610185237e-9\n", - "Kc = 4.2929085353443195e13\n", - "CH2O2X+O=CC=[Pt]<=>CHO2X+O=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.7157326451879074e-27\n", - "Kc = 1.4571034753064335e37\n", - "CH2O2X+O=CC=[Pt]<=>CO2HX+O=CC[Pt]\n", - "kf = 753631.9525109725\n", - "krev = 9.011518944421836e14\n", - "Kc = 8.362984721654206e-10\n", - "CHOX+O=CC=[Pt]<=>OCX+O=CC[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.7867840452424854e-14\n", - "Kc = 1.3991618106600694e24\n", - "HOX+O=CC=[Pt]<=>OX+O=CC[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 1.9866745274914506e-30\n", - "Kc = 1.4859387148609413e22\n", - "CH2OX+O=CC=[Pt]<=>CHOX+O=CC[Pt]\n", - "kf = 176.6698786931541\n", - "krev = 1.870392435490979e-11\n", - "Kc = 9.44560485493934e12\n", - "H2OX+O=CC=[Pt]<=>HOX+O=CC[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 7.324156308451427e-7\n", - "Kc = 0.043678018970166745\n", - "[H][H].[Pt]+O=CC=[Pt]<=>HX+O=CC[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 7.587328136505701e-13\n", - "Kc = 43096.38318446866\n", - "OC[Pt]+O=CC=[Pt]<=>OC=[Pt]+O=CC[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 4598.938099177113\n", - "Kc = 6.089703295881323e-12\n", - "O=CC=[Pt]+O=CC=O.[Pt]<=>O=CC(=O)[Pt]+O=CC[Pt]\n", - "kf = 2.1514853509561807e8\n", - "krev = 7.777866186524473e-13\n", - "Kc = 2.7661640086888258e20\n", - "OC=[Pt]+O=CC=[Pt]<=>OC#[Pt]+O=CC[Pt]\n", - "kf = 4.052122584605618e-24\n", - "krev = 469.09529347560436\n", - "Kc = 8.638165082797514e-27\n", - "O=CC=[Pt]+COC=O.[Pt]<=>O=CC[Pt]+O=COC[Pt]\n", - "kf = 12581.204150344678\n", - "krev = 0.2112685438632624\n", - "Kc = 59550.76851614742\n", - "CX+O=CC[Pt]<=>CHX+O=CC=[Pt]\n", - "kf = 3.0449395213240036e-51\n", - "krev = 1.4315520101841116e12\n", - "Kc = 2.1270198355785863e-63\n", - "CH2X+O=CC=[Pt]<=>CHX+O=CC[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 4.477216581188038e-53\n", - "Kc = 6.362980552705156e44\n", - "CH2X+O=CC=[Pt]<=>CHX+O=CC[Pt]\n", - "kf = 1.2416194499098324e10\n", - "krev = 2.271594136432873e-13\n", - "Kc = 5.465850743300345e22\n", - "CH3X+O=CC=[Pt]<=>CH2X+O=CC[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 3.536759710167166e-36\n", - "Kc = 8.195394062368554e27\n", - "O=CC=[Pt]+O=COC=[Pt]<=>O=COC#[Pt]+O=CC[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 4.830700359768998e-42\n", - "Kc = 5.292381792522405e33\n", - "O=CC=[Pt]+O=CC=[Pt]<=>O=CC#[Pt]+O=CC[Pt]\n", - "kf = 4.786286134353719e-11\n", - "krev = 0.0006355923790078162\n", - "Kc = 7.530433486042254e-8\n", - "OC(O)=[Pt]+O=CC[Pt]<=>OC(O)[Pt]+O=CC=[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 4.830559203625511e-40\n", - "Kc = 5.175384245624519e49\n", - "O=CC=[Pt]+COC=O.[Pt]<=>O=CC[Pt]+COC(=O)[Pt]\n", - "kf = 3.616153302567068e-14\n", - "krev = 8.41503036896324e-15\n", - "Kc = 4.297255201721382\n", - "C=C=O.[Pt]+O=CC=[Pt]<=>O=C=C[Pt]+O=CC[Pt]\n", - "kf = 2.3627317133785774e-11\n", - "krev = 3.856091265609508e13\n", - "Kc = 6.127271246016828e-25\n", - "O=COC=[Pt]+O=CC[Pt]<=>O=CC=[Pt]+O=COC[Pt]\n", - "kf = 6.326940367296449e-9\n", - "krev = 1.8372911814097844e13\n", - "Kc = 3.443624195943553e-22\n", - "O=CC=[Pt]+O=C=CO.[Pt]<=>O=C=CO[Pt]+O=CC[Pt]\n", - "kf = 1.3389399016858639e-14\n", - "krev = 2.773400746132106e14\n", - "Kc = 4.8277909478217395e-29\n", - "O=C=C[Pt]+O=CC=[Pt]<=>O=C=C=[Pt]+O=CC[Pt]\n", - "kf = 5.454404325893404e-20\n", - "krev = 5.084145007870193e-7\n", - "Kc = 1.072826270189e-13\n", - "CX+O=CC=[Pt]<=>CHX+O=CC#[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 6.322264310888409e-36\n", - "Kc = 4.669334354059592e27\n", - "CX+O=CC=[Pt]<=>CHX+O=CC#[Pt]\n", - "kf = 6.004181315465852e-13\n", - "krev = 0.19478740167193392\n", - "Kc = 3.082427951669201e-12\n", - "CH2X+O=CC=[Pt]<=>CHX+O=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.0684033679389293e-18\n", - "Kc = 1.2086617333693171e28\n", - "CH2X+O=CC=[Pt]<=>CHX+O=CC[Pt]\n", - "kf = 0.0002345113953695938\n", - "krev = 4.688941595078633e-10\n", - "Kc = 500137.1644631481\n", - "OX+C.[Pt]<=>HX+CO[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.181818068125566e-8\n", - "Kc = 2.1153848188876897e18\n", - "OCX+C.[Pt]<=>HX+CC(=O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.084742232092733e-42\n", - "Kc = 4.9166700805815915e51\n", - "CX+C.[Pt]<=>HX+CC#[Pt]\n", - "kf = 4.648157058598011e-13\n", - "krev = 1.3999921584371802e15\n", - "Kc = 3.3201307811515004e-28\n", - "CHO2X+CH3X<=>CO2X+C.[Pt]\n", - "kf = 1.2211065235504926e-16\n", - "krev = 1.2627143633797795e15\n", - "Kc = 9.670488900451568e-32\n", - "CO2HX+CH3X<=>CO2X+C.[Pt]\n", - "kf = 1.3855440631402604e-13\n", - "krev = 1.3305165391638203e-7\n", - "Kc = 1.0413580157455412e-6\n", - "CH2O2X+CH3X<=>CHO2X+C.[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 0.48922244404245907\n", - "Kc = 6.68379802887317e-8\n", - "CH2O2X+CH3X<=>CO2HX+C.[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 1.2259112200812889e-16\n", - "Kc = 2.0854618352769157e8\n", - "OCX+C.[Pt]<=>CHOX+CH3X\n", - "kf = 6.519502059052115e-22\n", - "krev = 142.86665816232104\n", - "Kc = 4.563347489828482e-24\n", - "CH2OX+CH3X<=>CHOX+C.[Pt]\n", - "kf = 1.0442633465244387e6\n", - "krev = 1.3478746647554358e-10\n", - "Kc = 7.747481081365339e15\n", - "OX+C.[Pt]<=>HOX+CH3X\n", - "kf = 2.5e10\n", - "krev = 1.956562857492216e-7\n", - "Kc = 1.2777509244984459e17\n", - "vacantX+C.[Pt]<=>HX+CH3X\n", - "kf = 946026.2069742308\n", - "krev = 3.910739827671124e-49\n", - "Kc = 2.419046647594547e54\n", - "CH3X+CO[Pt]<=>CH2OX+C.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.158806984045244e-56\n", - "Kc = 2.729613151969499e65\n", - "CH3X+OC[Pt]<=>CH2OX+C.[Pt]\n", - "kf = 3.712816041087776e-19\n", - "krev = 9.367983662004229e16\n", - "Kc = 3.9633032838716965e-36\n", - "OC=[Pt]+C.[Pt]<=>CH3X+OC[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 0.8868529608572997\n", - "Kc = 364007.2889878057\n", - "CH3X+OC(O)[Pt]<=>CH2O2X+C.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.179306692567296e-20\n", - "Kc = 4.826900873793963e29\n", - "OC(O)=[Pt]+C.[Pt]<=>CH3X+OC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.1021348140038195e-19\n", - "Kc = 2.2683250435743298e29\n", - "CH3X+OCO[Pt]<=>CH2O2X+C.[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.0473065138531246e-21\n", - "Kc = 2.475989854235963e13\n", - "HOX+C.[Pt]<=>H2OX+CH3X\n", - "kf = 2.5e10\n", - "krev = 5.933915365824659e-14\n", - "Kc = 4.2130698634468396e23\n", - "OC#[Pt]+C.[Pt]<=>OC=[Pt]+CH3X\n", - "kf = 2.77963678004065e-20\n", - "krev = 3.601218827022036\n", - "Kc = 7.718600045027592e-21\n", - "CH3X+O=CC(=O)[Pt]<=>C.[Pt]+O=C=C=O.[Pt]\n", - "kf = 3.0713096503932575e-11\n", - "krev = 7.4063619158875634e-6\n", - "Kc = 4.146853320528285e-6\n", - "CH3X+O=CC=O.[Pt]<=>C.[Pt]+O=CC(=O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.777307049025005e-32\n", - "Kc = 9.001525419660186e41\n", - "C.[Pt]+O=COC=[Pt]<=>CH3X+O=COC[Pt]\n", - "kf = 2.4512530384253315e-9\n", - "krev = 3.614837695546209e14\n", - "Kc = 6.781087409389048e-24\n", - "OO[Pt]+CH3X<=>O=O.[Pt]+C.[Pt]\n", - "kf = 1.0293700832173347e-6\n", - "krev = 1.2050997101819434e12\n", - "Kc = 8.541783509863451e-19\n", - "CX+C.[Pt]<=>CHX+CH3X\n", - "kf = 4.3007284274917255e-15\n", - "krev = 1.9561961334382385\n", - "Kc = 2.1985159636997663e-15\n", - "CHX+C.[Pt]<=>CH2X+CH3X\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.6370748462102965e-36\n", - "Kc = 1.5839961798805036e28\n", - "CH3X+O=CCO[Pt]<=>C.[Pt]+O=CC=O.[Pt]\n", - "kf = 5.6170237484075445e-31\n", - "krev = 0.000416281746068688\n", - "Kc = 1.3493322254588399e-27\n", - "CH3X+C=C=O.[Pt]<=>C.[Pt]+O=C=C[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.070292208974654e-29\n", - "Kc = 4.118417884898294e38\n", - "CH3X+CC(=O)[Pt]<=>C.[Pt]+C=C=O.[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 4.790462195255654e-44\n", - "Kc = 6.162404531970363e35\n", - "CH3X+O=C([Pt])CO<=>C.[Pt]+O=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.910701225296475e-27\n", - "Kc = 3.160276097908509e36\n", - "C.[Pt]+O=C=C=[Pt]<=>CH3X+O=C=C[Pt]\n", - "kf = 48.10704508093828\n", - "krev = 9.042054006745243e-12\n", - "Kc = 5.320366926038167e12\n", - "C.[Pt]+O=COC#[Pt]<=>CH3X+O=COC=[Pt]\n", - "kf = 8.803023976547135e-28\n", - "krev = 1.526615583505237e17\n", - "Kc = 5.766365856383213e-45\n", - "CH3X+O=C=CO[Pt]<=>C.[Pt]+O=C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.0352496226011906e-17\n", - "Kc = 4.9649971448853606e26\n", - "CH2X+C.[Pt]<=>CH3X+CH3X\n", - "kf = 5.56726706794292e-16\n", - "krev = 4.282042054393877e17\n", - "Kc = 1.3001430152303739e-33\n", - "CH3X+O=C=CO.[Pt]<=>C.[Pt]+O=C=CO[Pt]\n", - "kf = 21.19822615963559\n", - "krev = 2.8273094218491462e-14\n", - "Kc = 7.497667568967851e14\n", - "CH3X+COC=O.[Pt]<=>C.[Pt]+O=COC[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 4.347223516290618e-14\n", - "Kc = 644231.1603064304\n", - "CH3X+COC=O.[Pt]<=>C.[Pt]+COC(=O)[Pt]\n", - "kf = 7.314142036323851e-21\n", - "krev = 492.5535033039904\n", - "Kc = 1.4849436634317805e-23\n", - "CH3X+O=CC[Pt]<=>C.[Pt]+C=C=O.[Pt]\n", - "kf = 5.6012337000223925e-8\n", - "krev = 1.5412075197181771e-21\n", - "Kc = 3.634315060340885e13\n", - "C.[Pt]+O=CC=[Pt]<=>CH3X+O=CC[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 6.743155058263278e-19\n", - "Kc = 4.8491603395127426e10\n", - "C.[Pt]+O=CC#[Pt]<=>CH3X+O=CC=[Pt]\n", - "kf = 1.1751099635722393e10\n", - "krev = 2.6165323686065496e-10\n", - "Kc = 4.491096604312415e19\n", - "CHO2X+O=CCC(=O)[Pt]<=>CH2O2X+O=C=CC=O.[Pt]\n", - "kf = 94.52002480700446\n", - "krev = 2.1721444498187882e-10\n", - "Kc = 4.351461285868434e11\n", - "CO2HX+O=CCC(=O)[Pt]<=>CH2O2X+O=C=CC=O.[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 5.2914067977129154e-14\n", - "Kc = 9.449282943358521e23\n", - "CHOX+O=CCC(=O)[Pt]<=>CH2OX+O=C=CC=O.[Pt]\n", - "kf = 682.402665705397\n", - "krev = 9.146137340080099e-11\n", - "Kc = 7.461102324748392e12\n", - "HOX+O=CCC(=O)[Pt]<=>H2OX+O=C=CC=O.[Pt]\n", - "kf = 7.798842461270165e-20\n", - "krev = 4.754727023110295e15\n", - "Kc = 1.640229275700578e-35\n", - "O=CC(=O)[Pt]+O=CCC(=O)[Pt]<=>O=CC=O.[Pt]+O=C=CC=O.[Pt]\n", - "kf = 1.1387724551001077e-9\n", - "krev = 1.0085447542339825e12\n", - "Kc = 1.129124364902415e-21\n", - "O=COC[Pt]+O=CCC(=O)[Pt]<=>COC=O.[Pt]+O=C=CC=O.[Pt]\n", - "kf = 2.102944101806726e6\n", - "krev = 2.1222813318800094e-47\n", - "Kc = 9.908884699767143e52\n", - "COC(=O)[Pt]+O=CCC(=O)[Pt]<=>COC=O.[Pt]+O=C=CC=O.[Pt]\n", - "kf = 49681.794329643395\n", - "krev = 1.619563011452047e-41\n", - "Kc = 3.067604901960581e45\n", - "OX+O=C=CC=O.[Pt]<=>CHO2X+O=C=C[Pt]\n", - "kf = 4.3330274516676855e9\n", - "krev = 2.2436011536981487e9\n", - "Kc = 1.9312824137772955\n", - "HOX+O=C=CC=O.[Pt]<=>CH2O2X+O=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.653410057160789e-56\n", - "Kc = 4.422109796959484e65\n", - "vacantX+O=C=CC=O.[Pt]<=>CHOX+O=C=C[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 224.3395816271696\n", - "Kc = 1.2483828443014824e-10\n", - "OCX+O=C=CC=O.[Pt]<=>O=C=C[Pt]+O=CC(=O)[Pt]\n", - "kf = 7.322080914983208e7\n", - "krev = 1.5034306029083408e-18\n", - "Kc = 4.870248683789505e25\n", - "O=C=C[Pt]+O=CC=O.[Pt]<=>CHOX+O=C=CC=O.[Pt]\n", - "kf = 6.183244140051347e-23\n", - "krev = 2731.92216309053\n", - "Kc = 2.2633310068601865e-26\n", - "O=C=C[Pt]+O=COC[Pt]<=>CH2OX+O=C=CC=O.[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 8.503469161971292e7\n", - "Kc = 3.7620485485108396e-16\n", - "O=C=C[Pt]+O=CCO[Pt]<=>CH2OX+O=C=CC=O.[Pt]\n", - "kf = 1.2622729508690855\n", - "krev = 0.21733806909375467\n", - "Kc = 5.807877819713996\n", - "CX+O=C=CC=O.[Pt]<=>O=C=C[Pt]+O=CC#[Pt]\n", - "kf = 6.62483386040773e-8\n", - "krev = 1.624406101098726e-9\n", - "Kc = 40.783113631048195\n", - "O=C=C[Pt]+O=CCC(=O)[Pt]<=>C=C=O.[Pt]+O=C=CC=O.[Pt]\n", - "kf = 1.4778859852656565e-10\n", - "krev = 2.404289853338368e13\n", - "Kc = 6.146871115450596e-24\n", - "O=C=C[Pt]+O=CCC(=O)[Pt]<=>C=C=O.[Pt]+O=C=CC=O.[Pt]\n", - "kf = 2.735304068777078e8\n", - "krev = 1.1929824589169815e-11\n", - "Kc = 2.2928284052560617e19\n", - "CX+O=C=CC=O.[Pt]<=>CHOX+O=C=CC#[Pt]\n", - "kf = 1.542530561493995e-10\n", - "krev = 1.2789927244807063e12\n", - "Kc = 1.2060510837700736e-22\n", - "OX+O=C=CC=O.[Pt]<=>CHOX+O=C=CO[Pt]\n", - "kf = 5.096371548170163\n", - "krev = 1.334665402115114e-9\n", - "Kc = 3.8184638187920933e9\n", - "O=C=CO[Pt]+O=CCC(=O)[Pt]<=>O=C=CO.[Pt]+O=C=CC=O.[Pt]\n", - "kf = 1.7013748640380587e-8\n", - "krev = 1.0085447542339823e12\n", - "Kc = 1.6869602036949763e-20\n", - "CHO2X+O=C=CC(=O)[Pt]<=>CO2X+O=C=CC=O.[Pt]\n", - "kf = 4.979908332469234e7\n", - "krev = 1.5792793738708088e-40\n", - "Kc = 3.1532789035694767e47\n", - "CO2HX+O=C=CC(=O)[Pt]<=>CO2X+O=C=CC=O.[Pt]\n", - "kf = 2.8272029837629057e7\n", - "krev = 9.315217559083137e-42\n", - "Kc = 3.035036987414363e48\n", - "CHO2X+O=C=CC=O.[Pt]<=>CH2O2X+O=C=CC(=O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.572502010357685e-47\n", - "Kc = 6.997896691875328e56\n", - "CO2HX+O=C=CC=O.[Pt]<=>CH2O2X+O=C=CC(=O)[Pt]\n", - "kf = 1.9145907695639512e-44\n", - "krev = 1.1771971588384226e12\n", - "Kc = 1.626397715275781e-56\n", - "OCX+O=C=CC=O.[Pt]<=>CHOX+O=C=CC(=O)[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 0.0025285011306884937\n", - "Kc = 1.5664103465194285e-5\n", - "OCX+O=C=CC=O.[Pt]<=>CHOX+O=C=CC(=O)[Pt]\n", - "kf = 5.113182125834635e-8\n", - "krev = 3.03538509820146e-7\n", - "Kc = 0.16845250142607343\n", - "CH2OX+O=C=CC(=O)[Pt]<=>CHOX+O=C=CC=O.[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 3.035294805594631e-5\n", - "Kc = 1.6472864483489508e15\n", - "OX+O=C=CC=O.[Pt]<=>HOX+O=C=CC(=O)[Pt]\n", - "kf = 2.5157725911236352e-27\n", - "krev = 8837.406478086354\n", - "Kc = 2.84673178421957e-31\n", - "vacantX+O=C=CC=O.[Pt]<=>HX+O=C=CC(=O)[Pt]\n", - "kf = 1.0053469908846067e8\n", - "krev = 5.485808774926133e-25\n", - "Kc = 1.8326322191173056e32\n", - "CO[Pt]+O=C=CC(=O)[Pt]<=>CH2OX+O=C=CC=O.[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 0.4688595936220698\n", - "Kc = 1.7478623517301195e-7\n", - "OC[Pt]+O=C=CC(=O)[Pt]<=>CH2OX+O=C=CC=O.[Pt]\n", - "kf = 0.21718769045422626\n", - "krev = 2.002779166423329e-13\n", - "Kc = 1.0844315444028296e12\n", - "OC=[Pt]+O=C=CC=O.[Pt]<=>OC[Pt]+O=C=CC(=O)[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 7.666152073113618e-12\n", - "Kc = 3780.924152337611\n", - "OC(O)[Pt]+O=C=CC(=O)[Pt]<=>CH2O2X+O=C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.918397706885573e-39\n", - "Kc = 5.082956175951557e48\n", - "OC(O)=[Pt]+O=C=CC=O.[Pt]<=>OC(O)[Pt]+O=C=CC(=O)[Pt]\n", - "kf = 8.901266563864654e-15\n", - "krev = 1.309728963703428e15\n", - "Kc = 6.79626610584771e-30\n", - "OCO[Pt]+O=C=CC(=O)[Pt]<=>CH2O2X+O=C=CC=O.[Pt]\n", - "kf = 1.6716561102658422e-25\n", - "krev = 524619.2678123232\n", - "Kc = 3.186417680076247e-31\n", - "HOX+O=C=CC=O.[Pt]<=>H2OX+O=C=CC(=O)[Pt]\n", - "kf = 3.7147962989308654e-50\n", - "krev = 4.0636001726377395e18\n", - "Kc = 9.141638303749602e-69\n", - "OC#[Pt]+O=C=CC=O.[Pt]<=>OC=[Pt]+O=C=CC(=O)[Pt]\n", - "kf = 1.941245658968684e-59\n", - "krev = 1.9443160961908433e9\n", - "Kc = 9.98420813761623e-69\n", - "O=CC(=O)[Pt]+O=C=CC(=O)[Pt]<=>O=C=C=O.[Pt]+O=C=CC=O.[Pt]\n", - "kf = 365995.57053717994\n", - "krev = 1.0054621985249468\n", - "Kc = 364007.290452202\n", - "O=CC=O.[Pt]+O=C=CC(=O)[Pt]<=>O=CC(=O)[Pt]+O=C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.5470432905792705e-19\n", - "Kc = 1.615985806747468e29\n", - "O=COC=[Pt]+O=C=CC=O.[Pt]<=>O=COC[Pt]+O=C=CC(=O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.939852621840177e-35\n", - "Kc = 8.503827645738055e44\n", - "OO[Pt]+O=C=CC(=O)[Pt]<=>O=O.[Pt]+O=C=CC=O.[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 0.00012609781336559052\n", - "Kc = 1.9825879079693838e14\n", - "CX+O=C=CC=O.[Pt]<=>CHX+O=C=CC(=O)[Pt]\n", - "kf = 1.2784478936507186e-21\n", - "krev = 132.59733776930153\n", - "Kc = 9.641580405445367e-24\n", - "CHX+O=C=CC=O.[Pt]<=>CH2X+O=C=CC(=O)[Pt]\n", - "kf = 3.1239379458734235e-11\n", - "krev = 5.024094937764025e-9\n", - "Kc = 0.006217911851927968\n", - "O=CCO[Pt]+O=C=CC(=O)[Pt]<=>O=CC=O.[Pt]+O=C=CC=O.[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.4992009477647154e-32\n", - "Kc = 1.1812081765045545e24\n", - "O=C=C[Pt]+O=C=CC=O.[Pt]<=>C=C=O.[Pt]+O=C=CC(=O)[Pt]\n", - "kf = 1.107119853181277e-14\n", - "krev = 2.5289157654010746e13\n", - "Kc = 4.377843929513773e-28\n", - "CC(=O)[Pt]+O=C=CC(=O)[Pt]<=>C=C=O.[Pt]+O=C=CC=O.[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 8.140240591000901e-25\n", - "Kc = 3.0711622980330195e34\n", - "O=C([Pt])CO+O=C=CC(=O)[Pt]<=>O=C=CO.[Pt]+O=C=CC=O.[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 1.683521621093348e-30\n", - "Kc = 1.753512730243651e22\n", - "O=C=CC(=O)[Pt]+O=CCC(=O)[Pt]<=>O=C=CC=O.[Pt]+O=C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.4692339232304496e-35\n", - "Kc = 7.206201874309107e44\n", - "O=C=C=[Pt]+O=C=CC=O.[Pt]<=>O=C=C[Pt]+O=C=CC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.906984656058423e-6\n", - "Kc = 0.017553122325364576\n", - "O=COC#[Pt]+O=C=CC=O.[Pt]<=>O=COC=[Pt]+O=C=CC(=O)[Pt]\n", - "kf = 1759.880392627519\n", - "krev = 3.2877732722109866e-12\n", - "Kc = 5.352803392808232e14\n", - "O=C=CO[Pt]+O=C=CC(=O)[Pt]<=>O=C=C=O.[Pt]+O=C=CC=O.[Pt]\n", - "kf = 8.336773502217888e-19\n", - "krev = 4.018028855986407\n", - "Kc = 2.0748416203624424e-19\n", - "CH3X+O=CCC(=O)[Pt]<=>C.[Pt]+O=C=CC=O.[Pt]\n", - "kf = 0.24675966205104702\n", - "krev = 5.277017405064255e15\n", - "Kc = 4.6761199198288865e-17\n", - "CH2X+O=C=CC=O.[Pt]<=>CH3X+O=C=CC(=O)[Pt]\n", - "kf = 4.1241018831024145e-7\n", - "krev = 7.782310155024181e12\n", - "Kc = 5.2993286067375974e-20\n", - "CHOX+O=C=CO.[Pt]<=>HOX+O=C=CC=O.[Pt]\n", - "kf = 1.7365155933402038e8\n", - "krev = 4.134590691869886e-13\n", - "Kc = 4.199969773924241e20\n", - "O=C=CO.[Pt]+O=C=CC(=O)[Pt]<=>O=C=CO[Pt]+O=C=CC=O.[Pt]\n", - "kf = 1.438969400016978e-30\n", - "krev = 1.6093339940290013e17\n", - "Kc = 8.941396909254915e-48\n", - "CO[Pt]+O=C=CC=O.[Pt]<=>O=C=C[Pt]+COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.766742910705455e-15\n", - "Kc = 6.637033796213575e24\n", - "O=COC[Pt]+O=C=CC=O.[Pt]<=>COC=O.[Pt]+O=C=CC(=O)[Pt]\n", - "kf = 347843.58123444836\n", - "krev = 178209.4487483253\n", - "Kc = 1.9518806868971765\n", - "COC(=O)[Pt]+O=C=CC=O.[Pt]<=>COC=O.[Pt]+O=C=CC(=O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.796471055455441e-33\n", - "Kc = 4.31296900490357e42\n", - "CH2X+O=C=CC=O.[Pt]<=>O=C=C[Pt]+O=CC[Pt]\n", - "kf = 1.3358759661274015e-7\n", - "krev = 3.1165281946439875e14\n", - "Kc = 4.286423490161954e-22\n", - "O=CC[Pt]+O=C=CC(=O)[Pt]<=>C=C=O.[Pt]+O=C=CC=O.[Pt]\n", - "kf = 6.192873660096324e-8\n", - "krev = 3.90827625278604e13\n", - "Kc = 1.584553716150872e-21\n", - "O=CC=[Pt]+O=C=CC=O.[Pt]<=>O=CC[Pt]+O=C=CC(=O)[Pt]\n", - "kf = 4.52195120819324e-12\n", - "krev = 5.920081591014324e14\n", - "Kc = 7.638325821483257e-27\n", - "vacantX+O=C=CC=O.[Pt]<=>OCX+O=CC=[Pt]\n", - "kf = 2.9228830020630096e-5\n", - "krev = 1.1970265496551398e-9\n", - "Kc = 24417.86276925173\n", - "CHX+O=C=CC=O.[Pt]<=>O=C=C[Pt]+O=CC=[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 6.095879365149742e-19\n", - "Kc = 5.364056293281289e10\n", - "O=CC#[Pt]+O=C=CC=O.[Pt]<=>O=CC=[Pt]+O=C=CC(=O)[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 1.7806643358524245e-19\n", - "Kc = 1.572793251160735e11\n", - "CH3X+O=C=CC=O.[Pt]<=>C.[Pt]+O=C=CC(=O)[Pt]\n", - "kf = 2.610914590914038e-25\n", - "krev = 48838.0104312493\n", - "Kc = 5.3460707507516085e-30\n", - "OCX+O=C=CC=O.[Pt]<=>CHOX+O=C=CC(=O)[Pt]\n", - "kf = 2.73273606062798e-19\n", - "krev = 1.7143250273592365e15\n", - "Kc = 1.594059479396106e-34\n", - "OCX+O=C=CC=O.[Pt]<=>CHOX+O=C=CC(=O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.587375799156772e-36\n", - "Kc = 6.968882380785518e45\n" - ] - }, - { - "ename": "BoundsError", - "evalue": "BoundsError: attempt to access 724-element Vector{Float64} at index [725]", - "output_type": "error", - "traceback": [ - "BoundsError: attempt to access 724-element Vector{Float64} at index [725]\n", - "\n", - "Stacktrace:\n", - " [1] getindex(A::Vector{Float64}, i1::Int64)\n", - " @ Base ./essentials.jl:13\n", - " [2] top-level scope\n", - " @ ~/Work/Electrocat/CO2_RR_RMG/CO2_Reduction_Ag/jl_notebook_cell_df34fa98e69747e1a8f8a730347b8e2f_X54sdnNjb2RlLXJlbW90ZQ==.jl:3" - ] - } - ], - "source": [ - "for (i,rxn) in enumerate(domaincat.phase.reactions)\n", - " str = getrxnstr(rxn)\n", - " kf = inter.kfs[i]\n", - " krev = inter.krevs[i]\n", - " Kc = kf/krev\n", - " println(str)\n", - " println(\"kf = $kf\")\n", - " println(\"krev = $krev\")\n", - " println(\"Kc = $Kc\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 78, - "id": "c7d9f420", - "metadata": {}, - "outputs": [ - { - "ename": "ErrorException", - "evalue": "type ConstantTAPhiDomain has no field reactions", - "output_type": "error", - "traceback": [ - "type ConstantTAPhiDomain has no field reactions\n", - "\n", - "Stacktrace:\n", - " [1] getproperty(x::ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, f::Symbol)\n", - " @ Base ./Base.jl:37\n", - " [2] top-level scope\n", - " @ ~/Work/Electrocat/CO2_RR_RMG/CO2_Reduction_Ag/jl_notebook_cell_df34fa98e69747e1a8f8a730347b8e2f_X53sdnNjb2RlLXJlbW90ZQ==.jl:1" - ] - } - ], - "source": [ - "for (i,rxn) in enumerate(domaincat.reactions)\n", - " str = getrxnstr(rxn)\n", - " kf = inter.kfs[i]\n", - " krev = inter.krevs[i]\n", - " Kc = kf/krev\n", - " println(str)\n", - " println(\"kf = $kf\")\n", - " println(\"krev = $krev\")\n", - " println(\"Kc = $Kc\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 74, - "id": "44de0eb2", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "vacantX+CO2<=>CO2X\n", - "kf = 20654.615923781494\n", - "krev = 11189.298481041604\n", - "Kc = 1.8459259048971917\n", - "proton+CO2X<=>CHO2X\n", - "kf = 6.700453386611787e9\n", - "krev = 154.2911945001599\n", - "Kc = 4.342732200835248e7\n", - "proton+CO2X<=>CO2HX\n", - "kf = 7.803841747257553e9\n", - "krev = 7.148654626970559e-10\n", - "Kc = 1.0916518078541791e19\n", - "proton+CHO2X<=>CH2O2X\n", - "kf = 2.5e10\n", - "krev = 3.2154148400024995e-34\n", - "Kc = 7.775046531781437e43\n", - "proton+CO2HX<=>CH2O2X\n", - "kf = 2.5e10\n", - "krev = 8.082730550170151e-23\n", - "Kc = 3.0930141546625875e32\n", - "proton+OCX<=>CHOX\n", - "kf = 2.5e10\n", - "krev = 9.19383930722573e-19\n", - "Kc = 2.71921219901589e28\n", - "proton+CHOX<=>CH2OX\n", - "kf = 2.5e10\n", - "krev = 2.4457047139990357e-18\n", - "Kc = 1.0222002622353312e28\n", - "vacantX+vacantX+CO2<=>OX+OCX\n", - "kf = 3.0109478093923404e-24\n", - "krev = 3.037156297092479e15\n", - "Kc = 9.913707148607306e-40\n", - "OX+proton<=>HOX\n", - "kf = 2.5e10\n", - "krev = 1.678437078622112e-22\n", - "Kc = 1.4894809176000438e32\n", - "vacantX+C=O<=>CH2OX\n", - "kf = 500114.13488002896\n", - "krev = 399.6803280141717\n", - "Kc = 1251.2853393732605\n", - "proton+CHO2X<=>OX+C=O\n", - "kf = 0.00010342351299484538\n", - "krev = 3.7647642123828275e-11\n", - "Kc = 2.747144499904435e6\n", - "HX+CO2<=>CHO2X\n", - "kf = 6.542996392927688e-8\n", - "krev = 15.579156394796986\n", - "Kc = 4.199839983064083e-9\n", - "HX+CO2<=>CO2HX\n", - "kf = 6.542996392927688e-8\n", - "krev = 6.197590078701277e-11\n", - "Kc = 1055.7323588427441\n", - "vacantX+vacantX+C=O<=>HX+CHOX\n", - "kf = 2.0718885766149262e-11\n", - "krev = 0.008867505326838887\n", - "Kc = 2.336495440655708e-9\n", - "vacantX+O=CO<=>CH2O2X\n", - "kf = 403943.82249737746\n", - "krev = 29.756334575496034\n", - "Kc = 13575.053119278344\n", - "vacantX+vacantX+O=CO<=>HOX+CHOX\n", - "kf = 8.486192390111145e-15\n", - "krev = 9.7037034735699e11\n", - "Kc = 8.745312975839684e-27\n", - "vacantX+vacantX+O=CO<=>HX+CHO2X\n", - "kf = 1.2668346793097018e-21\n", - "krev = 380.13410282264914\n", - "Kc = 3.332599390328158e-24\n", - "vacantX+vacantX+O=CO<=>HX+CO2HX\n", - "kf = 9.840171155787102e-15\n", - "krev = 0.011746228705195169\n", - "Kc = 8.377302539184302e-13\n", - "proton+CH2OX<=>CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 0.0001729697966089756\n", - "Kc = 1.4453390412729847e14\n", - "HX+C=O<=>CO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.180104845075902e-9\n", - "Kc = 9.475050217848336\n", - "proton+CO2HX<=>H2O+OCX\n", - "kf = 2.5e10\n", - "krev = 1.421137905927188e-15\n", - "Kc = 1.7591536961847018e25\n", - "vacantX+vacantX+H2O<=>HX+HOX\n", - "kf = 1.7047654949014593e-31\n", - "krev = 21441.30602897437\n", - "Kc = 7.950847269274322e-36\n", - "proton+CH2OX<=>OC[Pt]\n", - "kf = 2.094291727583087e10\n", - "krev = 6.539117564188543e-11\n", - "Kc = 3.202713067971846e20\n", - "HX+C=O<=>OC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.886422105564557e-15\n", - "Kc = 2.099567387708916e7\n", - "vacantX+vacantX+O=CC=O<=>CHOX+CHOX\n", - "kf = 3.132095071630788e8\n", - "krev = 159.05427897483804\n", - "Kc = 1.9691988746346629e6\n", - "proton+CH2O2X<=>OC(O)[Pt]\n", - "kf = 0.33148947903056336\n", - "krev = 0.22094946278291003\n", - "Kc = 1.5002954741567418\n", - "HX+O=CO<=>OC(O)[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 29981.045237801853\n", - "Kc = 1.0670229661561413e-12\n", - "proton+CH2O2X<=>OCO[Pt]\n", - "kf = 0.23228315702691824\n", - "krev = 0.21874826816857254\n", - "Kc = 1.061874267493242\n", - "HOX+C=O<=>OCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.962949149852605e-13\n", - "Kc = 201771.41789913058\n", - "HX+O=CO<=>OCO[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 42359.465576793365\n", - "Kc = 7.552140562327293e-13\n", - "vacantX+H2O<=>H2OX\n", - "kf = 4.842414926683719e6\n", - "krev = 2.0721934488233277e8\n", - "Kc = 0.023368546645263413\n", - "proton+HOX<=>H2OX\n", - "kf = 2.5e10\n", - "krev = 4.456327978496074e-40\n", - "Kc = 5.610000009118949e49\n", - "vacantX+vacantX+H2<=>HX+HX\n", - "kf = 3.8736093818093735e10\n", - "krev = 4.9917087254698525e28\n", - "Kc = 7.760086965901168e-19\n", - "proton+CHOX<=>OC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 836.113886499964\n", - "Kc = 2.990023297502197e7\n", - "vacantX+vacantX+O=CO<=>OX+OC=[Pt]\n", - "kf = 1.3995006080437096e-36\n", - "krev = 7.971831424002446e14\n", - "Kc = 1.755557203367275e-51\n", - "proton+OC=[Pt]<=>OC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.2832873000074666e-31\n", - "Kc = 1.0949125850224037e41\n", - "proton+OC(O)[Pt]<=>H2O+OC=[Pt]\n", - "kf = 5.0e10\n", - "krev = 1.6222106700956051e-18\n", - "Kc = 3.0822137298020145e28\n", - "proton+O=CC(=O)[Pt]<=>OCX+C=O\n", - "kf = 2.986526002688191e9\n", - "krev = 1.177582616520277e-15\n", - "Kc = 2.5361498724508097e24\n", - "vacantX+vacantX+O=CC=O<=>HX+O=CC(=O)[Pt]\n", - "kf = 1.43713660093583e-9\n", - "krev = 0.00032277677938391324\n", - "Kc = 4.452416322137251e-6\n", - "proton+OCX<=>OC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.3233693919112797e9\n", - "Kc = 7.522486083204378\n", - "proton+OC#[Pt]<=>OC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.3130431223595305e-25\n", - "Kc = 1.0808272339729469e35\n", - "vacantX+O=CC=O<=>O=CC=O.[Pt]\n", - "kf = 359723.7676387533\n", - "krev = 0.32068189796600394\n", - "Kc = 1.121746409511672e6\n", - "proton+O=CC(=O)[Pt]<=>O=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.1987210746671435e-18\n", - "Kc = 4.808875036943709e27\n", - "vacantX+vacantX+OO<=>HOX+HOX\n", - "kf = 4.0912386971316826e8\n", - "krev = 1.7763617117679594e-6\n", - "Kc = 2.3031563166601894e14\n", - "OCX<=>vacantX+CO\n", - "kf = 2.010168305725754e-19\n", - "krev = 2.61760793808642e-25\n", - "Kc = 767940.9419866255\n", - "vacantX+vacantX+O2<=>OX+OX\n", - "kf = 1.0945721587141857e10\n", - "krev = 4.219325007995329e-16\n", - "Kc = 2.594187830138819e25\n", - "proton+HX<=>[H][H].[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 4.2182399573625954e-24\n", - "Kc = 5.926642451045138e33\n", - "vacantX+H2<=>[H][H].[Pt]\n", - "kf = 2338.960705505517\n", - "krev = 9707.159813448116\n", - "Kc = 0.24095211683495363\n", - "CHOX+C=O<=>O=COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 7.563806299311394e-5\n", - "Kc = 0.0005236345532350701\n", - "proton+OO[Pt]<=>OX+H2O\n", - "kf = 2238.846752341849\n", - "krev = 2.856092619409056e-69\n", - "Kc = 7.83884506100184e71\n", - "vacantX+vacantX+OO<=>HX+OO[Pt]\n", - "kf = 4.980245005159166e-22\n", - "krev = 5.509834949091977\n", - "Kc = 9.038827934364735e-23\n", - "proton+OC#[Pt]<=>H2O+CX\n", - "kf = 0.004250927229403503\n", - "krev = 4.255087166696794e-10\n", - "Kc = 9.990223614393027e6\n", - "vacantX+vacantX+O=C=C=O<=>OCX+OCX\n", - "kf = 74.64023007210145\n", - "krev = 2.953439666185894e-39\n", - "Kc = 2.52723056870475e40\n", - "HX+O=C=C=O<=>O=CC(=O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 5.0006650398424424e-61\n", - "Kc = 1.1597065597154312e53\n", - "proton+OC=[Pt]<=>H2O+CHX\n", - "kf = 2.5e10\n", - "krev = 2.298435109298346e-13\n", - "Kc = 1.087696576634346e23\n", - "proton+CX<=>CHX\n", - "kf = 2.5e10\n", - "krev = 2.124472809651395e-41\n", - "Kc = 1.1767625307523824e51\n", - "H2+CX<=>CH2X\n", - "kf = 4.832014059685671\n", - "krev = 1.8278921581756875e-33\n", - "Kc = 2.643489681857502e33\n", - "vacantX+vacantX+C=O<=>OX+CH2X\n", - "kf = 4.5608316796485725e-28\n", - "krev = 3.884151005592286e17\n", - "Kc = 1.1742158513101117e-45\n", - "proton+OC[Pt]<=>H2O+CH2X\n", - "kf = 934895.4476836504\n", - "krev = 8.923256806166294e-10\n", - "Kc = 1.0477065358441816e15\n", - "proton+O=COC[Pt]<=>CH2X+O=CO\n", - "kf = 257035.79866672424\n", - "krev = 6.729989470427483e-12\n", - "Kc = 3.819260041879346e16\n", - "proton+CHX<=>CH2X\n", - "kf = 2.5e10\n", - "krev = 2.370438376324263e-23\n", - "Kc = 1.0546572418712873e33\n", - "proton+O=COC#[Pt]<=>CX+O=CO\n", - "kf = 8.024182777649594e9\n", - "krev = 1.713385513637571e-29\n", - "Kc = 4.683232532189445e38\n", - "vacantX+vacantX+C=C=O<=>OCX+CH2X\n", - "kf = 2.4823885573387985e-14\n", - "krev = 9.351132511056354e15\n", - "Kc = 2.6546394828687704e-30\n", - "CHOX+C=O<=>O=CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.4949222028864902e7\n", - "Kc = 2.6494156850764662e-15\n", - "HX+O=CC=O<=>O=CCO[Pt]\n", - "kf = 5.6976884072695144e-8\n", - "krev = 2.551666729065355e-8\n", - "Kc = 2.23292812590636\n", - "proton+O=CC=O.[Pt]<=>O=CCO[Pt]\n", - "kf = 1.6117056515547888e10\n", - "krev = 0.4241906612356468\n", - "Kc = 3.79948405007307e10\n", - "O=O.[Pt]+proton<=>OO[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.2517365237178077e-36\n", - "Kc = 1.9972254165554745e46\n", - "proton+O=CC#[Pt]<=>CX+C=O\n", - "kf = 7.436243130002853e-15\n", - "krev = 7.618143862840909e-6\n", - "Kc = 9.761226965369721e-10\n", - "proton+CO2HX<=>OC(O)=[Pt]\n", - "kf = 2.355118429524867e-13\n", - "krev = 1.0085447542339824e12\n", - "Kc = 2.3351650183472963e-25\n", - "proton+OC(O)=[Pt]<=>OC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.2580528275000757e-47\n", - "Kc = 1.987197950159092e57\n", - "proton+OC(O)=[Pt]<=>H2O+OC#[Pt]\n", - "kf = 7.647664939071944e6\n", - "krev = 1.3495259820101604e-44\n", - "Kc = 5.666926788382771e50\n", - "proton+O=C(O)C#[Pt]<=>CX+O=CO\n", - "kf = 1.577998856851828e-7\n", - "krev = 1.7401723222676178e-10\n", - "Kc = 906.8060884887184\n", - "proton+O=C=C=O.[Pt]<=>O=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 9.354213865452181e-57\n", - "Kc = 2.6725923054135235e66\n", - "vacantX+O=C=C=O<=>O=C=C=O.[Pt]\n", - "kf = 366139.2749661925\n", - "krev = 442.06521987276346\n", - "Kc = 828.2471873077366\n", - "HOX+C=O<=>OOC[Pt]\n", - "kf = 1.5395975576095126e-29\n", - "krev = 2.622153295712258e16\n", - "Kc = 5.871500953537159e-46\n", - "proton+OOC[Pt]<=>OO+CH2X\n", - "kf = 2015.4980994888942\n", - "krev = 1.5583753177625496e-15\n", - "Kc = 1.293332919557955e18\n", - "vacantX+vacantX+O=C=CO<=>OCX+OC=[Pt]\n", - "kf = 73.33238091278024\n", - "krev = 14511.198914062346\n", - "Kc = 0.005053502563576338\n", - "vacantX+C=C=O<=>C=C=O.[Pt]\n", - "kf = 422670.5724931744\n", - "krev = 9.80980243728561e-11\n", - "Kc = 4.3086552985681545e15\n", - "proton+CO[Pt]<=>OX+CH4\n", - "kf = 7.027691701271914e7\n", - "krev = 9.157133997597336e-26\n", - "Kc = 7.674553744780683e32\n", - "HX+C=C=O<=>CC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.3310785577331067e-33\n", - "Kc = 2.514767798332947e25\n", - "proton+C=C=O.[Pt]<=>CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.244084982305732e-16\n", - "Kc = 1.1140398067417758e26\n", - "proton+CC(=O)[Pt]<=>OCX+CH4\n", - "kf = 1.3012361379695292e10\n", - "krev = 1.990497991828919e-14\n", - "Kc = 6.537239139708557e23\n", - "vacantX+vacantX+COC=O<=>CHOX+CO[Pt]\n", - "kf = 5.858305523872122e-8\n", - "krev = 9.372228401924443e12\n", - "Kc = 6.250707166578664e-21\n", - "vacantX+vacantX+COC=O<=>HX+O=COC[Pt]\n", - "kf = 8.724708246600757e-23\n", - "krev = 252.56605644619947\n", - "Kc = 3.454426287270814e-25\n", - "vacantX+vacantX+COC=O<=>HX+COC(=O)[Pt]\n", - "kf = 7.165711269221808e-16\n", - "krev = 0.1859922027934253\n", - "Kc = 3.852694447186316e-15\n", - "proton+O=COCC#[Pt]<=>CX+COC=O\n", - "kf = 105.5087249891725\n", - "krev = 9.918244171872598e-12\n", - "Kc = 1.063784306585105e13\n", - "HOX+C=C=O<=>O=C([Pt])CO\n", - "kf = 3.3473534940386794e-8\n", - "krev = 9.042590347389556e-30\n", - "Kc = 3.70176394754519e21\n", - "HX+O=C=CO<=>O=C([Pt])CO\n", - "kf = 2.8488442036348548e-8\n", - "krev = 1.614840618256874e-45\n", - "Kc = 1.7641643214981894e37\n", - "vacantX+vacantX+COO<=>HOX+CO[Pt]\n", - "kf = 3.442529358831723e8\n", - "krev = 2.6586367586035048e-11\n", - "Kc = 1.294847574679578e19\n", - "vacantX+vacantX+COO<=>HX+OOC[Pt]\n", - "kf = 1.3336211820914592e-23\n", - "krev = 16620.58178963317\n", - "Kc = 8.023913957833202e-28\n", - "CHOX+C=C=O<=>O=CCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 2.6714659015861004e-16\n", - "Kc = 1.2530025152300434e8\n", - "vacantX+vacantX+CO-2<=>HX+CO[Pt]\n", - "kf = 3.6896065237788346e-26\n", - "krev = 1200.2597905170037\n", - "Kc = 3.0740066050113714e-29\n", - "vacantX+vacantX+CO-2<=>HX+OC[Pt]\n", - "kf = 1.1691860289045307e-22\n", - "krev = 1.716447494000275\n", - "Kc = 6.811662069427353e-23\n", - "proton+OCO[Pt]<=>OX+CO-2\n", - "kf = 8.415426775358086e9\n", - "krev = 2.2521891994794312e-15\n", - "Kc = 3.736554094701821e24\n", - "proton+COC(=O)[Pt]<=>OCX+CO-2\n", - "kf = 2.5e10\n", - "krev = 3.535364355320737e-17\n", - "Kc = 7.071406929352247e26\n", - "proton+O=C([Pt])CO<=>OCX+CO-2\n", - "kf = 2.563914200342384e9\n", - "krev = 5.568313503115363e-15\n", - "Kc = 4.6044717110628266e23\n", - "proton+OCC#[Pt]<=>CX+CO-2\n", - "kf = 2.4021541557833424e-8\n", - "krev = 7.766959077565021e-8\n", - "Kc = 0.30927859047461714\n", - "vacantX+vacantX+COOC<=>CO[Pt]+CO[Pt]\n", - "kf = 3.028654941635431e8\n", - "krev = 1.0392777770118965e-11\n", - "Kc = 2.914191959673513e19\n", - "vacantX+vacantX+C=C=O<=>HX+O=C=C[Pt]\n", - "kf = 3.6584912239485734e-16\n", - "krev = 0.32395775785233605\n", - "Kc = 1.1293111942132156e-15\n", - "vacantX+vacantX+O=C=CO<=>HOX+O=C=C[Pt]\n", - "kf = 3.132095071630788e8\n", - "krev = 5.819571251914923e7\n", - "Kc = 5.382003133994065\n", - "proton+O=C=C[Pt]<=>C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.432948758337896e-37\n", - "Kc = 7.282369111767359e46\n", - "vacantX+vacantX+O=CCO<=>CHOX+OC[Pt]\n", - "kf = 9001.813049524091\n", - "krev = 8.180569891408677e12\n", - "Kc = 1.1003894800749632e-9\n", - "vacantX+vacantX+O=CCO<=>HX+O=CCO[Pt]\n", - "kf = 3.705974451661604e-28\n", - "krev = 2668.9209237076484\n", - "Kc = 1.3885665996103351e-31\n", - "vacantX+vacantX+O=CCO<=>HX+O=C([Pt])CO\n", - "kf = 1.2718474027465153e-10\n", - "krev = 0.0002705673832361486\n", - "Kc = 4.7006678614933393e-7\n", - "proton+O=CCOC#[Pt]<=>CX+O=CCO\n", - "kf = 5.011103886030472e-21\n", - "krev = 6.896680096586553e-19\n", - "Kc = 0.007265965386027795\n", - "proton+COC#[Pt]<=>CX+CO-2\n", - "kf = 4.64412268136931e-20\n", - "krev = 4.4743512788423464e-26\n", - "Kc = 1.0379432440474117e6\n", - "proton+O=CC(=O)C#[Pt]<=>CX+O=CC=O\n", - "kf = 7.775170632726667e-10\n", - "krev = 7.739686395050031e-10\n", - "Kc = 1.004584712592403\n", - "vacantX+vacantX+OCO<=>HOX+OC[Pt]\n", - "kf = 1.653107374238179e-12\n", - "krev = 3.492310477620836e11\n", - "Kc = 4.7335635958815765e-24\n", - "vacantX+vacantX+OCO<=>HX+OC(O)[Pt]\n", - "kf = 4.0412190145177725e-23\n", - "krev = 628.7683045605482\n", - "Kc = 6.427198993979533e-26\n", - "vacantX+vacantX+OCO<=>HX+OCO[Pt]\n", - "kf = 1.1281154422531313e-23\n", - "krev = 247.99076039714222\n", - "Kc = 4.5490220702034325e-26\n", - "proton+OC(O)C#[Pt]<=>CX+OCO\n", - "kf = 0.7216092218623162\n", - "krev = 1.1659522251493753e-8\n", - "Kc = 6.1890119191621915e7\n", - "proton+OCOC#[Pt]<=>CX+OCO\n", - "kf = 2.9829932789111093e-16\n", - "krev = 8.136723289652317e-19\n", - "Kc = 366.6086669930953\n", - "proton+O=COC=[Pt]<=>O=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.654502873565959e-54\n", - "Kc = 6.840875726444761e63\n", - "proton+O=COC=[Pt]<=>CHX+O=CO\n", - "kf = 5.289547656637059e7\n", - "krev = 2.1352018805017766e-40\n", - "Kc = 2.4773056379071775e47\n", - "proton+O=COC#[Pt]<=>O=COC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.12378969712814e-32\n", - "Kc = 2.2246155187120725e42\n", - "proton+O=C=CC#[Pt]<=>CX+C=C=O\n", - "kf = 1.6293289822172011e-13\n", - "krev = 7.740036852315493e-9\n", - "Kc = 2.1050661816032238e-5\n", - "vacantX+vacantX+COCO<=>CO[Pt]+OC[Pt]\n", - "kf = 3.0636862331912886e-9\n", - "krev = 3.008499680951675e11\n", - "Kc = 1.0183435459837431e-20\n", - "proton+CC#[Pt]<=>CX+CH4\n", - "kf = 4.11558111763413e-6\n", - "krev = 1.6637324348077724e-7\n", - "Kc = 24.73703722744123\n", - "HX+O=C=C=O<=>O=C=CO[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.1302052975227224e-55\n", - "Kc = 2.7224155607861307e47\n", - "proton+O=C=CO[Pt]<=>OX+C=C=O\n", - "kf = 6.172603247806586\n", - "krev = 1.291687223902065e-14\n", - "Kc = 4.778713556645498e14\n", - "proton+O=C=C=O.[Pt]<=>O=C=CO[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 7.969498365351247e-51\n", - "Kc = 6.273920604260804e60\n", - "vacantX+vacantX+O=C=CO<=>HX+O=C=CO[Pt]\n", - "kf = 0.0007071288662616175\n", - "krev = 2.8988454126647536e-5\n", - "Kc = 24.393465866522067\n", - "vacantX+vacantX+OCCO<=>OC[Pt]+OC[Pt]\n", - "kf = 2.961131444342359e-9\n", - "krev = 1.299206322752899e13\n", - "Kc = 2.2791849088819035e-22\n", - "proton+COC(=O)C#[Pt]<=>CX+COC=O\n", - "kf = 3.270015659434578e-8\n", - "krev = 1.7533480653497175e-11\n", - "Kc = 1865.0122722679996\n", - "proton+O=C=CC(=O)[Pt]<=>OCX+C=C=O\n", - "kf = 2.7877482479606147e9\n", - "krev = 8.98671268743291e-18\n", - "Kc = 3.1020778619739604e26\n", - "vacantX+vacantX+OC=CO<=>OC=[Pt]+OC=[Pt]\n", - "kf = 1.351949923589269e-23\n", - "krev = 7.975137957191956e11\n", - "Kc = 1.6952056890377485e-35\n", - "vacantX+OX+CH4<=>HOX+CH3X\n", - "kf = 1181.9069662995785\n", - "krev = 1.0235810933777192e20\n", - "Kc = 1.1546783874244874e-17\n", - "vacantX+HOX+CH4<=>H2OX+CH3X\n", - "kf = 5.28370763875636e9\n", - "krev = 1.2149259925984929e9\n", - "Kc = 4.348995470461149\n", - "HX+CH3X<=>vacantX+vacantX+CH4\n", - "kf = 5.733311120080377e8\n", - "krev = 8.483521653048543e-25\n", - "Kc = 6.758173497465076e32\n", - "proton+CH2X<=>CH3X\n", - "kf = 2.5e10\n", - "krev = 2.728240377953911e-36\n", - "Kc = 9.163415438763194e45\n", - "CO2+CH3X<=>COC(=O)[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.00447183609125585\n", - "Kc = 1.463156578060128e-5\n", - "vacantX+vacantX+COC=O<=>CHO2X+CH3X\n", - "kf = 0.05589950368763065\n", - "krev = 5.054770535995559e16\n", - "Kc = 1.1058761874463802e-18\n", - "vacantX+vacantX+COO<=>OO[Pt]+CH3X\n", - "kf = 9.385776922831516e-7\n", - "krev = 3.9782610412247473e11\n", - "Kc = 2.359266228528335e-18\n", - "vacantX+vacantX+CO-2<=>HOX+CH3X\n", - "kf = 9.872876935778847e-16\n", - "krev = 6.917821124819518e13\n", - "Kc = 1.427165686657795e-29\n", - "vacantX+vacantX+COCO<=>CH3X+OCO[Pt]\n", - "kf = 3.9072411322938125e-9\n", - "krev = 8.599564777209447e13\n", - "Kc = 4.543533578174534e-23\n", - "O=O+HX<=>OO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 8.854082166234876e-41\n", - "Kc = 8.666474551788235e32\n", - "vacantX+O=O<=>O=O.[Pt]\n", - "kf = 484458.3574999593\n", - "krev = 584.920039726471\n", - "Kc = 828.247152767255\n", - "vacantX+O=C=CO<=>O=C=CO.[Pt]\n", - "kf = 359723.7676387533\n", - "krev = 0.4900054095759742\n", - "Kc = 734122.0333670193\n", - "proton+O=C=CO.[Pt]<=>O=C([Pt])CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.450353404652874e-38\n", - "Kc = 4.586858528963997e47\n", - "proton+O=C=CO[Pt]<=>O=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.352118282059013e-11\n", - "Kc = 5.7443291702477246e20\n", - "vacantX+vacantX+O=C=C=O<=>OX+O=C=C=[Pt]\n", - "kf = 149.2804601441562\n", - "krev = 1.2008902564793325e-12\n", - "Kc = 1.2430816166483347e14\n", - "proton+O=C=C=[Pt]<=>O=CC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.002571023024303106\n", - "Kc = 9.723755782691377e12\n", - "proton+O=C=C=[Pt]<=>O=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.1152446342994757e-23\n", - "Kc = 1.181896391302251e33\n", - "vacantX+vacantX+C=CO<=>CH2X+OC=[Pt]\n", - "kf = 3.7510196251812924e-36\n", - "krev = 6.624293894020312e13\n", - "Kc = 5.662519938264367e-50\n", - "proton+O=C(C#[Pt])CO<=>CX+O=CCO\n", - "kf = 2.7439565220867836e-15\n", - "krev = 5.60405879527954e-7\n", - "Kc = 4.896373543400539e-9\n", - "vacantX+vacantX+C=C<=>CH2X+CH2X\n", - "kf = 9.387035392806688e-46\n", - "krev = 5.259242712748897e15\n", - "Kc = 1.784864457776713e-61\n", - "proton+O=COC[Pt]<=>COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.1027992925080103e-36\n", - "Kc = 2.266958291489692e46\n", - "proton+COC(=O)[Pt]<=>COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.2299433704122521e-26\n", - "Kc = 2.032613907388314e36\n", - "vacantX+COC=O<=>COC=O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.8619443782965007\n", - "Kc = 410274.8449265323\n", - "HX+O=C=C=C=O<=>O=C=CC(=O)[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 3.561089909521239e-25\n", - "Kc = 1.4777843564830474e17\n", - "vacantX+vacantX+O=C=C=C=O<=>OCX+O=C=C=[Pt]\n", - "kf = 135.4631249389026\n", - "krev = 3.092595390223456e6\n", - "Kc = 4.3802407960361956e-5\n", - "CH3X+O=C=C=O<=>CC(=O)C(=O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 3.5093718907449027e-71\n", - "Kc = 1.6525190917893694e63\n", - "proton+OOC#[Pt]<=>OO+CX\n", - "kf = 5.136678216751685e-50\n", - "krev = 2.063334055048756\n", - "Kc = 2.489503919243124e-50\n", - "proton+O=CC[Pt]<=>CH2X+C=O\n", - "kf = 1.277565794776397e-10\n", - "krev = 3.752447070055582e-7\n", - "Kc = 0.0003404620427484067\n", - "HX+C=C=O<=>O=CC[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 3.6888123831707493e-19\n", - "Kc = 9.074339235332521e10\n", - "proton+C=C=O.[Pt]<=>O=CC[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 0.06219023230090054\n", - "Kc = 4.0199238811394476e11\n", - "vacantX+vacantX+O=CCO<=>HOX+O=CC[Pt]\n", - "kf = 3.3834985622063113e-5\n", - "krev = 2.9362980773683545e12\n", - "Kc = 1.1523007790948657e-17\n", - "vacantX+vacantX+O=CC=O<=>OX+O=CC=[Pt]\n", - "kf = 6.170227811474367e-18\n", - "krev = 2.1467268001769245e15\n", - "Kc = 2.874249210922341e-33\n", - "proton+O=CC=[Pt]<=>CHX+C=O\n", - "kf = 45.65094374677705\n", - "krev = 8.967858326569276e-10\n", - "Kc = 5.0905067948638275e10\n", - "proton+O=CC#[Pt]<=>O=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.1079184319144836e-21\n", - "Kc = 2.2564838060144904e31\n", - "proton+O=C=C[Pt]<=>O=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.13466450883801714\n", - "Kc = 1.8564653906005447e11\n", - "proton+O=CC=[Pt]<=>O=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.585390854652908e-37\n", - "Kc = 1.576898209462252e47\n", - "proton+O=CCO[Pt]<=>OX+CC=O\n", - "kf = 1.4120852874068921e7\n", - "krev = 3.000260496950355e-29\n", - "Kc = 4.706542278052925e35\n", - "vacantX+vacantX+CC=O<=>HX+CC(=O)[Pt]\n", - "kf = 4.3209399543319175e-11\n", - "krev = 0.0003615296985530135\n", - "Kc = 1.195182573278502e-7\n", - "proton+O=CCC(=O)[Pt]<=>OCX+CC=O\n", - "kf = 9.552144537727627e8\n", - "krev = 4.245639842324063e-20\n", - "Kc = 2.2498716076912407e28\n", - "proton+O=CCC#[Pt]<=>CX+CC=O\n", - "kf = 15.24168336652918\n", - "krev = 2.925086878294221e-11\n", - "Kc = 5.2106771527474915e11\n", - "vacantX+vacantX+CC=O<=>CHOX+CH3X\n", - "kf = 6.063283190982672e-6\n", - "krev = 7.026751658283665e14\n", - "Kc = 8.628856526948432e-21\n", - "proton+CC(=O)C#[Pt]<=>CX+CC=O\n", - "kf = 1.0700076742100442e-15\n", - "krev = 2.910581039741659e-8\n", - "Kc = 3.67626827633364e-8\n", - "proton+CC(=O)C(=O)[Pt]<=>OCX+CC=O\n", - "kf = 4.440492535767249e9\n", - "krev = 9.213887643325446e-17\n", - "Kc = 4.819347389138122e25\n", - "vacantX+vacantX+CC=O<=>HX+O=CC[Pt]\n", - "kf = 3.2094062904328744e-20\n", - "krev = 74.41720028073364\n", - "Kc = 4.312721089110603e-22\n", - "vacantX+CH4<=>C.[Pt]\n", - "kf = 11983.404197457203\n", - "krev = 27576.843954134933\n", - "Kc = 0.4345458899280744\n", - "proton+CH3X<=>C.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.459954780972869e-39\n", - "Kc = 5.605437998307831e48\n", - "HX+O=C=CC=O<=>O=CCC(=O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 3.8194581898791103e-32\n", - "Kc = 6.789235995427004e23\n", - "vacantX+vacantX+O=C=CC=O<=>CHOX+O=C=C[Pt]\n", - "kf = 2.850945414803626e8\n", - "krev = 4.6591458607721776e7\n", - "Kc = 6.119030182779314\n", - "vacantX+vacantX+O=C=CC=O<=>HX+O=C=CC(=O)[Pt]\n", - "kf = 1.1776167531898308e-10\n", - "krev = 0.0005032011998508361\n", - "Kc = 2.3402502886298994e-7\n", - "vacantX+vacantX+O=C=CC=O<=>OCX+O=CC=[Pt]\n", - "kf = 0.006845452357086415\n", - "krev = 1.638610749190394e14\n", - "Kc = 4.177595173514284e-17\n", - "vacantX+vacantX+C=C(O)O<=>CH2X+OC(O)=[Pt]\n", - "kf = 1.3631835715271243e-51\n", - "krev = 1.0974745099569602e16\n", - "Kc = 1.242109551665655e-67\n", - "proton+O=C=CC=O.[Pt]<=>O=CCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.1640600284881483e-24\n", - "Kc = 1.1552359764005922e34\n", - "proton+O=C=CC(=O)[Pt]<=>O=C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.732517656232023e-19\n", - "Kc = 9.149071715230376e28\n", - "vacantX+O=C=CC=O<=>O=C=CC=O.[Pt]\n", - "kf = 327433.4917974331\n", - "krev = 0.29189612518083846\n", - "Kc = 1.1217466199476891e6\n", - "vacantX+vacantX+CC(=O)O<=>HOX+CC(=O)[Pt]\n", - "kf = 3.661873055903852e-12\n", - "krev = 2.1682718089028445e11\n", - "Kc = 1.6888441019563762e-23\n", - "vacantX+vacantX+CC(=O)O<=>CO2HX+CH3X\n", - "kf = 1.1977509649486271e-8\n", - "krev = 1.0254845667743408e14\n", - "Kc = 1.1679853639496008e-22\n", - "CO2+CH3X<=>CC(=O)O[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 3.3286101924403974e-7\n", - "Kc = 0.19656841788766613\n", - "proton+CC(=O)O[Pt]<=>OX+CC=O\n", - "kf = 0.000861247081568792\n", - "krev = 5.418955290289518e-14\n", - "Kc = 1.5893230990705927e10\n", - "vacantX+vacantX+CC(=O)O<=>HX+CC(=O)O[Pt]\n", - "kf = 2.4753542791841756e-22\n", - "krev = 11382.562807978633\n", - "Kc = 2.1746897609465158e-26\n", - "proton+CC(=O)OC#[Pt]<=>CX+CC(=O)O\n", - "kf = 2.5e10\n", - "krev = 5.708424354052639e-26\n", - "Kc = 4.379492211760938e35\n", - "vacantX+vacantX+CC(=O)C=O<=>CHOX+CC(=O)[Pt]\n", - "kf = 2.810784197367395e8\n", - "krev = 8.682228189641076\n", - "Kc = 3.237399589106622e7\n", - "vacantX+vacantX+CC(=O)C=O<=>CH3X+O=CC(=O)[Pt]\n", - "kf = 0.010756441693245073\n", - "krev = 2.0353876594794328e15\n", - "Kc = 5.284714016589902e-18\n", - "vacantX+vacantX+CC(=O)C=O<=>HX+CC(=O)C(=O)[Pt]\n", - "kf = 2.426386880233808e-11\n", - "krev = 0.0003222108693910823\n", - "Kc = 7.530431499158364e-8\n", - "proton+O=C=C([Pt])C=O<=>C=O+O=C=C=[Pt]\n", - "kf = 1.7265852223755207e6\n", - "krev = 2.1173801346453913e-15\n", - "Kc = 8.15434694094115e20\n", - "HX+O=C=C=C=O<=>O=C=C([Pt])C=O\n", - "kf = 5.262522960320117e-8\n", - "krev = 8.417963556232881e-20\n", - "Kc = 6.251539253129229e11\n", - "vacantX+vacantX+O=C=CC=O<=>HX+O=C=C([Pt])C=O\n", - "kf = 3.109950102720783e-13\n", - "krev = 0.31413419650430946\n", - "Kc = 9.900068624582613e-13\n", - "proton+O=C=C([Pt])C=O<=>O=C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.1559495343730438e-24\n", - "Kc = 2.162724172345407e34\n", - "proton+O=C=COC#[Pt]<=>CX+O=C=CO\n", - "kf = 4.324230983561045e-22\n", - "krev = 1.3691212371032431e-19\n", - "Kc = 0.003158398881248938\n", - "vacantX+vacantX+COC(C)=O<=>CO[Pt]+CC(=O)[Pt]\n", - "kf = 6.614441053978493e-6\n", - "krev = 7.629970776987544e11\n", - "Kc = 8.669025409544227e-18\n", - "vacantX+vacantX+COC(C)=O<=>CH3X+COC(=O)[Pt]\n", - "kf = 1.5563360867242215e-10\n", - "krev = 4.0343976517667425e14\n", - "Kc = 3.857666549162974e-25\n", - "vacantX+vacantX+COC(C)=O<=>CH3X+CC(=O)O[Pt]\n", - "kf = 0.0003463783354588583\n", - "krev = 6.683486846094463e16\n", - "Kc = 5.182599194629471e-21\n", - "vacantX+vacantX+COO<=>HX+COO[Pt]\n", - "kf = 1.175900379595729e-21\n", - "krev = 0.27982743013843664\n", - "Kc = 4.2022341377111815e-21\n", - "proton+COO[Pt]<=>OX+CO-2\n", - "kf = 16837.01815689783\n", - "krev = 6.867163373297897e-65\n", - "Kc = 2.4518155811417657e68\n", - "vacantX+vacantX+COOC<=>CH3X+COO[Pt]\n", - "kf = 1.8186835430204133e-8\n", - "krev = 4.141977957602716e12\n", - "Kc = 4.39085760869917e-21\n", - "O=O+CH3X<=>COO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 4.970959816815508e-38\n", - "Kc = 1.543639067721808e30\n", - "proton+CO[Pt]<=>CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.781216654859147e-34\n", - "Kc = 2.846985899860024e43\n", - "proton+OC[Pt]<=>CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.945821466805435e-27\n", - "Kc = 1.2848044091652411e37\n", - "vacantX+CO-2<=>CO.[Pt]\n", - "kf = 484125.61468448705\n", - "krev = 1.0558750276780043e7\n", - "Kc = 0.04585065485913965\n", - "vacantX+vacantX+CC(=O)CO<=>OC[Pt]+CC(=O)[Pt]\n", - "kf = 4.324183911493771e7\n", - "krev = 7.8667392573421875e12\n", - "Kc = 5.496793232924203e-6\n", - "vacantX+vacantX+CC(=O)CO<=>CH3X+O=C([Pt])CO\n", - "kf = 0.43146252134138535\n", - "krev = 2.5450806210309695e15\n", - "Kc = 1.695280368629765e-16\n", - "HX+O=C=C=O<=>O=C=C(O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 7.390785994602033e-44\n", - "Kc = 7.846667531546056e35\n", - "proton+O=C=C=O.[Pt]<=>O=C=C(O)[Pt]\n", - "kf = 5.0e10\n", - "krev = 2.765031941810381e-39\n", - "Kc = 1.8082973742163328e49\n", - "vacantX+vacantX+O=C=CO<=>HX+O=C=C(O)[Pt]\n", - "kf = 2.8707175642480555e-12\n", - "krev = 0.04083063397693327\n", - "Kc = 7.030793511239207e-11\n", - "proton+O=C=C(O)[Pt]<=>O=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.2543869389072832e-22\n", - "Kc = 1.9930054454949844e32\n", - "proton+O=C=C(O)[Pt]<=>H2O+O=C=C=[Pt]\n", - "kf = 1.5989383651417568e8\n", - "krev = 5.387605632290379e-38\n", - "Kc = 2.967808845470406e45\n", - "vacantX+vacantX+O=CCC=O<=>HX+O=CCC(=O)[Pt]\n", - "kf = 3.286584099620913e-11\n", - "krev = 0.0009472638388816695\n", - "Kc = 3.469555117295539e-8\n", - "vacantX+vacantX+O=CCC=O<=>CHOX+O=CC[Pt]\n", - "kf = 5.621568394735124e8\n", - "krev = 2.2372815421494465e13\n", - "Kc = 2.51267812692642e-5\n", - "proton+O=C=C(O)C#[Pt]<=>CX+O=C=CO\n", - "kf = 4.008872108623533e-29\n", - "krev = 0.04458949177209046\n", - "Kc = 8.990620770279273e-28\n", - "proton+COOC#[Pt]<=>CX+COO\n", - "kf = 9.541010615775616e-58\n", - "krev = 6.285347549669836e9\n", - "Kc = 1.5179766179002778e-67\n", - "vacantX+vacantX+COC=C=O<=>CO[Pt]+O=C=C[Pt]\n", - "kf = 1.4053920986837533e8\n", - "krev = 2.5815645207863396e8\n", - "Kc = 0.5443954963619013\n", - "vacantX+vacantX+COC=C=O<=>CH3X+O=C=CO[Pt]\n", - "kf = 1.4053920986837533e8\n", - "krev = 1.2268284001067661e8\n", - "Kc = 1.1455490421981163\n", - "HX+O=CC=O<=>O=CC(O)[Pt]\n", - "kf = 5.6976884072695144e-8\n", - "krev = 1.248882373151946e-25\n", - "Kc = 4.562229822244678e17\n", - "proton+O=CC(O)[Pt]<=>C=O+OC=[Pt]\n", - "kf = 1.9433361133957645e-7\n", - "krev = 3.518243282535333e-12\n", - "Kc = 55235.97879210185\n", - "proton+O=CC=O.[Pt]<=>O=CC(O)[Pt]\n", - "kf = 5.0e10\n", - "krev = 6.440846716581066e-18\n", - "Kc = 7.762954499643958e27\n", - "HX+O=C=CO<=>O=CC(O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 2.6755933088589045e-38\n", - "Kc = 1.0647523277182356e30\n", - "vacantX+vacantX+O=CCO<=>HX+O=CC(O)[Pt]\n", - "kf = 5.743984385098034e-15\n", - "krev = 0.20246227896672986\n", - "Kc = 2.8370639777506056e-14\n", - "proton+O=C=CO.[Pt]<=>O=CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 9.030568673797047e-31\n", - "Kc = 2.7683749388385245e40\n", - "proton+O=CC(O)[Pt]<=>H2O+O=CC=[Pt]\n", - "kf = 59626.15667838481\n", - "krev = 5.052054449161558e-13\n", - "Kc = 1.1802358283822616e17\n", - "proton+O=CC(O)C#[Pt]<=>CX+O=CCO\n", - "kf = 27.216448700907318\n", - "krev = 1.122343511964246e-9\n", - "Kc = 2.4249660118117508e10\n", - "vacantX+vacantX+O=C=CCO<=>OC[Pt]+O=C=C[Pt]\n", - "kf = 4067.906517801298\n", - "krev = 9.581534474143486e11\n", - "Kc = 4.245568941779481e-9\n", - "proton+O=CC(=O)[Pt]<=>O=CC(O)=[Pt]\n", - "kf = 1210.7940477205082\n", - "krev = 2.947449197084421e11\n", - "Kc = 4.107938650539627e-9\n", - "proton+O=CC(O)=[Pt]<=>OC#[Pt]+C=O\n", - "kf = 4.4806064283670194e7\n", - "krev = 9.647714416341851e-27\n", - "Kc = 4.6442154431701585e33\n", - "proton+O=CC(O)=[Pt]<=>H2O+O=CC#[Pt]\n", - "kf = 1.4211346889283953e7\n", - "krev = 2.9898684736722955e-43\n", - "Kc = 4.753167911707138e49\n", - "proton+O=C=C(O)[Pt]<=>O=CC(O)=[Pt]\n", - "kf = 4.481316095514531e9\n", - "krev = 7.381060539485826\n", - "Kc = 6.07137154822294e8\n", - "proton+O=CC(O)=[Pt]<=>O=CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.751017958044156e-54\n", - "Kc = 9.087545185555175e63\n", - "proton+OC(O)[Pt]<=>OCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.522467022601021e-34\n", - "Kc = 1.6420716921204226e44\n", - "proton+OCO[Pt]<=>OCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0775667741820985e-34\n", - "Kc = 2.3200418386114085e44\n", - "vacantX+OCO<=>OCO.[Pt]\n", - "kf = 395377.4080430906\n", - "krev = 715.0601225795458\n", - "Kc = 552.9289014422803\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 7.340819523839582e-21\n", - "Kc = 3.405614307613962e30\n", - "vacantX+O=C=C=C=O<=>O=C=C=C=O.[Pt]\n", - "kf = 332249.5811031886\n", - "krev = 401.14766551623046\n", - "Kc = 828.2475748067037\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.735276356245465e-15\n", - "Kc = 1.4406927121447852e25\n", - "proton+O=CCO[Pt]<=>O=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.64244938326729e-40\n", - "Kc = 3.7636718863039337e49\n", - "proton+O=C([Pt])CO<=>O=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.2486460747567866e-15\n", - "Kc = 1.1117801187411852e25\n", - "vacantX+O=CCO<=>O=CCO.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 1291.5767888759226\n", - "Kc = 273.8002875141987\n", - "proton+O=CC(O)[Pt]<=>O=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3571588049567083e-22\n", - "Kc = 1.842083616795123e32\n", - "proton+OCC#[Pt]<=>OCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.287360377049269e-14\n", - "Kc = 1.9419581684890723e24\n", - "proton+OCC=[Pt]<=>CHX+CO-2\n", - "kf = 3.162060147889592e9\n", - "krev = 1.6872184207187113e-17\n", - "Kc = 1.8741261410260308e26\n", - "vacantX+vacantX+O=CCO<=>OX+OCC=[Pt]\n", - "kf = 3.3881471741726223e-34\n", - "krev = 2.264159139077055e16\n", - "Kc = 1.4964262518904662e-50\n", - "vacantX+vacantX+O=C=CCO<=>OCX+OCC=[Pt]\n", - "kf = 1.8009876630720204e-13\n", - "krev = 6.668943472119082e14\n", - "Kc = 2.7005591974222413e-28\n", - "vacantX+vacantX+C=CC=O<=>CH2X+O=CC=[Pt]\n", - "kf = 3.2830355290077765e-39\n", - "krev = 2.9277080237249806e14\n", - "Kc = 1.121367124864694e-53\n", - "vacantX+vacantX+C=COC=O<=>CH2X+O=COC=[Pt]\n", - "kf = 1.0242943870290668e-63\n", - "krev = 2.920849603333263e13\n", - "Kc = 3.5068371403311754e-77\n", - "vacantX+O=C=CCO<=>O=C=CCO.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 1179.037991138623\n", - "Kc = 273.8002884035305\n", - "vacantX+vacantX+O=CC=CO<=>OC=[Pt]+O=CC=[Pt]\n", - "kf = 6.284377773759944e-35\n", - "krev = 2.1623088290446475e12\n", - "Kc = 2.90632757418676e-47\n", - "vacantX+vacantX+COC<=>CH3X+CO[Pt]\n", - "kf = 3.3416169046706564e-11\n", - "krev = 3.110510590664853e12\n", - "Kc = 1.0742985137872191e-23\n", - "proton+O=C=CC(O)[Pt]<=>OC=[Pt]+C=C=O\n", - "kf = 1.0231284428350907e-6\n", - "krev = 5.347289159896318e-14\n", - "Kc = 1.9133591100858454e7\n", - "HX+O=C=CC=O<=>O=C=CC(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 3.0624966294759025e-24\n", - "Kc = 8.467340919226885e15\n", - "proton+O=C=CC=O.[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.7351745231274126e-16\n", - "Kc = 1.4407772628508256e26\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=CC(O)[Pt]\n", - "kf = 2.2665619116480148e-11\n", - "krev = 0.03466826587817799\n", - "Kc = 6.537857761944495e-10\n", - "proton+O=C=CC(O)[Pt]<=>O=C=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.127497746946197e-18\n", - "Kc = 7.993610874511712e27\n", - "proton+O=C=CC=[Pt]<=>CHX+C=C=O\n", - "kf = 23528.318259479824\n", - "krev = 3.804584505072925e-13\n", - "Kc = 6.184201777646898e16\n", - "proton+O=C=CC#[Pt]<=>O=C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.241214001168533e-20\n", - "Kc = 4.0056309550224184e29\n", - "vacantX+vacantX+O=C=CC=O<=>OX+O=C=CC=[Pt]\n", - "kf = 3.709849833927781e-21\n", - "krev = 2.4389911159903437e17\n", - "Kc = 1.5210591828750508e-38\n", - "proton+O=C=CC(O)[Pt]<=>H2O+O=C=CC=[Pt]\n", - "kf = 609.0850331655664\n", - "krev = 1.809911455986725e-11\n", - "Kc = 3.3652753075343477e13\n", - "vacantX+vacantX+CCO<=>CH3X+OC[Pt]\n", - "kf = 1.5510087911871897e-15\n", - "krev = 9.749013808701775e13\n", - "Kc = 1.5909391674086975e-29\n", - "proton+O=C=C([Pt])CO<=>CO-2+O=C=C=[Pt]\n", - "kf = 3.3619651735570975e7\n", - "krev = 2.294747094683907e-27\n", - "Kc = 1.465070020720604e34\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=C([Pt])CO\n", - "kf = 4.040764431615523e-20\n", - "krev = 30.812673220085827\n", - "Kc = 1.3113969056672023e-21\n", - "proton+O=C=C([Pt])CO<=>O=C=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.2732947353179126e-30\n", - "Kc = 3.985146729875919e39\n", - "proton+O=C=CC[Pt]<=>CH2X+C=C=O\n", - "kf = 7.803274248124281e-6\n", - "krev = 4.005137429327759e-12\n", - "Kc = 1.9483162277989595e6\n", - "vacantX+vacantX+O=C=CCO<=>HOX+O=C=CC[Pt]\n", - "kf = 8.032715739528718e-6\n", - "krev = 4.997427676480693e14\n", - "Kc = 1.6073700830795308e-20\n", - "proton+O=C=CC=[Pt]<=>O=C=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.4680026972653605e-34\n", - "Kc = 3.347615287974457e43\n", - "vacantX+vacantX+CC(O)O<=>CH3X+OC(O)[Pt]\n", - "kf = 1.0212279299691738e-21\n", - "krev = 4.839386960246169e15\n", - "Kc = 2.1102423475497943e-37\n", - "proton+O=C=CC(O)=[Pt]<=>OC#[Pt]+C=C=O\n", - "kf = 1.958692755771878e8\n", - "krev = 1.5396661662617642e-23\n", - "Kc = 1.272154184258975e31\n", - "proton+O=C=CC(O)=[Pt]<=>H2O+O=C=CC#[Pt]\n", - "kf = 7.529508093382038e8\n", - "krev = 1.2471462888159226e-34\n", - "Kc = 6.037389647794065e42\n", - "proton+O=C=CC(=O)[Pt]<=>O=C=CC(O)=[Pt]\n", - "kf = 3.941830019983858e7\n", - "krev = 2.1489363690309378e11\n", - "Kc = 0.0001834316770282698\n", - "proton+O=C=CC(O)=[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.4788881606878414e-49\n", - "Kc = 7.186203995433136e58\n", - "C=O+O=C=C[Pt]<=>O=C=CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 80798.59947863563\n", - "Kc = 4.901904683810505e-13\n", - "HX+O=C=CC=O<=>O=C=CCO[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 2.019947796444839e-5\n", - "Kc = 0.0012837560986177624\n", - "proton+O=C=CC=O.[Pt]<=>O=C=CCO[Pt]\n", - "kf = 4.688885919704075e6\n", - "krev = 0.21465318980713355\n", - "Kc = 2.1844007647485003e7\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=CCO[Pt]\n", - "kf = 7.342900678318069e-26\n", - "krev = 740.7927312780465\n", - "Kc = 9.912220204496055e-29\n", - "proton+O=C=CCO[Pt]<=>O=C=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.741682594755e-37\n", - "Kc = 5.272390021983691e46\n", - "vacantX+vacantX+CCOC=O<=>CH3X+O=COC[Pt]\n", - "kf = 1.714178070740009e-17\n", - "krev = 1.2983121019578911e14\n", - "Kc = 1.3203127877765141e-31\n", - "proton+O=CC([Pt])C=O<=>C=O+O=CC=[Pt]\n", - "kf = 1.3144481008935517e-8\n", - "krev = 1.352598964325052e-13\n", - "Kc = 97179.44014170248\n", - "HX+O=C=CC=O<=>O=CC([Pt])C=O\n", - "kf = 2.5931203025755725e-8\n", - "krev = 5.183135272095574e-24\n", - "Kc = 5.002995612590211e15\n", - "proton+O=C=CC=O.[Pt]<=>O=CC([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.9367034031976796e-16\n", - "Kc = 8.512946854891207e25\n", - "vacantX+vacantX+O=CCC=O<=>HX+O=CC([Pt])C=O\n", - "kf = 6.269624738894468e-15\n", - "krev = 24.522149705338403\n", - "Kc = 2.556719053684591e-16\n", - "proton+O=CC(=[Pt])C=O<=>C=O+O=CC#[Pt]\n", - "kf = 5.451669985706379\n", - "krev = 9.628263387104526e-16\n", - "Kc = 5.662152941316492e15\n", - "proton+O=C=C([Pt])C=O<=>O=CC(=[Pt])C=O\n", - "kf = 2.5e10\n", - "krev = 1.785247265622252e-8\n", - "Kc = 1.4003662395352387e18\n", - "proton+O=CC(=[Pt])C=O<=>O=CC([Pt])C=O\n", - "kf = 2.5e10\n", - "krev = 1.9015186281967622e-32\n", - "Kc = 1.3147386320221257e42\n", - "vacantX+vacantX+COCC=O<=>CH3X+O=CCO[Pt]\n", - "kf = 1.7650043109029407e-12\n", - "krev = 1.4735149295451475e13\n", - "Kc = 1.1978190892492496e-25\n", - "vacantX+vacantX+COCC=O<=>CO[Pt]+O=CC[Pt]\n", - "kf = 10.947009513309483\n", - "krev = 5.112987413682155e11\n", - "Kc = 2.1410202348661592e-11\n", - "proton+O=CCC(=O)[Pt]<=>O=CCC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.3281787530995323e-14\n", - "Kc = 1.0738007108224487e24\n", - "vacantX+O=CCC=O<=>O=CCC=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 165389.8266532618\n", - "Kc = 1.951879075907524\n", - "proton+O=CC([Pt])C=O<=>O=CCC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.715637531959152e-22\n", - "Kc = 1.4571842556656794e32\n", - "proton+O=CCC#[Pt]<=>O=CCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.130905447828635e-25\n", - "Kc = 1.1732101968895276e35\n", - "proton+O=CCC=[Pt]<=>CHX+CC=O\n", - "kf = 1.3759337537057946e9\n", - "krev = 2.6326332155148577e-19\n", - "Kc = 5.226454431999965e27\n", - "vacantX+vacantX+O=CCC=O<=>OX+O=CCC=[Pt]\n", - "kf = 1.2771337705277995e-31\n", - "krev = 6.599290845791489e16\n", - "Kc = 1.935259106426951e-48\n", - "vacantX+vacantX+CCOO<=>CH3X+OOC[Pt]\n", - "kf = 1.1728434846364774e-18\n", - "krev = 2.6840450809869076e16\n", - "Kc = 4.3696862356918e-35\n", - "proton+OOCC#[Pt]<=>CX+COO\n", - "kf = 32.04286700116282\n", - "krev = 1.9859440346373588e-10\n", - "Kc = 1.61348287979394e11\n", - "vacantX+vacantX+C=C=O<=>OX+C=C=[Pt]\n", - "kf = 5.2796000958546504e-37\n", - "krev = 1.4614931014553018e17\n", - "Kc = 3.612470076387919e-54\n", - "proton+C=C=[Pt]<=>CC#[Pt]\n", - "kf = 180747.02922982755\n", - "krev = 2.4491522098934374e-37\n", - "Kc = 7.379983510199714e41\n", - "vacantX+vacantX+CC(C)=O<=>CH3X+CC(=O)[Pt]\n", - "kf = 0.0015322757193851075\n", - "krev = 1.9084257758101816e14\n", - "Kc = 8.029003479239911e-18\n", - "vacantX+vacantX+C=C=C=O<=>CH2X+O=C=C=[Pt]\n", - "kf = 0.014873013888318402\n", - "krev = 6.520037160662236e15\n", - "Kc = 2.2811240981957472e-18\n", - "HOX+C=C=C=O<=>O=C=C([Pt])CO\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.9529365102554657e-31\n", - "Kc = 9.99708792916859e22\n", - "HX+C=C=C=O<=>O=C=CC[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.4091973858076736e-32\n", - "Kc = 1.225336127134283e24\n", - "vacantX+vacantX+C=C=C=O<=>OCX+C=C=[Pt]\n", - "kf = 0.8504584217531632\n", - "krev = 1.347597642765549e15\n", - "Kc = 6.310922450174717e-16\n", - "proton+O=C(O)C=[Pt]<=>CHX+O=CO\n", - "kf = 1.0224949765277231e10\n", - "krev = 9.139651486927123e-14\n", - "Kc = 1.1187461337997911e23\n", - "proton+O=C(O)C#[Pt]<=>O=C(O)C=[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.6210077020119595e-21\n", - "Kc = 9.538316114374366e30\n", - "vacantX+vacantX+CC=C=O<=>CH3X+O=C=C[Pt]\n", - "kf = 0.0008567749561878586\n", - "krev = 1.2359860589695025e13\n", - "Kc = 6.931914401220598e-17\n", - "vacantX+vacantX+CC=C=O<=>HX+O=C=CC[Pt]\n", - "kf = 2.2773385768535307e-19\n", - "krev = 181.8091471864856\n", - "Kc = 1.2525984594810374e-21\n", - "proton+O=C=CCO[Pt]<=>OX+CC=C=O\n", - "kf = 4.9314791816760385e8\n", - "krev = 1.5573633218480681e-21\n", - "Kc = 3.1665566489802946e29\n", - "proton+CC(=O)[Pt]<=>CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.95438690090272e-19\n", - "Kc = 2.511455526983069e28\n", - "proton+O=CC[Pt]<=>CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.5919612012855e-33\n", - "Kc = 6.95998609090013e42\n", - "vacantX+CC=O<=>CC=O.[Pt]\n", - "kf = 412885.969273148\n", - "krev = 2.625517699834265\n", - "Kc = 157258.8786200951\n", - "proton+CC=[Pt]<=>CHX+CH4\n", - "kf = 4.870524122777267e9\n", - "krev = 1.4627043997234466e-16\n", - "Kc = 3.3298075289157106e25\n", - "proton+CC#[Pt]<=>CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.8597141571613083e-17\n", - "Kc = 8.742132474112804e26\n", - "vacantX+vacantX+CC=O<=>OX+CC=[Pt]\n", - "kf = 6.186864182993887e-31\n", - "krev = 2.034915252803989e19\n", - "Kc = 3.04035471475717e-50\n", - "vacantX+vacantX+CC=C=O<=>OCX+CC=[Pt]\n", - "kf = 5.619880038277716e-8\n", - "krev = 4.919193785592355e16\n", - "Kc = 1.14243924578405e-24\n", - "vacantX+vacantX+CC<=>CH3X+CH3X\n", - "kf = 1.6866972609475142e-22\n", - "krev = 6.547125244410207e13\n", - "Kc = 2.576241018739606e-36\n", - "proton+O=C=CC[Pt]<=>CC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.405314737692951e-28\n", - "Kc = 2.974308610704312e37\n", - "vacantX+CC=C=O<=>CC=C=O.[Pt]\n", - "kf = 365995.57053717994\n", - "krev = 187509.1639624155\n", - "Kc = 1.9518809790573244\n", - "proton+O=C(O)C[Pt]<=>CH2X+O=CO\n", - "kf = 6.536709868845801e-7\n", - "krev = 3.607475609111285e-11\n", - "Kc = 18119.90038778431\n", - "HOX+C=C=O<=>O=C(O)C[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.348252838458729e-29\n", - "Kc = 4.5553052781738184e20\n", - "vacantX+vacantX+CC(=O)O<=>HX+O=C(O)C[Pt]\n", - "kf = 1.1112170024966995e-23\n", - "krev = 36323.66987445037\n", - "Kc = 3.0592090676342045e-28\n", - "proton+O=C(O)C=[Pt]<=>O=C(O)C[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.839307771146613e-42\n", - "Kc = 6.511590497610387e51\n", - "vacantX+vacantX+O=C=C=CO<=>OC=[Pt]+O=C=C=[Pt]\n", - "kf = 0.004371453552681894\n", - "krev = 1.2572855491392857e13\n", - "Kc = 3.476897953431907e-16\n", - "HX+O=C=C=CO<=>O=C=CC(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.3635197599529065e-33\n", - "Kc = 1.9017841755847633e25\n", - "HX+O=C=C=CO<=>O=C=C([Pt])CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 6.797711819853139e-22\n", - "Kc = 3.814695843684052e13\n", - "proton+O=C(O)CC#[Pt]<=>CX+CC(=O)O\n", - "kf = 16.31407647715237\n", - "krev = 4.543665668210859e-11\n", - "Kc = 3.5905098808857336e11\n", - "proton+CC([Pt])=C=O<=>CH4+O=C=C=[Pt]\n", - "kf = 6.42025766569729e6\n", - "krev = 5.830346192866458e-31\n", - "Kc = 1.1011794931753108e37\n", - "HX+C=C=C=O<=>CC([Pt])=C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.301177455844525e-32\n", - "Kc = 1.2828548214436644e24\n", - "vacantX+vacantX+CC=C=O<=>HX+CC([Pt])=C=O\n", - "kf = 4.581183222917958e-20\n", - "krev = 34.93361388628861\n", - "Kc = 1.3113968791863429e-21\n", - "proton+CC([Pt])=C=O<=>CC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.799869928114263e-28\n", - "Kc = 2.8409510827118884e37\n", - "CH3X+O=C=C=O<=>CC(=C=O)O[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.951682102619952e-64\n", - "Kc = 1.9647454732667077e56\n", - "proton+CC(=C=O)O[Pt]<=>OX+CC=C=O\n", - "kf = 0.00024916353007790583\n", - "krev = 2.3097496644853503e-11\n", - "Kc = 1.0787469045197308e7\n", - "vacantX+C=C<=>C=C.[Pt]\n", - "kf = 36.21750369826068\n", - "krev = 0.32335117013731834\n", - "Kc = 112.00671914340097\n", - "vacantX+vacantX+C=CO<=>HOX+C=C[Pt]\n", - "kf = 1.7018617233469498e-12\n", - "krev = 4.164837143763027e13\n", - "Kc = 4.086262354568991e-26\n", - "vacantX+vacantX+C=C<=>HX+C=C[Pt]\n", - "kf = 6.071347272542775e-23\n", - "krev = 1180.067101472276\n", - "Kc = 5.144916983930861e-26\n", - "vacantX+vacantX+C=CC=O<=>CHOX+C=C[Pt]\n", - "kf = 0.3274906030624493\n", - "krev = 2.9425898600264806e14\n", - "Kc = 1.1129332276687114e-15\n", - "vacantX+vacantX+C=COC=O<=>CHO2X+C=C[Pt]\n", - "kf = 0.2513917911405871\n", - "krev = 1.0405847657707406e16\n", - "Kc = 2.4158703779829617e-17\n", - "proton+C=C=[Pt]<=>C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.636533990647995e-42\n", - "Kc = 2.8946797438730698e51\n", - "proton+C=C[Pt]<=>CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.121676848269518e-7\n", - "Kc = 2.228805920222842e17\n", - "proton+C=C[Pt]<=>C=C.[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.016303466992672e-34\n", - "Kc = 4.155375495461265e43\n", - "proton+C=CC#[Pt]<=>CX+C=C\n", - "kf = 1.4084647229282898e-13\n", - "krev = 5.945859073264746e-8\n", - "Kc = 2.3688161888353193e-6\n", - "vacantX+CC(=O)O<=>CC(=O)O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 181176.05501028927\n", - "Kc = 1.9518809818483447\n", - "proton+CC(=O)O[Pt]<=>CC(=O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4592826402667932e-32\n", - "Kc = 1.7131705202379013e42\n", - "proton+O=C(O)C[Pt]<=>CC(=O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.0528218624629457e-34\n", - "Kc = 1.2178358218576924e44\n", - "proton+C=CC(=O)[Pt]<=>OCX+C=C\n", - "kf = 9.194493638543996e8\n", - "krev = 1.3639804620724132e-13\n", - "Kc = 6.74092767030842e21\n", - "vacantX+vacantX+C=CC=O<=>HX+C=CC(=O)[Pt]\n", - "kf = 3.052485738368744e-11\n", - "krev = 0.0007099643372969683\n", - "Kc = 4.29949164769375e-8\n", - "HX+C=C=C=O<=>C=CC(=O)[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 5.604440911093213e-48\n", - "Kc = 5.267388203494818e39\n", - "HX+O=C=CC=O<=>O=CC=CO[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 5.6159867257682645e-34\n", - "Kc = 4.61739037002591e25\n", - "proton+O=C=CC=O.[Pt]<=>O=CC=CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 3.181951939141392e-26\n", - "Kc = 7.856812572331283e35\n", - "proton+O=CC=CO[Pt]<=>OX+C=CC=O\n", - "kf = 4.75028668267054e-8\n", - "krev = 4.308357958526409e-11\n", - "Kc = 1102.5747462022132\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC=CO[Pt]\n", - "kf = 4.135805741920728e-10\n", - "krev = 0.028732529553568358\n", - "Kc = 1.4394158141245496e-8\n", - "HX+C=C=O<=>C=CO[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.272169613200064e-8\n", - "Kc = 0.46029640012283785\n", - "proton+C=C=O.[Pt]<=>C=CO[Pt]\n", - "kf = 0.4548020863581974\n", - "krev = 0.22303963782401687\n", - "Kc = 2.0391087915819077\n", - "vacantX+vacantX+C=CO<=>HX+C=CO[Pt]\n", - "kf = 1.5839272910037507e-20\n", - "krev = 3600.161649580889\n", - "Kc = 4.399600476795654e-24\n", - "proton+C=CO[Pt]<=>OX+C=C\n", - "kf = 8.684971623379145e8\n", - "krev = 1.9668877403064286e-15\n", - "Kc = 4.415590908114604e23\n", - "vacantX+vacantX+C=COC=O<=>CHOX+C=CO[Pt]\n", - "kf = 0.024290856013790354\n", - "krev = 3.5586883050271985e15\n", - "Kc = 6.825789148062155e-18\n", - "vacantX+vacantX+O=CCCO<=>OC[Pt]+O=CC[Pt]\n", - "kf = 2.162232232095232e-5\n", - "krev = 5.66671683371172e13\n", - "Kc = 3.815670158833332e-19\n", - "proton+C=COC(=O)[Pt]<=>OCX+C=CO\n", - "kf = 1.1089294417172325e9\n", - "krev = 2.3905126075631446e-16\n", - "Kc = 4.638877193990873e24\n", - "vacantX+vacantX+C=COC=O<=>HX+C=COC(=O)[Pt]\n", - "kf = 3.5117597357119104e-15\n", - "krev = 0.7837038908782975\n", - "Kc = 4.480977798612533e-15\n", - "CO2+C=C[Pt]<=>C=COC(=O)[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.08399332498323721\n", - "Kc = 7.789900440580834e-7\n", - "proton+C=COC#[Pt]<=>CX+C=CO\n", - "kf = 4.6616085133202476e-21\n", - "krev = 1.7198034057689652e-11\n", - "Kc = 2.7105473205153534e-10\n", - "vacantX+vacantX+CCC=O<=>CH3X+O=CC[Pt]\n", - "kf = 1.2257627381394946e-12\n", - "krev = 3.270257576074817e14\n", - "Kc = 3.748214657790771e-27\n", - "proton+CC(O)=[Pt]<=>OC#[Pt]+CH4\n", - "kf = 9.111664842232262e8\n", - "krev = 5.142811625352043e-10\n", - "Kc = 1.7717282891162747e18\n", - "proton+CC(=O)[Pt]<=>CC(O)=[Pt]\n", - "kf = 2.5e10\n", - "krev = 9007.024893837408\n", - "Kc = 2.7756112917046514e6\n", - "proton+CC(O)=[Pt]<=>H2O+CC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.493939353913987e-14\n", - "Kc = 7.155247263234393e23\n", - "vacantX+vacantX+CC(=O)O<=>OX+CC(O)=[Pt]\n", - "kf = 1.1829749543892744e-33\n", - "krev = 3.758913107590896e15\n", - "Kc = 3.1471197139415875e-49\n", - "vacantX+vacantX+CC(O)=C=O<=>CH3X+O=C=C(O)[Pt]\n", - "kf = 1.049990631922765e-6\n", - "krev = 1.7955210884029898e15\n", - "Kc = 5.847832357439309e-22\n", - "vacantX+vacantX+CC(O)=C=O<=>HOX+CC([Pt])=C=O\n", - "kf = 0.0029164033711847528\n", - "krev = 3.4437539939134434e12\n", - "Kc = 8.468675103794464e-16\n", - "vacantX+vacantX+CC(O)=C=O<=>HX+CC(=C=O)O[Pt]\n", - "kf = 1.7528367761452354e-6\n", - "krev = 1.1970864565480504e-5\n", - "Kc = 0.14642524494009906\n", - "vacantX+vacantX+CC(O)=C=O<=>OCX+CC(O)=[Pt]\n", - "kf = 65.80946386077328\n", - "krev = 1217.699742052305\n", - "Kc = 0.054044081301896585\n", - "vacantX+vacantX+C=CC=O<=>HX+O=CC=C[Pt]\n", - "kf = 6.342176392543457e-21\n", - "krev = 776.2437464870187\n", - "Kc = 8.170341366672147e-24\n", - "vacantX+vacantX+O=CC=CO<=>HOX+O=CC=C[Pt]\n", - "kf = 4.672349699632388e-15\n", - "krev = 8.81363422062413e13\n", - "Kc = 5.301274800693419e-29\n", - "proton+O=CC=C[Pt]<=>O=CCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.7537190144509203\n", - "Kc = 3.316885937687581e10\n", - "proton+C=CC(=O)O[Pt]<=>OX+C=CC=O\n", - "kf = 586.9890181697751\n", - "krev = 3.5182371632669316e-15\n", - "Kc = 1.668417991539588e17\n", - "CO2+C=C[Pt]<=>C=CC(=O)O[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 450683.30306117237\n", - "Kc = 1.4517947189269602e-13\n", - "vacantX+vacantX+O=C=CO<=>OX+OC=C=[Pt]\n", - "kf = 7.548264554696059e-34\n", - "krev = 5.749061160710156e15\n", - "Kc = 1.3129560364189368e-49\n", - "proton+OC=C=[Pt]<=>OCC#[Pt]\n", - "kf = 5.478042817438384\n", - "krev = 6.82639714107839e-51\n", - "Kc = 8.02479361253951e50\n", - "vacantX+vacantX+O=C=C=CO<=>OCX+OC=C=[Pt]\n", - "kf = 1.463392220587488e-22\n", - "krev = 7.968303762369095e13\n", - "Kc = 1.8365166090912173e-36\n", - "proton+CC[Pt]<=>CH2X+CH4\n", - "kf = 192.6103918491207\n", - "krev = 4.515166477555994e-12\n", - "Kc = 4.265853602664468e13\n", - "HX+C=C<=>CC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 3.1627439012977165e-12\n", - "Kc = 25911.109388377805\n", - "vacantX+vacantX+CCO<=>HOX+CC[Pt]\n", - "kf = 2.1035625708276702e-15\n", - "krev = 1.0019023766861524e15\n", - "Kc = 2.099568400850909e-30\n", - "vacantX+vacantX+CCOC=O<=>CHO2X+CC[Pt]\n", - "kf = 0.08561452397466171\n", - "krev = 3.215769317238553e17\n", - "Kc = 2.6623341268826044e-19\n", - "vacantX+vacantX+CCOO<=>OO[Pt]+CC[Pt]\n", - "kf = 1.262172875849309e-6\n", - "krev = 1.5596341944506717e13\n", - "Kc = 8.092749443044025e-20\n", - "proton+CC=[Pt]<=>CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.036795069902944e-35\n", - "Kc = 8.232363206780035e44\n", - "vacantX+vacantX+CC<=>HX+CC[Pt]\n", - "kf = 8.697106954471648e-14\n", - "krev = 5.359609736165605e16\n", - "Kc = 1.6227127314485718e-30\n", - "proton+C=C.[Pt]<=>CC[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 1.1323573491720412e-8\n", - "Kc = 4.415567226773338e18\n", - "vacantX+vacantX+CCC=O<=>CHOX+CC[Pt]\n", - "kf = 0.0004422945453165714\n", - "krev = 9.363325052982716e15\n", - "Kc = 4.723691026572629e-20\n", - "vacantX+vacantX+CC(O)C=O<=>CH3X+O=CC(O)[Pt]\n", - "kf = 9.477814531468979e-7\n", - "krev = 7.52142668687151e15\n", - "Kc = 1.2601086105129898e-22\n", - "proton+CCC#[Pt]<=>CX+CC\n", - "kf = 4.839333835070635e-9\n", - "krev = 3.439572341169614e-8\n", - "Kc = 0.14069580038037627\n", - "C=O+CH3X<=>CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.1808191230067762e-17\n", - "Kc = 3.354171909251678e9\n", - "HX+CC=O<=>CCO[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 2.639709061724686e-6\n", - "Kc = 0.012387213631168494\n", - "vacantX+vacantX+CCO<=>HX+CCO[Pt]\n", - "kf = 5.372480262216755e-24\n", - "krev = 2113.809062877283\n", - "Kc = 2.5416109508508876e-27\n", - "vacantX+vacantX+CCOC=O<=>CHOX+CCO[Pt]\n", - "kf = 4.80530366959931e-5\n", - "krev = 5.681813674074216e13\n", - "Kc = 8.457341168235823e-19\n", - "vacantX+vacantX+CCOO<=>HOX+CCO[Pt]\n", - "kf = 3.028654941635431e8\n", - "krev = 1.2132864881112858e-12\n", - "Kc = 2.496240559268171e20\n", - "proton+CC=O.[Pt]<=>CCO[Pt]\n", - "kf = 3.2683771317360777e8\n", - "krev = 0.21738478314597703\n", - "Kc = 1.5034985818401628e9\n", - "proton+CCO[Pt]<=>OX+CC\n", - "kf = 1.9694718683312347e9\n", - "krev = 1.5816714472418169e-18\n", - "Kc = 1.245183929801401e27\n", - "proton+CCOC(=O)[Pt]<=>OCX+CCO\n", - "kf = 2.5e10\n", - "krev = 3.6333074127753494e-17\n", - "Kc = 6.880783033138235e26\n", - "vacantX+vacantX+CCOC=O<=>HX+CCOC(=O)[Pt]\n", - "kf = 2.5742212027881315e-15\n", - "krev = 0.39729482671494754\n", - "Kc = 6.479372570927264e-15\n", - "CO2+CC[Pt]<=>CCOC(=O)[Pt]\n", - "kf = 3.860701485876577e-7\n", - "krev = 0.0037771400241392917\n", - "Kc = 0.00010221229451921966\n", - "CH3X+C=C=O<=>CCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.9339597186194493e-34\n", - "Kc = 1.7308289628845924e26\n", - "HX+CC=C=O<=>CCC(=O)[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 2.728234417234893e-33\n", - "Kc = 1.0624138213938816e25\n", - "proton+CCC(=O)[Pt]<=>OCX+CC\n", - "kf = 4.304987235328105e9\n", - "krev = 7.891318764743676e-17\n", - "Kc = 5.45534575863498e25\n", - "proton+CC=C=O.[Pt]<=>CCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.406329298480467e-31\n", - "Kc = 1.038926800907375e41\n", - "vacantX+vacantX+CCC=O<=>HX+CCC(=O)[Pt]\n", - "kf = 1.3037608552158366e-12\n", - "krev = 0.18236199715464047\n", - "Kc = 7.149301255514685e-12\n", - "vacantX+vacantX+C=C(O)C=O<=>CH2X+O=CC(O)=[Pt]\n", - "kf = 3.506980389191063e-59\n", - "krev = 1.6121784785918364e12\n", - "Kc = 2.1753053001019147e-71\n", - "proton+CCOC#[Pt]<=>CX+CCO\n", - "kf = 2.1281066335723717e-20\n", - "krev = 4.7998990065431355e-20\n", - "Kc = 0.4433648771924941\n", - "proton+CCC(=O)O[Pt]<=>OX+CCC=O\n", - "kf = 7.2938132405514685e-6\n", - "krev = 2.191544710090903e-13\n", - "Kc = 3.3281608205241356e7\n", - "CO2+CC[Pt]<=>CCC(=O)O[Pt]\n", - "kf = 3.860701485876577e-7\n", - "krev = 2.2515045234693432e-8\n", - "Kc = 17.147207325738\n", - "vacantX+vacantX+OC=CCO<=>OC=[Pt]+OCC=[Pt]\n", - "kf = 3.6700973989487563e-44\n", - "krev = 3.0504263460080312e13\n", - "Kc = 1.203142440646588e-57\n", - "proton+CC(=C=O)O[Pt]<=>CC(O)=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.82558147454442e-8\n", - "Kc = 2.5443786777167984e17\n", - "vacantX+CC(O)=C=O<=>CC(O)=C=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 165389.73964983693\n", - "Kc = 1.9518801026953096\n", - "proton+OOC=[Pt]<=>OO+CHX\n", - "kf = 3.7259548765787992e9\n", - "krev = 3.6992581168771994e-31\n", - "Kc = 1.0072167874903892e40\n", - "proton+OOC=[Pt]<=>OOC[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.043799531501529e-45\n", - "Kc = 8.21341870292861e54\n", - "proton+OOC#[Pt]<=>OOC=[Pt]\n", - "kf = 5.776653727817663e-40\n", - "krev = 0.19860841474496846\n", - "Kc = 2.9085644408548448e-39\n", - "vacantX+vacantX+C=CCO<=>CH2X+OCC=[Pt]\n", - "kf = 3.3256293066300124e-48\n", - "krev = 2.638642223210571e15\n", - "Kc = 1.2603562837645906e-63\n", - "vacantX+vacantX+C=CCO<=>OC[Pt]+C=C[Pt]\n", - "kf = 1.4930923415267688e-9\n", - "krev = 1.1121057711212152e14\n", - "Kc = 1.3425812366942817e-23\n", - "vacantX+OO<=>OO.[Pt]\n", - "kf = 469882.2241291155\n", - "krev = 15.560302693769444\n", - "Kc = 30197.498941795184\n", - "proton+OO[Pt]<=>OO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.920455993640651e-33\n", - "Kc = 6.376809238658043e42\n", - "C=O+CO[Pt]<=>COCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 9.545218685674386e-14\n", - "Kc = 414937.62088874576\n", - "HX+COC=O<=>COCO[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 0.02522938529859348\n", - "Kc = 1.1100614687459063e-6\n", - "vacantX+vacantX+COCO<=>HX+COCO[Pt]\n", - "kf = 1.0488506310161173e-19\n", - "krev = 521.1543106644776\n", - "Kc = 2.0125529225284944e-22\n", - "proton+COC=O.[Pt]<=>COCO[Pt]\n", - "kf = 11433.101373849615\n", - "krev = 0.22138456904438245\n", - "Kc = 51643.62368705808\n", - "proton+COCO[Pt]<=>OX+COC\n", - "kf = 660785.6964241413\n", - "krev = 2.737556590691246e-13\n", - "Kc = 2.413779129429028e18\n", - "CO[Pt]+C=C=O<=>COCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.680149232421768e-23\n", - "Kc = 1.9922953446306685e15\n", - "HX+COC=C=O<=>COCC(=O)[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 2.661991446097411e-38\n", - "Kc = 9.604054388173769e29\n", - "proton+COCC(=O)[Pt]<=>OCX+COC\n", - "kf = 1.133196546666376e10\n", - "krev = 9.97059352398989e-15\n", - "Kc = 1.1365387064870632e24\n", - "vacantX+vacantX+COCC=O<=>HX+COCC(=O)[Pt]\n", - "kf = 2.290241001822749e-10\n", - "krev = 0.0004872161822843353\n", - "Kc = 4.7006669423105973e-7\n", - "proton+COCOC#[Pt]<=>CX+COCO\n", - "kf = 4.25143681327651e-15\n", - "krev = 1.001308193612447e-19\n", - "Kc = 42458.82377071624\n", - "proton+COCC#[Pt]<=>CX+COC\n", - "kf = 185.93529229739633\n", - "krev = 1.904541046621029e-10\n", - "Kc = 9.762734839833265e11\n", - "proton+COC[Pt]<=>CH2X+CO-2\n", - "kf = 35.92356832171279\n", - "krev = 1.3784436111735967e-12\n", - "Kc = 2.6060963270835383e13\n", - "vacantX+vacantX+COCO<=>HOX+COC[Pt]\n", - "kf = 8.90444501639475e-13\n", - "krev = 8.409201083164982e12\n", - "Kc = 1.0588931015362724e-25\n", - "C=O+CH3X<=>COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 8.422687202008296e-11\n", - "Kc = 470.23832623775377\n", - "vacantX+vacantX+COC<=>HX+COC[Pt]\n", - "kf = 2.786306429788959e-20\n", - "krev = 52.25975865319748\n", - "Kc = 5.3316481009398625e-22\n", - "vacantX+vacantX+COCC=O<=>CHOX+COC[Pt]\n", - "kf = 1.4060776479118306e6\n", - "krev = 6.613786245273692e13\n", - "Kc = 2.1259798786461146e-8\n", - "vacantX+vacantX+C=C=CO<=>OC=[Pt]+C=C=[Pt]\n", - "kf = 1.5975335437882445e-34\n", - "krev = 2.2957840869759923e8\n", - "Kc = 6.958553083676594e-43\n", - "vacantX+vacantX+C=C=CO<=>CH2X+OC=C=[Pt]\n", - "kf = 9.363402027600756e-56\n", - "krev = 7.047835211144391e9\n", - "Kc = 1.328550079149818e-65\n", - "vacantX+vacantX+COC=O<=>OX+COC=[Pt]\n", - "kf = 1.1797200153280936e-59\n", - "krev = 4.3408253155831816e16\n", - "Kc = 2.7177320660497494e-76\n", - "proton+COC=[Pt]<=>CHX+CO-2\n", - "kf = 6.2161685505804725e7\n", - "krev = 4.785686680273161e-40\n", - "Kc = 1.298908383660767e47\n", - "proton+COC#[Pt]<=>COC=[Pt]\n", - "kf = 1.5305016921747763e9\n", - "krev = 0.1627608300478634\n", - "Kc = 9.403378513888744e9\n", - "vacantX+vacantX+COC=C=O<=>OCX+COC=[Pt]\n", - "kf = 2.7777170398864307e-21\n", - "krev = 2.5089215324603047e13\n", - "Kc = 1.107135876490541e-34\n", - "proton+COC=[Pt]<=>COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.755986506689556e-57\n", - "Kc = 5.256532995801423e66\n", - "vacantX+COC=C=O<=>COC=C=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 1179.0380002145982\n", - "Kc = 273.8002862958761\n", - "proton+COC=C=O.[Pt]<=>COCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 3.7340035459822127e-34\n", - "Kc = 6.695226636005739e43\n", - "vacantX+vacantX+C=C=C<=>CH2X+C=C=[Pt]\n", - "kf = 4.78083312177258e-41\n", - "krev = 4.774618642094983e15\n", - "Kc = 1.0013015656628172e-56\n", - "proton+O=C=COC[Pt]<=>CH2X+O=C=CO\n", - "kf = 0.006471827705681551\n", - "krev = 4.258755653145197e-10\n", - "Kc = 1.5196522723490711e7\n", - "C=O+O=C=C[Pt]<=>O=C=COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.852140732586457e13\n", - "Kc = 2.1384283940268284e-21\n", - "vacantX+vacantX+COC=C=O<=>HX+O=C=COC[Pt]\n", - "kf = 3.256466928453685e-21\n", - "krev = 26.50445975246776\n", - "Kc = 1.2286486722863626e-22\n", - "proton+O=C=COC[Pt]<=>COC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.877454242443708e-31\n", - "Kc = 4.253542259753193e40\n", - "CH3X+O=C=C=O<=>COC([Pt])=C=O\n", - "kf = 5.799304049644909e-8\n", - "krev = 3.1615249923835833e-35\n", - "Kc = 1.8343375629216876e27\n", - "proton+COC([Pt])=C=O<=>CO-2+O=C=C=[Pt]\n", - "kf = 4.069225267716308e7\n", - "krev = 5.753482545458429e-41\n", - "Kc = 7.072629899483041e47\n", - "vacantX+vacantX+COC=C=O<=>HX+COC([Pt])=C=O\n", - "kf = 2.779636780044878e-20\n", - "krev = 3.601218910546807\n", - "Kc = 7.718599866018197e-21\n", - "proton+COC([Pt])=C=O<=>COC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.6923262566046736e-29\n", - "Kc = 6.770799290902607e38\n", - "vacantX+vacantX+C=C=C(O)O<=>OC(O)=[Pt]+C=C=[Pt]\n", - "kf = 2.937512138355157e-45\n", - "krev = 8.778136400287878e10\n", - "Kc = 3.34639609639561e-56\n", - "proton+O=C=COC=[Pt]<=>CHX+O=C=CO\n", - "kf = 2.72779390176573e9\n", - "krev = 7.780637869692039e-32\n", - "Kc = 3.505874386457851e40\n", - "proton+O=C=COC#[Pt]<=>O=C=COC=[Pt]\n", - "kf = 1.8192290523055587e7\n", - "krev = 0.1716042050140899\n", - "Kc = 1.0601308121535759e8\n", - "proton+O=C=COC=[Pt]<=>O=C=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0274874875606104e-56\n", - "Kc = 2.433119653783159e66\n", - "proton+CCOO[Pt]<=>OX+CCO\n", - "kf = 21946.411665990272\n", - "krev = 2.5837051406163863e-64\n", - "Kc = 8.494162635274467e67\n", - "vacantX+vacantX+CCOO<=>HX+CCOO[Pt]\n", - "kf = 1.893449523720139e-21\n", - "krev = 0.6694879211592951\n", - "Kc = 2.8282056537202555e-21\n", - "O=O+CC[Pt]<=>CCOO[Pt]\n", - "kf = 4.5276782379965965e-7\n", - "krev = 1.4949208469184493e-38\n", - "Kc = 3.0287076719344122e31\n", - "vacantX+vacantX+C=CC(=O)O<=>CH2X+O=C(O)C=[Pt]\n", - "kf = 4.72289540105198e-39\n", - "krev = 9.498795808374404e14\n", - "Kc = 4.9720990916429044e-54\n", - "vacantX+vacantX+C=CC(=O)O<=>CO2HX+C=C[Pt]\n", - "kf = 5.354197885861111e7\n", - "krev = 1.376967106369583e14\n", - "Kc = 3.888399266107105e-7\n", - "vacantX+vacantX+C=CC(=O)O<=>HOX+C=CC(=O)[Pt]\n", - "kf = 0.03947248649742643\n", - "krev = 2.5171232142616846e11\n", - "Kc = 1.5681586929785789e-13\n", - "vacantX+vacantX+C=CC(=O)O<=>HX+C=CC(=O)O[Pt]\n", - "kf = 2.4490000178339845e-20\n", - "krev = 458.0011375503109\n", - "Kc = 5.3471483300955e-23\n", - "proton+O=C=C=CO.[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.055946827834815e-26\n", - "Kc = 4.944672254535185e35\n", - "proton+O=C=C=CO.[Pt]<=>O=C=C([Pt])CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.5205992990749725e-14\n", - "Kc = 9.918276185022613e23\n", - "vacantX+O=C=C=CO<=>O=C=C=CO.[Pt]\n", - "kf = 327433.4917974331\n", - "krev = 0.4460204906723957\n", - "Kc = 734122.0832787583\n", - "HX+O=C=C=C=O<=>O=C=C=C(O)[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 1.3048903398306852e-5\n", - "Kc = 0.004032923533638046\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C=C(O)[Pt]\n", - "kf = 7.128503770743534e7\n", - "krev = 0.0007669975897549733\n", - "Kc = 9.294036729660156e10\n", - "proton+O=C=C=C(O)[Pt]<=>O=C=CC(O)=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.719414628142839e-6\n", - "Kc = 6.721487787577715e15\n", - "vacantX+vacantX+O=C=C=CO<=>HX+O=C=C=C(O)[Pt]\n", - "kf = 8.233814429551885e-18\n", - "krev = 0.5740049812746953\n", - "Kc = 1.434449995759099e-17\n", - "proton+O=C=C=C(O)[Pt]<=>O=C=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.559249128827655e-29\n", - "Kc = 9.768490186593142e38\n", - "vacantX+vacantX+CC=CO<=>OC=[Pt]+CC=[Pt]\n", - "kf = 1.6816353348966163e-33\n", - "krev = 8.021148128032321e14\n", - "Kc = 2.0965020319468163e-48\n", - "proton+O=C=C=C[Pt]<=>O=C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.526991850186384e-11\n", - "Kc = 2.6241231642820084e20\n", - "vacantX+vacantX+C=C=C=O<=>HX+O=C=C=C[Pt]\n", - "kf = 3.6772489817592154e-10\n", - "krev = 0.00723599763490509\n", - "Kc = 5.081882509221477e-8\n", - "vacantX+vacantX+O=C=C=CO<=>HOX+O=C=C=C[Pt]\n", - "kf = 0.00020826365169953766\n", - "krev = 1.0739954827079557e13\n", - "Kc = 1.939148302322696e-17\n", - "vacantX+OC=CO<=>OC=CO.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.48171019889246675\n", - "Kc = 734122.0861712244\n", - "vacantX+vacantX+C=CC<=>CH2X+CC=[Pt]\n", - "kf = 3.8695500910369183e-44\n", - "krev = 2.1644248520711738e17\n", - "Kc = 1.787795999169979e-61\n", - "vacantX+vacantX+C=CC<=>CH3X+C=C[Pt]\n", - "kf = 1.1726078415532691e-17\n", - "krev = 1.59532697721828e15\n", - "Kc = 7.350266486422159e-33\n", - "HX+O=C=CO<=>OC=C(O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 2.762063581333058e-24\n", - "Kc = 1.0314187634521844e16\n", - "vacantX+vacantX+OC=CO<=>HX+OC=C(O)[Pt]\n", - "kf = 6.089904416870865e-20\n", - "krev = 3.928023437111271\n", - "Kc = 1.550373747604081e-20\n", - "proton+O=C=CO.[Pt]<=>OC=C(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.322420103995465e-17\n", - "Kc = 2.681707080469945e26\n", - "proton+OC=C(O)[Pt]<=>H2O+OC=C=[Pt]\n", - "kf = 6.827226723819953e-5\n", - "krev = 2.862909610249775e-7\n", - "Kc = 238.47161291356\n", - "proton+OC=C(O)[Pt]<=>OC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.7660724730806307e-32\n", - "Kc = 9.038085676821402e41\n", - "vacantX+vacantX+OC=CO<=>HOX+OC=C[Pt]\n", - "kf = 1.882970379851619e-8\n", - "krev = 6.2613640604613945e13\n", - "Kc = 3.0072846134950095e-22\n", - "vacantX+vacantX+C=CO<=>HX+OC=C[Pt]\n", - "kf = 5.986889507133711e-22\n", - "krev = 1492.047811549125\n", - "Kc = 4.0125319448830507e-25\n", - "proton+OC=C[Pt]<=>OCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.05979204840625116\n", - "Kc = 4.181157974408231e11\n", - "vacantX+vacantX+O=CC=CO<=>CHOX+OC=C[Pt]\n", - "kf = 3.6404040231768274e-5\n", - "krev = 5.1339082800935775e14\n", - "Kc = 7.090901949480236e-20\n", - "proton+OC=C=[Pt]<=>OC=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.7075333850654e-54\n", - "Kc = 3.727152526093054e63\n", - "vacantX+vacantX+OC=CCO<=>OC[Pt]+OC=C[Pt]\n", - "kf = 1.39754480380523e-13\n", - "krev = 4.435737343310229e14\n", - "Kc = 3.1506482364492156e-28\n", - "vacantX+vacantX+CC=CO<=>CH3X+OC=C[Pt]\n", - "kf = 3.0518560755450534e-15\n", - "krev = 1.440283576497463e15\n", - "Kc = 2.1189272205454667e-30\n", - "vacantX+vacantX+CC=C(O)O<=>OC(O)=[Pt]+CC=[Pt]\n", - "kf = 3.314404876424973e-50\n", - "krev = 3.298291971460818e17\n", - "Kc = 1.0048852269912959e-67\n", - "HX+O=C=CO<=>OC=CO[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 5.830973747204281e-42\n", - "Kc = 4.885709192226705e33\n", - "vacantX+vacantX+OC=CO<=>HX+OC=CO[Pt]\n", - "kf = 6.3392542923960805e-6\n", - "krev = 0.0008631955285686626\n", - "Kc = 0.007343937824733329\n", - "proton+O=C=CO.[Pt]<=>OC=CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.9680498035664946e-34\n", - "Kc = 1.2702930563390754e44\n", - "proton+OC=CO[Pt]<=>OX+C=CO\n", - "kf = 2.9355344566104805e-6\n", - "krev = 1.175996281956839e-11\n", - "Kc = 249621.0661249539\n", - "proton+OC=CO[Pt]<=>OC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3102559490834589e-14\n", - "Kc = 1.9080241549361273e24\n", - "proton+OC=COC#[Pt]<=>CX+OC=CO\n", - "kf = 2.9180289159703806e-27\n", - "krev = 9.401864294760527e-11\n", - "Kc = 3.103670532233209e-17\n", - "vacantX+vacantX+CCC(=O)O<=>CH3X+O=C(O)C[Pt]\n", - "kf = 8.997747599742267e-17\n", - "krev = 6.572577910715489e15\n", - "Kc = 1.368983026442782e-32\n", - "vacantX+vacantX+CCC(=O)O<=>CO2HX+CC[Pt]\n", - "kf = 3.388822996448631e-6\n", - "krev = 1.0293603282987281e15\n", - "Kc = 3.292163981148853e-21\n", - "vacantX+vacantX+CCC(=O)O<=>HOX+CCC(=O)[Pt]\n", - "kf = 2.1491486919570496e-14\n", - "krev = 4.131728096070369e12\n", - "Kc = 5.201573390081201e-27\n", - "vacantX+vacantX+CCC(=O)O<=>HX+CCC(=O)O[Pt]\n", - "kf = 2.415446383235281e-20\n", - "krev = 451.7273406124814\n", - "Kc = 5.347133472063615e-23\n", - "proton+O=C([Pt])C=CO<=>OCX+C=CO\n", - "kf = 29084.357636714656\n", - "krev = 3.7625287044080875e-13\n", - "Kc = 7.730002857556974e16\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=C([Pt])C=CO\n", - "kf = 2.859565189776071e-11\n", - "krev = 0.000933578065584948\n", - "Kc = 3.06301668300697e-8\n", - "HX+O=C=C=CO<=>O=C([Pt])C=CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.1750295723598082e-43\n", - "Kc = 2.206855353748942e35\n", - "proton+O=C=C=CO.[Pt]<=>O=C([Pt])C=CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 4.3570230615432705e-36\n", - "Kc = 5.737862675242513e45\n", - "proton+OC=C(O)C#[Pt]<=>CX+OC=CO\n", - "kf = 3.720866574817531e-22\n", - "krev = 0.000333999453543238\n", - "Kc = 1.114033731296463e-18\n", - "vacantX+vacantX+C=COO<=>OO[Pt]+C=C[Pt]\n", - "kf = 0.00256837059370255\n", - "krev = 1.2695573429161084e13\n", - "Kc = 2.0230441799526235e-16\n", - "vacantX+vacantX+C=COO<=>HOX+C=CO[Pt]\n", - "kf = 3.07907263663438e8\n", - "krev = 5.547742278067932e-15\n", - "Kc = 5.5501364019864025e22\n", - "vacantX+vacantX+C=COO<=>CH2X+OOC=[Pt]\n", - "kf = 7.483948884590266e-53\n", - "krev = 2.8103204909201245e17\n", - "Kc = 2.6630232775123643e-70\n", - "proton+OC=CC#[Pt]<=>CX+C=CO\n", - "kf = 1.3743850393273974e-17\n", - "krev = 6.122610931292474e-6\n", - "Kc = 2.2447695186753714e-12\n", - "proton+OCC[Pt]<=>CH2X+CO-2\n", - "kf = 0.0005163317635413589\n", - "krev = 1.6229254340255067e-10\n", - "Kc = 3.1814879027476255e6\n", - "vacantX+vacantX+OCCO<=>HOX+OCC[Pt]\n", - "kf = 2.110093084979835e-12\n", - "krev = 2.4085316622580622e14\n", - "Kc = 8.760910716040024e-27\n", - "HX+C=CO<=>OCC[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 1.1429411507382647e-15\n", - "Kc = 2.8609207088741057e7\n", - "HOX+C=C<=>OCC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 2.2750559854988554e-15\n", - "Kc = 3.602118089238167e7\n", - "proton+OCC=[Pt]<=>OCC[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.024019970371648e-43\n", - "Kc = 6.212692825600234e52\n", - "vacantX+vacantX+CCO<=>HX+OCC[Pt]\n", - "kf = 4.51610258482867e-23\n", - "krev = 15472.547765874588\n", - "Kc = 2.918784063985339e-27\n", - "vacantX+vacantX+O=CCCO<=>CHOX+OCC[Pt]\n", - "kf = 2.0496526220764064\n", - "krev = 1.4633869198921762e15\n", - "Kc = 1.4006224835106677e-15\n", - "HX+C#C<=>C=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 2.375601900047824e-24\n", - "Kc = 3.580716650609497e16\n", - "CHOX+C#C<=>O=CC=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 3.2359557228060194e-16\n", - "Kc = 2.6287001452988416e8\n", - "HOX+C#C<=>OC=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 2.419253665005007e-25\n", - "Kc = 3.516108046777805e17\n", - "proton+OCCC#[Pt]<=>CX+CCO\n", - "kf = 4.746132232562072\n", - "krev = 2.6352119522517757e-10\n", - "Kc = 1.8010438319796345e10\n", - "OC[Pt]+C=C=O<=>O=C([Pt])CCO\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.869121889511259e-30\n", - "Kc = 1.7908695590280368e22\n", - "HX+O=C=CCO<=>O=C([Pt])CCO\n", - "kf = 2.5565910629172877e-8\n", - "krev = 3.7973012083800085e-37\n", - "Kc = 6.732652804247709e28\n", - "proton+O=C=CCO.[Pt]<=>O=C([Pt])CCO\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.3265145938724705e-33\n", - "Kc = 4.69350070471215e42\n", - "proton+O=C([Pt])CCO<=>OCX+CCO\n", - "kf = 1.245555554261223e10\n", - "krev = 1.4588737337488966e-13\n", - "Kc = 8.537788606697952e22\n", - "vacantX+vacantX+O=CCCO<=>HX+O=C([Pt])CCO\n", - "kf = 4.786286134347495e-11\n", - "krev = 0.0006355926831038164\n", - "Kc = 7.530429883135883e-8\n", - "vacantX+vacantX+C=COC<=>CO[Pt]+C=C[Pt]\n", - "kf = 1.9108708710628152e-14\n", - "krev = 5.750545812867103e12\n", - "Kc = 3.322938262290088e-27\n", - "vacantX+vacantX+C=COC<=>CH3X+C=CO[Pt]\n", - "kf = 8.809048609670953e-10\n", - "krev = 5.30334818480063e15\n", - "Kc = 1.6610353125441853e-25\n", - "vacantX+vacantX+C=COC<=>CH2X+COC=[Pt]\n", - "kf = 2.00333233616492e-67\n", - "krev = 2.0086736136424638e14\n", - "Kc = 9.973408932933319e-82\n", - "C=O+OC[Pt]<=>OCCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.726586049973397e-6\n", - "Kc = 0.00837955829095468\n", - "HX+O=CCO<=>OCCO[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 7.096612291679358e-6\n", - "Kc = 0.003946413774492056\n", - "vacantX+vacantX+OCCO<=>HX+OCCO[Pt]\n", - "kf = 1.0265256602604584e-26\n", - "krev = 112849.3186381155\n", - "Kc = 9.09642763154215e-32\n", - "proton+O=CCO.[Pt]<=>OCCO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 0.09087129568777781\n", - "Kc = 2.751143780968724e11\n", - "proton+OCCO[Pt]<=>OX+CCO\n", - "kf = 1.2341194948677085e8\n", - "krev = 1.5290672892581859e-24\n", - "Kc = 8.071060727918856e31\n", - "proton+OCCOC#[Pt]<=>CX+OCCO\n", - "kf = 8.219996171491995e-20\n", - "krev = 2.347130357335255e-19\n", - "Kc = 0.3502147269240011\n", - "vacantX+vacantX+C=CC(O)O<=>OC(O)[Pt]+C=C[Pt]\n", - "kf = 1.3588265576828814e-16\n", - "krev = 6.093754170226661e16\n", - "Kc = 2.2298676968656565e-33\n", - "proton+O=C=C=C=[Pt]<=>O=C=CC#[Pt]\n", - "kf = 0.00014470508438140734\n", - "krev = 1.2597560252212088e-64\n", - "Kc = 1.1486754695695751e60\n", - "vacantX+vacantX+O=C=C=C=O<=>OX+O=C=C=C=[Pt]\n", - "kf = 6.451439297868635e-57\n", - "krev = 8.482832416110645e14\n", - "Kc = 7.60528910793525e-72\n", - "proton+O=C=C=C(O)[Pt]<=>H2O+O=C=C=C=[Pt]\n", - "kf = 2.095196876444184e-9\n", - "krev = 5.9307219702134525e-8\n", - "Kc = 0.03532785530947383\n", - "proton+O=C=C=C=[Pt]<=>O=C=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4257912410930978e-59\n", - "Kc = 1.7534123705819296e69\n", - "vacantX+C=CO<=>C=CO.[Pt]\n", - "kf = 412885.969273148\n", - "krev = 1.1342794009872417\n", - "Kc = 364007.288604364\n", - "proton+C=CO[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.583064462297258e-35\n", - "Kc = 1.5792155402011454e45\n", - "proton+OC=C[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4437894439004186e-36\n", - "Kc = 1.731554424754771e46\n", - "proton+C=CO.[Pt]<=>OCC[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.6664784319671228e-8\n", - "Kc = 1.5001694303651932e18\n", - "vacantX+vacantX+C=COCO<=>OCO[Pt]+C=C[Pt]\n", - "kf = 1.4197397308458187e-12\n", - "krev = 3.0290185667479297e13\n", - "Kc = 4.6871278586123213e-26\n", - "vacantX+vacantX+C=COCO<=>OC[Pt]+C=CO[Pt]\n", - "kf = 1.0263854075463885e-7\n", - "krev = 1.9545487277553856e14\n", - "Kc = 5.251265384031101e-22\n", - "HX+C=C=O<=>C=C(O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 3.2362559658776053e-12\n", - "Kc = 10343.290300064218\n", - "proton+C=C=O.[Pt]<=>C=C(O)[Pt]\n", - "kf = 9868.238361499898\n", - "krev = 0.2153664742836313\n", - "Kc = 45820.68028148021\n", - "vacantX+vacantX+C=CO<=>HX+C=C(O)[Pt]\n", - "kf = 4.00965787691315e-19\n", - "krev = 4.055766485027893\n", - "Kc = 9.886313454472895e-20\n", - "vacantX+vacantX+C=C(O)O<=>HOX+C=C(O)[Pt]\n", - "kf = 3.9452234947489745e-7\n", - "krev = 1.361002505571871e12\n", - "Kc = 2.8987628447394044e-19\n", - "proton+C=C(O)[Pt]<=>H2O+C=C=[Pt]\n", - "kf = 18.267803269894422\n", - "krev = 2.792024654707504e-9\n", - "Kc = 6.542851704082885e9\n", - "proton+C=C(O)[Pt]<=>CC(O)=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.704607370852364e-18\n", - "Kc = 6.748353468359037e27\n", - "vacantX+vacantX+C=C(O)C=O<=>CHOX+C=C(O)[Pt]\n", - "kf = 2.8052009086647103\n", - "krev = 2.294429327232502e13\n", - "Kc = 1.2226137782366527e-13\n", - "proton+C=C(O)[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.5572937987101485e-31\n", - "Kc = 7.027814235941051e40\n", - "HOX+C=C=O<=>C=C(O)O[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.6625343699967689e-31\n", - "Kc = 2.0134040862236038e23\n", - "proton+C=C(O)O[Pt]<=>OX+C=CO\n", - "kf = 9.888055232525487e-8\n", - "krev = 7.779707979835849e-8\n", - "Kc = 1.2710059629685642\n", - "vacantX+vacantX+C=C(O)O<=>HX+C=C(O)O[Pt]\n", - "kf = 8.7276566297004e-6\n", - "krev = 1.546723677424112e-6\n", - "Kc = 5.6426734503963205\n", - "vacantX+vacantX+C=CCOO<=>OOC[Pt]+C=C[Pt]\n", - "kf = 2.5331825038162864e-12\n", - "krev = 1.769892843246248e17\n", - "Kc = 1.4312632052740838e-29\n", - "proton+C=C(O)OC#[Pt]<=>CX+C=C(O)O\n", - "kf = 1.393899600447792e-20\n", - "krev = 8.328492808111743e-5\n", - "Kc = 1.6736516829193498e-16\n", - "proton+C=C(O)C#[Pt]<=>CX+C=CO\n", - "kf = 4.789035386292112e-18\n", - "krev = 2.8243399365414766e-5\n", - "Kc = 1.695629950322654e-13\n", - "vacantX+vacantX+C=COOC<=>COO[Pt]+C=C[Pt]\n", - "kf = 0.0009962735751002543\n", - "krev = 4.495422962203487e13\n", - "Kc = 2.21619541359445e-17\n", - "vacantX+vacantX+C=COOC<=>CO[Pt]+C=CO[Pt]\n", - "kf = 2.772273774659678e8\n", - "krev = 3.7705323383409334e-17\n", - "Kc = 7.352473141443741e24\n", - "proton+C=C(O)C(=O)[Pt]<=>OCX+C=CO\n", - "kf = 127808.30444689187\n", - "krev = 2.3626964909258914e-13\n", - "Kc = 5.40942541446813e17\n", - "HOX+C=C=C=O<=>C=C(O)C(=O)[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 3.5720015577500406e-52\n", - "Kc = 8.264488540948707e43\n", - "vacantX+vacantX+C=C(O)C=O<=>HX+C=C(O)C(=O)[Pt]\n", - "kf = 2.8595651897765786e-11\n", - "krev = 0.000933577098423846\n", - "Kc = 3.063019856211522e-8\n", - "proton+C=COO[Pt]<=>OX+C=CO\n", - "kf = 5699.926944847187\n", - "krev = 3.054251108472864e-67\n", - "Kc = 1.866227347527155e70\n", - "O=O+C=C[Pt]<=>C=COO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 1.0833501613715598e-32\n", - "Kc = 7.082998693235901e24\n", - "vacantX+vacantX+C=COO<=>HX+C=COO[Pt]\n", - "kf = 4.552726448583842e-23\n", - "krev = 27.53540659037694\n", - "Kc = 1.6534081069915729e-24\n", - "vacantX+vacantX+C=COOC<=>CH3X+C=COO[Pt]\n", - "kf = 2.287071149777874e-9\n", - "krev = 2.2490557638427473e13\n", - "Kc = 1.0169028205286352e-22\n", - "vacantX+vacantX+CC(O)=CO<=>OC=[Pt]+CC(O)=[Pt]\n", - "kf = 7.128045206079291e-31\n", - "krev = 1.6024698052635947e11\n", - "Kc = 4.4481619451835966e-42\n", - "vacantX+vacantX+CC(O)=CO<=>CH3X+OC=C(O)[Pt]\n", - "kf = 1.2021042471738558e-26\n", - "krev = 3.79937896614338e12\n", - "Kc = 3.163949313521812e-39\n", - "proton+O=CC=C=[Pt]<=>O=CCC#[Pt]\n", - "kf = 1.060146069558954e6\n", - "krev = 4.940969414534533e-35\n", - "Kc = 2.1456236228469465e40\n", - "vacantX+vacantX+O=C=CC=O<=>OX+O=CC=C=[Pt]\n", - "kf = 1.1758489216219413e-43\n", - "krev = 2.1453863988577092e16\n", - "Kc = 5.480825842132732e-60\n", - "proton+O=CC=C=[Pt]<=>O=CC=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.294133341553474e-55\n", - "Kc = 7.589249556063902e64\n", - "proton+C=C=C=O.[Pt]<=>O=C=CC[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 7.847086633519948e-25\n", - "Kc = 3.1858957556564916e34\n", - "vacantX+C=C=C=O<=>C=C=C=O.[Pt]\n", - "kf = 372758.92921022984\n", - "krev = 0.5077615475124772\n", - "Kc = 734122.012658058\n", - "proton+C=C=C=O.[Pt]<=>CC([Pt])=C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 7.495250892056493e-25\n", - "Kc = 3.3354453853566298e34\n", - "proton+C=C=C=O.[Pt]<=>C=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.8254433456081984e-40\n", - "Kc = 1.3695303149312766e50\n", - "proton+O=C=C=C[Pt]<=>C=C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.066753580889227e-20\n", - "Kc = 2.7573265090930278e29\n", - "vacantX+vacantX+C=C(C)O<=>CH2X+CC(O)=[Pt]\n", - "kf = 1.2526307828427685e-31\n", - "krev = 1.8291181793687947e14\n", - "Kc = 6.848276929132241e-46\n", - "vacantX+vacantX+C=C(C)O<=>CH3X+C=C(O)[Pt]\n", - "kf = 6.412809230790006e-14\n", - "krev = 6.896161957802356e13\n", - "Kc = 9.299098933624258e-28\n", - "HX+O=C=C=C=O<=>O=C=C=CO[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 6.474039280394542e-15\n", - "Kc = 8.128654665807662e6\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C=CO[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 2.6691128365256186e-10\n", - "Kc = 1.8732816131177477e20\n", - "proton+O=C=C=CO[Pt]<=>OX+C=C=C=O\n", - "kf = 9.958136134339127e-12\n", - "krev = 3.084761262689636e-10\n", - "Kc = 0.03228170767956455\n", - "vacantX+vacantX+O=C=C=CO<=>HX+O=C=C=CO[Pt]\n", - "kf = 4.194899212644372e-10\n", - "krev = 0.014508998351933198\n", - "Kc = 2.891239705796395e-8\n", - "proton+O=C=C=CO[Pt]<=>O=C=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.1583552721722075e-20\n", - "Kc = 4.846506043286232e29\n", - "proton+CC(O)[Pt]<=>OC=[Pt]+CH4\n", - "kf = 7705.934977783516\n", - "krev = 5.863572986161853e-13\n", - "Kc = 1.3142046659894356e16\n", - "HX+C=CO<=>CC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 1.2254518112062234e-21\n", - "Kc = 2.668292606261641e13\n", - "HX+CC=O<=>CC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 2.4645381117653586e-12\n", - "Kc = 13267.654460532101\n", - "vacantX+vacantX+CCO<=>HX+CC(O)[Pt]\n", - "kf = 1.7361137032745595e-19\n", - "krev = 63.774720976875884\n", - "Kc = 2.72225997492652e-21\n", - "vacantX+vacantX+CC(O)O<=>HOX+CC(O)[Pt]\n", - "kf = 7.380915652046712e-14\n", - "krev = 2.775462823415347e13\n", - "Kc = 2.6593458899096773e-27\n", - "proton+CC=O.[Pt]<=>CC(O)[Pt]\n", - "kf = 6.081485750645586e8\n", - "krev = 3.776470929291763e-7\n", - "Kc = 1.6103621249869132e15\n", - "proton+CC(O)[Pt]<=>H2O+CC=[Pt]\n", - "kf = 384539.88399328274\n", - "krev = 8.957560610185237e-9\n", - "Kc = 4.2929085353443195e13\n", - "proton+CC(O)=[Pt]<=>CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.7157326451879074e-27\n", - "Kc = 1.4571034753064335e37\n", - "vacantX+vacantX+CC(O)C=O<=>CHOX+CC(O)[Pt]\n", - "kf = 753631.9525109725\n", - "krev = 9.011518944421836e14\n", - "Kc = 8.362984721654206e-10\n", - "proton+C=CO.[Pt]<=>CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.7867840452424854e-14\n", - "Kc = 1.3991618106600694e24\n", - "HX+C#CC=O<=>O=CC=C[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 1.9866745274914506e-30\n", - "Kc = 1.4859387148609413e22\n", - "proton+CC(O)C#[Pt]<=>CX+CCO\n", - "kf = 176.6698786931541\n", - "krev = 1.870392435490979e-11\n", - "Kc = 9.44560485493934e12\n", - "O=CO+CH3X<=>CC(O)O[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 7.324156308451427e-7\n", - "Kc = 0.043678018970166745\n", - "HOX+CC=O<=>CC(O)O[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 7.587328136505701e-13\n", - "Kc = 43096.38318446866\n", - "HX+CC(=O)O<=>CC(O)O[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 4598.938099177113\n", - "Kc = 6.089703295881323e-12\n", - "proton+CC(O)O[Pt]<=>OX+CCO\n", - "kf = 2.1514853509561807e8\n", - "krev = 7.777866186524473e-13\n", - "Kc = 2.7661640086888258e20\n", - "vacantX+vacantX+CC(O)O<=>HX+CC(O)O[Pt]\n", - "kf = 4.052122584605618e-24\n", - "krev = 469.09529347560436\n", - "Kc = 8.638165082797514e-27\n", - "proton+CC(=O)O.[Pt]<=>CC(O)O[Pt]\n", - "kf = 12581.204150344678\n", - "krev = 0.2112685438632624\n", - "Kc = 59550.76851614742\n", - "vacantX+vacantX+OC=C=CO<=>OC=[Pt]+OC=C=[Pt]\n", - "kf = 3.0449395213240036e-51\n", - "krev = 1.4315520101841116e12\n", - "Kc = 2.1270198355785863e-63\n", - "CH3X+O=C=CO<=>CC(O)C(=O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 4.477216581188038e-53\n", - "Kc = 6.362980552705156e44\n", - "proton+CC(O)C(=O)[Pt]<=>OCX+CCO\n", - "kf = 1.2416194499098324e10\n", - "krev = 2.271594136432873e-13\n", - "Kc = 5.465850743300345e22\n", - "HOX+CC=C=O<=>CC(O)C(=O)[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 3.536759710167166e-36\n", - "Kc = 8.195394062368554e27\n", - "HX+CC(O)=C=O<=>CC(O)C(=O)[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 4.830700359768998e-42\n", - "Kc = 5.292381792522405e33\n", - "vacantX+vacantX+CC(O)C=O<=>HX+CC(O)C(=O)[Pt]\n", - "kf = 4.786286134353719e-11\n", - "krev = 0.0006355923790078162\n", - "Kc = 7.530433486042254e-8\n", - "proton+CC(O)=C=O.[Pt]<=>CC(O)C(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 4.830559203625511e-40\n", - "Kc = 5.175384245624519e49\n", - "proton+CC(O)OC#[Pt]<=>CX+CC(O)O\n", - "kf = 3.616153302567068e-14\n", - "krev = 8.41503036896324e-15\n", - "Kc = 4.297255201721382\n", - "vacantX+vacantX+CCOC<=>CO[Pt]+CC[Pt]\n", - "kf = 2.3627317133785774e-11\n", - "krev = 3.856091265609508e13\n", - "Kc = 6.127271246016828e-25\n", - "vacantX+vacantX+CCOC<=>CH3X+CCO[Pt]\n", - "kf = 6.326940367296449e-9\n", - "krev = 1.8372911814097844e13\n", - "Kc = 3.443624195943553e-22\n", - "vacantX+vacantX+CCOC<=>CH3X+COC[Pt]\n", - "kf = 1.3389399016858639e-14\n", - "krev = 2.773400746132106e14\n", - "Kc = 4.8277909478217395e-29\n", - "proton+O=C=C(O)C[Pt]<=>CH2X+O=C=CO\n", - "kf = 5.454404325893404e-20\n", - "krev = 5.084145007870193e-7\n", - "Kc = 1.072826270189e-13\n", - "HOX+C=C=C=O<=>O=C=C(O)C[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 6.322264310888409e-36\n", - "Kc = 4.669334354059592e27\n", - "vacantX+vacantX+CC(O)=C=O<=>HX+O=C=C(O)C[Pt]\n", - "kf = 6.004181315465852e-13\n", - "krev = 0.19478740167193392\n", - "Kc = 3.082427951669201e-12\n", - "proton+O=C=C(O)C[Pt]<=>CC(O)=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.0684033679389293e-18\n", - "Kc = 1.2086617333693171e28\n", - "proton+O=C=C(O)C=[Pt]<=>CHX+O=C=CO\n", - "kf = 0.0002345113953695938\n", - "krev = 4.688941595078633e-10\n", - "Kc = 500137.1644631481\n", - "proton+O=C=C(O)C#[Pt]<=>O=C=C(O)C=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.181818068125566e-8\n", - "Kc = 2.1153848188876897e18\n", - "proton+O=C=C(O)C=[Pt]<=>O=C=C(O)C[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.084742232092733e-42\n", - "Kc = 4.9166700805815915e51\n", - "vacantX+vacantX+CCCO<=>OC[Pt]+CC[Pt]\n", - "kf = 4.648157058598011e-13\n", - "krev = 1.3999921584371802e15\n", - "Kc = 3.3201307811515004e-28\n", - "vacantX+vacantX+CCCO<=>CH3X+OCC[Pt]\n", - "kf = 1.2211065235504926e-16\n", - "krev = 1.2627143633797795e15\n", - "Kc = 9.670488900451568e-32\n", - "proton+CC([Pt])OC=O<=>CH4+O=COC=[Pt]\n", - "kf = 1.3855440631402604e-13\n", - "krev = 1.3305165391638203e-7\n", - "Kc = 1.0413580157455412e-6\n", - "CHOX+CC=O<=>CC([Pt])OC=O\n", - "kf = 3.269864007171502e-8\n", - "krev = 0.48922244404245907\n", - "Kc = 6.68379802887317e-8\n", - "HX+C=COC=O<=>CC([Pt])OC=O\n", - "kf = 2.5565910629172877e-8\n", - "krev = 1.2259112200812889e-16\n", - "Kc = 2.0854618352769157e8\n", - "vacantX+vacantX+CCOC=O<=>HX+CC([Pt])OC=O\n", - "kf = 6.519502059052115e-22\n", - "krev = 142.86665816232104\n", - "Kc = 4.563347489828482e-24\n", - "proton+CC([Pt])OC=O<=>O=CO+CC=[Pt]\n", - "kf = 1.0442633465244387e6\n", - "krev = 1.3478746647554358e-10\n", - "Kc = 7.747481081365339e15\n", - "proton+CC(=[Pt])OC=O<=>CH4+O=COC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.956562857492216e-7\n", - "Kc = 1.2777509244984459e17\n", - "proton+CC(=[Pt])OC=O<=>O=CO+CC#[Pt]\n", - "kf = 946026.2069742308\n", - "krev = 3.910739827671124e-49\n", - "Kc = 2.419046647594547e54\n", - "proton+CC(=[Pt])OC=O<=>CC([Pt])OC=O\n", - "kf = 2.5e10\n", - "krev = 9.158806984045244e-56\n", - "Kc = 2.729613151969499e65\n", - "vacantX+vacantX+CCC(O)O<=>OC(O)[Pt]+CC[Pt]\n", - "kf = 3.712816041087776e-19\n", - "krev = 9.367983662004229e16\n", - "Kc = 3.9633032838716965e-36\n", - "vacantX+O=CC=CO<=>O=CC=CO.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 0.8868529608572997\n", - "Kc = 364007.2889878057\n", - "proton+O=CC=CO[Pt]<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.179306692567296e-20\n", - "Kc = 4.826900873793963e29\n", - "proton+O=C([Pt])C=CO<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.1021348140038195e-19\n", - "Kc = 2.2683250435743298e29\n", - "HX+O=C=CC=O<=>O=CC=C(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.0473065138531246e-21\n", - "Kc = 2.475989854235963e13\n", - "proton+O=C=CC=O.[Pt]<=>O=CC=C(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.933915365824659e-14\n", - "Kc = 4.2130698634468396e23\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC=C(O)[Pt]\n", - "kf = 2.77963678004065e-20\n", - "krev = 3.601218827022036\n", - "Kc = 7.718600045027592e-21\n", - "proton+O=CC=C(O)[Pt]<=>H2O+O=CC=C=[Pt]\n", - "kf = 3.0713096503932575e-11\n", - "krev = 7.4063619158875634e-6\n", - "Kc = 4.146853320528285e-6\n", - "proton+O=CC=C(O)[Pt]<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.777307049025005e-32\n", - "Kc = 9.001525419660186e41\n", - "vacantX+vacantX+CCOCO<=>OCO[Pt]+CC[Pt]\n", - "kf = 2.4512530384253315e-9\n", - "krev = 3.614837695546209e14\n", - "Kc = 6.781087409389048e-24\n", - "vacantX+vacantX+CCOCO<=>OC[Pt]+CCO[Pt]\n", - "kf = 1.0293700832173347e-6\n", - "krev = 1.2050997101819434e12\n", - "Kc = 8.541783509863451e-19\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC([Pt])=CO\n", - "kf = 4.3007284274917255e-15\n", - "krev = 1.9561961334382385\n", - "Kc = 2.1985159636997663e-15\n", - "HX+O=C=C=CO<=>O=CC([Pt])=CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.6370748462102965e-36\n", - "Kc = 1.5839961798805036e28\n", - "proton+O=CC([Pt])=CO<=>C=O+OC=C=[Pt]\n", - "kf = 5.6170237484075445e-31\n", - "krev = 0.000416281746068688\n", - "Kc = 1.3493322254588399e-27\n", - "proton+O=C=C=CO.[Pt]<=>O=CC([Pt])=CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.070292208974654e-29\n", - "Kc = 4.118417884898294e38\n", - "HOX+C#CC=O<=>O=CC([Pt])=CO\n", - "kf = 2.952076594227614e-8\n", - "krev = 4.790462195255654e-44\n", - "Kc = 6.162404531970363e35\n", - "proton+O=CC([Pt])=CO<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.910701225296475e-27\n", - "Kc = 3.160276097908509e36\n", - "proton+OC=CC=[Pt]<=>CHX+C=CO\n", - "kf = 48.10704508093828\n", - "krev = 9.042054006745243e-12\n", - "Kc = 5.320366926038167e12\n", - "vacantX+vacantX+O=CC=CO<=>OX+OC=CC=[Pt]\n", - "kf = 8.803023976547135e-28\n", - "krev = 1.526615583505237e17\n", - "Kc = 5.766365856383213e-45\n", - "proton+OC=CC#[Pt]<=>OC=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.0352496226011906e-17\n", - "Kc = 4.9649971448853606e26\n", - "vacantX+vacantX+CCCOO<=>OOC[Pt]+CC[Pt]\n", - "kf = 5.56726706794292e-16\n", - "krev = 4.282042054393877e17\n", - "Kc = 1.3001430152303739e-33\n", - "proton+OCC(O)[Pt]<=>OC=[Pt]+CO-2\n", - "kf = 21.19822615963559\n", - "krev = 2.8273094218491462e-14\n", - "Kc = 7.497667568967851e14\n", - "HX+O=CCO<=>OCC(O)[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 4.347223516290618e-14\n", - "Kc = 644231.1603064304\n", - "vacantX+vacantX+OCCO<=>HX+OCC(O)[Pt]\n", - "kf = 7.314142036323851e-21\n", - "krev = 492.5535033039904\n", - "Kc = 1.4849436634317805e-23\n", - "HX+OC=CO<=>OCC(O)[Pt]\n", - "kf = 5.6012337000223925e-8\n", - "krev = 1.5412075197181771e-21\n", - "Kc = 3.634315060340885e13\n", - "HOX+C=CO<=>OCC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 6.743155058263278e-19\n", - "Kc = 4.8491603395127426e10\n", - "proton+O=CCO.[Pt]<=>OCC(O)[Pt]\n", - "kf = 1.1751099635722393e10\n", - "krev = 2.6165323686065496e-10\n", - "Kc = 4.491096604312415e19\n", - "proton+OCC(O)[Pt]<=>H2O+OCC=[Pt]\n", - "kf = 94.52002480700446\n", - "krev = 2.1721444498187882e-10\n", - "Kc = 4.351461285868434e11\n", - "proton+OC=CO.[Pt]<=>OCC(O)[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 5.2914067977129154e-14\n", - "Kc = 9.449282943358521e23\n", - "proton+OCC(O)C#[Pt]<=>CX+OCCO\n", - "kf = 682.402665705397\n", - "krev = 9.146137340080099e-11\n", - "Kc = 7.461102324748392e12\n", - "vacantX+vacantX+CCC<=>CH3X+CC[Pt]\n", - "kf = 7.798842461270165e-20\n", - "krev = 4.754727023110295e15\n", - "Kc = 1.640229275700578e-35\n", - "proton+O=C([Pt])CO<=>OCC(O)=[Pt]\n", - "kf = 1.1387724551001077e-9\n", - "krev = 1.0085447542339825e12\n", - "Kc = 1.129124364902415e-21\n", - "proton+OCC(O)=[Pt]<=>H2O+OCC#[Pt]\n", - "kf = 2.102944101806726e6\n", - "krev = 2.1222813318800094e-47\n", - "Kc = 9.908884699767143e52\n", - "proton+OCC(O)=[Pt]<=>OC#[Pt]+CO-2\n", - "kf = 49681.794329643395\n", - "krev = 1.619563011452047e-41\n", - "Kc = 3.067604901960581e45\n", - "proton+OC=C(O)[Pt]<=>OCC(O)=[Pt]\n", - "kf = 4.3330274516676855e9\n", - "krev = 2.2436011536981487e9\n", - "Kc = 1.9312824137772955\n", - "proton+OCC(O)=[Pt]<=>OCC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.653410057160789e-56\n", - "Kc = 4.422109796959484e65\n", - "HX+COC=O<=>COC(O)[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 224.3395816271696\n", - "Kc = 1.2483828443014824e-10\n", - "proton+COC(O)[Pt]<=>OC=[Pt]+CO-2\n", - "kf = 7.322080914983208e7\n", - "krev = 1.5034306029083408e-18\n", - "Kc = 4.870248683789505e25\n", - "vacantX+vacantX+COCO<=>HX+COC(O)[Pt]\n", - "kf = 6.183244140051347e-23\n", - "krev = 2731.92216309053\n", - "Kc = 2.2633310068601865e-26\n", - "O=CO+CH3X<=>COC(O)[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 8.503469161971292e7\n", - "Kc = 3.7620485485108396e-16\n", - "proton+COC=O.[Pt]<=>COC(O)[Pt]\n", - "kf = 1.2622729508690855\n", - "krev = 0.21733806909375467\n", - "Kc = 5.807877819713996\n", - "proton+COC(O)[Pt]<=>H2O+COC=[Pt]\n", - "kf = 6.62483386040773e-8\n", - "krev = 1.624406101098726e-9\n", - "Kc = 40.783113631048195\n", - "vacantX+vacantX+CCOOC<=>COO[Pt]+CC[Pt]\n", - "kf = 1.4778859852656565e-10\n", - "krev = 2.404289853338368e13\n", - "Kc = 6.146871115450596e-24\n", - "vacantX+vacantX+CCOOC<=>CO[Pt]+CCO[Pt]\n", - "kf = 2.735304068777078e8\n", - "krev = 1.1929824589169815e-11\n", - "Kc = 2.2928284052560617e19\n", - "vacantX+vacantX+CCOOC<=>CH3X+CCOO[Pt]\n", - "kf = 1.542530561493995e-10\n", - "krev = 1.2789927244807063e12\n", - "Kc = 1.2060510837700736e-22\n", - "proton+COC(O)C#[Pt]<=>CX+COCO\n", - "kf = 5.096371548170163\n", - "krev = 1.334665402115114e-9\n", - "Kc = 3.8184638187920933e9\n", - "proton+COC(=O)[Pt]<=>COC(O)=[Pt]\n", - "kf = 1.7013748640380587e-8\n", - "krev = 1.0085447542339823e12\n", - "Kc = 1.6869602036949763e-20\n", - "proton+COC(O)=[Pt]<=>OC#[Pt]+CO-2\n", - "kf = 4.979908332469234e7\n", - "krev = 1.5792793738708088e-40\n", - "Kc = 3.1532789035694767e47\n", - "proton+COC(O)=[Pt]<=>H2O+COC#[Pt]\n", - "kf = 2.8272029837629057e7\n", - "krev = 9.315217559083137e-42\n", - "Kc = 3.035036987414363e48\n", - "proton+COC(O)=[Pt]<=>COC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.572502010357685e-47\n", - "Kc = 6.997896691875328e56\n", - "vacantX+vacantX+C=C=COO<=>OOC=[Pt]+C=C=[Pt]\n", - "kf = 1.9145907695639512e-44\n", - "krev = 1.1771971588384226e12\n", - "Kc = 1.626397715275781e-56\n", - "C=O+O=CC[Pt]<=>O=CCCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 0.0025285011306884937\n", - "Kc = 1.5664103465194285e-5\n", - "HX+O=CCC=O<=>O=CCCO[Pt]\n", - "kf = 5.113182125834635e-8\n", - "krev = 3.03538509820146e-7\n", - "Kc = 0.16845250142607343\n", - "proton+O=CCC=O.[Pt]<=>O=CCCO[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 3.035294805594631e-5\n", - "Kc = 1.6472864483489508e15\n", - "vacantX+vacantX+O=CCCO<=>HX+O=CCCO[Pt]\n", - "kf = 2.5157725911236352e-27\n", - "krev = 8837.406478086354\n", - "Kc = 2.84673178421957e-31\n", - "proton+O=CCCO[Pt]<=>OX+CCC=O\n", - "kf = 1.0053469908846067e8\n", - "krev = 5.485808774926133e-25\n", - "Kc = 1.8326322191173056e32\n", - "CHOX+C=C<=>O=CCC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 0.4688595936220698\n", - "Kc = 1.7478623517301195e-7\n", - "proton+O=CCC[Pt]<=>CH2X+CC=O\n", - "kf = 0.21718769045422626\n", - "krev = 2.002779166423329e-13\n", - "Kc = 1.0844315444028296e12\n", - "HX+C=CC=O<=>O=CCC[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 7.666152073113618e-12\n", - "Kc = 3780.924152337611\n", - "proton+O=CCC=[Pt]<=>O=CCC[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.918397706885573e-39\n", - "Kc = 5.082956175951557e48\n", - "vacantX+vacantX+O=CCCO<=>HOX+O=CCC[Pt]\n", - "kf = 8.901266563864654e-15\n", - "krev = 1.309728963703428e15\n", - "Kc = 6.79626610584771e-30\n", - "vacantX+vacantX+CCC=O<=>HX+O=CCC[Pt]\n", - "kf = 1.6716561102658422e-25\n", - "krev = 524619.2678123232\n", - "Kc = 3.186417680076247e-31\n", - "vacantX+vacantX+CC=COO<=>OOC=[Pt]+CC=[Pt]\n", - "kf = 3.7147962989308654e-50\n", - "krev = 4.0636001726377395e18\n", - "Kc = 9.141638303749602e-69\n", - "proton+C=COOC#[Pt]<=>CX+C=COO\n", - "kf = 1.941245658968684e-59\n", - "krev = 1.9443160961908433e9\n", - "Kc = 9.98420813761623e-69\n", - "vacantX+C=CC=O<=>C=CC=O.[Pt]\n", - "kf = 365995.57053717994\n", - "krev = 1.0054621985249468\n", - "Kc = 364007.290452202\n", - "proton+C=CC(=O)[Pt]<=>C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.5470432905792705e-19\n", - "Kc = 1.615985806747468e29\n", - "proton+O=CC=C[Pt]<=>C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.939852621840177e-35\n", - "Kc = 8.503827645738055e44\n", - "proton+C=CC=O.[Pt]<=>O=CCC[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 0.00012609781336559052\n", - "Kc = 1.9825879079693838e14\n", - "vacantX+vacantX+C=CC=O<=>HX+C=C([Pt])C=O\n", - "kf = 1.2784478936507186e-21\n", - "krev = 132.59733776930153\n", - "Kc = 9.641580405445367e-24\n", - "proton+C=C([Pt])C=O<=>C=O+C=C=[Pt]\n", - "kf = 3.1239379458734235e-11\n", - "krev = 5.024094937764025e-9\n", - "Kc = 0.006217911851927968\n", - "HX+C=C=C=O<=>C=C([Pt])C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.4992009477647154e-32\n", - "Kc = 1.1812081765045545e24\n", - "vacantX+vacantX+C=C(O)C=O<=>HOX+C=C([Pt])C=O\n", - "kf = 1.107119853181277e-14\n", - "krev = 2.5289157654010746e13\n", - "Kc = 4.377843929513773e-28\n", - "proton+C=C=C=O.[Pt]<=>C=C([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 8.140240591000901e-25\n", - "Kc = 3.0711622980330195e34\n", - "HX+C#CC=O<=>C=C([Pt])C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 1.683521621093348e-30\n", - "Kc = 1.753512730243651e22\n", - "proton+C=C([Pt])C=O<=>C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.4692339232304496e-35\n", - "Kc = 7.206201874309107e44\n", - "CHOX+C=C=O<=>C=C(C=O)O[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.906984656058423e-6\n", - "Kc = 0.017553122325364576\n", - "proton+C=C(C=O)O[Pt]<=>OX+C=CC=O\n", - "kf = 1759.880392627519\n", - "krev = 3.2877732722109866e-12\n", - "Kc = 5.352803392808232e14\n", - "vacantX+vacantX+C=C(O)C=O<=>HX+C=C(C=O)O[Pt]\n", - "kf = 8.336773502217888e-19\n", - "krev = 4.018028855986407\n", - "Kc = 2.0748416203624424e-19\n", - "vacantX+vacantX+COCOC<=>CH3X+COCO[Pt]\n", - "kf = 0.24675966205104702\n", - "krev = 5.277017405064255e15\n", - "Kc = 4.6761199198288865e-17\n", - "vacantX+vacantX+COCOC<=>CO[Pt]+COC[Pt]\n", - "kf = 4.1241018831024145e-7\n", - "krev = 7.782310155024181e12\n", - "Kc = 5.2993286067375974e-20\n", - "proton+C=CC=[Pt]<=>CHX+C=C\n", - "kf = 1.7365155933402038e8\n", - "krev = 4.134590691869886e-13\n", - "Kc = 4.199969773924241e20\n", - "vacantX+vacantX+C=CC=O<=>OX+C=CC=[Pt]\n", - "kf = 1.438969400016978e-30\n", - "krev = 1.6093339940290013e17\n", - "Kc = 8.941396909254915e-48\n", - "proton+C=CC#[Pt]<=>C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.766742910705455e-15\n", - "Kc = 6.637033796213575e24\n", - "vacantX+CC(O)O<=>CC(O)O.[Pt]\n", - "kf = 347843.58123444836\n", - "krev = 178209.4487483253\n", - "Kc = 1.9518806868971765\n", - "proton+CC(O)O[Pt]<=>CC(O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.796471055455441e-33\n", - "Kc = 4.31296900490357e42\n", - "vacantX+vacantX+COCCO<=>OC[Pt]+COC[Pt]\n", - "kf = 1.3358759661274015e-7\n", - "krev = 3.1165281946439875e14\n", - "Kc = 4.286423490161954e-22\n", - "vacantX+vacantX+COCCO<=>CO[Pt]+OCC[Pt]\n", - "kf = 6.192873660096324e-8\n", - "krev = 3.90827625278604e13\n", - "Kc = 1.584553716150872e-21\n", - "vacantX+vacantX+COCCO<=>CH3X+OCCO[Pt]\n", - "kf = 4.52195120819324e-12\n", - "krev = 5.920081591014324e14\n", - "Kc = 7.638325821483257e-27\n", - "proton+OC(O)C[Pt]<=>CH2X+OCO\n", - "kf = 2.9228830020630096e-5\n", - "krev = 1.1970265496551398e-9\n", - "Kc = 24417.86276925173\n", - "HOX+C=CO<=>OC(O)C[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 6.095879365149742e-19\n", - "Kc = 5.364056293281289e10\n", - "HX+C=C(O)O<=>OC(O)C[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 1.7806643358524245e-19\n", - "Kc = 1.572793251160735e11\n", - "vacantX+vacantX+CC(O)O<=>HX+OC(O)C[Pt]\n", - "kf = 2.610914590914038e-25\n", - "krev = 48838.0104312493\n", - "Kc = 5.3460707507516085e-30\n", - "vacantX+vacantX+CCC(O)O<=>CH3X+OC(O)C[Pt]\n", - "kf = 2.73273606062798e-19\n", - "krev = 1.7143250273592365e15\n", - "Kc = 1.594059479396106e-34\n", - "proton+OC(O)C[Pt]<=>CC(O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.587375799156772e-36\n", - "Kc = 6.968882380785518e45\n" - ] - } - ], - "source": [ - "for (i,rxn) in enumerate(inter.reactions)\n", - " str = getrxnstr(rxn)\n", - " kf = inter.kfs[i]\n", - " krev = inter.krevs[i]\n", - " Kc = kf/krev\n", - " println(str)\n", - " println(\"kf = $kf\")\n", - " println(\"krev = $krev\")\n", - " println(\"Kc = $Kc\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 75, - "id": "ef575a57", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "10962-element SparseArrays.SparseVector{Float64, Int64} with 528 stored entries:\n", - " [47 ] = 2767.01\n", - " [48 ] = 25.5592\n", - " [49 ] = 25.5592\n", - " [50 ] = 0.00155335\n", - " [53 ] = 25.5592\n", - " [54 ] = 25.5592\n", - " [56 ] = 6.13485e-8\n", - " ⋮\n", - " [10084] = -3.00535e-29\n", - " [10087] = 6.07876e-36\n", - " [10088] = 3.16019e-34\n", - " [10242] = 3.39005\n", - " [10243] = 1154.72\n", - " [10253] = -6.63785e-5\n", - " [10264] = -2.05407e-8\n", - " [10266] = -1.43934e-8" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "rops(ssys, \"CH2O2X\", 1e-12)" - ] - }, - { - "cell_type": "code", - "execution_count": 76, - "id": "6852cfa6", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "10962-element SparseArrays.SparseVector{Float64, Int64} with 17 stored entries:\n", - " [10253] = 6.63785e-5\n", - " [10254] = 1.42545e-7\n", - " [10255] = 4.41868e-32\n", - " [10256] = 4.65077e-34\n", - " [10265] = 5.7985e-17\n", - " [10268] = 1.57587e-18\n", - " [10273] = 0.000235443\n", - " ⋮\n", - " [10310] = 1.34103e-49\n", - " [10352] = 3.68017e-28\n", - " [10540] = 9.71107e-29\n", - " [10555] = 1.48134e-30\n", - " [10835] = 1.0098e-27\n", - " [10865] = 4.21006e-22\n", - " [10867] = 6.60825e-41\n", - " [10908] = 2.45269e-16" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "rops(ssys, \"O=CO\", 1e-12)" - ] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.9.1", - "language": "julia", - "name": "julia-1.9" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.9.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/CO2RR_RMS/Ag/CO2RR_RMS_Diffusion_Interface_1.jl b/CO2RR_RMS/Ag/CO2RR_RMS_Diffusion_Interface_1.jl new file mode 100644 index 0000000..25212b8 --- /dev/null +++ b/CO2RR_RMS/Ag/CO2RR_RMS_Diffusion_Interface_1.jl @@ -0,0 +1,299 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,jl:percent +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.17.2 +# kernelspec: +# display_name: Julia 1.9.1 +# language: julia +# name: julia-1.9 +# --- + +# %% +using ReactionMechanismSimulator +using PyPlot +using Sundials +using SciMLBase +using QuadGK + +# %% +outdict = readinput("chem300.rms") + +# %% +boundarylayerspcs = outdict["gas"]["Species"] +boundarylayerrxns = outdict["gas"]["Reactions"] +surfspcs = outdict["surface"]["Species"] +surfrxns = outdict["surface"]["Reactions"] +interfacerxns = outdict[Set(["surface", "gas"])]["Reactions"] +solv = outdict["Solvents"][1]; + +# %% +sitedensity = 2.292e-5; # Ag111 site density is 2.292e-9 mol/cm^2 or 2.292e-5 mol/m^2 +boundarylayer = IdealDiluteSolution(boundarylayerspcs,boundarylayerrxns,solv,name="boundarylayeruid",diffusionlimited=true); +surf = IdealSurface(surfspcs,surfrxns,sitedensity,name="surface"); + +# %% +# Reservoir is a 100 mL (100e-6 m^3) cell +# Proton concentration is 10^-7 mol/L (10^-4 mol/m^3) +# CO2 concentration is 0.01 mol/L (10 mol/m^3), saturation solubility ~0.03 mol/L +# AVratio in experiments is 36 m^-1 but is measured by surface area/reservoir volume +# Area of the electrode is therefore 3.6e1 m^-1 * 1e2*1e-6 m^3 = 3.6e-3 m^2 = 36 cm^2 +# Assume boundary layer thickness d_bl = 1 mm or 1e-3 m +# Volume of the boundary layer V_bl = 3.6e-3 m^2 * 1e-3 m = 3.6e-6 m^3 +# Actual AVratio is therefore 3.6e-3 m^2 / 3.6e-6 m^3 = 1e3 m^-1 (reciprocal of d_bl) +# Amount of sites is 2.292e-5 mol/m^2 * 1e3 m^-1 = 2.292e-2 mol/m^-3 + +C_proton = 1e-7*1e3; +C_co2 = 1e-2*1e3; +C_default = 1e-12; +V_res = 1000.0e-6; +AVratio = 1e3; +A_surf = 100.0e-6*36; +V_bl = A_surf/AVratio; +sites = sitedensity; + +initialcondsboundarylayer = Dict(["proton"=>C_proton, + "CO2"=>C_co2, + "V"=>V_bl,"T"=>300,"Phi"=>0.0,"d"=>0.0]); +initialcondsreservoir = Dict(["proton"=>C_proton, + "CO2"=>C_co2, + "V"=>V_res,"T"=>300]); + + +# Assume voltage is -0.5 V vs. R.H.E. which equates to -0.914 V vs. S.H.E. at pH=7 +initialcondssurf = Dict(["CO2X"=>0.4*sites, + "CHO2X"=>0.1*sites, + "CO2HX"=>0.1*sites, + "OX"=>0.1*sites, + "OCX"=>0.1*sites, + "vacantX"=>0.1*sites, + "CH2O2X"=>0.05*sites, + "CHOX"=>0.04*sites, + "CH2OX"=>0.01*sites, + "A"=>A_surf,"T"=>300,"Phi"=>-1.5]); + +# %% +domainboundarylayer, y0boundarylayer, pboundarylayer = ConstantTVDomain(phase=boundarylayer, initialconds=initialcondsboundarylayer); +domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf, + initialconds=initialcondssurf); + +# %% +inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainboundarylayer, + domaincat,interfacerxns,298.15,A_surf); + +# %% +# start with 1mm layer thickness +diffusionlayer = ConstantReservoirDiffusion(domainboundarylayer, initialcondsreservoir, A_surf, 1/AVratio); + +# %% +interfaces = [inter, diffusionlayer]; + +# %% +@time react,y0,p = Reactor((domainboundarylayer,domaincat), (y0boundarylayer,y0cat), (0.0, 1e3), interfaces, (pboundarylayer,pcat,pinter)); + +# %% +@time sol = solve(react.ode,Sundials.CVODE_BDF(),abstol=1e-22,reltol=1e-8); + +# %% +sol.t[end] + +# %% +sol.retcode + +# %% +ssys = SystemSimulation(sol,(domainboundarylayer,domaincat,), interfaces,p); + +# %% +plotmolefractions(ssys.sims[1], 1e-8,tol=1e-25) +yscale("log") +xscale("log") + +# %% +plotmolefractions(ssys.sims[2], 1e-8,tol=3e-2) +xscale("log") + +# %% +concentrations(ssys.sims[1], 1e3) + +# %% +""" +diffusive flux to the reservoir +""" +function flux_to_reservoir(sim,t,reservoirinterface) + cs = concentrations(sim,t) + return reservoirinterface.A .* sim.domain.diffusivity .* (cs - reservoirinterface.c) / reservoirinterface.layer_thickness +end + +""" +Integrates the flux to the reservoir and computes the concentration assuming +there is no prior concentration of that species in the reservoir +""" +function get_reservoir_concentration(sim,t,reservoirinterface,Vres) + intg,err = quadgk(x -> flux_to_reservoir(sim,x,reservoirinterface), 0, t) + return intg./Vres +end + +# %% +flux_to_reservoir(ssys.sims[1],1e2,diffusionlayer) + +# %% +res_cs = get_reservoir_concentration(ssys.sims[1],1e2,diffusionlayer,1.0) + +# %% +sort(res_cs) + +# %% +getfield.(ssys.sims[1].domain.phase.species,:name) + +# %% +getfield.(ssys.sims[2].domain.phase.species,:name) + +# %% +# Helper function +function plotX(sim, tol, t_end, exclude) + clf() + xs = molefractions(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Mole Fraction") +end + +# %% +# Helper function +function plotC(sim, tol, t_end, exclude) + clf() + xs = concentrations(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Concentration") +end + +# %% +exclude_species = ["H2O"] +plotX(ssys.sims[1], 1e-25, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1) +ylim(1e-25, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V") +gcf() + +# %% +exclude_species = ["H2O"] +plotC(ssys.sims[1], 1e-25, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1) +ylim(1e-25, 1e8) +title("Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys.sims[2], 1e-2, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e-8) +ylim(1e-6, 5) +title("Surface Mole Fractions vs. Time on Ag111@-0.5V") +gcf() + +# %% +exclude_species = ["H2O"] +plotC(ssys.sims[2], 1e-4, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1) +ylim(1e-6, 1) +title("Surface Concentrations vs. Time on Ag111@-0.5V") +gcf() + +# %% +getfluxdiagram(ssys,1e-8;speciesratetolerance=1e-8) + +# %% +plotrops(ssys,"CH2O2X",1e-8;N=15,tol=0.0) + +# %% +plotrops(ssys,"CHO2X",1;N=10,tol=0.0) + +# %% +plotrops(ssys,"CO2HX",1;N=10,tol=0.0) + +# %% +plotrops(ssys,"OX",1;N=10,tol=0.0) + +# %% +plotrops(ssys,"OCX",1.0e-6) + +# %% +for (i,rxn) in enumerate(domaincat.phase.reactions) + str = getrxnstr(rxn) + kf = inter.kfs[i] + krev = inter.krevs[i] + Kc = kf/krev + println(str) + println("kf = $kf") + println("krev = $krev") + println("Kc = $Kc") +end + +# %% +for (i,rxn) in enumerate(domaincat.reactions) + str = getrxnstr(rxn) + kf = inter.kfs[i] + krev = inter.krevs[i] + Kc = kf/krev + println(str) + println("kf = $kf") + println("krev = $krev") + println("Kc = $Kc") +end + +# %% +for (i,rxn) in enumerate(inter.reactions) + str = getrxnstr(rxn) + kf = inter.kfs[i] + krev = inter.krevs[i] + Kc = kf/krev + println(str) + println("kf = $kf") + println("krev = $krev") + println("Kc = $Kc") +end + +# %% +rops(ssys, "CH2O2X", 1e-12) + +# %% +rops(ssys, "O=CO", 1e-12) diff --git a/CO2RR_RMS/Ag/CO2RR_RMS_Diffusion_Interface_Matt.ipynb b/CO2RR_RMS/Ag/CO2RR_RMS_Diffusion_Interface_Matt.ipynb deleted file mode 100644 index 30c3917..0000000 --- a/CO2RR_RMS/Ag/CO2RR_RMS_Diffusion_Interface_Matt.ipynb +++ /dev/null @@ -1,7147 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 41, - "id": "8a590634", - "metadata": {}, - "outputs": [], - "source": [ - "using ReactionMechanismSimulator\n", - "using PyPlot\n", - "using Sundials\n", - "using SciMLBase\n", - "using QuadGK" - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "id": "e941d4fb", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[06:16:05] WARNING: not removing hydrogen atom without neighbors\n", - "[06:16:05] WARNING: not removing hydrogen atom without neighbors\n", - "┌ Warning: failed to generate StokesDiffusivity model for species vacantX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2O2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species H2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [H][H].[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(=O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH3X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(C#[Pt])CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)C(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C([Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C([Pt])CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC([Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=[Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC([Pt])=C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=C=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC(=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCOC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCC(=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC([Pt])=C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=COC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCOO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C=CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])CCO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)C(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)C(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC([Pt])OC=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=[Pt])OC=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC([Pt])=CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C([Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(C=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n" - ] - }, - { - "data": { - "text/plain": [ - "Dict{Any, Any} with 4 entries:\n", - " \"Solvents\" => Solvent[Solvent(\"water\", RiedelViscosity{Float64}(…\n", - " Set([\"surface\", \"gas\"]) => Dict{Any, Any}(\"Reactions\"=>ElementaryReaction[vac…\n", - " \"gas\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…\n", - " \"surface\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "outdict = readinput(\"chem300.rms\")\n" - ] - }, - { - "cell_type": "code", - "execution_count": 43, - "id": "fe2767e9", - "metadata": {}, - "outputs": [], - "source": [ - "boundarylayerspcs = outdict[\"gas\"][\"Species\"]\n", - "boundarylayerrxns = outdict[\"gas\"][\"Reactions\"]\n", - "surfspcs = outdict[\"surface\"][\"Species\"]\n", - "surfrxns = outdict[\"surface\"][\"Reactions\"]\n", - "interfacerxns = outdict[Set([\"surface\", \"gas\"])][\"Reactions\"]\n", - "solv = outdict[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "id": "c54ee65e", - "metadata": {}, - "outputs": [], - "source": [ - "sitedensity = 2.292e-5; # Ag111\n", - "boundarylayer = IdealDiluteSolution(boundarylayerspcs,boundarylayerrxns,solv,name=\"boundarylayeruid\",diffusionlimited=true);\n", - "surf = IdealSurface(surfspcs,surfrxns,sitedensity,name=\"surface\");" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8894c84d", - "metadata": {}, - "outputs": [], - "source": [ - "initialcondsboundarylayer = Dict([\"proton\"=>10.0^-4,\n", - " \"CO2\"=>10.0^-3*10^6,\n", - " \"V\"=>1.0e-3,\"T\"=>300,\"Phi\"=>0.0,\"d\"=>0.0]);\n", - "initialcondsreservoir = Dict([\"proton\"=>10.0^-4,\n", - " \"CO2\"=>10.0^-3*10^6,\n", - " \"V\"=>1.0,\"T\"=>300]);\n", - "AVratio = 1e5;\n", - "initialcondssurf = Dict([\"CO2X\"=>0.4*sitedensity*AVratio,\n", - "# \"CHO2X\"=>0.1*sitedensity*AVratio,\n", - "# \"CO2HX\"=>0.1*sitedensity*AVratio,\n", - "# \"OX\"=>0.1*sitedensity*AVratio,\n", - "# \"OCX\"=>0.1*sitedensity*AVratio,\n", - " \"vacantX\"=>1.0*sitedensity*AVratio,\n", - "# \"CH2O2X\"=>0.05*sitedensity*AVratio,\n", - "# \"CHOX\"=>0.04*sitedensity*AVratio,\n", - "# \"CH2OX\"=>0.01*sitedensity*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>300,\"Phi\"=>-1.0]);" - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "id": "ddb39b3d", - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "domainboundarylayer, y0boundarylayer, pboundarylayer = ConstantTVDomain(phase=boundarylayer, initialconds=initialcondsboundarylayer);\n", - "domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf,\n", - " initialconds=initialcondssurf);" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "id": "ed49d2b4", - "metadata": {}, - "outputs": [], - "source": [ - "inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainboundarylayer,\n", - " domaincat,interfacerxns,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "id": "dee14906", - "metadata": {}, - "outputs": [], - "source": [ - "# start with 1mm layer thickness\n", - "diffusionlayer = ConstantReservoirDiffusion(domainboundarylayer, initialcondsreservoir, AVratio*1.0, 1e-3);" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "id": "e70ac4b0", - "metadata": {}, - "outputs": [], - "source": [ - "interfaces = [inter, diffusionlayer];" - ] - }, - { - "cell_type": "code", - "execution_count": 50, - "id": "244f0912", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.067722 seconds (61.60 k allocations: 139.523 MiB, 21.90% gc time)\n" - ] - } - ], - "source": [ - "@time react,y0,p = Reactor((domainboundarylayer,domaincat), (y0boundarylayer,y0cat), (0.0, 100.0), interfaces, (pboundarylayer,pcat,pinter));\n" - ] - }, - { - "cell_type": "code", - "execution_count": 51, - "id": "962f838c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 4.182686 seconds (3.17 M allocations: 10.057 GiB, 23.77% gc time)\n" - ] - } - ], - "source": [ - "@time sol = solve(react.ode,Sundials.CVODE_BDF(),abstol=1e-16,reltol=1e-6);" - ] - }, - { - "cell_type": "code", - "execution_count": 52, - "id": "56b6f906", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "100.0" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sol.t[end]" - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "id": "4714593e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ReturnCode.Success = 1" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sol.retcode" - ] - }, - { - "cell_type": "code", - "execution_count": 54, - "id": "6667bb5a", - "metadata": {}, - "outputs": [], - "source": [ - "ssys = SystemSimulation(sol,(domainboundarylayer,domaincat,), interfaces,p);" - ] - }, - { - "cell_type": "code", - "execution_count": 55, - "id": "abcf6608", - "metadata": {}, - "outputs": [], - "source": [ - "plotmolefractions(ssys.sims[1], 0.99e2,tol=1e-25)\n", - "yscale(\"log\")\n", - "xscale(\"log\")" - ] - }, - { - "cell_type": "code", - "execution_count": 56, - "id": "afae3194", - "metadata": {}, - "outputs": [], - "source": [ - "plotmolefractions(ssys.sims[2], 0.99e2,tol=3e-2)\n", - "xscale(\"log\")" - ] - }, - { - "cell_type": "code", - "execution_count": 57, - "id": "d4939a87", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "get_reservoir_concentration" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "\"\"\"\n", - "diffusive flux to the reservoir\n", - "\"\"\"\n", - "function flux_to_reservoir(sim,t,reservoirinterface)\n", - " cs = concentrations(sim,t)\n", - " return reservoirinterface.A .* sim.domain.diffusivity .* (cs - reservoirinterface.c) / reservoirinterface.layer_thickness\n", - "end\n", - "\n", - "\"\"\"\n", - "Integrates the flux to the reservoir and computes the concentration assuming\n", - "there is no prior concentration of that species in the reservoir\n", - "\"\"\"\n", - "function get_reservoir_concentration(sim,t,reservoirinterface,Vres)\n", - " intg,err = quadgk(x -> flux_to_reservoir(sim,x,reservoirinterface), 0, t)\n", - " return intg./Vres\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 58, - "id": "4d4dfc9c", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "108-element Vector{Float64}:\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 2.127051950376656e-25\n", - " -3.510243060654668e-24\n", - " -8.96648312396144e-32\n", - " ⋮\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "flux_to_reservoir(ssys.sims[1],0.99e2,diffusionlayer)" - ] - }, - { - "cell_type": "code", - "execution_count": 59, - "id": "782dc215", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "108-element Vector{Float64}:\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 999.0002936231041\n", - " 9.990001587581694e-5\n", - " 0.0\n", - " -1.467825103225412e-21\n", - " -6.296704606711658e-22\n", - " -8.269101685197958e-22\n", - " ⋮\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "res_cs = get_reservoir_concentration(ssys.sims[1],0.99e2,diffusionlayer,1.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 60, - "id": "e8885c97", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "108-element Vector{Float64}:\n", - " -3.510028156283103e-20\n", - " -1.467825103225412e-21\n", - " -8.269101685197958e-22\n", - " -6.296704606711658e-22\n", - " -4.143209291884549e-22\n", - " -2.4664908632623496e-22\n", - " -1.4501328070805046e-22\n", - " -2.4297366095524073e-24\n", - " -4.26741575269268e-27\n", - " -1.7565743538985845e-30\n", - " ⋮\n", - " 2.9311480681523782e-24\n", - " 6.298841337396956e-23\n", - " 1.2552996666635814e-22\n", - " 3.8512926576472575e-22\n", - " 1.2001691194545139e-21\n", - " 1.9879062943569044e-21\n", - " 6.998718825476003e-21\n", - " 9.990001587581694e-5\n", - " 999.0002936231041" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sort(res_cs)" - ] - }, - { - "cell_type": "code", - "execution_count": 61, - "id": "9606a8ed", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "108-element Vector{String}:\n", - " \"Ar\"\n", - " \"He\"\n", - " \"Ne\"\n", - " \"N2\"\n", - " \"CO2\"\n", - " \"proton\"\n", - " \"H\"\n", - " \"C=O\"\n", - " \"O=CO\"\n", - " \"H2O\"\n", - " ⋮\n", - " \"CCOCO\"\n", - " \"CCCOO\"\n", - " \"CCC\"\n", - " \"CCOOC\"\n", - " \"C=C=COO\"\n", - " \"CC=COO\"\n", - " \"C=CCO[O]\"\n", - " \"COCOC\"\n", - " \"COCCO\"" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "getfield.(ssys.sims[1].domain.phase.species,:name)" - ] - }, - { - "cell_type": "code", - "execution_count": 62, - "id": "9be02a3e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "192-element Vector{String}:\n", - " \"vacantX\"\n", - " \"CO2X\"\n", - " \"CHO2X\"\n", - " \"CO2HX\"\n", - " \"OCX\"\n", - " \"OX\"\n", - " \"CH2O2X\"\n", - " \"CHOX\"\n", - " \"CH2OX\"\n", - " \"HOX\"\n", - " ⋮\n", - " \"O=CCCO[Pt]\"\n", - " \"O=CCC[Pt]\"\n", - " \"C=COOC#[Pt]\"\n", - " \"C=CC=O.[Pt]\"\n", - " \"C=C([Pt])C=O\"\n", - " \"C=C(C=O)O[Pt]\"\n", - " \"C=CC=[Pt]\"\n", - " \"CC(O)O.[Pt]\"\n", - " \"OC(O)C[Pt]\"" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "getfield.(ssys.sims[2].domain.phase.species,:name)" - ] - }, - { - "cell_type": "code", - "execution_count": 63, - "id": "87dcaf99", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotX (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotX(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = molefractions(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Mole Fraction\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 64, - "id": "ddf6da6b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotC (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotC(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = concentrations(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Concentration\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 65, - "id": "386a52a2", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "108×2718 Matrix{Float64}:\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 … 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 1.0e6 1.0e6 1.0e6 1.0e6 1.0e6 1.0e6 1000.0 1000.0\n", - " 0.1 0.1 0.1 0.1 0.1 0.1 … 0.0001 0.0001\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 1.26649e-24 1.70973e-24\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 -1.08044e-22 2.70162e-24\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 -2.08817e-30 -5.98544e-32\n", - " ⋮ ⋮ ⋱ \n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 … 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 … 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "concentrations(ssys.sims[1])" - ] - }, - { - "cell_type": "code", - "execution_count": 66, - "id": "da1def09", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "192×2718 Matrix{Float64}:\n", - " 2.292e-5 2.292e-5 2.292e-5 … 1.48811e-9 1.48778e-9\n", - " 9.168e-6 9.168e-6 9.16803e-6 2.67667e-6 2.67609e-6\n", - " 0.0 3.24252e-16 2.68962e-15 3.72688e-11 3.72614e-11\n", - " 0.0 2.91093e-18 2.41457e-17 2.79838e-11 2.79778e-11\n", - " 0.0 4.98345e-26 3.06528e-24 2.18384e-11 2.18338e-11\n", - " 0.0 1.77024e-40 1.0888e-38 … 3.77888e-17 3.7788e-17\n", - " 0.0 5.58937e-24 3.43799e-22 2.45322e-5 2.45235e-5\n", - " 0.0 8.53155e-34 3.83663e-31 2.05333e-10 2.05293e-10\n", - " 0.0 1.0452e-42 3.42982e-39 7.18635e-9 7.18497e-9\n", - " 0.0 3.03063e-48 1.36279e-45 7.40575e-19 7.40568e-19\n", - " ⋮ ⋱ \n", - " 0.0 7.44284e-106 7.87499e-97 1.84255e-24 1.84169e-24\n", - " 0.0 3.7116e-143 2.15143e-126 5.74841e-29 5.74626e-29\n", - " 0.0 0.0 8.02521e-256 … 3.6977e-80 3.69116e-80\n", - " 0.0 4.10532e-147 8.28194e-117 1.62355e-26 1.62278e-26\n", - " 0.0 7.16192e-143 1.43798e-127 3.20669e-43 3.20538e-43\n", - " 0.0 4.40393e-195 1.07731e-146 -3.82267e-47 9.8272e-48\n", - " 0.0 5.00958e-203 5.55362e-151 1.03891e-38 1.03856e-38\n", - " 0.0 5.74078e-104 4.36787e-89 … 7.76022e-19 7.75873e-19\n", - " 0.0 1.59781e-96 1.23158e-88 3.57634e-24 3.57635e-24" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "concentrations(ssys.sims[2])" - ] - }, - { - "cell_type": "code", - "execution_count": 67, - "id": "e719a85d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys.sims[1], 1e-6, 1e2, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e2)\n", - "ylim(1e-9, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 68, - "id": "1ef78267", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotC(ssys.sims[1], 1e-6, 1e2, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e2)\n", - "ylim(1e-6, 1e8)\n", - "title(\"Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 69, - "id": "1ee8224d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotC(ssys.sims[2], 1e-6, 1e2, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e2)\n", - "ylim(1e-6, 1e-4)\n", - "title(\"Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 70, - "id": "1f7d8918", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "1406×1462 Array{RGB{N0f8},2} with eltype ColorTypes.RGB{FixedPointNumbers.N0f8}:\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "getfluxdiagram(ssys,1e2;speciesratetolerance=1e-6)" - ] - }, - { - "cell_type": "code", - "execution_count": 71, - "id": "36206466", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[\"Ar\", \"He\", \"Ne\", \"N2\", \"CO2\", \"proton\", \"H\", \"C=O\", \"O=CO\", \"H2O\", \"O=CC=O\", \"H2\", \"OO\", \"CO\", \"O2\", \"O=C=C=O\", \"C=C=O\", \"O=C=CO\", \"CH4\", \"COC=O\", \"COO\", \"CO-2\", \"COOC\", \"O=CCO\", \"OCO\", \"COCO\", \"OCCO\", \"OC=CO\", \"O=O\", \"C=CO\", \"C=C\", \"O=C=C=C=O\", \"C#COO[CH2]\", \"C#COC[O]\", \"CC=O\", \"O=C=CC=O\", \"C=C(O)O\", \"CC(=O)O\", \"[OH]\", \"CC(=O)C=O\", \"COC(C)=O\", \"CC(=O)CO\", \"O=CCC=O\", \"COC=C=O\", \"O=C=CCO\", \"[CH2]OOC=C\", \"C=COC[O]\", \"C=CC=O\", \"C=COC=O\", \"O=CC=CO\", \"COC\", \"CCO\", \"CC(O)O\", \"CCOC=O\", \"COCC=O\", \"CCOO\", \"CC(C)=O\", \"C=C=C=O\", \"CC=C=O\", \"CC\", \"O=C=C=CO\", \"[CH2]OCC=O\", \"[O]CCC=O\", \"[CH2]COC=O\", \"[CH3]\", \"O=CCCO\", \"CCC=O\", \"CC(O)=C=O\", \"[CH]=O\", \"C[O]\", \"CC(O)C=O\", \"[CH2]O\", \"C=C(O)C=O\", \"OC=CCO\", \"C=CCO\", \"[CH]=C\", \"C[CH2]\", \"C=C=CO\", \"C=C=C\", \"C=C=C(O)O\", \"C=CC(=O)O\", \"CC=CO\", \"C=CC\", \"CC=C(O)O\", \"CCC(=O)O\", \"C=COO\", \"C#C\", \"C=COC\", \"C=CC(O)O\", \"C=COCO\", \"C=CCOO\", \"C=COOC\", \"CC(O)=CO\", \"C=C(C)O\", \"C#CC=O\", \"OC=C=CO\", \"CCOC\", \"CCCO\", \"CCC(O)O\", \"CCOCO\", \"CCCOO\", \"CCC\", \"CCOOC\", \"C=C=COO\", \"CC=COO\", \"C=CCO[O]\", \"COCOC\", \"COCCO\", \"vacantX\", \"CO2X\", \"CHO2X\", \"CO2HX\", \"OCX\", \"OX\", \"CH2O2X\", \"CHOX\", \"CH2OX\", \"HOX\", \"HX\", \"CO[Pt]\", \"OC[Pt]\", \"OC(O)[Pt]\", \"OCO[Pt]\", \"H2OX\", \"OC=[Pt]\", \"O=CC(=O)[Pt]\", \"OC#[Pt]\", \"O=CC=O.[Pt]\", \"[H][H].[Pt]\", \"O=COC[Pt]\", \"OO[Pt]\", \"CX\", \"CHX\", \"CH2X\", \"O=COC#[Pt]\", \"O=CCO[Pt]\", \"O=O.[Pt]\", \"O=CC#[Pt]\", \"OC(O)=[Pt]\", \"O=C(O)C#[Pt]\", \"O=C=C=O.[Pt]\", \"OOC[Pt]\", \"C=C=O.[Pt]\", \"COC(=O)[Pt]\", \"CC(=O)[Pt]\", \"O=COCC#[Pt]\", \"O=C([Pt])CO\", \"O=CCC(=O)[Pt]\", \"OCC#[Pt]\", \"OC(O)C#[Pt]\", \"OCOC#[Pt]\", \"O=CCOC#[Pt]\", \"O=C=C[Pt]\", \"COC#[Pt]\", \"O=CC(=O)C#[Pt]\", \"O=COC=[Pt]\", \"O=C=CC#[Pt]\", \"CC#[Pt]\", \"O=C=CO[Pt]\", \"COC(=O)C#[Pt]\", \"O=C=CC(=O)[Pt]\", \"O=CCC#[Pt]\", \"CH3X\", \"O=C=CO.[Pt]\", \"O=C=C=[Pt]\", \"CC(=O)C#[Pt]\", \"O=C(C#[Pt])CO\", \"COC=O.[Pt]\", \"CC(=O)C(=O)[Pt]\", \"OOC#[Pt]\", \"O=CC[Pt]\", \"O=CC=[Pt]\", \"C.[Pt]\", \"O=C=CC=O.[Pt]\", \"CC(=O)O[Pt]\", \"CC(=O)OC#[Pt]\", \"O=C=C([Pt])C=O\", \"O=C=COC#[Pt]\", \"COO[Pt]\", \"CO.[Pt]\", \"O=C=C(O)[Pt]\", \"O=C=C(O)C#[Pt]\", \"COOC#[Pt]\", \"O=CC(O)[Pt]\", \"O=CC(O)C#[Pt]\", \"O=CC(O)=[Pt]\", \"OCO.[Pt]\", \"O=C=C=C=O.[Pt]\", \"O=CCO.[Pt]\", \"OCC=[Pt]\", \"O=C=CCO.[Pt]\", \"O=C=CC(O)[Pt]\", \"O=C=CC=[Pt]\", \"O=C=C([Pt])CO\", \"O=C=CC[Pt]\", \"O=C=CC(O)=[Pt]\", \"O=C=CCO[Pt]\", \"O=CC([Pt])C=O\", \"O=CC(=[Pt])C=O\", \"O=CCC=O.[Pt]\", \"O=CCC=[Pt]\", \"OOCC#[Pt]\", \"C=C=[Pt]\", \"O=C(O)C=[Pt]\", \"CC=O.[Pt]\", \"CC=[Pt]\", \"CC=C=O.[Pt]\", \"O=C(O)C[Pt]\", \"O=C(O)CC#[Pt]\", \"CC([Pt])=C=O\", \"CC(=C=O)O[Pt]\", \"C=C.[Pt]\", \"C=C[Pt]\", \"C=CC#[Pt]\", \"CC(=O)O.[Pt]\", \"C=CC(=O)[Pt]\", \"O=CC=CO[Pt]\", \"C=CO[Pt]\", \"C=COC(=O)[Pt]\", \"C=COC#[Pt]\", \"CC(O)=[Pt]\", \"O=CC=C[Pt]\", \"C=CC(=O)O[Pt]\", \"OC=C=[Pt]\", \"CC[Pt]\", \"CCC#[Pt]\", \"CCO[Pt]\", \"CCOC(=O)[Pt]\", \"CCC(=O)[Pt]\", \"CCOC#[Pt]\", \"CCC(=O)O[Pt]\", \"CC(O)=C=O.[Pt]\", \"OOC=[Pt]\", \"OO.[Pt]\", \"COCO[Pt]\", \"COCC(=O)[Pt]\", \"COCOC#[Pt]\", \"COCC#[Pt]\", \"COC[Pt]\", \"COC=[Pt]\", \"COC=C=O.[Pt]\", \"O=C=COC[Pt]\", \"COC([Pt])=C=O\", \"O=C=COC=[Pt]\", \"CCOO[Pt]\", \"O=C=C=CO.[Pt]\", \"O=C=C=C(O)[Pt]\", \"O=C=C=C[Pt]\", \"OC=CO.[Pt]\", \"OC=C(O)[Pt]\", \"OC=C[Pt]\", \"OC=CO[Pt]\", \"OC=COC#[Pt]\", \"O=C([Pt])C=CO\", \"OC=C(O)C#[Pt]\", \"OC=CC#[Pt]\", \"OCC[Pt]\", \"OCCC#[Pt]\", \"O=C([Pt])CCO\", \"OCCO[Pt]\", \"OCCOC#[Pt]\", \"O=C=C=C=[Pt]\", \"C=CO.[Pt]\", \"C=C(O)[Pt]\", \"C=C(O)O[Pt]\", \"C=C(O)OC#[Pt]\", \"C=C(O)C#[Pt]\", \"C=C(O)C(=O)[Pt]\", \"C=COO[Pt]\", \"O=CC=C=[Pt]\", \"C=C=C=O.[Pt]\", \"O=C=C=CO[Pt]\", \"CC(O)[Pt]\", \"CC(O)C#[Pt]\", \"CC(O)O[Pt]\", \"CC(O)C(=O)[Pt]\", \"CC(O)OC#[Pt]\", \"O=C=C(O)C[Pt]\", \"O=C=C(O)C=[Pt]\", \"CC([Pt])OC=O\", \"CC(=[Pt])OC=O\", \"O=CC=CO.[Pt]\", \"O=CC=C(O)[Pt]\", \"O=CC([Pt])=CO\", \"OC=CC=[Pt]\", \"OCC(O)[Pt]\", \"OCC(O)C#[Pt]\", \"OCC(O)=[Pt]\", \"COC(O)[Pt]\", \"COC(O)C#[Pt]\", \"COC(O)=[Pt]\", \"O=CCCO[Pt]\", \"O=CCC[Pt]\", \"C=COOC#[Pt]\", \"C=CC=O.[Pt]\", \"C=C([Pt])C=O\", \"C=C(C=O)O[Pt]\", \"C=CC=[Pt]\", \"CC(O)O.[Pt]\", \"OC(O)C[Pt]\"]\n" - ] - } - ], - "source": [ - "println(ssys.names)" - ] - }, - { - "cell_type": "code", - "execution_count": 83, - "id": "8a278180", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "10962-element SparseArrays.SparseVector{Float64, Int64} with 17 stored entries:\n", - " [10253] = 1.81165e-7\n", - " [10254] = 2.86301e-26\n", - " [10255] = -2.17534e-23\n", - " [10256] = -6.02979e-30\n", - " [10265] = 1.19176e-22\n", - " [10268] = 1.18009e-22\n", - " [10273] = 2.99461e-24\n", - " ⋮\n", - " [10310] = -1.12058e-48\n", - " [10352] = -9.82087e-28\n", - " [10540] = -4.14154e-35\n", - " [10555] = 1.26353e-50\n", - " [10835] = 8.25969e-48\n", - " [10865] = 9.36983e-37\n", - " [10867] = -1.9707e-52\n", - " [10908] = 3.09459e-35" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "rops(ssys, \"O=CO\", 1e-12)" - ] - }, - { - "cell_type": "code", - "execution_count": 72, - "id": "64238bc0", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"CH2O2X\",1;N=15,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 73, - "id": "e8bb3c43", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"CHO2X\",1;N=10,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 74, - "id": "0bb84a7f", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"CO2HX\",1;N=10,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 75, - "id": "1044d2b9", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"OX\",1;N=10,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 76, - "id": "7086e403", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"OCX\",1.0e-6)" - ] - }, - { - "cell_type": "code", - "execution_count": 77, - "id": "44de0eb2", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "vacantX+CO2<=>CO2X\n", - "kf = 20654.615923781494\n", - "krev = 11189.298481041604\n", - "Kc = 1.8459259048971917\n", - "proton+CO2X<=>CHO2X\n", - "kf = 5.164749496653815e7\n", - "krev = 3.369038128826839e8\n", - "Kc = 0.1533004168893831\n", - "proton+CO2X<=>CO2HX\n", - "kf = 463658.8965294065\n", - "krev = 1.20318988446587e-5\n", - "Kc = 3.853580407511801e10\n", - "proton+CHO2X<=>CH2O2X\n", - "kf = 2.5e10\n", - "krev = 9.108706843764319e-26\n", - "Kc = 2.7446266993557504e35\n", - "proton+CO2HX<=>CH2O2X\n", - "kf = 1.9190551016885178e10\n", - "krev = 1.757621070775451e-14\n", - "Kc = 1.0918480289052538e24\n", - "proton+OCX<=>CHOX\n", - "kf = 2.5e10\n", - "krev = 2.604453583293511e-10\n", - "Kc = 9.59894242706594e19\n", - "proton+CHOX<=>CH2OX\n", - "kf = 1.7890196451453958e9\n", - "krev = 4.957912234830633e-11\n", - "Kc = 3.608413300616868e19\n", - "vacantX+vacantX+CO2<=>OX+OCX\n", - "kf = 3.0109478093923404e-24\n", - "krev = 3.037156297092479e15\n", - "Kc = 9.913707148607306e-40\n", - "OX+proton<=>HOX\n", - "kf = 2.5e10\n", - "krev = 4.7547181516587526e-14\n", - "Kc = 5.25793521352646e23\n", - "vacantX+C=O<=>CH2OX\n", - "kf = 500114.13488002896\n", - "krev = 399.6803280141717\n", - "Kc = 1251.2853393732605\n", - "proton+CHO2X<=>OX+C=O\n", - "kf = 7.971946163368602e-7\n", - "krev = 8.220582009654122e-5\n", - "Kc = 0.009697544716428197\n", - "HX+CO2<=>CHO2X\n", - "kf = 6.542996392927688e-8\n", - "krev = 15.579156394796986\n", - "Kc = 4.199839983064083e-9\n", - "HX+CO2<=>CO2HX\n", - "kf = 6.542996392927688e-8\n", - "krev = 6.197590078701277e-11\n", - "Kc = 1055.7323588427441\n", - "vacantX+vacantX+C=O<=>HX+CHOX\n", - "kf = 2.0718885766149262e-11\n", - "krev = 0.008867505326838887\n", - "Kc = 2.336495440655708e-9\n", - "vacantX+O=CO<=>CH2O2X\n", - "kf = 403943.82249737746\n", - "krev = 29.756334575496034\n", - "Kc = 13575.053119278344\n", - "vacantX+vacantX+O=CO<=>HOX+CHOX\n", - "kf = 8.486192390111145e-15\n", - "krev = 9.7037034735699e11\n", - "Kc = 8.745312975839684e-27\n", - "vacantX+vacantX+O=CO<=>HX+CHO2X\n", - "kf = 1.2668346793097018e-21\n", - "krev = 380.13410282264914\n", - "Kc = 3.332599390328158e-24\n", - "vacantX+vacantX+O=CO<=>HX+CO2HX\n", - "kf = 9.840171155787102e-15\n", - "krev = 0.011746228705195169\n", - "Kc = 8.377302539184302e-13\n", - "proton+CH2OX<=>CO[Pt]\n", - "kf = 4.612846333154699e7\n", - "krev = 90.4105198560361\n", - "Kc = 510211.23874742666\n", - "HX+C=O<=>CO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.180104845075902e-9\n", - "Kc = 9.475050217848336\n", - "proton+CO2HX<=>H2O+OCX\n", - "kf = 2.5e10\n", - "krev = 4.0258346788129556e-7\n", - "Kc = 6.20989235637749e16\n", - "vacantX+vacantX+H2O<=>HX+HOX\n", - "kf = 1.7047654949014593e-31\n", - "krev = 21441.30602897437\n", - "Kc = 7.950847269274322e-36\n", - "proton+CH2OX<=>OC[Pt]\n", - "kf = 1.2443063594454413e6\n", - "krev = 1.1005987164187474e-6\n", - "Kc = 1.1305722429827158e12\n", - "HX+C=O<=>OC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.886422105564557e-15\n", - "Kc = 2.099567387708916e7\n", - "vacantX+vacantX+O=CC=O<=>CHOX+CHOX\n", - "kf = 3.132095071630788e8\n", - "krev = 159.05427897483804\n", - "Kc = 1.9691988746346629e6\n", - "proton+CH2O2X<=>OC(O)[Pt]\n", - "kf = 1.9695177200694968e-5\n", - "krev = 3718.799864740736\n", - "Kc = 5.296111088803661e-9\n", - "HX+O=CO<=>OC(O)[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 29981.045237801853\n", - "Kc = 1.0670229661561413e-12\n", - "proton+CH2O2X<=>OCO[Pt]\n", - "kf = 1.3800914441571782e-5\n", - "krev = 3681.751563599994\n", - "Kc = 3.748464339097702e-9\n", - "HOX+C=O<=>OCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.962949149852605e-13\n", - "Kc = 201771.41789913058\n", - "HX+O=CO<=>OCO[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 42359.465576793365\n", - "Kc = 7.552140562327293e-13\n", - "vacantX+H2O<=>H2OX\n", - "kf = 4.842414926683719e6\n", - "krev = 2.0721934488233277e8\n", - "Kc = 0.023368546645263413\n", - "proton+HOX<=>H2OX\n", - "kf = 2.5e10\n", - "krev = 1.2623996335027457e-31\n", - "Kc = 1.9803554545269617e41\n", - "vacantX+vacantX+H2<=>HX+HX\n", - "kf = 3.8736093818093735e10\n", - "krev = 4.9917087254698525e28\n", - "Kc = 7.760086965901168e-19\n", - "proton+CHOX<=>OC=[Pt]\n", - "kf = 3.6460821201937575e9\n", - "krev = 3.454391742229775e10\n", - "Kc = 0.10554917890812951\n", - "vacantX+vacantX+O=CO<=>OX+OC=[Pt]\n", - "kf = 1.3995006080437096e-36\n", - "krev = 7.971831424002446e14\n", - "Kc = 1.755557203367275e-51\n", - "proton+OC=[Pt]<=>OC[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.468152848309303e-23\n", - "Kc = 3.8650910988497585e32\n", - "proton+OC(O)[Pt]<=>H2O+OC=[Pt]\n", - "kf = 6.989877198043828e9\n", - "krev = 6.424310280494338e-11\n", - "Kc = 1.0880354299303816e20\n", - "proton+O=CC(=O)[Pt]<=>OCX+C=O\n", - "kf = 2.302032083373261e7\n", - "krev = 2.5713202543754838e-9\n", - "Kc = 8.952724109165363e15\n", - "vacantX+vacantX+O=CC=O<=>HX+O=CC(=O)[Pt]\n", - "kf = 1.43713660093583e-9\n", - "krev = 0.00032277677938391324\n", - "Kc = 4.452416322137251e-6\n", - "proton+OCX<=>OC#[Pt]\n", - "kf = 26781.620683797883\n", - "krev = 1.0085447542339806e12\n", - "Kc = 2.6554717151981333e-8\n", - "proton+OC#[Pt]<=>OC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.552445879282663e-17\n", - "Kc = 3.815369170624406e26\n", - "vacantX+O=CC=O<=>O=CC=O.[Pt]\n", - "kf = 359723.7676387533\n", - "krev = 0.32068189796600394\n", - "Kc = 1.121746409511672e6\n", - "proton+O=CC(=O)[Pt]<=>O=CC=O.[Pt]\n", - "kf = 1.508798479649927e9\n", - "krev = 8.88806985342612e-11\n", - "Kc = 1.6975547048252826e19\n", - "vacantX+vacantX+OO<=>HOX+HOX\n", - "kf = 4.0912386971316826e8\n", - "krev = 1.7763617117679594e-6\n", - "Kc = 2.3031563166601894e14\n", - "OCX<=>vacantX+CO\n", - "kf = 2.010168305725754e-19\n", - "krev = 2.61760793808642e-25\n", - "Kc = 767940.9419866255\n", - "vacantX+vacantX+O2<=>OX+OX\n", - "kf = 1.0945721587141857e10\n", - "krev = 4.219325007995329e-16\n", - "Kc = 2.594187830138819e25\n", - "proton+HX<=>[H][H].[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.1949534688419614e-15\n", - "Kc = 2.0921316730623565e25\n", - "vacantX+H2<=>[H][H].[Pt]\n", - "kf = 2338.960705505517\n", - "krev = 9707.159813448116\n", - "Kc = 0.24095211683495363\n", - "CHOX+C=O<=>O=COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 7.563806299311394e-5\n", - "Kc = 0.0005236345532350701\n", - "proton+OO[Pt]<=>OX+H2O\n", - "kf = 17.257164508221003\n", - "krev = 6.236444643145301e-63\n", - "Kc = 2.767147869610126e63\n", - "vacantX+vacantX+OO<=>HX+OO[Pt]\n", - "kf = 4.980245005159166e-22\n", - "krev = 5.509834949091977\n", - "Kc = 9.038827934364735e-23\n", - "proton+OC#[Pt]<=>H2O+CX\n", - "kf = 3.276640102032806e-5\n", - "krev = 0.0009291230748795855\n", - "Kc = 0.03526594259277716\n", - "vacantX+vacantX+O=C=C=O<=>OCX+OCX\n", - "kf = 74.64023007210145\n", - "krev = 2.953439666185894e-39\n", - "Kc = 2.52723056870475e40\n", - "HX+O=C=C=O<=>O=CC(=O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 5.0006650398424424e-61\n", - "Kc = 1.1597065597154312e53\n", - "proton+OC=[Pt]<=>H2O+CHX\n", - "kf = 2.5e10\n", - "krev = 6.511063937864271e-5\n", - "Kc = 3.839618261865876e14\n", - "proton+CX<=>CHX\n", - "kf = 2.5e10\n", - "krev = 6.018259224258551e-33\n", - "Kc = 4.1540251206244773e42\n", - "H2+CX<=>CH2X\n", - "kf = 4.832014059685671\n", - "krev = 1.8278921581756875e-33\n", - "Kc = 2.643489681857502e33\n", - "vacantX+vacantX+C=O<=>OX+CH2X\n", - "kf = 4.5608316796485725e-28\n", - "krev = 3.884151005592286e17\n", - "Kc = 1.1742158513101117e-45\n", - "proton+OC[Pt]<=>H2O+CH2X\n", - "kf = 7206.229958253159\n", - "krev = 0.0019484451144913943\n", - "Kc = 3.6984516036184127e6\n", - "proton+O=COC[Pt]<=>CH2X+O=CO\n", - "kf = 1981.2472905766488\n", - "krev = 1.4695324127813272e-5\n", - "Kc = 1.3482161219069803e8\n", - "proton+CHX<=>CH2X\n", - "kf = 2.5e10\n", - "krev = 6.715036577093663e-15\n", - "Kc = 3.722987911231938e24\n", - "proton+O=COC#[Pt]<=>CX+O=CO\n", - "kf = 6.185088018779624e7\n", - "krev = 3.741277098492221e-23\n", - "Kc = 1.6532023306352497e30\n", - "vacantX+vacantX+C=C=O<=>OCX+CH2X\n", - "kf = 2.4823885573387985e-14\n", - "krev = 9.351132511056354e15\n", - "Kc = 2.6546394828687704e-30\n", - "CHOX+C=O<=>O=CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.4949222028864902e7\n", - "Kc = 2.6494156850764662e-15\n", - "HX+O=CC=O<=>O=CCO[Pt]\n", - "kf = 5.6976884072695144e-8\n", - "krev = 2.551666729065355e-8\n", - "Kc = 2.23292812590636\n", - "proton+O=CC=O.[Pt]<=>O=CCO[Pt]\n", - "kf = 957581.7759153218\n", - "krev = 7139.55197608848\n", - "Kc = 134.12351070801344\n", - "O=O.[Pt]+proton<=>OO[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.545950245153839e-28\n", - "Kc = 7.050296330064662e37\n", - "proton+O=CC#[Pt]<=>CX+C=O\n", - "kf = 5.731900626219973e-17\n", - "krev = 16.634660991475336\n", - "Kc = 3.4457574032662074e-18\n", - "proton+CO2HX<=>OC(O)=[Pt]\n", - "kf = 8.313674902647437e-22\n", - "krev = 1.0085447542339753e12\n", - "Kc = 8.243238455949296e-34\n", - "proton+OC(O)=[Pt]<=>OC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.563843227039955e-39\n", - "Kc = 7.014898918762039e48\n", - "proton+OC(O)=[Pt]<=>H2O+OC#[Pt]\n", - "kf = 58948.65819613129\n", - "krev = 2.9467686111082447e-38\n", - "Kc = 2.0004508658710534e42\n", - "proton+O=C(O)C#[Pt]<=>CX+O=CO\n", - "kf = 1.2163309452954808e-9\n", - "krev = 0.00037997676558546045\n", - "Kc = 3.201066632117316e-6\n", - "proton+O=C=C=O.[Pt]<=>O=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.649884885591097e-48\n", - "Kc = 9.434372087609898e57\n", - "vacantX+O=C=C=O<=>O=C=C=O.[Pt]\n", - "kf = 366139.2749661925\n", - "krev = 442.06521987276346\n", - "Kc = 828.2471873077366\n", - "HOX+C=O<=>OOC[Pt]\n", - "kf = 1.5395975576095126e-29\n", - "krev = 2.622153295712258e16\n", - "Kc = 5.871500953537159e-46\n", - "proton+OOC[Pt]<=>OO+CH2X\n", - "kf = 15.535579749933543\n", - "krev = 3.4028033042152773e-9\n", - "Kc = 4.5655238816444645e9\n", - "vacantX+vacantX+O=C=CO<=>OCX+OC=[Pt]\n", - "kf = 73.33238091278024\n", - "krev = 14511.198914062346\n", - "Kc = 0.005053502563576338\n", - "vacantX+C=C=O<=>C=C=O.[Pt]\n", - "kf = 422670.5724931744\n", - "krev = 9.80980243728561e-11\n", - "Kc = 4.3086552985681545e15\n", - "proton+CO[Pt]<=>OX+CH4\n", - "kf = 541698.6744405399\n", - "krev = 1.9995135619129721e-19\n", - "Kc = 2.7091522896313173e24\n", - "HX+C=C=O<=>CC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.3310785577331067e-33\n", - "Kc = 2.514767798332947e25\n", - "proton+C=C=O.[Pt]<=>CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.357099551204697e-8\n", - "Kc = 3.9326110592781875e17\n", - "proton+CC(=O)[Pt]<=>OCX+CH4\n", - "kf = 1.0030005882936613e8\n", - "krev = 4.3463683404291294e-8\n", - "Kc = 2.3076750743003805e15\n", - "vacantX+vacantX+COC=O<=>CHOX+CO[Pt]\n", - "kf = 5.858305523872122e-8\n", - "krev = 9.372228401924443e12\n", - "Kc = 6.250707166578664e-21\n", - "vacantX+vacantX+COC=O<=>HX+O=COC[Pt]\n", - "kf = 8.724708246600757e-23\n", - "krev = 252.56605644619947\n", - "Kc = 3.454426287270814e-25\n", - "vacantX+vacantX+COC=O<=>HX+COC(=O)[Pt]\n", - "kf = 7.165711269221808e-16\n", - "krev = 0.1859922027934253\n", - "Kc = 3.852694447186316e-15\n", - "proton+O=COCC#[Pt]<=>CX+COC=O\n", - "kf = 0.8132675549526747\n", - "krev = 2.165706403032533e-5\n", - "Kc = 37552.06863746147\n", - "HOX+C=C=O<=>O=C([Pt])CO\n", - "kf = 3.3473534940386794e-8\n", - "krev = 9.042590347389556e-30\n", - "Kc = 3.70176394754519e21\n", - "HX+O=C=CO<=>O=C([Pt])CO\n", - "kf = 2.8488442036348548e-8\n", - "krev = 1.614840618256874e-45\n", - "Kc = 1.7641643214981894e37\n", - "vacantX+vacantX+COO<=>HOX+CO[Pt]\n", - "kf = 3.442529358831723e8\n", - "krev = 2.6586367586035048e-11\n", - "Kc = 1.294847574679578e19\n", - "vacantX+vacantX+COO<=>HX+OOC[Pt]\n", - "kf = 1.3336211820914592e-23\n", - "krev = 16620.58178963317\n", - "Kc = 8.023913957833202e-28\n", - "CHOX+C=C=O<=>O=CCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 2.6714659015861004e-16\n", - "Kc = 1.2530025152300434e8\n", - "vacantX+vacantX+CO-2<=>HX+CO[Pt]\n", - "kf = 3.6896065237788346e-26\n", - "krev = 1200.2597905170037\n", - "Kc = 3.0740066050113714e-29\n", - "vacantX+vacantX+CO-2<=>HX+OC[Pt]\n", - "kf = 1.1691860289045307e-22\n", - "krev = 1.716447494000275\n", - "Kc = 6.811662069427353e-23\n", - "proton+OCO[Pt]<=>OX+CO-2\n", - "kf = 6.4866612293733e7\n", - "krev = 4.917786339628338e-9\n", - "Kc = 1.319020547335029e16\n", - "proton+COC(=O)[Pt]<=>OCX+CO-2\n", - "kf = 5.096893185474306e9\n", - "krev = 2.041829224680708e-9\n", - "Kc = 2.49623872744369e18\n", - "proton+O=C([Pt])CO<=>OCX+CO-2\n", - "kf = 1.9762803815844387e7\n", - "krev = 1.2158736968776066e-8\n", - "Kc = 1.6253994034574272e15\n", - "proton+OCC#[Pt]<=>CX+CO-2\n", - "kf = 1.8515947729382765e-10\n", - "krev = 0.16959607683462066\n", - "Kc = 1.091767455649245e-9\n", - "vacantX+vacantX+COOC<=>CO[Pt]+CO[Pt]\n", - "kf = 3.028654941635431e8\n", - "krev = 1.0392777770118965e-11\n", - "Kc = 2.914191959673513e19\n", - "vacantX+vacantX+C=C=O<=>HX+O=C=C[Pt]\n", - "kf = 3.6584912239485734e-16\n", - "krev = 0.32395775785233605\n", - "Kc = 1.1293111942132156e-15\n", - "vacantX+vacantX+O=C=CO<=>HOX+O=C=C[Pt]\n", - "kf = 3.132095071630788e8\n", - "krev = 5.819571251914923e7\n", - "Kc = 5.382003133994065\n", - "proton+O=C=C[Pt]<=>C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.724942318590629e-29\n", - "Kc = 2.570709334924167e38\n", - "vacantX+vacantX+O=CCO<=>CHOX+OC[Pt]\n", - "kf = 9001.813049524091\n", - "krev = 8.180569891408677e12\n", - "Kc = 1.1003894800749632e-9\n", - "vacantX+vacantX+O=CCO<=>HX+O=CCO[Pt]\n", - "kf = 3.705974451661604e-28\n", - "krev = 2668.9209237076484\n", - "Kc = 1.3885665996103351e-31\n", - "vacantX+vacantX+O=CCO<=>HX+O=C([Pt])CO\n", - "kf = 1.2718474027465153e-10\n", - "krev = 0.0002705673832361486\n", - "Kc = 4.7006678614933393e-7\n", - "proton+O=CCOC#[Pt]<=>CX+O=CCO\n", - "kf = 3.8625888100004036e-23\n", - "krev = 1.5059302822169408e-12\n", - "Kc = 2.564918745318097e-11\n", - "proton+COC#[Pt]<=>CX+CO-2\n", - "kf = 3.5797175052253717e-22\n", - "krev = 9.770006712968626e-20\n", - "Kc = 0.0036639867406372244\n", - "proton+O=CC(=O)C#[Pt]<=>CX+O=CC=O\n", - "kf = 5.9931479699583235e-12\n", - "krev = 0.0016900056192162703\n", - "Kc = 3.546229611199523e-9\n", - "vacantX+vacantX+OCO<=>HOX+OC[Pt]\n", - "kf = 1.653107374238179e-12\n", - "krev = 3.492310477620836e11\n", - "Kc = 4.7335635958815765e-24\n", - "vacantX+vacantX+OCO<=>HX+OC(O)[Pt]\n", - "kf = 4.0412190145177725e-23\n", - "krev = 628.7683045605482\n", - "Kc = 6.427198993979533e-26\n", - "vacantX+vacantX+OCO<=>HX+OCO[Pt]\n", - "kf = 1.1281154422531313e-23\n", - "krev = 247.99076039714222\n", - "Kc = 4.5490220702034325e-26\n", - "proton+OC(O)C#[Pt]<=>CX+OCO\n", - "kf = 0.005562206988621036\n", - "krev = 0.025459246171787766\n", - "Kc = 0.21847492856189518\n", - "proton+OCOC#[Pt]<=>CX+OCO\n", - "kf = 2.2993090387825977e-18\n", - "krev = 1.7767009384663083e-12\n", - "Kc = 1.2941452266960681e-6\n", - "proton+O=COC=[Pt]<=>O=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.03525663068036e-45\n", - "Kc = 2.4148601669491608e55\n", - "proton+O=COC=[Pt]<=>CHX+O=CO\n", - "kf = 407721.49317133107\n", - "krev = 4.66233771243883e-34\n", - "Kc = 8.745001291595743e38\n", - "proton+O=COC#[Pt]<=>O=COC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.1834993039887084e-24\n", - "Kc = 7.852993706854812e33\n", - "proton+O=C=CC#[Pt]<=>CX+C=C=O\n", - "kf = 1.255896512556004e-15\n", - "krev = 0.016900821436021087\n", - "Kc = 7.430979123176135e-14\n", - "vacantX+vacantX+COCO<=>CO[Pt]+OC[Pt]\n", - "kf = 3.0636862331912886e-9\n", - "krev = 3.008499680951675e11\n", - "Kc = 1.0183435459837431e-20\n", - "proton+CC#[Pt]<=>CX+CH4\n", - "kf = 3.172314510568854e-8\n", - "krev = 0.363285670785801\n", - "Kc = 8.732286367659409e-8\n", - "HX+O=C=C=O<=>O=C=CO[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.1302052975227224e-55\n", - "Kc = 2.7224155607861307e47\n", - "proton+O=C=CO[Pt]<=>OX+C=C=O\n", - "kf = 0.047578794564636824\n", - "krev = 2.8204743128358057e-8\n", - "Kc = 1.6869075654441754e6\n", - "proton+O=C=C=O.[Pt]<=>O=C=CO[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 2.257619247094878e-42\n", - "Kc = 2.2147224366704162e52\n", - "vacantX+vacantX+O=C=CO<=>HX+O=C=CO[Pt]\n", - "kf = 0.0007071288662616175\n", - "krev = 2.8988454126647536e-5\n", - "Kc = 24.393465866522067\n", - "vacantX+vacantX+OCCO<=>OC[Pt]+OC[Pt]\n", - "kf = 2.961131444342359e-9\n", - "krev = 1.299206322752899e13\n", - "Kc = 2.2791849088819035e-22\n", - "proton+COC(=O)C#[Pt]<=>CX+COC=O\n", - "kf = 2.520547604265173e-10\n", - "krev = 3.828537658551766e-5\n", - "Kc = 6.583577932517004e-6\n", - "proton+O=C=CC(=O)[Pt]<=>OCX+C=C=O\n", - "kf = 2.14881300259784e7\n", - "krev = 1.9623010758881652e-11\n", - "Kc = 1.0950475587061772e18\n", - "vacantX+vacantX+OC=CO<=>OC=[Pt]+OC=[Pt]\n", - "kf = 1.351949923589269e-23\n", - "krev = 7.975137957191956e11\n", - "Kc = 1.6952056890377485e-35\n", - "vacantX+OX+CH4<=>HOX+CH3X\n", - "kf = 1181.9069662995785\n", - "krev = 1.0235810933777192e20\n", - "Kc = 1.1546783874244874e-17\n", - "vacantX+HOX+CH4<=>H2OX+CH3X\n", - "kf = 5.28370763875636e9\n", - "krev = 1.2149259925984929e9\n", - "Kc = 4.348995470461149\n", - "HX+CH3X<=>vacantX+vacantX+CH4\n", - "kf = 5.733311120080377e8\n", - "krev = 8.483521653048543e-25\n", - "Kc = 6.758173497465076e32\n", - "proton+CH2X<=>CH3X\n", - "kf = 2.5e10\n", - "krev = 7.728626954425352e-28\n", - "Kc = 3.2347272222377345e37\n", - "CO2+CH3X<=>COC(=O)[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.00447183609125585\n", - "Kc = 1.463156578060128e-5\n", - "vacantX+vacantX+COC=O<=>CHO2X+CH3X\n", - "kf = 0.05589950368763065\n", - "krev = 5.054770535995559e16\n", - "Kc = 1.1058761874463802e-18\n", - "vacantX+vacantX+COO<=>OO[Pt]+CH3X\n", - "kf = 9.385776922831516e-7\n", - "krev = 3.9782610412247473e11\n", - "Kc = 2.359266228528335e-18\n", - "vacantX+vacantX+CO-2<=>HOX+CH3X\n", - "kf = 9.872876935778847e-16\n", - "krev = 6.917821124819518e13\n", - "Kc = 1.427165686657795e-29\n", - "vacantX+vacantX+COCO<=>CH3X+OCO[Pt]\n", - "kf = 3.9072411322938125e-9\n", - "krev = 8.599564777209447e13\n", - "Kc = 4.543533578174534e-23\n", - "O=O+HX<=>OO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 8.854082166234876e-41\n", - "Kc = 8.666474551788235e32\n", - "vacantX+O=O<=>O=O.[Pt]\n", - "kf = 484458.3574999593\n", - "krev = 584.920039726471\n", - "Kc = 828.247152767255\n", - "vacantX+O=C=CO<=>O=C=CO.[Pt]\n", - "kf = 359723.7676387533\n", - "krev = 0.4900054095759742\n", - "Kc = 734122.0333670193\n", - "proton+O=C=CO.[Pt]<=>O=C([Pt])CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.543989619636675e-29\n", - "Kc = 1.6191818702694958e39\n", - "proton+O=C=CO[Pt]<=>O=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.012328788524416852\n", - "Kc = 2.0277742578265605e12\n", - "vacantX+vacantX+O=C=C=O<=>OX+O=C=C=[Pt]\n", - "kf = 149.2804601441562\n", - "krev = 1.2008902564793325e-12\n", - "Kc = 1.2430816166483347e14\n", - "proton+O=C=C=[Pt]<=>O=CC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 728325.7738813914\n", - "Kc = 34325.299057824195\n", - "proton+O=C=C=[Pt]<=>O=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.992117420427329e-15\n", - "Kc = 4.1721478812771864e24\n", - "vacantX+vacantX+C=CO<=>CH2X+OC=[Pt]\n", - "kf = 3.7510196251812924e-36\n", - "krev = 6.624293894020312e13\n", - "Kc = 5.662519938264367e-50\n", - "proton+O=C(C#[Pt])CO<=>CX+O=CCO\n", - "kf = 2.1150580786972557e-17\n", - "krev = 1.2236788896896236\n", - "Kc = 1.728442074565594e-17\n", - "vacantX+vacantX+C=C<=>CH2X+CH2X\n", - "kf = 9.387035392806688e-46\n", - "krev = 5.259242712748897e15\n", - "Kc = 1.784864457776713e-61\n", - "proton+O=COC[Pt]<=>COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.124037165592671e-28\n", - "Kc = 8.002465615756261e37\n", - "proton+COC(=O)[Pt]<=>COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.484214060387906e-18\n", - "Kc = 7.175219308200797e27\n", - "vacantX+COC=O<=>COC=O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.8619443782965007\n", - "Kc = 410274.8449265323\n", - "HX+O=C=C=C=O<=>O=C=CC(=O)[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 3.561089909521239e-25\n", - "Kc = 1.4777843564830474e17\n", - "vacantX+vacantX+O=C=C=C=O<=>OCX+O=C=C=[Pt]\n", - "kf = 135.4631249389026\n", - "krev = 3.092595390223456e6\n", - "Kc = 4.3802407960361956e-5\n", - "CH3X+O=C=C=O<=>CC(=O)C(=O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 3.5093718907449027e-71\n", - "Kc = 1.6525190917893694e63\n", - "proton+OOC#[Pt]<=>OO+CX\n", - "kf = 3.959382254258936e-52\n", - "krev = 4.505410128222608e6\n", - "Kc = 8.78806177812034e-59\n", - "proton+O=CC[Pt]<=>CH2X+C=O\n", - "kf = 9.847553463617368e-13\n", - "krev = 0.8193686811731042\n", - "Kc = 1.2018464568987987e-12\n", - "HX+C=C=O<=>O=CC[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 3.6888123831707493e-19\n", - "Kc = 9.074339235332521e10\n", - "proton+C=C=O.[Pt]<=>O=CC[Pt]\n", - "kf = 4.477750650627013e6\n", - "krev = 3155.453532604055\n", - "Kc = 1419.0513675324908\n", - "vacantX+vacantX+O=CCO<=>HOX+O=CC[Pt]\n", - "kf = 3.3834985622063113e-5\n", - "krev = 2.9362980773683545e12\n", - "Kc = 1.1523007790948657e-17\n", - "vacantX+vacantX+O=CC=O<=>OX+O=CC=[Pt]\n", - "kf = 6.170227811474367e-18\n", - "krev = 2.1467268001769245e15\n", - "Kc = 2.874249210922341e-33\n", - "proton+O=CC=[Pt]<=>CHX+C=O\n", - "kf = 0.3518802014338951\n", - "krev = 0.0019581841163396926\n", - "Kc = 179.69719930710195\n", - "proton+O=CC#[Pt]<=>O=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.1385387905668107e-13\n", - "Kc = 7.9654902068249e22\n", - "proton+O=C=C[Pt]<=>O=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.814809579170971e7\n", - "Kc = 655.3407052478085\n", - "proton+O=CC=[Pt]<=>O=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.4911345025101916e-29\n", - "Kc = 5.566522219725765e38\n", - "proton+O=CCO[Pt]<=>OX+CC=O\n", - "kf = 108844.3774855493\n", - "krev = 6.551243603618761e-23\n", - "Kc = 1.6614307766761425e27\n", - "vacantX+vacantX+CC=O<=>HX+CC(=O)[Pt]\n", - "kf = 4.3209399543319175e-11\n", - "krev = 0.0003615296985530135\n", - "Kc = 1.195182573278502e-7\n", - "proton+O=CCC(=O)[Pt]<=>OCX+CC=O\n", - "kf = 7.362850070977087e6\n", - "krev = 9.270601965584902e-14\n", - "Kc = 7.94214884676321e19\n", - "proton+O=CCC#[Pt]<=>CX+CC=O\n", - "kf = 0.11748380587607415\n", - "krev = 6.387097627333538e-5\n", - "Kc = 1839.3926745898334\n", - "vacantX+vacantX+CC=O<=>CHOX+CH3X\n", - "kf = 6.063283190982672e-6\n", - "krev = 7.026751658283665e14\n", - "Kc = 8.628856526948432e-21\n", - "proton+CC(=O)C#[Pt]<=>CX+CC=O\n", - "kf = 8.247683071468342e-18\n", - "krev = 0.06355423283679383\n", - "Kc = 1.2977393799478706e-16\n", - "proton+CC(=O)C(=O)[Pt]<=>OCX+CC=O\n", - "kf = 3.422758172577326e7\n", - "krev = 2.0119060511296993e-10\n", - "Kc = 1.7012514926606157e17\n", - "vacantX+vacantX+CC=O<=>HX+O=CC[Pt]\n", - "kf = 3.2094062904328744e-20\n", - "krev = 74.41720028073364\n", - "Kc = 4.312721089110603e-22\n", - "vacantX+CH4<=>C.[Pt]\n", - "kf = 11983.404197457203\n", - "krev = 27576.843954134933\n", - "Kc = 0.4345458899280744\n", - "proton+CH3X<=>C.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.2634270430964172e-30\n", - "Kc = 1.9787450440137642e40\n", - "HX+O=C=CC=O<=>O=CCC(=O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 3.8194581898791103e-32\n", - "Kc = 6.789235995427004e23\n", - "vacantX+vacantX+O=C=CC=O<=>CHOX+O=C=C[Pt]\n", - "kf = 2.850945414803626e8\n", - "krev = 4.6591458607721776e7\n", - "Kc = 6.119030182779314\n", - "vacantX+vacantX+O=C=CC=O<=>HX+O=C=CC(=O)[Pt]\n", - "kf = 1.1776167531898308e-10\n", - "krev = 0.0005032011998508361\n", - "Kc = 2.3402502886298994e-7\n", - "vacantX+vacantX+O=C=CC=O<=>OCX+O=CC=[Pt]\n", - "kf = 0.006845452357086415\n", - "krev = 1.638610749190394e14\n", - "Kc = 4.177595173514284e-17\n", - "vacantX+vacantX+C=C(O)O<=>CH2X+OC(O)=[Pt]\n", - "kf = 1.3631835715271243e-51\n", - "krev = 1.0974745099569602e16\n", - "Kc = 1.242109551665655e-67\n", - "proton+O=C=CC=O.[Pt]<=>O=CCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.130402878837127e-16\n", - "Kc = 4.078035407151288e25\n", - "proton+O=C=CC(=O)[Pt]<=>O=C=CC=O.[Pt]\n", - "kf = 2.964275004938465e9\n", - "krev = 9.178277268525813e-12\n", - "Kc = 3.229663822756335e20\n", - "vacantX+O=C=CC=O<=>O=C=CC=O.[Pt]\n", - "kf = 327433.4917974331\n", - "krev = 0.29189612518083846\n", - "Kc = 1.1217466199476891e6\n", - "vacantX+vacantX+CC(=O)O<=>HOX+CC(=O)[Pt]\n", - "kf = 3.661873055903852e-12\n", - "krev = 2.1682718089028445e11\n", - "Kc = 1.6888441019563762e-23\n", - "vacantX+vacantX+CC(=O)O<=>CO2HX+CH3X\n", - "kf = 1.1977509649486271e-8\n", - "krev = 1.0254845667743408e14\n", - "Kc = 1.1679853639496008e-22\n", - "CO2+CH3X<=>CC(=O)O[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 3.3286101924403974e-7\n", - "Kc = 0.19656841788766613\n", - "proton+CC(=O)O[Pt]<=>OX+CC=O\n", - "kf = 6.638543952734307e-6\n", - "krev = 1.1832604608796647e-7\n", - "Kc = 56.10382643732599\n", - "vacantX+vacantX+CC(=O)O<=>HX+CC(=O)O[Pt]\n", - "kf = 2.4753542791841756e-22\n", - "krev = 11382.562807978633\n", - "Kc = 2.1746897609465158e-26\n", - "proton+CC(=O)OC#[Pt]<=>CX+CC(=O)O\n", - "kf = 3.5372794201475537e8\n", - "krev = 2.288049006228874e-19\n", - "Kc = 1.5459806195224992e27\n", - "vacantX+vacantX+CC(=O)C=O<=>CHOX+CC(=O)[Pt]\n", - "kf = 2.810784197367395e8\n", - "krev = 8.682228189641076\n", - "Kc = 3.237399589106622e7\n", - "vacantX+vacantX+CC(=O)C=O<=>CH3X+O=CC(=O)[Pt]\n", - "kf = 0.010756441693245073\n", - "krev = 2.0353876594794328e15\n", - "Kc = 5.284714016589902e-18\n", - "vacantX+vacantX+CC(=O)C=O<=>HX+CC(=O)C(=O)[Pt]\n", - "kf = 2.426386880233808e-11\n", - "krev = 0.0003222108693910823\n", - "Kc = 7.530431499158364e-8\n", - "proton+O=C=C([Pt])C=O<=>C=O+O=C=C=[Pt]\n", - "kf = 13308.622034460761\n", - "krev = 4.6234228919871786e-9\n", - "Kc = 2.8785214645897607e12\n", - "HX+O=C=C=C=O<=>O=C=C([Pt])C=O\n", - "kf = 5.262522960320117e-8\n", - "krev = 8.417963556232881e-20\n", - "Kc = 6.251539253129229e11\n", - "vacantX+vacantX+O=C=CC=O<=>HX+O=C=C([Pt])C=O\n", - "kf = 3.109950102720783e-13\n", - "krev = 0.31413419650430946\n", - "Kc = 9.900068624582613e-13\n", - "proton+O=C=C([Pt])C=O<=>O=C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.274602487927107e-16\n", - "Kc = 7.6345144463093386e25\n", - "proton+O=C=COC#[Pt]<=>CX+O=C=CO\n", - "kf = 3.333143073629419e-24\n", - "krev = 2.9895559923107984e-13\n", - "Kc = 1.1149291340260339e-11\n", - "vacantX+vacantX+COC(C)=O<=>CO[Pt]+CC(=O)[Pt]\n", - "kf = 6.614441053978493e-6\n", - "krev = 7.629970776987544e11\n", - "Kc = 8.669025409544227e-18\n", - "vacantX+vacantX+COC(C)=O<=>CH3X+COC(=O)[Pt]\n", - "kf = 1.5563360867242215e-10\n", - "krev = 4.0343976517667425e14\n", - "Kc = 3.857666549162974e-25\n", - "vacantX+vacantX+COC(C)=O<=>CH3X+CC(=O)O[Pt]\n", - "kf = 0.0003463783354588583\n", - "krev = 6.683486846094463e16\n", - "Kc = 5.182599194629471e-21\n", - "vacantX+vacantX+COO<=>HX+COO[Pt]\n", - "kf = 1.175900379595729e-21\n", - "krev = 0.27982743013843664\n", - "Kc = 4.2022341377111815e-21\n", - "proton+COO[Pt]<=>OX+CO-2\n", - "kf = 129.78074174016686\n", - "krev = 1.499485133709293e-58\n", - "Kc = 8.65502023478731e59\n", - "vacantX+vacantX+COOC<=>CH3X+COO[Pt]\n", - "kf = 1.8186835430204133e-8\n", - "krev = 4.141977957602716e12\n", - "Kc = 4.39085760869917e-21\n", - "O=O+CH3X<=>COO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 4.970959816815508e-38\n", - "Kc = 1.543639067721808e30\n", - "proton+CO[Pt]<=>CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.487564815762018e-25\n", - "Kc = 1.0049989387851077e35\n", - "proton+OC[Pt]<=>CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.512171272873819e-19\n", - "Kc = 4.535417853038886e28\n", - "vacantX+CO-2<=>CO.[Pt]\n", - "kf = 484125.61468448705\n", - "krev = 1.0558750276780043e7\n", - "Kc = 0.04585065485913965\n", - "vacantX+vacantX+CC(=O)CO<=>OC[Pt]+CC(=O)[Pt]\n", - "kf = 4.324183911493771e7\n", - "krev = 7.8667392573421875e12\n", - "Kc = 5.496793232924203e-6\n", - "vacantX+vacantX+CC(=O)CO<=>CH3X+O=C([Pt])CO\n", - "kf = 0.43146252134138535\n", - "krev = 2.5450806210309695e15\n", - "Kc = 1.695280368629765e-16\n", - "HX+O=C=C=O<=>O=C=C(O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 7.390785994602033e-44\n", - "Kc = 7.846667531546056e35\n", - "proton+O=C=C=O.[Pt]<=>O=C=C(O)[Pt]\n", - "kf = 5.0e10\n", - "krev = 7.832851008293297e-31\n", - "Kc = 6.383371769367348e40\n", - "vacantX+vacantX+O=C=CO<=>HX+O=C=C(O)[Pt]\n", - "kf = 2.8707175642480555e-12\n", - "krev = 0.04083063397693327\n", - "Kc = 7.030793511239207e-11\n", - "proton+O=C=C(O)[Pt]<=>O=C=CO.[Pt]\n", - "kf = 1.7351014576291664e10\n", - "krev = 2.4662443446341767e-14\n", - "Kc = 7.03539964077054e23\n", - "proton+O=C=C(O)[Pt]<=>H2O+O=C=C=[Pt]\n", - "kf = 1.2324712433709262e6\n", - "krev = 1.176415080398485e-31\n", - "Kc = 1.0476499867321094e37\n", - "vacantX+vacantX+O=CCC=O<=>HX+O=CCC(=O)[Pt]\n", - "kf = 3.286584099620913e-11\n", - "krev = 0.0009472638388816695\n", - "Kc = 3.469555117295539e-8\n", - "vacantX+vacantX+O=CCC=O<=>CHOX+O=CC[Pt]\n", - "kf = 5.621568394735124e8\n", - "krev = 2.2372815421494465e13\n", - "Kc = 2.51267812692642e-5\n", - "proton+O=C=C(O)C#[Pt]<=>CX+O=C=CO\n", - "kf = 3.0900625689798e-31\n", - "krev = 97363.75326657317\n", - "Kc = 3.1737299203323514e-36\n", - "proton+COOC#[Pt]<=>CX+COO\n", - "kf = 1.3396315820930446e-65\n", - "krev = 2.5e10\n", - "Kc = 5.3585263283721787e-76\n", - "vacantX+vacantX+COC=C=O<=>CO[Pt]+O=C=C[Pt]\n", - "kf = 1.4053920986837533e8\n", - "krev = 2.5815645207863396e8\n", - "Kc = 0.5443954963619013\n", - "vacantX+vacantX+COC=C=O<=>CH3X+O=C=CO[Pt]\n", - "kf = 1.4053920986837533e8\n", - "krev = 1.2268284001067661e8\n", - "Kc = 1.1455490421981163\n", - "HX+O=CC=O<=>O=CC(O)[Pt]\n", - "kf = 5.6976884072695144e-8\n", - "krev = 1.248882373151946e-25\n", - "Kc = 4.562229822244678e17\n", - "proton+O=CC(O)[Pt]<=>C=O+OC=[Pt]\n", - "kf = 1.4979350850413518e-9\n", - "krev = 7.682289195925664e-6\n", - "Kc = 0.00019498551106820976\n", - "proton+O=CC=O.[Pt]<=>O=CC(O)[Pt]\n", - "kf = 3.43386635836783e8\n", - "krev = 1.2530721027853126e-11\n", - "Kc = 2.7403581571523903e19\n", - "HX+O=C=CO<=>O=CC(O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 2.6755933088589045e-38\n", - "Kc = 1.0647523277182356e30\n", - "vacantX+vacantX+O=CCO<=>HX+O=CC(O)[Pt]\n", - "kf = 5.743984385098034e-15\n", - "krev = 0.20246227896672986\n", - "Kc = 2.8370639777506056e-14\n", - "proton+O=C=CO.[Pt]<=>O=CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.5582018736355307e-22\n", - "Kc = 9.77248912904274e31\n", - "proton+O=CC(O)[Pt]<=>H2O+O=CC=[Pt]\n", - "kf = 459.6019775429135\n", - "krev = 1.1031455244918085e-6\n", - "Kc = 4.166286018833649e8\n", - "proton+O=CC(O)C#[Pt]<=>CX+O=CCO\n", - "kf = 0.2097860124056399\n", - "krev = 0.0024507024511013467\n", - "Kc = 85.60240036947854\n", - "vacantX+vacantX+O=C=CCO<=>OC[Pt]+O=C=C[Pt]\n", - "kf = 4067.906517801298\n", - "krev = 9.581534474143486e11\n", - "Kc = 4.245568941779481e-9\n", - "proton+O=CC(=O)[Pt]<=>O=CC(O)=[Pt]\n", - "kf = 1.4625119078213113e-5\n", - "krev = 1.0085447542339824e12\n", - "Kc = 1.4501209804339615e-17\n", - "proton+O=CC(O)=[Pt]<=>OC#[Pt]+C=O\n", - "kf = 345367.8200620121\n", - "krev = 2.1066346546856475e-20\n", - "Kc = 1.6394291211996983e25\n", - "proton+O=CC(O)=[Pt]<=>H2O+O=CC#[Pt]\n", - "kf = 109541.91076063467\n", - "krev = 6.52855201530546e-37\n", - "Kc = 1.6778898368861259e41\n", - "proton+O=C=C(O)[Pt]<=>O=CC(O)=[Pt]\n", - "kf = 266253.7431100425\n", - "krev = 124230.61178859882\n", - "Kc = 2.1432217009695007\n", - "proton+O=CC(O)=[Pt]<=>O=CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.793151847783197e-46\n", - "Kc = 3.207944678649035e55\n", - "proton+OC(O)[Pt]<=>OCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.3128823116835e-26\n", - "Kc = 5.796587570283467e35\n", - "proton+OCO[Pt]<=>OCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.052557862362137e-26\n", - "Kc = 8.189852945376913e35\n", - "vacantX+OCO<=>OCO.[Pt]\n", - "kf = 395377.4080430906\n", - "krev = 715.0601225795458\n", - "Kc = 552.9289014422803\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.079525546868e-12\n", - "Kc = 1.2021973010936467e22\n", - "vacantX+O=C=C=C=O<=>O=C=C=C=O.[Pt]\n", - "kf = 332249.5811031886\n", - "krev = 401.14766551623046\n", - "Kc = 828.2475748067037\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 4.91573386591171e-7\n", - "Kc = 5.08571063485824e16\n", - "proton+O=CCO[Pt]<=>O=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.8816895227328687e-31\n", - "Kc = 1.3285932507978942e41\n", - "proton+O=C([Pt])CO<=>O=CCO.[Pt]\n", - "kf = 3.74256001789537e8\n", - "krev = 9.536073355505413e-9\n", - "Kc = 3.9246342581191416e16\n", - "vacantX+O=CCO<=>O=CCO.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 1291.5767888759226\n", - "Kc = 273.8002875141987\n", - "proton+O=CC(O)[Pt]<=>O=CCO.[Pt]\n", - "kf = 1.712472301799593e10\n", - "krev = 2.6335036754646568e-14\n", - "Kc = 6.5026387384762e23\n", - "proton+OCC#[Pt]<=>OCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.6468663797080987e-6\n", - "Kc = 6.855200437039605e15\n", - "proton+OCC=[Pt]<=>CHX+CO-2\n", - "kf = 2.437334851076409e7\n", - "krev = 3.684139726492616e-11\n", - "Kc = 6.615750302708541e17\n", - "vacantX+vacantX+O=CCO<=>OX+OCC=[Pt]\n", - "kf = 3.3881471741726223e-34\n", - "krev = 2.264159139077055e16\n", - "Kc = 1.4964262518904662e-50\n", - "vacantX+vacantX+O=C=CCO<=>OCX+OCC=[Pt]\n", - "kf = 1.8009876630720204e-13\n", - "krev = 6.668943472119082e14\n", - "Kc = 2.7005591974222413e-28\n", - "vacantX+vacantX+C=CC=O<=>CH2X+O=CC=[Pt]\n", - "kf = 3.2830355290077765e-39\n", - "krev = 2.9277080237249806e14\n", - "Kc = 1.121367124864694e-53\n", - "vacantX+vacantX+C=COC=O<=>CH2X+O=COC=[Pt]\n", - "kf = 1.0242943870290668e-63\n", - "krev = 2.920849603333263e13\n", - "Kc = 3.5068371403311754e-77\n", - "vacantX+O=C=CCO<=>O=C=CCO.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 1179.037991138623\n", - "Kc = 273.8002884035305\n", - "vacantX+vacantX+O=CC=CO<=>OC=[Pt]+O=CC=[Pt]\n", - "kf = 6.284377773759944e-35\n", - "krev = 2.1623088290446475e12\n", - "Kc = 2.90632757418676e-47\n", - "vacantX+vacantX+COC<=>CH3X+CO[Pt]\n", - "kf = 3.3416169046706564e-11\n", - "krev = 3.110510590664853e12\n", - "Kc = 1.0742985137872191e-23\n", - "proton+O=C=CC(O)[Pt]<=>OC=[Pt]+C=C=O\n", - "kf = 7.886335155622577e-9\n", - "krev = 1.1676117437495351e-7\n", - "Kc = 0.0675424446340125\n", - "HX+O=C=CC=O<=>O=C=CC(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 3.0624966294759025e-24\n", - "Kc = 8.467340919226885e15\n", - "proton+O=C=CC=O.[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 5.4417257022505686e7\n", - "krev = 1.0699402207865258e-10\n", - "Kc = 5.086009102686402e17\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=CC(O)[Pt]\n", - "kf = 2.2665619116480148e-11\n", - "krev = 0.03466826587817799\n", - "Kc = 6.537857761944495e-10\n", - "proton+O=C=CC(O)[Pt]<=>O=C=CCO.[Pt]\n", - "kf = 1.693513701515947e9\n", - "krev = 6.001577582317764e-11\n", - "Kc = 2.8217809039168078e19\n", - "proton+O=C=CC=[Pt]<=>CHX+C=C=O\n", - "kf = 181.35768264661723\n", - "krev = 8.307531938850336e-7\n", - "Kc = 2.183051283841528e8\n", - "proton+O=C=CC#[Pt]<=>O=C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.768026569342988e-11\n", - "Kc = 1.4140058997693788e21\n", - "vacantX+vacantX+O=C=CC=O<=>OX+O=C=CC=[Pt]\n", - "kf = 3.709849833927781e-21\n", - "krev = 2.4389911159903437e17\n", - "Kc = 1.5210591828750508e-38\n", - "proton+O=C=CC(O)[Pt]<=>H2O+O=C=CC=[Pt]\n", - "kf = 4.694863820330143\n", - "krev = 3.9520471176425216e-5\n", - "Kc = 118795.74510565875\n", - "vacantX+vacantX+CCO<=>CH3X+OC[Pt]\n", - "kf = 1.5510087911871897e-15\n", - "krev = 9.749013808701775e13\n", - "Kc = 1.5909391674086975e-29\n", - "proton+O=C=C([Pt])CO<=>CO-2+O=C=C=[Pt]\n", - "kf = 259142.28390262663\n", - "krev = 5.010713983419634e-21\n", - "Kc = 5.171763640074528e25\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=C([Pt])CO\n", - "kf = 4.040764431615523e-20\n", - "krev = 30.812673220085827\n", - "Kc = 1.3113969056672023e-21\n", - "proton+O=C=C([Pt])CO<=>O=C=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.777114479215893e-21\n", - "Kc = 1.4067748753603438e31\n", - "proton+O=C=CC[Pt]<=>CH2X+C=C=O\n", - "kf = 6.0148104045883e-8\n", - "krev = 8.74545093406659e-6\n", - "Kc = 0.006877644674854341\n", - "vacantX+vacantX+O=C=CCO<=>HOX+O=C=CC[Pt]\n", - "kf = 8.032715739528718e-6\n", - "krev = 4.997427676480693e14\n", - "Kc = 1.6073700830795308e-20\n", - "proton+O=C=CC=[Pt]<=>O=C=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.1155543114237032e-25\n", - "Kc = 1.1817233840324226e35\n", - "vacantX+vacantX+CC(O)O<=>CH3X+OC(O)[Pt]\n", - "kf = 1.0212279299691738e-21\n", - "krev = 4.839386960246169e15\n", - "Kc = 2.1102423475497943e-37\n", - "proton+O=C=CC(O)=[Pt]<=>OC#[Pt]+C=C=O\n", - "kf = 1.5097720767202745e6\n", - "krev = 3.361950781834918e-17\n", - "Kc = 4.490761985207459e22\n", - "proton+O=C=CC(O)=[Pt]<=>H2O+O=C=CC#[Pt]\n", - "kf = 5.803789817126122e6\n", - "krev = 2.7232165859221153e-28\n", - "Kc = 2.1312259359498893e34\n", - "proton+O=C=CC(=O)[Pt]<=>O=C=CC(O)=[Pt]\n", - "kf = 0.6530550593549805\n", - "krev = 1.0085447542339824e12\n", - "Kc = 6.475221417923034e-13\n", - "proton+O=C=CC(O)=[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.85508059604632e-41\n", - "Kc = 2.5367626125786886e50\n", - "C=O+O=C=C[Pt]<=>O=C=CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 80798.59947863563\n", - "Kc = 4.901904683810505e-13\n", - "HX+O=C=CC=O<=>O=C=CCO[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 2.019947796444839e-5\n", - "Kc = 0.0012837560986177624\n", - "proton+O=C=CC=O.[Pt]<=>O=C=CCO[Pt]\n", - "kf = 278.5863350248319\n", - "krev = 3612.827309769227\n", - "Kc = 0.07711033800910536\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=CCO[Pt]\n", - "kf = 7.342900678318069e-26\n", - "krev = 740.7927312780465\n", - "Kc = 9.912220204496055e-29\n", - "proton+O=C=CCO[Pt]<=>O=C=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3432355963676785e-28\n", - "Kc = 1.861177597407629e38\n", - "vacantX+vacantX+CCOC=O<=>CH3X+O=COC[Pt]\n", - "kf = 1.714178070740009e-17\n", - "krev = 1.2983121019578911e14\n", - "Kc = 1.3203127877765141e-31\n", - "proton+O=CC([Pt])C=O<=>C=O+O=CC=[Pt]\n", - "kf = 1.0131844482393167e-10\n", - "krev = 2.9534786470384583e-7\n", - "Kc = 0.00034304783251277847\n", - "HX+O=C=CC=O<=>O=CC([Pt])C=O\n", - "kf = 2.5931203025755725e-8\n", - "krev = 5.183135272095574e-24\n", - "Kc = 5.002995612590211e15\n", - "proton+O=C=CC=O.[Pt]<=>O=CC([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 8.319166178505196e-8\n", - "Kc = 3.005108861101275e17\n", - "vacantX+vacantX+O=CCC=O<=>HX+O=CC([Pt])C=O\n", - "kf = 6.269624738894468e-15\n", - "krev = 24.522149705338403\n", - "Kc = 2.556719053684591e-16\n", - "proton+O=CC(=[Pt])C=O<=>C=O+O=CC#[Pt]\n", - "kf = 0.04202179791424184\n", - "krev = 2.102387409121332e-9\n", - "Kc = 1.9987656761987723e7\n", - "proton+O=C=C([Pt])C=O<=>O=CC(=[Pt])C=O\n", - "kf = 2.5e10\n", - "krev = 5.057292696382588\n", - "Kc = 4.943356357025204e9\n", - "proton+O=CC(=[Pt])C=O<=>O=CC([Pt])C=O\n", - "kf = 2.5e10\n", - "krev = 5.3866690937421086e-24\n", - "Kc = 4.641087017771969e33\n", - "vacantX+vacantX+COCC=O<=>CH3X+O=CCO[Pt]\n", - "kf = 1.7650043109029407e-12\n", - "krev = 1.4735149295451475e13\n", - "Kc = 1.1978190892492496e-25\n", - "vacantX+vacantX+COCC=O<=>CO[Pt]+O=CC[Pt]\n", - "kf = 10.947009513309483\n", - "krev = 5.112987413682155e11\n", - "Kc = 2.1410202348661592e-11\n", - "proton+O=CCC(=O)[Pt]<=>O=CCC=O.[Pt]\n", - "kf = 2.1814901321970692e8\n", - "krev = 5.7550523540318155e-8\n", - "Kc = 3.7905652251256815e15\n", - "vacantX+O=CCC=O<=>O=CCC=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 165389.8266532618\n", - "Kc = 1.951879075907524\n", - "proton+O=CC([Pt])C=O<=>O=CCC=O.[Pt]\n", - "kf = 1.6062704929440186e10\n", - "krev = 3.122654421781107e-14\n", - "Kc = 5.1439265316711864e23\n", - "proton+O=CCC#[Pt]<=>O=CCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.03648176110191e-17\n", - "Kc = 4.141485220927174e26\n", - "proton+O=CCC=[Pt]<=>CHX+CC=O\n", - "kf = 1.0605779567215914e7\n", - "krev = 5.748508015003e-13\n", - "Kc = 1.8449621257439228e19\n", - "vacantX+vacantX+O=CCC=O<=>OX+O=CCC=[Pt]\n", - "kf = 1.2771337705277995e-31\n", - "krev = 6.599290845791489e16\n", - "Kc = 1.935259106426951e-48\n", - "vacantX+vacantX+CCOO<=>CH3X+OOC[Pt]\n", - "kf = 1.1728434846364774e-18\n", - "krev = 2.6840450809869076e16\n", - "Kc = 4.3696862356918e-35\n", - "proton+OOCC#[Pt]<=>CX+COO\n", - "kf = 0.24698833297799483\n", - "krev = 0.0004336424509567548\n", - "Kc = 569.5667765760919\n", - "vacantX+vacantX+C=C=O<=>OX+C=C=[Pt]\n", - "kf = 5.2796000958546504e-37\n", - "krev = 1.4614931014553018e17\n", - "Kc = 3.612470076387919e-54\n", - "proton+C=C=[Pt]<=>CC#[Pt]\n", - "kf = 10.738937415423795\n", - "krev = 4.122167482176662e-33\n", - "Kc = 2.60516766042539e33\n", - "vacantX+vacantX+CC(C)=O<=>CH3X+CC(=O)[Pt]\n", - "kf = 0.0015322757193851075\n", - "krev = 1.9084257758101816e14\n", - "Kc = 8.029003479239911e-18\n", - "vacantX+vacantX+C=C=C=O<=>CH2X+O=C=C=[Pt]\n", - "kf = 0.014873013888318402\n", - "krev = 6.520037160662236e15\n", - "Kc = 2.2811240981957472e-18\n", - "HOX+C=C=C=O<=>O=C=C([Pt])CO\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.9529365102554657e-31\n", - "Kc = 9.99708792916859e22\n", - "HX+C=C=C=O<=>O=C=CC[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.4091973858076736e-32\n", - "Kc = 1.225336127134283e24\n", - "vacantX+vacantX+C=C=C=O<=>OCX+C=C=[Pt]\n", - "kf = 0.8504584217531632\n", - "krev = 1.347597642765549e15\n", - "Kc = 6.310922450174717e-16\n", - "proton+O=C(O)C=[Pt]<=>CHX+O=CO\n", - "kf = 7.88145235948431e7\n", - "krev = 1.995696153847229e-7\n", - "Kc = 3.949224607308452e14\n", - "proton+O=C(O)C#[Pt]<=>O=C(O)C=[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.424855572557093e-13\n", - "Kc = 3.3670688615684534e22\n", - "vacantX+vacantX+CC=C=O<=>CH3X+O=C=C[Pt]\n", - "kf = 0.0008567749561878586\n", - "krev = 1.2359860589695025e13\n", - "Kc = 6.931914401220598e-17\n", - "vacantX+vacantX+CC=C=O<=>HX+O=C=CC[Pt]\n", - "kf = 2.2773385768535307e-19\n", - "krev = 181.8091471864856\n", - "Kc = 1.2525984594810374e-21\n", - "proton+O=C=CCO[Pt]<=>OX+CC=C=O\n", - "kf = 3.801213612232799e6\n", - "krev = 3.4005935521726275e-15\n", - "Kc = 1.1178088630451637e21\n", - "proton+CC(=O)[Pt]<=>CC=O.[Pt]\n", - "kf = 2.2108223076011086e9\n", - "krev = 2.493722128340101e-11\n", - "Kc = 8.865551949337277e19\n", - "proton+O=CC[Pt]<=>CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0175396707648368e-24\n", - "Kc = 2.456906665978799e34\n", - "vacantX+CC=O<=>CC=O.[Pt]\n", - "kf = 412885.969273148\n", - "krev = 2.625517699834265\n", - "Kc = 157258.8786200951\n", - "proton+CC=[Pt]<=>CHX+CH4\n", - "kf = 3.754229088708618e7\n", - "krev = 3.193900280463504e-10\n", - "Kc = 1.1754371642948722e17\n", - "proton+CC#[Pt]<=>CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.101069134371629e-9\n", - "Kc = 3.086012424450092e18\n", - "vacantX+vacantX+CC=O<=>OX+CC=[Pt]\n", - "kf = 6.186864182993887e-31\n", - "krev = 2.034915252803989e19\n", - "Kc = 3.04035471475717e-50\n", - "vacantX+vacantX+CC=C=O<=>OCX+CC=[Pt]\n", - "kf = 5.619880038277716e-8\n", - "krev = 4.919193785592355e16\n", - "Kc = 1.14243924578405e-24\n", - "vacantX+vacantX+CC<=>CH3X+CH3X\n", - "kf = 1.6866972609475142e-22\n", - "krev = 6.547125244410207e13\n", - "Kc = 2.576241018739606e-36\n", - "proton+O=C=CC[Pt]<=>CC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.381078389100095e-19\n", - "Kc = 1.0499444333476355e29\n", - "vacantX+CC=C=O<=>CC=C=O.[Pt]\n", - "kf = 365995.57053717994\n", - "krev = 187509.1639624155\n", - "Kc = 1.9518809790573244\n", - "proton+O=C(O)C[Pt]<=>CH2X+O=CO\n", - "kf = 5.038535015011119e-9\n", - "krev = 7.877133180076684e-5\n", - "Kc = 6.396407042799381e-5\n", - "HOX+C=C=O<=>O=C(O)C[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.348252838458729e-29\n", - "Kc = 4.5553052781738184e20\n", - "vacantX+vacantX+CC(=O)O<=>HX+O=C(O)C[Pt]\n", - "kf = 1.1112170024966995e-23\n", - "krev = 36323.66987445037\n", - "Kc = 3.0592090676342045e-28\n", - "proton+O=C(O)C=[Pt]<=>O=C(O)C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0876086200539217e-33\n", - "Kc = 2.2986209872776243e43\n", - "vacantX+vacantX+O=C=C=CO<=>OC=[Pt]+O=C=C=[Pt]\n", - "kf = 0.004371453552681894\n", - "krev = 1.2572855491392857e13\n", - "Kc = 3.476897953431907e-16\n", - "HX+O=C=C=CO<=>O=C=CC(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.3635197599529065e-33\n", - "Kc = 1.9017841755847633e25\n", - "HX+O=C=C=CO<=>O=C=C([Pt])CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 6.797711819853139e-22\n", - "Kc = 3.814695843684052e13\n", - "proton+O=C(O)CC#[Pt]<=>CX+CC(=O)O\n", - "kf = 0.12574987603391333\n", - "krev = 9.921358720719502e-5\n", - "Kc = 1267.4662772882168\n", - "proton+CC([Pt])=C=O<=>CH4+O=C=C=[Pt]\n", - "kf = 49487.72961177987\n", - "krev = 1.2730900614037961e-24\n", - "Kc = 3.8872135689451003e28\n", - "HX+C=C=C=O<=>CC([Pt])=C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.301177455844525e-32\n", - "Kc = 1.2828548214436644e24\n", - "vacantX+vacantX+CC=C=O<=>HX+CC([Pt])=C=O\n", - "kf = 4.581183222917958e-20\n", - "krev = 34.93361388628861\n", - "Kc = 1.3113968791863429e-21\n", - "proton+CC([Pt])=C=O<=>CC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.492848961236613e-19\n", - "Kc = 1.0028686209532082e29\n", - "CH3X+O=C=C=O<=>CC(=C=O)O[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.951682102619952e-64\n", - "Kc = 1.9647454732667077e56\n", - "proton+CC(=C=O)O[Pt]<=>OX+CC=C=O\n", - "kf = 1.920567374031219e-6\n", - "krev = 5.0434729686975995e-5\n", - "Kc = 0.03808025513274787\n", - "vacantX+C=C<=>C=C.[Pt]\n", - "kf = 36.21750369826068\n", - "krev = 0.32335117013731834\n", - "Kc = 112.00671914340097\n", - "vacantX+vacantX+C=CO<=>HOX+C=C[Pt]\n", - "kf = 1.7018617233469498e-12\n", - "krev = 4.164837143763027e13\n", - "Kc = 4.086262354568991e-26\n", - "vacantX+vacantX+C=C<=>HX+C=C[Pt]\n", - "kf = 6.071347272542775e-23\n", - "krev = 1180.067101472276\n", - "Kc = 5.144916983930861e-26\n", - "vacantX+vacantX+C=CC=O<=>CHOX+C=C[Pt]\n", - "kf = 0.3274906030624493\n", - "krev = 2.9425898600264806e14\n", - "Kc = 1.1129332276687114e-15\n", - "vacantX+vacantX+C=COC=O<=>CHO2X+C=C[Pt]\n", - "kf = 0.2513917911405871\n", - "krev = 1.0405847657707406e16\n", - "Kc = 2.4158703779829617e-17\n", - "proton+C=C=[Pt]<=>C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.446578752089028e-33\n", - "Kc = 1.0218350820979533e43\n", - "proton+C=C[Pt]<=>CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 31.775139733809926\n", - "Kc = 7.867786014296917e8\n", - "proton+C=C[Pt]<=>C=C.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.7043133558442046e-25\n", - "Kc = 1.4668664019015827e35\n", - "proton+C=CC#[Pt]<=>CX+C=C\n", - "kf = 1.0856530221273585e-15\n", - "krev = 0.12983129718682296\n", - "Kc = 8.36202861444987e-15\n", - "vacantX+CC(=O)O<=>CC(=O)O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 181176.05501028927\n", - "Kc = 1.9518809818483447\n", - "proton+CC(=O)O[Pt]<=>CC(=O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.133892027559991e-24\n", - "Kc = 6.04756965913213e33\n", - "proton+O=C(O)C[Pt]<=>CC(=O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.815284645396005e-26\n", - "Kc = 4.2990157016290936e35\n", - "proton+C=CC(=O)[Pt]<=>OCX+C=C\n", - "kf = 7.087170621400232e6\n", - "krev = 2.9783308105065206e-7\n", - "Kc = 2.3795780496911715e13\n", - "vacantX+vacantX+C=CC=O<=>HX+C=CC(=O)[Pt]\n", - "kf = 3.052485738368744e-11\n", - "krev = 0.0007099643372969683\n", - "Kc = 4.29949164769375e-8\n", - "HX+C=C=C=O<=>C=CC(=O)[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 5.604440911093213e-48\n", - "Kc = 5.267388203494818e39\n", - "HX+O=C=CC=O<=>O=CC=CO[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 5.6159867257682645e-34\n", - "Kc = 4.61739037002591e25\n", - "proton+O=C=CC=O.[Pt]<=>O=CC=CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 9.013912308921113e-18\n", - "Kc = 2.7734904826239954e27\n", - "proton+O=CC=CO[Pt]<=>OX+C=CC=O\n", - "kf = 3.6615493516163485e-10\n", - "krev = 9.407550626549198e-5\n", - "Kc = 3.892138875429521e-6\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC=CO[Pt]\n", - "kf = 4.135805741920728e-10\n", - "krev = 0.028732529553568358\n", - "Kc = 1.4394158141245496e-8\n", - "HX+C=C=O<=>C=CO[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.272169613200064e-8\n", - "Kc = 0.46029640012283785\n", - "proton+C=C=O.[Pt]<=>C=CO[Pt]\n", - "kf = 2.7021695253394946e-5\n", - "krev = 3753.979595717479\n", - "Kc = 7.19814654406251e-9\n", - "vacantX+vacantX+C=CO<=>HX+C=CO[Pt]\n", - "kf = 1.5839272910037507e-20\n", - "krev = 3600.161649580889\n", - "Kc = 4.399600476795654e-24\n", - "proton+C=CO[Pt]<=>OX+C=C\n", - "kf = 6.694428008398142e6\n", - "krev = 4.294813980591457e-9\n", - "Kc = 1.5587236231070068e15\n", - "vacantX+vacantX+C=COC=O<=>CHOX+C=CO[Pt]\n", - "kf = 0.024290856013790354\n", - "krev = 3.5586883050271985e15\n", - "Kc = 6.825789148062155e-18\n", - "vacantX+vacantX+O=CCCO<=>OC[Pt]+O=CC[Pt]\n", - "kf = 2.162232232095232e-5\n", - "krev = 5.66671683371172e13\n", - "Kc = 3.815670158833332e-19\n", - "proton+C=COC(=O)[Pt]<=>OCX+C=CO\n", - "kf = 8.547694380469097e6\n", - "krev = 5.219823560516419e-10\n", - "Kc = 1.637544695020963e16\n", - "vacantX+vacantX+C=COC=O<=>HX+C=COC(=O)[Pt]\n", - "kf = 3.5117597357119104e-15\n", - "krev = 0.7837038908782975\n", - "Kc = 4.480977798612533e-15\n", - "CO2+C=C[Pt]<=>C=COC(=O)[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.08399332498323721\n", - "Kc = 7.789900440580834e-7\n", - "proton+C=COC#[Pt]<=>CX+C=CO\n", - "kf = 3.59319568894763e-23\n", - "krev = 3.7552909398960855e-5\n", - "Kc = 9.568355012853036e-19\n", - "vacantX+vacantX+CCC=O<=>CH3X+O=CC[Pt]\n", - "kf = 1.2257627381394946e-12\n", - "krev = 3.270257576074817e14\n", - "Kc = 3.748214657790771e-27\n", - "proton+CC(O)=[Pt]<=>OC#[Pt]+CH4\n", - "kf = 7.023325690411809e6\n", - "krev = 0.001122962882704699\n", - "Kc = 6.254281239906934e9\n", - "proton+CC(=O)[Pt]<=>CC(O)=[Pt]\n", - "kf = 9.881755573608883e9\n", - "krev = 1.0085447542339819e12\n", - "Kc = 0.009798033782957261\n", - "proton+CC(O)=[Pt]<=>H2O+CC#[Pt]\n", - "kf = 7.254296675241664e9\n", - "krev = 2.8720393080667615e-6\n", - "Kc = 2.5258347456688205e15\n", - "vacantX+vacantX+CC(=O)O<=>OX+CC(O)=[Pt]\n", - "kf = 1.1829749543892744e-33\n", - "krev = 3.758913107590896e15\n", - "Kc = 3.1471197139415875e-49\n", - "vacantX+vacantX+CC(O)=C=O<=>CH3X+O=C=C(O)[Pt]\n", - "kf = 1.049990631922765e-6\n", - "krev = 1.7955210884029898e15\n", - "Kc = 5.847832357439309e-22\n", - "vacantX+vacantX+CC(O)=C=O<=>HOX+CC([Pt])=C=O\n", - "kf = 0.0029164033711847528\n", - "krev = 3.4437539939134434e12\n", - "Kc = 8.468675103794464e-16\n", - "vacantX+vacantX+CC(O)=C=O<=>HX+CC(=C=O)O[Pt]\n", - "kf = 1.7528367761452354e-6\n", - "krev = 1.1970864565480504e-5\n", - "Kc = 0.14642524494009906\n", - "vacantX+vacantX+CC(O)=C=O<=>OCX+CC(O)=[Pt]\n", - "kf = 65.80946386077328\n", - "krev = 1217.699742052305\n", - "Kc = 0.054044081301896585\n", - "vacantX+vacantX+C=CC=O<=>HX+O=CC=C[Pt]\n", - "kf = 6.342176392543457e-21\n", - "krev = 776.2437464870187\n", - "Kc = 8.170341366672147e-24\n", - "vacantX+vacantX+O=CC=CO<=>HOX+O=CC=C[Pt]\n", - "kf = 4.672349699632388e-15\n", - "krev = 8.81363422062413e13\n", - "Kc = 5.301274800693419e-29\n", - "proton+O=CC=C[Pt]<=>O=CCC=[Pt]\n", - "kf = 1.2673656466904085e10\n", - "krev = 1.0824082827935274e8\n", - "Kc = 117.08757839689983\n", - "proton+C=CC(=O)O[Pt]<=>OX+C=CC=O\n", - "kf = 4.524546416801015\n", - "krev = 7.68227583414659e-9\n", - "Kc = 5.889591202505473e8\n", - "CO2+C=C[Pt]<=>C=CC(=O)O[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 450683.30306117237\n", - "Kc = 1.4517947189269602e-13\n", - "vacantX+vacantX+O=C=CO<=>OX+OC=C=[Pt]\n", - "kf = 7.548264554696059e-34\n", - "krev = 5.749061160710156e15\n", - "Kc = 1.3129560364189368e-49\n", - "proton+OC=C=[Pt]<=>OCC#[Pt]\n", - "kf = 0.00032547344886471076\n", - "krev = 1.1489507349403094e-46\n", - "Kc = 2.832788551909668e42\n", - "vacantX+vacantX+O=C=C=CO<=>OCX+OC=C=[Pt]\n", - "kf = 1.463392220587488e-22\n", - "krev = 7.968303762369095e13\n", - "Kc = 1.8365166090912173e-36\n", - "proton+CC[Pt]<=>CH2X+CH4\n", - "kf = 1.4846524062695914\n", - "krev = 9.859129077434927e-6\n", - "Kc = 150586.56749586415\n", - "HX+C=C<=>CC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 3.1627439012977165e-12\n", - "Kc = 25911.109388377805\n", - "vacantX+vacantX+CCO<=>HOX+CC[Pt]\n", - "kf = 2.1035625708276702e-15\n", - "krev = 1.0019023766861524e15\n", - "Kc = 2.099568400850909e-30\n", - "vacantX+vacantX+CCOC=O<=>CHO2X+CC[Pt]\n", - "kf = 0.08561452397466171\n", - "krev = 3.215769317238553e17\n", - "Kc = 2.6623341268826044e-19\n", - "vacantX+vacantX+CCOO<=>OO[Pt]+CC[Pt]\n", - "kf = 1.262172875849309e-6\n", - "krev = 1.5596341944506717e13\n", - "Kc = 8.092749443044025e-20\n", - "proton+CC=[Pt]<=>CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.602708332438123e-27\n", - "Kc = 2.9060615603731233e36\n", - "vacantX+vacantX+CC<=>HX+CC[Pt]\n", - "kf = 8.697106954471648e-14\n", - "krev = 5.359609736165605e16\n", - "Kc = 1.6227127314485718e-30\n", - "proton+C=C.[Pt]<=>CC[Pt]\n", - "kf = 5.504599623053448e9\n", - "krev = 0.3531497863658743\n", - "Kc = 1.558715263486103e10\n", - "vacantX+vacantX+CCC=O<=>CHOX+CC[Pt]\n", - "kf = 0.0004422945453165714\n", - "krev = 9.363325052982716e15\n", - "Kc = 4.723691026572629e-20\n", - "vacantX+vacantX+CC(O)C=O<=>CH3X+O=CC(O)[Pt]\n", - "kf = 9.477814531468979e-7\n", - "krev = 7.52142668687151e15\n", - "Kc = 1.2601086105129898e-22\n", - "proton+CCC#[Pt]<=>CX+CC\n", - "kf = 3.73018742862406e-11\n", - "krev = 0.075105066117345\n", - "Kc = 4.966625583946592e-10\n", - "C=O+CH3X<=>CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.1808191230067762e-17\n", - "Kc = 3.354171909251678e9\n", - "HX+CC=O<=>CCO[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 2.639709061724686e-6\n", - "Kc = 0.012387213631168494\n", - "vacantX+vacantX+CCO<=>HX+CCO[Pt]\n", - "kf = 5.372480262216755e-24\n", - "krev = 2113.809062877283\n", - "Kc = 2.5416109508508876e-27\n", - "vacantX+vacantX+CCOC=O<=>CHOX+CCO[Pt]\n", - "kf = 4.80530366959931e-5\n", - "krev = 5.681813674074216e13\n", - "Kc = 8.457341168235823e-19\n", - "vacantX+vacantX+CCOO<=>HOX+CCO[Pt]\n", - "kf = 3.028654941635431e8\n", - "krev = 1.2132864881112858e-12\n", - "Kc = 2.496240559268171e20\n", - "proton+CC=O.[Pt]<=>CCO[Pt]\n", - "kf = 19418.796323941955\n", - "krev = 3658.802750537776\n", - "Kc = 5.30741820424393\n", - "proton+CCO[Pt]<=>OX+CC\n", - "kf = 1.5180806810718186e7\n", - "krev = 3.4536717602694347e-12\n", - "Kc = 4.395555763392486e18\n", - "proton+CCOC(=O)[Pt]<=>OCX+CCO\n", - "kf = 1.100364657251968e9\n", - "krev = 4.5302115405928314e-10\n", - "Kc = 2.4289476272623954e18\n", - "vacantX+vacantX+CCOC=O<=>HX+CCOC(=O)[Pt]\n", - "kf = 2.5742212027881315e-15\n", - "krev = 0.39729482671494754\n", - "Kc = 6.479372570927264e-15\n", - "CO2+CC[Pt]<=>CCOC(=O)[Pt]\n", - "kf = 3.860701485876577e-7\n", - "krev = 0.0037771400241392917\n", - "Kc = 0.00010221229451921966\n", - "CH3X+C=C=O<=>CCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.9339597186194493e-34\n", - "Kc = 1.7308289628845924e26\n", - "HX+CC=C=O<=>CCC(=O)[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 2.728234417234893e-33\n", - "Kc = 1.0624138213938816e25\n", - "proton+CCC(=O)[Pt]<=>OCX+CC\n", - "kf = 3.3183098775357734e7\n", - "krev = 1.723115430616528e-10\n", - "Kc = 1.9257618024745373e17\n", - "proton+CC=C=O.[Pt]<=>CCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.816709270833084e-23\n", - "Kc = 3.667458740974689e32\n", - "vacantX+vacantX+CCC=O<=>HX+CCC(=O)[Pt]\n", - "kf = 1.3037608552158366e-12\n", - "krev = 0.18236199715464047\n", - "Kc = 7.149301255514685e-12\n", - "vacantX+vacantX+C=C(O)C=O<=>CH2X+O=CC(O)=[Pt]\n", - "kf = 3.506980389191063e-59\n", - "krev = 1.6121784785918364e12\n", - "Kc = 2.1753053001019147e-71\n", - "proton+CCOC#[Pt]<=>CX+CCO\n", - "kf = 1.6403573057503937e-22\n", - "krev = 1.0480859144262605e-13\n", - "Kc = 1.5650981309565184e-9\n", - "proton+CCC(=O)O[Pt]<=>OX+CCC=O\n", - "kf = 5.622114816602621e-8\n", - "krev = 4.785365563630673e-7\n", - "Kc = 0.11748558687619057\n", - "CO2+CC[Pt]<=>CCC(=O)O[Pt]\n", - "kf = 3.860701485876577e-7\n", - "krev = 2.2515045234693432e-8\n", - "Kc = 17.147207325738\n", - "vacantX+vacantX+OC=CCO<=>OC=[Pt]+OCC=[Pt]\n", - "kf = 3.6700973989487563e-44\n", - "krev = 3.0504263460080312e13\n", - "Kc = 1.203142440646588e-57\n", - "proton+CC(=C=O)O[Pt]<=>CC(O)=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 27.83415070046663\n", - "Kc = 8.981772165076653e8\n", - "vacantX+CC(O)=C=O<=>CC(O)=C=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 165389.73964983693\n", - "Kc = 1.9518801026953096\n", - "proton+OOC=[Pt]<=>OO+CHX\n", - "kf = 2.8719882764673755e7\n", - "krev = 8.077545633440945e-25\n", - "Kc = 3.555520955000709e31\n", - "proton+OOC=[Pt]<=>OOC[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.62255074484058e-37\n", - "Kc = 2.899374064566577e46\n", - "proton+OOC#[Pt]<=>OOC=[Pt]\n", - "kf = 3.432151727081939e-44\n", - "krev = 3342.777740155216\n", - "Kc = 1.0267364431242663e-47\n", - "vacantX+vacantX+C=CCO<=>CH2X+OCC=[Pt]\n", - "kf = 3.3256293066300124e-48\n", - "krev = 2.638642223210571e15\n", - "Kc = 1.2603562837645906e-63\n", - "vacantX+vacantX+C=CCO<=>OC[Pt]+C=C[Pt]\n", - "kf = 1.4930923415267688e-9\n", - "krev = 1.1121057711212152e14\n", - "Kc = 1.3425812366942817e-23\n", - "vacantX+OO<=>OO.[Pt]\n", - "kf = 469882.2241291155\n", - "krev = 15.560302693769444\n", - "Kc = 30197.498941795184\n", - "proton+OO[Pt]<=>OO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.110596489625074e-24\n", - "Kc = 2.251042591395165e34\n", - "C=O+CO[Pt]<=>COCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 9.545218685674386e-14\n", - "Kc = 414937.62088874576\n", - "HX+COC=O<=>COCO[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 0.02522938529859348\n", - "Kc = 1.1100614687459063e-6\n", - "vacantX+vacantX+COCO<=>HX+COCO[Pt]\n", - "kf = 1.0488506310161173e-19\n", - "krev = 521.1543106644776\n", - "Kc = 2.0125529225284944e-22\n", - "proton+COC=O.[Pt]<=>COCO[Pt]\n", - "kf = 0.6792883990466445\n", - "krev = 3726.123137157573\n", - "Kc = 0.00018230433457033608\n", - "proton+COCO[Pt]<=>OX+COC\n", - "kf = 5093.375621150868\n", - "krev = 5.977614318003391e-7\n", - "Kc = 8.520749834613165e9\n", - "CO[Pt]+C=C=O<=>COCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.680149232421768e-23\n", - "Kc = 1.9922953446306685e15\n", - "HX+COC=C=O<=>COCC(=O)[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 2.661991446097411e-38\n", - "Kc = 9.604054388173769e29\n", - "proton+COCC(=O)[Pt]<=>OCX+COC\n", - "kf = 8.734746675052269e7\n", - "krev = 2.1771371890779743e-8\n", - "Kc = 4.012033196103488e15\n", - "vacantX+vacantX+COCC=O<=>HX+COCC(=O)[Pt]\n", - "kf = 2.290241001822749e-10\n", - "krev = 0.0004872161822843353\n", - "Kc = 4.7006669423105973e-7\n", - "proton+COCOC#[Pt]<=>CX+COCO\n", - "kf = 3.2770328923262016e-17\n", - "krev = 2.1864147814239428e-13\n", - "Kc = 0.0001498815741719407\n", - "proton+COCC#[Pt]<=>CX+COC\n", - "kf = 1.433200340176918\n", - "krev = 0.00041586763423335837\n", - "Kc = 3446.289689792732\n", - "proton+COC[Pt]<=>CH2X+CO-2\n", - "kf = 0.2769010105768301\n", - "krev = 3.0099119392563808e-6\n", - "Kc = 91996.38267332179\n", - "vacantX+vacantX+COCO<=>HOX+COC[Pt]\n", - "kf = 8.90444501639475e-13\n", - "krev = 8.409201083164982e12\n", - "Kc = 1.0588931015362724e-25\n", - "C=O+CH3X<=>COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 8.422687202008296e-11\n", - "Kc = 470.23832623775377\n", - "vacantX+vacantX+COC<=>HX+COC[Pt]\n", - "kf = 2.786306429788959e-20\n", - "krev = 52.25975865319748\n", - "Kc = 5.3316481009398625e-22\n", - "vacantX+vacantX+COCC=O<=>CHOX+COC[Pt]\n", - "kf = 1.4060776479118306e6\n", - "krev = 6.613786245273692e13\n", - "Kc = 2.1259798786461146e-8\n", - "vacantX+vacantX+C=C=CO<=>OC=[Pt]+C=C=[Pt]\n", - "kf = 1.5975335437882445e-34\n", - "krev = 2.2957840869759923e8\n", - "Kc = 6.958553083676594e-43\n", - "vacantX+vacantX+C=C=CO<=>CH2X+OC=C=[Pt]\n", - "kf = 9.363402027600756e-56\n", - "krev = 7.047835211144391e9\n", - "Kc = 1.328550079149818e-65\n", - "vacantX+vacantX+COC=O<=>OX+COC=[Pt]\n", - "kf = 1.1797200153280936e-59\n", - "krev = 4.3408253155831816e16\n", - "Kc = 2.7177320660497494e-76\n", - "proton+COC=[Pt]<=>CHX+CO-2\n", - "kf = 479145.9852086257\n", - "krev = 1.0449825701778588e-33\n", - "Kc = 4.5852055228736854e38\n", - "proton+COC#[Pt]<=>COC=[Pt]\n", - "kf = 90933.51053402986\n", - "krev = 2739.427130274527\n", - "Kc = 33.194352764155155\n", - "vacantX+vacantX+COC=C=O<=>OCX+COC=[Pt]\n", - "kf = 2.7777170398864307e-21\n", - "krev = 2.5089215324603047e13\n", - "Kc = 1.107135876490541e-34\n", - "proton+COC=[Pt]<=>COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3472876439887766e-48\n", - "Kc = 1.8555799952254487e58\n", - "vacantX+COC=C=O<=>COC=C=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 1179.0380002145982\n", - "Kc = 273.8002862958761\n", - "proton+COC=C=O.[Pt]<=>COCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.0577777781824875e-25\n", - "Kc = 2.3634453772469967e35\n", - "vacantX+vacantX+C=C=C<=>CH2X+C=C=[Pt]\n", - "kf = 4.78083312177258e-41\n", - "krev = 4.774618642094983e15\n", - "Kc = 1.0013015656628172e-56\n", - "proton+O=C=COC[Pt]<=>CH2X+O=C=CO\n", - "kf = 4.988523456059943e-5\n", - "krev = 0.0009299241102698363\n", - "Kc = 0.05364441464596958\n", - "C=O+O=C=C[Pt]<=>O=C=COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.852140732586457e13\n", - "Kc = 2.1384283940268284e-21\n", - "vacantX+vacantX+COC=C=O<=>HX+O=C=COC[Pt]\n", - "kf = 3.256466928453685e-21\n", - "krev = 26.50445975246776\n", - "Kc = 1.2286486722863626e-22\n", - "proton+O=C=COC[Pt]<=>COC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.6649798034152577e-22\n", - "Kc = 1.5015197150571575e32\n", - "CH3X+O=C=C=O<=>COC([Pt])=C=O\n", - "kf = 5.799304049644909e-8\n", - "krev = 3.1615249923835833e-35\n", - "Kc = 1.8343375629216876e27\n", - "proton+COC([Pt])=C=O<=>CO-2+O=C=C=[Pt]\n", - "kf = 313658.31445379555\n", - "krev = 1.256306436150439e-34\n", - "Kc = 2.496670441448219e39\n", - "vacantX+vacantX+COC=C=O<=>HX+COC([Pt])=C=O\n", - "kf = 2.779636780044878e-20\n", - "krev = 3.601218910546807\n", - "Kc = 7.718599866018197e-21\n", - "proton+COC([Pt])=C=O<=>COC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0459713323621888e-20\n", - "Kc = 2.390122867281724e30\n", - "vacantX+vacantX+C=C=C(O)O<=>OC(O)=[Pt]+C=C=[Pt]\n", - "kf = 2.937512138355157e-45\n", - "krev = 8.778136400287878e10\n", - "Kc = 3.34639609639561e-56\n", - "proton+O=C=COC=[Pt]<=>CHX+O=C=CO\n", - "kf = 2.102599834403735e7\n", - "krev = 1.6989476123058672e-25\n", - "Kc = 1.237589563782969e32\n", - "proton+O=C=COC#[Pt]<=>O=C=COC=[Pt]\n", - "kf = 1080.8801129554665\n", - "krev = 2888.2699525834805\n", - "Kc = 0.37423098626520285\n", - "proton+O=C=COC=[Pt]<=>O=C=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.9106920181466426e-48\n", - "Kc = 8.589022763019266e57\n", - "proton+CCOO[Pt]<=>OX+CCO\n", - "kf = 169.16425212622386\n", - "krev = 5.6416707126946964e-58\n", - "Kc = 2.9984779463568512e59\n", - "vacantX+vacantX+CCOO<=>HX+CCOO[Pt]\n", - "kf = 1.893449523720139e-21\n", - "krev = 0.6694879211592951\n", - "Kc = 2.8282056537202555e-21\n", - "O=O+CC[Pt]<=>CCOO[Pt]\n", - "kf = 4.5276782379965965e-7\n", - "krev = 1.4949208469184493e-38\n", - "Kc = 3.0287076719344122e31\n", - "vacantX+vacantX+C=CC(=O)O<=>CH2X+O=C(O)C=[Pt]\n", - "kf = 4.72289540105198e-39\n", - "krev = 9.498795808374404e14\n", - "Kc = 4.9720990916429044e-54\n", - "vacantX+vacantX+C=CC(=O)O<=>CO2HX+C=C[Pt]\n", - "kf = 5.354197885861111e7\n", - "krev = 1.376967106369583e14\n", - "Kc = 3.888399266107105e-7\n", - "vacantX+vacantX+C=CC(=O)O<=>HOX+C=CC(=O)[Pt]\n", - "kf = 0.03947248649742643\n", - "krev = 2.5171232142616846e11\n", - "Kc = 1.5681586929785789e-13\n", - "vacantX+vacantX+C=CC(=O)O<=>HX+C=CC(=O)O[Pt]\n", - "kf = 2.4490000178339845e-20\n", - "krev = 458.0011375503109\n", - "Kc = 5.3471483300955e-23\n", - "proton+O=C=C=CO.[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.4322611471299928e-17\n", - "Kc = 1.7454917387164855e27\n", - "proton+O=C=C=CO.[Pt]<=>O=C=C([Pt])CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 7.140416160377535e-6\n", - "Kc = 3.5011964903006675e15\n", - "vacantX+O=C=C=CO<=>O=C=C=CO.[Pt]\n", - "kf = 327433.4917974331\n", - "krev = 0.4460204906723957\n", - "Kc = 734122.0832787583\n", - "HX+O=C=C=C=O<=>O=C=C=C(O)[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 1.3048903398306852e-5\n", - "Kc = 0.004032923533638046\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C=C(O)[Pt]\n", - "kf = 4235.342411204313\n", - "krev = 12.909334546967292\n", - "Kc = 328.0837130523738\n", - "proton+O=C=C=C(O)[Pt]<=>O=C=CC(O)=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1053.6449933824201\n", - "Kc = 2.3727156828928486e7\n", - "vacantX+vacantX+O=C=C=CO<=>HX+O=C=C=C(O)[Pt]\n", - "kf = 8.233814429551885e-18\n", - "krev = 0.5740049812746953\n", - "Kc = 1.434449995759099e-17\n", - "proton+O=C=C=C(O)[Pt]<=>O=C=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.249904355928212e-21\n", - "Kc = 3.4483213533096645e30\n", - "vacantX+vacantX+CC=CO<=>OC=[Pt]+CC=[Pt]\n", - "kf = 1.6816353348966163e-33\n", - "krev = 8.021148128032321e14\n", - "Kc = 2.0965020319468163e-48\n", - "proton+O=C=C=C[Pt]<=>O=C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.0269882986128818\n", - "Kc = 9.263273820479827e11\n", - "vacantX+vacantX+C=C=C=O<=>HX+O=C=C=C[Pt]\n", - "kf = 3.6772489817592154e-10\n", - "krev = 0.00723599763490509\n", - "Kc = 5.081882509221477e-8\n", - "vacantX+vacantX+O=C=C=CO<=>HOX+O=C=C=C[Pt]\n", - "kf = 0.00020826365169953766\n", - "krev = 1.0739954827079557e13\n", - "Kc = 1.939148302322696e-17\n", - "vacantX+OC=CO<=>OC=CO.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.48171019889246675\n", - "Kc = 734122.0861712244\n", - "vacantX+vacantX+C=CC<=>CH2X+CC=[Pt]\n", - "kf = 3.8695500910369183e-44\n", - "krev = 2.1644248520711738e17\n", - "Kc = 1.787795999169979e-61\n", - "vacantX+vacantX+C=CC<=>CH3X+C=C[Pt]\n", - "kf = 1.1726078415532691e-17\n", - "krev = 1.59532697721828e15\n", - "Kc = 7.350266486422159e-33\n", - "HX+O=C=CO<=>OC=C(O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 2.762063581333058e-24\n", - "Kc = 1.0314187634521844e16\n", - "vacantX+vacantX+OC=CO<=>HX+OC=C(O)[Pt]\n", - "kf = 6.089904416870865e-20\n", - "krev = 3.928023437111271\n", - "Kc = 1.550373747604081e-20\n", - "proton+O=C=CO.[Pt]<=>OC=C(O)[Pt]\n", - "kf = 6.4368819183992445e7\n", - "krev = 6.799608634080986e-11\n", - "Kc = 9.466547657075904e17\n", - "proton+OC=C(O)[Pt]<=>H2O+OC=C=[Pt]\n", - "kf = 5.262467142275111e-7\n", - "krev = 0.6251329939834178\n", - "Kc = 8.418156125054411e-7\n", - "proton+OC=C(O)[Pt]<=>OC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.835798651062412e-24\n", - "Kc = 3.190485247679302e33\n", - "vacantX+vacantX+OC=CO<=>HOX+OC=C[Pt]\n", - "kf = 1.882970379851619e-8\n", - "krev = 6.2613640604613945e13\n", - "Kc = 3.0072846134950095e-22\n", - "vacantX+vacantX+C=CO<=>HX+OC=C[Pt]\n", - "kf = 5.986889507133711e-22\n", - "krev = 1492.047811549125\n", - "Kc = 4.0125319448830507e-25\n", - "proton+OC=C[Pt]<=>OCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.693803965028289e7\n", - "Kc = 1475.967733939179\n", - "vacantX+vacantX+O=CC=CO<=>CHOX+OC=C[Pt]\n", - "kf = 3.6404040231768274e-5\n", - "krev = 5.1339082800935775e14\n", - "Kc = 7.090901949480236e-20\n", - "proton+OC=C=[Pt]<=>OC=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.9001266800545872e-45\n", - "Kc = 1.3157017509633512e55\n", - "vacantX+vacantX+OC=CCO<=>OC[Pt]+OC=C[Pt]\n", - "kf = 1.39754480380523e-13\n", - "krev = 4.435737343310229e14\n", - "Kc = 3.1506482364492156e-28\n", - "vacantX+vacantX+CC=CO<=>CH3X+OC=C[Pt]\n", - "kf = 3.0518560755450534e-15\n", - "krev = 1.440283576497463e15\n", - "Kc = 2.1189272205454667e-30\n", - "vacantX+vacantX+CC=C(O)O<=>OC(O)=[Pt]+CC=[Pt]\n", - "kf = 3.314404876424973e-50\n", - "krev = 3.298291971460818e17\n", - "Kc = 1.0048852269912959e-67\n", - "HX+O=C=CO<=>OC=CO[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 5.830973747204281e-42\n", - "Kc = 4.885709192226705e33\n", - "vacantX+vacantX+OC=CO<=>HX+OC=CO[Pt]\n", - "kf = 6.3392542923960805e-6\n", - "krev = 0.0008631955285686626\n", - "Kc = 0.007343937824733329\n", - "proton+O=C=CO.[Pt]<=>OC=CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.575140256117379e-26\n", - "Kc = 4.4841921192150256e35\n", - "proton+OC=CO[Pt]<=>OX+C=CO\n", - "kf = 2.262727495050209e-8\n", - "krev = 2.5678564004292932e-5\n", - "Kc = 0.0008811736881672694\n", - "proton+OC=CO[Pt]<=>OC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.711725523568878e-6\n", - "Kc = 6.73541182968781e15\n", - "proton+OC=COC#[Pt]<=>CX+OC=CO\n", - "kf = 2.2492341197526439e-29\n", - "krev = 0.00020529518482061674\n", - "Kc = 1.0956097785332785e-25\n", - "vacantX+vacantX+CCC(=O)O<=>CH3X+O=C(O)C[Pt]\n", - "kf = 8.997747599742267e-17\n", - "krev = 6.572577910715489e15\n", - "Kc = 1.368983026442782e-32\n", - "vacantX+vacantX+CCC(=O)O<=>CO2HX+CC[Pt]\n", - "kf = 3.388822996448631e-6\n", - "krev = 1.0293603282987281e15\n", - "Kc = 3.292163981148853e-21\n", - "vacantX+vacantX+CCC(=O)O<=>HOX+CCC(=O)[Pt]\n", - "kf = 2.1491486919570496e-14\n", - "krev = 4.131728096070369e12\n", - "Kc = 5.201573390081201e-27\n", - "vacantX+vacantX+CCC(=O)O<=>HX+CCC(=O)O[Pt]\n", - "kf = 2.415446383235281e-20\n", - "krev = 451.7273406124814\n", - "Kc = 5.347133472063615e-23\n", - "proton+O=C([Pt])C=CO<=>OCX+C=CO\n", - "kf = 224.18396606543615\n", - "krev = 8.215700647740584e-7\n", - "Kc = 2.728726078001508e8\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=C([Pt])C=CO\n", - "kf = 2.859565189776071e-11\n", - "krev = 0.000933578065584948\n", - "Kc = 3.06301668300697e-8\n", - "HX+O=C=C=CO<=>O=C([Pt])C=CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.1750295723598082e-43\n", - "Kc = 2.206855353748942e35\n", - "proton+O=C=C=CO.[Pt]<=>O=C([Pt])C=CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.234268290529092e-27\n", - "Kc = 2.0254915557527025e37\n", - "proton+OC=C(O)C#[Pt]<=>CX+OC=CO\n", - "kf = 2.8680661830740045e-24\n", - "krev = 729.307267106125\n", - "Kc = 3.932589612680575e-27\n", - "vacantX+vacantX+C=COO<=>OO[Pt]+C=C[Pt]\n", - "kf = 0.00256837059370255\n", - "krev = 1.2695573429161084e13\n", - "Kc = 2.0230441799526235e-16\n", - "vacantX+vacantX+C=COO<=>HOX+C=CO[Pt]\n", - "kf = 3.07907263663438e8\n", - "krev = 5.547742278067932e-15\n", - "Kc = 5.5501364019864025e22\n", - "vacantX+vacantX+C=COO<=>CH2X+OOC=[Pt]\n", - "kf = 7.483948884590266e-53\n", - "krev = 2.8103204909201245e17\n", - "Kc = 2.6630232775123643e-70\n", - "proton+OC=CC#[Pt]<=>CX+C=CO\n", - "kf = 1.0593841984272302e-19\n", - "krev = 13.369077699035607\n", - "Kc = 7.924138241066921e-21\n", - "proton+OCC[Pt]<=>CH2X+CO-2\n", - "kf = 3.9799160772985795e-6\n", - "krev = 0.00035437522440524626\n", - "Kc = 0.011230796633647675\n", - "vacantX+vacantX+OCCO<=>HOX+OCC[Pt]\n", - "kf = 2.110093084979835e-12\n", - "krev = 2.4085316622580622e14\n", - "Kc = 8.760910716040024e-27\n", - "HX+C=CO<=>OCC[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 1.1429411507382647e-15\n", - "Kc = 2.8609207088741057e7\n", - "HOX+C=C<=>OCC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 2.2750559854988554e-15\n", - "Kc = 3.602118089238167e7\n", - "proton+OCC=[Pt]<=>OCC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.1399343496076094e-34\n", - "Kc = 2.1931087530264836e44\n", - "vacantX+vacantX+CCO<=>HX+OCC[Pt]\n", - "kf = 4.51610258482867e-23\n", - "krev = 15472.547765874588\n", - "Kc = 2.918784063985339e-27\n", - "vacantX+vacantX+O=CCCO<=>CHOX+OCC[Pt]\n", - "kf = 2.0496526220764064\n", - "krev = 1.4633869198921762e15\n", - "Kc = 1.4006224835106677e-15\n", - "HX+C#C<=>C=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 2.375601900047824e-24\n", - "Kc = 3.580716650609497e16\n", - "CHOX+C#C<=>O=CC=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 3.2359557228060194e-16\n", - "Kc = 2.6287001452988416e8\n", - "HOX+C#C<=>OC=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 2.419253665005007e-25\n", - "Kc = 3.516108046777805e17\n", - "proton+OCCC#[Pt]<=>CX+CCO\n", - "kf = 0.036583470766554806\n", - "krev = 0.0005754138836916786\n", - "Kc = 63.577664361948486\n", - "OC[Pt]+C=C=O<=>O=C([Pt])CCO\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.869121889511259e-30\n", - "Kc = 1.7908695590280368e22\n", - "HX+O=C=CCO<=>O=C([Pt])CCO\n", - "kf = 2.5565910629172877e-8\n", - "krev = 3.7973012083800085e-37\n", - "Kc = 6.732652804247709e28\n", - "proton+O=C=CCO.[Pt]<=>O=C([Pt])CCO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.5089082544191712e-24\n", - "Kc = 1.6568270421201532e34\n", - "proton+O=C([Pt])CCO<=>OCX+CCO\n", - "kf = 9.600816617542319e7\n", - "krev = 3.185535798116408e-7\n", - "Kc = 3.0138781121904944e14\n", - "vacantX+vacantX+O=CCCO<=>HX+O=C([Pt])CCO\n", - "kf = 4.786286134347495e-11\n", - "krev = 0.0006355926831038164\n", - "Kc = 7.530429883135883e-8\n", - "vacantX+vacantX+C=COC<=>CO[Pt]+C=C[Pt]\n", - "kf = 1.9108708710628152e-14\n", - "krev = 5.750545812867103e12\n", - "Kc = 3.322938262290088e-27\n", - "vacantX+vacantX+C=COC<=>CH3X+C=CO[Pt]\n", - "kf = 8.809048609670953e-10\n", - "krev = 5.30334818480063e15\n", - "Kc = 1.6610353125441853e-25\n", - "vacantX+vacantX+C=COC<=>CH2X+COC=[Pt]\n", - "kf = 2.00333233616492e-67\n", - "krev = 2.0086736136424638e14\n", - "Kc = 9.973408932933319e-82\n", - "C=O+OC[Pt]<=>OCCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.726586049973397e-6\n", - "Kc = 0.00837955829095468\n", - "HX+O=CCO<=>OCCO[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 7.096612291679358e-6\n", - "Kc = 0.003946413774492056\n", - "vacantX+vacantX+OCCO<=>HX+OCCO[Pt]\n", - "kf = 1.0265256602604584e-26\n", - "krev = 112849.3186381155\n", - "Kc = 9.09642763154215e-32\n", - "proton+O=CCO.[Pt]<=>OCCO[Pt]\n", - "kf = 3.478307222117794e6\n", - "krev = 3581.5775849412535\n", - "Kc = 971.1662360023528\n", - "proton+OCCO[Pt]<=>OX+CCO\n", - "kf = 951266.6788585404\n", - "krev = 3.3388075163598663e-18\n", - "Kc = 2.8491210535420697e23\n", - "proton+OCCOC#[Pt]<=>CX+OCCO\n", - "kf = 6.336022152476698e-22\n", - "krev = 5.125095889500872e-13\n", - "Kc = 1.2362738744959868e-9\n", - "vacantX+vacantX+C=CC(O)O<=>OC(O)[Pt]+C=C[Pt]\n", - "kf = 1.3588265576828814e-16\n", - "krev = 6.093754170226661e16\n", - "Kc = 2.2298676968656565e-33\n", - "proton+O=C=C=C=[Pt]<=>O=C=CC#[Pt]\n", - "kf = 8.597534639917141e-9\n", - "krev = 2.1202950562509243e-60\n", - "Kc = 4.0548765204023916e51\n", - "vacantX+vacantX+O=C=C=C=O<=>OX+O=C=C=C=[Pt]\n", - "kf = 6.451439297868635e-57\n", - "krev = 8.482832416110645e14\n", - "Kc = 7.60528910793525e-72\n", - "proton+O=C=C=C(O)[Pt]<=>H2O+O=C=C=C=[Pt]\n", - "kf = 1.6149902683641734e-11\n", - "krev = 0.12950076972214764\n", - "Kc = 1.2470893198775887e-10\n", - "proton+O=C=C=C=[Pt]<=>O=C=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.039016761990757e-51\n", - "Kc = 6.189625216528679e60\n", - "vacantX+C=CO<=>C=CO.[Pt]\n", - "kf = 412885.969273148\n", - "krev = 1.1342794009872417\n", - "Kc = 364007.288604364\n", - "proton+C=CO[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.484544240591893e-27\n", - "Kc = 5.574702502366298e36\n", - "proton+OC=C[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.090002516938126e-28\n", - "Kc = 6.112465676112982e37\n", - "proton+C=CO.[Pt]<=>OCC[Pt]\n", - "kf = 1.7684909297990441e9\n", - "krev = 0.3339506079512917\n", - "Kc = 5.295666148501179e9\n", - "vacantX+vacantX+C=COCO<=>OCO[Pt]+C=C[Pt]\n", - "kf = 1.4197397308458187e-12\n", - "krev = 3.0290185667479297e13\n", - "Kc = 4.6871278586123213e-26\n", - "vacantX+vacantX+C=COCO<=>OC[Pt]+C=CO[Pt]\n", - "kf = 1.0263854075463885e-7\n", - "krev = 1.9545487277553856e14\n", - "Kc = 5.251265384031101e-22\n", - "HX+C=C=O<=>C=C(O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 3.2362559658776053e-12\n", - "Kc = 10343.290300064218\n", - "proton+C=C=O.[Pt]<=>C=C(O)[Pt]\n", - "kf = 0.5863133386822127\n", - "krev = 3624.832599039063\n", - "Kc = 0.00016174908017480404\n", - "vacantX+vacantX+C=CO<=>HX+C=C(O)[Pt]\n", - "kf = 4.00965787691315e-19\n", - "krev = 4.055766485027893\n", - "Kc = 9.886313454472895e-20\n", - "vacantX+vacantX+C=C(O)O<=>HOX+C=C(O)[Pt]\n", - "kf = 3.9452234947489745e-7\n", - "krev = 1.361002505571871e12\n", - "Kc = 2.8987628447394044e-19\n", - "proton+C=C(O)[Pt]<=>H2O+C=C=[Pt]\n", - "kf = 0.1408093188614318\n", - "krev = 0.006096548509334685\n", - "Kc = 23.09656334987455\n", - "proton+C=C(O)[Pt]<=>CC(O)=[Pt]\n", - "kf = 1.124057689749841e8\n", - "krev = 4.718570974473911e-12\n", - "Kc = 2.382199390092179e19\n", - "vacantX+vacantX+C=C(O)C=O<=>CHOX+C=C(O)[Pt]\n", - "kf = 2.8052009086647103\n", - "krev = 2.294429327232502e13\n", - "Kc = 1.2226137782366527e-13\n", - "proton+C=C(O)[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0077190030498644e-22\n", - "Kc = 2.4808503088993487e32\n", - "HOX+C=C=O<=>C=C(O)O[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.6625343699967689e-31\n", - "Kc = 2.0134040862236038e23\n", - "proton+C=C(O)O[Pt]<=>OX+C=CO\n", - "kf = 7.621772041144703e-10\n", - "krev = 0.16987445654378072\n", - "Kc = 4.4867087119601115e-9\n", - "vacantX+vacantX+C=C(O)O<=>HX+C=C(O)O[Pt]\n", - "kf = 8.7276566297004e-6\n", - "krev = 1.546723677424112e-6\n", - "Kc = 5.6426734503963205\n", - "vacantX+vacantX+C=CCOO<=>OOC[Pt]+C=C[Pt]\n", - "kf = 2.5331825038162864e-12\n", - "krev = 1.769892843246248e17\n", - "Kc = 1.4312632052740838e-29\n", - "proton+C=C(O)OC#[Pt]<=>CX+C=C(O)O\n", - "kf = 1.0744261387122509e-22\n", - "krev = 181.85749301564874\n", - "Kc = 5.908066370516815e-25\n", - "proton+C=C(O)C#[Pt]<=>CX+C=CO\n", - "kf = 3.691417083839596e-20\n", - "krev = 61.67110810051338\n", - "Kc = 5.985650651555046e-22\n", - "vacantX+vacantX+C=COOC<=>COO[Pt]+C=C[Pt]\n", - "kf = 0.0009962735751002543\n", - "krev = 4.495422962203487e13\n", - "Kc = 2.21619541359445e-17\n", - "vacantX+vacantX+C=COOC<=>CO[Pt]+C=CO[Pt]\n", - "kf = 2.772273774659678e8\n", - "krev = 3.7705323383409334e-17\n", - "Kc = 7.352473141443741e24\n", - "proton+C=C(O)C(=O)[Pt]<=>OCX+C=CO\n", - "kf = 985.1540455146012\n", - "krev = 5.159085449148215e-7\n", - "Kc = 1.9095517126533618e9\n", - "HOX+C=C=C=O<=>C=C(O)C(=O)[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 3.5720015577500406e-52\n", - "Kc = 8.264488540948707e43\n", - "vacantX+vacantX+C=C(O)C=O<=>HX+C=C(O)C(=O)[Pt]\n", - "kf = 2.8595651897765786e-11\n", - "krev = 0.000933577098423846\n", - "Kc = 3.063019856211522e-8\n", - "proton+C=COO[Pt]<=>OX+C=CO\n", - "kf = 43.93537738533433\n", - "krev = 6.669135249611683e-61\n", - "Kc = 6.587867203306832e61\n", - "O=O+C=C[Pt]<=>C=COO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 1.0833501613715598e-32\n", - "Kc = 7.082998693235901e24\n", - "vacantX+vacantX+C=COO<=>HX+C=COO[Pt]\n", - "kf = 4.552726448583842e-23\n", - "krev = 27.53540659037694\n", - "Kc = 1.6534081069915729e-24\n", - "vacantX+vacantX+C=COOC<=>CH3X+C=COO[Pt]\n", - "kf = 2.287071149777874e-9\n", - "krev = 2.2490557638427473e13\n", - "Kc = 1.0169028205286352e-22\n", - "vacantX+vacantX+CC(O)=CO<=>OC=[Pt]+CC(O)=[Pt]\n", - "kf = 7.128045206079291e-31\n", - "krev = 1.6024698052635947e11\n", - "Kc = 4.4481619451835966e-42\n", - "vacantX+vacantX+CC(O)=CO<=>CH3X+OC=C(O)[Pt]\n", - "kf = 1.2021042471738558e-26\n", - "krev = 3.79937896614338e12\n", - "Kc = 3.163949313521812e-39\n", - "proton+O=CC=C=[Pt]<=>O=CCC#[Pt]\n", - "kf = 62.9877146015209\n", - "krev = 8.316144406521062e-31\n", - "Kc = 7.574148730766316e31\n", - "vacantX+vacantX+O=C=CC=O<=>OX+O=CC=C=[Pt]\n", - "kf = 1.1758489216219413e-43\n", - "krev = 2.1453863988577092e16\n", - "Kc = 5.480825842132732e-60\n", - "proton+O=CC=C=[Pt]<=>O=CC=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.331702565774384e-47\n", - "Kc = 2.6790395240083815e56\n", - "proton+C=C=C=O.[Pt]<=>O=C=CC[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.2229421483387703e-16\n", - "Kc = 1.1246356554390213e26\n", - "vacantX+C=C=C=O<=>C=C=C=O.[Pt]\n", - "kf = 372758.92921022984\n", - "krev = 0.5077615475124772\n", - "Kc = 734122.012658058\n", - "proton+C=C=C=O.[Pt]<=>CC([Pt])=C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.123273247571115e-16\n", - "Kc = 1.1774273531962195e26\n", - "proton+C=C=C=O.[Pt]<=>C=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.171161147913428e-32\n", - "Kc = 4.834504144216726e41\n", - "proton+O=C=C=C[Pt]<=>C=C=C=O.[Pt]\n", - "kf = 3.820491632517615e9\n", - "krev = 3.925100397444825e-12\n", - "Kc = 9.733487670798667e20\n", - "vacantX+vacantX+C=C(C)O<=>CH2X+CC(O)=[Pt]\n", - "kf = 1.2526307828427685e-31\n", - "krev = 1.8291181793687947e14\n", - "Kc = 6.848276929132241e-46\n", - "vacantX+vacantX+C=C(C)O<=>CH3X+C=C(O)[Pt]\n", - "kf = 6.412809230790006e-14\n", - "krev = 6.896161957802356e13\n", - "Kc = 9.299098933624258e-28\n", - "HX+O=C=C=C=O<=>O=C=C=CO[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 6.474039280394542e-15\n", - "Kc = 8.128654665807662e6\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C=CO[Pt]\n", - "kf = 2.4048564698523636e10\n", - "krev = 0.03636685994081414\n", - "Kc = 6.612769080877996e11\n", - "proton+O=C=C=CO[Pt]<=>OX+C=C=C=O\n", - "kf = 7.675790818902377e-14\n", - "krev = 0.0006735755949001122\n", - "Kc = 1.1395589265731426e-10\n", - "vacantX+vacantX+O=C=C=CO<=>HX+O=C=C=CO[Pt]\n", - "kf = 4.194899212644372e-10\n", - "krev = 0.014508998351933198\n", - "Kc = 2.891239705796395e-8\n", - "proton+O=C=C=CO[Pt]<=>O=C=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4612716650323904e-11\n", - "Kc = 1.71083862078759e21\n", - "proton+CC(O)[Pt]<=>OC=[Pt]+CH4\n", - "kf = 59.397807135376084\n", - "krev = 1.2803453253139382e-6\n", - "Kc = 4.639202093451769e7\n", - "HX+C=CO<=>CC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 1.2254518112062234e-21\n", - "Kc = 2.668292606261641e13\n", - "HX+CC=O<=>CC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 2.4645381117653586e-12\n", - "Kc = 13267.654460532101\n", - "vacantX+vacantX+CCO<=>HX+CC(O)[Pt]\n", - "kf = 1.7361137032745595e-19\n", - "krev = 63.774720976875884\n", - "Kc = 2.72225997492652e-21\n", - "vacantX+vacantX+CC(O)O<=>HOX+CC(O)[Pt]\n", - "kf = 7.380915652046712e-14\n", - "krev = 2.775462823415347e13\n", - "Kc = 2.6593458899096773e-27\n", - "proton+CC=O.[Pt]<=>CC(O)[Pt]\n", - "kf = 36132.65188770086\n", - "krev = 0.006356177292382113\n", - "Kc = 5.68465135971048e6\n", - "proton+CC(O)[Pt]<=>H2O+CC=[Pt]\n", - "kf = 2964.0563969386994\n", - "krev = 0.019559355499681682\n", - "Kc = 151541.61889367664\n", - "proton+CC(O)=[Pt]<=>CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.860369956892034e-19\n", - "Kc = 5.143641373338227e28\n", - "vacantX+vacantX+CC(O)C=O<=>CHOX+CC(O)[Pt]\n", - "kf = 753631.9525109725\n", - "krev = 9.011518944421836e14\n", - "Kc = 8.362984721654206e-10\n", - "proton+C=CO.[Pt]<=>CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.061646123775542e-6\n", - "Kc = 4.939104668453628e15\n", - "HX+C#CC=O<=>O=CC=C[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 1.9866745274914506e-30\n", - "Kc = 1.4859387148609413e22\n", - "proton+CC(O)C#[Pt]<=>CX+CCO\n", - "kf = 1.3617819786307934\n", - "krev = 4.084110860281074e-5\n", - "Kc = 33343.413663777814\n", - "O=CO+CH3X<=>CC(O)O[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 7.324156308451427e-7\n", - "Kc = 0.043678018970166745\n", - "HOX+CC=O<=>CC(O)O[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 7.587328136505701e-13\n", - "Kc = 43096.38318446866\n", - "HX+CC(=O)O<=>CC(O)O[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 4598.938099177113\n", - "Kc = 6.089703295881323e-12\n", - "proton+CC(O)O[Pt]<=>OX+CCO\n", - "kf = 1.6583777607664147e6\n", - "krev = 1.6983423991371652e-6\n", - "Kc = 9.764684445309413e11\n", - "vacantX+vacantX+CC(O)O<=>HX+CC(O)O[Pt]\n", - "kf = 4.052122584605618e-24\n", - "krev = 469.09529347560436\n", - "Kc = 8.638165082797514e-27\n", - "proton+CC(=O)O.[Pt]<=>CC(O)O[Pt]\n", - "kf = 0.7475019896975738\n", - "krev = 3555.8603422114556\n", - "Kc = 0.00021021691454639312\n", - "vacantX+vacantX+OC=C=CO<=>OC=[Pt]+OC=C=[Pt]\n", - "kf = 3.0449395213240036e-51\n", - "krev = 1.4315520101841116e12\n", - "Kc = 2.1270198355785863e-63\n", - "CH3X+O=C=CO<=>CC(O)C(=O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 4.477216581188038e-53\n", - "Kc = 6.362980552705156e44\n", - "proton+CC(O)C(=O)[Pt]<=>OCX+CCO\n", - "kf = 9.570476890072168e7\n", - "krev = 4.96015815008412e-7\n", - "Kc = 1.929470109720163e14\n", - "HOX+CC=C=O<=>CC(O)C(=O)[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 3.536759710167166e-36\n", - "Kc = 8.195394062368554e27\n", - "HX+CC(O)=C=O<=>CC(O)C(=O)[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 4.830700359768998e-42\n", - "Kc = 5.292381792522405e33\n", - "vacantX+vacantX+CC(O)C=O<=>HX+CC(O)C(=O)[Pt]\n", - "kf = 4.786286134353719e-11\n", - "krev = 0.0006355923790078162\n", - "Kc = 7.530433486042254e-8\n", - "proton+CC(O)=C=O.[Pt]<=>CC(O)C(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.368412782384192e-31\n", - "Kc = 1.8269341182594315e41\n", - "proton+CC(O)OC#[Pt]<=>CX+CC(O)O\n", - "kf = 2.7873525673015004e-16\n", - "krev = 1.8374709107747412e-8\n", - "Kc = 1.516950581887719e-8\n", - "vacantX+vacantX+CCOC<=>CO[Pt]+CC[Pt]\n", - "kf = 2.3627317133785774e-11\n", - "krev = 3.856091265609508e13\n", - "Kc = 6.127271246016828e-25\n", - "vacantX+vacantX+CCOC<=>CH3X+CCO[Pt]\n", - "kf = 6.326940367296449e-9\n", - "krev = 1.8372911814097844e13\n", - "Kc = 3.443624195943553e-22\n", - "vacantX+vacantX+CCOC<=>CH3X+COC[Pt]\n", - "kf = 1.3389399016858639e-14\n", - "krev = 2.773400746132106e14\n", - "Kc = 4.8277909478217395e-29\n", - "proton+O=C=C(O)C[Pt]<=>CH2X+O=C=CO\n", - "kf = 4.2042874371743854e-22\n", - "krev = 1.1101526849597185\n", - "Kc = 3.787125405481442e-22\n", - "HOX+C=C=C=O<=>O=C=C(O)C[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 6.322264310888409e-36\n", - "Kc = 4.669334354059592e27\n", - "vacantX+vacantX+CC(O)=C=O<=>HX+O=C=C(O)C[Pt]\n", - "kf = 6.004181315465852e-13\n", - "krev = 0.19478740167193392\n", - "Kc = 3.082427951669201e-12\n", - "proton+O=C=C(O)C[Pt]<=>CC(O)=C=O.[Pt]\n", - "kf = 1.859235052213257e9\n", - "krev = 4.357618832801525e-11\n", - "Kc = 4.266630753057283e19\n", - "proton+O=C=C(O)C=[Pt]<=>CHX+O=C=CO\n", - "kf = 1.807627844430322e-6\n", - "krev = 0.0010238577171457239\n", - "Kc = 0.0017655068806528764\n", - "proton+O=C=C(O)C#[Pt]<=>O=C=C(O)C=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.347883511420028\n", - "Kc = 7.467404380923659e9\n", - "proton+O=C=C(O)C=[Pt]<=>O=C=C(O)C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4404183806094484e-33\n", - "Kc = 1.735606844271341e43\n", - "vacantX+vacantX+CCCO<=>OC[Pt]+CC[Pt]\n", - "kf = 4.648157058598011e-13\n", - "krev = 1.3999921584371802e15\n", - "Kc = 3.3201307811515004e-28\n", - "vacantX+vacantX+CCCO<=>CH3X+OCC[Pt]\n", - "kf = 1.2211065235504926e-16\n", - "krev = 1.2627143633797795e15\n", - "Kc = 9.670488900451568e-32\n", - "proton+CC([Pt])OC=O<=>CH4+O=COC=[Pt]\n", - "kf = 1.0679856406424377e-15\n", - "krev = 0.2905260385078575\n", - "Kc = 3.6760410396521245e-15\n", - "CHOX+CC=O<=>CC([Pt])OC=O\n", - "kf = 3.269864007171502e-8\n", - "krev = 0.48922244404245907\n", - "Kc = 6.68379802887317e-8\n", - "HX+C=COC=O<=>CC([Pt])OC=O\n", - "kf = 2.5565910629172877e-8\n", - "krev = 1.2259112200812889e-16\n", - "Kc = 2.0854618352769157e8\n", - "vacantX+vacantX+CCOC=O<=>HX+CC([Pt])OC=O\n", - "kf = 6.519502059052115e-22\n", - "krev = 142.86665816232104\n", - "Kc = 4.563347489828482e-24\n", - "proton+CC([Pt])OC=O<=>O=CO+CC=[Pt]\n", - "kf = 8049.244255788158\n", - "krev = 0.00029431628636694825\n", - "Kc = 2.7348959703006394e7\n", - "proton+CC(=[Pt])OC=O<=>CH4+O=COC#[Pt]\n", - "kf = 4.771264023974434e9\n", - "krev = 10.578082715743388\n", - "Kc = 4.510518732164335e8\n", - "proton+CC(=[Pt])OC=O<=>O=CO+CC#[Pt]\n", - "kf = 7292.02651577905\n", - "krev = 8.53932827082491e-43\n", - "Kc = 8.539344412712957e45\n", - "proton+CC(=[Pt])OC=O<=>CC([Pt])OC=O\n", - "kf = 2.5e10\n", - "krev = 2.5945295399651927e-47\n", - "Kc = 9.635658262860014e56\n", - "vacantX+vacantX+CCC(O)O<=>OC(O)[Pt]+CC[Pt]\n", - "kf = 3.712816041087776e-19\n", - "krev = 9.367983662004229e16\n", - "Kc = 3.9633032838716965e-36\n", - "vacantX+O=CC=CO<=>O=CC=CO.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 0.8868529608572997\n", - "Kc = 364007.2889878057\n", - "proton+O=CC=CO[Pt]<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.467206835324098e-11\n", - "Kc = 1.703917907012588e21\n", - "proton+O=C([Pt])C=CO<=>O=CC=CO.[Pt]\n", - "kf = 3.672999120067293e9\n", - "krev = 4.587068754429701e-12\n", - "Kc = 8.00729031262133e20\n", - "HX+O=C=CC=O<=>O=CC=C(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.0473065138531246e-21\n", - "Kc = 2.475989854235963e13\n", - "proton+O=C=CC=O.[Pt]<=>O=CC=C(O)[Pt]\n", - "kf = 9.946079261837086e6\n", - "krev = 6.687641252513296e-9\n", - "Kc = 1.4872327755468685e15\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC=C(O)[Pt]\n", - "kf = 2.77963678004065e-20\n", - "krev = 3.601218827022036\n", - "Kc = 7.718600045027592e-21\n", - "proton+O=CC=C(O)[Pt]<=>H2O+O=CC=C=[Pt]\n", - "kf = 2.367383825493301e-13\n", - "krev = 16.1722227709439\n", - "Kc = 1.463858035487058e-14\n", - "proton+O=CC=C(O)[Pt]<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.867624236214861e-24\n", - "Kc = 3.177579311035777e33\n", - "vacantX+vacantX+CCOCO<=>OCO[Pt]+CC[Pt]\n", - "kf = 2.4512530384253315e-9\n", - "krev = 3.614837695546209e14\n", - "Kc = 6.781087409389048e-24\n", - "vacantX+vacantX+CCOCO<=>OC[Pt]+CCO[Pt]\n", - "kf = 1.0293700832173347e-6\n", - "krev = 1.2050997101819434e12\n", - "Kc = 8.541783509863451e-19\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC([Pt])=CO\n", - "kf = 4.3007284274917255e-15\n", - "krev = 1.9561961334382385\n", - "Kc = 2.1985159636997663e-15\n", - "HX+O=C=C=CO<=>O=CC([Pt])=CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.6370748462102965e-36\n", - "Kc = 1.5839961798805036e28\n", - "proton+O=CC([Pt])=CO<=>C=O+OC=C=[Pt]\n", - "kf = 4.3296354594819855e-33\n", - "krev = 908.9754469679581\n", - "Kc = 4.76320397203711e-36\n", - "proton+O=C=C=CO.[Pt]<=>O=CC([Pt])=CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.7196074204687593e-20\n", - "Kc = 1.4538201977044896e30\n", - "HOX+C#CC=O<=>O=CC([Pt])=CO\n", - "kf = 2.952076594227614e-8\n", - "krev = 4.790462195255654e-44\n", - "Kc = 6.162404531970363e35\n", - "proton+O=CC([Pt])=CO<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.2409630475480663e-18\n", - "Kc = 1.1155918000233681e28\n", - "proton+OC=CC=[Pt]<=>CHX+C=CO\n", - "kf = 0.3708119772368373\n", - "krev = 1.9743851754031655e-5\n", - "Kc = 18781.136621992628\n", - "vacantX+vacantX+O=CC=CO<=>OX+OC=CC=[Pt]\n", - "kf = 8.803023976547135e-28\n", - "krev = 1.526615583505237e17\n", - "Kc = 5.766365856383213e-45\n", - "proton+OC=CC#[Pt]<=>OC=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4263979915391943e-8\n", - "Kc = 1.7526665172195773e18\n", - "vacantX+vacantX+CCCOO<=>OOC[Pt]+CC[Pt]\n", - "kf = 5.56726706794292e-16\n", - "krev = 4.282042054393877e17\n", - "Kc = 1.3001430152303739e-33\n", - "proton+OCC(O)[Pt]<=>OC=[Pt]+CO-2\n", - "kf = 0.16339719354915763\n", - "krev = 6.17359485423602e-8\n", - "Kc = 2.6467106670766133e6\n", - "HX+O=CCO<=>OCC(O)[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 4.347223516290618e-14\n", - "Kc = 644231.1603064304\n", - "vacantX+vacantX+OCCO<=>HX+OCC(O)[Pt]\n", - "kf = 7.314142036323851e-21\n", - "krev = 492.5535033039904\n", - "Kc = 1.4849436634317805e-23\n", - "HX+OC=CO<=>OCC(O)[Pt]\n", - "kf = 5.6012337000223925e-8\n", - "krev = 1.5412075197181771e-21\n", - "Kc = 3.634315060340885e13\n", - "HOX+C=CO<=>OCC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 6.743155058263278e-19\n", - "Kc = 4.8491603395127426e10\n", - "proton+O=CCO.[Pt]<=>OCC(O)[Pt]\n", - "kf = 698182.0065765544\n", - "krev = 4.403884986144656e-6\n", - "Kc = 1.5853774764171848e11\n", - "proton+OCC(O)[Pt]<=>H2O+OCC=[Pt]\n", - "kf = 0.7285659975205578\n", - "krev = 0.0004743003964980969\n", - "Kc = 1536.0855755124403\n", - "proton+OC=CO.[Pt]<=>OCC(O)[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 1.4989628309182922e-5\n", - "Kc = 3.3356397482764175e15\n", - "proton+OCC(O)C#[Pt]<=>CX+OCCO\n", - "kf = 5.26000051169577\n", - "krev = 0.00019971123776726528\n", - "Kc = 26338.02969978857\n", - "vacantX+vacantX+CCC<=>CH3X+CC[Pt]\n", - "kf = 7.798842461270165e-20\n", - "krev = 4.754727023110295e15\n", - "Kc = 1.640229275700578e-35\n", - "proton+O=C([Pt])CO<=>OCC(O)=[Pt]\n", - "kf = 4.019918430047713e-18\n", - "krev = 1.0085447542339827e12\n", - "Kc = 3.9858602339377106e-30\n", - "proton+OCC(O)=[Pt]<=>H2O+OCC#[Pt]\n", - "kf = 16209.61875952926\n", - "krev = 4.634124941714537e-41\n", - "Kc = 3.4978812533984058e44\n", - "proton+OCC(O)=[Pt]<=>OC#[Pt]+CO-2\n", - "kf = 382.95023851607715\n", - "krev = 3.536410198453644e-35\n", - "Kc = 1.0828784474253827e37\n", - "proton+OC=C(O)[Pt]<=>OCC(O)=[Pt]\n", - "kf = 6875.768524790738\n", - "krev = 1.0085447542339824e12\n", - "Kc = 6.8175145385720384e-9\n", - "proton+OCC(O)=[Pt]<=>OCC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.6015120113778689e-47\n", - "Kc = 1.5610248204439706e57\n", - "HX+COC=O<=>COC(O)[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 224.3395816271696\n", - "Kc = 1.2483828443014824e-10\n", - "proton+COC(O)[Pt]<=>OC=[Pt]+CO-2\n", - "kf = 564390.3708916149\n", - "krev = 3.282828318007529e-12\n", - "Kc = 1.7192198806002883e17\n", - "vacantX+vacantX+COCO<=>HX+COC(O)[Pt]\n", - "kf = 6.183244140051347e-23\n", - "krev = 2731.92216309053\n", - "Kc = 2.2633310068601865e-26\n", - "O=CO+CH3X<=>COC(O)[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 8.503469161971292e7\n", - "Kc = 3.7620485485108396e-16\n", - "proton+COC=O.[Pt]<=>COC(O)[Pt]\n", - "kf = 7.49969185016536e-5\n", - "krev = 3658.0165064396892\n", - "Kc = 2.0502072193940793e-8\n", - "proton+COC(O)[Pt]<=>H2O+COC=[Pt]\n", - "kf = 5.10646151413012e-10\n", - "krev = 0.003546985366877098\n", - "Kc = 1.439662413557134e-7\n", - "vacantX+vacantX+CCOOC<=>COO[Pt]+CC[Pt]\n", - "kf = 1.4778859852656565e-10\n", - "krev = 2.404289853338368e13\n", - "Kc = 6.146871115450596e-24\n", - "vacantX+vacantX+CCOOC<=>CO[Pt]+CCO[Pt]\n", - "kf = 2.735304068777078e8\n", - "krev = 1.1929824589169815e-11\n", - "Kc = 2.2928284052560617e19\n", - "vacantX+vacantX+CCOOC<=>CH3X+CCOO[Pt]\n", - "kf = 1.542530561493995e-10\n", - "krev = 1.2789927244807063e12\n", - "Kc = 1.2060510837700736e-22\n", - "proton+COC(O)C#[Pt]<=>CX+COCO\n", - "kf = 0.03928313633337953\n", - "krev = 0.002914319669063903\n", - "Kc = 13.479350515448948\n", - "proton+COC(=O)[Pt]<=>COC(O)=[Pt]\n", - "kf = 6.005930457604258e-17\n", - "krev = 1.0085447542339825e12\n", - "Kc = 5.955046052632466e-29\n", - "proton+COC(O)=[Pt]<=>OC#[Pt]+CO-2\n", - "kf = 383854.3090963643\n", - "krev = 3.448448528690976e-34\n", - "Kc = 1.113121758677009e39\n", - "proton+COC(O)=[Pt]<=>H2O+COC#[Pt]\n", - "kf = 217922.49486435574\n", - "krev = 2.0340320286285714e-35\n", - "Kc = 1.0713818258372662e40\n", - "proton+COC(O)=[Pt]<=>COC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0120272229346644e-38\n", - "Kc = 2.4702892801149458e48\n", - "vacantX+vacantX+C=C=COO<=>OOC=[Pt]+C=C=[Pt]\n", - "kf = 1.9145907695639512e-44\n", - "krev = 1.1771971588384226e12\n", - "Kc = 1.626397715275781e-56\n", - "C=O+O=CC[Pt]<=>O=CCCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 0.0025285011306884937\n", - "Kc = 1.5664103465194285e-5\n", - "HX+O=CCC=O<=>O=CCCO[Pt]\n", - "kf = 5.113182125834635e-8\n", - "krev = 3.03538509820146e-7\n", - "Kc = 0.16845250142607343\n", - "proton+O=CCC=O.[Pt]<=>O=CCCO[Pt]\n", - "kf = 2.3901708430508703e8\n", - "krev = 41.103568870106145\n", - "Kc = 5.814995896351951e6\n", - "vacantX+vacantX+O=CCCO<=>HX+O=CCCO[Pt]\n", - "kf = 2.5157725911236352e-27\n", - "krev = 8837.406478086354\n", - "Kc = 2.84673178421957e-31\n", - "proton+O=CCCO[Pt]<=>OX+CCC=O\n", - "kf = 774927.4661784222\n", - "krev = 1.1978583087682196e-18\n", - "Kc = 6.469274875884902e23\n", - "CHOX+C=C<=>O=CCC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 0.4688595936220698\n", - "Kc = 1.7478623517301195e-7\n", - "proton+O=CCC[Pt]<=>CH2X+CC=O\n", - "kf = 0.0016740956920828355\n", - "krev = 4.373185000711893e-7\n", - "Kc = 3828.0925499614495\n", - "HX+C=CC=O<=>O=CCC[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 7.666152073113618e-12\n", - "Kc = 3780.924152337611\n", - "proton+O=CCC=[Pt]<=>O=CCC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3932958912707058e-30\n", - "Kc = 1.794306590339518e40\n", - "vacantX+vacantX+O=CCCO<=>HOX+O=CCC[Pt]\n", - "kf = 8.901266563864654e-15\n", - "krev = 1.309728963703428e15\n", - "Kc = 6.79626610584771e-30\n", - "vacantX+vacantX+CCC=O<=>HX+O=CCC[Pt]\n", - "kf = 1.6716561102658422e-25\n", - "krev = 524619.2678123232\n", - "Kc = 3.186417680076247e-31\n", - "vacantX+vacantX+CC=COO<=>OOC=[Pt]+CC=[Pt]\n", - "kf = 3.7147962989308654e-50\n", - "krev = 4.0636001726377395e18\n", - "Kc = 9.141638303749602e-69\n", - "proton+C=COOC#[Pt]<=>CX+C=COO\n", - "kf = 8.811176921711816e-67\n", - "krev = 2.5e10\n", - "Kc = 3.5244707686847265e-77\n", - "vacantX+C=CC=O<=>C=CC=O.[Pt]\n", - "kf = 365995.57053717994\n", - "krev = 1.0054621985249468\n", - "Kc = 364007.290452202\n", - "proton+C=CC(=O)[Pt]<=>C=CC=O.[Pt]\n", - "kf = 3.399604827397095e9\n", - "krev = 5.959510760846119e-12\n", - "Kc = 5.704503211458966e20\n", - "proton+O=CC=C[Pt]<=>C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.32808736312024e-27\n", - "Kc = 3.00188973889839e36\n", - "proton+C=CC=O.[Pt]<=>O=CCC[Pt]\n", - "kf = 5.197601136262071e7\n", - "krev = 74.26603000820454\n", - "Kc = 699862.5260684955\n", - "vacantX+vacantX+C=CC=O<=>HX+C=C([Pt])C=O\n", - "kf = 1.2784478936507186e-21\n", - "krev = 132.59733776930153\n", - "Kc = 9.641580405445367e-24\n", - "proton+C=C([Pt])C=O<=>C=O+C=C=[Pt]\n", - "kf = 2.4079500300331376e-13\n", - "krev = 0.010970404022735962\n", - "Kc = 2.194951092997765e-11\n", - "HX+C=C=C=O<=>C=C([Pt])C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.4992009477647154e-32\n", - "Kc = 1.1812081765045545e24\n", - "vacantX+vacantX+C=C(O)C=O<=>HOX+C=C([Pt])C=O\n", - "kf = 1.107119853181277e-14\n", - "krev = 2.5289157654010746e13\n", - "Kc = 4.377843929513773e-28\n", - "proton+C=C=C=O.[Pt]<=>C=C([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.305987527913534e-16\n", - "Kc = 1.0841342243780513e26\n", - "HX+C#CC=O<=>C=C([Pt])C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 1.683521621093348e-30\n", - "Kc = 1.753512730243651e22\n", - "proton+C=C([Pt])C=O<=>C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.827731832923639e-27\n", - "Kc = 2.5438219545478565e36\n", - "CHOX+C=C=O<=>C=C(C=O)O[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.906984656058423e-6\n", - "Kc = 0.017553122325364576\n", - "proton+C=C(C=O)O[Pt]<=>OX+C=CC=O\n", - "kf = 13.565263195704604\n", - "krev = 7.179044500174065e-6\n", - "Kc = 1.8895638821260543e6\n", - "vacantX+vacantX+C=C(O)C=O<=>HX+C=C(C=O)O[Pt]\n", - "kf = 8.336773502217888e-19\n", - "krev = 4.018028855986407\n", - "Kc = 2.0748416203624424e-19\n", - "vacantX+vacantX+COCOC<=>CH3X+COCO[Pt]\n", - "kf = 0.24675966205104702\n", - "krev = 5.277017405064255e15\n", - "Kc = 4.6761199198288865e-17\n", - "vacantX+vacantX+COCOC<=>CO[Pt]+COC[Pt]\n", - "kf = 4.1241018831024145e-7\n", - "krev = 7.782310155024181e12\n", - "Kc = 5.2993286067375974e-20\n", - "proton+C=CC=[Pt]<=>CHX+C=C\n", - "kf = 1.3385165927063483e6\n", - "krev = 9.028119675350497e-7\n", - "Kc = 1.4826083845132273e12\n", - "vacantX+vacantX+C=CC=O<=>OX+C=CC=[Pt]\n", - "kf = 1.438969400016978e-30\n", - "krev = 1.6093339940290013e17\n", - "Kc = 8.941396909254915e-48\n", - "proton+C=CC#[Pt]<=>C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.067052266556579e-6\n", - "Kc = 2.342903040792558e16\n", - "vacantX+CC(O)O<=>CC(O)O.[Pt]\n", - "kf = 347843.58123444836\n", - "krev = 178209.4487483253\n", - "Kc = 1.9518806868971765\n", - "proton+CC(O)O[Pt]<=>CC(O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.64203868551119e-24\n", - "Kc = 1.5224976257010135e34\n", - "vacantX+vacantX+COCCO<=>OC[Pt]+COC[Pt]\n", - "kf = 1.3358759661274015e-7\n", - "krev = 3.1165281946439875e14\n", - "Kc = 4.286423490161954e-22\n", - "vacantX+vacantX+COCCO<=>CO[Pt]+OCC[Pt]\n", - "kf = 6.192873660096324e-8\n", - "krev = 3.90827625278604e13\n", - "Kc = 1.584553716150872e-21\n", - "vacantX+vacantX+COCCO<=>CH3X+OCCO[Pt]\n", - "kf = 4.52195120819324e-12\n", - "krev = 5.920081591014324e14\n", - "Kc = 7.638325821483257e-27\n", - "proton+OC(O)C[Pt]<=>CH2X+OCO\n", - "kf = 2.252975678309519e-7\n", - "krev = 0.002613777215265548\n", - "Kc = 8.619616335895816e-5\n", - "HOX+C=CO<=>OC(O)C[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 6.095879365149742e-19\n", - "Kc = 5.364056293281289e10\n", - "HX+C=C(O)O<=>OC(O)C[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 1.7806643358524245e-19\n", - "Kc = 1.572793251160735e11\n", - "vacantX+vacantX+CC(O)O<=>HX+OC(O)C[Pt]\n", - "kf = 2.610914590914038e-25\n", - "krev = 48838.0104312493\n", - "Kc = 5.3460707507516085e-30\n", - "vacantX+vacantX+CCC(O)O<=>CH3X+OC(O)C[Pt]\n", - "kf = 2.73273606062798e-19\n", - "krev = 1.7143250273592365e15\n", - "Kc = 1.594059479396106e-34\n", - "proton+OC(O)C[Pt]<=>CC(O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0162407066861682e-27\n", - "Kc = 2.4600470966688416e37\n" - ] - } - ], - "source": [ - "for (i,rxn) in enumerate(inter.reactions)\n", - " str = getrxnstr(rxn)\n", - " kf = inter.kfs[i]\n", - " krev = inter.krevs[i]\n", - " Kc = kf/krev\n", - " println(str)\n", - " println(\"kf = $kf\")\n", - " println(\"krev = $krev\")\n", - " println(\"Kc = $Kc\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 78, - "id": "dd1b08a5", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "vacantX+CO2<=>CO2X\n", - "kf = 20654.615923781494\n", - "krev = 11189.298481041604\n", - "Kc = 1.8459259048971917\n", - "proton+CO2X<=>CHO2X\n", - "kf = 5.164749496653815e7\n", - "krev = 3.369038128826839e8\n", - "Kc = 0.1533004168893831\n", - "proton+CO2X<=>CO2HX\n", - "kf = 463658.8965294065\n", - "krev = 1.20318988446587e-5\n", - "Kc = 3.853580407511801e10\n", - "proton+CHO2X<=>CH2O2X\n", - "kf = 2.5e10\n", - "krev = 9.108706843764319e-26\n", - "Kc = 2.7446266993557504e35\n", - "proton+CO2HX<=>CH2O2X\n", - "kf = 1.9190551016885178e10\n", - "krev = 1.757621070775451e-14\n", - "Kc = 1.0918480289052538e24\n", - "proton+OCX<=>CHOX\n", - "kf = 2.5e10\n", - "krev = 2.604453583293511e-10\n", - "Kc = 9.59894242706594e19\n", - "proton+CHOX<=>CH2OX\n", - "kf = 1.7890196451453958e9\n", - "krev = 4.957912234830633e-11\n", - "Kc = 3.608413300616868e19\n", - "vacantX+vacantX+CO2<=>OX+OCX\n", - "kf = 3.0109478093923404e-24\n", - "krev = 3.037156297092479e15\n", - "Kc = 9.913707148607306e-40\n", - "OX+proton<=>HOX\n", - "kf = 2.5e10\n", - "krev = 4.7547181516587526e-14\n", - "Kc = 5.25793521352646e23\n", - "vacantX+C=O<=>CH2OX\n", - "kf = 500114.13488002896\n", - "krev = 399.6803280141717\n", - "Kc = 1251.2853393732605\n", - "proton+CHO2X<=>OX+C=O\n", - "kf = 7.971946163368602e-7\n", - "krev = 8.220582009654122e-5\n", - "Kc = 0.009697544716428197\n", - "HX+CO2<=>CHO2X\n", - "kf = 6.542996392927688e-8\n", - "krev = 15.579156394796986\n", - "Kc = 4.199839983064083e-9\n", - "HX+CO2<=>CO2HX\n", - "kf = 6.542996392927688e-8\n", - "krev = 6.197590078701277e-11\n", - "Kc = 1055.7323588427441\n", - "vacantX+vacantX+C=O<=>HX+CHOX\n", - "kf = 2.0718885766149262e-11\n", - "krev = 0.008867505326838887\n", - "Kc = 2.336495440655708e-9\n", - "vacantX+O=CO<=>CH2O2X\n", - "kf = 403943.82249737746\n", - "krev = 29.756334575496034\n", - "Kc = 13575.053119278344\n", - "vacantX+vacantX+O=CO<=>HOX+CHOX\n", - "kf = 8.486192390111145e-15\n", - "krev = 9.7037034735699e11\n", - "Kc = 8.745312975839684e-27\n", - "vacantX+vacantX+O=CO<=>HX+CHO2X\n", - "kf = 1.2668346793097018e-21\n", - "krev = 380.13410282264914\n", - "Kc = 3.332599390328158e-24\n", - "vacantX+vacantX+O=CO<=>HX+CO2HX\n", - "kf = 9.840171155787102e-15\n", - "krev = 0.011746228705195169\n", - "Kc = 8.377302539184302e-13\n", - "proton+CH2OX<=>CO[Pt]\n", - "kf = 4.612846333154699e7\n", - "krev = 90.4105198560361\n", - "Kc = 510211.23874742666\n", - "HX+C=O<=>CO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.180104845075902e-9\n", - "Kc = 9.475050217848336\n", - "proton+CO2HX<=>H2O+OCX\n", - "kf = 2.5e10\n", - "krev = 4.0258346788129556e-7\n", - "Kc = 6.20989235637749e16\n", - "vacantX+vacantX+H2O<=>HX+HOX\n", - "kf = 1.7047654949014593e-31\n", - "krev = 21441.30602897437\n", - "Kc = 7.950847269274322e-36\n", - "proton+CH2OX<=>OC[Pt]\n", - "kf = 1.2443063594454413e6\n", - "krev = 1.1005987164187474e-6\n", - "Kc = 1.1305722429827158e12\n", - "HX+C=O<=>OC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.886422105564557e-15\n", - "Kc = 2.099567387708916e7\n", - "vacantX+vacantX+O=CC=O<=>CHOX+CHOX\n", - "kf = 3.132095071630788e8\n", - "krev = 159.05427897483804\n", - "Kc = 1.9691988746346629e6\n", - "proton+CH2O2X<=>OC(O)[Pt]\n", - "kf = 1.9695177200694968e-5\n", - "krev = 3718.799864740736\n", - "Kc = 5.296111088803661e-9\n", - "HX+O=CO<=>OC(O)[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 29981.045237801853\n", - "Kc = 1.0670229661561413e-12\n", - "proton+CH2O2X<=>OCO[Pt]\n", - "kf = 1.3800914441571782e-5\n", - "krev = 3681.751563599994\n", - "Kc = 3.748464339097702e-9\n", - "HOX+C=O<=>OCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.962949149852605e-13\n", - "Kc = 201771.41789913058\n", - "HX+O=CO<=>OCO[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 42359.465576793365\n", - "Kc = 7.552140562327293e-13\n", - "vacantX+H2O<=>H2OX\n", - "kf = 4.842414926683719e6\n", - "krev = 2.0721934488233277e8\n", - "Kc = 0.023368546645263413\n", - "proton+HOX<=>H2OX\n", - "kf = 2.5e10\n", - "krev = 1.2623996335027457e-31\n", - "Kc = 1.9803554545269617e41\n", - "vacantX+vacantX+H2<=>HX+HX\n", - "kf = 3.8736093818093735e10\n", - "krev = 4.9917087254698525e28\n", - "Kc = 7.760086965901168e-19\n", - "proton+CHOX<=>OC=[Pt]\n", - "kf = 3.6460821201937575e9\n", - "krev = 3.454391742229775e10\n", - "Kc = 0.10554917890812951\n", - "vacantX+vacantX+O=CO<=>OX+OC=[Pt]\n", - "kf = 1.3995006080437096e-36\n", - "krev = 7.971831424002446e14\n", - "Kc = 1.755557203367275e-51\n", - "proton+OC=[Pt]<=>OC[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.468152848309303e-23\n", - "Kc = 3.8650910988497585e32\n", - "proton+OC(O)[Pt]<=>H2O+OC=[Pt]\n", - "kf = 6.989877198043828e9\n", - "krev = 6.424310280494338e-11\n", - "Kc = 1.0880354299303816e20\n", - "proton+O=CC(=O)[Pt]<=>OCX+C=O\n", - "kf = 2.302032083373261e7\n", - "krev = 2.5713202543754838e-9\n", - "Kc = 8.952724109165363e15\n", - "vacantX+vacantX+O=CC=O<=>HX+O=CC(=O)[Pt]\n", - "kf = 1.43713660093583e-9\n", - "krev = 0.00032277677938391324\n", - "Kc = 4.452416322137251e-6\n", - "proton+OCX<=>OC#[Pt]\n", - "kf = 26781.620683797883\n", - "krev = 1.0085447542339806e12\n", - "Kc = 2.6554717151981333e-8\n", - "proton+OC#[Pt]<=>OC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.552445879282663e-17\n", - "Kc = 3.815369170624406e26\n", - "vacantX+O=CC=O<=>O=CC=O.[Pt]\n", - "kf = 359723.7676387533\n", - "krev = 0.32068189796600394\n", - "Kc = 1.121746409511672e6\n", - "proton+O=CC(=O)[Pt]<=>O=CC=O.[Pt]\n", - "kf = 1.508798479649927e9\n", - "krev = 8.88806985342612e-11\n", - "Kc = 1.6975547048252826e19\n", - "vacantX+vacantX+OO<=>HOX+HOX\n", - "kf = 4.0912386971316826e8\n", - "krev = 1.7763617117679594e-6\n", - "Kc = 2.3031563166601894e14\n", - "OCX<=>vacantX+CO\n", - "kf = 2.010168305725754e-19\n", - "krev = 2.61760793808642e-25\n", - "Kc = 767940.9419866255\n", - "vacantX+vacantX+O2<=>OX+OX\n", - "kf = 1.0945721587141857e10\n", - "krev = 4.219325007995329e-16\n", - "Kc = 2.594187830138819e25\n", - "proton+HX<=>[H][H].[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.1949534688419614e-15\n", - "Kc = 2.0921316730623565e25\n", - "vacantX+H2<=>[H][H].[Pt]\n", - "kf = 2338.960705505517\n", - "krev = 9707.159813448116\n", - "Kc = 0.24095211683495363\n", - "CHOX+C=O<=>O=COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 7.563806299311394e-5\n", - "Kc = 0.0005236345532350701\n", - "proton+OO[Pt]<=>OX+H2O\n", - "kf = 17.257164508221003\n", - "krev = 6.236444643145301e-63\n", - "Kc = 2.767147869610126e63\n", - "vacantX+vacantX+OO<=>HX+OO[Pt]\n", - "kf = 4.980245005159166e-22\n", - "krev = 5.509834949091977\n", - "Kc = 9.038827934364735e-23\n", - "proton+OC#[Pt]<=>H2O+CX\n", - "kf = 3.276640102032806e-5\n", - "krev = 0.0009291230748795855\n", - "Kc = 0.03526594259277716\n", - "vacantX+vacantX+O=C=C=O<=>OCX+OCX\n", - "kf = 74.64023007210145\n", - "krev = 2.953439666185894e-39\n", - "Kc = 2.52723056870475e40\n", - "HX+O=C=C=O<=>O=CC(=O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 5.0006650398424424e-61\n", - "Kc = 1.1597065597154312e53\n", - "proton+OC=[Pt]<=>H2O+CHX\n", - "kf = 2.5e10\n", - "krev = 6.511063937864271e-5\n", - "Kc = 3.839618261865876e14\n", - "proton+CX<=>CHX\n", - "kf = 2.5e10\n", - "krev = 6.018259224258551e-33\n", - "Kc = 4.1540251206244773e42\n", - "H2+CX<=>CH2X\n", - "kf = 4.832014059685671\n", - "krev = 1.8278921581756875e-33\n", - "Kc = 2.643489681857502e33\n", - "vacantX+vacantX+C=O<=>OX+CH2X\n", - "kf = 4.5608316796485725e-28\n", - "krev = 3.884151005592286e17\n", - "Kc = 1.1742158513101117e-45\n", - "proton+OC[Pt]<=>H2O+CH2X\n", - "kf = 7206.229958253159\n", - "krev = 0.0019484451144913943\n", - "Kc = 3.6984516036184127e6\n", - "proton+O=COC[Pt]<=>CH2X+O=CO\n", - "kf = 1981.2472905766488\n", - "krev = 1.4695324127813272e-5\n", - "Kc = 1.3482161219069803e8\n", - "proton+CHX<=>CH2X\n", - "kf = 2.5e10\n", - "krev = 6.715036577093663e-15\n", - "Kc = 3.722987911231938e24\n", - "proton+O=COC#[Pt]<=>CX+O=CO\n", - "kf = 6.185088018779624e7\n", - "krev = 3.741277098492221e-23\n", - "Kc = 1.6532023306352497e30\n", - "vacantX+vacantX+C=C=O<=>OCX+CH2X\n", - "kf = 2.4823885573387985e-14\n", - "krev = 9.351132511056354e15\n", - "Kc = 2.6546394828687704e-30\n", - "CHOX+C=O<=>O=CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.4949222028864902e7\n", - "Kc = 2.6494156850764662e-15\n", - "HX+O=CC=O<=>O=CCO[Pt]\n", - "kf = 5.6976884072695144e-8\n", - "krev = 2.551666729065355e-8\n", - "Kc = 2.23292812590636\n", - "proton+O=CC=O.[Pt]<=>O=CCO[Pt]\n", - "kf = 957581.7759153218\n", - "krev = 7139.55197608848\n", - "Kc = 134.12351070801344\n", - "O=O.[Pt]+proton<=>OO[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.545950245153839e-28\n", - "Kc = 7.050296330064662e37\n", - "proton+O=CC#[Pt]<=>CX+C=O\n", - "kf = 5.731900626219973e-17\n", - "krev = 16.634660991475336\n", - "Kc = 3.4457574032662074e-18\n", - "proton+CO2HX<=>OC(O)=[Pt]\n", - "kf = 8.313674902647437e-22\n", - "krev = 1.0085447542339753e12\n", - "Kc = 8.243238455949296e-34\n", - "proton+OC(O)=[Pt]<=>OC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.563843227039955e-39\n", - "Kc = 7.014898918762039e48\n", - "proton+OC(O)=[Pt]<=>H2O+OC#[Pt]\n", - "kf = 58948.65819613129\n", - "krev = 2.9467686111082447e-38\n", - "Kc = 2.0004508658710534e42\n", - "proton+O=C(O)C#[Pt]<=>CX+O=CO\n", - "kf = 1.2163309452954808e-9\n", - "krev = 0.00037997676558546045\n", - "Kc = 3.201066632117316e-6\n", - "proton+O=C=C=O.[Pt]<=>O=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.649884885591097e-48\n", - "Kc = 9.434372087609898e57\n", - "vacantX+O=C=C=O<=>O=C=C=O.[Pt]\n", - "kf = 366139.2749661925\n", - "krev = 442.06521987276346\n", - "Kc = 828.2471873077366\n", - "HOX+C=O<=>OOC[Pt]\n", - "kf = 1.5395975576095126e-29\n", - "krev = 2.622153295712258e16\n", - "Kc = 5.871500953537159e-46\n", - "proton+OOC[Pt]<=>OO+CH2X\n", - "kf = 15.535579749933543\n", - "krev = 3.4028033042152773e-9\n", - "Kc = 4.5655238816444645e9\n", - "vacantX+vacantX+O=C=CO<=>OCX+OC=[Pt]\n", - "kf = 73.33238091278024\n", - "krev = 14511.198914062346\n", - "Kc = 0.005053502563576338\n", - "vacantX+C=C=O<=>C=C=O.[Pt]\n", - "kf = 422670.5724931744\n", - "krev = 9.80980243728561e-11\n", - "Kc = 4.3086552985681545e15\n", - "proton+CO[Pt]<=>OX+CH4\n", - "kf = 541698.6744405399\n", - "krev = 1.9995135619129721e-19\n", - "Kc = 2.7091522896313173e24\n", - "HX+C=C=O<=>CC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.3310785577331067e-33\n", - "Kc = 2.514767798332947e25\n", - "proton+C=C=O.[Pt]<=>CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.357099551204697e-8\n", - "Kc = 3.9326110592781875e17\n", - "proton+CC(=O)[Pt]<=>OCX+CH4\n", - "kf = 1.0030005882936613e8\n", - "krev = 4.3463683404291294e-8\n", - "Kc = 2.3076750743003805e15\n", - "vacantX+vacantX+COC=O<=>CHOX+CO[Pt]\n", - "kf = 5.858305523872122e-8\n", - "krev = 9.372228401924443e12\n", - "Kc = 6.250707166578664e-21\n", - "vacantX+vacantX+COC=O<=>HX+O=COC[Pt]\n", - "kf = 8.724708246600757e-23\n", - "krev = 252.56605644619947\n", - "Kc = 3.454426287270814e-25\n", - "vacantX+vacantX+COC=O<=>HX+COC(=O)[Pt]\n", - "kf = 7.165711269221808e-16\n", - "krev = 0.1859922027934253\n", - "Kc = 3.852694447186316e-15\n", - "proton+O=COCC#[Pt]<=>CX+COC=O\n", - "kf = 0.8132675549526747\n", - "krev = 2.165706403032533e-5\n", - "Kc = 37552.06863746147\n", - "HOX+C=C=O<=>O=C([Pt])CO\n", - "kf = 3.3473534940386794e-8\n", - "krev = 9.042590347389556e-30\n", - "Kc = 3.70176394754519e21\n", - "HX+O=C=CO<=>O=C([Pt])CO\n", - "kf = 2.8488442036348548e-8\n", - "krev = 1.614840618256874e-45\n", - "Kc = 1.7641643214981894e37\n", - "vacantX+vacantX+COO<=>HOX+CO[Pt]\n", - "kf = 3.442529358831723e8\n", - "krev = 2.6586367586035048e-11\n", - "Kc = 1.294847574679578e19\n", - "vacantX+vacantX+COO<=>HX+OOC[Pt]\n", - "kf = 1.3336211820914592e-23\n", - "krev = 16620.58178963317\n", - "Kc = 8.023913957833202e-28\n", - "CHOX+C=C=O<=>O=CCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 2.6714659015861004e-16\n", - "Kc = 1.2530025152300434e8\n", - "vacantX+vacantX+CO-2<=>HX+CO[Pt]\n", - "kf = 3.6896065237788346e-26\n", - "krev = 1200.2597905170037\n", - "Kc = 3.0740066050113714e-29\n", - "vacantX+vacantX+CO-2<=>HX+OC[Pt]\n", - "kf = 1.1691860289045307e-22\n", - "krev = 1.716447494000275\n", - "Kc = 6.811662069427353e-23\n", - "proton+OCO[Pt]<=>OX+CO-2\n", - "kf = 6.4866612293733e7\n", - "krev = 4.917786339628338e-9\n", - "Kc = 1.319020547335029e16\n", - "proton+COC(=O)[Pt]<=>OCX+CO-2\n", - "kf = 5.096893185474306e9\n", - "krev = 2.041829224680708e-9\n", - "Kc = 2.49623872744369e18\n", - "proton+O=C([Pt])CO<=>OCX+CO-2\n", - "kf = 1.9762803815844387e7\n", - "krev = 1.2158736968776066e-8\n", - "Kc = 1.6253994034574272e15\n", - "proton+OCC#[Pt]<=>CX+CO-2\n", - "kf = 1.8515947729382765e-10\n", - "krev = 0.16959607683462066\n", - "Kc = 1.091767455649245e-9\n", - "vacantX+vacantX+COOC<=>CO[Pt]+CO[Pt]\n", - "kf = 3.028654941635431e8\n", - "krev = 1.0392777770118965e-11\n", - "Kc = 2.914191959673513e19\n", - "vacantX+vacantX+C=C=O<=>HX+O=C=C[Pt]\n", - "kf = 3.6584912239485734e-16\n", - "krev = 0.32395775785233605\n", - "Kc = 1.1293111942132156e-15\n", - "vacantX+vacantX+O=C=CO<=>HOX+O=C=C[Pt]\n", - "kf = 3.132095071630788e8\n", - "krev = 5.819571251914923e7\n", - "Kc = 5.382003133994065\n", - "proton+O=C=C[Pt]<=>C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.724942318590629e-29\n", - "Kc = 2.570709334924167e38\n", - "vacantX+vacantX+O=CCO<=>CHOX+OC[Pt]\n", - "kf = 9001.813049524091\n", - "krev = 8.180569891408677e12\n", - "Kc = 1.1003894800749632e-9\n", - "vacantX+vacantX+O=CCO<=>HX+O=CCO[Pt]\n", - "kf = 3.705974451661604e-28\n", - "krev = 2668.9209237076484\n", - "Kc = 1.3885665996103351e-31\n", - "vacantX+vacantX+O=CCO<=>HX+O=C([Pt])CO\n", - "kf = 1.2718474027465153e-10\n", - "krev = 0.0002705673832361486\n", - "Kc = 4.7006678614933393e-7\n", - "proton+O=CCOC#[Pt]<=>CX+O=CCO\n", - "kf = 3.8625888100004036e-23\n", - "krev = 1.5059302822169408e-12\n", - "Kc = 2.564918745318097e-11\n", - "proton+COC#[Pt]<=>CX+CO-2\n", - "kf = 3.5797175052253717e-22\n", - "krev = 9.770006712968626e-20\n", - "Kc = 0.0036639867406372244\n", - "proton+O=CC(=O)C#[Pt]<=>CX+O=CC=O\n", - "kf = 5.9931479699583235e-12\n", - "krev = 0.0016900056192162703\n", - "Kc = 3.546229611199523e-9\n", - "vacantX+vacantX+OCO<=>HOX+OC[Pt]\n", - "kf = 1.653107374238179e-12\n", - "krev = 3.492310477620836e11\n", - "Kc = 4.7335635958815765e-24\n", - "vacantX+vacantX+OCO<=>HX+OC(O)[Pt]\n", - "kf = 4.0412190145177725e-23\n", - "krev = 628.7683045605482\n", - "Kc = 6.427198993979533e-26\n", - "vacantX+vacantX+OCO<=>HX+OCO[Pt]\n", - "kf = 1.1281154422531313e-23\n", - "krev = 247.99076039714222\n", - "Kc = 4.5490220702034325e-26\n", - "proton+OC(O)C#[Pt]<=>CX+OCO\n", - "kf = 0.005562206988621036\n", - "krev = 0.025459246171787766\n", - "Kc = 0.21847492856189518\n", - "proton+OCOC#[Pt]<=>CX+OCO\n", - "kf = 2.2993090387825977e-18\n", - "krev = 1.7767009384663083e-12\n", - "Kc = 1.2941452266960681e-6\n", - "proton+O=COC=[Pt]<=>O=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.03525663068036e-45\n", - "Kc = 2.4148601669491608e55\n", - "proton+O=COC=[Pt]<=>CHX+O=CO\n", - "kf = 407721.49317133107\n", - "krev = 4.66233771243883e-34\n", - "Kc = 8.745001291595743e38\n", - "proton+O=COC#[Pt]<=>O=COC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.1834993039887084e-24\n", - "Kc = 7.852993706854812e33\n", - "proton+O=C=CC#[Pt]<=>CX+C=C=O\n", - "kf = 1.255896512556004e-15\n", - "krev = 0.016900821436021087\n", - "Kc = 7.430979123176135e-14\n", - "vacantX+vacantX+COCO<=>CO[Pt]+OC[Pt]\n", - "kf = 3.0636862331912886e-9\n", - "krev = 3.008499680951675e11\n", - "Kc = 1.0183435459837431e-20\n", - "proton+CC#[Pt]<=>CX+CH4\n", - "kf = 3.172314510568854e-8\n", - "krev = 0.363285670785801\n", - "Kc = 8.732286367659409e-8\n", - "HX+O=C=C=O<=>O=C=CO[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.1302052975227224e-55\n", - "Kc = 2.7224155607861307e47\n", - "proton+O=C=CO[Pt]<=>OX+C=C=O\n", - "kf = 0.047578794564636824\n", - "krev = 2.8204743128358057e-8\n", - "Kc = 1.6869075654441754e6\n", - "proton+O=C=C=O.[Pt]<=>O=C=CO[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 2.257619247094878e-42\n", - "Kc = 2.2147224366704162e52\n", - "vacantX+vacantX+O=C=CO<=>HX+O=C=CO[Pt]\n", - "kf = 0.0007071288662616175\n", - "krev = 2.8988454126647536e-5\n", - "Kc = 24.393465866522067\n", - "vacantX+vacantX+OCCO<=>OC[Pt]+OC[Pt]\n", - "kf = 2.961131444342359e-9\n", - "krev = 1.299206322752899e13\n", - "Kc = 2.2791849088819035e-22\n", - "proton+COC(=O)C#[Pt]<=>CX+COC=O\n", - "kf = 2.520547604265173e-10\n", - "krev = 3.828537658551766e-5\n", - "Kc = 6.583577932517004e-6\n", - "proton+O=C=CC(=O)[Pt]<=>OCX+C=C=O\n", - "kf = 2.14881300259784e7\n", - "krev = 1.9623010758881652e-11\n", - "Kc = 1.0950475587061772e18\n", - "vacantX+vacantX+OC=CO<=>OC=[Pt]+OC=[Pt]\n", - "kf = 1.351949923589269e-23\n", - "krev = 7.975137957191956e11\n", - "Kc = 1.6952056890377485e-35\n", - "vacantX+OX+CH4<=>HOX+CH3X\n", - "kf = 1181.9069662995785\n", - "krev = 1.0235810933777192e20\n", - "Kc = 1.1546783874244874e-17\n", - "vacantX+HOX+CH4<=>H2OX+CH3X\n", - "kf = 5.28370763875636e9\n", - "krev = 1.2149259925984929e9\n", - "Kc = 4.348995470461149\n", - "HX+CH3X<=>vacantX+vacantX+CH4\n", - "kf = 5.733311120080377e8\n", - "krev = 8.483521653048543e-25\n", - "Kc = 6.758173497465076e32\n", - "proton+CH2X<=>CH3X\n", - "kf = 2.5e10\n", - "krev = 7.728626954425352e-28\n", - "Kc = 3.2347272222377345e37\n", - "CO2+CH3X<=>COC(=O)[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.00447183609125585\n", - "Kc = 1.463156578060128e-5\n", - "vacantX+vacantX+COC=O<=>CHO2X+CH3X\n", - "kf = 0.05589950368763065\n", - "krev = 5.054770535995559e16\n", - "Kc = 1.1058761874463802e-18\n", - "vacantX+vacantX+COO<=>OO[Pt]+CH3X\n", - "kf = 9.385776922831516e-7\n", - "krev = 3.9782610412247473e11\n", - "Kc = 2.359266228528335e-18\n", - "vacantX+vacantX+CO-2<=>HOX+CH3X\n", - "kf = 9.872876935778847e-16\n", - "krev = 6.917821124819518e13\n", - "Kc = 1.427165686657795e-29\n", - "vacantX+vacantX+COCO<=>CH3X+OCO[Pt]\n", - "kf = 3.9072411322938125e-9\n", - "krev = 8.599564777209447e13\n", - "Kc = 4.543533578174534e-23\n", - "O=O+HX<=>OO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 8.854082166234876e-41\n", - "Kc = 8.666474551788235e32\n", - "vacantX+O=O<=>O=O.[Pt]\n", - "kf = 484458.3574999593\n", - "krev = 584.920039726471\n", - "Kc = 828.247152767255\n", - "vacantX+O=C=CO<=>O=C=CO.[Pt]\n", - "kf = 359723.7676387533\n", - "krev = 0.4900054095759742\n", - "Kc = 734122.0333670193\n", - "proton+O=C=CO.[Pt]<=>O=C([Pt])CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.543989619636675e-29\n", - "Kc = 1.6191818702694958e39\n", - "proton+O=C=CO[Pt]<=>O=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.012328788524416852\n", - "Kc = 2.0277742578265605e12\n", - "vacantX+vacantX+O=C=C=O<=>OX+O=C=C=[Pt]\n", - "kf = 149.2804601441562\n", - "krev = 1.2008902564793325e-12\n", - "Kc = 1.2430816166483347e14\n", - "proton+O=C=C=[Pt]<=>O=CC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 728325.7738813914\n", - "Kc = 34325.299057824195\n", - "proton+O=C=C=[Pt]<=>O=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.992117420427329e-15\n", - "Kc = 4.1721478812771864e24\n", - "vacantX+vacantX+C=CO<=>CH2X+OC=[Pt]\n", - "kf = 3.7510196251812924e-36\n", - "krev = 6.624293894020312e13\n", - "Kc = 5.662519938264367e-50\n", - "proton+O=C(C#[Pt])CO<=>CX+O=CCO\n", - "kf = 2.1150580786972557e-17\n", - "krev = 1.2236788896896236\n", - "Kc = 1.728442074565594e-17\n", - "vacantX+vacantX+C=C<=>CH2X+CH2X\n", - "kf = 9.387035392806688e-46\n", - "krev = 5.259242712748897e15\n", - "Kc = 1.784864457776713e-61\n", - "proton+O=COC[Pt]<=>COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.124037165592671e-28\n", - "Kc = 8.002465615756261e37\n", - "proton+COC(=O)[Pt]<=>COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.484214060387906e-18\n", - "Kc = 7.175219308200797e27\n", - "vacantX+COC=O<=>COC=O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.8619443782965007\n", - "Kc = 410274.8449265323\n", - "HX+O=C=C=C=O<=>O=C=CC(=O)[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 3.561089909521239e-25\n", - "Kc = 1.4777843564830474e17\n", - "vacantX+vacantX+O=C=C=C=O<=>OCX+O=C=C=[Pt]\n", - "kf = 135.4631249389026\n", - "krev = 3.092595390223456e6\n", - "Kc = 4.3802407960361956e-5\n", - "CH3X+O=C=C=O<=>CC(=O)C(=O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 3.5093718907449027e-71\n", - "Kc = 1.6525190917893694e63\n", - "proton+OOC#[Pt]<=>OO+CX\n", - "kf = 3.959382254258936e-52\n", - "krev = 4.505410128222608e6\n", - "Kc = 8.78806177812034e-59\n", - "proton+O=CC[Pt]<=>CH2X+C=O\n", - "kf = 9.847553463617368e-13\n", - "krev = 0.8193686811731042\n", - "Kc = 1.2018464568987987e-12\n", - "HX+C=C=O<=>O=CC[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 3.6888123831707493e-19\n", - "Kc = 9.074339235332521e10\n", - "proton+C=C=O.[Pt]<=>O=CC[Pt]\n", - "kf = 4.477750650627013e6\n", - "krev = 3155.453532604055\n", - "Kc = 1419.0513675324908\n", - "vacantX+vacantX+O=CCO<=>HOX+O=CC[Pt]\n", - "kf = 3.3834985622063113e-5\n", - "krev = 2.9362980773683545e12\n", - "Kc = 1.1523007790948657e-17\n", - "vacantX+vacantX+O=CC=O<=>OX+O=CC=[Pt]\n", - "kf = 6.170227811474367e-18\n", - "krev = 2.1467268001769245e15\n", - "Kc = 2.874249210922341e-33\n", - "proton+O=CC=[Pt]<=>CHX+C=O\n", - "kf = 0.3518802014338951\n", - "krev = 0.0019581841163396926\n", - "Kc = 179.69719930710195\n", - "proton+O=CC#[Pt]<=>O=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.1385387905668107e-13\n", - "Kc = 7.9654902068249e22\n", - "proton+O=C=C[Pt]<=>O=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.814809579170971e7\n", - "Kc = 655.3407052478085\n", - "proton+O=CC=[Pt]<=>O=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.4911345025101916e-29\n", - "Kc = 5.566522219725765e38\n", - "proton+O=CCO[Pt]<=>OX+CC=O\n", - "kf = 108844.3774855493\n", - "krev = 6.551243603618761e-23\n", - "Kc = 1.6614307766761425e27\n", - "vacantX+vacantX+CC=O<=>HX+CC(=O)[Pt]\n", - "kf = 4.3209399543319175e-11\n", - "krev = 0.0003615296985530135\n", - "Kc = 1.195182573278502e-7\n", - "proton+O=CCC(=O)[Pt]<=>OCX+CC=O\n", - "kf = 7.362850070977087e6\n", - "krev = 9.270601965584902e-14\n", - "Kc = 7.94214884676321e19\n", - "proton+O=CCC#[Pt]<=>CX+CC=O\n", - "kf = 0.11748380587607415\n", - "krev = 6.387097627333538e-5\n", - "Kc = 1839.3926745898334\n", - "vacantX+vacantX+CC=O<=>CHOX+CH3X\n", - "kf = 6.063283190982672e-6\n", - "krev = 7.026751658283665e14\n", - "Kc = 8.628856526948432e-21\n", - "proton+CC(=O)C#[Pt]<=>CX+CC=O\n", - "kf = 8.247683071468342e-18\n", - "krev = 0.06355423283679383\n", - "Kc = 1.2977393799478706e-16\n", - "proton+CC(=O)C(=O)[Pt]<=>OCX+CC=O\n", - "kf = 3.422758172577326e7\n", - "krev = 2.0119060511296993e-10\n", - "Kc = 1.7012514926606157e17\n", - "vacantX+vacantX+CC=O<=>HX+O=CC[Pt]\n", - "kf = 3.2094062904328744e-20\n", - "krev = 74.41720028073364\n", - "Kc = 4.312721089110603e-22\n", - "vacantX+CH4<=>C.[Pt]\n", - "kf = 11983.404197457203\n", - "krev = 27576.843954134933\n", - "Kc = 0.4345458899280744\n", - "proton+CH3X<=>C.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.2634270430964172e-30\n", - "Kc = 1.9787450440137642e40\n", - "HX+O=C=CC=O<=>O=CCC(=O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 3.8194581898791103e-32\n", - "Kc = 6.789235995427004e23\n", - "vacantX+vacantX+O=C=CC=O<=>CHOX+O=C=C[Pt]\n", - "kf = 2.850945414803626e8\n", - "krev = 4.6591458607721776e7\n", - "Kc = 6.119030182779314\n", - "vacantX+vacantX+O=C=CC=O<=>HX+O=C=CC(=O)[Pt]\n", - "kf = 1.1776167531898308e-10\n", - "krev = 0.0005032011998508361\n", - "Kc = 2.3402502886298994e-7\n", - "vacantX+vacantX+O=C=CC=O<=>OCX+O=CC=[Pt]\n", - "kf = 0.006845452357086415\n", - "krev = 1.638610749190394e14\n", - "Kc = 4.177595173514284e-17\n", - "vacantX+vacantX+C=C(O)O<=>CH2X+OC(O)=[Pt]\n", - "kf = 1.3631835715271243e-51\n", - "krev = 1.0974745099569602e16\n", - "Kc = 1.242109551665655e-67\n", - "proton+O=C=CC=O.[Pt]<=>O=CCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.130402878837127e-16\n", - "Kc = 4.078035407151288e25\n", - "proton+O=C=CC(=O)[Pt]<=>O=C=CC=O.[Pt]\n", - "kf = 2.964275004938465e9\n", - "krev = 9.178277268525813e-12\n", - "Kc = 3.229663822756335e20\n", - "vacantX+O=C=CC=O<=>O=C=CC=O.[Pt]\n", - "kf = 327433.4917974331\n", - "krev = 0.29189612518083846\n", - "Kc = 1.1217466199476891e6\n", - "vacantX+vacantX+CC(=O)O<=>HOX+CC(=O)[Pt]\n", - "kf = 3.661873055903852e-12\n", - "krev = 2.1682718089028445e11\n", - "Kc = 1.6888441019563762e-23\n", - "vacantX+vacantX+CC(=O)O<=>CO2HX+CH3X\n", - "kf = 1.1977509649486271e-8\n", - "krev = 1.0254845667743408e14\n", - "Kc = 1.1679853639496008e-22\n", - "CO2+CH3X<=>CC(=O)O[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 3.3286101924403974e-7\n", - "Kc = 0.19656841788766613\n", - "proton+CC(=O)O[Pt]<=>OX+CC=O\n", - "kf = 6.638543952734307e-6\n", - "krev = 1.1832604608796647e-7\n", - "Kc = 56.10382643732599\n", - "vacantX+vacantX+CC(=O)O<=>HX+CC(=O)O[Pt]\n", - "kf = 2.4753542791841756e-22\n", - "krev = 11382.562807978633\n", - "Kc = 2.1746897609465158e-26\n", - "proton+CC(=O)OC#[Pt]<=>CX+CC(=O)O\n", - "kf = 3.5372794201475537e8\n", - "krev = 2.288049006228874e-19\n", - "Kc = 1.5459806195224992e27\n", - "vacantX+vacantX+CC(=O)C=O<=>CHOX+CC(=O)[Pt]\n", - "kf = 2.810784197367395e8\n", - "krev = 8.682228189641076\n", - "Kc = 3.237399589106622e7\n", - "vacantX+vacantX+CC(=O)C=O<=>CH3X+O=CC(=O)[Pt]\n", - "kf = 0.010756441693245073\n", - "krev = 2.0353876594794328e15\n", - "Kc = 5.284714016589902e-18\n", - "vacantX+vacantX+CC(=O)C=O<=>HX+CC(=O)C(=O)[Pt]\n", - "kf = 2.426386880233808e-11\n", - "krev = 0.0003222108693910823\n", - "Kc = 7.530431499158364e-8\n", - "proton+O=C=C([Pt])C=O<=>C=O+O=C=C=[Pt]\n", - "kf = 13308.622034460761\n", - "krev = 4.6234228919871786e-9\n", - "Kc = 2.8785214645897607e12\n", - "HX+O=C=C=C=O<=>O=C=C([Pt])C=O\n", - "kf = 5.262522960320117e-8\n", - "krev = 8.417963556232881e-20\n", - "Kc = 6.251539253129229e11\n", - "vacantX+vacantX+O=C=CC=O<=>HX+O=C=C([Pt])C=O\n", - "kf = 3.109950102720783e-13\n", - "krev = 0.31413419650430946\n", - "Kc = 9.900068624582613e-13\n", - "proton+O=C=C([Pt])C=O<=>O=C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.274602487927107e-16\n", - "Kc = 7.6345144463093386e25\n", - "proton+O=C=COC#[Pt]<=>CX+O=C=CO\n", - "kf = 3.333143073629419e-24\n", - "krev = 2.9895559923107984e-13\n", - "Kc = 1.1149291340260339e-11\n", - "vacantX+vacantX+COC(C)=O<=>CO[Pt]+CC(=O)[Pt]\n", - "kf = 6.614441053978493e-6\n", - "krev = 7.629970776987544e11\n", - "Kc = 8.669025409544227e-18\n", - "vacantX+vacantX+COC(C)=O<=>CH3X+COC(=O)[Pt]\n", - "kf = 1.5563360867242215e-10\n", - "krev = 4.0343976517667425e14\n", - "Kc = 3.857666549162974e-25\n", - "vacantX+vacantX+COC(C)=O<=>CH3X+CC(=O)O[Pt]\n", - "kf = 0.0003463783354588583\n", - "krev = 6.683486846094463e16\n", - "Kc = 5.182599194629471e-21\n", - "vacantX+vacantX+COO<=>HX+COO[Pt]\n", - "kf = 1.175900379595729e-21\n", - "krev = 0.27982743013843664\n", - "Kc = 4.2022341377111815e-21\n", - "proton+COO[Pt]<=>OX+CO-2\n", - "kf = 129.78074174016686\n", - "krev = 1.499485133709293e-58\n", - "Kc = 8.65502023478731e59\n", - "vacantX+vacantX+COOC<=>CH3X+COO[Pt]\n", - "kf = 1.8186835430204133e-8\n", - "krev = 4.141977957602716e12\n", - "Kc = 4.39085760869917e-21\n", - "O=O+CH3X<=>COO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 4.970959816815508e-38\n", - "Kc = 1.543639067721808e30\n", - "proton+CO[Pt]<=>CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.487564815762018e-25\n", - "Kc = 1.0049989387851077e35\n", - "proton+OC[Pt]<=>CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.512171272873819e-19\n", - "Kc = 4.535417853038886e28\n", - "vacantX+CO-2<=>CO.[Pt]\n", - "kf = 484125.61468448705\n", - "krev = 1.0558750276780043e7\n", - "Kc = 0.04585065485913965\n", - "vacantX+vacantX+CC(=O)CO<=>OC[Pt]+CC(=O)[Pt]\n", - "kf = 4.324183911493771e7\n", - "krev = 7.8667392573421875e12\n", - "Kc = 5.496793232924203e-6\n", - "vacantX+vacantX+CC(=O)CO<=>CH3X+O=C([Pt])CO\n", - "kf = 0.43146252134138535\n", - "krev = 2.5450806210309695e15\n", - "Kc = 1.695280368629765e-16\n", - "HX+O=C=C=O<=>O=C=C(O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 7.390785994602033e-44\n", - "Kc = 7.846667531546056e35\n", - "proton+O=C=C=O.[Pt]<=>O=C=C(O)[Pt]\n", - "kf = 5.0e10\n", - "krev = 7.832851008293297e-31\n", - "Kc = 6.383371769367348e40\n", - "vacantX+vacantX+O=C=CO<=>HX+O=C=C(O)[Pt]\n", - "kf = 2.8707175642480555e-12\n", - "krev = 0.04083063397693327\n", - "Kc = 7.030793511239207e-11\n", - "proton+O=C=C(O)[Pt]<=>O=C=CO.[Pt]\n", - "kf = 1.7351014576291664e10\n", - "krev = 2.4662443446341767e-14\n", - "Kc = 7.03539964077054e23\n", - "proton+O=C=C(O)[Pt]<=>H2O+O=C=C=[Pt]\n", - "kf = 1.2324712433709262e6\n", - "krev = 1.176415080398485e-31\n", - "Kc = 1.0476499867321094e37\n", - "vacantX+vacantX+O=CCC=O<=>HX+O=CCC(=O)[Pt]\n", - "kf = 3.286584099620913e-11\n", - "krev = 0.0009472638388816695\n", - "Kc = 3.469555117295539e-8\n", - "vacantX+vacantX+O=CCC=O<=>CHOX+O=CC[Pt]\n", - "kf = 5.621568394735124e8\n", - "krev = 2.2372815421494465e13\n", - "Kc = 2.51267812692642e-5\n", - "proton+O=C=C(O)C#[Pt]<=>CX+O=C=CO\n", - "kf = 3.0900625689798e-31\n", - "krev = 97363.75326657317\n", - "Kc = 3.1737299203323514e-36\n", - "proton+COOC#[Pt]<=>CX+COO\n", - "kf = 1.3396315820930446e-65\n", - "krev = 2.5e10\n", - "Kc = 5.3585263283721787e-76\n", - "vacantX+vacantX+COC=C=O<=>CO[Pt]+O=C=C[Pt]\n", - "kf = 1.4053920986837533e8\n", - "krev = 2.5815645207863396e8\n", - "Kc = 0.5443954963619013\n", - "vacantX+vacantX+COC=C=O<=>CH3X+O=C=CO[Pt]\n", - "kf = 1.4053920986837533e8\n", - "krev = 1.2268284001067661e8\n", - "Kc = 1.1455490421981163\n", - "HX+O=CC=O<=>O=CC(O)[Pt]\n", - "kf = 5.6976884072695144e-8\n", - "krev = 1.248882373151946e-25\n", - "Kc = 4.562229822244678e17\n", - "proton+O=CC(O)[Pt]<=>C=O+OC=[Pt]\n", - "kf = 1.4979350850413518e-9\n", - "krev = 7.682289195925664e-6\n", - "Kc = 0.00019498551106820976\n", - "proton+O=CC=O.[Pt]<=>O=CC(O)[Pt]\n", - "kf = 3.43386635836783e8\n", - "krev = 1.2530721027853126e-11\n", - "Kc = 2.7403581571523903e19\n", - "HX+O=C=CO<=>O=CC(O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 2.6755933088589045e-38\n", - "Kc = 1.0647523277182356e30\n", - "vacantX+vacantX+O=CCO<=>HX+O=CC(O)[Pt]\n", - "kf = 5.743984385098034e-15\n", - "krev = 0.20246227896672986\n", - "Kc = 2.8370639777506056e-14\n", - "proton+O=C=CO.[Pt]<=>O=CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.5582018736355307e-22\n", - "Kc = 9.77248912904274e31\n", - "proton+O=CC(O)[Pt]<=>H2O+O=CC=[Pt]\n", - "kf = 459.6019775429135\n", - "krev = 1.1031455244918085e-6\n", - "Kc = 4.166286018833649e8\n", - "proton+O=CC(O)C#[Pt]<=>CX+O=CCO\n", - "kf = 0.2097860124056399\n", - "krev = 0.0024507024511013467\n", - "Kc = 85.60240036947854\n", - "vacantX+vacantX+O=C=CCO<=>OC[Pt]+O=C=C[Pt]\n", - "kf = 4067.906517801298\n", - "krev = 9.581534474143486e11\n", - "Kc = 4.245568941779481e-9\n", - "proton+O=CC(=O)[Pt]<=>O=CC(O)=[Pt]\n", - "kf = 1.4625119078213113e-5\n", - "krev = 1.0085447542339824e12\n", - "Kc = 1.4501209804339615e-17\n", - "proton+O=CC(O)=[Pt]<=>OC#[Pt]+C=O\n", - "kf = 345367.8200620121\n", - "krev = 2.1066346546856475e-20\n", - "Kc = 1.6394291211996983e25\n", - "proton+O=CC(O)=[Pt]<=>H2O+O=CC#[Pt]\n", - "kf = 109541.91076063467\n", - "krev = 6.52855201530546e-37\n", - "Kc = 1.6778898368861259e41\n", - "proton+O=C=C(O)[Pt]<=>O=CC(O)=[Pt]\n", - "kf = 266253.7431100425\n", - "krev = 124230.61178859882\n", - "Kc = 2.1432217009695007\n", - "proton+O=CC(O)=[Pt]<=>O=CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.793151847783197e-46\n", - "Kc = 3.207944678649035e55\n", - "proton+OC(O)[Pt]<=>OCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.3128823116835e-26\n", - "Kc = 5.796587570283467e35\n", - "proton+OCO[Pt]<=>OCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.052557862362137e-26\n", - "Kc = 8.189852945376913e35\n", - "vacantX+OCO<=>OCO.[Pt]\n", - "kf = 395377.4080430906\n", - "krev = 715.0601225795458\n", - "Kc = 552.9289014422803\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.079525546868e-12\n", - "Kc = 1.2021973010936467e22\n", - "vacantX+O=C=C=C=O<=>O=C=C=C=O.[Pt]\n", - "kf = 332249.5811031886\n", - "krev = 401.14766551623046\n", - "Kc = 828.2475748067037\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 4.91573386591171e-7\n", - "Kc = 5.08571063485824e16\n", - "proton+O=CCO[Pt]<=>O=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.8816895227328687e-31\n", - "Kc = 1.3285932507978942e41\n", - "proton+O=C([Pt])CO<=>O=CCO.[Pt]\n", - "kf = 3.74256001789537e8\n", - "krev = 9.536073355505413e-9\n", - "Kc = 3.9246342581191416e16\n", - "vacantX+O=CCO<=>O=CCO.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 1291.5767888759226\n", - "Kc = 273.8002875141987\n", - "proton+O=CC(O)[Pt]<=>O=CCO.[Pt]\n", - "kf = 1.712472301799593e10\n", - "krev = 2.6335036754646568e-14\n", - "Kc = 6.5026387384762e23\n", - "proton+OCC#[Pt]<=>OCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.6468663797080987e-6\n", - "Kc = 6.855200437039605e15\n", - "proton+OCC=[Pt]<=>CHX+CO-2\n", - "kf = 2.437334851076409e7\n", - "krev = 3.684139726492616e-11\n", - "Kc = 6.615750302708541e17\n", - "vacantX+vacantX+O=CCO<=>OX+OCC=[Pt]\n", - "kf = 3.3881471741726223e-34\n", - "krev = 2.264159139077055e16\n", - "Kc = 1.4964262518904662e-50\n", - "vacantX+vacantX+O=C=CCO<=>OCX+OCC=[Pt]\n", - "kf = 1.8009876630720204e-13\n", - "krev = 6.668943472119082e14\n", - "Kc = 2.7005591974222413e-28\n", - "vacantX+vacantX+C=CC=O<=>CH2X+O=CC=[Pt]\n", - "kf = 3.2830355290077765e-39\n", - "krev = 2.9277080237249806e14\n", - "Kc = 1.121367124864694e-53\n", - "vacantX+vacantX+C=COC=O<=>CH2X+O=COC=[Pt]\n", - "kf = 1.0242943870290668e-63\n", - "krev = 2.920849603333263e13\n", - "Kc = 3.5068371403311754e-77\n", - "vacantX+O=C=CCO<=>O=C=CCO.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 1179.037991138623\n", - "Kc = 273.8002884035305\n", - "vacantX+vacantX+O=CC=CO<=>OC=[Pt]+O=CC=[Pt]\n", - "kf = 6.284377773759944e-35\n", - "krev = 2.1623088290446475e12\n", - "Kc = 2.90632757418676e-47\n", - "vacantX+vacantX+COC<=>CH3X+CO[Pt]\n", - "kf = 3.3416169046706564e-11\n", - "krev = 3.110510590664853e12\n", - "Kc = 1.0742985137872191e-23\n", - "proton+O=C=CC(O)[Pt]<=>OC=[Pt]+C=C=O\n", - "kf = 7.886335155622577e-9\n", - "krev = 1.1676117437495351e-7\n", - "Kc = 0.0675424446340125\n", - "HX+O=C=CC=O<=>O=C=CC(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 3.0624966294759025e-24\n", - "Kc = 8.467340919226885e15\n", - "proton+O=C=CC=O.[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 5.4417257022505686e7\n", - "krev = 1.0699402207865258e-10\n", - "Kc = 5.086009102686402e17\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=CC(O)[Pt]\n", - "kf = 2.2665619116480148e-11\n", - "krev = 0.03466826587817799\n", - "Kc = 6.537857761944495e-10\n", - "proton+O=C=CC(O)[Pt]<=>O=C=CCO.[Pt]\n", - "kf = 1.693513701515947e9\n", - "krev = 6.001577582317764e-11\n", - "Kc = 2.8217809039168078e19\n", - "proton+O=C=CC=[Pt]<=>CHX+C=C=O\n", - "kf = 181.35768264661723\n", - "krev = 8.307531938850336e-7\n", - "Kc = 2.183051283841528e8\n", - "proton+O=C=CC#[Pt]<=>O=C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.768026569342988e-11\n", - "Kc = 1.4140058997693788e21\n", - "vacantX+vacantX+O=C=CC=O<=>OX+O=C=CC=[Pt]\n", - "kf = 3.709849833927781e-21\n", - "krev = 2.4389911159903437e17\n", - "Kc = 1.5210591828750508e-38\n", - "proton+O=C=CC(O)[Pt]<=>H2O+O=C=CC=[Pt]\n", - "kf = 4.694863820330143\n", - "krev = 3.9520471176425216e-5\n", - "Kc = 118795.74510565875\n", - "vacantX+vacantX+CCO<=>CH3X+OC[Pt]\n", - "kf = 1.5510087911871897e-15\n", - "krev = 9.749013808701775e13\n", - "Kc = 1.5909391674086975e-29\n", - "proton+O=C=C([Pt])CO<=>CO-2+O=C=C=[Pt]\n", - "kf = 259142.28390262663\n", - "krev = 5.010713983419634e-21\n", - "Kc = 5.171763640074528e25\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=C([Pt])CO\n", - "kf = 4.040764431615523e-20\n", - "krev = 30.812673220085827\n", - "Kc = 1.3113969056672023e-21\n", - "proton+O=C=C([Pt])CO<=>O=C=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.777114479215893e-21\n", - "Kc = 1.4067748753603438e31\n", - "proton+O=C=CC[Pt]<=>CH2X+C=C=O\n", - "kf = 6.0148104045883e-8\n", - "krev = 8.74545093406659e-6\n", - "Kc = 0.006877644674854341\n", - "vacantX+vacantX+O=C=CCO<=>HOX+O=C=CC[Pt]\n", - "kf = 8.032715739528718e-6\n", - "krev = 4.997427676480693e14\n", - "Kc = 1.6073700830795308e-20\n", - "proton+O=C=CC=[Pt]<=>O=C=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.1155543114237032e-25\n", - "Kc = 1.1817233840324226e35\n", - "vacantX+vacantX+CC(O)O<=>CH3X+OC(O)[Pt]\n", - "kf = 1.0212279299691738e-21\n", - "krev = 4.839386960246169e15\n", - "Kc = 2.1102423475497943e-37\n", - "proton+O=C=CC(O)=[Pt]<=>OC#[Pt]+C=C=O\n", - "kf = 1.5097720767202745e6\n", - "krev = 3.361950781834918e-17\n", - "Kc = 4.490761985207459e22\n", - "proton+O=C=CC(O)=[Pt]<=>H2O+O=C=CC#[Pt]\n", - "kf = 5.803789817126122e6\n", - "krev = 2.7232165859221153e-28\n", - "Kc = 2.1312259359498893e34\n", - "proton+O=C=CC(=O)[Pt]<=>O=C=CC(O)=[Pt]\n", - "kf = 0.6530550593549805\n", - "krev = 1.0085447542339824e12\n", - "Kc = 6.475221417923034e-13\n", - "proton+O=C=CC(O)=[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.85508059604632e-41\n", - "Kc = 2.5367626125786886e50\n", - "C=O+O=C=C[Pt]<=>O=C=CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 80798.59947863563\n", - "Kc = 4.901904683810505e-13\n", - "HX+O=C=CC=O<=>O=C=CCO[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 2.019947796444839e-5\n", - "Kc = 0.0012837560986177624\n", - "proton+O=C=CC=O.[Pt]<=>O=C=CCO[Pt]\n", - "kf = 278.5863350248319\n", - "krev = 3612.827309769227\n", - "Kc = 0.07711033800910536\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=CCO[Pt]\n", - "kf = 7.342900678318069e-26\n", - "krev = 740.7927312780465\n", - "Kc = 9.912220204496055e-29\n", - "proton+O=C=CCO[Pt]<=>O=C=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3432355963676785e-28\n", - "Kc = 1.861177597407629e38\n", - "vacantX+vacantX+CCOC=O<=>CH3X+O=COC[Pt]\n", - "kf = 1.714178070740009e-17\n", - "krev = 1.2983121019578911e14\n", - "Kc = 1.3203127877765141e-31\n", - "proton+O=CC([Pt])C=O<=>C=O+O=CC=[Pt]\n", - "kf = 1.0131844482393167e-10\n", - "krev = 2.9534786470384583e-7\n", - "Kc = 0.00034304783251277847\n", - "HX+O=C=CC=O<=>O=CC([Pt])C=O\n", - "kf = 2.5931203025755725e-8\n", - "krev = 5.183135272095574e-24\n", - "Kc = 5.002995612590211e15\n", - "proton+O=C=CC=O.[Pt]<=>O=CC([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 8.319166178505196e-8\n", - "Kc = 3.005108861101275e17\n", - "vacantX+vacantX+O=CCC=O<=>HX+O=CC([Pt])C=O\n", - "kf = 6.269624738894468e-15\n", - "krev = 24.522149705338403\n", - "Kc = 2.556719053684591e-16\n", - "proton+O=CC(=[Pt])C=O<=>C=O+O=CC#[Pt]\n", - "kf = 0.04202179791424184\n", - "krev = 2.102387409121332e-9\n", - "Kc = 1.9987656761987723e7\n", - "proton+O=C=C([Pt])C=O<=>O=CC(=[Pt])C=O\n", - "kf = 2.5e10\n", - "krev = 5.057292696382588\n", - "Kc = 4.943356357025204e9\n", - "proton+O=CC(=[Pt])C=O<=>O=CC([Pt])C=O\n", - "kf = 2.5e10\n", - "krev = 5.3866690937421086e-24\n", - "Kc = 4.641087017771969e33\n", - "vacantX+vacantX+COCC=O<=>CH3X+O=CCO[Pt]\n", - "kf = 1.7650043109029407e-12\n", - "krev = 1.4735149295451475e13\n", - "Kc = 1.1978190892492496e-25\n", - "vacantX+vacantX+COCC=O<=>CO[Pt]+O=CC[Pt]\n", - "kf = 10.947009513309483\n", - "krev = 5.112987413682155e11\n", - "Kc = 2.1410202348661592e-11\n", - "proton+O=CCC(=O)[Pt]<=>O=CCC=O.[Pt]\n", - "kf = 2.1814901321970692e8\n", - "krev = 5.7550523540318155e-8\n", - "Kc = 3.7905652251256815e15\n", - "vacantX+O=CCC=O<=>O=CCC=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 165389.8266532618\n", - "Kc = 1.951879075907524\n", - "proton+O=CC([Pt])C=O<=>O=CCC=O.[Pt]\n", - "kf = 1.6062704929440186e10\n", - "krev = 3.122654421781107e-14\n", - "Kc = 5.1439265316711864e23\n", - "proton+O=CCC#[Pt]<=>O=CCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.03648176110191e-17\n", - "Kc = 4.141485220927174e26\n", - "proton+O=CCC=[Pt]<=>CHX+CC=O\n", - "kf = 1.0605779567215914e7\n", - "krev = 5.748508015003e-13\n", - "Kc = 1.8449621257439228e19\n", - "vacantX+vacantX+O=CCC=O<=>OX+O=CCC=[Pt]\n", - "kf = 1.2771337705277995e-31\n", - "krev = 6.599290845791489e16\n", - "Kc = 1.935259106426951e-48\n", - "vacantX+vacantX+CCOO<=>CH3X+OOC[Pt]\n", - "kf = 1.1728434846364774e-18\n", - "krev = 2.6840450809869076e16\n", - "Kc = 4.3696862356918e-35\n", - "proton+OOCC#[Pt]<=>CX+COO\n", - "kf = 0.24698833297799483\n", - "krev = 0.0004336424509567548\n", - "Kc = 569.5667765760919\n", - "vacantX+vacantX+C=C=O<=>OX+C=C=[Pt]\n", - "kf = 5.2796000958546504e-37\n", - "krev = 1.4614931014553018e17\n", - "Kc = 3.612470076387919e-54\n", - "proton+C=C=[Pt]<=>CC#[Pt]\n", - "kf = 10.738937415423795\n", - "krev = 4.122167482176662e-33\n", - "Kc = 2.60516766042539e33\n", - "vacantX+vacantX+CC(C)=O<=>CH3X+CC(=O)[Pt]\n", - "kf = 0.0015322757193851075\n", - "krev = 1.9084257758101816e14\n", - "Kc = 8.029003479239911e-18\n", - "vacantX+vacantX+C=C=C=O<=>CH2X+O=C=C=[Pt]\n", - "kf = 0.014873013888318402\n", - "krev = 6.520037160662236e15\n", - "Kc = 2.2811240981957472e-18\n", - "HOX+C=C=C=O<=>O=C=C([Pt])CO\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.9529365102554657e-31\n", - "Kc = 9.99708792916859e22\n", - "HX+C=C=C=O<=>O=C=CC[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.4091973858076736e-32\n", - "Kc = 1.225336127134283e24\n", - "vacantX+vacantX+C=C=C=O<=>OCX+C=C=[Pt]\n", - "kf = 0.8504584217531632\n", - "krev = 1.347597642765549e15\n", - "Kc = 6.310922450174717e-16\n", - "proton+O=C(O)C=[Pt]<=>CHX+O=CO\n", - "kf = 7.88145235948431e7\n", - "krev = 1.995696153847229e-7\n", - "Kc = 3.949224607308452e14\n", - "proton+O=C(O)C#[Pt]<=>O=C(O)C=[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.424855572557093e-13\n", - "Kc = 3.3670688615684534e22\n", - "vacantX+vacantX+CC=C=O<=>CH3X+O=C=C[Pt]\n", - "kf = 0.0008567749561878586\n", - "krev = 1.2359860589695025e13\n", - "Kc = 6.931914401220598e-17\n", - "vacantX+vacantX+CC=C=O<=>HX+O=C=CC[Pt]\n", - "kf = 2.2773385768535307e-19\n", - "krev = 181.8091471864856\n", - "Kc = 1.2525984594810374e-21\n", - "proton+O=C=CCO[Pt]<=>OX+CC=C=O\n", - "kf = 3.801213612232799e6\n", - "krev = 3.4005935521726275e-15\n", - "Kc = 1.1178088630451637e21\n", - "proton+CC(=O)[Pt]<=>CC=O.[Pt]\n", - "kf = 2.2108223076011086e9\n", - "krev = 2.493722128340101e-11\n", - "Kc = 8.865551949337277e19\n", - "proton+O=CC[Pt]<=>CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0175396707648368e-24\n", - "Kc = 2.456906665978799e34\n", - "vacantX+CC=O<=>CC=O.[Pt]\n", - "kf = 412885.969273148\n", - "krev = 2.625517699834265\n", - "Kc = 157258.8786200951\n", - "proton+CC=[Pt]<=>CHX+CH4\n", - "kf = 3.754229088708618e7\n", - "krev = 3.193900280463504e-10\n", - "Kc = 1.1754371642948722e17\n", - "proton+CC#[Pt]<=>CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.101069134371629e-9\n", - "Kc = 3.086012424450092e18\n", - "vacantX+vacantX+CC=O<=>OX+CC=[Pt]\n", - "kf = 6.186864182993887e-31\n", - "krev = 2.034915252803989e19\n", - "Kc = 3.04035471475717e-50\n", - "vacantX+vacantX+CC=C=O<=>OCX+CC=[Pt]\n", - "kf = 5.619880038277716e-8\n", - "krev = 4.919193785592355e16\n", - "Kc = 1.14243924578405e-24\n", - "vacantX+vacantX+CC<=>CH3X+CH3X\n", - "kf = 1.6866972609475142e-22\n", - "krev = 6.547125244410207e13\n", - "Kc = 2.576241018739606e-36\n", - "proton+O=C=CC[Pt]<=>CC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.381078389100095e-19\n", - "Kc = 1.0499444333476355e29\n", - "vacantX+CC=C=O<=>CC=C=O.[Pt]\n", - "kf = 365995.57053717994\n", - "krev = 187509.1639624155\n", - "Kc = 1.9518809790573244\n", - "proton+O=C(O)C[Pt]<=>CH2X+O=CO\n", - "kf = 5.038535015011119e-9\n", - "krev = 7.877133180076684e-5\n", - "Kc = 6.396407042799381e-5\n", - "HOX+C=C=O<=>O=C(O)C[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.348252838458729e-29\n", - "Kc = 4.5553052781738184e20\n", - "vacantX+vacantX+CC(=O)O<=>HX+O=C(O)C[Pt]\n", - "kf = 1.1112170024966995e-23\n", - "krev = 36323.66987445037\n", - "Kc = 3.0592090676342045e-28\n", - "proton+O=C(O)C=[Pt]<=>O=C(O)C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0876086200539217e-33\n", - "Kc = 2.2986209872776243e43\n", - "vacantX+vacantX+O=C=C=CO<=>OC=[Pt]+O=C=C=[Pt]\n", - "kf = 0.004371453552681894\n", - "krev = 1.2572855491392857e13\n", - "Kc = 3.476897953431907e-16\n", - "HX+O=C=C=CO<=>O=C=CC(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.3635197599529065e-33\n", - "Kc = 1.9017841755847633e25\n", - "HX+O=C=C=CO<=>O=C=C([Pt])CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 6.797711819853139e-22\n", - "Kc = 3.814695843684052e13\n", - "proton+O=C(O)CC#[Pt]<=>CX+CC(=O)O\n", - "kf = 0.12574987603391333\n", - "krev = 9.921358720719502e-5\n", - "Kc = 1267.4662772882168\n", - "proton+CC([Pt])=C=O<=>CH4+O=C=C=[Pt]\n", - "kf = 49487.72961177987\n", - "krev = 1.2730900614037961e-24\n", - "Kc = 3.8872135689451003e28\n", - "HX+C=C=C=O<=>CC([Pt])=C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.301177455844525e-32\n", - "Kc = 1.2828548214436644e24\n", - "vacantX+vacantX+CC=C=O<=>HX+CC([Pt])=C=O\n", - "kf = 4.581183222917958e-20\n", - "krev = 34.93361388628861\n", - "Kc = 1.3113968791863429e-21\n", - "proton+CC([Pt])=C=O<=>CC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.492848961236613e-19\n", - "Kc = 1.0028686209532082e29\n", - "CH3X+O=C=C=O<=>CC(=C=O)O[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.951682102619952e-64\n", - "Kc = 1.9647454732667077e56\n", - "proton+CC(=C=O)O[Pt]<=>OX+CC=C=O\n", - "kf = 1.920567374031219e-6\n", - "krev = 5.0434729686975995e-5\n", - "Kc = 0.03808025513274787\n", - "vacantX+C=C<=>C=C.[Pt]\n", - "kf = 36.21750369826068\n", - "krev = 0.32335117013731834\n", - "Kc = 112.00671914340097\n", - "vacantX+vacantX+C=CO<=>HOX+C=C[Pt]\n", - "kf = 1.7018617233469498e-12\n", - "krev = 4.164837143763027e13\n", - "Kc = 4.086262354568991e-26\n", - "vacantX+vacantX+C=C<=>HX+C=C[Pt]\n", - "kf = 6.071347272542775e-23\n", - "krev = 1180.067101472276\n", - "Kc = 5.144916983930861e-26\n", - "vacantX+vacantX+C=CC=O<=>CHOX+C=C[Pt]\n", - "kf = 0.3274906030624493\n", - "krev = 2.9425898600264806e14\n", - "Kc = 1.1129332276687114e-15\n", - "vacantX+vacantX+C=COC=O<=>CHO2X+C=C[Pt]\n", - "kf = 0.2513917911405871\n", - "krev = 1.0405847657707406e16\n", - "Kc = 2.4158703779829617e-17\n", - "proton+C=C=[Pt]<=>C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.446578752089028e-33\n", - "Kc = 1.0218350820979533e43\n", - "proton+C=C[Pt]<=>CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 31.775139733809926\n", - "Kc = 7.867786014296917e8\n", - "proton+C=C[Pt]<=>C=C.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.7043133558442046e-25\n", - "Kc = 1.4668664019015827e35\n", - "proton+C=CC#[Pt]<=>CX+C=C\n", - "kf = 1.0856530221273585e-15\n", - "krev = 0.12983129718682296\n", - "Kc = 8.36202861444987e-15\n", - "vacantX+CC(=O)O<=>CC(=O)O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 181176.05501028927\n", - "Kc = 1.9518809818483447\n", - "proton+CC(=O)O[Pt]<=>CC(=O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.133892027559991e-24\n", - "Kc = 6.04756965913213e33\n", - "proton+O=C(O)C[Pt]<=>CC(=O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.815284645396005e-26\n", - "Kc = 4.2990157016290936e35\n", - "proton+C=CC(=O)[Pt]<=>OCX+C=C\n", - "kf = 7.087170621400232e6\n", - "krev = 2.9783308105065206e-7\n", - "Kc = 2.3795780496911715e13\n", - "vacantX+vacantX+C=CC=O<=>HX+C=CC(=O)[Pt]\n", - "kf = 3.052485738368744e-11\n", - "krev = 0.0007099643372969683\n", - "Kc = 4.29949164769375e-8\n", - "HX+C=C=C=O<=>C=CC(=O)[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 5.604440911093213e-48\n", - "Kc = 5.267388203494818e39\n", - "HX+O=C=CC=O<=>O=CC=CO[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 5.6159867257682645e-34\n", - "Kc = 4.61739037002591e25\n", - "proton+O=C=CC=O.[Pt]<=>O=CC=CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 9.013912308921113e-18\n", - "Kc = 2.7734904826239954e27\n", - "proton+O=CC=CO[Pt]<=>OX+C=CC=O\n", - "kf = 3.6615493516163485e-10\n", - "krev = 9.407550626549198e-5\n", - "Kc = 3.892138875429521e-6\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC=CO[Pt]\n", - "kf = 4.135805741920728e-10\n", - "krev = 0.028732529553568358\n", - "Kc = 1.4394158141245496e-8\n", - "HX+C=C=O<=>C=CO[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.272169613200064e-8\n", - "Kc = 0.46029640012283785\n", - "proton+C=C=O.[Pt]<=>C=CO[Pt]\n", - "kf = 2.7021695253394946e-5\n", - "krev = 3753.979595717479\n", - "Kc = 7.19814654406251e-9\n", - "vacantX+vacantX+C=CO<=>HX+C=CO[Pt]\n", - "kf = 1.5839272910037507e-20\n", - "krev = 3600.161649580889\n", - "Kc = 4.399600476795654e-24\n", - "proton+C=CO[Pt]<=>OX+C=C\n", - "kf = 6.694428008398142e6\n", - "krev = 4.294813980591457e-9\n", - "Kc = 1.5587236231070068e15\n", - "vacantX+vacantX+C=COC=O<=>CHOX+C=CO[Pt]\n", - "kf = 0.024290856013790354\n", - "krev = 3.5586883050271985e15\n", - "Kc = 6.825789148062155e-18\n", - "vacantX+vacantX+O=CCCO<=>OC[Pt]+O=CC[Pt]\n", - "kf = 2.162232232095232e-5\n", - "krev = 5.66671683371172e13\n", - "Kc = 3.815670158833332e-19\n", - "proton+C=COC(=O)[Pt]<=>OCX+C=CO\n", - "kf = 8.547694380469097e6\n", - "krev = 5.219823560516419e-10\n", - "Kc = 1.637544695020963e16\n", - "vacantX+vacantX+C=COC=O<=>HX+C=COC(=O)[Pt]\n", - "kf = 3.5117597357119104e-15\n", - "krev = 0.7837038908782975\n", - "Kc = 4.480977798612533e-15\n", - "CO2+C=C[Pt]<=>C=COC(=O)[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.08399332498323721\n", - "Kc = 7.789900440580834e-7\n", - "proton+C=COC#[Pt]<=>CX+C=CO\n", - "kf = 3.59319568894763e-23\n", - "krev = 3.7552909398960855e-5\n", - "Kc = 9.568355012853036e-19\n", - "vacantX+vacantX+CCC=O<=>CH3X+O=CC[Pt]\n", - "kf = 1.2257627381394946e-12\n", - "krev = 3.270257576074817e14\n", - "Kc = 3.748214657790771e-27\n", - "proton+CC(O)=[Pt]<=>OC#[Pt]+CH4\n", - "kf = 7.023325690411809e6\n", - "krev = 0.001122962882704699\n", - "Kc = 6.254281239906934e9\n", - "proton+CC(=O)[Pt]<=>CC(O)=[Pt]\n", - "kf = 9.881755573608883e9\n", - "krev = 1.0085447542339819e12\n", - "Kc = 0.009798033782957261\n", - "proton+CC(O)=[Pt]<=>H2O+CC#[Pt]\n", - "kf = 7.254296675241664e9\n", - "krev = 2.8720393080667615e-6\n", - "Kc = 2.5258347456688205e15\n", - "vacantX+vacantX+CC(=O)O<=>OX+CC(O)=[Pt]\n", - "kf = 1.1829749543892744e-33\n", - "krev = 3.758913107590896e15\n", - "Kc = 3.1471197139415875e-49\n", - "vacantX+vacantX+CC(O)=C=O<=>CH3X+O=C=C(O)[Pt]\n", - "kf = 1.049990631922765e-6\n", - "krev = 1.7955210884029898e15\n", - "Kc = 5.847832357439309e-22\n", - "vacantX+vacantX+CC(O)=C=O<=>HOX+CC([Pt])=C=O\n", - "kf = 0.0029164033711847528\n", - "krev = 3.4437539939134434e12\n", - "Kc = 8.468675103794464e-16\n", - "vacantX+vacantX+CC(O)=C=O<=>HX+CC(=C=O)O[Pt]\n", - "kf = 1.7528367761452354e-6\n", - "krev = 1.1970864565480504e-5\n", - "Kc = 0.14642524494009906\n", - "vacantX+vacantX+CC(O)=C=O<=>OCX+CC(O)=[Pt]\n", - "kf = 65.80946386077328\n", - "krev = 1217.699742052305\n", - "Kc = 0.054044081301896585\n", - "vacantX+vacantX+C=CC=O<=>HX+O=CC=C[Pt]\n", - "kf = 6.342176392543457e-21\n", - "krev = 776.2437464870187\n", - "Kc = 8.170341366672147e-24\n", - "vacantX+vacantX+O=CC=CO<=>HOX+O=CC=C[Pt]\n", - "kf = 4.672349699632388e-15\n", - "krev = 8.81363422062413e13\n", - "Kc = 5.301274800693419e-29\n", - "proton+O=CC=C[Pt]<=>O=CCC=[Pt]\n", - "kf = 1.2673656466904085e10\n", - "krev = 1.0824082827935274e8\n", - "Kc = 117.08757839689983\n", - "proton+C=CC(=O)O[Pt]<=>OX+C=CC=O\n", - "kf = 4.524546416801015\n", - "krev = 7.68227583414659e-9\n", - "Kc = 5.889591202505473e8\n", - "CO2+C=C[Pt]<=>C=CC(=O)O[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 450683.30306117237\n", - "Kc = 1.4517947189269602e-13\n", - "vacantX+vacantX+O=C=CO<=>OX+OC=C=[Pt]\n", - "kf = 7.548264554696059e-34\n", - "krev = 5.749061160710156e15\n", - "Kc = 1.3129560364189368e-49\n", - "proton+OC=C=[Pt]<=>OCC#[Pt]\n", - "kf = 0.00032547344886471076\n", - "krev = 1.1489507349403094e-46\n", - "Kc = 2.832788551909668e42\n", - "vacantX+vacantX+O=C=C=CO<=>OCX+OC=C=[Pt]\n", - "kf = 1.463392220587488e-22\n", - "krev = 7.968303762369095e13\n", - "Kc = 1.8365166090912173e-36\n", - "proton+CC[Pt]<=>CH2X+CH4\n", - "kf = 1.4846524062695914\n", - "krev = 9.859129077434927e-6\n", - "Kc = 150586.56749586415\n", - "HX+C=C<=>CC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 3.1627439012977165e-12\n", - "Kc = 25911.109388377805\n", - "vacantX+vacantX+CCO<=>HOX+CC[Pt]\n", - "kf = 2.1035625708276702e-15\n", - "krev = 1.0019023766861524e15\n", - "Kc = 2.099568400850909e-30\n", - "vacantX+vacantX+CCOC=O<=>CHO2X+CC[Pt]\n", - "kf = 0.08561452397466171\n", - "krev = 3.215769317238553e17\n", - "Kc = 2.6623341268826044e-19\n", - "vacantX+vacantX+CCOO<=>OO[Pt]+CC[Pt]\n", - "kf = 1.262172875849309e-6\n", - "krev = 1.5596341944506717e13\n", - "Kc = 8.092749443044025e-20\n", - "proton+CC=[Pt]<=>CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.602708332438123e-27\n", - "Kc = 2.9060615603731233e36\n", - "vacantX+vacantX+CC<=>HX+CC[Pt]\n", - "kf = 8.697106954471648e-14\n", - "krev = 5.359609736165605e16\n", - "Kc = 1.6227127314485718e-30\n", - "proton+C=C.[Pt]<=>CC[Pt]\n", - "kf = 5.504599623053448e9\n", - "krev = 0.3531497863658743\n", - "Kc = 1.558715263486103e10\n", - "vacantX+vacantX+CCC=O<=>CHOX+CC[Pt]\n", - "kf = 0.0004422945453165714\n", - "krev = 9.363325052982716e15\n", - "Kc = 4.723691026572629e-20\n", - "vacantX+vacantX+CC(O)C=O<=>CH3X+O=CC(O)[Pt]\n", - "kf = 9.477814531468979e-7\n", - "krev = 7.52142668687151e15\n", - "Kc = 1.2601086105129898e-22\n", - "proton+CCC#[Pt]<=>CX+CC\n", - "kf = 3.73018742862406e-11\n", - "krev = 0.075105066117345\n", - "Kc = 4.966625583946592e-10\n", - "C=O+CH3X<=>CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.1808191230067762e-17\n", - "Kc = 3.354171909251678e9\n", - "HX+CC=O<=>CCO[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 2.639709061724686e-6\n", - "Kc = 0.012387213631168494\n", - "vacantX+vacantX+CCO<=>HX+CCO[Pt]\n", - "kf = 5.372480262216755e-24\n", - "krev = 2113.809062877283\n", - "Kc = 2.5416109508508876e-27\n", - "vacantX+vacantX+CCOC=O<=>CHOX+CCO[Pt]\n", - "kf = 4.80530366959931e-5\n", - "krev = 5.681813674074216e13\n", - "Kc = 8.457341168235823e-19\n", - "vacantX+vacantX+CCOO<=>HOX+CCO[Pt]\n", - "kf = 3.028654941635431e8\n", - "krev = 1.2132864881112858e-12\n", - "Kc = 2.496240559268171e20\n", - "proton+CC=O.[Pt]<=>CCO[Pt]\n", - "kf = 19418.796323941955\n", - "krev = 3658.802750537776\n", - "Kc = 5.30741820424393\n", - "proton+CCO[Pt]<=>OX+CC\n", - "kf = 1.5180806810718186e7\n", - "krev = 3.4536717602694347e-12\n", - "Kc = 4.395555763392486e18\n", - "proton+CCOC(=O)[Pt]<=>OCX+CCO\n", - "kf = 1.100364657251968e9\n", - "krev = 4.5302115405928314e-10\n", - "Kc = 2.4289476272623954e18\n", - "vacantX+vacantX+CCOC=O<=>HX+CCOC(=O)[Pt]\n", - "kf = 2.5742212027881315e-15\n", - "krev = 0.39729482671494754\n", - "Kc = 6.479372570927264e-15\n", - "CO2+CC[Pt]<=>CCOC(=O)[Pt]\n", - "kf = 3.860701485876577e-7\n", - "krev = 0.0037771400241392917\n", - "Kc = 0.00010221229451921966\n", - "CH3X+C=C=O<=>CCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.9339597186194493e-34\n", - "Kc = 1.7308289628845924e26\n", - "HX+CC=C=O<=>CCC(=O)[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 2.728234417234893e-33\n", - "Kc = 1.0624138213938816e25\n", - "proton+CCC(=O)[Pt]<=>OCX+CC\n", - "kf = 3.3183098775357734e7\n", - "krev = 1.723115430616528e-10\n", - "Kc = 1.9257618024745373e17\n", - "proton+CC=C=O.[Pt]<=>CCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.816709270833084e-23\n", - "Kc = 3.667458740974689e32\n", - "vacantX+vacantX+CCC=O<=>HX+CCC(=O)[Pt]\n", - "kf = 1.3037608552158366e-12\n", - "krev = 0.18236199715464047\n", - "Kc = 7.149301255514685e-12\n", - "vacantX+vacantX+C=C(O)C=O<=>CH2X+O=CC(O)=[Pt]\n", - "kf = 3.506980389191063e-59\n", - "krev = 1.6121784785918364e12\n", - "Kc = 2.1753053001019147e-71\n", - "proton+CCOC#[Pt]<=>CX+CCO\n", - "kf = 1.6403573057503937e-22\n", - "krev = 1.0480859144262605e-13\n", - "Kc = 1.5650981309565184e-9\n", - "proton+CCC(=O)O[Pt]<=>OX+CCC=O\n", - "kf = 5.622114816602621e-8\n", - "krev = 4.785365563630673e-7\n", - "Kc = 0.11748558687619057\n", - "CO2+CC[Pt]<=>CCC(=O)O[Pt]\n", - "kf = 3.860701485876577e-7\n", - "krev = 2.2515045234693432e-8\n", - "Kc = 17.147207325738\n", - "vacantX+vacantX+OC=CCO<=>OC=[Pt]+OCC=[Pt]\n", - "kf = 3.6700973989487563e-44\n", - "krev = 3.0504263460080312e13\n", - "Kc = 1.203142440646588e-57\n", - "proton+CC(=C=O)O[Pt]<=>CC(O)=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 27.83415070046663\n", - "Kc = 8.981772165076653e8\n", - "vacantX+CC(O)=C=O<=>CC(O)=C=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 165389.73964983693\n", - "Kc = 1.9518801026953096\n", - "proton+OOC=[Pt]<=>OO+CHX\n", - "kf = 2.8719882764673755e7\n", - "krev = 8.077545633440945e-25\n", - "Kc = 3.555520955000709e31\n", - "proton+OOC=[Pt]<=>OOC[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.62255074484058e-37\n", - "Kc = 2.899374064566577e46\n", - "proton+OOC#[Pt]<=>OOC=[Pt]\n", - "kf = 3.432151727081939e-44\n", - "krev = 3342.777740155216\n", - "Kc = 1.0267364431242663e-47\n", - "vacantX+vacantX+C=CCO<=>CH2X+OCC=[Pt]\n", - "kf = 3.3256293066300124e-48\n", - "krev = 2.638642223210571e15\n", - "Kc = 1.2603562837645906e-63\n", - "vacantX+vacantX+C=CCO<=>OC[Pt]+C=C[Pt]\n", - "kf = 1.4930923415267688e-9\n", - "krev = 1.1121057711212152e14\n", - "Kc = 1.3425812366942817e-23\n", - "vacantX+OO<=>OO.[Pt]\n", - "kf = 469882.2241291155\n", - "krev = 15.560302693769444\n", - "Kc = 30197.498941795184\n", - "proton+OO[Pt]<=>OO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.110596489625074e-24\n", - "Kc = 2.251042591395165e34\n", - "C=O+CO[Pt]<=>COCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 9.545218685674386e-14\n", - "Kc = 414937.62088874576\n", - "HX+COC=O<=>COCO[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 0.02522938529859348\n", - "Kc = 1.1100614687459063e-6\n", - "vacantX+vacantX+COCO<=>HX+COCO[Pt]\n", - "kf = 1.0488506310161173e-19\n", - "krev = 521.1543106644776\n", - "Kc = 2.0125529225284944e-22\n", - "proton+COC=O.[Pt]<=>COCO[Pt]\n", - "kf = 0.6792883990466445\n", - "krev = 3726.123137157573\n", - "Kc = 0.00018230433457033608\n", - "proton+COCO[Pt]<=>OX+COC\n", - "kf = 5093.375621150868\n", - "krev = 5.977614318003391e-7\n", - "Kc = 8.520749834613165e9\n", - "CO[Pt]+C=C=O<=>COCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.680149232421768e-23\n", - "Kc = 1.9922953446306685e15\n", - "HX+COC=C=O<=>COCC(=O)[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 2.661991446097411e-38\n", - "Kc = 9.604054388173769e29\n", - "proton+COCC(=O)[Pt]<=>OCX+COC\n", - "kf = 8.734746675052269e7\n", - "krev = 2.1771371890779743e-8\n", - "Kc = 4.012033196103488e15\n", - "vacantX+vacantX+COCC=O<=>HX+COCC(=O)[Pt]\n", - "kf = 2.290241001822749e-10\n", - "krev = 0.0004872161822843353\n", - "Kc = 4.7006669423105973e-7\n", - "proton+COCOC#[Pt]<=>CX+COCO\n", - "kf = 3.2770328923262016e-17\n", - "krev = 2.1864147814239428e-13\n", - "Kc = 0.0001498815741719407\n", - "proton+COCC#[Pt]<=>CX+COC\n", - "kf = 1.433200340176918\n", - "krev = 0.00041586763423335837\n", - "Kc = 3446.289689792732\n", - "proton+COC[Pt]<=>CH2X+CO-2\n", - "kf = 0.2769010105768301\n", - "krev = 3.0099119392563808e-6\n", - "Kc = 91996.38267332179\n", - "vacantX+vacantX+COCO<=>HOX+COC[Pt]\n", - "kf = 8.90444501639475e-13\n", - "krev = 8.409201083164982e12\n", - "Kc = 1.0588931015362724e-25\n", - "C=O+CH3X<=>COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 8.422687202008296e-11\n", - "Kc = 470.23832623775377\n", - "vacantX+vacantX+COC<=>HX+COC[Pt]\n", - "kf = 2.786306429788959e-20\n", - "krev = 52.25975865319748\n", - "Kc = 5.3316481009398625e-22\n", - "vacantX+vacantX+COCC=O<=>CHOX+COC[Pt]\n", - "kf = 1.4060776479118306e6\n", - "krev = 6.613786245273692e13\n", - "Kc = 2.1259798786461146e-8\n", - "vacantX+vacantX+C=C=CO<=>OC=[Pt]+C=C=[Pt]\n", - "kf = 1.5975335437882445e-34\n", - "krev = 2.2957840869759923e8\n", - "Kc = 6.958553083676594e-43\n", - "vacantX+vacantX+C=C=CO<=>CH2X+OC=C=[Pt]\n", - "kf = 9.363402027600756e-56\n", - "krev = 7.047835211144391e9\n", - "Kc = 1.328550079149818e-65\n", - "vacantX+vacantX+COC=O<=>OX+COC=[Pt]\n", - "kf = 1.1797200153280936e-59\n", - "krev = 4.3408253155831816e16\n", - "Kc = 2.7177320660497494e-76\n", - "proton+COC=[Pt]<=>CHX+CO-2\n", - "kf = 479145.9852086257\n", - "krev = 1.0449825701778588e-33\n", - "Kc = 4.5852055228736854e38\n", - "proton+COC#[Pt]<=>COC=[Pt]\n", - "kf = 90933.51053402986\n", - "krev = 2739.427130274527\n", - "Kc = 33.194352764155155\n", - "vacantX+vacantX+COC=C=O<=>OCX+COC=[Pt]\n", - "kf = 2.7777170398864307e-21\n", - "krev = 2.5089215324603047e13\n", - "Kc = 1.107135876490541e-34\n", - "proton+COC=[Pt]<=>COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3472876439887766e-48\n", - "Kc = 1.8555799952254487e58\n", - "vacantX+COC=C=O<=>COC=C=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 1179.0380002145982\n", - "Kc = 273.8002862958761\n", - "proton+COC=C=O.[Pt]<=>COCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.0577777781824875e-25\n", - "Kc = 2.3634453772469967e35\n", - "vacantX+vacantX+C=C=C<=>CH2X+C=C=[Pt]\n", - "kf = 4.78083312177258e-41\n", - "krev = 4.774618642094983e15\n", - "Kc = 1.0013015656628172e-56\n", - "proton+O=C=COC[Pt]<=>CH2X+O=C=CO\n", - "kf = 4.988523456059943e-5\n", - "krev = 0.0009299241102698363\n", - "Kc = 0.05364441464596958\n", - "C=O+O=C=C[Pt]<=>O=C=COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.852140732586457e13\n", - "Kc = 2.1384283940268284e-21\n", - "vacantX+vacantX+COC=C=O<=>HX+O=C=COC[Pt]\n", - "kf = 3.256466928453685e-21\n", - "krev = 26.50445975246776\n", - "Kc = 1.2286486722863626e-22\n", - "proton+O=C=COC[Pt]<=>COC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.6649798034152577e-22\n", - "Kc = 1.5015197150571575e32\n", - "CH3X+O=C=C=O<=>COC([Pt])=C=O\n", - "kf = 5.799304049644909e-8\n", - "krev = 3.1615249923835833e-35\n", - "Kc = 1.8343375629216876e27\n", - "proton+COC([Pt])=C=O<=>CO-2+O=C=C=[Pt]\n", - "kf = 313658.31445379555\n", - "krev = 1.256306436150439e-34\n", - "Kc = 2.496670441448219e39\n", - "vacantX+vacantX+COC=C=O<=>HX+COC([Pt])=C=O\n", - "kf = 2.779636780044878e-20\n", - "krev = 3.601218910546807\n", - "Kc = 7.718599866018197e-21\n", - "proton+COC([Pt])=C=O<=>COC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0459713323621888e-20\n", - "Kc = 2.390122867281724e30\n", - "vacantX+vacantX+C=C=C(O)O<=>OC(O)=[Pt]+C=C=[Pt]\n", - "kf = 2.937512138355157e-45\n", - "krev = 8.778136400287878e10\n", - "Kc = 3.34639609639561e-56\n", - "proton+O=C=COC=[Pt]<=>CHX+O=C=CO\n", - "kf = 2.102599834403735e7\n", - "krev = 1.6989476123058672e-25\n", - "Kc = 1.237589563782969e32\n", - "proton+O=C=COC#[Pt]<=>O=C=COC=[Pt]\n", - "kf = 1080.8801129554665\n", - "krev = 2888.2699525834805\n", - "Kc = 0.37423098626520285\n", - "proton+O=C=COC=[Pt]<=>O=C=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.9106920181466426e-48\n", - "Kc = 8.589022763019266e57\n", - "proton+CCOO[Pt]<=>OX+CCO\n", - "kf = 169.16425212622386\n", - "krev = 5.6416707126946964e-58\n", - "Kc = 2.9984779463568512e59\n", - "vacantX+vacantX+CCOO<=>HX+CCOO[Pt]\n", - "kf = 1.893449523720139e-21\n", - "krev = 0.6694879211592951\n", - "Kc = 2.8282056537202555e-21\n", - "O=O+CC[Pt]<=>CCOO[Pt]\n", - "kf = 4.5276782379965965e-7\n", - "krev = 1.4949208469184493e-38\n", - "Kc = 3.0287076719344122e31\n", - "vacantX+vacantX+C=CC(=O)O<=>CH2X+O=C(O)C=[Pt]\n", - "kf = 4.72289540105198e-39\n", - "krev = 9.498795808374404e14\n", - "Kc = 4.9720990916429044e-54\n", - "vacantX+vacantX+C=CC(=O)O<=>CO2HX+C=C[Pt]\n", - "kf = 5.354197885861111e7\n", - "krev = 1.376967106369583e14\n", - "Kc = 3.888399266107105e-7\n", - "vacantX+vacantX+C=CC(=O)O<=>HOX+C=CC(=O)[Pt]\n", - "kf = 0.03947248649742643\n", - "krev = 2.5171232142616846e11\n", - "Kc = 1.5681586929785789e-13\n", - "vacantX+vacantX+C=CC(=O)O<=>HX+C=CC(=O)O[Pt]\n", - "kf = 2.4490000178339845e-20\n", - "krev = 458.0011375503109\n", - "Kc = 5.3471483300955e-23\n", - "proton+O=C=C=CO.[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.4322611471299928e-17\n", - "Kc = 1.7454917387164855e27\n", - "proton+O=C=C=CO.[Pt]<=>O=C=C([Pt])CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 7.140416160377535e-6\n", - "Kc = 3.5011964903006675e15\n", - "vacantX+O=C=C=CO<=>O=C=C=CO.[Pt]\n", - "kf = 327433.4917974331\n", - "krev = 0.4460204906723957\n", - "Kc = 734122.0832787583\n", - "HX+O=C=C=C=O<=>O=C=C=C(O)[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 1.3048903398306852e-5\n", - "Kc = 0.004032923533638046\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C=C(O)[Pt]\n", - "kf = 4235.342411204313\n", - "krev = 12.909334546967292\n", - "Kc = 328.0837130523738\n", - "proton+O=C=C=C(O)[Pt]<=>O=C=CC(O)=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1053.6449933824201\n", - "Kc = 2.3727156828928486e7\n", - "vacantX+vacantX+O=C=C=CO<=>HX+O=C=C=C(O)[Pt]\n", - "kf = 8.233814429551885e-18\n", - "krev = 0.5740049812746953\n", - "Kc = 1.434449995759099e-17\n", - "proton+O=C=C=C(O)[Pt]<=>O=C=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.249904355928212e-21\n", - "Kc = 3.4483213533096645e30\n", - "vacantX+vacantX+CC=CO<=>OC=[Pt]+CC=[Pt]\n", - "kf = 1.6816353348966163e-33\n", - "krev = 8.021148128032321e14\n", - "Kc = 2.0965020319468163e-48\n", - "proton+O=C=C=C[Pt]<=>O=C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.0269882986128818\n", - "Kc = 9.263273820479827e11\n", - "vacantX+vacantX+C=C=C=O<=>HX+O=C=C=C[Pt]\n", - "kf = 3.6772489817592154e-10\n", - "krev = 0.00723599763490509\n", - "Kc = 5.081882509221477e-8\n", - "vacantX+vacantX+O=C=C=CO<=>HOX+O=C=C=C[Pt]\n", - "kf = 0.00020826365169953766\n", - "krev = 1.0739954827079557e13\n", - "Kc = 1.939148302322696e-17\n", - "vacantX+OC=CO<=>OC=CO.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.48171019889246675\n", - "Kc = 734122.0861712244\n", - "vacantX+vacantX+C=CC<=>CH2X+CC=[Pt]\n", - "kf = 3.8695500910369183e-44\n", - "krev = 2.1644248520711738e17\n", - "Kc = 1.787795999169979e-61\n", - "vacantX+vacantX+C=CC<=>CH3X+C=C[Pt]\n", - "kf = 1.1726078415532691e-17\n", - "krev = 1.59532697721828e15\n", - "Kc = 7.350266486422159e-33\n", - "HX+O=C=CO<=>OC=C(O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 2.762063581333058e-24\n", - "Kc = 1.0314187634521844e16\n", - "vacantX+vacantX+OC=CO<=>HX+OC=C(O)[Pt]\n", - "kf = 6.089904416870865e-20\n", - "krev = 3.928023437111271\n", - "Kc = 1.550373747604081e-20\n", - "proton+O=C=CO.[Pt]<=>OC=C(O)[Pt]\n", - "kf = 6.4368819183992445e7\n", - "krev = 6.799608634080986e-11\n", - "Kc = 9.466547657075904e17\n", - "proton+OC=C(O)[Pt]<=>H2O+OC=C=[Pt]\n", - "kf = 5.262467142275111e-7\n", - "krev = 0.6251329939834178\n", - "Kc = 8.418156125054411e-7\n", - "proton+OC=C(O)[Pt]<=>OC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.835798651062412e-24\n", - "Kc = 3.190485247679302e33\n", - "vacantX+vacantX+OC=CO<=>HOX+OC=C[Pt]\n", - "kf = 1.882970379851619e-8\n", - "krev = 6.2613640604613945e13\n", - "Kc = 3.0072846134950095e-22\n", - "vacantX+vacantX+C=CO<=>HX+OC=C[Pt]\n", - "kf = 5.986889507133711e-22\n", - "krev = 1492.047811549125\n", - "Kc = 4.0125319448830507e-25\n", - "proton+OC=C[Pt]<=>OCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.693803965028289e7\n", - "Kc = 1475.967733939179\n", - "vacantX+vacantX+O=CC=CO<=>CHOX+OC=C[Pt]\n", - "kf = 3.6404040231768274e-5\n", - "krev = 5.1339082800935775e14\n", - "Kc = 7.090901949480236e-20\n", - "proton+OC=C=[Pt]<=>OC=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.9001266800545872e-45\n", - "Kc = 1.3157017509633512e55\n", - "vacantX+vacantX+OC=CCO<=>OC[Pt]+OC=C[Pt]\n", - "kf = 1.39754480380523e-13\n", - "krev = 4.435737343310229e14\n", - "Kc = 3.1506482364492156e-28\n", - "vacantX+vacantX+CC=CO<=>CH3X+OC=C[Pt]\n", - "kf = 3.0518560755450534e-15\n", - "krev = 1.440283576497463e15\n", - "Kc = 2.1189272205454667e-30\n", - "vacantX+vacantX+CC=C(O)O<=>OC(O)=[Pt]+CC=[Pt]\n", - "kf = 3.314404876424973e-50\n", - "krev = 3.298291971460818e17\n", - "Kc = 1.0048852269912959e-67\n", - "HX+O=C=CO<=>OC=CO[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 5.830973747204281e-42\n", - "Kc = 4.885709192226705e33\n", - "vacantX+vacantX+OC=CO<=>HX+OC=CO[Pt]\n", - "kf = 6.3392542923960805e-6\n", - "krev = 0.0008631955285686626\n", - "Kc = 0.007343937824733329\n", - "proton+O=C=CO.[Pt]<=>OC=CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.575140256117379e-26\n", - "Kc = 4.4841921192150256e35\n", - "proton+OC=CO[Pt]<=>OX+C=CO\n", - "kf = 2.262727495050209e-8\n", - "krev = 2.5678564004292932e-5\n", - "Kc = 0.0008811736881672694\n", - "proton+OC=CO[Pt]<=>OC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.711725523568878e-6\n", - "Kc = 6.73541182968781e15\n", - "proton+OC=COC#[Pt]<=>CX+OC=CO\n", - "kf = 2.2492341197526439e-29\n", - "krev = 0.00020529518482061674\n", - "Kc = 1.0956097785332785e-25\n", - "vacantX+vacantX+CCC(=O)O<=>CH3X+O=C(O)C[Pt]\n", - "kf = 8.997747599742267e-17\n", - "krev = 6.572577910715489e15\n", - "Kc = 1.368983026442782e-32\n", - "vacantX+vacantX+CCC(=O)O<=>CO2HX+CC[Pt]\n", - "kf = 3.388822996448631e-6\n", - "krev = 1.0293603282987281e15\n", - "Kc = 3.292163981148853e-21\n", - "vacantX+vacantX+CCC(=O)O<=>HOX+CCC(=O)[Pt]\n", - "kf = 2.1491486919570496e-14\n", - "krev = 4.131728096070369e12\n", - "Kc = 5.201573390081201e-27\n", - "vacantX+vacantX+CCC(=O)O<=>HX+CCC(=O)O[Pt]\n", - "kf = 2.415446383235281e-20\n", - "krev = 451.7273406124814\n", - "Kc = 5.347133472063615e-23\n", - "proton+O=C([Pt])C=CO<=>OCX+C=CO\n", - "kf = 224.18396606543615\n", - "krev = 8.215700647740584e-7\n", - "Kc = 2.728726078001508e8\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=C([Pt])C=CO\n", - "kf = 2.859565189776071e-11\n", - "krev = 0.000933578065584948\n", - "Kc = 3.06301668300697e-8\n", - "HX+O=C=C=CO<=>O=C([Pt])C=CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.1750295723598082e-43\n", - "Kc = 2.206855353748942e35\n", - "proton+O=C=C=CO.[Pt]<=>O=C([Pt])C=CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.234268290529092e-27\n", - "Kc = 2.0254915557527025e37\n", - "proton+OC=C(O)C#[Pt]<=>CX+OC=CO\n", - "kf = 2.8680661830740045e-24\n", - "krev = 729.307267106125\n", - "Kc = 3.932589612680575e-27\n", - "vacantX+vacantX+C=COO<=>OO[Pt]+C=C[Pt]\n", - "kf = 0.00256837059370255\n", - "krev = 1.2695573429161084e13\n", - "Kc = 2.0230441799526235e-16\n", - "vacantX+vacantX+C=COO<=>HOX+C=CO[Pt]\n", - "kf = 3.07907263663438e8\n", - "krev = 5.547742278067932e-15\n", - "Kc = 5.5501364019864025e22\n", - "vacantX+vacantX+C=COO<=>CH2X+OOC=[Pt]\n", - "kf = 7.483948884590266e-53\n", - "krev = 2.8103204909201245e17\n", - "Kc = 2.6630232775123643e-70\n", - "proton+OC=CC#[Pt]<=>CX+C=CO\n", - "kf = 1.0593841984272302e-19\n", - "krev = 13.369077699035607\n", - "Kc = 7.924138241066921e-21\n", - "proton+OCC[Pt]<=>CH2X+CO-2\n", - "kf = 3.9799160772985795e-6\n", - "krev = 0.00035437522440524626\n", - "Kc = 0.011230796633647675\n", - "vacantX+vacantX+OCCO<=>HOX+OCC[Pt]\n", - "kf = 2.110093084979835e-12\n", - "krev = 2.4085316622580622e14\n", - "Kc = 8.760910716040024e-27\n", - "HX+C=CO<=>OCC[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 1.1429411507382647e-15\n", - "Kc = 2.8609207088741057e7\n", - "HOX+C=C<=>OCC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 2.2750559854988554e-15\n", - "Kc = 3.602118089238167e7\n", - "proton+OCC=[Pt]<=>OCC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.1399343496076094e-34\n", - "Kc = 2.1931087530264836e44\n", - "vacantX+vacantX+CCO<=>HX+OCC[Pt]\n", - "kf = 4.51610258482867e-23\n", - "krev = 15472.547765874588\n", - "Kc = 2.918784063985339e-27\n", - "vacantX+vacantX+O=CCCO<=>CHOX+OCC[Pt]\n", - "kf = 2.0496526220764064\n", - "krev = 1.4633869198921762e15\n", - "Kc = 1.4006224835106677e-15\n", - "HX+C#C<=>C=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 2.375601900047824e-24\n", - "Kc = 3.580716650609497e16\n", - "CHOX+C#C<=>O=CC=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 3.2359557228060194e-16\n", - "Kc = 2.6287001452988416e8\n", - "HOX+C#C<=>OC=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 2.419253665005007e-25\n", - "Kc = 3.516108046777805e17\n", - "proton+OCCC#[Pt]<=>CX+CCO\n", - "kf = 0.036583470766554806\n", - "krev = 0.0005754138836916786\n", - "Kc = 63.577664361948486\n", - "OC[Pt]+C=C=O<=>O=C([Pt])CCO\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.869121889511259e-30\n", - "Kc = 1.7908695590280368e22\n", - "HX+O=C=CCO<=>O=C([Pt])CCO\n", - "kf = 2.5565910629172877e-8\n", - "krev = 3.7973012083800085e-37\n", - "Kc = 6.732652804247709e28\n", - "proton+O=C=CCO.[Pt]<=>O=C([Pt])CCO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.5089082544191712e-24\n", - "Kc = 1.6568270421201532e34\n", - "proton+O=C([Pt])CCO<=>OCX+CCO\n", - "kf = 9.600816617542319e7\n", - "krev = 3.185535798116408e-7\n", - "Kc = 3.0138781121904944e14\n", - "vacantX+vacantX+O=CCCO<=>HX+O=C([Pt])CCO\n", - "kf = 4.786286134347495e-11\n", - "krev = 0.0006355926831038164\n", - "Kc = 7.530429883135883e-8\n", - "vacantX+vacantX+C=COC<=>CO[Pt]+C=C[Pt]\n", - "kf = 1.9108708710628152e-14\n", - "krev = 5.750545812867103e12\n", - "Kc = 3.322938262290088e-27\n", - "vacantX+vacantX+C=COC<=>CH3X+C=CO[Pt]\n", - "kf = 8.809048609670953e-10\n", - "krev = 5.30334818480063e15\n", - "Kc = 1.6610353125441853e-25\n", - "vacantX+vacantX+C=COC<=>CH2X+COC=[Pt]\n", - "kf = 2.00333233616492e-67\n", - "krev = 2.0086736136424638e14\n", - "Kc = 9.973408932933319e-82\n", - "C=O+OC[Pt]<=>OCCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.726586049973397e-6\n", - "Kc = 0.00837955829095468\n", - "HX+O=CCO<=>OCCO[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 7.096612291679358e-6\n", - "Kc = 0.003946413774492056\n", - "vacantX+vacantX+OCCO<=>HX+OCCO[Pt]\n", - "kf = 1.0265256602604584e-26\n", - "krev = 112849.3186381155\n", - "Kc = 9.09642763154215e-32\n", - "proton+O=CCO.[Pt]<=>OCCO[Pt]\n", - "kf = 3.478307222117794e6\n", - "krev = 3581.5775849412535\n", - "Kc = 971.1662360023528\n", - "proton+OCCO[Pt]<=>OX+CCO\n", - "kf = 951266.6788585404\n", - "krev = 3.3388075163598663e-18\n", - "Kc = 2.8491210535420697e23\n", - "proton+OCCOC#[Pt]<=>CX+OCCO\n", - "kf = 6.336022152476698e-22\n", - "krev = 5.125095889500872e-13\n", - "Kc = 1.2362738744959868e-9\n", - "vacantX+vacantX+C=CC(O)O<=>OC(O)[Pt]+C=C[Pt]\n", - "kf = 1.3588265576828814e-16\n", - "krev = 6.093754170226661e16\n", - "Kc = 2.2298676968656565e-33\n", - "proton+O=C=C=C=[Pt]<=>O=C=CC#[Pt]\n", - "kf = 8.597534639917141e-9\n", - "krev = 2.1202950562509243e-60\n", - "Kc = 4.0548765204023916e51\n", - "vacantX+vacantX+O=C=C=C=O<=>OX+O=C=C=C=[Pt]\n", - "kf = 6.451439297868635e-57\n", - "krev = 8.482832416110645e14\n", - "Kc = 7.60528910793525e-72\n", - "proton+O=C=C=C(O)[Pt]<=>H2O+O=C=C=C=[Pt]\n", - "kf = 1.6149902683641734e-11\n", - "krev = 0.12950076972214764\n", - "Kc = 1.2470893198775887e-10\n", - "proton+O=C=C=C=[Pt]<=>O=C=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.039016761990757e-51\n", - "Kc = 6.189625216528679e60\n", - "vacantX+C=CO<=>C=CO.[Pt]\n", - "kf = 412885.969273148\n", - "krev = 1.1342794009872417\n", - "Kc = 364007.288604364\n", - "proton+C=CO[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.484544240591893e-27\n", - "Kc = 5.574702502366298e36\n", - "proton+OC=C[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.090002516938126e-28\n", - "Kc = 6.112465676112982e37\n", - "proton+C=CO.[Pt]<=>OCC[Pt]\n", - "kf = 1.7684909297990441e9\n", - "krev = 0.3339506079512917\n", - "Kc = 5.295666148501179e9\n", - "vacantX+vacantX+C=COCO<=>OCO[Pt]+C=C[Pt]\n", - "kf = 1.4197397308458187e-12\n", - "krev = 3.0290185667479297e13\n", - "Kc = 4.6871278586123213e-26\n", - "vacantX+vacantX+C=COCO<=>OC[Pt]+C=CO[Pt]\n", - "kf = 1.0263854075463885e-7\n", - "krev = 1.9545487277553856e14\n", - "Kc = 5.251265384031101e-22\n", - "HX+C=C=O<=>C=C(O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 3.2362559658776053e-12\n", - "Kc = 10343.290300064218\n", - "proton+C=C=O.[Pt]<=>C=C(O)[Pt]\n", - "kf = 0.5863133386822127\n", - "krev = 3624.832599039063\n", - "Kc = 0.00016174908017480404\n", - "vacantX+vacantX+C=CO<=>HX+C=C(O)[Pt]\n", - "kf = 4.00965787691315e-19\n", - "krev = 4.055766485027893\n", - "Kc = 9.886313454472895e-20\n", - "vacantX+vacantX+C=C(O)O<=>HOX+C=C(O)[Pt]\n", - "kf = 3.9452234947489745e-7\n", - "krev = 1.361002505571871e12\n", - "Kc = 2.8987628447394044e-19\n", - "proton+C=C(O)[Pt]<=>H2O+C=C=[Pt]\n", - "kf = 0.1408093188614318\n", - "krev = 0.006096548509334685\n", - "Kc = 23.09656334987455\n", - "proton+C=C(O)[Pt]<=>CC(O)=[Pt]\n", - "kf = 1.124057689749841e8\n", - "krev = 4.718570974473911e-12\n", - "Kc = 2.382199390092179e19\n", - "vacantX+vacantX+C=C(O)C=O<=>CHOX+C=C(O)[Pt]\n", - "kf = 2.8052009086647103\n", - "krev = 2.294429327232502e13\n", - "Kc = 1.2226137782366527e-13\n", - "proton+C=C(O)[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0077190030498644e-22\n", - "Kc = 2.4808503088993487e32\n", - "HOX+C=C=O<=>C=C(O)O[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.6625343699967689e-31\n", - "Kc = 2.0134040862236038e23\n", - "proton+C=C(O)O[Pt]<=>OX+C=CO\n", - "kf = 7.621772041144703e-10\n", - "krev = 0.16987445654378072\n", - "Kc = 4.4867087119601115e-9\n", - "vacantX+vacantX+C=C(O)O<=>HX+C=C(O)O[Pt]\n", - "kf = 8.7276566297004e-6\n", - "krev = 1.546723677424112e-6\n", - "Kc = 5.6426734503963205\n", - "vacantX+vacantX+C=CCOO<=>OOC[Pt]+C=C[Pt]\n", - "kf = 2.5331825038162864e-12\n", - "krev = 1.769892843246248e17\n", - "Kc = 1.4312632052740838e-29\n", - "proton+C=C(O)OC#[Pt]<=>CX+C=C(O)O\n", - "kf = 1.0744261387122509e-22\n", - "krev = 181.85749301564874\n", - "Kc = 5.908066370516815e-25\n", - "proton+C=C(O)C#[Pt]<=>CX+C=CO\n", - "kf = 3.691417083839596e-20\n", - "krev = 61.67110810051338\n", - "Kc = 5.985650651555046e-22\n", - "vacantX+vacantX+C=COOC<=>COO[Pt]+C=C[Pt]\n", - "kf = 0.0009962735751002543\n", - "krev = 4.495422962203487e13\n", - "Kc = 2.21619541359445e-17\n", - "vacantX+vacantX+C=COOC<=>CO[Pt]+C=CO[Pt]\n", - "kf = 2.772273774659678e8\n", - "krev = 3.7705323383409334e-17\n", - "Kc = 7.352473141443741e24\n", - "proton+C=C(O)C(=O)[Pt]<=>OCX+C=CO\n", - "kf = 985.1540455146012\n", - "krev = 5.159085449148215e-7\n", - "Kc = 1.9095517126533618e9\n", - "HOX+C=C=C=O<=>C=C(O)C(=O)[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 3.5720015577500406e-52\n", - "Kc = 8.264488540948707e43\n", - "vacantX+vacantX+C=C(O)C=O<=>HX+C=C(O)C(=O)[Pt]\n", - "kf = 2.8595651897765786e-11\n", - "krev = 0.000933577098423846\n", - "Kc = 3.063019856211522e-8\n", - "proton+C=COO[Pt]<=>OX+C=CO\n", - "kf = 43.93537738533433\n", - "krev = 6.669135249611683e-61\n", - "Kc = 6.587867203306832e61\n", - "O=O+C=C[Pt]<=>C=COO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 1.0833501613715598e-32\n", - "Kc = 7.082998693235901e24\n", - "vacantX+vacantX+C=COO<=>HX+C=COO[Pt]\n", - "kf = 4.552726448583842e-23\n", - "krev = 27.53540659037694\n", - "Kc = 1.6534081069915729e-24\n", - "vacantX+vacantX+C=COOC<=>CH3X+C=COO[Pt]\n", - "kf = 2.287071149777874e-9\n", - "krev = 2.2490557638427473e13\n", - "Kc = 1.0169028205286352e-22\n", - "vacantX+vacantX+CC(O)=CO<=>OC=[Pt]+CC(O)=[Pt]\n", - "kf = 7.128045206079291e-31\n", - "krev = 1.6024698052635947e11\n", - "Kc = 4.4481619451835966e-42\n", - "vacantX+vacantX+CC(O)=CO<=>CH3X+OC=C(O)[Pt]\n", - "kf = 1.2021042471738558e-26\n", - "krev = 3.79937896614338e12\n", - "Kc = 3.163949313521812e-39\n", - "proton+O=CC=C=[Pt]<=>O=CCC#[Pt]\n", - "kf = 62.9877146015209\n", - "krev = 8.316144406521062e-31\n", - "Kc = 7.574148730766316e31\n", - "vacantX+vacantX+O=C=CC=O<=>OX+O=CC=C=[Pt]\n", - "kf = 1.1758489216219413e-43\n", - "krev = 2.1453863988577092e16\n", - "Kc = 5.480825842132732e-60\n", - "proton+O=CC=C=[Pt]<=>O=CC=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.331702565774384e-47\n", - "Kc = 2.6790395240083815e56\n", - "proton+C=C=C=O.[Pt]<=>O=C=CC[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.2229421483387703e-16\n", - "Kc = 1.1246356554390213e26\n", - "vacantX+C=C=C=O<=>C=C=C=O.[Pt]\n", - "kf = 372758.92921022984\n", - "krev = 0.5077615475124772\n", - "Kc = 734122.012658058\n", - "proton+C=C=C=O.[Pt]<=>CC([Pt])=C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.123273247571115e-16\n", - "Kc = 1.1774273531962195e26\n", - "proton+C=C=C=O.[Pt]<=>C=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.171161147913428e-32\n", - "Kc = 4.834504144216726e41\n", - "proton+O=C=C=C[Pt]<=>C=C=C=O.[Pt]\n", - "kf = 3.820491632517615e9\n", - "krev = 3.925100397444825e-12\n", - "Kc = 9.733487670798667e20\n", - "vacantX+vacantX+C=C(C)O<=>CH2X+CC(O)=[Pt]\n", - "kf = 1.2526307828427685e-31\n", - "krev = 1.8291181793687947e14\n", - "Kc = 6.848276929132241e-46\n", - "vacantX+vacantX+C=C(C)O<=>CH3X+C=C(O)[Pt]\n", - "kf = 6.412809230790006e-14\n", - "krev = 6.896161957802356e13\n", - "Kc = 9.299098933624258e-28\n", - "HX+O=C=C=C=O<=>O=C=C=CO[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 6.474039280394542e-15\n", - "Kc = 8.128654665807662e6\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C=CO[Pt]\n", - "kf = 2.4048564698523636e10\n", - "krev = 0.03636685994081414\n", - "Kc = 6.612769080877996e11\n", - "proton+O=C=C=CO[Pt]<=>OX+C=C=C=O\n", - "kf = 7.675790818902377e-14\n", - "krev = 0.0006735755949001122\n", - "Kc = 1.1395589265731426e-10\n", - "vacantX+vacantX+O=C=C=CO<=>HX+O=C=C=CO[Pt]\n", - "kf = 4.194899212644372e-10\n", - "krev = 0.014508998351933198\n", - "Kc = 2.891239705796395e-8\n", - "proton+O=C=C=CO[Pt]<=>O=C=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4612716650323904e-11\n", - "Kc = 1.71083862078759e21\n", - "proton+CC(O)[Pt]<=>OC=[Pt]+CH4\n", - "kf = 59.397807135376084\n", - "krev = 1.2803453253139382e-6\n", - "Kc = 4.639202093451769e7\n", - "HX+C=CO<=>CC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 1.2254518112062234e-21\n", - "Kc = 2.668292606261641e13\n", - "HX+CC=O<=>CC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 2.4645381117653586e-12\n", - "Kc = 13267.654460532101\n", - "vacantX+vacantX+CCO<=>HX+CC(O)[Pt]\n", - "kf = 1.7361137032745595e-19\n", - "krev = 63.774720976875884\n", - "Kc = 2.72225997492652e-21\n", - "vacantX+vacantX+CC(O)O<=>HOX+CC(O)[Pt]\n", - "kf = 7.380915652046712e-14\n", - "krev = 2.775462823415347e13\n", - "Kc = 2.6593458899096773e-27\n", - "proton+CC=O.[Pt]<=>CC(O)[Pt]\n", - "kf = 36132.65188770086\n", - "krev = 0.006356177292382113\n", - "Kc = 5.68465135971048e6\n", - "proton+CC(O)[Pt]<=>H2O+CC=[Pt]\n", - "kf = 2964.0563969386994\n", - "krev = 0.019559355499681682\n", - "Kc = 151541.61889367664\n", - "proton+CC(O)=[Pt]<=>CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.860369956892034e-19\n", - "Kc = 5.143641373338227e28\n", - "vacantX+vacantX+CC(O)C=O<=>CHOX+CC(O)[Pt]\n", - "kf = 753631.9525109725\n", - "krev = 9.011518944421836e14\n", - "Kc = 8.362984721654206e-10\n", - "proton+C=CO.[Pt]<=>CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.061646123775542e-6\n", - "Kc = 4.939104668453628e15\n", - "HX+C#CC=O<=>O=CC=C[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 1.9866745274914506e-30\n", - "Kc = 1.4859387148609413e22\n", - "proton+CC(O)C#[Pt]<=>CX+CCO\n", - "kf = 1.3617819786307934\n", - "krev = 4.084110860281074e-5\n", - "Kc = 33343.413663777814\n", - "O=CO+CH3X<=>CC(O)O[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 7.324156308451427e-7\n", - "Kc = 0.043678018970166745\n", - "HOX+CC=O<=>CC(O)O[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 7.587328136505701e-13\n", - "Kc = 43096.38318446866\n", - "HX+CC(=O)O<=>CC(O)O[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 4598.938099177113\n", - "Kc = 6.089703295881323e-12\n", - "proton+CC(O)O[Pt]<=>OX+CCO\n", - "kf = 1.6583777607664147e6\n", - "krev = 1.6983423991371652e-6\n", - "Kc = 9.764684445309413e11\n", - "vacantX+vacantX+CC(O)O<=>HX+CC(O)O[Pt]\n", - "kf = 4.052122584605618e-24\n", - "krev = 469.09529347560436\n", - "Kc = 8.638165082797514e-27\n", - "proton+CC(=O)O.[Pt]<=>CC(O)O[Pt]\n", - "kf = 0.7475019896975738\n", - "krev = 3555.8603422114556\n", - "Kc = 0.00021021691454639312\n", - "vacantX+vacantX+OC=C=CO<=>OC=[Pt]+OC=C=[Pt]\n", - "kf = 3.0449395213240036e-51\n", - "krev = 1.4315520101841116e12\n", - "Kc = 2.1270198355785863e-63\n", - "CH3X+O=C=CO<=>CC(O)C(=O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 4.477216581188038e-53\n", - "Kc = 6.362980552705156e44\n", - "proton+CC(O)C(=O)[Pt]<=>OCX+CCO\n", - "kf = 9.570476890072168e7\n", - "krev = 4.96015815008412e-7\n", - "Kc = 1.929470109720163e14\n", - "HOX+CC=C=O<=>CC(O)C(=O)[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 3.536759710167166e-36\n", - "Kc = 8.195394062368554e27\n", - "HX+CC(O)=C=O<=>CC(O)C(=O)[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 4.830700359768998e-42\n", - "Kc = 5.292381792522405e33\n", - "vacantX+vacantX+CC(O)C=O<=>HX+CC(O)C(=O)[Pt]\n", - "kf = 4.786286134353719e-11\n", - "krev = 0.0006355923790078162\n", - "Kc = 7.530433486042254e-8\n", - "proton+CC(O)=C=O.[Pt]<=>CC(O)C(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.368412782384192e-31\n", - "Kc = 1.8269341182594315e41\n", - "proton+CC(O)OC#[Pt]<=>CX+CC(O)O\n", - "kf = 2.7873525673015004e-16\n", - "krev = 1.8374709107747412e-8\n", - "Kc = 1.516950581887719e-8\n", - "vacantX+vacantX+CCOC<=>CO[Pt]+CC[Pt]\n", - "kf = 2.3627317133785774e-11\n", - "krev = 3.856091265609508e13\n", - "Kc = 6.127271246016828e-25\n", - "vacantX+vacantX+CCOC<=>CH3X+CCO[Pt]\n", - "kf = 6.326940367296449e-9\n", - "krev = 1.8372911814097844e13\n", - "Kc = 3.443624195943553e-22\n", - "vacantX+vacantX+CCOC<=>CH3X+COC[Pt]\n", - "kf = 1.3389399016858639e-14\n", - "krev = 2.773400746132106e14\n", - "Kc = 4.8277909478217395e-29\n", - "proton+O=C=C(O)C[Pt]<=>CH2X+O=C=CO\n", - "kf = 4.2042874371743854e-22\n", - "krev = 1.1101526849597185\n", - "Kc = 3.787125405481442e-22\n", - "HOX+C=C=C=O<=>O=C=C(O)C[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 6.322264310888409e-36\n", - "Kc = 4.669334354059592e27\n", - "vacantX+vacantX+CC(O)=C=O<=>HX+O=C=C(O)C[Pt]\n", - "kf = 6.004181315465852e-13\n", - "krev = 0.19478740167193392\n", - "Kc = 3.082427951669201e-12\n", - "proton+O=C=C(O)C[Pt]<=>CC(O)=C=O.[Pt]\n", - "kf = 1.859235052213257e9\n", - "krev = 4.357618832801525e-11\n", - "Kc = 4.266630753057283e19\n", - "proton+O=C=C(O)C=[Pt]<=>CHX+O=C=CO\n", - "kf = 1.807627844430322e-6\n", - "krev = 0.0010238577171457239\n", - "Kc = 0.0017655068806528764\n", - "proton+O=C=C(O)C#[Pt]<=>O=C=C(O)C=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.347883511420028\n", - "Kc = 7.467404380923659e9\n", - "proton+O=C=C(O)C=[Pt]<=>O=C=C(O)C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4404183806094484e-33\n", - "Kc = 1.735606844271341e43\n", - "vacantX+vacantX+CCCO<=>OC[Pt]+CC[Pt]\n", - "kf = 4.648157058598011e-13\n", - "krev = 1.3999921584371802e15\n", - "Kc = 3.3201307811515004e-28\n", - "vacantX+vacantX+CCCO<=>CH3X+OCC[Pt]\n", - "kf = 1.2211065235504926e-16\n", - "krev = 1.2627143633797795e15\n", - "Kc = 9.670488900451568e-32\n", - "proton+CC([Pt])OC=O<=>CH4+O=COC=[Pt]\n", - "kf = 1.0679856406424377e-15\n", - "krev = 0.2905260385078575\n", - "Kc = 3.6760410396521245e-15\n", - "CHOX+CC=O<=>CC([Pt])OC=O\n", - "kf = 3.269864007171502e-8\n", - "krev = 0.48922244404245907\n", - "Kc = 6.68379802887317e-8\n", - "HX+C=COC=O<=>CC([Pt])OC=O\n", - "kf = 2.5565910629172877e-8\n", - "krev = 1.2259112200812889e-16\n", - "Kc = 2.0854618352769157e8\n", - "vacantX+vacantX+CCOC=O<=>HX+CC([Pt])OC=O\n", - "kf = 6.519502059052115e-22\n", - "krev = 142.86665816232104\n", - "Kc = 4.563347489828482e-24\n", - "proton+CC([Pt])OC=O<=>O=CO+CC=[Pt]\n", - "kf = 8049.244255788158\n", - "krev = 0.00029431628636694825\n", - "Kc = 2.7348959703006394e7\n", - "proton+CC(=[Pt])OC=O<=>CH4+O=COC#[Pt]\n", - "kf = 4.771264023974434e9\n", - "krev = 10.578082715743388\n", - "Kc = 4.510518732164335e8\n", - "proton+CC(=[Pt])OC=O<=>O=CO+CC#[Pt]\n", - "kf = 7292.02651577905\n", - "krev = 8.53932827082491e-43\n", - "Kc = 8.539344412712957e45\n", - "proton+CC(=[Pt])OC=O<=>CC([Pt])OC=O\n", - "kf = 2.5e10\n", - "krev = 2.5945295399651927e-47\n", - "Kc = 9.635658262860014e56\n", - "vacantX+vacantX+CCC(O)O<=>OC(O)[Pt]+CC[Pt]\n", - "kf = 3.712816041087776e-19\n", - "krev = 9.367983662004229e16\n", - "Kc = 3.9633032838716965e-36\n", - "vacantX+O=CC=CO<=>O=CC=CO.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 0.8868529608572997\n", - "Kc = 364007.2889878057\n", - "proton+O=CC=CO[Pt]<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.467206835324098e-11\n", - "Kc = 1.703917907012588e21\n", - "proton+O=C([Pt])C=CO<=>O=CC=CO.[Pt]\n", - "kf = 3.672999120067293e9\n", - "krev = 4.587068754429701e-12\n", - "Kc = 8.00729031262133e20\n", - "HX+O=C=CC=O<=>O=CC=C(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.0473065138531246e-21\n", - "Kc = 2.475989854235963e13\n", - "proton+O=C=CC=O.[Pt]<=>O=CC=C(O)[Pt]\n", - "kf = 9.946079261837086e6\n", - "krev = 6.687641252513296e-9\n", - "Kc = 1.4872327755468685e15\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC=C(O)[Pt]\n", - "kf = 2.77963678004065e-20\n", - "krev = 3.601218827022036\n", - "Kc = 7.718600045027592e-21\n", - "proton+O=CC=C(O)[Pt]<=>H2O+O=CC=C=[Pt]\n", - "kf = 2.367383825493301e-13\n", - "krev = 16.1722227709439\n", - "Kc = 1.463858035487058e-14\n", - "proton+O=CC=C(O)[Pt]<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.867624236214861e-24\n", - "Kc = 3.177579311035777e33\n", - "vacantX+vacantX+CCOCO<=>OCO[Pt]+CC[Pt]\n", - "kf = 2.4512530384253315e-9\n", - "krev = 3.614837695546209e14\n", - "Kc = 6.781087409389048e-24\n", - "vacantX+vacantX+CCOCO<=>OC[Pt]+CCO[Pt]\n", - "kf = 1.0293700832173347e-6\n", - "krev = 1.2050997101819434e12\n", - "Kc = 8.541783509863451e-19\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC([Pt])=CO\n", - "kf = 4.3007284274917255e-15\n", - "krev = 1.9561961334382385\n", - "Kc = 2.1985159636997663e-15\n", - "HX+O=C=C=CO<=>O=CC([Pt])=CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.6370748462102965e-36\n", - "Kc = 1.5839961798805036e28\n", - "proton+O=CC([Pt])=CO<=>C=O+OC=C=[Pt]\n", - "kf = 4.3296354594819855e-33\n", - "krev = 908.9754469679581\n", - "Kc = 4.76320397203711e-36\n", - "proton+O=C=C=CO.[Pt]<=>O=CC([Pt])=CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.7196074204687593e-20\n", - "Kc = 1.4538201977044896e30\n", - "HOX+C#CC=O<=>O=CC([Pt])=CO\n", - "kf = 2.952076594227614e-8\n", - "krev = 4.790462195255654e-44\n", - "Kc = 6.162404531970363e35\n", - "proton+O=CC([Pt])=CO<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.2409630475480663e-18\n", - "Kc = 1.1155918000233681e28\n", - "proton+OC=CC=[Pt]<=>CHX+C=CO\n", - "kf = 0.3708119772368373\n", - "krev = 1.9743851754031655e-5\n", - "Kc = 18781.136621992628\n", - "vacantX+vacantX+O=CC=CO<=>OX+OC=CC=[Pt]\n", - "kf = 8.803023976547135e-28\n", - "krev = 1.526615583505237e17\n", - "Kc = 5.766365856383213e-45\n", - "proton+OC=CC#[Pt]<=>OC=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4263979915391943e-8\n", - "Kc = 1.7526665172195773e18\n", - "vacantX+vacantX+CCCOO<=>OOC[Pt]+CC[Pt]\n", - "kf = 5.56726706794292e-16\n", - "krev = 4.282042054393877e17\n", - "Kc = 1.3001430152303739e-33\n", - "proton+OCC(O)[Pt]<=>OC=[Pt]+CO-2\n", - "kf = 0.16339719354915763\n", - "krev = 6.17359485423602e-8\n", - "Kc = 2.6467106670766133e6\n", - "HX+O=CCO<=>OCC(O)[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 4.347223516290618e-14\n", - "Kc = 644231.1603064304\n", - "vacantX+vacantX+OCCO<=>HX+OCC(O)[Pt]\n", - "kf = 7.314142036323851e-21\n", - "krev = 492.5535033039904\n", - "Kc = 1.4849436634317805e-23\n", - "HX+OC=CO<=>OCC(O)[Pt]\n", - "kf = 5.6012337000223925e-8\n", - "krev = 1.5412075197181771e-21\n", - "Kc = 3.634315060340885e13\n", - "HOX+C=CO<=>OCC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 6.743155058263278e-19\n", - "Kc = 4.8491603395127426e10\n", - "proton+O=CCO.[Pt]<=>OCC(O)[Pt]\n", - "kf = 698182.0065765544\n", - "krev = 4.403884986144656e-6\n", - "Kc = 1.5853774764171848e11\n", - "proton+OCC(O)[Pt]<=>H2O+OCC=[Pt]\n", - "kf = 0.7285659975205578\n", - "krev = 0.0004743003964980969\n", - "Kc = 1536.0855755124403\n", - "proton+OC=CO.[Pt]<=>OCC(O)[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 1.4989628309182922e-5\n", - "Kc = 3.3356397482764175e15\n", - "proton+OCC(O)C#[Pt]<=>CX+OCCO\n", - "kf = 5.26000051169577\n", - "krev = 0.00019971123776726528\n", - "Kc = 26338.02969978857\n", - "vacantX+vacantX+CCC<=>CH3X+CC[Pt]\n", - "kf = 7.798842461270165e-20\n", - "krev = 4.754727023110295e15\n", - "Kc = 1.640229275700578e-35\n", - "proton+O=C([Pt])CO<=>OCC(O)=[Pt]\n", - "kf = 4.019918430047713e-18\n", - "krev = 1.0085447542339827e12\n", - "Kc = 3.9858602339377106e-30\n", - "proton+OCC(O)=[Pt]<=>H2O+OCC#[Pt]\n", - "kf = 16209.61875952926\n", - "krev = 4.634124941714537e-41\n", - "Kc = 3.4978812533984058e44\n", - "proton+OCC(O)=[Pt]<=>OC#[Pt]+CO-2\n", - "kf = 382.95023851607715\n", - "krev = 3.536410198453644e-35\n", - "Kc = 1.0828784474253827e37\n", - "proton+OC=C(O)[Pt]<=>OCC(O)=[Pt]\n", - "kf = 6875.768524790738\n", - "krev = 1.0085447542339824e12\n", - "Kc = 6.8175145385720384e-9\n", - "proton+OCC(O)=[Pt]<=>OCC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.6015120113778689e-47\n", - "Kc = 1.5610248204439706e57\n", - "HX+COC=O<=>COC(O)[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 224.3395816271696\n", - "Kc = 1.2483828443014824e-10\n", - "proton+COC(O)[Pt]<=>OC=[Pt]+CO-2\n", - "kf = 564390.3708916149\n", - "krev = 3.282828318007529e-12\n", - "Kc = 1.7192198806002883e17\n", - "vacantX+vacantX+COCO<=>HX+COC(O)[Pt]\n", - "kf = 6.183244140051347e-23\n", - "krev = 2731.92216309053\n", - "Kc = 2.2633310068601865e-26\n", - "O=CO+CH3X<=>COC(O)[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 8.503469161971292e7\n", - "Kc = 3.7620485485108396e-16\n", - "proton+COC=O.[Pt]<=>COC(O)[Pt]\n", - "kf = 7.49969185016536e-5\n", - "krev = 3658.0165064396892\n", - "Kc = 2.0502072193940793e-8\n", - "proton+COC(O)[Pt]<=>H2O+COC=[Pt]\n", - "kf = 5.10646151413012e-10\n", - "krev = 0.003546985366877098\n", - "Kc = 1.439662413557134e-7\n", - "vacantX+vacantX+CCOOC<=>COO[Pt]+CC[Pt]\n", - "kf = 1.4778859852656565e-10\n", - "krev = 2.404289853338368e13\n", - "Kc = 6.146871115450596e-24\n", - "vacantX+vacantX+CCOOC<=>CO[Pt]+CCO[Pt]\n", - "kf = 2.735304068777078e8\n", - "krev = 1.1929824589169815e-11\n", - "Kc = 2.2928284052560617e19\n", - "vacantX+vacantX+CCOOC<=>CH3X+CCOO[Pt]\n", - "kf = 1.542530561493995e-10\n", - "krev = 1.2789927244807063e12\n", - "Kc = 1.2060510837700736e-22\n", - "proton+COC(O)C#[Pt]<=>CX+COCO\n", - "kf = 0.03928313633337953\n", - "krev = 0.002914319669063903\n", - "Kc = 13.479350515448948\n", - "proton+COC(=O)[Pt]<=>COC(O)=[Pt]\n", - "kf = 6.005930457604258e-17\n", - "krev = 1.0085447542339825e12\n", - "Kc = 5.955046052632466e-29\n", - "proton+COC(O)=[Pt]<=>OC#[Pt]+CO-2\n", - "kf = 383854.3090963643\n", - "krev = 3.448448528690976e-34\n", - "Kc = 1.113121758677009e39\n", - "proton+COC(O)=[Pt]<=>H2O+COC#[Pt]\n", - "kf = 217922.49486435574\n", - "krev = 2.0340320286285714e-35\n", - "Kc = 1.0713818258372662e40\n", - "proton+COC(O)=[Pt]<=>COC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0120272229346644e-38\n", - "Kc = 2.4702892801149458e48\n", - "vacantX+vacantX+C=C=COO<=>OOC=[Pt]+C=C=[Pt]\n", - "kf = 1.9145907695639512e-44\n", - "krev = 1.1771971588384226e12\n", - "Kc = 1.626397715275781e-56\n", - "C=O+O=CC[Pt]<=>O=CCCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 0.0025285011306884937\n", - "Kc = 1.5664103465194285e-5\n", - "HX+O=CCC=O<=>O=CCCO[Pt]\n", - "kf = 5.113182125834635e-8\n", - "krev = 3.03538509820146e-7\n", - "Kc = 0.16845250142607343\n", - "proton+O=CCC=O.[Pt]<=>O=CCCO[Pt]\n", - "kf = 2.3901708430508703e8\n", - "krev = 41.103568870106145\n", - "Kc = 5.814995896351951e6\n", - "vacantX+vacantX+O=CCCO<=>HX+O=CCCO[Pt]\n", - "kf = 2.5157725911236352e-27\n", - "krev = 8837.406478086354\n", - "Kc = 2.84673178421957e-31\n", - "proton+O=CCCO[Pt]<=>OX+CCC=O\n", - "kf = 774927.4661784222\n", - "krev = 1.1978583087682196e-18\n", - "Kc = 6.469274875884902e23\n", - "CHOX+C=C<=>O=CCC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 0.4688595936220698\n", - "Kc = 1.7478623517301195e-7\n", - "proton+O=CCC[Pt]<=>CH2X+CC=O\n", - "kf = 0.0016740956920828355\n", - "krev = 4.373185000711893e-7\n", - "Kc = 3828.0925499614495\n", - "HX+C=CC=O<=>O=CCC[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 7.666152073113618e-12\n", - "Kc = 3780.924152337611\n", - "proton+O=CCC=[Pt]<=>O=CCC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3932958912707058e-30\n", - "Kc = 1.794306590339518e40\n", - "vacantX+vacantX+O=CCCO<=>HOX+O=CCC[Pt]\n", - "kf = 8.901266563864654e-15\n", - "krev = 1.309728963703428e15\n", - "Kc = 6.79626610584771e-30\n", - "vacantX+vacantX+CCC=O<=>HX+O=CCC[Pt]\n", - "kf = 1.6716561102658422e-25\n", - "krev = 524619.2678123232\n", - "Kc = 3.186417680076247e-31\n", - "vacantX+vacantX+CC=COO<=>OOC=[Pt]+CC=[Pt]\n", - "kf = 3.7147962989308654e-50\n", - "krev = 4.0636001726377395e18\n", - "Kc = 9.141638303749602e-69\n", - "proton+C=COOC#[Pt]<=>CX+C=COO\n", - "kf = 8.811176921711816e-67\n", - "krev = 2.5e10\n", - "Kc = 3.5244707686847265e-77\n", - "vacantX+C=CC=O<=>C=CC=O.[Pt]\n", - "kf = 365995.57053717994\n", - "krev = 1.0054621985249468\n", - "Kc = 364007.290452202\n", - "proton+C=CC(=O)[Pt]<=>C=CC=O.[Pt]\n", - "kf = 3.399604827397095e9\n", - "krev = 5.959510760846119e-12\n", - "Kc = 5.704503211458966e20\n", - "proton+O=CC=C[Pt]<=>C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.32808736312024e-27\n", - "Kc = 3.00188973889839e36\n", - "proton+C=CC=O.[Pt]<=>O=CCC[Pt]\n", - "kf = 5.197601136262071e7\n", - "krev = 74.26603000820454\n", - "Kc = 699862.5260684955\n", - "vacantX+vacantX+C=CC=O<=>HX+C=C([Pt])C=O\n", - "kf = 1.2784478936507186e-21\n", - "krev = 132.59733776930153\n", - "Kc = 9.641580405445367e-24\n", - "proton+C=C([Pt])C=O<=>C=O+C=C=[Pt]\n", - "kf = 2.4079500300331376e-13\n", - "krev = 0.010970404022735962\n", - "Kc = 2.194951092997765e-11\n", - "HX+C=C=C=O<=>C=C([Pt])C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.4992009477647154e-32\n", - "Kc = 1.1812081765045545e24\n", - "vacantX+vacantX+C=C(O)C=O<=>HOX+C=C([Pt])C=O\n", - "kf = 1.107119853181277e-14\n", - "krev = 2.5289157654010746e13\n", - "Kc = 4.377843929513773e-28\n", - "proton+C=C=C=O.[Pt]<=>C=C([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.305987527913534e-16\n", - "Kc = 1.0841342243780513e26\n", - "HX+C#CC=O<=>C=C([Pt])C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 1.683521621093348e-30\n", - "Kc = 1.753512730243651e22\n", - "proton+C=C([Pt])C=O<=>C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.827731832923639e-27\n", - "Kc = 2.5438219545478565e36\n", - "CHOX+C=C=O<=>C=C(C=O)O[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.906984656058423e-6\n", - "Kc = 0.017553122325364576\n", - "proton+C=C(C=O)O[Pt]<=>OX+C=CC=O\n", - "kf = 13.565263195704604\n", - "krev = 7.179044500174065e-6\n", - "Kc = 1.8895638821260543e6\n", - "vacantX+vacantX+C=C(O)C=O<=>HX+C=C(C=O)O[Pt]\n", - "kf = 8.336773502217888e-19\n", - "krev = 4.018028855986407\n", - "Kc = 2.0748416203624424e-19\n", - "vacantX+vacantX+COCOC<=>CH3X+COCO[Pt]\n", - "kf = 0.24675966205104702\n", - "krev = 5.277017405064255e15\n", - "Kc = 4.6761199198288865e-17\n", - "vacantX+vacantX+COCOC<=>CO[Pt]+COC[Pt]\n", - "kf = 4.1241018831024145e-7\n", - "krev = 7.782310155024181e12\n", - "Kc = 5.2993286067375974e-20\n", - "proton+C=CC=[Pt]<=>CHX+C=C\n", - "kf = 1.3385165927063483e6\n", - "krev = 9.028119675350497e-7\n", - "Kc = 1.4826083845132273e12\n", - "vacantX+vacantX+C=CC=O<=>OX+C=CC=[Pt]\n", - "kf = 1.438969400016978e-30\n", - "krev = 1.6093339940290013e17\n", - "Kc = 8.941396909254915e-48\n", - "proton+C=CC#[Pt]<=>C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.067052266556579e-6\n", - "Kc = 2.342903040792558e16\n", - "vacantX+CC(O)O<=>CC(O)O.[Pt]\n", - "kf = 347843.58123444836\n", - "krev = 178209.4487483253\n", - "Kc = 1.9518806868971765\n", - "proton+CC(O)O[Pt]<=>CC(O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.64203868551119e-24\n", - "Kc = 1.5224976257010135e34\n", - "vacantX+vacantX+COCCO<=>OC[Pt]+COC[Pt]\n", - "kf = 1.3358759661274015e-7\n", - "krev = 3.1165281946439875e14\n", - "Kc = 4.286423490161954e-22\n", - "vacantX+vacantX+COCCO<=>CO[Pt]+OCC[Pt]\n", - "kf = 6.192873660096324e-8\n", - "krev = 3.90827625278604e13\n", - "Kc = 1.584553716150872e-21\n", - "vacantX+vacantX+COCCO<=>CH3X+OCCO[Pt]\n", - "kf = 4.52195120819324e-12\n", - "krev = 5.920081591014324e14\n", - "Kc = 7.638325821483257e-27\n", - "proton+OC(O)C[Pt]<=>CH2X+OCO\n", - "kf = 2.252975678309519e-7\n", - "krev = 0.002613777215265548\n", - "Kc = 8.619616335895816e-5\n", - "HOX+C=CO<=>OC(O)C[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 6.095879365149742e-19\n", - "Kc = 5.364056293281289e10\n", - "HX+C=C(O)O<=>OC(O)C[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 1.7806643358524245e-19\n", - "Kc = 1.572793251160735e11\n", - "vacantX+vacantX+CC(O)O<=>HX+OC(O)C[Pt]\n", - "kf = 2.610914590914038e-25\n", - "krev = 48838.0104312493\n", - "Kc = 5.3460707507516085e-30\n", - "vacantX+vacantX+CCC(O)O<=>CH3X+OC(O)C[Pt]\n", - "kf = 2.73273606062798e-19\n", - "krev = 1.7143250273592365e15\n", - "Kc = 1.594059479396106e-34\n", - "proton+OC(O)C[Pt]<=>CC(O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0162407066861682e-27\n", - "Kc = 2.4600470966688416e37\n" - ] - } - ], - "source": [ - "for (i,rxn) in enumerate(inter.reactions)\n", - " str = getrxnstr(rxn)\n", - " kf = inter.kfs[i]\n", - " krev = inter.krevs[i]\n", - " Kc = kf/krev\n", - " println(str)\n", - " println(\"kf = $kf\")\n", - " println(\"krev = $krev\")\n", - " println(\"Kc = $Kc\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 79, - "id": "11333da0", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 80, - "id": "ef575a57", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.9.1", - "language": "julia", - "name": "julia-1.9" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.9.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/CO2RR_RMS/Ag/CO2RR_RMS_Diffusion_Interface_Matt.jl b/CO2RR_RMS/Ag/CO2RR_RMS_Diffusion_Interface_Matt.jl new file mode 100644 index 0000000..b67c57a --- /dev/null +++ b/CO2RR_RMS/Ag/CO2RR_RMS_Diffusion_Interface_Matt.jl @@ -0,0 +1,265 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,jl:percent +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.17.2 +# kernelspec: +# display_name: Julia 1.9.1 +# language: julia +# name: julia-1.9 +# --- + +# %% +using ReactionMechanismSimulator +using PyPlot +using Sundials +using SciMLBase +using QuadGK + +# %% +outdict = readinput("chem300.rms") + + +# %% +boundarylayerspcs = outdict["gas"]["Species"] +boundarylayerrxns = outdict["gas"]["Reactions"] +surfspcs = outdict["surface"]["Species"] +surfrxns = outdict["surface"]["Reactions"] +interfacerxns = outdict[Set(["surface", "gas"])]["Reactions"] +solv = outdict["Solvents"][1]; + +# %% +sitedensity = 2.292e-5; # Ag111 +boundarylayer = IdealDiluteSolution(boundarylayerspcs,boundarylayerrxns,solv,name="boundarylayeruid",diffusionlimited=true); +surf = IdealSurface(surfspcs,surfrxns,sitedensity,name="surface"); + +# %% +initialcondsboundarylayer = Dict(["proton"=>10.0^-4, + "CO2"=>10.0^-3*10^6, + "V"=>1.0e-3,"T"=>300,"Phi"=>0.0,"d"=>0.0]); +initialcondsreservoir = Dict(["proton"=>10.0^-4, + "CO2"=>10.0^-3*10^6, + "V"=>1.0,"T"=>300]); +AVratio = 1e5; +initialcondssurf = Dict(["CO2X"=>0.4*sitedensity*AVratio, +# "CHO2X"=>0.1*sitedensity*AVratio, +# "CO2HX"=>0.1*sitedensity*AVratio, +# "OX"=>0.1*sitedensity*AVratio, +# "OCX"=>0.1*sitedensity*AVratio, + "vacantX"=>1.0*sitedensity*AVratio, +# "CH2O2X"=>0.05*sitedensity*AVratio, +# "CHOX"=>0.04*sitedensity*AVratio, +# "CH2OX"=>0.01*sitedensity*AVratio, + "A"=>1.0*AVratio,"T"=>300,"Phi"=>-1.0]); + +# %% +domainboundarylayer, y0boundarylayer, pboundarylayer = ConstantTVDomain(phase=boundarylayer, initialconds=initialcondsboundarylayer); +domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf, + initialconds=initialcondssurf); + +# %% +inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainboundarylayer, + domaincat,interfacerxns,298.15,AVratio*1.0); + +# %% +# start with 1mm layer thickness +diffusionlayer = ConstantReservoirDiffusion(domainboundarylayer, initialcondsreservoir, AVratio*1.0, 1e-3); + +# %% +interfaces = [inter, diffusionlayer]; + +# %% +@time react,y0,p = Reactor((domainboundarylayer,domaincat), (y0boundarylayer,y0cat), (0.0, 100.0), interfaces, (pboundarylayer,pcat,pinter)); + + +# %% +@time sol = solve(react.ode,Sundials.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +# %% +sol.t[end] + +# %% +sol.retcode + +# %% +ssys = SystemSimulation(sol,(domainboundarylayer,domaincat,), interfaces,p); + +# %% +plotmolefractions(ssys.sims[1], 0.99e2,tol=1e-25) +yscale("log") +xscale("log") + +# %% +plotmolefractions(ssys.sims[2], 0.99e2,tol=3e-2) +xscale("log") + +# %% +""" +diffusive flux to the reservoir +""" +function flux_to_reservoir(sim,t,reservoirinterface) + cs = concentrations(sim,t) + return reservoirinterface.A .* sim.domain.diffusivity .* (cs - reservoirinterface.c) / reservoirinterface.layer_thickness +end + +""" +Integrates the flux to the reservoir and computes the concentration assuming +there is no prior concentration of that species in the reservoir +""" +function get_reservoir_concentration(sim,t,reservoirinterface,Vres) + intg,err = quadgk(x -> flux_to_reservoir(sim,x,reservoirinterface), 0, t) + return intg./Vres +end + +# %% +flux_to_reservoir(ssys.sims[1],0.99e2,diffusionlayer) + +# %% +res_cs = get_reservoir_concentration(ssys.sims[1],0.99e2,diffusionlayer,1.0) + +# %% +sort(res_cs) + +# %% +getfield.(ssys.sims[1].domain.phase.species,:name) + +# %% +getfield.(ssys.sims[2].domain.phase.species,:name) + +# %% +# Helper function +function plotX(sim, tol, t_end, exclude) + clf() + xs = molefractions(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Mole Fraction") +end + +# %% +# Helper function +function plotC(sim, tol, t_end, exclude) + clf() + xs = concentrations(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Concentration") +end + +# %% +concentrations(ssys.sims[1]) + +# %% +concentrations(ssys.sims[2]) + +# %% +exclude_species = ["H2O"] +plotX(ssys.sims[1], 1e-6, 1e2, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e2) +ylim(1e-9, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V") +gcf() + +# %% +exclude_species = ["H2O"] +plotC(ssys.sims[1], 1e-6, 1e2, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e2) +ylim(1e-6, 1e8) +title("Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V") +gcf() + +# %% +exclude_species = ["H2O"] +plotC(ssys.sims[2], 1e-6, 1e2, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e2) +ylim(1e-6, 1e-4) +title("Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V") +gcf() + +# %% +getfluxdiagram(ssys,1e2;speciesratetolerance=1e-6) + +# %% +println(ssys.names) + +# %% +rops(ssys, "O=CO", 1e-12) + +# %% +plotrops(ssys,"CH2O2X",1;N=15,tol=0.0) + +# %% +plotrops(ssys,"CHO2X",1;N=10,tol=0.0) + +# %% +plotrops(ssys,"CO2HX",1;N=10,tol=0.0) + +# %% +plotrops(ssys,"OX",1;N=10,tol=0.0) + +# %% +plotrops(ssys,"OCX",1.0e-6) + +# %% +for (i,rxn) in enumerate(inter.reactions) + str = getrxnstr(rxn) + kf = inter.kfs[i] + krev = inter.krevs[i] + Kc = kf/krev + println(str) + println("kf = $kf") + println("krev = $krev") + println("Kc = $Kc") +end + +# %% +for (i,rxn) in enumerate(inter.reactions) + str = getrxnstr(rxn) + kf = inter.kfs[i] + krev = inter.krevs[i] + Kc = kf/krev + println(str) + println("kf = $kf") + println("krev = $krev") + println("Kc = $Kc") +end + +# %% + +# %% diff --git a/CO2RR_RMS/Cu/CO2RR_Cu.ipynb b/CO2RR_RMS/Cu/CO2RR_Cu.ipynb deleted file mode 100644 index cd6082a..0000000 --- a/CO2RR_RMS/Cu/CO2RR_Cu.ipynb +++ /dev/null @@ -1,554 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "using DifferentialEquations\n", - "using ReactionMechanismSimulator\n", - "using PyPlot" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[14:57:35] WARNING: not removing hydrogen atom without neighbors\n", - "[14:57:35] WARNING: not removing hydrogen atom without neighbors\n", - "┌ Warning: failed to generate StokesDiffusivity model for species vacantX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2O2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species H2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH3X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [H][H].[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n" - ] - }, - { - "data": { - "text/plain": [ - "Dict{Any, Any} with 4 entries:\n", - " \"Solvents\" => Solvent[Solvent(\"water\", RiedelViscosity{Float64}(…\n", - " Set([\"surface\", \"gas\"]) => Dict{Any, Any}(\"Reactions\"=>ElementaryReaction[vac…\n", - " \"gas\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…\n", - " \"surface\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "outdict1 = readinput(\"Cu_012925.rms\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "liqspcs1 = outdict1[\"gas\"][\"Species\"];\n", - "liqrxns1 = outdict1[\"gas\"][\"Reactions\"];\n", - "surfspcs1 = outdict1[\"surface\"][\"Species\"];\n", - "surfrxns1 = outdict1[\"surface\"][\"Reactions\"];\n", - "interfacerxns1 = outdict1[Set([\"surface\", \"gas\"])][\"Reactions\"];\n", - "solv1 = outdict1[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "sitedensity1 = 2.943e-5; # Cu111\n", - "sitedensity2 = 2.292e-5; # Ag111\n", - "AVratio = 36;\n", - "Phi1 = -1.414;\n", - "Phi2 = -0.614;" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "initialcondsliq = Dict([\"proton\"=>10.0^-4,\"CO2\"=>10.0^-3*10^3,\n", - " \"V\"=>1.0,\"T\"=>298.15,\"Phi\"=>0.0,\"d\"=>0.0]);\n", - "initialcondssurf1 = Dict([\"CO2X\"=>0.4*sitedensity1*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity1*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity1*AVratio,\n", - " \"OX\"=>0.1*sitedensity1*AVratio,\n", - " \"OCX\"=>0.1*sitedensity1*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity1*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity1*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity1*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity1*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>Phi1]);" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "initialcondssurf2 = Dict([\"CO2X\"=>0.4*sitedensity1*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity1*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity1*AVratio,\n", - " \"OX\"=>0.1*sitedensity1*AVratio,\n", - " \"OCX\"=>0.1*sitedensity1*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity1*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity1*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity1*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity1*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>Phi2]);" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "liq1 = IdealDiluteSolution(liqspcs1,liqrxns1,solv1,name=\"liquid\",diffusionlimited=true);\n", - "\n", - "surf1 = IdealSurface(surfspcs1,surfrxns1,sitedensity1,name=\"surface\");\n" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "domainliq1,y0liq1,pliq1 = ConstantTVDomain(phase=liq1,\n", - " initialconds=initialcondsliq,constantspecies=[\"proton\",\"CO2\"]);" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "domaincat1,y0cat1,pcat1 = ConstantTAPhiDomain(phase=surf1,\n", - " initialconds=initialcondssurf1);\n", - "\n", - "inter1,pinter1 = ReactiveInternalInterfaceConstantTPhi(domainliq1,\n", - " domaincat1,interfacerxns1,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "domaincat2,y0cat2,pcat2 = ConstantTAPhiDomain(phase=surf1,\n", - " initialconds=initialcondssurf2);\n", - "\n", - "inter2,pinter2 = ReactiveInternalInterfaceConstantTPhi(domainliq1,\n", - " domaincat2,interfacerxns1,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 21.536523 seconds (51.04 M allocations: 3.047 GiB, 10.94% gc time, 99.91% compilation time: <1% of which was recompilation)\n", - " 7.551352 seconds (18.91 M allocations: 1.187 GiB, 8.74% gc time, 98.02% compilation time)\n" - ] - } - ], - "source": [ - "@time react1,y01,p1 = Reactor((domainliq1,domaincat1), (y0liq1,y0cat1), (0.0, 1.0e3), [inter1], (pliq1,pcat1,pinter1));\n", - "\n", - "@time sol1 = solve(react1.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-8);\n", - "\n", - "ssys1 = SystemSimulation(sol1,(domainliq1,domaincat1,),(inter1,),p1);" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.002376 seconds (6.54 k allocations: 3.020 MiB)\n", - " 0.275685 seconds (753.23 k allocations: 199.470 MiB, 29.83% gc time)\n" - ] - } - ], - "source": [ - "@time react2,y02,p2 = Reactor((domainliq1,domaincat2), (y0liq1,y0cat2), (0.0, 1.0e3), [inter2], (pliq1,pcat2,pinter2));\n", - "\n", - "@time sol2 = solve(react2.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-8);\n", - "\n", - "ssys2 = SystemSimulation(sol2,(domainliq1,domaincat2,),(inter2,),p2);" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotX (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotX(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = molefractions(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Mole Fraction\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotC (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotC(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = concentrations(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Concentration\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys1.sims[1], 1e-10, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-12, 5)\n", - "title(\"Liquid-phase Mole Fractions vs. Time on Cu111@-1.0V vs RHE\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotC(ssys1.sims[1], 1e-10, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-12, 1e5)\n", - "title(\"Liquid-phase Concentrations vs. Time on Cu111@-1.0V vs RHE\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "39×2990 Matrix{Float64}:\n", - " 0.0 0.0 0.0 … 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0\n", - " 1.0 1.0 1.0 1.0 1.0\n", - " 0.0001 0.0001 0.0001 … 0.0001 0.0001\n", - " 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 3.27496e-27 6.54991e-27 3.29138e-17 3.28967e-17\n", - " 0.0 1.24107e-27 2.49736e-27 0.0691037 0.0691037\n", - " 0.0 2.50461e-21 5.00922e-21 41.9391 42.135\n", - " ⋮ ⋱ \n", - " 0.0 1.02567e-110 1.48474e-89 … 7.38278e-26 7.38278e-26\n", - " 0.0 4.46254e-123 2.68246e-122 1.65112e-93 1.63978e-93\n", - " 0.0 4.39016e-85 1.58444e-84 5.88359e-47 5.88359e-47\n", - " 0.0 1.30327e-57 5.21314e-57 1.68635e-14 1.68635e-14\n", - " 0.0 1.22005e-82 9.71798e-82 4.50202e-27 4.50202e-27\n", - " 0.0 3.13785e-83 2.5273e-82 … 1.14862e-14 1.14862e-14\n", - " 0.0 9.69845e-87 7.72537e-86 8.31806e-15 8.33851e-15\n", - " 0.0 2.01214e-138 1.60272e-137 2.20627e-61 2.21169e-61\n", - " 0.0 0.0 8.98209e-107 3.89495e-22 3.89495e-22" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "concentrations(ssys1.sims[1])" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys1.sims[2], 0.1, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-12, 5)\n", - "title(\"Surface coverage on Cu111@-1.0 V vs. RHE\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys2.sims[1], 1e-10, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-12, 5)\n", - "title(\"Liquid-phase Mole Fractions vs. Time on Cu111@-0.2V vs RHE\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotC(ssys2.sims[1], 1e-10, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-12, 1e5)\n", - "title(\"Liquid-phase Concentrations vs. Time on Cu111@-0.2V vs RHE\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Julia 1.9.1", - "language": "julia", - "name": "julia-1.9" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.9.1" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/CO2RR_RMS/Cu/CO2RR_Cu.jl b/CO2RR_RMS/Cu/CO2RR_Cu.jl new file mode 100644 index 0000000..38fe79b --- /dev/null +++ b/CO2RR_RMS/Cu/CO2RR_Cu.jl @@ -0,0 +1,202 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,jl:percent +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.17.2 +# kernelspec: +# display_name: Julia 1.9.1 +# language: julia +# name: julia-1.9 +# --- + +# %% +using DifferentialEquations +using ReactionMechanismSimulator +using PyPlot + +# %% +outdict1 = readinput("Cu_012925.rms") + +# %% +liqspcs1 = outdict1["gas"]["Species"]; +liqrxns1 = outdict1["gas"]["Reactions"]; +surfspcs1 = outdict1["surface"]["Species"]; +surfrxns1 = outdict1["surface"]["Reactions"]; +interfacerxns1 = outdict1[Set(["surface", "gas"])]["Reactions"]; +solv1 = outdict1["Solvents"][1]; + +# %% +sitedensity1 = 2.943e-5; # Cu111 +sitedensity2 = 2.292e-5; # Ag111 +AVratio = 36; +Phi1 = -1.414; +Phi2 = -0.614; + +# %% +initialcondsliq = Dict(["proton"=>10.0^-4,"CO2"=>10.0^-3*10^3, + "V"=>1.0,"T"=>298.15,"Phi"=>0.0,"d"=>0.0]); +initialcondssurf1 = Dict(["CO2X"=>0.4*sitedensity1*AVratio, + "CHO2X"=>0.1*sitedensity1*AVratio, + "CO2HX"=>0.1*sitedensity1*AVratio, + "OX"=>0.1*sitedensity1*AVratio, + "OCX"=>0.1*sitedensity1*AVratio, + "vacantX"=>0.1*sitedensity1*AVratio, + "CH2O2X"=>0.05*sitedensity1*AVratio, + "CHOX"=>0.04*sitedensity1*AVratio, + "CH2OX"=>0.01*sitedensity1*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>Phi1]); + +# %% +initialcondssurf2 = Dict(["CO2X"=>0.4*sitedensity1*AVratio, + "CHO2X"=>0.1*sitedensity1*AVratio, + "CO2HX"=>0.1*sitedensity1*AVratio, + "OX"=>0.1*sitedensity1*AVratio, + "OCX"=>0.1*sitedensity1*AVratio, + "vacantX"=>0.1*sitedensity1*AVratio, + "CH2O2X"=>0.05*sitedensity1*AVratio, + "CHOX"=>0.04*sitedensity1*AVratio, + "CH2OX"=>0.01*sitedensity1*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>Phi2]); + +# %% +liq1 = IdealDiluteSolution(liqspcs1,liqrxns1,solv1,name="liquid",diffusionlimited=true); + +surf1 = IdealSurface(surfspcs1,surfrxns1,sitedensity1,name="surface"); + + +# %% +domainliq1,y0liq1,pliq1 = ConstantTVDomain(phase=liq1, + initialconds=initialcondsliq,constantspecies=["proton","CO2"]); + +# %% +domaincat1,y0cat1,pcat1 = ConstantTAPhiDomain(phase=surf1, + initialconds=initialcondssurf1); + +inter1,pinter1 = ReactiveInternalInterfaceConstantTPhi(domainliq1, + domaincat1,interfacerxns1,298.15,AVratio*1.0); + +# %% +domaincat2,y0cat2,pcat2 = ConstantTAPhiDomain(phase=surf1, + initialconds=initialcondssurf2); + +inter2,pinter2 = ReactiveInternalInterfaceConstantTPhi(domainliq1, + domaincat2,interfacerxns1,298.15,AVratio*1.0); + +# %% +@time react1,y01,p1 = Reactor((domainliq1,domaincat1), (y0liq1,y0cat1), (0.0, 1.0e3), [inter1], (pliq1,pcat1,pinter1)); + +@time sol1 = solve(react1.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-8); + +ssys1 = SystemSimulation(sol1,(domainliq1,domaincat1,),(inter1,),p1); + +# %% +@time react2,y02,p2 = Reactor((domainliq1,domaincat2), (y0liq1,y0cat2), (0.0, 1.0e3), [inter2], (pliq1,pcat2,pinter2)); + +@time sol2 = solve(react2.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-8); + +ssys2 = SystemSimulation(sol2,(domainliq1,domaincat2,),(inter2,),p2); + +# %% +# Helper function +function plotX(sim, tol, t_end, exclude) + clf() + xs = molefractions(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Mole Fraction") +end + +# %% +# Helper function +function plotC(sim, tol, t_end, exclude) + clf() + xs = concentrations(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Concentration") +end + +# %% +exclude_species = ["H2O"] +plotX(ssys1.sims[1], 1e-10, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e3) +ylim(1e-12, 5) +title("Liquid-phase Mole Fractions vs. Time on Cu111@-1.0V vs RHE") +gcf() + +# %% +exclude_species = ["H2O"] +plotC(ssys1.sims[1], 1e-10, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e3) +ylim(1e-12, 1e5) +title("Liquid-phase Concentrations vs. Time on Cu111@-1.0V vs RHE") +gcf() + +# %% +concentrations(ssys1.sims[1]) + +# %% +exclude_species = ["H2O"] +plotX(ssys1.sims[2], 0.1, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e3) +ylim(1e-12, 5) +title("Surface coverage on Cu111@-1.0 V vs. RHE") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys2.sims[1], 1e-10, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e3) +ylim(1e-12, 5) +title("Liquid-phase Mole Fractions vs. Time on Cu111@-0.2V vs RHE") +gcf() + +# %% +exclude_species = ["H2O"] +plotC(ssys2.sims[1], 1e-10, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e3) +ylim(1e-12, 1e5) +title("Liquid-phase Concentrations vs. Time on Cu111@-0.2V vs RHE") +gcf() + +# %% diff --git a/CO2_Reduction_Ag/Ag_C2_042925.rms b/CO2_Reduction_Ag/Ag_C2_042925.rms index 3306074..522e0b9 100644 --- a/CO2_Reduction_Ag/Ag_C2_042925.rms +++ b/CO2_Reduction_Ag/Ag_C2_042925.rms @@ -4288,13 +4288,13 @@ Reactions: - comment: 'Volmer. Made up by Richard. A = kB / h / concentration to get units right. n = 1 so that overall the A = k_B * T / H -Ea = 0.8 eV for Cu or 1.0 eV from Figure 1a of Yang 2024 +Ea = 0.9795 eV for Ag from Table 1 of Yang 2024 assume DeltaS+ = 0 q = 0.5' electronchange: 1 kinetics: - A: 1e13 - Ea: 103789.0 + A: 2.084e10 + Ea: 94507.0575 n: 1.0 q: 0.5 V0: -0.559 @@ -4309,13 +4309,13 @@ q = 0.5' - comment: 'Heyrovsky. Made up by Richard. A = kB / h / concentration to get units right. n = 1 so that overall the A = k_B * T / H -Ea = 0.8 eV for Cu or 1.0 eV from Figure 1a of Yang 2024 +Ea = 0.4205 eV for Ag from Table 1 of Yang 2024 assume DeltaS+ = 0 q = 0.5' electronchange: 1 kinetics: - A: 1e13 - Ea: 103789.0 + A: 2.084e10 + Ea: 40571.9425 n: 1.0 q: 0.5 V0: 0.559 diff --git a/CO2_Reduction_Ag/CO2RR_RMS.ipynb b/CO2_Reduction_Ag/CO2RR_RMS.ipynb deleted file mode 100644 index 41de817..0000000 --- a/CO2_Reduction_Ag/CO2RR_RMS.ipynb +++ /dev/null @@ -1,1197 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "8a590634", - "metadata": {}, - "outputs": [], - "source": [ - "using DifferentialEquations\n", - "using ReactionMechanismSimulator\n", - "using PyPlot" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "e941d4fb", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[11:25:07] WARNING: not removing hydrogen atom without neighbors\n", - "[11:25:07] WARNING: not removing hydrogen atom without neighbors\n", - "┌ Warning: failed to generate StokesDiffusivity model for species vacantX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2O2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC([Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species H2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "[11:25:08] WARNING: not removing hydrogen atom without neighbors\n", - "[11:25:08] WARNING: not removing hydrogen atom without neighbors\n", - "┌ Warning: failed to generate StokesDiffusivity model for species vacantX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2O2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species H2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [H][H].[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n" - ] - }, - { - "data": { - "text/plain": [ - "Dict{Any, Any} with 4 entries:\n", - " \"Solvents\" => Solvent[Solvent(\"water\", RiedelViscosity{Float64}(…\n", - " Set([\"surface\", \"gas\"]) => Dict{Any, Any}(\"Reactions\"=>ElementaryReaction[vac…\n", - " \"gas\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…\n", - " \"surface\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "outdict1 = readinput(\"chem43_Ag.rms\");\n", - "outdict2 = readinput(\"chem43_Cu.rms\")\n" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "fe2767e9", - "metadata": {}, - "outputs": [], - "source": [ - "liqspcs1 = outdict1[\"gas\"][\"Species\"];\n", - "liqrxns1 = outdict1[\"gas\"][\"Reactions\"];\n", - "surfspcs1 = outdict1[\"surface\"][\"Species\"];\n", - "surfrxns1 = outdict1[\"surface\"][\"Reactions\"];\n", - "interfacerxns1 = outdict1[Set([\"surface\", \"gas\"])][\"Reactions\"];\n", - "solv1 = outdict1[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "2e3c1e9a", - "metadata": {}, - "outputs": [], - "source": [ - "liqspcs2 = outdict2[\"gas\"][\"Species\"];\n", - "liqrxns2 = outdict2[\"gas\"][\"Reactions\"];\n", - "surfspcs2 = outdict2[\"surface\"][\"Species\"];\n", - "surfrxns2 = outdict2[\"surface\"][\"Reactions\"];\n", - "interfacerxns2 = outdict2[Set([\"surface\", \"gas\"])][\"Reactions\"];\n", - "solv2 = outdict2[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "711d8a69", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "100000.0" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sitedensity1 = 2.292e-5; # Ag111\n", - "sitedensity2 = 2.943e-5; # Cu111\n", - "AVratio = 1.0e5" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "8894c84d", - "metadata": {}, - "outputs": [], - "source": [ - "initialcondsliq = Dict([\"proton\"=>10.0^-4,\"CO2\"=>10.0^-3*10^3,\n", - " \"V\"=>1.0,\"T\"=>298.15,\"Phi\"=>0.0,\"d\"=>0.0]);\n", - "initialcondssurf1 = Dict([\"CO2X\"=>0.4*sitedensity1*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity1*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity1*AVratio,\n", - " \"OX\"=>0.1*sitedensity1*AVratio,\n", - " \"OCX\"=>0.1*sitedensity1*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity1*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity1*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity1*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity1*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-1.5]);\n", - "initialcondssurf2 = Dict([\"CO2X\"=>0.4*sitedensity1*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity1*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity1*AVratio,\n", - " \"OX\"=>0.1*sitedensity1*AVratio,\n", - " \"OCX\"=>0.1*sitedensity1*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity1*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity1*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity1*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity1*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-1.0]);\n", - "initialcondssurf3 = Dict([\"CO2X\"=>0.4*sitedensity1*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity1*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity1*AVratio,\n", - " \"OX\"=>0.1*sitedensity1*AVratio,\n", - " \"OCX\"=>0.1*sitedensity1*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity1*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity1*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity1*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity1*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-2.0]);\n", - "initialcondssurf4 = Dict([\"CO2X\"=>0.4*sitedensity2*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity2*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity2*AVratio,\n", - " \"OX\"=>0.1*sitedensity2*AVratio,\n", - " \"OCX\"=>0.1*sitedensity2*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity2*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity2*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity2*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity2*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-1.5]);\n", - "initialcondssurf5 = Dict([\"CO2X\"=>0.4*sitedensity2*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity2*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity2*AVratio,\n", - " \"OX\"=>0.1*sitedensity2*AVratio,\n", - " \"OCX\"=>0.1*sitedensity2*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity2*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity2*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity2*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity2*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-1.0]);\n", - "initialcondssurf6 = Dict([\"CO2X\"=>0.4*sitedensity2*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity2*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity2*AVratio,\n", - " \"OX\"=>0.1*sitedensity2*AVratio,\n", - " \"OCX\"=>0.1*sitedensity2*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity2*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity2*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity2*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity2*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-2.0]);" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "ddb39b3d", - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "liq1 = IdealDiluteSolution(liqspcs1,liqrxns1,solv1,name=\"liquid\",diffusionlimited=true);\n", - "\n", - "liq2 = IdealDiluteSolution(liqspcs2,liqrxns2,solv2,name=\"liquid\",diffusionlimited=true);\n", - "\n", - "surf1 = IdealSurface(surfspcs1,surfrxns1,sitedensity1,name=\"surface\");\n", - "\n", - "surf2 = IdealSurface(surfspcs2,surfrxns2,sitedensity2,name=\"surface\");\n", - "\n", - "domainliq1,y0liq1,pliq1 = ConstantTVDomain(phase=liq1,\n", - " initialconds=initialcondsliq,constantspecies=[\"proton\",\"CO2\"]);\n", - "\n", - "domainliq2,y0liq2,pliq2 = ConstantTVDomain(phase=liq2,\n", - " initialconds=initialcondsliq,constantspecies=[\"proton\",\"CO2\"]);" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "29ec7f86", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat1,y0cat1,pcat1 = ConstantTAPhiDomain(phase=surf1,\n", - " initialconds=initialcondssurf1);\n", - "\n", - "inter1,pinter1 = ReactiveInternalInterfaceConstantTPhi(domainliq1,\n", - " domaincat1,interfacerxns1,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "02daf794", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat2,y0cat2,pcat2 = ConstantTAPhiDomain(phase=surf1,\n", - " initialconds=initialcondssurf2);\n", - "\n", - "inter2,pinter2 = ReactiveInternalInterfaceConstantTPhi(domainliq1,\n", - " domaincat2,interfacerxns1,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "b6bac559", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat3,y0cat3,pcat3 = ConstantTAPhiDomain(phase=surf1,\n", - " initialconds=initialcondssurf3);\n", - " \n", - "inter3,pinter3 = ReactiveInternalInterfaceConstantTPhi(domainliq1,\n", - " domaincat3,interfacerxns1,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "5ed60871", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat4,y0cat4,pcat4 = ConstantTAPhiDomain(phase=surf2,\n", - " initialconds=initialcondssurf4);\n", - " \n", - "inter4,pinter4 = ReactiveInternalInterfaceConstantTPhi(domainliq2,\n", - " domaincat4,interfacerxns2,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "5b589c3f", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat5,y0cat5,pcat5 = ConstantTAPhiDomain(phase=surf2,\n", - " initialconds=initialcondssurf5);\n", - " \n", - "inter5,pinter5 = ReactiveInternalInterfaceConstantTPhi(domainliq2,\n", - " domaincat5,interfacerxns2,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "8eaa5eaf", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat6,y0cat6,pcat6 = ConstantTAPhiDomain(phase=surf2,\n", - " initialconds=initialcondssurf6);\n", - " \n", - "inter6,pinter6 = ReactiveInternalInterfaceConstantTPhi(domainliq2,\n", - " domaincat6,interfacerxns2,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "244f0912", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 10.851519 seconds (50.44 M allocations: 3.017 GiB, 11.09% gc time, 99.93% compilation time: <1% of which was recompilation)\n", - " 4.063472 seconds (19.08 M allocations: 1.154 GiB, 9.18% gc time, 97.88% compilation time)\n" - ] - } - ], - "source": [ - "@time react1,y01,p1 = Reactor((domainliq1,domaincat1), (y0liq1,y0cat1), (0.0, 1.0e2), [inter1], (pliq1,pcat1,pinter1));\n", - "\n", - "@time sol1 = solve(react1.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6);\n", - "\n", - "ssys1 = SystemSimulation(sol1,(domainliq1,domaincat1,),(inter1,),p1);\n" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "3b06f7a9", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.000678 seconds (3.32 k allocations: 960.422 KiB)\n", - " 0.090015 seconds (571.54 k allocations: 82.069 MiB, 33.06% gc time)\n" - ] - } - ], - "source": [ - "@time react2,y02,p2 = Reactor((domainliq1,domaincat2), (y0liq1,y0cat2), (0.0, 1.0e2), [inter2], (pliq1,pcat2,pinter2));\n", - "\n", - "@time sol2 = solve(react2.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6);\n", - "\n", - "ssys2 = SystemSimulation(sol2,(domainliq1,domaincat2,),(inter2,),p2);" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "ab03df14", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.000723 seconds (3.32 k allocations: 960.422 KiB)\n", - " 0.041817 seconds (335.25 k allocations: 45.316 MiB, 27.65% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "[CVODES ERROR] CVode\n", - " At t = 8.08742 and h = 1.35613e-09, the error test failed repeatedly or with |h| = hmin.\n", - "\n" - ] - } - ], - "source": [ - "@time react3,y03,p3 = Reactor((domainliq1,domaincat3), (y0liq1,y0cat3), (0.0, 1.0e2), [inter3], (pliq1,pcat3,pinter3));\n", - "\n", - "@time sol3 = solve(react3.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6);\n", - "\n", - "ssys3 = SystemSimulation(sol3,(domainliq1,domaincat3,),(inter3,),p3);" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "9b238da8", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.000737 seconds (3.67 k allocations: 866.000 KiB)\n", - " 0.035751 seconds (282.48 k allocations: 32.996 MiB, 32.97% gc time)\n" - ] - } - ], - "source": [ - "@time react4,y04,p4 = Reactor((domainliq2,domaincat4), (y0liq2,y0cat4), (0.0, 1.0e2), [inter4], (pliq2,pcat4,pinter4));\n", - "\n", - "@time sol4 = solve(react4.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6);\n", - "\n", - "ssys4 = SystemSimulation(sol4,(domainliq2,domaincat4,),(inter4,),p4);" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "b7c78e37", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.000749 seconds (3.67 k allocations: 866.000 KiB)\n", - " 0.031855 seconds (285.34 k allocations: 33.355 MiB, 21.41% gc time)\n" - ] - } - ], - "source": [ - "@time react5,y05,p5 = Reactor((domainliq2,domaincat5), (y0liq2,y0cat5), (0.0, 1.0e2), [inter5], (pliq2,pcat5,pinter5));\n", - "\n", - "@time sol5 = solve(react5.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6);\n", - "\n", - "ssys5 = SystemSimulation(sol5,(domainliq2,domaincat5,),(inter5,),p5);" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "8498a9b3", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.000716 seconds (3.67 k allocations: 866.000 KiB)\n", - " 0.021732 seconds (259.36 k allocations: 30.961 MiB)\n" - ] - } - ], - "source": [ - "@time react6,y06,p6 = Reactor((domainliq2,domaincat6), (y0liq2,y0cat6), (0.0, 1.0e2), [inter6], (pliq2,pcat6,pinter6));\n", - "\n", - "@time sol6 = solve(react6.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6);\n", - "\n", - "ssys6 = SystemSimulation(sol6,(domainliq2,domaincat6,),(inter6,),p6);" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "39632165", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotX (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotX(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = molefractions(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Mole Fraction\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "6ef159b3", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys1.sims[1], 1e-10, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e-3)\n", - "ylim(1e-12, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V\")\n", - "gcf()\n", - "savefig(\"Ag111@-1.5V_X.png\")" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "bce46a3f", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys2.sims[1], 1e-10, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e-3)\n", - "ylim(1e-12, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.0V\")\n", - "gcf()\n", - "savefig(\"Ag111@-1.0V_X.png\")" - ] - }, - { - "cell_type": "code", - "execution_count": 52, - "id": "78344a8c", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys3.sims[1], 1e-10, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e-3)\n", - "ylim(1e-12, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-2.0V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "a5b06177", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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itW6DBg0q8LxZs2YAREZG3nAbmZmZ7N27l/vvvx8PDw9ruUajYeTIkVy5cqXETaNlYcuWLTRu3JjmzZsXKH/kkUfKbBuZmZns37+f++67DxcXF2t5fm3h9cxm8w1rZYEbxpqWlsY///xToLwkn09cXByTJk2ievXqODk5odVqCQsLA+DEiRPW+dq1a8fChQt555132LNnT5Hmml27dpGUlMTo0aMLxG82m+nTpw/79+8vcU2Hh4cHDzzwAPPnz8doNLJo0SLGjBlT7D/5LVu2ABRpbm7Xrh0NGza86e9o3bp1qFQqRowYUSDmKlWq0Lx58xL3cCxun3D9OWXDhg0rdrmvv/6aVq1a4eLiYn3vN2/eXOB9//3333FxcbllE2FJnTp1iujoaEaOHFmg5sDDw4Nhw4axZ88esrKyCixT3PcoJyeHuLg4ANq2bQvAgw8+yIoVK4iKiipRLCXdV7Zr146UlBQefvhhfv3111vWhpa3AQMGFHjesGFDwNLhoHD59b+1devW4ePjw8CBAwt831q0aEGVKlVu+n0rj8+tsvn111+ZMGGC9fnYsWPZs2cP33zzDUuXLuXgwYOsWLHCOr1Xr17Ex8dba3YL15Dnf2fLwldffcWYMWPo0qULgwcPZvHixUyZMoXFixdz6NChAvOOGzeOhIQE1qxZA1hq1xcvXszdd99N3bp1S7XdCpWcNWzYkDZt2hS4tW7dusA8Y8eOJSoqik2bNgGWE/Vyc3MLHEASExOpUqVKkQNOUFAQTk5OBZqL7pTExESqVq1apDy/51nhmPz9/Qs8z+/ldLPq+eTkZBRFKdV2ylP+51BYcWW3Kzk5GbPZXKLtjB07Fq1Wa70V7ghxs3WU9vMxm8306tWLX375hRdeeIHNmzezb98+9uzZU2A+sJyQP3r0aL799ls6duyIn58fo0aNIjY2FsDaBHj//fcXiF+r1fL++++jKIq1Ka8kxo0bxz///MO7775LfHz8DbvH57/mG32fbvZdunr1KoqiEBwcXCTmPXv2lDgJKG6fcL3iYvvkk0944oknaN++PT///DN79uxh//799OnTp8D7Hh8fT0hISJmd03Kr98tsNlubk/Pd6nvUpUsXVq9ejdFoZNSoUVSrVo0mTZrc9ITvfCXZV44cOZL58+cTGRnJsGHDCAoKon379tZl7jQ/P78Cz3U63Q3Lc3JyrM+vXr1KSkoKOp2uyPctNjb2pt+38vjcilOjRg3A0gRYkSQnJxMfH2/9gxoXF8eqVatYtGgRDzzwAL169WLVqlUF/jxrtVp8fX2t5wP26NGjwGdWVn+YbmTEiBEA1v1xvvvvvx9vb2/rKTG//fYbV69eLVVHgHwVqrdmSfTu3ZuQkBAWLFhA7969WbBgAe3bty/Qnd3f35+9e/eiKEqBBC0uLg6j0UhAQMAN15//BSrcceC//qP09/cnJiamSHl0dDTATWMqKV9fX9Rqdblvp6T8/f2tCcb1iitzcXEptrNGQkLCTWP29fVFpVKVaDtvvPFGgfPdPD09bxlXflnhnfGtHDt2jH///ZeFCxcyevRoa3lxPbECAgKYNWsWs2bN4tKlS6xZs4aXXnqJuLg4NmzYYH39X3zxxQ17HJW0ezdYupXXr1+ft956i549exapzc2X/5pjYmKKDHsQHR19088lICAAlUrFjh07rAeu6xVXdjuKq/FbvHgx3bp1Y86cOQXK09PTCzwPDAxk586dmM3mMknQrn+/CouOjkatVuPr61vq9Q4ePJjBgweTm5vLnj17mDlzJo888gjh4eF07NjxhsuVZF8JlvPTxowZQ2ZmJtu3b2f69OkMGDCA06dPW2t67V1AQAD+/v5s2LCh2OmFf+vXK6/PrbA2bdrg5+fHr7/+ysyZM2953ll5HYvKWn5Nf368+Z3pWrVqZZ3H09OzwFBNer2e+Ph46z5k7ty5BX6f5X2cUhQFKNrZwNXVlYcffphvvvmGmJgY5s+fj6enJw888ECpt1Ghas5KIr+JbvXq1ezYsYMDBw4UybJ79OhBRkZGkYEjFy1aZJ1+I/m9Fo8cOVKgPL+a83rOzs63PNH0+pj++usva5J0fUxubm5l0rXc3d2d9u3b88svvxSIy2w2s3jxYqpVq0a9evX+83ZKqnv37hw/fpx///23QPmSJUuKzBseHl7kPT99+vQtm2Hd3d1p164dv/zyS4F/0unp6axdu7bINq6vgSk8rtuNYvX09CywoymJ/B1v4SRk7ty5N12uRo0aTJkyhZ49e1qbUjt37oyPjw8RERFFapHyb/k1DCX12muvMXDgwAJjUBV2zz33ABQZXmP//v2cOHHipr+jAQMGoCgKUVFRxcbbtGnTUsVbGiqVqsj7fuTIkSKnDvTt25ecnJxbDmhc0t95/fr1CQ0NZcmSJdadP1ia3n/++WdrT8Db5ezsTNeuXXn//fcBijTJFFaSfeX13N3d6du3L6+++ip6vZ7jx4/fdqx32oABA0hMTMRkMhX7fbvZGI7l/bnl02q1vPjii5w8eZK333672Hni4uL4+++/gdIdi2wpICAAV1dXTp8+DVz7o3j9iAcmk4nLly9bn//www/UqFHDejyqX79+gc+rLAe0Lk5+LlDccXfcuHGYTCY+/PBDfvvtNx566KHb+vwrVM3ZsWPHiu2FVLt27QJj6IwdO5b333+fRx55BFdXV4YPH15g/lGjRvHVV18xevRoLl68SNOmTdm5cyczZsygX79+3HvvvTeMoW3bttSvX5/nn38eo9GIr68vq1atKrbHTtOmTfnll1+YM2cOrVu3Rq1W33BMpunTp7Nu3Tq6d+/O66+/jp+fHz/++CPr16/ngw8+KHYYg9sxc+ZMevbsSffu3Xn++efR6XTMnj2bY8eOsXTp0v/US+jo0aPFjozftm3bYv9hT506lfnz59O/f3/eeecdgoOD+fHHHzl58mSReUeOHMmIESOYPHkyw4YNIzIykg8++KDYsZMKe/vtt+nTpw89e/bkueeew2Qy8f777+Pu7l6q5r6QkBAGDRrEG2+8QdWqVVm8eDGbNm3i/fffL/WPs0GDBtSuXZuXXnoJRVHw8/Nj7dq1RZqLUlNT6d69O4888ggNGjTA09OT/fv3s2HDBmvPYg8PD7744gtGjx5NUlIS999/P0FBQcTHx/Pvv/8SHx9fpJboVkaMGGGt2r+R+vXrM2HCBL744gvUajV9+/bl4sWL/N///R/Vq1e/ae+0zp07M2HCBMaMGcOBAwfo0qUL7u7uxMTEsHPnTpo2bcoTTzxRqphLasCAAbz99ttMnz6drl27curUKd566y1q1qxZYP/y8MMPs2DBAiZNmsSpU6fo3r07ZrOZvXv30rBhQx566CHA8jvfunUra9eupWrVqkVqAfKp1Wo++OADHn30UQYMGMDEiRPJzc3lww8/JCUlhffee6/Ur+X111/nypUr9OjRg2rVqpGSksJnn32GVqula9eut1z+VvvKxx9/HFdXVzp37kzVqlWJjY1l5syZeHt7W893i4yMpHbt2owePZrvvvuu1K/hTnjooYf48ccf6devH8888wzt2rVDq9Vy5coVtmzZwuDBgxk6dGixy5bH53Yj//vf/zhx4gTTp09n3759PPLII9ZBaLdv3868efN48803rSMB3HvvvcycORNfX1/CwsLYvHmztad9Yfn75vyhag4cOGA99/j6868jIyPZv38/YOlRfv2y+X9g823bts3a9GgymYiMjLTO27VrVwIDA1Gr1dx7770sW7aMFi1aEBYWRvv27Zk8eTLz5s3Dx8eHGTNmEBMTQ0ZGBt9++y1Tp07lxx9/LNF7VtJ4i/ueLlmyhF9++YX+/fsTFhZGSkoKK1euZNmyZTz22GNFzjEGSw1ns2bNmDVrFoqi3FaTJlDxe2tyg95UnTp1UgDl0UcfLXadiYmJyqRJk5SqVasqTk5OSlhYmPLyyy8rOTk5BeYrrpfg6dOnlV69eileXl5KYGCg8tRTTynr168v0nMmKSlJuf/++xUfHx9FpVIV6EVCod5IiqIoR48eVQYOHKh4e3srOp1Oad68eZEeNfk9dFauXFmg/FY9dK63Y8cO5Z577lHc3d0VV1dXpUOHDsratWuLXV9pemve6JYfU3HvZUREhNKzZ0/FxcVF8fPzU8aNG6f8+uuvRd5Ls9msfPDBB0qtWrUUFxcXpU2bNspff/1Vot6aiqIoa9asUZo1a6bodDqlRo0aynvvvWftWVUSYWFhSv/+/ZWffvpJady4saLT6ZTw8PAivcRK8/nkv3ZPT0/F19dXeeCBB5RLly4V+G7k5OQokyZNUpo1a6Z4eXkprq6uSv369ZXp06dbe4jm27Ztm9K/f3/Fz89P0Wq1SmhoqNK/f/8isRRW0s+6uJ5QJpNJef/995V69eopWq1WCQgIUEaMGKFcvny5wHyFe2vmmz9/vtK+fXvrd7F27drKqFGjlAMHDtw0lvx9wv79+4udfqPPQVEUJTc3V3n++eeV0NBQxcXFRWnVqpWyevXqYmPMzs5WXn/9daVu3bqKTqdT/P39lXvuuUfZtWuXdZ7Dhw8rnTt3Vtzc3BTA+n28UW+61atXK+3bt1dcXFwUd3d3pUePHsrff/9dYJ7872Z8fHyxrzu/t/i6deuUvn37KqGhoYpOp1OCgoKUfv36KTt27Ljp+3e9m+0rv//+e6V79+5KcHCwotPplJCQEOXBBx9Ujhw5Yp0n//tzo556N8Jt9NYs/Hnf6H0aPXq04u7uXqDMYDAoH330kdK8eXPFxcVF8fDwUBo0aKBMnDhROXPmzC3jLcvP7VZ+/fVXpX///kpgYKDi5OSk+Pr6Kt27d1e+/vprJTc31zpfTEyMcv/99yt+fn6Kt7e3MmLECOXAgQPF7gNvto8uLtbiboU/465du95w3uu/91u3blXc3NyUiIgIRVEU5dSpU0rjxo2t8/bp00cZNmyYAihNmjRRfvvttxK9T6WJt7jv6e7du5UePXooVapUUbRareLm5qa0bdtWmT17doGeuYV99tlnCqA0atSoxHEWplKU6+phhXAAW7dupXv37mzZsqXUl/IoL+Hh4TRp0oR169bZOhQhhHA4Tz31FGvXrmXNmjXWzgEXLlzAycmJ6tWrc/nyZbRabZl2CLNnle6cMyGEEELYl1mzZjFkyBDatWvHk08+yY4dO/D29iYgIIBz587xxx9/MHToUKZPn27rUO+ICnXOmRBCCCEcj0ajYdasWQwbNoz33nuPXr16Feik1bhxYyZMmMCkSZNsGOWdI82aQgghhLArOTk5XLlyhezsbEJCQko9HJGjk+RMCCGEEMKOyDlnQgghhBB2RJIzIYQQQgg7Ih0CbpPZbCY6OhpPT8//NDCrEEIIIe4cRVFIT08v02vjljVJzm5TdHT0Da8pKIQQQgj7dvny5SLX/bUXkpzdpvwL4V6+fBkvLy8bRyOEEEKIkkhLS6N69eo3vaC9rUlydpvymzK9vLwkORNCCCEcjD2fkmSfja1CCCGEEJWUJGdCCCGEEHZEkjMhhBBCCDsiyZkQQgghhB2R5EwIIYQQwo5IciaEEEIIYUckORNCCCGEsCOSnAkhhBBC2BFJzoQQQggh7IgkZ0IIIYQQdkSSMyGEEEIIO1Kpk7N169ZRv3596taty7fffmvrcIQQQgghKu+Fz41GI9OmTWPLli14eXnRqlUr7rvvPvz8/GwdmhBCCCEqsUpbc7Zv3z4aN25MaGgonp6e9OvXjz/++MPWYQkhhBCiknPY5Gz79u0MHDiQkJAQVCoVq1evLjLP7NmzqVmzJi4uLrRu3ZodO3ZYp0VHRxMaGmp9Xq1aNaKiou5E6EIIIYQQN+SwzZqZmZk0b96cMWPGMGzYsCLTly9fztSpU5k9ezadO3dm7ty59O3bl4iICGrUqIGiKEWWUalUpY7jzNV0PLKuLVd4FYXXWPwmVDedp7hFCsd6q+2oilnLrV5ucdNLu93itn3L11cW66BsYi38VK0CtUqFWqVCpQKNWpX3/Pa+P0IIIURhDpuc9e3bl759+95w+ieffMK4ceMYP348ALNmzeKPP/5gzpw5zJw5k9DQ0AI1ZVeuXKF9+/Y3XF9ubi65ubnW52lpaQAMnb0LtbPbf305ooIonLypVSo06muP86errnucn9hZEj2KLOukUeGkVuOU91iryX+sRps/TaNCm39/g+k6jRoXrRpnJw3O1927FLp3dlLjotVY753UKkk8hRDiDnLY5Oxm9Ho9Bw8e5KWXXipQ3qtXL3bt2gVAu3btOHbsGFFRUXh5efHbb7/x+uuv33CdM2fO5M033yxS7u+uReOiA6BwZVzhurniauuKzlP6ZQoXlMl2i27llq+vmEWKrKc83iN7YlbArCgU+2Y4KLUKXLQaXLQa3HQa3HVOuDnn3es0uDs74arT4K7T4KZzwt250H0x87vpLMmfJH1CCFFUhUzOEhISMJlMBAcHFygPDg4mNjYWACcnJz7++GO6d++O2WzmhRdewN/f/4brfPnll5k2bZr1eVpaGtWrV2fbC/fg5eVVPi9E3LbCSd4tE8viliky3ZJsKnkJmMmsYFYsy+UnZWbl2nSzAmazcu2xohSc13xtmSLT89ZtMisYzGaMJgWjyYzBbLk3mhVLmdmMwXStzGCyzFvcMnqjGb3JTI7BTK7RVPy9wUSu0Uyu0Wx93WYFsvQmsvQmkjL/w4dSiEatumGy5+7sdJNkT4PbDaY7O2nQqCXhE0I4tgqZnOUr/K9cUZQCZYMGDWLQoEElWpezszPOzs5lGp8oP0XONyvR8VoO6vnMZgW9yUzudYlbtsFElt5Ilt5EZm7evd5IVm7efV55tr7g8+vny8g1WhM/k1khPcdIeo6xTGPXqFU4O6nROanRafLunSzNuDonNc6a/OfXpuXPp9VYyrXXLWd9rFFde64putz1yxcsszQpSy2hEKKkKmRyFhAQgEajsdaS5YuLiytSmyaEKEqtVuGitjRlgrZM120yK0WTvFwjmXojmbmWBNB6rzeRlZt3f4vpBddvqemzJ/lJWn7i5qrT4JrXVOymszQNu+XdXLWWWkRX6/P8x9fKpZlYiIqrQiZnOp2O1q1bs2nTJoYOHWot37RpE4MHD7ZhZEIIjVqFp4sWT5eyS/rMZoUcoymvpi+/CddkfWwty2vazTWarM9z88r0RjMG671iXcZw/bTrmoeLm99w3XSTuWDDuMGkYDCZCiSSZUmtAve8JC8/YXO7runXVXutCTh/2rX5LM3EroXKJOkTwjYcNjnLyMjg7Nmz1ucXLlzg8OHD+Pn5UaNGDaZNm8bIkSNp06YNHTt2ZN68eVy6dIlJkybZMGohRHlQq1V5yYStI7nGlHcOYOFELj8hzDGYrDV82QZLDWK2/royvTGvKfm6coOlPDPXZG1mzjFYmonNCqTnGknPNUJ67i2iKzmNWoWbVmM9L9BVp7H24tVq1NbexFpNXg9hdX4v42u9hTVqy6kGKgCVZcgalcpyIoGq0HPy5itcfn1+WFyymF90/XA418oKPr9+vpsNGaQqUEYxZUXXoSq0QPHrKF2MFLP+69+DwsuWzeu0PFDnDRmk1agL9h7P6yFumaYqME9+5yFJ7G+fwyZnBw4coHv37tbn+Sfrjx49moULFzJ8+HASExN56623iImJoUmTJvz222+EhYXZKmQhRCWiUavQWJuGy09+M7HlXL+88/4M15qMs65rEs7WX2sitjQnX3ucdV3Sl1n43MD8pI+yS/pExZdfm+tWqMbW00WLj5sWPzcdvu46fN10+Llr8XXTEeTlQhUvF1x15fu7sXcqpbixC8QtpaWl4e3tTWpqqvTWFEJUOMWdG5jfuSPXYMaY1yPYYO09nNdz2NqD+Nrj/J7IkN/ruWDvZ0u5UqQ8//n1faevzX8t1vwhe6zTrnsd18oKLFDMfEqBMqXo7AV6dCtFHhQTx02mFb+tYl7nTWIsbr5ihyP6DzGaFQWjWcmrCbZ8zvm9yE0m5YY9yP8rXzctVbxdqertQlVvF6r5ulEzwJ1age6E+bvh7HT7yZsjHL8dtuZMCCFE+SmPcwNF5XB9Yp9VqDY3W28iLcdAcpaB5Ew9SZl6y+Msy+OraTlk6U15ZQZOxKQVWb9aBaG+rtQM8KBOoAcNq3rSKMSLukGe6Jwc9qqUBUhyJoQQQogy818Se0VRSMsxEpOaTUxqDrGpOcSkZHMpKYvzCZlciM8kPdfI5aRsLidls/10vHVZrUZF3SBLotayhg+tw3ypG+TpkGMfSrPmbXKEalEhhBCiIlEUhYQMPRcSMjkfn8Gpq+mciEkjIjqNtGLGTPR0dqJFDR9a1fClQy1/WtbwQZ+daffHb0nObpMkZ0IIIYR9UBSFK8nZRMSkcSwqlX8uJXP4UkqRoWt0TmqaBer4eeq9dn38lmZNIYQQQjg0lUpFdT83qvu50btxFcBy7tup2HQOXkrmwMUkdp9LJC49l30Xk2wc7a1JzdltkpozIYQQwnEoisL5hEz+OnKRCfc2tevjd8Xo1iCEEEIIcRMqlYragR4Mb1vD1qHckiRnQgghhBB2RJIzIYQQQgg7IsmZEEIIISoFs1nh6NYrtg7jlqS3phBCCCEqvIQrGWz54QSRZ2JtHcotSXImhBBCiArLaDBx8PdI/tkQidmsoHO2/4uqS3ImhBBCiAopMSqDTfOPkxiVCUCtFoG06FeFZ762cWC3IMmZEEIIISoURbGcW7br53OYjGZcPbV0fbg+tVsFkZZW9GLq9kaSMyGEEEJUGLnZRv5cEMHFIwkA1GjsT4/RDXHz0tk4spKT5EwIIYQQFUJidAa/f32U1LhsNE5qOg2rQ9NuoahUKluHViqSnAkhhBDC4Z09GMfmRScw5prw8HWm76SmBIXZ5+WZbkWSMyGEEEI4LMWssHfNeQ5uiAQgtL4vvcc3xtXTcZoxC5PkTAghhBAOyWgw8df3JzhzIA6AFj1r0HFILdQaxx5jX5IzIYQQQjicnAwDv319hJizqajVKrqPbECDjlVvuoxiNKKPir5DEd4+Sc6EEEII4VAyknNY89lhkmOz0Lk60WdiE6o38Cswjzkzk6zDh8k5HkHu6dPknjmD/vx50nNybBR1yUlyJoQQQgiHkRqfxa+zDpOemIOHrzMDnmqOf4gHislE9qFDZGzbRta+/WQfPw5GY5HlVVqtDaIuHUnOhBBCCOEQEqMzWPPZYbJS9XgHujLomRY4XTxOzLx1pP+5GVNCQoH5tSEhuLZsiXO9ejjXrYtzvbpke3iAr6+NXkHJSHImhBBCCLsXF5nG2s//JSfTgF8VV+4OOUP8qHfQnz9vnUft6YlH9264d+qEe9u2aENDi6wnR64QIIQQQgjx38RfTmfNZ4fJzTLi55xJ09/fID01HgCVmxteffrg1bcv7u3bodI57hAa+SQ5E0IIIYTdSozKYM2nh8jNMuKddoEm/36BxpSLc906+D46Aq8B/dF4eNg6zDIlyZkQQggh7FLSlTRWv7+PHIMaz7SLNP/3Szwa1ydg0kQ8unVDpXbs8cxuRJIzIYQQQtidq3uPs/bb8+Rq3PFIv0S71LWEfvUpHl27Oty1MktLkjMhhBBC2A3FaOTy7AVs/MeXXBc/PLJi6NVDS5WRKxxiGIyyIMmZEEIIIeyCIS6Oi8+9wt9KV3I9/PAgnaHTu+NVO8TWod1RFbOxVgghhBAOJXPvPs4OG85eQzsyPUJxdTYz9J1elS4xA0nOhBBCCGFjyUuXEjlmLEeDBpLqUweds5rBL3TAK8DV1qHZhDRrCiGEEMImFLOZ+E8+IeHb7zhd9yHiA1ugcVLR78nm+IdWrOExSkOSMyGEEELccYrRSPQrr5C2Zi2Xqt9LVOjdoIKeYxsTWs++L69U3iQ5E0IIIcQdpRgMRP3vBdI3bCA+qCXnag8B4O4H61K7VZBtg7MDkpwJIYQQ4o5R9HquTJtGxp+bSfcJ50TT8WCCJl1Dada9uq3DswvSIUAIIYQQd4RiNhP98itk/LkZvXsAxzv9D6MJqjf05e4H69o6PLshyZkQQgghyp2iKFydMZO09esx6Vw50ftNsrLAt4obvR9vglojKUk+eSeEEEIIUe4S5swhefFiFCDy/vdITAIXdy39n2yGs1vlGPm/pCQ5E0IIIUS5Sl6+goTPvwAgZcwMLkY7oVar6DOxCd6BbjaOzv5IciaEEEKIcpO5Zy+xb78NgHn0cxyO9AGg8wN1Kv2QGTciyZkQQgghyoX+yhWipk4FoxFt//vZm1QfxaxQr30wTbtVs3V4dkuSMyGEEEKUOVNGJleemIwpJQVtk2YcChhIdroB/2oedHu0ASqVytYh2i1JzoQQQghRphSzmeiXXiT3zBk0gQFc6vMScZEZOLs50XdiU7Q6ja1DtGuSnAkhhBCiTCV8+SUZf25GpdWSM+UjThxItl6ayTuwcl7MvDQqbXJ2+fJlunXrRqNGjWjWrBkrV660dUhCCCGEw0vbsIGE2XMAcH3hHXb/nQ1A2/41CWvib8vQHEalvXyTk5MTs2bNokWLFsTFxdGqVSv69euHu7u7rUMTQgghHFLOiRNEv/wKAN6jx7L9YhWM+gxC6/vSpl+4bYNzIJW25qxq1aq0aNECgKCgIPz8/EhKSrJtUEIIIYSDMiYmcvnJJ1Gys3G/6y5OVx9AYlQGrp5aeo5thFotHQBKym6Ts+3btzNw4EBCQkJQqVSsXr26yDyzZ8+mZs2auLi40Lp1a3bs2HFb2zpw4ABms5nq1eWCq0IIIURpKXo9V55+BmN0DLrwcHIee5XjO2Ms55mNaYy7t7OtQ3QodtusmZmZSfPmzRkzZgzDhg0rMn358uVMnTqV2bNn07lzZ+bOnUvfvn2JiIigRo0aALRu3Zrc3Nwiy27cuJGQkBAAEhMTGTVqFN9+++1N48nNzS2wrrS0tP/y8oQQQogKQVEUYt9+h+yDB1F7euI14zNWL4oEoFXvMKo38rNxhI5HpSiKYusgbkWlUrFq1SqGDBliLWvfvj2tWrVizpw51rKGDRsyZMgQZs6cWaL15ubm0rNnTx5//HFGjhx503nfeOMN3nzzzSLlqampeHl5leyFCCGEEBVM0o8/cvXtd0ClImT2HDbucSMuMp2qtb0ZMq2l3V3QPC0tDW9vb7s+ftvXO1ZCer2egwcP0qtXrwLlvXr1YteuXSVah6IoPPbYY9xzzz23TMwAXn75ZVJTU623y5cv31bsQgghREWRuWcPV2dYKkSCnn+eiJRqxEWm4+zuRM9xje0uMXMUDvmuJSQkYDKZCA4OLlAeHBxMbGxsidbx999/s3z5clavXk2LFi1o0aIFR48eveH8zs7OeHl5FbgJIYQQlZU+MpIrz0wFkwmvQQPJuXso/2y0NGfeM6Ihnn4utg3QgdntOWclUfjSD4qilPhyEHfddRdms7k8whJCCCEqNFN6OpcnP4k5NRWXZs3we2U6Kz/4FxRo2KkqtVoG2jpEh+aQNWcBAQFoNJoitWRxcXFFatOEEEIIUXYUk4moac+hP3cOpypVqPblF/y9KpL0pBy8Aly468G6tg7R4TlkcqbT6WjdujWbNm0qUL5p0yY6depko6iEEEKIii/ugw/J3LEDlYsL1b76ksjLcGpvLKq8yzPpXBy6Uc4u2O07mJGRwdmzZ63PL1y4wOHDh/Hz86NGjRpMmzaNkSNH0qZNGzp27Mi8efO4dOkSkyZNsmHUQgghRMWV8tNPJH3/PQAh783EFFKHrW/vBaB133Cq1PK2ZXgVht0mZwcOHKB79+7W59OmTQNg9OjRLFy4kOHDh5OYmMhbb71FTEwMTZo04bfffiMsLMxWIQshhBAVVtaBA8S8+RYAAVOm4NmrN2s+P0xulpGgME/a9A+3bYAViEOMc2aPHGGcFCGEEKIs6C9e5OLDj2BKTsazbx9CP/mEI1uusHPFGZy0ah58tS2+VRzj2tSOcPx2yHPOhBBCCHFnGBMTuTRhIqbkZFyaNCFkxgxS47LZs+ocAJ2G1XGYxMxRSHImhBBCiGKZs7K4POkJDJcuoa1WjepfzwFnFzZ/fwKjwUy1Br406Rpq6zArHEnOhBBCCFGEYjQS9ew0co4eRePjQ/Vv5uEUEMCRvy4Tez4VrYuG7iMblHh8UVFykpwJIYQQogBFUYh98y0ytm1D5exMtTmzca5Zk+TYTPb8eh6AzsPq4OXvauNIKyZJzoQQQghRQMKXX5GyciWo1YR+/BFuLVtiNiv8tegEJoOZ6o38aHRXiK3DrLAkORNCCCGEVeL8BSR89RUAwa+9iue99wLw7+bLxJ5PszRnjpDmzPIkyZkQQgghAEhetoy4Dz4AIHDqM/g98oilPDaTvWsszZl33V9XLmpeziQ5E0IIIQSpv/5KbN4gs/6PP47/xIkAmM0Km7+3NGfWaORHw85VbRlmpSDJmRBCCFHJpf3+O9EvvwKKgu+jjxI47Vlrs+XhPy9x9UIaOhcN3aQ5846Q5EwIIYSoxFLXrCHquefBbMb7vvsIfvUVawKWHJvJvjUXAOj8gDRn3imSnAkhhBCVVMrPPxP94kuWxOz+YVR9+y1UaktqYO2daTRTo7EfDTtJc+adIsmZEEIIUQklL1tGzKuvgaLg8/BDVH3rLVQajXX60S1XrL0zuz0qzZl3kpOtAxBCCCHEnZU4f4G1V6bvqJEEv/xygeQrNT6LPavzrp15Xx1pzrzDJDkTQgghKgnFbCbugw9JWrgQAL9xYwl6/vkCiZliVtiy+CRGg5nQ+j40lsFm7zhJzoQQQohKQNHriX7lVdLWrQMg6H/P4zd2bJHmyuM7o4k6lYKTTm0ZbFYtzZl3miRnQgghRAVnysgk6umnydy1C5ycCHn3HbwHDy4yX3pSDrt+OQtAh8G18Q50u9OhCiQ5E0IIISo0/ZUrXHliMrlnzqByc6PaZ5/hcfddReZTFIWtP57EkGOiSi1vmnavZoNoBUhyJoQQQlRYmfv2EfX0M5hSUnAKDKTa7Nm4Nm1S7Lyn9sRy6XgSGic194xqgFqaM21GhtIQQgghKqDk5Su4NHYcppQUXJo0IfynlTdMzDJTc9m58gwAbQeE41vF/U6GKgqRmjMhhBCiAjHr9cS99x7JS5YC4NWvH1VnvIvapfjhMBRFYduSU+RmGQms4UnLnjXuZLiiGJKcCSGEEBWE/soVoqY+S86xYwAETn0G/4kTbzqA7NmDcVz4NwG1WsU9oxqi1kijmq1JciaEEEJUAGmbNhHzyquY09PReHtT9f338OzW7abLZKfr2bH8NACt+4YRUM3jDkQqbkWSMyGEEMKBmfV64j/+mKTvFwHg2qIFoZ98jDbk1oPH7lhxhux0A34h7rTuG17OkYqSkuRMCCGEcFA5J04Q/cKL5J6xnMzvN2YMQdOeRaXV3nLZ84fjObP/KioV9BjdEI2TNGfaC0nOhBBCCAejGI0kfjef+C+/BIMBjZ8fVd95B897updo+ZxMA9uWngKgZa8aBIV5lWe4opQkORNCCCEciP7iRaJfepnsw4cB8Li3B1XffBMnf/8Sr+Pvn8+SlarHJ9iNtv1rllOk4nZJciaEEEI4AEWvJ3H+fBJmz0HR61F7eBD86qt4Dxl8096YhUUeT+TkrhhQwT0jG+Ck05Rj1OJ2SHImhBBC2LmsgweJmT4d/dlzALh36kTVt99CGxpaqvXkZBrYsugEAM26V6NqHZ+yDlWUAUnOhBBCCDtlTEoi/tNZpKxcCYDGz4/gl1/Ga0D/UtWW5dux4jSZec2ZHYbULutwRRmR5EwIIYSwM4peT9KPS0iYPRtzejoAPg/cT9Bzz6Hx8bmtdZ4/FM/pvdd6Z2qlOdNuSXImhBBC2AlFUcjYspW4999HHxkJgHOjhlR59VXcWre+7fVmp+vZuuQkAC17hVGllneZxCvKhyRnQgghhB3IPnqUuE8+IWv3HgA0AQEEPTsV7yFDUGluv5Yr/9qZ+YPNthsgvTPtnSRnQgghhA3lnDpN/Oefk7F5MwAqrRa/xx7Df+JENB7u/3n9Zw5c5dyheNRqFfc+1giNVgabtXeSnAkhhBA2oL94kfgvviTtt99AUUCtxnvQIAKmPImuWrUy2UZmSi7bl+ZdO7NfOIE1PMtkvaJ8SXImhBBC3EG5Z8+S+M23pK5bByYTAJ59+hD41BSca5ddD0pFUdiy+CS5WUYCa3jSum9Yma1blC9JzoQQQog7IPvoURLnzSN905/WMo+uXQl85mlcGjUq8+0d2xZF5LFE1E4qejzWEI1GmjMdhSRnQgghRDlRFIWsvXtJnDePzF27reWePe/Ff8IEXJs2LZftJkZn8PfPZwHoNLQO/iEe5bIdUT4kORNCCCHKmFmvJ+2330j+YTE5x49bCjUavAcMwP/x8TjXqVNu2zYaTGz6LgKTwUyNxn40u6dszl8Td44kZ0IIIUQZMVyNI2X5MpKXr8CUmAiAytkZn2HD8Bs7Fl210l1u6XbsWXWexKgMXD219Bjd6LauJCBsS5IzIYQQ4j/K/vdfkn5YTNqGDWA0AuAUHIzvI4/g8+ADOPn63pE4Io8n8u9flwG4Z1RD3Lx0d2S7omxJciaEEELcBkWvJ+2PjST98AM5R45Yy11bt8Zv5Ag8e/RApdXesXiy0/Vs/t5yUfOm3aoR3jTgjm1blC1JzoQQQohSMCYkkLx8OcnLlmGKTwAsA8d69e+P74gRuDZpfMdjUswKm78/QXaaHr8QdzrdJxc1d2SSnAkhhBAlkH30GMmLfyDtt99RDAYAnAID8X3kYXwefBAnf3+bxfbPxkgijyWi0arpObYxTnJRc4cmyZkQQghxA4rBQPqmTSQt+oHsw4et5a7Nm+M7ciRevXqi0tn2vK6oU8ns/fU8AF0eqkdANRk2w9FV+uQsKyuLhg0b8sADD/DRRx/ZOhwhhBB2wJiURMqKFSQvWYoxLs5SqNXi1bcPfiNG4NqsmW0DzJOZmssf3x1HUaBBxyo06hxi65BEGaj0ydm7775L+/btbR2GEEIIO5Bz4oSl1+W6dSh6PQCagAB8hw/HZ/iDaIOCbBzhNWaTmU3fHSc7TY9/qDtdHq5v65BEGanUydmZM2c4efIkAwcO5NixY7YORwghhA0oRiPpf/1F8qIfyDpwwFru0qQJfqNG4tmnD2obN10WZ9/aC0SdTkHrrKH3403QynlmFYbdXmhr+/btDBw4kJCQEFQqFatXry4yz+zZs6lZsyYuLi60bt2aHTt2lGobzz//PDNnziyjiIUQQjgSU2oqid/N51yv3kQ9/YwlMdNo8OrXl7ClSwhfuQLvQYPsMjE7ezCOgxsiAeg+sgG+VdxtHJEoS3Zbc5aZmUnz5s0ZM2YMw4YNKzJ9+fLlTJ06ldmzZ9O5c2fmzp1L3759iYiIoEaNGgC0bt2a3NzcIstu3LiR/fv3U69ePerVq8euXbtuGU9ubm6BdaWlpVkeLB4GrtePY1NoJOaSjMxcZJ6SrONW85TDOsptO7faRknWcYdiVamvu6lApSlUVni6GtQ3mkdV6Hnh+VSWZdVa0GhB7WS5abR5ZU7XTSv8/Pr58p/rwMm5ZN9JISqw3PPnSfrhB1JX/4qSnQ2AxscHn+HD8X34IbRVqtg4wpuLv5zO5u8jAGh+b3Xqtgm2cUSirKkURVFsHcStqFQqVq1axZAhQ6xl7du3p1WrVsyZM8da1rBhQ4YMGVKi2rCXX36ZxYsXo9FoyMjIwGAw8Nxzz/H6668XO/8bb7zBm2++WaQ89SVPvJzlYCcciJPLtZvW5QbPncHJ1XKvzb93A5173s2j4GPrtLxySQKFnVHMZjJ37iRp0Q9k7txpLXeuVw+/USPxGjAAtYuLDSMsmaw0PSvf209GUi41GvnR/8lmqDV22whml9LS0vD29iY1NRUvLy9bh1Msh0zO9Ho9bm5urFy5kqFDh1rne+aZZzh8+DDbtm0r1foXLlzIsWPHbtpbs7ias+rVq5O650e8PNzySgu9lUXe2mLe6lu9/cVOL+V2ymIdd2o7t7WO4hYpp1gVBRQzKKa8e/N1ZXk3s6ng8wLTC0+7bnqR5fLKzAYwG8F0/b0BTMa8+0LlZmPBacV9luVNpSmUwBVO6IpJ8G41n9YN1HIQEqVjzs4mZdUqkhf9gP7iRUuhSoXHPffgN3Ikbu3bOcy1J01GM7/OOkTM2VR8gt24/8XWOLvduSsQVBSOkJzZbbPmzSQkJGAymQgOLliVGxwcTGxsbLls09nZGWdn56ITGg4AO/1whQAsCZ7JAKZcMOaCMQcMOZb7/FtJnhuyLDd9Jugz8u6zrnucCUZLExGKCXJTLbeypL1FsufkbLlpdHk1gDrQOF9X7nxd2fXT8+41urzHumvNwBqdpVnYQQ7gwsKYmEjyj0tIXrIEU0oKAGoPD3yGDcN3xKPoqle3bYClpCgKW5ecIuZsKjpXJ/o90VQSswrMIZOzfIX/7SiKclv/gB577LEyikgIO6TWWG7aO9BkYzZdS9SuT+IMeUlcbsa1x4Xnyc0olPhdNz2/9s+Qablllv9LKUh1XbKmvS6hy0/qtIWmXffYOk1XcB1at2vNwVo30LnlJZ+Fy90tn58okdwLF0hasJDU1autQ2Foq1XDb/RovIcORePhmCfO7193gZO7YlCpoNe4xtIBoIJzyOQsICAAjUZTpJYsLi6uSG2aEOIOUmvAxctyKyuKAobsYhK3Yh7n1wya9EUfm/R5NYH6vFrEvMfGnGs1iyZD3ryFOxIpedOLdjC6IzR55/5dn8hdX3NYoEbRrWBTsHW+Ysqd7K8X4u3K+ucfEr+bT8Zff1lPSXBp1gz/sWPx7HkvKo3jJrgRO6PZv/4iAF0erk9YE9tdJkrcGaVOzkwmEwsXLmTz5s3ExcVhNpsLTP/rr7/KLLgb0el0tG7dmk2bNhU452zTpk0MHjy43LcvhLiDVKq8xMINCLwz21SUvHP38hO7YpI362P9tZsx//GN5r2uedmQfa2Z2JBlaSI25DUV55fn1xjmJ4Y5KWX7OtXaWyRzxXX4cLN0Frlp7+DCvYw1gCqvabi091x7ni+vXDGZSd+6naTvfyT7yFHrZI9uXfAfPQLXVi0trSmmXDBRqGlaVWBdxZcV3WaxZeXY5H3xSAJbl5wCoE2/cJp0CS23bQn7Uerk7JlnnmHhwoX079+fJk2alNuJlBkZGZw9e9b6/MKFCxw+fBg/Pz9q1KjBtGnTGDlyJG3atKFjx47MmzePS5cuMWnSpHKJRwhRiahUec2SWktSYguKkpfEXZ/AXXdf4HFG3vl/eY+vn+f6myHv3mRp7sNsgJxUy82BmE2QesGNxJMeGDIshzGVWsE7PAu/Bpk4ey2DP5bBH7aMsiTJX3Fl16ZF6xvwR8JLKIoLDdy20e7fR+BoCRLHYtd/s9huti51XvKdN5SPWnvd8+sTc82151qXYmp03a/9AXDxBlc/cPMDN39w9pRzOgspdXK2bNkyVqxYQb9+/cojHqsDBw7QvXt36/Np06YBMHr0aBYuXMjw4cNJTEzkrbfeIiYmhiZNmvDbb78RFhZWrnEJIcQdoVJZDnJaF8tBrCyZDMUnbTdK5grfjDk36TlcTE9iswlrLaCiYO35XNz9TZiNKpLPupF00gNjjqWZUq0z41snE7+6mTi5mm+6/J11/estftLNxOrrsi75BYyKCzV0/9DN8wtUJpOlBrCiUWuvJWoeweAVCt6h4BUCXtUsj72rg3PluaB7qYfSCAkJYevWrdSrV6+8YnIIjtAVVwghHJJSMGkzpaeRvGQpST/8iCk5GQCn4GD8x4zG576hqF3zO7sUlxDdbtl104pNsG4233/bZnxUDqvnXUGfYya0liv9H6uKVqe+jW0WF39JXud1ZWbTtQS7QMJtLDSEj+naY0POdYl9VtHa3JxUyE6GrERLeUl5VgX/OuBfO+++DgTUA9+apRpmxxGO36VOzj7++GPOnz/Pl19+6TBjw5QHR/hwhRDCkRmTk0n6/nuSf1yCOT0dAG2NGgRMeBzvQYNQ2eFllf6rhCsZ/PrpIXIyDVSt7c2Ap5qjc3HIvnslY8iGrCRLopaVAOmxkBoFafm3aEi9cvPzLXUeENwEqjS13Ko2szzXFD/UiCMcv0udnA0dOpQtW7bg5+dH48aN0WoLvvhffvmlTAO0V47w4QohhCMyxMWRNH8BycuXWy+vpKtTm4CJk/Dq2weVU8VMVmIvpLLui3/JzTISFO7F4GdaoHOtmK+11LKTIfE8JJ7Nu52x3CecsTSzF+bkCiEtoXo7y61aO/CwdChyhON3qT91Hx+fAj0khRBCiLKgvxJF4nffkvrzL9YxylwaNcL/iUl49uiBqgJfIeLKqWTWzz6CMddElVpe9H+yuSRm13P1hWqtLbfrmYyWJC32KMT+a7mPPmypabu0y3LLF9gAwu+GwELrsEMOcfkme+QImbcQQjiC3AsXSJz3Dalr14LRCIBrq1YEPDEJ97vuqvCn0Jw/HM/Gb49jMpqp1sCXvpOaVuymzPKmKJaE7fJeuLzPcos/Sf65dGm5Ct7vpdv18fu2P/34+HhOnTqFSqWiXr16BAbeofGHhBBCVAg5p06ROHcuaRv+gLwxM907dcR/0iTc2rat8EmZoij8u/kyf/98FhSo2TyAXuMb46R13AFz7YJKBQF1LbeWIyxlWUkQ+Tdc2AEntgAHbBrirZS65iwzM5OnnnqKRYsWWQeg1Wg0jBo1ii+++AI3N7dbrKFikJozIYS4PdlHjpDw9VzLaP55PLp3J2DSRFybN7dhZHeOyWRmx7LTHN8RDUDju0Po8lA91JqK23RrLxzh+F3qmrNp06axbds21q5dS+fOnQHYuXMnTz/9NM899xxz5swp8yCFEEI4vqz9+0mY8zWZu/LOA1Kp8OzTm4CJE3Fp0MC2wd1BOZkGNn57jMsnkkEFnYfVoXmP6hW+plCUXKlrzgICAvjpp5/o1q1bgfItW7bw4IMPEh8fX5bx2S1HyLyFEMLWFEUhc+ffJHz9NdkHD1oKNRq8Bw7Ef8LjONeqZdsA77C4yDQ2zDtGemIOTs4aeo1tRM3mclrQneQIx+9S15xlZWUVe3HxoKAgsrJKMZicEEKICksxm8n46y8S5nxNzvHjAKi0WryH3Yf/+PHoqlWzcYR3lqIoHNsWxc6fzmA2KngFuNBnYlMCq3vaOjRhh0qdnHXs2JHp06ezaNEiXFwsozJnZ2fz5ptv0rFjxzIPUAghhONQTCbSft9A4ty55J45A4DK1RXfBx/Eb+wYtMX8ua/ocjIMbF1yinP/xAGWE/97jG6Is1vxg6QKUerk7LPPPqNPnz5Uq1aN5s2bo1KpOHz4MC4uLvzxh02vMiuEEMJGFL2e1LVrSZz3DfrISADUHh74PvoofqNH4eRXxtcHdRAXjyaw5YeTZKXpUalVdLqvtpxfJm7ptsY5y87OZvHixZw8eRJFUWjUqBGPPvoorq6u5RGjXXKENmshhChv5qwsUn76icT5CzDGxgKg8fHBb/QofB99FE0l3T/qc4z8vfIMEX/HAOBbxY17xzQiKKxyvh/2xBGO37c1zpmrqyuPP/54WccihBDCQZhSU0lesoSkRT9cuxh5YCB+Y8bgO/xB1O7uNo7QNhRF4fyheHauPENGci6ooHmP6nQYVAsnnYxfJkqmRMnZmjVr6Nu3L1qtljVr1tx03kGDBpVJYEIIIeyPMT7ecjHypcswZ2YCoK1eHf/x4/EeMhi1s7ONI7SdlLgsdiw/zaXjSQB4Bbhwz6iGhNbztXFkwtGUqFlTrVYTGxtLUFAQ6ptc20ylUmEymco0QHvlCNWiQghRVvRXrpD43XcFrnvpXK8e/hMm4NWnd4W9GHlJGA0m/vnjEv9siMRkNKN2UtGqVxit+4RJbZkdcoTjd4l+TflXAij8WAghRMWWe+YMCd98Q9r63yDvz7drixb4T5yAR7dulfrEdsWscHpfLHvWnCcjKReAag186fpwfXyCK8fVckT5KPVfnUWLFjF8+HCcC1Vd6/V6li1bxqhRo8osOCGEELaR/e+/JMz7hozNm61l7p074z9xQqW47uWtXI5IYteqsyRczgDA3ceZzvfXoU7roEr/3oj/rtS9NTUaDTExMQQFBRUoT0xMJCgoSJo1hRDCQSmKQtbu3STM+4asPXsshSoVnj174j9hAq5NGts2QDsQfzmd3avOcTnCcl6ZzkVD677hNOteTZowHYQjHL9LXXOmKEqx/wquXLmCt7d3mQQlhBDizlHMZtI3byZx7jxyjh2zFDo5WS6x9Pj4SneJpeIkRmVw4PeLnD0YBwqoNSqadq1G635huHrobB2eqGBKnJy1bNkSlUqFSqWiR48eOF138qfJZOLChQv06dOnXIIUQghR9hSDgdT160n85lv0584BoHJxwef++/EfOwZtSIiNI7S9uMg0Dvx2kQv/JljL6rYJov3g2ngHVp6xPcWdVeLkbMiQIQAcPnyY3r174+HhYZ2m0+kIDw9n2LBhZR6gEEKIsmXOySHl559J+m4+huhoANSenvg+8gh+o0bi5O9v4whtL/Z8Kgd+u0jksURLgQpqtwyiTb8wAqrJ9TBF+SpxcjZ9+nQAwsPDeeihh4p0CBBCCGHfTOnpJC9dRtL332NKtCQdGn9//B4bje9DD6HxlKQj6nQyB367yJWTloF1VSqo2y6Y1r3D8QupnAPrijuv1OecNWrUiMOHD9O+ffsC5Xv37kWj0dCmTZsyC04IIcR/Z0xMJOn7RSQvWYI5w9K7UBsSgt/4cfjcdx9qFxcbR2hbiqJw+UQSB367SMzZVADUahX1O1ShVZ8wfIJkWAxxZ5U6OXvyySd54YUXiiRnUVFRvP/+++zdu7fMghNCCHH7DFFRJM5fQMpPP6HkWsbh0tWuTcCEx/Hq1w+VVmvjCG1LURQijyZy4PeLXL2QBoDaSUWjTiG07FUDrwA5p0zYRqmTs4iICFq1alWkvGXLlkRERJRJUEIIIW5f7rlzJH7zLanr1oHRCIBL06YETJyAxz33oLrJlV4qA8WscP5wPAd+v2gdp0yjVdP47hBa9gzDw1dO2xG2VerkzNnZmatXr1KrUNfqmJiYAj04hRBC3FnZR4+ROG8e6X/+CXlDWLp16EDAxAm4dehQ6QdHNZsVzh68ysHfI0mKtlwX1MlZQ9OuobS4twZuXjIkhrAPpc6mevbsycsvv8yvv/5qHdcsJSWFV155hZ49e5Z5gEIIIW5MURSy9u0nce5cMnftspZ73NuDgAkTcG3WzIbR2QeTyczpvVc5uOEiqXHZgGXw2Gb3VKf5PdVx8ajczbvC/pQ6Ofv444/p0qULYWFhtGzZErAMrxEcHMwPP/xQ5gEKIYQoSlEUMrZuJXHuPLIPH7YUajR4D+iP//jxONeta9P47IHJYObE7hj++SOS9MQcAJzdnWjRozpNu1XD2U2SMmGfSp2chYaGcuTIEX788Uf+/fdfXF1dGTNmDA8//DDaSn5yqRBClDfFZCL9jz9ImDuP3FOnAFDpdHjfNxT/8ePRVatm4whtz6g3EfF3NIc2XiIj2dIRwtVTS4ueNWjSJRSdi5yCI+zbbX1D3d3dmTBhQlnHIoQQ4gYUvZ7UNWsso/lHRgKgdnPD5+GH8Bs9Gm2h6x1XRvocI8e3R3Poz0tkp+kBcPfW0bJXGI3uDkEr174UDuK2/z5ERERw6dIl9Hp9gfJBgwb956CEEEJYmLOzSVn5E4nz52OMjQVA4+2N76iR+D36KBofH9sGaAdys40c3XqFf/+8TE6mAQBPPxda9QmjYceqaLSVu3eqcDylTs7Onz/P0KFDOXr0KCqVCiWvR1B+LyCTyVS2EQohRCVkSk8neclSy2j+SUkAOAUG4jdmDL7DH0TtLqPV52YZ+PevKxz56zK5WZYhQ7wCXWndJ4z6Haqg0UhSJhxTqZOzZ555hpo1a/Lnn39Sq1Yt9u3bR2JiIs899xwfffRRecQohBCVhjEpyTKa/48/XhvNv1o1/MePx3voENRy6TxyMg38u/kyR/66jD7HUiHgW8WN1n3DqdsmCLUkZcLBlTo52717N3/99ReBgYGo1WrUajV33XUXM2fO5Omnn+bQoUPlEacQQlRohpgYEhcsIGXFSpQcS89CXZ3aBEyYYBnNX8aRJDtDz+E/L3N0yxUMuZakzC/EnTb9wqnTKgiVunKP4yYqjlL/2k0mEx4eHgAEBAQQHR1N/fr1CQsL41RezyEhhBAlo78SReLcuaSsXg0Gy/lSLk2aEDBpoozmnycrTc/hPy9xdFsUxrykzD/Ug7b9w6nVIlCSMlHhlDo5a9KkCUeOHKFWrVq0b9+eDz74AJ1Ox7x584pcNUAIIUTxrEnZqlXWSyy5tWtHwKSJuHXsWOlH8wfITM3l8KZLHNsehVFvBiCwhidt+oVTs1mAJGWiwip1cvbaa6+RmWm57MU777zDgAEDuPvuu/H392f58uVlHqAQQlQkhqgoEubOI+WXX6xJmXunTgRMeRK3Yq5bXBllpuRyaOMlju2IwmSwJGVBYZ607V+TsKb+kriKCk+l5He3/A+SkpLw9fWtVD+YtLQ0vL29SU1NxcvLy9bhCCHsnDUpW7XK2nwpSVlBGck5/PPHJSJ2RmMyWpKy4JpetO1fkxqN/SrVMUaUH0c4fpeq5sxoNOLi4sLhw4dp0qSJtdzPz6/MAxNCiIrAEB19rabMmpR1JODJJ3Fr3drG0dmH9KQc/tkQScSuaMxGS31B1dretO1fk2oNK9cffyGglMmZk5MTYWFhMpaZEELcgiE6moR580j5+VpS5taxA4FTpkhSlictIZuDf0RyclcMZpMlKQup60Pb/uGE1pekTFRet3XO2csvv8zixYulxkwIIQoxxMSQMHdu0aTsySdxa9PGxtHZh9T4LA5uiOTU7ljMZktSFlrf15KU1fO1cXRC2F6pk7PPP/+cs2fPEhISQlhYGO6FRqn+559/yiw4IYRwFIaYGEtN2U8/X0vKOnQg8MnJuLVta+Po7ENybCYHf4/k9P6rKHlJWfWGvrTpX5OQOj62DU4IO1Lq5GzIkCHlEIYQQjgmQ0wMid98Q8rKn1Dyk7L27Ql4cjLu7drZODr7kBiVwYHfLnL2nzjI64JWo7E/bfuHU6WWt22DE8IOlbi35vz583n00UdxlkuHAI7R20MIUX4MsbEkzpsnSdlNxF9KZ//6C1z4N8FaVrN5AG36hRMUJvtNYRuOcPwucXKm0WiIiYkhKCgIgJCQEHbt2kV4eHh5xleuLly4wNixY7l69SoajYY9e/YUaaa9EUf4cIUQZc+SlH1DysqV15Kytm0JmDIF9/aSlAHEnk/lwG8XiTyWaClQQe2WQbTpF05ANQ/bBicqPUc4fpe4WbNwDpeeno7ZbC7zgO6kxx57jHfeeYe7776bpKQkqRUUQtyQ4epVS1K2YsW1pKxNGwKeekqSsjzRZ5LZv/4iV04mA6BSQd22wbTuG45f1ZL98RVC3MY5ZxXF8ePH0Wq13H333YCM1SaEKF5xSZlrm9YETnkK9w7tbRyd7SmKwpWTyRz47SLRZ1IAUKtV1OtQhda9w/AJdrNtgEI4oBJfUVelUhUYc6bw87K2fft2Bg4cSEhICCqVitWrVxeZZ/bs2dSsWRMXFxdat27Njh07Srz+M2fO4OHhwaBBg2jVqhUzZswow+iFEI7OcDWO2Hfe5VzPXiT/+COKwYBrm9bUWLiQsB9+qPSJmaIoXDyawM8fHGTNZ4eJPpOC2klF47tDePStDvQY1VASMyFuU6maNevVq2dNyDIyMmjZsiVqdcH8LikpqUwCy8zMpHnz5owZM4Zhw4YVmb58+XKmTp3K7Nmz6dy5M3PnzqVv375ERERQo0YNAFq3bk1ubm6RZTdu3IjBYGDHjh0cPnyYoKAg+vTpQ9u2benZs2ex8eTm5hZYV1paWpm8TiGEfTFcjSPx229JWb4cRa8HwLV1awKfmoJb+/aVfmBUxaxw4UgCB367SPyldAA0WjWN7gqhVa8aePi62DhCIRxfiZOzBQsWlGccRfTt25e+ffvecPonn3zCuHHjGD9+PACzZs3ijz/+YM6cOcycOROAgwcP3nD5atWq0bZtW6pXrw5Av379OHz48A2Ts5kzZ/Lmm2/e7ssRQtg5Q1wcid8USspatbIkZR06VPqkzGxWOPdPHAd/v0hiVCYATjo1TbpWo8W91XH3lnN2hSgrJU7ORo8eXZ5xlIper+fgwYO89NJLBcp79erFrl27SrSOtm3bcvXqVZKTk/H29mb79u1MnDjxhvO//PLLTJs2zfo8LS3NmtgJIRyXIS6/pmwFSl7tuCRl15hNZs4csCRlybFZAGhdNDTrVo3m91bH1UNn4wiFqHgcskNAQkICJpOJ4ODgAuXBwcHExsaWaB1OTk7MmDGDLl26oCgKvXr1YsCAATec39nZWXpzClGBGOLiSPruO5KXLb+WlLVsaUnKOnas9EmZyWTm1J5YDm6IJC0+GwBnNyea3VOdZt2r4eKutXGEQlRcDpmc5Su881QUpVQ71Fs1nQohKh5jfDyJ335bMClr0YKAp6bg3qmTJGUGMyd2x/DPhkjSk3IAcPHQ0uLe6jTtWg2dq0MfNoRwCA75KwsICECj0RSpJYuLiytSmyaEEJCflH1H8rJlkpQVw6g3cXxnNIc2XiIzJe/98dLRsmcNmnQJReussXGEQlQeDpmc6XQ6WrduzaZNmxg6dKi1fNOmTQwePNiGkQkh7I2l+XI+ycuXo+RYaoJcmze3DB7bWZIyfY6R49ujOfTnJbLTLB0h3H2cadW7Bo06h+Ckk6RMiDvttpMzvV7PhQsXqF27Nk5OZZ/jZWRkcPbsWevzCxcucPjwYfz8/KhRowbTpk1j5MiRtGnTho4dOzJv3jwuXbrEpEmTyjwWIYTjMVy9aul9uWKFtfelS/NmlsFj7+pc6ZOy3GwjR7de4d8/L5OTaRlc19PPhVZ9wmjYsSoabYmHwRRClLFSZ1VZWVk89dRTfP/99wCcPn2aWrVq8fTTTxMSElKkB+XtOnDgAN27d7c+z+8pOXr0aBYuXMjw4cNJTEzkrbfeIiYmhiZNmvDbb78RFhZWJtsXQjgmQ3S0pffldRckd23RwnJB8rvuqvRJWU6mgSN/XebIlivkZhkB8A50pXXfMOq1r4JGI0mZELZW4guf53vmmWf4+++/mTVrFn369OHIkSPUqlWLNWvWMH36dA4dOlResdoVR7hwqhCVif5KFInz5pGyahVcf5mlJ5+UITGA7HQ9h/+8zNFtVzDkmADwreJG677h1G0ThFqSMlFJOMLxu9Q1Z6tXr2b58uV0KLSza9SoEefOnSvT4IQQ4lb0ly6RMHcuqb+uAaOlJsitfXtLTVk7uSB5ZmouhzZd4vj2KIx6MwD+oR606RdO7ZaBqNSVO2kVwh6VOjmLj48nKCioSHlmZmal/2cqhLhzci9cIPHruaSuWwcmS02Qe6dOBEx+Arc2bWwcne2lJ+VwaOMlInZGYzJakrLAGp606RdOzWYBkpQJYcdKnZy1bduW9evX89RTTwHXxhr75ptv6NixY9lGJ4QQheSeO0fC13NJW78ezJakw73L3QQ88QRuLVvaODrbS0vI5uAfkZzcFYPZZDlrpUotL9r0q0mNxn7yJ1oIB1Dq5GzmzJn06dOHiIgIjEYjn332GcePH2f37t1s27atPGIUQghyTp8m8euvSft9A+SdKuvRvTsBk5/AtWlTG0dneylXszi44SKn9l5FMVven5C6PrTpH061+r6SlAnhQEqdnHXq1Im///6bjz76iNq1a7Nx40ZatWrF7t27aSo7SCFEGcs5cYKEOV+TvnGjtcyz570EPPEELo0a2TAy+5AUk8mB3y5y9sDV/JyV6g19adOvJiF1fWwamxDi9pS6t6awcITeHkI4suxjx0mYM4eMzZstBSoVnr17E/DEJFzq17dtcHYgMSqDA79f5OzBOMjbi4c19adNv3Cq1PS2bXBC2DFHOH6XqOYsLS2txCu01xcqhHAM2UeOkPDVbDLyT5NQqfDq14+ASRNxrlvXtsHZgYQrGRz47QLn/om3ltVsHkDb/jUJrOFpw8iEEGWlRMmZj4/PLc9XyL/ouCmv15QQQpRG1j+HSJg9m8ydOy0FajXeAwfgP3EizrVq2TY4OxB/KZ0Dv13k/OFrSVntVoG06RdOQDVJyoSoSEqUnG3ZsqW84xBCVFJZ+/cTP3s2Wbv3WAo0GrwHDSJg4gR04eE2jc0exEWmsX/9RS4eSbAUqKBO6yDa9A3HP9TDtsEJIcpFiZKzrl27lnccQohKRFEUsvbuI+Grr8jav99S6OSEz9Ah+E+YgK56ddsGaAeuXkhj/28XiDyaCIBKBXXaBNOmbzh+Ie42jk4IUZ5u64rlKSkpfPfdd5w4cQKVSkWjRo0YO3Ys3t5yEqoQ4sYURSFz1y4SZs8h++BBS6FWi8+w+wh4/HG0oaG2DdAOxF5IZf+6C1w6ngRYkrJ67arQum8YvlUkKROiMih1b80DBw7Qu3dvXF1dadeuHYqicODAAbKzs63DalQGjtDbQwh7oSgKmTt3kvDVbLIPHwZApdPh88AD+I8fh7ZqVdsGaAfiL6Wzb+15LubXlKlV1G8fTOs+4fgEu9k4OiEqDkc4fpc6Obv77rupU6cO33zzDU5Oloo3o9HI+PHjOX/+PNu3by+XQO2NI3y4Qtiaoihkbt9O/OzZ5Px7BACVszM+wx/Ef9x4tMFFLwVX2SRFZ7Jv3Xlr70uVWkX9DlVo0zcM70BJyoQoa45w/C51cubq6sqhQ4do0KBBgfKIiAjatGlDVlZWmQZorxzhwxXCVhRFIWPrVhJmzyHn6FEAVC4u+D70EH5jx6At5vq8lU1KXBb711/g9L6rlnHKVFC3TTDtBtSUmjIhypEjHL9Lfc6Zl5cXly5dKpKcXb58GU9P6c4tRGWmKAoZf/1FwlezyYmIAEDl6orvww/jP3YMTgEBNo7Q9tKTcjiw/gIndsdaL7NUq2Ug7QbUlN6XQgjgNpKz4cOHM27cOD766CM6deqESqVi586d/O9//+Phhx8ujxiFEHZOMZtJ37yZhNlzyD1xAgCVmxt+jzyM35gxOPn72zhC28tMzeXg75Ec3xmF2WhJysKa+tN+YC0ZPFYIUUCpk7OPPvoIlUrFqFGjMBqNAGi1Wp544gnee++9Mg9QCGG/FLOZ9I2bSJgzh9xTpwBQu7nhO2IEfmMew8nX18YR2l5uloF//rjEkb8uYzSYAajWwJf2g2pRpZb0cBdCFHXb19bMysri3LlzKIpCnTp1cHOrXOdIOEKbtRDlRVEUMjZvJv7zL8g9fRoAtbs7viNH4Dd6tCRlgNFg4ujWKA7+fpHcLMsf2Sq1vGk/uBbV6sv7I4StOMLx+7bGOQNwc3OjadOmZRmLEMLO5Q+JEf/Z5+QcOwaA2sMDv1Ej8Rs1Co2Pj20DtANms8LpfbHsXXOejKRcAPxC3Ok4pDZhTf1veSk8IYQocXI2duzYEs03f/782w5GCGG/MvfsJf6zz8g+dAjIO6ds5Ej8xzwmSRmWxDXyWCJ7Vp8jMSoTAA9fZ9oNrEn9DlVRqyUpE0KUTImTs4ULFxIWFkbLli25zZZQIYQDyvrnEPGff07WHsu1L1XOzvg+8gj+j4/Hyc/PxtHZh9gLqez+5RzRZ1IAcHZzolWfMJp1q4aTTmPb4IQQDqfEydmkSZNYtmwZ58+fZ+zYsYwYMQI/2TELUWFlHztO/Befk7ktb2BprRbfBx7Af+JEGTw2T1pCNrtXnePswTgANE5qmnWvRqs+Ybi4a20cnRDCUZWqQ0Bubi6//PIL8+fPZ9euXfTv359x48bRq1evSncehSOcUCjE7cg9e5b4zz4jfdOflgKNBp/7hhIwaZJc+zKPPtvIwQ2R/Lv5MiajGVTQoEMV2g2shaefi63DE0LchCMcv2+7t2ZkZCQLFy5k0aJFGAwGIiIi8PCoPAMoOsKHK0RpGGJjif/iC1JXrQazGVQqvAYOIPDJJ9GFhdk6PLtgNiuc3BXDnjXnyU7TAxBa35e7HqhDQDUZq0wIR+AIx+/b7q2pUqlQqVQoioLZbC7LmIQQd5ApNZXEb78ladEPKLmW3oWePe8l8JlncK5Tx8bR2Y8rp5LZufIMiVcyAPAOcqXzsDqENwuodC0HQojyVark7PpmzZ07dzJgwAC+/PJL+vTpg1qtLq8YhRDlwJybS/LiH0mYNw9zaioArm1aE/Tcc7i1bGnj6OxHSlwWu34+y4V/EwDQuTrRtn84TbtVQ+Mk+z0hRNkrcXI2efJkli1bRo0aNRgzZgzLli3DXy7JIoTDUUwmUn9dQ/wXX2CMiQHAuW5dAqc9i0e3blILlMeQa+LA7xc5vOkSZpOCSq2iyd0htB1YE1cPna3DE0JUYCU+50ytVlOjRg1atmx50533L7/8UmbB2TNHaLMW4nqKopCxbRvxH39M7pmzADhVrUrg00/jPWggKo0M+QCW9+n84Xh2rjhDRrKlmbdGIz86318XvxB3G0cnhPivHOH4XeKas1GjRsk/aiEcVM6p08S9/x6Zu3YDoPb2JmDiRHwffQS1s7ONo7MfKVez2LH8NJcikgDw9HPhrgfrUrO5nFcmhLhzSjUIrRDCsRgTE4n//AtSVq4EsxmVVovf6FH4T5iAxk7/MdqCIdfEwd8vcujPS5iNCmonFa16hdGqTxhaGURWCHGH3XZvTSGE/TLr9SQvWkTC13MxZ1h6F3r26UPQ88+hq1bNxtHZl/OH49mx4rT1Opg1Gvtz9/C6+AS52TgyIURlJcmZEBWIoiik/7GRuI8+wnDlCgAujRsT/PJLuLVpY+Po7EtGci7bl52y9sKUJkwhhL2Q5EyICiInIoLYGTPIPnAQAKegIAKnPYv3oEGoZKgbK8WscGx7FLtXn8OQY0KtVtGyVw1a9wuXJkwhhF2Q5EwIB2dKTSX+s89IXrbccl6Ziwv+Y8fiP34cajdpmrteUnQmWxafJPa8ZVy34JpedB/RAP/QynN1EyGE/ZPkTAgHpZjNpP7yC3Eff4IpORkAr379CHrhf2irVLFxdPbFZDBzYMNF/tkQidmkoHXW0GFIbZp0DUWtliZMIYR9keRMCAeUffQYsW+/Tc6RIwA4161D8Gv/h3v7djaOzP7ERabx58ITJMdkAhDeLIAuD9WTC5QLIeyWJGdCOBBjcjLxsz4jZcUKUBTU7u4ETJmC34hHUWm1tg6vTCmKQrYxm9TcVFL1qaTkppCam0q6Pp1cU67lZsy1Ptab9ChcN6a2SYXrkeq4Hq2OSlFhdtGT1eECx2ru59T5P3G66IRWrcVJ7WS9Xf+88GOdRoezxhmdRoeLxsX6PP+m0+hQq+TcPiHEfyfJmRAOQFEUSxPmBx9iyrsOptfAgQT973m0QUE2ju72ZegzOJ96nsi0SGIyYyy3jBjr42xj9m2t1z8zlO5nH8UtKxSAM/4H2VnzJ3Jzs+BkWb6CgnTq6xI4p4IJnIuTC+5O7rhr3XHTuuGmdbvpc3cndzx1nnjqPNGopaOCEJWJJGdC2Lnc8xeInT6drP37AXCuV48q//cabm3b2jiyklMUhUvplziWcIyIxAjOppzlXMo5rmZdveWyTmonfJx98HH2wUvnhZezFy4alwI1Vi5OLujUOjCrUA75oRzzB7MKXIyoulylfm0P6iuPYVJMGM1GDGYDRrPRclOMGEyGa4/NhoLT8+bXm/ToTfprtXZ5N7NitsaqN+vRm/VgKNv3z1PriZezl/X1e+ksN29nb2uZt84bb2dvfF188XPxw8fZBye17OKFcETyyxXCTpn1ehLnfUPi3LkoBgMqV1cCn3oKv1EjUTnZ908305DJobhD/HP1H44mHOV44nHS9enFzhvoGki4dzgh7iGEeIRQ1b0qVdyrEOIRQoBrAG5ObiUadyw5NpNN8yOIv2TZTq0WgXR9pD5uXuV7kfL8xK1wM+v1za05phyyjdlkGbLIMmSRacwk05BZ/HNjFpkGy/P8msN0QzrphnSiiCpVbN7O3vi5+BW55Sdw19+8nb2lWVYIO2Hfe3ghKqms/fuJmf4G+vPnAXDvcjdVXp+OrlqojSMrXo4xh4NXD7I/dj/7r+7neMJxTIqpwDw6tY4G/g1o4t+Eer71qO1Tm5reNfF29v5P21YUhYid0exccQajwYyzmxNdHqpH3bbBd2QwWa1ai1atxV1b9hdFN5gNpOWmkaa33FJzUy2Pc9NI1adem5Z7bXpybjLJOckoKJbz9XJTuZB64ZbbclI54efqR5BrEAFuAQS6BhLoGljgcaBbIH4uflIjJ0Q5k1+YEHbElJLC1Y8+IvWnnwHQBARQ5ZWX8ezb1+5GrY/OiGb7le1sv7KdfbH7yDXlFpge6hFKm+A2NAtsRpOAJtT1rYtWXbadFnIyDWxZfJLzh+IBqNbAl3sfa4S7T8W4mLtWrcXf1R9/V/9SLWcym0jJTSE5J5mknCSScpNIyk4iKSfpWlneLTk3mdTcVIyKkbisOOKy4iDxxutWocLPxY9At0ACXC2JW7B7MCHuIVT1qGqt+XTWVIzPQAhbkORMCDugKApp63/j6syZmBItR0afBx8k6LlpaLz/W81SWVEUhRNJJ9h4cSPbrmzjbMrZAtOruFehQ9UOtK3SljbBbQjxCCnXeKJOJbNpQQSZKbmoNSo6DK5Ni3uro5Jxy9CoNaVK6gxmA4nZiSRkJxCfFU98djwJ2QnEZcVZyrLjSchKIDEnEZNiIjEnkcScm2RwQIBrAFXdLclafnN1mFcY4d7hVHWvKk2oQtyEJGdC2Jjhahyxb7xBxpYtAOhq16bqW2/i1rq1jSO7lpD9cfEPNl7cyJWMK9ZpGpWG5oHN6VKtC3dXu5u6PnXvSO2eyWRm/9oLHPwjEhTwDnKl17jGBIV5lfu2KyqtWksV9ypUcb/54MUms4nk3OQCCVx8VjyxWbFFetkmZCeQkJ3A0YSjRdajU+uo4VWDmt41CfcKp6Z3Ter71aemd80yr10VwhGpFEVRbj1bxfTpp5/y7bffoigK9957L5999lmJDy5paWl4e3uTmpqKl5ccFETpKYpC6qrVXH3vPcxpaaDVEjBpIv6PP45aV74nsd/K+ZTzrDm3hj8u/lEgIXPRuHB3tbu5t8a9dA7t/J/PFyut9KQc/vjmGFcvpAHQsFNV7nqwLjoX+Z9pLxRFISU3hejMaGIzYonOjCY6I5qojCgupV3iUvolDObiu7Pq1Drq+NahoV9DGvg1oLF/Yxr4N5CETZQpRzh+V9rkLD4+ng4dOnD8+HG0Wi1dunTho48+omPHjiVa3hE+XGG/DDExxEyfTub2HQC4NGlC1XffxaV+PZvFlJqbyu8XfufXs79yLPGYtTw/IesV3osuoV1w09rmep2XjieyaX4EOZkGdK5OdHu0PnXbBNskFnH7jGYjMRkxXEi7wMXUi1xMu8i5lHOcSj5FpiGzyPwuGheaBTajRVALWgW1omVQS5t9B0XF4AjH70r9d9NoNJKTkwOAwWAgyIEH8xSOQVEUUlauJO79DzBnZqLS6Qh4agr+Y8bYZHgMg9nArqhd/HruV7Ze3mqt0dCoNNwdejf9a/e3aUIGYDYr7F9/gQO/XQQFAmt40vvxJngHutosJnH7nNROVPeqTnWv6nSp1sVablbMRKVHcSLpBCeTTnIi6QRH4o+Qpk9jX+w+9sXusy7fKqgVnUM7c1foXXesOV2IO8lua862b9/Ohx9+yMGDB4mJiWHVqlUMGTKkwDyzZ8/mww8/JCYmhsaNGzNr1izuvvvuEm/jiy++4NVXX8XJyYlJkyYxY8aMEi/rCJm3sC/6K1HEvv5/ZO7aDYBr8+ZUnfEuzrVr3/FYYjNjWXl6Jb+c+YWE7ARreX3f+gyuM5h+NfuVuodgechO17Pxu+NcOWm5sHvju0O468G6OGllxPzKwKyYuZB6gX/i/uHQ1UP8E/cPURkFx3oLcguiR40e9AnvQ4ugFtLRQNySIxy/7bbmLDMzk+bNmzNmzBiGDRtWZPry5cuZOnUqs2fPpnPnzsydO5e+ffsSERFBjRo1AGjdujW5ublFlt24cSOurq6sW7eOixcv4urqSt++fdm+fTtdunQpMr8Q/4ViNpO8bBnxH32MOSsLlbMzgVOnWgaT1dy5JMNkNrErehcrTq1ge9R268j2fi5+9KvZj8F1BtPAr8Edi+dWYs6l8sc3x8hMycVJp6bbow2o3/7mJ6yLikWtUlPbpza1fWrzQL0HAIhMi2Rn1E7+jvqb/bH7icuKY+nJpSw9uZQg1yB6hfdiYO2BNPJvZOPohbh9dltzdj2VSlWk5qx9+/a0atWKOXPmWMsaNmzIkCFDmDlz5i3XuXLlSrZu3cpXX30FwIcffoiiKLzwwgvFzp+bm1sg0UtLS6N69ep2nXkL29NfiSLmlVfI2mdpknFt05qQd95BFx5+x2JIzE5k1dlV/HT6pwK1Du2qtOOB+g/Qo3oPtJryO+HaZDJhMJTuekan91/l4G8XMZsVvAJcuGt4XXyDyn6Q14pIq9WiuYNJvy3lmnLZG7OXPy7+wZZLW0g3XLsKRSP/RgyrO4x+NfvhofOwYZTC3kjNWTnR6/UcPHiQl156qUB5r1692LVrV4nWUb16dXbt2kVOTg5arZatW7cyYcKEG84/c+ZM3nzzzf8Ut6g8LBcqX8XVGTMs55a5uhI0bRq+jz6CSn1nml0iEiNYHLGY3y/+jtFsBMBT58ng2oN5oP4D1PKuVa7bVxSF2NhYUlJSSrVMbpYRg8pE4/5eOOnUuHhoScmMI+XWg9yLPD4+PlSpUqXCn4vlrHGmS7UudKnWBb1Jz+7o3aw7v47NlzYTkRhBRGIEHx34iEG1BzG60Wiqe1W3dchClIhDJmcJCQmYTCaCgwv21AoODiY2NrZE6+jQoQP9+vWjZcuWqNVqevTowaBBg244/8svv8y0adOsz/NrzoQozJiYSMzr08nYvBkA11atCHlvJrq85vbyZDKb2Hp5Kz+c+IGDVw9ay5sGNOXB+g/SO7w3rk535kT6/MQsKCgIN7dbXx/TZDKTkZSD0dnS3OrqpcPVQ1vhE4yypCgKWVlZxMXFAVC1alUbR3Tn6DQ6ulbvStfqXUnOSWbtubX8dOYnLqReYPmp5aw8vZJ7a9zL2CZjaRzQ2NbhCnFTDpmc5Su801YUpVQ78nfffZd33323RPM6Ozvj7CyXIxE3l/7nn8S8Ph1TUhJotQQ+/RT+Y8eW+7llGfoMVp1dxY8nfrQ2XTqpnOhdszcjGo6gSUCTct1+YSaTyZqY+fvfumOBIddERnI2KrMTOq0KrwAXnN1kbKvb4epqSb7j4uIICgqqNE2c1/N18WVU41GMbDSS/bH7WXB8ATujdrIxciMbIzfSrXo3nm75NHV969o6VCGK5ZDJWUBAABqNpkgtWVxcXJHaNCHuBFN6OlffnUHq6tUAONevT8gH7+NSv365bvdK+hWWnFzCL2d+sY4R5e3szQP1HuCh+g8R7G6b30P+OWZubrcegiMn00BaYg4oChonNd5BrtIb8z/Kf98NBkOlTM7yqVQq2lVtR7uq7TidfJqFxxay/sJ6tl7eyrbL2xhQawBPtnySUI9QW4cqRAEOmZzpdDpat27Npk2bGDp0qLV806ZNDB482IaRicooc89eol95GWN0DKhU+I8fR8BTT5XrKP8nk04y/+h8/oj8w9rrsqZ3TUY0HMHA2gPvWNPlrdysJltRFDJTcslK0wOgc3XCy98FtUaGQvivpCm4qHq+9Zhx9wzGNxvPl4e+ZFPkJtaeX8vGyI2MbzqeMU3GyMXahd2w2+QsIyODs2evXVj5woULHD58GD8/P2rUqMG0adMYOXIkbdq0oWPHjsybN49Lly4xadIkG0YtKhNzTg7xn84i6fvvAdBWr07IezPL7ZqYiqKwP3Y/84/N5+/ov63lHat2ZFTjUXQK6eQwYzwpZoW0xBxys/Jq2Lx0uPs4S1Ihyl0t71p80u0TjiUc49ODn7Ivdh9fHf6KdefX8Uq7V+gU2snWIQphv8nZgQMH6N69u/V5/sn4o0ePZuHChQwfPpzExETeeustYmJiaNKkCb/99hthYWG2CllUItnHjhP90ovoz54DwOfBBwl64QU0HmU/3INZMfPXpb+Yf2y+9SLSapWa3uG9GdtkrF2NTVYSJpOZ1LhsjHoTAJ7+Lrh62PZaoqLyaRLQhG97fcuGixv4YP8HRKZFMvHPiQyqPYiX270sw28Im3KIcc7skSOMkyLKnmI0kjBvHgmz54DRiCYggKrvvI1nt25lvi29Sc+68+tYcGwBF9MuApahA4bUGcLoxqOp7mm/vYVzcnK4cOECNWvWxMXFxVpu1JtIjc/GZDSjUqvwDnSVi5aXgxu9/6J46fp0Zh+ezZKTSzArZkI9Qnn3rndpHVw+teDCthzh+O0YbSBC2IHc8xe4+MijJHz+BRiNePbuTa21a8o8McsyZLHw2EL6/tyX6bumczHtIp46Tx5v+jh/DPuD1zq8ZteJ2Y3os40kX83CZDSjcVLjW8XNbhOz2NhYnnrqKWrVqoWzszPVq1dn4MCBbM4bHgVg165d9OvXD19fX1xcXGjatCkff/wxJpPJOs/FixcZN24cNWvWxNXVldq1azN9+nT0er0tXpa4AU+dJy+2e5EFvRcQ6hFKVEYUYzaMYdbBWdbrzQpxJ9nnnlEIO6KYzSQvWUrcRx+h5OSg9vSkyuv/h9eAAWV6jlS6Pp0lJ5bww4kfSM1NBSzXDRzVaBT317sfd63jjpCfnaEnPTEHAK2zBu9AV7s98f/ixYt07twZHx8fPvjgA5o1a4bBYOCPP/7gySef5OTJk6xatYoHH3yQMWPGsGXLFnx8fPjzzz954YUX2LNnDytWrEClUnHy5EnMZjNz586lTp06HDt2jMcff5zMzEw++ugjW79UUUir4Fb8NPAn3tv3Hr+e+5Xvjn3H4fjDfNT1IwJcA2wdnqhEpFnzNjlCtaj47wyxscS88iqZeVeecOvYgZAZM9CW4eCeqbmpLD6xmB8jfrRefibMK4xxTcYxoNaAcr20UnnJb1YLDw/HlKsmKzUXRVEw6zR4+TmjUt+5E/9dtZpSJdH9+vXjyJEjnDp1Cnf3gglxSkoKWq2WsLAwunbtys8//1xg+tq1axk0aBDLli1j+PDhxa7/ww8/ZM6cOZw/f770L6aEpFnzv9t4cSOv73qdTEMmQa5BfNL9E5oHNrd1WKIMOMLxW2rOhCiGoiikrVtH7FtvY05PR+XiQtDzz+P7yMNldvmlpJwkFh1fxLJTy6xjlNX2rs2EZhPoHd4bjdqxx6fKHyrDrLe8Xyo3LR0/2XLH44h4qzduupLt6pKSktiwYQPvvvtukcQMLJdFWrVqFYmJiTz//PNFpg8cOJB69eqxdOnSGyZnqamp+Pn5le5FiDuuV3gv6vjWYeqWqVxIvcCYDWN4u/Pb9K/V39ahiUpAkjMhCjEmJxP75lukb9gAgEvTpoS8/z7OtWqWyfoTshNYeGwhK06vINuYDVjGYJrYbCL3ht3rMMNh3IxBbyInw0CusxGtkw5PPxcUZ/t/XWfPnkVRFBo0uHEP2NOnTwPQsGHDYqc3aNDAOk9h586d44svvuDjjz/+78GKclfLuxZL+y/llR2v8Nflv3hpx0tEZ0Qzvul4GfZFlCtJzoS4Tsa2bUS/9hqm+ARwciLgiUkETJyIyum//1RiM2NZcGwBP5/5mVxTLgCN/BsxsdlEulXvViGSMoCcDANbFp2gSgsNqCw9Mp3dtCiKQsRbve94PK6luNpA/lkeJTnw3uiMkBtdRi46Opo+ffrwwAMPMH78+BLHJGzLXevOp90/5ZMDn/B9xPd8fuhz4rPjeandSxXmNyvsjyRnQgDmzEyuvv8BKStWAKCrVYuQ99/Htel/vyZldEY03x39jlVnV1l7fjULbMakZpO4K/SuCvUPPD0ph7WfHyY7O4cqLb3x9He2XiNTpVKVuHnRVurWrYtKpeLEiRMMGTKk2Hnq1asHwIkTJ+jUqeiApSdPnqRRo0YFyqKjo+nevbt1wGzhWNQqNc+3fZ4QjxDe2/ceS08uJceYw/SO0x3+9ANhn+x7TynEHZD1zz9Ev/gShsuXAfAbPYrAZ59F/R9PpI7JiGHe0XmsPrMao2IEoHVwayY2m0iHqh0qVFIGkBiVwdrPD5OZqsevhgtu3jp0zo61i/Hz86N379589dVXPP3008V2COjVqxd+fn58/PHHRZKzNWvWcObMGd5++21rWVRUFN27d6d169YsWLAAdRmdsyjuvEcaPoKnzpPX/n6NVWdXkWPK4d273kWrdrxOO8K+OdaeU4gyZNbrSfjiSxK/+w7MZpyqViVk5gzcO3T4T+uNzYzl26Pf8vOZnzGaLUlZ+6rtmdhsIm2rtC2L0O1O9Jlk1s8+ij7biF+IO73GNSAuKdrWYd2W2bNn06lTJ9q1a8dbb71Fs2bNMBqNbNq0iTlz5nDixAnmzp3LQw89xIQJE5gyZQpeXl5s3ryZ//3vf9x///08+OCDgKXGrFu3btSoUYOPPvqI+Ph463aqVKliq5co/oOBtQfirHHmxe0v8vuF3zGZTXzQ5QOpQRNlSpIzUSnlnDpF9AsvknvqFADegwcT/NqraDw9b3udcVlxfHf0O1aeXmltvmxfpT2TW0ymVXCrMonbHl08msCGeccwGcxUreNNvyeagcYESbaO7PbUrFmTf/75h3fffZfnnnuOmJgYAgMDad26NXPmzAHg/vvvZ8uWLcyYMYMuXbqQnZ1NnTp1ePXVV5k6daq1VnTjxo2cPXuWs2fPUq1atQLbkVGMHFev8F44a5yZunUqGyM34rHHgzc6vlHhasOF7cg4Z7fJEcZJEUUpJhNJCxYQ/9nnKAYDGl9fqrz5Bl69et32OhOyE5h/bD4rTq2wnujfKqgVU1pOqbA1ZflO749l84ITmM0K4c0C6D2+MU46jYyzZWPy/t8ZmyI38fy25zErZkY1GsXzbZ6XBM0BOMLxW2rORKWhv3yZ6JdeJvvgQQA8unen6ttv4RRweyN/J+UksfDYQsvJwSbL6PctAlvwZMsnaV+lfYXfSR/bHsW2padAgXrtg7lnVEM0djrqvxDloWdYT97o+Aav73qdRRGL8Hf1Z2yTsbYOS1QAkpyJCk9RFFJWruTqe++jZGWhdnMj+NVX8L7vvttKoFJyUlh4fCFLTi6xjlPWLKAZk1tMplNIpwqflAH880cku1edA6BJ11C6DK93R0f9F8JeDK07lHR9Oh8e+JBPD35KNY9q9Aq//Zp4IUCSM1HBGeLiiPm//yNz23YAXNu0JuS999AVOv+nJFJzU1kUsYgfT/xoHdG/kX8jnmzxJHeH3l0pkjJFUdj763kObogEoHWfMNoPrlUpXrsQNzKq8SiiMqJYcnIJr+x8hSruVWgW2MzWYQkHJsmZqLDSNmwgdvobmFJTUWm1BD77LH6jR6HSlK5XVbo+ncURi1kUsYgMQwYA9X3r82SLJ+lWvVulSUwUs8L25ac5ti0KgI5Da9Oqd5iNoxLCPrzQ9gWiMqLYdmUbT//1NCsGriDILcjWYQkHJcmZqHBMqanEvvMuaWvXAuDcsCEh77+HS97goSWVacjkxxM/svD4QtL1lguS1/Gpw5MtnuSeGvdUqtHBTSYzfy06wem9V0EF3R6pT+O7Q20dlhB2Q6PW8EGXDxjx+wjOJJ/h+W3P813v72QMNHFbJDkTFUrG338T88qrGK9eBbUa/4kTCHziCVQ6XYnXkWXIYunJpSw4voDU3FTAckHyJ1o8Qc+wnpUqKQMwGkxs/PY4F/5NQK1W0WNMQ+q1lTG6hCjMTevGp90+5aF1D3Eo7hCfHPiEF9u9aOuwhAOS5ExUCOasLOI++pjkJUsA0IWFEfL+e7i2aFHidehNelaeXsk3R74hMScRgHCvcJ5o/gS9w3tXykEmDXoTv399lMsRSWi0avo83oTwZrfXu1WIyiDMK4x373qXZ7Y8w+ITi2ke2Jw+NfvYOizhYCQ5Ew4v+/Bhol98CX2k5SR130ceIej551C7uZVoeaPZyNpza5nz7xxiMmMACPUIZXKLyfSr2Q8ndeX8mRhyTayf/S9Rp1JwctYwYHIzQuv72josIezePTXuYVyTcXx37Dte3/U69fzqUcu7lq3DEg6kch51RIWg6PXEz5lD4tx5lssvBQdT9d138birc4mWNytm/rj4B7MPz+Zi2kUAglyDmNh8IkPrDEWrqbzniuizjaz76l9izqaiddEwcEpzqtbxsXVYQjiMKS2ncDThKPti9/HyjpdZ3Hdxpd6niNKR5Ew4pNwzZ4h68UVyI04A4DVwIFVeexWNt/ctl1UUhW1XtvHFoS84nXwaAF9nX8Y1Hcfw+sNxcarcI6rnZhlY+8W/XL2Qhs7ViUFPtyC4pn2Ooi2EvXJSOzHjrhnct+Y+IhIjmPPvHJ5u9bStwxIOonKd2SwcnmIykTh/AReG3U9uxAk03t6EzvqU0A8/KFFitidmDyN+G8FTfz3F6eTTeGg9eLLFk/w+7HdGNx5d6ROznEwDv846zNULaTi7OzHk2ZaSmJWR8PBwZs2aZeswxB0U7B7M9I7TAfju2Hccijtk44iEo5CaM+Ew9FeiiHnpJbIOHADAvWsXqr79NtqgW48ldDjuMF8c+oJ9sfsAcNG48EjDRxjbZCzezrdO6iqD7HQ9v846TGJUBq6eWgY905KAah62Dsvu6fV6dKXoDSwql17hvRh0ZRBrzq3h5R0v8/Ogn3HXuts6LGHnpOZM2D1FUUhetpwLgwaRdeAAajc3qrz1JtW//vqWidnJpJNM2TyFkb+PZF/sPrRqLY80eITfh/3Os62flcQsT2ZqLqs+OURiVAZuXjqGPNuq7BMzRQF95p2/KUqpwuzWrRtTpkxhypQp+Pj44O/vz2uvvYaSt57w8HDeeecdHnvsMby9vXn88ccB+Pnnn2ncuDHOzs6Eh4fz8ccfF1hnZGQkzz77LCqVqsDAxTdbLn97M2bMYOzYsXh6elKjRg3mzZt3u5+CsIGX271MqEcoURlRfPbPZ7YORzgAqTkTds0QFWW5/NKu3QC4tm5NyHsz0VWvftPlLqRe4KvDX/HHxT8A0Kg0DKo9iEnNJxHiEVLucTuSjORcfp11iJSrWbj7ODPk2Zb4BJesp2upGLJghg3e+1eiQVe6morvv/+ecePGsXfvXg4cOMCECRMICwuzJmIffvgh//d//8drr70GwMGDB3nwwQd54403GD58OLt27WLy5Mn4+/vz2GOP8csvv9C8eXMmTJhgXUdJlsv38ccf8/bbb/PKK6/w008/8cQTT9ClSxcaNGjw398fUe48dB680ekNHt/4OMtOLqNfzX60CGph67CEHZPkTNil/IuVx73/AebMTFQuLgQ9OxXfkSNRqW9c4RuVEcWcw3NYe34tZsUMQN/wvkxuMZlw7/A7FL3jSE/KYfWnh0iLz8bDz5KYeQeWQ2LmYKpXr86nn36KSqWifv36HD16lE8//dSaWN1zzz08//zz1vkfffRRevTowf/93/8BUK9ePSIiIvjwww957LHH8PPzQ6PR4OnpSZUq1wbw/eSTT266XL5+/foxefJkAF588UU+/fRTtm7dKsmZA+lQtQND6wxl1dlVTN81nZUDV6LTSHO4KJ4kZ8LuGGJiiHnt/8j8+28AXFu1ImTGu+jCw2+4THxWPPOOzOOnMz9hNBsB6Fa9G1NaTKG+X/07EbbDSUvIZvUnh0hPysErwIXBz7bEy9+1/DaodbPUYt1p2tInmx06dCjQ9NixY0c+/vhjTCYTAG3atCkw/4kTJxg8eHCBss6dOzNr1ixMJhOaG1zPtaTLNWt27SLaKpWKKlWqEBcXV+rXJWzruTbPsf3Kds6nnmfekXlMaTnF1iEJOyXJmbAbiqKQ+vPPXH3vfcwZGaicnQmcOhW/USNveLHylJwU5h+fz9ITS8kx5QDQvmp7nmr5FM0Dm9/J8B1KWkI2qz75h4ykXLyDXBnybEs8fMu5p6pKVermRXvl7l7wdSiKUiCZyy+7lZIup9UWHB9LpVJhNptLGq6wE97O3rzS/hWe2/Yc3x37joG1BxLmFWbrsIQdkuRM2AVDbCwx//c6mTt2AODaogVVZ8zAuVbNYufP0GfwQ8QPLIpYRIYhA4Bmgc14uuXTtK/a/o7F7YiuT8x8gt0YMq0l7t7Otg7LruzZs6fI87p1696wBqxRo0bs3LmzQNmuXbuoV6+edRmdTmeteSvNcqJi6RnWk86hnfk76m/e3/c+s++dbeuQhB2S5EzYlKIopP6yiqvvvYc5PR2VTkfgM8/g99joYmvLcow5LDu5jO+OfUdKbgoA9X3r81TLp+hSrUuRWghRUH5TpiRmN3f58mWmTZvGxIkT+eeff/jiiy+K9KK83nPPPUfbtm15++23GT58OLt37+bLL79k9uxrB97w8HC2b9/OQw89hLOzMwEBASVaTlQsKpWKl9q+xNCYoeyI2sG2y9voWr2rrcMSdkaSM2EzhthYYqZPJ3PbdgBcmjcjZOZMnGsVvQadwWTg5zM/M+/IPOKz4wHLRcmfbPkkvcJ6oVbJqDC3cv05ZpKY3dyoUaPIzs6mXbt2aDQannrqKSZMmHDD+Vu1asWKFSt4/fXXefvtt6latSpvvfVWgZP633rrLSZOnEjt2rXJzc1FUZQSLScqnnDvcEY1GsX8Y/N5b997dAjpgLNGfoviGpXy/+3deVxU9f7H8dew7yAo+yKiqKCsarmQkiVCiluL5s+9xSzRq9a1283Sm3ozl/LmmpXZSmaakolYIBWWKe64oaCoIAoKyg5zfn+Q3Eu4oAJngM/z8ZjHozlzOOd95psznznnfL/f2twYIWrIz8/H2tqavLw8rKxkBPW7oWi1XI2OJnvhosqemEZGtIqajO3YsWgMqv9eKNeWE3M6hpUHVnL++nkAnM2dmeg/kYFeA5vtpOR3Kz/nz8Is58/C7G+BmNvU35dBcXExaWlpeHp6YmLSuGZd6NOnDwEBAY16NP/G/P43F4VlhQzcOJDsomwmB07mOb9bF/+ibjWG72/5ZhMNquR0GpmzXqdoz14ATP39cZr7FsZt21ZbT6toiTsTx7L9y0jLSwOgpWlLnvN7jmHthkkX9Lvwv4XZjZv/67MwE0LcmZmhGdO6TGPmzzNZc2gNQ9oOoZVZK7VjCR0hxZloEEpZGTkffsTl5ctRSkvRmJlhP3UqLUY+Xe3eMkVR+Pn8z7y/732O5lZOam5tbM34TuMZ0WEEpgb1ONRDE3Qtt5jvlvxZmLUyZfDfgqQwE0JHRHhG8MWxLzh46SArD6zk9e6vqx1J6AgpzkS9Kzp8hMx//pOSY8cAMO/VC6fZb2Lo4lJtveSLybyX/B7J2ckAmBmYMcZ3DKN8RmFpZNnguRu7a7nFbFqcTP7lYqxamTJ4WiAWLaQwu5OEhAS1I4hmQqPRMC14GmO3jWXDyQ2M8hklg2ULQIozUY+0RUVcev99ctd+AhUV6Ftb4/CPV7GKjKzWq/JY7jGWJi/l5/OVw2gY6RkxosMIJnSeQAuTFmrFb9T+WpgNmdYA45gJIe5asEMwfVz7kHAugaX7lrK4z2K1IwkdIMWZqBcFv/1O5qxZlJ09C4BVRDgOr72GgZ1d1Tpn8s+wbN8yfkj/Aaic/3Jw28FM9J+Io7njTbcr7qxaYdbSpGEGmBVC3LOooCgSzycSdyaOA5cOyADaQoozUbcq8vPJfmchV9evB8DAwQHHN97A8uHQqnUuFlxk5cGVbDy5kQqlclDO/q3782LAi3JK/z5dv/LnXJk3CrNpQVjaSmEmhC5r16IdkV6RbErdxJK9S/g47GMZs7GZk+JM1AlFUcj/fisX//1vKi5fBsBm+FPYT5+OvmXl/WJXi6/y4eEP+fLYl5RUlADQy6UXUYFRdLTrqFr2puL6lWI2Lq6cxFwKMyEalxcDXuSHtB/Ye3Evv5z/hRDXELUjCRVJcSbuW2l6Ollz/kVBUhIARp6eOM5+E/Nu3YDK8XzWpazjkyOfVE21FGgfyJSgKQQ7BKuWuym5fqWETVKYCdFoOZo7MqLDCNYeWcuKAyvo5dJLzp41Y1KciXumLS0l54MPyFm1unJ4DCMjWr4wEdsJE9AzMqK0opSvj3/NB4c+ILc4F6icaikqKIoQlxD54KkjBXklbFqSTN6lIiztTBj0t0ApzIRohMb4juGrY19x6PIhfr3wK71ceqkdSahEijNxTwp++42sN2dTmp4OgHnPnjjOeh0jDw/KteV8d3IjKw6sILMgEwA3SzdeCniJ/p79ZaqlOlSYX8p3S/aRl12Epa0Jg6cFYmUnY8EJ0Ri1NG3Jk+2fZF3KOlYcWEFP557yI7aZkm9JcVfKc3I4/8ornB07jtL0dPRbtcRl8SLc1nyAobs7cWfiGLp5KLOSZpFZkIm9qT2vP/g63w3+jog2EVKY1aHi62Vsfm8fV7IKsWhhzKC/SWFWV7Kyspg8eTJt2rTB2NgYNzc3Bg4cyI8//njP2/zkk0/o1q0b5ubmWFpa8tBDDxETE1OHqUVTMK7TOEz0TTh46SBJF5LUjiNUIt+UolYUrZYr0V9zKjyC/M1bQKOhxciReG3dimV4OLsydzHi+xFMS5hGWl4a1sbWTAuexvdDv+fJ9k9iqGeo9iE0KcUFZXz33j5yzhdgZmXEoKmBWLeSwqwupKenExwczE8//cSCBQs4dOgQ27ZtIzQ0lBdffPGetjljxgyef/55nnzySQ4cOMDu3bsJCQlh0KBBvP/++3V8BKIxa2nakifaPwHAigMrkOmvmye5rCnuqPjoUbJmz6Fo/34AjH064jR7NqadO3Pg0gGWJi1ld9ZuAEwNTBnlM4qxvmNlVP96UlpUzpb/HOByxnVMLQ0ZNDUQGwcztWPdkaIoFJUXNfh+TQ1M7+rS0KRJk9BoNOzevRtzc/Oq5b6+vowfP/6u9//bb7+xaNEili5dyuTJk6uWz507l+LiYqZNm8agQYNwc3O7622Lpml8p/F8ffxrDlw6wG+Zv9HdubvakUQDaxbF2ZAhQ0hISKBv375888031V6LiYlh+vTpaLVa/v73v/PMM8+olFL3VFy9yqWl/+HKV1+BVoueuTmtpkyhxdMjSL2Wxn9+iiI+Ix4AQz1Dnmz/JM92fhY7U7s7bFncq9LiysIsOz0fY3MDIqcEYutsfuc/1AFF5UU88MUDDb7f35/+HTPD2hWvubm5bNu2jblz51YrzG6wsbEBIDw8nJ9//vm227p+vbJn8pdffomFhQXPP/98jXWmT5/O4sWL2bBhA1OnTq1VRtH0tTRtybB2w/ji2Bd8fPhjKc6aoWZRnEVFRTF+/Hg++eSTasvLy8uZNm0a8fHxWFlZERQUxNChQ7G1tVUpqW5QtFqubtjApcVLqLhyBagc4d/+73/nolkZC3fNIuZ0DAoKeho9Ir0iecH/BZwtnFVO3rSVlVawdflBsk7nYWxmwKApgbR0tVA7VpOSmpqKoih06NDhtuutWbOGoqLanQU8ceIEXl5eGBkZ1XjN2dkZa2trTpw4cU95RdM12nc00cej2ZW5i5ScFHzsfNSOJBpQsyjOQkNDbzqZ8e7du/H19cXlzwm4IyIiiI2NZcSIEQ2cUHcUHTxI1r/eovjQIQCM27XF4bV/UuTvxYIDq/jm5DeUa8sBeMT9ESYHTqaNTRs1IzcL5WUV/LDiIOdPXMXQRJ+BkwNo5d64LhubGpjy+9O/q7Lf2rpxf8+dLoPe+MyoC4qiSI88UYOLhQthrcPYmraVtYfXsqD3ArUjiQakeoeAxMREBg4ciLOzMxqNhk2bNtVYZ/ny5Xh6emJiYkJwcPAdLyfU1oULF6p9yLq6unL+/Pk62XZjU56by4V//pP0J5+i+NAh9CwscHh1JnZffcIao9+I+DaCr45/Rbm2nO5O3fnysS9ZErpECrMGUFGmZduqw2QcvYKBsT4DX/LHwdNK7Vh3TaPRYGZo1uCPuyl82rVrh0aj4ejRo7ddLzw8HAsLi9s+bvD29ubUqVOUlpbW2M6FCxfIz8+nXbt2tX8jRbMxrtM4AGLPxHLu2jmV04iGpPqZs4KCAvz9/Rk3bhzDhg2r8Xp0dDRTp05l+fLl9OzZk1WrVhEeHk5KSgru7u4ABAcHU1JSUuNvt2/fjrPzrS+13awXzK0+yEtKSqrtIz8//47H1hgo5eVc+SqaS0uXov3zmKwHD8Zy6iSiL8Xy0eYBXCu9BkDnlp2ZEjSFB5wa/r6h5qqiQkvsmsOcOZyDgaEeAyb54dTWRu1YTZatrS1hYWEsW7aMqKioGvedXb16FRsbm7u6rDl8+HCWLl3KqlWrqnUIAFi4cCGGhoY3/ewTooNtB3o49yDpQhKfHPmE1x58Te1IooGoXpyFh4cTHh5+y9cXL17MhAkTqm7Uf/fdd4mNjWXFihXMnz8fgL17997Tvl1cXKqdKTt37hwPPHDzwmP+/PnMnj37nvajqwr37CHrX29Rcvw4UNkLs+U/XmWrxSlWJY7mclHlHJltbdoyOXAyoW6hcvmlAWkrtMR9mELagcvoG+gR8YIfLu1bqB2ryVu+fDk9evSgW7duzJkzBz8/P8rLy4mLi2PFihUcPXr0ri5rdu/enSlTpvDyyy9TWlrK4MGDKSsr47PPPuO9997j3XfflZ6a4pbGdxpP0oUkNqVu4oWAF7A1ad73RDcXqhdnt1NaWsrevXuZOXNmteX9+vUjKen+B+fr1q0bhw8f5vz581hZWbF161ZmzZp103VfffVVpk2bVvU8Pz+/0X6gll24QPbCReRv3QqAnrU1LadMJqmLBcsPzeLc9crT5y4WLrwY8CIRnhHo6+mrGbnZ0WoVfvzkKKeSs9HT19D/+U64+ciHckPw9PQkOTmZuXPnMn36dDIzM2nVqhXBwcGsWLHinrb57rvv4ufnx4oVK3j99dfRaDQEBQWxadMmBg4cWMdHIJqSbo7d8LHzISUnhejj0bzg/4LakUQD0Oni7PLly1RUVODg4FBtuYODA1lZWbXeTlhYGMnJyRQUFODq6srGjRvp2rUrBgYGLFq0iNDQULRaLa+88gp2djcfBsLY2BhjY+P7Oh61aQsLyVnzITkffYRSXAwaDdaPP86JJ7sy8/RHpO5KBcDOxI7n/Z/n8XaPY6gvg8c2NEWrEP/ZMU7svoienoawZzvRunNLtWM1K05OTrz//vt1OkDs+PHj72mcNNG8aTQaRvuMZubPM/n6+Nc80+kZ+VxuBnS6OLvhr5fS7rZ3U2xs7C1fi4yMJDIy8p6zNQaKopAfE0P2wkWUX7wIgFmXLlx+PpK5177jQPJGACyNLBnfaTxPd3i61uNCibqlKAo7vzrBsaRMNBp4dIIvbQJaqR1LCKGifh79WLRnEZeKLrH9zHYea/OY2pFEPdPp4qxly5bo6+vXOEuWnZ1d42yauLmigwe5OHceRQcOAGDo4kLJC8OZZ7WbpNNzADDRN2Fkx5GM6zQOa2NrNeM2a4qi8MvXJzmSeB408Mg4H9oG26sdSwihMkP9ykG+l+1fxudHP5firBlQfSiN2zEyMiI4OJi4uLhqy+Pi4ujRo4dKqRqHsosXufD3v5P+5FMUHTiAxswM/RdGs2qmL8ML3iMpcxcGGgOeav8UW4duZWrwVCnMVKQoCru+PcXB+Mr7/R4e1QHvbo4qpxJC6IonvJ/AUM+QQ5cPcfDSQbXjiHqm+pmz69evk5qaWvU8LS2N/fv3Y2tri7u7O9OmTWPUqFF06dKF7t27s3r1as6ePcvEiRNVTK27tMXF5H78MZdXf4DyZ1d/wwFhrO9jyFe5X6G9oEWDhsfaPMakgEm4WTbOTg1Nze4taeyLOwtA76fb07GHzLYghPgvO1M7wj3D2XxqM58d/YwFrWRQ2qZM9eJsz549hIaGVj2/0SNyzJgxrF27lqeeeoqcnBzmzJlDZmYmnTp1YuvWrXh4eKgVWScpisK1H34ge+Eiyi5cAMDQvzM/DvFgVdmPlOWUAdDHrQ+TAyfj3cJbzbjif+zZmsaerekAhDzVjk4P1d3o80KIpmNkx5FsPrWZuPQ4srtkY28mtz00VaoXZ3369LnpYLD/a9KkSUyaNKmBEjU+hcnJXHz7bYoPVJ7q1nd04MCT/iy02kVhSeVI510duxIVGEWAfYCKScVf7Ys7y++b0wDoMbQtfqFyJlMIcXM+dj4E2QeRnJ1M9PFoJgdOvvMfiUZJ9eJM3LvSM2fIXrSYa9u3A6AxNSVjUBf+3SaFbOUnqKj8xzwlcArdnbvLALI65vDOcyRtqLyk/0CkJ4H93FVOJITQdU93fJrk7GS+PfktE/0nYqgnw2o0RVKcNUIVV69yecUKcr/4EsrKQE+P3EeDeMc/g1P6u0CB1latmRw4mUc9HpWiTAcd25XJzi9PABDU34MuEZ4qJxJCNAYPuz9MS9OWXC66TEJGAo96PKp2JFEPpDhrRLSlpVz5/Asur1hRNQ9mUZeOLOt5jd1m+wFwNHdkkv8kBnoNxEBPmlcXndxzkZ/WVV5u9gt15cFBMnm8EKJ2DPUMGdJ2CB8c+oCvj38txVkTpdNDaYhKiqKQ/8MPnI54jOy330abn095G1c+ebY1Yx49yW6zLFoYt+CVrq8QMySGIe2GSGGmo9IOXmbHRykoCvj0dKLXk+3kzKYOysjIYMKECTg7O2NkZISHhwdTpkwhJyfnvrYbHx9PREQEdnZ2mJmZ4ePjw/Tp06vN8VtRUcGSJUvw8/PDxMQEGxsbwsPD+fXXX+/3sEQTMcx7GBo0/Jb5G2fyz6gdR9QDKc50XGHyPs4MH8H5v02j7Nw5FDsbtg73ZOQTmXzf8hzmhuZMCpjED8N+YJTPKIz1G/cUU01ZxtFctq0+hFar0K6rA71HdpDCTAedPn2aLl26cOLECb788ktSU1NZuXIlP/74I927dyc3N/eetrtq1SoeeeQRHB0d2bBhAykpKaxcuZK8vDwWLVoEVP4QGz58OHPmzCEqKoqjR4+yc+dO3Nzc6NOnD5s2barDIxWNlYuFC71cegHwzYlvVE4j6oNGuVNXSXFT+fn5WFtbk5eXh5WVVZ1vv/Ts2cqb/W9MPWVizO8PO/N+x7OUGGkw0jNiRIcRTOg8gRYmLep8/6JuXUi9ypal+ykv1dImoBVhz/qip990fxsVFxeTlpaGp6cnJiYmase5K+Hh4Rw+fJgTJ05gampatTwrKwsvLy9Gjx591xOgnzt3Di8vLyZNmsSSJUtqvH716lVsbGyIjo5m+PDhbN68ucaE6MOGDWPnzp2cOXMGc3Pz2+6vMb//onYSMhKY/NNkbIxt2PHEDvlhfhfq+/u7Lsi1Lx1TebP/SnK/+KLyZn+NhhM93VgYeJ6rFhnoawwY1nYwE/0n4mguI8g3BhfT84l5/wDlpVrcfW3pN6FpF2a3oihK1cDIDUljalrrM5S5ubnExsYyd+7caoUZgKOjIyNHjiQ6Oprly5fzwgsv8Nlnn912eykpKbi7u7N+/XpKS0t55ZVXbrqejY0NAF988QXe3t41CjOA6dOn8+233xIXF8fgwYNrdTyi6QpxCcHR3JGsgizizsQxoM0AtSOJOiTFmY7QlpRw5bPPubx6Ndq8PACyfB1Z0j2HtFYXAA39W/fnxYAXaW3dWtWsovYun7vOlqX7KSuuwLmdDf2f74y+YfMrzACUoiKOBwU3+H7bJ+9FY2ZWq3VPnjyJoih07Njxpq937NiRK1eucOnSJebMmcOMGTNuuz1nZ+eq7VpZWeHk5HTb9U+cOHHbfd9YRwh9PX2GtRvGsv3LWH98vRRnTYwUZypTKirI27yFS0uXUp6ZCcA11xasCClkT+vLAPRy6UVUYBQd7W7+oS1005WsAja/t4+SwnIcPK147EU/DI301Y4l7sONu0A0Gg2tWrXC3r52I7QrilJn9xfKfYrihqHthrLywEqSs5M5eeUk7Vq0UzuSqCNSnKlEURQKEhPJXrSYkj9/CZfYWfB5zwpiO+aj6GkItA9kStAUgh0a/myDuD/5l4v47t39FF0ro6WbBQMn+2Nk0rz/uWlMTWmfvFeV/dZW27Zt0Wg0pKSk3PTS4bFjx2jRogUtW7Zk4sSJtb6s6e3tTV5eHpmZmbc9e+bt7U1KSspNXzt6tHL4lXbt5AtYVLI3s6e3a29+yviJTambeLnry2pHEnVEOgTco/u5obDo0CGy31lI4e7dAJSbGbO5pwEb/IspM9TQvkV7ooKiCHEJkV/JjdD1K8V8uzCZaznFtHAyZ8i0QEwtjdSO1aAa8w3pYWFhHDlyhJMnT962Q0B2djb5f443eCutW7fGwMCAjIwM2rZte8cOAV9++SVPP/20dAgQtbYzYycv/fQStia27Hh8B4b6MmPAnUiHAFFN6ZkzZC95l2vbtgGgNTQg/gFTPutSSIFpBW6W7rwU8BL9Pfujp2me9yU1doX5pXz37n6u5RRj1cqUQVMDml1h1ti9//779OjRg7CwMN566y08PT05cuQIL7/8Mi4uLsydOxcAe3v7Wl/WdHNzY8mSJbz00kvk5+czevRoWrduzblz51i3bh0WFhYsWrSI4cOHs379esaMGcM777xD3759yc/PZ9myZWzevJn169ffsTATzUtPl55VMwYknkukr0dftSOJOiAVQAMov3yZrDlzOPXYAK5t24ai0bA3yIqXnlVYFVKEua0Drz/4Ot8N/o6INhFSmDVSxdfL2PzePq5eLMSihTGDpgZgbi3d2xubdu3asWfPHry8vHjqqafw8vLiueeeIzQ0lF27dmFra3tP2500aRLbt2/n/PnzDBkyhA4dOvDMM89gZWVV1bFAo9Hw9ddf89prr7FkyRI6dOhASEgIZ86cIT4+XnppihoM9AyI9IoEYGPqRpXTiLoilzXvUW1Oi2oLCsj5eC25H32EtrAQgJMdLFndo5AzDhqsja2Z0GkCIzqMwMRALj00ZiVF5Wx+dx/ZZ65hZmXEkBlB2NjXrodgUySX1dQl73/zkpaXRuSmSPQ0esQ9Hoe9We3O6DZXclmzmVLKyriyfj2Xly2n4s/pXrLcLFgVUsgRjyJMDcx4zmcUY33HYmlkqXJacb/KSir4/v0DZJ+5hom5IZFTA5p1YSaEaFie1p4E2geyL3sfW05tYULnCWpHEvdJirM6pCgK12JjyV6yhLIzZwHIa2XKRz1L2NWhCEN9Y0a2f5JnOz+LnamdymlFXSgvq2DrioNknsrDyNSAyCkB2DlbqB1LCNHMDGk7hH3Z+9iUuonxncZLZ7JGToqzOlKwezfZCxdRfPAgAMWWRnzevZwdAaUoBgYM9orkBf8XcLZwVjmpqCsVFVpiVx/m3LErGBjrM3CyP63c5UyoEKLh9Wvdj/m755Oen87+S/sJtA9UO5K4D1Kc3afik6nkrV7N9Z07ASg3NuC7rgrfdaug2FiPRz0e5aWAl2hj00blpKIuabUKOz5KIf1QDvqGegyY5IdjG2u1YwkhmilzQ3PCWoexKXUTG09ulOKskZPi7D6dGTECCz09tHoa4gMN+KqHljwLDd2dujMlaAq+LX3VjijqmKJViF93lNS92ejpawif2BmX9jL5vBBCXUPaDmFT6ia2pW9jZreZmBnKva+NlRRn90tR2ONjyKe9tGTaKfi19GdK0BS6OXVTO5moB4qikPjVCY79loVGT0PYM53w8JX7B4UQ6gu0D8TDyoMz+WeITY9lSLshakcS90gG1LpPs0fos2CQgrlXO94LfY/PIj6TwqyJUhSFpG9PcTjxPGjgkbEdaRPYSu1YQggBVI6TN7jtYAA2pW5SNYu4P1Kc3afidi7M6zWPbwZ+w8PuD0sPmSbsj5g09sdV9sINHdkB726OKicSQojqIr0qxztLzk4m41qG2nHEPZLi7D5FD4hmoNdA9PX01Y4i6lHy9jP88X06AL2eaIdPL+l1K4TQPfZm9jzo9CAAMadjVE4j7pUUZ/dJJplt+g4lnGPXt6cAeGBQG/z7uqmcSAghbm1AmwEAbDm1BZkEqHGS4kyI2ziadIHEr04AENzfgy7hrdUNJOrd2LFjbzqHZUJCAhqNhqtXr5KQkMCgQYNwcnLC3NycgIAAPv/884YPK8RN9HXvi6mBKRnXMjhw6YDaccQ9kOJMiFs4ueci8Z8eA8DvYVceGCRj1YlKSUlJ+Pn5sWHDBg4ePMj48eMZPXo0W7ZsUTuaEJgZmvGox6MAbD61WeU04l5IcSbETaQduMSOj1JQFPDp5UyvJ9pJZw9R5R//+Af/+te/6NGjB15eXkRFRdG/f382btyodjQhgMqOAQDb0rdRUlGichpxt2ScMyH+4mxKDts+OIxWq+DdzYHeT7eXwqwOKIpCeam2wfdrYKTXIO2Xl5dHx44d630/QtRGV8euOJo7klWQxc6MnfRr3U/tSOIuSHEmxP+4cPIKP6w4hLZcoU1gK/qO6YienhRmdaG8VMvqKTsbfL/PvdcbQ+O7600dExODhUX1CewrKipuuf4333zDH3/8wapVq+4poxB1TU+jx4A2A1hzaA1bTm2R4qyRkcuaQvzpYlo+Me8fpLxMi7uvHf0m+KKnL/9EmqPQ0FD2799f7bFmzZqbrpuQkMDYsWP54IMP8PWV6dqE7hjYZiAAv5z/hZyiHJXTiLshZ86EAC6fu86W/+ynrKQCF28bwp/vhL6BFGZ1ycBIj+fe663Kfu+Wubk5bdu2rbbs3LlzNdbbuXMnAwcOZPHixYwePfqeMwpRH9rYtKGTXScO5xxmW/o2RnYcqXYkUUtSnIlm7+rFQjYv3U9JYTkOnlZETPLDwEgGFa5rGo3mri8v6rKEhAQGDBjA22+/zXPPPad2HCFuaoDXAA7nHGbzqc1SnDUicmpANGv5OUV89+4+ivJLaelmwYCX/DEykd8s4vYSEhJ47LHHiIqKYtiwYWRlZZGVlUVubq7a0YSoJtwzHAONASk5KaReSVU7jqglKc5Es1WQV8Lmd/dz/UoJNg5mDJwcgIm5zPgg7mzt2rUUFhYyf/58nJycqh5Dhw5VO5oQ1dia2NLLtRcAW07LOHyNhUaRuR3uSX5+PtbW1uTl5WFlZaV2HHGXiq+XsXFxMrkXCrC0M2HojCAsWpioHavJKC4uJi0tDU9PT0xM5H1taPL+i/8VdyaOaQnTsDezZ/uw7c1+LujG8P0tZ85Es1NaVM6W/+wn90IBZtZGDJoaIIWZEKLJ6u3aG0sjS7ILs9mdtVvtOKIWpDgTzUpZaQUxyw6QfeYaJhaGDJoSiHUrM7VjCSFEvTHSNyK8dThQORm60H1SnIlmo6JMy7aVh8hMzcPIRJ/IqABsnc3VjiWEEPVuoFflmGc7zu6gsKxQ5TTiTqQ4E82CtkLL9o+OcDYlFwMjPQa85E8rd0u1YwkhRIPwb+WPu6U7ReVF7Di7Q+044g6kOBNNnqJV+GndMU7vu4SegYaIF/xwamujdqxmQfobqUPed/FXGo2GAV4DANiculnlNOJOpDgTTZqiKCR+dYLjv2eh0dMQ9kwn3Draqh2ryTM0rBySpLBQLp+o4cb7fqMdhACI9IoEYHfWbjKvZ6qcRtyOjLYpmixFUdi18RSHE8+DBh4Z15E2Aa3UjtUs6OvrY2NjQ3Z2NgBmZmZoNDKBfH1TFIXCwkKys7OxsbFBX795D5kgqnOxcKGLQxf2XNxDzOkYnvV7Vu1I4hakOBNN1t4fzrBv+1kA+jzdHu+ujional4cHSvf7xsFmmg4NjY2Ve+/EP8r0iuSPRf3sPnUZp7p/Iz8aNJRUpyJJunAjxn8vvk0AD0fb4tviIvKiZofjUaDk5MT9vb2lJWVqR2n2TA0NJQzZuKW+rXux/zd80nPT+fg5YP4t/JXO5K4iWZRnA0ZMoSEhAT69u3LN998U7U8IyODUaNGkZ2djYGBAa+//jpPPPGEiklFXUj59QK/rD8JQNcBngQ84q5youZNX19figUhdIS5oTl93fsSczqGzambpTjTUc2iQ0BUVBTr1q2rsdzAwIB3332XlJQUduzYwd/+9jcKCgpUSCjqysk9F4n/7BgAAY+40fWx1uoGEkIIHXOjY8AP6T9QUlGichpxM82iOAsNDcXSsuaYVk5OTgQEBABgb2+Pra0tubm5DZxO1JX0g5fZ8VEKKOAb4kyPYW3lfgohhPiLbo7dcDBz4FrpNRIyEtSOI25C9eIsMTGRgQMH4uzsjEajYdOmTTXWWb58edUEvsHBwfz88891nmPPnj1otVrc3NzqfNui/p07lsu21YfRahW8uznQe0R7KcyEEOIm9PX0q2YM2HxKxjzTRarfc1ZQUIC/vz/jxo1j2LBhNV6Pjo5m6tSpLF++nJ49e7Jq1SrCw8NJSUnB3b3yXqLg4GBKSmqemt2+fTvOzs53zJCTk8Po0aNZs2bNLdcpKSmpto+8vDygcnZ7oa6LaXl8v+IQ5aUVtO5kR9chLly7fk3tWEIIobNCW4WyqmgViamJpHVKw87UTu1IDebG97ZOD9as6BBA2bhxY7Vl3bp1UyZOnFhtWYcOHZSZM2fe1bbj4+OVYcOG1VheXFyshISEKOvWrbvt37/xxhsKIA95yEMe8pCHPJrAIyMj467qiIak+pmz2yktLWXv3r3MnDmz2vJ+/fqRlJR039tXFIWxY8fy8MMPM2rUqNuu++qrrzJt2rSq51evXsXDw4OzZ89ibW1931lEw8jPz8fNzY2MjAysrKzUjiNqSdqt8ZK2a5yacrspisK1a9dqdWVNLTpdnF2+fJmKigocHByqLXdwcCArK6vW2wkLCyM5OZmCggJcXV3ZuHEjXbt25ddffyU6Oho/P7+qe90+/fRTOnfuXGMbxsbGGBsb11hubW3d5P7HbQ6srKyk3RohabfGS9qucWqq7abrJ1V0uji74a83diuKclc3e8fGxt50ea9evdBqtfeVTQghhBCiLqneW/N2WrZsib6+fo2zZNnZ2TXOpgkhhBBCNAU6XZwZGRkRHBxMXFxcteVxcXH06NFDpVSVjI2NeeONN256qVPoLmm3xknarfGStmucpN3UpVEUdfuSXr9+ndTUVAACAwNZvHgxoaGh2Nra4u7uTnR0NKNGjWLlypV0796d1atX88EHH3DkyBE8PDzUjC6EEEIIUedUL84SEhIIDQ2tsXzMmDGsXbsWqByEdsGCBWRmZtKpUyeWLFnCQw891MBJhRBCCCHqn+rFmRBCCCGE+C+dvudMCCGEEKK5keJMCCGEEEKHSHEmhBBCCKFDpDirJ0OGDKFFixY8/vjj1ZZnZGTQp08ffHx88PPzY/369SolFDdzq3YDiImJoX379rRr1441a9aokE7U1pIlS/D19cXHx4eoqCjdnuBYVElLSyM0NBQfHx86d+5MQUGB2pFELRUWFuLh4cGMGTPUjtIkSIeAehIfH8/169f55JNP+Oabb6qWZ2ZmcvHiRQICAsjOziYoKIjjx49jbm6uYlpxw63arby8HB8fH+Lj47GysiIoKIjff/8dW1tbFdOKm7l06RIPPvggR44cwdDQkIceeoiFCxfSvXt3taOJO+jduzdvvfUWISEh5ObmYmVlhYFBo5jIptl77bXXOHnyJO7u7ixcuFDtOI2enDmrJ6GhoVhaWtZY7uTkREBAAAD29vbY2tqSm5vbwOnErdyq3Xbv3o2vry8uLi5YWloSERFxy2nBhPrKy8spLi6mrKyMsrIy7O3t1Y4k7uBGMR0SEgKAra2tFGaNxMmTJzl27BgRERFqR2kymmVxlpiYyMCBA3F2dkaj0VRNev6/li9fjqenJyYmJgQHB/Pzzz/XeY49e/ag1Wpxc3Or8203RWq224ULF3Bxcal67urqyvnz5+tk281Nfbdjq1atmDFjBu7u7jg7O/PII4/g5eVVh0fQPNV3u508eRILCwsiIyMJCgpi3rx5dZi++WqIz80ZM2Ywf/78OkosoJFMfF7XCgoK8Pf3Z9y4cQwbNqzG69HR0UydOpXly5fTs2dPVq1aRXh4OCkpKbi7uwMQHBxMSUlJjb/dvn07zs7Od8yQk5PD6NGj5d6lu6Bmu93s6r9Go7mPo2m+6rsdTU1NiYmJIT09HVNTU8LDw0lMTJSBq+9TfbdbWVkZP//8M/v378fe3p7+/fvTtWtXHn300Xo/tqasvtvtjz/+wNvbG29vb5KSkur9eJoNpZkDlI0bN1Zb1q1bN2XixInVlnXo0EGZOXPmXW07Pj5eGTZsWI3lxcXFSkhIiLJu3bq7zisqNXS7/frrr8rgwYOrnkdFRSmff/753YUWNdRHO3799dfKpEmTqp4vWLBAefvtt+87q/iv+mi3pKQkJSwsrOr5ggULlAULFtx3VvFf9dFuM2fOVFxdXRUPDw/Fzs5OsbKyUmbPnl1XkZutZnlZ83ZKS0vZu3cv/fr1q7a8X79+dfKrQFEUxo4dy8MPP8yoUaPue3uiUn23W7du3Th8+DDnz5/n2rVrbN26lbCwsPverqiuLtrRzc2NpKQkiouLqaioICEhgfbt29dHXPGnumi3rl27cvHiRa5cuYJWqyUxMZGOHTvWR1zxp7pot/nz55ORkUF6ejoLFy7k2WefZdasWfURt1lplpc1b+fy5ctUVFTg4OBQbbmDgwNZWVm13k5YWBjJyckUFBTg6urKxo0b6dq1K7/++ivR0dH4+flVXfv/9NNP6dy5c10eRrNT3+1mYGDAokWLCA0NRavV8sorr2BnZ1fXh9Hs1UU7Pvjgg0RERBAYGIienh59+/YlMjKyPuKKP9VFuxkYGDBv3jweeughFEWhX79+DBgwoD7iij/V1eemqHtSnN3CX+8nUhTlru4xulVPvl69eqHVau8rm7i1+mo3gMjISPmSbyD3245z585l7ty5dR1L3MH9tlt4eDjh4eF1HUvcwf222w1jx46to0RCLmv+RcuWLdHX16/xqyE7O7vGrwuhO6TdmgZpx8ZJ2q1xknbTXVKc/YWRkRHBwcHExcVVWx4XF0ePHj1USiXuRNqtaZB2bJyk3RonaTfd1Swva16/fp3U1NSq52lpaezfvx9bW1vc3d2ZNm0ao0aNokuXLnTv3p3Vq1dz9uxZJk6cqGJqIe3WNEg7Nk7Sbo2TtFsjpWJPUdXEx8crQI3HmDFjqtZZtmyZ4uHhoRgZGSlBQUHKzp071QssFEWRdmsqpB0bJ2m3xknarXGSuTWFEEIIIXSI3HMmhBBCCKFDpDgTQgghhNAhUpwJIYQQQugQKc6EEEIIIXSIFGdCCCGEEDpEijMhhBBCCB0ixZkQQgghhA6R4kwIIYQQQodIcSaEEEIIoUOkOBNC6Kw333yTgICABt9vQkICGo2Gq1evNvi+hRBCijMhhCo0Gs1tH2PHjmXGjBn8+OOPDZ6tR48eZGZmYm1tfV/b2bBhAw888ADW1tZYWlri6+vL9OnT6yilEKKpMlA7gBCiecrMzKz67+joaGbNmsXx48erlpmammJhYYGFhUWDZzMyMsLR0fG+trFjxw6GDx/OvHnziIyMRKPRkJKSokqxKYRoXOTMmRBCFY6OjlUPa2trNBpNjWV/vaw5duxYBg8ezLx583BwcMDGxobZs2dTXl7Oyy+/jK2tLa6urnz00UfV9nX+/HmeeuopWrRogZ2dHYMGDSI9Pf2W2f56WXPt2rXY2NgQGxtLx44dsbCwoH///tUKzL+KiYmhV69evPzyy7Rv3x5vb28GDx7Mf/7zn2rrbdmyheDgYExMTGjTpk3V8dxw9epVnnvuORwcHDAxMaFTp07ExMTU/o0WQjQ6UpwJIRqVn376iQsXLpCYmMjixYt58803GTBgAC1atOD3339n4sSJTJw4kYyMDAAKCwsJDQ3FwsKCxMREfvnll6riqrS0tNb7LSwsZOHChXz66ackJiZy9uxZZsyYccv1HR0dOXLkCIcPH77lOrGxsfzf//0fUVFRpKSksGrVKtauXcvcuXMB0Gq1hIeHk5SUxGeffUZKSgr//ve/0dfXr3VuIUQjpAghhMo+/vhjxdrausbyN954Q/H39696PmbMGMXDw0OpqKioWta+fXslJCSk6nl5eblibm6ufPnll4qiKMqHH36otG/fXtFqtVXrlJSUKKampkpsbOxN88THxyuAcuXKlap8gJKamlq1zrJlyxQHB4dbHtP169eViIgIBVA8PDyUp556Svnwww+V4uLiqnVCQkKUefPmVfu7Tz/9VHFyclIURVFiY2MVPT095fjx47fcjxCi6ZF7zoQQjYqvry96ev896e/g4ECnTp2qnuvr62NnZ0d2djYAe/fuJTU1FUtLy2rbKS4u5tSpU7Xer5mZGV5eXlXPnZycqvZxM+bm5nz//fecOnWK+Ph4fvvtN6ZPn857773Hrl27MDMzY+/evfzxxx9VZ8oAKioqKC4uprCwkP379+Pq6oq3t3etcwohGj8pzoQQjYqhoWG15xqN5qbLtFotUHlpMDg4mM8//7zGtlq1anVf+1UU5Y5/5+XlhZeXF8888wyvvfYa3t7eREdHM27cOLRaLbNnz2bo0KE1/s7ExARTU9Na5xNCNB1SnAkhmrSgoCCio6Oxt7fHyspK1SytW7fGzMyMgoKCqmzHjx+nbdu2N13fz8+Pc+fOceLECTl7JkQzIsWZEKJJGzlyJO+88w6DBg1izpw5uLq6cvbsWb799ltefvllXF1d62W/b775JoWFhURERODh4cHVq1dZunQpZWVlPProowDMmjWLAQMG4ObmxhNPPIGenh4HDx7k0KFDvPXWW/Tu3ZuHHnqIYcOGsXjxYtq2bcuxY8fQaDT079+/XnILIdQnvTWFEE2amZkZiYmJuLu7M3ToUDp27Mj48eMpKiqq1zNpvXv35vTp04wePZoOHToQHh5OVlYW27dvp3379gCEhYURExNDXFwcXbt25cEHH2Tx4sV4eHhUbWfDhg107dqVESNG4OPjwyuvvEJFRUW95RZCqE+j1OamCSGEEEII0SDkzJkQQgghhA6R4kwIIYQQQodIcSaEEEIIoUOkOBNCCCGE0CFSnAkhhBBC6BApzoQQQgghdIgUZ0IIIYQQOkSKMyGEEEIIHSLFmRBCCCGEDpHiTAghhBBCh0hxJoQQQgihQ/4f/1idjEB9anwAAAAASUVORK5CYII=", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys4.sims[1], 1e-10, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e-3)\n", - "ylim(1e-12, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Cu111@-1.5V\")\n", - "gcf()\n", - "savefig(\"Cu111@-1.5V_X.png\")" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "a15be1a0", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys5.sims[1], 1e-10, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e-3)\n", - "ylim(1e-12, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Cu111@-1.0V\")\n", - "gcf()\n", - "savefig(\"Cu111@-1.0V_X.png\")" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "076638f2", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys6.sims[1], 1e-10, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e-3)\n", - "ylim(1e-12, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Cu111@-2.0V\")\n", - "gcf()\n", - "savefig(\"Cu111@-2.0V_X.png\")" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "id": "87dcaf99", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys1.sims[2], 0.1, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e-3)\n", - "ylim(1e-12, 5)\n", - "title(\"Evolution of Solid-phase Mole Fractions vs. Time at phi = -1.5V on Ag111\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "4dfc055c", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Dict{String, Float64} with 17 entries:\n", - " \"O=CC=O\" => 3.45195e-29\n", - " \"proton\" => 2.7869e-5\n", - " \"O=CO\" => 0.646064\n", - " \"Ne\" => 0.0\n", - " \"COC=O\" => 1.65033e-15\n", - " \"[O]C=O\" => 2.21456e-42\n", - " \"C=O\" => 1.78999e-10\n", - " \"[CH]=O\" => 2.77632e-32\n", - " \"CO2\" => 0.27869\n", - " \"O=[C]O\" => 4.57005e-35\n", - " \"N2\" => 0.0\n", - " \"O=CCO\" => 2.01265e-6\n", - " \"Ar\" => 0.0\n", - " \"H2O\" => 0.07521\n", - " \"He\" => 0.0\n", - " \"H\" => 5.33777e-37\n", - " \"H2\" => 6.18657e-6" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "Dict([ssys1.sims[1].names[i]=>molefractions(ssys1.sims[1],1)[i] for i in 1:length(ssys1.sims[1].names)])" - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "id": "1f7d8918", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "1009×1012 Array{RGBA{N0f8},2} with eltype ColorTypes.RGBA{FixedPointNumbers.N0f8}:\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,0.933) RGBA{N0f8}(1.0,1.0,1.0,0.933)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fd1 = getfluxdiagram(ssys1,1e-3;speciesratetolerance=1e-4)" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "id": "13ecdbf2", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "1020×1012 Array{RGB{N0f8},2} with eltype ColorTypes.RGB{FixedPointNumbers.N0f8}:\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fd2 = getfluxdiagram(ssys2,1e-3;speciesratetolerance=1e-4)" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "id": "379c4050", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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MVwGHm1JfJuMCuUzw51Hiy2S8P5ex/hzshoGIDB9ppovxgVzGB3J5tmE3g60qo5C3l8/i2pJp+B0uROTcmIiIiJyj1kiQre11bO2oY0v7MWqCbaQsi+HEbtgo9WVS4c9hbFoOY/3ZVPhzqEjLId3pQURGnvpQF4PB73BxTfFU3jF2NlMyChGRgTMRERE5g9ZIkG0d9WxsrWVrRx21wTYshg+/w8WEQB7j/XmMC+RSlVFIVUYhbrsDERk96kNdnI+qjEJuHTub60urcdsdiMj5MxEREfkr9aEuNrTWsrntKFs6jtMe6WM4sBs2ytOymJiez+T0AiYF8pmYnk+BJ4CIjG7hZJzOaIhzle/xc2PZDG4cM5MyXyYiMrhMRETkkheMR9jUdpQNrbVsaD1CXaiLi81rOqnKKGRyegET0/OpTC9gvD8Xl91ERC499aEuLM6O3TCYlzuWW8tnc3VRJXbDhogMDRMREbnkJC2LAz3NbGytZUNbLVvaj5FIpbhY7IaN8rRsqjILqcooYnZ2GZXpBdgNAxGRk+pDXZxJeVo2K0umcnP5LAo8AURk6JmIiMgloT7Uxca2Wja21rK+tZZgPMLFkutOY3Z2GTOzy6jKKKQqowi33URE5B9pCHXx97jsJksLJnJr+WwuyxuLgYGIXDgmIiIyKoUSMda11LC2pYb1rUdoDvdyMRR4AkzLLGZaZhHTMouZmllEmulCRORcNPR38efG+XNZVTadW8pnke70IBdfayTIkd42DgfbONLbRk2wlbeVTOXOinnI6GUiIiKjRkc0xLqWGl5o3MeG1iPEUkkutFJfJjOzS5mdXcasrDLGB3IRETlf9aEu/A4X1xRP5baxc5icUYBceEkrxYn+HhpCXRwOtnGkt42aYCv7u5sJJ+P8OQP40pybkNHNRERERrSa3jZWNx/i1eaDbO+ox+LCsRsG5Wk5zM4uY0FeBfNyyslyeRERGWzvmbCQb867FZfdRIZe0kpxor+HmmAbR3rbOBxs5UhvG0eC7USScc7GzOxSSrwZyOhmIiIiI0rSstjRWc/q5kO8dGI/x/s6uVBMm41JgXwW5FUwK7uMOdll+B1uRESG2ryccmTwxVJJjgbbqQ22czjYSm2wnZreVo6HOkmkUpyPa0umIaOfiYiIDHu98QivNR/mj00HWdtSQ18iyoXgspvMzi5jQW4Fs3PKmJpRhMNmR0RERp6a3jb29zRT09tKbV87h3tbaQh1k7RSDDbTZmN5cRUy+pmIiMiw1BuP8NKJ/TzfsIfNbcdIWimGmgFMSs9nYd44Ls8bx6zsMtx2ExERGV4KCwtZvHgxNpuNs3U81MEntz5F0rIYagvzxpHl8iKjn4mIiAwbkWSCjW21PFO3k1eaDhJPJRlq2S4fc3PGsCCvgsX5EyjwBBARkeFt/PjxZGdnY7fbOVtvKazk0zNW8pntzzLUriuZhlwaTERE5KKKJhNsaKvlhca9vNS4n3AyzlBy2x3MzC5lYW4FC/IqmJJRgIGBiIgMb4lYgtU/W83EhRMpnVJKWloaiWiCV3/2KpMXTaa4shjDZnA6t5bP5kR/Dz84uJah4rE7WFY4Cbk0mIiIyAUXSyVZ11LD7xv38semg/QnYgyliYE8riyYyOV545iZXYrTZkdEREYWw2bgSnOx9uG13HjfjXgCHna9vIsTB08w+7rZYHBW/nXKUtoiQX5zfAdD4S1FlXhNJ3JpMBERkQsiaVns6KznxcZ9PNewm85oP0PFbhhMzyphacEk3lJUydi0bEREZGSzm3ZmXjOT+l31bHtuGxMum8DWZ7ay6K5FZBRkYBgGZ8PA4HMzrqMt0sfalhoGW5kvi6SVwm7YkNHPREREhtT+7maePL6d3zfuoTPaz1DxO1xckT+etxRWsjh/PH6HGxERGV3SMtO44s4r+P23fs+xHccoqy6jYlYFhmFwLkybjW/Mu4W71/2cPV0nGEzfO7CGJ49v461FU1hePIXZ2WXI6GUiIiKDLhiP8PvGvfzq6Fb2djcxVIq86VyRN54lhRO5Im8cDpsdEREZ3YonF+PwOKjfW8/V91yNw+PAMAzOldd08v0Fd3DHmgepC3UxmFrCQR4+spmHj2xmnD+HFcVVXFdazZi0LGR0MRERkUGRsiw2tx3lt/U7+UPjfiLJOENhnD+XpYUTWVIwkVnZpRgYiIjIpaNudx2x/hh5Y/Ooeb2G3DG5GHaDgch2+fjR5Xdxx5oH6YiGGApHgu1898AavntgDeP8uawqm86qsunkuNOQkc9ERETOS0N/N08d38FTdTto6u9hsBlAdVYJbyuuYnlxFfkePyIicmmK9EVY/bPVzF45m9zyXJ7/1vOMnTmWwgmFGDaDgSjzZfL9BXdw97qf05+IcX4swOAfORJs42t7X+Yb+15helYJN5RNZ2XJNHymExmZTERE5JzFUkn+2HSQp+t2srblMEnLYrCN8+eyongK15dVU+bLQkREZP3j6/Fl+KhaVoXL62LKlVNY/dPV3PyZm3G4HRiGwUBMzSzi63Nv5t5NvyRppRg4g7ORtCy2ddSzraOe+3e9wILcCm4om85bCifhsNmRkcNERETO2u6uE/zm+Haea9hDMB5hsI3z5/K2kiquKZnK2LRsRERE3nR813EOrDvAjZ+8EY/fg2EzmLtqLk987gm2P7+duavmYtgNBmpxwQTun30D//HGU1hcONFkgtXNh1jdfAi/w83SwomsKp3O/Nyx2AwDGd5MRETktGKpJH9sOshDNZvY3lnPYCvypvOWwkqWF09hdnYZIiIif0/+uHxu+cwtZJdkg8Epvgwf1338OhwuB4bN4HxdX1pNfaiL7+xfzcUQjEd4pm4Xz9TtotCbztuKp3Jd6TQmpecjw5OJiIj8XXWhTn59bBtPHNtGdyzMYCrwBLi6aDLLi6cwK7sUAwMREZHTcfvcuH1u/lpWURaD6UOVV9IS7uXXx7ZxtubllFPb1057pI/B0tTfw4OH1/Pg4fWM8+eyongK15dVU+bLQoYPExER+ZOkZbG6+SCP1m5hY2stFoPHY3ewvHgKbx8zk1nZZdgMAxERkeHoMzOupSvWz8snDnAmBnD/7Bso9KSzvbOeZ+p28XzDHvoSUQbLkWAb3z2whu8eWENVRiHXl01nZclUsl0+5OIyERERQokYTx7fzkM1m2js72YwVWUUcn3ZdG4orSbd6UFERGS4sxsGX5lzE+9e9xA7Oxs4nVnZZRR7MzhpdnYZs7PLuK96BRvaanmmbievNB0knkoyWPZ2N7G3u4kv736RebljuaG0mquKJuMznciFZyIicglr6O/m8aNv8PjRrQTjEQZLwOFmRXEVt1fMpTI9HxERkYvNwuI7+9ewsmQqFf4czsRtd/D9BXdwx5oHOdrXwT9yXWk1f81lN1laMJGlBRMJxiP8sekgLzTuY23LYZKWxWBIWhYbW2vZ2FqLa8ezLMit4Iay6bylcBIOmx25MExERC5Be7ubeOjIJp6r30PSSjEYbIbB/Nyx3Fo+m6sKKzFtNkRERIaDWCrJfVt/y3MNe3imbie/XPI+sl0+ziTD6eGHl7+T29c8SHukj79m2mwsL57C6fgdbm4om84NZdNpCQd58cQ+Xmzcy7aOegZLNJlgdfMhVjcfIuBws6RwIqtKp3NZ3lgMDGTomIiIXCKSlsVLJ/bz4OH17Ok6wWAZm5bN28tncn3pdHLdaYiIiAwnPbEwH9r0S7Z21HFSQ38392x8lIcWvRuP3cGZlHgzePDyu3jnaz8hGI/y5xbljSfD6eFs5Xv8vGvcfN41bj5Hgu38vmEPv6vfTV2ok8HSG4/wTN0unqnbRYEnwNVFk1lVNp0pGYVcEO3tcPQoVFRAdjanRCJQVwfRKEybxinhMNTXQ0MDRKPg9UJpKZSVgWkyUpiIiIxy0WSCp+p28NPDG6kLdTIY3HYHK0umctOYmczKLkVERGQ4qgt1cc+GRzja18Gf29N1go++/gTfuew27IbBmUwM5PGt+e/gAxseIZZK8qZrS6cxUOP8OXx48hI+PHkJe7ubeLpuJ8837KEjGmKwNId7efjIZh4+splx/lxWFE/h+rLplPkyGTK7d8M3vwn/9m+wZAmndHTAY49BczM88ACEQvD66/Cb30BzM6RSYJowZgzcdBPMmwc2GyOBiYjIKNWXiPKb4zt48NB6WiNBBkOZL4tbymdxc/ksMpweREREhqudnQ3cu+kxOqP9/D2rmw/xlT1/4D+mLedsXJY7lvtnr+LjW57EAjx2B0sLJzEYqjIKqcoo5BPTlrOjs55n6nbxXMNuQokYg+VIsI3vHljDdw+soSqjkOvLprOyZCrZLh8XlGXB4cPw05+Czwef+QyUlMD+/fDzn8P3vgclJVBSwkhgIiIyyrRH+vhJzQZ+dXQroUSM82U3DJYUTOKOirksyBuLgYGIiMhwtq2jnvesf4hoMsHp/LxmE8XeDO4aN5+zsbJkKo393Xx97ytcXTwZj93BYLIbBrOzy5idXcZ91SvY0FbLM3U7eaXpIPFUksGyt7uJvd1NfHn3i8zLHcsNpdVcXTQZr+lkyEUisHs31NfDN74BU6dyyvz50N8PX/86rF0Lt9/OSGAiIjJKtISDPHh4Pb8+tpVIMsH5ynJ5ubV8Nu8YO4cCTwARGcH6+6GuDhobIR6HtDQoK4OiIjBNREabqoxCqjIK2dZRz5n89+4XKfSkc1VRJWfj/ROvoD3Sx6L88Qwll91kacFElhZMpDce4dWmgzxdv4tNrbVYDI6kZbGxtZaNrbV8dsezLCmYyPVl01mUNx7TZmPAOjvh5ZehsZFTurpg/37IzIS+Pjh+HAIBmDyZP7HZID8fCguhpoaRwkREZIRr6u/hpzUb+fWxrUSSCc5XeVo2t1fM5dbyWbjtDkRkhOvrg3Xr4JlnoLUVLAtMEyor4aabYNo0sNkQGU1cdpPvXnY7t695kGN9HZxOyrL4+BtP8rMr7mZ6Vgln4xPTlgMWF0rA4eaGsuncUDadE/09PNewm2frd3Oot5XBEkkmeKFxHy807uP2sXP49IyVDFgoBLt2QXs7p4RC0NAAmZlgWZBKgc0GNht/wTDAbodkkpHCRERkhKoPdfHDQ+t4um4n8VSS82EAiwomcPe4y1iQNxYDAxEZBSwL9u6Fhx+GggL44hchPx+2bYOf/xweegj+/d8hPx+R0SbD6eGHC+/k9jUP0hENcTqRZIJ7Nz3GY1e+lzJfFmdiNwzA4GIo8qbzzxOv4J8nXkFNbxsvNO7ld/W7qAt1MViuKprMeSkqgve/Hy6/nFOamuDhh6G7G7xeyM+HYBDq6qCiglNSKejqgrY2mDOHkcJERGSEaQ738r0Da3iqbgeJVIrz4babrCqbwV3j5lPhz0FERplwGLZvh54euO8+qKzklCVLoK0NnnwStm2Da65BZDQq9WXywII7eNfanxFJxjmdzmg/9258jEevfC8Bh5uRYHwglw8HlvDhyUvY293E03U7eb5hDx3REAOV7fIxP7ec82K3Q1oaZGZySn8/uN2c4vXC1Knw4ovw6KNw992QlQUNDfDyy5yyYAEnpVIp4vE4lmXhdrsZjkxEREaIzmg/P63ZwMNHNhNNJjgfaaaLG8fM4J8nXkGuOw0RGaV6e6G+HrKyYMIE/sRuh5ISSEuD+npERrNpmUX89+xVfHTLE6Qsi9M5EmznQ5t+yYOX34XTZmckqcoopCqjkE9MW87rbUf5bf1OXj5xgP5EjHOxsnQadsPGkLHZYPJkePvb4cUX4VvfgrQ06OqCUAhuuw0qKzkpEomwfft2du3axeLFi6msrMRutzOcmIiIDHPdsTC/OLKZn9VsJJSIcT5y3Gm8o3w2d49fgN/hQkRGOcsCywKbDWw2/oLNBoYBySQnpVIpTrLZbIiMNsuLp/DR/qv46p6XOJM32o/zya2/5atzb8LAYKSxGwYL8ipYkFdBZEaC1c2HeLpuJ+taa0ikUpzJypKpnJcxY+CWW2DMGP7E74dFi6Cvj1OysuDaa6GwELZvh74+GDcOZs2COXPAbuckwzBIJpMcPnyYY8d251IKAAAgAElEQVSOMX36dBYtWkRpaSnDhYmIyDAVSsT4yeEN/LxmI6FEjPMxMZDHeydczttKpmLabIjIJcLng9xc2LcPGhthzBhOSaWgtRX6+yE/n5P27dtHU1MTM2fOJCcnB5HR5r0TFtLU38Mjta9zJs837KE8LZt/mbyEkcxtN1lRPIUVxVPoiYVZ3XyIp+t3sam1Fou/VebLZFpmEeelogIqKvgLgQAsW8ZfSE+HZctg2TL+EY/Hw2WXXUZBQQGrV6/m9ddfZ+/evVx++eUsXLiQjIwMLjYTEZFhJpFK8Zu67Xx7/2raI32cj0np+dwzaTHLiydjYCAil5i0NKiuhnXr4Ne/httvh/R0qK2FNWsgEIDp0zmpqamJZ555hl27drFo0SKqqqrw+XyIjCafrF5Bc7iHV5oOcibfO7CGPLefd4ydzWiQ7vRwQ9l0biibTnO4lz+c2M/TdTvZ193Em64rrcbAYDhxOp1MnDiRkpIS9u7dy9q1a3nppZfYunUrS5cuZc6cObjdbi4WExGRYeTV5kN8afeLHO/r5HxUphfwgUmLWF48GQMDEblE2WwwfTqsXAlr1kBbG3g80N4OqRTcdBOUl3PS3LlzSSaTbNiwgccff5yJEyeyePFixo8fj8PhQGQ0sBsGX537du5e+3N2dTVyJl/c9TylvkwW5lUwmhR4Arxr3HzeNW4+Nb1tvNC4l2fqd7GydBrDldfrZc6cOUyYMIGtW7eyYcMGfvWrX7F582ZWrFjB5MmTsdlsXGgmIiLDwM7OBr6y5yW2dtRxPmZll/K+iVewtGAiIiKn5OTAqlVQUgK7dkF/P1RVwdy5UF1NNJFg365d9Pb2ctlll1FdXc1rr73Gtm3bqK2tpbq6mkWLFlFSUoLNZkNkpHPbHXznstu4bc2POdHfw+kkUin+dfOv+MXif2JSej6j0fhALh8OLOFDk6/EwGA4MwyDjIwMlixZwpQpU9i0aRNbt27lRz/6EVOnTmX58uWUlpZyIZmIiFxEx/s6+cqeP/BK00HOx+zsMj4yZSnzcsoREfkbWVnw1rfCW9/K34hGaW1t5YUXXmDLli0sW7aM6667jhkzZrB69WreeOMNDhw4wMKFC5k/fz5ZWVmIjHS57jR+uPBObl/zE4LxCKfTl4jygY2P8Msr30eBJ8BoZWAwUtjtdgoLC7n22muZPn0669evZ+vWrezevZtly5axaNEiXC4XHo8Hm83GUDIREbkIwsk4Dx5az48OrSOWSjJQ1ZnF3FO5mKUFExERGQin08ns2bOJx+O88cYbPPLII0yYMIG3vOUt3HXXXezbt4/169fz4osvsn37dpYuXcr06dPxer2IjGTj/Ll857J38L71vyCeSnI6LeEgH9r0Sx5e9G68phMZHhwOBxUVFRQUFGCz2fjmN79JIBCgs7MTm83G4sWLGTt2LEPJRETkAkpZFr+r38VX975Me6SPgRofyOVDlUtYXjwZAwMRGR6CXSF8AQ82u42RwjAMcnJyuOaaa6iurmbt2rXs2LGD2tpa5s6dy+LFi5kwYQJvvPEGGzdu5NFHH2XLli0sX76ccePGYZomIiPVvJxyPjvjWv5z29Ocyb7uJv7P67/mewtux27YkOHD6/WSm5tLQUEBy5cv58SJE6xbt47JkyczduxYhpKJiMgF8kb7ce7f/QL7u5sZqHH+HD40eQnLi6ZgMwxEZHh55oev8OqvNjH18onc9rFrKRiTw0hht9spKyvj7W9/OzNmzGDdunWsW7eOnTt3smzZMubNm8fkyZPZsGEDW7du5YEHHmDp0qUsWbKE9PR0REaqm8bMoKG/iwcOvMaZvNZSw+d2PMfnZ16HDD8+n4/JkyfjdDpZu3YtlmUx1ExERIZYayTIl3b/gecb9jBQeW4/H568hJvGzMRuGIjI8NTX3U9DTTMNNc1sfn4nhRW5LLxuNte/bylOj5ORwO12U1VVRWlpKXv27GHz5s089dRTbN68mRUrVnDNNddQVVXFmjVriMVixONxREa6f5m8hBP9PTxdt5Mz+fWxbZSnZfOeCQsRMRERGSJJK8UjtVv49r5X6UtEGQiP3cGd4+Zxz6TF+EwnIjK8hfsivKmrrYeuth72v3GE5378R8ZWlXDnf1zPuOoxjASBQIAFCxYwfvx4tm3bxuuvv86PfvQjpk6dyqxZs3C73WRnZ+P3+xEZ6QwMvjjzelrCvWxqO8qZfHXPS+S5/VxbOg25tJmIiAyBPV0n+NzO59jTdYKBMG02biqbyUemLCXb5UNERoZoOMZfs5IWTcfaaDrWxu6NhyiuKGDBtTO4/v1X4fG5GM4MwyAvL4+rrrqKyspKNm/ezJYtW9iyZQuhUIh3vetduFwuREYD02bj25e9gzvX/IRDva2cjgV8avszFPsymJlVily6TEREBlFHNMTX9rzMb+t2YDEwby2azMemXkWZLwuR0SIeTRANR4n2x4jFEkRCERLxJKHeMKlkilBPP8lEiv6+CPFonGg4RiwcJxFP4klzEeoJ86a0TC+hnjBWyuIkj99NPBonEUtyktPjwDAMov0xzoXdtOHxu3lTLBwnFolj2AzcPhfhYISTvAE3/b0RTnJ5nSTiSZLxJHaHne62Xk4n2BniQOcRDm6t5cWHXqOiqpTrP3A11YsmMZyZpkl5eTn5+flMnTqV9evXs3HjRkRGmzTTxfcW3M5tax6kPdLH6USTCe7d+BiPXfleytOykUuTiYjIILCwePLYdr6y5yV64xEGojK9gPuqVzA3Zwwiw0UsEifUG6Y/GCbUGybU00+oN0yop5/+YIRQbz/JRIo3pZIpTrLZbZxkt9uIReL40j3YbDZ8GV7sNhvegBvTYeL2uXB5nPgzfXh8buwOO76AB5vNIC3Dx0jzhXd+h7NhWRYtx9tJxFP8+DO/4t4v3UHl3HEMdx6Ph6qqKlKpFEeOHEFkNCr2ZvD9BXdw12s/JZyMczrdsTDv3/AIj135XrJdPuTSYyIicp7qQl18dsezbGytZSAynB4+WHkld1bMw24YiAwVy7Lo7eijpz1IT0cfPR1Bult76OnoIx5NYLMbpJIWbzJsBk63A6/fjS/gxet340v3kl+WTVpGGb6AB6/fg+mwI/8rkUhxOg6Xg7zSLHJLsli4chZX3b4Qr9/DSGO327HZbIiMVlUZhXx93i18aNNjJC2L06kPdXHvxsf4+aK7cdsdyKXFRERkgJJWikdqt/CNva8QTsY5V6bNxu1j5/Ivk5fid7gQGaie9iAdzd20NXTSfqKLrpYekokkGAZWyuJNNruBPzON9Ow00nP8FI7NZfKcCgLZfhwuEzl/yXiSv+YNuMkvzaGoIo9lty5g/jUzMB12RGR4u7JgAv81fSWf3fEsZ7Krq5FPbv0tX5t7MzbDQC4dJiIiA7Crq5FPb/8dB3taGIjFBRO4b9oKxqRlIfKPWJZFV0sv7U1ddJzoorWhg+62IFbKwrIsbDaDVMoiIzdATlEG2YWZjKsuIyPHj+k0kQsvmUhyUnqOn7ySbCbMGMOKuxczYWY5hmEgIiPLO8bOpravnYdqNnEmLzTuo8T3Ch+rugq5dJiIiJyDSDLBN/a9wi+ObCZpWZyrQm86901bwVVFlYiEQ1FajrXRdKyNlrp2utuCnGRZFoZhYNgMMnL85JZkkV2YyaTZFWTmBTBsBjI8lYwvYOrCiay4axHZRZmIyMj3ialvpam/h5dO7OdMfnxoPYWedO6omItcGkxERM7Szs4G7tv2NLXBds6VabNx+9i5/OuUZfhMJ3JpsCyLtsZOmo620Xy0jbbGTpKJJJbFKZ40F/ljcigYk0vl3HFk5gWQke1DX3snIjK62AyDL8+5iX9a93N2dDZwJvfv+j0FngDLCicho5+JiMgZJFIpvn/wNb5/8DWSlsW5mpMzhk9PfxsTAnnI6NTd1ktjTQsNNc201neQTKQwbAYn5ZZkUVSRx/QrJ5NbnIXdtCEiIiOL227yvQW3c9vqB6kLdXI6Scvi42/8hl8s+icmZxQgo5uJiMhp7O1u4j+2PkVNbxvnKsvl5RPTlnNd6TQMDGRkSyVTNB9vp+7ACeoOnSAcjGBZnJKZF6B4fD7VV0wirzQHu2lDRERGl0ynlwcW3M4dr/2EnliY0+lPxPjAxkd4/Mr3UehNR0YvExGRvyORSvG9g2v44cF1JK0U5+r6smr+Y9pyMp1eZGRJJVM0Hmnh2P5GGg43E+2PYRhg2AwKxuRSVllE9aJJeP0eRETk0lLhz+G7l93Ge9Y9RCyV5HTaIn28f+MjPLr4PfgdbmRoTZo0iXe+8514vV5KS0tZtWoVJSUlDDUTEZG/0tDfzb9v+Q3bO+s5VyXeDD4z41quyB+HDH/BrhBHdtdxbG8D3W1BLMvCbtooHpdP+ZQS5r+1GqfHiYiIyJtmZ5fx37Nv5GNbnsDi9Gp62/jwpsf58eXvxGGzI0OntLSU4uJi7HY7+fn55ObmYrPZGGomIiJ/5um6nXx+5/P0J2KcC7th446KufzblGV4TScy/DQdbaVm53GO7m0gmUhhGAb+TB9jp5aw5Ob5ZOQGEBERORvXlFRxLNTBt/a9ypm83n6Mz+14ji/Ouh4ZfKlkipotNWz93VYWvmMhY6rHYKUsarfUsvXZrVxxxxWUVpUyVExERP6v7liY/9r+DC+fOMC5mpSez/2zbmBKRiEyPHQ0dXN4xzGO7m0gHIyQSCTJK8liwoxy5q+YgdPtQERE5Hx8cNJi2sJBHjv6Bmfy5PHtlPgyuWfSImRwGTaDoklFtBxpYctvt1AwroDulm72r91PyeQSSqaUMJRMROSSt6ntKP+x9SlawkHOhd2w8U8TFvAvk5fitNmRi6OjqZsDW45wZHcdyXgSDIOiijwmzCxn7tXV2E0bIjK48vPzWblyJUVFRYhcyu6rvoa6UBfrW49wJt/a90eKPOlcX1aNDB7DMEjLTGP8vPG0H29n7S/W4gl4iIaizLl+DoZhMJRMROSSlUil+Ma+V/jJ4Q1YnJtx/hzun72K6sxi5MJJxJMc3VvP3o2H6Wzu4aS0TC9V8ydw28euxel2ICJDLysriwULFmAYBiKXMtNm45vzb+Wdr/2EAz0tnI4F/Of2p8nz+LksdywyuPLG5lF5RSXPfeM5skuzWXL3EjwBD0PNREQuSc3hXj625Qm2ddRzLgzglvLZfLJ6OW67Axlanc097Nl4iKN76kmlLBwuk/HTx7D0lstIz/EjIhdOIp5gw+Mb6OvsY96N88gpzSERS/DqQ6+SSqaYc/0cMgszEbnU+EwnP1h4J+9Y/WOaw72cTiKV4iObH+eRxe9hQiAPGTw2uw1vhhd/th+P30PhxEIuBBMRueS81nyYT2x9iu5YmHNR5svk/tmrmJ1dhgyNjqZu9m0+zNG9DSRiSfyZPqbMH8/Ca2dhOuyIyMVjN+1MWTyFdY+u49CGQ6SvSufQhkP0tPRQfXU1GQUZiFyq8tx+frjwTu587ScE41FOJxiP8sGNj/H4kveR7fIh58+yLLqbuzm8+TCmy8ThdrDjhR3Mu3EeNruNoWQiIpeMpJXigQOv8cDB10hZFufi+rJqPj19JT7TiQwOK2VRu7eePesP0dnczUnF4wuoWjCBRavmIiLDi2EY5JTlMH7eeA5tPMS2Z7fRuL+RoklFjKkeg2EYiFzKJgTy+Nrcm/ngxsdIWilOp7G/m3s2PspDi96Nx+5Azk88EqduVx3tx9tZ+a8r6WzsZMeLOyidWkrRpCIMw2ComIjIJaEjGuL/2/Ikm9qOci78Dhefnr6Sa0unIeev8UgLO1/bT/OxdgybwdipJSxaNZesgnREZGSYdPkkWmpaeO0Xr1F5eSXj54/H4XYgIrAofzyfnbGS/9r+O85kT9cJPvr6E3znstuwGwYyMKlUiuaaZmq21DDp8kkUTCjAm+Gl9VgrW3+3lZzSHFw+F0PFRERGvS3tx/k/r/+ajmiIczE/t5z/nn0jBZ4AMjBdrb3s2XCQ2t31xOMJiirymbVsKgVjchCRkcnusOPP9ePyusguyyY9Px0R+X9uLp/F8VAnPz60njNZ3XyIL+/5A5+ctpzR4GhfB2PTsrmQwr1hmg434cv0MXXpVE4K5AaYtHAS257bxtFtR6lcVMlQMRGRUe1Xx7byhZ3Pk0ilOFt2w8Y9kxbxwcorsRsGcvZikTi71x9kz8bDJONJsgrSmXHlFK64YQ6GYSAiI5tlWTTub6RxfyOZRZm01LRQv6eesTPHYtgMROR/fbTqLbSEe/ld/W7O5KGaTZR4M7hr3HxGotZIkBca9/F03U58ppOHFr2bC8mX4WP+TfP5a4UTC1k5cSVDzURERqVoMsFndzzLb+t2ci5KvBl8fd4tTM0sQs5O07E2tq/eR/PRNpLJJNMun8QdH78Oh8tEREaXcG+YfWv2EcgNsPidi9n63FaObDlCVnEW6fnpGIaBiICBwRdmXk9jfzfbOuo5k//e/SKFnnSuKqpkJIgkE6xuPsTTdTtZ21JD0kpx0vsmXs6lxkRERp3WSJAPb/olu7tOcC6uKqrk/lk34He4kX8sFo6xd3MN+18/QiQUJbswgwXXziSvJBsRGb2SiSQH1h0gGopS+dZKssuymbpsKpuf3Ezt1lqqr6rGdJmIyP9y2U2+e9nt3LHmQY72dXA6Kcvi4288yc+uuJvpWSUMRynLYntnPc/U7eK5ht2EEjH+2oysEi41JiIyqhzubeUDGx+lqb+Hs2U3bPzblGW8d+JCDAzkb/W0B9n8wk7qDp3A7XVRfcUkbv0/b8N02BGRS0N3czftde2UVpVSPKWYk/5/9uADvMrCfPjw7z3nPTs7ZA+W7E2QKUPFWUQEZFr3QBytWm21tVWr1qrdVq3VWlsBFScWEFBkCCFhJuydvfeZOev9Lu3V/2ct5CSQQMZz38n9kuk5oidVhVVUF1WT0DsBIcT/F2W08JfxC5m/8Q2qG500xRPwc3fmMt6Zchvpthjai2MNlXxWvJ+PC3IodtXRlGHRqXQ1KkKITiOz4gQ/yH4Pu6+R5kq0RPDb0bMZEZOG+G/lBVVkrtxNaV4lUXERjJo6mMtvuAghRNcUmxrL5XdfzncNv2o4QojTS7NF88q4Bdy4+e94Aj6aUut1sThzGUsn30aEwcz5UuGx81nxAVYU5LC/rpTmSLFG0c0cRlejIoToFD7I380Te/6FPxikuS5O7MuvMmYQabQgQNM0ju7OY8fn+3A53CT3SmDSdaOJSYxECCGEEGduSHQyz2XM4MHt7xPUNJpy3F7FPdve4Y0J38eo03OuuPxePi85xCeFOWRVniSgabTEsJhUuiIVIUSH98qhTfzx4Jc0l05RWNx/Mov7T0JBoas7vPMk2WtyaPR46TeyJ9ctvgxLmBkhhBBCtJ4rUgbyoGsqL+5bRyg7qvJ5dOfHvHjhTBQU2kpA09hWeYIVhbmsKz6IO+DjTA2LSaUrUhFCdFgaGi/u+5y/Hd1Kc9lUI89lXMfU5P50ZfkHi8lak0NdpZ1eg9OY/YOrsNhMCCGEEKLt3NZnPKWuepacyCaUVUX76B4Ww/0DLqa1HWuo5LPi/XxckEOxq47WMDwmla5IRQjRIQU0jcd3reCjgj00V6/wbrw0dh49w2LpivIPFrPtsxwaqu30HJTGNbdfgiXMjBBCCCHOnUeHXkmZu54vSg8TyiuHNhFvDmdez1GcrQqPnX8V7mVFYS6H68tpTSa9yoDIRLoiFSFEh+MNBnho+/t8XnKI5hob15M/jplDuMFMV1JeUMXGD7NpqHZwwbDuTL/zUiw2E0IIIYQ4P/SKwosXzuKmzW+RW1tMKM/kribdFsP4+F60VEALsrJwHysKc9lWeYKAptEWBkQmYtDp6YpUhBAdii8Y4IHs5awvPUxzzUgfxlMjrsGg09MVOBvcZK7czdE9eXRLiuayBRcRHR+BEEIIIdoHs97AS2PnMW/j65S46mmKPxjkB1nv8c9Jt9A/MoGW0Cs6KhsdbK04jkbbGR6TRlelIoToMHzBAD/MXs760sM0hwIs7j+ZewZMRkGhMwsGguRsPsSejQf52qSZFzJ1/niEEEII0T7FmcN4bfxC5m/8G3afh6Y4/I0sylzCO5NvJ9ESQUvc1mc8yZZIfrLzI7zBAG1hWEwqXZWKEKJD8AYD3Jf1LpvKjtIcekXhqRHTmdl9OJ1Z3oFiNn2Ujc/rZ9TUIdz8+EwUnYIQQggh2r/e4XG8NHYut295G18wQFPK3XYWb1vG2xNvwaoaaYmrUgcRbwnnnm3vUO9109qGx6TSVakIIdo9XzDAfVnvsqnsKM1h1On5zYWzmZrcn87I6/GR9dkeju7OJ6lXHNf/8GosNhNCCCGE6HhGd+vBsyOv5ZEdH6LRtIN1ZTyQvZyXx81Hr+hoiYzYdJZOupW7ti6hyFVHa0mwhJNoiaCrUhFCtGsBTePHOz5iU9lRmsOiN/CnsXOZEN+bzqbgUAmZq3bjanAzadZoJs64ECGEEEJ0fNPShnDCUcUrhzYRyqbyYzy5ZyVPjbiGluoV3o1lk2/j7m3L2FdbQmsYHpNGV6YihGi3NDR+tusTVhfvpzmijBb+Mn4hQ6NT6Cy8bi9Za3I4ujufxJ5xXLtoKmarCSGEEEJ0LvcNmEKJq55PCnIIZXneLrqHxXJbn/G0VDdzGP+YeDMPZr/PhrIjnK1h0al0ZSpCiHbr+b3r+Lggh+aIMJj56/gbGBydTGdQdLSML97Zik6vY/KsMUyccSFCCNFSvkY/BpOKEKL9U1B4esR0yt0NbKs8SSi/2beOBHM409KG0FIWvYGXxs7jzq1vs7XiBGdjeGwqXZmKEKJd+sOB9fz9WCbNEWW08OZFN9E/MoGOTNM09mw8SM6mQ8QkRjLnwe9hsZkQQogzUVVSy/Lfr+bu5xcghOgYVJ2OP42dy8KNf+NIQwVN0YCf7V5BsjWKkbFptNSOqny2V+Xzbxqg0FIGnZ4BkUl0ZSpCiHbnvbydvHp4M80RYTDz+oTv0z8ygY7K7Wxk4/tZ5B0sZvjkAdz0+HUoioIQQpwpr8fHUwtfIjo+AiFExxKmmnh53HzmbXyDKo+DpjQG/NyzbRnLJt9Gj7BYmutoQwX3Zb2LLxjg3xTOxIDIRMx6la5MRQjRrnxRepin9qykOSKNFv5+0U30j0ygIyrNq2TD+1l4HB4unT+BK2+ahBBCtIZnb3mVo3tOMn5aBkKIjifFGsWr4xbw/U1v4g74aEqd182dW5ewbPJtxJpshFLutnPn1iXYfR7O1vCYVLo6FSFEu7G3toSHt39AQNMIxaw38PLY+fSPTKCjObLrJBs/zCYhvRvX3nUp1nALQgjRWt54fDm7vzyAFgSdTocQomMaFJXE70Zfzz3blhHQNJpS6KxlceYy3pp4E2a9gdNx+BtZlLmEMncDrWFIdApdnYoQol3Id9Rw19YluAM+QjHpVV4dt4CRsWl0JPszj5K9Npf0fknc8ovZqAY9QgjRmjZ+mM3aJV/R6G7ka4pOQQjRcU1O7MPjw77HE3v+RSi5tcU8uvNjfnPhbHSKwnf5g0F+kPUeh+rLaS3DY9Po6lSEEOedw9/IPdveodbrIhRVp+P3o69nTFwPOgItqJG1JofczYcYOrE/N/98JoqiIIQQre3k/iLefOID6qvt/IdOpyCE6Njm9szghKOKfxzbRiifFR8g1fYFDw2ayrdpaDy+ewVbK07QHHf3n8TBujI2lB3hdGJNNlKtUXR1KkKI8yqgBbk/6z2O2ysJRQGeHTmDKYl9ae98jX42f7yd43sLmHBNBnc+Ow8hhGgr9lonv7r1L5TlV/Jtik6HEKLj+/Hgyyl11bOu5CChvH5kC0mWSBb0upD/+NOBDXxckENzzOo+gvsHXExA03gmdzXLTmznVIbHpCFARQhxXj2T+xmZFSdojocGT+WatCG0Z163l9VvbaKqtJbLFlzEJXPHIYQQbcnvC/DE3D9ScKiY71JVHUKIjk+nKDw/aia3fPUWe2qKCOXZ3NUkWiK4JKkfH+Tv5pXDm2iOMXE9+MXw7/E1vaLw82FX0yMsll/vXUNQ0/i24TGpCFARQpw3S05ks+zEdppjQa8Lua3PBNorv9fP58u2knewmGtuv5iUCxIRQohz4YW7XufgjuOcil7VI4ToHMx6lZfHzWfehjcocNbQlICm8fCOD3lo0FSezf2M5ugTEc+fxszDoNPzbTf2HkOCOZwf7/yIxoCf/xgWk4oAFSHEebGrupDn9q6hOaYk9uWxoVfRHvm9fj5ftpX8Q8VcfcsUrrxpEkIIca4s+fUKstfkEAwEORXVqEcI0XlEG638dcJC5m98g5pGF01x+b08k7uKoEZICZZwXhu/kHCDiVO5ImUg8ZZwFmcuo87rRq/oGBSVhAAVIcQ5V+62c3/Wu/iDQUIZEp3M70Zfj15RaE/8vgCbPszmyO48Lls4gStvmoQQQpxL29ftZeXfNuB2eDgd1aAihOhc0m0x/HHMXG796h94gwGaEtQIKUw18ZdxC0m0RNCUETFpvD3pFu7cuoQooxWrakSAihDinPIHgzy0/X2qG52EEmcO449j5mLWq7QXwUCQz5dtJe9gMZcvmMAlc8chhBDnw6o3N6IadDRFNagIITqfjNh0nsu4joe2v4/GmVN1Ov4wZg79IhNojt7hcSybfBvrSw8j/k1FCHFOPZ27ip3VBYRi1qu8NHYeiZYI2ovdGw7w1Sc7uHTeeC6/4SKEEOJ8+sXSe3HUOVn55kayPttD8ZEy6mscfJvBqEcI0TldlTqIfGcNfziwnjOhAL8cMZ3x8b1oiXhzOPN6jkL8m4oQ4pxZUZDLuyd3EooC/HrUTIZGp9AeHN2Tx5p/fsWwif2473c3IoQQ7UVYlI25D1zN3Aeu5s8/eptAIMiBzKOUnKzA6/GhGp77XosAACAASURBVFWEEJ3Xon4TqXA3sOzkDkADFJrr/oGXMCN9GOLsqAghzol8Rw1P5aykORb3n8zlyQM43yqLa1jzz810S4rm7l8vQK/qEEKI9qi6tI7E7nHMuu8KtKDG9nV7+eTVdcQkRCKE6NweG3oVBc5atlQcp7lmdR/Bon4TEWdPRQjR5vzBII/s+BCn30soUxL7srj/ZM4nR52TFa+tJxgIMuu+K7CEmRFCiPbsy+XbmDJ7DF9TdAqjrxjK6CuGIoTo/FSdjkuS+7Gl4jjNoSgKV6cORrQOFSFEm3th/zpya4sJJd0Ww/OjrkOnKJwPwUCQ1W9torKohmsXTSU6PgIhhOgI6qoa6JYcjRCi69lUfoxncz6juTRN44fZ77Fk0q30iYhHnB0VIUSb2lR+jH8e20YoFr2Bl8bOJdxg5nw4sjuPtW9/xWULJvC9W6cghBAdxZFdJ7lgWHeEEF3PgbpSHsheTkAL0hJ2XyN3Zy7j3Sm3E2uyIc6cihCizZS77fxkx0dohPbEiGn0iYjnXGuocfDpX9cTHm3jnhcWougUhBCiI9n6r90seHgaQoiupczdwD3b3sHl93Imil11LMpcyj8m3oxFb0CcGRUhRJsIaho/2fkRtV4XoVyXPpzpaUM5lwL+IOuWfEX+oWLmP3wNETFhCCFER+P3+vma0WJECNF1OPyN3LV1CWXuBs7GvtoSHshezp/HzkevKIiWUxFCtIm/HN7MtsqThJJui+Gnw67iXNq39QgbP8zm6lsmc+VNkxBCiI5q22c5jL5iKEKIrsMXDHDftnc50lBBaBqg0JSNZUd5ft9aHh1yBaLlVIQQrW5ndQF/PrSRUIw6Pb8ffT021ci54Kh38e5vV9JzUBqLX1iIoigIIURHdiDrGHc8PQchRNegofGz3SvYVnmS5hgQlcTBujJC+cexbaRYo7ix9xhEy6gIIVqVO+DjsZ0fE9CChPLw4MsZEJXIubDzi33sXL+fuQ9cTWS3cIQQoqOrq2wgOi4CRVEQQnQNv9u/nhUFuTTH7B4j+fmwq7lj69tkVeYRyq/3riHZEsnU5P60VEALold0dEUqQohW9cK+dRQ4awllUmIfFva+kLbmsrt558WVdB+QzJ3PzEUIITqLDe9nMXn2aIQQXcPyvF389chXNMekhAt4Yvj30Cs6fj96Dgs2vsFJRzVNCWoaD+/4gL9fdBPDYlJpjoAW5Omc1UxN7s+E+N50RSpCiFaTXZXHOye2E0qCJZznMmagoNCWdn6xj8yVu5n/8DXEJkUhhBCdSWVxDfGpsQghOr9NZUd5cs9KmmNgVBK/G309ekXH16KMFv4yfiHzN75BdaOTpngCfu7OXMY7U24j3RZDU1x+Lw9sf59NZUeJN4czIb43XZGKEKJVeAI+Ht/1KRpN0ykKz2VcR7TRSltx2d288+JKeg1N497ffh8hhOhs8vYX0WtwGkKIzm9/XSkPbH+fgBYklBRrFH8ZtwCrauTb0mzRvDJuATdu/juegI+m1Hpd3J25jGWTbyPCYOZUKjx2FmUu5WBdGV/LqS2iq1IRQrSK3+3/ggJnDaHc3W8SY+N60lby9hfx6evrueEn1xKdEIkQQnRGGz/azpwHrkYI0bkVu+pYlLkUl99LKOEGEy+Pm083cxinMiQ6mecyZvDg9vcJahpNOWGv4p5t7/DGhO9j1On5tiMNFdy1dQll7gb+I6emCA0NBYWuRkUIcdb21BTx9olsQukfmciifpNoK+vf20b+wWIWv3ADelWHEEJ0RgF/kGAgiMVmQgjRedl9jSzOXEaVx0EoBp2eP46ZS9+IeJpyRcpAHnJN5YV96whlR1U+j+78mBcvnImCwte2VBznh1nLcfgb+bY6r5tCZx3ptmi6GhUhxFnxBHz8ZOdHBDWNphh0en496jpUnY7W5mv0s+zFT7lgaHdu+cUshBCiM9u+NpdRlw5GCNF5+YIB7s96lyMNFYSiAE+PmM7YuJ40x619xlPiqmfJiWxCWVW0j+5hMdw/4GI+yN/NE3v+hT8Y5FRya4pIt0XT1agIIc7K7w+sJ99RQyh395tE34h4WltlcQ3v/mYls+6/kqQecQghRGeXu+Uwdzw9ByFE56Sh8bNdK9hWeZLmeHDQVKanD6UlHh16JWXuer4oPUworxzayIG6UjaWHaUpubXFTEsbQlejIoQ4Yzk1Rbx9PItQ+kcmcEffi2ht2WtyOZB1jLt+NR+DSUUIITo7e62TyNgwFEVBCNE5/Wbf56wozKU5ru8xktv7TqCl9IrCixfO4qbNb5FbW0zTFDaWHSWUnJoiuiIVIcQZ8QeD/Gz3CgKaRlNUnY5fZcxA1eloTZ/85XNsEVZu/vlMhBCiq9jwfhaTrrsQIUTn9F7eTt44upXmmJTYh18M/x5nyqw38NLYeczb+DolrnrO1qH6MrzBAEadnq5ERQhxRt46vo1jDZWEclffifSPTKS1BANB3nr6I4ZM6MuoqUMQQoiupCy/kqSe8QghOp+NZUd5as8qmmNQVBK/u3A2ekXH2Ygzh/HquAUs3PQ37L5GzoY3GOBQfRlDo1PoSlSEEC1W5m7g5UMbCaVfZAJ39ZtIa/G4Gnn9Z+9x9a1T6DU4DSGE6EoKDpXQvX8KQojOZ19tCQ9kLyegBQklxRrFq+MWYFWNtIY+EfG8NHYed2x5G28wwNnIqSliaHQKXYmKEKLFntu7BpffS1P0io6nR0zHoNPTGmrK6nnr6Q+58bEZxCZHI4QQXc2mj7Yz674rEEJ0LkWuOhZlLsUd8BFKpNHCa+MX0s0cRmsa3a0Hz2bM4OHtH6Bx5nJri+lqVIQQLbKl4jhrig8Qyu19JzA4OpnWkHegmBWvfcGi5+ZjCTMjRFfm8nvxa0FE1xIMBHF4PPhM4PN5OJ/CVBM6RUEIcfbqvW7u3PI21Y1OQjHo9Px+9PX0Cu9GW6hudIICaJyx3JoiuhoVIUSz+YIBnslZTShJ1kju6jeR1rD3q8Ps2nCAe39zAzq9DiE6Gk/AR3WjkyqPgxqvi5pGJ7WNLhz+Rlx+L05/I06/lwafB6evEae/Eaffi8vv5WveYABPwIfo2iy5bjQj/OFfh2jvIgxmvs2qGjHo9Hwt3GBGAfSKDpvBxNfMOhWTXuVrYQYzOhT0ioLNYEJBIcJgxqDTY1ENmPUGjDqVcIMJVdETZjBh1Okx6w1YVSMGnZ4IgxkhOoLGgJ97tr3DSUc1oSjA0yOnMzauJ60toAX5Zc4q3j25k7NV4KylptFFjMlKV6EihGi2149u4aSjmlAeH3Y1Fr2Bs5X71SH2Zx7lpp9dhxDtTUDTqPTYKXHVU+Kqo9RdT6m7gXJ3AzWNTqobnVR5HLgDPoQ4W+YDHurmRNERNPg8fFuDz8O5pld02FQjZr0Bq2rEphqJMFqw6o3YVCNW1UiYwUS4wYxVb8SqGrGqRiINZmwGE1a9EatqJMxgIkw1oVMUhGhNGhqP717BzuoCmuNHgy9jetpQWpvL7+Wh7R+woewIrWVvbTGTE/vQVagIIZql1FXPXw9/RSgTEy7g4sS+nK3ta3PJO1DM/IevQYjzxeFvJN9RQ56jmjxHNQXOGkpc9ZS66in3NOAPBhGirencQYI2HZpOQTRPQAvS4PPQ4PPQGsJUExFGMxEGM+EGMxEGM+EGMxEGM+EGMxFGCxEGM+EGMxEGM+EGMxEGMxFGM2GqCSG+64V96/i0cC/NMadHBrf2GU9rq/DYuWvrUg7Vl9EyGqBwOjm1RUxO7ENXoSKEaJanc1fjDvhoilmv8viwqzlbWZ/lUFlUzfU/vAoh2lpQ0yh01nK0oYJ8ZzV5jhryHNWctFdR3ehEiPPNluXENcqKOH8c/kYc/kZKqKeldIpClNFCpMFClNFKlNFCpNFClNFKpNFClNFCtNFKlNFKlNFCpNFClNGKWa8iOqd3T+7kzaOZNMfkxD78fPjVtLajDRXclbmUUlc9LafQlNyaYroSFSFESJvKj7G+9DCh3Nl3Imm2aM7Gxg+zsdc6mXb7JQjR2mq9Lg7Xl3OkvpwjDRUcbijnWEMlnoAPIdortcyPb4oB0TEFNY2aRhc1jS6gmuYy61WijFaijBaijFa6mcOIMdmINdnoZgojxmQlxmQj3hxOtNGKSa8i2r8NZUf4Zc5KmmNwdDK/G309ekVHa9pScZwfZi3H4W+kLeTWFqOhoaDQlIKCAvbu3UteXh6FhYUUFhZSUVGBz+fD4XDg9XoxGo0YDAbCwsKwWCz06NGDtLQ00tLS6NevH4MHD8ZgMHA+qQghmhTQNF7ct45Q0m0x3NpnPGdjw/tZ+H0Bpt12MUKcrRJXPfvqSthXW8L+uhKONFRQ5XEgREeilvvwJRoQXY8n4KfM3UCZu4HmsKlG4s3hxJhsRJusxJnDiTFaiTXZiDOHE22yEmOyEWcOI0w1Ic69fbUlPJj9PgFNI5RUaxSvjluARW+gNWVX5bEocyn+YJC2Yvd5OGmvpld4N/4jEAiQlZXFmjVryMzMZNeuXVRXVxMfH0/Pnj1JS0sjNTWVoUOHYjKZsFqtWK1WXC4Xfr8fu92O0+kkPz+fffv2UVhYyMmTJ9Hr9QwZMoRRo0YxdepULr30UqKjozmXVIQQTXo/bxdHGyoI5adDr8SkVzlT65ZswWBWmTp/PEK0VIXHzv66UvbXlrC/rpS9tcVUNzoRoqOzZblomBqOEKE4/V5OOqo56agmFKNOT6TRQoTBQrwlnDhzGJEGC/HmcOLMYUQYLcSbw4kzhxFrsqFXdIizU+SqY1HmUtwBH6FEGS28NuEGYk02Wtvobj1YceliVhbuZUVhLoXOWtpCbm0xaeZIVq9ezdKlS1m7di0ul4uJEycyefJkfvCDHzBy5EiSkpI4Uy6Xi9zcXHbt2sW2bdu47777qKysZMyYMVx//fXMnz+fhIQE2pqKEOK0XH4vfz60gVAuTx7ApMQ+nKmtn+5C0zSmzBqDEKEEtCD760rZU13IzuoC9tQUUeGxI0Rno2igawyiWXUI0Zq8wQCVHgeVHgfH7ZU0RacoxJhsdDOFkWiJIN4cTrwlnERLBHGmMBKtkXQzhRFjsiJOrc7r5s4tb1Pd6CQUk17lpbHz6BkWS1vpGRbLvQOmsLj/ZLKr8vikIIe1JQdx+b20lpdXvMMdT76O3+9n9uzZ/POf/2TKlCnYbDZai9VqZezYsYwdO5bFixejaRo5OTmsWrWK119/nYcffpjLL7+cRYsWMW3aNBRFoS2oCCFO642jW6n0OGiKWW/g0aFXcqZ2rt9PZUkN1941FSFOxeFvZHd1IbtrCtlZVcDe2mLcAR8dWbjBRJTRilU1YlON2FQTNtVIhMGCzWDEqjdi1hsw6lXMepX/sOqNqDo9omsoyMwneG2QHqN70h7ZfR40NE4lqGk4fI18TUOjwefha75gALffx9c8AR/eoJ+v2X2NBNEIakEcvka+5g0G8AR8uPxefMEAdp8HDXGuBTWNKo+DKo+DQ/VlnI5RpyfeHE6CJYJ4Szhx5nCSLBHEmcNJtEQQZw4j3hyBWa/SlTQG/NyzbRknHdWEogC/HDGdjNh0zgWdojA2ridj43ryxPBpfFl2hE8KcthcfoyAFuRslJsCvPLKK0ybNg2z2cy5oCgKw4cPZ/jw4Tz22GPs2rWLt956i4ULF5KWlsaPfvQjbrjhBgwGA61JRQhxShUeO28e3Uoot/QZR6IlgjNxIOsY+QeKmHnvFQjxHw0+D9ur8smuPEl2VR5HGioIahrtnUmvkmyJJNEaSbw5nBiTlThTODEmK9EmG3GmMGJMNmJMVgw6PUKE8tc9e7njievRqzrEvwW0IE6/F0/AR2PAj9PfiC8YxOHz4A0GcAd8uPxe/FqABq8Hb9CP0+/F4WvE7vfg8ntx+b24/F4afB6c/kZcfi+egB9xdrzBAEWuOopcdTQl0mgh3hxOoiWCOHMYiZZI4sxhJFgiSDCHE28OJ9ZsQ0GhowtqGo/s+JBd1YU0xyNDLueatCGcLW8wgFGnpyVMepUrUwZyZcpAytwNfFqYyycFuRy3V3ImgvHhTJt2LWa9gfNl5MiRjBw5kieffJJXXnmFxx57jOeee44XXniB6dOn01pUhBCn9IcD63EHfDQl1mTj1j7jOROHd55k+9pcbnp8JqJrc/q97KjKJ7sqj6zKkxyqLyOgabQ3Jr1Kd1sMabYYUqyRJFujSLJGkmSJJNkaSazJhhCtxe1sxBpuQa/qEP+fXtERYTATYTDTmgKahtPfiN3nweX34vR7cfm9NPg8OHweGnwe7D4PDT4Pdp+HBp8Hu89DvdeD3eehwefBE/AhQqv3uqn3ujnaUMHpqDod3UxhJFoiiDOHk2SJIMUaRaI1kiRLJMnWSGJNNtq75/etZW3JQZpjbs8Mbr5gHGcroGnM+vIvvDBqFv0jEzgTiZYI7uh7EXf0vYh9tSV8UpjDysJ91HpdNJc/GGR/XSkZsemcb1FRUTz66KP84Ac/4Pnnn2f+/PmMGzeOV199lQsuuICzpSKE+B+H68v5pCCHUO4bcDFhqomWyjtQzKaPsrn9l3MQXY8/GGR3TSFbKo6zrfIk+2pLCGhB2gO9oiPFGkmPsFh6hMXSIyyWHmGxdA+LJdESgU5REOJc2PRhNhOmjUScG3pFIcJgJsJg5kz5ggEafB7sPg8NPg92n4cGn4c6r5t6r5s6r4s6r5t6r5s6r4s6r5s6r4t6rxsN8W3+YJAydwNl7gZOx6RXSbJEkmSNJMkSQbI1imRrJEmWSJIskSRZIzHq9Jwv75zcwVvHttEcUxL78viw79Eail21HGuoZN7G13lw0FRu7D2GszE4OpnB0cn8ZMiVZFee5OPCHNYWH8AT8BNKbk0xGbHptBdWq5UnnniC22+/nQceeIDhw4fz4osvctddd6EoCmdKRQjxP17Yt46AptGUXuHdmN1jBC1VXlDF2rc3c8fTc1EUBdE1FLnq+Kr8GF+VHyer8iQOfyPnW7w5nL6R8fSLSKBvRAJ9I+PpHR6HQadHiPOt4HAJV3x/IqLjMOj0xJpsxJpstISGRp3XTb3XTZ3XTZ3XRb3XTZ3XTZ3XRZ3XTaXHQa3XSU2ji0qPHaffS1fXGPCT56gmz1HN6cSZw0iyRJJkjSTJEkmSNZIUayRJlkgSLZHEmKy0hS/LjvB0ziqaY0h0Mr8dPRu9otAa8uzVfK0x4OdXuZ+xv66EJ4ZPw6I3cDb0isK4+F6Mi+9F6q5ynnzvdS6YcxkN3cxonFpubRHtUWpqKsuXL2fJkiXce++9rFq1irfffpuIiAjOhIoQ4r98VX6cLRXHCeXhwZehV3S0hMvuZvkfPuOuZ+eh6BRE5+UJ+Miuyuer8mN8VX6Mk45qzhe9ouOCiDgGRyXTLzKBvhEJ9ItMIMpoQYj2qLygiqQecYiuQUEh2mgl2miluTwBP7WNTiobHdQ0OqlpdFHpsVPT6KTG66LK46C60UlNo5OaRicaXVOlx0Glx0FubTGnYtarpFijSLJGkmiJJNkSSbI1kiRrJCnWKBItEegVHS2xt7aEh7LfJ6BphJJmi+aVcQuw6A20ljxHNd+2oiCX/bUl/H70HC6IiONs+P1+HnzwQd544w3efPNN5syZw0lHNSsL97KiMJdCZy3fllNbTHu2cOFCJk2axIwZM5gwYQIrVqygZ8+etJSKEOK//Ongl4QyulsPpiT2pSX8vgCvP76cm352HQaTiuh8ahpdbC4/yoayI2wuP4bT7+V8iDOHMSgqmYzYdEbEpjEwKgmL3oAQHcWXy7dx9c1TEOJ0zHqVJGskSdZImqPB56HCbafe56bS46DCY6fB66bB56HSY6fCY6fe66HMXY/T76Wr8AT8HLdXcdxexamoOh3RRivx5nDSbNGk2qJJs0WTZo0m1RZNqi0KBYX/KHTWcnfmUtwBH6FEGS38ZfxCYk02WlOes4bvOm6vYu7G1/nliGu4OnUwZ6KxsZHZs2ezZ88eNm/ezMiRI/laz7BY7h0whcX9J7O7ppAVBbmsLNqL0++l1FVPhcdOvDmc9iotLY3Nmzdz4403MmbMGD7//HOGDh1KS6gIIf7PF6WHyK0tpik6ReGRIZfTEpqm8eaT7zPrviuI7BaO6Bw0NA7VlfNl2WG+LDvC/toSNM6tSKOFETFpjIxNY1hMKgOjkghTTQjRUWmahqPeRURsGEK0lgiDmQiDmeaw+zxUehzUel1UNzqp8jioanRQ5mqgqtFBmbuBCo+deq+bzs4fDFLpcVDpcbC/rpTvsqpGUq1RpNqiiTOHs67kIDWNTkIx6VX+PHY+PcNiaW15jmpOxeX38tD2D8iqzOOnw67CqNPTXF6vlzlz5nD48GG2bdtGSkoK36VTFDJi08mITeexoVfyZdkRPinI4UBdKfGJ4bRnVquV5cuXc8899zB16lTWr1/P4MGDaS4VIcQ3NDReOriBUK5JG8qgqCRa4v0/fMaEazJI6Z2A6Nj8wSBZVSf5vOQQG8qOUOZu4FzqHhbDiJg0RsamMzI2jV7h3VBQEKKz2LflCIPH9UWI8yXcYCbcYCYUT8BPhaeBSo+DUlc9lR4HZZ4GKj12Ktx2yt0NVHjseIMBOiuX38uRhgqONFTQXDpF4SdDrmBYTApt4aS9iqa8l7eTfXUl/H709aTZoglF0zRuuOEG9u/fz4YNG0hJSSEUk17lypSBXJkykKCm0REoisKf//xnAoEAl156KZmZmfTq1YvmUBFCfOOz4gMcqi+nKSa9yg8GXExLbPwwm7i0GAaOuQDRMXmDAbZWHGdt8UHWlx2m3uvmXFCACyLiGRvXkwu7dWdkbDqxJhtCdGbZ63K56WczEaK9M+tV0m0xpNtiIJbTqml0UemxU+ZuoNJjp9xjp8Jtp8Jjp8zdQKXHTnWjk64iqGk8uWclz+SuJskSSaotmnRbNOm2GLqHxZBuiyHNFoNZr9JSnoCPCo+dUA7UlTL7y9d4btR1XJzYl6Y888wzfPnll2zfvp3U1FRaSqcodBSKovDKK69QXV3NzJkz2bJlCzabjVBUhBAENI0/H9xAKHN7ZJBkjaS59m45Qm15PTPuvgzRsXgCPjaVH2Nt8QE2lh3F4W/kXOgZFsuYuJ6MjuvB6G49iDXZEKKr8LgaMZoMqAY9QnQWMSYrMSYr/SITOB1fMEClx0GZu4EKj50Kj50KdwOVHgfFrjpK3fWUu+0EtCCdhT8YpNBZS6Gzlkz+mwIkWCJIt8WQHhZDd1sMabZouofFkG6LwaoaOZV8Rw1BTaM5Gnwe7slcxq19JvDAoEvQKzq+a/Xq1fzyl7/ks88+o0ePHpxX69fDa6/Bnj1gNMKkSfDQQ5CeDno9zJkD06fD7NlgNvONVavgd7+DTz4Bq5Xm0Ol0/P3vf2fcuHHccccdLF26lFBUhBCsLNzLcXsVTTHrVW7rO4HmqiiqJmvNHm5/ag6iY/AE/GwsO8Kqon1sKj+GJ+CjrSVYwrko/gLGxPVkTFwP4s3hCNFVbVmxkwnTMxCiqzHo9CRbI0m2RnI6AU2j0mOnxFVPiauOUnc9pe4GSl31FLvqKHXV4/A30hloQJm7gTJ3A9lVeXxXN3MY3W0xpNtiSA+LobsthvSwGI40VNASGvDG0S3sqSnkt6NnE28O5z/q6+u5/fbbefLJJ7n44os5r/71L/jlL+Haa+GRR8DthldegUWL4PXXITUVKivB4eC/uN1QUQGaRkuEhYXx4YcfMnz4cD744ANmzZpFU1SE6OICmsarhzcRysJeY4g3h9McXo+Pd174F4uem49o33zBAFsqjrOqaB/rSw/j9HtpS0adnoxu3bkovjcXJVxA34h4hBD/dnRPPpfOG48Q4n/pFYVESwSJlghGxqZxKnZfI6XuekpcdZS46il111PqqqfUXU+xq44qj4OAptHRVXkcVHkc7KwuoDXsrC5g5vq/8OKFsxgb15OvPfbYY3Tr1o2HHnqI88rrhT/9CaZOhZtugsRECAahZ0+YMQM+/hhuvZXW1qdPH5544gnuvfdeLr30UqKiojgdFSG6uI/yd3PSUU1TrKqRW/qMo7mWPPcJ8x+5BqPFiGh/AprG9qo8VhbtY13JQeq9btpSj7BYLkrozUXxFzA6rgcWvQEhxH+rKqklqUccQogzF24wEW6Ip29EPKfiDwYp9zRQ6qqnxFVPibueUlc9pe56Slz1lLjqcAd8dEXVjU5u/eof3NZ3Apdpibz22mtkZmZiMBg4rw4fhpMn4ac/hYQE0OtBr4ekJJg4EbKyYOFC2sIDDzzA0qVLefbZZ3n++ec5HRUhujBfMMArhzcRyk29xxJrstEcn/51PaOmDiEuJQbRvuyvK2VFQQ4ri/ZR3eikregVHRmx6UxJ7MslSf3oHhaDEKJpX7ybyeULJiCEaDuqTkeKNYoUaxSnU+d1U+yqo8hZS5GrjmJnLUWuOgqdtZS46vAGA3RWGvD6kS28W+Zk2tzZjBo1ijP1+OOP8+677+JyuWipK664gieeeIK0tDSorgadDmJiQK/n/ygKpKTAwYMQCPCNZ5+Fl14CReEbDQ1gNnOmVFXlqaeeYv78+TzyyCN069aNU1ERogv7uCCHElc9TQk3mLi5zziaY/+2o+gNeoZc1A/RPpS77awpOcDHBXs4WFdGW7HoDYyJ68nFSX25NKk/sSYbQojms9c6iE6IRAhxfkUZLUQZLQyKSuK7ar0u5m54nUJnLZ2ZPdFGxdzh7KouZGRsGmfiwQcfZNGiRWiaRkuZzWaioqL4Rng4+P3gcoGmgaLwf2prwWYDnY5v3HgjXH01mEx8Y/16+Mc/OBvTpk2jd+/evPTSSzzxxBOciooQXVRA03jj6BZCuaXPeCIMZkKpLK5hy6e7uPOZuYjzy+n3sq7kIJ8U5JBdlUdQ02gLiZYILk8ewMVJ/RgV9ZMajgAAIABJREFU2x1Vp0MI0XL7tx1lwKjeCCHaL0/Az+LMZRQ6awlFpyjM7jGSMNVEkbOWIlcdRc5aGnweOooav4cbN/+dRf0msrj/ZHSKQktER0cTHR3NWevXD2JjYfNm6NcPIiP5hscDGzbAZZeB0cg3UlJg2DAwmfjGiROgKJwNRVG4//77efrpp/nFL36Boih8l4oQXdSa4v3kO2poSpTRwvd7jyEUv9fPOy/+i7t+NR9xfmho7Kgq4P28XawtOYgn4KMtpNuiuSx5IJenDGBIdDIKCkKIs7Nt9R5ufOw6hBDtU1DTeGTHh+ypKaI5fjzkCm7sPYbvsvs8FDprKXLVUeSspchZS76zhkJnLSWuOgKaRnsS0IL8+dBGDtWX86uMawk3mDnnbDa44w54+WUID4fp08Htht/+FpxOmDULrFa+oSig14Oq8g2dDhSFszVr1iwWL15MdnY2Y8aM4btUhOiCNDT+emQLodzedwJhqolQlr7wKTPvuRyj2YA4txp8Hj4r3s/bx7M52lBBW0izRTMlsS9XpAxkZGwaCgpCiNbhdXsxmgwYTCpCiPbpub1rWFdykOa4+YJx3Nh7DKcSbjAzMCqJgVFJfJc/GKTUXU+Rs5ZCVy2FzlqKnLUUOms5bq/EE/BzvnxReohZX5bzu9HXMygqiXNKUWDBArBYYMkSeP55UFUYMQJefhn69AGdjrYUFRXF1KlT+eijjxgzZgzfpSJEF7S57BiH6stoSqTRwryeFxJK9ppc0vslk3JBIuLcCGoaWytO8H7+LtaXHsYXDNDaeoV34+rUwVyZMoje4d0QQrSNTR/vYPw1IxFCtE9/O7qVfx7PojmuSBnIw4Mv40yoOh1ptmjSbNGM478FtCDFrnoKHDUUOGvId9ZQ4KihwFlDkbMWbzBAWyt01rJw09/46dCruL7HSM4pqxVmzoTLLwevFxQFTCaIiABVBUWB994DiwVMJv7PVVfBRReBxcLZmjhxImvWrOFUVITogl478hWhLOw1GptqpClVJbUcyDrGzT+fiWh75W47H+bv5oP83RS76mhtKdYork4dzNWpg+gfmYgQou2d2FfI1PnjEUK0P58VH+A3+z+nOYZGp/Bcxgx0ikJr0ys60m3RpNuigd58W1DTKHXX8+jOj9lelU9b6R0ex5UpA5kQ35vzwmIBi4XTiovjf1itYLXSGjIyMvjVr35FMBhEp9PxbSpCdDE7qwvYWV1AUyx6Awt7jaYpAX+Qpc9/yl2/modoO0FNI6vyJO/l7WRdySECWpDWFG20clnyAKanD2VkbBoKCkKIc6O8oIqkHnEIIdqf3NpiHt35MUFNI5R0WzQvj5uPWW/gXNMpCinWKOw+D60txmTle6lDmJE+jIFRSXRlgwcPpqGhgZKSElJTU/k2FSG6mNcObyaUOT0ziDFZacq7v13JjLsvw2QxIlpfobOWD/J381H+Hio8dlqTTTVyWfIArk0fxuhuPdApCkKIc2/9e9v43i1TEEK0LwXOWu7OXIon4COUaKOV18bfQKzJxvmioZHvqKE16FGYmNiHa9OHcWlSPww6PQLi4uJQFIWamhpSU1P5NhUhupBD9eVsLj9GU1Sdjpt6j6UpOz7fS0J6LOn9khCtxx8Msq70IMvzdpFVeZKgptFa9IrCuPheTE8bxmXJ/THrDQghzh9N03DZ3UTEhiGEaD9qvS7u3Po2NY0uQjHrVV4eN5/uYTGcT+VuO+6Aj7MxJDqZ3X/7iMeuvZnvj5uD+G+qqhIWFkZtbS3fpSJEF/L6ka/QaNq1acNIskZyOvVVdnZ9eYA7n5mLaB3VjU4+yt/DkhPZlLkbaE29w+O4MmUg13UfToo1CiFE+5Cz+RBDJ/RDCNF+eAJ+FmcuI99RQyg6ReGFUbMYHpPK+ZbnqOZMJFjCuSZtKDPSh9E7PI4eNz9D+Ewj4tRUVcXv9/NdKkJ0EeVuO2tKDtAUvaJwe98JNOWd3/yLhT+ejjh7+2pLePtENquL9uENBmgt4QYT09KGcn33kQyISkQI0f7sWLeXW34xGyFE+xDQNH60/QP21BTRHD8ZcgVTk/vTHpy0V9FcJr3KxYl9mZ4+jEkJF6BXdPxHVFQUtbW1iP8VCASor68nNjaW71IRoov45/Es/MEgTbk8eSA9wmI5nbVvf8WYq4YTFmVDnJmAprGp/Cj/PJ5FZsUJWtOgqCTm9MzgmrShWPQGhBDtk8vuxhJmRq/qEEK0D8/t/YwvSg/RHLf1Gc/3e4+hvchz1hDKoKgkpqcPY3raUKKMFk4lOjqampoaxP+qq6sjGAwSFRXFd6kI0QW4Az6W5+0klDv6XsTplOVXUVFUzeU3XIRouepGJx/l72HJiWzK3A20lnCDmatSBrGg14X0i0xACNH+bfwwm4kzLkQI0T68cXQLbx/PpjmuTBnIg4Om0p7kOao5lURLBNPShnB9j5Gk22IIpVevXhw+fBjxvw4dOoTZbCYlJYXvUhGiC/gofw8NPg9NGRvXkwFRiZyKFtR4/w+rufOZuYiWOVBXyrsnd7KiMAdPwE9r0CkKw2NSuTZ9GNPThmHWqwghOo6io2VcddNkhBDn3+ri/fx2/xc0R0ZsOs9lXIdOUWhP8uzV/IdZrzIlsS9zemQwNr4nCgrNlZGRwRtvvIH4Xzt27GDYsGEYDAa+S0WITk5DY8mJbEK56YKxnM5HL6/l6lunYLQYEaH5g0E+Lz3Ee3k7yaw4QWuJM4dxbfowru+RQbotGiFEx1N8rIzUPokIIc6/ndUFPLrzY4KaRijpthj+OGYuJr1Ke+ILBih11zMyNo1r04cxLXUIVtXImRg1ahQPPPAADoeDsLAw2orf62ftK2uJSYlhyNQh2KJs+Bp9rPrDKlL6pzDo4kFYwi20J1lZWWRkZHAqKkJ0chvKjnLCXkVTuofFMCmhD6dyYl8hKAq9BqchmlbvdbP05HbeObGDCo+d1qBXFCYm9OH6HiOZnNgHvaJDCNFxffl+FjPuvgwhxPl1wl7FPdveoTHgJ5Roo5W/TlhIjMlKexPUNNZefj+JlgjO1qhRo+jWrRuffvop8+fPp63oDXoGTh7IV0u/Iq57HD1G9CBnTQ5et5fUgamYbCbaE4/Hw6pVq3jnnXc4FRUhOrm3jmUSyk29x6JTFL4r4A+y6s2NLH5+AeL0Slz1/P1YJu/n7cId8NEa4s3hzO2ZwazuI0mwhCOE6PiCgSA+j4+wSCtCiPOnptHF3ZnLqPe6CcWsV3ll3HzSbTG0Rya9SqIlgtag0+mYOXMmy5cvZ/78+bQVRVFIG5RG2qA09m/Yj9fj5eCmg4ycNpLY1Fh0Oh3tyerVq9HpdFxyySWciooQndiRhgqyK/NoSoTBzLXpwziVj15eyzW3X4xOr0P8ryMNFbxxdAurivbhDwZpDYOikvh+7zF8L3UIqk6HEKLz2PnFPkZcPBAhxPnjCfhYvG0ZBc4aQtErCi9eOIthMal0FQsXLmTy5MkUFBSQnp5OW9Eb9GRMy2Dl71ey7tV1DJg4gNSBqagmlfbm1VdfZd68eRiNRk5FRYhO7B/HtqHRtOt7ZGBVjXxX0dEyFEWh+4AUxH/bWV3A60e2sLHsCBpnz6DTc2lSP268YCwjYtIQQnROezYd5Pan5iCEOD8CmsaPtn9ATk0RzfHo0Cu5NKk/XcnYsWMZN24cL774In/84x9pS7ZoG5EJkRTuLyR9aDph0WEoikJ7snv37v/HHnwASFHmCR/+ddVbXdUTuicPYYYhSM4gIJJEQSSIEXFdEVdBwbzqum4w7XrrerjBuAbAnBUVFBEMiJIkKGHIShhy7h5murqrqvs7uGM/jlNA4oT/8/D555/zxBNP8FMUQlRRpY7NR+sXcyi6T+PKBh05WDKR5P2nP2XEX3+B+G+JZJIvt6zkmeVfsWDneo6HHCuNC+u05sr6ncgPpCOEqLpKd5WRnpmKT/MhhDg1Hlo4ic82LedIDGvUhV/W70h19Ic//IELLriAO++8kzp16nCirFu8jh0lO8guzGbVN6vIq5dHZs1MKpJ77rmHwYMH07BhQ36KQogq6r2132F7DodyXu1m1AgEOdiE0Z/TZ0hXlKFT3cUTHh+vX8yzK77mh9LtHA/NM2oypEEn+he0RGkaQoiq74u3Z9Hj4o4IIU6N51Z8zas/fMOR6Fu7Ob9udg7VVe/evenRowc33XQT48eP50Swy2zmfjCXum3qUq9tPT4f+zlrF6wlJZSCmWJSEbzzzjt88cUXLFq0iENRCFEFJUny5pp5HM6QBp042JZ12ykvjdKwTV2qsz1ujHFrv2PMiulstUs5Voamc07Nxgw9rTNtsgoQQlQvm9dup2a9PIQQJ18imWTBzg0cidNzivjr6Reh+XxUZ//6179o0aIFb7/9NoMGDeJ4++7j79CURoMODcirl0eb89qwcPJC8uvnU6NhDXw+H6fSrl27uOWWW3jggQeoX78+h6IQogqavW0NP5Ru51CahGrQOquAg73z2CSGPziY6mqrXcqYlTN4Z818yt04xyrPSufy+qdzWd32ZJupCCGqnzXF66nfohAhxKmh+Xw82ukyHlo4iVd/+Iaf0iA9hyc6Dcav6VR3devW5aGHHuK6666jTZs2NGzYkONl4/KNfD/ne9r2b0t2YTaartG4S2PWLlhL8dRi0rLSSM9J51RJJBIMGTKEoqIibrvtNg5HIUQV9PoPczicKxt05GBT35lNl/Pb4bcMqpvN0QjPrfiad9d+S8xzOVZNQvlc07ALfWs3R2kaQojq68tx33DZ7f0RQpw6us/HH1v3pU5aFg8v+oREMsmBsswUnur8C0L+AOK/3XzzzcyfP5+BAwcye/ZsgsEgx0Ne/Twu/N2FmCkmuqGzl2EanDP8HPbyB/ycSvfddx9z585l7ty5KKU4HIUQVcw2ew+fb17OoaQbJv0KWnCg8tIoPywq4ZoHLqU62VQe5vlVM3lrzTxinsuxapddyLBGXTmrRkN8+BBCVG9u3CXhJQikmgghTr2rGnSiZiDIXXPHYXsue1m6wVNn/II6qVmI/+3JJ5+kW7duXHzxxUyYMIFAIMCxUoZCZSgOZqVZnGpPP/00o0aNYsqUKRQUFHAkFEJUMW+vmYebSHAoF9VpQ0A3ONCbf/uIC0f2prrYUL6bF1fN4s3Vc4knPI6F5vPRPb8hIxp3o3VWAUIIsd/sSQvoeF5rhBAVR+9aTXmh61BumPU64XiURzpcQuusAsT/lZKSwqRJkzj77LO54IIL+OCDDwgEAlRFY8eO5bbbbuPNN9+kW7duHCmFEFWIl0zw9pr5HIoPuKze6RxoxbdrqFEvl6waIaq69eW7eW7517y79lu8ZIJj4dd0zitozvWNulE/PQchhDhY8ayVDP+PwQghKpbWWQW80v0aFu/ayDk1GyN+Wm5uLp9++ilnnXUWffr0Ydy4ceTk5FCV/PWvf+W+++7j9ddf54ILLuDnUAhRhXy1ZRWboxEOpWNuXRqk57Bfwksw6cVp3Pz3IVRlJWW7GL1iOu+u/RYvmeBYpCmTi4raMKxRF/KsdIQQ4sfs2hohq0YGPp8PIUTFUy8tm3pp2YjDy8/PZ/r06Vx66aV07NiRCRMm0Lx5cyq7eDzO9ddfz7vvvsu4cePo378/P5dCiCrknTXfcjiX1+vAgT4aO5X+156FT/NRFa2KbOO5lV/zUckivGSSY5FjpTG4bnuGntaZdMNECCEO5fM3Z9Ljko4IIURVkJWVxaRJk7jhhhvo1KkTjzzyCNdffz0+n4/KaNGiRVx11VWUlZUxZ84cGjduzNFQCFFF7IiV8eWWFRxKjpVGr5pN2G/X1gi7toZp0LIOVc2KyFaeXDqVTzctI5FMciwah/K55rQz6VfQAqVpCCHEkdi1LUxu7SyEEKKq8Pv9jB49mrPPPpubbrqJDz74gGeffZbCwkIqC8dx+Nvf/sb999/PlVdeyT/+8Q/S09M5WgohqogP1i3ATSQ4lIvrtEFpGvu9+/gkLvt1P6qSdWU7eXzpVCauX0wimeRYtMysxcgmPTirRkN8+BBCiCO1bO4PNGpbDyGEqIquuOIKunfvznXXXUeTJk244447+O1vf0tqaioV2Ycffsidd97Jnj17ePvttzn//PM5Vgohqohxa7/jUHzAxUVt2W/VgrUUnFaDYFYaVcHmaISxK2fw5uq5xBMex6JNVgHXNe7GWTUa4sOHEEL8XDM/+pZf/nYgQghRVRUUFDBx4kQ+/PBD7rzzTsaMGcOdd97JsGHDSE9PpyKZMmUKDz30ELNnz+aOO+7gt7/9LampqRwPCiGqgG93lvB96TYO5fScIorSstgrmUwy5dXpXP/Q5VR2u+LljF05g1e+n43tuRyLdtmFDGvUlZ41GiGEEEcrbjtouobfMhBCiKpuwIAB9OnThzFjxvDII4/w5z//mREjRnDttdfSoEEDTpWysjLeffdd/vnPf7J8+XKuvvpqXnzxRQoLCzmeFEJUAe+u+ZbDuaSoLft98dYsug5sj6ZrVFZlbpzXf5jDM8u/Yo8b41i0yy5kWKOu9KzRCCGEOFbTJ8zjzAFtEUKI6sIwDEaMGMHw4cMZN24c//znP/nrX/9Kly5dGDJkCBdccAH5+fmcaLFYjGnTpvHqq6/y7rvvEgwGGT58ODfeeCO5ubmcCAohKrmo5zBpQzGHkqZM+tRuxl6xaJzVS9Zz9uDOVEa25/DK99/w3IqviTg2x6JddiE3N+3JGbn1EEKI42Xlt2voOegMhKhUXn4ZUlKgZ0/IymKfpUvhww/h4ouhQQP2WbQIPv4YVq0CTYPmzeGii6BWLdA0Tgnbhq+/hsmTYft2yMyEzp2hXz9ISYGSEnjtNejbF1q1Yp9wGKZOha1bYfhwxPGh6zqDBg1i0KBBrFy5kpdffpmHH36YESNG0KZNG/r06UP37t1p164d+fn5HCvbtlm4cCGzZs1i8uTJTJ06lb0uuOAC3n77bXr37o2u65xICiEquY/XF1PmxjmU/oUtsHSDvd57ajIDrzuHysZJeLy37jueWDqVbfYejkW77EJuaXo2nXLrIoQQx9P2jbvIr5ODEJXO3LkQCkHHjpCVxT5btsAXX0CPHtCgAcydC48/DtnZ0L49JBIwaxYsXw533w21a4PPx0kVjcJHH8ELL0CnTtCkCWzbBu+8A2vWwG23we7d8Nln0Lo1tGrFPrYNxcXw/fcwfDji+GvYsCF/+tOf+NOf/sTy5cv55JNPmDx5Ms888wy7du2idu3atG7dmvr161NYWEhBQQF5eXmkpqbi9/vJyMigvLyceDzOrl27iEajrF27lpKSEkpKSiguLmbJkiX4fD5atWpFr169uP322+nSpQumaXKyKISo5MaXLOBwLilqx147Nu7Cp2nk1s6isvCSSd5f9x1PLvuSTeVhjpYPOKtGI0Y26UHLzFoIIcSJ8NmbMzn3ii4IUeU4DowZA34//OIX0Lw5JBLQti385jcwZQoMGgRpaZw0ySRs2wZPPw3dusGwYZCVBbt3Q82a8NxzcOaZkJ6OOLUaN25M48aNueWWW9hr9erVzJ8/n0WLFrFmzRo++eQTSkpK2L59O+Xl5cRiMfbz+XxkZGRgWRZFRUUUFhZSWFhIz549adeuHS1btsTv93OqKISoxLZES5m7fS2H0jCYR8vMWuz13r+mcMVd51NZfLl5JY8UT2FVZBvHomt+A25tejYtMmshhBAnSjKZJLKjlMz8EEJUOSUlMG8e3HEHtGgBgQD7dOgAbdvCjBnQty+kpXHSuC4sXQo//ADPPQc1a7JPXh506QLjx8PUqXD++YiKpV69etSrV49LLrmEnxIOh0lNTUUpRUWmEKIS+3D9QrxkkkO5uKgNe/2wuITChjVJSQ9Q0S3etZFHiqcwe9sajkWbrAJua3YOnXLrIoQQJ9riGStp0bkRQlRaH30E8+dDSgr7bNsG27axz5Yt4DhQUACWxb/pOjRoAJ99Bo7DSeW6sGkTmCYUFvJvPh+kpEDt2rB+Pfts3gx/+QuMHcs+tg0bN0Lr1oiKKRQKURkohKjExq9byKHoPh8DClqy1ycvfcV1f7mcimxzNMK/lk3jnbXzSSSTHK2GwTxuaNKD82o3QwghTpZvJi9g6B8vRohKq0kTOOssyM5mn+JimDSJfUwTEgmIxyGRAF3n38rLwe8Hn4+TyucD0wTHAccBpfi3RAJsG1JT2SctDc46C9q0YZ9wGKZORYhjpRCikloW3syKyFYOpXNefXKsNGZPWsDpvVqgK42KKByPMnrldF7+fjYxz+Vo1U/P4bpGXTm/sBWaz4cQQpwsdnkM0/KjDB0hKq26deGcc6B2bfZJT4fp09mnfn3IyoJ586BNG8jMZJ9YDGbPhqZNIRDgpDIMaNIEkkmYPh169WKfRAJ27oTiYrj2WvZJTYWOHaF3b/bZuhVKSmDtWoQ4FgohKqkJJYs4nPMLW5HwEsz/vJiR/3kFFY2T8Hh99VyeWDqVUsfmaNVMCTGicTcuKWqL7tMQQoiTbdq4OXQZ2A4hKjVdB8MA02QfwwBNY59gEAYPhjfegKws6NcPXBdeeAE2boQ774RgkL1s26a8vJxQKISu6xxPyWQSz/PYtGkThQUFUKcODBgADz0ElgUtW8KqVfDkk5CRAX37wrZt4POBUmCa7OP3g1IIcawUQlRCiWSSiesXcygB3aBXzSZ89sZMel1xJhVJkiSfbFjK3xZPYX35bo5WlpnCr047k6tOOwO/piOEEKfKmqUbOPfKrghRZWkaXH45+P0wcSI8+yz4fFBUBPfeC23bglLstW7dOu666y66d+/Or371KzIyMvD5fBwrz/OYP38+Tz/9NEVFRdxzzz34MjLg1lvhhRfg/vshHIa0NGjTBm67DfLyYNs2hDhRFEJUQt9sX8PmaIRD6V2rKf6ExroVG+n9yy5UFLO2rebhRZNZFt7M0crwBxjWqCu/rN8BSzcQQohTafPa7dSqn4cQR2L8uoV0r9GQDH+ACuXuu0HTICuLf+vQAZ56CvLy2CcjAwYNgrPPhvJy8PkgNRXy8sA0wedjrzp16vDrX/+a119/nSuvvJJrr72W/v37Y5omRyORSLBhwwaeeeYZpk+fzoUXXsill17KProORUVw660wZAjE46AUZGRATg5oGjRsCM8+C9nZ/Ft2NgwfDvE4QhwLhRCV0KQNxRzOwDqt+Oj5qfS+oisVwbqynfznosl8tmk5R8vSDa5q0IlhjbqSbpgIIURF8NkbMzh/+NkIcSTeXfst93/3IZfWbcewRl3Is9KpEGrW5P9ITYXUVP6X9HRIT+dQLMvizDPPpFGjRsyYMYMxY8bw3nvvcccdd9CyZUt0XedIJJNJysrKePHFF3n55Zfp2rUrjz/+OIWFhQSDQXw+H/voOmRnQ3Y2P8qyoG5d/helIDcXIY6VQohKxksm+XTjMg4l20yldUot3t78HXUa1+RUKnfjjF05g+dWfE084XE0NJ+Pc2s15c4WvamdkoEQQlQUyUSSaJlNMCsNIY5EivIT9Rxe/n42b66ey4V12jCySXdqBIJUJYZhULNmTfr370+HDh2YMGECI0eOpFu3btx2223UrFkTn8/HT0kkEkyePJmHHnqIgoIC/v73v9O4cWMyMzPRNA0hKgqFEJXMvB1r2REr41D6FbTgo+e+oO/VPThVEskkE0oWMmrxFHbEyjhanfPqc1eL3jQJ1UAIISqa+VOX0LZHM4Q4UqnKz37xhMdba+bx3rrv6FvQnBub9KBOahZViWVZFBYWcvXVV9OrVy9Gjx5N//79ue666/jVr36FaZr4fD72SyaTLF68mPvvv5/du3dzxx130KVLF0KhEEophKhoFEJUMpM2LOFwuqfU44fyJdQoyuFU+Gb7Gh5a+AnLwps5Wg2DedzZvBfdazRECCEqqvmfL+baBwYhxJFKVSYHcxIe49ctZOL6xfQraMGIxt2pl5ZNVeHz+UhNTaVhw4bce++9XHLJJfzjH//gtdde449//CO9e/dG0zR27drFI488wrhx47jmmmsYOnQoGRkZ+P1+hKioFEJUIolkkk83LuVQcqw01o1bzvnDz+Fk2xyN8I8lnzF+3UKOVo1AkJFNunNpUTs0nw8hhKioyiJR0kIpaLqGEEcqRfn5KW4iwfh1C/mwZBHd8xtyS9OeNM2oQVWhaRrp6el06NCB0aNH89FHH/G73/2OF198kbp16/L2228zcOBAJk2aRH5+PqZp4vP5EKIiUwhRiczbsY5t9h4OpVf6aSS8JJl5QU6WqOcwZsV0Rq+cTsxzORpBw2J4o64MadAJU1cIIURF98Xbs+h6wekI8XOkKj+Hk0gmmbp5BdO2rKR7fkNubNKDFpm1qCp0XSc9PZ1LL72UPn36cP311/PMM8/w6aef0qxZM/x+Pz6fDyEqA4UQlcgnG5ZwOKmfl9J3+ABOhiRJPli3kL8Vf8p2ew9Hw6/pXNmgE9c37kbQsBBCiMpi4w9bGXBtT4T4OVKVyZFKJJNM3byCLzevoGfNxoxo3J2WmbWoKpRSZGRkMGTIEMrKymjdujWapiFEZaIQopJIJJNM2biUQ8lJpJCn0siumcGJtiy8mT8vmMj8HSUcrbNqNOL3rc6jMDUTIYSoTNYu3UBRk1oI8XOlKD8/VxL4fNNyPt+0nHbZhdzctCdn5NajKvD5fOi6jqZpaJqGEJWNQohK4tudJWy1SzmUZrMV/W7rwYlU6tg8vnQqr/3wDV4yydFokJ7L3S370DW/AUIIURlNe28Ol95yHkL8XCnKz7GYv6OEX339Eu2yCxnWqCs9azRCCHHqKISoJCZvWMKhaNEERXoGObUyORGSJBm/biGjFk9hR6yMo5HhDzCySQ9+Wb8jus+HEEJURp6bwI27BNIshDhQIplkjxujzIlR7jnNGTo+AAAgAElEQVRE3Tiljk25F6fcdYh6cb7dUcLxMH9HCTfMfJ22WYWMaNKd7vmnIYQ4+RRCVAJJkkzZtIxDyZsW4+rf9edEWLJ7E39eMJHvdq7naChN4xf1OnBz056kGyZCCFGZzZm8kNN7tURUDbbnEnGiROI2sYSL7TlEHJtIPEos4WJ7LpF4lFjCJea5hJ0okbhNLOES8xzCcZuIEyXmuexxYySSSU6mb3eWcP2MV2kSyufq0zpzfmErNJ8PIcTJoRCiEvhu53o2lYf5Kb5YkgYqi1pFeRxP4XiUJ5d9yWs/fIOXTHI0zqrRiN+1Oo86qZkIIURVsOCrpVz3l8sRJ5/tucQTLrbnEInbhJ0occ/FTrhE4lHCjk3cc7E9h4hjE/Nc7IRDJG4TcaLEPBfbc4k4UcLxKPGER1WxLLyFu+e9z5iVM7i24ZkMKGyF7vMhhDixFEKcZDt27KC4uJi1a9eyadMmNm7cyJYtW7Btmz179uB5HtFolLS0NHRdJxgMsr1TIdQP8lPSPy/lkpEXcLwkkkneXjOffyz5jHA8ytFoHMrn7pZ9OCO3HkIIUVVEdu4hIy+Ez+dDHJ7tuUScKDHPJea5hJ0oEccm5rnEPIewYxOJR4klXGKeS9iJEonbxBIuMc8hHLeJJ1xsz2FnrAwvmUQc2srIVu6e9z6zt63hP9oPxIcPIcSJoxDiBCorK2PGjBlMmzaNWbNmUVxczKZNm/i5Chv/klSC/BhfLIFZmqBuSoDjYVl4Cw989yHf7VzP0cjwB7i12dkMqtse3edDCCGqki/emkXPSztRFdmeSzzhYnsOkbhNLOFiew4RxyYSjxJLuNieSyQeJeLYxDwXO+EQidtEnCgxz8X2XCJOlJjnEnFsxMkXNCxub96LQXXb4cOHEOLEUghxnK1evZr33nuP999/n1mzZuE4Dseq5MFXMfIySOvYhLTTG5HSvAifrrNX2tQ9rFNraNakKTVq1KBfv35cdNFF9OrVC8uyOFK25zB6xXSeXfE1TsLj5/IB59dpxW9b9CHLTEEIIaqibRt2kleYTUVgey4RJ0rMc4l5LmEnStxzsRMukXiUsGMT91xszyHi2ISdKHHPxfZcIk6UcNwmnnCxPYdd8XLcRAJRuZ1Xuxl/bN2PbDMVIcTJoRDiOIhEIrzyyiuMGTOG+fPncyI4W3ez68NZ7PpwFnp6CmntG5J2eiO0VvXZ/twi9tq8eTNjx45l7NixpKenc9FFFzFixAg6d+7MoXyxeQUPLpjIxvIwR6N5Rk3uad2P1lkFCCFEVbV83mpOa1PE0bI9l4gTJRK3iSVcbM8h4thE4lFiCRfbc4nEo8QSLjHPJexEicRtYgmXmOcQjttEnCgxz2WPGyORTCLEXkVpWdzbuj9n5tVHCHFyKYQ4BitXrmTUqFG8/vrr7Nmzh59L0zTy8/PJz88nOzsbn89HKBRC0zTKy8uJxWJEo1F27NhBSUkJZWVl7OWVlhOeuoDw1AVsMg2SrsfBSktLeemll3jppZdo3bo1N998M1dddRWGYbDfVruUhxZOYtKGJRyNkD/ADU16cGX9jmg+H0IIUVXYnks84WJ7DpG4TdiJMvGNzzjjxs58sG4BYccm7rnYnkPEsYl5LnbCIRK3iThRYp6L7blEnCjheJR4wkOI483SFSMad+eahmdiaDpCiJNPIcRRWLFiBQ8++CCvvfYanudxOJqm0apVKzp06EDz5s1p0aIFTZo0IT8/H6UUR2rPnj388MMPLF26lEWLFrFo0SKmT5/Ojh07OJQFCxYwbNgwHnzwQX7/+98zZOhVvFXyHY8t+ZwyN87Ppfl8DChsyd0t+5DpT0EIIU4lN5Gg3ItT6thEXYdyL06ZE2OPGyPqOpR7cfY4McrcGOWeQ9SNU+rYlHsOUTdOuRun1LEp9xyibpwyN87BtHiC9M0RXvt2A0IcLd2nkar87HFjJJJJjkX3Gg25p3U/ClIyEEKcOgohfobS0lLuv/9+HnvsMVzX5VAKCgq48MILOffcc+natSuZmZkcq7S0NFq1akWrVq0YPHgweyWTSRYvXszUqVOZMGECU6dOxXEcfsyaNWu47rrr+Pt7r8Dwszka7bPr8MfWfWkSqoEQQhwt23OJOFEicZtYwsX2HCKOTSQeJZZwsT2XSDxKxLGJeS52wiESt4k4UWKei+25RJwoMc8l4ticaIG55URPT0FUP6auCBoWQSOApStMXRE0AgT9FpZmYOqKoGER9AewdIWpKYL+AJam8OuKkBEg6LewdIN0w8SHj3MnP0ZJ2S6ORp6Vzu3Nz+GCOq0RQpx6CiGO0Pvvv89NN93Ehg0b+CmZmZlcddVVXHHFFXTo0AGfz8eJ5vP5aNmyJS1btuTmm29m165djB8/njFjxvDVV1/xY5Z9PI1aTXIJdmvJkco2U7mrxbmcX6clPnwIIaoP23OJOFFinkvMcwk7UeKei51wicSjhB2buOdiew4RxybsRIl7LrbnEnGihOM28YSL7TnsjkdxEh6VjfmDQ9mZaYiKzdQVpqYwdUXQCBDyW5i6gakpgn6LkBHA1BWmpgj6A4QMC1M3MHVF0LAIGQFMXWHqikx/CoamcyKkKj8/l+7TuKJ+B25p1pM0ZVKVpKamUqtWLYSojBRCHEY0GuX222/n6aef5qe0aNGCO+64g8GDBxMIBDiVMjMzGTp0KEOHDqW4uJinnnqKsWPHYts2B9oy5mNSWzdAD6ZwKD7g/Dqt+F3L88jwBxBCVHy25xJxokTiNrGEi+05RBybmOcS8xzCjk0kHiWWcIl5LmEnSiRuE0u4xDyHcNwm4kSJeS573BiJZJLqTG1zcWopxPFn6oqgYRE0Ali6wtQVQSOApSv8uiJkBAgaFpZu4NcVIcMi6A9gaQq/rggZAYJ+C0s3SFMmms9HZZCqTH6ONlkF3NdmAE1C+VRFTZs2ZdiwYQhRGSmEOITVq1czcOBAFi9ezI9p2bIl9957LxdffDGaplHRNG/enCeffJI//OEPPPzwwzzzzDPEYjH28iLlbHvlU2rcMJCf0jiUz/1tBtAmqwAhxIlhey7xhIvtOUTiNmEnStxzsRMukXiUWMLF9lwi8SgRxybmudgJh0jcJuJEiXkutucScaKE41HiCQ9xfKXOLKP0nDSqO1NXmJrC1BVBI0DIb2HqBqamCPotLM3A1BVBwyLoD2DpClNTBP0BgoaFpRuYmiLotwgZAUxdUV2lKD9HIt2wuKnpWVxZvyOaz0dVkvASlBSXkFkrk9zcXPLy8kh4CdYtWkdOnRzSstIQojJQCPETFi1aRN++fdmwYQMHC4VCPPDAA9x0003ouk5FV6tWLR599FFuueUWbrnlFiZOnMheuz+bT7BbS1Ja1uNAlm5wbcMzub5xNwxNRwjx/9meS8SJEvNcYp5L2IkScWxinkvMcwg7NpF4lFjCJea5hJ0occ/F9lwiTpRw3CaecLE9h52xcrxkAlFx+ZKgxRIkUnUqG1NXBA0LSzfwa4qQ3yJoBLB0hV9XhIwAQcPC0g38uiJkWJi6gakrgoZFyAhg6gpTV2Sbqeg+DXF8pCo/h3Ne7Wb8sXU/ss1UqqKEl2D2uNlk1cqix1U9UKZi4/KNfPz4xwz49QDSstIQojJQCPEjpk2bxoABAygtLeVg/fv357nnnqNmzZpUNg0aNOCjjz7izTffZMSIEezevZvNz3xIvX+MxGco9kotCTPu6j9QJ5iNEFWB7blEnCiRuE0s4WJ7DhHHJhKPEku42J5LJB4l4tjEPBc74RCJ28QSLjHPIRy3iThRYp5LqWOTRFQn1qIo0eYBTgZTVwQNi6ARwNIVpq4IGgGCfgtLMzB1RdCwCPoDWLrC1BRBfwBLU/h1RcgIEPRbWLpBumHiw4eomFKUn59SlJbFfa370zmvPlWZ8it6XNWD9//6PnVb16Vmo5pMe3kazc9qTmGLQoSoLBRCHGTBggUMHDiQ0tJSDuT3+3n44Ye59dZb8fl8VGaDBw/mjDPO4Be/+AUzZ85kx7ivyejdni1jJ1E6o5g/zNnGSy+9hM/nQ4iTyfZc4gkX23OIxG3CTpS452InXCLxKGHHJu652J5DxLEJO1HinovtuUScKOG4TTzhYnsOu+NRnISHEMfCWmKze3AmBzN1hakpTF0RNAKE/BambmBqiqDfImQEMHWFqSmC/gAhw8LUDUxdETQsQkYAU1eYuiLTn4Kh6YjqI1WZHMzSFdc27MJ1jbvh13Sqg/z6+bTt25YZb82gqHURbsyl44UdEaIyUQhxgHXr1nHeeecRDoc5UCgU4r333qNnz55UFUVFRXzxxRdcffXVvPnuO+z8YAYJO85er7zyCrVq1eLhhx9GiEOxPZeIEyUSt4klXGzPIeLYxDyXmOcQdmwi8SixhEvMcwk7USJxm1jCJeY5hOM2ESdKzHMpc2N4ySRCnAimrggaFkEjgKUrTF0RNAJYusKvK0JGgKBhYekGfl0RMiyMcljSchE9e3QnZAQI+i0s3SBNmWg+H0IcrVTl50A9ajTkj637UZCSQXXTtm9b5k2Yx8y3ZjL4gcFY6RZCVCYKIf6H53lceeWVbN68mQPl5eUxefJkWrduTVVjmiavvvoqubm5PP744xxo1KhRdOvWjQEDBiCqBttziSdcbM8hErcJO1HinoudcInEo8QSLrbnEolHiTg2Mc/FTjhE4jYRJ0rMc7E9l4gTJeLYxDwXIU4EU1eYmsLUFUEjQMhvYeoGpqYI+i0szcDUFUHDIugPYOkKU1ME/QGChoWlG5iaIui3CBkBTF1xNN57agpXDe1LXnY2QhxPKcrPXnlWOrc3P4cL6rSmuirdUYo/xU9KRgrJZBIhKhuFEP/jL3/5C1999RUHSk9PZ+LEibRu3ZqqStM0Hn30USKRCC+++CL7JZNJrrnmGhYsWEDNmjURJ5/tuUScKDHPJea5hJ0oEccm5rnEPIewYxP3XGzPIeLYhJ0occ/F9lwiTpRw3CaecLE9h52xcrxkAiFOBFNXBA0LSzfwa4qQ3yJoBLB0hV9XhIwAQcPC0g38uiJkWJi6gakrgoZFyAhg6gpTV2Sbqeg+jYpgx6Zd5BVmI8Txlm5YDGnQiVubnU2q8lNdOTGH2e/OJqdODk26NuHrN74mt14u6dnpCFFZKIT4L99//z0PPvggB9I0jbfffpv27dtT1fl8PkaPHs369ev57LPP2G/btm389re/5aWXXkIcnu25RJwokbhNLOFiew4RxyYSjxJLuNieSyQeJeLYxDwXO+EQidvEEi4xzyEct4k4UWKeS6ljk0SIE8PUFUHDImgEsHSFqSuCRoCg38LSDExdETQsgv4Alq4wNUXQH8DSFH5dETICBP0Wlm6Qbpj48FHVLJv7Aw3b1kWIE+Gyuu3RfD6qu5WzV7JxxUYG/mYg6dnprF24lnkT5tF9SHc0XUOIykAhxH/53e9+Rzwe50B33XUXffr0obpQSvHqq6/Spk0bNm/ezH6vvvoqt956K+3bt6cqsT2XeMLF9hwicZuwEyXuudgJl0g8StixiXsutucQcWzCTpS452J7LhEnSsxzsT2XiBNldzyKk/AQ4kQwdYWpKUxdETQChPwWpm5gaoqg3yJkBDB1hakpgv4AIcPC1A1MXRE0LEJGAFNXmLoi05+CoemIw5v54Xx+efcFCHEiaD4f1d3OjTv55r1vaD+gPdmF2WiaRvcruzPx0YnUbVOXum3qIkRloBDV3oIFC3jnnXc4ULNmzfjTn/5EdZOfn89jjz3GZZddxn6JRIL777+fCRMmcCrZnkvEiRLzXGKeS9iJEnFsYp5LzHMIOzaReJRYwiXmuYSdKJG4TSzhEvMcwnGbiBMl5rmUuTG8ZBIhTgRTVwQNi6ARwNIVpq4IGgEsXeHXFSEjQNCwsHQDv64IGRZBfwBLU/h1RcgIEPRbWLpBqjLRfT7EyRWPxtENHb9lIIQ4MTzH47QOp9G0e1N8Ph97FTQr4PTzT8dzPISoLBSi2hs9ejTJZJIDjRo1CsMwqI4GDRpEly5dmD59OvtNnDiRkpISCgsLORK25xJPuNieQyRuE0u42J5DxLGJxKPEEi625xKJR4k4NjHPxU44ROI2ESdKzHOxPZeIEyXi2MQ8FyFOBFNXmJrC1BVBI0DIb2HqBqamCPotLM3A1BVBwyLoD2DpClNTBP0BgoaFpRuYmiLotwgZAUxdISq/L9+bQ5eB7RFCnDi5RbnkFuVysHYD2iFEZaIQ1Zpt27z22mscqEOHDvTr14/q7N5776VPnz7sl3ZmM+6Y9ALtz+hEuRun1LWJug5RL84eJ8YeN0bUdYh6cUqdGEKcCLpPI1X5STcsLN0gRRmkGRapyk+K7iegDNINixTlJ0X3E1AGQSNAQDcIKINUZZJumAR0PwFlkKZMhPgxqxeX0PuKLgghhBCHoxDV2vTp09m5cycHuvbaa6nuevXqRVFREWvXrmWvYPdWLMpJsGjVTIT4OUxdETQsgkYAS1eYuiJoBAj6LSzNwNQVQcMi6A9g6QpTUwT9ASxN4dcVISNA0G9h6QbphokPH0KcSJvWbKP2aTUQQvx/2+w95FppCCH+L4Wo1mbOnMmBNE1j0KBBnEwvvfQS27ZtY/DgwRQUFLDXnDlzGDNmDHfffTd169blZNM0jcsuu4xRo0axVyIaQ1R9pq4wNYWpK4JGgJDfwtQNTE0R9FuEjACmrjA1RdAfIGRYmLqBqSuChkXICGDqClNXZPpTMDQdISqbz9+cyQXXn4MQ1d2qyDYmbShm6uYVNA7l8x/tLkAI8X8pRLU2e/ZsDtS0aVOysrI4mbZu3crGjRuJxWLsV1payqpVq4jFYpwqXbp0YdSoUeyViMYRFY+pK4KGRdAIYOkKU1cEjQCWrvDripARIGhYWLqBX1eEDIugP4ClKfy6ImQECPotLN0gVZnoPh9CVGeemyBaZpOWkYoQ1dGqyDYmbSjm4w3F/FC6nf2uanAGQogfpxDV2vr16zlQ27ZtEf+tXbt27Jew44hjY+oKU1OYuiJoBAj5LUzdwNQUQb+FpRmYuiJoWAT9ASxdYWqKoD9A0LCwdANTUwT9FiEjgKkrhBDH19xPF3F6r5YIUV0kkkmWhjfzxablTChZxLqynfyYjrl1EUL8OIWo1rZv386B8vLyqKg+++wzHMfhvPPO42TIy8tjv0Q0RnVj6oqgYWHpBn5NEfJbBI0Alq7w64qQESBoWFi6gV9XhAwLUzcwdUXQsAgZAUxdYeqKbDMV3achhKjYFny1jOF/vgwhqrJEMsm3O0v4ZMMSJm9cwpZoKYdSLy2bGoEgQogfpxDV2p49ezhQWloap8I777zDm2++iVKKvWzbJi0tjQPdcMMN7N69my1btnAymKaJ3+8nHo+TsONUdKauCBoWQSOApStMXRE0AgT9FpZmYOqKoGER9AewdIWpKYL+AJam8OuKkBEg6LewdIN0w8SHDyFE9bF7W4SM3HR8mg8hqhovmeS7nSV8smEJH28oZru9hyN1Rm49hBA/TSGqtVAoxO7du9kvHA5zKvTv35+hQ4dSVFTEXtOnT+eJJ57gQM8//zyu63KylJWVEY/H2SsRjXM8mbrC1BSmrggaAUJ+C1M3MDVF0G8RMgKYusLUFEF/gJBhYeoGpq4IGhYhI4CpK0xdkelPwdB0hBDiWHz+1izOurQTQlQVMc9lxrYfmLppBZ9uWsrOWDlHo2NuPYQQP00hqrWcnBzWrl3Lflu2bOFUCAQC5ObmUrNmTfbKyspCKcWBzjzzTE6mLVu2sJ9XWo6zZReF+TWpkZVDQPkJGhYB3SCg/KQqP+mGRUA3SFF+UpVJmjIJKIOAbpBuWKQoPynKT0A3EEKIimb7xl3kFWQjRGUW9Ry+3LySyRuXMG3zSsrcOMfCB3TMqYsQ4qcpRLVWVFTEvHnz2G/u3LmI/zZ37lz2K525hNKZS3hjzhxOP/10hBCiKln6zfc07VAfISqjUifG1M0rmLxxCV9vWYXtuRwvDYN5ZJkpCCF+mkJUa507d2bcuHHst2rVKjZu3EitWrU4WRo0aEBmZiapqansl5OTQ+fOnUlLS+NU+eqrrzhQSkoKrVu3RgghqpqZH33LkN9fiBCVRcSx+WLTciZtWMKMrd8TT3icCGfk1UcIcWgKUa2deeaZHOy1117jzjvv5GS56KKLOFirVq1o1aoVp4rjOLz11lscqGPHjhiGgRBCVCV2eQzl1zFMhRCVxTZ7D/9Y8hlboqWcSJ1y6iKEODSFqNY6depErVq12LhxI/uNGTOG22+/HU3TqK7ef/99tm7dyoEuuugihBCiqpk2bg7dLjwdISqTBuk5vNTtV1zz9UtsKN/NiaD7fHTIKUIIcWgKUa3pus7QoUN56KGH2G/ZsmW8+uqrDBkyhOrI8zweeOABDuT3+7niiisQQoiqZs3SDZx7ZVeEqGzqpGbyeo9rGTb9ZVZEtnK8NcuoSbphIYQ4NIWo9q699lpGjRqF67rs98c//pGLLrqItLQ0qpvnnnuO4uJiDnTZZZeRk5ODEEJUJetXbqawUQ2EqKxyrTSe7zqU62a8QvHuTRxPHXPqIYQ4PIWo9ho0aMCwYcN4+umn2W/dunXccsstjB07lupk1apV3HXXXRzI7/dz3333IYQQVc0Xb8/ikpv7IERllmWm8FK3q7lx1hvM2raa4+WM3HoIIQ5PIcR/ue+++3jllVfYs2cP+z3//PP06NGDoUOHUh3s2bOHQYMGETV85Fzek10TZ+NFyhk5ciSnnXYaQghRlbhxFyfmkpIeQIjKLkX5+VfnX3Dr7LeYtmUVx0ppGu2yCxFCHJ5CiP9So0YNRo0axciRIznQ8OHDycvLo2/fvlRljuMwaNAgvvvuO/Ku7kPWwM5kDexMcs733Hj3bxBCiKpm5sffcUa/NghRVVi6wRNnXM5dc8YxaeMSjkXrzAJSlB8hxOEphPgfI0aMYPLkybz33nvs5zgOgwYNYty4cZx77rlURbZtc8UVVzBp0iT0tAAZ57ZnL83yQ7emXDLzefoWNOf6Rt2on56DEEJUBcUzV3L9Q5cjRFWi+zQ0TeNYdcqthxDiyCiEOMDo0aNZunQpy5YtY7+ysjIGDBjAmDFjGDJkCFXJrl27uPDCC5k2bRp7ZfbvhGb5OZCT8Bi/biEfliyie35DbmzSgxaZtRBCiMpq+8Zd1CjKwefzIURVkSTJnxZ8xMT1i4Ek4ONodcypixDiyCiEOEBWVhZTpkyhS5curFu3jv0cx+Gqq65iypQpPPPMMwQCASq7efPmcfnll7Nq1Sr20iw/mX078lMSySRTN69g6uYVtMsu5OamPTkjtx5CCFHZfPr6dPoO7YEQVcnfFn/Gm6vn8d98HC1TV7TOKkAIcWQUQhykoKCAjz/+mN69e7Nx40YO9PLLL7N48WJefPFFWrZsSWXkui5/+9vfuPfee4nH4+yX0ed09GAKR2L+jhJ+9fVLtMsuZFijrpxVoyE+fAghREWXTCTZs7ucUE46QlQV/1o+jTErp/PTkoCPI9E2qxBLVwghjoxCiB/RrFkzvvnmG/r168fChQs50Lfffku7du244YYb+POf/0wwGKSy+Oqrr7jxxhtZtGgRB/IZiqzzO/Nzzd9Rwg0zX6dJKJ+rT+vMgMJW6D4fQghRUc3/opi2ZzVDiKri9R/m8NiSLzg0H0eqU249hBBHTiHET6hduzZffPEFl19+OVOmTOFAruvy2GOP8cYbb/Cb3/yGkSNHkpqaSkU1b948HnjgAT788EOSySQHyz27HSornaO1LLyFu+e9z7MrvmZYoy6cX9AKpWkIIURFM+/zYob9aRBCVAXjSxby4MKPORIB3cBLJognPA7ljNx6CCGOnEKIQ8jKymLSpEn853/+J/fccw+u63KgrVu38pvf/IZRo0YxcuRIhg0bRkFBARWB53lMmjSJp556io8//phkMsmPadmyJa///Xm2ZimeWvYli3dt5Gj9ULqd38/7gMeXTuXq0zpzWd12WLqBEEJUBJGdewjlpKPpGkJUdp9vWs7v531AIpnkcCzd4LkuV+ImEtw463XK3Dg/JkX5aZFRCyHEkVMIcRiapnH33Xdz9tlnM2LECL799lsOtnXrVh544AEefPBB+vfvzxVXXEG/fv1IT0/nZFu0aBHvvPMOL7zwAuvWrSM7Uyc1xceesiQH8vv9/PrXv+a+++4jEAjQHOhZoxHzdqzjiaVTmbVtNUdrU3mYhxZO4ull07iifgeuOu0MgoaFEEKcSp+9MZOel3ZCiMpu1rbV3D7nHbxkgsMxNJ1HO11G++w67DW261VcN+NVwvEoBzs9pwilaQghjpxCiCPUsWNH5syZw7/+9S/uuecedu/ezcE8z2P8+PGMHz8ey7Lo3bs3vXv3pkePHrRo0QJN0zjedu3axddff82XX37J+PHjWblyJXul1K/J0F/V4OE7Uhj7WoTf/2U7+51zzjk88cQTNGnShIO1z67D812vYt6OdYxeMZ0vN68gydHZFS/nyWVf8sKqmVxc1JZhjbqQZ6UjhBCnwvaNO8krzEaIymzhrg3cOOsNYp7L4eg+Hw+ffhHd809jv1aZtXm529VcO/1lttl7OFCnnLoIIX4ehRA/g67r3HTTTfzyl7/kn//8J48++ijhcJgfY9s2EyZMYMKECeyVmZlJ+/btadGiBc2bN6dp06bUqlWLmjVrYlkWh7N9+3Y2b97M6tWrKS4uZvHixSxcuJDi4mISiQT7+XSddjeeRaTTWQTz15Kb/SW/HpHB82+Eya/Vifvuu49evXpxOO2z69C+cx2Whbfw/KoZfFSyCC+Z5GiUuXFe/n42b66ey3kFzbmxSQ/qpGYhhBAny5LZq2ja8TSEqMxWRLZy3YxXKXfjHI4PuL/NAPrWbs7BGgbzeLHb1Vzz9ewH2UMAACAASURBVEtsjkbY74zcegghfh6FEEchMzOTBx54gNtuu42nn36aZ599ljX/jz34AI+qThy2/ZyZMzPJJJNeIYUkJCS0UAVCRxGw0BVYQQSxra6sBcS2YmPV1d2/rg0FFQFBAVEEERGlQxJCJ0BCSyMF0stMpp3vgvdiP9aVZCYkYQK/+z5zhrqUlpbyyy+/8Msvv/B7/v7+eHt7I8syBoOBC6xWK5WVlVgsFoqKiqitraU+sYNiCHhgNAX4ccHawihGBJ1hWGAW29ePIihuBc6K9w7mze5jeCx+EItPJvP16T2Y7TYawmy3sSb7ID/mHua2sI48GNefGEMAgiAITW3nur1MfX4sgtBSZVeXMGPHYsrNRhwxq+OtjG/TjSuJ8vTnqwHTmb5jMWeqijFo3GjnHYIgCM6REYSr4Ovry7PPPsszzzzDhg0bWLhwIevXr6empgZnFBcXU1xcjKM8/L3w8NRQlFXMBX6Bbtw8dwT7fLtRoKi43IvH+tDDu5AArwMotduQdP1piHAPX57rPJxpbfvw+YldrDizF5PNQkNY7XbWZB9kbc4hBgTH8kj8ADr7tkYQBKEpGKtrcdPr0OhkBKElKjBWMH37Ys6ZqnDE4wmDmRbbh/qE6r1ZMmAaM3YsIczDB7UkIQiCc2QEoRGoVCpGjBjBiBEjqKmp4aeffmL16tVs2rSJ/Px8HOHuJhEaLNMqWMbHR0VokEyrEBlfHzUBoZ60aq0nNFiFj6dCoGctv6b7cPvwEkY/nEDugFHsMXuCwv8osbjxamYv/q/DFpTKeUi6HwCZhgrVe/Nc5+E8Ej+ApSdTWHwymQqLiYawKwqbCzLYXJBBN/9wZsT1Y3BIHIIgCI1p88rdDBjdE0FoiUpqa5ixYzF5NWU4YnLMTTwSPwBH+es8WNR/Kull+QiC4DwZQWhker2esWPHMnbsWC7IzMxk69atJCcnc/jwYY4cOUJFRQWXe//vQTxynzd1q+VyoUESGbs7YPXRMTLFjbqsLYxieGAWw4NOotQsQ9JP4Wr5avU8ljCIabFJrMrax8KMHRSZKmmovcU5/HnXMtr7hPJAXD+GtU5AQkIQBOFq5WQUMGLqQAShpam01PLgziWcrDyPI0ZHJPJc5+E4y0vjRu/AKARBcJ6MIDSx2NhYYmNjuf/++7kkKyuLnJwc8vLyyM/PJ67NZiAdZwToTdj1GiL0FcyM3s+bJ3pQlxeP96GnTwH+Ve8hud0JKh8ag4es5d6YXkyM6sH63MN8eGwr2dUlNFR6WT5PpKwgziuI6bFJ3BHeCbWkQhAEoSHOpOcR1SEMQWhpTDYLj+z6iiNl+TjillbxvNZtJBISgiA0HxlBuAYiIyOJjIzkEqUmFKXiRZzh72ZkU3YUIW2quD/8CJvORbCnPIgrKbXoeDmjF+913IJS9S6S10s0Jq1KzaiIRG4P68S63EN8mrGdk5XnaaiMiiLmpH3H+0c3M6Vtbya06Y5OLdMUys1GvLXuCIJw/dmyKpm7n7wdQWhJLHYbM5O/Ia04G0ckBUXzTs/xqCUVgiA0LxlBcAXqAJylVikcLw3g1janUEkK8xK2MzJlJCa7zJX8WBTFiKIsRgQtR9JPBLkdjU1WqRgVkcid4Z3ZUpjJx8e2crA0j4bKrSnj7wd/4pPj25gY1YOpbftg0OhoLCabhQlbFvBZ33tppfdGEITrh9VsBUnC3UOHILQUNkXhmT2r2Vp4Akd08Qvj/d4T0arUCILQ/GQEwQVIqkAUnJdX1YpLovUV/DV6H2+c6EldXjrem54+hQRWvI7k9yVNRSVJDA6JY3BIHGnF2SzI2MHmggwaqri2mg+ObWHRid1MjO7BjNi+eGvduVpfn04jq6qE2Xu+ZVH/+1BLEoIgXB+2r0mjz+1dEYSWQkFh7v61rM87giPivYOZn3QP7moNgiBcGzKC4ApUATREmcmGWfFEK1VxwfTwdH45F8me8iCupMTixqz0fnzW5RdUpp+R3G6lqXX3j6B7nwjSy/L5NGM7G/LSUWiYKmstCzJ28NWpVMZFduX+2L4EuxtoCKvdzqKTu7kgrTibTzK28Ui7AQiCcH04nnaKQeN7IQgtxT8Ob2Tlmb04ItLTjwV9p+ClcUMQhGtHRhBcgSoQkAAFZ/joqjlafR+Jnu9zgUpSmJewnZEpIzHZZa5kW0lrFuUkcJ/6DSTdQJB0NIf2PqH866a7yKgoYmHmDtblHMam2GmIGquZxSeTWX56DyPCOvBIuwG08fTHGd9l7ye/ppxLPji6hT6B0XTxC+NasVgsVFVVYTQaMZlMmEwmVCoVWq0Wd3d33NzcMBgMyLKMIAhXVpB1nlbRwQhCS/Hvo5v5PHMXjghx9+Kzvvfir/NAEIRrS0YQXIGkAZU32MtwRqC+hv3FvUn0Xg22PC6I1lfwRPQ+/n6iJ3V560R3evmso737Z0iej9Cc4ryCeLP7GP6SMJgvT+zmmzNp1NqsNITFbmNN9kHW5hxiQHAsjyUMooNPKPWxKQoLM3dyOZtiZ1bqKr4d8jAGjY6mUlpaypEjRzhy5AiHDx/mzJkz5OXlkZ+fT2FhIYqiUBeVSkVwcDCtWrWiVatWREdH06FDBzp16kT79u3x8vJCEG50v63YzR33D0YQWoIlJ1P48NgWHOGv8+CzfvfSSu+NIAjXnowguApVANjLcEagew37z55DSpyFUvZXLrkv/CgbzkWytzyIKzErap5MH8Bqz0/Ru48CdSuaW5jeh+c6D+ehdv1ZdiqVL0/uptJSS0PYFYXNBRlsKchgYEgcD7XrTxe/MK5kQ94RzlQV83u5NWX8bd8a/nXTXTSWnJwcNm/ezJYtW9i6dSuZmZlcDbvdTn5+Pvn5+aSlpXE5SZJISEhg4MCBDBgwgEGDBhESEoIg3EjsNjumKhMGXw8EwdV9l32AeQfX4wiDxo0FfScT5emPIAiuQUYQXISkCkThBM4I8ahi39F8JLcZKNqvwJzCBWrJztvttzEydSRVVg1Xklntw98zOvKK/v+QvN/iWvHXefBYwiAmx/RiyclklpxKodxspCEUYHNBBpsLMujmH86MuH4MColFQuJyCzN3ciU/5aUzOPsgIyM601CnTp3ihx9+YMWKFezcuRNFUWgOiqKQnp5Oeno6H330ERe0b9+eu+66i4kTJxIfH48gXO9SNx6i280dEQRX98vZY7ywdw0K9XNTa/i4z5+I9w5BEATXISMIrkIdjLNCPKrIr6ikoLKKEMPz2IvHAjYuiHCv5G+xycw+2o+6LM2Lp7/fr9zaLg203bmWfLTuPJYwiOmxSazM2sdnmTsoNFbSUHuLc/jzrmXEe4dwX9ve3BHeGbUksbUgk/SyfOryyoF1dPEPJ8LDF0eVl5ezZMkSPv74Yw4fPoyrSE9P5+WXX+bll1+mZ8+ePPTQQ0ycOBEPDw8E4Xp0YNsxHnjtbgTBle0sOsVTqSuxKXbqo1Gp+XevCXTzD0cQBNciIwiuQh2Ks0I9q7hgf14+w+MTkPTjUWq+5pKxoSfYVtqKHwqiqcuzx/rSyf8tQlstA1Rca3pZy70xvZgU1YMfcw/z8fFtnKkqpqGOlRcwJ+07Pjy2lfvjkvg++yD1qbaaeSp1JV8NmI5GpaYuJ0+e5K233mLp0qVUV1fjylJTU0lNTeWpp55i6tSpzJo1i7CwMAThelFaVIFfkDeSJCEIrmp/SS6P7V6O2W6jPmpJ4u2e4+gXHIMgCK5HRhBchSoUZwW4G9GqbOzLy2d4fCyS5xMopvVgr+CSV+J2s788iByjJ1dSatHx5P5glvh8h1o/FlehUakZFZHIneGd2VKYyQdHN3OkLJ+Gyq4u4aV9a3HU4dKzvH90M090uJk/cuLECV577TWWLl2K1WqlJSkvL+e9995j/vz5zJgxgzlz5hAWFoYgtHS/fr2LwXf3RhBc1bHyQh7auRSjzUJ9JOCVriO5tVUCgiC4JhlBcBXqUJwloRDkUcP+3LNcpPJD8ngUpfLvXGKQzfxfh81M2HsbVruKK0kuC2HBkdU81ONWkDxxJSpJYnBIHINCYvk1P4NPjm/jYGkezWFB5g6SgmLoFdiGSyorK5k7dy7vvfceVquVlqy2tpYPPviAhQsX8swzzzBnzhzc3NwQhJZIURRKz5XjH+qDILiirKoSZuxYTIXFhCPmdBrG2MguCILgumQEwUVI6lAUnNfKo5L9BUWYbTa0ajWSx70oxpVgzeSSRK/zPNrmIO+e6kJd/nmiHT2DP6JbxCxckYTEzaHtuDm0HWnF2SzI2MHmggycowASjrIrCs+kfct3Qx7BR+vOypUr+etf/0peXh7XE5PJxMsvv8ySJUv497//zYgRIxCuMbsdvvoK3noLMjLA3x/Gj4e5c8HXF4qKYNQomD0bxozhoooKWLQINm6ENWu40RzYepTEfvEIgisqMFYwfceXFNdW44gnO9zMvW17IwiCa5MRBFehCqEhQjyqMBfYSC8ookvrUECN5PU8Ssl9XO7RyAPsLg0huTSEK7EoKv6cWsEa36MEGRJwZd39I+jeJ4Jj5QV8fmIX63IOYVMU6ifhrEJjJU8nr6D2040sWbyE69nJkye57bbbmDJlCh9//DF6vR7hGlAU+OADeO01+OADuOUWOHMGnn8exoyB9esR/teeXw4zfe54BMHVFNdWM337l5ytKccRD8b144G4fgiC4PpkBMFVqLxA8gSlCmeEeFZzwb68fLq0DuUCSZsEukEotZu5RCUpvNN+G3ckj6LMquVKimrdeWLncr689SXUkgpXF+8dwpvdx/Bo/EAWZuzk2+x9WO12GtuO86cpKDrGjWLx4sUcOHCAr7/+mvj4eIRmVlMDc+fCu+/C+PFclJgICxbAwIGwfDncfjvC/6+ipAovf09UahWC4EoqLSZm7FjC6apiHDEpqgdPdLgZQRBaBhlBcCXqELCewBmhHpVcsD8vn8tJXs+jnN8JiplLQnTVvJ6wg0cPDaYuu4p1vLN3KbO7T6GliPDw4+Wud/BQu/58cWIXK86kYbJZaUzB04djPJZDbVYhN4KDBw9y0003sXLlSm699VaEZpSWBhUVMHo0/yFJ4OUFgwfDtm1w++1gt0N1NZSWclFlJdTUcCP6ZdlOBo3vhSC4EpPNwsO7vuJYeQGOuDO8Ey8k3oYgCC2HjCC4EEndCsV6Ame08qjigrScs/wXdSSSfgpK9UIuNywwi3GhmazKj6Uu849nkxiUzrDw9rQkrfTePNd5OA+3G8BXp1L48mQylRYTjUHSyLR6chxnZn2KYrbQFPR6PaGhofj4+CBJEj4+PiiKQllZGRcUFxdTUFCAyWSiOVRWVjJy5Ei+/PJL7r77boRmUlYG7u6g1/NfJAl8fSEzk4sqK2HOHHj9dS6y26GmBrp25UZTWlROUJg/guAqLHYbf0n+mr3FOThicEgc87qNRiVJCILQcsgIgitRh+CsEI8qLiiqqqKgsooQgyeXSJ5/RjF+D/bzXO7ldskcq/TjSJU/V6Ig8dSuNcR4B9HWK4CWxk+n57GEQUyLTeLhXV+x53wWjUEXHkTQlFsoXLieqxEYGEjfvn3p3LkzHTt2JCEhgfDwcLy9vXFESUkJubm5pKenc+jQIQ4ePMiOHTsoLS2lsdXW1jJp0iQsFgv33HMPQjMICQGTCYqKICSEixQFbDbIy4OQEC4yGGDWLBg+nIuqquCbbyA5Gex2MBqhogIkCfR68PLienRoRwYdesUiCK7Cpig8nbqK7YUncUSvwDb866a7kFUqBEFoWWQEwZWoQnFWuKGCS/blnmVEQhz/IRmQDE+glD/P5dxUVt7ruIUxe+6gwqrlSmqsdh7e+g3fDbsfT42Olshit3Gk9CyNyfe2m6g+eIqq1OM4SpZlBg4cyOjRoxk8eDDt27dHkiQays/PDz8/Pzp37szEiRO5wG63c+jQITZt2sR3333Hzp07sdlsNAa73c60adMICAhg2LBhCE2sc2do0wYWL4aHHwa9HiwWyMyElBSYN4+LVCrw8YHQUC6qqAAvLy4yGmHTJliyBLRa6NoV/vIX0Gq53iT/tJ/7/jYOQXAFCgp/27eGn88exRGdfVvzQe9J6NQygiC0PDKC4ErUrXGWXmPB391IsdGdtNyzjEiI43KS+ziUmuVgOcTlIvUVvN1+Gw8dHIKCxJWcqijjuZT1vNd3NC3RFyd2YbRZaFSSROijIzn9xMdYSyupS9euXXn44YcZP348fn5+NCWVSkViYiKJiYk8+eSTFBUVsWzZMubPn8/Ro0e5WhaLhXHjxrF161a6deuG0ITc3GDuXJg3Dzw8oGtXKCyEhQuhZ0+44w4oL6dOWi307QsjRsDp0/DRR5CbC9HRXE+qymvw9NEja9QIgit449DPfJu1H0fEegUxP+kePGQtgiC0TDKC4EIkdTgKzgs3VFBsdCctJ4//pULl9QL24omAwuWGBOTwcJtDfHSmM3VZm5VO14DWTGvXk5akylrLV6dSaQpqLw9C/zKanFeXgKJwOUmSGDlyJM8++yy9evXiWgkKCmLmzJk8/vjjbN68mXnz5vHLL79wNaqrq5k4cSJ79+7F09MToQlNnAheXvDll/Dll+DlBbfcAg89BDodyDLExYGPD/+hUkFgIMTEgEYD/v5gs4HJBGo16HRcbzYt38nAsTchCK7gn0c28eWJ3TgiwsOXhX2n4KN1RxCElktGEFyJHEFDhBvK2V8UzLHCc1TW1mLQ6fgvmq5IbrejmNbye09E7eNwhT/bSlpTl3l7N9HBN5ibgiJoKZadSqXSYqKpeHSJwe/OPpSs2cklt9xyC2+99RZdu3bFVUiSxODBgxk8eDA7duxg1qxZ7Nq1i4bKzMzkscce44svvkBoQioV3HEH3HEHf8jPDxYt4r94esLEiTBxIhcpCpw/Dykp0Lo1tG7N9eb82VJCo4IQhGvtyxO7+TRjO44IdjewsN+9BLp5IghCyyYjCK5EFQCSOyhGnBFuqOACm6KwP6+A/tGR/J5kmI1SuwkUI5dTSQrvdNjG6NQ7OGvy5Epsip3Hd3zHd8OmEaI34OpMNiuLTuymqQVOvpmaw6fxqVH417/+xcSJE3Flffv2Zfv27Xz22WfMnj2b0tJSGmLRokWMGzeOO++8E8FFKQpUVsK2bZCTA089xfUmPfkE7bpHIwjX2rLTe/j7oQ04wlerZ2HfKYTpfRAEoeWTEQSXIoE6HKwZOCPCq4JL0nLy6B8dyf9QhyB5PIBS9R6/56cx8e+Om5mUNgKzouZKioxVPLDlG74eei96WYMrW5W1l+LaapqaJKtp+/wU1gx7jKjW4bQEKpWKGTNmMGzYMCZPnszWrVtpiFmzZjFixAhkWUZwQRYL7N0LS5fC1KmQkwORkeDpyfVi94/7ufeFMQjCtbQ25xCvHfgRR3jKOj7tO5kYQyCCIFwfZATBxUjqcBRrBs4IM1RwSVpuHlciecxAMa4CWx6/l+h1nhfbpfDisT7U5UhpIU/tWsMH/caikiRckdVu57PMnTQXq6+epecP80LrcFqS8PBwNm3axOOPP85HH32Es44fP85nn33Ggw8+iOCCamuhsBD8/CA1FbKyYMwY8PTkelBdYcTNQ4esUSMI18pvBRk8u/c77IpCfdzUMh/1mUQHn1AEQbh+yAiCq5EjoBanRBjKueRAXgEWmw2NWs3/kNyQDM+ilD3GH5nU6jgHKgJYeTaWumzIOc67h7bxROcBuKIfcg9ytqYcZygWK7YqI7YqE/ZqI7YqE7ZqI/YqE7YqI4rZit1ixV5lxFZtwl5tYs7jT/LQ1Gn4aPVoVWpaIlmW+fDDDwkODmbu3Lk4a968ecyYMQOVSoXgYgwGmDABJkzgevTbit0MHHcTgnCtJJ87wxMpK7Da7dRHVqn4v5vupkdAJIIgXF9kBMHVqCNwVqDeiLtswWjVYLJaOVxQRNfWofwRye1W0A1Aqd3KH3k5bjfHKn05XBlAXd4/vJ1oLz9GtemIq8muKmFcZFc8NToMGjcMsg4PjQ6Dxg2DrMNL645Bo8NTduOHld9y3+QpOOvNN99k9kOPc7146aWXqKqq4u2338YZWVlZbNq0iaFDhyIIzangzDlaxwQjCNfCwdI8Ht29jFqblfqoJYm3uo9lYEgsgiBcf2QEwdWow3GWhEKYoZLMUj8u2JOTR9fWoVyJ5PUCyvk7QDHzezqVjX933MzYPXdSatFxJQowJ/lHwj196BYQhiuZ2X4Ijvrys89x1r333svs2bO53rz11lukp6fz448/4oyFCxcydOhQ/ojVYmPL6lTc9Fr63tENQWgMGXtP07ZLJIJwLWRWFPHQzqVUW83URwJe6nIHI8I6IAjC9UlGEFyMpI5AwXlhhgoyS/24IC0njwd69+CK1G2Q9PeiVC/gj4S7V/FR503cu3cYZkXNldTarDywZQUrht5LtJc/Lc358+fZvHkzzoiKiuL999/neiRJEp9//jkdO3bk3LlzOOr777+ntrYWnU7HJefySlj2zjoObs+gMOc8N0/oQ987uiEIjWHHmjQmPzsaQWhu2dWl3L9jMWVmI454uuNQ7mrTDUEQrl8yguBq1K0BNWDDGZGGci5JyzmLXVFQSRJXInk+imL6AWyF/JEe3kW8Fr+L2Uf7UZfSWiPTNn/NqlunEuDmQUuyY8cO7HY7znjzzTcxGAxcr4KCgpg7dy6PPvoojjKZTKSlpdGndx/2/HqY7z/5ldzMAgqyznNJdVkNLYFiV6iuMFJTZcJUU4upupbqCiPGShOmmlpMNbXEdY2ibWIEwrVhrK5Fo9Og0ckIQnMqNFZy//YvOWeqwhGPxg9kemwSgiBc32QEwdVIGlAHg+0szojyKeOScpOJE+eLiQsM4IokDyTPWSjlT3MlY0NPkFHtw4LsjtQlp6qM6Zu/Zvktk9HLWlqK3bt344yEhATGjx/PVTt2DE6dgm7dICSEi4qLYd8+8PWF7t25osJC2LcPTp0Cmw1CQ6FHDwgPB7WaxvDAAw/w6quvUlBQgCO0KncWvfY9n59fz7n8UkzVtfyeqaaWpmC32ampNFFTacRUU4uxupaaShM1FUZMNbWYasxUVxipqTRiqqnFarFhtymo1BKX2K12VLKKC1QqFW56LZ4+Hrjptbh7uOHmocXTxwPfYC/c9DqCwv0Rrp3NK3czYExPBKE5lZpruH/HYnJrynDEPdE38VjCIARBuP7JCIILktSRKLazOCPau4zLpeWcJS4wgLpI7neiGJeDeQ9XMjsmjdNGLzadi6Auh0sKeGz7aj4deBdqSUVLsGfPHpwxdepUJEniqh04AOvWQWAghIRwUVERrF4NsbHQvTt/KDsbli+HzEzw9wdZhgMHYM8emDwZ2rcHlYqrpdFomDx5Mm+//TZ18VEHEeWeiEHtT9buEupitdi4xGyyUFlWjdlkwWyyUFVWQ2VZNZZaC7VGC1VlNVSVV2M2Wag1WbCYLFygcdNwgcVk4QKNmwZLrRWNTsbgo8fT2wOtuwatToOnj56QyEC0bhq0bho8ffQYfD3Q6jQILVtORgEjpg5EEJpLlbWWB3cu5WTlORwxMqIzz3UejiAINwYZQXBFcjSYd+GMaO9SLpeWm8ekbp2pm4TKay7286MAG39EJSn8M2EbE4y3cazKl7psPnuSF1N/4vWbbkPC9RUUFOCMoUOHcs3YbPDjj7B3L4wZA7fcAlotHDoE774L69ZBUBAEBdEYbr75Zt5++21+TyPpiNB1IFgbiV7lhVrS4Iiqshren7UUtazG3UOH3uCO3uCGm16Hm4cODy93fIO8cNPrcNPr8PByx93TDbWsQhAuOX0kh5hO4QhCczHZrDyyaxmHS8/iiJtD45nXbRQqSUIQhBuDjCC4IjkGZ/m7G/HRmSirdeOClKxcHCLHIeknodQs4Uo8ZAsLEzdyV9ptnDV5UpflJ/bjo3VndpfBuLqSkhIcJUkSHTt25Jo5fx6Sk6FtW7jlFvD356JeveCmm+DwYcjOhqAgGkNiYiJ/RKtyR1ZpUBQFi2JGJamRUFEfWSvz2D/uQRCuxuaVKfxp9p0IQnOw2u38NeUb9pzPwhF9gqL5503jUUsqBEG4ccgIgiuSo2mIaO8y9haFcEFBZRVnKypp5WWgPpLnTBTTj2Av4UqCdTUsTPyFiWkjKLfqqMvH6bvw1rrzUPveuLKSkhIcZTAY0Gq1NJpDh+CFF8Dfn4sqKuDsWYiN5Q+VlEBlJQQHg68v/6FWQ0QEpKZCRQWNJSAggD9SbSvjeE0yF2gkHYHacILlKLx1/vgaAqmpMPJHbFYbgnA1zEYzskaNzl2LIDQ1m6LwTNpqthRk4ohEvzDe7zUBrUqNIAg3FhlBcEGSOgYF50X7lrK3KIRL9mTnMbJjPPVSeSN5PolS8QJ1ifUo48POvzFt31DMipq6vLX/V7y0Oia17Yqr0ul0mEwmHGEymWhUoaFwyy0QG8tFubmwYQNXpNGAJIHZDDYbqFT8R20tqFQgyzQWo9FIfSxKLWdrT3C29gRtQ9oy/5uNbFi6nYy9ZyguKKO0qAJFUbjAarYhOMdSa2Hn8p3EJcURGhuKoijUVtWS8n0K8X3jCYoK4kayeVUKfUd2RxCamoLCy/vX8mPuYRzRzjuYT5LuQS9rEQThxiMjCK5IHQySAZRKnNHWu4TLpeXmMbJjPI6Q9ONRjCvAcoC69PIp4K3223kyfQB2ReJKFODF1J8waHTcEdkeVxQQEEB5eTmOMJvNFBUVERQURKPw94c+faBHDy46dgwOHuSi/HxYuRKSkyEkBO66Czp1gtatITMTsrMhJoaLzGbYvx8MBggMpLHk5ubiDF8/X+K6tSGuWxsuKMwuZvO3Kez55TDFBeVUV9QgOEeSJKwWK9uWbmP07NGotWoO/3aY7EPZdB7amRvNmaN53Dq5H4LQSr8T4QAAIABJREFU1N45/AsrzuzFEZGefixImoyXxg1BEG5MMoLgquQosBzEGTE+ZVwuLScPx6lQeb2EvXg8YKcudwSfJs/kyT9OdqcudkXhqV0/YNC6MTA0Glfj7+/PyZMncdTu3bsZOXIkjUKSQJZBo+EiWQaViov0ehg9GsaPh7Vr4dAhaNsWbr8d3n0X5s+H6dPBYIDlyyElBf78Z4iOprHs3r0bZwQEBHC54Ah/Jvx1BBP+OoJao5nDuzIRnKPWqOl+Z3d+ePsH9v+0n/BO4Rz8+SD9J/fHJ9iHG0n28XzaJLRGEJrah8e2sDBzJ44Icffis773EuDmiSAINy4ZQXBRkhyDYjmIM6J9Srlc5rliyowmfNzdcIimI5L7OBTjCurzUOQhyiw6Ps3uSF0sdhsPbVnBRwPGMbhVW1xJdHQ0KSkpOGrlypWMHDmSJuflBV5eXOThAVVVoCgwZAh4eMAnn8Dw4VBbC4mJMGsWDBkCWi2NZeXKlTgjJiaGK9G5a+k+pAOCcyRJwjvQm97je7NpwSZO7ztNRKcIorpGcaP57Ztd3P3k7QhCU/rqVCr/ProZR/jp9CzsO4VWem8EQbixyQiCq5JjcFaoRxXushWjVeYCBdibe5YhsdE4SjLMQqn9Beyl1Gd22zTKrTq+ORtLXcx2G49sXcXHA8YzqFUMriIpKYnly5fjqFWrVvH2228TFBTEVZkwASZM4L8kJMAHH/AfigI5OXD6NLRrBwEBXJSUBElJNKUTJ07w888/44ykpCSEJiBBRMcIVCoVOUdyuPmBm5F1MjcSs8nCBe4eOgShqazJPsjrB9fjCINGx4KkKUQbAhAEQZARBFclx+AslaQQ5VVGekkAl6Tl5DEkNhqHqXyQPGeiVMylPhIKr7bbRZVV5seiKOpittv487ZVLBh4N0khbXAFSUlJOKOmpoa5c+fy4Ycf0qQUBUpLYdUqCA2F226jOT333HPYbDackZSUhNAEFMhNz8VmseEf7s+ZA2cIiAjgRrL9+z30G9UDQWgqm/KP8dze77ErCvVxU2v4qM+fSPAJQRAE4QIZQXBRkhyDgvOifUtJLwngkj05eThL0k9EMa4GywHqo5bsvNNhG1VWDVtLwqiLyWblga0rWDDwLvoEt+FaS0xMxN/fn+LiYhz1ySefMGHCBAYOHEiTMRph2TIoK4MhQ6C2FrRakGWa2urVq1mxYgXOiImJITIyEqFxKYpCTWUN25Zso8fIHngHe7N50WYiO0cSGBnIjeLEgSyGTOiDIDSF3edO82TKSmyKnfpoVGre63U33f0jEARBuERGEFyVOhwkLShmnBHjU8rlDuUXYrRYcdfIOE6Fyusl7MXjATv10Uh23u+0man7h7GvPJC6GK0WHtiygk8H3k2f4EiuJVmWmTx5Mu+++y6OstlsTJ48mZSUFEJDQ2kSublQUAAnTsD8+dCnD4wYAQEBNKUTJ04wY8YMnHXfffchND5FUdi9Yjeefp50uqUTkkoiqksU2xZvY9ScUahlNde77OP5RCa0RhCawoGSXB7dvRyz3UZ91JLEWz3G0j+4LYIgCJeTEQSXpQZ1JFgzcUY732IuZ7XbOXi2gF6RYThF0xFJfxdKzdc4Qq+28lniRqbuv5WDFQHUpcZqYdpvy3m372iGhbfjWpo2bRrvvvsuzsjNzWX48OFs2bIFHx8fGl1cHLz6Ks2poKCAYcOGUVJSgjPUajX33XcfQuPLOpDFsR3HGP/CeNw83VAUhe53dmftO2s59MshugzvwvXutxW7mfDkbQhCYzteXsiDO5dSYzVTHwl4ueudDG/dHkEQhN+TEQQXJskxKNZMnNHO7zy/l5abR6/IMJwleT6NYtoI9hIcYZDNfNHlZ6buG8ahSn/qYrbbeGz7at7sfTtjozpxrSQmJtK3b1927NiBMw4ePMiQIUNYt24doaGhtGQnT55kxIgRnDp1CmeNHDmSsLAwhMYX0jaE8S+MJ7BNIBdIkoRPiA+3P3E7Wr2W653ZaEaSwE2vQxAaU1ZVCTN2LqHCYsIRz3QaxrjIrgiCIPwRGUFwZXIc8BPOaO1Zhbe2lnKzjkv2ZOdBX5yn8kYyPIVS/jyO8pLNLOq6gXv33crhygDqYlPsPLN7LWabjYltu3CtvPHGG/Tv3x9n7du3j6SkJFauXEn37t1pibZu3crdd99NYWEhzlKr1bz22msITcPd4I67wZ3LqdQq/MP9uRFsXpVC35HdEYTGVGCsYPqOLzlvqsIRM9sPYWrb3giCIFyJjCC4Mk08DdHO/zwp+a25ZG/eWax2O7JKhbMk93EoNSvBsg9HeclmFnXdyNR9t3K40p+62BSF51N+pMpSy4yEXlwL/fr1Y/To0Xz33Xc468yZMyQlJfHGG28wc+ZMVCoVLYHVauX111/n1VdfxWaz0RDTp0+nffv2CEJTOJOey62T+yEIjaWktob7dyzmbE05jrg3phcPt+uPIAhCXWQEwYVJcgIKzov3KyYlvzWX1JgtHM4vpEvrUJynQuX1EvbicYANR3nLtXzWZSOT9w0jo8qXuijAvH2bKDMbeSpxEBLN7x//+AcbN26kuroaZ5nNZp588kmWL1/Ohx9+SPfu3XFlW7du5bHHHuPQoUM0VEBAAK+88gqC0BROH8khulMEgtBYKi21PLBzCacqz+OIMRFdmNN5GIIgCPWREQRXpm4FKm+wl+OMeL9ifi8lO5curUNpEE17JP1ElJqlOMNPY2JJ1w1MPzCcwxU+1OfDIzs5W13Bm71vR6NS05zatm3Le++9x/33309DpaSk0KtXLyZOnMgLL7xAfHw8rmTfvn288sorfP/99yiKQkNJksTChQsJCQlBEJrC5hXJ/OmZkQhCYzDZLDyy6yvSy/JxxNBWCbzabSQSEoIgCPWREQSXJoHcDswpOCPe/zy/l5Kdy4N9etJQkuEpFNPPYD+HM/w0JhZ3+ZEZhyeQVqKmPt+dOUyhsZKP+o/DS+tGc5o+fTo///wzX3/9NQ1ls9lYunQpy5cvZ8yYMTz88MMMGTIESZK4Fmw2G+vXr+ejjz5i/fr1KIrC1Xr00UcZOXIkgtAUjNW1aHQadO5aBOFqWew2Hk/+hrTibBzRNyiGt3uOQy1JCIIgOEJGEFycJMejmFNwRqxPCRqVHYtdxSV7cvKw2u3IKhUNInkiGZ5GKX8GZxlkM190Ws6jxx5na2Ex9dlVmMVdGxfz+aAJtPLwojktWLCAU6dOkZqaytWw2WysXLmSlStXEhsby8SJExk7dixdunShqSmKQmpqKqtWrWL58uVkZ2fTWIYOHco777yDIDSV31bsZsCYngjC1bIpCrP3fMu2whM4oqtfOP/uPQGtSo0gCIKjZATB1WnicZZGZSfap5TjJf5cUmO2cKSgiMRWITSU5D4axbgKzCk4y11t4ePOa3ni2FQ25GRQn8zyc4zfuIgFA++mvW8wzcXT05N169bRv39/jh8/TmPIzMzk1Vdf5dVXXyUqKopBgwYxcOBA+vbtS0xMDJIkcTVsNhuZmZls376drVu38ttvv5Gbm0tj69GjB6tWrUKr1SIITSU3s4Db7huIIFwNBYWX9v3AT3npOCLeO4T5SX/CXa1BEATBGTKC4OIkOQEF58X7nud4iT+XS8nOJbFVCA0nofL6G/bzowErztLajvPvriU8p+nMylMHqU9BTSXjfl7E33vdxug2HWkugYGBbNiwgZtvvpmTJ0/SmE6fPs3p06f5/PPPucDDw4P27dvTvn17IiIiCAkJISwsDL1ej16vR6fTcYHJZMJoNFJVVUVubi4FBQVkZWVx9OhR0tPTMRqNNKXOnTvz448/YjAYEISmkrH3NHFd2yAIV+utQxtZlbUPR7Tx9GdB38kYNG4IgiA4S0YQXJ0cC8iAFWfE+xfz/Un+S0pWLg/07sFVkeOQPCajVH9BQ6iqP+DNnuto7eHNu4e2UZ9am5Wndq4ho+wcTycOQiVJNIfIyEiSk5MZOXIkO3fupKlUV1eTmppKamoqrmrw4MGsXr0ab29vBKEpbft+D/c+NwZBuBrvpv/KFyd24YhQvTef9Z2Cv84DQRCEhpARBFcnaUGOBmsGzkjwO8/v7cnJw2a3o1apuBqS5+Moxh/BXoTTFCNUvMrMTvMJ0Rt4IeUnbIqduijAx+m7OFZWxP8ljcJL60Zz8Pf3Z8OGDUyaNIm1a9dyI5o8eTILFy5Eq9UiCE2pusKIzl2LRicjCA21+GQyHx/fhiOC3Aws6jeVUL03giAIDSUjCC2ApElAsWbgjHj/Yn6v2mzmSEERnVuFcFUkTySv51DK/kpDKLW/gWkjE2KG4qfT89ed32O0WqjP5rMnGb3hC+YPGE+sdwDNwdPTkzVr1vDee+8xe/ZszGYzNwI3NzfeeOMNZs6cidB0zhzN43jaaYZN7seN7rdvdjH4rt4IQkOtzt7P3w/+hCN8tO4s7DuFcA9fBEEQroaMILQEcjzwPc7w0ZkI0VdRUOPJ5ZKzc+ncKoSrJbndBrrvUGo30xBK5WtIur4MDYtj6c338MCWFRSbqqnPmcoSxv28iHk3jeCOyPY0B0mSmDlzJklJSdxzzz1kZmZyPevcuTNfffUVHTp0QGhaaz75lelzxyFAQfZ5WscEIwgNsfHsUV7cuwaF+nnKOj5Jmkxbr0AEQRCulowgtASaeBqiY+A5CrI8uVxKVi4P9O5BY5C8XkI5nwyKEafZ8lGq3kMyzKGLfytW3Xov0377mtOVJdSnylLL4zu+Y2fhGV7sNhR3WUNz6NmzJ0eOHOHDDz/k+eefp7q6muuJh4cHTz/9NM899xxarRahaWVn5BPY2g9Pbz03uvTkE8T3iEEQGmJH0UmeTl2FTVGoj5ta5oM+E+nk2wpBEITGICMILYAkJ6DgvMTAQn7JiuJye3LysNntqFUqrpq6NZLHgyhV79IQSvUiJLeRoGlPhKcv3w+fxpO71vBLbiaOWH5iP6lFOfy73xjifYJoDhqNhpkzZ3LnnXcyZ84cVq1ahd1upyWTZZnJkyfz+uuv06pVK4Tm8d3Hm5j+t7EIsHPdXu57cRyC4Kx9JTn8ZffXmO026iOrVPzrpru4KaANgiAIjUVGEFoClR+oQ8BWgDMSg4r4vWqzmfTCc3QKDaYxSB4PopjWgvUkzrNhr3gRlf8KQIWnRsf8AXfx3qFtvHdoGwr1O1lRzJgNXzC7y2CmtetJc4mOjuabb77hyJEjvPnmm3z11VfYbDZaEpVKxbhx43jttdeIi4tDaD7ZGfn4h3jj6aPnRldVXoOHlx5Zo0YQnHGsvICHdn6F0WahPipJ4o3uYxgUEocgCEJjkhGEFkLSJKLYCnBGYmARapWCzS5xueSsHDqFBtMoJA0qr1ewl0wGFJxmOYRSswJJP4ELJGBmp/5Ee/kzJ3kdRquF+tTarLyatpGUomxe7TmcADcPmkuHDh348ssvef7555k/fz6LFi2ipKQEVxYcHMy0adN48MEHiYqKQmh+38/fxLQXxyLApmU7GXJ3bwTBGWeqipmxYwmVFhP1kYC/Jd7O7WEdEQRBaGwygtBSaBLBtAFn6NQW2vqUcLzEn8slZ+Uyo3cPGo22J5L7KBTjdzSEUvU2ktstoPLnkjsj29PWK4CHt60kp6oMR2zIOc6uwiye6TKYSW270pzatWvHP//5T+bNm8eKFStYtmwZmzZtwmw24wrc3d0ZPnw4kyZNYtSoUWi1WoRrI+9kEb5B3nj66BHgXF4JwREBCIKj8mvKmb5jMcW11TjiqY63MCGqO4IgCE1BRhBaCEmTiILzOgcUcbzEn8vtycnDarcjq1Q0FsnwLErtFrCX4jR7OUrlm0jeb3G5BN8gVg+7jyd2fs+2/NM4osJs4vmU9Ww+e5LXbhpBoJsHzcnNzY0pU6YwZcoUysvLWbt2LWvWrGHLli0UFhbSnMLCwhg0aBCjRo1ixIgReHh4IFx7qz/ayNTnRyPAoe3H6dgnDkFwVHFtNdN3LCa/phxHPNJuAPfH9kUQBKGpyAhCS6HpCKgBG87oGlTEiowELldtNnPwbAHdwlrRaFS+SJ5PolS8SEMoxu/BfSyStjeX89Pp+WLwJOan7+KfB7dgtdtxxMbcDFKLcnix+1DGRHXkWvD29uaee+7hnnvu4YJjx46xdetWUlNTOXToEOnp6VRWVtIYfHx86NixIx07dqR3797079+f6OhoBNdy9lQRPoEGDL4eCJD88wGm/W08guCIMrOR+7Yv4kxVMY6YFN2Tx9sPRhAEoSnJCEJLIbmDHAvWYzijZ6ti/sjurBy6hbWiMUn6u1CMq8GyF+cpKOV/QwpYA5Ibl5OAh9v3ISm4DY/v+I7sqlIcUWY28tSuNaw4dYC/dR9KvE8Q11J8fDzx8fE8+OCDXHLmzBmysrLIycmhoKCAvLw8qqurKSsrQ1EUysrKuMDX15cLfH198fDwIDw8nODgYMLDw4mKiiIsLAzB9a364GemPjcaASqKqzD4eqKWVQhCfaqtZh7cuYQTFedwxMjwzrzQeQSCIAhNTUYQWhBJ2wXFegxnhHmew1Nrpsqs5XK7s3L4c99eNC4VKu9XsJ8fDVhxmu0MStWHSIYn+SOd/UNZO2I6z6es54esdBy1uzCLO9d/xt0xiTydOBBfnR5X0aZNG9q0aYNw/Tt7qgifQC+8/D0RYONXOxh8Vy8EoT4mm5U/71rGodKzOGJIaDvmdR+FSpIQBEFoajKC0JJoEoHlOEPCTgf/cyTnt+Zy+3LzMVmtuMkyjUqOQ/K4F6X6MxpCqf4UyW0EaBL4I54aHe/2Hc1NQRHM27cJo9WCI2yKnWUn9vFTznGeThzIhJguqCQJQWgu3364kSlzRiKAoiiUFpUTFOaPINTFarfzRMoKUs6fwRG9A6P4Z8/xqCUVgiAIzUFGEFoQSZOIgvO6h5wjOb81l6u1Wtmfm0/vNuE0NslzJoppA9jycJ4Ne8WLqPy/BtRcyT2x3egfGsUzu9eRXJSNo0pra3g+ZT1LM/fyl479GBoWh0qSEISmlH/6HAY/D7wDDAiwf8tREgckIAh1sSsKc9JWs7kgA0d09m3NB70nolPLCIIgNBcZQWhJ5BhQeYG9Amf0Cy/nw338j11ZOfRuE06jk9yRDM+ilD1Gg1gOotQsQ9JPpi4Rnr58dctklp/Yx7x9m6i2mHFUemkhj2xbRYSnD1Pb9WRS2664qWUEoSl8+9FG7pl1J8L/k7rxEDNeuQtBuBIFhVcOrGNd7mEcEecVxCdJ96CXtQiCIDQnGUFoUSQkuQOKeRfOiPc5yx/ZfSYbBibRFCS3W0E3BKX2VxpCqXwHSXcLqEOoiwRMatuVfiFRzEn+kV2FZ3BGdlUZr6Zt5OMjOxkV1ZGxUZ2I9wlCEBpL/plzeHi54xNoQIDSwnL8grxRqVUIwpW8c3gTX59OwxERHn4s6DsFb607giAIzU1GEFoaTSKYd+EMvVxGK49KzlYbuNzB/EKqas146rQ0BcnrRZTzu0Ax4jSlGqXiFSTfD3FEuKcPS27+E8tO7OMf+3+j3GzCGedM1Sw4msyCo8kk+AYxNqoTI9t0JNDNA0G4Gms+/ZUJf70N4f/ZtHwXQyb0QRCu5OPj21iYuQNHhLh78Vm/KQS6eSIIgnAtyAhCS6NNhGqc1jusmG+PG7iczW5nT04eg9pG0STUrZE8Z6JUvkFDKLW/gGkDktswHCEBf2rblRHh7Xj7wBa+Prkfu6LgrKOlRbxeuok39v1Kr+BIbmkdy9CwOFp7eCMIzig9V4FarcYn0IAAdpud8pJK/EK8EYQ/suxUKu+m/4oj/HR6FvSdQmu9D4IgCNeKjCC0MJKmCwrOGx5dyrfH2/B7u7NyGNQ2iqYieUxFMa0Fy2EaQql4BUn7/7EHJ4BxlgXi/7/PO5PJTOadzJGzTWbatE0P2nL0pLSAXArlrtyCi+C1u+iu63qzIq4Hurvqz/XY1UVdEARERURgwXL24ihX0zP3TNKkyWSuvJNM5nif/xb+XUOokok0mUmez2cdaOWMl7e0jK+uOY9rGlfw5Z2P8UJfiInIScm23g629Xbw5Z2P0+iu5Ky6Rs6sW8DKKj8CRfnzHviPzZz/gdNR3rDjkVdYc87xKMrRPBh6ja+89gjj4Sop5UenXMt8VyWKoihTyYqiFButAix1kOsmHydUBoGTGGt7R5Bjy4Lm/hpmeBOQJW9mP9L4FqL8S+RrqbeGe86+jgc7mvjGK0/SOzTIX6I5HqY5HuY/9mynzunm9FnzOHXWPNbVzKHcZkdRRksmhhk2UsxqqEJ5w2tb9vORr1+Fooz1RM9+Pr/zt5hS8nbslhJ+uO4alnpmoSiKMtWsKEoREraVyOFu8uEu6aHKMUT/cBmj7TvUT3RoGG+Zg2PGuhjh/Ctk8nYmQg7dg7BfCLaV5EsAF89dxjn1C7njwE5+uu95+lNJ/lLdyTh3t7zM3S0vYxGCEypms6G2gVNnzePEytlYhIYysz10+5NsvP40lDccbOvDv3AWQggUZbQd/e38wwv3k5Mmb6dEs/D/1l7ByooAiqIohcCKohSjktUw/CD5kZw+J8z9+wKMJoHngl2cu7iRY0noH0emHoNciPyZmInPo1X8DoSNiSiz2vjocev4wKLV/Kp9Fz/eu4POwSjvhJyUvBTu5qVwN99t2oJeUsq6mjmcXDOHtdUBFnuq0YRAmTnSIxkOBQeYu6QO5Q2P372Vy//uXBRltNei3fztjnsYyWV5OxYh+MaqSzmtZgGKoiiFwoqiFCFhW4skf+fOi3H/vgBjPdcZ4tzFjRxTwoEo/xIyeiMTkm1HJn+E0G/iL1FqsXLNgpO4cv6JPBbazy/bXuXZnjZyUvJOMTIjPN51gMe7DnBYuc3Oqqp61lYHWFMdYJmvFovQUKavR+94lrOuWofyhvRwmsPKXA4U5YgDiT4+vO0uhrJp3o4AvnTiBZxXtxRFUZRCYkVRipF1LmjVYPaRj+WVQeB4xtrWEWQyiNJTwX4hMvU7JkIm/wNhPw+s8/lLWYTgvMBizgsspm/Y4MGO3fyqfRf7Y3280xLpFE90t/BEdwuHOUtsrKqsZ011gFVVfpZXzMJusaJMD7msyYGXO7joQ2eivOGJ+3Zw+qWrUZQjgskIH9x6J/H0MOPxqWXv5rK5K1AURSk0VhSlSAnbamTq9+TDbe2iwjHMwLCD0doHovQkBplV7uJYE+U3I9NbwIySN5nGTHwRzfdzQPBOqXbofHDJWj64ZC17ood4oKOJx0L7CRoxjoVkJs3TPW083dPGYVZNY6m3lhWVdayoqmdlZT21ZS6U4vTsgzs57ZJVKH8UPNDDuX91GopyWO9wghu23El/ymA8PrbkXXygcR2KoiiFyIqiFCvbGkj9nvxIzmmIcs8eB2NtbQ9y2QlLOeY0L8L1aWT8c0xI+gXk0C8RZVdwLBznreE4bw2fP+ks9sf6eLyrmce7DtAU6UFybGRNk1cHDvLqwEF+uv8FDqstc7Gqys9JlXWsqKxjqbcWq6ahFL4XHt/FP37/Ayhv2Pt8K4tXzUNRDouMDPHBrXfSPRRjPK6dv4a/WXw6iqIohcqKohQpYVuLJH/vmRflnj2zGWtbRyeXnbCUySAcm2D4d8j0NiZCDt6GKD0VLLM4lhZ5qlnkqeamZevpHRrkD90HeLzrAM/3hRjJZTmWeocGeahzDw917uEwm2ZhibeG5b5ZHF8xi+W+Wha4q7AIgVI4dm09wPJTGhGaQHnD1od2cv0/vRdFMbIjfHjbz2kdDDMelwRO4PPHn4uiKEohs6Ioxco6D7RqMPvIx1JfJ7CUsba2BzGlRBOCY08g3F9Chi8CmSJv0kAmvojw/pjJUlvm4trGlVzbuJJULsvO/hBbezvY0tvO7kgvkmMrbeZ4deAgrw4chGZeZ9U0Glw+VlX5WVlVz3JfLfPLK9GEQJkaf7h3O3/7zWtQ3pAYMHB5nFhLLCgzWyqX4a+3/4LdsR7G4+zZi/nKiosQCBRFUQqZFUUpYsK2Cpl6mHyUW4NUOoYJDzsYLTo0zP6+MEtqqpgUlrkI518jjW8zEXLkaUj9DmG/kMlmt1hZX9vA+toGPs0ZREaG2HGok629HTx5sIXeoUEmQ9Y0aY6HaY6H+UXLyxxWZrWxxFvNct8slvlqWe6rZX55JZoQKMdWd+shavwV2OwlKG947K4tnHXVKSgzW8bM8XfP3ceL4U7G45Tqefzb6suwCA1FUZRCZ0VRipltNaQeJj+SCxqH+NlrDsba1h5kSU0Vk0XoH0aOPAqZvUyETPwzwrYOtEqmkq+0jI2BJWwMLOGwoBHjxf4QO/u7eKanje5knMkylE2zs7+Lnf1dHKGXlLLIU8Vy3yyW+WpZ7qtlgbsKgfJO+t3tT3LlJzaivEGaklh/gsrZXpSZKycln3nxNzxzqIXxONFXz/dOvgqbZkFRFKUYWFGUIiZsa5Hk75yGAX72WgVjbW3v5MaTVzJ5LGjl/4w5cCWQI29mDJn4CsLzHQpJQPcQ0D1saljOYR2DEZ7vC/FcXyfP94XoTsaZTEZmhJ39Xezs7+IIX2kZx1fMYrlvFst8tSzx1lDvdKNMzGA0iSY0vFXlKG947n9eZdU5y1FmLonkS688xCPduxmPxe4a/vOU9+GwlKAoilIsrChKMbPOB60SzDD5WOxtBxYy1guhblLZLHarlUlTcjyi7Crk0F1MhEw9DKnzEfZzKFRzXT7munxcMf8EDutOxnm+L8TL4W52hkMciPWTk5LJFBkZ4qmDrTx1sJUjym12FnuqWeKpZrG3muO8NTS6q7BbrCh/3kO3P8W5f3Uqyh+9+sxePvy1q1Bmrn9pepz7O15iPOboPv5r/XWUl9hRFEUpJlYUpagJhG0VMvUo+XBq7dQ6R+hNljLaSDbLy10HWTc3wGQSrk+q0BBrAAAgAElEQVQiRzZDrpeJkIlbEba1oJVTDOqcbi5tcHNpwzIOG8pm2BPt5cX+Ll7sD/FyuJvoyDCTLZFO8XxfkOf7ghxhEYI6p5sF7kqW+2axzFdLo7sKv+5BoByWTWfp7QwTWDgL5Q097X3MnleDEAJlZvr3vU/x0+btjEeto5yfrH8/FaVOFEVRio0VRSl2tjWQepT8SK5anuQ7O0oZa1t7kHVzA0wqoSPK/xkZ/RATYvYhB29DuL9GMSqzlrCqys+qKj+wDlNKWhNhXgp3s7O/i12RXlri/eSkZLLlpCRoxAgaMZ7obuEIb6mDJd4aFnuqWeKpYbG3moXuSko0CzPN0795gdM2rUL5o833bOfSv303ysz089bn+cG+pxmPilInP9nwfmaXuVEURSlGVhSlyAnbGiT5O8t/kO/s8DHW1vYgnzyDSSdKTwfHRcjhB5kIOXw/2M9DlJ5KsdOEoNFdRaO7iivnn8hhWdOkfXCAF/u7eLE/RFOkl9bEAKaUTIXoyDDbejvY1tvBERahMa/cR6O7ikZ3Jct8tSz3zaLaoTOd7XxiN5/64Y0obxgZTpPL5nCWO1Bmnt8GX+Vrrz3CeLhK7PzX+mtp0CtQFEUpVlYUpdhZG0GrAHOAfDS49iBYikQw2p5DfUSGhvGVOZhswnUzcmQbmGEmQib+CVH5exBOphurptHorqLRXcXVC07iMCMzQlOkl12RHpoivbwW6aFzMMpUyUmT5niY5niY0SrtTpZ4qznOW8MiTzWN7ioWlFdQarFS7PbtbGfxqnkITaC8YfO92zl90xqUmecPB/fxhZceRPL27JYS/mPdNSx216IoilLMrChK0RMI2ynI1O/Ih5UBVs0e4oWDTkYzpWRHZ4iNSxYy6TQPovxmZOzvmZDcQeTgvyHKv8hMoJeUcnLNHE6umcMRRmaEfbE+dkV6aYr00BTppSUeRjJ1wqkkz/a082xPO6NVO3SW+WpZ6K5igbuShe4qFrgrsVusFIvH797KjV96L8ofdR3oYeP1p6PMLNv72vjkC/eTkyZvp0Sz8O9rr2RFhR9FUZRiZ0VRpoPSDZD6Hfm6YkmUFw46GWtbe5CNSxYyFYR9I9gfRqYeYyLk0N0I+0awrWIm0ktKWVXlZ1WVnyMGMyPsj/WxK9JLU6SHpkgvzfEwU61v2OCJ7hae6G7hCIvQqHOWs8BdyUJ3FQvclSx0V7HQU4VNs1BIYv2DOHQ7ZS4HyhtefXYfy9cvQplZXol08bc77iFt5ng7FiH419XvZUPNfBRFUaYDK4oyDYjSDUgEIMnH2tpOoJ6xtrR3MpVE+S3I9HNgxsmfiZn4PFrFgyDsKOAqKWVVlZ9VVX6OODRssGugh93RXvbF+tgbPUTIiCGZWjlpEjRiBI0YT3S3cESJZmF+eQWN7koWeapZ4K5kkbuKet2DRQimwsM/e5pzr9uA8kc7Hn6ZD33lSpSZY1/8EB/ZdhfDuQxvRwBfPuki3j17CYqiKNOFFUWZDrQqsC6E7H7yUWXfj8O6huFsCaMdjCfojMaY4/UwJbQqhOtzyPhnmZBsB9L4HsL1jyhHV+PQqalv5Oz6Ro5IZtK0D0Y4EO+nKdLLrkgPe6OHGMpmmGoZM8e+WB/7Yn38rnMPR5RoFua6vDS6q2h0V9LorqTRXcn88ko0IThWspkcfV0R6hfUoryhr2uAan8lmkVDmRk6jQgf3HoniUyK8fjs8vewac6JKIqiTCdWFGWaEKUbkNn95EPIES5aGOPePVWMtaWtkzkrPUwV4dgEqYeRI88wETJ5O8J+LpQsQxkfZ4mNZb5alvlq2dSwnMNMKek0ouyNHmJvtI+9sUPsi/VxMJmgEGTMHM3xMM3xMKOVWW0scFewyFPNgvIKFnqqmefyUed0ownBX2rLgztZf+EKlD967OdbuOjDZ6HMDL3DCW7YegcDI0nG4x+WnsX7F5yMoijKdGNFUaaL0g2QvJ18XdTYy717qhhra3sn71t5AlNJlN+KDF8AMkn+cpjxz6FV/BpECcrEaELQ4PLR4PKxMbCEIwYzI+yP9dEcD9McD7Mr0sOe6CGGsxkKwVA2zWsDPbw20MNoJZqFuS4vje4qArqHBe5KFrqrmF9egcNawnjtfHI3//Dd61HekBnJksvkKPfpKNPfwEiSG7bcwcGhOOPx/gUn86GFG1AURZmOrCjKNCFKViGFA+Qw+Vjm3Y1gGRLBaNs7QmRyOUosFqaMpQ7h+kdk4lYmJLsfmfweQv8EyjvLVVLKqio/q6r8HJGTJt3JBM3xfpoiveyK9NASDxM0YhSKjJmjOR6mOR5mrGqHTqO7ikZ3JY3uSgK6h0WeairtTkbraumlfkEtQhMob3jivu2ctmk1yvQ3mBnhQ9t+TrsxwHhc3bCKzy1/D4qiKNOVFUWZLkQpwrYGOfI0+SjVoiyrjLArXMFoyXSal7p6WDunnqkkyq5Gph6G9AtMhDR+hCg9E0pOQDm2LEIjoHsI6B7OqmvkiMjIEHujh9gX66M5HuZArJ/mRJhkJk0h6Rs26Bs22NrbzmhVdicL3JXMK69ggbuSAw/s4X1XnonyR8H9B3nPdaeiTG+pXIa/3n43e2O9jMcF/uXcfMJGFEVRpjMrijKdlL4LRp4mX1cuHWDX0xWMtaWtg7Vz6plaGpr7q5jhi0CmyF8OM/4ZtIoHQNhRJp+vtIz1tQ2sr21gtEPDBi3xfg7Ew7TEwxyI97M32sdQNk0h6U8l6U8l2X6ok9fVwy+23oFtu4U5Li+N7ioa3ZU0uisJ6F4WuCuxW6zMFLu3N7NkzQKU6S1j5vjYc/eycyDIeJxRu5Cvr7gETQgURVGmMyuKMo2I0jORfBmQ5OPUug5gIWM909bBJ8/YwJSzzEXoH0cOfpMJybYhje8gXJ9FKRw1Dp0ah8762gaOMKWkKxnjQCxMc7yf/fF+WuJhWuJh0maOQpI2czTHwzTHw4xm1TTm6F4WuCuZV17B/PIK5pdX0ODyUW6zM91s/d1Obrj1cpTpKycln3rx12w51Mp4rK2ay7fXXI5V01AURZnurCjKdGKZBdZGyB4gHzX2diodQ4SHyxht36F++o0kVbqTqSacH0CmHoHMLiZCJn+GKD0TbGtQCpcmBAHdS0D3cnZ9I0fkpKQ7Gac53k9zPExzvJ/meJiWeJhULkshyZomrYkBWhMDjOW22fHrHgK6l0Z3JY3uSgK6lwXuSuwWK8VmoCeGr9aDtcSCMj1JJF98+UH+p3sP43G8t47vn3w1pRYriqIoM4EVRZlmROkZyOwB8mOycUEvd+yax2gS2NLeyaXLj2PqWdDc38QcuBhkmvyZmPHPolX+DoQTpbhYhCCgewjoHs6qa+SInDTpTiZojvfTHA/THO+nOR7mQKyftJmj0MTTKeKRXpoivYxV7dBpdFcR0D0scFey0F2JX/dS73SjCUEheuznz3Le9aejTF+37XqMX3e+wng0llfzn6e8D6fVhqIoykxhRVGmGVF6BjL5n+RrU2M3d+yax1jPtnVw6fLjKAjW+QjnR5DGvzMhuS7k4L8iym9BmR4sQiOgewjoHs6qa+SItJmjNT5AS6KfA7EwbYMDtCYGaE9EyJg5ClHfsEHfsMFW3sxZYqPB5aPB5WNeeQXzyn00uCpocPlwltiYKtl0lmFjBE9VOcr09K3dm7mjZQfjEXB6uX39dXhsDhRFUWYSK4oy3dhOAM0LZpR8LPTsx1lyMslMCaNtaevElBJNCAqB0P8GOfIkZJqYCDl0N5SegSg9DWX6smkWlnirWeKthjn8n5w06U4mCBlRDsTDtMTDBI0Y+2J9DKSSFKJkJk1TpJemSC9juW12/LqHRnclje4qArqHgO6l0V1JqcXKsfT0r59nwyWrUKanO1p28OMDWxiPGoeL2ze8nyq7jqIoykxjRVGmHQui9HTk8APkQyPDafVBHmmfz2ix4RRNPYc4fnYthcGC5v4m5sClIEfIn0QmvoCoeAg0N8rMYhEaAd1DQPewvraB0fqGDVoTYVoTA7TEB2hNDNCaCNM7NEihiqdTxCO9NEV6Ga1EsxDQPcwrr6DB5aOh3Mdcl48Gl49qh847ofmVTs666hSU6efXna9w267/YTy8tjJuX38d9WUeFEVRZiIrijIdlZ4Bww+Qr/cu6uGR9vmM9UxbB8fPrqVgWBcg9JuQg//GhOQOIQdvQ7i/jqIcUe3QqXborKuZy2hpM8c/f/6nrPnIOtqMCM3xMEEjSnM8zEguSyHKmDlaEwO0JgYYy6ZZqC1zscBdyUJ3FX7dQ0D34Ne9+HUPgre357kWlqyZjzL9PBTaxT+9/CCSt6dbS/nRKe9jvqsKRVGUmcqKokxDovR0pCgFOUI+1tQ2Y9PWkTYtjLalrZObNpxMIRHODyFHnoL0TiZCDv8KSs9E2M9BUf6c4cgQc+1eLmxYymg5adKdTNAc76c5HiZkxDgQ72dfrI9kJk2hSps5gkaMoBHjie4WRrNpFua4vDS6qwjoHvy6h4Duwa978eseBG/Y8tsXueHWy1Gmlyd7D/C5lx7AlJK3Y7dY+cG6q1nmnY2iKMpMZkVRpiNRhrCdghx5knzYtBRrZ3XzbHeA0V7t7iE+nMLtsFM4NLTyr2EOXAwyxUTIxBcRthWgVaAof8qT9z/PuzatZiyL0AjoHgK6h7PqGhntYDJB2+AArYkBWuMDtA9GaB8coCeZQFK40maO5niY5niYscptdua6vNSlHJSIKA9172Wuy8dclxePzYFS3J7r7+ATz/+SrGnydqyaxnfWXMHqyjkoiqLMdFYUZbqynwMjT5KvjfODPNsdYLSclGzrCHLekoUUFGsDQv8EcvDrTIg5gEx8BeH5Nu88iUz+GFF6NljnoRSv5lc7ueSjZ5GP2c5yZjvL2VDbwGgZM0fP0CDN8X6a42FCRoygEWN/rI9wKkkhS6RTvDbQQ/dDEWJnuHlw24Mc4bbZ8eseArqXgO7Br3sI6B4WeqqpsjtRCttr0W7+dscvGMlleTsWIfjGyks5vbYRRVEUBawoyjQlSs9G8k9AjnycM6eNm7X15EzBaFvaOjlvyUIKjXD+FXJkM6SfZyJk6veQOgdh38g7xowi459EjmxBOC5FKV7B/QdpWFrHO6VEsxDQPQR0D2fVNTLaQCpJa2KA9sEI7YkI7YMRWhMDBI0oWdOkEGgZiTAlOaeF0eLpFPFIL02RXsbylpbR4PIy1+VjrsvHHJeXObqXOS4vbpsdZWo1J/r4yLa7SGbTvB0B3HLiBWysX4aiKIryBiuKMl1pHrCthPTz5EMvSbJ2VjfbuusZ7dm2DiQgKDQamvs2zPCFIJNMhEzcirCtBq2Kv1hmF2bsY5A7yOtEOUrx2nzvDi760JlMhgq7kwq7kzXVAUbLSZPuZIKQESVoxGiOh2mOhwkZUUJGDMnkKd8xSGJ1OfmIjgwRHRnipXA3Y7ltdvy6h4DuJaB78OseAroHv+7Fr3sQKMdSMBnlg1t/Tiw9zHh8ctk5XD53BYqiKMofWVGUaUzYz0GmnydfGxta2NZdz2i9gwbN/WEWVlVScCz1CNenkYlbmBAziox/DuH9MSCYKDl0L3LwyyAzvE7YQJSiFCdpSuIDBhWzPEwli9AI6B4Cuof1vFnazNE5GKE5HiZoxAgZMQ7E+9kf68fIjPCOkhLboTSxU8t5p8TTKeKRXpoivYxl0yzUlrnw614CuocF7koWuivx617qnG4sQqBM3KHhQW7ccgd9qUHG428Wn86NjaegKIqivJkVRZnGROnZSL4GSPJxbkMHt24zyZgaoz3T2sHCqkoKkSi7CkY2I0eeYSLkyDMwdDei7H3kTSaR8c8jU4/wJsKNUrxefmYvJ5y6iEJm0yw0uqtodFcxVu/QIO2DEdoHI3QMRugYjNCeiBAyYqTNHPly7hkmeVwZkyVt5ggaMYJGjK28mU2z4Nc9BHQvc11e5ri8BHQvc11e6p0erJqG8qdF00PcuPVOuoZijMc181bzsSXvQlEURXkrK4oynVnqoGQZZHaRD71kmHWzu3imK8BoT7e288GTV1GYBKL8q8iBC8CMMxFy8DaEbTVYFzJu2VbM2E2QbeUttHKU4rXjkVf5wBc3Uaxqy1zUlrlYVzOHseLpFM3xfprjYUJGjKARI2hEaYmHSeWyHI1z9xB9l1dQCNJmjtbEAK2JAY6m2qHT6K4ioHvw6x4CuoeA7qXB5cNZYmMmM7IjfHjbXbQO9jMeFwWO5wvHn4eiKIpydFYUZZoT9vORmV3k6/x5zTzTFWC0F0MHSaRGKLeXUpAsNQjX55HxzzAhcgQz/mk0330gbLwdOfwAMnELyGGOSpSjFKdc1iSXzeFwljIduW12VlX5WVXlZ7ScNOlOxukYjNIxGKFjMErHYISOAweJ15WCEBSDvmGDvmGDrbxVbZmLOboXv+4hoHsJ6B78uoeA7qHC7mQ6S+Wy/M32X9AUPch4nDVrMV9bcTGaECiKoihHZ0VRpjlhPw85+A1Ako+z53RQaskxkrNwRM402dYR5NzFjRQq4bgURjYjU48xIZk9SOM7CNen+ZPkCHLwX5BDd/DnCK0cpTi98sxejt+wiJnGIjQCupeA7uW0WfM44qdP3c8V3/woA3KEkBElaMQIGTGCRozmeD9tiQg5aVIMeocG6R0a5Lm+IGPZNAu1ZS78upeA7sGvewjoHgK6l3nlFZRZSyhWWdPk75+/jxfCnYzHyVUNfGvNZViEhqIoivKnWVGU6c4yC2wnQfol8uEsSbOhLsjmYAOjPdXSzrmLGylkovzLyPROMAeYCJn8CZSeirCt4y1y3Zixj0NmF29Lc6MUpx2PvsoNX9yEAkYsid1ZitPpwImDgO5hPW+WNU0ODiUIGVGCRoyQEeNAvJ+WeJjuZJyclBSDtJkjaMQIGjG28lZumx2/7iGgewnoHvy6h4Duwa97qXe60YSgEJlS8pmdv+Hp3mbG4wRfPd8/+SpsmgVFmXS5HPzyl/C970FbG1RWwiWXwCc/CW43dHbCxz4GN90E7343rwuH4c47ob0dvvtdFGUyWVGUGUDYNyLTL5GvixccYHOwgdGebm3HlBJNCAqW5kOU/xMy9vdMjImMfxpR8RBobo6QI5uR8c+CGWdchAul+OSyJrmsiUO3o8CjdzzL2des58+xahoB3UNA97CeN0ubOToHo3QMRugcjNJpROkcjBI0onQnE+SkSbGIp1PEI700RXoZq8xagl/34tfdBHQvft1DQPfg1z34nR5KLVamgkRy6yu/5+GuJsZjkbuGH53yPsqsNhRl0pkm/OQn8NWvwle+Ahs2QFsb/Mu/wAc/CHfdBbkcJBKQyfB/pIRUCpJJFGWyWVGUGUDYz0Mmvg7kyMcZgQ48pSliI3aOGEgOsbu3j+Wzaihkwr4R7I8hUw8zIblDyMTnEJ7vAybS+AHS+B4gGTfNjVJ8Xnl2L8dvWIQCuaxJfGCQqjofE2XTLDS6K2l0VzJW1jQ5OJQgZEQJGjFCRoygESNoRGlLDDCUzVAshrIZ9sf62B/r42jcNjt+3UNA9xLQPfh1DwHdg1/3Uu90ownBsfBvTX/gvo6djEfA6eO/TrmW8hI7ijIlhobg1lvhS1+Cq64CiwXq66G2Fi67DB58EFasQFEKiRVFmQm0KrCtgvRz5KNEM3nP3Dbu3X8coz3V0s7yWTUUOlH+ZWTmFcgdZCJk6g9g/Acy/Qykd5I3UY5SfJ579DWuv/kSFHj2gRdYf+FKjhWrphHQPQR0D+t5q3g6RciIcSDeT0s8TNCIETSidAxGMTIjFJN4OkU80ktTpJexbJqF2jIXft1LQPfg1z0EdA8B3UuDy4ezxMZE/GDf09zevI3xqHWU85MN11Fp11GUKfPSSzAwAJddBlYrr7NYoLYWTj4Znn0WVqxAUQqJFUWZIYR9IzL9HPm6uHE/9+4/jtGeamnjY6eeTMHTytHc/4oZuQ7IMRHS+A4gmRDNhVJcclmTbDpLmcuBAvt3tvGuy9YyVdw2O25fLct8tYwVT6cIGTGCRpSgESNkxAgaMUJGlKARo5ikzRxBI0bQiLGVt3Lb7Ph1DwHdS0D34Nc9BHQPft1LvdONJgRj3d32Av++9ynGw1daxu3rr6OuzIOiTKlwGMrKwO3m/wgBFgtUVUF3N6/r6YH3vx/sdl5nmiAlnH8+ijLZrCjKDCHsG5GDXwWZJh8rqnuZWx6nI+HmiN29ffQnk1Q5nRQ82yqE8wZk8sdMjGTCRDlKcdm17QDLTlmIAnufb2Xx6vkUKrfNjttXyzJfLWPF0ylCRoygESVoxAgZMYJGjJARpSsZx5SSYhJPp4hHemmK9DJWiWZhVpkLv+4loHvw6x76UnHu6XiB1wn+LFdJKT8+5VrmuSpRlCnn80EyCYYBLhf/xzQhEgGPh9dVV8NnPgNnnMHrIhG47z4Ih1GUyWZFUWYKzY2wnYYc+QP5umD+Ab738mqOMKXk2dYONh2/lGIgXJ9App+DzGtMKs2NUlxe3NzEFX93Lgo8+9sXueFLl1GM3DY7bl8ty3y1jDWUzRA0ogSNGF1GjKARI2hECRkxQkaMtJmjmGTMHEEjRtCIsZXRLIAFIQAhEUKiCQkChJAITeKwlvDDdddwnGcWilIQVqwAlwseeACuu47XSQnRKGzZAjffzOssFqiuhrlzeZ3TCW43hMMoymSzoigzieNiGPkD+bpo/gG+//IqJIIjnm7tYNPxSykOVjTPv2GGLwY5xGQRohyluBixIcp9OjPdwMEolbM8WEssTDdl1hIWe6pZ7KlmLAkcGhokaEQJGjFCRoygESNkRAkaMcKpJMVGSkAKJAKTN5Oahc9tfxS/7qFed+N3eqjX3dQ7PdQ53XhLHSjKpNJ1uPlm+NSnoKwMzjwTmpvh5pthzhy47DLo7uZ1QoAQvE4IEAJFmQpWFGUGEaVnIDU3mHHyEShPsLKmlxcPzeKIZ9s6yJomVk2jKFjmIFyfQSZuYdJobpTi0dsZpnZOJQo8euezXPihM5lpBFBb5qK2zMWa6gBjpc0cvUODhIwoQSNGyIgRNGIEjShtiQhD2TTFJGPmaEmEaUmEOZpSi5Uah45f9xLQPfh1DwHdQ0D3EtA9lNvsKMo7StPgppvA7YZbb4XrroPKSrjiCvjCF6C0FIQATeOohEBRJpsVRZlJhA1hPxc5dC/5umzRXl48NIsjjJE0O0MHWTunnmIhyq6GkWeQI5uZFMKFUjxeeHwXq89exkw3Mpwmm85S7tNR3symWQjoHgK6h/W8VTydImTECBpRgkaMkBEjaMQIGVG6knFMKSkmI7ksQSNG0IixlbcqtVipcej4dS8B3YNf9xDQPQR0L3NdXvSSUhQlbxYLXH89XH89R9XQAE88wZtUVcHnPoeiTAUrijLDCPslyKF7yde5Da18bcd6EulSjniqpY21c+opJsJ9G3LgYsgd5NjSQNNRikfLa0EuuPFdzHSb79nGGVesQ8mf22bH7atlma+WsdJmjt6hQUJGlKARI2TECBoxgkaU9sEIyUyaYjOSyxI0YgSNGFt5K7fNjl/3ENC9VDt0qh06Ad1DQPcyr9xHmdWGohyNlBIpJaZpYrVaUZRCZkVRZhrbCrAEIBckH3ZLlvPntfCLfUs54unWDj5z1mkUFc2N5v5XzMi1gMkxo+mAhlIc0iMZ7GU2hBDMZFJKupp72fiBd6G8s2yahYDuIaB7WM9bxdMpQkaMoBElaMQIGTGCRoyQEaUrGceUkmITT6eIR3ppivRyNG6bHb/uIaB7Cege/LqHaodOjcPF/PIKHNYSlKN7pqeNU2fNQzA95XI5HnzwQe6//37uvvtuFKWQWVGUGUcgHBcjjX8nX5ct2ssv9i3liJbwAMFojIDXQ9GQaWTqUcDkmBJulOLx2pb9LF+/iJlu5+YmVpy5FGXyuW123L5alvlqGStj5ugZGiRkRAkaMUJGjJbEAFt6W0nlciApSvF0inikl6ZIL0fjttnx6x4CupeA7sGvewjoHvy6lzpnORahMVN9esdDNLqr+Mba85ntLEdRlKljRVFmIOG4FGl8HzDJx9KKfo7zhdkTqeSIZ9s6ed9KD0Uh140Z+xhkmjjmNBdK8XjpyT2879MXMtO98PguPvr1q1EKS4lmIaB7COge1gODmRGu3/LfyJIUpSUgJSAFUoIpBUiBNAVSgpSCYhVPp4hHemmK9HI0bpsdv+4hoHsJ6B78uoeA7sGve6lzurEIwXSUMXOEU0n6hg3OffjHfO6kM7lqwUkIFEWZClYUZSay1CNsJyPT28jXZYv28uXtp3LEk81tvG/lCRQ6OfIUMv4pMONMBiHcKMVj2EjhLHcwk3W39DJnSR1CEyiFK5XL8Nfb72ZPrIcjhACERAAaktHOmrWYTy59NweTMYJGjJARI2jECBpROgajGJkRilU8nSIe6aUp0stYVk1jdlk5ft1LtcNJjcOFX/cQ0D34dS/1TjeaEBSjg8kEppQcZmRG+MLzj/BYaD9fX3s+tWUuFEWZXFYUZaYquwLS28jXBfOb+ZcXTmY4W8JhOzpDJNNpnDYbhSmHHPx/yOR/ApJJo7lQikN36yHq5tcw0z1211au/tQFKIUrY+b4+HP3sXMgyHicUj2Pb625DJtmocHlZT1vFU4lCRkxupJxupNxuowYoWSMLiNOdzJO2sxRjLKmSdCIETRiHE2pxUq9002d002d081sZzl1Tjf1Tjf1Tg9VDh2LEBSi7mScsZ7uaePch3/MZ048g6sXnISiKJPHiqLMUKL0HKTmAzNCPsptI5w/v4X79y/hsHQux5a2Tt6zuJGCY4aRsX9Apncw6YQbpTi89OQeVp65lJnMiCWxl9mwl5WiFKaclHz6xV/z7KEWxuMkn5/vnXwVNs3Cn1Npd1Jpd3JSZR1HE0+nCBkxgkaUoG0pUUYAACAASURBVBEjZMQIGjH6hgcJGTFSuSzFaCSXpTUxQGtigKOxahq+0jKqHToB3UtA9+DXPQR0D9UOnXqnB4e1hKlwcCjB0STSKb7w/CP8oauZr6/dSLVDR1GUY8+KosxUogThuBiZ/Cn5unbJLu7fv4QjNje38Z7FjRSU9IuYsb8Hs48poblQikP7nm4uuOFdzGT/c+cWzr5mPUphkkhuefl3PNq9h/FY7K7lP0+5BoelhL+U22bH7atlma+Wo4mnU4SMGEEjStCIETJiBI0YISNKdzJBTpoUo6xp0jds0Dds0BTp5WjcNjt+3UNA9xLQPVQ5dGocOgHdy1yXF72klGOhOxnnz3nyYAvnP3I7X1l9Lu/xL0JRlGPLiqLMYMJxJTL5U/K12DfAippeXjpUy2FPtrSRM00smsbUk8ihO5CJbwBZpozmQSkOQoDQBDNVLmsS7Y9TVedDKUzf3PU4v+p8mfGYq1fwX+uvxVViZzK4bXbcvlqW+WoZK2uaDIwM0T9sEDSiBI0YISNG0IgRMqJ0J+PkpKRYxdMp4pFemiK9HI3bZseve6h26NQ4XPh1DwHdQ0D34tc9uG12JuLgUIK3M5BK8tfP/opL5i7jllXvxm2zoyjKsWFFUWYy6zwoOQkyL5OvaxY38dKhWg6LD6d4qauH1YE6ppQ0kPHPI1OPMuWEC6Xwdbf2Mauhiplsy4MvsuHClSiF6bt7nuRnLdsZj1llbn6y/joqSp0UAqumUePQqXHoLPPVMlbGzNEzNEjIiHJo2KBv2CBkxAgaMUJGlK5kHFNKilU8nSIe6eVPKbVYqXHo+HUvAd2DX/cQ0D1UO3SqHS78ugfBW3UZccbrgY4mtva289U1Gzm7vhFFUd55VhRlhhNllyPjL5Ov9zS0ctvzpxAeLuOwJ5pbWR2oY8pk9mDGPg65IAVBK0cpfE3bD7D8lIXMZMnEMItXz0cpPHe2PscP9z/DeFSUOvnJ+uuYVeamWJRoFgK6h4Du4WjSZo7eoUFCRpSgESNkxDg0PEjfcJKQESVkxJAUr5FclqARI2jE2Mpb2TQLtWUu/LqXgO6h2qFT7dBpGwyTj/5Ukg8/80s2Bpbw1TXn4bbZURTlnWNFUWY4Yb8AOfgNMOPko0QzuXzhXn746koO+8OBVj5z1mlMBTn8ADJxC8hhCoZwoxS+5lc7OevKdcxkG68/HaXwPBB8la+/9ijj4bE5+NmGv2KuXsF0YtMsBHQPAd3Det5qKJsmZMToSsYJGTG6knG6jBhdyThdyTiJdIpiljZzBI0YQSPGVv5yDwf38urAQb558vmsq5mLoijvDCuKMtMJO8KxCZn8Kfm6ekkTP951EllTozMaozUcYX6lj0kjR5CD/4wcuo9CI7RylMJnZk2sJRYUpZA8fnAvN7/0WyRvz2m18aNTrmVBeRUzTZnVxiJPNYs81RxNIp2iKxknZMToTsbpSsYJGTFCyRjdyTjJTJqZpjsZ59rNd3PVgpP4woqzKLPaUBTlL2NFURRE2TXI5H8DJvmoLhvi7DntPNo+n8M2N7cyv9LHpMh2YMY+Btn9FCThQilsAz0xKmd7UZRCsq2vjX984VfkpOTt2C1WfrDuapZ7Z6O8VbnNznE2O8d5aziaVC5L37BByIgSNGKEjBhBI8ah4UH6hw1CRgzJ9COBX7S8zJbedr6x9nxOrpmDoigTZ0VRFLDMQZRuQI48Q75uXP4Kj7bP57Anmtv48LrVTAprPZrnW8jMbsg0IbNNkGkCmaYgaG6Uwvba1v0sW9eIohSKlyMhbtpxD2kzx9uxahrfXnM5ayrnokyM3WIloHsI6B7W81YjuSyHhg1CRpSgEaNv2KBv2CBoxAgZUbqScUwpKVYhI8b7Nt/FVQtO4uYVZ+OwllBIcrkcuVwORSl0VhRFeUPZtTDyDPlaXtnHyppedh6q5ZXuHsLJISqdZRx7VrA2IqyN4LgEwf+SI5Ddh8w0QWY3MrMLsi1AjkknXCiFbd/Odm744iYUpRDsi/fykW13M5zL8HY0Ibht5aW8q3YhyrFTarES0D0EdA/reauMmaNnaJC+4UH6hg2CRoyQESNoxAgZUbqTCXLS5J0lAcE7RQK/aHmZF/pC/Ou6Czm+YhZTSUqJaZocOnSI/fv3k06nUZRCZ0VRlNeJ0tORlrmQ6yBfNyx/hZ2HzsWUkqdb23nv8UuZEqIUSk5AlJzAYYLDspBtR2Z2Q6YJmW2CTBPINMeMcIAoRSlsmVSGUocNRZlqHcYAH9z6cwYzKd6OAL54wvmcX78MZWqVaBYCuoeA7uFPiadThIwYQSNK0IgRMmIcGh6kb9igLTHAUDZDfgTHQksizHsf+28+etw6Pr58AyWahamQSCRoaWnh3nvvZdu2bVx44YUoSqGzoijK/08gyq5EDn6DfJ0Z6GCeO0Zb3MPmA6289/ilFA4rWBsR1kZwXILgsCxk25GZ3ZBpQmabILMLZIZ3hHChFLbh5AhlLgeKMtV6huLcsPVOBkaSjMcnl53NlQ0rUYqD22bH7atlma+Wo4mnU4SMGEEjyqFhg/5hg6ARI2hE6RiMYmRGmCw5afL93VvZfqiTO868ijKrjckyPDxMV1cXTzzxBPfccw8rV67kvvvuY/bs2ShKobOiKMr/EY7LkMZ3QQ6TD4Hk/Utf40vbTmNreyfDmSyOEiuFywrWRoS1ERyXIDgsC9l2ZGY3ZJqQ2SbI7AKZIW+aG6Wwtb4WZN6yehRlKg2MJLlh6530DMUZj48uOpUbG9ejTB9umx23r5ZlvlqOJjIyRHcyTncyTncyzg93bycyMsQ7TQBra+bw3objOS+wiDKrjcmQzWbp6elh+/bt3HXXXZSXl/Ptb3+bE088EUUpFlYURfkjzY1wXIocupt8XdK4n+++tJpIysGOziBnLJhHcbGCtRFhbQTHJQj+l8xArgOZfgkyO5GZJsi2Azn+LM2FUthaXg2y4owlKMpUGcyk+ODWn9NhDDAeV89bzd8ddybKzOIrLcNXWsZy3ywO+17TVt5JAd3LpnnL2dSwnHqnm8kipaS/v5+9e/fy29/+ll27dnHjjTdy+eWXY7FYUJRiYkVRlDcRzuuRQ/cAJvmwW7JcvXg3339lFZsPtHHGgnkUPVEC1kaEtRG4EsH/kkOQ2YvMNkFmNzLTBNl2IMcRQrhRCltXSy8XfegMFGUqJLNpbtx6J/vivYzHRf7jufn481BmtmQmTTyd4i9lt1g5s66RqxecyCm1DQgmVyKRoK2tjd///vds3ryZ8847j1tuuQW3242iFCMriqK8mWUuwn4mMvUH8nXd0l38bPcJPNHciinPQhOCaUeUgW0lwraSwwT/SyYhsxeZ2QXZ3aDNRilsUko0i4aiTLZULsvfbP8Fu6IHGY8zZy3iaysvRhMCZWbrTsaZKE0I1tXM5b3zlvOe+kU4rCW84+JxOHgQEgkQAtxu8PvB4QAhyGQydHR0sHXrVn77299SV1fHD37wAxYuXIimaShKsbKiKMpbiLIbkak/kC9PaYorF+3mJ00nsqvnECfMrmVGEE6wrULYVqEUvvRIBpu9BEWZbFnT5BPP/5Lnwx2Mx8lVDXxr9WVYhIaidA/FyVeDy8emecvZ1LCcWWXlHDORCDzwADz+OPT2ghBQUwNXXglnnw1OJwMDA3z7298mEolw0003cdppp1FSUoKiFDsriqK8lW0llJwImVfI1w3LX+Xuvcv4w4FWTphdy7SXSsGWLfDYYxAOg88H69fDueeCw8GU2L0bHn0U9u8HTYOlS2HTJpg1CzQNvvENWLkSTjsNbDZe99xz8Otfw9e/DprGdNa+u4u5x9VRsKSEbdvg97+Hnh7QdVi9Gt77XnA6UYqTKSWf3fkbnuo9wHgc763j+ydfRanFiqIc1p2MMx6uklLOrm9kU8NyTqltQHCMmSb85jdw771wxRVwwQWQy8HPfw633cb/xx58wEdd348ff33uvjeTy2UnEAiEGSCAEEBWQSSgKIi4sChoQXGLqLR0WK2zWnHXidqK4FZcOHCiIApR0LCXQfbKvktufD//R+if/jRVuYQEksv7+SQpCfr3p1peXh55eXl4PB6UUggRDQyEED9LxfwOXTyN2kp2+Tir8xreX5fCdScMIqpVVsJbb8HTT8PAgdC1K+zeDS++CIWFcOWVYBgcVV9/DQ89BF4v9OkDWsOSJbB2LfzpT9CyJXz4IXg8MGgQ/7V1K7z1FtxxB9Fu48qtZPdpR6O1cCHcdRcMHgzDhkFJCbzxBqxZAzffDDYbomnRaG5e+TZvbysgEp3iUnl84Hm4DTtCHLKjopRfYlGKAWltGZeVw8mts3EbNo6a0lJ49VUYNgzGjYOkJA6aPh2WLoUFC6BbN9LT0znjjDMQItoYCCF+lnKORFszIbyV2rqoxwpeeLEbG/bup2NKElFJa9i/Hx55BIYMgcmTITERioogORnmzYMBA+D44zlqQiGYMweUgnPOgR49QGvo2ROuvx4WLoSzz6a5K1y7g5POG0SjFAjALbdA375w0UWQmgo+H7RrBzNmQF4eDB+OaFruWfUhL2zJJxKZMYnMHjQRr92FED+2vaKUmtrHJTG6TVfObNeDVjFejomtW2H/fujZE+Lj+S+7Hfr1g/x88PsRIloZCCF+gRUVcyG69GZqK91dzukd1vH+uo10TEkiKoVCsGYNbNoEs2dDixYclJYGgwbBu+/C55/D8cdz1GzbBvn5cPHF0LMnuN0c1Lcv9OoFixfDKafQ3IWCYQy7QaO0bh189RU8+SS0asVBNhsMGQKdO8M778Dw4Yim49F1nzF7/WIike6K46nBE0lxxiJETdsrSqgWZ3dyamYXxmXlkJvSGsUxVlUFSoHNBhYLP+F2QyAAWiNEtDIQQvwi5TobXf4omHuorak9v2b654O5YvDxRCXThB07wOGA1q35L6UgJgbS02HHDo6qvXshEICWLcHl4r+sVmjfHj76CIJBDnr6aVi4EKxWDtq+HcJhop3WGotF0Wht3QpWK7Rrx38pBTYbdOgAmzcjmo7nNi/j/tUfEYlEh5vZgyaS4Y5HiJ/TKT6Zydl9yWvVCbvFSqORkgJ2O+zYAX4/uN0cFA7D5s2Qmgo2G0JEKwMhxC9TDlTM79Bld1JbrT2ldIpdzNai08hMiCcqOZ0QDEIwCIbBf5kmVFWBx0M10zQJh8PYbDYalN0OpgmBAJgmWK38l88HdjtYLByUmwsnnAB2Owd98QW89RbRbu/2IlIyEmi0XC4IBiEQAMPgv7QGnw9cLqpprQkGg9jtdkTj9MYP33Lrt+8QiVjDweMDz6e9Jxkhfsnt/U6hUcrIgJ494bPPoEsXyMkBrWHNGsjPhwsvhJgYhIhWBkKIX6XcE9AVT4B5gNq6otcyPly/lguP70/UsdkgOxu0hsWLIS+Pg0wT9u2D9eth6FCqfffdd8yZM4cLLriA7t2702DatoWkJFixAvr1g6QkDqqqgqVLoVs3cDo5qFs3GDUKnE4OqqqCt98m2m3ftJuMDuk0Wt27g8sFH34IY8ZwkNbg88GSJXDBBVQrKSlh+vTpXHzxxQwcOBDRuHy0cx1/yn8dU2sOx2m18ciA39ItvgVCNEk2G0ycCA8+CM8/Dz17gmnCJ59AdjaMHAkxMQgRrQyEEL9OuVDuSejy+6itjNhy9LYXgP5EHaWgdWsYOxZuvx2cTsjJgXXr4OGHITkZRoygWnJyMgkJCdx0000MHjyY3/72t6Snp1MftNbs3buX2NhY3B4PnH02PPssJCbCaadBOAxPPw07d8LMmeDxcJDVCnY7OBwcZBigFNFu24ZddB/YiUYrKQmuuAJuuAFcLjj+eNi1C+65BwwDzj6bana7nT59+nD77beTk5PDpZdeStu2bRHH3tK9W7h22cuEtcnh2CxW7j/+HPokt0GIJq1vX7j+enj9dXj/fVAKevSAc8+FjAxQCiGilYEQ4rBUzCS07ykwS6mtMW0/YnfZHtI8qUQVpSAuDq6+Gv71L7jxRigtBY8HeveGGTMgOZlqaWlpXHzxxXz77be89dZbXH311Zx99tmccsopxMTEUFfbtm1j7ty5bN++nUsuuYSuXbuizjgDrFZ4+214+mlQCtq0gZtugp49wWqlOduxZQ8nnT+YRstigenTIS4O7roLDhwApxOys+Hhh6FFC6o5nU4mTJhAv379eOutt7jkkksYPXo0kyZNwuv1Io6Nb4u2c+XS56kKhzgcq1Lc2WccQ9I6IERU6NEDevRAiObGQAhxeCoW5T4fXf4wtZXo9LNy58OkeW4i6lit0LYtTJsGEydCIAA2G8THQ1ISVcEgy5Yt44MPPmDSpEkMGTKETp06sXTpUubPn89bb73FlClTGDRoEFarlUiVlpayYMECXn75ZVq2bMn48ePJysrioPh4OPNMGDoUfD5QCmJiIDUVHA5QCh5/HDwecDj4r5Ej4bjjQCmiWbAqhN1po1FLSYHLLoOzzoJAAKxWiIuD1FRMYNOGDTzwwANcdtll9O7dm8zMTIYOHcrzzz/Pueeey5QpUxg7diw2mw1x9Kwv3cPUJXOpCAU4HAXcdNxoRmV0Q4hos3btWlq3bk1MTAxCNAcGQoiIKPfv0BX/Bl1BbXV0vwbmdLB4iToWCyQlQVISNdmUolWrVlRVVXHppZdy1llnMX78eEaPHk3Pnj354IMPmDVrFgsWLGDKlCl07NiRXxMMBlm8eDFPPPEEoVCICRMm0L9/f5KTk7HZbCilOCg2FmJj+UVt2/I/vF7weol2WmsaPaUgPh7i46lJaU1qaiqtW7fmoosu4uSTT+aKK65g8ODBdOzYka+++opPP/2UAQMGkJGRgTg6tlYc4KLFcygJ+InEjJyRnNW2N0JEo4cffpjLL7+c7OxshGgODIQQkbF4Ue7z0RWPUVtuw4+/5HFcCTNoTpRStGrVimuvvZZvv/2WefPm8fbbbzN16lRGjBjBpEmTGDhwIK+88grTpk1j9OjRnHPOOSQnJ1PT+vXreeyxx1i7di1jxoxhxIgRtGzZEqfTiVIKcXihQAi700ZT5/F4mDp1Knl5ecydO5exY8cyefJkzj//fE499VSGDBlCfHw81UpLS3njjTeYN28eW7duJTExkSFDhjBp0iQ6deqEOHK7/WVM/nwOeyvLicRVXU7gdx0HIES0Wr58OaWlpQjRXBgIISKmYi5C+58Ds5TaslbOAfNCsKTQXCilMAyD5ORkhgwZQufOnfnoo4944okneOONN7jsssvo0aMHWVlZ5Ofn8+9//5uFCxdy8cUXM3z4cBwOB7t372bevHm899579O/fn7///e+0b98ep9OJxWJBRG7Hlj2kt0mhKVNKoZTC6/XSs2dP2rRpw7Jly3jqqad47bXXuPbaaxk2bBjVioqKePLJJ3nhhRe45JJLyM3NJRQKsWzZMhYuXEinTp0QR6Yo4GPK4mfY7ismEue378fl2UMRQggRPQyEEJGzeFHuKejye6ktQ1Wiy+5DeW+juVFKYbPZyMjIYPz48fTv35+XXnqJ6667jry8PC688EKGDBlC165dee+993jwwQf54IMPyM7O5u2338bj8TBz5kz69OmDy+XCarUiam/bxt206pBGNFBKYbVaSUxMZPjw4Rx33HG88847PPDAA7Rr147WrVtTWFjI3LlzmT59Oueccw42m41qOTk5mKaJODLloSouXvwsm8r2EYmxmT35U4+TEUIIEV0MhBC1omIuRPvmgLmP2tL+V1DuCWDrRnOklMLhcNChQwemT5/OyJEjeeqpp5g0aRIXXnghY8eOZfz48cTGxvLQQw+xZs0apkyZwrBhw/B6vVitVpRSiLrZtXUfx4/sSTRRSmGz2UhLS2PChAmMGTMGpRSVlZUUFBQQCoUYM2YMTqeTQ5xOJ+LIVIZDXPbFc6wq3kkk8lpmc1vv01AohBBCRBcDIUTtKBcqZiq67HZqz0SX3YlKfIbmzGKx4HK5yM3NpXPnzixatIjHHnuM1157jREjRrB06VL69u3LtGnTSE9Px2q1opRCHJl924tIyUjgkPwPClAWRa8TuqIsiqZMKYXdbicpKYlqZWVlFBUVERsbS3x8PD+mlELUXdAMM+2rF1m+r5BIDEhtx6y+Z2FVFoQQQkQfAyFErSn3BLTvaQjvpLZ0YClUfYxyDKM5U0qhlMLj8XDKKafQt29fnn/+eZ599lksFgsnnngiGRkZKKUQ9SNQGcTutHHIZ68v5+OXl5KemULbri0548qT6ZybRVOllOIQq9WKx+OhoqKCiooKYmNjEUcurDV/WP4ai3ZtIBLHJbbin/3PxW6xIoQQIjoZCCFqT9lRMVegS/9CXeiyv6McvwEMmjulFEopUlNTufrqqxk+fDjz5s1DKYVSCtGwqnwBCtdup3Dtdr56/ztatE2mfY82nDP9FFp3akFT5XK56N69O6FQiIULFzJu3DgO0VpTTSmFiJxGc9OKt3hn+yoike1N47GB5+Gy2hBCCBG9DIQQdaLcZ6J9syH0PbUW2oL2vYByn4f4D6UU1VwuF06nE3H0+csr2Vywjc0F2/jy3ZWkZSaT3SeLM68eRXqbZJoSi8VC27ZtOeecc7jhhhsIBAIMHjyYyspKPv74Y8rKypg+fToicncXfMDL339NJNrEJjJ70ETibE6EaG7OPPNMUlNTEaK5MBBC1JEVFft7dPHl1IUufwDlHA0WL0I0NG1qlEURqdID5ZQeKGfDiu/5/M18Wmal0XNINqdNHU58ShxNQVJSEtdccw0tWrTg7rvv5sorryQlJYW8vDwuvfRSROQeWvMJT21YQiTSXXE8NWgSSY4YhGiOrrvuOoRoTgyEEHWmnHlgH4gOLKHWzCJ0+b2ouJsQ0WXpOyvYum4HjYmvrJLtG3fx4n0LOGTX93uJRNHuUop2l7L+6y0seOoTrnt0Cn1H9KAp8Hq9XHTRRUydOpVqWmuUUiilEJGZu/kr/rn2UyKR5IjhqcGTaOn2IkRzYoZNNi3bhNvrJrVdKjaHjXAozLol60hsmUhKmxSsNitCRCMDIcQRUZ4/oPePA0xqS/ueR7nGga0nInr0H3Uc/UcdR2Oy7usttGyXxsjzBnHIjk17YNEafo3FokjNTKZlVionX/AbBo7OxbBZaSoqKipYv349OTk5BINBtm7dSlpaGomJiYjDe33rSm7/9l0i4bE5eGLg+WTFJiFEc6O1Zm/hXvZt3Uf/s/uTkpnC9tXbWfHOCvqN60dyZjJCRCsDIcSRsXVBuU5H+1+l9kzM0r9hSXoJsCJEQ9m3vYjkjAQioZQipXUSLTKTGDS2DyPPH4zT7aApKiwsZMaMGTz33HMUFRVxzz33cMEFFzB48GDEr/tw51r+/PUbmFpzOE6rjUcGTKBLfDpCNEdWw0rOiTl8OPtDNn21CYXi6wVf0zqnNRldMjDsBkJEKwMhxBFTnmvRle+A9lNrwQK07wWUewJCNJT9u4rp2TGbX5OQ5qVlVirHDe3C2EvyiEuKRTRPX+zZzLVfvUxYmxyOzWLlwePHk5uUiRDNWVxKHN3zupP/Zj57C/cSDobJHpSNI8aBENHMQAhx5CypqJiL0OUPUhe6bBbKOQIsKQjREIr3lZGQEkdNsfExtGyXSu8TuzF26nAS0ryI5m3FgW1csfR5AmaYw7EqxT/6nMHgtPYIIaBtz7asfG8laxev5aTLTsKb7sVisSBENDMQQtQLFXMx2v8yhHdSa7oMXXY3ynsnQjSE8mIfMV43P3bq5BMYf92ptGibghDV1pXs5pIlc/GHgxyOAm7udRonZXRFCPEfZfvK0KYmNjGWKl8VZthEiGhnIISoH8qJir0OXXI9daH988F1Bsp+PELUNzNsYjUs/FjHXm0R4pDC8gNMWTyH0mAlkZjZ/STOaHMcQoj/CAaCrFy4ErfXTe6puWxavom09mm06toKq2FFiGhlIISoN8p1GvhfRgeWUnsaXfJHVPJboNwIIcTRsstfyuTFz7C/qoJIXNttOJM69EcI8X8KVxSyZ8seckfnktE5g9J9paz+ZDWJLROJTYpFKYUQ0chACFGvVNxf0ftOA0LUWngbuvx+lOePCCHE0bC/qoLJnz/DDl8JkZjUoT8XdxqMEOL/lOwuoeDjAjJzMmnRsQVOj5Neo3rxweMfsDl/M12GdMHusiNENDIQQtQvowMq5nfoiieoC13xb5RjJNhzaY5sNhtJSUl4PB6EOFJ2u52MjAysVis2m43U1FScTifiP8qCVVy85Fm2lO8nEme0OY6Z3UcihPgpZVG0y21H626tcXlcVEvOTCZ3dC5WmxWlFEJEKwMhRL1TsVeiKxdAeDu1Z2KW/glL0hugHDQ3SUlJjBw5ErfbjRBHKj09ncsvv5zY2FgcDgfjx4+nZcuWCKgMB7nsi3msKd5FJEa37s4tvU5DoRBC/FRcShw98npQU8f+HREi2hkIIeqfcqE8M9HFV1EnoS3o8odQnutoDrSpKd1Xir/UT3yLeDp27Ig2NQe2HyAUCBGfHo/dZUfUjTY1yqJoTrTWVPmqKC4spnt2dxwOB3a7nY5tO7J/2358dh/uODfNVdAMc9WXL5C/fyuRGJbeiTt6n45FKYQQQogfMxBCNAjlPAkcJ6CrPqEudMVslPMksOUQ7bTW7Fy/k3WL19FlSBc69OtA+YFyvlnwDcqq6DOmD3aXHVE3FWV+YuJcNCsayg+Us/SVpWR2z6TPaX0IB8Js/Gojqz5dxYmTT8Qd56Y5CmvNjOWv8vnuTUTi+JS23NvvbAyLBSGEEKImAyFEg1Fxf0Hv+xK0n9oLY5bMxJL0CigH0cxitZDZPZN9W/exafkmvKletq/djr/MT48RPYhLiUPUna/Uj9vjojlRFoU31UuPET1Y9voyWnRsgcVqYd2SdWQPyiY1K5XmSKO58Zs33j68KgAAIABJREFUeW/7aiLRIyGDf/b/LQ6rgRBCCPFzDIQQDceaiYqdhi77O3USWo8uuwsVdwPRzu11075ve1a8s4KlLy9FWRSturSiZeeWiCNT6Q/gcNlpbmwOG626tmLXhl0seWEJia0Scce56TqkK83Vnd+9zyuF3xCJjnGpPDbwPGIMO0IIIcQvMRBCNCgVcyG66n0IfE1daN+z4BiMcgwj2qVmpZLcJpnP5n5Gh34dyMrNwrAbiCMTrAzicNlojtxxbjr278jK91ZStq+MU6efit1tpzm6d9WH/HvjUiKRGZPA7EHnE293IYQQQvwaAyFEA7Ngibsdc/9Y0FXUnkaX/BGV/CZYUohmAX+AcDCMy+PC5rCBRtSDqsogdqed5igcCuMv8+OIdeCIdaC1pjl6ZuNSHl//OZFIc3l4cvAkUp0ehBBCiMMxEEI0PKMdKvYKdNk91Il5AF0yE5UwG1BEIzNssm31NvYW7qVjv45U+irZuGwjPUb0wOF2IOou4A/gcNpobrSpKd1byppP19C6W2ucHiffvPMNCS0ScHvdNBevFq7g79+9RyQS7G6eHDSRVu54hBBCiEgYCCGOChVzMbryfQgWUBe66jPwzUW5zycaFe0q4vsV3xOXEkfvU3qzafkmflj1AyltUmjTsw1KKRoVcz9YkmgKqiqD2J02mpsqXxUbl22ksrySvKl5+Mv8LH5+MWs/X0uvUb1QFkW0e3/HGv76zRtoDi/WcPD4wPNo70lBCCGEiJSBEOIosWLx3o657wwgRF3osjtR9n5gdCKaVJZXsjl/M1W+KnKG5eBJ9tAutx0Hth9gS/4WElok4E3z0ljoqkXo4qtQnmtR7gto7AKVAeISY2lOQsEQOzfsZNOyTfQZ04f4FvG44910HtSZNYvW0LJTS9I7phPNFu/ZxPXLXiGsNYfjtBo8POC35CS0RAghhKgNAyHE0WNko2IvRZc/RJ3oKsziq7AkvQIqlmihtcab4iWhRQKp7VKpFpcSR5ffdKFoZxHa1DQa4d3okhmg/ejS2yCwDBV3O1jiaKwClUEcLjvNigabw0bngZ3J6p1FNbvLTlbvLHRYY4ZNotmXe7/niqXPEzTDHI5hsXBfv3Pom9wGIYQQorYMhBBHlYq9gpKSD4mzrqFOQlvQxb9HJfwTUEQDl8dFpwGdqKlFpxa06NSCxsNEl8wAs4hDdOX76GABlvh7wdaLxqiqMojdaaM5MewGrbq2olXXVvxYbEIsPUb2IJp9W7SdK5Y+R1U4xOFYlOLO3HEMTe+IEEIIURcGQoijzIon9QF8u07FbQtQF7rqA6h4GhUzmUZFl0NoPTq4HuU+l2ijyx9CB5byP8I7MPdPQMVejoq9ArDQmAQrg9gcNkT021C6h0uWzKUiFOBwFHDjcadySqschBBCiLoyEEIcdVZbGz7cNZ4xredQV7rsHyhbDtj7cUyYe9DBAgiugtBGdGgDhDYDJtWU6wxQdqJG4Ct0+SP8sjC6/EEIfI2K/wdYkmkswqaJxWJBRLetFUVctPhZigN+InFdzgjOaZuLEEIIcSQMhBDHRGbLi1iw+QtOabeRugljFl+DJXk+WFJpMGYphDagQxshtAEdKoDgGtB+fpX2g7ITFcwDmMXXAmEORwcWo/efgcU7C+x9EeJo2O0vY8rnz7CnsoxIXJ49lCkdByKEEEIcKQMhxDHRK6MFt7w7huPSZtMypow6MfdhFl2FJWkuYHBkwhDajA5thNBGCBagQxshvA3Q1JquALw0fRpd8icw9xCx8C7MA5NQsZejYi8HrBxrSiGiVFHAx5TFc9jmKyYSE9r15aouJyCEEELUBwMhxDEztGNPZi4axr9OfhOL0tRJ8Bt06W2ouBuJmFkCoY3oUAGENqJDGyC4GnQl9Ub7iQa6Yja66iNqL4wufxAd+ApL/CywpHLMaESUKg9VMXXJXDaV7SUSp2X24M89RiGEEELUFwMhxDEzNqcr//z8S2Z/14upPb6mrrRvLhjtUe7z+akQhLagg6sgtBFCG9DBAjD30uC0nyYv+B26/D6OSOBLzH1jUN67UI6hCFFfKsMhLv/iOQqKdhCJ4S06c3vvsViUQgghhKgvBkKIY6ZtYjw56Wncn9+XnKQ9DMzYRl3p0tvQ5j4UDgitQ4fWQqgQCHMsaF2BogkzSzGLp4EOcsTMInTRVHBPRHn+AMrG0aaUQkSPkGlyzVcvsmxfIZHon5LFrL5nYVUWhBBCiPpkIIQ4psbkZFOwaze/XzScV8a+TJq7groJQ/nDaBoJ7acp04HPILyD+qPRvmfQwZVY4u8DawZHi9YaET1MrflD/mt8umsDkeiZ2Ip/9j8Xh9VACCGEqG8GQohj6rRu2dz10Wfs87u55qORPHPK69gsJk2e9tGUKeepkJiELr4OzL3Um+BKzH1jUN5bUM5TEaI2NJq/rXibBdsKiERnbxqPDZiA27AjhBBCNAQDIcQxlRTjpn+b1izeUsg3e9KZtaw/M49fQpOn/TR1yt4flfwmuuT36KpF1Btdji6eDq5PUXF/A+WiISmlENFhVsEHvPh9PpHIjElk9sDz8dpdCCGEEA3FQAhxzJ2Wk83iLYVU+9eqnvRM3cOorI00adpPVLAkohKeAN8z6NI7gRD1Rfvno4MFWOLvA6MTDcVqtRAOhxFN2yNrF/HkhiVEIt0Vx1ODJ5LsjEUIIYRoSAZCiGNuZOcO3PTuh/iDIar9+fMT6Jiwnw7xRTRZ2kf0UCj3BShbL8zi6RD+gXoT2oi5/yyU5zqU+wIagmE3CFaFEE3XvM3LeGDNx0Qi0eHmyUETyXDHI4QQQjQ0AyHEMRdjtzOsY3sWrF5HNV/QxrSPTuKF0a8Saw/QJGk/UcfWA0vyfHTJDejKBdQbXYkuvQ0C+SjvbaA81Ceb3SAYCCGapje2fstt375DJDw2B08MPJ92nmSEEEKIo8FACNEonNYtmwWr13HIpuIErvl4BI+NWIDVomlytI+opDyo+PvAfwK69K+gK6kvuvJddGgtFu99YOtKfTHsBsFACNH0fLhzHX/6+nVMrTkcp9XGIwMm0DW+BUIIIcTRYiCEaBSGtG9LgttFkc/PIZ9vz+SmJUO5ZfAnNDnaTzRTrtNRtm6YxddAaAP1JvQ95oFzUJ4ZKPckQHGkbA6DYFUI0bQs3buF65a9TFibHI7NYuX+488hNykTIYQQ4mgyEEI0CobFwqjsTsz7eiU/9tL6LvRpUcrY9l/TpGgfUc/oiCXpJXTpjWj/69QbHUCX3gZVX6K8d4DFy5Gw2QxCwRCi6Vh5YBtXLH2eqnCIw7EqxV19zmBIWgeEEEKIo81ACNFonJaTzbyvV1LTnxb15YQsB17LFzQZ2kezoNwo7z/APghdehNoH/VFV32A3r8Ki/cesOdSVzaHQaAyiGga1pfu4ZIv5uELBTgcBfyt1xhOzuiKEEIIcSwYCCEajd6tWtIuKZHN+w/wY2Ft4b6VZ3Fj3/0QWk+TYPppTpTrdJStJ2bJNRBcQ70J78Q8cD4q9nJU7BWAhdqy2Q18ZX5E47e14gBTFs+hJOAnEr/vPpIz2/RCCCGEOFYMhBCNyrjuXZj1yWJqml9QyB+GPYSzdAKY+2jstPajaGaMLCyJL6LL/oH2PUP9CaPLH4TAMlT8LLCkUBs2h0GgMoho3Hb5S5n8+Rz2VZYTiau7DuPCDgMQQgghjiUDIUSjcnr3rtz36RLCWvNj/mCQd9ZXcGaXxzEPTARdQaOmfTRLyoGK+wvY+6NL/whmCfVFB5ai941Bee9COYYQKafbQaUvgGi8DlT5mLJ4Dtt9xURiYvvjuazzEIQQQohjzUAI0aikeWIZlNWGRZu/p6ZXVq7izB7noBIeQRddDLqKRkv7aM6UMw9l64pZci0EvqbemAfQRReDeyIqbiZgcDiuWCf+8krqnVkMlnjEkSkLVnHxkmfZXLaPSJye2ZM/9jgJIYQQojEwEEI0Omf07Maizd9T0/IftrNlfxFZSf3BOwtdPA0I0yhpP82etSWWxLno8ofR5f8ETOqHRvueQQdXYIm/D6yt+DXuWCf+iirqlQ5gFl2EJfFZUE5E3VSGg1z2xTxWF+8kEiNaduHW3mNRKIQQQojGwEAI0eiM6NSeeJeTYn8lNc0vWMP0oQNRzpHgvQNd8gdA0+hoH6KaFRV7Fdj7oIuvB3Mv9Sb4Lea+sSjvLSjnKfwSZ6wDf1kl9UmX3QHBbyG0Gmy9EbUXNMNM+/JF8vdvJRIDU9txd98zsSqFEEII0VgYCCEaHZvVyqldOzM3fyU1vfrtKq4eMgCrUijX6aBL0aW30uhoP6ABhQBlH4BKfgNd8nt01WfUG12GLr4GXJ+g4m4G5aQmu8NGoCpIfdGV76N9c6mmAytQtt6I2glrze+Xv8qi3RuJRK/E1jzU/1zsFitCCCFEY2IghGiUzuzRjbn5K6lpd1k5X3y/lcFZbaim3JMgvBtd8QSNiwk6AMqB+P8sSaiE2eB7Bl16JxCivmj/fHRoPZb4+8DalgYT3oku/TP/FVyBqB2N5sZv3uTd7auJRLY3nccGTsBltSGEEEI0NgZCiEYpp0UanVOTWbdnHzW9snIVg7PacIjyXA+6Au2bR6OifaAciB9TKPcFKNtxmMXXQHg79Sa4GnPfOFTcTSjXWH5CUQ/CmMXTwSzhEB34GoWojbu+W8grhd8QibaxScwedD4emxMhhBCiMTIQQjRaZ3Tvyh0fLqKmD9ZvoqSyEq/TyX8oVNyNgAXte5ZGQ/uABMTPsPXEkvQauuQP6KqPqTe6Al0yAwKLUXE3gXJzkOaI6bJ7Ifg1P2HugfAusKYjDu+B1R/zr41fEIkWbi9PDZpIkiMGIYQQorEyEEI0WqfldOEfH39OyDT5sapQiLdXr2NC7578H4WKuwGUga74F/VHAZo60X7Er7DEoxIeBd8z6LK7QAepL9o/Hx1ciSX+fjCyOVK66jN0xWx+jg6uQFlPRvy6OZu+5JF1i4hEkiOGJwdNpIXbixBCCNGYGQghGq2kGDcndMjig/WbqOmVlauY0LsnP6VQnj+BcqHLH6F+aFB20AFqTfsRh6NQ7gtQtlzM4ukQLqTehLZg7j8b5bkeMKgzcx+6ZCZg8rOCK8B5MuKXzd+6kju+fZdIeGxOZg86n6zYJIQQQojGzkAI0aid0aMbH6zfRE3f7dzNuj376JyaTE0qdhpULkCHCqkXOgDKCbqS2tDah0JExJaDJXk+uuSv6Mo3qTe6Cl16G7pyGJijweKldkx08Qww9/JLdGAFCvFLFu5Yw1++fh3N4bmsNh4bOIFsbzpCCCFEU2AghGjUhnXIIiUmhr0VFdT02nermTl8CDXpsrvRoULqla4EDCBExLQPUQsqBhU/C/y/QZfeCNpPfXHYt+LfPg5X+t1g602kdPmj6MBiflWoAHQAlB3xU0v2bOb6Za8Q1prDcVoNHh04gV6JrRFCCCGaCgMhRKNmtVgYnZPN01/mU9PrBWu4fthgDIuFQ3Tl++iKJ2kYIUDxH5rD0n5E7SnX6ShbD8ziaRBaR32Iiw9Qun8vDtt5qNjLUbFXABZ+VWA5uvxBDksHILQWbD0Q/+ebAz9w5dLnCZhhDsewWLi339n0S26LEEII0ZQYCCEavbN6dOPpL/OpaX+Fj083bWF4x/YcFFqHLpkBaBqO5j8sgMmv0j5EHRntsCS9jC77B9r3DEfKkxCitMhGSnoVuvxBCOSj4v8BlhR+llmCWXI9ECYSOrgCZeuB+I+1Jbu5ZMk8/OEgh2NRir/njuOE9E4IIYQQTY2BEKLR65iSRE6LNAp27qaml1YUMLxjezBLMIuuAO3n6DA5LO1HHAHlQMX9Bez90KV/ArOUuvLGBykrtnGIDixB7zsN5f0HyjGYn9Lo0j9CeAcRC6wA9yQEfF++n4sWz6EsWMnhKOCvPU/l1FY5CCGEEE2RgRCiSTizRzcKdu6mpk83bmF7STEtzeshvJXD04DiqNA+xJFTzpEoWzfM4msh+A114YkPUbTPxk+Y+9FFU8A9ERU3EzCopn3PoCs/oDZ08BsUYqevhMmL57C/qoJIXNstj/FZuQghhBBNlYEQokkY3a0zd364iMpQiB8La80ry57kypxFREZx1Gg/op5YM7AkzUOXP4wu/ydgUhue+CCFG9z8L432PYMOrcHivQfMveiyf1Br4e1g7gVLCs3V/qoKpiyew05fCZG4tPNvuKjTIIQQQoimzEAI0SR4nU5O7tKJ+d+tpqYXCiq5tKsFw2LSqGg/oj5ZUbFXgb03ungGmPuIlDchSGmxjV8UWIa5fwxgBx2gLnRgJcqZR3NUFqzkosXPsqV8P5H4bbu+TOt6IkIIIURTZyCEaDLO7dWd+d+tpqa9Pjef/tCG4W220KiYRYj6p+yDUEmvYpZcB4FlRMLjDVJWavCrzGKOSHAFOPNobvzhIJcsmcfakl1E4rTWPfhLj1EIIYQQ0cBACNFk9G7Vki5pKazZvZeanl/XleFttlAryo3yXIcufwDMEuqbrnwbbN1Q7vMBK6IeWdOxJD6DLn8YXf4wEObXGDZNKGChIengChTNS9AMc9XSF/jmwA9E4sQWnbk9dywWpRBCCCGigYEQokk557ju/O29j6hp8fbWbCvz0MpTRmQUyns7ynkKynEiZvE0CH5LvdJBdOltaP98LHE3gK03oj5ZUbFXgb0fuvg6MPdwTAW/A8KAleYgZJpc/eWLLN6ziUj0T8ninr5nYVUWhBBCiGhhIIRoUk7LyeauDz/CH+InTK14aX1Xpud+SSRUzCUo5ykcZM3AkjgXXXoz2v8S9S64CnP/BJTrDFTsNLCmIeqPsh+PSn4dXfIHdNUijhnth+A6sHWlvmmt2bVrF4WFhZSXl1NaWkowGKSkpIRqFosFr9eLw+HA7XaTnJxMZmYmiYmJNARTa2bmv8Ynu9YTiR4JGTzU/1wcVgMhhBAimhgIIZqUWP0pp7Zby8vrs6np1fXZXNVrGYbF5Nco+yCUZxo/oRwo721g74cu/StoP/XLRPtfRle+jnKdgYqdBpZkRD2xJKESngDfM+iyu0AHORZ08BuUrSt1FQ6HWbduHfn5+SxfvpyCggK2bt3KDz/8QFVVFbXl8XjIzMwkKyuL4447jtzcXHJzc2ndujV1pdHcsnIBb28rIBKd4lJ5fOB5xBh2hBBCiGhjIIRoOkLr0SUzGJ/t4eX12dS01+/mw61ZnNR2E7/ImoGKvxew8nOUayzK1gWzeBqENlHvdBDtewHtfxsV8ztUzGRQMYj6oFDuC1C2XMziayC8laMuuBI4j9pYs2YNCxYs4J133uHLL7+kvLyc+lJWVsaqVatYtWoVb731FoekpaUxdOhQRo0axahRo0hLSyNS96z6kOe3LCcSmTGJzB40Ea/dhRBCCBGNDIQQTYNZgll0BWg/3ZP95CTtpWB/CjU9v64rJ7XdxM9SbiwJj4Elnl9ldMKSNB9d/iC64kkgTL3T5ejyB9G+OaiYi1DuSaCciHpgy8GSPB9dcgO68m0Osdo0wYAFm92koejAChSHt3z5cubMmcObb77Jli1b+DVKKdLT02nbti2ZmZl4vV7i4+MxDIO4uDiqaa0pLi4mGAxSXl7Orl272Lp1K4WFhRQVFVHT7t27efHFF3nxxRdRSpGbm8u4ceOYOHEirVu35pc8tu4zZq9fTCTSXB6eGjyRFGcsQgghRLQyEEI0ASa65DoIF3LIOdmrKVg8lJqWbs/g+1IvbeNK+CmF8t4ORiciohwoz/Uo53DMkpkQ2kKDMIvRZXejfc+iYqaiXGeCciGOkIpFxd8L/qHo0htB+4lPCFJabJCUGqDBhAvBLAJLAjXt2bOHZ599lqeffpqCggJ+jsfjoXfv3uTm5pKbm0vv3r3JysrC4XBQV2VlZaxbt478/HyWL19Ofn4+BQUFBINBqmmtWb58OcuXL+eGG24gLy+PCy+8kHHjxuF0Ojnkuc3LuG/1R0Qiwe7myUGTyHDHI4QQQkQzAyFEo6fLZqGrFvFjo9tt4K5lAygP2PkxjeKldV2Z0fcLfkzFTEU5T6HWbL2wJL2BLn8QXfEkEKZBhHehS29Glz+Icp+Pck8ESzziyCjX6ShbDmbxNcQnl1G0z0FSaoCGo9HBlSjHCRxSWFjIPffcwxNPPIHf76emdu3aMXr0aMaMGcOQIUOw2+3UJ4/HQ58+fejTpw+XXHIJ1Xw+H0uWLOHNN99k/vz5bN26lWqmafL+++/z/vvvk5KSwuWXX84111zDZ2U/cOu37xCJWMPBE4POp70nGSGEECLaGQghGjVduRBdMZua3LYgo9tt4Pm13ajp1Q3ZTMv9CrslTDVlH4TyXEOdKQfKcz3KORyzZCaEttBgzCJ0+YPoiidRrrNQMVPA2gJxBIwOWJJeJqHFLRTv/5AGF1wBjhPYsGEDt956K8899xzBYJAf69ixIxdccAETJ04kMzOTo83tdpOXl0deXh73338/y5cv59///jfz5s3jwIEDVNu7dy9/+9vfeOCBB+h/19WYSYrDcVptPDpwAt3iWyCEEEI0BwZCiMYrtB5dcj2g+Tm/zV7F82u7UVNRpZOFW9pxavsNYM1Axd8LWDlitl5Ykuajy+5B+54FwjQY7UP7nkH7n0M5x6BiLgKjA+JXmAdAxYBy8D+Uk8Q2Z1C4/CvgAA0p7F/On2/5A/fddx+BQIBDbDYb5557LlOnTmXQoEEopWgs+vTpQ58+fbj77rt54403eOihh1i0aBHVioqKeGfq32h72TiceT35JTaLlfv7nU1uUiZCCCFEc2EghGiczBLMoitA+/klnRP30zNlNyv3plHTC+u6cmqH7VgSHgNLPPVGuVBxf0a5f4suvQUdWEyD0kG0/1W0/1Ww90a5L0A5RwAG4qd0cCX4XkQlPARY+akwXsd9HNiraWgVJV8ya9ZGwmEOcjqdTJ48mRkzZtC2bVsaM4fDwdlnn83ZZ5/N559/zu233867776L1prvH36NpJ17SZmYR01WpbizzziGpHdECCGEaE4MhBCNkIkuuQ7ChRzO+OzVrNybRk1f7WrJptCNdDQ60SCMdqjEp6HqI3TpzRDeQYMLfI0OfI22pKBc41Du88DaAvH/hXejqz6Ekpko752AhUN0+cPEe5dRvD+LhuaJVXTt5GDVuiCTJ0/m5ptvpkWLFjQ1gwcPZsGCBeTn5zN9+nQ+++wz9r/2OWZVgLQpo0ApqingpuNGMyqjG0IIIURzYyCEaHR02T3oqkVE4pR2G7nzy4GUBBzU9PKaRP6YQYNSjhNRyQPQFbPRFY+BDtDgzL3oisfRFU+iHEMg5gKUfQCgaNbMPVTT/tdBxaLibuSgwDJ0+cPY7SbBgIWj4ZxxnRk++lEGDBhAU5ebm8uiRYt48803ueqqqyhc8BVmRRXpV45FWS38rkVvzmrbGyGEEKI5MhBCNCq6ciG64gki5bSGGNNhPc+u7k5Nr363mmuGDsJlM2hQyoWKvQrlPBVddiu66nOOjjC66mOo+hhttEe5Tkc5x4I1nWYpvJtDtG8uWJJQ7omYJTOAMEfTn39/Kso7gGgyZswYhg0bxowZM3j00UcxQyHsLZO4feF99HrpJfLy8hBCCCGaGwMhROMR2oQu+QOgqY3fZq9i7uocNIofK/FX8kbBGsb36s5RYbRDJTwFVR+hy+6B0HqOmtAmdNksdNm9KHt/cJ2Ocp4EykWzYe7mx3T5A+jKtyG8g6NNB79BEX1iY2N55JFHOP3007nwwgvZtXgV1UaNGsWDDz7IpZdeihBCCNGcGAghGgezBLPoUtDl1Fb7+CJ6p+0mf3c6NT2z/BvO6dUdxdGjHCeiHCegK99Dl90L4e85ekx0YAkElqBL/4pyDAPXWJRjKGAlmunwHv5HaBPHRGgLmKVgiSManXTSSXzzzTeceeaZLFmyhFAoxGWXXcaOHTu4+eabEUIIIZoLAyFEI2CiS66DcCF1dX7X78jfnU5NG/bu54stWxmYlcnRZUE5R6GcI9C+V9AVD0F4N0eVrkRXvgOV76AtCSjHUHCejHIMBaxEHXM3h2O1aYIBCza7ScMy0cGVKMdviFbp6el89NFHTJ48mXnz5lHtlltuQWvNLbfcghBCCNEcGAghjjlddg+6ahFH4qSuw2mR72FnaRk1PbP8GwZmZXJsGCj3eJTrDLT/VXT5/WDu46gzi9D++eCfj7bEoxwngPNklP03oGw0eToIZjGHk5AYoKTIRnJaFQ0uuAIcvyGaORwOnn32WVq1asVdd91FtVtvvZWYmBhmzpyJEEIIEe0MhBDHlK5ciK54giOh7IMwvNcwoXc+sz5ZTE0fb9jM9weKaJuYwDGjbCj3eJTrVHTFM2jfHDD3c0yYxWj/fPDPR1viUY48cOah7ANAuWiSzD2A5nDadPBxYK+N5LQqGlxwJc2BUoo777wTq9XKHXfcQbU//vGPJCQkcMkllyCEEEJEMwMhxLET2oQu+QOgqTNrBir+HsDKub168PDiL/EHQ/yYBubmr+TPI07gmFOxqNjLUTEXoSsXoCsehtD3HDNmMdr/MvhfRisHypYLjoEox3Aw2tNkhHcTiT5D9rN2RRxHgw6uQGFCUQls2wYlJRyUkABt2kBMDCjFUVdZCTt3wu7dEAyC2w0tW0JqKlitsHMnlJZCRgbExnJQeTls2wbx8ZCezs+5/fbbCQQCzJo1i2pXXXUV3bp1Y/DgwQghhBDRykAIcWyYJZhFl4Iup86UG0vCY2BJoJrX5WR0t2xeWlFATS+vXMXVQwbgcThoFJQd5Tod5RqDrlyALn8CQms5pnQVOrAEAkvQZXeDkYVynACOE1C2PqBsNFba3E0kDJumQ045R4X5/9iDD/isykPx47/nnPO+ebN3AoQsIIEQCCGDMAUEQRAEBYsDFET/BxY2AAAgAElEQVTF1kUtVVt7q1avtLe9otWigigiiFDALchQCBIII8wAARIgLBMyyXrnOf+GfvCvXLSQHfN8vxegaDd8mAUbN8L58yAEBATALbfAjTeCtzcIQZOpqYGsLFi+HI4dA7sdvLwgJQUmTIDYWFizBrZsgUcegV69uOjYMXjlFbj+epgyhR/z17/+lbNnz7J06VIcDgd33HEHWVlZBAcHI0mSJEk/RxqSJDUDHaN8FrhOUncC4fsiaLF839TUJFbsOYDBD1XZ7Xy47yB3p/amZVERlrEIy1iw78Komodh+5oWwXkcw3kcqt7BEO4IU28wJ4M5GWHuA2i0GK4zXC2Lu4vGI0AJAMUfFH/Y+BmsyIDbboMxY0DXYelSePllCA6GAQPAbKZJGAbk5sJbb4GqwuzZEBYGO3bAwoVw4QI88QT1IYRg/vz57N+/nwMHDnD69GnuuusuvvzyS4QQSE2oqgpOnoRz58DhAC8viIyE9u1B02g2ZWVw8iQUFoLLBX5+EB0NQUGgqnDkCDidEBkJnp5cVFoKx49Dhw7Qrh2SJEktiYYkSU3OqHgJw7aJ+hCeDyAso7lcTHAgaVHhbDtxisu9t3MPk1MSUYSgRTInI8xvIhz7MaqXYFi/AMNKi2DUYNgzwJ5BLUN4I8ypYO6LcOsLWldA0GxqPqaxWG0GZ791cqHKjYSEgaimAFBCQA0G4QuKD0IJATUElEBA5aLycnj3bhg8GMaPh6AgLnrkEdi2DdasgZ49ISiIJmG3w759kJ8P//M/kJDARTfcACUlsHIl7N5NfXl6erJq1SpSU1MpLy9n3bp1LF68mClTpiA1kQsXID0dPv8czp8HwwBNg+7d4ZZboEcPUBSaXHExfPEFbNoEZWVgGGA2Q2oqjB8P0dHw/vtQVQUzZkCXLlx05AjMmQO33w7jxyNJktSSaEiS1KQM6zqMqvnUhzAPQHjP5MfcndKbbSdOcbmTpWWk555gSJdoWjRTT4TvnxE+T2PUfIFR/S44j9GiGBUYtq/A9hVGBSA8EaZeYE4GUzzClAKKD03BsH6B4cyhToQvwnIdKO1BDQbhC4oPQgkhc+dxBg0ej8OhY7FY2LdvH1pQDFft5EkoKoKEBPD35ztmM6SmwvbtUFNDk6mshOPHwccHevTgO6oKERHg4wMnToCqQlER7NgBJSVclJsLxcVcrZiYGF5++WWmTZtGrVmzZjFmzBj8/f2RGpmuw+7dsGQJREbCr38NQUGQlQXvvguLFsFvfwuhoTQpXYcNG+Cjj6B/f5g4ETw9YeNGeO89UFW45x4kSZJaGw1JkpqOMxej/EnAoM7UMITfS4DKj7k+phMR/n7kl5ZxuXd37GZIl2haBeGN8JiE8LgNw7YFqt/HsG0EXLQ4RhWGPQPsGdQyUMEUhzD1BnMSwtQL1I40ONcpjIo5INzBqOGaGeWgVyF8ZwIalzidTu574A4cDp1aTz75JDExMVwTux2EAJMJFIUfcHcHhwN0nVq6riOEQAhBo3G5wOEAkwk0jR8wmUBRwOEAVYXjx2HxYvDx4aILF6C4mGtxzz338M4775Cenk5hYSFPP/00c+fORWpkNTWwYwfY7TB1KsTGctHQoVBQAB99BLt3w4030qQuXIBNmyA8HH7xCwgP56Lx4+HIEdi7F3JzkSRJam00JElqGno5eumDYFRSZ8IDxf9NUPz5KYoQ3JXci9nrN3G5LcdPcqSwiNiQIFoPBeE2CNwGIVxnMGqWY9R8BK5ztFwucBzAcByA6vcw+BfFF6H1AFMPMMUjTD1A7Ui9qOEowevQi0aC8zh1Ydi+gvLfIXz/AijUWrZsGQcOHKBW586deeqpp7hmQUFgNsO5c1BTAx4eXORywfHjEBwMZjO1tmzZQmRkJGFhYaiqSqOwWCAoCCoqoLAQ2rfnIl2H4mKoqYHAQKiqgl69YPp0iI/nogMHYP58roUQgrlz59K7d28cDgdvvfUWTz75JJGRkUiNqKwMzpyBoCDo3JnvqCqEh4OXF5w6RZMrKIDCQujfH9q35zuaBjExkJ0N589z0bFj8MknEBrKRbm5UFCAJElSS6QhSVIT0DHKZ4HrJHUnEL4vghbL1fhFYg9e3byVSpudyy3etZc/jRpGq6SGIbx+jfB6DMOeCTUfYljXglFNi6eXY9i3gH0LtQz+RfFFaD3AFAdaLEKLAa0LCDeuiauA+jBqPgbhhfB5BsMw+Otf/8olL774IhaLhWsWFga9esHmzdCtGyQkgGHA4cOwaxfceSd4eVFryZIltGvXjqFDh5KQkICfnx9CCOrLMAxcLhcOhwN3Ly/o3h1Wr4ZPP4UJE8DTE779FrZvB02D+HjYvh3MZvDzg6AgLvLzA7OZaxUfH8+9997Lm2++icPh4OWXX2bOnDlIjUjXwTBAVUEIfkBRQAjQdZqcroNhgKqCEPyApnGRYXBRQQHs3Ak+PlxUWAjl5UiSJLVEGpIkNTqj4iUM2ybqQ3g+gLCM5mp5ms2M79mdxTv3cLmPDxzk8SED8HO30HopCHM/MPdD+DyLYV0LNR9i2DMBnVZDL8ewbwH7FmoZ1FJBi0RoXUGLBS0GoXUGNQKEif/DqASjmvoyqpeAEsDq9M7s3buXWp06dWLChAnUickEd90Ff/87LFsGhw+DYUB6OsTEwMiR4OVFrccee4yFCxeyYMEC0tLS6Nu3L927d8disSCEoC6cTicFBQXk5OTg7u5O3759EfHxMHw4rFsHNTUQGAhHj8LRozBmDHTtCtu305CeeOIJFixYgNPpZP78+Tz99NMEBQUhNRJvbwgKggMH4Nw5CA/nIl2HggKoroaQEJpcYCD4+sK5c1BSAsHBXORyQX4+aBr4+XFRairccw9ER3PRrl3wxhtIkiS1RBqSJDUqw7oOo2o+9SHMAxDeM7lWd6f05v1de9ENg++rcThZsfcA9/VN4WdBeCDcx4P7eITrHIb1E4yaz8F5mNbJBc48DGcesJpaBrVUUDsitGjQOoEaDVoUAoWGYlS+yrncEC554oknUFWVOktJgVmz4NNPYd06EAJ69oRJkyA8HKvNxv79+4mIiOCFF15gy5YtvPfee+zfv59BgwaRkpJCly5dUFWVq6XrOuXl5ezfv59vvvmGEydOMHLkSC4KDYXJkyE0FDZuhAsXICwMpk2DQYNA0yAiAqqqwMeH7/j6Qu/eEB7OterUqRO33nory5cvp6qqisWLFzNz5kykhqPrOjabjVruPj6QmAi7d8OqVXDbbeDjA8eOQXo6+PpCQgK1rFYruq7j4eFBY6iqqkJRFNzd3SEwEFJT4euv4csvYeRIcHOD/fshMxO6doWoKC4ym8HHB/z9ucjbGzQNSZKklkhDkqTG48zFKH8SMKgzNQzh9xKgcq2iAvwY2CmS9NwTXG7xzj1M65OEqij8rKjtEZ4zEJ4zwHUSw/olhnUNOA7Q+rnAdRLDdRJsG7nEoGFNnVjIps0+fLTG4O6776beEhIgIYErqS4vZ9myZYSEhDBgwABSUlJISUlh1apVfPLJJ+zevZvrr7+epKQk2rVrx08xDAOr1crhw4fZtm0be/bswc/PjwceeIDk5GSEEFwUHAx33gl33skVDRsGw4bxA9HR8Oij1NVDDz3E8uXLqbVixQpmzpyJ1DAuXLhAVlYW+fn5pKSk0L17d0hNhTNnYOtWOHsW3N2hqAgMA269FaKicDqdZGZmkp2dzcCBA+nWrRtms5mGYLVaOXz4MJmZmSQkJJCWloaiqnDjjVBaChs3wqFDoGlw9iy0bw833QShoUiSJLU2GpIkNQ69HL30QTAqqTPhjuL/Jij+1NU9qUmk557gcmcvVLD+SC4ju8Xws6VGIjwfQHg+AK6zGLZ1GNbVYN8D6EhXJgQsmBNKUnJn3N3daUz+/v7cdtttLF68mPfee4/Dhw+TkpLCHXfcwfDhw1m0aBGLFi1i3759DBgwgMTERLy9vbmc0+kkPz+fbdu2kZmZSXV1NWPHjmXkyJG4ubnR3AYOHEj79u05d+4cGRkZnDp1ivDwcKS6q6mp4dChQ6Snp5Ofn09kZCRubm5cFBoKEyZARAQcOAA1NdCjB6SmQs+eoKoYDge1Tpw4wYkTJ+jZsycDBw4kMjISRVGoC5fLxfHjx9m0aROHDx/Gw8ODpKQkvhMVBXffDZmZcOQIOBzQrx/07w9duoCiwHXXgd0O/v58p0MHuOUW6NoVSZKklkZDkqRGoGOUzwLXSepOIHxngxZLfQzsFEmnwADyiku43DvbsxjZLYY2Qe2A8LgH4XEPuAowbOvBthHDngmGFemHVBUevvsEhu0bhNtAGosQgrS0NBITE1m7di0rVqxg3759XHfddaSkpPDkk09y4MABFixYwFtvvUW/fv3o168f3bt3x2Qyoes658+fJysri23btnHixAkGDhzIhAkTCAgIoKVQFIVbbrmFuXPnYhgGn3zyCQ899BDNYemufRRcqOQXST3o4OtDa+N0OsnPz+err75i3759eHt7c/3119OvXz8CAwP5TlAQjBoFo0ZxJSaTiQEDBtCxY0c2bdrE7t27OXToEH379qV///4EBQVxtQzDoLCwkM2bN7Nr1y4cDgcJCQkMHjyY8PBwFEXhO2FhcOut/Kjrr+f/CA+HSZOQJElqiTQkSWpwRsUcDNsm6kN4PoCwjKa+BDAlJZHnvvyKy2WdPsuuU2dIDg+jTVFDER53gcddCMOK4cgCWwaGbT0485D+TREujLJHEAGLwNSTxuTm5sbYsWNJS0tj5cqVfPjhh+zdu5fBgweTnJzM3/72N7788ks++OADsrOzGTx4MGlpaZw+fZr09HQOHjxI165d+eMf/0jnzp1picaOHcvcuXOptW3bNh566CGaQ2FFJa9/k8mbW7bTNyqcSUk9uaFbF1RFoTnpuk7RySLO5pwlKjEKv3Z+6LpOYV4hBXkFRCVGYfG1sH37dj799FNUVSU1NZWBAwcSFRWFEIJrpWkanTt3pkOHDhw+fJjNmzfz9ddfs2fPHgYPHkxycjJeXl78lPLycrZv386WLVu4cOECXbp0YdCgQcTGxuLm5oYkSdLPnYYkSQ3KsK7DqJpHfQjzAIT3TBrKLT278/KmDMqtVi43b+tO3gwPo80SFoS5P5j7I7xngfMYhm0T2DZhOLLAsNOmGVXopfehBCwBrQuNLSQkhF/+8pcMGTKE9957jyVLlnDgwAH69evHsGHDSEtLY+nSpfz9739n4MCBVFZWYhgG9957L4MGDUJRFFqq1NRULsnKyqK5OFw6tXTDION4PhnH8wnx9mJczzjuTOlFB19vmoNA4HK4OHP4DNVl1fS5tQ+VpZUc3nIYW5WNTsmdqCWEIDIyksGDB9O1a1dMJhP15e7uTu/evenUqRO7d+8mIyODFStWsGPHDkaOHEm3bt0wmUx8n9VqJTs7m6+++or8/HzCw8MZMWIEPXv2xNvbG0mSpLZCQ5KkhuPMxSh/EjCoMzUM4fcSoNJQPMwm7kzuxetbMrncxmN5HCo4T1xoMNK/aF0QWhfwnI4wrODIxnDsAlsGhmMHGA7aHL0UvfRelICloIbRFOLi4nj++edJT0/n/fffJycnh7S0NPr27cvEiRPZv38/Z86c4eabb2bUqFF4eHjQ0gUGBhIREUF+fj45OTlUVVXh6elJU3PqOpcrrKhkfsYOFmzdSd+ocCYl9eSGuBhUIWgqQhEERQQR3Tuaw1sOc3TbUexWO6VnS0kZm4J3oDe6rpOcnExiYiJeXl40NF9fX6677jq6detGZmYmu3fv5u2336Zbt26MGDGCqKgoDMPgxIkTrFmzhoMHDxIcHMzo0aNJTk4mODgYIQSSJEltiYYkSQ1DL0cvfRCMSupMuKP4vwmKPw3t7pRE3snchdXp5PsM4J3MXfzPzTciXUZYwJyMMCeD5wMIowrDvh3s2zDs28CRA+i0Ca5v0UumogS+D0owTUFVVYYOHUpqaiqrVq1izZo1ZGdn0717d5KSkrjlllsIDQ2lNUlMTCQ/Px+Xy8WRI0fo3bs3Tc2l6/wY3TDIOJ5PxvF8Ivz9+EVSD27tFU+gpwdNwWQxEd4jnJIzJWSuysQ3xJfwHuG0j21PLUVRcHd3pzEpikK7du246aabSEhIYMuWLezatYucnBzi4uKw2+3k5eXh7u7OoEGDSEtLIzw8HFVVkSRJaos0JElqADpG+SxwnaTuBMJ3NmixNIZATw8m9Ipnya69XO6zgzk8Nrg/Yb4+SD9BeCLchoLbUAT/YlSD4xCGYxfYd2E4skAv52fLdRK99D4U//dA8aGpeHl5MWXKFAYPHszSpUspKCjgySefpDVq3749l5SUlNAcHC6dq5FfWsbfNnzDKxu3MqxrZyYl9aRfdASCxuXp70lo51B2r96NxctCTFoMmlmjqWmaRnR0NKGhofTo0YP09HS++OIL3N3dGTFiBH379iU6Oho3NzckSZLaMg1JkurNqJiDYdtEfQjPBxCW0TSm6WnJfLB7Py5d5/ucus4bGdt5ftRwpGsgPMCcjDAngycIXOA4guHIAsduDPtucJ3iZ8VxCL1sBor/2yDcaSpCCCIjI3nyySeprKyktfLz86NWl6df5FcZ+yBjHyZVxd1k4hJPswlNVbjEx2LhErOq4G4ycYm72YRJVbnEx+KG4N80RcHDbOYSd5OGWVM5cO5broXD5WLNwSOsOXiEqEB/JibGMzGxB/4e7jQGa4WVkjMlmCwmVLNKyZkSfEN9aS4eHh706tWLkJAQjh49iq+vLxMnTsTLywtJkiQJNCRJqhfDug6jah71Icz9Ed4zaWwd/XwZHRfLp9mHudzKvdnM6JdKRz9fpLpSwRSHMMUBdyH4F6MSHDkYzgPgyMZwHABnLmDQatl3YZTNRPi/AQiakhACb29vWis/Pz9qCUXlEofLhcPl4pILVis/VE5LcaK4lL9t+IZXN21jVPdYbk9OoHfH9jQUl9PF2SNnOXPoDCljUqiuqOZg+kECIwLxCfKhuQgh8PX1JTAwEE9PT7y8vJAkSZL+TUOSpLpz5mKUPwkY1JkahvCbA6g0hRn9Uvn8YA66YfB9Tl3njYwdvDB6OFIDEl5gTkaYk6kl+Be9HMN5ABzZ4MjBcB4BVx4YDloFJRg87gIE0rXRNI2LVJXWzOZ08tG+g3y07yBdQ4O4PSmBm3vG4eVmpj5Kz5aSuyOXgLAA4q+Pp/hUMbtX7+ZQ+iFSx6WiqAqSJElSy6IhSVLd6OXopQ+CUUmdCXcU/zdB8aepxIYEMaJrF9YcPsrlVu3L5sH+qXT080VqRIovwjwAzAOoJajlBGcehvMYOA6B8xiGMwdcZwGdlkJYRiN8ngPFF+nalZSUgBAIIfi5yCko4rnVX/HXDZsZ06Mbk1MS6RoaxLWquVBDXlYe1eXVJI9Jxt3bnZBOIUQlRnEs8xinu5wmIiECSZIkqWXRkCSpDnSM8lngOkndCYTvbNBiaWqPDOrH2pxj6IbB9zl1nTcydvDC6OFITU0DLRahxYJlNLUE/2I4QP8Ww3kUnMfAdQqcpzCcR0AvoskIT4T3UwiPSUh1V1ZWhlAUEIKfE1UIenfsQEp4GOH+vtSFyWKic0pnIhMiCQgLoJbZYqZzSmeCI4Px8vdCkiRJank0JEm6ZkbFHAzbJupDeD6AsIymOcQEBzKiaxfWHD7K5Vbuy2ZanyQ6BwUgtQDCBGo4Qg0Ht+u5RPAvegnGhacxrBtoVKYkFL+/gdoRqX6KiopACGwF5wiPjsbNzY1aNXYHdpfOJRVWKwYtX9fQIMb17M7YHl0J8faiPjSzRmDHQC7n4euBh68HkiRJUsukIUnSNTGs6zCq5lEfwtwf4T2T5vTIoH6szTmGbhh8n0vXeTk9g1dvHYPUwikBYDhpPCrCczrCeyagIdXfvn37MJxO8uf+jayiIgICAvhPnLpOtd3OJTUOJ3ani0suWG2AQS2nblBlt3OJ1eHE7nRySYXNzsLMLI6dL6auQry9GNujK+N6dqdraBCSJElS26YhSdLVc+ZhlD8JGNSZGobwmwOoNKeY4EBu7BbDF4eOcLm1h4+y+8w5eoe1R2rZDFcBjeFcoUJYt8VgTkZqGJWVlRw9epRaUVFRBAQEcDU0RcHHYuESHwv18nl2DsfOF3MtLJrGkNhOjOsZx+AuUaiKgiRJkiTV0pAk6ero5eilM8CopM6EBcXvNVD8aQlmDu7P2pxjOHWd7zOA2es3seye2xFILZpeSENbvKKCWc9VcPZcLzSkhrJ37150XadWYmIizcWl61wNVQj6dYpgXM84bujWBXeTCUmSJEm6nIYkSVdBxyifBa6T1J1A+P4ZTPG0FFEB/kzq3ZMlu/ZyuT1nzrHhSC7DYzsjtVCGA/RSGoziw5//4cbTfzpKrU2bNjFs2DCkhrF69WouSU1Npbk4XDo/pUtwIDfGxTAhMZ4Ovj5IkiRJ0k/RkCTpPzIq5mDYNlEfwvN+hGU0Lc0jg/rx8YFDVNrsXO6vX29maJdoVEXh+8prrLz6zTbG94ijR/tQpGaiFwIGDUGY+yF8/4JvyEogg1orV65k2LBhSA1j5cqVXDJ+/Hiai1N3cbkQby9ujIthfEJ34tuHIEmSJElXS0OSpJ9kWNdjVM2jPoS5P8L717REAR7uTOuTzKubt3K548Wl/HPvAW7vnUAt3TD45MAhXly/ibIaK/HtQujRPhSpmeiF1JswI7x+g/CcCggmTJjAo48+iq7rrFq1ildffRVVVZHqZ//+/Rw+fJha8fHxxMXF0Vycuk4ti6YxJLYT43rGMbhLFKqiIEmSJEnXSkOSpB/nzMMofwIwqDM1DOE3B1Bpqe7rm8wHu/dxvrKKy72SvpWx8d3IKy7l2TUb2H+ugEtyi0qQmo/h+pb6KCsLIaDzPDB155J27drRr18/tmzZQkFBAZ999hnjxo2juTkdTvau2Utkr0iCIoIwDANbtY1D6YeI6hWFfwd/WrL58+dzycSJE2lOqREdmd43heHduuBu0pAkSZKk+tCQJOnK9HL00hlgVFJnwoLi9xoo/rRk7iYTDw/syzNrNnC54qpq7ly0nMOF5zH4odyiEqRmpBdSNwIst7FySSz3P9+dy02fPp0tW7ZQ6y9/+Qvjxo2j2Rlw7ug5zh09x8hfjURRFY5tO8aBrw8QHh9OS1ZcXMzbb79NLU3TuOeee2hOT48cgiRJkiQ1FA1Jkq5AxyifBa6T1J1A+P4ZTPG0Br/o3ZP3du7hWFExlztUeJ4rOVZUjNSMXIVcMyUQ4fsiwm0oNusSrmTy5Mk8++yz5Ofns3XrVjZv3sygQYNoTqpJJW1CGp/+7VNyMnII7RTKnjV76DWiF0ERQbRkr732GlVVVdS67bbbiI6ORmp9zGYzI0eOxGQyIUmSJP1/GpIk/R9GxRwM2ybqQ3jej7CMprVQheDxIQP41YpP+DcDEPyU02Xl2JxO3DQNqRnohVwL4TYI4ftnUIL5KSaTiUcffZRZs2ZR6/e//z3p6ekIIWguQggCwwNJuimJ7R9uJ7RzKD7BPnQb2I2WrLCwkFdeeYVLfvvb3yK1Tpqm0adPHyRJkqQf0pAk6QcM63qMqnnUhzD3R3j/mtamV4d2BHp4UFxdDQj+E5dhcLKkjNiQIKRm4CrgqggLwvs3CI+7AcFPsTqdVNhsjLxtEi8tWkxZdTV7yir49evz6JmUQoXNRoXNRoXNTqXNRoXNRmJYBx4fMgBB4xJC0G1ANzKWZZCzJYfbX7gds7uZlmzWrFmUlpZS66abbqJ3795IrYfL4WLHxzsoPFFI2oQ0QqNDcTlcbPnnFsq+LSPt1jSCIoKQJElqyzQkSfr/nHkY5U8ABnWmhiH85gAqrYVT11m4PYt/fJNJld3OtThWVExsSBBS0zP0Av6TC64YtpfN5OzJQCpsmVTabFTYbFTY7Jw5ksdXb79Phc1Ghc1Ghc2Ow+XiEs9Jd+PJv31RVs0XX6VzueTwMH41IA1B0yg+U4xqUvEK9KKyuJKWLD09ncWLF1PLzc2Nl156Cal1UTSF2H6xFJ8q5tDGQwS0D+DEnhMU5hUS0y+GwPBAJEmS2joNSZL+TS9HL50BRiV1Jiwofq+B4k9rkXnyNH9a+xVHzxdTF7nFJUjNxFXIjxO4LHcxdlEgBZUHuJLAigqKvy2grrqGBPHGbTfjbtJobIZhYKu2kbkyk+je0fi182PHJzsIjQnFN9iXlqa0tJRp06ZhGAa1nn76aWJjY5FaFyEEAWEBdEnrQvbX2ez4aAclZ0vwb+9PbFosQggkSZLaOg1Jkv5FxyifBa6T1J1A+P4ZTPG0BucuVPDnDemsPnSE+sgtKkFqBkYlGFVckdoBxfd/UMx9uD0pk1fSM2honQIDePfOifhaLDSV7I3ZVJZUMuy+YagmlVPZp9j9xW6um3wdiqrQUui6zpQpU8jLy6NWXFwcTzzxBFLr1Tm5M4V5hWxZtoVOSZ1IHZeK2cOMJEmSBBqSJGFUzMGwbaI+hOf9CMtoWotqu4Mj54u4KgYguKJjxSVIzcBVyJUIyyiEz59A8aXW5ORevLVtJ1V2Ow0l0M3MwjsnEODhTlM5f/I8u7/YzcA7BuIb6ovu0kkZm8KmdzeR3yufqMQoWooXX3yRzz//nFqenp4sX74cNzc3pNZLMSl4B3lj8bbg38Ef/zB/JEmSpH/TkKQ2zrCux6iaR30Ic3+E969pTToHBbBy6p38YfU6PsvO4ScJftSJ4lJchoEqBFLTMfQCfkB4IbyfRHhM4vt83S1M6t2TtzN30RBcVZUcfetdzg7tR7ukJJqKoigkDE+gS58u1FJUhbC4MJLGJKGZNVqKd999l2eeeYZL5s6dS48ePZBaL8Mw+PbYt+Tvz8cn2IeygjJyd+bStX9XFEVBkiSprdOQpLbMmYdR/gRgUFNGePYAACAASURBVGdqGMJvDqDS2niYTbw0bjTJHcOYvX4TdpeLa2V3uThVWk5UgB9SE3IV8B1TIorf30CN4Eqm9UnivZ17cLhc1Idw2Dmz4HVsBecYNWoUmzZtolu3bjSFoIgggiKC+D7NrNHj+h60FMuWLWP69Onouk6thx9+mLvvvhupdbNWWsnZkoPZYuamR2/iYPpB8nbmERIZQkDHAIQQSJIktWUaktRW6eXopTPAqKTOhAXF7zVQ/GnN7kruRWJYex5Z9Rmny8q5VrnFxUQF+CE1Ib0AUBFev0J4/QpQ+TGh3l4Mj+nM6sNHqCsPs4mXx93ILz9YyOGCcxQWFjJ8+HC+/PJL4uPjaeuWLVvGlClTcLlc1Lr99tt5+eWXkVo3l9PF0cyjlBeW02NoD4Iig+g6oCs7PtxBTkYOqeNSMVlMSJIktWUaktQm6RjlvwXXSepOIHz/DKZ4fg7i24WwatqdzPpkNem5J7gWuUUlDIvpjNSEhBdK4HIw9eSnHCwoZGFmFmtzjlJXbprGGxPH0TcqnPXr13PdddeRl5fHmTNn6NevH8uWLWPUqFG0Va+88gqPP/44uq5T6+abb2bRokWoqorUul04f4HzJ87TPqY9UYlR1ArtFEqnlE6cPniagtwCOsZ3RJIkqS3TkKQ2yKiYg2HbSH0Iz/sQltH8nPi5W5g/6Rbmb93BnI1bcBkGVyO3qASpaQmPu/gpu06dYd7WnXx9LI/6UIXgrzffSN+ocGqFhYWxfv16brjhBnJzc6moqGDcuHG8+eabTJs2jbbE6XTy8MMP8+abb3LJmDFjWL58OSaTCan182/vz7D7hnG57oO7031wdyRJkiTQkKQ2xrCux6iaR30Ic3+E9+P8HAnggX6p9GwfyuMfr6a4qpr/5FhRMVLz0w2DjceOM3dLJvvOfkt9CeCFm27gxm4xfF90dDSZmZnccsstbN68GYfDwb333svq1auZN28efn5+/NwdP36cyZMnk5GRwSX33Xcfr7/+OpqmIUmSJElthYYktSXOPIzyJwCDOlPDEH5zAJWfs35REXx071089uHnZJ0+y085XlKKAQik5uBwufj8YA5vZOwgr7iEhvK74YOZkBDPlQQGBrJu3TqmTZvG0qVLqfXPf/6T7du3s3jxYgYOHMjP1aJFi3jooYeorKyklhCCP/7xjzz77LNIkiRJUlujIUlthV6OXjoDjErqTFhQ/F4DxZ+2INTbiyWTb2POpgzmb92BwZVV2uwUVFTSztsLqelU2e2s2JvNW9t2UlBRSUP6zdCBTO2TxE9xc3Nj8eLF9O7dmz/84Q/Y7XZOnjzJkCFDmDFjBs8//zwBAQH8XBw8eJBHH32UDRs2cEm7du145513uPHGG5EkSZKktkhDktoEHaP8t+A6Sd0JhO9sMMXTlqiKwqyhA0no0I6nPvuSSpudKzlWVEw7by+kxldSXcOSXXtYtGMP5VYrV8ukqtwUF0t2QSFHzxfzY6b2SWJGv1SuhqIo/Pa3v2XYsGHceeed5OTk4HK5mDt3LsuXL+eFF17g/vvvR1EUWqvy8nKee+45XnvtNRwOB5eMGTOGBQsWEBISgiRJkiS1VRqS1AYYFS9j2DZSH8LzPoTlJtqqEV27EBscxKOrPuNw4Xkul1dUwsDoSKTGc6b8Au9sz+Kfe/ZT43BytTzMJib26sF9fVNo5+3F6kNHeOzDz7mSO5IS+N3wwVyrpKQkdu3axR/+8Adee+01nE4nRUVFPPjgg7z00ks89dRTTJ48GZPJRGtRVFTEq6++yquvvkppaSmXBAYGMnv2bO677z6EEEiSJElSW6YhST9zhnU9RtWb1Icw90d4P05bFxXgxz+n3s7zazeyfM9+vi+3uASpceQUFrFg204+PZiDS9e5WgEe7tyV3Iu7U3rj627hkpHdYogK8KeSc3zfzT268czI6xHUjaenJ3PmzGH69Ok89thjfPXVV9Q6cuQI9957L88++yyPP/4499xzD35+frRUubm5/OMf/2DevHlUVVVxiaqqPPDAAzz//PMEBgYiSZIkSRJoSNLPmguj4i+AQZ2pHRF+rwAqErhpGi+MHk5KeAeeWbOBGoeTWseKipEa1q5TZ5i3dScbj+VhcPXCfH2Y2ieJXyT2xN2kcTlFCO7rk8TL/zzEJdfHdOLPY0aiCEF99ejRgw0bNrBixQqeffZZsrOzqZWfn8/MmTN56qmnuOWWW5g2bRrDhg1DURSaW1VVFStXruTtt98mPT0dwzC4RAjBqFGj+O///m8SExORGl5ZjZUVew4wvV8KAkmSJKk10ZCknzUVJXAJeunD4NjDNRMWFL9XQfFF+qHxPbvTNSSYR1d9xsnSMnKLSpDqzwC+PprHvK07yDp9lmsRGxLEfWnJjI3vhqoo/JRhEVG84WOhVt/IcF655SY0RaEhTZw4kQkTJvDJJ5/w4osvsn37dmpZrVaWLl3K0qVL6dChA6NHj2bUqFEMHz4cHx8fmsqpU6dYs2YNq1evZt26dVRWVvJ9iqIwceJEfve735GYmIjUOM5XVnHvklUcKSyiwmrj10MHIEmSJLUeGs3I5XKRl5dHdnY2+fn5fPvtt5w9e5aCggKKi4vRdZ0LFy7gcrmopaoqPj4+KIpCYGAgoaGhhIWF0a5dOyIjI+nevTudOnVCURQk6TtKCErAYowLz2HU/JOrJxC+s8EUj3RlcaHBfHjvXfz+87WsOXyU0uoa/D3caVJZWTBvHnz9NTgckJICjzwCaWlgNtNaOHWdz7IPM3/bTo6eL+ZaJHXswAP9Uhka0wnB1bGWW0mNjSSggzuv33YzbppGYxBCMG7cOMaNG8fXX3/NW2+9xapVq7BardR64pcOKqo+5OPly/jlDDtd4/rQp08fUlJSSElJoXPnzgghqC+Hw8H+/fvZuXMnO3fuZOvWrRw4cIArCQ0NZfLkyTzwwAPExsYiNZ68ohKmv7+Ks+UV1Hrjm+34ulu4t28ykiRJUuug0YRyc3PZvHkz6enp7Nmzh0OHDmG1WmlI7u7uxMXF0atXL6677joGDhxIly5dkNo4YUb4/jeYEjAq/gSGg/9EeN6HsNyE9NO83My8cusYFu3YTX5ZOf4e7jSZjAz4y18gIgIWLQIPD1iyBJ55Bp56CoYNA1WlJatxOFi+5wDvZO7i7IUKrpYAhnTpxIz+qSR17MC1qiirYlCPLvx+Yh88zWaawtChQxk6dChlZWUsXbqUzG/e5pH7yrnEAM5+e5o1G47wjzlzydhZg7e3L9HR0URGRhIZGUlkZCT+/v54eXnh4eGBm5sb7u7u1NTUUFVVhd1up7S0lPPnz5Ofn8/JkyfJz88nNzcXu93Oj7FYLIwcOZJp06YxevRoTCYTUuM6cK6A+9//kJLqGr7vf9al42uxMCExHkmSJKnl02hE1dXVrF27lo8//pi1a9dy9uxZGltNTQ1ZWVlkZWXxzjvvUKtDhw6MGDGC8ePHM2LECNzd3ZHaJuExCaHFoJc9Avp5foww90N4P450dQRwT2pvDJqQwwErV0JwMDz4IMTFcdHTT8Njj8GaNRATA9HRtESVNjsr92UzL2MH56uquFqaojCme1fu75dKTHAgdVVRUklQsC++7haamp+fH7/85S95cIoDo/I1LhFAWDuN6Xf5MP0uH2pqDHbstfLusuN8smY/H5e5aEjR0dHccMMNDB8+nBtvvBFvb2+kppFxPJ+Hln9Ctd3B5QzgmS820DcqnDA/HyRJkqSWTaOBuVwuPv/8c9555x3Wrl1LdXU1ze3s2bMsXLiQhQsX4uHhwahRo5g6dSqjRo1CVVWkNsachBL0IXrpw+DYw/+hdkD4vQyoSNdG0IROnYK8PBg8GLp0AUXhIi8vSEuD9HQoKIDoaFqS81VVfJC1j4Xbd1Nhs3G1zKrK6LhYHhrUl0h/P+qrorSK0MggmpNhXc9PcXcXXNfXnev6umO8FMLJ004+XlPJqs8qydhZg65z1UJCQkhMTCQlJYWUlBRSUlIIDw9Hanrrc3J5fNUX2JxOrkQVgmdHXU+Ynw+SJElSy6fRQM6cOcO8efNYsGABZ86coaWqrq5m5cqVrFy5ko4dOzJ9+nRmzJhB+/btadEc2WCKR2ogSghKwGKMC89h1PyT7wgLit8/QPFHauEqKsDlAh8fMJv5jhAQEAAOB9hstBT5pWUs2rmHZbv3Y3M6uVpebmZuTYhnRr9Ugr08aSgVpVXE9I6i2bjOgPMwV0sIiArXeOx+Px673495ywdzKNcDq9VKTU0N7u7ueHl54ebmhq+vL/7+/kRERBAREUF0dDTu7u5IzW/prr38afXX6IbBlZhVlf+9dTQjunWhrtbn5HJdlyjMqookSZLU+DTqKT8/n//93/9l3rx5WK1WWpPTp0/z3HPPMXv2bCZNmsQzzzxD586daYmMmqVQ7UT4vgBoSA1AmBG+/w2mBIyKP4HhRPjOBlM8Uivg6QmKApWV4HSCycR3yspA08BsprkdLChkYWYWn2YfxmUYXK1gT09uT+rJ1D5JeLu50dAqyqrw9vOkuRjWddSZ4suDj74BqEitx/yMHfxtwzf8GB+LG69PGkdKRBh1tf3kaR5a/gmBnh7c2iueu1J70d7HG0mSJKnxaNTR+fPnefrpp1m4cCEOh4PWzG63895777Fs2TKmTZvG888/T3BwMC2NUbMKXOcQ/q+B8EZqGMJjEkKLwXDsQFhuQmolIiIgPBwOHIDjxyE2lotsNti+HQIDISSE5rLr1Bnmbd3J18fyuBYR/n5MSUnk9t49cdM0GktFaRVefh40F8O2gboSbkMAFal1MIC/rEvnnW27+DFBXp68dcctxLULpj7ezcyiVnFVNfMzdrAwM4sbu8cwY0AfYoIDkSRJkhqexjXSdZ3Fixfzm9/8hqKiIn5O7HY7b775JsuWLePZZ5/l4YcfRlVVWhLDvhWj+A4U//mgtkdqIOYkhDkJqRUxm2HiRHjhBXjtNXjwQfD0hPnzYd8++K//gqgompJuGGw8dpy5WzLZd/ZbrkX30BCm9unN2B5xqELQ2JwOF5pJpVnoZWDfSZ25DUFqHVy6zh8+W8+qvdn8mI5+vrx9161EBvhRH6fLyvn6SB7f53C5+HT/YSb0iicmOBBJkiSp4Wlcg8OHDzN58mR27drFz1lZWRkzZ85k8eLFLF68mK5du9KiOI+gF9+G4j8fTHFIUps1eDBYLPDaazB0KNjt0LcvzJ4NAwaAqtIUHC4Xnx/M4fWM7RwvLuVaJHXswAP9Urk+phNNSQhBczFsXwMu6kZFmAcitXw1DiePrviU9GMn+DExIYG8feethHh7UV/vbMvCZRhcLiYkkL7REUiSJEmNQ+MqLVq0iF/96ldUVVXRVuzcuZPevXsze/ZsHnvsMVoUvRC95A6E398RbtchSW1WWhqkpdEcqux2VuzN5q1tOymoqORqKUIwuHM0Dw1MI6FDO9oc23rqzJwCii9Sy3bBamXGBx+TdeosPyY1IozXbx+Ht5sb9XXBamPV3myuZFpaMgJJkiSpsWj8B1arlWnTpvHBBx/QFtXU1DBz5kx27NjBggULcHNzo8UwqjFKZ4DPcwiPXyBJbZHT6UQIgaIo6LpOLUVREELQWIqrqnk/ay+Lduyh3GrlaplUlZviYvnlgDSiA/1pLtUVNXj6uNMsDCuG7RvqSrgNQWrZzldWMf39VeQUFPFjro/txJwJN2HRNBrC8t37qbY7uFygpwdjenRFkiRJajwaP6G0tJTx48eTnp5OW7dkyRLy8vL45JNPCAoKouVwYVz4L9ALEF4PA4Imd+4cbN4Me/aAzQYdO8LQoRAfDyYTzWL3bli7Fs6eBYsFEhJg/Hjw9ET6efn9739Pp06dmDJlCvPmzcMwDCZNmkRYWBgN7XRZOQt37Gb57v1YnU6ulqfZzIRe8dzfN4VQby+aW+GpEoI7BtAcDPs3YNRQV8JtCFLLdaq0nHuXrCK/tIwfMy4hjtljR6AqCg3Bpess2bGHK7kzpRdumoYkSZLUeDR+xKlTp7jhhhvIyclB+retW7cyePBg1q1bR4cOHWg5DIzKV8F1BuH7AqDRZE6dgmXLIDsbOneGwEDIy4OjR+H222HgQFAUmtTWrfDSSxAZCZ06gdUKH30EOTnwX/8FJhOSdK2eX/s17+/ai8swuFpBnh7c0yeJO5MS8HZzo6UoOFVMaHggzcK6gTpTo0DrjNQyZZ8r4P6lH1FcVc2PubtPb34/cgiChrPm0FHOlldwObOqcntyApIkSVLj0riCoqIiRo4cSU5ODk1FURQiIiLo2LEjHTp0oH379lgsFry9vdE0jVpOp5OKigpqamo4d+4c586d48yZM5w8eRJd12kKBw8eZMSIEaSnpxMQEEBLYtSsAte3CP9XQXjT6Fwu2LIFMjNh9GgYMwbc3eHIEXj9dfjiC4iOhvBwmozDAS+9BD4+cO+90KkT1NRAXBzMnAnXXw9DhiBJ1yrYyxOXYXA1wnx9mNoniUm9e2LRNFqawlPFJAzsStNzYdi+pq6EZSRSy7T95Gl+uexjKm12rkQAvxk2kPv7p9LQ3s3M4kpuTogjyNMDSZIkqXFpXKaiooJRo0Zx6NAhGlNcXByDBg2if//+9OjRg7i4ODw8PKiL6upqDh06xP79+8nIyCA9PZ2cnBwaS3Z2NqNHj2b9+vV4eXnRkhj2DIziO1D854PankZVXg579oC/P9x4IwQHc1GvXpCWBunpkJcH4eE0mZMnYfNmWLECunYFVQWLBUaPhn/8Az7+GIYMQZKu1eTkROZv3UmFzcaP6RoSxPS0ZMbGd0NVFFqqcyfOM+KuATQ5exboJdSVsIxAank25OTy61VfYHM6uRJVCJ67aTi39e5BQ9t9+ix7z3zLldyd2htJkiSp8Wl8j2EYTJkyhZ07d9LQ3NzcGDZsGOPHj2fs2LG0a9eOhuLh4UFycjLJyclMnTqVWufOnePTTz/lo48+4quvvsJms9GQMjMzmTp1KitWrKDFcR5BL74NxX8+mOJoNOXlUFICgYEQEsJ3VBU6dADDgJISmtT/Yw8+AKOs78ePv7/PPbeSkB0SCARIAgkZQNgbBBFBEAIKAlURFQda66qt2mqR2lZx1FEHiBMQB4gyRATZhL3CFBQIAYJAyL4kd/f8i/23v5ZerGRcLsnn9Tp+HFwuSEgATeNfdB3at4fMTISojACrhRvSUpmRsZVLdWzWlMk9unBF61gUvq+0pAyr3YK3GaVfU2mmSDCnIHzL/F17eXzR17jcbjyxmExMTx/C4LatqQlvZ2zHk16xLUiIDEcIIUTN0/k3r776KgsXLqQ6JSYmMnnyZG666SbCwsLwliZNmjB58mQmT57M2bNneffdd5kxYwYHDx6kunz66ae89tpr3HXXXfgc9xnc58ehgl9CWftSIzQNlAK3G9xuMJn4F5eLH2kaF7lcLi4ymUzUhMLCQvz8/NB0HdxucLn4L2VloOsIUVm3dOvEe1t3Uup0ooD+8bHc0bMLHZs1pS5RSlEbDMc3VJayXgUohO+YsWELz61Yh4FngTYrr40dQeeYaGrCybx8vj54BE8mduuIEEII79D5/3bt2sXDDz/M5bjxxhvp0KEDnkRFRdGtWzfi4uKobeHh4Tz44IM8+OCDHDlyhIyMDHJycvBk9+7dvPvuu/xcDzzwAL179yY1NRWfYxRj5N4BgX9A+Y2h2oWGQlQUfP89HD8OcXH8yOmE777jR40bc9HChQspLS3lyiuvJCIiguqSl5fHokWLCAsL44orrsAaHw82G2zeDEOHgq7zo9JS2LABhgxBiMoK9/fjuvbJFJeVc3uPzsSHh1HX5J7JIzgiEK9zHgLXUS6XASj+zjYI4RsM4Nmv1/DWxm1UJNzfj5njR9E2KoKa8u6mHbjcbi7VKiyE3nEtEEII4R06f2cYBnfffTcOh4PLMWzYMMaMGUNdEhcXR1xcHBX55JNPePfdd/m5HA4HU6ZMYc2aNfgmF0b+78Cdgwq4l2rl7w/dusG+fTB3LkyYAEFBsHEjrF0LaWnQpg0X+fn5sXLlSnbu3MmQIUPo0qUL/v7+VFZ5eTnr1q1jwYIFuN1uJk6ciMlkgshIGDMGXnkFgoKgUycoKID33oMLF2DMGISoiicGD6Au+35fNq2SovE2w/E1laH4Oy0YZemCqH0ut5vfLf6aT3fupSLNgoOYNWEULUKDqSkFpaV8sjMTTyZ274imFEIIIbxD5+8+/vhjNmzYgKictWvXMn/+fEaNGoVvMjAKXwbXaVTQVMBEtdA06N4d8vNhxQp47DFQCgwD2reH9HQICeGinj17EhwcTEZGBnPnzmX9+vWMGDGChIQEzGYzl2P//v3MnTuXkydPkpycTI8ePUhJScFkMoFSMGUKvPkmvPkm/2IYMHUqJCYiREN2dF823Qa3x9sMx1IqS1kHAiZE7Sopd3LfJ4tYffh7KtI6Ioy3JowislEANWnO1l0UlpZxqSC7jRGpbRFCCOE9ellZGb/5zW8QVfPII48wfPhwzGYzvsoo+Rhc2aiQl0E1olqEhsKQIRAXBydOQHk5hIRAQgI0bUpRSQlff/01FouFHj160KpVK3bu3MnGjRt58cUX6dixI9deey1NmzZF0zR+ysmTJ5k/fz67du2iefPmXHfddXTp0gV/f39WrFiB0+lk8ODB2OLj4Z57YN8+yMsDXYfoaEhLA5MJIRqyk9+doUnLcLzKeRScB6k021WI2pXvKOXODxeyLSubinSIbsIb40YSbLdRk0qdTt7bvBNPxndqj91sRgghhPfoCxcu5Pvvv6da7d8PX38N334LmgaJiTBsGDRpAiYTXldUBBs2wOrVcP48hIVBjx5wxRVgt1MdDh8+zKJFi0hPT8eXGWUbMM6NQwuZAaYmVIugIOjSBbp04VK6y4VSis8++4x169aRnp5Onz59aN26NVu2bGHr1q3s37+fsLAw7HY7FTEMg0WLFpGVlcVVV11Ft27daNq0KXv27GHOnDnk5uZy/fXXo2kaP4qJgZgYGqI/LFuJ0+3mps5ptI4IQ4h/ZxgGmknDmwzHEipNC0JZeiNqz9nCIm6ds4ADOT9QkStax/Lidddg03Vq2vxd+zhbWMSlrLrOL7q0RwghhHfpb731FpUVFBTEf9m1C157DSwWiI0Fw4CMDDh0CO6/H5o1A6XwmsJCWLIEPvoIUlIgORnOnIG5c+HkSZg4EXSdfwoMDKSyZsyYQXp6Oj7PeQj3uevRQmaAuS01yWKx0KtXL4KCgti0aRNvvPEGiYmJjBw5kmHDhpGcnExwcDBms5mLDhw4wLJly9izZw9ut5vmzZtz9dVX06FDB7p160bv3r2JjY3lzJkzvPDCC+zbt4+EhASuueYa0tLSMJvNNHR5DgeL9h5k3o49pERFMjYtlRGpbbHpOqJhK3OUY7VZ8DbD8SWVpaxXgTIjakdWbh63zpnPsfMXqMi1qW3507VXoWsaNc1lGLydsQ1PRndIJjzAHyGEEN6lL1++nMqIiYmhX79+/AenEz74ABwOGD8eOnYEw4AdO+B3v4Ovv4brr4eAALzCMCA7G955B7p3h1tvhbAwOHMGFiyABQugUydIS+Of+vTpQ7NmzThx4gSX66uvvuL48ePExMTg89xncJ8fjwr+K8ral5qilCIsLIzevXsTHx/P1q1b2bhxI88++yx9+/blqquuIjw8nIt27tzJq6++itlspn379oSGhnLu3DlWr15NTEwM7dq1o7CwkIULF/Lll18SHh5Oeno6nTt3JjIyEpPJhPhPmadzyFyaw7PfrGVI2zbc2KkDbRqHIxqm/VuOkNC5FV7lPArOA1Sa/RpE7dh76gy3z13AuaJiKnJT1zR+e1U/NKXwhmX7DnHs/AUuZVKKid06IoQQwvt0t9vN5dJ1nTlz5mCz2fgPJ0/C5s0wcSJ06gT+/vyoVy9o1w4yMmDwYAgIwCvKyuDAAcjKgpdfhuhoftS8OfTrB2vXwoYNkJbGP9ntdubMmcOAAQNwOp38lGUfRhPb0sy/CywfjfuHQKqdcZ5qZxRhXLgLAv+Iso+kJplMJqKjowkLCyMxMZFNmzaxdu1aAgMDGThwILquM2fOHMrKyhg/fjxpaWnY7Xby8vLIyckhODgYpRTvvPMO3377LQMGDKBz587ExcVhNptRSiEqlu8oZd6OPczbsYeUqEjGpqVybUpb7Gad+sDlclFaWorL5ULTNIRnmRu/ZfAveuNNhmMJlaaFoSzdEN63+dgJ7p73OQWlpXiigCl9u3Nvvx5408yN2/BkSHIbWoQGI4QQwvt0KuHee++lV69e/JecHHA4oHlzsNv5F5MJWreGlSuhrAyvKS+HkyfBZoMWLfgXpaBRI2jcGLKzuVSfPn24++67eemll/gp0U11YluY+U954MqjzjDKMfIeAddJVMDd1DSbzUZCQgJNmjShbdu2+Pv7c9HJkyfZvn07119/PV26dCEgIICLGjduTEREBP+UmppK9+7dadu2Lf7+/iilEJcn83QOmUtzmL5qHempSYzpkEJ8eBh1kWEY6LpOVlYWmzdvpri4mMaNG6NpGuK/nTudR3jTELzJcCylspTtasCE8K6Vh45w/6dLcDideGJSiieHDmRMx1S8ad13x9h7KgdPJnXvjBBCiNqhc5kCAwP53e9+h0dmMz9yOsEw+A+lpaDroBQXlZeXo+s6Simqm8vlori4mEaaBmYzuFzgcoGu8y9uNzidoOt48vvf/55Zs2ZRWFhI/WdgFL4IruOooGmATk0LDAykc+fOOJ1ONE3j7NmzlJaW0qxZM/z8/Ph3Sin+qUePHpjNZjRNQ1RNXomDdzZv553N20mJimRsWirXpiRiN5upC0pKSjh16hRms5lVq1Zht9tJS0sjLi6O4OBgxH9yOd2YdA2vZD3JLgAAIABJREFUch4F50EqS9muQXjXZ7v38egXy3G53XhiMZmYnj6EwW1b420z1m/Bkz5xLUlu0hghhBC1Q+cy3XDDDYSEhOBR8+YQHAyZmdC1K4SG8qOyMti2DVq0ALudi6ZNm0bPnj3p168fNpuN6uByucjOzmbx4sWkpKTQp3t3iIuDsjLYvh169OBHbjecPQvHjkHfvngSFhbGmDFjmDVrFg2FUTIf3D+ggl8C5U9NU0phNpu5yGw2YxgG5eXlGIZBRaxWK7XNZRhsOpqFrzpbWMzlyjydQ+bSHKZ/s45rUxIZm5ZKm4hwfFFZWRnnzp1j+/btLFiwAIfDwW9+8xv69u2Lv78/wrMje44Tm9IcbzIcS6g0UxRYOiK8573NO3h62SoMPPOzmHnl+uH0im2Bt+05mUPG0Sw8mdyrC0IIIWqPzmUaPnw4FQoJgeHDYdEiiIiAq68Gtxs++QSOHoVbboGgIC5q1aoV7733HitXruSmm24iMTERk8lEZRiGQX5+Pp9//jlLliyhTZs2DBs2DHQd4uOhe3d48UWwWiEuDg4dgnffheBg6N+figwfPpxZs2bRkBilazHOjUULmQGmJnhL8+bNCQsLIzMzk549e9K4cWP+yTAMLlJK4QvKnC4mzv2U+ijP4eD9rTt5f+tO0qKbMDYtlSFtE7CbdWqby+XiwoUL7N27ly+++IJjx44xZMgQhg8fTnh4OOKn7c04TOcrU/Amw7GUylK2IYCGqHkGMP3rtczcuJWKhPv7MWN8OklRjakNMzZswZPUppF0bdEMIYQQtUfnMnXs2JEKaRpcfz0YBixfDp9+yo/8/WHKFOjaFSwWLhoxYgTx8fGsW7eOJ598kh49ejBhwgQiIiLQNI2fq7y8nPXr1/POO+9gsVhIT0+nU6dOREdHg1IQGQl33QUffABPPQVOJ5jN0LIl3HwzNG1KRTp37kyD5DyE+9z1aCEzwNwWbwgKCmL48OF88sknBAcHM2zYMMLCwjhy5Ag7duxgyJAhREVFIbxnR/YpdmSf4o/LV3NtSiJj01JJbByBtxmGQUFBAUePHmXVqlWsX7+ehIQEpk2bRuvWrVFKIf63rEOnGHnnQLzGeRScB6ksZbsWUfNchsHvF3/NJzsyqUh0cCCzxo+iZVgIteF47gW+PnAYTyb36ooQQojapXOZwsPD+UmRkTB+PPTsCbm5oBSEhkJ8PPj7cz43lxkzZtC/f3+6dOlCbGwsHTp0YPny5UyZMoWRI0cyatQo7HY7Sikq4na7OXDgADNnzuTMmTP07duX7t27Ex8fT3FxMXPmzCEsLIwhQ4ZAu3bwy19CVhY4HGC3Q9Om0KIFaBoViYiIoMFyn8GdeyNayDtgTqGmaZrGiBEjuGjt2rUsXboUXdcJCwujZ8+emM1mRO0oKC1l9rZdzN62i3ZNo7izZ1eubBOHNzgcDk6ePMmGDRv48ssvCQoK4v7776dTp06YzWbEz1Ne6sRsM6OUwlsMxxIqTW8N5mREzSpzuXhw/hK+OnCYisRHhPHW+FFEBQZQW95cvwWXYXCpVmEhXJkQhxBCiNqlc5lKS0uxWCz8pLAwCAvDEz8/P4KDg/nzn/9M+/btueWWWxgwYADx8fFs27aN5cuX061bN+Li4lBK4YlhGJSWlvLuu+8SFBTEDTfcQEJCAlarla+//prZs2cTGRnJpEmT+JHZDK1aQatWXI6SkhIaMmXpAXo83hIREcHo0aPp2rUr58+fx+1206hRI5o3b05QUBCi9iige8sYxnZIoV9cS6qspARycuDsWXC5wM8PoqIgNBRMJlwuFz/88AM7duxg2bJlnD9/npEjRzJo0CCCgoIQl2f7qn20752ANxmOpVSWsqcjala+o5S75i1k6/FsKtI+Ooo3x6UTbLdRW84WFvH5ngN4cluPzmhKIYQQonbpXKajR4+SmppKZVmtVkaNGkXbtm1ZuXIl9913H4MHD2bChAkMHz6clJQUmjRpglKKi9auXcu8efM4cuQIdrudpKQkJkyYQJs2bbjxxhsJCQmhcePG7Nmzh5kzZ5Kfn8/QoUPp2rUrLVu2pCqOHj1KQ6X8bkIFPgpoeFNISAghISEI3xDu78fQpATGdkildUQY1aK4GDZuhPnz4dtvobwcgoKgTx8YNQpatqSoqIglS5awfPlyevTowcMPP0x0dDSicrav2sctv0vHa5xHwXmQytFQtmGImnO2sIjb5i5g/+kfqEj/1q14cfQw7Gad2vR2xnZKnU4uFdkogBHt2iKEEKL26VymNWvWkJqaSmUppYiIiCA0NJTY2Fi2b9/OkiVLWLNmDTfeeCODBg3CbDZz0eLFi5k6dSpDhw5l4MCB+Pv7c/DgQT799FMee+wxkpKSyMnJ4ZlnniEjI4O+ffty1VVXERsbS6NGjaiqNWvW0PCYUIGPo/wmIDzTFKREReKrsvLyyCtxUFmaUvRsGcOYtFQGto7FbDJRbQwDdu6Et96CiAh48UWIiIB16+D996G4GO69FzSNhIQEOnfuTHJyMiaTCVE5hmFQXurE5mfFWwzHEipLWXuBKQpRM05cyGPS7PkcO3+BigxPTeTP1w5G1zRqU77DwYfbd+PJTd3SMJtMCCGEqH06l+mDDz5gypQpVJXJZKJZs2aEh4fTtm1b1q1bx8yZM2nVqhUJCQmUl5czdepU+vfvz+TJkwkNDcVkMpGWlkZ+fj5KKUpKSpg2bRp2u51HHnmENm3aEBERgVKK6vD+++/ToCg7KvgFlHUAomJWXWf+pPH4qgcWLmHR3oNcrgh/f9LbJTGmQwoxIcHUCIcDNm2C0lK4/XZISuJHw4fDmTOwahXs2UNgnz706tULUXUHtx8lvn0M3mQ4llJp9nREzfj2zFkmzVnAmYJCKnJjlw48Org/mlLUtnc37aCwtIxLNbJaGdsxFSGEEL5B5zJlZGSwatUq+vfvT3Ww2Wy0bt2ayMhIOnbsSGBgIBcdOHCAPXv28N577xEVFYVSiovCw8MJDw/nIovFwrhx44iJiSE6OhqTyUR1WbFiBVu3bqXB0MLRQt4Acyqi4dCUonvL5oztkMqghHh0TaNGnT8Px49DZCS0acO/6DrExsKGDZCVhag+m5btYtgt/fEa51FwHqRSVADKOhBR/bYcz+auDxdSUFqKJwqY0rc79/brgS8oKC3lvc078GRCl/Y0sloRQgjhG3Qq4f7772fTpk1YLBaqS2BgIO3atcPpdKKU4tSpU5jNZmJiYvh3Sin+yWQy0bVrVywWC9WprKyMBx98kAbD1AItdAaYWiIahshGAVzXPpnr2qcQHRSI1zid4HKB2QwmE//BbAaloLwcUX1yc/IJaxKMtxiOxVSWsg0BZUdUr5WHvuP+TxfjcDrxxKQUTwwdyNiOqfiK9zbtIN9RyqXsZjM3dU1DCCGE79CphJ07d/Loo48yffp0qpNSCrPZzEX+/v6UlZXhcDiw2Wx4opTCYrFQ3X7961+za9cu/pcX3rhAWIjGv5s4cSKJiYlUu9KvMMp2U+0sndGCXwMtCFG/aUrRvWVzxnZIZVBCPLqm4XUBARAUBMePw7lz0LgxP3K74exZcDohJARRPbK+PU3T2MZ4k+FYRGUpezqien22ex+PfrEcl9uNJ2aTiekjr+bqpDb4isLSMt7dvANPxnduR5i/H0IIIXyH3rhxY86cOcPlev7557n77ruJjY2lJiQnJxMQEMDSpUsZN24c/2QYBhcppagJ3333HX/961/5Od6ance/i4yMZNrzf0GZzVQ3w3UcynZTnZRtMCroWVA2RP3VOCCAkaltGdexHdFBgdSq4GBISYHMTFi+HIYOBbsdsrNh82bw94eEBET1WDFvI9fc0g+vcR4F5xEqxRQDlk6I6vPe5h08vWwVBp75Wcy8fP1wese2wJe8v2UHeSUOLmXVdW7p3gkhhBC+Rb/pppuYPn06l8swDLZt20ZsbCw1ITg4mF/96lc89dRTWCwW+vXrh8ViISMjg+3bt/Pb3/6WmrBjxw4qa+LEiZjNZuoC5XcTKvBRQEPUP5pSdG/ZnLEdUrkqIR6TpuETTCbo3h0OHYKlSyE3F4KCYN8+OHkSRo+G+HhE1Rlug7yzBUREh+IthmMxlaX8xgEKUXUGMH3FWmZu2EpFguw23hw3kg7RTfAlxWXlvLdpB56M69SOiAB/hBBC+Bb9tttu4/nnn8ftdnO5DMOgpmiaxpQpUwgODmbGjBk8+eST+Pv7k5CQwI033khNMQyDytA0jVtvvRXfZ0IFPo7ym4Con0a3S+Y3A/vSOCAAn9SiBUyaBMuWwYYNUFQEMTFw223QoweYTIiq27pyLx36tcWbjJJPqBSlo+wjEVXnMgyeWPw1H+/IpCJNgwKZNWEUrcJC8DXvb9nB+eISLmXVdW7t0QkhhBC+R09ISGD8+PF88MEH+Jrg4GBuvvlmrr32WsrKytA0DZvNRkhICL7m5ptvpnXr1vg0ZUcFv4CyDsDXOMudrJu9joCwANr2aYt/sD/OMicrZ60kMjaShF4J2PxtiP+tV6sW+LzoaJg0CSZNQtSMjYt3cOefbsBryveDK5vKUNarQQtDVE2Zy8VDC5aybP+3VCQ+Ioy3xo8iKjAAX1NSXs67m3bgydiOqTRuFIAQQgjfo/N3Tz/9NJ9++iklJSX4moCAAAICAvBlfn5+PPXUU/g0LRwt5A0wp+KLTCYTzZKbsXXhVkKiQmiZ1pK9q/aSl5NHUr8kLDYLov7JycmhrKyM5s2bI6pPUX4JNn8rFpsZbzFK5lFpfmMQVZPvKOWueQvZejybirRrGsWb40YS4mfHF83esotzRcVcymIycVvPzgghhPBNOn/XvHlzHnzwQaZNm4a4fA899BDR0dH4LFMLtNAZYGqJr1KaokW7FpzYe4ID6w/gcrrY980+kvon0bhFYzSThqh/1q5dy7lz57jjjjsQ1eebTzbRb1QXvMeN4ficSjE1QVm6ISrvbFExt82Zz/7TP1CRHq1ieHXMcPwtFnxRSbmTWRnb8GRMx1QiGwUghBDCN+n8f48//jhLly5l27Zt/Fx33XUXDzzwABXp1q0bd955JwMGDMBkMlGbXC4XK1as4PXXX2fz5s1UpKSkhMvRpUsXHnvsMXyWOQ0t5HXQQvB1ZquZtCFpfPXaV6yYuYJWaa2IaReD2W5G1E/Hjx/n5MmTiOp1cPv3DJvUH68p3QjuQipD+d0EKETlnLiQx6TZ8zl2/gIVGZ6SyJ9HDEbXNHzV3G27OFdUzKXMJhO39uiEEEII36Xz/1mtVubOnUunTp0oKCjg5zh//jw/Zf78+cyfP59mzZoxadIkxowZQ3JyMt6UmZnJvHnzePvtt8nOzqY6BQUF8eGHH2KxWPBFyjYYFfQsKBt1RWBEIIGNAzm2+xgx7WJoFNYIpRRCiJ/n4PbviU+NwZuMor9RKcqEsqcjKufbH85x6+z55BQUUpEJndvz+NVXoCmFryp1Onk7YzueXJ+WQtOgQIQQQvgunX/TunVrZs6cybhx43C73VSXEydOMHXqVKZOnUqbNm0YMWIE/fr1o1evXgQHB1OdcnNzWb9+PatXr2bhwoV8++231ARN05g1axaxsbH4IuV3EyrwUUCjLsk+kE3uyVxCo0M5tusYTds0JTgqGCHEz7Ps/XXcPm0M3uPEKN9OZShzP9BCEZdvZ/Yp7pj7GRdKHFTk9p5deGhgb3zd3G27OVNQyKV0TeO2Hp0RQgjh23QuMWbMGHJycvjlL39JTTh06BDPPvsszz77LJqmkZSURHJyMikpKbRt25amTZvSrFkzIiMjsVgseFJWVkZOTg4nTpwgOzubAwcOkJmZSWZmJvv378ftdlPTXn31VUaNGoXvMaECH0f5TaCuKS0uZfui7TRt05SWaS1ZO3stR3cdJSkoCYvdghDip50+dpaQyCDs/la8xSiaCYaLylABtyIu3zfffsevPlmMw+nEE5NS/H7oAG7o2A5fV+p0MmvjNjy5rkMK0cGBCCGE8G06Htx7772cP3+eJ598kprkdrvJzMwkMzOTefPmcSmz2UxAQABms5mLysvLKSwspLy8nNr0xz/+kTvvvBOfo+yo4BdQ1gHURXtW7MHlchHXJY6o+ChSB6ayb9U+omKjiIyPRCmFEKJiX8z8htH3XIVXFc+mUrRIsHRBXJ7P9+znt59/hdPtxhOzycSzI69mSFIb6oJ52/eQU1DIpXRN4/ZenRFCCOH7dCrwxBNPEBwczAMPPIDb7aY2lJeXk5ubi69QSvH73/+eRx99FJ+jBaOFvA7mjtRFpw+f5vDmwyT3SyaiVQQms4nE3olkZWaxb/U+/EP9aRTWCCGEZ4UXinE6XYRGBuE1ziMYrhwqQ/nfhrg8723ewZ++Wo3bMPDEbjbzypjh9I5tQV1Q5nIxc8NWPElvn0Sz4CCEEEL4Pp2fcN9999GsWTNuvPFGSkpKaMisVivvvPMON9xwAz7H1AItdAaYWuJVRgm4sjBcx8GZBcqG8htHZYTHhHPNfddg9bditpq5yGK30P+W/lxkC7AhhKjY4rdXMfTmvniTu+BpKkdH+d2A+HkM4JXVG3llTQYVCbLbeHPcSDpEN6Gu+HDbbnIKCrmUrmnc0asrQggh6gad/2H06NE0adKE8ePHc+zYMRqili1bMnfuXLp3747PMaehhbwOWgg1wp0HriwMVxa4ssCVBc4sDFcWuE4ABv+krH3AbxyVoVt0GoU34lL+wf6I+qtDhw60atUKUTXlpU5OHT1Li8SmeI1RBGUbqRRbX1BWxP/mMgyeXLKCj7bvoSJNgwKZNWEUrcJCqCuKy8p5Y91mPBnRri3NQ4IQQghRN+j8DD179mT37t3cfffdzJ49m4Zk9OjRzJgxg5CQEHyNsg1GBT0LykalGaXgPoPhygJnFriywJWF4coC5xEwShCipgwYMABRdSs/yaD/6K54k1H0JhhOKkPzfwjxv5W5XDy0YCnL9n9LReLCQ3lrwiiaBDaiLnln03bOFhVzKZOmcUevrgghhKg7dH6mwMBAPvjgA66++moeeughcnJyqM+ioqKYPn06EyZMwBcpv5tQgY8CGv+TOw9cWRiuLHBlgSsLnFkYrixwnQAMhPAWt9vND0d/IP+HfJq2aYp/iD9ul5uc73IoziumSZsm+AX6IX4eZ5mTPesPMfhvvfEaowyj6H0qQ5magDke8dOKy8q55+MvWP/dMSqS2jSSGePSCfGzU5fkOxy8nbEdT67rkEyL0GCEEELUHTqX6Re/+AXDhw/niSee4NVXX8XpdFKfmM1m7rnnHp588kkCAwPxPSZU4OMovwn8i1EK7jMYrixwZoErC1xZGK4scB4BowQhfIYBhecL2b92PyUFJST3TyYvJ4+93+xFt+pExkYifr7Fb69myM198Saj5FMwCqkUv/GIn3a2qJjb5yxg3+kzVKRHqxheHTMcf4uFuuaN9VvIdzi4lFXXuatPN4QQQtQtOpUQFBTEiy++yB133MG0adOYN28eLpeLusxkMjFu3Dgee+wxEhMT8UnKDn43g+s0xoVfYbiOgysL3HkIUVdoJo3oxGjOZZ0ja08WQRFB/HDsB0qLSknsk0hAaADi5ykpKuXo/mxG3DEQ73FhFL5O5ZhQfhMRFcu+kM+kOfM5ei6XigxLSeAvI65G1zTqmh8Ki5i9ZSeeTOjcniaBjRBCCFG36FRB27ZtmT17Nk888QRPP/00H374IaWlpdQlVquVCRMm8Nvf/pb4+Hh8lgpBC30btAjcubeB83t8j0KIn8MWYCO2YywXTl8g49MMbAE2YlJiiIqLQvx8C/62nOG3XYE3GY6l4D5FZShrV1BWhGff/nCO2+bM53R+IRWZ0Lk9j199BZpS1EWvrMmgpNzJpfwsZm7r2RkhhBB1j041aNOmDe+88w4vvvgiH330Ea+88gp79uzBlyUkJHDLLbcwadIkIiIi8HWq0a8AExdpoR/hvnAnlG1DiLoqtFko4THh7Fu9j1YdW9GqYyt0i474efLPFXLhbAGxKc3xJqNoJpWl/KcgPNuVfZrJcxdwocRBRW7v2YWHBvamrsq+kM+nO/fiyaTunQjz90MIIUTdo1ONgoODmTx5MrfffjsZGRksWLCABQsWcPjwYXxB69atSU9PZ9SoUXTr1o26xcS/aEFoIe9i5P0aw7EEIeoiR6EDR6EDW4ANTdcoKylD/HwfvfQl6XddiTcZpaugfB+VogWDpQviv6369nt+9ekiSsqdeKKA317Vj5u7daQue2HVespdLi4V4mfnlu6dEEIIUTfp1AClFD169KBHjx4888wzZGZmsnz5ctasWcO6des4e/Ys3hAeHk7v3r3p27cvgwYNIiUlhXpDWVDBL0BBNEbRDISoS1xOF1l7sziXdY6kfkkUXSjiUMYhAiMCsQXYED/tTNY5LmrSMgJvMoreoLKUfRygEP/piz0H+M3ny3C63XhiNpl4ZsRghiYnUJd9e+YsizMP4skdvboQYLUghBCibtLxgpSUFFJSUrj//vsxDIP9+/eza9cu9uzZw759+8jMzOTEiROUlpZSGVarlWbNmpGSkkJycjIpKSl06NCBxMRElFLUXwrV6GHQwjEK/gK4EaIuOJ99nmO7jxEcFUza0DSO7znO4c2HycrMIr5rPEpTiIp9/PIyxj88DK8q2wJl26gsZU9H/Kf3t+zk6WWrcBsGntjNZl6+fhh94lpS1z3/zQbchsGlGjcKYFzn9gghhKi7dLxMKUVSUhJJSUmMGzeOf3f27FlOnz5NdnY2+fn5lJWVUVRURFlZGRdZLBb8/f2xWCwEBgYSHR1NVFQU4eHhNGTK/xYwNcPIexAMB0L4spKCEr7b9h1lJWW0H9SegNAAYtrFcO7EOb7f8T2hzUIJaxaG8GxvxmGatIwgJCIQb3IXvkSlWdqD3hLxDwbwyuqNvLImg4oE2W28ccNI0po1oa7bffI03xw6gif39u2OTdcRQghRd+n4kPDwcMLDw0lJSUFcHmUbhDK9hzv3TnCfRwhfpZQiPCacxi0bE94inIsCQgJI7JXI+ZPnMZlMCM9cTjeL317FA6/cgjcZZeuhbBOVpWyjEf/gMgz+sGQF87bvoSKNGwXw1vh02jQOpz54bsU6DP5bi9BgRnVIRgghRN2mI+oPcwe0sI9wn78NXEcRwhfZAmzEdY7jUhEtI4hoGYGo2Py/fcWwW69AN5vwJqPgr1SaMqNsVyOg3OXioc++5Mt9h6hIbHgob40fRdOgRtQH6787RsbRLDy5r39PdE1DCCFE3aYj6hdTDFrYHNy5d0L5boQQ9cOZE+c5n5NHUtc4vMkoXQnlO6ksZb0StGAauuKycu79+AvWfXeMiqQ0iWTG+HRC/ezUF39dtQFP2jQOZ0hSG4QQQtR9OqL+0cLRQt/HuPAARukKhBB13wd/+ZzbnrwO7zIwCl+iSuwjaOjyShxMnvsZO7NPUZHuLZvzt7HX4m+xUF98deAwu7JP48mDA3qjKYUQQoi6T0fUT8qOCnkF8qdhFM/GOxRCiOq3YdEOUnu2ITAsAG8yHMugfB+VpoWirH1pyE7m5TNp9ny+P5dLRQYlxvNc+hCsuk594TIM/rpqA550bN6U/q1bIYQQon7QEfWYCRX4BOgtMfL/BLgRQtQtpSVlrF+8g4f+dgve5cYofIWqULbhgE5DdfiHc9w6Zz6n8wupyLhO7fn9kCvQlKI++Xz3fg7/cA5P7r+iF0IIIeoPHVHvKb+bARtG/u8BAyFE3TH7mS8Y+6urUUrhTUbJF+A8RFUov9E0VLtPnmby3M/ILS6hIrf37MJDA3tT3zicTl5avQFP+sS1pGuLZgghhKg/dET9ZxRiFH8AGNQshRCi+mRu/JbA0ABiEpriXU6MwleoEnMK6Ik0RBu+P86Ujz6nuKwcTxTwyKC+3NK9E/XROxnbOZlXwKUU8Mv+PRBCCFG/6Ih6zomRew84D1LzDIQQ1aMwr5jFb6/m4dcm4W1G8WxwHaMqlH00DdEXmQf4zcJlON1uPDGbTPxlxGCuSU6gPjpfXMKMDVvwZHBSG9o1jUIIIUT9oiPqMQMj71GMsg14h0IIUT1m/WE+Ex9PRzNpeJU7D6PwVapEWVG2YTQ0H2zZyR+XrcJtGHhiN5t56bph9I1vSX318uqNFJaWcSmzycQDV/RCCCFE/aMj6i2j4HmMks8QQtQtKz/eREr3eCJjwvA2o/BlcF+gKpT1KtCCaEhmbNjC9BXrqEigzcab40aQ1qwp9dX353L5aPsePJnQuT0tQoMRQghR/+iIesko+Rij6A28SyGEqJqzJ3PZve4gv/rrTXid83uM4jlUmd9oGgqXYTB1yUo+3L6bikQE+PPW+FEkRIZTnz27Yi1Ot5tLBdqs3NWnG0IIIeonHVHvGKVrMPJ+jxCibjHcBrOmzueuP91AbTAK/gQ4qRJTNMrSnYag3OXi4c++ZOm+Q1QkNjyUt8aPomlQI+qzLcezWXHwCJ7c1acbwXYbQggh6icdUb+UZ2Jc+CXgQghRt3z66ldcNa4njUL88TajLAOjdBVVpeyjAI36rqS8nHs++oJ13x2jIslNIpk5Pp1QPzv1mQE8t2ItnjQLDuIXXToghBCi/tIR9YcrG3fuHWAUI4SoW47sPk5BbhEd+rXF+1wY+dOoOoWyj6S+yytxMHnuZ+zMPkVFurVszt/GXEuA1UJ9t2TvQXacOIUnDwzohcVkQgghRP2lI+oHowB37h3g/oEq0VuDUQiuUwghvKPwQjGfvPIVD7w8kdpgFH8MzkNUlbL0AFNz6rOTeflMmj2f78/lUpErE+J4ftRQrLpOfVfqdPLcynV40q5pFEOTExBCCFG/6Yi6zyjHyJ0CzkNUiak5Wui7gIE79w4oz+TyKIQQl8dwG7zx+DxufXI0ZquO1xkFGIVh1oCEAAAgAElEQVR/pVr4XUd9duTseW6dPZ9T+QVUZFT7ZKYNuxKTptEQvLVxG9kX8vHkkUF9UQghhKjvdEQdZ2DkP4pRlkGVaMFoITNBC+ciLXQ2xoX7MEpXIYSoOR888wVXjetFeNMQaoNR8Dy4z1FlWhDKeiX11Z6TOdw+dwG5xSVU5PaeXXhoYG8aijMFhczYsAVPBiXG0zkmGiGEEPWfjqjTjIJnMUoWUiXKihbyOuit+BdlR4W8BvlTMYrnIoSofhuX7CQoLIDUXm2oFeV7MIo/pDoo20hQNuqjjd8fZ8pHX1BUVoYnCvj1oL5M6t6JhuT5b9ZTXFbOpcwmEw8P7IMQQoiGQUfUWUbxPIyimVSNhgqaDuaO/DcTKvAPoMdi5D8NGAghqseJw6fZtnIv90yfQO1w4c7/HeCiOii/66mPFmUe5JGFX+J0u/HEpGk8dc2VjO6QTEOy7/QZFu7ejyc3d0ujRWgwQgghGgYdUScZpasw8p+kqlTgb1G2wfwU5XczqCCM/MfAKKdiCiHE/1ZS6OCDv3zB/S/dTG0xit6B8n1UC0sn0NtQ38zeuotpX36D2zDwxG7Weem64fSNb0lD88dlq3AbBpcK8/fjzt5dEUII0XDoiLqnPBPjwn2Ai6pQ/reg/G7m51D2kWCKwrhwD7jzEUJUjmEYvPn4R9z82Eisdgu1wnUSo/Blqouyj6W+mbFhC9NXrKMigTYbb9wwgo7Nm9LQLN57kK3Hs/Hkvv49aWS1IoQQouHQEXWL6wTu3MlglFAVyjoA1ejXXA5l6Y4KnYs793ZwnUQIcfk+fmkZvUd0oknLCGqLkf8UGMVUCy0QZRtMfWEAf/pqNe9u2k5FIgL8eWv8KBIiw2loSp1Onlu5Dk8SIyO4Li0FIYQQDYuOqDvcF3Dn3grus1SJuR0q+AXAxGXTW6OFfYw7dzKU70UI8fOtXbgVs0Wn0xXJ1BbDsQyjdAXVRdnSQdmpD8pdLn69cBlL9h6kIs1Dgpg1YRQxIcE0RG9t3Eb2hXw8+fWVfTAphRBCiIZFR9QNRinuC3eB83uqxBSDFvIGKDuVpkWghc7GuHAfRulq/o9CCOFZ5sZv2bf5CHf8cSy1xijEKJhGdVJ+11MflJSXc+/Hi1h75CgVSW4SyYxxIwnz96MhyikoZMaGLXhyZUIcvWJbIIQQouHREXWAgZH3KJRto0q0ELTQmaCFUWXKDxXyOuT/AaP4Q4QQFTt+6BTLPljH/S/dTG0yCp4DVw7VxtIJ9DbUdXklDu748DN2nDhFRbq2aMZrY0cQYLXQUP1l+RqKy8q5lNlk4tdX9kUIIUTDpCN8nlHwZwzHF1SJsqGFvA6mllQfEypwKpiaYRQ8hxDiv53PyeODP3/Og6/egmbSqC1G2QaM4jlUJ2UfS113pqCQW+cs4NCZs1RkYEIcL4wailXXaai2ZWWzZO9BPLm5axotQoMRQgjRMOkIn2YUz8Uoepuq0VBBz4E5jZqg/CeDFgGl3yCE+D8lhQ5e+82HTHlmPFa7hVrjzsfIexQwqDZaIMo2mLrsu7PnuXXOfE7mFVCR9PZJ/HHYIEyaRkPlcrt5cslKDP5beIA/d/bpihBCiIZLR/gso3QlRv5UqkoFPoqyDaImKXs6WHshhPgHZ7mLlx+azcTH0wmOaERtMvKfANdJqpOypYOyU1dlnsrh9jkLOF9cQkVu79mFBwf2RtGwzd66i0NnzuLJQwN608hqRQghRMOlI3xT+R6MC/cDLqpC+d+G8rsJr9AaI4QAwzB447F5XHvbFUTHNaY2GY4vMByLqW7K73rqqoyjWdw973OKysrwRAEPX9mXW3t0oqE7V1TMy6s34klasyaMbJ+EEEKIhk1H+B5XFu7cyWCUUBXKNgTV6CGEEN41d/piOvZPIrFzLLXKlYORP5VqZ+kKehvqouUHDvPggqWUOp14YlKKp4YNYnSHZAQ8t3Id+Y5SLqUpxWODr0AhhBCiodMRvsV9AXfureA+R5VYOqOCngE0hBDe8/mMlYRGBdFjaAdql4GR/xi486huym8CddHcbbuYuvQb3IaBJ3azzoujh9G/dSsEZJ7KYcGufXgytmM7UptGIoQQQugI32E4cOfeCc6jVImpBVrwK6CsCCG859NXv8JiNXP1jX2obUbxBxila6h2WgTKNoi6ZsaGLUxfsY6KBNqsvH7DCDo1j0aA2zD4w5KVuA2DSwXZbdzXvwdCCCHERTrCR7gx8h6C8u1UiRaKFjoTtFCEEN7zySvLCAptxKDxPal1zu8wCp6lJii/cYBOXWEAf1m+hrcztlGR8AB/3hqfTmJkBOIfPtmRye6Tp/Hk/it6EeJnRwghhLhIR/gEI/9PGI6vqBJlRwt5HUwtEEJ4h2EYvPenhbRKakbfkZ2pdUYp7rwHwHBQ/XSU3xjqinKXi0cWLmPx3oNUpFlwELMmjKJFaDDiHy6UOHj+m/V4khTVmDEdUxFCCCH+SUfUOqNoFkbxu1SNCRX8HJg7IITwjpKiUt54dB79RnUhrV9bfIFR8DSU76MmKNvVoDWmLigpL+eXnyxizeGjVKR14zBmjR9F40YBiP/zl+VryC0u4VIKeGxwf0xKIYQQQvyTjqhVhmMpRsEzVJUKfAxlvRIhhHec/O4M7/1pIRMfTyeqRTi+wHAswSieS01Rfr+gLsh3OJg8dyE7TpykIl1bNONvY6+lkdWK+D9bj2ezYNdePBnZPonOMdEIIYQQ/05H1J7y3Rh5vwHcVIXyvwPl9wuEEN6xdUUm67/Yzn0v3oTd34pPcB3DyHucGqMngqUjvu6HwiJunTOfgzlnqciANnG8MHooNl1H/B+X281TX36DwX8LtNl4eGAfhBBCiEvpiNrhOo47dzIYJVSFsg1FNbofIUTNKystZ/ZfviAwLIBfvnAjSil8glGCO/ceMAqpKcr/Rnzdd2fPc+uc+ZzMK6AiI9sl8fTwQZg0DfGf3s7YzoGcH/DkoYG9CfP3QwghhLiUjvA+dy7u87eB+zxVYumCCnoG0BBC1Kyj+7KZ9+JSrrvnKuLaxeBLjLxHwXmQGqMFomzD8GWZp3K4fc4CzheXUJGbuqbx6OD+KMSlTuYV8OraDDxJbRrJ9WkpCCGEEJ7oCO8yHLhz7wTXUapEj0cL/hsoC0KImuN2ufn01a/IO1fIAy9PxGzV8SVG0VsYjsXUJGW/DpQdX7XpaBZ3f/Q5haVleKKAhwb24baenRGePfXlNxSXlXMpk1JMveZKNKUQQgghPNERXuTCyHsQyndQJVoEWsgM0IIQQtScQzuOMv9vyxk2qT8pPVrja4yyDIyC6dQshbLfgK/6+uARHpi/hFKnE09MSjH1miu5Li0F4dmaw0dZeegInkzo0oGkqMYIIYQQFdERXmPkP43hWE6VKH+0kBlgikYIUTMK84r56MWl2PysPPDKRCxWMz7HlYVx4T7ARU1S1j6gt8QXzd+1l8cXfY3L7cYTi8nEc6OGclViPMKzknInf1i6Ek/CA/z5Zf8eCCGEED9FR3iFUTQDo/h9qsaECp4O5iSEEDVj7cKtbFi8kwm/Hkaz+Ch8klGIO/cucOdS4/wm4otmbNjC9BXrqEigzcprY0fQOSYaUbFXVm/kxIU8PHl8cH8aWa0IIYQQP0VH1DjDsQSj4DmqSgU+jrIORAhR/fZvOcIXb62i9/COPPLmbfguF0buveA8RI3TW6OsvfAlBvDM8jXMythGRcID/Jk5Lp22URGIih3I+YF3Nm3Hk16xLRiS1AYhhBDif/l/7MEHYJX1vfj/9/d5nnNOTvZiJCQsGbIUVKaADBFkiOJErBO01nH1aquto8N1bbW21aoVtK3XrYgoKAgigjJV9kwIhBFICNk5J2c93/+P3r+t4jmanZB8Xi8L0bD8X6JL7wFs6kLF/gwVPQMhRP06kHWEec8tJa1zKnf8+WqcLgfNmS57CO3/gsagYq4FFM1FyLZ5YOFS5m7cRiQZiQm8NGManZITEZGFbJtffbCEoG1zIqdp8sCE0QghhBDVYSEaTnAPdsnNoH3UhYqahIr9L4QQ9efY4RLeeWYxUdEurv/1NGITomnudOUctOc1GoWRjIqaQnPhDQS5/Z0PWJG9j0i6t03hxSun0S4uFvHD/r72a7Ydziecm0cMpktKEkIIIUR1WIiGYRdhF/8U7FLqxDkYlfA4oBBC1F1RfinvPb+UoD/EpbdPILldAicDXfUBuvwPNBYVPR1UFM1BWVUVN70xn68P5BHJwI4deO6KqcS5XIgfdqikjGc+W0M4XVOTmTnsLIQQQojqshD1T3uxi2+CUC51YnXDSPwrKCdCiLo5eqiI+X9bhqeiiktuPY/0rm05WWj/anTpvYCmUSgHKvpKmoOjFZXc8Nq77MovJJIxPbry1MWTiLIsxI97YOFSvIEAJzKU4pHJ43CaJkIIIUR1WYh6FkKX3AWBTdSJ0RYjaQ4Y8Qghaq/gwDHen/MpAX+QS28bT2p6EieVwFZ08c2gAzQWFTUJjDY0tQPFpVz/6rvsLy4hkqmn9eLRKedhGQbix83duI0vcnIJ56qB/TkjMx0hhBCiJixEvdJlD6N9S6kTFYORNBvMdIQQtZO9aT+L/nclsYnRXHLreBLbxHHSCWZhF98A2kNjUtFX09S2Hc5n1uvvcazSQyRXDxrAr8aPQiGqo9jj5Q+frCSc9IQ47hg9DCGEEKKmLES90ZXPoz2vUjcWKvEv4OiFEKJmtK3ZuHInK9/7kuT2iVx7/0XEJkZzUgrtwy66FuxiGpVzMDj60pTW5R7k5jfnU+HzE44C7ho7nFnDBiKq76FFn1Ls8RLOAxNGE+N0IoQQQtSUhagXumohuvwp6kahEh5CuUYghKg+b6WPT99Zy9bVWZwxqje3/GEGpmVw0grlYRddC/ZRGpuKuZam9MmuPdz57of4gkHCMZXit5PO5dIBfRHVtzxrLwu37SKcSX16MqbHKQghhBC1YSHqzr8OXXoPoKkLFXsryn0xQojqOZB1hI9f/QJPuZdxV57NxGtGctIL5WEXzYBQHo3OzEC5RtFU5m3azn0LlhCybcJxmiZPXHQ+43t1R1Rfuc/Hbz78hHAS3FH8avwohBBCiNqyEHUTzMYuuQW0n7pQUVNQsbcihPhhQX+Q1R9tZN3HW0hul8DUG8eQmp5EixA6hF10DYQO0RRUzHWASVOYvWo9T37yOZrwop0O/nrZBQzr0hFRM499/BmHy8oJ595xI0mNiUYIIYSoLQtRe/ZR7OKZYJdSF8o5BJXwP4BCCBHescMlLH7lcw5kHWHYpP7c8edrMC2DFiO0D7voGggdpm4UoKkxIx7lnkZj08Aflq7gxdVfEUlqTDSzr7yI3u3bImpm5Z59zN24jXCGdenIRaf3QQghhKgLC1E7uhK7eBaE8qgTqwcq8RlQDoQQ3+Xz+vn8/a/Y9Pku2makMP6qs2nTIZkWJ7gXu/hqCOXTVJT7SlAxNKaQ1jywYAlzN24jkg6J8fx9xsV0Sk5E1EyFz88DC5YSjtvh4LeTxqIQQggh6sZC1EIQXXI7BLZTJ2Y7jKTZYMQjhPiPrI25LH1zNVUVPoZO6s8df7oawzRokQLbsItngV1IXSnrVHRwJzWmnKiYn9CYvIEgd8xdwPKsvUTSvU0KL86YRru4WETNPbbkMw6XlRPOL84dQcekRIQQQoi6shA1psseRvtWUicqFiNpNphpCCEgf/8xlr21hsO5R+k7pDvX3nch7tgoWjLtX4Mu/hnoCupKRY1H+5ZTG8p9MRhtaCxlVT5++sZ8vjpwiEhO79CeF6ZfRKI7ClFzq/fuZ+6GrYQzqFMG0886HSGEEKI+WIga0RXPoD2vUTcWKulpsE5FiNas+GgZK9/7kj2bD9CuYwqjLx1MWuc2tAa6agG69B7QAepKRZ0LZgZoHzVnomKuo7EUVlRyw2vz2Jl/lEhGd+/Kny6ZRJRlIWquwufnVx98jOb73A6LhyePQyGEEELUDwtRbbpqAbriaepGoRIeQTnPRojWqLLMy+oPN7Jj/R6iol0MmzSAC2aNoTXRlX9Hlz8O2NSVco1ExT+CffRcakNFjQezM43hYEkp17/6LrlFJURyQb9ePHbBeViGgaidx5euIK+0nHDuHjuCTsmJCCGEEPXFQlSL9q9Fl94LaOpCxd6Bcl+EEK2Jt6KKtR9vYdOKHbhjohg2eQBjLxuCMhStSwhd9gja8wr1QTmHoBKfQXv+Cbqc2lAxM2kMWQWFXP/aPArKK4jk6kED+OV552AohaidNfsO8PbXWwjnjMx0rjzrdIQQQoj6ZCF+XDALXXILaD91odyXomJvRojWoKLEw5pFm9i2JgtXtJNB553GrU9chWkZtEp2KbrkdrR/NfXCMQCV9Dyg0JUvUxvKOQwcfWlo63IP8rM336fc5yMcBdwycgi3nTMUUXvlPh+/fP9jNN/ndlg8PnU8hlIIIYQQ9clC/DC7ALt4Fthl1IVyjUQl/A4hWrLy4krWLt7Mzi9zMEyDM0b35tYnrsK0DFq14F7s4psgtI964TwDI2kOqGi053/BPkqtxN5EQ1u2ew93zv2QqmCQcEyl+M3EsVx2Rj9E3Ty8aDl5pWWE899jhtMxKREhhBCivlmIyHQldvEsCOVRJ1YPVOJTgIkQLU1eTgGrP9rIgd1HSEiNY+jE/oy9fAhKKQRo3yfo0nvALqNeOAdiJL0AKgZ0AF35IrXi6IVyDqEhvbd5O7/6YAkh2yYcp2nyxEXnM75Xd0TdLN21h/c2byecARnpXDWwP0IIIURDsBARBNElt0FgB3VitsNImgMqDiFaAm1rsjfvZ/2SLRTmFZPcPpHB40/j4lvOQ3xbCF3+FLpyNqCpD8o1ApX4V1BRHKe9b0Moj9pQMT8FFA3l5XUbeHTxcjThRTsdPHPpFM7u2glRN4UVldy/YAnhuB0Wj08dj6EUQgghREOwEGFodOn9aN/n1ImKxUiaA2Z7hDiZecq9bPxsJxtX7iTgC3DqwK5MvPYcEtvEIcKwj6FL7kT711BflOscVOIzoFz8nyC6cja1Ymaios6jIWjgiU9WMmfVl0SSGhPNC9Mvok9aW0Td3b9gKcUeL+HcM24knZITEUIIIRqKhfgeXfE02vsudWOhkv4KVk+EONloW5O9eT9fLdvGkdxCouOiGHBOL2b+9hKcUQ5EZNq3DF36K7CLqC/KfQEq/jFQDr6hvfMgdIjaUDGzAJP6FtKaBxcu5Z0NW4mkQ2I8L105jc4pSYi6e/PrLXyalUM4Z3ftxBVnno4QQgjRkCzEd2jvO+iKZ6gbhUp4FOUcihAni7JjFWz6fCc71uVQXlJJZo80hk0eQMceaYhq0FXo8ifQnv8FNPVFRV+Niv8VYPAfIXTF89SK0Qblvoj65g+FuOvdD/l4ZzaRdGuTwotXTqN9fCyi7g4Ul/L4khWEEx/l4pEp41AIIYQQDctC/Jv2r0GX/Zq6UnH/jXJfiBDNmR2y2bPlABs+28GRfUeJS46l/8hTuf7X07CcFqIGAluxS++C4F7qj0LF3YuKuY4Tae98CB2gNlTMTFAu6lNZlY+b35zPl/sPEclp6e2ZfeVFJLqjEHVna80v319Mpd9POL+dOJa0+DiEEEKIhmYh/k9wN7r4FtAB6kJFX4aKuQkhmqPiglK+WradnV/mEAqG6D6gM2MvG0JKWiKiFnQVuuKv6Mo5QIh6o5yohMdQUVP4vhC68m/UipGEir6c+lRYUcnM1+ex48hRIhnVvQt/ungyboeFqB8vfLGe9fsPEc6UfqcysU9PhBBCiMZgISCUj108C3Q5daFc56Dif4sQzUVFiYetq7PY/MUuvBVVtOuYyplj+jD2siEoQyHqwP8ldtn9EMyhXhmJqMSnUc7BhKO9CyC4l9pQMTNBRVNfDpaUcv2r75JbVEIkU/qdyv9cMB7LMBD1Y/uRAp5ZsYZw2sfH8uCE0QghhBCNxaK10xXYxTMhdJg6cfRFJf4ZMBGiqVSUeti6Ooutq7LwlHuJTYym79Du/OTeC3DHRiHqgV2GrvgL2vMKYFOvrB4YSc+DmUF4NrpyNrViJKKir6S+ZBUUcv1r8ygoryCSqwb2577xozCUQtQPXzDIPfMXEwiFOJECHp48jvioKIQQQojGYtGqBdHFt0JwF3VidsBI+huoaIRoTN5KHzu/zGHTyp2UHavAdJicdnYPrvjvicQmRiPql/YtQ5f9GkL51DflGolKfApUHJHoqkUQ3E1tqJjrQcVQH9bvP8TNb8yn3OcjklnDBnL32OGI+vXI4uXsLigknJ8MGsCIUzojhBBCNCaLVkujS3+F9q+iTowEjKQXwWiDEA2tyuNjx/ocNq7YSXlRBabD5LSze3DxLecRlxSDaCChA+iyR9C+ZdQ/hYqZhYq7EzCJTKMrnqNWVBzKfSX1YdnuHO6cu5CqYJBwTKV4cOIYrjjjNET9WrIzmze/3kI4XVOTuWvscIQQQojGZtFK6fKn0N73qBPlQCU+DVZXhGgIVR4fO9bnsGH5do4dKSUm3k2/Yd255NbziEuKQTQw7UFXPI/2/B20j3pnxKMSHke5xvJjdNVHENxFbaiYa8GIp67mb97BLz/4mJBtE47DNPnDhRM4v3cPRP06XFbOfQuWEI7DNPnDhROIsiyEEEKIxmbRCmnv2+jK56kbhYp/FOUcghD1peBgEdvWZJG1IZcqjw93bBR9hnTj0tsnEJcUg2gsGl21CF3+OITyaBCOXhiJT4PZkR8XQlc8Ta2oWFT01dTVy+s28Oji5WjCi3Y6ePrSKQzv2glRv2ytuXf+Ykq9VYRzx+hh9E1rhxBCCNEULFoZ7VuBLn2QulJxv0C5pyJEbYWCNgezj7BtbTZ7tx0k6A+SkpZIt9M7MeOeKcTEuxFNILAVu+xhCHxNQ1HuS1HxD4JyUR3aOw+Ce6gNFXMNGAnUlgae/ORzZq9aTyQJ7ihemH4h/TukIerf85+vY82+A4QzqFMG1w85EyGEEKKpWLQmgW3oktuBEHWhoq9AxdyAEDXhKfey6+t9bFuTRdGRUlCKjj3S6DOkG+f/ZATKUIgmZBegy/+M9s4FbBqEkYiKfwgVNZ5q0wF0xbPUinKjoq+mtkJa8+uFS3l7w1YiSU+I56UZ0+iSkoSof1vy8vnrijWEkxzt5smLzsdQCiGEEKKpWLQWoSPYJTeD9lAXyjUKFf9rhPgxh/cdZduabPZs2Y/P48cV7aT3oFOYcsNoElLjEM2EXYqunI32vAy6ioainENRCY+D2Z6a0N43IHSQ2lDRV4ORRG34QyHunvcRi3dkEckpqcm8OGMaafFxiPpX7vNxx9yFBG2bEyngkSnjaBsXixBCCNGULFoDXY5dPBNCR6gTR19U4p8BEyG+reRoObs37GX3hn0U5ZehFGR2T6P34FMYdfEgLIeJaGa0B135D3Tli6DLaTDKiYq9CxVzLaCoEV2FrnyBWlFuVMy11IbHH+CWt95n1d79RNIvvR2zp19EUrQb0TB+++EyDpaUEs5PBg1gTI9TEEIIIZqaRUunA+jiWyG4mzoxMzCSXgDlRrRu3kofOVsOkLUxl7y9BQT9QZxuB30Gd2PSdeeQ1DYB0ZwF0Z656Iq/gH2UBuU4AyPhYbC6URva808I5VMbKvpqMFKoqcJKD7Nem8f2IwVEMrRLR/562RRinE5Ew3h30zY+2LqTcHq2S+XuscMRQgghmgOLFk5Xzkb7V1MnRhJG0ktgpCJal1DQ5mD2EbI25rJv+yE85V6iol107ZfJgFG9mHrTGJRSiJOADqCr3kNX/BVCeTQoFYuKuxsVfQVgUCu6HF05h1pRcaiYmdTUoZIyrnt1LrlFJUQype+p/M/U8ViGgWgYWUeP8buPPiUcl2XxxIXn47IshBBCiObAooVTMTMhuAdd9QG1olwYic+B1RnR8h07UsL2tdnsWJ9DVaWP4zr2TKd7/06MmjYQy2khTjLaj/bOQ1c+C6HDNDTlGoWK/y2YadSFrnwR7FJqQ8VcD0YCNZF19Bg3vPou+eUVRDLjrNO5f8JoDKUQDcMbCHDH3IV4AwHC+dX4c+jRNhUhhBCiubBo6ZQTlfgEVHRGVzxNzRiohCfAeQaiZbFDNgeyjrBn835yth7EW1mFUooOp7Sj55lduPb+i3BGORAnMe1Be99GV8wGu4AGZ6Si4n6Bcl9IndnF6Mp/UitGEirmWmpi06Ej3Pj6PEq8VUQya9hA7h47HNGwfvPhMrKPHiOccad244ozTkMIIYRoTixaBYWKvQ3M9ujSB4EQ1aHi7kVFjUec3IKBEIf25JO1MZe92w7irahCGYrM7ml06pXO5eP6EZcUg2gh7GK052W053/BLqPhGSj3xai4X4CRQH3Qlc+DrqQ2VMxPQcVQXZ9m5XDHOwupCgYJx1SKB84fw/QzT0M0rDe+3sx7m7cTTnpCHA9PHocQQgjR3Fi0Isp9KRhJ6JK7QHv5ISp6OirmWsTJxVtRRc7Wg+TuyiNvTwGeci9aazqd2oHu/Tsx8sKzcEY5EC1QMAfteRntnQfaS6Nw9MeIvx8cp1Fv7AK053VqxWiLip5Odb2/ZQe/fP9jgrZNOA7T5A8XTuD83j0QDWt3QSGPLf6McCzD4I/TJpHojkIIIYRobixaGeU6F5X8CnbxTWAXEo5yjUHFP4ho3oryS8nZeoA9m/eTv/8YKEV0XBSn9Muk79DuTLhqOIZpIFoyjfavhsp/on3LAU2jMNqgYm9HRV8KGNQnXf5n0FXUhoq9DVQU1fHyug089vFn2FoTjtvh4JlLpzD8lE6IhuXxB/ivuQupCgYJ597zzmFARhpCCCFEc2TRGjn6YaS8hV08E4I5fIejHyrxKcBENA9+X4DcHXns3XaQfTsOUeXxc1xyu3i69slk1MWDadcxBdGKaA/a+wHa842JkaIAACAASURBVE8IZtN4LFT0lai4O0DFUu+C2Wjvu9SK2QkVfTE/RgPPfLaaZ1asIZIEdxR/u+JCBmSkIRregwuXklNYRDgTevfgJwP7I4QQQjRXFq2VmYGR/CZ2yc3g/5J/MTtiJL0Ayk3TCQEmrdWxIyXs33WY3B155O0tQBkKbWvSu7Sle/9OjLjwLNwxLkQrFcxCe95Ce98FXU5jUq4xqPhfgtmJhqLLHwNC1IaKux2w+CEhrfnNh5/w1tdbiCQ9IY6XZlxMl5QkRMN7ed0GPti6k3A6JSfy8ORzEUIIIZozi9bMSMBI+ge69B60fxVG0hwwUmgaQXTlS2CdgnKNpaXzVlRxMDuf3J155Gw9QFWlj2AwRNuMZDqdms6AUb2YetMYlFKIVk570VUL0Z63IbCBRufoi4q7C+U8m4ak/WvQvpXUitUDFTWJH+IPhbh73kcs3pFFJKekJvPijGmkxcchGt6WvHz+sHQl4bgsi6emTSLO5UIIIYRozixaO+VEJT6JCh0CM5MmEdiBXXYvBHZgpMyjJany+Ni/6zC5O/PYv+swnnIvWkN0XBSde3WgS58MRk0biOW0EOI7AlvR3vfQVfPBLqXRWV1Rsf+FipoAKBqWjS7/H2pLxd0JGETi8Qe49e0P+CInl0j6pbdj9vSLSIp2IxpescfL7e8swB8KEc5940fRJ60tQgghRHNnIf4fA8xMGl8QXfkSuvxPQJB/MTM5GQX9QQ7lFLB/Vx65O/MoOlLKccpQZHZPo1OvdAae24/ENnEIEZFdiK76CO19BwI7aBJmOir2NpT7QsCkMWjvXAhsp1Yc/VCuMURSWOnhxtfnse1wAZEM6ZzJs5dfQIzTiWh4Ia25+72PyCstI5xJfXpy+Rn9EEIIIU4GFqJpBHZgl90LgR38mxEPRjzNWdAf5FBOAft35ZG7M4+iI6UcpwxFZvc0OvVKZ8oNo0lIjUOIatFVaN+n4H0P7VsJBGkSRiIqZiYq+hpQLhqN9qLL/0xtqbifA4pwDpWUcf1r77LvWDGRjDu1G3+cNhGnaSIaxxNLV/L5nlzC6ZySxEOTz0UIIYQ4WViIRhZEV76ELv8TEOQ7zEyai9LCcvbvOsyB7CMcys6nyuNDa3DHuMjs0Z7OvTpwxug+xMS7EaLGdADtXwHeD9C+ZaCraDJGMirmWlT01aCiaWy6cg7YBdSGco1COYcQTvbRY9zw2rscKasgkivPOp0HJozGUArROD7ctou/r/mKcNwOB89cOoUYpxMhhBDiZGEhGk9gB3bZvRDYQTjKzKAxhYI2BQePcSS3kNwdeeTtLSDoD6K1Ji4phvad29CpZzqjLxmMO8aFEHWiA2j/aqhajPZ9DHYpTcpsj4q5AeW+DJSbJmEXoCvnUDsmKu5uwtmcd4RZr82jxFtFJLOGDeTuscMRjWd3QSG/+mAJmu9TwKNTxtG9TQpCCCHEycRCNDhtB9i+8ml69ZwDBInIzKQhVJZ5ObQnn4NZR9i/+zDlxZUopVCGIq1zGzJ7pDF4wmm075iKMhRC1BtdhfavgqpF6KpPQJfT5MwMVMw1KPcVoFw0JV3+J9BeakNFXwpWD060PGsvd8xdgDcQJBwF3HveOVw7+AxE4ymrquLWtz/AGwgQzg1Dz2Jin54IIYQQJxsL0WC0rfnk9Xd599kFeCsCvLg4yA8yM6gtb0UVh/YUkLe3gEN78jl2pARta46LiXfT4ZR2ZPZIY+C4fsQlxSBEg7FL0b5Pwfcx2vc56CqaBasHKvYmVNREwKTJBXehvfOoFRWNir2NE32wZSf3vr+YoG0TjsM0eXzqeCb16YloPLbW3D1vEblFJYQzpHMm/z3mbIQQQoiTkYWod1prVs5fx5t/fJ2D2eX4qizadQgSDCgshyYiM4MfEvAFKTxcTO7OPPbvOkxhXjFBf5B/UYqOPdLo1CudURcPon3HVJShEKLhaQhsQ/tWov2fgX8TEKJ5UCjnUIi5BuUaBSiaC13+OBCiNlTMjWC04dteWb+RRxYvx9aacNwOB09fOpkRp3RGNK6/LF/NZ9l7CSc9IY6nLp6EaRgIIYQQJyMLUa/WLN7MK4++xYHsI/i8CjA4zuc1KciLIr2Tl0iUmUnAF6TwcDFHcgvJ3ZFH3t4Cgv4gxylDkdk9jU690hkx9Uzad0xFGQohGp1divavAv8qtG85hPJpVpQTFTURFTMTrB40N9q3Au37nFox26NiruPbZq9azxOffE4k8VFRvDB9KgMy0hGNa9nuPTz/+VrCcVkWT186heRoN0IIIcTJykLUizWLN/Pa7z/gYNYBPBUhQPFtFWUWhw+4Se/kJRhQHD3iIv+gm9ysGA7tdxMKKFT0ZyjDol3HVDr2TGPwhNNol5mCYRoI0aR0FTqwAfxr0L7VENgChGh2zHRU9JUo9+VgJNAs6QC6/BFqS8XeCcrNcSGt+d2Hy3jj681E0iY2hpdmTKNH21RE49pTWMTP31uEJrzfThxL37R2CCGEECczC1Enaz/ezMuPvMfhffl4yv1EEgwq5v0zgzXLUnC6bNI7eUnv6GXI2ELapvlQjrYYba5FiGZB+yGwCe1fg/avhcBG0H6aLedAVPRVqKjzAJPmTHtehOBeasU6FeWeynGBUIifv7eIj7bvJpKuqcm8eOU00hPiEI2r1FvFzW/Op8LnJ5yfDOzPRaf3RgghhDjZWYhaWffxFl5+9D3y9hbgKa+iOuISA9zyYBZhmRkI0WR0Bdq/EQIbwP8VOrABtJdmzUhBuS9EuS8DqwsnhdBhdMVz1JaKvwcw8PgD3Pb2B3yek0skfdPaMfvKi0iOdiMaV9C2ue2dBeQWlRDOgIx07hk3EiGEEKIlsGimAlUB3vrNWwyaNojug7pzXMAb4K3fvsXQS4fS9cyuNJUV733Jy4/NJ+DzYCgPYFAdJYVOIlFmJkI0GrsA7f8K/F+hA19DYDtg0/wZKOcQiL4c5ToXlIOTiS5/FLSX2lCu0Sjn2ZR6q7jx9ffYeOgwkQzunMmzl11ArMuJaHwPffQpa/cdIJzU2Bj+cskkHKaJEEII0RJYNFOW06Lfuf1Y/MxiMp7JwB3vZuWrKzkuo3cGTWnk1H6MGLucUNlcDux1sXFNIpvXJlJ4xEVpkYPyMgfeSpMTeSpNIjIzEaJB2EfRga0Q2AqBbejAJrCPcVIx26Pcl6DcF4PZgZOR9q9GVy2mdkxU3N3klZZx/avvsvdYMZGc2/MU/jhtIi7LQjS+f6z9mje+3kw4Lsvi2csuoG1cLEIIIURLYdFMKUPRZ1QfstZkseT5JfQ/vz8bPtzAdU9fh9PtpMkENmGX3gvBPRgmdOoWpFO3SqZedYjj/D6T7O2xbFydyK5N8ZQUOygrdlBU6KK0yEFEZiZC1Jl9FB3YBoEtENiGDmwFu4CTkhGPcp0H7gtQzkGAwUlLB9Blv6O2VPRlZBcnc8Nrb3KkrIJIpp95Og+ePxpDKUTj+3xPLr9fsoJwFPDI5HGc3qE9QgghREti0YyZlsnE2yfy7HXPsnPVTsbdOI6k9CSahPahK55GV74IhIjE6QrRe0ApvQeU8o2Kcoudm+LZsi6RgN/A4bQ5kTIzEKLadCUE96KD2RDMhmAWOrAV7KOc1JQT5Twbos5HRY0H5aYl0J5/QHAPtWIksKXsSm58822KPV4imTVsIHePHY5oGnsKi7hj7kJCWhPOzSMGM6XfqQghhBAtjUUz54x2ktoxlUO7DtFjaA+UUjS6wCbs0nshuIfaiI0LctbwIs4aXkREZgZCfI9dBMEcdGgvBPdCcA86uBtCh2g5TJRzILgvQLnOAyOeFsU+iq54jtpaU3Qzt85fSqXfTzgKuGfcSK4bciaiaZR4q7j5zfmU+3yEc96p3bjtnKEIIYQQLZFFM2bbNl++/yV+r5/eI3uz+LnFXHD3BVhOi0ahfeiKp9GVLwIhGoxygtkW0UrZJRA6iA4dgFAuBHPQwb0Q2gd2KS2ScqCcQ8F1HipqLBgptFS67FHQFdTGgr0j+eWycoK2TTgO0+R/LhjP5L49EU0jaNvc/s4CcotKCKd3+7b8/sIJGEohhBBCtEQWzVh+Tj5r31nLxQ9cTFJaEn+/4+/sWLGDvmP7opSiQQU2Y5feC8FsGp6NXXQVyuwARlsw24ORhjLbgtEWjGRQTsRJyi4CuwAdyoPQQQgdhOBBdOgAhA6CrqRVUG6U6xyIGodyjQIVR4vn/xJd9SG18dr2fjyyqi+2tgnH7bD4yyVTGNmtM6LpPLhwKWv3HSCcNrExPHf5VNwOB0IIIURLZdFMeUo9LH1hKQMmDaBDrw4cN+6mcXwy+xPSe6aTkplCg9A+dMXT6MoXgRCNQgfB/yWaL/k2zbcY8WCkgpGCMlLBSAUjGYw2YKagjBQw2oCRAioK0Qh0OYQKwS5C24Vg50MoH+wCdCgPQvlg54P20WoZqSjXCHCNQ7mGg4qi9Qhhl/0W0NTUnE0DeHLdEEATTnxUFH+7YipnZKYjms6zK9cyd+M2wnFZFn+97ALax8cihBBCtGQWzVTRoSLikuMYPG0w3+gxtAcHtx/k0I5DpGSmUO8Cm7BLfwnBbJoduwzsMiAHzfdpvkW5wYgHlQBGAkolgBEPRgKoeDASwEgAlYAy4kElgBEPKg6Uk1bJLgNdCnYp2i4BXQp2CdhloEvALgG7CG0fA7sQ7CLQfsSJTHCcjnKNRLlGgqM3YNAa6cqXILiLmghpg4e+GM6bO/oQSZvYGF68cho926Uims6Crbv4y/JVhKOAR6aM4/QO7RFCCCFaOotmKqN3Bhm9MzjRmBvG0FB0cDcEsznpaS+EvEA+x2ki05zIACMOVBTgAiMelAuFC4wEUC5QLlDxoFygokDFAQYoByg3/6YcoKL5hsIJKop/Uy5QUXyH9oGu4nu0F02A77ErgBAQArsStAfwgV0B2gPaB7oCtBe0D63LQVeB9oEuA+0DXYWoAyMV5RoBrnNQzrPBSKDVCx1EVzxDTQRsg198OpZFOd2IJDMpgZdmTKNjUiKi6azLPcgv31+MJrxbRg5hSt9TEUIIIVoDC/Fvyn0phA6hK56l9bLBLgVK+ZcQ/6KpO41oEYx4lOMscA5BuYaA1RNQiG9odOn9oL1UlzdocduS8XxxsCOR9Elrx+zpF5ISE41oOrsLCvnZm+/jD4UI5/zePbj1nKEIIYQQrYWF+A4V+18QOoz2zkMI8f8oN8oxAFzDUI4zwXk6YCHC09530P5VVFepz8XNiyeyIb89kQzunMmzl11ArMuJaDoF5RXc9MZ7lPt8hHNWxw48PnU8CiGEEKL1sBAnUKiER8AuRPtWIkSrY7RBOfuD4wyU8wxwnAaYiGqwj6LLf0915VXEMfPDyewtTSSSc3uewh+nTcRlWYimU+HzM+v198grLSecTsmJPH3pFFyWhRBCCNGaWIgwLFTiX9BFMyCwHSFaLhOsLihHX3CciXKeAVY3QNFiBbaCoy8NQZc9BHYp1bGnJIlZH07mcGUskUw7vQ8PTz4X0zAQTSdo29z+zgJ25h8lnORoN7OnX0RytBshhBCitbEQ4akYjKQXsI9dBqE8hGgRzI4oR19w9AFHP5SjH6gYWhO7/HGUcwgq9hbqk/YtR1ctojq2HG3LTYsmUVwVRSSzhg3k7rHDEU1LAw8sWMoXObmE43ZYPHfFVDolJyKEEEK0RhYiMqMtRtIc7KLpYJcixEnFaINy9AVHX3D0QTn6g5FMq6cr0RV/Bu1Fxd1NvdDl6LIHqI61eR245ePzqQw4CEcBvxg3kuuHnIloen9Zvop3N20jHNMw+NPFk+nfIQ0hhBCitbIQP8zqhpH4HHbxdaB9CNHsGPFgdUNZ3cHqBlZ3lHUqGMmIMLSH43TlC0AIFfcLQFEXuvwPEMrnxyzd14W7PhmH3zYJxzQMHpp0Lhf374Noeq99uYlnV64lkvvGj2JU9y4IIYQQrZlFK+IPhQjZGrfDokacZ6ESfo8uuROwEaJJGKlgdUVZncE8BRw9UFYPMNogakB7+IaufBF0JSr+N4BBrfjXoz1v8mNe396Xh1cNx9aKcNwOiz9fMplzunVBNL0PtuzkoUWfEslNZw9ixlmnI4QQQrR2Fq2IZRjMfG0uFT4/w7p0ZFjXjgzqlIFlGPwYFXU+xB1Blz+GEA1GxYKZgbK6gNUZzK4oqytYnUHFIeqB9vBt2vMGaA8q4XHApEa0H7vsQUDzQ+ZsGsCT64YQSXxUFH+7YipnZKYjmt6y3Tnc8/5ibK0JZ1Kfntw55myEEEIIARYtyK6SAnomtiUSQyl+N3EsU194hW2H85m9aj3RTgf9O6QxrGtHhnXpSO+0dijCUzHXgX0YXfkP6ouKvR0IQSgPQvloOx9CeaC9iBZIucDsgDIzwMwAMwPMDJSZAWYGGImIBmZXciLtfR90EJX4BGBRXbriaQjuIRKN4vHVQ/nn1tOJpE1sDHOuvIhT27VBNL11uQe5Y+5CQrZNOIM7Z/L41PEohBBCCHGcRQvywo41HKvy8NjgiaRFxxNO55Qkbhk5hCeXfc5xHn+AVXv3s2rvfo5LjY3hrI4dGNalIyO7dSYtPo5vU3H3QugIumoRdadQMbNAufiG4v+nKyB0FOwitF0I9lGwi8AuhFAh2i4C+yjYhaC9iGbAiAejDcpoD2ZbMNPBaAdmO5SZDkZbMJIQTUhXASHC0VUfQrEXlfgXUC5+lP9rdOUcIgnYBvcuH8uHe7oRSWZSAi/NmEbHpERE09uZf5Rb3nofXzBIOKe2a8Mzl07BYZoIIYQQ4v9YtCBOw2LF4RwmLJzNvQPGML3bAMK5YeiZLN6RxdbD+ZyosKKSRdt3s2j7bo7LTEpgWJeODOvSkWFdOxEf5UIlPAl2Cdq/hjox24JyEZaKBSsW6ILi+xTfor1gHwW7EG2XgF0GuhTsMrBLQZeBXYrWpWCXgV0Kugy0DxGJCUYCGAmgElFGAhiJYCSB0QaMFDCSUUYKGKlgJINyIpo57eGHaN+nUDwLlfQ8qGgi0uXYpXcBIcLxBi1uXzKezw92JJI+aSnMnn4JKTHRiKaXW1TCDa++S1mVj3A6JSfy4oxpxEe5EEIIIcR/WLQgTtPkuPKAj/vWfcTHB3bx2OBJtI+O49tMw+CRKeO4eM5rBG2bH3KguJQ3i7fw5tdbsAyD0zukMbRLJsM6308/951Ydha1ZmZQL5QbzI5gdkQRmeIEugrsUtClYJej8YFdCtoH2ge6DLQPdBXoctA+0F7QFWhdBdoLdgUQBF3Ov2kbdDmNSsWBcoFygxELuFAqGoxowAVGLKhowAlGHCg34AIjDlQUqCiUigcjEYwEULGIFkh7+DHavwZdPBMj6QVQsYSjy34HoUOEU+Z38dNFE9mQ355IBmW6eW76FcS6nIimd6SsgmtfmUthpYdw0uLj+MdVF5MaE40QQgghvsuiBXGZFt/22eEcxi98gXsHjGF6twF826nt2nDj2QN5duVaqito23x14BBfHTjEMyvA7RhP/7b9GNZhL0M7HKR3aiEKTXUpM5MmpaLAjALacZyi+hQ1EQK7gv8Igvbwo1Q836MsUDEIUSvaQ7X4v8Quuhoj6e9gJPBt2vs22jufcAoqo5m1aAq7i5KJZGzXcv54+W1EWRai6RV5vFz36lzySssIJznazUszppGeEI8QQgghvs+iBXEaJicqD/i4b91HLDm4m0cHTaR9dBzfuHnEYD7emU320WPUhjcQYvWhdqw+1I7jUqM9jO+Sw33DPkeh+VFmJq2DCUYC35WCEI1OV1Jtga3YxddgJL0ERjL/EtyNLnuYcHJKEpn10WTyKuKI5MIe2Tw67R5My0I0vbIqHzNfe5ecwiLCiXO5eGnGxXRNTUYIIYQQ4Vm0IE7TIpLleXuY8OFs7uk/mundBnCc0zR5ZMo4rvz7m4S0pq4KPdEMSstDoakWMwMhROPR2kONBLZjF83ASP4nKDd2ya2gvZxoa2EbbvpoEkVVbiKZefoG7jp3HIajI6LpVfj8zHztXbYdLiCcKMviuSum0qt9G4QQQggRmUUL4jRMfkiZv4r71n3EisM5PDxwAilRMfTvkMZPBg3gH2u/pq4uOXUH53XZQ3UpMwMhRCOyPdRYcA/2sStQZjoE93GidXkduGXJBCr8TsJRaO4avIYbzlQY0TMQTc8bCPDTN95j06EjhGMZBn++ZDIDO3ZACCGEED/MogVxGibVsfjALtbk5/KL/qOZ3m0Ad4w+m2W7c9hfXEJtdU1N5r5xp0HVcqrNzEQI0Yh0JdVha8XOohR6pxTyL6GD6NBBTvRJbhfu+mQcvpBJOKay+d2IFUw7dR9GwnzAQDQtbyDIja+/x/r9hwjHUIrfXziBUd27IIQQQogfZ9GCuEyL6ir1V3Hfuo/44sg+fjdwPI9MGcfVL7+NpuacpsmTF51PdGJbdNkxtOdVfpRygtkWIUQj0h6qY1HOKfz683P45+T59E4pJJw3dvThoS9GYGtFOE4jxBNjlzKucw4q7mGwOiOaljcQYNZr81i//xDhKODB88cwqU9PhBBCCFE9Fi2I0zCpqQ/372BtwX4eGjiey87ox5tfb6GmZgw8nd7t23Kcir8fQvlo31J+kJkOGAghGpH28GNsrfjbxjOp8DuZ9eFkXr1gHp0TSvm2OZsG8OS6IUQS7/Tx7IQPObPdEZRrLCr6MkTTqgoG+ekb81m//xCR3D12BNPPPA0hhBBCVJ9FC+IyLWrjWFUlP1v5Lud36EW7uFjyyyuoiZfXbcQyTO4YPQzLMFGJT6KLroHARiJRZiZCiEamPfyYxTld2V2UzHFFVW5uXDSZV6fMo020B43i92uG8Y8tpxFJarSHFyYspFdKIRhtUQkPI5qWPxTi9rcXsGbfASK5a8xwZg47CyGEEELUjEUL4jRN6uKjQztITI6GcmokZNvMXrWetfsO8PsLJ9AlJQkj6XnsY1dAaB9hmZkIIRqZruSHaBTPbzyLbztQFs/Mj6bw0qT5PLZ6OAuzuxNJRlw5c87/gE4JpYCJkfgUGCmIphMIhbjt7Q/4LHsvkdw5+mxuPHsgQgghhKg5ixbEaVjUVYnlwYxzYJRb1NTmvCNcNPsV7h47ghkD+2Mkz8E+djnYx/geMwMhRCPTHn7Ixzld2V2UzIl2FyUz6a3plPqiiKR78jHmTFhA2xgPx6m4O8A5ENF0/KEQt7z1Piuy9xHJnaPP5qfDByGEEEKI2rFoQZymSX2wU4MYHhNCipryBoI8tOhTlu3O4dEp59E+6W/YRT8B7eU7zAyEEI3M9hCJrRXPbjiLSEp9UUQyMO0Qfz1vEXFOP8cp1yhUzI2IplMVDHL72wtYkb2PSG4/Zyg/HT4IIYQQQtSeRQviNEzqgzY0odQAZr6TcLq1ScEyFDvzC4nki5xcJj//Mj8/dwSX9XkKXXwLEOIbysxACNHItIdIlu7rwu6iZGpqdKd9/HHsEqLMIP9idUElPAEoRNPwBgL87M33WbV3P5HcOnIIt4wcghBCCCHqxqIFcZoW9cWODaEqQhiVJt/mdjh45tIppCfE8adPV/GPtV9ja0045T4fDy5cyuq9Pfj16AdJ8P+afzMzEUI0Ml1JOBrFcxvOoqamdt/NIyOXYRqaf1FujKS/gRGPaBplVT5ufH0eGw4eJpKfDh/EbecMRQghhBB1Z9GCOA2T+mS3CaC8Jsrm3359/hi6pCRx3D3jRnJer27cM38xuUUlRPLR9t2sy43m58NnMbXjbFBxYCQghPiPUCjE0aNHKSwsxOfzYds2paWlfFtSUhLHxcTEkJycTGpqKoZhUF1aewhn6b4u7DyWQk2c0e4Ij41ahkLzb7oK7fscFd0Z0fhKvVXMfG0em/OOEMl1Q87kztFnI4QQQoj6YdGCOE2T+pQWH8c5g7vzzurtHDehdw8uOr033zYgI513Z87g0Y+XM3fjNiI5Vunh3sUWn3a7jvtHbKAtQrQutm2TnZ3Nrl27yMrKIjs7m6ysLPLy8jh69ChHjx6lpgzDoE2bNrRp04YOHTrQrVs3evToQffu3enRowddu3ZFKcW/aQ8n0iie/fosampDfjvm7erJtJ47+Q+NLnsICKGir0E0noLyCq59ZS57CouIZObQs/j5uSMQQgghRP2xaEGchkV9SHK5uaXP2fykx5k4DJMjBZXkFBbx0KSxhBPrcvLolPOY0KsH9y1YQkF5BZEszo5i9YFh3H3uFi4/ox9CtFT5+fmsWLGC9evXs379er766ivKy8upT7Ztk5+fT35+Plu3bmXx4sV8W2JiIgMHDmTgwIEMHDiQyUMrMPiuT/Z1ZuexFGpKo3jw81EkunyM6byX/9DoskdAV6FibkI0vLzSMq59ZS65RSVEMmvYQO4eOxwhhBBC1C+LFsRpmNSFwzCZ0f0M7ug3gnhnFN/43cRzKaz0EB8VxQ8Z2a0z82+8igcXLmXJzmwiKfNpHly4lKW7svndpHNJi49DiJOdz+dj+fLlLF26lCVLlrB582a01jSlkpISlixZwpIlSzju6I6uJCeafEOjeO7rs6itkK3472XjeOH8BQxKy+PbdPmToL2o2DsQDWfvsWKue2Uuh8vKCUcBvxg3kuuHnIkQQggh6p9FC+IyTerixl5DuOv0czhRh8T4/489/ICvsrAb//33fc6dnZC9ScgOGRAymGGGLbJUVHCgUveoba2ritSq1Ufc1onaYtEqDigbDDMECCGBbEhISAJkkL3HGb+/vv4+j+3XEwIEyPhcF94Og+gOJ2sr3l00l++OZfPX7XtoaGvHlL0Fp5j7wec8Pm0Ci2KGoSBE36LX6zlw4ABr167lyy+/5Ny5c/RmdjYafmnXKT9yql24FO16LQ9tn80/rl1PmHMVv2Rseg8M9SiDlgMKomcdr6jirjXfUtXcwq/RKArLZyewOHY4WioJ3QAAIABJREFUQgghhLg8VPoRC63Kpfg8/wh3DR2Jo4U1l+q6qAjiA4bw3KZEduUXYkpjezvPbvqBLTkn+Mu10xjsYI8QvV1xcTEffvghn3zyCZWVlfQFFuYKZmYKPzOi8F56LD3Bw6aJk7VOhDlX8d+MLWsAHcqgPwMaRM84dqacu7/8nvrWNn6NVqPhr3NnMH94GEIIIYS4fFT6EXONyqVo6Gjj7cwknoubQU9wt7Plg5vnszXnBCu27KS2pRVTkotKuPaD1Tw4cQx3jY1DqygI0dvs2bOHN954g40bN6LX6+lLbG00/NLu4iFkV7lysaxUHbMDC7ghNJdo93K6Ymz5CgwtKA7/A2gRl2Z/YTEPr91Ic0cHv8ZMq+W1hbOZGRaMEEIIIS4vlX5E1WjQKAoGoxFTNIoGg9GAKf/MT2NJcDTB9q70lFnhIcQNGczzW3ayLTcfU1o7daxMTGLXiSJemjsdP2dHhOgNDh48yIsvvsjGjRvpq2ysFX7p/fRYLkaQYy3zg4+zaGgO9hbtdJexbQPU6VEcVgIq4uJ8k57F8s2J6A0Gfo2lqvLOorlMDPJDCCGEEJefSj9jptHSrtfx36xUM5aGxBHq4Mrvkv+NKXqjgVeO7mLVpBvpSS421rx9w7XsPFHIis2JVDQ2YcqR0jPM+WA1d46J5eFJY7BQVYS4GvLz8/nd737Hpk2b6OtsbTT8bFexH5nn3OguW/MOrgko4MawHCJcznGxjG2bobYdxeEtUMwRF+bj5MO8lpiEkV9nZWbG+zfNY6y/L0IIIYS4MlT6GXONlna9jp9pFIVZPkN5KjoBbxt7frS2MIPk8lOYsvNMAfvKipjg6U9PSwgJIM7Xm5WJ+/gqLRNTdAYDHycfZltuPs9dk8D4gCEIcaV0dnby+uuvs2LFCtra2ugP7Gw1/MiIwntpcXRHtHs5N4TmMjuwACtVR08wtidirF2GxvFDUKwR56c3Gnl+y07+dSQDUwZZWvDR4oVED/ZECCGEEFeOSj9jrlWhs50fxXv483T0VMIc3filp6OnMm/rpxiMRkx5IW0Hm6/5DVpFQ08bZGnB83OmMS00iOWbfqCsoRFTSmrrWLbmO2aFh7B81hScbawR4nJKS0tj8eLFnDhxgqvBzMwMW1tbNBoN9vb2/FJ9fT0Gg4HGxkZ0Oh0XwsZGw4/2lviSVeWKKfYW7cwLPs6iobkEO9ZwWXQcwlB7NxrHj0CxQZjWrtPxx3Vb2ZabjyludrZ8vHgBQ91dEUIIIcSVpdLPmGu0BNu78GR0AlO8gvg14Y7uXOc/jG8KMzAlv76KbwozuClwBJfLxCA/Ntx3G6/+sI+v0zIxYtrWnBMkFxbz8KSx3DpyBBpFQYie9v777/O73/2O9vZ2LhcbGxsiIyMJCgoiJCSEoKAgfHx8cHV1xc3NDScnJ7qjqqqKyspKqqqqKC4uJj8/n/z8fAoKCsjKyqKtrY1fsrVR+NF7aXH8mgiXc9wYlsPcoHys1E4uu47DGGpuQ+P4KWgcEP+v+tY27vtqPWmlZzElyNWZjxcvxMveDiGEEEJceSr9zEujr2GChz8aRaErf4iazOaSXFp0nZiy8tge5viGYWtmweViZ2HB83OmMSs8hGc3/sDpunpMaWhr58Vtu9mcfYLn50wlxM0FIXpCe3s7d911F1988QU9LTAwkISEBMaMGcPIkSMJDw9Hq9VyqVxcXHBxceHXdHZ2kpWVRUpKCgcPHiQxMRE7mzr2lvqScc6Nn7lYtTA78CSLhuYQ7FjDFdeZhaF2KRrHz0DjhPg/p+vq+c0X31NUXYspo4YM5m83zmOQpQVCCCGEuDpU+plJngF0h7uVLXeHjeGtzH2YUt3WzAc5B3gsajKX2zh/Xzbedzvv7TvIpweOoDMYMCX99FkWfryGO8bE8NDEsViZqQhxsZqamliwYAGJiYn0BDMzM6ZNm8aCBQuYNm0aAQEBXGlmZmZER0cTHR3Nvffey4/KCt/ktzvK0ShGRnud4aahOUz1K0LVGLh6tKCvwtjwAorDq4AWAdllldzzr3VUNTVjyqzwEF5dMAtzrRYhhBBCXD0qA9i94WNZW3iMs80NmPJJXgqLg6LxtrHncrMyU/lDwniuj4pgxZadHCgqwRSdwcCq5FQ2ZObxp5mTmRkWjBAXqrq6mtmzZ3P48GEu1dixY7njjju4/vrrcXZ2prep01gTP7iU16dux8u2ictGMQfFHjT2KBo30LqBMgi0bqBxA80gFI0baN1A4wxoEf9nW24+T6zfRmtnJ6bcNnIET8+cjEZREEIIIcTVpTKAWWpVfj98Eo8d2IAp7Xod/3N0N2/Fz+dK8XN25LNbr2d9Rg4v79hLbUsrplQ0NvHINxuZEhzA8tkJeNnbIUR3tLe3s2DBAg4fPszFsrS05JZbbuHBBx8kOjqa3myoSzuhsYe5GG3tRmrr9Jyt0FNeoaO23sDZch1llTpq6wycrdARFj6BN9/+DK2ZB6AgLowRWJV8mNd37sdgNPJrFODBiWN4eNJYhBBCCNE7qAxwC/2HsfpEKhnVZZiysTib20NiiXUdzJWiAAuGhzMxyJ9XduxlfUYORkzblV9ISvFpHpgwmqWjozHTahHCFKPRyN13301SUhIXw8zMjDvvvJPly5fj7e1Nn2Bs4T8oFqBxA60rimJPU6s1u/fmsHN3KqfPdlBeoae2Xs/pMh31DQbOJ3HvNlTL/+GNN95AXJjWTh1P/XsbW3JOYIqZVstf585g7rChCCGEEKL3UBngFGB57AwWbf8HRn6dEXgpPZFvZixF4cpysrbilfkzuSE6khWbEyk4V40pzR0dvJq4j6/TM/n9lHhmhYcgxK9ZuXIln3/+ORdj3rx5vPnmm/j7+9OXKFY3oljNB40TaJwBLb9k5whzb4bA4Tk89NBDJKXs4kK9+eabREVFcccddyC6p7KxiQe+/jeZZyswxdrcjLdvuJYJgX4IIYQQondREcS4eDPTZyhbS/MwJb3qDBuLc5g7JJyrYaSvN9/ffQurklP5ICmFdp0OU4pr6vjtt5uYcDSbp2dMIsDFCSF+lpeXx/Lly7lQXl5evPfee8yfP58+SfWnO8LDw0lMTGTNmjU8+uijVFdXcyEeffRRZsyYgZeXF6JrGWfLeeCrf3OuqRlTvOwH8cFN8wl1d0EIIYQQvY+K+MlT0QnsPJNPh0GPKS+n72SadzBWqhlXg7lWywMTRnNtZCh/3rKTpJPFdGXfyVPM/bCEJXFRPDJ5LHYWFoiBzWAwcPfdd9PW1saFWLFiBc8++ywajYaBQFEUbr31VhYvXswf/vAH3nrrLbqrvr6ee+65h40bNyJM25x9nKc3bKe1U4cp0YM9effGebjYWCOEEEKI3klF/MTH1oGloXF8nHsIU8paGvj78cPcHzGOq8nX0YFPllzHzhOF/HlLIuUNTZiiMxhYnZLOvzNzeXDiGG4ZOQKtoiAGpn/+858kJSVxIR577DGWL1+OoigMNFqtlpUrV9LQ0MBnn31Gd23atIlt27Yxc+ZMxH8yAu/uOcDf9h7EiGnXRoby4twZWKoqQgghhOi9VMT/eiRyAt8XZVHV1owp7+Ukc33AcNysbLnaEkICiPP15p09B/gi9Rg6gwFT6lrbeHHbbtZl5PLMzMnE+HghBhaj0chrr73GhXj55Zd54oknGMhUVeWTTz7BycmJ1157je569dVXmTlzJuL/NLa388T6bSQeP4kpWkXhsWkTuGtMLEIIIYTo/VTE/7IxM+eRYeNZfngbpjR3dvBW5j5eHDWb3mCQpQV/mjmZW+KieGn7HvYUFNGV7LIKFv/9K6YEB7B89hS87AchBoZt27aRkZFBdz311FM88cQTCFAUhZUrV9Lc3MwHH3xAdyQmJnLkyBFiY2MRkFt+jt9+u5HimjpMsTE3Z+XCWSSEBCKEEEKIvkFF/IfFQTH8Mz+NE3XnMOXrk0e5LSSWoQ5u9BZ+zo58tHgByUUlvLB1FyeraujKrvxCDp4qYdnYOO6OH4mlqiL6t1WrVtFd8+bN48UXX8Sk776Db76BRx6BMWP4SX4+fPABODjAs8+CwQB5efDxx7BuHTQ0QHg43HMPLFwINjagKFxxBgPs3w/vvw+7d4NOB6NGwe9+B/HxYGEBisKvefvtt8nKyiIpKYnuWLVqFbGxsQx06zJyWLE5kdZOHab4ONrz/k3zCXZ1RgghhBB9h4r4D1pF4ckRCdy1+ytM0RuN/OXID6yZuoTeZpy/L+vuuZXPDh7hg6QUWjo6MaW1U8e7ew+yLiOXP04dz8zwEBREf6TX69m5cyfd4eTkxIcffoiiKFw0oxEyMmDlSjAYYO1a8PKCTZvgs8+gogIefhgsLLiijEbYsQNefRXi4mDXLrC0hE8/heXL4cknYfZsUFV+jZmZGatXr2bYsGE0NzdzPlu3bmUga9PpeH7LTr49mk1XRvv58PYN1+JgZYkQQggh+hYV8f+Y7BXIRM8A9pYVYsqBilP8cDqfaYOD6W3MtVrujR/FdVERvLPnAGvTszAYjZhyuq6e3367iWEHUnls6gTG+Pkg+pfDhw9TW1tLdzz99NN4eHhwSTo7Yc8eaG6GZ56B2Fh+cscd0NoKSUmQlgZjx3JFtbfD119DRATcdx/4+fGTp5+G8nLYvh3CwyEwEFP8/f154IEHePXVVzmfU6dOcfLkSQIDAxloztY38Mg3G8k8W0FXbowZxnOzE1A1GoQQQgjR96iIX/VM7DRmb1qF3mjAlBfSdjDB0x8LrUpv5Gprw/NzpnFjzDBe2LqL9NNldCXzbAVLP/+Gcf6+/HHaBMI93BD9w759++gOW1tb7r77brqlvR0qK+H0aX5SXg7NzeDgAOfOQWEheHtDZCT/y8wMQkPhyBEoLISxY7miTp2CM2dg0SLw9uZ/WVjAyJGwcyecOweBgXTlt7/9LW+88QY6nY7z2bdvH4GBgQwkO08U8sT6bTS0tWGKhary2NTx3D4qGiGEEEL0XSriVwUNcuHmoBGsyU/DlJKmOj7NS+H+iHH0ZpGe7nx5582sz8jh1cQkqpqa6UpyUQnXr/qCGWHBPJYwHh9He0Tfdvr0abpj6tSpDBo0iG7JyoLHHwdra37S3g7t7bB0KbS3Q2cnWFuDmRn/wcoKNBpoa+NK0ev1KIqCprWVn1hZgaryH2xtQaeDzk7Ox9vbm7i4OA4ePMj5nD59moFCbzDw3r5DvLfvEAajEVO87Afx1g1zGO7lgRBCCCH6NhVh0qPDJrD+VDZNne2Y8rfsZBb6D8PD2o7eTAEWDA9nWmgQ7+07yOqUo3Tq9ZhiMBrZmnOCncdPcsvIEdw3fhQOVpaIvqmyspLuGDVqFN02fDjcdRfExPCTwkL4/HN+YmsLtrZQWwsNDeDgwE+MRqipgc5OsLfnctPr9dTW1tLY2IizszODHBzAzAyqq6G1Fayt+YnBAOXlYGkJ1tZ0x9ixYzl48CDnU1FRwUBQ0djE77/bTGrJGboyLTSQv86bySBLC4QQQgjR96kIk5wtbXg4Mp6/pu/ElBZdB68c3cUb4+bRF9hamPP4tIncGD2Ml3fsZVd+IV3p0Ov57OARvknP4u74OG4fFYOVmYroWyorK+kONzc3us3MDBwdwd2dnzQ0gJUVP3FygogIWLcOdu+GadPA3ByqquDIEVBVGDqUHxkMBgwGA4qioNVq6QkGg4GGhgby8/PZtm0bjo6OzJs3j0GDB0N4OKSnw7FjMGIEaDRw5gykpEBgIHh40B3u7u50R0VFBf3dttx8lm/6gbrWNkzRajT8PiGeZWPjUBBCCCFEf6EiunRn6Ci+OnmMwoZqTPn3qSwWB41glJsvfYWfsyMf3Dyf9NNlrEzcR2rJGbrS2N7O6zv38/eDadw/YTS3xEWh1WgQfYOVlRXd0draSo9QVRg/HvLyYO1aqK0FJydIS4O8PFi4EIYO5Uetra3k5+fT0dFBcHAwDg4OKIrCxWpqauLUqVPs27ePpKQkfH19WbhwId7e3qDRwI03wjvvwBdfQHExmJvDrl1gMMDs2eDpSXe0tLTQHTY2NvRXrZ06Xt+ZxOqUdLribGPNawtnM9bfFyGEEEL0LyqiS6pGw4q4Gdy+80tMMQJ/ObKDdbPuQqso9CXRgz1Zs/RGkotK+Ov2PZyorKIrNS2tvLhtN1+kHuPRyeOYGR6Cgujt3N3d6Y6ioiK6xd0dhg8He3v+l7U1hISArS0/CQyEBx6AjRthxw5obgY/P7jvPoiPB1XlR21tbezbt4/U1FTGjRvHuHHj8Pf3x9bWlgvR1tZGaWkpqamp7NmzB41Gw7Jlyxg1ahTNzc2cOnUKV1dX7GJj4Y9/hPXr4dtvQaeD8HBYtgwiIkCjoTuKioroDjc3N/qjjLPlPPb9Fopr6ujKSF9v3rh+Dq62NgghhBCi/1ER5zXew5+p3sEknsnHlOzaCtaePMbNQSPoi8b5+7Lu7ltYezSLd/cc5FxTM10pqq7lt99uIvpQGo9NnUCcrzei93J3d6c7EhMT6Zb4eIiP5z94e8O99/IffHzg/vvh/vsxxdnZmTvuuIPg4GA2b95MZmYm48aNY/To0QwePBgLCwu6otPpKC8vJzU1lb1799LU1MSMGTNISEhAo9GQmZnJ/v37MTMzY+7cudjZ2UFEBEREcLGMRiOJiYl0h4eHB/2J3mDgvX2HeD8pBb3BgCkKcE/8KH47ZRxaRUEIIYQQ/ZOK6JZnY6eRVF5Eu16HKa8e28VMn1AcLazoi7QaDTfHDGf+sDD+fiiNVcmpNLV30JX002Xc8o+vGR8whIcmjSV6sCei9wkLC6M7MjIySE1NJS4ujivJzs6OWbNmERMTw9atW9m3bx/Z2dmMHj2amJgYPDw8UFWVXzIajZw7d45jx46RkpJCcXExkZGRzJs3DxcXFwoKCjh06BDp6ek4OjqyYMECvLy86Albtmzh7NmzdEdYWBj9RXFNHY+v28rRM2V0xcnaipfmzWBKcABCCCGE6N9URLf42jpyZ+hIPsg5gCm17a28m5XEs7HT6cuszMy4f/xolsRG8XFyKqtT0mnX6ehKUmExSYXFjPP35XcJ8Qz38kD0HtOmTUNRFIxGI+fzwgsvsG7dOq4GNzc3br31VuLj49m0aRNbtmwhIyOD0aNHEx0djbOzM4qi0NDQQHZ2NsnJyRw/fpwhQ4bwyCOPEBAQwOnTp/n+++85cuQIiqIwf/58xo0bh729PT3BaDTy0ksv0R0WFhZMnDiR/mBdRg5/3rKTlo5OuhIfMISX583Azc4WIYQQQvR/KqLbHoqMZ92pLMpbGjFl9Ykj3BgYRaiDG32dvZUlj00dz+LY4by5O5mNWXkYjEa6klxUQvInJUwJDuDhSWOI8HRHXH2enp6Eh4eTnZ3N+axfv57vvvuO6667jqtBo9EQGBjIfffdR2ZmJps3b2b9+vVkZ2czevRotFot6enp5ObmYmtry5IlS4iNjaWhoYEtW7Zw5MgRmpubiY2NZfr06Xh4eKAoCj3lo48+Yv/+/XRHfHw81tbW9GU1La0s3/QDO/IK6IqlqvLHaRO4ZeQIFIQQQggxUKiIbrNWzXl8xBR+n/xvTNEbDTx/5AfWTF1Cf+HtMIhXF8xi2dhYViYmse/kKc5nV34hu/MLSQgN5OGJYwnzcEVcXQsWLCA7O5vuuPfee4mKiiIwMJCrxdzcnNjYWEJCQjh8+DCJiYmsWbOG6upqzMzMmDdvHgkJCRiNRvbv309qaiqVlZUEBQUxa9YsAgMD0Wq19KT09HQee+wxumvevHn0Zf/OzOWl7XuobWmlK+Eebry6YBZBrs4IIYQQYmBRERdkvl8kXxakc7iyFFMOVJxiW+lxZvqE0p8MdXdl1ZKFpJ8+y//8sI+00rN0xQgkHj9J4vGTjPP35bdTxjHC2xNxdTz44IOsXLmS9vZ2zqeqqoo5c+awb98+XF1duZrs7OxISEggPDycPXv2kJycjI+PD6GhoRw/fpykpCSKi4sZPHgwS5cuJSIiAktLS3pacXExc+fOpampie5wcHDgrrvuoi+qbGxixZadJB4/SVcU4LZR0fxx2gTMtVqEEEIIMfCoiAuiAMtjZ7Bg66fojUZM+UvaDiZ6BmClmtHfRA/24os7buKHvALe2XuA4xVVnE9yUQnJRSWM8/fl/gmjGTVkMOLK8vT05JZbbuHTTz+lO44fP87EiRPZvn07Pj4+XG0eHh4sWrSIuLg40tLS2LBhA9XV1Tg4OLBgwQJGjhyJvb09l0NeXh4zZszgzJkzdNcDDzyAnZ0dfYnBaOSfh4/yxq79tHR00hXPQXa8Mn8mo/18EEIIIcTApSIuWISjO4sCo/hXwVFMOdvcwKq8QzwcOZ7+SAGmDw1i2tAgdp0o5J09B8gpr+R8kotKSC4qIcbHi7vHjWRKSAAK4kp54oknWLNmDe3t7XRHXl4e8fHx7N69m4CAAK42jUZDYGAg1tbWGI1GIiMjGTNmDK6uriiKwuVw7Ngxpk2bRlVVFd3l4ODAI488Ql9SXFPHMxt3kFJ8mvOZGRbMX+ZMw97KEiGEEEIMbCriovwxagpbS45T19GKKe9nJ3Od/zC8bezprxQgISSAycH+bM05wbt7D3KyqobzSSs9y/1frSfC0537x49iamggGkVBXF4hISE8++yzPPPMM3RXaWkpCxcu5J133mHChAkoisLV5u7uzsKFC9FqtWg0Gi4Hg8HAjh07eOihh6iqquJCvPrqq7i7u9MXdOr1fLj/MB8kpdCp19MVeytLnpk5mXnDwhBCCCGE+JGKuCiOFlY8FBnPC2k/YEqbXscrR3fxdvwC+juNonBNRCizwkPYnpvPW3sOUFhVw/lkl1Xw0NoN+Do6cNuoEdwYMwxLVUVcPk888QTfffcdaWlpdFdGRgaTJk1i/PjxvP/++0RGRnI1aTQaNBoNl0t6ejr33XcfKSkpXKjJkyezbNky+oKc8kr+tGEHOeWVnM+U4AD+PGcq7na2CCGEEEL8TEVctKWhcawtzOB4XSWmbCzOYUlQNGPchzAQaBSFWeEhTA8LZnPWcT7cn0L+uWrOp6S2jhe37ebD/Ye5beQIlsQNZ5ClJaLnqarK6tWriY+Pp76+nguRlJRETEwMDz30EE8++SRubm70J6WlpbzwwgusWrUKg8HAhfLw8OAf//gHiqLQm9W1tvHGrv2sTctEbzTSFTc7W1bMTmBqaCBCCCGEEP9NRVw0raJheew0bkn8gq48l7qdzdcsQ6toGCi0isLcYUO5dthQdp0o5P19h8g4W875VDU188au/Xy4P4W5kUNZNjaOIU4OiJ4VERHB119/zZw5c9DpdFyIzs5O3njjDT766CMefvhhHn30Udzd3enLSkpKWLlyJR999BHt7e1cDGtra9avX4+vry+9ld5g4Juj2byxaz+1La10RQHmDQ/jTzMmY29liRBCCCHEr1ERl2Ssux8zfULZVnocU/Lrz/FlQTq3Bscy0ChAQkgACSEB7C04xftJh0grPcv5tHR08lVaJt8czeaa8BDuHBNDhKc7oufMmDGDv/3tb9x3330YjUYuVHNzMy+//DKvv/46N9xwAw8++CDjxo2jrzAajezcuZN3332XDRs2oNfruVharZbPP/+cUaNG0VsdKCrhxW27yT9XzfkMcXLghWunM2rIYIQQQgghuqIiLtmzMdPZW1ZIq64TU147toc5vmE4WlgzUE0M8mNikB9HSs/w8f5UduUXcj56g4ENWXlsyMojwtOd20eN4NrIoagaDeLS3XPPPVhaWrJs2TJ0Oh0Xo6Ojgy+++IIvvvgCPz8/5s2bx6JFixg/fjy9UXZ2NmvXrmXNmjUUFBRwqczNzVmzZg3XXXcdvVFZQyNv7NrP+oxczker0XBLXBS/T4jHyswMIYQQQojzURGXzMtmEL8ZOpp3spIwpb6jjTcz9/HnuJkMdLE+3sTe7E3G2XJWJaeyI68Ag9HI+WSXVfDE+m28uSuZW0ZGcWP0MOytLBGX5vbbb8fW1pYlS5bQ3t7OpTh16hRvv/02b7/9NkFBQUyfPp0ZM2YwZcoU7O3tuRqqq6tJTExk+/bt7Nixg5KSEnqKnZ0d69atIyEhgd6mtbOTD5JS+OxgGu06HecT7uHGC9dOJ8LTDSGEEEKI7lIRPeL+iHF8V5TJmeZ6TPkiP42bA6MJc3RDwHAvD96+4VpKauv49EAa3x/Lpk2n43zKGhpZmZjE3/YeZN6wMG4bOYJgNxfExbvuuuvYtWsXN910E6WlpfSEgoICCgoKeP/999FoNAwdOpS4uDji4uKIiooiJCQEDw8PetLp06fJz8/n6NGjpKamkpqaSn5+PkajkZ4WGhrK2rVrGTZsGL2JEdiYmcerifuoaGzifAZZWvDQxDHcOnIEWo0GIYQQQogLoSJ6hKVW5fERU/jt/nWYojcaeS51G19Nvw0F8TNfRwdWXJPAI5PHsubwUdakHqO2pZXzae3U8VVaJl+nZTLG35fFscOZGhqIqtEgLtzYsWNJT09n6dKlbNq0iZ5kMBjIyckhJyeH1atX8zM7OzuCg4MZPHgwrq6ueHh44OrqipWVFYMGDUKr1WJhYYHRaKSjowOdTkdjYyMtLS1UVlZSXl7OuXPnKC0tJT8/n5aWFq6EJUuW8OGHH2Jra0tvcqCohDd27efYmXLOR6MoLIqO5NEp8ThZWyGEEEIIcTFURI+ZOyScLwvSOVhRjCmp50rZXJLLHN8wxH9ysrbi4UljuXf8KDZnH+eDpBSKqms5HyNwoKiEA0UluNjasHB4ODfHDmOwgz3iwjg7O7Nhwwbee+89/vSnP1FfX8/l1NjYSFpaGmlpafQFrq6uvPbaa9x22230JsfOlPPmrv0kF5XQHcO9PHhm1hSivD0QQgghhLgUKqJH/TluBtds/gR8/+unAAAgAElEQVS90YApL6b9wBSvIKxVM8T/y1yrZcHwcOYNC+PgqVJWH0pnd34hRs6vqqmZj5MP88mBVMb4+XBTzDCmDw1Cq9EgukdRFB588EGuv/56Hn/8cT7//HMGOkVRuPXWW3n99ddxcXGht8g/V827ew+yLecERs7P3c6W3yfEM394OApCCCGEEJdORfSoYHtXbg4awZr8NEwpb2nko5wDPDp8IsI0jaIwzt+Xcf6+5FWcY3VKOhuzjtOu03E+BqOR5KISkotK8LK3Y1H0MK4fEYG7nS2iezw8PFi9ejV33nknzzzzDMnJyQxE06dP5y9/+QujR4+mtyisquHtPQfYmnMCI+dnqarcNTaWe+JHYWWmIoQQQgjRU1REj/tD1CQ2l+RR296CKR/lHuS6gOH42jogzm+ouysvzZ3Bk9MnsS4jh88OHuFsfSPdcba+kbd2J/POngOM8fNh/vAwZoaFYGWmIs5vypQp7N+/n61bt/Lcc8+RkpLCQDB58mSef/55JkyYQG9xtr6RD5IO8c3RbPQGA90xJTiAZ2ZNZrCDPUIIIYQQPU1F9DgHcyseHTaB51K3YUqbXsdzh7fy2ZSbEd03yNKC20dFsyQuim25+XyecpT002fpDoPRSHJRCclFJby0fQ9zI4dyXVQ4EZ7uiPObNWsWs2bNYv/+/fztb3/j22+/paOjg/7EysqKxYsX8+CDDxITE0NvUd7QxEf7U/g6PYtOvZ7uiB7sye8TxjNqyGCEEEIIIS4XFXFZLAmO4V8n08mtrcSUPWWF/HA6n2mDgxEXRtVomBMRypyIUAqravjuWA5fp2dS39pGd9S3tvHPw0f55+GjBLo4sTAqnIVREbjYWCO6Fh8fT3x8POXl5fz973/nyy+/JCMjg75s1KhR3HzzzSxduhQnJyd6i9LaelanpPNVWibtOh3dEezmzEMTxjAzPAQFIYQQQojLS0VcFlpF4c9xM7lpx+cYMW3FkW2M8/DDWjVDXJwAFycemzqeByaMZmNWHv9KyyC7rJLuOllVw8rEJN7clcyEQD/mRIYyLTQQKzMzhGkeHh48+eSTPPnkk+Tm5vLVV1+xbt06MjIyMBqN9GYajYa4uDgWLlzITTfdhL+/P71JdlkFH+4/zI68AgxGI90R4OLEI5PGMis8BAUhhBBCiCtDRVw2ca4+XDsknA3FOZhytrmB97OT+UPUJMSlsTY348aYYdwYM4zMsxV8eeQYm7OP09qpozt0BgO78gvZlV+IlZlKQkgg10aGMiHQDzOtFmFaWFgYK1asYMWKFZSXl/PDDz+wY8cOdu/eTUlJCb1BYGAgU6ZMYfr06UydOhVnZ2d6EyOwr+AUnx08QnJRCd012MGehyaOYd7wMLSKghBCCCHElaQiLqtnYqez++xJGjvbMeWj3IMs9I8kYJAzomcM83JnmNcMnpoxiQ2ZeXx3LJvMsxV0V2unjk3Zx9mUfZxBlpbMCAtibuRQRg4ZjFZREKZ5eHhw6623cuutt/KjiooKUlNTOXz4MEePHiUvL4+ioiI6Ojq4HCwsLAgKCiI0NJSYmBji4uKIi4vD2dmZ3qhNp2NdRg6rD6VzsqqG7nKzs+X+8aNYFB2JmVaLEEIIIcTVoCIuK1dLGx6OHM9L6YmY0mnQsyJ1O6sTFiN6lp2FBUviolgSF0X+uWq+O5rNvzNzqWpuobsa2tr4Jj2Lb9KzcLW1YfrQIGYMDWLUkMFoNRpE19zd3ZkzZw5z5szhZ3q9nuLiYvLz8ykrK6OiooKKigqqqqo4d+4cOp2O5uZmOjo6aG9vR6PRYGZmhoWFBdbW1piZmeHq6oqrqyseHh64urri7e1NUFAQvr6+aDQaervyhib+dSSDf6VlUNvSSnc5WltxT/xIlsRFYamqCCGEEEJcTSrisrtz6Ei+K8okr64SU5LKi9hSksds36GIyyPY1Zknpk/ksWkTOHSqlK/SMkk8fpJOvZ7uOtfUzBepx/gi9RiDLC0ZF+DLlGB/ZgwNxtrcDNE9Wq2WgIAAAgICGEiMwIGiEr5Ky2RHXgF6g4HucrGx5ubY4dwxJgY7CwuEEEIIIXoDFXHZaRUNz4+cyU07PseIaX9J28EkrwCsVXPE5aNVFMb5+zLO35eallY2ZuWxLiOX7LIKLkRDWxtbc06wNecEKzbvZGKQHzOGBjMp2A87CwuE+FldaxvfHs3mq7QMimvquBB+zo7cM24k84YNxUyrRQghhBCiN1ERV0Scqw/z/SJZdyoLU8pbGnknK4knRiQgrgwnaytuHxXN7aOiOVVdy8bs42zMyqOoupYL0drZybbcfLbl5mOm1RLn683EID8mBvoR5OqMGHj0RiP7Txbz7bFsdh4/SYdez4UY7uXBb8bFMX1oEBpFQQghhBCiN1IRV8zTMVPZebaAho42TFmVm8ICv0hCHdwQV5afsyMPTRzDQxPHkH+umq05J1ifmUtpbT0XolOv50BRCQeKSnhlx15cbG2ID/AlITiA+MAh2FlYIPqvsoZGNmbl8eWRDM7UNXAhNIrCpCB/bh8dzTh/X4QQQgghejsVccW4WNrw6LAJPH9kB6bojQaWp27jX9NuQ0FcLcGuzgRPGsuDE8dwpPQsm7KOsz0vn+rmFi5UVVMz6zNyWZ+Ri7lWS6yvNxOD/Bjn70uImwsaRUH0bafr6tmam8+2nHwyz5Zj5MLYWpizKHoYt40cgbfDIIQQQggh+goVcUXdFhLHN4UZ5NRWYMrhylI2Fmczd0gE4urSKAojfb0Z6evN8tlTSD99ll0nitiel09xTR0XqkOv50BRCQeKSviRjbk5Ud4ejAvwZZy/L2EebmgUBdH7nalrIPHESbbknCC99CxGLlyAixPXRYVzU8wwBllaIoQQQgjR16iIK0qrKDw/ciaLtq/GiGkvHPmByV5B2JlZIHoHjaIQ6+NNrI83j00dT3ZZBTvyTrLjeAEF56q5GM0dHSQXlZBcVMKPnKytGOXnw+ghgxnt50OgixOi9yg4V832vAK25eaTV3GOi2Gu1TIzPJglsVHE+HghhBBCCNGXqYgrLsZlMNcHDOebwgxMOdfWzBsZe1keOx3RO0V4uhPh6c6jU8ZRVF3LjrwCEo+fJPNsOXqjkYtR09LK1pwTbM05wY8crCyJ8vYkytuDKG9Phnt7MMjSAnFlVDU1c6ColAOnSjhQVMLZ+kYuVqCLE9ePiGRhVDhO1lYIIYQQQvQHKuKqeCp6Koln8qltb8WU1SdSmecXwQhnL0Tv5u/syD3xI7knfiR1rW0knSxmT0ERSSdPUdPSysWqa21jT0ERewqK+JECBLg4EeXtSdRgD0Z4exLs6oxWo0Fcuqb2DlKKSzlQVMqBohLyz1VzKewsLLgmIoTrRkQwwtsTIYQQQoj+RkVcFY4WVvx++CSePbwVUwxGI8sPb+X7mXeiVRRE3+BgZcm1kaFcGxmKwWgku6ySPQVF7C0oIvNsBQajkYtlBE5W1XCyqobvjmXzI3OtlmA3Z4a6uxLi5kKomwtD3V1xtLZCmKY3Gik8V01WWSXZZRVknC0nq6wSvcHApTDTahnr78PcyKHMCAvGUlURQgghhOivVMRVszgomm8KMzhWfRZTsmrK+Wf+EZaGxCH6Ho2iMMzLnWFe7jw0cQy1La3sLyzhUHEph06VUlxTx6Xq0OvJLqsku6ySX3KzsyXUzYWh7q4EuTrh5+zIEEcHHK2tGGj0RiOF56rJKqsku6yCrLJK8ioqae3U0RPMtVrGBw5hZlgwCSGBDLK0QAghhBBiIFARV41GUfhz3Eyu3/539EYjprx2bA8zB4fiYW2H6Nscra24NjKUayND+VFFYxMHi0o5VFxKSvFpSmvr6SmVjU1UNjax7+QpfmmQpQW+jg4McXJgiJMDPo72+Dk54utoj7OtDQp9V0VjE8U1dRTX1HGqppaSmjqKa+sorq6jTaejJ1mqKuMDhzArLIQpIQHYWpgjhBBCCDHQqIirarizJ0uCY/j8xBFMaeps5y9pO/jb+OsQ/Yu7nS3zh4cxf3gYPzpb38ChU6c5VFzK0dNlnKquxUjPamhrJ6usgqyyCv6bqtHgbGONxyBbXGxt8LCzxcXWBo9BtrjY2OAxyBZbCwvsLM2xs7DgSmnu6OBcYzM1La3UtLRyrqmZmuYWalpaqWhsoqS2jpKaOlo7dVxOLrY2jPX3YUpwAFOCA7A2N0MIIYQQYiBTEVfdH6Mms+P0CcpbGjFlS0keO88UkOAdhOi/vOwHsTAqnIVR4fyooa2No6fLOXamjGNnyjl2ppyGtjYuF53BQEVjExWNTXTHIEsLbC3MsbEwx9bcAjtLc2wtLLCzMOe/WZubo2o0/FJrZyedej1N7R3oDAYa29rRGQw0d3TSodPR1N5BTUsr7TodV4OdhQUjhwxmrL8PY/19CXZ1RgghhBBC/B8VcdXZmlnwp5hpPJz0PV15LnUbY9yHYK2aIQaGQZaWTAzyY2KQHz8yAqeqazl2poyjp8vJKa/gRGU1rZ2dXA0Nbe00tLXTX1ioKiMGezLW34ex/r4M8/JAqygIIYQQQohfpyJ6hTm+YXzvncnOMwWYcqa5nnezknh8xBTEwKQA/s6O+Ds7smB4OD+rbGwiq6ySk1XV5J+rJrusksKqGgxGI+LXaTUa/J0difB0I9LTnQhPNyI93bFQVYQQQgghRPeoiF7jz3EzOVhRTIuuE1M+zj3E3CERhDm6IcTP3OxsSbCzJSEkgJ81tXdworKKE+eqKK6uo7i2jpKaOkpq62nX6RhIbMzN8Xd2JMLTjUhPdyI83Ql1d0HVaBBCCCGEEBdPRfQa3jb2PBARz8pjuzFFbzTwp5TNfDNjKRpFQQhTbC3MifHxIsbHi18yAmX1jZTU1lFcU0dJTR3FtXWUNzRS0dhMdXMLeoOBvsbWwpwhTg74OjowxMmBIU4ODHFyYIiTIy421gghhBBCiJ6nInqVe8PHsLE4h7y6Skw5Wn2WtYXHuClwBEJcKAXwsrfDy96OMX4+/DeD0Uh1cwuVjc1UNjVR2dhMZWMTlU3NVDe30NTeQVN7Bw1tbTS2tdPU3oHOYOBy0CoKjjbWOFlb4Wprg7ONNU7WVrjYWuNsY42TtTUuttZ4DLLDxcYaIYQQQghxZamIXkWraHh+5Exu2vE5Rkx7JX0X07yDcba0QYiepFEUXG1tcLW1IQI3uqNNp6OpvYOmtnaaOzowAg1t7fy3tk4dHTodP7OztEDVaLC1MMdMq8XKzAxLMxULVYu1uTmqRoMQQgghhOi9VESvE+fqww2BUaw9eQxT6jpa+Wv6TlaOnYsQV5ulqmKpqrjYWCOEEEIIIQYOFdErPTkigcTT+dS0t2DK90WZXOc/jHEefgghhBBCCCHElaYieiVHCyueip7KHw9uwBQj8OShTWydcw/WqhlCCCGEEEIIcSWpiF7ruoBhfFeUyYGKU5hyurmed7L28cSIBIQQQgghhBDiSlIRvZYCvDBqFtdsXkW7Xocpq3JTmOMbTqSTB0IIIYQQQghxpaiIXs3fzol7w8bwdlYSpuiNBp46tIl1s+5Eq2gQQgghhBBCiCtBRfR6D0bGs6U0j/z6KkzJrq1gVW4K94aPQQghhBBCCCGuBBXR65lptLw8eg6LdqzGYDRiyluZe5nlE8oQO0eEEEIIIYQQ4nJTEX1CtIs3S4Ji+Gf+EUxp0+t4KmUza6begoIQQgghhBBCXF4qos94fMRkEs/kU9bSgCkHK4r5tjCDGwKGI4QQQgghhBCXk4roM2zNLHhx1Gzu2v0VXfnLkR1M8AzA3coWIYQQQgghhLhcVESfMtkrkDm+YWwqycWUxs52Xkz7gbfjFyCEEEIIIYQQl4uK6HOei5tBUnkR9R1tmLKxOIe5Q8KZPjgEIYQQQgghhLgcVESf42Jpw1PRU3ny0Ca6svzwVka7+TLI3BIhhBBCCCGE6Gkqok9aFBjFhuIc9pcXYUpFaxOvZezhz3EzEUIIIYQQQoiepiL6JAV4YeQsrtmyilZdJ6asyU/jWt9wRrr5IIQQQgghhBA9SUX0WUPsHHk4cjz/c3QXphiMRh47uIEt1/wGa9UcIYQQQgghhOgpKqJPuztsNJtLcsmqKceU0qY6Xs/YyzMx0xBCCCGEEEKInqIi+jStouGV0dcyf9un6AwGTPn78cPMGBzCKDdfhBBCCCGEEKInqIg+L8zRjd8MHc0HOQcwxWA08uShzWyavQwr1QwhhBBCCCGEuFQqol94dPhEEs8UkF9/DlNONdbwesZe/hQzFSGEEEIIIYS4VCqiXzDXaHllzBwWbf8HeqMRUz47nsKMwSGMdPNBCCGEEEIIIS6Fiug3Rjh7sWzoaD7KPYgpBqORJw9tYtM1v8FSqyKEEEIIIYQQF0tF9Cu/j5rErrMF5NdXYUpRYw2vZ+zh6eipCCGEEEIIIcTFUhH9irlGy8uj53DjjtXojUZM+TQvhRmDQ4hz9UEIIYQQQgghLoaK6HeiXby5c+goVuUewhSD0ciThzazcfYyLLUqQgghhBBCCHGhVES/9FjUZPacPUl+fRWmFDZU82bGXp6MTkAIIYQQQgghLpSK6JfMNVr+OnoON+1Yjd5oxJRVeYeYNjiYOFcfhBBCCCGEEOJCqIh+K8bFm6WhI/k0LwVTDEYjTx/awr9n34WlVkUIIYQQQgghuktF9Gt/GD6JnWcKONVYgykFDVWsPLabZ2KmIYQQQgghhBDdpSL6NSvVjFdGz2Fx4j8xGI2Y8lleClO8Aon38EcIIYQQQgghukNF9Hsj3XxYGhLHZ8cPY4oR+OPBjWy+5jc4mFshhBBCCCGEEOejIgaEP0RNJvFMASVNtZhS3tLIc4e381b8fIQQQgghhBDifFTEgGCtmvH6uLnctONz9EYjpmwozmba4GDmDglHCCGEEEIIIbqiIgaMGJfB3B02hg9yDtCV5Ye3MtLVBw9rO4QQQgghhBDCFBUxoPx++CSSK06RUV2GKfUdbTyavJ41U29BqygIIYQQQgghxK9REQOKqtGwcuxc5m35lDa9DlNSKkt4PzuZhyLjEUIIIYQQQohfoyIGnKBBLjwWNZkX0n6gK29l7mOs+xBiXQcjhBBCCCGEEP9NRQxIdw4dxb6yQvaUFWKK3mjgkf3r2HTNMhzMrRBCCCGEEEKIX1IRA5ICvDT6GuZs/oS6jlZMKWtp4NmUrbwzfiFCCCGEEEII8UsqYsDytB7EX0dfw/37vqUrm0pyGX/Sn5sCRyCEEEIIIYQQP1MRA9pMn1BuCY5hTX4aXVmRup1hTp6EO7ojhBBCCCGEED9SEQPeMzHTSKs6TW5tJaa063U8lPQ9/551J7ZmFgghhBBCCCGEihjwLLQqb46bz4Jtf6dV14kppxpreOrQZt4ZvxAhhBBCCCGEUBHi/yfY3pWno6fy7OGtdGVTSS6jTvhyW0gsQgghhBBCiIFNRYj/v1uCY0gqL2Jb6XG68mLaD0Q5ezHc2RMhhBBCCCHEwKUixC+8MnoOubWVlDTVYkqHQc8DSd+yYdYyHC2sEEII8f+1BydgVRcIv8e/5/DnsAooCAKSSSnumEpJGJg4ptes0OqiWaGQW2a+ljs1zWhpuZRbaplSObk1mlOaDhYiU5hlJeIuTYwhqKCIsqgczn147uMTwwsuJEj5+3xERERuTQYiFbhZHFkSPoD+WxMosZZSneOFBbyY+inLuj+OCRERERERuRUZiFTSysObqZ168tK3W7iSpONHeWf/Toa36YqIiIiIiNx6DESq8ESLTvyQm8X6f+/lSmbv2c5dXn7c7X0bIiIiIiJyazEQqcZfQ3qz93Q2R87mUh2rrYzR/9rAZ31i8XZyRUREREREbh0GItVwNuxZfN8AHt66gsJLF6lObkkh//P1Rj7oMQg7kwkREREREbk1GIhcQaCbJ6/d/X94/qtPuJLUE5nM35vC/3QIR0REREREbg0G9UB2djaHDh3il19+ITs7m6ysLE6dOsWlS5coKiriwoULlHN0dMTJyQkHBwc8PT1p2rQpTZo0oWnTprRq1YomTZogN16/Zm345kQmHx39geo42Bk0dXFHRERERERuHQZ17NSpU6SkpJCcnMyePXvYu3cvp0+f5kbw9PSkXbt2dOzYkfDwcMLDw/Hy8kJ+u5e79CLtdDbpp3OozNfZjbfv60+wpx8iIiIiInLrMKhlNpuNXbt2sWHDBj777DP279+PzWajNuTl5ZGcnExycjLz5s3DZDLRtm1bHnzwQaKioggJCcFkMiHXz2K2Y/F9A+j3+XLyLxZzWahPM+aHPYKnowsiIiIiInJrMaglR44c4Z133mH16tX88ssv3Aw2m4309HTS09OZOXMmAQEBREdHM2zYMO68807k+vi7uDMr9EGGJa+j3PA2obwQ3B07kwkREREREbn1GNxANpuNTz/9lAULFvDFF19gs9moT44dO8asWbOYPXs2PXv2ZMyYMfTt2xeTyYRcm0j/Foxpfx/tGjUh0r8FIiIiIiJy6zK4QbZt28bkyZP57rvvqO9sNhuJiYkkJibSoUMH4uPjefTRRzGZTMjVPd/+PkRERERERAx+o++//55Ro0bxzTffcL1MJhO33347bdu2pV27drRo0YImTZoQEBCAj48P9vb2NGzYkIry8/O5ePEiJ06c4NixY+Tk5HD48GH27dtHeno6mZmZ2Gw2rlVaWhqPP/44oaGhLFq0iLvuugsRERERERG5OoMaOnfuHFOmTGHx4sVYrVauVbt27YiMjKR79+5069YNLy8vroeHhwflvL29ad++PZXl5uaSkpJCcnIy27ZtY9++fVyL1NRUQkJCGDVqFK+++ioNGjRAREREREREqmdQA9999x0DBw7k6NGjXIuOHTsSHR1N//79adGiBbXJy8uLqKgooqKiKHf48GE2bNjARx99RFpaGlditVpZsGABW7ZsYdWqVXTu3BkRERERERGpmsF1mjdvHhMmTODixYtciYODAwMHDmTEiBHcc8893CwtW7Zk4sSJTJw4kdTUVJYsWcKaNWu4cOEC1Tly5AhhYWHMnj2b0aNHIyIiIiIiIv+bwTWy2WxMnDiRWbNmcSUWi4WYmBheeuklmjZtSn0SGhpKaGgo06dPZ/bs2bzzzjuUlJRQlQsXLvDcc89x5MgR3nzzTcxmMyIiIiIiIvIrg2tw6dIlnnjiCdatW8eVREVF8dZbb3HbbbdRnwUEBDBv3jzGjRvH888/z8aNG6nO/PnzOXHiBCtXrsQwDKT2xMXFcfvttxMbG4uvry/lkpKSmDVrFvHx8dx7772IiIiIiEj9YXAVNpuNoUOHsm7dOqrj5+fHO++8Q9++ffk9adasGZ988gmfffYZw4cP5/jx41RlzZo1ODo6smLFCkwmEyIiIiIiIgIGV/Hiiy+ycuVKqvPggw+yYsUKvLy8+L168MEH+fHHHxkyZAibNm2iKu+//z4+Pj68/vrr3ChFpZdwNuwRERERERH5PTK4gjVr1jB37lyqM3XqVKZNm4bJZOL3rnHjxnz66adMnTqVGTNmUJU33niDkJAQHn30UX6LMxeKePfAN6SfzuGDHgORXxUXF3PmzBksFgvlCgoKKC0tRURERERE6h+DamRmZjJixAiqYjKZWLhwIaNGjeKPxGQy8dprr+Hn58eYMWOw2WxUNmzYMO6++25uu+02rlf+xWLeP/Qd7x3cxflLF+jSOAD5bytXrmTt2rUYhkG5oqIi7O3tERERERGR+segGnFxceTn51OVuXPnMmrUKP6oRo8eTUlJCePHj6eyM2fOMGzYMLZs2cK1Kiq9yAeHd7NkfyoFF0uQ6g0aNIjo6Gi8vb0p9/XXX7NkyRJERERERKT+MajC5s2b2bZtG1UZN24cY8eO5Y/uxRdf5NixY8yfP5/Ktm7dytatW3nggQe4kuLSS6zO+JHF+74mt6QQuToXFxe8vb3x9fWlXKNGjbC3t0dEREREROofg0rKysqYMGECVQkJCWHmzJncKmbNmsVXX33F7t27qWzixIn06tULk8lEZZfKrHz8Uxrz9qZwsvg8IiIiIiIif0QGlXz55Zfs27ePyuzt7fnwww+xt7fnVmGxWPjwww8JDg7m0qVLVLRnzx62b9/O/fffz2WlZWX8I3Mf8/amcOx8PnJ9mjVrhq+vL/b29lzWoEED7rzzTlxdXRERERERkfrFoJLly5dTlZEjRxIUFMStpnXr1jzzzDO8/fbbVLZ8+XLuv/9+rDYbn/w7nQXpKfznfD5SMy+99BKVdenShS5duiAiIiIiIvWPQQVFRUVs2LCBygzDYNKkSdyqpkyZwtKlS7FarVT09/XrGfTXSSw4kMrB/JPIjZGTk0NJSQk+Pj44OTkhIiIiIiL1k0EF33zzDSUlJVTWt29ffH19qW2nT5/GYrHg7OyM2WymXHFxMefOncPb25ubxd/fn969e7Np0yYuc2p3B40G9ubZ1I3IjfXPf/6Tn376iaeeeorAwEBERERERKR+MqggNTWVqkRFRVEXRo4cSdeuXYmLi6NBgwaU27RpEy+//DL79+/nZhowYACbNm3CqUMLGj7WE4fApvxW+8+c4KEty6kPpof0oYOnLyIiIiIiItfKoII9e/ZQlbCwMG51Hh2C8J0ai2ObQG6UotKLpJ/OoT4oLL2AiIiIiIjI9TCoIDc3l8osFgt33HEHt6of846zMP1ffJl1FMc2gYiIiIiIiMj/Z1BBbm4ulXl6emIymagr6enpbNy4EScnJ8rt3LkTm81GXdt/5gRz05L5MusoIiIiIiIi8r8ZVGC1WqnMzs6OupSRkYHJZMJisVAuIyMDm81GXbIBe/KOs//MCURERERERKRqBhV4enpSWV5eHnWpd+/ePPnkk7i6ulJu48aNzJgxA5vNRmZmJsnJydjZ2dG8eXPCwsKoDSZg4DBHKqQAAA9BSURBVJ138WhgBz7+KY15e1M4WXweERERERER+ZVBBZ6enlRWXFxMdnY2vr6+1AUHBwfc3Nxo0KAB5ZydnTGZTJQ7d+4cNpuNCxcusH79elq2bEnjxo2pLfZmOwbeeReP3N6Opd8n8+buL7Fzd0VERERERETAoIJWrVpRla+//poBAwZwswUGBtKmTRvy8/PZtWsX+fn5NG7cmNrmZNjjn3mGX16Yi1ufMNz7hGF2dkRERERERORWZlDBvffeS1U2b97MgAEDqG1jx47F09MTR0dHLrvnnnuYO3cuJpMJFxcXrFYr//73v7Farfj6+lJXNm/eTFnxBfLXf0nBP1Nxf+Be3PqEYXZyoKY6evmzovv/pT5wtbcgIiIiIiJyPQwqCA0NxWw2U1ZWRkXr1q1j3rx5uLq6UptCQ0OpLCAggICAAMrZbDays7NJSEhg6NChuLq6UhcKCgpYt24dl5WdL+bM37/g/LZviN+yltWZeymxlnK9DJMZd4sj8t/uuusumjdvTsOGDRERERERkfrLoAJPT08iIyNJTEykonPnzrF48WLGjx/PzWKz2SgsLOSNN96gb9++hISEUFcWLVpEYWEhlfXoGsbLXfvwbMdw3ju4i+UHd3GxzIr8Nu3bt0dEREREROo/g0qGDh1KYmIilb322msMHToUT09PbgabzcY//vEPNm/ezKlTp9iyZQujRo0iKCiI2pSbm8vrr79OVWJjYynn6ejChI73M7hFZxbt+4q1GXuw2sqQa2cttZKWmIZrI1dua3cbDi4OWC9ZSUtMo0HjBgS0DcDB2QEREREREak/DCp55JFHaNKkCTk5OVSUn5/Ps88+y+rVq7kZzGYz/fv354EHHsDOzg6z2YyzszO1beTIkZw9e5bK/Pz8eOihh6jIz8WNV+/uw4g2oSzZn8rajB+x2mzI1ZlMJrBBWmIaTq5O+LXy4+cff+bod0fp0LMDZjszIiIiIiJSvxhU4ujoyCuvvMKIESOobM2aNfzpT38iNjaWm8HR0RFHR0fqytKlS/n444+pyl/+8hccHByoSoCrB6/e3YeYoBDm7U3h8/8cwIZcidnOTFBYEDkZORxOPUxZWRlp29Jo2qopTVs3xd7BHhERERERqV8MqhAXF8eCBQvYt28flY0cORJ/f3969+7NH9kXX3zBmDFjqErr1q2JiYnhalq4e7GwWxSH8sNYkP4Vm/9zAKmes7szHR/oSMrfUsg6lIWHjweBnQNxcndCRERERETqH4Mq2NnZsXTpUrp3705paSkVXbp0iccee4zPP/+cbt268Ue0Y8cOHn74YS5evEhlhmHw3nvvYRgG1yrIw5uF3aL4Ifdu5qQl83XOz0jVfAJ9cPFw4T97/0P7yPY09GuI2WxGRERERETqH4NqhIWFER8fzyuvvEJl58+fp2fPnnzwwQc8/vjj/JF88sknDBo0iOLiYqryyiuvEBoaSk3c5eXPyh6D+O7UMebsScZqsyH/7eTPJynML8Tdx53cY7kUFxRjcbIgIiIiIiL1j8EVxMfHk5qaytatW6nswoULDBo0iIMHDzJ16lTs7Oz4PbNarUybNo1p06ZRVlZGVfr27cvkyZP5rbo0DmBVz8EczD+J/Opi8UW+3/Q9Xrd5EdwrmB8+/4HMvZm0cmuFxcmCiIiIiIjULwZXYGdnx8cff0xkZCS7du2iMqvVyp///GeSkpJISEigWbNm/B5lZmby9NNPk5ycTHVCQ0NZu3YtZrOZG6WVhzfyq33b91FyvoT2ke1p0qIJ58+c53DqYbwCvPBt6YvJZEJEREREROoPg6twdXVl06ZN9OjRg71791KV7du307ZtW+Lj4xk3bhwWi4Xfg4sXLzJnzhymT59OUVER1QkODubTTz/F2dkZqR0nMk5w6KtDtA5vjXegN/YO9rSJaEPOkRwOf30Y10auuDV2Q0RERERE6g+Da+Dl5cWOHTuIiopi+/btVKWwsJDJkyezfPly4uPjGTRoEIZhUB+Vlpbyt7/9jWnTppGRkcGV9OjRg/Xr1+Pu7o7UnoZ+Dek5vCeuDV2xOFko59TAiW5PdAMbOLs7IyIiIiIi9YvBNfLw8GDLli3ExcWxcuVKqnPkyBGefvpppk+fztixYxk8eDBubm7UB2fPnmXlypW8+eabZGRkcDVPPfUU7777LhaLBaldFicLXgFeVObu7Y6IiIiIiNRPBtfBwcGBDz/8kO7duzNmzBiKioqozpEjR3j22WeZMGECAwcOZODAgURERGBnZ0ddKi0tJTk5mVWrVrF69WoKCwu5GhcXFxYsWMCQIUMQERERERGRqhnUQGxsLKGhocTGxrJz506upLCwkGXLlrFs2TK8vLx46KGHiIyMJCIiAn9/f2rDL7/8wo4dO/jiiy/YuHEjeXl5XKvQ0FDee+89WrdujYiIiIiIiFTPoIbatGnDV199xfLly5k0aRJ5eXlcTW5uLsuXL2f58uWUu+OOO+jUqRPt27enbdu2tGzZEl9fXzw9PbkWeXl5ZGdnc+jQIfbt20d6ejq7d+/mp59+4np5eXkxc+ZMhg4dislkQkRERERERK7M4Dcwm83ExcXRv39/5syZw4IFCzh37hzXKiMjg4yMDNatW0dFjo6O+Pj44OLigpOTE46OjpQrKSmhuLiYwsJCTpw4QUlJCb+Vm5sbY8aMYdy4cTRs2BARERERERG5NgY3QKNGjXj11VcZN24cb731FkuXLuXUqVPUVElJCZmZmdQmb29vhg8fztixY2nUqBEiIiIiIiJyfQxuIE9PT6ZNm0Z8fDwbNmxg6dKlJCcnY7PZqA/MZjMREREMHz6cqKgoLBYLIiIiIiIiUjMGtcDBwYHo6Giio6PJyspi/fr1rF+/npSUFKxWK3XJzs6OiIgI+vfvT1RUFH5+foiIiIiIiMhvZ1DL/P39ee6553juuec4e/Ys//rXv0hJSWHHjh2kpaVRWFjIjeTi4kJwcDDh4eHcd999dOvWDTc3N0REREREROTGMqhD7u7u9O3bl759+1KurKyMn3/+mfT0dA4ePEhWVhZZWVlkZ2dz8uRJysrKOHPmDDabjXImk4mGDRtiNpvx8fHB19cXPz8//P39adWqFe3ataN58+aYTCZERERERESkdhncRGazmcDAQAIDA3nooYcQERERERGR3w8DERERERERkRowEBEREREREakBAxEREREREZEaMBARERERERGpAQMRERERERGRGjAQERERERERqQEDERERERERkRowEBEREREREakBAxEREREREZEaMBAREaljXbp0YfTo0cTExFAbRo8ezaJFiyhnZ2dHaWkpFVmtViZNmkRCQgJFRUX06tWLJUuW4OPjQ2XDhg3j3Xff5a9//SsvvfQS1+Lo0aO8/PLLJCYmUq5Hjx7MnTsXf39/qmK1Wpk0aRIJCQkUFRXRq1cvlixZgo+PDyIiIvWZgYiIyB/MwoULWbhwIZ999hmPPPIIlc2YMYM1a9awbds2vL29iY2NJTo6mqSkJCqaOXMmf//731m0aBHjx48nMDCQJ554gqtZvHgxjz32GG+//TYFBQWMHDmS6OhoUlJSqMqMGTNYs2YN27Ztw9vbm9jYWKKjo0lKSkJERKQ+MxAREalD0dHR7N69myFDhjBkyBDuuecedu7cSV1asmQJEydOJDg4mHJz5syhTZs2HDp0iKCgIMqtXbuWWbNmkZiYSKdOnWjZsiWPPvooAQEBhIeHcyVz5szhMg8PD+Li4hg0aBDVWbJkCRMnTiQ4OJhyc+bMoU2bNhw6dIigoCAqmz9/Pm+++SYnT56kU6dOzJs3j06dOiEiIlLXDEREROrQ6tWrOXr0KKNHjyYmJobqxMTE8P7771OdqVOnMn36dK5XXl4eWVlZhISEcFnr1q1xdnZmz549BAUFkZqaypgxY9iyZQudOnWiXM+ePVm9ejXR0dEkJSURFBTEtTh+/DgJCQk8/PDDVCUvL4+srCxCQkK4rHXr1jg7O7Nnzx6CgoKo6PDhw7z44oskJSXRuXNnfvzxR1atWkWnTp0QERGpawYiIiL1UEJCAgkJCdxoBQUFlHN3d6ciDw8PCgoKKBcaGkpOTg6V9e7dm+PHj3MtEhISGDJkCOU6dOjA5s2bqUpBQQHl3N3dqcjDw4OCggIqs7e3x2Kx4ObmhqOjI127dqVr166IiIjcDAYiIiK3EDc3N8qdPXuWivLz83Fzc+N6rFy5kieffJLLzpw5g4eHB+ViYmJ4+umnycnJYfr06YSFhbF//36cnZ2pyM3NjXJnz56lovz8fNzc3KisefPmrFq1ivHjx5Obm0uHDh14/vnnCQ4ORkREpK4ZiIiI1DGz2czVxMTE8P7771OdqVOnMn36dK6Xp6cn/v7+fPvtt3Tt2pVyBw4coKioiODgYK7H4MGDGTx4MNUxmUz4+voyZcoU3n77bY4ePUqHDh2oyNPTE39/f7799lu6du1KuQMHDlBUVERwcDBV6devH/369aOsrIyPPvqI8PBwsrOzcXZ2RkREpC4ZiIiI1DFfX1/S0tIoLS3FMAyqkpCQQEJCArVhxIgRzJo1i/DwcHx8fHjhhReIiIggKCiI38pqtTJw4ECmTJlCq1atOHHiBNOmTaNJkyYEBQVRLi4ujp9//plt27ZRbsSIEcyaNYvw8HB8fHx44YUXiIiIICgoiMoSExNJSkpi6NChBAQEYLVaKS4upqysDBERkbpmICIiUscmTJhAXFwcCxYsoHPnzuzcuZMbadmyZTzzzDNcZjKZKHfq1Cm8vLyYPHky+fn5REZGUlRURK9evVixYgU3gp2dHU8++SQjR45kz549eHh40K1bN5KSknBwcKAqkydPJj8/n8jISIqKiujVqxcrVqygKhEREfzwww/06dOHrKwsWrZsydq1a3F1dUVERKSuGYiIiNSxsLAwDhw4QG2Ji4sjLi6O6tjZ2TF79mxmz55NbejXrx/9+vWjOsuWLaMiOzs7Zs+ezezZs7kai8XChAkTmDBhAiIiIjebgYiIiIiIiEgNGIiIiIiIiIjUgIGIiIiIiIhIDRiIiIiIiIiI1ICBiIiIiIiISA0YiIiIiIiIiNSAgYiIiIiIiEgNGIiIiIiIiIjUgIGIiIiIiIhIDRiIiIiIiIiI1ICBiIiIiIiISA0YiIiIiIiIiNSAgYiIiIiIiEgNGMAZRERERERERK7T/wMxBdZyS2V2ugAAAABJRU5ErkJggg==", - "text/plain": [ - "1056×916 Array{RGBA{N0f8},2} with eltype ColorTypes.RGBA{FixedPointNumbers.N0f8}:\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " ⋮ ⋱ ⋮\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,0.933) … RGBA{N0f8}(1.0,1.0,1.0,0.933)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fd3 = getfluxdiagram(ssys3,1e-3;speciesratetolerance=1e-4)" - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "id": "007de25f", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "930×750 Array{RGB{N0f8},2} with eltype ColorTypes.RGB{FixedPointNumbers.N0f8}:\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fd4 = getfluxdiagram(ssys4,1e-3;speciesratetolerance=1e-4)" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "id": "977f11cd", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "952×750 Array{RGBA{N0f8},2} with eltype ColorTypes.RGBA{FixedPointNumbers.N0f8}:\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,0.733) RGBA{N0f8}(1.0,1.0,1.0,0.733)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fd5 = getfluxdiagram(ssys5,1e-3;speciesratetolerance=1e-4)" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "id": "6eaab3dd", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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+o7OjSTAj3OLi4lRVNZlMqCGITK13UsvtWskSzfMvZpzBnxnBzYgYjsrEGBs7duw777yD8CGENGvWrEWLFi1LNWnSJK5UgwYN7HY7/k5RUdHp06fPnj175syZY8eOHTp06Ndff/3ll19ycnIQJoWFhf369Xv99defeeYZhA+hLWXnLEPdpRa/aSibUVGa5p2ul3wlOV4RTWngOI4LGUWY6Lr+888/r1ix4ueff87MzNR1HRWgquq+UgsXLgRAKe3QocN1113Xp0+fa6+9VhRF1EhJjuSVed+gAvy6b3vRtu1F2/5zbE47R/KVzo7JjhSLaEGY9O7dGzUQkan1Tmrpr/nna96ZzDiD3+nKFkADKCqHpmnDhw//9NNPUWE2m+3666+/+uqrO3XqlJqaGhUVhbJwlmrdujX+LD8/f9u2bdu3b9+4cePatWv9fj8qgDE2bty4/Pz8t956ixCC8BGk9qaYeXrwB634LUM7iIpheo5SOFS03CbZXyBCNDiO40JAUTGGYaxatWrRokXLly8vKChA5dA0bVupyZMnx8bG3nrrrQMGDOjVq5cgCKhJLo9sYREtJXoJKixoBHcUbdtRtI0S+kiL0UmOZFSAYRhnfjsjW2R7nJ3K1NCNM0fOyFbZHmenEkUNQSw04j5qHaz552vemcw4g3OYz1D3CVIKKoGmaQMHDly2bBkqIDEx8fbbb+/Vq1fnzp0ppQi32NjY3qUABIPBjRs3rlq1avHixYcPH0Z5TZ482e12z5o1ixCCsBJN/xDjrtcD36rFbzI9BxWjlywzgj9LjkmiuTc4juMuhqK8Tp8+/emnn86aNevIkSOoQvn5+bNLJSQk3H333aNGjWrUqBFqBpGIbe2JO4q2I3w6x3RJciSjYgzd2PfTPqVESe2XGntZbOGJwnX/WXd5p8vbprWlEkWNQiw04j5qHaT5F2je95lx1ghuFqQUVILHHnts2bJlKJf4+Pj77rtv8ODB7dq1Q1UxmUw3lHrjjTe2bdu2YMGCOXPmnD17FmX34YcfNmrUaPz48Qg/QTTfLJp6aP7PNM80xjyoAGYUKkUPi5a+kn0iEZzgOI47P4qyO3LkyKuvvjpnzhxVVVF9Tp48+eabb06ZMmXo0KHPPfdc06ZNUQO0cyTvKNqOMGlta3NPk3+iwqhEO9zc4YePfjiaeZRKNPPbTEc9R7MOzcyRZtRMxEoj7qPWQZp/gaHtRyXIyMiYMWMGyi4tLW3UqFH9+/eXJAnVp1OpSZMmLVy4cNq0adu3b0cZvfTSSy1atLjrrrtQGYhMI4aLlgGad6rm+zegowL0kq+M4EbJMUk03wSO47jzoCiLnJyciRMn/vvf/1ZVFTWDoigffvjhp59+OnTo0AkTJjRq1AjVwat5D3j2Zxfv2+XKRJg0MDd4uMUoSijCITo+OvGGxH0/7Cs8Weg+4+6c3tkeZ0cNR6w04j5AQ7itX79+zJgxKKNrr7120qRJaWlpqDHMZvO9pVasWDF+/PgdO3YgZIyxYcOGpaSkJCYmonIQwSnZJ4iWAWrxREPZhgpgRoFSNFI03yw5JhHBCY7juL+gCI2qqlOmTHn55Zd9Ph9qHlVVP/roo/nz548fP/7xxx+XJAmVj4Hl+I9lF+/bX5x90HNAZzrCJ5LaHmv5pFWMQPi07Nzy4PqDWd9lXTvk2nrN6olURO1AEVaBQOCBBx7QdR0ha9as2dSpU2+55RbUVDfffHPv3r0XLFjw5JNPnjp1CqEJBoP333//hg0bRFFEpRGkRFPMQj3wvVo8geknUQF6YIWhbJUcr4rmXuA4jvszihBs3rz5/vvvz87ORs3m9Xqffvrpzz777KOPPurSpQsqh1fzHvDszy7el+Xa5VJdqASU0EdaPBpnqoew8rv9RCBWh5UQwhhDXfXSSy8dPHgQIejSpcuwYcNSUlKuvPJKSilqNkLI4MGD09PTt27dmp2d/d577+3ZswcXs2XLloyMjCeffBKVTDR3F01Xq973Nd+HYEGUFzPylaIHResg2T4exAqO47jfUVwQY2zq1Kljx45VVRW1xL59+6699trnn39+/PjxgiAgHBhYjv9YdvG+/cXZBzwHDKaj0hCQoU2HtYxshbDSFG3vD3sFUUjqnpSzNye2cWyTlCZUpqhjcnJy3n33XYQmNTV1+PDhqFVkWe5W6vvvv9+zZw9C8NJLL913331OpxOVjVgl2xhqvUN1v6gH16ICdP+CQHCjHDVFkDuC4ziuFMX55efnDx48+Pvvv0dto2naxIkTN27cOG/evJiYGJSXV/Mc8BzILt6327XLrbpQJfrG33p1TFeE2/F9x08eOJnUPalxUuNNizYd2nIoqmFUdEI0IQR1yb/+9S9VVRGCdu3avfzyy6i1pkyZsnXr1qNHj+JiPB7PzJkzn332WVQJIjaWoz/TAytU93hmFKC8mH48WDCIRo6SbI8CIjiOq/MozuPo0aM33XTTwYMHUWutWbOmc+fO3377bYsWLRAyBpbjP5ZdvG9/cfYBzwGD6ahCnaI7942/FeFWfLZ4z3d74lvFN2rbyOqwptyYsnbO2iM7j1jtVovdgjAyzoI4QGTUSC6X66OPPkIIrrrqqpUrVzqdTtRa8fHx69ev79Gjx4EDB3Ax06ZNe/LJJ00mE6qKaL5ZkLtp3imabw5goJx0zZthKFvlqHeJ2AAcx9VtFH8nMzPz5ptvzsvLQy13+PDh6667bsWKFSkpKbggr+Y54DmQXbxvt2uXW3WhOrSMbHV/s+EEBOHGGGuS3OSydpdZo6wAYi+LbX9je13XEV4saBQ9CDAh6j2ICah55s2b5/F4cDHNmzf/+uuvo6Oj8UcbNmDdOtx6K9q0wTknT+LrrxEZiSFDcM7x4/jmG6xbB58PzZqhb19ccw1MJlSe7Gx8+SUyM6FpaNsWd9yBtm0hSfiDhISElStXdunS5fTp07igU6dOffXVVwMGDEAVIoJdsk8QzX0U93NMO4TyMpRNwbO9JMeroqUvOI6rwyj+Ijs7u2fPngUFBagEVqs1ISHBbreLomi32wEUFxfruu52u0+ePFlSUoJwy83N7dGjx7p161q3bo0/Y2A5/mPZxft2u3Yd9v7KwFB9Yk1xD7d4lBKKsihSTkiCKZLG4YIc9RwpN6bgD5qnNke4seKJUPcCMArSSdQUIndFDbNq1SpcjCzLy5Yti4uLw/9x+jSysnD99fgvvx+//IKoKJzz22+YPRtHj6JHD0RHY+dOzJqFM2dwxx0QRVSGnTvx3nuwWpGeDlnGjz/izTfx6KPo3BmCgD9o2rTpwoULb7jhBsMwcEGrVq0aMGAAqpwgp5pjv9Z8M1XvdDAF5cKYR3GNpsomyf4iiAUcx9VJFH+Wk5Nz4403FhQUIBycTme3bt2Sk5OTkpLatGnTpEkTh8OB83O5XDk5Ofv379+zZ8/u3bvXr1/vcrlQYfn5+TfeeOOGDRsaNWoEoFgt3lu8Z687K7t4n1fzogaIoBGPtxxjozaEwK2eOu7bebJk70n/bo96pm+jVyIj41DdmH8eK1mM/zKKWOH9sD1BIoYDBDWDpmk//fQTLubZZ59NTk5G6HQd69dj/37cey969IAsIzUVM2di1SokJSExEWGnaVi0COcMGYL27SEIaN8eL7yAlSvRuDESEvBnaWlpI0aMmDlzJi5ozZo1qC5EppGjRXNvxfWUoWahvDT/PF3ZJjunC7QVOI6reyj+wOv19u7d+8SJE6gAQRA6d+5822239ezZMzk5WRAEhCyqVHJy8qBBgwAYhpGVlbVmzZply5Zt2bLFMAyU1/ETxweMvP25Gc9m+/Yd9v7KwFCZBCLYaKRbLUYIRCI+1PyRBuYGOA8GozCYc6pkX45v5wn/rhLdjT8wizZUO3U387yKP9GZZzKUTBL1FogNNcDOnTvdbjcuKCoqasyYMSiTggLs3YuYGFx/PSIjcU58PDp2xJEj2L8fiYkIu+PHsXcvevVCSgosFpzTtCmuugo7dyIvDwkJ+IsXX3zx448/VhQF53fs2LEjR440a9YM1YTQlqbYJZr3I9U7BUxBuTDt12D+bbLjddHSDxzH1TEUfzB69Ojs7GyU1+WXXz5ixIi77747Pj4e4SAIQvtSY8eOzc3NnTNnzocffvjbb78hZCaHqfG1lzXqmpDQuaHJblp++gtUJqccneRIamdPbmNve8x/dPLBNxGCe5vc18beFn9mMD0/eDi3ZG+uf1+Of2dQ9+A8zKId1csoMFyPgin4Cxb8nhUMEKKmg7ZAdcvJycHFDB482Gaz4Xx27sT99yMyEucEAigpwT33wOuF1wuHA3Y7/osQREdDkuB2ozK4XFBVxMTAYsF/CQIaNEAgAL8ffyc+Pr5v375LlizBBeXk5DRr1gzVidLIhwTzP1TXU4a6B+XD/IrrMTH4k+x4DcQMjuPqDIrfLVy48JNPPkG5dO7c+cUXX+zdu7cgCKgc8fHx48aNe/rpp1esWPHKK69s3boVIaifFJc24RpUJoEIl1kap0S1T4lq39jahICgVIvIlmbRHNADuKA+DfteE9sNpQym5Qd/y/HtzC3Zm+vfEzR8CIFZsKE66cz1FPQ8nI92xCi4gzheJ+abUK3OnDmDi+nRowcuoFUrpKcjMRHnHD+OL7/EOSYTJAmBAFQVJhP+q6QEhgGzGWHl9XoppWaLBeeUlEDTIEn4L68XlEKScB49evRYsmQJLuj06dOoAQTayhS7VPN+pHrfBVNRLnrJsqB2SHa+R8Qm4DiubqAoVVhYOHLkSJRd69at33333d69e6NKCIJwS6lvvvnmySef/OWXX3BBuTvydEUXZRHhZpfsifZ2KVEdEu3tLKIFf0EJbWNrm+naifPr6OzUp+HNOb6duSV7T5XsPenfqzMFZWQSbag+zPM2UzbgwpiPuR6D9R5ifxYQUU3y8vJwMc2aNcMFREaiVStceSXOsduxfj3OiYtD8+b46Sfs3YuOHXGOquLgQfj9aNYMYeJyuRYtWuTz+fr169e8SRPExyMrCydPomlTnBMMYts2REcjNhbn0axZM1xMXl4eagpKIx8STNer7qcMdR/KxVD3Bs7eIke9KZpvBsdxdQBFqVdffbWwsBBlIcvy+PHjx44dK8syqlyfPn169Ojx9ttvv/LKK4qi4Dy0Eu30rjPxVzVEOAhEbG6JTInu1dae2NjahIDggpIcyZmunfgLgRhWQU2wmGPowQ8O3aYzDeUlC1aRUFQTFviO+T5BSBjzz2HaQSFqCoRYVAfDMHAxgiDgwgQBoohzBAGE4BxJQloatm7Fu+/iiSeQkICvv8ayZejdGx07AlAUxefzSZIUGRmJslMU5YcffnjvvfesVuvo0aMvu+wyUIqBA/H225g1C//8JywWfPwx9uzBuHFo0gTnIYoiLsYwDNQkgtTaFLNU9byl+T4GGMqBeZWiUTTiAcn+NEDBcdwljQI4evTo9OnTURZNmzadN29ely5dUH1MJtMLL7zQu3fvO++889ChQziP4xtPxF/VEBXgkBxtbS2TLYVt8bXVmkYcfRCaJEcyfkeJbhWVCDEYKQbNgopSp0pQQSYxEtVFO8LcTwMMoVO2GAXpQtQ0SCmocvXr18fF5OTktG/fHmVCCFJS8Nxz+OADDBiA4mK0aYMRI5CeDlkGUFBQ8M477xw8ePDxxx+/7rrrKKUI2Z49eyZPnnzkyJHhw4ffcsstDoeDEAJC0KsXrFa8/z6uvx6ahk6dMHEirr0WlOI8cnJycDH169dHTUNkyf6CaLpBcY9h+mmUB9N8Hxrqbtk5nQix4Dju0kUBvP3228FgECG77rrrvvjii6ioKNQAHTt23LJly6233rpu3Tr8nRMbT3Z+vBPKSCBi84jmKVHt20Zedhl+gu8TMA/Oka9GyGSBNbWaVD0vQgyaBA2VwCzaUC2Yz3A9AuZFWel5RuEQYhtPrANRterXr4+L+emnn/r164e/lZ6O9HT8r5Yt8c47+C9BQGIiMjKQkYG/aNiw4XPPPbdo0aKJEycmJiaOGjWqbdu2AAgh+DuMMQA5OTmzZs364YcfbrvttjfeeKNxcOK1AAAgAElEQVRBgwaBQGDJkiW//PLLrbfe2q5dO6SlIS0NIfvxxx9xMfXr10eNJJiuMcWuUN3P6IHvUC6GsjWY31d2zhKkZHAcd4migUBg3rx5CFmfPn2WLFliMplQYzidztWrV6enp69cuRJ/4Tri9pz02BJsCEGsKbatvV1be2KivZ2FBJh/LvO9CObF74jcBSEL6J4o8Ywu+FBpzKId1cLwgMgoH6aw4heg7SG2F0FkVJWEhARczOeff/7aa6+ZzWaEVXR09IMPPnjjjTd+8MEHI0eO7Nu37+DBgxs2bCiKIiEEv2OMGYbhdruXL1/+6aeftmjR4oMPPkhMTNQ0bdOmTRkZGS6Xa+TIkc2aNUMZFRYWfvHFF7iYRo0aoaYiQrTs/FAvWaq4XwArQdkxPS9YMFB2TBItA8Bx3KWILlu2rKioCKG55pprFi1aZDKZUMOYzebFixd379598+bN+IuTm3Nb334FzkMgYvOI5ilR7dvaE5tYm+Ico4j5PzJ8n4B58UdiU4gJCFmMqel1DZ7/6sSECDGIymEW7KgWYgMhegErfpmVLEK5MP8Cpu4Vot6DmIAqkZqaarVa/X4/zu/06dOzZs167LHHUAmaNm06adKkzMzMGTNmjBgx4u677+7Zs2d0dLQoioQQXdd9Pt+6des++OADSZJeeumlq6++mjF24MCBjz/+ODMzc8CAAXfccUdcXBzK7p133vF6vbighg0btmzZEjWbaEk3S8mK6zFDzUY5sKDiGkuVnZLjZYCC47hLC50/fz5CExsbu3DhQovFghrJarUuXrw4JSWloKAAf3Z848nWt1+BP9Ndxg0t/9HWnphob2cRLfgvo5D5/8N8n4B58RfE1BVl1Mbe/gOlUSw9FSX5UQlMYiSqCzERx6uQkpnnZTAV5aDuMwrSSdS7RL4Glc9kMqWlpX377be4oBdeeKF///5NmjRBJRAEoWPHjtOnT//uu+9mz569cuXKoUOHdurUSRCE/fv3//vf/z5y5MjAgQP79etntVpzc3O/+uqrb775pn379rNmzWrRogUhBGW3Z8+eyZMn42J69OhBCEGNR2gLU8xStfg1zT8H5aL55xl6jhw1jQhOcBx3CaEbNmxAaKZNmxYfH48aLCEhYerUqUOGDMGf5W47pSu6KIuGzs7uPZuz7nju1lMkX/j49GeEEPyXUch8HzP/v8FKcD7y1SgjSugVtsTdrmDQoPVNHoAhrMyiDdWKWAcRKdFwjYKei3IwiljhA7A9QSKGAwSVrGfPnt9++y0uyOv1pqen//zzz5GRkagcZrP5lltuufrqq5cuXZqRkdGqVSvDMPbu3duzZ89nn302Li6uoKDgu+++mz9/vs1me+mll1JTUyVJQrnk5+enp6crioKL6dmzJ2oLYpIcEwW5k+IeB+ZD2RnBDcH8W2XnB4LUGhzHXSpoQUEBQtC5c+dBgwahAnJzcy0Wi8PhEAQBgMfjKSgoaNq0KcLqzjvvnDJlyvbt2/EHWom2bdqO4hOeU9vztICG3x06dKhVq1YwCpnvY+b/N1gJLkQg8lUouyRH0i7XTouU1DP+2h9PTdFYEOFjFu2odlI7IWYpcz3BlE0oD515JkPJJFFvgdhQme66667nnnsuGAzignbu3Dlw4MClS5eazWZUmpiYmOHDh19//fWfffbZli1b+vTpM3DgQFmWf/rpp4ULFxYXF997773du3ePjIxEebnd7n79+v3666+4GKfT2b9/f9QqouUWs5SouB421AMoO6YfDxbcLkdliOYe4DjukkARmkcffZQQggp44oknunTp8sADD9hsNgCrVq0aP358dnY2wooQ8uijjw4dOhR/tm/+fvzF7swfWjZczvxzwAK4KKktBCfKLsmR4pSdo1o85pSjo6WEr05O8GuFCBOzYENNIEST6I/hmcJ8HwIMZceC37OC24Wo6aAtUWkaNGhw9913z549GxezcuXKG2+8ceXKlVarFZWpZcuWL7300vZS33333eHDh/fv33/DDTekp6c3aNAAFeByuf7xj39kZmYiBA8//LDNZkNtQ2gzU8wXqucNzfcpyoH5laKHJNtTNPIhcBxX+1GEgFLav39/1BK33XbbsGHDdF3H+dWLFZ940Hlrt6nMpyE0RL4a5RItR49r/YJTjgbQwNJmcJP3lp94IT/4G8LBLNpQU4jE9hSkNsz9HFgJykE7ahQMJI7XifkmVJqxY8d+8sknhmHgYtauXTtx4sQ333wTlYxS2qVLl5iYmM8++8xsNr/++uuXX345IQQVM2bMmMzMTITAZDI98sgjqKWISbJPEKRkxf0CmB9lpqueN5l+VHJMAig4jqvNKELQrl27iIgI1BI2my0xMTErKwt/p16s+MSDzkcfiLKYCaAhdPLVKK8YOQa/s0n1BjbJ+Db39d+8G1FhZtGOmoSY+xDaxnA9Au0wyoH5mOsxWO8h9mcBEZXgiiuuGDZs2EcffYQQZGZm/vzzzy1atIiPjyeEoDI1a9bshRdeoKVQAYyxnJyc3377LTs7G6EZO3Zsw4YNUZuJlttMUqJSNJJpv6HsNP8CQz8hR00nggMcx9VaFCFISEhAOOzcufPzzz83m80Atm/fzhhD5WjUqFFWVhb+rFFD+syjzvuHOEwyQVkRmcgdESaSYLml0UvrzszKLFyCijGJNtQ0tLkQs5i5x7HAKpQHY/45TDsgRP0LQiwqweTJk1esWJGbm4uLWVMKQJcuXWbOnJmSkoJKQ0uhYjZu3PjQQw/t2bMHIbBFCpERpEP7ls+Pu9UIbmCsGIaXMR+YlzEvjGLGvDB8jHnAfDTyYdHcBzWYQFuZY79SXE/pgZUoOyO4IVhwq8n5MaHNwXFc7UQRAkIIwiEvL2/fvn2SJAE4duwYYwyVQxAE/MFl8fSZR6OH3WU3yQTlI3UAsSB8CIS0eiMjaOz6Mx8ADOVlEe2ogUgEiZoK34fMMwXQUQ7KVqMgXYiaBikF4eZwON5///1bb70VIdu8efOVV1551113jR8/vmXLlqhpWCB73+aMjLfWr/8+yi7c3NPqjBKiHILZRMxm4owSohyC0yFERYlmEzGbidMhxEQLkkTwPwKs+I4gLkQ09xHNfVDzEavsnK55p6meDMBAGTHtWLBggOycKchXgeO4WogiBKdPn0Y4dO/e/d57742MjATw5Zdfvvbaa4yx3377bfXq1ZTSFi1a3HDDDQiHU6dOodRl8XTMSOfwexxmE0EFEPlqhJvGgr8W/wwwVIBZtKGGIiRiBKRk5noCRgHKQc8zCocQ24vEOgjh1q9fv6effvqtt95CyAzDmDt37vz58wcNGvToo4927twZ1UQtfs1QtjDmA/MxwwPmA9AsBv96GUA8wo3Qy+WoN1FrEBo5mkhJqutxZhSjjJhRFCy8W3ZMFi39wHFcbUMRgqysrGAwaDKZUDEmk8lWCoDFYiGEAAgEAtHR0ZqmffXVV4mJifXq1UPFBAKBPXv2NE6gTz7kHH6Pw2wiqDBiuhphxtacmpwXOIAKoMQkEhk1GJG7kJilhutRqFkoB6aw4heh7iD2l0HMCKvXX3/98OHDS5YsQVlomvafUqmpqQ888MDtt98eGxuLqqYZahaqBrHKzhkgEahVRNMNQsyXwaIRTDuEsmKq4nqcar9JtsfBcVytQhGCYDC4cuXK/v37oxI0b968devWLpdr7dq1bre7Xr16qJgfv/vPWy86ht/jMJsIwoJEQEpCWG08+/EvxT+iYsyiHTWf2FCI/g8rfpmVLEK5sJIvmHZIiHoPYgLCRxCEOXPm5OXlbdiwAWW3vdSoUaN69OiRnp7eq1evJk2aoPL9+uuvh/efSUtF1ZAdkwTaCrUQoU3NscsU1xg9sAplxjRvBphbsr8ICOA4rpagCM2MGTP69++PChg3blxUVJTFYkGpa665ZubMmYQQi8Wi6/rhw4d1XY+Pj0dF6CeZ7/3u7RfemBqF8CFyZ4AifPa712wrmIcKM4t21ArERByvQkpmnpfBVJSDus8oSCdR7xL5GoSP1WpdtWrVgAEDvv32W5SLpmnflgJwxRVX9OjR4+qrr05NTW3VqhUhBOGg6/qBAwe2b9++cePGNWvWHDly5IoWUubaBFQ+GjFUtNyG2otEyM4ZqidD804DGMpI833K9LNy1LsgMjiOqw2o3W4vLi7GxaxZs2b16tW9evVCeXXo0AF/0LAUAMZYbm7u7NmzR44cGRERgfLRTzLfJ6xkPphCKcLM1BXhk1uy9/u8dxEOJjECtQexDiJSouEaBT0X5WAUscIHEPkwiRwFEIRJRETEl19+ee+99y5YsAAVc7DU9OnTATgcjpSUlFatWrVs2bJFixaNGzeuX79+XFyc2WzG+ZWUlJw9ezYvLy8nJ+dQqYMHD2ZlZXm9XvzBL4fV4mLDbhdQmQSpvWR7HrWeINmeEKTWimsMWAnKSA98Eyw8JTs/IoITHMfVeLRLly6rV69GCB588MHMzMyoqCiED2PM6/VOmjRp4MCBKSkpKC/m/4z556ByELkLwqRYzfv6xASdqQgHs2hH7SK1E2KWMdfjTNmE8tCZdxrUbBL1FogNYSLL8ueff56cnDxhwgRN0xAObrd7bSn8mc1mi4mJEQTBYrGYzWYAJSUlgUBA07TCwkKv14sQMIZde5W0rmZUGiJEy84ZIBIuCaK5tymmoVI4ghlnUUaGsjNYMMgU/SkR48FxXM1GBwwYsHr1aoTg6NGjQ4cOXbp0qSiKCBPG2LJly1avXn327NmFCxc+/vjjbdq0QdmRyCeMwI9EP4bwE5n/35C7ErkrBAcqQDH8y0+8UKK7EQIqmDQjiAuyiHbUOoKTRH8MzxTm+xBgKDsW/J4V3C5ETQdtiTARBOG5557r1q3bnXfemZubi0rjKYUK27k7mNbVjMoiyFEZRGyIS4ggtTfFLleKhhvqXpQR0w4F82+TY+YI9ApwHFeD0UGDBj3xxBM+nw8hWL58+YMPPvjBBx8IgoBwEAThrrvuGjhwICklSRLKxWCmN6Y7nh4OUUS46cy/AP4FDCKkNkTuClNXInUEMaEsDKZ/c3JiQfAoQlDf3Kp3/Isrc185HfgF52cW7aiVRGJ7CnJ75noazIty0I4aBXcQx+vE3Bvhk5aWtmvXrjFjxsydO5cxhhps524FlUayPSGYuuGSQ8QGppgFiusxPfAdyogZZ5SCQbLzY0G+EhzH1VTUbrcPGDDgs88+Q2hmz55dVFQ0d+5ci8WCcKClUAHBYHDo0KELFiyheuzYR5yoLDrUvUzdC98HjJghtSVSKkxdiXwVQHExP5+ZnuPbgRDYpPr9Gr1qpc47mvxr9am3fyn+EedhEiJRaxFTDxKzxHA9Au1XlAPzM9fjsO4g9nEARZjExcXNmTPngQceGDlyZHZ2NmqqnVlBVA7RdAONfBiXKmKVnTNVz2TNOxNlxAx3sPAek3OmYLoWHMfVSBTAU089NXfuXF3XEZqlS5d279593rx5TZo0QXU7evTo4MGDt2zZAmDCWwU3/cOa1MaEysYCUHYyZSd8HzBiJVJ7mLoSuSukRIDgLzILl2QVLUcIZMHar9ErVuoEIBK5d/xzTvmyLflz8HfMoh21Gm0mxCxi7nEssArlwZh/DtMOCFH/ghCL8ElLS9u5c+esWbNef/31vLw81DxHjmmFRUa0U0BYETFeinoHEHApEyXbM0RsrLpfBHSUCfMHix6QozJE803gOK7moQDatWv3z3/+c/bs2QjZpk2b2rdvP23atCFDhhBCUB0YY3Pnzh09erTL5UKpoMLuf/z0xm8uo5SgyjA/UzZC2cgACHFEToXclZiuhRiPUsd829admYUQEJAb48fFmprj/0e6xN7rlButOTVZZwr+zCzaUNuRCBI1Fb4PmWcKoKMclK1GQboQNRVSe4SPyWQaPXr0Aw888P7777/11ltnzpxBTcIYMvcEu6dZEEZElp0zieBEHUCtdwriZcGikWBelAlTlKJRkmMStQ4Gx3E1DEWpiRMnzps3z+/3I2Qul+uee+6ZPXt2RkZGcnIyqtbu3btHjx69du1a/NmOrOAb04peeCIa1cI4ywIrEVjJAIiXEVPXQlyxMm8hg4EQpNUf2TyyK/7iCvs/bFK9r09MKNHd+AOzaMOlgJCIEZBSmOtxGAUoBz3PKLyb2MYS61CEldVqHTNmzCOPPLJgwYLp06dv27YNNcaOXUr3NAvCR7JPFKQk1BmCqZsp5nOlcBgz8lE2uup+DoabRj4IjuNqEopSCQkJb7zxxujRo1FGP/30U4cOHdLT01988cXk5GRUvt27d7/yyitLly5ljOHvTJpSeEuviPaJJlQv/bjft+grT4OgQRGCxKje7Z3pOI94S7tBTactP/5CoZKD35lFGy4VRO5MYpYarkehZqEcmMKKX4W6j9hfBjEjrMxm89BSWzd/+8lnXy5evDg/Px/VLTMriPARLbdT62DUMYKUZIpdEiz8J9OOoGyY6nmDsWLJNhYcx9UYFL8bNWrU6tWrv/76a5SRYRiLS6WlpT344IPp6elmsxnhFggElixZMmvWrHXr1uGCVJXdN/r0lm8vkyWC6qODfOOLcxsUIUiwJt9Q/zFckEOKH9T0vZW5rx71bkEps2jHpURsKER/zoonspJFKBdW8gXTfhGi3oPYCGGn7ux0xZdXvf/+tGnTvv/++wULFnzzzTdnzpxBNdm5W0GYEFBquQ11EhEbm2KWKkXDDWU7ykjzzoBRLDleBgg4jqsBKH5HCPn444+vvPLKEydOoFzWlrLZbDfffPPtt9/+j3/8IyYmBhWTn5//ww8/LFmyZMWKFV6vF6HJyg6+/E7hpHExqD7f+6JPaSaEwCnV65vwkkgoLkYWrH0TXl57Zsbuoi8BmAU7LjFEJo5XIXdixePBAigHNdsoSCeOd4mpG8LIOGsUjQZ0AlBKbyzFGNu1a9fq1avXrFmzadMmv9+Pymez2bp169arFBH+yYyzqDAGLVg4lEaOkmyjAQF1DBGiTNH/UVxP6IEVKCPNPxfQJMergACO46obxR/ExcWtWLHiuuuuKyoqQnl5PJ4FpQghiYmJaWlpKSkp7dq1S0xMdDgcuBi327137959+/ZlZmauW7cuOzubMYaye3t6Ud9eEZ2vNKM6bAk4DqoRCIGZGLeYd0sFvZmcCrkrMV0LMR7nJxDx+vqPxpqarz3zPhVMuBQRS39CWxiuUdBzUQ6GixUNR+TDJPIRQEAYaIbrMRhncI5xFkIcShFCOpR65plnNE3Lzs7eXiozM/PQoUMFBQUIh7i4uCuuuKJDhw6ppVq3bi0IAkophe304I8ID13zZjBtr+R4hwgO1DVElp1TVXe05p+LMtL88xl02fE6IILjuGpF8WdJSUnLly/v1atXSUkJKoYxtrcUfmez2Ro1alS/fv3o6GhRFO12O4Di4mJN0woLC8+cOXPixAmPx4Nw0DQ27LHT29c0tpgJqtavqnVrwIEQCAQ3R+RHiSqMsyywEoGVDIB4GTF1hdyVyF0hOPB32kX1ccqX4RImtRNiljHXE0zZiPLQmXca1H3E8RYEOyqGFb8KZTtKMXU/McXhLyilyaWGDRuGUoWFhYdK5ZU6+zvGmNvtNgyjpKSEEGI2m0VRtNvtoijGxcXFxsbWq1evQYMGDRs2bFnK4XDgPIiUjOCPCB898L2h3iw7ZwhSCuocUXK8QsQE1fMmykj3L1JYiRw1BaDgOK76UPxFt27dvvzyy/T0dK/Xi7DyeDz7S6FKHPhVGf9mwdsTYlGFTuvyGn80QnO9pTCBBvB/6MeZfwH8CxhESO2IfDVMXYnUAcSEP0iwJuPSJjhJ9Gx4pjDfhwBD2bHgD6xwgBA1HbQlyosFvmL+/+B/afthSkMIoqOjO5dCpRGkJFQUAwj+gOm5wYKBkm0cjbgPdQ+NfAiCVXVPBAyUhV7ytcJK5KgZIDI4jqsmFH+nZ8+eGzdu7N2798mTJ1GbzV9umvDsFZHyQVQJjyF+7YvTmIAQpJqLE2UvLkSHupupu+GbyYiZSFdC7gi5I5GvAijqBJHYnoLcnrmeAfOgHLSjRsEdxPE6MfdGOWgHmfsF/JG6HzWGICejogj+iilq8cuGmiU7XgWxoo6h1nsJsSuusYCGstAD3ytFD8rOmSAmcBxXHSjOIykpae3atf3799+zZw9qp5SUlC+++MKeQI38W8D8KAtivQ+0OZSNTNkIw40QKIx87avnN0SE4HLJ38XsRuhYgCkboWwEwIiVSO1h6krkrpASAYJLGjH1IDGLDdcj0H5FOTA/cz0O6w5iHwdQhM5wG0WPgJXgD5iWTVBTECGOiA2YnocyYwDBBeklXwTUPbJzhkBboY4RLf1lYlNco8ACKAs9+JNS9KDsnAViAsdxVY7i/Jo3b75169Znnnlm6tSpqG3uueeemTNnWq1WAMQ2lhVPRFkQy02QOsA6iECHup8pGxHcyNSdYAH8HQay2h+br0sIQT1R6WktIGAoH+ZnykYoGxkAIY7IqZC7EtO1EONxqaLNhJhFzP0sC3yL8mDMP4dp+4WoDAixCInB3E9Bz8H/oeWA+UGsqBkEKVnX81BmBCFg2uFgfrrseF209EUdI5q7m6I/UwofYMyDstCDPytFI2TnByAmcBxXtSguyGw2Z2RkpKWlPfLII6dPn0ZtUL9+/RkzZqSnp+N3xHoXgj+w4DqEiERASsL/R4TUjkjtEDGCQIe6nykbEdzIlK2Aht+tLYk6oloQgghB7xN5ViIMYWGcZYGVCKxkAMTLiKkr5K5E7grBgUsMiSBRGfB9yDxTAB3loGwzCtKFqKmQ2uNimPc9FvwZf8OAdgDSlagZBClJD6xG5WE+xTWaKpsk+0sgMuoSQb5KjvlcKfwnMwpQFnpwrVL0oOycBWICx3FViCIEt99+e/fu3SdMmDB9+nRd11FTCYIwZMiQKVOmxMTE4E8Isb/M8vuCeRECIncGKP6GCKkdkdohYgRhfqbuQnAjUzbu8x7NCtoQAgrWJ+JsJNFRGfTjzL8A/gUMIqQ2RO4KU1cidQQx4RJBSMQISCnM9TiMApSDnmcU3k1sY4l1KM6PBX9k3hk4D6buJ9KVqBmIlITKp/nnGeoe2TmdiI1RlwhSO1PMgmDhEKafRlnowZ+Voodl50wQCRzHVRWK0ERFRWVkZNx7773PPvvsmjVrUPPcdNNNr732WocOHfC3xARif5a5n0coTFfjooiVyF0hdz3u2/5T/vOAjoshYDdG5NcXFVQ6Hepepu6F7wNGzES6EnJHyB2JfBVAUcsRuTOJWWq4HoWahXJgCit+Feo+Yn8ZxIy/0k8y9zOAgfPR9qPGEKRkVAlD3Rs8e4sU9ZZovgl1CaGXm2IWBwuGMD0H/489+ACQqrz3Bvz7v+c958zOzs7MFkBgKcouFoooqHERg6JGENTg/YIajZooagRE8Uavij3BJBopGktigr3FFmyxoZCMBVEiIJEdbCx9y8yWmTnnvOf8v3zk5n56VXYYts6e59kdrvW63TDdKL4bZMDn83UIid0xevTol19++a233vrFL37x3HPPoWsYO3bsTTfdNH78eOwSFfwfZF5m6020howqZKfB3vjC5ps8dpGFqoLkPnoaHYwzbMdgxwAwBUkfBbOKjCrowwBCN6X1FSUPc+P1nH4COeH0M6zWi+jt0MrxZZzxEjPgJfDt2FlH6CpIFJNWzm4NsuDB8DgjSSAnzE12w09l4Vl6+CpAoscgrdwsfcSqP53V59gdrvWG3XC+UXw3yIDP52t/Ervv8MMPX7JkyapVq+6+++6HHnqoqakJnSEcDv/whz88//zzDzzwQGSHIj/n2hPgJbELogyyAlnIuI1/rrnacpuRhf2NloPNRnQuTrEdgx1jAKIXGWNgVJE5Dlo/dDtkUOTnMA7hxmvAGeTA+cirm0qR35B5BP6NG6+Fsxa7ptYDCpDoGoQ+0nVr0BoZPJPMqlT9+Q57GpEAIResWhZ7zkdG8SISvdFjkNbPLHnUqv8hq0+wO1zrDTsx0yi+A5Dw+XztTCJXo0aNuvPOO3/1q1899thjjz/++NKlS5VSaH+6ro8fP37aTqFQCLtF9Kaiqzj5M3w7MqsAQmtcVs9vuj5hb0IW+geHT9jrbHLehRVj+11AodN5OzjzIjIvMgBtAJlVMKrIqIKIoPuggpNJVnqJGXA3IQdeghvOQ+inFLoIEJy6n9NPo1VsQX0CORRdg9BHuJkXsEtCP1APXw0yjND5dvNdLjODNBLIiWe/a+2YaEQXCnMsegzS9jJLH7frz/Ccf2B3uJmX7YaZRvEiQMLn87UniT1TVFR07k719fVLlix5/vnnly1btm3bNrS1Pn36jBs3bvLkyVOmTCkpKUGuqOBkWK9x5i/4NsbhaB2/uvXWmtTfkYWI3veE/tdrWgTGKBROJ06xswpWjO0YnLUAo9O5Gzn1GFKPMTTo+5NRBbOK9NEgE12fPkyUPsWJS9iOIRcuNy+Cs5aCZ3DTL5EddtaRHIquQegjsEskokbxIpABIBD+mWu/69rve2Cwq5EACLuPvXqr/iwZmqEXzQIEegYSpUbJo3b9WZ7zd+wON/OSnbjciP4aEPD5fO1Goo2UlJSctROAdevWLVu2bOXKlatXr/7oo48aGxux+8Lh8LBhw4YPHz5mzJgjjzxyv/32Qxuh8PVsvwevDt+EjO+gNe/WPfyP5CvIQkArOmnAvAItgv9BQTKqYFQRAK+W7RWwY2wth7sZnc+Fs4adNWi5hylA+sEwRsMYTcahgESXJYqp5F403cYtvwMYu4+t19l6E3CRJbUOOAldAxkjAQF4+GZCj95G2gD8N1lQvLBl+/HMzR7AzBqBQMiFq5oXsLNaj95KIoqegUTEKLnfrj/Tcz7E7nDTTzkU0iPXAQSfz9c+JNrB/niVyDcAACAASURBVDvh3z777LMvvviipqZm69atNTU1LS0tyWTS87xkMgkgEolomhYOhwsLCwcMGNCnT5/y8vJBO6GdiBIK38iJn+LrtMHQ+mOX4k3L396xGFkQJCf1u6bYKMe3EWUUmIjARALgbmQrBjvGdgxeEp2OM2zHYMcAMAVJHwWziowq6MMAQpejUdFlMA7ixM/ATciFi+w569BlEBWRHMTqU3wTvWiWZo7HlwhtYCAyN524HACDFbMgoYGQE9d63audZBTfIfSD0DOQCBulD9p1Z3rO37E7VOp+kNTDc+Hz+dqHRPsbvBO6Egocg8AkzryAryLzcOzS9kz1y1t+yWBkYXyfiwYUHoQsaQMoOA3BaQQXzjq2Y7Bi7KwEW+h0nGI7BjvGAEQvMsbAqCLzSGh90ZWQOYFK/+QlLoKKoz2xWkfoQoQ+0lWf4muEOVaGZuBr9OBpylrmpJ/HTh57IBIgAmH3sbvFqjtVL7pSFp6FnoGoyCi5364/03M+xO5QLX8gEZGhWfD5fO1Aoqei8HVsr4C3A19mHI5v16LqltRc43gZZOHgkh+MiE5BLjTow0kfjsLpBBfOOrZjsGJsvwsodDpvB2deROZFBqANILMKRhUZVRARdAVyb1H6BCf/izMvof14CbhboPVF1yD04W76WXwVaX2N6CJAwzcJRH6u7BXsbsdOHjMDGoFAyAHbTuN1nv03PfJrEhH0ACTCRskDdv0ZnrMau8Npug0wZeh8+Hy+tibRY4koRW7khgvw/wkyDsO3cLz0MxuvbFY7kIXBocOO6H0u2oAGfTjpw1E4nTjFzipYMbZjcNYCjE7nbuTUY0g9xtCg709GFcwq0keDTHQiKqToArTcw03zARftg9VHpPVF1yD0kfjfpBFdRKIY34JESUH0N6m6MwHGTgxWzJKIIJATN/OK50wyoouEcTB6ABJho+Q+u/4Mz/kIu8Np+iVEkQyeDp/P16YkejAyj0bB9zn9NP5F3x+iGN+EwS9tnldrbUAWegWGTOp3NUGgbVGQjCoYVQTAq2V7BewYW8vhbkbnc+GsYWcNWu5hCpB+MIzRMEaTcSgg0QmICs8n/SAvMRteLdqDsw7mBHQNQh8OaICLf9Mj1wljNHZJmkcahWfZLYvxJYpZkCcgCLlgd7NV9wO96DIZOh8g5DsSxUbJw3b9mZ6zGruBneRcorBWMBk+n6/tSPRsFL6a7XfgbgZARhW+xV+33/NJcwxZCMqSKf1v0kUB2pUoo8BEBCYSAHcjWzHYMbZj8JLodJxhOwY7BoApSPoomFVkVEEfBhA6knGoKH3KS8yE83e0ObUOXQcFhRziqfXYSSs4UQZ/iCwEwlcq66+eiuNLPGaGpxERCLlwnaZfes5KPfJrElHkOxIRo+Q+u/50z/kHdoNnJy81RUSY4+Dz+dqIRA9HRRT5BdefAzCMw/FNPkq+9H79E8iCJHNK/+uL9F7oSNoACk5DcBrBhbOO7RisGDsrwRY6HafYjsGOMQDRi4wxMKrIPBJaX3QMbS9R8hA33cCpx9Gm2FlHyAozr99py5Yt+BoiYmbsRET9+vXbb7/9hgwZgt1E+gio9QCEHGpE5iFLFCiI/rql9hTAw5cw2GUIQBAhJ27mVc+ZZEQXCWM08h2JYqPkIavuVFbVyB47VsP5Zsn9whgDn8/XFiR6PDKqEPwBp58iYzS+ZlPqw9e3zkdW6Ji+c/Yq2B+dRoM+nPThKJxOcOGsYzsGK8b2u4BCp/N2cOZFZF5kANoAMqtgVJFRBRFBuyKDwjdBH8ON14AzaCvuJnhJiAi+ieu6b7311urVqwEIIfbdd98xY8b07dsXu8TMmzdvXrdu3SuvvAKAmcfsRERojdBHuOknQUGj+A5QEFnTjNFG4Rl2y/34Kga7YGbSSCAn7G6x6qbJ0Ay9aBYgkNdIlJgl91t109j9AtnjtN3wE6PkUaHvD5/Pt8ckfAAVXQn2QAX4qqSz+flN17uskIWqXufsGz4aXYUGfTjpw1E4nTjFzipYMbZjcNYCjE7nbuTUY0g9xtCg709GFcwq0keDTLQPKjiZZKWXmAG3BiC0AYb6GMah+BJmfu2119avX09Ehx9++IUXXojdQUT9dzrmmGMAMPOKFSvuvPNOZj7wwAOPOOIIfDuhjwDIiN5CsgK7yQxfoTKveO4WfI0HZvY0EoTcuKp5Aas1euQWElHkNdL2Mksfsep+wO4mZI29Rrvhx2bpE6SVw+fz7RkJ3z9RAYWvw1dl3KZnN16ZdpPIwtDw+ENKT0PXREEyqmBUEQCvlu0VsGNsLYe7GZ3PhbOGnTVouYcpQPrBMEbDGE3GoYBE29KHiZJHvLqJ8FrQFlitI+NQ7FRbW/v0009nMpkJEyYcc8wxaAtEdOhOAD744IOFCxcWFRWdcsop4XAYXyP0YTJ0oRaYiN1HFApE5qXqz8Y3YbBiTxIRCDlxM695ziQjulAYY5DXSOtnljxo1U1jbzuyxu5Wq/4Ms/RPJMrg8/n2gITvX0jHl3isXth0Q4Ndgyz0Kxh2XN/LAULXJ8ooMBGBiQTA3chWDHaM7Ri8JDodZ9iOwY4BYAqSPgpmFRlV0IcBhLbAzb+B14K24nwEoKGh4ZFHHiksLDzjjDMKCgrQPg7aqbGx8fHHH/c87/TTTw+FQvgyMvWiy5ArGThaD0xyMi/gm7Fi1kCCBHLC7har7lQZmqEXzQIE8hfJwUbp/XbdqewlkDVWn9v1PzZLHwUF4fP5ciXh+yZvbLt9Y+oDZCGs73VC+fUa6eh2tAEUnIbgNIILZx3bMVgxdlaCLXQ6TrEdgx1jAKIXGWNgVJF5JLS+yBWnHuT0M2g7nv3RfX/4gxDixz/+cSAQQPsLh8PnnntuU1PTww8/XFhYeNpppwkh8P8R9kAgeqPa/jf2kvgWLpjZ04gAQi5c1byAndV69BYSxchfQu5rlDxk15/OXhJZ85zVVv15ZslikA6fz5cTCd/XrKx7bHXiOWTBEMETy28KalF0bxr04aQPR+F0ggtnHdsxWDG23wUUOp23gzMvIvMiA9AGkFkFo4qMKogIsues4qZ5aFPsVJ845fiyXv3QsYqKiqZPn75ly5ZFixYdccQRo0ePRlsg0csM/1cmcQW+nQf2mDUSAoScuNbrXu0kI7pIGGOQv4R+gFH8e6v+R+A0subZMTt5pRH9FUDw+Xy7T8L3VZ82v/O3HfciCwRxfL+rSs3ByCsa9OGkD0fhdOIUO6tgxdiOwVkLMDqdu5FTjyH1GEODvj8ZVTCrSB8NMrELXq2XmAl20KaE8MqiCaAfOkPfvn0vvvjiJUuWfPjhh2effTYRYY8ZwdOc1GOu/QF2yWWPQRoJ5ITdrVbdqTI0Qy+aBQjkKWGMMYvvsRp+DHaQNTf9J0fbSy+aA5/Pt/skfF+yIxN/cfONDA9ZGN9nxt6hw5DHKEhGFYwqAuDVsr0Cdoyt5XA3o/O5cNawswYt9zAFSD8YZhXpo2GMAjR8hfISF8PdhnbAah3pB6DzTJkyZePGjTfffPMFF1xQXFyMPUWB8LUttd8HGLvkgQFPgwk4yIWrmhd4zntG9DYSvZCnhHmEEfm1nbgU8JA11Xw7iV6y8Efw+Xy7ScL3by2qfsmmuY6XQRZGFU8dWXwieg5RRoGJCEwkAO5GtmKwY2zH4CXR6TjDdgx2jAFQIekHwqwiowr6MIC48ZewV6CdOOtQgM41YMCASy+9dMGCBaeeeurAgQOxZzTjYL3gRCf9LFrjMXvIGMYodlYjJ571N6v2RCO6UBiHIE9pBSfp3Ogkr8HucBpvIK23FjgePp9vd0j4dlJsPVdzTZOzA1kYVDhmXO/z0WNpAyg4DcFpBBfOOrZjsGLsrARb6HTcwnYMdowBiF6Q/WGvQrth9RGh85mm+Z//+Z8LFiyYMGHCiBEjsGfM8JUq8zJzGllwIc2iy52mWwAXu4/drVbdaTI0Qy+aBQjkIxk8k91a1bwQu8G1E5eYJb2EMRo+ny9rEr7/h1/ZcsvWzD+QhRJz0MT+cwVp8EGDPpz04SicTnDhrGM7BivG9ruAQqfzdsDegXblfAwwQOhsRDR79uy77rrLMIx9990Xe0BofY3QeVbTQmTBtd9D0aVm6YN2Yja725ALVzUv8OwVRvF8Er2Qj/SiS+A1qNQDyB5n7IbzzLKnSRsEn8+XHQkf8Lcd965vXIosFGiRE8tvNEUhfP+bBn046cNROJ04xc4qWDG2Y3DWAox8xU1wN0IbiK7hggsumD9/fiQS2WuvvbAHjNCFduoxdrchC1bTrYVlT5tlLziJS1xrGXLi2TFrx0QjOl+YRyAf6ZHrmBNuegmyxl6DVf8Ts/RJEhH4fL4sSPR465Ivv1f3KLKgkTGl/MaI3g++XaMgGVUwqgiAV8v2CtgxtpbD3Yy8w8460gaiy5g1a9bNN988e/bsYDCIXBEVBop+lk7MQRZce6Wy3pTmd42SxaplsdP4C0Bh97FXZ9WfLUMz9KKZgIZ8I4zIrZZX71l/Q9ZYbbATF5kliwEJn8/XGomebXN6zWtbb0NW6Ji+c/oWHADfbhFlFJiIwEQC4G5kKwY7xnYMXhL5Qa0DvocsvPbaa+Xl5RUVFZqmAfjkk08++uijyZMno00JIS6++OJ77rln9uzZ2AN68BSr+S5PVSMLVtNt0vwuQLLwHKEfYCcuZncbcuGq5gWe/a5RPJ9Eb+QZ0s3iu626aZ6zFlnzrL/ZyauMyC/h8/laI9GDNTpbn6u51mUHWTis7Mz9whPg2xPaAApOQ3AawYWzlu23YMXYeR9softy1iE7t9xyy5QpUwYNGqRpGoC33377lltumTx5MtpaYWHhuHHjnnnmmZNPPhm5E2bR7HTDRciCa7+vrLekeTgAYRxmlr3gJOa41hvIiWe/Ze2YZERvE+Y45BkqNEr+YNWewm4NsuamHleyUhaeC5/Pt0sSPZXtpf5cc3XaTSILlUXf/U7ZmfC1GQ36SNJHovB84gycteyshBVj+11AoduQEIXMTYQuZ/To0StWrEgkEtFoFLnSCybbzbe7zjpkwW75vTQPx04kSoySe1Xzb52m+YCL3cdenVV/jgz9VC+aBUjkERK9zZIHrbqp7NUja07jPNIGaYFj4fP5vp1Ej+Sx+/ym6+usz5CFPoGhx/X9GUDwtQcKwBhNxmgUTidOsbMKVoztGJy1AKOTkBz6/hrjoIMPJxGACIMiIBNkEkUgwhARwIQIA4Su6uyzz/7d7343c+ZM5I6M0MXphguQBZV51VMbhByC/yZkaIYwDrUTF7O7FblwVfMiz1pmFC8kbSDyCMlBRskfrLrTwGlky7MTF5uljwp9JHw+37eQ6JHe3Hb7Fy0rkYUivc+J5T+XwoSvA1CQjCoYVQTAq2V7BewYW8vhbkbH+njLKU3YW4THo00tW7bMsiwpJYCVK1eiPQUCgQEDBqxfv37o0KHIlV4w0W4+wHU+QuvYblkciNyILxHGoWbZC05ijmstRU485++ZHScYkZ9rBScijwj9QCO6yG44H3CRJU7bDdPN0mdI2ws+n++bSPQ8H9Q/+WFiCbJgiOCJ5TcGZTF8HU+UUWAiAhMJgLuRrRjsGNsxeEm0NzJffaNuxsxz0Naampq2bNkipQSQSCTQzk4++eTbb7996NChyB2ZRbNT9dORBSf1uFl0KYlifAmJYqPkXtWy2Gn8BaCQA262Exdr1htG5CZQEPlCC0zQI9c4yWuRNXa32Q3TzdLHQAXw+XxfI9HDfN6yYvn2u5EFAn2v33+VmfvA1+m0ARSchuA0ggtnHdsxWDF2VoIttAPL3X/Q4H3RDo455pgzzjjDNE0ATzzxxB133OG6bjwef+ONNwzDGDp06NixY9GmotFoXV1daWkpciUD39P0A1znI7SGOW2nHjVDF+J/I1l4jjAOthtmsrsROXHTT2ecD43oQqEfgHwhgz9i9blq+QOy5jmr7cSlRvEdgIDP5/sqiZ6k3vr8xU03MTxk4cg+F+4TOhy+rkWDPpz04SicTpyBs5adlbBibL8LKLSRVeuCkyZNQjswTbOoqCgQCAAoKCgAwMzpdDoQCGQymRdffHG//fYrLS1F25k6derDDz987rnnIndkFJ6XTlyCLDgti83C80ASXyP0A82yZ53EZa71OnLCaoNVN1UvulIWngkQ8oIevordjW7mFWTNzbzkNP1aL7ocPp/vqyR6jJRqeKbmSstrQRaGRSeOKp4KX1dGARijyRiNwunEKXZWwYqxHYOzFmDsgS21gzVNQ4fQNK2ysnLEiBGbNm269dZbk8lkaWkp2k4wGLQsC3tGLzjJavqV525Bazx3i7Jel4Hj8E1IFBslv1cti52meWAHOWDLabzWs5frkV+RKEY+EEZ0vlX3H56zDllTzXeRNkAGT4fP5/sSiZ7BZfu5Tdc2OduQhYGFo4/uMxu+boSCZFTBqCIAXi3bK2DH2FoOdzN2k+sF9xowAe3goosuGjx4sK7r2GnMmDFXXHEFERUWFjqOs2nTJgBlZWVoa/3796+pqSkvL0fOSOrBM6ymXyMLdupRGTgO34pk4TnCGG03zGB3I3LiZl717OP06K2aeSTyAAWN4j9adSezuxVZc5LXCm2QMMfC5/P9m0SPwK9suWVL+iNkodgYMKnfXEEafN2UKKPARAQmEgB3I1sx2DG2Y/CSyELN9n6HHVaFdjB58mR8ydCdAHiet2nTpueff37KlCnhcBht7dhjj33yySd/9KMfYQ8YhWfazXcwp9AalXmD3W2k9cG3E/pIs9fzTuJyN/MicsJerV1/tiw8Sw9fBUh0c6T1MYrvseqmgdPIlrITM8zSp0juDZ/Pt5NED/B27f0fN76OLAS08InlN5laCL78oA2g4DQEpxFcOOvYjsGKsbMSbOFb1GwfuLemoaMwcyKRePDBB0eMGDFu3Di0g8LCwlQqhT1DIqoHp9otD6J1yk4/YYZmYJeIioziO1TLYqdpHthBLli1LPbsD4ziBaQNQjcn9BFG9Dd2w0WAh+ywl7AazjXLniEqgs/nAyTyXXXTm+/UPogsCJIn9L8mavSHLw9p0IeTPhyF04kzcNaysxJWjO13AYUv2bxjIDqQ4zhLly596qmnJkyYUFtbe9JJJ5WXl6NLMgp/Yrc8BDBa46QeM0MXAYRWkCw8RxgH2Q0z2a1BTjzn71btiXpknhaYhG5OCxyvF81xmn6NrLH6xElcahTfDQj4fD2eRF7blln/8pZfAYwsHNVnVnlwFHx5jwIwRpMxGoXTiVPsrIIVYzsGZy1TWUb1QwfSNG3UqFHz5s0LhUKBQCAcDqMdEBH2mJBDpPkdZb2F1njqc2W9Jc0qZEHoowK9XrSTV7vpZ5ET9hrthou0gu8bkZtAQXRnMvRTdmtU6hFkzc28qprvkKGZ8Pl6PIn81ehs/XPNVcqzkIVDSk8fHp0EX09DQTKqYFQRAHfrjq0flJV56ECapg3ZCe0pEAhYlmWaJvaMHjxVWW8hC07qcWlWIUsUMqLzXfNIOzkXnEJO3PTTGedDI7pQ6AegO9MjN3jqc8+OIWtO03zSh2nm0fD5ejaJPGV7qSU1c1OqAVmoKDri8F7nwNfDaXvVNe4VjaaQd6LRaCKR6NOnD/aMHpiUEdewl0RrVOZlcAYUQNa0gqkBfZSdmOU5a5ETVhusuu/rRVfIwrMBQncljeI7rLqprD5Ftjy7YVag7BmSFfD5ejCJfMTwXtr8i1rrU2Shd6DyuL5XEAi+nsZLQsVZxaGqoeKs1hXro+yii5B3wuFwY2Njnz59sIfI1AtOtlvuQ2uYm53M63rBJOwOkvuYpU85TfNUy30AIwdsO403uNZSI3oriV7onkhEzZI/WrXfZ68BWeIWq+GCQNkzoBB8vp5KIh+9ue23nza/jSwUytIp5TfoIgBf3vOSUHFWcahqqDirj+HV4auC5marwULeyWQygUAAbUEPnm633IcsqMyf9YJJ2F1k6OFrNfNoOzGHvR3IiWctt3ZM0qO3auaR6J5IG2QU32XVnwF2kB1WG+zEpUbx3QDB5+uRJPLOmsQLf294BlmQZE4pvyEke8GXf7wkVJxVHKoaKs6qGt4OtKZA35RIJJB3EolENBpFW9D0/TV9uOusQWuczOsBbiYKYfcJc5zZ6wUnMce1liEn7NXa9WfLwrP08FWARDckjEON8M/t5M+QNTfzimr+rQxdBJ+vR5LIL1+0vLd02wJkgUDH97uyT2Bf+PKA1wj3C1ZxqDhUNTtr4O3A7hNotjM1yDvNzc2hUAhtRC+Y6jpr0CrOqMzLesFU5IREmVGyWLUsdhp/ASjkglXLYs/+wCheQNogdENa8P9ItV61/B5Zc5p+Q/pwzfwufL6eRyKP1NtfvLD5Jo9dZOGI3ucNKRoLX3fETVCfs4pDxaGqWcXhbkRbUdXIO67rEhHaiF5wYqbx54CL1jjpJXrBVOSOZOE5whhtN8xi93PkxHP+ntkx2YjcpBWchG5ID1/Bar1rLUO2PCdxsSh9luQg+Hw9jES+yLiNS2rmWm4zsnBA5PiDS34AX7fAzVCfsYpDxaGqWcXh1gCM9hEN7YBvl0jrrRljXPsdtEZZy5ibiULYA0IfGej1nJ282k0/i9xws52YrVlvGpGbQEF0M5oeXeDVnsTuF8gOe0mr4dxA2dOgEHy+nkQiL7isnt90fcLehCz0D444eq/Z8HVN7MD9jFUcKg5nDas43E2Ah45SEq6HrzV6wRTXfgetYkdl3tALJmMPUciIznfNI+3kXHAKOXHTT2ecvxvRhUIfhm6FRNQovsuqOwWcRnZYxe3EZUbxnQDB5+sxJPIBv7r11prU35GFiN73hP7XaSTh6wrYgfsZqzhUHCrOqhrqE8BD5+lVkqypqSkvL0e+WLVq1YgRI9Cm9IITMsnrAIXWqMzLesFktAWtYGpAH2UnZnnOWuSE1SdW3VQ9dIkMTQcEug+h729EfmEnLkHW3MxfVPM9MnQ+fL4eQ6L7e7fu4X8kX0EWAlrRSQPmFWgR7JrzAfSD4Gt7CupTVnGoOFScVTXUp4CLrqS4qPahl1/70Y/OQptyMs4jVz8y7KhhBx57oDSknbLvufCeY88/dt+qfdHO3nrrrenTp6NNkSiVZpWylqE1ynoN7IB0tAWS+5ilTznNt6nmewAPOWDbafqla8eM6K0keqH70ApOls6HquWPyJrT9GuhDxfmWPh8PYNENxdvWv72jsXIgiA5qd81xUY5dk1t8BrOE72Wgwrg2yMK7hZW1XDWQsVZVUN9Crjo2ggpVpvR1qQpv/uj7y65ZcngkYNLykte/d2rvQf3Hnr4ULQ/13U1TUNbkwWTlLUMrWGvSdnvSnMs2goZetHlmjHWTlzK3g7kxLOWWzsm6dFbNfNIdB96+ErPWefZbyNbrp242Cx7jrS94PP1ABLd2fbM+r9suZnByML4PjMGFB6EXfOSXsMF8BqhNkAfDt9ucOFuZlUNFYeKs4pDrQfb6Ib2rZAbNmwYMmQI2g4RDRo5qPI7lUv/uHTU8aM+euOjC35/ARGhna1cuXL06NFoB3rguAyuBDy0RmVeluZYtClhHmH2esFJXOZabyIn7NXa9WfLwrP0oitBOroHaRT/1qo9id2NyA57dXbiYrP0IUDC58t3Et1Wi6pbUnON8ixkYXTJD0ZEJ6MVLidmwv0cAKs46cPh+1Yu3M2sqqHiUHFWcahqsIW8cOjBxb9d/OKMGTPQ1sb/aPy9M+598qYnv3fh90KlIbS/N99889JLL0U7IFGmGaNc+320RmVeRuR6tDUSZUbJH1XLYqdpHthBLli1LPbs943ihaQNQndAotgovtOq+w9wBtnx7Hedpvl60WXw+fKdRPfkeOlnNl7ZrGqRhcGhw8b2Phet4cafs/02/kVVw/dl3nZWcahqOGtZxaE2gNPIU+TGQ6H96uvrS0pK0KZkQJaUlzTWNu5zyD5of1988cXAgQPRbmTgWNd+H63x3E2eqhayEm2PZOE5whhtN8xi93PkxHM+zOyYbERu1ApORncg9GFG5Bd24lJkTTX/VuijtMAx8PnymkQ3xOCXNs+rtTYgC70CQyb1u5ogsEucfopTD+J/qGr0ZN52VnGoaqg4q2o468Bp5DERgRxCshKyArKS5NDTTw/ffffdM2fORNthj9e8vqa5vrnisIrXf//6lMumaFJDe3r00Ucvu+wytBs98D2r8ZfIgsosNUKVaB9CH2n2WuIkr3TTzyE33GwnLtHsmBG+DhREl6cVfF/aq1TqfmSLneR/Cv050vrD58tfEt3QX7ff/UlzDFkIypIp/W/SRQF2zXmfG6/Bl7CqJvQY3nZWcahqqDirajj/AKeQx0QE2gCSFdCHQVaSrIToha8yDAwePHjNmjXDhw9HG0lsS7z9p7ePOfeYPkP6/OHiP1S/U71v1b5EhPbx1ltvVVVVCSHQboSsEHIfT32C1ihrqRGajnZDVGREF7nmUXZyLjiFnLipJzLWW0b0NmGMQZenR+Z66mPPfgfZYS9hN8wwSx8H6fD58pREd7M2+dL79X9CFiSZU/pfX6T3wq55272GWWAbX+ZuBreACpF/vCRUnNUaqDirajgfg1uQx0QY2kCSFZAVkBUkK6ENQBamTJkyb968/fbbT0qJPeZYzvKHlu990N4DRg4wAsaEcycsvXdp+f7loZIQ2kE6nY7FYnPmzEE7k4EJdvMnaI2y32VuISpEe9IKpgb0UXZiluesRU7YrbHqTpWhGXrRTEBDlyaN4tut2insbkV2PGeV03SLHv4v+Hx5SqJb2ZT6cOnW+cgKHdv3sr0K9seuccZruBDedvxvDLUB+kh0d14SKs4qDlUNFWf1D3j1yGMUghxMsgKyArKCZCW0coCQk3PPPffee+89//zzsce2bdiWSqbG/XCcbuoAJJLeZAAAIABJREFUho0fFn8nvm7ZukNOPgTt4Le//e15552H9ifN8Xbz79AqdlwrJgPHop2R3Mcsfcppvk013wN4yIWrmhd49nIjehtpA9GFkSgziu+06n4AdpAd1fI7YRyqBSbA58tHEt1H0tn8/KbrXVbIQlWvc4aGj0IrmJNXwlmNb8KqmvSR6F68JFScVRyqGirOaj28WuQxMqANJH04ZAVkBclKaOUAoY306tWroqJi2bJlRx55JPZM+QHlp954Kr7kpMtPQvt47rnnjjzyyHA4jPYnjcOICplb0BplLZWBY9EByNCLLteMsXbiUvZ2ICee/b61Y7IeuUErOBldmNBH6UVXOo3XI1vsJOcIfQlpA+Dz5R2JbiLjNj278cq0m0QWhobHH1J6GlrDzXdx5jl8G1WNLs5LQsVZxaGqoeKsquHtQB4jHdogkpWQFZAVJCsghwAC7WnChAkPP/zwhx9+OHLkSHQHK1assCzrkEMOQccgQzO/ozKvoTUq8zoi6DDCPMLs9YKTuMy13kROmJvsxCWatcyI3AQKoquShWd79rtu5kVkh72k3TDDLP0TSIfPl18kuolmVWt7KWShX8Hw4/peDhB2ia1l3LwQu6Di6FK8RrhfsIpDxaGqWcXhbkQeIx3aIJKVkBWQFSQrIIcAAh3u9NNPX7hwYWlpaf/+/ZElL8npJ6jgBxBhdKCPP/74ww8//MlPfoIOJM2jVOY1tMZzN3sqLmQFOgqJMqPkj6plsdM0D+wgJ2766Yy9wojeJowx6KqM6K8ztR+z+gTZ8ZwPnaab9fBc+Hz5RaKbKDP3Pm3wnX+umbs9sx7fLqzvdUL5dRrp2DX1CScuAVx8O1bVhM7DTVCfs4pDxaGqWcXh1gCMvCUhB5OshKyArCBZAbkPoKFrmDFjxm233fb9739/n332wa6pzzj1IKefAKehDaTAcegoq1ev/utf/3rhhReiY8nAUUgiGyqz1AhVoEORLDxHGKPtxCxWnyMn7NZYdafK0Ay9aCagoQuiQiN6h1X3fXAG2VEtfxTGIVrgePh8eUSi+yiUpf8x8Dd/2TJvQ9Pf8E0METyx/KagFsWueUmv4XxwE3bN3QpuAhWhA3Az1Ges4lBxqGpWcbg1ACNvSWh9SVZAVkJWkKyAHAoy0FUJIebMmXPfffc1NzePHDkS38Bj+2203MfWGwDjX+zlCByHDvHee++tWbPmwgsvRIcT2gAhh3hqA1qjrKVG6Dx0OKGPDJQ9ZyfnuulnkCNXNS/w7OVG9DbSBqLrEfp+evgqJzkX2WInebnQDyBtIHy+fCHRregiMLn/dW/XPvBO7f34KoI4vt9VpeZgtMLl5By4n6N1DBWHfhDaHDtwP2MVh4pDxVlVQ30CeMhbGrR+JCsgKyErSFZAVoJMdDdnnXXWI488snHjxhNOOAH/g5s4/RS33Ae3Bl/F1puEjvDEE0/oun722Wejk0hzvK02oDXKfoe5hagQHY9CRvQ21xxnJ+eCU8iJZ79v7ZisR27QCk5G1yODZ3j2Sjf9DLLDXqPdMMMsfRKkw+fLCxLdD32n7EdFeu+lW+e7rPBv4/vM2Dt0GFrDjTeztQzZYRUn/SDsIXbgfsYqDhWHirOqhvoE8JC3NGj9SFZAVkJWkKyArAAFkBdOO+20FStWLFy48Kc//alEDace5PQT4DS+kbsV6hPIfdBu0un0HXfcMXHixGHDhqHzyMBRdsu9aBU7rhWTgWPRSbSCqQH9QDsxy3M+Qk6Ym+zEJZodM8LXgYLoYozIzzPOGlZxZMdzVjvNC/Siy+Dz5QWJ7mlY5Phio/y5mmvTbhLAqOKpI4tPRGs4/Qyn7kP2VDV2m4L6lFUcKg4VZ1UN9SngIo+JXiQrISsgK0lWQD8AVID8dcgho4fuXffZquP3Kd8IMHaJ7eUk90H7ePPNNz/44IMLLrggFAqhU0njMKIgcwqtUdZSGTgWnYfkELPsWafpdtW8CPCQEzf1RMZ6y4jeJowx6FIoaBTfYdWeDE4jO6r5Ts2sEkYVfL7uT6Lb6lcw/AeDFv655uqw3mdc7/PRKucDbrwau8WpRisU3C2sqqHiUHF21kB9CrjIY6IXyUrICshKkhXQDwAVoIfgZk4/yS33Fbk1ReXIirUcwbPQ1rZt2/bAAw+MHTt29uzZ6ArI1MzvqMzraI3KvIYIA4TOJPWi2ZpxiJ28jN2tyAm7NVbdqTI0Qy+aCWjoMoQcqoevdZJXIFuenZhjlr1Aohg+Xzcn0Z1Fjf4/GLRQkCZIw655O7zELLCN3cGqmvBlLtzNrKqh4lBxVnGoarCFPCZ6kayErICsJFkBfX9QED2Q+oxTD3L6CXAau4Ptd4kzoADaSG1t7aOPPhqNRi+++GJd19FlSPMolXkdrfHcLa6zTtMPQGcT5liz7AUnebmbeQU5clXzAs9aZhTPJ20gugwZnObZ77rpp5Addrc6ySuN4jvh83VzEt1cQCtCq9jyGi6Euw27y9vO6efgbYaKs4pDxcEZ5DERgRxCshKyguRw6PuBCtGjeWy/jZb72HoDYOSAM+y8T0YV9ti6deteffXVcDh83nnnmaaJLkYGjkIS2VCZ1zT9AHQBJIqN4nvc9FN2ci44hZx4zgfWjsl65Aat4GR0GUbkxoyzmlU1suNmXnJTj2nBafD5ujOJ/MecvBLOh8gJJy9FvhK9SFZCVkJWkl4BrQIiDN+/eElO/4lTD8GtwR6ylsGoQq62b9/+8ssv19fX77///jNmzCAidElCGyjkEE9tQGuU9bpZNBNdhlYwNaAfaCdme84a5IS5yU5colnLjMiNoEJ0BRQ0im+3ar8PTiE7duMNAeMQkvvA5+u2JPIdt9zDmSXwiQjkEJKVkBWQlSSHQpTB93WqmlMPcPpZcBptwU0vk0VXYHc0NTW99957//jHP1zX3WuvvU488cRwOIwuTwaOsZs3oDWu/QF7tSTK0GWQHGKWPe003a6aFwEecuKmn87YK4zobcIYgy5AyKFG5AY7cRmyxCk7MdssfRKkw+frniTyGlvLuWk+eiARhjaQZAVkBWQF6SMgesG3Ky5bS9HyANtvA4y2I7wNDyy+JW2HAei63rdv32AwWFhYGA6Hmblpp3Q6vXnzZtd1ATBzKBQaM2bM+PHjiQjdhzSPtpvvRus8lXlTD56CrkXqRbM14xA7eRm7W5ETdmusulNlaIZeNBPQ0Nm0glM0669u+hlkx3NWO8236kVXwOfrniTymNrAidmAi7xHRZCDSFZAVkBWkKyENgC+LHEzp5/klvvg1qBd8BnT9qaCUwA4jrNly5ZUKtXS0rJp0yYiCoVC/fr1KygoOPbYY6WU6M6keQiJCHtJtEZZr+nBU9D1CHOsWfaCk7zczbyCHLmqeYFnLTOK55M2EJ3NiPw846xi9Rmyo5p/pxnjhDkWPl83JJGvvKTXcCG4CfmHQpCDSVZAVkBWkKyEVg4QfLtLfcapBzn9BDiNdmUtR8EpAHRdHzhwIPKWlOaRTnoJWqMyb4AVSKLrIVFsFN/jpp+yk3PBKeTEcz6wdkzWIzdoBSejc1HQiC6wak8BFLLi2ck5ZtmLJIrh83U3EvnJ5eSlcD9DHiAD2kCSlZAV0IeRrIRWDhB8ufPYeh0tD7D9NsBof2zHCC6gId/JwAQnvQStYW5W9rvSrEJXpRVMDegH2onZnrMGOWFushOXaJlX9Mg8EmF0HqGP1ItmOk23ITvsbnOSVxjFd8Pn624k8hE3/Yqt5eiOSIc2iGQlZAVkBckKyCGAgK9NeElO/4lTD8GtQUfyEnDWQD8Q+U6aRwMa4KI1ynpdmlXowkgOMcuedppuV82LAA85cTMveM6HRvQ2YYxB55GhGa71lme/jey4mZdV6mEZPB0+X7cikXc4/TS3/BHdg4QcTLISsgKygmQF5D6ABl87cb+A/Q7cTehwbC0n/UDkOxJRzTjItd9Da1TmNYSvRlcn9aLZmnmonZjD7lbkhN0aq+5UGZqhF80ENHQOYURvsWonsdeI7DiNN2nG4ST3hs/XfUjkGWcNN16LLkpC60uyAvpwyAqSFZD7ABp8HUYfQcX3kFrPLb/n9BLARUdh+6+EGegBZGCCa7+H1nhqg6c+FXJvdHnCqDLL/uI0XuWmn0OOXNW8wLOWGcXzSRuIzkBafz1ys93wU2SJ03Zijln2BKDB5+smJPKJu81rOB+cQZegQetHsgKyErKCZAXkUJABX6eTQynyKyq8kFvu5vSfAYUOYP8dXiNEGPlONydY+CWyoKylhtwb3QGJsBFd5JpH2cm54BRy4jkfZHacYERu1ApORmfQAhO1glPc9JPIjud8oJrvlqGfwufrJiTyBlte4iJ4O/AtHFYWKwD0T4x/IhAIxKB/AhGI8E9EAAgEIgYRAELrNGj9SFZAVkJWkKyArASZ8HVZcm+K3EyhWdzyB04/Ds6gfblsv0WB7yHfCX0/oZV7bg1aozJ/MQp/jO5DK5ga0A+0E7M9Zw1yw8124hIt84oemUcijA5nRG7IOO+z+hTZcZrnC/Mooe8Pn687kOhwdsZ+6PKHqqZV7Vu1LwA7bT94+YPjfjiu8rBK7Am1Ad4OfDvGf+N/wr8wGP8P439j/DcGEYgJRMQAgUAEIiokrR/JgST3EXJ/0keS1oeoEL7uRetH4aspdD63/IFTj4BTaD/2cgS+hx5ABo62W+5Ha5T1DrvbSeuN7oPkELP0SafpFtXye4CREzfzgqfWGtH5Qh+FDkZBI7rAqjsF7CAb7NiJiwNlS0AmfL4uT6LD6aZ+2CmHvbjwxQHDBgQjwTcWvxEIBfY+eG/sIf0AUfYSt/yeW+4CO/gaBiMnzGAwmPFPjP/GSXhJOOvwZaSTKCYqJlFMoliIYtJ6kSghUSa0XiTKSJSSKIavqxG9qOhyCl3EqYe55XfwkmgHbC0j9AjSPNpuuR+t85zMX4zCM9G9kKGHr9QC4+3EHHa3IiesPrdq/0OGztOL5gASHUjoI/TQxU7TLcgOq2qneZFedBl8vi5PosMR0f7j9v/4bx+/tOilgycfvOqlVRf8/gKpS+w5KqDQTAoc5yWvhfM+vopBaG/ssLudsR27QJJEqRBlJHqTVkKiVIjeJEpJKxVaXxJlJErh6xQUosLpFPwhpx7mlj/Cq0XbcrdCbYAcgnwnzSqiAuY0WqMyzxuFZ6IbEkaVWfYXp/EqN/0ccuSq5rs8620jOp/kIHQgGbrQtWKeHUN2VPOdmjleGGPg83VtEp2BiCbOmHjHOXdUv1t9/EXHh3uF0YbkvqL0EU4/y003w6vH/8foClixu811twFr8Y1IJ1EsRB/SegvRh7Q+pPURojdpfYToTVovQMDXfqiQCs+j4NmceZ6b74D7OdoO238lOQR5jwLSPMrJvIDWKOsd9mpJlKEbIhE2ootc8yg7ORecQk48Z1Wm9gQ9fJUMnoaOI4zorVbt8ewlkRXPTv4sUPY8qAA+Xxcm0UmELkrLS7du2Dp41GC0PaKCk8k8ipsXcepBwAPAYHQL7LC73XW3w8E3IFOI3qT1EVof0voJrb/Q+pHWT2h9SfSCr62QTgUnU8FkTj/LjXPBCm3CWo7gWegBZMFEJ/MCWuc6mZeN4OnotrSCqQH9QDsx23PWIDfc4iSv9KzleuTnJIrRIUjbSw9fbydmIzusPnWafqmHr4PP14VJdAbP9VY8s4I9Hn7U8FfueeXE/zzRCBhocyJC4aspcLzXeB3UejDyAVueuxHuRhdfQzqJYiH6CDlQaANJ60Oij5ADhTaIRBi+XEhAAyu0EbbfJc6AAsh3MnAMKADOoDUq/bwRPB3dGckhZtnTTtPtqnkR4CEnbuZFz16hR3+lmUehQ2gFJ2mZl93MC8iOarlfmEdr5pHw+boqic6w6R+bPnjhg1OuPiXSJ/LAfz6w5vU1Bx1/EAlCezDGiLJnOPUQEtchv7HD7nbX3e46q/FVJCJC60daudAGCjlQaAOEHEjaAKIC+HaFOfVHtCHOsLOSjLHId0SF0jxSZV5Ga5T1Fnu1JMrQvUm9aLZmHmon5rC7FTlhr9au/4kMnqqH54IK0P70yE2evYK9HcgKO8nLRdlLJCLw+bokiQ7XXN+89A9LR08e3XdoXwATzpvw6l2vlu9X3nuf3mgvkoJncfPvoL5Aj8Re0vWScNbhq0hEhDZQyIFCG0hykNAGCjlQaP0ACR/A1ptw1qFtWcthjEUPoBdMUpmX0TrlpJcYheeg+xNGlVn2F6fxaje9BDlilXrEs1fq0duEfgDaGYliPTLPbjgX2WF3q9N4kxH9NXy+LkmiwzXuaCwbWDb6xNHYqeKQii3rt+z4fEfvfXqjPTFb8H0Ve0nXW+06q/FlJIVWLrQBQhso5CAh9xZyiNAGgXT0MNzyO7Q1tv5KRegJZOA4kAm20Bon9ZRReA7yAomwEV3omuPt5FxwCjnx1Hqrbqoemi1D0wGB9qQFJmgF/+Gm/4TsuOk/uYHvaYFj4PN1PRIdrt++/frt2w9fMu6H49ABvBb4ssHKU5956jN8FWm9NTlUaANJDtJkpdCHCq0/oCFfOR/CXoE2p9bD3QKtL/IdUUj+X/bgA7CKKmEb8HtmzszcufemEXoEEaWTIEIAKboUcVERFEXBZS0riijNjoDKWrChqCgsgrq6FlBZlaKIiELAQlEISAlFCMUAIeWWuVPOOT8fu36/fpowhCQkN/M8WncntgwnwuwN3Nkp0bMRL2T9Sp/Sziocy+1NKBth2qEnmZWlJj1D5PqoSErSg9xaLdgBuGMXTZDUTCIlweOpYihqCiFEFJ5TINghhx3CrxFFkhpItLFEm0lKC0luLNHGktwIIKj+ROQfcIn4ie9yEfs3hAkXhLWa6INQAyi+y5zYMrhgG/O1hHsQRwg9W6v9bzs03Qm/CHCUCTdXmUcuVhIfkfXLUWEISVCTnzbz/wIIuCD4ITv0uJr0JDyeKoaiZhDCADg85UvYnO3lbC/MLPyCSIkSbSbR5jI9R1JaSPQcSW6IasfZLWLL4A7xDyUJ95LgCBF5VRjvQRgonbkS+iDUAFTvR4omChHBidjR+VrCXYCEuEKVhLGymmkV3SVYHspE8GKrcIxsZamJD4EEUDEktSsNDHMib8AdFp3HfJfK2gXweKoSipqBEH9iw70QMcGLhCgSvEjwIiFMiJjgeTz2qbCzxTEEEBAQAASBEAKekyR4MbPWMWudjf8iJCjRsyTaTFJayLSZpDSX5EYAQRUmoq8BHG4QlQRuwDFyQ5I4kQRHiuhbIvpP8GKUQFirCBggI94R4qe+i2zjQ5wIZ/uZtUZWOyPuSFo3rfZndvGDzPgIZcWi78XMr9XkZyU1ExVDSbifmSuFsxvu2EUPyHWWgATg8VQZFDUK8RHZR1AP/0dwJKy1vPghODkg+P8IBIQABAAhELwdciMhigQvELxA8KOCFwhewHmB4AUQJjx/RIgws7OZnQ0D/0GkBIk2k2gLmZ4jKS0keo4kN0TVwYuE8RHcIb4BkOrif0m1SHAUCdwoom+LyGzwQvweL4K9CUo71ACK/0rb+BAuWNH5utoZ8YhIiWryNObraxeNF7wYZSLYPjN/CA0OVxLuAijKHdHVpGfM/MEAgwuC7bdDTymJk+HxVBkUnv9QO0q1PxLRt0ToOYgofkFACI4jhEjJxH8VSiBEVPACwQsFPyp4geBHBT8q+BHODgueL3i+YIeEiMADCB5i1npmrbfxX0RKkGhLWWkjK60lpY1MW4CoOE1E9C0IA64QErgJv0eCJHAL8Q8TxjwRmQ2Wh98S5kqitEMNQLUeRKoj+GGciGN8LJImERJEnJJ9l0hKhlV4J7fWoIyYE57Jza/V5OcIPQvlTVLPo8FbnPAMuONE/iX7LpPUTHg8VQOF5/+jxH890S4WocdEbAl+z8lByQjxE9kPOQ2lEDHO8wU7JPhRwY9wdkjwfMGPCp7H2WHBfhYijBpJ8BCz1jBrDf6LSso5Mm0tK60lpY2stCFSMiqJI4x34A7x9QE9GyUhOvFfT/ShIrZIhF8G+wm/EGYWCd6BGkFW/AOs8GyciBAR2/hY9Q9F/CLyGVrqO074FTs0FXBQJtzeEDtyiZJwLw3ciPKmBMdyczm3t8IVbhXd76u9CMQHj6cKoPD8H3J9kvwizC9E8d/BDuBXhJNDcGqIT5LTIKehJMIUvJDzQ4LlcX5IsDzB8jjby1me4IcEL0JN4XB7K7e32sZ8HEfkujJtLtFmspIhq+kSPQeQUAGEsQAsD+6QwM04IaIQfSDRLxPGQhH5B5ydOMbeAF4EKQk1gKIPssKz4YIdeVv1D0Wck2lwhKR1tQrHCmc3ykbE7OK/c+tbJWkKkVJQjoiqJE01jwwAHLggnF12eJqScD88niqAwvNHiNaL1D5fRGaLyEwIG//h5AACIKg4RCNyPVmuByUdvyNERLCfOTsk+EHu7BfsAOcHubNf8AOChxDXBDvksEMws3AckRIk2lpWWstKuqy2k+jZgITyIKL/hEtqRyjt4RYl+kCiXy7ML0X4JdjZwvqG+C5GDSArbSSlJbe34kSYvZHZ2bKSjngnKRm+2ovt0JNO5HWUFYst4dY6JflJWeuF8iMprWlwuBOeAXec8GzZd4mkZMDjOd0oPCUhOgmOIr6+vOgh2OtxjIiCHYCchtOEkAChZ0v0bPyeMDnP485ewfI4PyScPZzt5SxPsP1CRBF3BA8x61tmfYvjCAlISitZSZeVDFlNl2hzlImwvoH9I9wh/ptw0iSi9SJaT2F+BXYINYaqXxGzp8AFO/KWnPwEagLiUxIfktQudtF4wQtQJoIfsY7eTP3XKomTQHSUEyU4lsU+F04OXGF24b1a7QUgCjye04rCUzraQkp9RxgfidAU8ALh7CByGqogoklyY0lujP9LCHaYs/2c5XK2lzu5gu3lTi5nBwAH8UKICLPWMmstjiNyPVk5V1bbycq5stKOSAlwKfIaXJLPIL6eKCNCtD+hJlH8V8dCz0DYOBHb+EhLmkhIEDWD7LtYUjvYhfcx8wuUkXCi7zBrjZo8TVLaoFwQVU1+0jxyNcDgAne2OZGXaXAMPJ7TiiIu7Ajv+zZ/83VnXowKQYg+kGg9RfgZODugXYjqhBC5rizXldEevyV4EWd7ubOXs73C2cPZXu7s5SwXEKjmBMtz2BIntgTHEbkuVTNlNVNW0mUlHcSHP8R+EuZXcIcEbgRkeNwhUm3F19c2FuFEhIjY0Y/UwHWoMYhUW60124m+axc/AmGgTISzwzwykAZvVxJGAxJOmaS0p4FhTuR1uGOHX5J8/STaHB7P6UNR/R0wjkzMnlVgFedbxaOaXUVAUBGkJJL4CHgR4gWRkmQpXVbS8StCRIWzl7Nc7uzhbBd3dnNnN2cHAYFqS7BDtrHINhbhGKLIShtZOVdWO8hqJ0lugF+IyOsAhxtSItEHwXMyFP91trEILtjRN9XAdahZCPUPkdVMq3AstzejjBwn/Dy31qjJU4lcH6dMSbiXxZYLtgduCNsuvE+r/QEgoayKi4sLCgqOHj0aCARSUlJq1aolyzI8HtcoqrkjZuH9G18usIoBLDqwKuoYd7e8jhIZFURKQlwjxE+UlpLSEr8mbM4Pcns7c3KEs4ezvdzZy9leVEfCZtYPzPoBkdcBELkuVTNlNVOmrYjxb7hD9GtA/PCcDKp1k2gT7vyEE2H2j8xaJ6sdUMMQeo5W+0M7NN0JvwhwlAm3VpuH+ypJf5f1gThFRFeTp5j51wECLnD7Byc6j/qvhTtCiPXr13/99dffHrd7927HcfBbderU6dChQ+fOnbt06dKtW7eEhAR4PCWjqM6K7Mj4jTPyYkfxi+WH1kdYbGLrGzVJgae8EEWSG0tyY4o++IXgRZzt5c5ezvZyext3crizW4gwqhXBDtnGIttYpBKqEgpXZOK/Dp6TRlT/kFjxFLhgRWbragfURFRJGCtrna3CuwQ7iDIRImQVjpNjS5Wkx4mUhFMgqedT/2AnOhfuOMWPy1pPItdDqbZt2/av43766ScASUlJnTp16tevX0pKSq1atVJSUiKRSEFBwdGjR3Nzc7/77rtPP/0UgN/vHzhw4F/+8pe+ffvKsgyP53coqq0oi03Inrk3moff+i7/xwkbZ05uOzxAffBUGCIlyVK6rKTjVwTLY04Od7ZzeztztnN7qxBhVH0ElMhwh/j6QW4Iz8lT/NfEQlMhLJyIbXyqJe6V5MaokST1fK3OErvoQWZ8iLJiscXc3qAmPyupnXAKlMSJzFwh2EG4IETIDk1Rk6ehBCtWrHjwwQe/+uorQkjXrl3vvffeCy+8sGXLlpIkoWSHDh36+uuvP/jgg/nz57/99tsNGza87777br31Vk3T4PH8CkX1ZHL7oU2zc0K5+CPZRTvv3TD98YwRSUoQnkpE5HpUrgetO/5LcLaP2znc2cacHdzexp2dQkRQxVDIEgjcIYEb4CkTItVSfBfbxgKcGLMi//QlTkJNRUiCmvwc0y6wih6ECKNMBNtv5g+lwduUhDEARdmQoJL0mHX0JrjDjI+Yfrms9cJvrV27duLEiUuWLKlVq9ZDDz00bNiws88+G+7UrVt3wHEvv/zy/PnzX3zxxTFjxkydOnXSpEk33HADpRQez3EU1ZAj2KM/vraxcAdKtiO8764fXpyScVsdLRme04ZIciNJbgT0wn8JzvZxO4c725izg9vbuLNTiAhOKwUy3GHgRuH9staDat2pmgnig+dkKP7rbGMBXLAj72jBsURKQA0m61f41E5W4Z3c+g5lxJzwdB5bqqQ8L9EWKBNZ6ynrA5jxEdyxix6U63QB8eO4WCz28MMPP/3007qu33fffffff39ycjLKJBgM/vW4zz///J577hk+fPisWbPeeOONli1bwuMBKKohhzObOziR3Gjend8/P6WUauG0AAAgAElEQVTdyDP0OvBUFUSSG0lyI6AXfiFYHrOzmZ3N7I3czuFsLyqRDCITCe5YnDG+idmbrPAMgMpKK6p1l7UeVO0CQuE5EaqdL9Fm3MnBiQgRtqNz1eDNqNmInKalvuNE/mmHpkDYKBPubDOPDFCCY2nwFkDCyVMSH+LmSsGPwgXB9tvh6UrCvQDWrFlz/fXXb9myZejQodOmTatTpw7KQ58+fdatWzd79uy77777vPPOe/zxx0ePHi1JEjw1G0U15JPVR9NvfWLLGysPb0CpDpkFd33//GMZI84JngFPVUXkelSuR319cJzgxdzZxuxsZm3kTg5ztkLYqDAKoXCHQzAw/H8Os7OZnY3wDEICstpe1npQrbuspMNTIqIG/xYrvB8uWJE5avAGgKKmk2jgRkntaBWOFc4ulI0w7dCTzFqlJj1N5Po4SURKURInWIV3wR0nPEv2XTZrzopRo0alpKS89957V111FcqVJEm33HLLRRdddOONN44bN27p0qVz584NBoPw1GAU1RMl8gOtrn9envfpz9+gVIV2+N4N0//e9pa2SU3hqQ6IlCirmbKaiQD+h3A428WsbGZvZHY2t7cIEUE5IYBMZLhjCwclECLimFmOmWUCRK5L1UxZ66FovYhcH57fUvWrzOJnBD+CE+Fsv218puiXwANISrqv9iI79KQT+ScgUCbczDKPXKwk/l3WB+AkyfqVkjGfm6vgCtu1adjtt6/v3v2CefPm1atXDxXjrLPO+uKLL6ZMmTJp0qQePXosXLgwLS0NnpqKotqSiDS2xTUBqn+wbzlKFXFiD2ycOanNjZm1WsFT7RAq0eYSba5gEP4H585PzN7M7A3M2sDtbCGiKCtKKIErAnAEhwuCHbKNRbaxKAYiK61lrTvVulO1M4gPnmOIqgauM0PPwwUr8oqiXwLPfxCfkviQpPW0C+8R/BDKRPBiq3CsHPtMSXqcSEk4GWrio7Ejf4Yw4UJa/aMzX+j915sXaZqGiiRJ0oQJE5o1a3b99dd36dJl8eLF6enp8NRIFNUZAbnl7AHJanDOrgUolcmthza9Mq7FtRfV6wRP9SZJtKlEmyp6f/wPxp2dzMpm9kZmZzN7I4QF1xQiwx1HMAGBkyOYvZnZm63wP0B8VO0oaz0UX1+Jno2aTQ1cb4ZnQpg4EWatY9YaWc2E5xeydoFUZ7FddB+LLUNZsdhibm9Qk6dKame4RmgTJXi7HXoWLjhMuuH6qxVNQ6UYPHhwWlrawIED+/Tps3LlyubNm8NT81BUf4Mb9dZl7aWcDwQESsYEn7r1nbBjXJF2ITzxQ5Zoc4k2VzAIxwiHOVuYtYZZG5mdzZ0dgEAJZCJJIHDHFg5OhYg5ZpZjZpnFUyS5MfX1pr6LqNoZREHNQ6Tain65HX0PLpih6f7Uf8LzK0RKVVNmM2O+VTQJIooyEWy/mT+EBq5XEh4AUeAODYxwjAXCyUGpcg/Wb5bxJqHnoBJ169Zt2bJlf/rTn3r37r1y5comTZrAU8NQxIX+DbsHqf7M1rcdwVAyATFzx7+PmsV/a9ofnrhEqKyky0o6AjhG8KPM+oHZG5i9gVk/CH4Uv6ISCneY4BwC5YSzvVbkNSvyGpESqNaDan2orzeRUlCTqIGb7eh7cMExlzN7k6y0hee3ZP1Kn9LOKhzH7WyUkXAir3NztZI8TVJawQ2iqEmPmfnXAAJ/JO8QW7W+y3U3zgUIKl1GRsaCBQsuPi4rK6tOnTrw1CQU8aJn3Q5+2ffYj6+b3Eap5uUus7g94pwrCAg8cY1ItaivF/X1wnGc7WXWWmaucazvwHbKkOCOBQcVQPCQbSy2jcWALKuZiq8v1ftKcmPUALLSimrdHHMVXLBC0/VaM+H5HULP1mrPt0PTnfB0gKFMuLPdzL9CCY6lwVsACSciqZmyfzCLzsVvCUHe+SCUvePS56a9BhCcJt26dZs/f/5ll1127bXXfvbZZ7Isw1NjUMSRzqltHk2/9aFNs6MshlJ9uH9F2DHubDFEJhI8NYYkN5b0xop+JQARmiwib8EFDsEER8VizPqGWd+g+O+S3Jj6eiv6ZbLaESCIX2pguGOuggt27BPN2S7R5vD8AaokjJW1C6zCOwXbg7IRph16kllZatIzRK6PE1ES7uexzwXPxy9Mp2n/a9Y6ovVXX80ihOC06tu37zPPPDNmzJgJEyY88cQT8NQYFPElI/mcp9rdPiH7H0V2GKX6PG9NlMXGt/qrKinw1DTCEMZCuOMIB5WIs71W5DUr8hqR6yu+vtR3CdU6AzLiDvX1lOg53NmBExNm6GU9ZRo8JZDU87Q6C+yiB5nxIcqKm6vMI/2UpEdl36UoFZGSlcSJVuE4AIQkWPKtnS58tqjIt379+6qqogoYPXr02rVrn3rqqczMzEGDBsFTM1DEnWYJjaaeO2r8xhmHzUKUavWR7EnZsx5ue7Mua/DUJML4CLwI7tiC4XQQ7Gcr8oYVeYNIyVTrpeiXUe1CEAXxg2jB243CcXDBNj7SEsZKtAk8JSAkQU1+jvn62kUTBC9AmQheaBXcIfsWK0mPEykJJZP1gZLxAYGqJD12w3Vjd+3as2TJkrS0NFQZL7/88rp164YPH961a9cGDRrAUwNQxKNG/nrPnjv6/o0z9huHUaofCnPu2/DSo+m3JioBeGoMEX0LLvn6+NQejvmNY2YJfhing+CFtjHfNuYTKYX6+iq+flTrAaKg+lP8A8zQs5zl4sSYFZnlS3ocnlLJvn6S2tEuvI+Zy1FWLLaY2z+oyVMltQtKpqXMAVEXL148d+7ce+65p3fv3qhKgsHgO++807FjxzFjxsybNw+eGoAiTtX11Zp67ugJ2TN3hvejVNtCe+/e8OKUjNtS1SR4agJ7PZxtcEcK3CYp6Yp/CADubHPMLMdcycxvhYig0gleYEfn2tG5REqkvr6KPoBq3QCKaoyqwRGxoglwwYrO04KjiVwfnlIRqY5aa44TfdcufgTCQJkIdsDMH0oD1ysJ40FU/CGiFhcXjxgxokmTJg899BCqnoyMjHHjxj311FMffvjhwIED4Yl3FPErRU14qt0dD26atbloN0q1J/Lznd+/8ETGbQ302vDEOxF9Hy4pbaCk4xcSbaHSFmrgbwBj9o+OmcXMlY71LYSNyiV4sR19346+T6RkqvVS/FdRrRtAUA2p/mvM8AuC5eGEhGVGZvsSJ8JzYoT6h8hqR6vwTm5vQhkJJ/I6N1cryc9JSmv8kQceeGDfvn1Lly4NBAKokh5++OH58+ffcccdvXr1SkxMhCeuUcS1INWnZNz2982vrT26BaX6OZZ/5w8vPJ5x21mBBvDEMREVsU/gDvFfjz8my0q6rKQjeJsQUWatZ+ZKx8xi9iZAoBIJXmgb821jviQ3oL4/K/plspqJ6oWoWmB4rPhRuGBH/qUFbyNSKjwuENpMq/1vOzTdCU8HGMqEO9vN/CuV4FgavAWQ8Ctbt26dOXPmsGHDevfujapK1/UZM2ZcdNFFU6dOnTx5MjxxjSLeaZI6ue3NT27514rD36NUR63ie3548ZH0W1olNoEnTgljIUQEbkgpxNcPJ0KIn2rdqdZdAwTLc8wsx1zpWFmCHUIl4uygFXnNirwm0bMV/QrFP0iS01BNKIG/mOEZgufjRISIWpHXtYS74HGLKgljZe0Cq/BOwfagbIRph55k5ko1+RkiN8AvJk6cqCjKI488gqqtT58+ffv2ffbZZ0eOHFmvXj144hdFDUCJPL7VsAD1fXLwa5Qq5ETHb5zxUJu/tU9pDk88EsZ7cIfog0E0nAwi11P8gxT/IADc2e7EVjjmcsf6FsJCZeHOTjP0jBl6lmqdFf0qqvcjJIiqjRC/GrjBDE2FC1bkVTUwnEiJ8Lgmqef56iy0ix93ou+grLi12jx8sZI0WdavALB27dr58+ePHTu2cePGqDg//YTZszF3Lo4eRZs2uPVWXHEF/H7MnInNmzFiBNq0wTHr1+P553H55Rg0CH/k8ccfz8zMfOKJJ5577jl44hdFzSARaUzzwQnUPy93GUplMHPSplnjW/21W+0MeOKMsx32BrhCiP9qnAKJNleDzdXgzUIYzFrnxJY6sSWcHUAl4Y75tWN+jaIHFF8fRR9EfX8CKKoqNXCTFZkleAgnInjIiv5LC46E56SQoJL0uKT1sIsmCF6AMhEiZBXeKcc+V5IemzBhQjAYHD9+PCrOjh145hnk5mLOHDRpgkWL8MorOHwYd9wBzuE4EAL/IQQYA+coQYcOHa666qoZM2aMGzeucePG8MQpihqDgPytaf8Exf/qroUCAiWzufPoj6+Pa35N3/qd4Ykjwngf7hD1fMiNUR4I0anWnWrdkTSZ2T865nIn9gWz1gMMlUCYtrHINhZJcgNFv0LxD5ZoU1Q9REpQ/X8xwzPgghV+RQ3cSIgOz0mSff0kNdMuvI+ZX6CsWGyxFf0aztZRo8bVqVMHFYQxrFmDnTvx4IPo0QPH3HwzLAtZWejWDSdv8uTJ77///osvvvj000/DE6coapjBjXoHZN+LOe8LCJSMC/7stnfDjnHlGX+CJz4IWxgfwyX/1agAstJaVlprwdsFL3TMVU5sqRP7TIgwKh5nB83wy2b4ZVlJVwLXKfoVhOioStTgcCvyuhAGTkTwfDv6rhq4EZ6TR6Taaq3ZTuRNOzQFIoYykaWCd+fUjanXouIcPYqtW1G7NjIz8R+KglatsG4dduzAfwgBznEM5xACpWrVqtXFF188e/bshx9+OBAIwBOPKGqeSxt2C1D96a1vOYKhZALiHzs/LLBCf2vaH57qT5ifgR+FG1IS0fqgIhEpWdEvVfRLIUzHWuPEltqxxYLloeIxO5sV3m8WP6b4+iuBYbLSBlUDkWor/mutyGtwwQrPVP1/AVHgKQtCA3+VtW5W4ThuZ6NMFi5tMmx4OiqOZcEwEAxC0/C/AgFQimgUxyxciHnzQCmOcRwEAhg4EKUaNWrUp59++tZbb91yyy3wxCOKGulPdc/zU9+jm183uYVSzctdFuPWyHOuJCDwVGvR9+AO8Q0E0VA5iEa17lTr7kt6iFnfO7HP7NgS7uxCBRM8ZEXftqJvy2p71T+E6v0JCeB0U4MjrOi/IGycCGcHbeMDxX8tPGVF6Nla7fl2aLoTng4wnIyv15jN0h9DhdI0+P3IzYVhwO/HMUIgHIbjIBCAaaJPHwwbhubNcUx2NubMwYn069evefPmL7zwwvDhwwkh8MQdipqqU63Wj2eMeHDTrIgTQ6k+3r8y4hh3tRgqEwmeaortF9Y3cIf4B+E0kGS1g6x20BLHc2e7bSxyYp8zOxsVjFnfG9b3pOjvin65GrxZoufg9JHkBoo+yI6+CxfM8EuK/yqAwlN2VEkYK/sutArHCWcP3IkaeH5WvY8WdkOFSklBy5ZYvRrffIMLL4QkIRbD5s2IxXDOOfjuO/h8qFsXZ5yBY/Ly4PPhRAghI0aMuPPOO7/77rvOnTvDE3coarC2SU2fPXfM+I0zjlrFKNWyvLVRJ/ZA6+tVSYGnGhLG+wCHG0oGaEucVhJtriU01xLGcbbXiX1uGwuZtQ4QqDBChK3o21b0Xap1VQM3UV9vgOB00IIj7eh7AMOJcGePbSxS9AHwnBpJae+rvcgufsyJvgMXxo4/cmGvUahosoyOHbFiBZ57DkLgzDPx6adYsABXXIFzz8V336FMhgwZcs8998ybN69z587wxB2Kmq1JoMGz7ceM3/DywVg+SvV1/qYJ2f/4e9vhuqzBU81wYfwb7hD9alQZktxYDdykBm7izk92bLFjLGD2ZlQg7phZjpkl0eZq8CZFv4IQHZVLok0U/VLb+BgumKHnFb0/IMFzikhASXpc8vW1C+8V/DBKtnVn2lvv7Xn0qUGoBOecg3vvxWuvYfRoFBSgZUvccgsGDAClUBToOmQZ/yFJ8PmgKDiR+vXr9+jRY968eU8//bQkSfDEF4oar4EvdWr70Q9snPlT5CBKtbFwx70bpj+aPiJJCcBTfQgzC+wA3CA60S9F1SPRJlpwpBYcydk+21hgR+dxZycqDHe2xwrvN4ufUgPXq4GbiJSESqQljLGNhQDHiXBnh20sUPQB8JQHWfuTVOcTu+g+FluGP0Kk1FvH/dy1a9czzzwTlaNJE0yejMmT8X8MH45fa98es2fDncGDB48cOfLrr7/u1q0bPPGFwgOkqknPnDtqYvY/thbvQam2h3Lv/uHFKRm31daS4KkujPlwh/guAQmiCpPkM7TgbVrwNu5st41FdvQDzvaiYgh+1Aw9Z4VfUfxXawl3EKkOKoVEm1Ffbye2FC6YoecU/TJAhqc8EClVTZnNjPlW0SSIKH6D7Dlyy5q1t06bNgqViDFmmiYhRNd1lIdBgwaNHj36vffe69atGzzxhcJzXAL1P5ExcvLmOd8XbEep9kZ/vvOH55/IGNlQrw1P1SfCwvwC7hD9alQTEm2uJTTXEsYwa41tfGQbCwUvRAUQImxFXrOjc5XAdVrgViLXRcXTgqOc2FK4wJ1dtrFA0QfCU35k/Uqf2tEqvItba/EL6r9u/uv5APr3749KdODAgXfffTcQCIwcORLloW7dup06dVq6dCk8cYfC8wtd1h5pe8uULW+sOrIRpcqLHb3zhxemZIw4K9AQnqpNxD6FiMENejbU81DNSLLaWVY7+xIfts3P7egHjrkcwkF5EyJqhV+xIm+o/qFawigi1UZFktVzqdbdMbPgghl6TtEvAyg85YfIjbXUd5zwbDs0FXCIfKaSOP6LLwY0bty4adOmqOZ69er12GOPHTx4sEGDBvDEEQrPrygSndD6hue2vbs07zuUqsAqvvuH6Y+kD2+deBY8VZgwPoQ7RL8a1RdRFd8liu8SwYvs2CI7+j6z1qLcCdOKvGZH56qB69Xg7URKRIVRg6McMwsucGe3bXys6FeiTLizjbN8qnWF5/+iNDhC0s63Cu9Rk5+ybLp69eprr70W1V/Pnj0fffTRL7/8csiQIfDEEQrPb8lEuqvlkKCi/3vfVyhV2ImO3zjjwTY3dUhpCU/VxA7AWgtXKNEHoPojUpLqH6r6h3JnuxX9wDY+EOwQypUQUTM8w4q+owVvUwM3gvhQAah2PtXOd8yv4YIZmqbolwMUJ4OzfVZouhWd6099A54SSEo7X51PAHn1l19Go9GePXui+uvatavP51u+fPmQIUPgiSMUnt8hICPOvqKWmjhn1wKUKsasB7Nfub/VX3vUaQdP1SNiHwMcLhCtB6RUxBGJNvcljvcl3uPEvrCi7zixLwGG8iN4Yax4ihl5VQuOUQPXAhTlTUu42zEHwQXu/GRHP1L8g+AOZwes0AtWdB7gAFRW28NTGhnAypUrAfTs2RPVn8/n69Kly1dffQVPfKHwlGBwo96apMzY8W8BgZI5gj2+5Z9j2OA/1+8CTxUjjAVwSR+A+ESpry/19RUszzLm25F/cZaL8iNYXqzoASsyW0u4R9EvRbmS1UyqdXXM1XDBDE9T/AMAilIJnm+FZ5mRVyFMHCcrrQkJwnMiGzZsqF+/flpaGuJChw4dVqxYEQ6Hg8EgPPGCwlOyAWkXBKj+7LZ3mOAoGRd82ra5YTt6VaNe8FQd9iY4OXCDBInWC3GNyPW04G1a8FbHXG1H37JjSyAclBPu7DIKbrOj3X2JD0pKS5QfLeFux7wSLnBnjx39t+K/GiUQvMAKz7Qirwth4FdkNRMeFzZu3JiRkYF40a5dO8755s2bO3fuDE+8oPCUqk+9zIDse3zLGxa3UTIB8cquj4vsyN+a9oenahDGh3CH+PqB+FAjSFTrTrXuPn7YivzLivxL8MMoJ46ZFT58iRr4i5YwjkgpKA+y2pFqXR1zNVwwwy8o+hUgFL8lRMSKvGGFpwsewu/IaiY8JxKJRHbu3Dlw4EDEi4yMDAAbN27s3LkzPPGCwnMi59dOfzT9loc2zTaYiVLNy11mMPP2ZoMICDynGROxxXCH6ANQwxCpjpYwTgveYccWWOHXmL0B5cOxIq/bxodawjg1MAygOGVawj2OeQVc4M4e2/hA8V+DXwgRtaPvmqEXBc9HCajaEZ4T2bRpE+c8PT0d8aJVq1aqqm7cuBGeOELhcaFdcrOn2t0+IfsfxXYEpVpwICvsGHe3HEqJDM/pI8yV4EfghtwQakfUTERR9CsV/UpmrbMir9nGYsDBKRO8MFb0kB2d60t6TFY74NTIageqdXfMLLhghqYp+pUgCoRtGe+ZoWcFO4SSSbQJkevCcyJbt24F0KZNG8QLVVWbN2/+448/whNHKDzuNE9o/Ey7UQ9kzzhiFqFUyw+ti7LYhNY3aJICz+lifAh3iD4AkFCzyWoHXe2gJe63wrOs6NsQJk4Zs3+MHLlS0a/wJU0iUipOgZZwl2NmwQXO9tvReSA+M/QsZ7k4EVntBI8Le/fuBXDmmWcijjRq1Gjnzp3wxBEKj2tnBupPPXf0/RtnHDSOoFTf5m+emP2PyW1v9ss+eCqfCAtzOdwhvgHwHCfJab6kyVrCKCv8ihV5XQgDp0rYxnzHXKYljFMDNwASykRWO8hKBrM3wgWjeBKEA3eo2hEeF/bv3+/z+WrVqoU4csYZZ3z11VfwxBEKz8mo70t99tzRD2ycsTtyEKXaWLjj3g0vPZZ+a5IShKdyidinEAbcUNJBm8LzK0SqrSWOV4PDrfBsK/KGEGGcGsGLYkUP28bHvqQpstIKJ0/wI9zZC5eEA9dkNRMeF/bv35+WlkYIQRxJS0uLRqMFBQUpKSnwxAUKz0mqpSY+c+6oidmzthT/hFLlhHLv+uHFKRm31dGS4alEwvgI7hB9IDx/hEi1tcT71eAIKzzDjLwGEcOpYdb6yOFLteBwLeFOEA0ngRsFo4QoRHkjUqpEmyJOCZZH5HooJ/v27UtLS8PpwDl3HIdzjvKWlpYGYP/+/SkpKfDEBQrPyQtS/xMZIydvnrO+YBtKlRvNu/OHF6Zk3HaGXgeuOYJtLd7TNqkpPGXADsBaA1dk4usHT8mIlKwljlcCN1ih563oPMDBKXHM8Aw79okv6QmqdYU7ZmiqY65CBZDVTIAgTjHjPcf4mOpXyv5riJSCU5OXl9eiRQtULiFEJBLZuXPn3r17W7VqhfLWoEEDAAcPHmzbti08cYHCUyY+Wf172+FPbH0z6/AGlOpQ7OjdP7zwWPqIs4NpcEFAPLXlXxFmPJY+Ap6TJ2ILAA4XiHYBpNrwnIgkN/AlP6Em3GGFplvRdwGOU8Cdn6L5Q1T/EC1pIiFBlMoxV5uhl1ExqJqJ+CXr/e3Qs3boSTs8TdZ6U/9QSesKEJRJJBIJBoOoRJZlHThw4Ntvv12yZIllWc2bN0d5CwaDAKLRKDzxgsJTVopEJ7S6fpo8d8nP36JUBVbo3g3TJ7cd3japKUolIF7Y/t5Xh79XJcXktiYp8JwkYSyAS/oAeFyT5DN8yU8ogetiRY8w6xucEmFF33bML31Jj1NfL5RA8CNGwSiAoWLIaibiF5HPlJR23P4BwmSxxSy2mNCmVL9a9g8mUi2cJMMwdF1HpXAcJz8/f9OmTZ9//vnu3bv79es3YMCA5ORklDdd1wEYhgFPvKDwnAKJSONaXBuk+gf7vkSpwo7xwMaZD7a5sWOtVijZq7sWLj64GoDF7c1Fu85LaQHPSbE3wdkON0gC0XrBc5JkJT1Qe54T+zxWPJk7e3AKODsQPXqDol/qS3qCSEn4v7hRMErww6gYhOiy0gZxTdYv5/YP+IVwdtmhJ+3ws7J2EfUPlbSuAIELjDHbtnVdRwXjnIfD4S1btixfvnzDhg3t27e/7bbbGjdujIrh9/sBRKNReOIFhefUEJBbzh6YrCbM2bUApTK59dCm2fe1+ssFddrjj7y79/N5ucvwi/UF285LaQHPyRCxBXCH+P4M4oOnTKivT1D7kxV9wwxNFTyEU2Abi5j1gy/5Gap1w6+YoamOuQoVRlbbgyiIa7J+mV38GMDwa8JmscUstpjI9WV9IPUPI3JDlMowDAC6rqPCCCFisdju3bu/++67VatW+Xy+MWPGdOrUSZIkVBhd1wEYhgFPvKDwlIfBjXr7ZO3lnA8EBErmCDZly5thx7ikQVf81qIDq17bvRC/sq5g283wnBQuYovhDtEHwHMqCFUDNyn65WbxM1Z0LsBQVpztj+YPVQN/1RLHE+IH4JirzdDLqEiy2gnxjkh1JK0LN1fhjwj2sxOe6YRfkbQu1D9U9vUFKP5ILBYD4PP5UDFs2/7555/Xr1+/bNmywsLCq666qm/fvj6fDxVM13UAhmHAEy8oPOXk8obdg1SfuvVtRzCUjAv+wvb3wo4xuFFv/GLVkY3Td3yA39odPnDUKq6lJsLjjrDWgOXBDbkh1I7wnDIi1fYlP6EEhsYKJzB7A8pOWJF/OuZXevKzEm1iFIwCGCqSrHZEDUB9l1vmKpSGcXOVZa4icj1Zv4L6hxK5EX6LUgrAcRyUGec4eBB79iAahaqiQQM0aQJF4ZwXFxdv2LBhxYoVW7duPf/886+++up69eqhUti2DUBRFHjiBYWn/PSq28Ev+x778XWL2yiZgJiza0HIjt7U9DICsr5g25Qtb3DB8VsC4vuCbb3rZcLjUmwh3CH6AECCp5zISkagzsd2dH6s+BHBj6KsuPNT5MhVRKot+GFULFlWz0MNIOuXoPhBCBMnIlieE57phGdJ2vnUP1T29QUojtN1HYBhGCgbzrFzJ+bMwbZtsCwoCho2xLXXont3x3G2bNny6quvNmrUaNKkSS1btkQlMgwDgK7r8MQLCk+56pLa5rH0Wx/aNDvKYijVvNxlEcfoUz9z8uY5NnfwR9YVbO9dLxMeVxwR+wzuEF9/eMoZUfyDqK+3GXrOivwT4CgjLvghVDBZaU1IEDUBCcran1hsCUynUt8AACAASURBVNzi3FxlmauIVEf2D6L6tYSeqWmaJEmGYaAMhIBp4oUXsHUrJk9GejpyczFrFh59FHPmkPr1U1NTr7/++gsuuIBSisoVjUYB+P1+eOIFhae8ZSSf82S72ydmzyyyIyjVooOrl+R943COEqwv2CogCAg8JyLMLPACuKG0Aj0HngpApGRf0mRFv9QofIA721FVyWomagxZv5zFluAkCX7YCc90wjMlJV32D6mVohuGgbI5cADz5uHtt9G1K45p1Qp33IEbb8SnnyrDhzc/DqeDYRgAdF2HJ15QeCpA84RGz5w7evzGGUfMQpTK4RwlK7BCu8MHmgbT4Dmh2EK4Q3yXwVORZLVTsM4nZni6GZ4OYaPqkdVM1Biy1puQBCFCKBNuZ/Oi7E2ra2/4cQO3t0hKK5wUzrF1KxwHXbviPwhBUhLatkV2Nk4rwzAA6LoOT7yg8FSMxv56z547evzGGfuNwzgFawu2Ng2mwVM6YYrYF3CFEN8l8FQ0omgJ4xT9UqPwXmatRxVD1UzUHESTfH2Y8W+cgsQE0qPzz+aRSyS1A/VfK/suAfHDJdMEpVAU/C9CoGmIxXBaHT58GEBqaio88YLCU2Hq+Wo9c+6oBzbO2B05iLJaX7BtcKPe8JRKmMsgwnBDbQ85DZ5KIdHmgdrzrei7ZtEjQkRQNUj0TCLXRU0i65cz498oD9xaZ1nrQCZTvb/sHyIp6SgdIWjUCI6DnTvRogWOEQKGgT17kJmJ02r//v0A0tLS4IkXFJ6KVEtNfObc0ZOyZ/1YvBtlsrlot8ktTVLhKUVsIdwhvv7wVCpJ9Q+lWo9Y4b2OuQpVgKx2Qg0ja92JVFvwIygvIuxE33Gi7xDajOpXyv5riZSMP0QImjdHRgbmzMHo0ahTB8XF+OorHDyICy/EabV//35ZluvXrw9PvKDwVLAg1adk3PbIj6+uPboVJ8/idnbhzo61WsFTEhEW5kq4IhPfxfBUOklu5E9924q+YxY9IkQEpxVVO6LGobKvnxN9E+VNODl26EnHeM9XZykg4fcIQSCAO+/Eyy9jzhyccQaOHsWaNRgwAJ064bTat29f/fr1KaXwxAsKT8XzyerktsOnbHkj6/AGnLz1Bds61moFTwlEbAmECReIdj6k2vCcHkT1D6Vaj1jh3Y75NU4fWe2EmkfWL3eib6JiKMExgISSUIp+/RAM4tNPkZWFxERceSX694ei4LQ6cOBAw4YN4YkjFJ5KIRNJl1WUybqCbfCUIrYILvkug+e0kuRG/tR3reg7ZtFkIQxUOiKlSrQpah5J7UDkMwTbh/ImqefJen+UjlL07ImePVGVbN++vXfv3vDEEQpPpXgp54OlP69BmeyJ/HzELKqtJcHze/yoML+GG0QlWh94Tj+i+odStVP06N+4sxuVS1Y7AgQ1EZH1vk74VZQzoiQ+CBC4YFnWhg0bMjMzUQXs37//yJEj7dq1gyeOUHgq3uu7Fy04kIWyEhDrC7b1rd8Jnt8RsU8ABheIdiGkRHiqBkISBC9GpaNqJmoaYTIzi8UWMWMxypusXykp7eBOKBR68skn33//fVQBGzZsAJCRkQFPHKGoRIcOHcrLyysoKLAsyzCMWCwGwOfz6bquKEqtWrXq1q1br149xJcP9i1/Z+9SnJr1BVv71u8Ez++I2AK45LsM1cKaNXj5ZSxdCttGp0646y507QpVRVzhRuFYwfNR6WQ1EzUF49b3zJjvGAsgwqgIxK8k3APXbNv+5ptvUDVs2LABQLt27eCJIxQV4+jRo99///2PP/64efPmLVu27N69Oy8vz7IsnIiqqvXq1TvrrLNatWrVtm3b1q1bt2/fPiUlBdXTkp+/fWXnxzhl6wu2CwgCAs+vsYOwvocbRCfan1D1rVyJxx/HOedg8WIEAnj1VUyYgIkT0bcvZBnxwgxNdcxVqHSE6LLSFvGO29nMmM+MhYIfQUVSgrcRuR6qp+zs7JSUlDPOOAOeOEJRfo4ePbp06dKVK1euWLFi8+bNnHOcPMuyco9bsWIFjpMkqU2bNhdeeGGPHj369OlTq1YtVBNZhzdM2z5XQOCUFdnhHaF9zRIawfMrIrYQEHCB+PqC6KjibBvvv49GjTBqFJo3xzEPPoi8PHzyCVq0QNOmiAuOudoMvYzyRwCBUslqexAFcYo725mxmBkfCrYHFY/IDWjgb6i2srKyOnXqBE98oThle/fu/fDDDz/66KMVK1Y4joPyxjnPPm769OmU0gsvvHDgcWeccQaqsO8Ltj+x9U0uOMrJ+oJtzRIawfMrIrYQLvkuQ9W3Zw/27EGvXjjrLPyHpqFzZ3z5JfLy0LQpqj/B8oyC2wGG8iZrF1CltRWdJ3g+SiCrnRB3BDvAYkuYMZ/bm1CJlMSJIDqqp5ycnNzc3DvuuAOe+EJRVoyx5cuXz5o1a/78+YwxVArHcZYdN2bMmF69et1yyy0DBw5UFAVVzNbiPZM3z7G5g/KzrmDbNY37wPO/nJ9gb4EbUjLRuqHqi0TAOYJBUIr/lZwM24ZlIR5wo3Cs4PmoANzZoqW+qSXcZceW2tG3HHMVIPBbstoR8ULwAhb7lBnzubUOEKhcktpJ9l2CauuLL74A0PLC8+5YN/PeVoMa++vAExcoTl5xcfFLL7304osvHjx4EKcJ5/zz4xo2bDhmzJiRI0cGg0FUDcV25OltbxnMRLnaXLQrxiyfrMJznIgtgjvE92eAouoLBiFJCIVg21BVHCMECgqgKNA0VH9maKpjrkLFEOwQZ/slOU3RL1X0S7mz047Os6LvCl6A/5JlpT2qOSFCPLaUGYuYuQJwUEYCICg7SUmciOps+fLlybVSPsTm7QX7b/xm2k1NLxpy5gUSkeCp5ihORmFh4fPHFRQUoGo4cODAfffd99RTT40dO3b06NGJiYk43RKVwJzMB/KtopzQvpxQbk44d3sot8AqxqlxBNtYuKNTamt4jhOxT+AO8V2GaqFRI5x1FrKzsWMHWrbEMdEovv0WdeqgXj1Uc465wgy9hIrErHWSnobjJHq2ljheS7jTjn1uR99yzCxZaUWkBFRTwmRmFostYrFPIQycKoJTcDC/S9MG6ai2GGPLly/vOG7g9tB+ACa3Z+xYnHV48/g2gxv768BTnVG4I4R4880377333ry8PFQ9+fn5kyZNmjZt2qRJk0aNGiVJEk63VDUpNTWpS2obHHfELMwJ5eaE9+WEc3NC+wqsYpy8dQVbO6W2hucYZzec7XBDqgu1A6oFVcWgQXjiCcyYgRtugN+PN95ATg7Gj0fjxqjOBD9iFIwDOCoSs9Yp+uX4NaIp+qWKfimzNwuWi+qHcet7Zsx3jAUQYVQBoTB/4RVMex5lEAgEbr/9dpxuX375ZSQorC51AIFfZBftufGbaTc1vWjImRdIRIKneqJwITs7+9Zbb/36669RteXn548dO3bevHkzZ85MT09HVVJbS66tJZ9fOx3H5VtFOaF9OaHcnHBuTij3qFUMF9YXbIPnOBH7BO4Q/RJARnXRvTsefhj/+AeuvhqWhcxMPPIIunSBLKMa40bBKMEPo4Ixaz1KICttoLRB9cHtbGbMZ8YiwQ+jKln4eaN/vrH4yadMTdNwkhISEsaPH4/T7d15c5vd3Y9B4LdMbs/YsTjr8ObxbQY39teBpxqiKJUQ4pVXXhk3blw0GkU1sXr16szMzMmTJ99zzz2SJKFKSlWTUlOTuqS2wXH5VlFOaF9OKHdv9OefIj/vjf6MP7I3mnfILKirpaDGE7HFcIf4LkH10rEjOnZEHDFDUx1zFSoeczYLYRCio9ri9lYW+5gZHwu2H1UPkc9MSB1eWPiXzz77rH///nBHCGEZVvbn2U3ObVK7cW0hRLQoum31trPOPSulYQoql+M4WeSn1GbnogTZRXtu/GbaTU0vGnLmBRKR4KlWKEp25MiRYcOGffrpp6huTNO8//77V6xY8cYbb6SmpqLKS1WTUlOTuqS2wXFhJ/pT5OeccG5OaF9OKHdv9Gf8Yn3Btj/X74IaztkNZzvckBtAaYdqJRKJSJLk8/lisRgAVVVlWUa15ZgrzNBLqBzC4fYmWc1E9SOc8MvM+Jg721GFKYkPXHJpN7/fP2/evP79+8M1wUXe7rxDuw9ddOtFAmL76u3bV29vcm4TVLq3l31Ya2A6SmVye8aOxVmHN49vM7ixvw481QdFCXbt2nXJJZds27YN1dbixYs7d+78ySefNGvWDNVKkPrbJjVtm9QUxxVYxTmhfTnh3JxQ7k+Rg9i/H198gbVrEYvhzDPRty8yMqCqqCBr1mDRIuzbB58P7dvjmmsQDOK0ErFFcIf4/gwQVCuTJ09u2rTpsGHDZs2aJYS45ppr0tLSUD0JlmcUjAE4yhdRCEkiUhKRkghJJFISkZIISSRHTPLmAqx9FYSgdWsMGICGDSHLqAj5+fjqK6xahVAIDRuiZ0906QJNw8qV2L4dF12Exo1xzJ49+OwztG6Nbt1QGsJiy7izHZWCyGmy1tMx5kNE4ZqkdZN9fQPAwIEDP/jgg2nTpqWmpsIFQojqVztc2uGzGZ9tW7UtJS3lxxU/tu/XvlbDWqh0b+z6gjQLwoXsoj03fTvt1rP7DWrUTSIEnuqA4o98883/Yw9O4KKuE//xv96fz2duZgYYhuG+h2tUUBE8UfHI+0IxM03M1PLatq3WTvtW1m7Z2m6XR6VZW5qaqXnkLah4H8gRhwoCMsIgMBxzfT6fPz/6sw9dUwc5xHWez7QxY8aUlZWhDbi5uSkUCkKIs7MzgMrKSp7nq6qqDAYDWlt+fn6/fv22bdvWo0cPPLRchIpYVWSsKhINCgqwdi1yc9GpE6RS5ORgxQpMmYIBA0BRaHUpKfjgA+h06NkTdXXYuRPZ2Vi6FAIBHhzetAv2IeLhcHhguPrKP/GcAfYgIkIpCVESSkkoJSFKQikJ5UwoJYiYQEQoJaGUhFISoiS0O0DwX86fx2efQSRCp07geZw6hZwcvPgifHxACFpXWRk2bsThw4iKQmgorlzBmjUwGDB2LPLycOwYYmLg54cGN27g6FGIxejTB3dFS8Zw1rNoS4RyocXDaMkEStgdIDxfx9Zvhr1ogeJ1NJo/f/6///3v1atXv/zyy7APRVFufm6dB3c++fNJlZ9K5aPSxmnR7goLCw//+ctx7z93vZPYxrO4FxNr/Thn6379+cW6JD+pGg4dHoPbnDx5cujQoUajES3m7OwcFxfXuXPnyMjI8PBwHx8fjUYjFArxRywWi16vv3r1anZ2dmZmZnp6+okTJyorK9Eyer1+8ODB+/fv7969Ox52LIvUVJw9i7FjMXw4JBJcuoRPPsHOnQgOhr8/WpfVig8/hLc3kpPh7w+TCeHhmDMHQ4diyBA8KLbLsOXAHrQnBFFweEAsNas421Va0JlQSkIpCHEGpSSUghAloRSEUhKiJJSCUEpClCAMWsJmw/ffw2zG1Kno1g08j65d8cor2LsXkybByQmtiOOQlYVduzB4MCZPhlyOoiKsWYPt26HT4X7RktHW6ncAFq2NUApKNIgWj6TF/QEGTWjJGLZ+M+zDSKdQTBga9erVq0ePHp999tkLL7zAMAzsQwvo4JjgYxuOFZwrSHorSSAWoN19+umnVpPljUFPi/1VSzM35BiLYYf0qoLktOUzg4ZM8Y+nCAWHDozBrTIzM0eMGGE0GnG/hELhgAEDRo0a1b9//06dOlEUBfsIhULfRr1790YjjuPS09MPHTq0ffv2gwcPWq1W3Jfq6urhw4enpKSEhYWhDfy74NdOyqAuziFoa5WVOH8erq4YOhQqFRpERiI2FgcO4NIl+PujdV26hLQ0/PwzgoNB0xCJkJAAnQ5bt2LIEDwgvOkX2KeQjfIHCBwegCu1105Xho3zPkwTCu3g2jWcOoUpU9C9O2QyNOjZE1FROHYMw4bByQmtqLYWFy/CYsG4cXB3R4PgYPTqhe++w8WLuF+EUlGiXpw5Fa2FiGhhH1oykhYPB5HgNrSoD6HceK4c90IoJSP/M24yb968GTNmbN26dcKECbAPz/GGIgPN0GK5uEpfpQnWoH3V19d/+eWXQ4YM6dSpE4CVsfPXF6Ssyt9t41nci5mzfp63I7UsY7EuyU+qhkNHxeAmer3+scceKy8vR/MRQuLj459++unRo0c7OzujNVAUFdVo4cKFlZWVW7duXb16dUpKCpqvrKxs6NChp06dUqvVaG1X6/Rrr+yIV0fP0050Fjih7VRXo7ISbm5QqfA7ioKnJxpUVqLVFRWB4xASAorC7xgGOh0uXMCDw5t2wT7LC6vp0n8t0E4KkHnCoX2ZOevK/C17Sk8sDJ0UqQhEW7t+HSYTfHwgkeB3NI2QEOzfD4sFrau+HmVlkMvh5YXfURTc3CCVoqwMIhHOn8eSJXB1RYOKChQWIiEBdmDEYyzmVLQUTQm70pIJjGQ0iBPuhqHFI2x13+BeGKdFhHLBTR5//PGXX375vffeGz9+PCEE98LzfG1l7eltp7U9tU6uTmd2nNGEaJTuSrSjFStWGAyGBQsWoBFD6KkBA+JUYUszN+QYi2GH9KqC5LTlM4OGTPGPpwgFh46HQROO45566qmioiI0k0gkSk5OXrRoUXh4ONqMs7Pz9EZZWVnLly9fs2aNxWJBcxQWFs6YMWP79u2EELSBw2Xnztz47cmAYeO84wkI2gJNg6Jgs4HjQNP4nc2GBjQNwGazEUJomkbLGI1GmUxGCYXgONhsuJnJBKEQD4rtMmw5sIOZuGXXO/P1l547/cFor74zAkdKaBEc2tfl2pI/n/1ngiZmTvA4pUCGtiMQgOdhs4Hn8R9mMxgGhACwWq0MwxBC0HIUBYaBzQaWBU3jdywLjgPDoIGrK6Kj4euLBlevwmiEfWjJcFS/Ad6E+0IJOtOS8bRkNKHcYB9aMtpW9w3uijDBjGwabiUSiV555ZVFixZt3rw5MTER98La2IyDGTaLLWZMDM/xJb+VnNt5rt+T/SiaQruoqal5//33Y2JiRo0ahZuEyD1Xxs5fX5CyKn+3jWdxL2bO+nnejtSyjMW6JD+pGg4dDIMmy5Yt2717N+7qmWeeiYmJQRNCSERERNeuXWUyGdpLRETEihUrli1bdu7cuaysLJ7n0eTMmTMrVqzAne3YsWPZsmV/+ctf0DZqbPVf5P2UUnZugTYpUOaJVufqCk9P5OXhyhVotWhgsyEvD4TA3R3Axo0bzWbzsGHDNBoN7ktlZeXmzZvd3d0HDx4s1mohkeDYMYweDYZBA7MZKSkYNw4PCG/aDvtUkN48bABYnttSfDi1/Pyc4PHx6mg4tC8e/D79yROGjJlBo4Z79iIgaAs+PnBxQUYGevaESoUGFgvOnIG/PyQSAG+99daAAQPi4+OFQiFayMkJfn7Yvx9ZWYiKQgOWxdWrMBrh64uSEnh5YdgwdO6MBunpyM+HnYgTLRrAmnahOQijpcUjGOl4QvujmShhd0L78uxV3JlA8RrA4DZz5879+OOPX3nllbFjxzIMgzvjOK40tzTrcFb8k/EKtYK1slFDo46uP1qYXhgQHYB28dFHH+n1+u+++44QglsxhJ4aMCBOFbY0c0OOsRh2SK8qSE5bPjNoyBT/eIpQcOgwGDTKzc197bXXcC+DBw9OSkpCB+Dk5NS3EW6ycePGFStW4K5effXVcePGhYSEoM1kVF2ed/qD0V59ZwSOlNAitCKpFD17IiMD336L6dPh7IyUFBw+jLg4hIUBcHNz27Jly5kzZ0aPHt2zZ08nJyfYzWKxHDx48McffxSJRLNmzWIYBmo1nngCH38MhQKxsaiuxurVqK3F5Ml4QHjTLtingvQGDqNJubnq3cw1e1W6eSGJGrErHNqX0Vb3cc6GffpTC7VJ/jIPtDpnZ4wYge3b4eGBxx4Dz2PTJly5ghkzoFAA8Pf3X7NmzYEDB6ZPn67VaimKQjPxPG82m41Go9rNDZ07w9MTK1di3jx4euLMGWzfDj8/dO2KkhLQNMRiSKVoIBKBpmE3WjKGNe2CHQjtRYuH0pKJlECH+0doyShbzee4A0rUhxYNwB8RCoWvv/56cnLyunXrkpOTcSueq+JMv7Km7QLn5QTOErkkZnSMf7Q/AFpAe0d49xjbQyKXoF0YDIZly5YNaoQ7CJF7roydv74gZVX+bhvP4l7MnPXzvB2pZRmLdUl+UjUcOgYGjV588UWLxYJHgMVi+etf/7px40a0JZbnthQfTi0/Pzd4Qj91FFoLRSEuDrW12LULL74InodAgJ49MWEClEoAcXFxKpXq2LFj33///eHDhxMTEyMjIwUCAe7l4sWLa9euLSsri2sUERFB0zQIwbx5EImwYgX+9S8QAqkUf/87QkLwQNguwZYLe9CeRhICHMatjhsyzt3IneSbMMV/CENoOLSvi1WXnjv9wSivPjMCR0poEVoRRWHCBLAs9uzBTz+hgViMOXMQGwuhEMCECRO0Wm1qaurrr7/et2/fqVOnurq6EkJgn/r6+lOnTu3atSsyMvKJJ54gWi2Sk7F5M15/HSwLgQAREUhMhJsbWoYWJRAi53kj7oBQLrR4GC2ZQAm7AwQtRovH2Go+xx+jBYo3cGfTpk378MMPFy9ePHbsWFdXVzTgTaz5CFu/mTXvAW8FwNiyKWEvla9K5atCE6FEGNo7FO3lpZdeqqmpWbp0Ke6KIfTUgAFxqrClmRtyjMWwQ3pVQXLa8plBQ6b4x1OEgsODxgA4dOjQzz//jEfGpk2bUlNT+/btizZWbq56J/PrOJVufkiiu9gVrcLZGUOGICQEpaWw2aBQICgIGk1NXd3OnTtFIlG/fv18fX11Ol1KSsqyZcu6du2amJjo4+NDURT+SFFR0Q8//JCenh4RETFy5MioqCiJRLJz506r1Tp69Gixvz+efRZ5eaiuBsPAwwORkaBpPAi86RfYh4iHw0zwR8yc5duCXQfLzizQTop21sKhfdl4dkvx4TRDxjxtYqxrJFqRhwcefxyxsaioQAM3N4SFwcmp4saNL7/8MiEhoXfv3sHBwWfPnt2/f/9zzz03ceLEcePGCQQC3JXNZrt8+fKPP/6YmZnZoxEayGTo3Rve3rh6FRYLnJwQEABvb1AUBg1C164ICMDvAgOxcCHc3GAnIqLEQ9n6TbgVIXJKPJgWj6TF/QEGrYcShFNMKGfLwW0Y2XSKCcWd0TS9evXqPn36vPrKC58sf5I1/cKadoOvw004axYl7IUH59ChQ19//fXcuXNjY2NhhxC558rY+esLUlbl77bxLO7FzFk/z9uRWpaxWJfkJ1XD4YFiALz//vuwj0wmw3+5eBE7dyI7G4SgUydMmABvb9A02kJtLQ4exN69qKiAmxvi4zF0KCQSNJFKpbDP+++/v337drSL44aMczdyJ/kmTPEfwhAaLSeXo0sXdOmCmwiFQplMtnnz5kOHDiUlJfXo0SMwMPDcuXOpqalZWVlqtVoikeA2PM9v3brVYDBMnDixe/fu7u7u586d+/rrr+vr66dOnUpRFBp4ecHLCx0Ab9oF+xDxcJhxF0V11/96/rMETcyc4LFKgRMc2lepyfB6+so4lW6+dqK7yAWtRa2GWo1bSSQSqVT63nvvde/e/amnnho2bJhWqz1x4sS2bdv27Nkze/bsmJgY/BGe5w0Gw08//bR3716tVjtz5kydTufu7k4IQQOJBOHhCA/Hf/Hzg58f/kOpRNeuaA5aMoat34TfEREt7ENLRtLi4SAStA1aMoYzfohbEcqZcVqAu+MtPaJrD+7oGRa033LjIP4IZ83Cg2M2m+fOnevh4bF06VLYjSH01IABcaqwpZkbcozFsEN6VUFy2vKZQUOm+MdThILDA8IUFRXt2bMHdnB3d4+Pj8fNzpzBJ59AoUBcHHgeaWnIzcVLL8HPD4SgdRmN2LoVGzagZ0906YJr17B+PYqKMGcOGAaN4uPjPTw8SktLcS+7du0qLCz08/NDuzBzlm8Ldh01pC/UTopQBKANCASC3r17q1Sqo0ePfvbZZ6GhoUlJSYMHDw4PD1coFAKBAEBmZua2bdvOnTvHsmxAQMDo0aO7d++ekJDAMIyvr++1a9fee++97Ozs7t279+7dW6fTCQQCdBy2S7Dlwh60JwRdgIu4Kx78Pv3JUxWZs4LGDPGIJSBwaF/HDRkXKvOmBwwf6x1PEwptQywWJyYmhoaGHj58eOHChSNGjJg8ebKfn59Opzty5MjSpUt1Ot3s2bN9fX1xE5PJdPDgwe+//97JyWny5MnR0dH+/v40TaPt0aI+hNYQ2peWTGAko0Gc0MZoyTircRnA4yaM/M+EcsEfYzlzmq1+E2vaA74mpgsACnfA27Lw4Lz66qvZ2dmbN292dnZGM4XIPVfGzl9fkLIqf7eNZ3EvZs76ed6O1LKMxbokP6kaDg8C8+WXX7Isi3sRCoU7duyQy+X4D5sN69aBEEyejC5dwPOIjsZLL2HPHkyeDLkcrYjnUVyMtWuRkIAZM+DiAoMBP/+MrVsRG4sePdDIyclpy5Yt/fr1s1qtuCuWZdeuXfv666+jHV2qKX7+7McJmpg5weOUAhlaFSHE2dm5R48eAQEBkZGRhw4dWrp0af/+/UeMGOHu7g7g9OnTH3/8sVwuHzRokEql0uv1hw8fDgwMDAsLq6mpWb9+/c6dO/38/GbMmBEVFeXm5kZRFDoS3rQD9iHiYQCBfaqstct++3536fEF2kkBMk84tK961rwif8uvpScWhSZFKALQBgghHh4earU6JCTkxIkT+/btO3z48PTp0wcMGBAYGNilS5c9e/bMmzdvzJgxTzzxhFQqtdlsFy9eXLNmzY0bN/r37x8XFxccHCwWi9F+aLH6EIgI7YXQ3pSwK2c5gyaE0TLSKfhvLGc5y5p+Yeu38lwF7MPZcsBbQQRorflOJwAAIABJREFUdz/99NNHH300ZcqU8ePH474whJ4aMCBOFbY0c0OOsRh2SK8qSE5bPjNoyBT/eIpQcGhfzKZNm2CHpUuXdu/eHTcrKsLp05g1C1FRkErRICYGXbvi+HGMGAG5HK3IbEZWFq5dw+OPw8MDDTw90bs3DhxAWhp69ECTuLi4d9555+WXX8a9bN68+fXXX0f74sHv0588YciYGTRquGcvAoJWRVGURqMZOHBgaGjoyZMn9+3b5+zsPHToUIFA8O233zIMM2XKlKioKJFIZDQaDQaDq6srIWTFihUFBQWJiYldu3b18/NjGIYQgg6GN+2CfYh4BJrpYtWl505/MNqr74zAkRJahAfNZrPV19fbbDaapvEIuFxb8vzZjxM0MXOCxykFMrQBmqYDAwM9PDx0Ol1KSsqnn366a9euuXPn9u/fPzAw8MSJE7/++uuhQ4fmzJlz4sSJQ4cOxcbGTp06NTQ0VKlUov0REdoXLR7DWc6giUDxGsDg/8dxljOs6Re2fjvPlaO5eCvHXqKYMLSv3Nzc5OTk0NDQL774Ai0TIvdcGTt/fUHKqvzdNp7FvZg56+d5O1LLMhbrkvykaji0IyYjIwP3EhkZuWjRIvyX69dhscDbGxIJfkfTCA7Gvn2wWNC6rFZcuwaJBD4++B0hkMuhVqOkBLd6/vnnv/766+zsbNxVenp6VVWVUqlEuzPa6j7O2bBff3ph6CQ/qQdam1AoDAwMVKvVERERIpGIEFJcXHzhwoUpU6Z07dpVJpMBUKlUrq6uaNSnT5/HHnssODhYIpEQQtABsVdgy4E9aE8IuqD5WJ7bUnw4tfz83OAJ/dRReEA4jhMIBJcvX05LSzOZTB4eHjRN4xHAg9+nP3nCkDEzaNRwz14EBG1AIpF06tTJ29s7Ojp63759CxYsGDJkyIwZM0aPHh0cHPzBBx+88cYbcXFx8+fP1+l0np6ehBA8GmjJKGv12wALgBYPpkXxADhrOlu/ma3fwXPX0QK8NQtMGNqR0WhMTEzkOG7Lli0KhQItxhB6asCAOFXY0swNOcZi2CG9qiA5bfnMoCFT/OMpQsGhXTAcx+Fe3nzzTYZh8F+EQvA8rFZwHGgav6uvh0AAQgBYrVaGYQghaAGWZWtraxU0DaEQVitsNjAMfseysFggFOJWAoHgtddee/LJJ3GbPmunyfxd0STp3Jt4cNKr8p87/WGS76DH/QYLKQFam5OTU6dOnViWpSjKYDBYLBYvLy+JRIImhBA06t69O8MwFEWhzZg56xPH3sT9GueSPdUV9thqkK/LeRWAjWfRfOXmqncyv+7t1vnZkAnuIhe0r9ra2oKCAgAXLlxwc3OLiYkJCAhQKpVoDTNPvFtlrUV74XgOzWe01X2cs+Hg9bMLtBN9pRq0DRcXl549e/r7+3fv3v2XX3556qmnZsyYER4eLpFI5s6d26NHD19fX4Zh8CghlIoS9ebMKSACWjLeWv0Oa/qFZ0vRGjhrJi0Zh/ZiMpnGjh2bkZGxYcOG8PBwtJ4QuefK2PnrC1JW5e+28SzuxcxZP8/bkVqWsViX5CdVw6HtMbgXV1fXcePG4Xb+/nBxwfnz6NEDKhUaWCw4eRIBAZBIALz66qv9+/cfNGiQWCxG87Ese/Xq1S1btkRHRw/o2xdaLaxWnDqFvn3RgONQVoYrV5CQgNskJiYuWLDgxo0b6NisnO27gt37r5+eHzIxxjUcrY0QwjAMAKFQyPO82WzmeR63EQqFaHN8ja0O9ytGWgT7HKx2q7HVoWWOlqefrvhtkm/CFP8hDKHR9sxmc2lp6enTp3ft2sVx3EsvvdSnTx+pVIrWU2urr7HV4WFwvjJ37qm/j/Lqkxw4SkwL0QYIIV5eXmq1Ojg4+OjRoz/88IOnp+eLL74YEBAglUrxSKJFsZw5BURiuTEPrYqzZaG9sCz75JNPHjhw4KOPPkpMTERrYwg9NWBAnCpsaeaGHGMx7JBeVZCctnxm0JAp/vEUodB8PxUdG+/TCw52YHAv/fv3FwqFuJ1SifHjsXEjVCqMGgWOw7//jatXMXcunJ0BREdHf/PNN7/++uvTTz8dGRnJMAzsw/N8dXX1jz/+uH379q5du4aFhYGmERyMvn2xbBmEQoSGIisLq1fDzQ0DB+I2YrE4Pj7+559/xsPgWn35q+lfxKl0C7WT3ETOaAN+fn5ubm4XLlzo3bu3RqNBI57nARBC0LG5MaZQcSXsUG4TZ9c7ozWYOcu3BbuOlJ9foE3SKQPRZliWLS8vP3/+/K+//qrX64c1UqlUeLTZeHZL8eHjhox52ok9XCPQNgQCgVar9fT0jI6OrqmpiYyMxKOHs+Ww9TtY0zbedgkNuGq0Nt6aiXZhtVqnT5++adOmd9999/nnn0ebCZF7roydv74gZVX+bhvP4l7MnPXzvB2pZRmLdUl+UjWa45eSUx9lb4lyDgxy8oDDvTC4ly5duuAPURQSE0EI9u/HDz+ggZsb/vxnxMRAIAAwcuTIsLCwAwcOvPbaaz179kxOTtZoNBRF4a6sVuvBgwdXr16tUCiefvrpqKgojUYDQqDR4LnnsG4dliyByQSJBJGRmDIF7u74I1FRUT///DMeHscNGbOr8qcFDB/r1Y8iFFqVXC4fN27cd999p1AoxowZo1arc3NzT506NXr0aC8vL3RsfeWlBHZJNXrwaE2Xa6+9cO6fCZqYOcFjlQIntCqe5ysrK3Nzc1NTU8+cORMRETF37tzg4GBCCBwaXTMZXktfEafSzddOdBe5oA0QQuRyeVRUlNVqxaOEZ4tY0x62fjNnvYg2xnMVPHedUO5oS5WVlRMnTty3b99f//rXV155BW2MIfTUgAFxqrClmRtyjMWwQ3pVQXLa8plBQ6b4x1OEgh3KzdWf5G7jwX9XcPB13eNwuBcG96JSqXAnbm5ISkKfPqiuBiFQKuHnB6m03GD49NNPBw8eHBMT4+vr26NHj23bts2aNSsxMXHy5MlSqZQQgtuwLJuZmfn5558bDIaRI0f27NnTz8+vurp6zZo1arV69OjRiIzEn/6E0lKYzRCJ4O4OT09QFP6ISqXCw6bWZvoi76eD18+83Wm2QiBD66EoauzYsTRN79mzZ9u2bTRNazSaQYMGicVidHi95aWwz1GjB1obD36f/uSpiqxXIp+KdtaildTV1RUUFBw9evTw4cMqlWrRokXR0dECgQAOtzluyEivzH8hbEpfdRTaBiFEKBTiEcBzZWzdj6xpO2fNQjvirFm0yB1tpqioaNSoURcvXnz//fdffvlltJcQuefK2PnrC1JW5e+28SzuxcxZP8/bkVqWsViX5CdV417ez9xotNYD2FN6LjlwiI9UBYe7YnAvdXV1uAtnZzg741ZyudzHx2fp0qWdO3eeM2dOr169AgMDz507t2XLlj59+mi1WkIIbsXzvMVi+frrr729vZ999tmAgACGYXbu3Ll27Vp/f/85c+agAcPA2xve3rBDbW0tHkLeEvVTASMUAhlam4uLy9ixY2NjY6uqqgBIpVIPDw+lUomOzZk268Q3YIdKVpRhckEbEFHC0V59OymD0Cy1tSgqgl4Pmw1OTvD1hbs7aNpms127du306dMHDx6sq6ubMGHCwIEDFQoFHO6AIfQorz6xqkg4tBghzgDN2QrRvix1FySi/mgbmzdvnjt3bl1d3aZNm8aOHYv2xRB6asCAOFXY0swNOcZi2CG9qiA5bfnMoCFT/OMpQuEOfik5mWbIRiOO59YXHn4hfDwc7orBvRQWFqKZhELhhAkToqKidu7cOXfu3BEjRsyYMWPo0KE6nc7T05MQAuDgwYPffPNNbm6uVCrt3LnzjBkzIiIinn32WaVS6eLicu7cuc8++6y+vn7q1Kk9evTw8vJCMxUWFuKhIqIEk3wHPe43WEAxaBuKRnio9HK6ThEedjhW487xBK0tTqWbr53oLnJBsxiNSEnB9u0oLgbLQiJBt26YMAFabW1t7d69ew8dOtS7d+/Ro0d7enrC4c66OIcs0E7yk2rg0CqIgHGaQ0vGWY1/Y+u3ADzaxa4dH3uFxMbFxaFVVVVVLVy48JtvvgkPD9+1a1e3bt3wgITIPVfGzl9fkLIqf7eNZ3EvZs76ed6O1LKMxbokP6katyk3V3+Sux032V5y8qnAQW4iBRzujMG9pKamopkIIS4uLt26dfPz8+vZs+fGjRunT5/+9NNPDx8+XCAQANiyZcuSJUuSkpIef/xxqVR68eLFH3/8ccmSJcHBwaWlpW+//XZaWtqIRj4+PlKpFM2XmpqKh0eUs3aBdqKvVAOHW/WRl8I+R4weaFUeYtU8bWKsaySai+dx7hy+/RZeXvjb36BW4+hRrFsHsxkLF1ICQWRkZGxsbEREBEVRcLgDF6FiVtDoQZoYAgKHVkVojdD5I042w1q1hLOeRdsL8rfG9O07e/bsV1991cvLCy1ms9nWrFnz1ltvFRcXL1q06L333pNIJHigGEJPDRgQpwpbmrkhx1gMO6RXFSSnLZ8ZNGSKfzxFKNzk/cyNRms9bmLlbD8Wpj6rHQGHO2NwLxcuXMjIyNDpdGgmiqLc3d379+8fFhaWmpq6atWq4ODgiIgIq9X61ltvjR49evbs2QqFgqIonU5XU1NDCKmvr3/jjTdcXV3ff//9wMBAZ2dnQgiaLz09/eLFi3gYuAoVc0PG91d3hcNtnChrlMwAO9RwgvO1KrQShtCTfBOm+A8RUULch/p6nDgBiwUzZyI8HA2GD0dpKfbvR3q6vH//uLg4ONwZARnl1WdG4EgnRgKHNkMJuojcNtrqNtiMH/BcBdpSaLBg2pOTvvjii6+//nrevHkvvfSSWq3GfbHZbOvXr1+yZEleXp5Op1u7dm1CQgI6jBC558rY+esLUlbl77bxLO7FzFk/z9uRWpaxWJfkJ1Wj0S8lJ9MM2bjNpqKjTwQMUAqkcLgDBnb4+OOPV65cifsiFAr9/PzGjh0bExPj5OQEIDMz87ffftu4caNKpSKEAHBuBEAoFM6ZM8fPz8/NzY2madyv5cuX449c2XBWqBSjyQsvvKBWq9FiB6+fya8pRjMRkOGevWYFjZExYvyvYwizKDQJzeSFIww42KGaip0X+jhukl9TvL3kCJqvkzJooTbJX+aB+3bjBoqK4O6OkBD8jmEQEAChEEVFeEBmB481c1a0F72p4ofCvWi+YCfvBdpJEYoAOLQHipE+TouH22qW22rXASzaCrt65eK/vPjakiVLli1b9o9//GPgwIHTpk2bOHGiVCqFfTIyMtatW7d27drS0tKAgIAVK1Y8/fTTNE2jg2EIPTVgQJwqbGnmhhxjMeyQXlWQnLZ8ZtCQKf7xFZaaT3K344+YWMtPRUdnBA6Gwx0wbm5u5eXluKuvvvpqwYIFnTt3xv2SyWRarZZlWUJIaWmpQCDw9vZGE0IIGtE03bVrV4Zh0ALnzp1bu3Yt/kjxLxfRxN3d/blvJxNC0GKXa0rya4rRHMFO3gu1SeEKfzwaaEKN8OyNZuIrv+VNsIe3y1QfUW/c5Gh5+vaSI2gOOSOdGTRquGcvAoKWYFmwLAQC0DT+QyAAIWBZPCCDND3Qjn4zFv5QuBfNIaaFU/0fm+gzkCIUHNoRoZQCxZuMdJq1+v9Y8yG0Dd6aGRk5ecOGDadPn161atWGDRv27t27cOHCXr169ezZMy4uLiIiQqVSOTk5oZHFYqmoqCgqKjre6NixY3l5eTRNJyQkfPjhh5MnT2YYBh1YiNxzZez89QUpq/J323gW92LmrJ/n7Ugty6Ap2mitxx38WHjkcb94MS2Ewx9hEhISNmzYgLtiWfbJJ588fvy4WCzG/SKEMAwDQC6Xm83muro6kUiEWxFCGIZBC9TX10+bNo1lWdxLQkICIQTtTkwLp/o/NtFnIEUoONwFX8+bj8AeREKEfdACBCRBEzMneJxSIEPLOTnBxQWXL6OsDB4eaMBxuH4dVitcXeHwR+JUugXaSWqRMxyAi1f1aw6f7uSj0floIrzdncRCtD3CBAld17Cmfdbqt3j2KlobZ8ui8f90b/Txxx9v27btp59+Onbs2K5du9BEKBQqlUqTyWQ0GtFEoVDExsbOnj37iSee8Pb2xkOCIfTUgAFxqrClmRtyjMWwQ3pVAe6qylr7c/HxyX794PBHmOTk5A0bNuBeLly4MGfOnLVr16LFOnXqJJfLt2/fPm3aNDTieR4AIQQtNmvWrIsXL8IOM2fORLuLV0fPDRmvEirhcC+8+SD4etiBiAaASHC/gpy8F2onRSgC0FqUSnTujPR07NyJMWMgkaCwEGlpUCoRFgaHW3lK3OaHTIxxDYdDk1OXinad/23X+d/QSK2QRXprdD7ukd6aboFeCokYbYYWD6JFfaw1X9hqV4A3ofVw1izcRCQSTWwEQK/XHz9+/PLlyxWNDAaDTCZTNfLw8OjWrVtERARFUXg4hcg9V8bOX1+Qsip/t41n0WI/FBye4NNbQNFwuA0zdOhQPz+/wsJC3Ms333zz/PPPR0dHo2UUCsVLL720ZMkSgUAwaNAgkUiUmpp68uTJJUuWoGXOnTv373//G3YIDAwcNGgQ2pGnWDVPO7GHawQc7GTaAzuJh+K+iCjhJN+EKf5DGEKjFdE04uKQn4/9+2EwQC5HXh5u3EBiIoKC4NCEIfQorz7JgaPEtBAON0kvKsVNyqprD1VfOpR1CY18XJVdA7x0PppIH/dIb41YwKB1EbFA/idG+rjV+He2/ie0Et6WDfAAwW00Gs2YMWPwv4sh9NSAAd1dQ97NWH+5Vo+WKTNX7bp2erR3LBxuw1AUNXfu3FdeeQV2yMnJiY6ORstQFPXcc8+5uLisWrXq1VdflclknTp1mj17NlosLy8P9nn22WcpikK7YAg9yqtPcuAoMS2Eg514C28+CHsQIRH1R/PFqXTzQxLdxa5oC76+mD4d+/fj+HHU1cHHB+PGISYGNA2HRl2cQxZoJ/pJPeBwm4tX9bizooqqooqqbWeyAFAUCVS7Rnq763w0kT7uOm+NSMCgNRDaQ+j8ESeZYKl4mocFLcZz1TxbQmhvPKrCFT5f9/zT+oKUVfm7bTyLFvj2yoGRXjEUoeBwKwbAokWLPv300+LiYrQXmUz25JNPjh8/3mq1UhQlEAhkMhnai5+f3/z589EuOimDFmqT/GUeeKBsFtvBtQflKnmnhE4yZ5nNbPv1i189tB6R8ZFiJzE6Ht5yBHwN7ECEfUCc0BxuIudng8f3VUehTXl6YupUTJ0Kh1u5COWzgsYM0sQQEDxolnrLD6//0GtSL22cluf5GkPN9n9s75XUKyAqAA/Ijdr64ooq2Ifj+Hy9IV9v2HYmCwBNUQFql0hvd52PJtLHXeejETEMWoCznuNhBghaA2fNomlvPMIYQk8NGBCnCluauSHHWIz7VVxvOHA9fZAmCg63YgBIpdJ33313xowZaEfiRngQ3nnnHYlEgjYmZ6Qzg0YN9+xFQPCg0QI6OCb42I/HXL1dg7oHpe9Lr62s9QjxEEqE6JhMv8JO4qGwG0PoUV59ZgSOlNAitIvi4mKLxRIYGAgHgIAkaGLmBo9TCGToGBgR02Vwl/2r9/tE+jBC5vhPx0UykVeoFx4cipAXR8VnFOkzi68XlN/gediP5bh8vSFfb9h2JguAkKG1Hm4R3u5hnupwL3Wop5tMJITdePaqteZTgKCV8LYsYDAeeSFyz5Wx89cXpKzK323jWdyXdVf2J2i6EBA43IRBo2nTpq1cufLo0aP4X9e3b9+pU6eiLRGQBE3MnOBxSoEMHQMhxFfnezX9anZqNmtlMw9ldhnSxc3PjaIpdEQsb94Pu9BElAD7dFIGLdQm+cs80I6OHDlSXl7+3HPP4ZEX5OS9UDspQhGAjoQQEtEvIjct9/C6w9o4be6x3IlvThRKhHhwlFLxU/Hd0ajWbPntWllm0fWMIn1m8fVL1w08D/tZbGxGkT6jSI8maoUs0luj83GP9NaEeKh8XJW4M2v1W+BNaD2cNQsOjRhCTw0YEKcKW5q5IcdYjObLM15LK/+tl1s4HG7CoBFFUT/88EN0dHRFRQXuLDk5efbs2bgJRVFjxoxZvHhxWFgY2kt2dvby5cs3btxos9lwE6vVirtycXFZt24dRVFoMz4S9YLQpGhnLToYRsh0HdF11ye79q7cG9oz1Lezr0AkQIfEW06CuwE7EGEsKBfci5yRzgwaNdyzFwFB+yoqKiopKcGjTUwLp/o/lugzkCYUOhhCiFAq7P9U/+9f+f7y2csxY2JUPip0GDKRsFuAd7cAbzSqMVlySssyi65nFOkzi69fum7geTRLWXXtoepLh7IuoZFcIgrRqCJ9NDpv9xCNSuvpJqBpNGJNv7KmfWhVnC0TDjcJkXsujZo+9diHZtaK5ltzeW8vt3A43IRBE19f31WrViUmJuLO6urqcJu1a9euW7du2LBhzzzzzKhRoxiGQduwWq3btm1btWrVr7/+ynEcmokQsmbNmoCAALQNESWY5Dtoiv8QhtDokJxcnZQaZUF6gV8XP7mrnBCCjsm0D3YSD8VdEZAETcyc4HFKgQwOD0KcSjdfO9Fd5IIOzMXTxUnlVFlaGREfQdEUOionsbBbgHe3AG80qjGZc0rLM4uuZxTpM4uv5+sNaCZjvfnslZKzV0rQiKEpfzeXSG/3Lr4uIwPfEhC0Lt52FXwtiAwOTT7M+snMWnFfMqoKz924FO0SBIcmDG4yYcKEJY3QTBzH7Wik0WjGjRs3fvz4gQMHCoVCtAaLxbJ///6ffvppy5Yt169fx/169913x4wZg7YRp9LNC0nUiF3RgRVlFpVfLXf1ds0/la8J1rh4uqBD4s37YBeKiIfgzgJlXgtDJ0UqAuHwIHiKVc9pE2NdI9HB8fjt2G/1xnpNsOb09tP9p/fHQ8JJLOoW4N0twBuNyo21GUX6jCJ9RtH1jCJ9ubEWzWRjuXy9IV9v8JUeFQSVoPVxnDWbEnaHQ6NfSk6mGbLRAuuuHIh2CYJDEwa3evPNNysqKv75z3/ivuj1+hWNZDJZz549+/bt26tXr06dOnl7e6M5ioqKMjIyjh07lpKSkpaWVldXh5Z54YUXFi9ejLYxPXCEp1iFjs1cZz617ZSfzi+oe9CBrw9cOXdFqpSKpCJ0NLZssEWwhyAKlDvuoJMy6NPuf6EJBYcHwUfivqLHX0WUAB0bz/M1lTWH1hwaPGuwk8rp57//HNor1FPriYeQm1zWPyKof0QQGumrajKL9dklZdklZdklZcUVVbBPkMrwZPczsJtA/qKtfgtvy4UdOFsWJewOB6DcXP1J7na0zHHDb79VF4UpfODQiMFt/vGPf9TW1n755Zdogdra2n2N0MjFxSU8PNyrkUajkcvlYrFYKpUCqKurM5lMRqNRr9cXFxeXlJRkZ2dXVlai9cyZM+eDDz5Am/EUq9Dhnd99HkBQjyCPYI+oYVEXdl/wCPbw0HoQQtCR8KY9sA8RD8GdKQQyODw4MkaMh8SBrw746HxCeoZwLNdlcJcDXx6Y/M5kmqHxkNMonTRKp4GRwWhUY7LklJbl6yvy9IbMIn1m0XWzzYbbUIR/ZfABAcXBPgfyw7+/oAr1fGFIyIlOqh9oUoe74q1ZcGj0fuZGo7UeLfZtwcG3Oz8Jh0YMbkNR1OrVq7Va7eLFi3meR2u4cePGsWPH0O4IIW+88caSJUvwaLuWcy3vZF7U0Ci1v5qiqfA+4YUXCi/uvyhzlSncFOhIePNe2IeIBsPBoWXyjuddOXtlxvIZjIDhGT56eHTB+YIz28/0GNcD/1ucxMJuAd7dArzRyMZyeXpDdsn17JKy366VZZeUGevNACZ0SY/yKoF9ai2CD/b3LqspOXulZP0xJzenKQv6Hhke8RsBjzvgrFlwAH4pOZVmyEZrOHQ9vbCuzE+qhgPA4A5efvlld3f3Z5991mw24+EkFotXrFgxffp0PPLcg9zHLx4vEAloAQ2AETKDZg0CIBAL0KGwxbBmwx6MFkwAHBxaJrBb4NOfPi1VSAEQQpxcnBLfSKQZGv/rGJoK91KHe6nR5Hp1TW5Jdmf5l7DbqrSeZTVOaFJeI3tz19D156L+MuBQZ89S/BGbNZu3WsQCIR5h181V/8rZilbC8fx3Vw4sjkyCA8DgzpKTk2NjY6dMmZKeno6HTXh4+Pfffx8dHQ0HgGZoiVyCm4hkInQ8vHkvwMMORDQID4MePXpUV1fDoaNihAwjZNCEUEQil+CR5K5wcma/Yk21sE9+uev6c1G4TWapZtb6ScMjflvUL8VFWo9bUaiftOw9nvbXergFa1yD3VWB7q6B7i4ihsEj4++Zm2psJrSe3dfOJgcN8RC74JHH4K50Ol1aWtrzzz+/atUqnufxMCCEzJ49+6OPPpJKpXB4uJj2wT5EPBgPg379+sGhbXA8fyqj8Hh6wdyJfQQCGg4tw5oPsKadsA8P8uGhBBtL4Y9wPPklM/xQfuCM2FNPdDsroDjcJNjt+t4cxZWyG3vS8R9qhSxEo/JxVQZrVMEaVainm8pJiv9Fv5ScTDNko1XZeHZ9QcqisDF45DG4F6lUumLFilmzZs2fP//EiRPo2KKjo//1r3/17dsXDu3u8Ol8H41zkI8K94er4i0nYQ/KHYLO6MA4jtPn6ytLK30ifeQqOcdyJTkltZW1PhE+MmcZHFqmoKRiT9pvO1IyS8qqljw7XCCg4dBCfK216lXYjZFOXP3s+1fKb+TrDfl6Q76+Ik9vuHy9guN5NKkxiz5J6bPtYuRfBh7u6V+AJlq3sr05IbhVWXVtWXUtbqKQiH1UymB31xAPVbC7KsRD5e2iJAQPtXrWsqPklJfE1WirN7EWK8eilWwrOf5U4CBnoQyPNgb26dGjx9GjR1esWPH222+Xlpai4/H09HzjjTeVDep7AAAgAElEQVSeeeYZmqbh0O4yL5W+8ekvFEW9M39k7+hANB9vPgCwsAMRDwEIOjaT0ZR3Is9cZ+6c0LmytDLrcJZIKvKJ8IHD/aquMf16LHtHamZmfikadQ33eax3BBxazGr8kGevwT6EchHI/0ooKkSjCtGo0MRiYwsNlZlF+nx9RZ7ekK83FN+oKrjhsmDz2H5Bl/8y8JCXohpAqLoMdqiuN2UWmTKL9GgiZGhflXOIRhWscQ3WqHxdlSEebkKGxsNDQgs/jXkWNzFzVqO13sLZzJzVaK03WussnM3MWY3WeqOt3sxZLayt2lZntNZbOJuZsxqt9RbOauZsNyw1HM+hiYm1/pi585kaD4SFQa1GA6MReXlgGHTujAbV1cjLQ2EhrFY4OyM0FN7eYBi0nZISZGfDYABFwcMDnTtDLgch2L8fvr4IDATDoMHVq0hPx5AhEAjQYgzsRtP0c889N2vWrDVr1rz99ttFRUXoGHx9fV944YXZs2dLJBI4PAglZVUvfLjFZLEBePEfP/952sDEwVFoLvNe2Ek0CB0bRVGeYZ7lV8uLMooUborywnJLnUU3UCdzlsGhmWwsd+z85V9SMo+cvWS1sWjC0NRfZiQQAocW4qwXbLXrYDeB4g1CueI2QoYO0ahCNCo0qa435ZYa8vWG3NLyv6f07Oy2Z0q3I1p1Oe6Lxcbm6w35egOaCGg6QO0cqHYNdHcN1qgC1S6B7q5iAYOHh4gSiEQC3JcaW309azGxljqbucZmok+cxFf/xKJFUKvR4Pp1/PvfcHJC5864cQN792LvXtTWghDwPEJCkJgInQ4UhbZQUIB165CbC45DA45DQgImToRCgaVLMWECZswAw6DByZP4v/9DfDwEArQYg2YSCoWzZ89+6qmnNmzYsGrVqpSUFDwghJD4+Phnnnlm0qRJQqEQDg9Osb7KZLGiEctyH6zZV2qofjapL0UI7MSbeHMK7EHkRBiHDk8sEwd1D6osrUzblCZTygKiAzSBGjg0x6Uiw84jmb8czqioqsNtkh7rGuzjhuarsdUV1ukjFYFw+H9s1qpXABb2oYS9aMlY2EchEXcP9O4e6I3/3xMV1ZcFVX97c1z3zGuWS9cr8vWGyjoT7peVZXNLDbmlBjQhBJ7OCn83lwC1c6C7a4Cbi7/axdNZThGC/zlOjMSJkeA/+Fz8IY7DqVPYuBE6HZ58Ei4uOHUKa9bgxx+h0cDdHa2OZfHNNzhxArNmoV8/WK34+WesXAk/P/Tvj7bE4L6IRKJpjbKysr766qtNmzZdvnwZ7SUoKGjixIkzZ84MCwuDQwfQo5Pf6jenvPDhT6UGIxqt23byamnlkmeHi4UM7MBbjoCvhx2IqD+IAA8DF08XN1+3jAMZQd2DAroG0AIaDnYor6zdfSRrR0pmflE57sDNxWnWhF5ovqzqK3/LWhftEhqpCIQDYKv5krNmwE5ELHR+DyC4X66KQCi+mOTLAwSNqutNRYaqPL0hX1+Rpzfk6w0lN6o5nsd94XmU3KguuVF9LLcATQQ0rVE6BWtUIRqVj0rp46oM9XRTOUnRXqrqTCIBIxYweCBqa3HiBGgaU6ciKAgNEhJQUIADB5CRAXd3tLqyMmzbhjlzMGgQnJzQIDkZe/Zg1y7ExKAtMWiZiIiIDxqdO3duy5YtO3fuPHPmjM1mQ2tjGKZbt27Dhw8fP358VFQUHDqYYF+31W898ZdlW7Iv69Ho4Mnc5yqMH/55nKtSinsy7YOdxIPRAVw33wDPu4tdcWf1xvraylqxk5gQUl9dr3RXwuHOrFb2eHrBziOZh07l2VgOd7Xoif5SsRDNwfHcxqIDay/vsPGsa10pHACeLbbW/BN2EzgtJLQ/WgFBE4VEHOkjjvTRoImVZQvKK/P1hny9IV9fcbWiKr/UYLbZcL+sLFtUUVVUUXUo6xKaKCRiH5Uy2N01xEPl46r0dVUGe6hEDIM2kPrblfe3HpzRv/uTfbuKGAZtR6/H1q3IyECDsjJkZyMmBpWVKC2FWg0/P/yOpuHvD4ZBaSnaQkEBamrQqROkUvxOIEDXrjh5EhYLGhw7Bo6DUIgGZ8/CakUrYdBKohstWbKktrb22LFjKSkpZ86cycjIuHLlCs/zaD5CSEBAgE6n69atW79+/Xr16iWTyeDQgbk5yz5/LemNT3eknMlHo8z80hmvf/fhC+NC/dW4G443H4I9iJCI4vFAXa699uPV/Yeun/m/zs+4i11xB6yNvXrxakVJRefBnY0GY+7xXKVGKZFL4HCby8WGH3ad2Xc8p6bODDvERPoN6RWG5rhuvvG3rHUXqy6hUUFtKRzAW6r+Cr4O9qEE4YzTM2h7ApoO0ahCNCo0YTnuWqXxqqEqX2/I1xvy9Iaca+W1ZgtaoLrelFlkyizSowlNUZ7Ocl+VMkijCtGofFyVviqlt4uSELRQQXnljdr6f+xI/f7o+Rnx3ZN6dhEyNNpCfT0KCmC1okFVFSor0YDnwfOgKBCC/yAEDXgebYHnQQgIwc1oGjyP3+n1yMkBw6BBcTF4Hq2EQWuTyWSDG6FRbW1tVlZWQUFBcXHxtWvXSkpK6urqKisreZ6vrKwE4OzsTAhxdnaWSqXe3t4eHh7e3t7+/v4REREymQwODxWJSPC3P435/MfUddtOotH1CuPct9e/M39k7+hA3InlDLgy2IEIe4I44QG5WHVpw9V9JwyZPHgAIkqIOzNcNRRcKFB5q6KHRRemF+am5RZeKAztFUooAodbyaWiI+cu19SZYQcBQ/9lRgKaI7Xs/PKc9UZbHZrU2OpvWKpdhAo8wmx1GzhzKuxFCRTvAgweBJqifFyVPq7KXlo/NKmuN+XpDfn6ijy94ZLecNVQVVRRhRZgOa6ooqqooupYbiGayCUiX5Wzr6vSx1Xpo1L6uCq1Hio3uQzNcdVQiUallcb3tx78JuXMMwmxiT06URRB6/L1xcyZiItDgytX8NVXaKBQQK1GXh5KSuDnhwYsi+Ji2GxQq9EWvL0hFiMnBzodZDI0sFpx8SJ8fSEQoMGwYXjiCUgkaLBtGz74AK2EQRuTyWQxjeDwaKAoMm9yP2+18oO1+1mWA1Bnsrz4j59fmDZwwuAo/BHevBd2Eg1Gu+PBHzdk/lC4J6v6Cm4ipBjcQV113aXTl2wWm7aXVuYs8+vsV1FUceXcFZWvys3PDQ63cnNx+vvzY559Z4PZYsO9PD6sW4CXK+xj5qxfXdq2pfgwblNQp3cRKvCo4lm9zfge7MbIplHCbuhIFBJxtwDvbgHeaFJZZ7pSVnG57MaV6zeulN+4UnajsLzSyrJoAWO9ObNIn1mkx01cZJIAtYu/m4u/m7Ofm7O/m4u/m7NEKMAdFBoqcZOSG9Vvbdr7XerZeUN7De6kJQSthqYhk0GpRAMnJwiFaKBQoGtXXLyIzZsxaRLkcmRmIiUFXl6IiADAsqzFYqFpWigUogV4nq+qqpLJZAJPz/+PPfgAj6pM2Ab8vKfNJJkkk0x6TwgJBAiE3nsJRQEbq2Jb9VNsqOCu7tp1VUSxrqKruK6oKCq9BkILXekEEgLpvUwmZTLtnPN7Zf98F3zJwRNSyEze+8aECdiwAcHBGDIEDgdSU5GRgb/9De7u+J1WCy8vuLvjd+7uIATthANFdYA5ExOD/Lz+/tHG+gYbAFGU3v73zpziqifnj2cIwZVkSypUIUQzHp3IIYu7y46tytuRby5FMwLDQwHLssFxwSG9QvzC/QB46D16je5lKjXxWh5USxJigv7+4NSXPtksy7iKQIPnn+cMhzo59cVvnvtPTn0xWpJXXzJA3xPdlb3mBVkyQR3CBHCei9Dl6d21AyJDBkSG4DJlNXUXS6sKqkxZpZWXSivzK02FRpMsoy2M9Q3G+objOUW4jJebNszg3SPANzbIEObrHe7rHR3g6ybwAPIqqtFMVmnlU99s7BlkeHjy8Kn94ghBR2EYDBuG0lIcOoScHAgCjEZ4e2PuXISEAKipqdm+fbvZbJ4wYUJERATDMGi98vLyPXv2VFRUzJkzJzAwkNx/P774Aj/+iK1bIcsoLsZNN2HMGGg06EgcKKpjDE+M+vzFPy16Z01JZS0a/bjteHlV3UsLpmsFDv/LcQFiDtTgE8EGoVOYRcu2ksM/5adWWE1QoGF4KNB4aCITI3EZQ7jBEG4ApWzqiF4X8yu/Xn8YyhbeOc5Ny+OPyJDXFu798tIGu+SAgjxzKborsWGNaEmBarz3a4R4wjkFeOkCvHS4TJ3FllthzCk3ZpdX5ZRX51YYs8uqLHYH2qamwZJeYEkvKEUThpBgvWeor7exvgEKLpRULlq5qX/EscemjRzRMwJtER+PO+9EZCT+y2DAjBkQBPwuMBA33YSYGGRmwmpF//5ISkLPnmAYABzHCYJw5MiRzMzMYcOGjR492s/PD6rV19cfOXIkNTW1urp66NChgiDgd71749FHcfQoiovBMBg7FqNGwccHhODBBxEXB57Hf/XtiyefhCCgPXCgqA7TI9zvi5dvX7xs3fnsUjTadfRCWVXd0qdn+3q7o5FsTYU6RDsZHc9oq9lYdGBt4Z46RwOuimd4UO2nwWLPKarE5WSA4H8N6xc5cWgc/ojRVvtOxre/Vp3HVeWaS9AtyVKVveZ1qMZqk1ntVLgQnVboExbYJywQl6lpsGSVVl4srSqoNBVUmbJKK7PLqyRJRhtIslxorCk01uCPnMwrfvBfPydFhSxMHjU4JgzXJiYGMTH4X3o9JkzA/zIYMGkSJk1CM56ensnJyVFRUWlpaampqSdPnpw8efKAAQM8PDxwVQ6H4/Tp01u2bCkuLg4LC5s6dWpSUpKHhwchBL+LiUFMDJqbNw+Xi4tDXBzaCQeK6kh+PrpPn7/thX9uSjt2CY3OXix+4OXv3108JzrUAEC2pEIdopmCjpRTX7w6P3V32TGHLEIFgeFAtZOyqtq/vLf+fHYpLkfwv3iOffruifgjR6vOvXP+22p7Hf5IXn0JuiW76XlZqoJKRMd7vYRuwMtNOzAqdGBUKJpYHY7c8urcCmNuRXVeZXVehTG7zFhZZ0aHOZ5TdO/y1WN7Rz8+dWTv0AB0Ijc3t6SkpOjo6BMnThw+fHjVqlWHDh1KTk6Oi4vjeR4tyc3N3bhx47lz5wwGw9SpU0eMGOHr68swDK4rDhTVwdw0/NtPzn7/290/bjuORkXlpvtf+v4fj88c0c8b9lNQg40CF4OOccZ06cf8nUcq02XIUE3DCqDaw8mMwmc/2GCsMaMJz7F2h4jL3DljcGSwD5Q5ZPH73JRvc7fJkKFCtb3OZK/35j3QnYiWLaJlC1Tjvf5C2CB0SxqOiwv2iwv2w2VsDjGvsvpiaWVBlamg0lRQZcqvNBVUmdB+9p7L3nc+e2yvmCeSR8YH+6MT6fX6cePG9erV62ijTz75ZODAgcnJySEhIYQQNKmoqEhJSTl8+LCbm9uYMWNGjBgREhLCcRy6AA4U1fEYhjx914SYUMPSr1NFUQJgttgWL1v3wRNkYKgIFYh2MtqbDPlwZfoPeTvSa7LRegLDgWqzbQfO/+Nf2212B5rMmZg4bUT8E0t+sTtENAry87p3zjAoyzeXvnXum6y6ArRGvrnU2zsG3YYsGe2mF6EaIwzj3OeDuozAsbGBhthAAy5T02ApqDTlV5kKqkwFlaas0soLJZV1FiuulSxjz7lL+85nz0zq9ciU4eEGPToLISQoKGj69Om9e/c+fPjwiRMnzp49O378+DFjxvj4+FgslkOHDm3atMlsNiclJY0aNSomJkaj0aDL4EBRnWXOxMQgP6+/f7SxvsEGQBSlWuM2hEINopmE9mOXHDtKj/6Un1rQUI5rwjMcAQHVBpIkf7o67ZsNR9GE59i//nnyrLF9ADx7/5TXPtuKRk/dNV4rcFCwpfjQ8ou/WEQbWinXXNLXOwbdhr3mVVmqgErETfBeAhBQf8TLTZsQpk0IC8RlKuvMOeXGvIrqj7cfKDXVofUkWd5w7NyWkxlzBvd5eNKwIL0nOgvHcbGxsaGhof369UtLS9u4cePhw4ejo6MvXrxYW1sbFxc3ZMiQvn376nQ6Qgi6Eg4U1YmGJ0Z99sK8Re+uLa2s5VlxSM8CqMHoIQxAe2gQrVtLDv2Un1phNaENNAwPqg3MFtuLn2xOO3YJTfSebm8+cUNS7zA0mjkmISuv/Pstvw1PjBo3KBYtqXOY38/8YV/5SVyT/PpSdBuiNVVsWAvVeM9FhIsEda0MOneDzn1QdOj7W9JwrTQcFxfsxzLMr5cKZiT1YghBJ3Jzc0tMTAwLC0tMTFy7du1XX301YsSIuXPnDhgwwMfHh2EYdD0cKKpzxUb4f/ny7YuXrfMWjrpr7FCBaMYDLNqmwmpaU7hnc9EBs2hBm/EMD+paFZZWL162LruwEk1iI/yXPjU72N8Ll3n8jrHFFTWPzBuNlpyryVly7ptiSyWuVZ65FN2DLNfaTX+Hagw/gPO4F1Sb1VlslXVmqKbhuV7B/r1DA/qEBSaEBcQGGliGwXXl6+s7cuTIhoaGwsLC8ePHjx07lud5dFUcKKrT+fnoPv37bceOpkAlzUS0QYXV9HXOptTS3xyyiHaiYXhQ1+RERuGzH6yvrmlAk1EDYl59dIaHm4ArMYS8+cQNhOD/kGTpp4JdX2dvdsgi2iDXXILuwV7zuiyWQCUi8PolAAuqzfIqq3FVWp6LD/HvExqYEBaQEBrYI9CXZRh0MQzD+Pn5BQYGent78zyPLowDRV0Pblp+RK8ciFCBI5pRaAODxivKI4Qlxx2yiHYiMByo1lubeuqdr1MdooRGhGD+rCELbhvNEIKWEIL/o8xS9db5b86astFmlVZTvcPiwWnh0kTrHtG8GqrxuicYLg5Ue8irMOJKPMtG+OkTQgP6hAUmhAX0Cw/iWRZUO+FAUdeF/RzEIqhANMNBPNEGBOTmsPHDDX2WZXx/xnQJ7UFgeFCtIYrSB9/t+XHbcTQReO65+ydPH50A1faWH/8g88c6RwPagww5z1zS2ysKrkuWauym5wAZ6jB8Aqd7CFQ7yauodhf4+BD/hLDAPqEBsYGGnsF+PMuC6hgcKOp6kK07oZJmItpDqJv/OwMe31J88POL6xpEK9pGw/KgVKups/z9o41Hz+ahiZ+P7u0nb0zoEQR1LKLtk6yft5UcRrvKN5f29oqC67LXvCCLxVCL5b2XAByodvKnkf0fmDiUIQRUp+BAUdeDbE2FOkQzHu2EgMwIHjnQJ35ZxqqT1RfQBgLDg1Inr8T4zLtrc4uNaBIXFbD0qdmBBk+opmH50f79q+11RyrTZchoJ7nmUrgu0bJdbFgP1TjdYwzfF1T78XLTgupEHCiq80nlsJ+FCiKJZdgwtKsgrWFJ/0fWF+5bkb3RItpwTQSGB6XCoVM5L3y8qdZsRZNJw+JeeChZK3BoDQIy1DdhqG9ChdW0pfjgxqK0ansd2izPXAIXJUtVdtPfoBrhYnndI6AoZ8aBojqdbNkFyFBh3QH/wcOqokJ80a4IyOzQsUMNfZZlfH+qOgutJzAcqD/yw7ZjH3y7R5JkNCIE988dcf/cEYTgmvlpvO+KSv5TxOR9FSc3FqWdNWWjDfLqS+Gi7Ka/y1Il1GIF/bsgAijKmXGgqM5nTYU6W38N+mzrqjcXzhqcEIH2Fqw1vN3/0VfPrjhQcRqtJDACKGV2u7jkqx0b955FEzct/9LD08cPjkV74BluYsCgiQGD8s2lG4v2bys53CBa0XqlliqLaNOyAlyLaF4tWrZCNU73IMMngqKcHAeK6mSyRbYdhArGOrf0vABJtixc8suiuyfeNCkR7a2ooeK3qvNoPQ3Dg1JQXdvw3Icbjp8rQJMAX8+3n7qxV3Qg2lu4e+CC2JvujZ65/OIvW4sPo5VkyAUNZbG6MLgQWSyy17wG1QgXw+sWgqKcHweK6lyy7QDkBqhwOCNakgkAUZTe/mpHTlHlk/PHM4SgnciQP7qw2irZ0XoahgfVkqy88mfeW1dcXoMm/XqGLHnyRl9vd3QYN1aTXVeMa5JbXxKrC4PrkO2m52S5Fmqxgv5dEC0oyvlxoKhOZk2FOgMS7w7cXllaWYtGP247XmGsf+nhZI3AoT2klBw5bszENeEZDlQz+09cevGfm+sbbGgybWSvvz84VeA5dKRT1VkZtXm4JvnmUrgQR/3XonUvVON0Cxh+ACjKJXCgqE4ly5bdUINoQsKSv3xZWvTu2oycMjRKPZJZVlW79OnZPl7uaJtqe93nF9fhWmlYHtRlZBkrNx799Mc0SZbRiGHIgltH33XDEHS8nwt2QRkBkSFDQZ65FK5Cdlyy174N1Rg+gdc9AYpyFRwoqjPZz0IqgwpEGA7i7ueD5c/Pe+Gfm9KOX0KjM1nF97/0/bJn5kaF+KINPr+4rtZhhrJI96BccwkUCAwPqonN7njji5St+8+hibtWePWRGaMHxqDjFTaUH65Mh7JX+z14uvritpJDJns9msk1l8BFOGzViyA3QCUi8N7vgvCgKFfBgaI6kWzdA5U0E9HITcu//dTs977ZtTrlBBoVlZsefGXVWwtvGJQQjmtyxnQptfRXKIv2CPl40KIDFac/zPyx1mFGMwLDg2pUYaz7y3vr0y+VoElooP6dp2dHhxrQKX4u2C1DhoLBvr2H+iYM9U24O2r6wcozawv3nDVl4zLFDRV2ycEzHJyco265ZD8B1XjPRQzfCxSlQnh4+C233BITE4OujQNFdSLZuheqEKKZgCYMQxbdMzEsSP/Bt3skSQZQW295YsnPi++ZOHdiIlpJlKV/Zv0sQ4YCArIw7jaOsGP9B/T1jvnwwuqDFadxJYHhQAGZOWXPvLeutLIWTQbEh7618Ea9lxs6Ra3DvLP0KJTdHDYejXiGG+s/YKz/gAu1+ZuLD6aW/WoRbQBEWSpsKI/yCIYzk+zp9roPoRojDOY87gdFqWMwGEaNGoUujwNFdRrJCPspqMH3AhuEK82bNjAy2PdvH240W2wARFFasmJHdmHlk/PHM4RAtbWFey7VFULZ3LBxvb2i0MhX8Hq5z/17y098dGF1jb0eTTQMj25vx6GM1z/fZrE50GTOxMTF90zkWAadZUNhmkW0QUGUR3CSTxyu1NMzfKFn+AMxN+4pP7amYG+euSTPXBLlEQznJVvt1U9DtkMl4i54LwVYUNRVOWyOHZ/vYFhmyJwh+iC9w+rY8tEWTz/PwTcM9vTzRNfDgaI6i2zdB4hQgWgmoCXDE6M+e3He4nfXllbWotGP245XGOtfejhZI3BQocJq+iZnK5QFaH3vjpqOK431H9DPO+bDC6sPVJxGI4ER0I3JMr5cc/DLNQdlGf/FsszCO8bdNi0JncguOTYUpUHZzWHjCQha4sFpZwSPnB484pgxA07OXvOq5MiAarzX3wgXBYr6I5zADZw1cPdXu7N/y+47qe+plFMOmyNueJynnye6JA4U1Wmse6AO0YyFgp4R/l++fPvT767NzClDo9QjmWVVtUufnu3j5Y4/8vnFtQ2iFcoeib3JjdWgGR/B66U+9+8tP/HRhdU19nqB4dBdNVjsryzfsvvXLDTx0mnfeGLW4IQIdK5dZceqbDVQ4CN4TQgYhKsiIIN8esGZidZdDvP3UI3RjOLc7wBFqRMQFdBzeM/sY9kOu+Pirxf7jO8T2CMQXRUHiuokomzbBzUYb/D9oczPR/fZ8/Ne+OemtOOX0OhMVvEDL3//7uK5USG+UHbcmLmn/DiUDfbtPcLQF8rG+g/o593jowurBYZHt1RWVfvMsnUZOWVoEhHks3TRnMhgH3QuGfLPBbug7MaQ0TzDwaXJUoW9+i+ADHUI8RS8lwIEFKVa3wl9C88V7vl6T/9p/SMTIzmBQ1fFgaI6h/0kpGqoQISxAIurctPybz81+71vdq1OOYFGhWWmB19Z9dbCGwYlhKMlDln8JOtnKNMw/GM9b8Ef8RE8X+zzZ7vkQPdz+kLRX99fX2Uyo8nwxKjXH5upc9eg0+0rP5lTXwwFGkaYGTIKLk6yVT8pSxVQjfd+lbDBoKjWYFjG0+DJu/F+EX7u3u7owjhQVKeQrXuhkmYcVGAYsuieiWFB+g9W7pFkGUBtveXJt3959v4pM8ckoJlfCnbnmUuhbF7E5GCtAerwDIduZv3uM0v/vdPuENHktmlJT945nmEIOp0M+Ye8HVA2JWiIN+8Bl+ao/0Ky7odqrHYK6zYHFNUasiTnnMgpyykLig3KPZXrF+kXlhDGMAy6JA4U1Slk6x6owhDNKKg2b9rAiCCfv3+0yWyxAbA7xNc+25qRU/rk/PEMIWhSba9blZcCZSFufreGTwTVEkmSP12d9s2Go2jCc+xf/zx51tg+uE4OV6Zn1RVAAQGZGzoOLk2yn7HXvgPVCOPLe78Bimql2qraM7vOhMaH9h7bO+37tEu/XtIH6j39PAkh6Ho4UFQnkMphT4cafH8wBrTGiP7Rn704b9E7a8uqatHox23HK4z1Lz2crBE4NPo6e3O9wwJlj8beLDA8qGbMFtuLn2xOO3YJTfSebm8+cUNS7zBcPz/k7YCyUf6JYe4BcGGy2Vb9JGQ71CK8filh/EBRreGwOU7vOM0JXMzgGJ8Qn6TpSQd/PJh/Oj9uVByv4dH1cKCojidb9wAyVCCasWi9nhH+X75y+6J312bmlKFR6pHMsqrapU/P9vFyv1RXuLXkEJSN9u8/2Lc3qGYKSqufWbYuu7ASTWIj/Jc+NTvY3wvXz69V59NrsqFsXvhkuDR7zWuy4yJU49zvYjUTQVGtVF1SXVtZGzsk1j/KH0BYQlh0UnRlQWVdZZ1PiA+6Hg4U1Qmse6EO0YzDNfH30X32/LwX/rkp7fglNDqTVfzAy98vWzx3eflaSZagQMsKD/eYC6qZ4+cLnvtwQ3VNA5qMGhDz6i1NpS4AACAASURBVKMzPNwEXFff522HsmGGPnGe4XBdomW7w7wKqhGuJ+/1HCiq9fwi/JIfTcZlBs8ejC6MA0V1OFG2HYAajD/4PrhWblr+7admL/tm108pJ9CosMz04IovyJgiKJsXPtlfowd1pbWpp975OtUhSmhECObPGrLgttEMIbiuTlVnnTFdgrJ54ZPhumSxxG56FuoRQdB/AKIFRXUDHCiqg8m2XyHVQAWiGQsQtAHDkMX3TAwP0n+wco8ky4SFnFhGoMhPo785fDyoy4ii9P63e1ZvP44mAs/97YEpyaN6owv4Lm87lCX5xPXxjobLkmymxbJkhGq857MM3xtU91BYZdp8MsPbTXvb8ER0SxwoqqNZ90AlzTi0h3nTBgb5eb30z81y7yrG2wFl/9NjtoYRQDWpqbP87cONv6bnoYmfj+7tp25MiAlCF3C+Jve4MRPK7oiYCtflqPtcsu6HaqxmLOdxLyhXV222pJy+sP639BO5RX6eHusX3YPuigNFdTDZugeqsEQYiXYyblDsshdn/y3rAxmKentFjfUfAKpJXonxmXfX5hYb0SQuKmDpU7MDDZ7oGr7L2w5lvb2iEvWxcFGS/aS9bhlUI4yB178LEFAuqrbBuiv94rZTF9IyckRJQqPn507ydNOgu+JAUR1KLIbjAtQQBoPxQvvZYz0o8xIUEJAFsTcREAAOUVqyYseieyZqBQ7d1aFTOc9/vKnObEWTycPjX/ifaRqBQ9dwsa7wSGU6lM2PTIaLkqUam/FxyHaoRXjvJYTxA+VyGmz2XemXNp84vz8j1y6KuMykvrGT+vRAN8aBojqSbN0FdYhmLNrPxbrC7aVHoGxK0JB4zwg0WvbNrg17zgT46h68eSS6pR+2Hfvg2z2SJKMRIbh/7oj7544gBF3Hd3nbZchQEKsLG+QbD9ck201/kcV8qMZ53M1qJ4FyITaHuD8zZ/OJjF1nL1rsDjSj0wp/nz0B3RsHiupQ1r1Qh2jGof0sv7hGkiUocTCDHElo9M3Go7/sOAlg5aZfZ43tG+zvhe7Ebhff+mrHpr1n0cRNy7/08PTxg2PRleSZS/eXn4Ky+VHJBASuyFG/QrRsg2qE68l7PgvKJUiyfCK3aNupC5uPnzfWN0DZk9NHB3jr0L1xoKiOI9tk2yGowQaDi0M72Vd+8lR1FpRZTni9cHr7cw/Ibhr+0x/S0Mhqc3y8au8/Hp+FbqO6tuG5DzYcP1+AJgG+nkufnh0fFYAuZmXOVhkyFMToQocb+sAVSfZT9tolUI8Igv4DEC0oJ5dVWrnht3Prj6WX19Tjj/QLD7ptWCK6PQ4U1WFk22HIZqhANOPRThyyuCJ7A5RJdazttE52iK8u38qyjCTLaLLzcOYtkwuSeoehG8jKK1+8bF1JRQ2aJMaFvLXwRl9vd3Qx2fXFe8tPQNntEVMICFyOLNXYjI9BtkM13vNvDN8blNPKKC7fciJjy4mMQmMN1OFY5tVbpzAMQbfHgaI6jnUvVNKMQzv5KX9XUUMFlPGng2QHg0aiKOFKS7/e+c0/7mJZBi5t19ELry7f2mC1o8mN4/s+c+8knmPR9XyVvVGGDAXh7oFj/PvDBcl2019kMR+qsZpxnMfdoJzWs99v2Xj8PFrpvnGDewb5gQI4UFSHka17oAYRiDAc7cFoq/0hbweUJXhFP/fQn59++5es/Eq05FJB5fo9Z+ZOTISLkmWs3Hj00x/TJFlGI4YhC24dfdcNQ9AlZdbmHalMh7LbIyYTELgcR/0K0bINqhHGwOuXAgSU03o8edT+zFxjfQNUi/TTPzxpGKhGHCiqg4h5EHOgAhGGgbijPazI3mgWLVBAQBbEzvV19/DWuQOVUPDpj2kTh8Z567RwOTa7440vUrbuP4cm7lrh1UdmjB4Yg65qRfZGGTIUhLj5jQ8YBJcj2U/Za5egFRhev4ww/qCcWaiP19t3zHjoy18kSYYKhODFmyZreA5UIw4U1TFkSypU0oxFe8iqK0gpOQJlU4KGxnlGvPFFym/n8qGsps6yYs2hp+4aD9dSYaz7y3vr0y+VoElYoP6dRXOiQnzRVZ02XTxuzISyu6Oms4SBa5GlGpvxMch2qMbpHmU1Y0E5vxE9I56aPvrdTfugwuxBfYbFhqP1jlUUBrjpwjy84Vo4UFQHse2FOkQzDu1hedYaGTIUuLGa+6JnfrPh6Prdp/FHft5xYu6kxKgQX7iKzJyyZ95bV1pZiyZJvcLefOIGvZcburAvL22AskiPoPEBA+FqZLvpL7KYD9UYYRjvuRCUq7h37OCDF/IOZObiqnw83BbPGotr8tyRzRdM5T29/SaF9pwYEjvIP9wuOQSGg5PjQFEdQW6QbUehBhsONgpttrf8+GnTRSj7U8SUEydKPv0xDSo4ROn9lbvf/8tNcAk7DmW89vk2q82BJnMmJi6+ZyLHMujCDlWePVeTA2X3Rs0kIHAtjvovRcs2qEYYg6D/AGBBuYoNx9KPZRfij/z1hnF6dy1aL7fWeMFUDuCCqeKCqWJ5+sEQdy9PLV9qrYr1NoS5+/Tw9I/18g9z9+nh6a9leTgPDhTVAWTbAchWqEA0E9FmDllckb0JyoK0hpvCxh03FY1KijlwMlsUJfyRQ6dy0o5dGj0wBs5MlvHlmoNfrjkoy/gvlmWevHPcrVOT0LVJsrQiewOU9fQMH+HXF65Fsp+y176NVmAE/XuEDQTlEqwOx1vrdq8+fBp/ZGiP8JlJvXFNthdm4EpF5hqYwTDyWbnobHURmrCEmRAU/8HQeXASHCiqI1j3QiXNOLTZ+sJ9xQ0VUPZAzI0Cww/rFzmsX2SlqX7HoYx1u05fKqjEVb337e5h/SJ5noVzarDYX/50y57fstDES6d944lZgxMi0OVtLz2SW18CZfdFzyQgcCGyVGMzPgbZDtU43aOMZgwol5BfWf3UNxvPF5Xjj2h57pVbJhOCa5NScAEtYVkJVxJlyYPTwHlwoKgOIFv3QA3iRoQhaJt6h+X7vBQoS/CKHu2fiCYGb4950wbeNnXg8fP563af2XXkgs3uQEsKS6t/2H58/szBcEJlVbXPLFuXkVOGJhFBPksXzYkM9kGXZ5XsK3O2Qllf75hBPr3gUiS76WlZzIdqjDCM91wIyiXsOXfpuVXbahosuJLAsjZRxJUWTBkebtDjmlRa6o9XFKAlDCuhmR6efnAeHCiq3TkyIRZBBSKMBNGgbX7I31Fjr4cCArIg9iYCgisRgoG9wwf2Dn/mnok7DmWsST2VkVOGZlasOZQ8qref3gNOJf1iydPvrKmubUCT0Ukxrzwyw8NNgDNYW7Cn3FoNZfdFz4Jrsdd+KFp2QjXCGAT9BwALyslJkrx856HlOw5LsowrRQf4vjd/1j9TDqacvoAmPYP87hkzCNdqZ2GWKMtohhCZYWQ008PTH86DA0W1N9m6ByppxqJtKqzVawv2QNmUoKFxnuFQpnPXzJmYOGdi4rns0g27T28/mFFntqKJ2WJb/mPa8/8zDU4lwOAp8Bya3DYt6ck7xzMMgTOoc5h/zE+FsuGGPn29Y+BCJOs+R93HaAVG0L9H2EBQTs5Y3/CX77YcvJCLZmYl9Xrp5sluAv/6bVMvlVVdLK0EwBDy8s2TOZbBtUopzERLWFZCS2I8/eE8OFBUe5Ote6AO0YxF23yds8Uq2aFAw/B3R02HOr2jA3tHBz5x5/idhzPX7z59MqMQjTbvS795yoDe0YFwHn56j6VPz37o1VWiJD/758kzx/aB81iZu63OYYYChjB/jr4BLkQWC2zVCwERqnG6RxnNGFBO7lhO4eKVm8tq6nAlgWOfnjFm/ugkNPLQCB/cfcOfPvq+zmK9fdSA/pHBuFYNov1ASQ5awnIymtEwXKi7Hs6DA0W1L7kOtmNQg4sDG4o2yK4v3lF6FMpuChvvr9GjNbQCN3NMwswxCXklxg17zmzae7bKZF72n9TPX7ydEDiR+KiAlxZM99Pr+vUMhvMosVRuLNoPZVMDh0Z6BMFlyBab8WFZMkI1RhjGey4E5eRWHz79xtpddlHElYL0nu/On9k/IhiXifL3eWPetNfXpj4+dQTaYG/RpQbRjmY45ncSmon29GMJA+fBgaLalWzdBzigAtGMQ9usuLRBkiUo8OY9bg2fhGsVEeTz6LwxC24d/Vt6/tpdp3Yezpg8PB5OZcKQnnA2X1xab5ccUKBh+PlRyXAhNtMzkv0sVCOMQdB/ALCgnFZtg/WF1dt3nMlCM6Pjo966fbreXYtmJvbp0Tc8UKfVoA1SCjPREoEjMloQ4+kPp8KBotqXdS/UIZpxaINT1VlHqtKh7I7IaR6cFm3DMGRI34ghfSMarHZQHeysKTut/BSU3RQ23l+jh6tw1P9LbNiIVmAE/XuEDQTltNILyxat3JRfWY0rEYI/jxuycPoohhAoCPDSoQ1EWd5VdBEtccDKogU9dH5wKhwoqj3JsnUf1CA6CANxrWTIK7I3QlmQ1jAzeCTaj5uGB9WRZMjLL/4iQ4YCb97j1vBJcBWS7aC9Zglag9M9ymjGgHJaqw+ffnPdLptDxJX07tq3bp8+Oj4KHeloeZ7RakYzPGFYVkZLenj6w6lwoKh2ZD8HqQwqEM1ogMO12l12/FxNDpT9OWYWz3DoCBYLdu3Cpk0oL4fBgHHjcMMNcHdHBzl1CuvX49w5MAwSE/GnPyE0FAyDl1/GsGGYNAmCgN/t349Vq/DBB2AYOKdtJYcza/Oh7PbIqR6cFi5BFottxscBEaoxmlG850JQzqnOYnv55x1bT2agmYSwwPfmzwz19UYH21FwAS2J9vbJtxWjJT08/eFUOFBU+5Ft+6CSZhyulUMWv87ZDGVxnhFj/QegIzQ0YO1afPUVpkzBuHEoLMTPPyMnB4sWgePQ7o4cwQcfICgI06dDkpCaildewcsvIzQUBw4gIACiiP8qKkJqKpxWg2j9d/ZmKAt285sVPAquQbbZjAtkqRKqETZE0H8IsKCc0NmC0qdXbiqsMqGZO0cNWDxrLM+y6HgphZloicFNm29DcwLDRXj4wqlwoKh2ZN0PVQjRjMG12lCYVtxQAWV/jp5FQNDuZBmVlfj0U0yfjnvvhbc3TCYYDFixAmPGYORItC+7Hf/5Dzw8cPvt6NMHsox+/fD449i6FbffDtfyfV6K0VYDZf8TM5tnOLgEe82Lkv0k1CMawedTwviCckKrD59+c90um0PElXRa4eWbJyf3j0enOFddll9XjWYYQqyyFS3p4enPMSycCgeKai+yWbb/BjX4PmACcE0aROuqvBQoG2pISPKJQ0dwOJCejrw83Hkn/P3xOz8/DB2KjRuxfz9GjkT7ys/HiRNYsAB9+sDNDb9LTMTgwTh4EDfeCBdSYqlcU7AHyvrre4706weX4DB/5zD/gNYQvF5l+ERQzqbOYnvp55RtJzPRTEJowDvzZ0YY9Ogs2wsy0JIBhpBccyFaEucVCGfDgaLaiWw7DNkOFYgwGtdqVV5Ktb0OCgjIvVEz0UFEEcXF0GgQGor/IgTu7ggMRHEx2l1FBRwOBAdDq8V/sSyio7FjB+x2/G75cqxbB4bB70pKIIpwTp9dXGuT7FDAEObhHnPgEiT7CXvNK2gNzv0u1v02UM4mvaB00beb8yur0cytw/o9N3uCwLHoRDsKMtGSwf5h53Kz0ZJ470A4Gw4U1V6saVCHaMbgmlTaTGsK9kLZ1KChPXSh6CCEwN0dNhtsNri54b9EERYL/P0BSJIkiiLP82gXWi0kCVYrJAksi/+qq4NWC4bB78aPx6RJ0Gjwu3378MsvcEK/Gc8fqDgNZdODhsfoQuH8ZKnCZlwA2QbVGD6J93oelLNZffj0G2t32UURV9JphZdvnpzcPx6dq8hck24sRUvCPD2hIM4rEM6GA0W1E9m2D2oQDwhJuCZfZ2+2SjYoEBj+rqjp6Dg8j9698bu9ezFtGn4nSSgvx/nzmDABwIkTJ1asWPHAAw8MGDAAbRcVBX9//PYbhgyBnx9+Z7XiwAEMGACtFr+Li8OECdBq8TujEWvWwNnYJccnF36GMjdWc1dUMlyAbLcZH5XFEqhGGH/B51MQAZTzqLPYXvo5ZdvJTDSTEBrwzvyZEQY9Ol1KQaaMFkR5+prsZiiI9wqEs+FAUe1CLIQjByoQYTjAofXyzKU7So9C2U1h4/w1enQcQhAWhltuwWuvQaNB//44dw4ffYSgIEybBiA4ODgsLOz5558fM2bMXXfdFRISgtaTZbm0tNTT09NDp8O8efjiC+j1mDsXoojPP0dZGWbPhqcnfscw4HkIAn7HcSAEzubH/J0FDeVQdldUso/gBednr3lJsh1BK3CCz8eEDQTlPE7nlyz+dnNhlQnN3DlqwKKZYwWOxfWQUpCJliSHx2fWlKIlfhqdr8YDzoYDRbUH2boPKmlG45r869I6UZagQMe53xo+ER2KEHh5YeFCeHvjhRdQVQVvb4wZgwcegI8PgICAgIceemj06NE//fTTww8//Kc//enGG2/U6XRQLT8//6uvviosLHzsscf69u1LbroJgoDVq/Gvf4EQxMfjrbfQrx9YFs6vxFL5Q94OKAtx85sdOhbOz1H/L4f5e7QG7/UCIwwF5SRkGd/uP/7upn12UcSVdFrh5ZsnJ/ePx3VSY7McKc9DSyaHxv3txGm0JM47EE6IA0W1C1sa1CGa0Wi906aLRyrToWx+5DQd546OxjAICcETT+C+++BwgGWh08HLy2qzHTp0aOvWrQ888MCwYcN69ux56NCh7777bt26dQ899NDYsWM5jsNV1dTUrFu37ocffoiJiXnggQfi4uLwO50Os2djwgRYrfidVgu9HjwPQvCf/8DdHRoN/mvGDIwcCULgPJZnrbFKdihb0OMmjrBwcqJ1j71mCVqDdZvDedwNyklU1Zn/9sO2tIwcNJMQGvDO/JkRBj2un9SiLIckoRk/rUdPb0Oh2YiW9PIKghPiQFHtQJRth6EGGwY2Eq0kQ/7XxXVQFqQ1zAoZhc7BMPDygpcXLiMIQnR0NCHkvvvumzdv3p133pmcnDxgwICtW7cuXbp0w4YNDz/8cHx8PFpit9v37t37ySefEEIWLFgwfPhwb29vlmUJIfidmxvc3NBcUBAu5+EBDw84j1+rzh+sPANlI/36DTUkwMnJjiy78XFAhGoM31vwfgOUkzh4Ife5VdsqauvRzK3D+j03e4LAsbiuUgoy0ZIpYXEXa8slWUZLenoFwAlxoKi2s52EZIIKRDMWrbe//FRGbR6U3Rs9k2c4XFehoaF//etfZ8yY8eWXX65fv/6RRx6ZPn36PffcM2bMmFWrVj3yyCM33HDDnXfe6e/vj8ucP3/+448/zszMnDdvXnJysr+/P8/zhBC4NKtk//jCaijTMPzDPebCycmS0Wp8QJZroRph9ILPchA3UF2ezSEu27zv2/3HZRn/h6eb5tVbpkzp1xPXm00S95ZcQkumhMZl1pRCQbxXIJwQB4pqM9mWBpWE0WglSZa+ztkCZT10oeMDknBdEUJYlvXy8hoxYkR8fPzOnTs///zzX375ZeHChQMGDHj22WePHTu2fPnybdu2LViwYNq0aRqNpqSk5Ouvv96yZcuECRMWLlwYGRnJ8zwhBN3AypytxZZKKPtTxJRArS+cm8NmfER25KIVGF7/HmEjQHV5OeXGZ77bfK6wDM30Cw96+47p4QY9uoD9Jdn1dhuaceeEEYGRb5w+i5ZwDBvj6Q8nxIGi2ky27oMqLNEMQyvtLPs1z1wCZQ/GzCYg6AIIISzL+vn53XLLLSNHjvz222+feOKJKVOmPPjggyNHjkxISNiyZcuHH364ffv23r17r1+/3mAwvPnmmwMHDhQEgRCC7iG7vuiXgt1QFuzmd0v4BDg5u+kFyXYIrcF7LmY140F1eet/S399TarZZseVCMEdo5KemTmWYxl0DSkFmWjJ+JAeGpZLry5GS2J0fjzDwglxoKg2kkywn4EaQhKIJ1rDIYvf5myDsiG+vZN84tCVEEI4jgsPD1+8ePGsWbP++c9/zps37/7777/llltuu+02nU63bNmyjIyMxx57bNKkSe7u7qQRugdJlt7N+N4hi1D2SI+bBIaHM3PU/8thXoXWYLXJnO5hUF1bncX22pqdm46fRzOB3rolt08fHBOGLkOS5Z2FF9CSKaE9bZLjQm0ZWtLPJxTOiQNFtY1sOwCIUIEIo9FKW4oPFlsqoYCA3Bc9C10SIYTn+X79+r3//vt79+597733fvrpp+Tk5EOHDo0YMWLx4sV+fn7ofn4p2H2hNh/KRvklDjUkwJmJ1t32miVoDYZPEPTvAgRUF3Y6v+Qv323Jr6xGMxP79Hj11ql6dy26khOVheWWejTDMcz4kNjMmlK7JKIlCd7BcE4cKKqNrGlQh2hGozWskn1VXgqUjQtI6qELRdem1WqnTp06aNCgVatW/fDDD4SQ5ORkPz8/dD8llspvcrdCmZYVHu4xB85MdlywG58ARKhGGH/B5wsQd1BdlSzj2/3H39m01yFKuJKG456aMfrOUUmEoKtJKchES4b6R3gL2i2FRVDQRx8C58SBotpGtu2HGow3+D5ojXWFeyusJihgCDM/chqchMFgePTRRydMmLBy5Up0Vx9mrraINii7N2pmgNYXTkuWjNaqB2W5FuoRjeD7GWGDQXVVlXXm51ZtPZCZi2ZiAnyX3jkjPtgfXVJK4QW0ZEpYHIB0UzFawjFsT68AOCcOFNUWjosQi6ACEUYBLFSrd1hW56dC2bSgoeHugXAqGo1Gq9WiW9pZevQ343koi/eMmB06Bk7MYTMukMVctAIRvN9i+CRQXdXOM1kv/ZRSbbagmduGJ/71hnEankOXdLGm8lJNJVoyKbQngLPVRWhJrKe/luXhnDhQVBvI1n1QSTMarfFzwa4aez0U8Ax3R+Q0UE6i0mb6NGsNlLGEeSLuNoYwcFp20wuS7TBag9M9xrrNAdUlWeyO97akfZt2HM3otJqXb56U3D8eXVhKQSZa0tcnKMzD2yo5smrL0ZI++hA4LQ4U1Ra2NKhDhFFQzWSv/6VgN5TNChkVoPEB5STez/ih1mGGstvCJ8XqwuC0HHWfOMyr0Bqsdjrv+RSoLulUXslzq7bkVlSjmf4RwW/fMT3U1xtdW0phJloyOSwOQKap1CGJaEmCdzCcFgeKumayTbYdhRpcT7DBUG1VXkqDaIUCN1YzL3wyKCexteTQkap0KAt18789ciqcltiw3l77DlqD4fsI+ncAAqqLESXp33t/+2jbAYco4UoMQx6eNOzhScMZhqBrq7DUn6wsQkumhsUBOFtdBAV99CFwWhwo6lrJ9l8hN0AFohkN1Sptpk1F+6HsprDxPoInKGdQYTX96+I6KCMgj/e8VcPwcE6S7aDN9AwgQzXC+As+/wJxB9XF5JQbn1215Ux+KZoJ8fFacvv0pKgQOIPtBZmSLKOZMA/vXvoAAOmmYrSEY9g470A4LQ4Udc2saVBJGA3VvsnZapXsUKDj3G4KGwfKGciQ38n4ts7RAGXJwcOSfOLgnCRHhq3qIcg2qEc0gu9nhA0G1cWs/y399TWpZpsdzUxLjHvp5kleblo4iR0FmWjJ1LB4NDpTXYSWxHr6axgOTosDRV0r2boPahANEQZDncKG8pSSI1A2L2KyjnMH5Qw2Fu0/bsyEMj+N9wMxN8I5yWKJrepeWa5FKxDBewnDJ4HqSqrqzC/9tGNX+kU0o9Nqnp87cVZSLzgPs8N2sCwXLZkc1hOARbRfrC1HS/roQ+DMOFDUtZHK4ciECoQfDOIGdb7J2eKQRSjwFbxmh44B5QyKLZVfXtoAZQTk6fjbdZw7nJAsVVur5stiCVqD0z3Ous0G1ZWkZeS8sHp7eU09mhkeG/GPedMCvXVwKruKLlpFB5rx0bgN8Q8HcLa6yCGJaEkffQicGQeKuiaydT8gQw3NaKiTXV+8u+w4lN0eOVXDCKC6PFGW3j63skG0QtmMkJGDfHrBGckWm/FB2XERrcFqk3nPhaC6DKvdsWxL2nf7j8sy/g8Nxz0ydfh94wYzhMDZpBRkoiUTQ2JZwgA4aSyAgr76EDgzDhR1baz7oA7RjIE6/87eKEOGggCt7/Sg4aCcwbe529JrsqEsUOv7YMyNcEqSrfppyfYrWoPh+wj6dwEGVNdwOr/kuVVbc8qNaCY20LDkjunxwf5wQg5J2lN8ES2ZHBaHRieq8tESLcvHewXCmXGgqGshy7YDUIPxB9cTKmTU5h2uTIeyu6OSeYYD1eWdMV36Pi8FygjI4vg73FgNnJC95hXRsgWtQdhAwecLEHdQXYAoSf/e+9tH2w44RAlXIgR3jEpaNGOMwLFwTofLck02C5rRstyYoBg0OllVgJb01YdwDAtnxoGiroE9HVIlVCCaMQCBCisubZAhQ0GYe8DEgMFwcoIgBAQE6PV6uK46R8OS8yslWYKyOaFjE/WxcEKOuuWO+v+gVYiH4PMlYYNAdQG5FdXPrdpyKq8EzQTrPd+YlzykRxicWUrhBbRkdFC0O8cDKDAbK6x1aEl/33A4OQ4U1XqyLQ0qaUZDhePGzBPVF6DsvqiZLGHg5AwGw5QpU9zc3OC6PrqwusxSBWXBWsM90TPghMSGDfbapWgdTuPzKcP3AXW9yTJ+OnJ66YY9ZpsdzUxLjHvxpkne7lo4MxlIKchES6aExaHRqaoCKBjgGwYnx4GiWk+2pkEVhggjoMK/czZBWZxn+Cj/RDgtWZKNJUZztdkQbujRo4csyeW55XaL3RBu0Lhr4EK2lhzaXXYMyljC/LX3XW6sBs5Gsh2ymRYDElqBCPq3GM0YUNdbobHmxdXbD2floxmdVvP8nAmzBvaG8ztbVVJsrkEzDCETQmLR6ISxAAoSfcLg5DhQVGvJDbAfhiW9DAAAIABJREFUhxp8AhgD/siRyvTzNblQdm/0TAICpyXLcnlO+fm08/Ej4+NGxNVW1J7cdpITuEF+gzTuGriKooaK5VlrcFV3Rk7r7RUFZyM5Mm3GhyDb0Bq8519Yt5tBXVeyjJ+OnH5n4956qw3NDIsNf2NecqC3Di4hpTATLRnkF+an9UCjE1X5aEmYh4+fRgcnx4GiWkm2HYRsgwpEGA0VVuZuhbK+3jGDfHrBmTEsE943vCKvIvtYtpe/V3FmsbXeGj8q3tPgCVdhk+z/SP93g2iFsr7eMbdHTIGzkcUSW9W9slSD1uDc7+B0D4O6rspr6l/+eceec5fQjIbjHpk6/L5xgxlC4Cq2F2SiJVPC4tDIItoza0rRkv4+YXB+HCiqtaxpUIdoRuOPHKw8k1GbB2X3Rs+E83P3co8dEnt88/FDPx1ieTaiX0Rwz2C4kI8u/JRVVwBlOs7tr73mM4SBU5Elo7XqLlksRmuw2qm896ugrqtfjpx5e+PeOosVzSSEBf7jtqk9g/zgQgrqTRnVZWjJpNCeaHS2usguiWjJAN9wOD8OFNVKsjUNahAP8Em4KhnyypytUDbUkNDPuwdcgl+kn1+k376V+2KHxUYnRXMCB1expfjQ9pLDuKrHe94aoPWFc5HrbFX3yI4stAbD9xf07wMsqOukorb+lZ937kq/iGZYhrl37KDHpo3gWRauZXtBBlrS09s/2tMXjU4aC6Cgv08YnB8HimoVsRBiDlQgwjAQHld1oOJ0Vl0BlN0VmQxXYTPbbA02raeW5VnRIcJVZNcXfZr1C65qevDw8QED4Vxki7XqQcl+Gq1BuEjBdwWIG6jrZNupzNd+2VlttqCZnkGGf8xLTggNgCtKKchES6aGxaHJyaoCtETL8vFegXB+HCiqNWTbAaikGYOrkiGvzN0GZSP8+sV5RsAliA4x/2x+ZX5lr9G9zCZz1pEsnY9O46GBk2sQra+n/9sq2aAsxM3voR5z4WREW/VTku0QWoMwARrflYTxBXU9VNaZX/1l584zWWiGZZh7xw56dOoIgWPhiozWhl/LC9CSKaFxaHLSWICW9NGHcAwL58eBolrFehDqEM1oXFVa+alLdYVQQEDuikyGqzAWGXNO5uiD9EnTky4du5R7MrcwozB6QDRhCJyWDPnt8ysLzGVQxjPc3xPudWM1cCayzfScaNmKViEegu8KwoaBuh62ncp8fU2qsb4BzfQINPzjtml9wwPhunYWXhBlCc0Euun6GYLRKL++qtxSi5YM8A2HS+BAUa0gy7ZDUIMNAxsJZTLkb3O3QdlIv349dKFwCQ21DZd+u2S32PtP6a8z6KIHRlcVVmX/lu0b7KsP1sNp/Zy/60DFaVzVgh5zY3VhcCr2mtdF82q0Dif4fMLwfUB1OmN9w6u/7Ew5fQHNMITcPmrAohljBI6FS9tRmImWTAmLJ/j/jlbmQkGiTyhcAgeKUs+RCakCKhDNKFzV3vIT2fVFUEBA5kdOg6sghBjCDf5R/n6RfgA8DZ69x/Q2lZoIS+C0jhkzVmRvxFVNCBg4M2QUnIq99l1H/Qq0DhH0S1jNWFCdbs+5Sy//vKO8ph7NhPl6v37btMExoXB1FtGRVpKNlkwJi0OTXyty0BICDPSNgEvgQFGqydYDUEkYAWUy5O9zt0PZGP/+MbpQuAqtTttjcA9cJrBHYGCPQDitgobyf6R/LcoSlIW5ByyMmwen4qhf4aj7GK3Eey5m3W4C1bmM9Q1vrNu15UQGmmEImT86aWHyKA3PoRvYV3zJ7LCjGU9eMzwgAk2OVuaiJbFeAb4aD7gEDhSlnu0AVCFEGA5lu8uOZdcXQwEBuSNyKqiuyixaXjnzZZ3DDGVurOalPn92YzVwHo76/9hrXkMrce63c7pHQHWubacyX1+TaqxvQDOhvt6v3zp1SI8wdBsphZloyfiQWJ5h0aikwVRkrkZLBhui4Co4UJRaomz7DWrwvcD4QoEkS9/mboeycQFJ0R4h6HrqzNZKkzky2AfdmCRLb6b/J89cgqt6vOetEe5BcB5iw0/2mlfQSqx2Ku/9KqhOVF5T//ra1J1nstAMIbhlaL9nbhjnLvDoNkRZTi3MQkumhPVEk8MVOVAwxC8SroIDRalkOwG5DioQYSSU7Sr7Ld9cCgUMYe6MnIYuptJUv2bnqTU7T3312h3o3j67uPZIVTquak7o2EmBg+E8RMtmW/WzgITWYDSjBP1HAAeqU8gyfjpy+t1Ne+ssNjQT4uP16q1ThsdGoJv5rTy/ympGMxzDjA2KQZNfK3LQEgIMNkTCVXCgKHVk2wGoJIyAAkmWvstLgbLx/kkR7oHoMi7mV6xOObF5X7rN7rh1alKArye6sS3FB9cW7sVV9faKerDHbDgP0bLNZnwCENEaDD9A4/M5iACqU+SUG19cnXIspxDNEIJbhvZbPOv/sQcfgFHWh//435/neW7mksveOyQQIOywdwigIjJEUXHVqnVUW7XOVlvbirZubGu1VisuFAVkKIS9EvYIEEhCQpK7jMtOLpdbz/P5ff/pP99f/OU5uEACd7nP6zXVT6WE78kxFkHOxIjEAKUanQ7Vl0FOoi40RKVDfyGAYdxD7fvhDqIgyky4sLXmsMFiggsc4W5PmA3PcOh0+ecbDx/Iv0Ap/odSIdx9YyZ82Mmm4veKVuOiQlX63w25VyA8vIRo221vegwQ0ROcMFAZ/DGIFkzfEyXpy/0n3v5hr9XhRDcxwfrfL86akJoAX7XNWAQ52TFp6FRjbaloa4CczNBE9CMCGMYd1AL7CbhDMRJEAzkSlVaV58C1meGj47QRuKZEUdp+sOizjYfOXTChi4Uzh4UG6eCrytqq/3D6304qwjUlp3hxyH0hSj28hGTba298ANSOniBCgjJkJeECwfS9c1W1L36Tc9pQg244QhaPHfqbG6dplQr4qsLm2gutDeiGAFkxqeh0uK4MLmSGJKAfEcAwbqD2g4ATbiDKCXBhS81BQ3stXOAId1t8Nq6ddptj876CLzYdKa9uxE8pFcKd88bAV9XZmn+b/0+z0wLXCMgTA5cO9I+Hl5Bse22N94Pa0BOEj1AFryRcGJg+ZnM4P9p56IPtB52ihG5SI0NeXjI7Iy4Svm2LoRByhoVER2r90elQ/QW4MDo0Af2IAIZxhz0X7iGqiZDjpOJXZTlwbVZEZqw2HNdCQ7Pl6y3Hvtt2osVshZzFs4aHBungkyyi9XenPjDZGnFRtyfMnhE+Gl5Csu21Nd4PakVPEC5IFbyS8HFg+tjRC8aXVm8tNTWgG4Hn7p4y+tE5ExQ8D5+XYyiEnOyYNHRxuK4MchL8QiLUAehHBDCMG6htP9xB/KDIgJwt1QeqrPVwQSD87QmzcdUZa5pWbTm2bke+ze6ECxqV4s55mfBJTiq+fPrfJWYjLmpiaMadiXPhJSTbXlvj/aBW9AjRKYM/IUIqmL5kttpWbMn9ct9xiVJ0Mzwh6uWbs1MiQsAA1e2tpxqqICc7Ng2d6mzmC+Y6yMkMTUD/IoBhLkmqh7MQbiDK8YCAbpxU/LJ8K1ybFZEZpQ7BVXSysPLzjYf3HD0vUYqLWjxreLBeC99DQV8rWHmssRAXlayLeXrQMgICbyDZ9toa7we1okeIRhX8EacYBqYv7S4ofXnNtuqmVnSjVggPZY+/d+oYjiNgOuQYCilkJPgHpepD0elwXRmFvDEhiehfBDDMpVB7LkDhDtUEyNlcfcBkbYALAuFvS8jG1XK2tOaNT3fkF1XCDRq1YtkNmfBJ7xev2V17HBcVpPT/w5D7NLwK3kCy7bU13g9qRY8QtSr4I045FkyfaTBb/rph9/qjBZAzeWDii4uyooMCwHSRYyiEnNkxaejiQF0pXBgTmoD+RQDDXJItF+4hygnoxknFr8u3wbU5keMi1SG4WhKiggEK9yzJHhkYoIHvWXnhx7XG3bgoFad8ach94epgeAPJttfWeD+oFT1CFMqgv3HKCWD6BqVYe/j06xt3N1us6CbIT/PMjdPmjUoH81OtDtsBUznkZMemoYv9techJ1YbFKXRo38RwDCXQu374Q4uFMIAdLO15lC1tR4uCIS/NX4WriKNWvHWbxb9cvnqgtIaXJRGrbj9utHwPd8adn5W9iMuSiD8i0PuTQ9IhDcQbbvtjQ+CWtEzgjLwb7xqJpi+caG28U9rtucVl0POnGFpLyyYEazTgulmZ2WxQxLRTYjab2RoLDqVtzUY2hohZ2xoIvodAQxzcWIZRCPcQFSTAIKfkqj0dfk2uDY3anyEOhhXl06revuZxQ//+evzFXVwbencUYEBGviYtcbdH5xfi4siII+n3TImOB3eQLRttzc+DGpDz/DKwDd4dTaYPmB1OP+989CH2w85RBHdhAX4vbBg5qyhA8C4kGMogpysmAE8Iei0z1QMFyaGp6DfEcAwF0Vt++Em5QR0s8102NheCxcEwt8al4VrQa9Tv/P04qVPf2xut0OOTqu6/brR8DE/Vue9X7wGl3J30vWzI8fBG4jWjfbGXwFO9AynDHyN18wH0wd2nilZvm6HsbEF3RCCeSPTn50/Xa9Vg3HBLok7q85DTnZMGrrYbyqBHI6QcaFJ6HcEMMzF2XPhHqKcgJ+SqPRV+Va4NidyXLg6GNeCwym+uXKHud0OF5bOHeXvp4Yv2VJ98O1zqygoLuqGqIm3xWfDG4jt6+xNTwIieoYo9H/gNYvB9Laqptbl63ZsP30echLDgn6/OHtMcgyYi8qtKTM7bOhGwysmRiaik0ilQ/UXICddHxWs8kO/I4BhLkai9gNwh5AEPgo/tbP2mMFiggsC4W+Jz8K1YHc4n3tnw77jJXDBX6u6de4o+JLdtcfeKvyKguKixocMeTT1ZngDp+UrR/MLgISeIQr9y4J2GZheJUrSl/tPrNi8v81mRzcqQbhvxpifzxirFHgwl7LVUAg5U6OTNbwCnU40GFodVsiZFJ6C/kgAw1yE4wykRriBKCfipyjoqvKtcG1WRGakOgRXndXufPrNdQdPlaHTpJFJZ0tM9c1t6HTb9aP9tSr4jJyag2+e+0qiEi5qWOCA5wffwxEOHs9p+czR/CJA0TNEoX9Z0C4D06uOXjD+8bvtRdV1kDM2Je53C2cmhQeDcQMFtlUWQU52TBq62F97Hi5MDEtBfySAYVyj9ly4STkRP7W79viFtiq4wBHulvgsXHXtVsdTb649cqYCneZPz3j2vlmlxvpH/vxNU2s7gACd+tY5o+AzNlTue69oNQXFRaUHJL489H4Vp4DHc5r/4Wj9C3qMU+pf4bW3guk9Le3Wv+XkfbnvuEQpugkL8Pv1dZPnjx4Mxm0n6iurLa3ohidkRnQKuthvOg85Gl45PDgW/ZEAhrkIey7cwhPlWHRBQb8sy4FrWeFjYjRhuLpaLbZf/+W7U8VV6LQoa9hT92RxhKTEhq547uZHXvmmxWy9/frRfholfMPXFds+KlmPS0nRxfwp4wENr4Kno47Wd5zmd9BjRKH/A6+9FUwvoRTrj57564bdjW3t6IYjZPHYoU/eMFWnVoLpiRxDIeSMDY8PUmnRqdVhPdVUCTljQxOVnID+SADDuEId1H4E7lAMAadHF/tqT5a2VcIFjnBL42fh6mpssTz26rdF5bXodOe8zEeWTkGn1PiwN59a+Lu/bbxl9kj4AAr6Ucn6byq241KS/KJfHfawTtDC04mO5t85LV+ix4hC/7KgXQaml1yobfzTmu15xeWQkx4T/uKirIy4SDA9t9VYCDmzYtLQRV5tiUglyJkQnox+SgDDuEAdR0Db4QainIAuKOhXFVvh2vSwkbHacFxF9c1tjy3/9ryhDp3uvDHzkVun4KeGDoha+ec7tWol+jsK+n7xmrXG3biUWG348mG/CFD4wcNRu73pV6L1B/QYp9S/wmtvBdMbrA7nv3ce+nD7IYcoohudWvXo7Am3TxzBcQRMz5W1NhY110HOrJhUdLG/tgQuTApLQT8lgGFcsefCTaqJ6CKv7lRRawVcICC3xs/CVVRd3/roK98YaprQ6cGbJ927YBzk6LQq9HdOKr5+9osdpiO4lFhN2OvDHw1SBsDDUYu98SHRths9xisDX+U1N4PpDTvPlCxft8PY2AI509KTX1yUFaHXgblcmw3nICc9MDxOF4gu9teeh5wIdUCyfxj6KQEM4wK17Yc7iIooRqKLL8pz4NrUsBGJflG4Wiprmx99ZXVlbTM6EIJfLZt+65xR8FVmp+VPZz451liIS4nShL42/JEgZQA8G5Wa7Y33SfYj6DFeGfg6r1kA5oqV1zf9Zf2unWdKICcxLOiFBTMnpMaDuTI5xkLImR07EF2UtzUY2hohZ1J4CvovAQwji7bCcQpuIIrRIGp0OlB/urC1HC4QkNsSsnG1lFU2PLp8dW2jGR04jjx3X/aN04bCV1W117146sNySw0uJU4b8eqwh0JVgfBsVKq1N9wlOc6ip4hCGbiCV88Bc2WsDue/dx76aMdhm9OJbhQ8f9eUUQ/PHq8SBDBXpt7adrzOCDmzYtPQxT7TebgwITwF/ZcAhpFD7QcAEe5QTUAXX5VvhWuTwoYl+UXjqigsq33stdVNLe3owHHktw/MuX7yYPiq082lfzj9UbPDjEsZoIt9Zdgv9AodPBt1nrc13ENFA3qKaJRB7/OqqWCuAKXYkl/4+obdVU2tkJOZEvviwqyk8GAwvWGrsUikFN1EawMGB0Wgi101hZDDETI+NAn9lwCGkWXLhXuIciI6HW4oONNSChcIyNK4WbgqzpbWPP7at81mKzooBP6Pj1w/PTMVvmpL9cF3Clc5qYhLGapPfnnoA36CGp5Nchy3N9xHpQb0FNGqgj7gVJPAXIEzRtPydTuOXaiEnFB/vyeunzx/9GAwvSfHWAg5s2MHEvxf7aL9YG0p5KTro4JVfui/BDCMHGrPgzu4ACgGo9OX5TlwbXzo0FT/OPS9E+eMT7y+pq3djg4KgX/lsXlTRqXAJ1HQzy5s/qzsR7hhRGDq74f+XMOr4NlE6xZ70+OgVvQQIf7K4I855Wgwl6vBbHnnx31rDp2WKEU3PMctnTDsl3Mm6tQqML3H4nTsr74AOdmxqehin+m8TXJCzpSIVPRrAhimO6kezmK4gSgnADw6HGssPNVcAtduj89G3ztaUPHkG2vbrQ500KgUf/n1TZlD4+GT7JLjzXNf7jAdhRsmhGY8n36XklPAszktnzqaXwZE9BDhgpXBn3CKDDCXRZSkL/efeG9Lrtlqg5zMlNjn5s9IiwoF09t2V523ik50E6BUZ4bFo4ud1YVwYUZkGvo1AQzTDbUfACjcoRyPTl+Ub4FrY4MHp/nHo4/tP1767Dvr7Q4nOui0qrd+szAjNRo+yWRtePnMx0WtFXDD7Mhxv067lSMcPBp1tL7jNL+DniN8hDL4U05IA3NZDhRXvPr9jqLqesiJ0Osenztp/ujBYPpGjqEQcmZGDxA4Dp0kSnfXFEFOmNp/SGA0+jUBDNOdPQ/uIcqJ6FDQcuFkUzFcWxqfjT625+j559/d4HCK6ODvp3776YVDUqLgkw7Wn/nL2c9anRZcCgFZEjfzZ8nzCAg8GXXYm58W29ei54iQogr+lPDRYHquuqn1nR/3rT9aADkqhbBs0sgHZ43TKhVg+oZI6c6qEsjJjk1DFycbDfU2M+RMi0gjIOjXBDBMN9SeB3dwYRCS0OHzss1wbUzwoCH6JPSlLbln//D+j6IooUNQgHbFs4sHxIfB90hU+rxsy+dlmykoLkXBCb9OW5oVMQaejUot9qaHJds+9BynyFAGf0K4YDA9ZHU4/73z0Ec7DtucTsiZlp78/IIZMUEBYPrSQVN5o82CbpQcPzUyGV3srC6ECzMi09DfCWCY/4dUC+cFuIEox6PDebPxcMNZuHZb/Gz0pXU78l/791aJUnQI0futeO7m5NgQ+J4mh/nVgk+PNRbCDXqF34tD7huqT4Zno2KFreE+6ixCz3HKcargf4HowPTQzjMlr6zbUdnYAjlJ4cHPzZ8+MS0BTN/baiyEnEmRSX4KJbrYUX0OctS8YnxYMvo7AQzzU9SWCzepxqPDl+VbKChcGBGYOlSfjD7z3dYTf/3PNkrxX5GhAe89d3NsRCB8z8mm4uUFnzbYW+CGRL+ol4feH6EOhmeT7EftjQ9QqR49x6uzlIHvgajB9ESB0bR83c6jF4yQE6BRP5w9/raJw3mOA3NVbDUWQU52bBq6MFqailtNkDM+LFnNK9DfCWCY/4f9ANxDlOMBVFhq9taehGu3JcxGn1m5/tDfVu1Bp+gw/XvP3xwdpoePoaBrjbs/PL9OpBLcMCZ40PPp9/gJang2sX2tvfkZUDt6jtfcrAxcDghg3NbY1v7Oj/u+O3hKohTdcBy5ZdywX86ZqNeqwVwtZxprKsxN6IYjJCsmFV1srz4LF2ZEpsEHCGCYn6L2PLiDjwIfB+Cr8q0UFC4MCkgYEZiKvrFy/aG/rdqDTonRwe89d3NokA4+ptlh/uvZzw81FMA9C2KmPpiygCMcPBp1mv/paP0LQNFzgt89ioDfARwY9zhEcVXuyfe25JqtNsgZkxz7/E0z0qJCwVxdOYZCyBkREhOm9kMXO6sLIYcAUyJS4QMEMExXYiXECriBKMcDMNkad5qOwrXb42ejD1CKFV/u+mLTEXRKSwx/9+nFgQEa+Ji8+tNvF37VaG+FGwTCPzRg0bzoSfBw1G5vfkZsX4vLwSv0Lwrau8C4h1JsyS98c9NeY0Mz5ITrdb+aO+nGUYMJAXP15RgLISc7Ng1dtDqsR+rLIGdoUEyEOgA+QADDdEHteXCTcjyAr8q3OqkIF5J1MWNDBqO3UYq3Ptvx9eZj6JSeFPH2M4v1OjV8Sbto++D8uk1V++GeUJX++fR7huiT4NmoZLI3/EJyHMNlIGpl4Nu8eg4Y95wsr/7rhl3HLlRCjkohLJs08sFZ47RKBZhrwdjWXNBYAznZManoYq+p2CGJkDM9ciB8gwCG6cqeB/cQ5dhGe8vW6oNwbWn8LAKCXiVJdPlHOet3nUKnEQNj3nhqoZ9GCV9ypqX0r2c/r2yvg3uGB6Y+l35nkDIAnk1ynLY3PkDFSvQc4fTKoA85ZSYYN5TVNb37474t+YWUQta09OTnb5oeE6wHc+3kGAspZAwICE0OCEEXO6sL4cKMiDT4BgEM0wW1H4Q7+DjwMd9cWGeTHHAhShM6JXQ4epUk0T9+sPmHvWfQaVR63BtPLtCoFfAZdsmx8sKPqw07JCrBDQRkSdzMe5Nu4AgHzya2r7M3PwtqRc8RPlYV/AkRUsBcSrPF+o+teatyTzpEEXLSY8J/M2/q2JQ4MNdajqEIcmbFpqILkUp7TEWQE6XRp+kj4BsEMMz/EsshVsINRDm+1WnZVLUfrt0en80RDr3H4RR/97dNOw8VodOkEcnLH5+nVAjwGaVtVX89+9l5sxHu0Sv8nh5055jgQfB0oqP1daf5fVwWThioDP6E8JFgLsruFL/Yf/yDbQdb2q2QE6HXPTZ30o2j0jlCwFxrTfb2g6ZyyMmOSUMXebUlzfZ2yJkeOZCAwDcIYJhO1JYHNynHrTHsahdtcCFMFTgzYgx6j8MhPr9iw56j59Epa1zaHx6+XuA5+AYnFb8u3/Z52WYnFeGeofrk5wffHaLUw7NRqdHe9EvJtg+XhVdNUwb9DcQPjGsSpTn5RW9t2mtoaIYcjVJx+8QRD2SN9VMpwXiGHZXnRSqhm1C13/CQaHSxufIMXJgRmQafIYBh/pc9D+5p50esM74P126JnyUQHr2k3eZ4+q11h06Vo9OciYNefHAuz3PwDUWtFW8Xrio2G+AeAnJTzJT7U24SCA/PJjnO2hsfpGI5LougvU2hfxkQwLiWW1T+5qY9BUYT5HCE3DBy0BPXTwkL8APjSXIMhZAzOzaNIwSdnJK4reos5Pgr1JmhifAZAhimE7UfhDuEpPXVhWanBS4EKf3nRI5DLzFbbL/+65r8okp0WjBz2NP3ZnGEwAe0Oa3/Ll2/sXI/BYV7gpT+T6TdNjZkMDye2L7B3vwMqAWXg1cEvCj43QXGtVMVNW/9sOdAcQVcmJAa/9S8qQOjwsB4GLsk7qkugZxZsWnoIq+utMlugZyZkQOVnACfIYBh/stZAskENziEcWuNu+Ha4tgZKk6B3tDaZn38L9+dOV+NTotnDX/q7ixC4Avy6k+vKPqmztYEt40NHvzrgUuDlQHwdE5H6xtO8/u4PESrDHyXV2eBcaGysWXF5v0bjhVQClnJ4cFP3jBlWnoyGI+0t6q0zWFHN1pBOSE8AV1sNp6GC3Oih8CXCGCYDtSeB/f80BTdYD8LF/wF7bzoSegNDc2Wx177tri8Fp3uvDHzkVunwAfU2Zr/XvztvrqTcJuWV9+fMv/6qInweFSstjc9KtmP4LIQPlIZ9C9OMQSMnHqz5R85easP5jtFCXIi9LpHZ0+8afRgjiNgPFWOsRByZkSnqHgBnZySuK36LOT4K9QTwpPhSwQwzH/ZD8ANTsp9W1MN1xbETtXwKlyxuqa2x15dXWKoR6efL5rw80UT0N+JVPq+cs9/Sje1iza4bYg+6TcD74jShMLjSfZce+NjVKrDZeEUI5XBHxAuFEw3Zqvt411HVu45arE7IMdfo/r5jMxlk0aqFAIYDyZRut1YBDnZsWnoIre2pNneDjlZUYOUnABfIoBh/j+U2g/BDdvbRpmsTXBBw6tuipmKK1Zd1/LI8tXGmiZ0IASP3T7ttutGo7/Lbz7/j+LvzpuNcJuKU9ybPG9BzFQCAk8nOc0rHK3vAhIuC6+Zr9T/BUQF5qesDufqA/kfbD/YYLZAjoLnF4wZ/Ms5E4N1WjAe71idsdbahm4EjpsWlYIuNleegQtzoofAxwhgmP/hLIJUh0vO9CNuAAAgAElEQVShIN/WRwEiXJgXPclf0OLKlFc3PvrKalNDKzoQgifunLFk9kj0a3W2pn+Xbtxec5iCwm1JftHPpC9L8ouGx6NSo6Pp16JtFy4TEXSPKfwfBwiYLpyitObw6X/k5JlazJDDEZKdkfrr6yfHBuvBeIkcYyHkjAtP0CvV6OSUxO3VZyHHX6GeEJYMHyOAYQBqz4Mbcs0R5VYRLig5xcLYabgyFyobHl2+uq7RjA4cR57/+ex5U4eg/7KK9q/Kc74z7LRJDrhNwQm3xWcvjc/mCQePJ9kP2Zsep2IVLgvhAhSB7/Cq6WC6kCjNyS96+4d9FfVNcGFCavyTN0wdFB0GxqtsNRZBTnZMKrrYV3u+2d4OObOi0hUcDx8jgGH+hz0PbljdkAzX5kaOC1HqcQUKL5gee+3bptZ2dOB57ncPzJk7KR39FAXdU3viw5LvTdYG9MRQffLjabfEayPhBUSn+UNH6xuAE5eFCEmqoA+IMABMJ0qxJb/wvS25paYGuJARF/nE9VMyU2LBeJvilrqSlnp0Q4Ds2DR0sdl4Bi7MiR4M3yOAYSBR+2FcyklLSEF7IFwQCL8kbiauQEFpzeOvfdtitqKDQuD/+OgN08cMQD9V2Frx/vnvTjeXoid0gmZZ4twFMVMJCDweFavtTY9L9oO4XLxqhiLwbcIFgOm0u6B0xZb9BUYTXEiNDHl0zqSZg1MIAeONcgyFkDMkODJKG4BOTkncWXMOcgIUmvFhyfA9AhjGcRZSEy7l64ZkuDY9fFS4OhiX69hZw5Ovr7VY7eigVgqv/fqmcRkJ6I9qrA2flG7cYTpKQdETM8NHPzhgYaBCB28gWnMczc9QqRGXiQi6BxX+vwE4MB1yi8pXbN53srwaLkQHBdw/c+zizKEcR8B4rRxDIeRkx6Shi32m8832dsiZFTVIwfHwPQIYn0ftebiUUpv/0bYwuEBAlsTNxOXKO3nhmbe/t9md6KBRKf765E1jBsej32l2tK2u2L7WuNsuOdATUeqQR1OXjAkeBK9AbY7WV5xtKwGKy0O0ysDXefV1YDocvWB898f9h0sMcCFCr7t32phbxg9TCjwYb1bTbj5RXwk5s2PT0MXmytNwYU7MEPgkAQxjP4BL+bohhcKlsSGDE/2icFn2Hit5/t0NdocTHfy1qjd/sygjNQr9S7toW1+598uyHItoRU/whLsxevK9SfPUvBLeQHIWOpp+JTkKcLmIkKoK+jsRBoABjl4wvrc59+D5CrgQqFXfO33MskkjVQoBjPfbaiykkBHrpx8YGI5Odsm5vfoc5OiVmvGhSfBJAhhfJ1LHEVxUtUOzpzUKrt0Sl4XLsu1A4Ut/3+QUJXTw91O/8/SiwSmR6EfskmN95b5V5TnNjjb00IjA1IcGLEr0i4J3oE7LV46WP4K243LxmvlK/XIQLXze0QvG9zbnHjxfARe0SsVtE0fcPzNTp1aB6S+2GgohZ07cIHSxu6ao1WGFnOyodIHj4ZMEMD7OcRZSCy7q24ZkkRK4MCggYag+GT23ef/Zl//5oyhK6BCs16549uaUuFD0FxR0T+2Jf5esr7LWo4fCVIH3JN0wKyITXoKKRnvTbyR7Li4fr/B/StD9Aj7v4PmKv+fkHi4xwgU/lfL2SSPumTpar1WD6UcsTnueqRxysmNS0cXa8uNwYU70EPgqAYxvo/ZDuKgmUZXTHAvXboufjZ5bs/3kXz/eJlGKDhEh/u89d3NcZBD6BQq6y3Ts87LN5ZYa9JCGV92eMHthzDQFJ8BLiNZNjubnqNSCy0X4KGXQ3zjFSPi2/YVlH2w/cLjECBe0SsXtk0bcPXV0kJ8GTL+zo/K8TXSimyCVZnRYLDo12Nr2mIohJ1CpHRuaCF8lgPFx9oO4qO8bE2yUhwtx2ohxIYPRQ6tzjr/x6XZK8V9RYQHvPXtzTEQgvB8F3VN7YuWFH8otNeghAjIzYsz9yTcGKQPgJahU72h+TrTm4ApwyonKoHcJFwJfRSl2FZR8sP3AyfJquKBRKhaNHXr/jMxQfz8w/VSOoRBysmJSecKh0wbDSackQs71MUMFjoevEsD4NEodh+GaVeI3NiXAtVvjswgIemLl+kN/W7UHnRKiglY8d3N4sD+8nJOKO01HvyzPMVhM6LmB/vEPDViUHpAI7yFaf3A0v0ClRlw+XuH/uKB7BODgkyRKdxeU/n1r3hlDDVxQK4TF4zJ+Pj0zLMAPTP/llKRdVechZ1ZMGrpYW3ECLiyIHwEfJoDxZc5CSE1wbVNzfIuogAuhqsAZ4aPREx9+u/+jNXnolBQTsuLZxaFBOngzJxW3VB9YVb6t2lqPngtXB/88+capYSMICLwEleocLa+I7WtwBQgfpQx8m1OOhU9yitKm42c/3HGo1NQAF5QCf9PowQ9nTwgL8APT3+WZyprtVnSj5oXJkUnoVNhSc665GnJS/MOGBEbDhwlgfBi1H4RrTkrWNSTCtcWx0wXCwz2U4t0vdn35wxF0GpgY/s4ziwP9NfBaTiruNB39rGxzVXsdei5A4bckbuaCmKlKTgHvIVo3OZp/S6VGXAFena3Qv0a4IPgeu1Nce/j0RzsOGRtb4IJKISwZl/HzGZmh/n5gfEOOoRBypkQlawUFOq0pPwYXFsSPgG8TwPgy+yG4tqMlxuTUwAV/QXtd1AS4h1K8+en2b3KOo9Pg5Mi3n14UoFPDO1lE6+bqA6srdtTZmtBzGl51Y/TkpfHZfoIa3oOKBnvz85JtD64EUSn8nxH87gEIfEybzf7NgfxPdx81tZjhgp9KeeuEYXdPHR2i04LxGRTYaiyCnOyYNHQSqbTRcApyeMLdEJMB3yaA8V2U2g/DBQp825gE1+bHTNHwKrhBkuif/7Vl4+7T6DRyUOwbTy3QqpXwQiZrw/rKfZuq9pud7eg5gfCzI8fdlXhdkNIf3oQ6LV85Wv4EasEVIEKKMvBdTjEYPqaxrf3L/cc/33e82WKFCzq18tbxw382fYxeqwbjY041VFVZWtANT8jMmAHotKumsN5mhpyJ4SkRmgD4NgGMz3KWQKqDCwdaI8ps/nBBxSlvipkCNzhF6cW/bdp+sBCdxg9LfO1X81VKAd6mxGxcbdi5y3TUSUX0HAGZEjb8Z8k3RqlD4FUkZ6Gj6VnJcQxXRtDeqgh4CUQDX2JsaP5077HVB/JtDidcCPLT3DZx+J2TR/lrVGB8Uo6hEHJGh8UFq7TotK78BFy4KW44fJ4AxldR+0G49k1jMlybEzlWr9DhUhxO8bcrNu46UoxOk0cmv/LYPKVCgPegoEcazq02bD/WWIjLQkAmhmbck3R9vDYS3oVaHK1vO9s+Bpy4AoQLUuj/zKuvgy85W1n7n91HNh0/J0oSXAjRae+aOuqOSSPVCgGMD9tiKISc7JhUdGqyW3bXFEGOv0I9I3IgfJ4AxmfZD8KF/PbgM+1BcIEj3KLY6bgUq935zFvrDuSXodOs8QN//9B1As/BS9gkxw7TkbWGXaVtVbgsBGRS2LA74mcn62LgbUTrNkfLi1SsxJXhVVMV+tcIHwmfcfSC8aMdh3efLaEUrkQHBdw1ZdSS8RkqQQDj2wxtzYXNtZCTFZOKThsN+XbJCTnXxwxV8wr4PAGMr6L2Q3Dhm/oUuDYtbGSUJhQX1W5z/OaNdYfPlKPT3Enpv3tgDs9z8AZ1tuYfqnLXV+5pdrThshCQsSGD70q8boAuFt6GOsscLS+Jtl24QkSj8P+N4HcPQOADnKL048nC/+w+UmA0wbWBUWH3Th9z3fA0nuPAMMAWwznISdOHJfoHo9O6ihNw4ab4EWAAAYxvEi9AMkFOqc3/cFsYXLs5bgYuqtVi+/VfvjtVXIVOi7KGPXVPFkcIPN6p5pJ1xt376k6KVMJlISBTwobflXhdnDYCXodaHeb3nW3/ALXjynDKUUr9G0RIhA8wW21rD5/5ZPeR6qZWuDYyMfq+6ZnT0pMJAcP8r80V5yBndmwaOhW3mk43VUJOoi5kWFAMGEAA45Oo/RBcWN2QTOHSmOD0AbpYuNZitv7qL9+dKalGpztuGPPo0qmEwJO1i7YdpiPrjHsutFXhcgmEnxY+6vaE2bGaMHgh0fqDo+XPVDTiChGVwv9Jwe8+gEN/V1Hf9Nm+498dPNVud8AFjpApg5IemDl2eEIUGOanGmyWo3UGyJkVk4ZOa8qPw4UF8SMICBhAAOOb7Achp9ap2d0aDddujcuCaw3Nll++uvp8RR063Xlj5iO3ToEHKzEbf6jK3Vpz2CJacblUnCI7cuwtcVkR6mB4Iclx0tHyJ8l+CFeMUwxVBL7BCWno745eMH6+93jOqSJJonBBwfNzh6fdP3NscngwGEZOjqFQpBTdRGr8M0Ki0MEpiRsqTkIOR8j82OFgOghgfBK1H4Kc1Q3JTkrgQpp//LDAAXChur71l8tXV1Q3otMDN0/82YLx8Eh2yZFXf3pT1f5jjYW4AnqF35zI8Qtip4Yo9fBCVKx2mt91WlYBEq4QUQl+v1DoHgFRoP9yiOL20+c/2XUkv6IarvmplAsyh9w3bUy4XgeGcW2LoRByZscNJPj/bas+W2czQ874sOQITQCYDgIYHyQaIFaim1ZJkdMcC9eWxs+CC1W1LY8u/8ZoakYHQvD4HdOXzh0Fz1PWVr215tCmqlyz04IrEKkOWRA79fqoCSpOCW9E251t/3GYV4BacMU45Ril/lUipKD/qm1p++bAya/z8uta2+BaTLD+jkkjFmUO1amVYJiLsjjt+2suQM7s2DR0+vrCEbiwIG4EmE4CGN9D7QchZ11DYrvEw4VYbfjE0AzIKatqfPSVb2obzehACJ68a+bN2SPgSdpF2w7TkU1VuUWtFbgyA3SxC2OnzQgfzRMOXkkSLasdrW9QyYQrR3SKgGcE7R0AQT91xlCzcu+xH06cc4oSXBscG7Fs0ogbRg7iOQ4M44adledtohPdBCjVY8Pi0eGCuf5AbQnk+CvUWVGDwHQSwPgg+0F0Y6P8hqYEuLYkbiYBQTelxvpfLl9d19SGDhxHXrh/zg1TBsMzUNDjjUU5NYf21Z2winZcAQIyLmTwkrisofpkeCtJtO5wmt+UHGfQG3jVdIX+z4SPRn9kd4o/njj36Z6jZytr4RpHyJRBSffPzByREA2G6YkthkLImRWTKnAcOnxTdoRC3vy44WpeAaaTAMb3UPtBdPNDU1yzqIQLQcqAmeGj0c3Z0prHX/u22WxFB4XA/+Hh62aOTYMHMFhMO0xHt9YcqrbW48poefX08FELY6fGayPhrSSxfYPDvII6i9EbCBekCHiR1yxAf1RR37T6wKlvD+Y3WaxwTadW3jRmyN1TRkUHBYBhesgpSbuqzkNOdmwaOtgl5/cVJ+DCkoTRYLoQwPR3DoejpqbGbrc3NzdLkiRwDRlRBvyUk5I1jUlw7ebY6UpOgZ86cc74xOtr2trt6KAQ+D//ct7U0Sm4ptqc1tz6/K01h443FlFQXJlYTdi8mMlzI8dreBW8lSRadzjNb0qOM+gdhNcsUAT8lnDB6F8kSg8UV6w+kJ9zqkiSKFyLDdYvGZ9xy7hh/hoVGOay7K+50Gy3ohs1L0yJTEaHzcYzDbY2yBkdkpAaEA6mCwFMPyKKYkFBwalTp/Lz8wsKCkpKSqqrq00mE6UUXUSG82NGqCdlarKmakcOVXEczloDG5xquOAnqK+PnoifOlZgePKNtRarHR3USuEvT9w0dmgCrhGH5DzUULDDdCS3/pRDcuLKcISbEDJ0fsyUEYGp8GKS2L7RYV5BnUXoJZwiQ6H/I6cYjv6ltqVt7eHT3x48ZWhohmuEYGJqwu2TRkwZlMQRAoa5AjmGQsiZEpWsFRTo8HXZYbiwJGE0mJ8SwHi/Y8eObd26ddeuXXv37m1ubsalVJvEDVvaNmxpw58R4M9ljlTPmtL4y/H1VfEDNzQnmiUFfurG6MlaXo0uck+UPvvOepvdiQ4ateL1JxaMHhyHq46Cnm4u3VN7fIfpSLOjDVdMJ2hmRWQuip0eoQ6G96JmZ/t6Z9tH1HkevYRwAYLuV4LfXQCP/kKi9EBxxeoD+dtOFztFCa7p1Mrrhg+8Y/LIAREhYJgrRoFtlUWQkx2Thg5FLaaj9eWQE6jUzo4ZDOanBDBeKzc3d/Xq1WvWrCktLcXlammVtu22bNttAer8tKXjJ/unLBhaN2iImdPgv0TauqO8Qd8QHByMDnuPljz37nqHU0QHf63qracXDR0QhavrbEvZTtPRXbXHGuwtuGIEJCMw5fqoCZNChyk5BbwWdZ53tv3H2f4tqAW9hvCaxYqAZwkXgv6itqXt+6Nnvs7LNzY046ISw4KWThi+aOxQrVIBhuklx+uM1ZZWdMMTkhUzAB1WluTBhYXxI1ScAOanBDDepqWl5bPPPnv//ffz8/Mhx9/ff/DgwRkZGampqdHR0TExMZGRkVqtNiAggBCi0WgsFovdbm9ra2toaKiqqjIYDBUVFadPnz516tSOrRe2bdnHKfKistISlo7WJYZUbDz1+JvvPvPIk7fccssvfvELM4J///4PoiihQ1CA9t1nF6fGh+FqOW827qk9vtN0tMpaj96gV+iyI8deFzk+VhsOLyaJtp3Otk8k216AovdwinRFwMuccgz6BYnSA8UVqw/kbztd7BQluMYRMmVQ0rLJI8cPiCcEDNO7coyFkDM2PD5IpQXQ4mjfaMiHHALcnDAaTDcCGO9RX1//1ltvrVixoqWlBT8VGRmZlZU1tcPAgQMJIXBNpVKhQ3JyMn7KbDbv379/9+7du3btyrv/q6DMeHNpHQCr1frpp5+uyzkwaMb9IAQdQoN07z13c2J0MPpeWVv17trjO2uPGiwm9JJU/7jroyZkRWSqOAW8FpUaxPa1TstK6ryAXkW4UMH/SUG7BODh/YwNzeuOnPnu0OnqplZcVKi/3+KxQ28ZPyxCrwPD9I0thkLIyY5NQ4fVZUetogNyxoclJ+pCwHQjgPEG7e3tr7766ltvvdXa2oouEhMTlyxZsnDhwnHjxnEchyum0+lmdwBQX1///fffr1mz5scff3Q4HABaaoqbKs8GxqQDCNIp3//tLbERgegzFPRsS9me2hN7607UWBvQS4KUAbMjx86NHB+tCYX3onbRtkds/060bgGc6F1EIWjvEPyfIMQfXs7mcO4sKFl9ID+vuJxSXARHyLgBcTePy8gaMkDgOTBMnylqritpqYecrOhUACKVVpUehgvLkseBkSOA8XgbNmx47LHHSktL0YnjuJkzZz7wwAOLFi3ieR59IyQk5N4ONTU1n3zyyT//+c/S0tKiPf8ZOOPnKr/gnd+//7zl4Ouvvx4eHo5eJVLpZFNxbv2pfXUn62xN6CVKTjE+ZGh2RObo4EE84eC1JEe+2P6d2P49lRrQB3jVTIX+94SPg5c7Y6j55kD+puPn2mx2XFSov99NowcvGZ8RG6wHw/S9HEMh5AwNiozTBQLYUX3OYGmEnBht4JSIVDByBDAerLW19eGHH/7ss8/QSRCEZcuWvfDCCwMGDMDVEhER8cwzzzz11FNffPHFn/70p8Kd/+YUKkd7y8qVK3/44YdPPvnkhhtuwBWzSfZjjUUH6k/vrzvZ5DCj96T6x2VFjJkZPkav8IPXomKZ2L7e2f4ddZaib3DKUYqA33KKkfBm1U2tG4+fXX3gVEV9Ey6KI2TcgLibx2VkDRkg8BwY5mrZYjgHOdmxaejweclBuHBH8jiecGDkCGA81ZEjR5YuXVpcXIxON9100xtvvJGSkoJrgef5O++88/bbb//000+fffZZU3sLgLq6uhtvvPFXv/rVq6++qlQq0XMN9pbc+lO5dfnHm4ockhO9J1wVlBUxZlbk2FhNGLyW5DgjWjdLti2S4yz6DBGSFLoneM0NAIF3MlvtW08VrT185kipgVJcXLhetzhz6KKxQ6MC/cEwV1d1e2t+QxXkzIkbCKCoxXSorhRyNLxyYfwIMC4IYDzS999/f9ttt1ksFnRISEhYsWLFjTfeiGuN5/l77713wYIFL7zwwvvvv087vPXWW/n5+d9++21AQADcIFKpoOXCoYYzhxvOnjcbKSh6j07QTg4dNiNi9PDAAQQEXkmS7EdF2zbRupk6S9GXCB8n6B4StEsAAV7I5nTuOXth07GzuwpKbU4nLkrB89PSkxaMGTJ1UBLHETDMtbCl4hyFjHhdUJo+DMB/zudSyJsfNyxAoQHjggDG83z44YcPPfSQKIrocMstt3zwwQd6vR4eIygo6O9///v8+fPvvvtuk8kEYOvWrdOnT9+0aVNkZCRcaHKYTzYV59WfPlB/2uy0oFcpOcXIoLSpYSOmhA1XcUp4ISo1S/Zc0bZTsuZQqQF9jAiJCt1jvGY+wMPbSJQeL6vcfLJo07GzjW3tuJSUiJD5o9MXjhkSrNOCYa6pLYZCyJkTmwag3mbeZMiHC0uTMsG4JoDxMJ9++umDDz5IKQUgCMK777770EMPwSPNnTv3xIkTCxcuzMvLA3Ds2LE5c+bs2rUrMDAQnSQqnTcb8+pPH2g4XdxqoKDoVRzhhgcOmBWROSl0mIZXwfs4JUeBZNsn2vdKtgOAE32P8HGC7iFBuwQQ4G2Ka+rXHyn4/uiZ2pY2XIpeq56dkbpk/LDBMeFgGA/QYrcerC2HnNmxAwGsPH/AJjkhZ3xYclpABBjXBDCeZOPGjffddx+lFIBWq121atW8efPgwSIjI7dt27Z06dL169cDOHny5Pz58zdv3tzG2Q41nD3cWHCs8Vyb04rexhNuWOCAKWEjpoQOD1D4wctQyVko2fZItn2i/SCoBVcLERIVul/ympsAHl6lsKrux5OFm46dNTQ041IUPD8tPWnBmCGTByYKPAeG8RjbKoudkoRuQtV+I0JjrKLjm7IjcOGu5PFgLkoA4zFKSkpuv/12p9MJQK1Wb9q0adq0afB4Wq32u+++W7Jkydq1awHs2bPnZ+8/1TBKgT4gEH5EUNqUsOETQjL0Cj94EdouOU5LjnzJfliy51KpEVcXpxwj+N3Lq+cAPLzHGUPNlvyinPyisromuCEjLnLeyEHXjxwU5KcBw3ieLYZzkJMdm8YT8mXZ0Sa7BXKSdKFTIlLBXJQAxjM4nc5ly5a1tLQA4Hn+s88+mzZtGryEIAirVq2aN29eTk4OgC0rvx8zajF6j4IThuqTx4UMmRE+OlChg5egYo3kOCU5Dkv2w5LjJKgdVx9R8errBd2DnDAQ3qO4pn7LycKNx86W1TXBDcnhwXOHp10/YlBiWBAYxlNZReeeqhLIyY5NE6n0WckBuHDPgAkcIWAuSgDjGd58883c3Fx0eOmllxYvXgyvolQqv/jiixEjRhiNxqZTVZJN5FQ8royWV48JTp8YmjEuZLCWV8PjUbFGcpySHPnUkS85TlHJhGuH8BG8ZqngdzfhguANJEqPl1VuPlm0Nb+optkMN4TrddkZqXOGpY5KjAHDeLw9VSUWpwPdaAXlhPCEnMqCirYGyAlW+c2LHQbmUgQwHqCurm758uXoMHXq1Oeffx5eKDQ0dOXKlbNmzZIcYuNJQ0hmAi6LXqEbE5w+NWzE6KCBCk6Ap6K0lTpLJEcBdZyRnGckRwGoBdce4ZQTBL+7eXUWwMPj2RzOA8UVOwtKtp0qrjdb4IZArXr2sLTrRwwalRTNEQKG8RI5xkLImRk9QMULHxfvhwt3JI1V8wowlyKA8QDLly9vamoCIAjC+++/z/M8vNOMGTPuuuuuTz75pP5weUhmAnoiwS9yQsjQiaHD0vzjCAg8DJWaqbNIchZRsZw6CiVnMRUrAAqPQfhoXjNf0C4lfAI8nqnZvOts6a6CkryicqvDCTfo1Krpg5OvHz5wYlqCwHNgGK8iUrrNWAw52bFp+03nTzUZIUfNK25NygTjBgHMtWa1Wj/++GN0uO+++9LT0+HN/vjHP65atar+cDncoOKUg/WJo4IGTggZGqeNgAegtJU6DVQ0UNFARQMVDVQ0SM5S0HZ4JMLpefU8XrOQU46Gxyuuqd9VULLzTMnxskpK4Y4AjXpaetKcYWkT0xKUAg+G8U6HassbbRZ0I3DctKjkxw59BRcWxo8MUmrBuEEAc62tWbOmsbERACHkqaeegpeLjY1dunTpx598bGuwqIK1kBOlDhkZNHBcyJDRQQMVnICrjVKpjoq1VKqGWEelGirWUamKipVUNFCpGd5B4NXTeM1iXpUFooQHs9gduUXluwpKdheU1rW2wT0hOm3W0AHZGaljU2J5jgPDeLkcQyHkTI5IKjHXHqq7ADk84e5MGQfGPQKYa23t2rXoMHXq1AEDBsD73XfffR9//HHD0YqoWQPRScUpB+sTx4UMmRSSEa4ORl+gFkrbIFkobaRSE6QmKjVRqQm0kUrNkBqp1EilWirWAiK8FFHwyomceg6vnkO4YHgqSaJnK025xeV5ReVHSo12pwj3BPlpJg9MnDMsbcqgRJ7jwDD9xVZjEeRkx6Z9ULgHLsyOHpzgFwLGPQKYa23//v3osGDBAvSBf/3rXyaTadmyZfHx8QByc3P/8Y9//P73v09OTkbfmDhxYnh4eMOR8oUL/Meq62IDIsJVocHqII60Anlw5DmdfoCA/yICiB+6om2gTvxfNkqtoCKoGQClraASqJXCBqmVUgtoG6iFSs3ox4gfr5rGq+dw6hmE+MNTGRua9xWW5RaVHyiuaGm3wm0DIkKmpSfPHJIyLD6KEDBMP3OqsbrC3IRuOEIS/fV/Pl0IF36WOgmM2wQw15ShAzpMnDgRfaCpqamurs7hcKBDe3t7ZWWlw+FAnyGETJgwYePWHwJ3NMy8Qw2UQoTUBglMzxAuiFNN59WzeNV0EC08Umu77eD5iv1F5bmFZeX1TXCbUuDHJMdOS0+enp4UE6wHw/RfOSbKUrsAACAASURBVIZCyBkREvNtxVEKedMi0wbro8C4TQBzTRkMBnTKyMhAf5GRkbFu3TpBdABqMD3Dc8qRnHISr5rMKUcCPDyP2WrPr6jOKyo/esGYX1HtFCW4LchPMzYlblp60swhKTq1CgzjA7YYCiEnMzz287K9cOGB1ClgekIAc03V1dWhg5+fn0ajQd9wOp0Wi8VsNgOwWq2SJKHTxo0bHQ7HggUL0KtCQ0MBqFQEjHsIH8+rJnGqyZxyMuEC4HlMzeZDJYYjpcYjpcYSUz2lcB8hGBQdPnVQ0rT05KFxERwhYBifYWhrPtdkgpzydpNIJcjJDE0cERwHpicEMNeU2WxGBz8/P/SZDRs2/PDDDwqFAoDFYlEoFOj0wgsvNDU1LViwAL3K398fgFpNwLhG+ChOOY5XTeKUkwkfCQ9DKS7UNhwvrzpSYjxcYjA0NKOHwgN0E1LjJ6QlTEiND9FpwTA+6ceKs5CT6B+8x1QIFx5ImwKmhwQw11RQUBA6NDY2UkoJIegDc+fOvfvuuxMSEgDs27dvxYoV6PTBBx84nU70toaGBgAaNQHzEzwRknnlGE45hlNmEj4OHqa13XbKUHPsgvG0wXSyvKqxrR09pFIIoxKjx6fGTxgQnx4TQQgYxsdtMRRCjloB0SpBTro+akJYMpgeEsBcUyEhIejgcDiam5sDAwPRB9RqdWhoaGRkJICgoCBBENBp7Nix6AMmkwmASkng8wgXzClHcopRnHIMp8gA0cCTOEWpsKr26IXK04aaM0ZTiameUlyGlIiQ6enJ41PjRyVFqwQBDMN0qLe2HaszQE5ZuwkEsh4aOI2AgOkhAcw1lZycTAihlAI4cuRIVlYW+oUjR45oIuO/M2aX5rZFBrRGBrRE+rdG+rcqeRH9HeHCOcVQosjgFGlEGMAJqQCBx6hpNhdW1RVV1xVW1xVV1RXX1IuShJ7jOW5wTPjopJjRyTGjEmP0WjUYhukmx1gkUopu1IIAYoecdH3UzKiBYHpOAHNNBQcHDxo0qKCgAMDevXuzsrLQ29LT06OionQ6HTpERkZmZWUFBASgzzgcjoMHD2oGDDtcO+RwLf4XITTEzxLl3xLpb44KaIkKaI30b4nWt0b4t/gpHfBSRMsJKUQYyCkGc4rBRDGYEH94jHqzpayusbi6vrCqrrimrrCqvqXdisulFPiMuMgxybGjk2JGJEZrlQowDHNRWwznIEeEXYC8RwdNJyBgek4Ac61Nnjy5oKAAwNdff/3SSy+ht91www3oYnAH9KUNGzaYzeYIfQh+ilJSZ/arM/vlV+H/4ad0hOtag/0s4X7mYL/2cJ05SNseoWsN1lrCdGY/pQOegXB6IqRyQirh44mQyilSCR8LcPAApmZzeX1TeV1TRX1zeX1TeX1T+f9hDz7goyrQvmH/T5mWSa+TMukdQugd6R1EBQssVrBg12cVxbIWBHVdCysqKoKigAVREanSpXcS0kid9D7J9HLO68fz4/30zUxISEImyX1d1fV6swVt4y6X9gkPHhAVOiAqLCU8SMbzIIS0jMFmOVJRCEcYToAjvbxDRqviQa4JD9LZ7rjjjs8++wzAxYsXjxw5MmzYMHRxq1evBiD19kOL6S2S/Frf/FpfOCLnrYHuej+lwV+p91Pq/d31PgqTp9zkKTN5yY2eCrOn3CTj7GhHjILl1AwXxnBhDB/KcGEMp2b5aDBKdB5BFGsaDZUNusoGXVl9Y5VWX65trNDqKht0ZfWNZqsN7YHn2PjggBS1qk+4KkWtigzwYRkGhJDW21uaa7bb0AQDcJwARx5NHMuAAbkmPEhnGzt2bExMTG5uLoDXXntt27Zt6MpOnDjx22+/AZB6+6GdmGySonrvonpvOCfnrZ5ys6fc5KUwecpMXgqzl8zkpTB6ys1ecpOn3OQmsXrIzQqJVcZblVIrAIbxABfEsAEMF8SwAQwXxHDBDBfGcGEM64vryGKzGyxWncmsM1m0BlOtzlBnMNbrTfV6Y53BWKsz1OmN9XpTrd5gswvoAGG+Xn3CVSlqVUq4KikkUCbhQQhps53F2XCE4+1wpJd3yKigWJBrxYN0NoZhHn300aeeegrA9u3bd+/ePWHCBHRZixcvFkURgF2TPWu8sVwrK2vwKG/0sNg5dCSTTWLSSSp17mgZd7nMTSqRS3h3hUzO8zIJJ+V5uUSU8KUKSSXPsW5SKcexSpkEV8h4Xibh0QJWu91osQJoNJpFESar1WKz2wTBYLYCaDSZDWarwWIxmK0NRrPBYrHZBVxHEo6LDvSNU/nFBfvHqwJ6q4N8lAoQQtqVTRD2l+XCEZYT4ciTSeMZMCDXigdxAQ8//PDKlSsvXboE4IEHHjhz5oyXlxe6oE8++WTv3r247Nk5U++/2SIKBoiNQG1VI1vWwJbV28obmFItX6aVlmm5Mq1Eb2HRGXQms85kRg/AMkywt0esyj9e5R8f7B+r8osK8OU5FoSQjvRHRUGDxYQmGIBlRTTR11c9PDAGpA14EBcglUqXLVt22223AcjPz1+0aNH69evR1aSlpT399NO4LDk5eeHChbxEgitCvBACBxqMpvJ6Xbm2sVZnqNDqahoNFQ26mkZDZYOuptFgttlAWoxlmRBvT7Wfd7i/d7ifV7i/d7ift9rPW8pzIIRcX7uKs+AIywkMI6KJJ5PGg7QND+Iabr311vnz53/99dcANmzYEB8f/8orr6DrKC0tnTlzptFoBCCTyb7++muJRIIW8FTIPRXy+GB/OKI1mKoa9VUN+upGfVWDvrJBV91oqG7UaQ0mrcGsNZjMNht6Hh+lItDTXeXtEeTlHuCpVHl7BHq6h/p4hvp6SjgOhJDOJoji7pIcOMJxApq4IShukH8kSNvwIC5j5cqVR44cyc3NBfDqq6/6+fk99thj6AqqqqomT55cUFCAy956661+/fqhPXi5yb3c5LFBfnDCZLVpDSatwaQ1mOoNRq3BVG8waQ0mrdGkNZi0BpPWYNQazFqDyWyzoStQSCU+SoWvu8JHqfB2U3grFT5ucm+lws/dzVupCPJyD/BUyngehBAXdramtNKogwMixwn4O5ZhHk8aB9JmPIjL8PT03L59+8iRIysqKgA8/vjjJSUly5cvZxgGLiw/P3/q1KlZWVm47MEHH3ziiSdwvcglvNzLPcjLHVcjCKLObNaZLCarzWSxao1mo8Vqstr0ZovRYrXa7SaLzWKzm2w2i9VmttnNVpvZZjNbbbhCb7bYBBEtwDLwkMsAKGVSjmWlPCeX8AzDeMhlANzlUoVU4iaVKOVSD7nMTSZxk0rdZBJPhcxNKuU5FoSQLm5XcRYcYTmAwf9jWmhKklcwSJvxIK4kNjb2l19+GT9+vE6nA/DWW2+VlZV9/PHHbm5ucEkHDhy47bbbKioqcNns2bNXrlwJl8SyjKdC7qmQgxBCOtiukhw4wnEC/k7Cco8mjgFpDzyIixk8ePDvv/8+c+bMyspKAF999dXx48c3bNjQt29fuBJRFFesWPHMM89YrVZcNn/+/NWrV3McB0II6cFytFV5DTVwQOQ4AX93R+QgtdIXpD3wIK5n8ODBBw8enDp1al5eHoDMzMyhQ4c+88wzS5YsUSgUcAEnT5589K3nsnKyrVYrLlu8ePHy5csZhgEhhPRsO4uz4QjLgmFE/IUbL70/fiRIO+FBXFJ8fPyJEycWLFjw008/ATCbzUuXLv3mm2+WL19+6623siyLTlJcXPz666+v37U59d3b+ihSMt/ebj5V9umnn952220ghBAC7CzOhiMcJ+Dv7osd4SdzB2knPIir8vX13bx588qVK5999lmDwQAgPz//jjvueP3111988cU5c+bwPI/rqLCw8O233169ejU8JH0/mMt7yAEkPT/9Vr9ht/WbDUIIIUC5sTGttgyOcJyAvwhSeN4TOwyk/fAgru2RRx6ZMWPGk08++dNPP+Gy9PT0uXPn/vOf/1ywYMHChQvVajU6kt1u37Zt26pVq/b88TtYCDK271tz5EGe+F8Mvq89ImRzj8TNYhkGhBDSs+3QZIlwgGFFhhXxF/9MnqjgpCDthwdxeREREZs3b96+fftLL7108uRJXFZSUvLaa68tXbp0+PDht9xyy8033xwZGYn2Y7FY9u3bt2nTpp9++qmysjJ8ZOgt30ytK2osMfm5Rfjh7zZpDlWZG17sNU/K8iCEkB5sZ3E2HOFYAX/R11c9Naw3SLviQbqIKZf9+uuvS5cuPXbsGC4TBOHQZU8//XRMTMwNN9wwevTo/v37JyQkSKVStFJlZeWFCxf++OOPAwcOHDlyxGAwAJB5Sm9YMiTpljgA9cpgL6scjhyoPL/Yalja5x4lLwchhPRI9Rbj8coiOMLxIq5ggOd6T2HAgLQrHqRLmXHZ6dOnV61atX79ep1OhytyL1uzZg0AiUQSf1lYWJhKpQoNDXVzc1MqlVKpFJc1NDTYbLaKiory8vKSkhKNRnPhwoWqqir8XcQNYaOeH6IMUAAoM3g1WuVw7kzdpcdPffRm3wUBMi8QQkjPs6fkkl0U0ATDiCwr4Iob1akpPqEg7Y0H6YL69++/atWq999/f/fu3d9///0vv/yi1WrxF1arNf0yXCuFr3zks4OiJ0TgMgGMVWBxNbm60kUnVryZuiDWIwSEENLD7CrOhiMcJ+AKOSd5PGkcSAfgQboshUIx8zKz2Xz8+PF9+/YdPHjw6NGjjY2NuFYMw8TFxY26e7hiPGPlrbiChahW1pcbPbUWOZpVbdY+dmrlS73/Mdw/GYQQ0mOY7LaD5XlwhOVEXHF//CiVwgukA/AgXZ9MJht1GQBRFAsKCtLT09PS0oqKioqLi8vKysrLy/V6vdlsNhgMABiG8fb2Zlk2ICAgKChIrVYHBwfHx8f36dMnOTlZy9UtvfiCFSL+jmHEYDethLVXm5RoltFufvH82sfiZ90cNgKEENIzHCjLM9isaIoROU7EZSFu3vfEDAPpGDxI98IwTNRlM2bMwDVxh/vYwIl7KnfCEX+5jmOESpOHKKIZgih8kLW52FD1SNwslmFACCHd3a7iLDjCcSIg4rIXU6bJOQlIx+BBSBM3hd6e3nC+wlQOR3xkBp4VyvSeAhg0a5PmUKWp/oVe/5BzEhBCSPdlF8U9pblwhOMEXDZOlThaFQ/SYXgQ0oSUld4d+eA7Wa8LogBHPCQmzl0o0XvbRQbNOliV9tTpj99IvddX6gFCCOmmjlcW1ZkNcEDkWAGAnJMsTpkM0pF4EOJItDJ2fOCUXRW/wQk33hLuXltu8DfaRTQro6HooRMfLOtzX6xHCAghpDvaVZwNR1hOBIM/PZRwQ5ibD0hH4kGIE7NCb01vOFdqLIETMs4W6l6pt8SUGRvQrEpT/aOnPnyh17xRAb1BCCHdzo7iTDjCcSKACKXf3THDQDoYD0Kc4Bn+nsiH3sp8xS7a4QTPCD6yghDFwFO1eWiWyW55+fyXd0dNvDt6IgMGhBDSXZyvKSszNMIRjhMAvJw6XcryIB2MByHOhbtFTgyatr18C5wTYPWVld2iHvGj5g80S4S4Nn9nkaFycfLtMlYCQgjpFt5P3wdHWE5gGHF6WMrQgGiQjseDkGbNCLnlgvZsiVED5zTGglmhg/4ncc77WT/aRQHN2lNxttxUt7TPPb5SDxBCSBdXZtQeLMuHIxwn+Ejdnus9BeS64EFIs3iGvyfywTcz/2UX7XBua+nm55Neey3l7tfTvzHZLWjWRW3hQyc+WNbnvliPEBBCSFe2+MRmuwCHOE58PmWqr0wJcl3wIORq1G4RU1U3/lq2Gc7ZRNvaglWLE1/5oP+iJefX1Jgb0KxKU/2jpz58Num2cUF9QQghXdP3BaeOVWoADk0wrDhaFTs9LAXkeuFBSAtMC551QXu20JAP5zSGwu1lv8wIuWXVoCdfPL8ms0GDZpnsltfSvj5Td+mJhJt5hgMhhHQpxYa6f6fvtNtZOKKQsP9KnQFyHfEgpAVYhrsn6sFlGS9ZBSuc+638lxTvfhFuUSsGPPLvjO92lZ/G1WwpOVqkr3wl5S4fqTsIIaSLEETxhdM/6awWQZDAkQUJQ1QKL5DriAchLRMsD52mmvVz6Q9wThDta/NXLUl6XcpKlvSaG+Ue/Hnub4Ioolnn6vMePPH+ayl3J3qqQQghXcEXl/44WVNot7NwRM5zT/QaC3J98SCkxSarZpzTninQ58K5MlPJb2U/zQq9lQEzL2JsiML3zYsbTXYrmlVpqn/81MqnE2dPCR4EQghxbVna8pWZ+wAINhaOzAhPZsGAXF88CGkxluHujrx/WcZLVsEK53ZUbE317h+pjAEwJjA1TBGw5PwXlaZ6NMsi2N68+G26tvCJhJt5hgMhhLgki2B77vRmi2CDyNhFFo7cEtUH5LrjQUhrBMtDZwbP/rFkI5wTRPvq/I9eTH5DxsoBxHqEfDTwsSXn1mQ3FuNqtpQcLTFUv9R7vo/UHYQQ4nr+m7E3u6ECgN3OQERTPjLFoAA1yHXHg5BWmqiadl575pIuC85VmSs3F397R/jduMxf5vXhwEffzdy0vewEruZ03aX7jr3zYq9/DPCNAyGEuJI/Ki+tzT2My+wCC0fGhcRyDAty3fEgpJUYMPdEPvD6xSVmwQzn9lf93turb2+vVFwmZfnnkm/v5RXxQdZmm2hHs+osumfOfnZX5IS7oiayDANCCHEBNWbdktM/CaKI/w9jt7NwZFJYAkhn4EFI6/nLAm8MnfO95hs4J0JcV7j65eRlSt4dV8wMHRquDHzlwro6SyOaJYjC2vydmY2aJclzPSVuIISQTiWI4uJTP1abdbhMsDMQ0ZSCk4wMjgLpDDwIuSbjAiefqz+V3ZgJ57TWunWFqx+KeQJ/keod/engJ186vzazQYOrOVqdsfD4u//qfWcvrwgQQkjnWZV94EhVHq6w2Vk4MjokRsFJQDoDD0KuCQPmroj7X7/4glkwwbmz9SeP1x4e7DscfxEg81ox4JH3MjdtKzuBq6k01T9+auWCmKlzI8YwYEAIIdfdyZrCj7P24//H2G0MHJkcFg/SSXgQcq38ZYG3qud9XfgFmrWh6MtY9wRfqR/+Qsryi5NvT/aK+CBrs020o1l2Ufj00tZ0bcHzyXe48woQQsh1pLUYnzv1o10UcIVdAMCgCZ5lx4TEgnQSHoS0wUj/sefrz5zXnoFzRrvhi/yP/yfhBQYM/m5m6FC1W8CraevqLDpczR9V6Q8cf//FXvOSvSJACCHXhSCKz57aVGbU4i8EGwdHhgdFeknlIJ2EByFtc2fk/a9ffL7BqoVzl3RZeyp3jA+cgib6+sR8MeSfr6d/c7o2B1dTaqx57NTKOyMn3BU1gWVYEEJIB1uRsedQ5SX8nd3OwJFJYQkgnYcHIW3jwXv8I/zej3PfR7M2F3+b6NErVKFGEz5S93/3vX9d/u6vCnYJoohm2UVhbf7O47VZL/aaF6LwAyGEdJg95Zmf5xzE3wl2VhQZNMEyzITQOJDOw4OQNkv1HjDc74bDNQfgnE20rS1YtTjxFZ7h0QTHsPdET0rwDFt+cWOD1YCruagtvP/4e08m3DxRNQCEENIB8nXVS07/JOL/ZRcYONLfPyxQ4Q7SeXgQ0h5uU8/P1mVUm6vgnMZQuLV086zQW+HEMP/kzwc//WraunRtIa5GbzO9kb7hj6qL/0ya484rQAgh7UdvMz9x/NtGqwlNCHYWjkwOiwfpVDwIaQ9yTnFv5EP/yX5DEAU4t718S5Jn73iPJDgRKPdeMeCR1bnbNhTuEyHiavZVnsts0LzYa15v70gQQkh7ECE+f3pzbmMVmhBERhAYODIxLAGkU/EgpJ3EuMdPCJq6s3wrnBMhrilY9VLyG26cEk5wDPtA7PQET/XbGd/pbSZcTbmp9snTH8+PGj8/cjzPcCCEkLZZlXXg97JMOCLYWDiS7BMU7u4N0ql4ENJ+bgyZc1F7odhYBOfqLDVfF37xQPRjaNbowD4x7iGvpX2d3ViMq7GJ9rV5Ow9VpT2ffEeMewgIIeRa7Sy9uDJrH5yw2Rk4MiksAaSz8SCk/fAMvyD64WUZL1kFK5w7XXf8WO0fQ3xHoFlhbv4fD3p8Xf7urwp2C6KAq7nUWPrA8fdvDx99b/QUCcuBEEJaKb2+9PnTmwVRhCOiyIgCC0emqBNAOhsPQtpVsDz0xpA5m4o3oFnrC9dGK2MDZEFoFsew90RPSvWJXpa+ocqsxdXYRWF94d4jNRnPJ98R7xEGQghpsRJD/aKj6012K5zw5NxNMKOJCA+feK8AkM7Gg5D2NiFo6gXtmezGTDhnFkxrCz79n/gXWIbF1fTziV079Jn/ZP6wp+IsWiBfV77oxIrbw0ffGz1ZwvIghJCr0dnMjx7bUGPWwQk3XqqS+FbqytDElLAEEBfAg5D2xoC5N3LR0owX9DYdnMvVZW8r/3l68M1oASUvf7n3/CF+ie9nbTbazbgauyisL9x7pCbjuaTbEzzVIIQQ5+yi8NTx77IbKuAEAzzXa8pzR3fCkUlhCSAugAchHcBH6js//L5VeSvQrK1lPyd5pkQrY9Eyk4MHJntFvJ72dXZjCVogX1f+yMkPb4sYfVfkRDknASGEOPL6+a2Hq3Lh3IPxN9jsrF0U0IRK4dHXPxTEBfAgpGP08xk01G/k0ZpDcE4Q7V/kf/xi0lI5p0DLqN0CVg58fHXetu+K9guiiKuxifb1BXt+Lz/zePxNIwJ6gRBC/u6jrH3fF5yCc5NDej2aNHbB/u/gyMSweAbEJfAgpMPMDb87T3ep0lwO56rNld9q1t0d+QBaTMJyD8XOGBWQ8ubFjRpDFVqgwlT3wvk1/X3jnkq4Re0WAEIIuWxj/omVmfvgXG/v0GX9bzJYrUcqCuHIZHUCiGvgQUiHkbHy+6IW/TvrNbtoh3NHag4me6YM8h2G1ujlFfH5kKe/zNu5sWi/IApogdO1OQuPvTs3Yuy8yHFSlgchpGfbXZax7MI2OBfq5v3R0LlyTrKl+KLZbkMT3lLFkMBwENfAg5COFKmMnho869fSH9GsDUVrY9zjfKX+aA0ZK3kgdvqIgN5vZXxbpK9EC5gF69r8nbvKTz+ecNMQv0QQQnqqo1V5z5zcZBcFOOHOyz4cMtdP5g5gZ3EWHJkQFscxLIhr4EFIB5umujGjIS1Xlw3nDHbD2oJVT8Y9zzIsWqmXV8Rng5/6PHfbJs1BQRTRAiXG6sVnPx8TmPpI/I0BMi8QQnqYC3Uljx3faBFscIJnufcG3xbvGQTAItj3leXCkUlhCSAugwchHYxluHsjH1qa8YLJboRz2Y2Z28p/nh58M1pPxkoeibtxTGDqWxnfFukr0TL7Ks8dqb44Wz3yH5HjlbwchJCeIbex6qGj3xhsFjjBAC/3mT48IAaXHSzL01staELBSUaoIkFcBg9COp6/LGCu+u41BZ+gWb+Wbo51T0jwSMY16eUV8fngp9fm7dhYtF8QBbSAWbCuL9y7tfT4nVETbgkbwTIsCCHdWr6ueuHhr+otBjj3ZPKE2RH9ccWO4iw4MiYkRsFJQFwGD0KuiyF+I9Ibzh+vPQznRIhrC1a9mPSGknfHNZGy/AOx08cE9X0vc1NGQxFaRmvVf5j985aSo4tiZwz1TwIhpJvKa6y6948vq806ODcvavDCuJG4wi6Ke0ouwZHJ6gQQV8KDkOtlbvjdubrsGks1nKuz1K4tWPVw7NMMGFyreI/QlQMf/bnkyOrc7TqbES1TqK947tzqoX5Ji+JmRCiDQAjpXjK0ZQsPr6u3GODcLHXqkj5T8RfHK4tqzQY0wbPsmOAYEFfCg5DrRcG53Ru16N3sNwRRgHMXtGf3V+4eEzgRbcAy7M1hI8YE9vk459dd5adFiGiZozUZJ2qzpocMuStqor/ME4SQbuGituz+w+vqLQY4N1oV/3q/WQwY/MXO4iw4MjIoylMqB3ElPAi5jmLd46eoZv5W9jOatalkQ6xHQpgiHG3jI/VY0mvujNCh72VtyteVo2XsovBLyZGd5Senhwy5M3KCt9QdhJCuLL2+9P4j67QWI5xL9Qn7z8A5HMPiL0RgZ3E2HJmkTgBxMTwIub5mBN+c1ZiRq8uGc1bB+mnuf5ckvS7n5GizPt5Rnw9+enPxH1/kbjfYzWgZk926SXNoW+mJm8KGz4+a4MbJQAjpgk5UFzx6bIPOZoZziV6qVcPmKzgp/u58TWmZoQFNsAwzPjQOxMXwIOT6YhluYdTDSzNe1Nt0cK7SXP5d8dd3RSxEe+AYdo561A0BKStzftlfeR4tZrCb1xfu3Vl+6q6oidNCBvMMB0JI17Gz9OJzp340CzY4l+QV/PnwOz0kcjSxozgLjgzwDwuQK0FcDA9Crjsfqd/8iAWrcj9Asw5X70/0SB7sOxztJFDu/WrKXefq8z7K2ZLVoEGLVZsb3s3c9F3R/nujJ48N7MsyDAghLm9d3tG303YIogjnenmHfDbsTi+pAo7sLM6GI5PVCSCuhwchnaGf98DRAeP3V/2OZn1TuCbCLTpIrkL7SfWO/mTQ4/srz3+Ss7XcVIsWKzZUv572zTrl7rkRYyeq+rMMC0KIS7KLwvIL2zfkH0ezenmHfD78Tk+JAo7kaKvyGmrgyMTQeBDXw4OQTjIn7B+5upxiYxGcMwum1fkfPZv4Ms/waD8MmDGBqcP8kzdpDn1T8LveZkKLFegrll/cuKFw39yIMRNVA1iGASHElRjtln+e3LSvPAvN6ucb/smwf7jzMjixozgbjvT2UandvUFcDw9COomElSyIfnh5xssWwQLnigz5P5d8PztsLtqbjJXMixg7PWTwV/m7NhcfFkQBLVagL19+cePGon13R00cHdiHAQNCiAuoNusePro+vb4UzRrkH/nx0HkKTgrndmqy4MgkdQKIS+JBSOcJlofeGGAqMQAAIABJREFUpr7z68LVaNbuim0JHsm9vVLRAbwkysfib5oeMuTT3N+OVmegNfJ15a9cWBfvEXpP9ORh/kkMGBBCOs+5uuKnTnxXYWxAs4YHxPx3yB1yTgLnSvTa9LpyODI5LB7EJfEgpFON9B+T3ZhxvPYwnBMhrin45IWk132l/ugY0e7Bb6YuuKgt/DT3t7N1uWiN7MaSJee+iHYPvj189ERVf5ZhQQi57r4vOPXGhd+sgh3NmqVOfbXvjRKWQ7N2FGeJcCDSwzfOKwDEJfEgpLP9I+LeAn1epbkczultus/yPvyfhBd5hkeHSfaKeL//olO1OZ9c+jWnsQStkacrW35x45f5u+ZGjJ0WMphjWBBCrguzYFt2/rcfCk/jauZHD3kuZQoDBlezQ5MFR6aoE0BcFQ9COpuMld8XteidrNdtog3O5etzfy75fnbYXHSwAb5xqwY9eaDq/GeXtpUYq9Eapcaa/2T+8E3Bnjnho24MHSZleRBCOlK5UfvE8e/S6kvQLI5hX+gz7fbIgWiBGpP+dHUxHJkclgDiqngQ4gIildE3hsz5sWQjmrW7YluMe1xf74HoYCzDjAlMHeHf+9fSo+vyd9daGtEa5abaD7N//q5o/+3hY2aEDpGxEhBCOsDx6vz/OflDrVmPZrnx0ncGzhkdFI+W2VWSYxdFNKFSePTxCwFxVTwIcQ0TVdNydJkXtGfhnAjxq4LPwpLC/WWB6HgSlrs5bMSMkCHby06uzd9ZY25Aa1Sa6v+b/dO6gt03hQ6/RT3SU+IGQkg7sYvCJ1kHVmUfsIsCmhUg9/ho6Lxkr2C02E5NFhyZpE5gQFwXD0JcAwPmzoiFSzNeaLBq4ZzBbvgs78NnEl/mGR7XhYTlZ4YOnajq/2vpsfUFe2otjWiNeotubf7OjUX7Jqr63x4+JszNH4SQtsnXVS8+9WN6fSmuJskr+L9D7ghWeKHF9FbL4YoCODI5LB7EhfEgxGV4SrwWRj3yfs6bgijAuUJD/g/F6+9Q34XrSM5J56hHzQgZ8mvpsW8K9tRZGtEaJrtlS8nRraXHhvgl3R01MdFTDULINflZc27p+a0GmwVXMyOsz6t9Z8o5CVrj99Ici2BHEz4yxeDAcBAXxoMQVxLvkTQ9+OYtpZvQrH2Vu6KVsYN9h+P6knPSOepRU4MHbdIc/L7oQKPNiNYQRPFI9cWj1RmD/BLuiBjT3ycWhJAWq7MYXj7zy57yTFwNx7BPJI1bEDcSrbdDkwVHxofGcQwL4sJ4EOJipgXPytPlpDecR7O+KVwT7hapkofgulPy8ruiJs5Wj/pRc+gHzUGtVY/WECEer8k8XpMZ7xF6a/gNYwL7SlgOhJBmHaq89MLpn6rNOlxNkMLzvUG3pfqEofXMdtuB8jw4MjksAcS18SDExTBg7ota9EbGS7WWajhnFkyf5X24OPEVKStFZ1Dy8jujJtwafsOvpcc2Fu6rNmvRStmNJW+kb/go59dZocNuVo/wkihBCGmi0Wr6z8VdPxScEnF1A/0i/jPoVn+ZO67JwfJ8vdWCJtx46QhVFIhr40GI61Hy7vdHP/JO1lK7aIdzJUbNd5qv50fch84j56Rz1KNmhQ7fU3Hmq/zdJcZqtFKdpXFt/s5vCveMDUydFzkuUhkEQsgVO0rTl53fVm3W4WoY4O7Y4U8nT+AYFtdqZ3EWHBkTEiPneBDXxoMQlxSljJ0VcuuPJRvRrEPVe2Pc44b5jUKnkrDc5OCB41X9dpWf/qbg92JDNVrJKth2lp/aXXF6iF/SrepR/XxjGTAgpAerNuuWnv9tV+lFtICvTLm076zRqni0gV0Ufy+5BEcmh8WDuDwehLiqiappl3RZ57Vn0KyNRV9GKqOD5aHobDzDTQ0eNFk1YF/l+Y2Fe7MbS9BKgigeqb54pPpipDJoVtjwycED3TgZCOlhRIi/aM6/lbZdazGiBUYExr7Rb1aA3ANtc6yysM5sQBNSlhsbEgvi8ngQ4qoYMPdEPbgs46VqcxWcMwvmT3Lffy7xVQXnBhfAMuy4oL7jgvpeqM9fX7j3aHWGCBGtVKCv+CBr82eXfhuv6ndz2Iho92AQ0jNkN1S8cf63kzWFaAE5J3mm16TbowYyYNBmOzRZcGS4KtJdIgNxeTwIcWFunHJh1KPvZL1uE21wrsJUvqZg1aKYJxkwcBkp3lHLvaNydWXfFu77veKMXRTQSga7eUvJ0S0lR+M9wmarR45X9eMZDoR0U41W04eZezfkn7CLAlogzjPw7QGz4z2D0B5EYHdJDhyZHJYA0hXwIMS1RSqjbwmb+51mHZp1vv709vItU1U3wsXEuAcv6TV3QcyU74r2by09brJb0HrZjcXLL278NPe3yaoBN6tHBsi8QEg3Iojij0WnP8jYU2vWowVYhrknZvjjSeMkLId2cq6mtMzQgCZYhhkXGgfSFfAgxOWNC5xUoM89XnsYzfql5Ae1IqK3VypcT5Dc57H4m+6OmvRz8eHNxX/UWhrRejXmhvWFe7/XHLghoM/NYSN6e0eCkK4vvb70jfO/nasrRstEKP1e7TtzkH8k2tXO4iw4MjBAHSBXgnQFPAjpCv4RcW+RoaDcVArnRIhf5H+8JOk1f1kgXJKnxO3OqAl3RIz9ozrt28L9GQ1FaD2rYP+94szvFWcilEEzQ4fOCBki56QgpAuqMDV8cHHPL5qzIlpEwnL3x416IH6UhOXQ3nYWZ8ORSWHxIF0ED0K6Ahkrvz/60TczX7EKFjhnsOs/yf3g2cR/SVkpXJWE5cYEpo4JTL1Qn79Jc+hA1QVBFNB6hfqKD7N/XpO3Y1xQ39nqUZHKIBDSRRhslg35x1dlH9TbzGiZvr7qV/vOjPUIRAfI1lblNdTAkYmh8SBdBA9CuohQhXp++H1rCj5Bs4qNRV8Xrr4vahFcXop3VIp3VJG+8gfNwR1lJ82CFa2nt5m2lBzdWnqsv0/ctJDBowJ6S1gehLgqq2D/qejsisw9tWY9WkbOSR5OGH1P7HCOYdExdmiy4EhvX5Xa3Ruki+BBSNcxxG9Erj77QNUeNOt47eFo97gxARPQFYQrA59OnL0gZsrWkmM/lxypMNWh9QRRPFmbfbI221PiNkk1YEbokEilCoS4Erso/KI592HmvnKjFi02WhX/Ysq0EDdvdKSdxVlwZHJYAkjXwYOQLuV29V2lxuJLumw063vN12EKdax7AroIL4lyXuS4OyLGnqm79IPm4NHqDBEiWq/BavhBc/AHzcF4j7CZoUPHq/q5cTIQ0qlEiHvLsz64uOdSYyVaLELp91zKlBuC4tDBivXai3UVcGRSWAJI18GDkC6FY7j7ox9blvGS1loP5+yi/dO8/y5Jet1b4oOug2WYAb5xA3zjSozVW0uO/Vp6rMFqwDXJbiz+T+YPH2b/PMw/eWbo0AG+cSDkuhMh7i/P/ihrf3p9KVpMzknuix1xf/xIKcuj4+3QZIpwINLDN87LH6Tr4EFIV+Ml8X4g+vH3spfZRBuca7BqP81d8XTCCzzDo6sJVfg/EDv9nujJeyvOfld0IFdXimtiFqz7Ks/tqzwXrgycEjxoWvAgb6k7COl4IsT95dkfZe1Pry9Fa4xWxb/UZ3qwwgvXy47ibDgyVZ0I0qXwIKQLinGPuzn09u+Lv0Gz8vSXfizecJv6TnRNUpafHDxwcvDA7MbiH4oO7qk4axPtuCZF+spPL21dk7djhH+vScEDhvolsgwLQjqACHF/efbKzH0XtWVojUQv1ZKUqQP8InAdVZv0Z6qL4cjksASQLoUHIV3T+KApBYa8E7VH0Kw9lTsjlNFDfEegK4v3CFvSa+6DsdN/LT22peRItbkB18Qq2PZVnttXeS5Y4TstePCUkEEBMi8Q0k5sgv23krQvLv2R01CJ1ghWeD2aOHamug/HsLi+dhZn20URTagUHil+wSBdCg9Cuqy7IhaWm0o1hkI06+vC1YEyVZQyBl2cn8zz7qiJd0aOP1qTuUlz8HTtJREirkmZsXZ13vY1+TuSPSMmBw8cr+rnxslAyLXS28w/Fp358tKRMqMWreElVSyIHfGP6CFyToLOsLM4C45MVicwIF0MD0K6LAkrfSjmyWUZL+ltOjhnFawf5773fOJrPlJfdH0sww73Tx7un5yvK/+p5PDu8tN6mwnXRBDFNG1BmrZgZc4vNwSkTAoe0N8njmUYENJi1Wbdt/knv8471mA1ojXknOQf0UPujxvpIZGjkzRazUcqCuHIpLAEkK6GByFdmZ/U/57IBz669J4IEc41WLUf5b77TMLLUlaK7iLKXfVUwi2PxN14uDp9S8nR07WXRIi4Jia7ZWf5qZ3lp/xlnqMD+0wJHhTnEQpCmpXdULH20uHfStKsgh2twTHszeF9H04cEyT3RKfaU5JjFexowkemGByoBulqeBDSxaV49ZsefNOvZZvRLI2hcE3BJw9EP8aAQTciZfkxgaljAlM1hqptpce3lZ2sszTiWlWbGzZpDm3SHIpUBk0KHjg1eKCP1AMdT28zKXk5SFdgF4XdZRkb8k+cqC5AK3EMOy2094MJN0S5+8MF7CjOhiMTQuM5hgXpangQ0vVND7m50JB/QXsWzTpTd2Jb2S/TgmehO1K7BTwQO31hzNQzdblbSo4erLpgFwVcqwJ9xaeXtn6eu62fT8wk1YDRgalyToKOIUJ8/NRHr6TcqXYLAHFhNWbdT0VnN+SfKDNq0Uosw0wMTn4saWyUuz9cg8luO1CWC0cmhyWAdEE8COn6GDD3Ri1anvFylbkCzdpSuilIrhrgMwTdFMuwA3zjBvjGVZrqt5Wd+K30eIWpDtdKEIVTtTmnanP+m/3z2KDUyaqBvbwjGDBoVxnaolxd6eKzn68c+KiP1APE9aTXl35feGqL5rzJbkUrsQwzMTj5saSxUe7+cCUHyvIMNiuacOOlI1SRIF0QD0K6BTfObVHMk29nvWqym+CcCPGrgs8CZSq1WwS6tUC5991RE++MnHCm7tKOspP7K8+bBSuulc5m3FJydEvJ0UC596iA3mMCU1O8o9BODlWnAyg11jx37osP+i+Sc1IQ19BoNW0vSf+24GSGtgytx7PctNDeD8bfEOnuB9ezszgLjowNiZFxPEgXxIOQ7iJEEbYw6tGPct8VRAHOmQXzx7nvPZf4qqfEC90dyzADfOMG+MY9nnDT3opzPxUfztWVog0qTfWbNIc2aQ6p5L7jglKnBA8KVwaibQ5VpeGyrAbNK2nr3uhzL8ewIJ0qvb70+8JTWzTnTXYrWs+Nl94S3u/umGEhbt5wSXZR2FuaC0cmhSWAdE08COlGenul3hgy56eS79CsWkvNqrwPnopfwjM8egZ3XjEzdOjM0KFp2oIdZSf3VpzT2Yxog3JT7frCvesL98Z5hI4L6jsuqG+Q3AetpzFUFekrccXR6oz3sjb9M/FWkM5Qbdb9XHT2h8LTRfpaXBM/mfvtkQPnRw/xkirgwo5WFNaZDWhCynJjQ2JAuiYehHQvU1Qzy4wlx2r/QLNydTlfF66+J/JB9DC9vSJ7e0U+Hn/TidrsnWWnDlWl2UQ72iCnsSSnsWTVpa3xHmGTggeMDUz1k3mixQ5UXsDf/VpyTCX3nR85HuSKUzWFA/wi0GHMgu1IZe4vmvO/l2faBDuuSYTSb270oNsiB8pYHi5vR3E2HBmhinKXyEC6Jh6EdDvzIxZUmivy9ZfQrKM1h8IU4ROCpqLnkbD8cP/k4f7JDVbD/srzO8pOpmkL0DbZjcXZjcUf5fyS7BkxJih1QlA/b6k7ruZQVRqaWJ273V/mOSV4EAjwbcHJZRe2HZryjIdEjnYliOKJmoJfNOd2lWbobWZcEwYYGhB9V8ywUUGxDBh0BSKwuyQbjkwOSwDpsngQ0u1IWMmimCeXZ/6rzlKDZm0q3hAkV6V49UNP5Slxmxk6dGbo0AJ9+Y6yU7vKT1ebtWgDQRTTtAVp2oJVl34d5JswOrDPiIBe7rwCjlSbGzIbNGhChPhOxg9+Us9Bfgno2VbnHHr34m4Ap2uKRqvi0U6yGyp+Lb6wtfhCuVGLa+XOy25Up86LHhzl7o8u5Ux1SbmhEU1wDDM+NBaky+JBSHfkKfFaFPPEO1lLLYIFzokQV+d//M+EF8MU4WgNo93AMbyUlaK7iFSqHoydfn/MtHRtwc7yU7vLzxjtZrSBVbAfrr54uPoiy7DJnuFjglLHB/XzkbrjLw5Xp4sQ4YhNtL+Stu6D/g/HeoSgRxIh/id915pLh3HZiZqC0ap4tE1uY9X2kvTtpel5jVVogwil3+yIfrdGDvCUKNAF7SzOgiMDA9R+ciVIl8WDkG4q3C3q3siHPs37rwgRzpnsxv/mvLM48WVfqT9axmg3rMh5+5awO+LcE9G9sAyT4h2V4h31aPysI9UXd5SdOl6TaRcFtIEgCmnagjRtwUc5W5I9w8cEpY4L6usr9QBwsCoNzultpsXnPv9o4GNBch9cG0HAnxgGDIM/iSJEEQwDhsGfRBGiiP+LYfAnhoELsIvCq+d+3VR4GlecqC7EtcrXVW8vSd9ekn6psRJtwDHsGFX8vKjBQwKiGDDosnYVZ8ORSWEJIF0ZD0K6r34+g6YFz9pa9hOapbXW/TfnnWcSX3LjlLgao92wIuftfH2uxlAY556IbkrGSsYEpo4JTK001e8uP/17xZlcXRnaRhCFNG1Bmrbgo5wt/Xxihvolna27hGbVmBsWn/38vwMf9eAVuAb/+hfMZjzwAGJj8afjx/H++5gzB7NnQxBw+DA+/RR798JiQf/+ePRRjB0LhQIMg05lEWyLT/24s/Qi/iJDW6azmd15GVosU1v+e1nm7rKM7IYKtI1a6XtLeL+bwvsGyj3QxWXVV+Y31qIJBpgUFg/SlfEgpFubEXJLqbH4TP1JNKvMVPJJ7vuPxy3mGR7OGeyGFTlvF+hzAWgMhegBAuXe8yLHzYscV6Cv2Fdx7veKMxpDFdpGEIVTtTmnanPQAgX6ihfPrfl3vwekLI/2IorYswdvv42UFOzcCaUS69bhzTeh0+GWWyCRoPMY7ZbHj317uCoXf2cXhbO1mpGBsWiWIIpnazX7KrJ/L8so0NWgbaQsP1aVcGvkgKEBUQwYdAvbNVlwpJevKlTpBdKV8SCkW2PA3Be16J2spYWGfDQruzFzTf4nC6MfYcDAEYPdsCLnrQJ9Hi4rMhSgJ4lUBt0TPeme6ElZDZo9FWf3VJytMmtxXZyrz1uWvuHl3vNZhkG7MJvx/feIi8OiRYiNxZ+eeQbV1dizB336ICkJnURrMS46+s25umI4cqK6YGRgLBzR2cxHq/L2l2fvq8iuNevRZvGeQbMj+s8M6+MlVaB72abJhCOTwxJAujgehHR3Elb6YMwTb2b+q8GqRbNO1R3zLfabHTYXTRjshhU5bxXo83BFmanUKlgkrBQ9TIKnOsFT/WDsjHRtwb7Kc3sqztVZGtHB9lWeC7zk/XDcTLSW0YiaGnh44E91dbBY8KfCQhQXY8YMRETgf0ml6N8f27ejtBRJSegMFcaGhUfW5TVWwYmTNYX4u2J93d6KrP3l2SdrCq2CHW3mLXWbGJJ0Y1hqf79wdEd5DTXZ2io4MkWdCNLF8SCkB/CV+j0Y/cT7OcutghXN2lXxm4/Ub1zgJPyFwa7/IPutQkM+/kIQ7SXG4khlNHoklmFSvKNSvKMeibsxXVu4r/Lc7vIzWqseHea7ov0BMq9bw29Aq/z6K7Ztg1SKP5lMYBjMmweDAaIINzfwPP4vd3cIAiwWdIYCXc39R9aVGurhXFp9qdFuEUUcr87fV5F9oCKnwtiA9iBj+TGqhBvVfUYGxvIsh+7rN00mHIn3Cojx9APp4ngQ0jPEuMfdE/nQ53kfihDRrO81X8s5+XC/G3CZwa7/IPutQkM+mtAYCyOV0ejZWIZN8Y5K8Y56KHbGidrsfRXnDlalGe1mdICPcrZ4S90nqvqj5aZPx/z5iIjAn86cwerV+JO3NyQS1NXBaISbG/4kiqiqAs/DzQ3XXU5D5QNH1lWaGtEsm2C//cBnBY01dlFAe+AYdoh/1Ax1nwnBiUpehh5guyYTjkxVJ4J0fTwI6TEG+AyuC5v7Q/F6NEuE+HXhagWr6OczqNHW+H728hKjBo5oDAUgV0hYfrh/8nD/ZLNgPVWbs6/i3KGqNIPdjPYjQvx3xndBcp8+3lFoITc3+PsjOBh/KiqCVIo/hYUhIQHnz+PCBfTtC5ZFVRVOnIC/P8LCAAiCIIoiwzAsy6KDnaopfOTYhkarCS2Q21CFNuMYdqBfxJTQXhOCk3xlSvQYGl39xboKODI1PBGk6+NBSE8yIWhqnaX298rtaJYgCqvzP7oHi7aV/VRi1MCJIkMhSBMyVjLcP3m4f7JFsJ2szd5Xce6P6nS9zYT2YBFsL5z74sOBj0Yog3DNJBLMno0PPsBXX6GqCgoFtm9HRQVmz0ZkJACDwZCfny+Xy0NDQxUKBcMw6Bj7K7KfPvG9yW5Fx2MZJtVHPTk0eUpIrwC5B3qerUUZcCTKwzfeKwCk6+NBSA8zRz2vzlp7uu44mmUTbavzPhQhwrkSY5FdtHMMB+KIlOWH+ycP90+2CLaTtdn7Ks79UZ2ut5nQNo024z/PfLpy4GOBcm80LzgYVitkMvwvpRKRkfD2xp+GDMFzz+G77/Dee7Ba0bs3nnsOAweC4wA0NDSsW7eusrJy5syZgwYNCgoKkslkaG9biy8sOfOTTbCjI/EsN9gvcnxw4vjgxAC5B3qw7ZpMODItPAmkW+BBSA/DgLkvapHepstqvIhmiRDRLKtgLTeVhirUIM2Ssvxw/+Th/smCKKRrC58/94XOZkQbVJm1S85/sWLAI26cDM14+GH8Ve/eWL4c/1efPujTB46EhIQ899xzW7du3bRp0+HDh6dMmZKamurr68vzPNrJ+vzjyy9sE0QRHUPOSYYERE0O6TVOleAhkaPHKzM0XKgtgyNT1Ikg3QIPQnoenuEfinninaylJUYN2kZjKAxVqEFahmVYT4mbzmZEm11qLH35/Jdv9l3AMxw6gK+v75133jlq1KiNGzeuWbOmT58+Y8aMSUhI8PLyYlkWbbM659C7F3ejAwTJPUcFxY5VJQwLjJGxPMgV2zSZIhxQu3sn+wSBdAs8COmRFJzbw7FPv535qtZajzbQGAqH+o0EabGDVWloJydrs5enb3yx9zwGDDpGZGTks88+e/78+fXr13/88cdDhw4dPnx4TEyMUqlkGAatJ0J868KOdXlH0X44hk30Uo0Oih+jik/2DmbAgDSxTZMJR6aqExmQboIHIT2Vn9T/ibjF/8l+Q2/T4VppjAUgrfFHVTraz+8VZ0IUfgtipqDDsCzbt2/fxMTEgwcP/vjjjxcuXBg5cuSgQYPUarVcLkdr2EXhlbNbfiw6g/bgL3MfHhgzRhU/PCDGQyIHca7KpD9TXQJHpqgTQboLHoT0YCGKsMdi//l+zpsmuwnXpMhQKEJkwKDFLBaLXq+3WCwsy/I87+7uLpFI0DNUmxsyGzRoDwyYCGVQX5/oKHeVIAosw6IjyeXyiRMnDhgwYPv27bt37z59+vTo0aNTU1ODgoJkMhlawCzY/ufE93vLs9Bmt0UOnBPRP9k7mAED0gLbijIEUUQTKjePVL8QkO6CByE9W6QyZlHMUx9eescqWNF6Jrux2lwZIAvC31mt1pycnLTLCgoKSktLy8rKSkpKtFotHPH19Q0ODg4NDQ0ODo6Oju7Vq1dKSkpMTAzHcehG/qhKEyHiWrEME+0e3Nc7po93dKpPtJdEievL19d33rx5Q4cO3bx587fffnvixIm5c+cmJSXhagw2yxPHvz1clYv2ECT36OUdAtJi2zVZcGSaOokB6T54ENLjBcpUbpxSK9TjmhQZCgNkQQC0Wu3BgwcPXHbmzBmLxYIWq70sPT0dfyGXywcOHHjDDTeMHj16+PDh7u7u6OIOVaWhlTiGjfMITfWOTvWJ6eMd5c4r0Nmio6OffPLJn3/+ed26dQMHDkxKSkKzTHbrwsNfnasrRjs5UVP4EEhL1ZkNJ6o0cGSKOgGkG+FBSM9WZ6l5N3u51lqPa5Vefv7U92e3bNmyY8cOq9WK9mMymQ5dtmzZMo7jhg4deutlISEh6IL0NtPZ+ly0AMewMe4hKd6RKd5RA33j3XkFXAzHcTGXKRQKXI2ck3w2/M7j1QWHK3OPVOXl66rRNmdrNVbBLmE5kBbYpsmyiwKaCJAr+/uHgXQjPAjpweosNe9mL6syV6INvv19w2+P7UEHs9vtf1z29NNPjxs37sEHH5w1a5ZEIkHXcaQ6wyrY4QTHsDHuIQN943p7R6V6Ryt5OboRJS8bq0oYq0oAUGbUHq7MPVKVd7Qqr85iQOuZ7Na0+pJ+vuEgLbBdkwlHpqgTWYYB6UZ4ENJT1Vqq381eVm2uQtv4J/jiOhIEYfdlKpVq4cKFTzzxhL+/P7qCQ1Vp+Ds5J4l1D+3jHTXANz7FO0rK8ugBghVesyP6z47oL4hihrbscFXu4cq8s7Uai2BDi52sKeznGw5yNVqL6VhlERyZok4E6V54ENIj1Vqq/5P1Ro2lGm2m8JUrA930lQZcX+Xl5UuXLn3vvfcWLFjw/PPPq1QquDCrYDtekwlAwcmSvcJTvKJSvKP6eEdJWB49FcswvbxDenmH3B83ymS3nqnVHKnKO1qVd7G+VMRVnKguvD9uFMjV7CrOtgp2NOEjcxscqAbpXngQ0vPUWmrezV5eY6lGO/FP9NVXGtAZ9Hr9ihUrvvjii5deeumpp56SSCRwSZXm+nuiJ6V6R8d5hLIMC/J3ck4yLCB6WEA0gFqz/kRNwZGqvAPlORWmBjhyprbIJth5lgNp1jZNJhyZok7gGBake+FBSA9Tba56N3tZraUa7cc/wadOJac1AAAgAElEQVTwQDE6j06nW7x48Zdffrly5coxY8bA9YQq/G8LHw3SRJmpIkDmxzM8rvCVKSeH9Joc0gupKNbXHanKO1KVd6jykt5mxhUGmyVDW57iEwrinM5qPlxRAEemqBNBuh0ehPQktZbq93OW11qq0a78E3zhAi5evDhu3LjHHnvs7bfflslkIC5PhPhy2htmwaySq6KUEWGKkFBFcJxHjAfvjsvClD63KgfcGjnAZLeeqdUcqco7WpWXoS0TRPFETUGKTyiIc7tLcsx2G5rwlMqHBoaDdDs8COkxaizV72a9UWOpRnvzT/SFaxBFccWKFYcOHdq4cWNcXByIa6s0VRvsRgAlxtISYymu8JZ4RSkjopQRYW4hoYqQUEWwnJMMC4geFhANoMasO1KVZ7LbQJq1XZMJRyaFxUtYDqTb4UFIz2AVLF8VfFZrqUEHcFcp5V4yk9YM13D69OkBAwb88MMPkyZNAnFhhQYNHKm3as/Unz9Tfx6XuXFuYW4hUcqIKGVElDIiRK6aEdYHpFkGm+VAWR4cmRKWCNId8SCkZ5Cw0qfinzfaDRpDYaEhv9CQX6QvqDJXiBDRHvwSfEuOl8FlNDY2zpw588svv7zjjjtAXFWhoQj/hz34gG+yTvzA/3mePNlJszrSNG2a7sEsUKBlD0GmhwtETkBxgfdDUJmK5+I4BeRcIB7DBYgTAQERKbNAWYUCLW1DunfTkdFmPH/+8dX765/VPb/vdz1YnJa0qvS0qnS4MRTjI/DWi3V6sU4v1gWK/fk0H8RfHcpLtzkduIWYy4tXB4LojBgQRFci5IjCpJFh0ki42Zy2HGtWlsVgtBiyzDcKbHksWDSKV4Qy93Q+bsHlckNDQ6OiorRuarVaKBR6eHigjslkslqteW7Z2dkpKSkZGRlOpxNNVltbO336dJvNNnPmTBDtktGcjYZzsI5ca16uNe9YyUkANEV78lR+Ql+9WKcX64IlehnXA13evuxU3M4ovzA+hwHRGTEgiC5MwBGESMJCJGFwszmtG7//9LMfN6giFF4RKnmgB0VTqB9VhAJ1vLy8hroNHjw4MjKSx+OhIWw226VLl44dO5aQkHDkyJHy8nI0lsvlmjNnjkqlmjhxIoj254YlC03mYl1FNcVFNcXnTclwk3NlWpHGT6jRi3V6sc5P6EuBQldiczoO52Xgdsb6h4PopBgQBFHnt32HFjz2ksPhgBtPzFWGKrwilZ6RSq8IlUIvA4U78QxXajSaRx555G9/+1t8fDyHw0FjCQSCfm4vvviiw+E4fPjwDz/8sHPnzuLiYjScw+F49NFHDx48GBcXB6I9qbRXldea0AJM9gpTRcXliqtwE3KE/iI/vVinFWr8hJogsY5Lc9GpJeRnWBy1uIWQwx2sDgLRSTEgCMItOzt7xowZDocDdWrN9oILRQUXiuDGE3OVoQqvSKVnpNIrQqXQy0Dhf+QBHqmZqRK+BM2KYZhRbmvWrPnuu+8+/vjj48ePo4GsVuujjz568eJFpVIJopkolcp+/fppNBo0ltGShVZhdVrTqtLTqtLhxqE4aoGPXqzTi3VaoSZQ7C9hJOhc9mWn4nZG+IWIGC6ITooBQRCA0+mcMWNGeXk57qzWbC+4UFRwoQhuPDFXGaoY+uCgPmN7W4TVBba8AnteCD8MLYPP5z/mdvjw4ddffz0hIQENkZOT89RTT33//fcgmom3t/fIkSNFIhEay2jJRltwss5ca16uNe9YyUm4ybkyvVinF+v0Yp1WpPHme6Ejq3U5D+Vex+2M9Y8A0XkxIAgCWLt2bUJCAhoi0E//0bsfjRo1Cm5mRzVaxbBhww4fPvzjjz/+3//9X1ZWFurthx9+2LJly8yZM0E0gdPhvHTwEiiE9Avx9PR02p3nfzlPc+iQfiFihRgN4c33jlH0NJqzS2vL0KZM9orzpuTzpmS4ybkyndhfJ/LXiQJ0Yn+1wJsChY7jWL6hyl6DW/A5zDDfYBCdFwOC6PJKSkreeust1BtN0y+99NIbb7zB5/NRR8xI0IoeeOCB0aNHv/TSS+vXr0e9LVu27OGHHxaLxSAai6IpsUJ86bdLfCE/bGCYMdloTDYG9w3mCXlooFhlTKwyBoDFac225BrMRoPZmGvNy7Hm2l0OtB2TvcJkqrhougw3AYfvK1D7CTV6sU4v1unFOh7NRTu2L+cabmeob5CYywPReTEgiC7vzTffrKioQP2oVKpt27aNHj0abU0sFn/yySejRo2aOXNmdXU16iEvL2/NmjWvvvoqiMaiaTqge0BhRqHhvIFm6PTT6SqNKrBnIFfARWOJOMJwaUi4NARuTtaZbys0mI0Gs9FgNhrN2TWuGrQdm7PGYDYazMZjJScBcChaLVBrhRo/oa9erAuRBHlwpWg3HC7XwZzruJ2x/hEgOjUGBNG15eXlrV+/HvWj0+n27dsXERGBduPBBx/U6XTjx48vKipCPbz77rvz58+XSqUgGosv4kcPiz627djRL4966731ffRipRjNh0NxtEKNVqgZ7DkQbuW1JoPZaDAbDWajwWw02SvQdpysK9eal2vNQx05V6YX67QijZ9Qoxfr/IS+FCi0kROFN0y1VtyCoenhmhAQnRoDgujatm7dWltbi3rw8/M7fPhwYGAg2pm+ffv+/vvvgwcPLisrw71UVVXt2LHjqaeeAtEEMrVM5iW7fup61LAor0AvmqbxV5dNN967tlPMCMSMUMIIJIxQwggkjFDCFYoZgZgRSDhCCVcgZoRiRiDi8HFXCp5cwZPHKHrCzeyw5FjzDGajwWw0mI151nwWLNqOyV5x3pR83pQMNxFHqBX56cU6vVinFWq0Qj8uzaC17Mu+htsZrA6S8QQgOjUGBNGFsSy7efNm1INEItm/f39gYCDapaioqF27do0YMaK2thb3smnTpqeeegpEExTfKC7LK5OqpOV55eV55eoQNf4qWq4DkFJhRP3waEbKFUkZoYQRSrkiKSPkc7g8mpEyIglXKGWEUq5IygilXKGEEcm4onBpSLg0BG42p81oycm15uVY8wxmo8FstLvsaDsWpzWtKj2tKh1uHIqjFvjoxTq9WKcX6wLF/nyaj5bhZNlfc6/jdu73jwDR2TEgiC7s9OnT169fRz18+OGH0dHRaMfi4+PfeuutV155Bfdy8uTJjIyM4OBgEI1Sa6u9/NtlsVzcbUS3lMMpmecyPbw8RDIR/oQC9XDAkHev7kT91LocpTWVpTWVqIc5weOmB45AHQFHEC4NCZeGwM3JuvJtBQazMdeal2PJS6/OrHJUo+04WWeuNS/Xmnes5CTc5FyZXqzTi3V6sS5IEijnytBMThdlldrMuAWHokf6hYDo7BgQRBeWkJCAehg+fPgTTzyBdm/hwoU7duw4e/Ys7uXIkSPBwcHoFOx2Z+LFG/6+ikA/JVpF6vHUqtKqbiO6BfYKdNQ6Ug6nePp7hvYPpWgKfzJa3eezjH3ltVVoVtEy3TTdMNwZh6K1Qo1WqEGd8lqTwWw0mI0GszHXml9UU4w2ZbJXnDclnzclw03OlWlFGj+hRi/W6cU6P6EvBQqNsi/7Gm4nzken4ItANER+fn51dXVlZaXVarXZbFKplMfjyWQylUolk8nQLjEgiC4sMTER9fDuu++ioaqqYDZDLodAgJtqamAygceDQoFb2WwwmWA2g2UhEEChgEgEikID0TT95ptvjhs3Dvdy4sSJWbNmoSNzudhLaXn7jl757USqTqPc8OY0tIriG8XXT13XRmq10VqGxwT3DS7MKMxMypSr5d56b/wJj2Ye0MZtztyP5iPg8BZHTaUpGg2h4MkVPHmMoifcLE5LtiXPYDYazEaD2ZhvK3CxLrQdk73CVFFxueIq3AQcQYBIqxVq/IQavVgXJNZxaS7qwcWyB3JScTtj/SNA3FVubu4pt6ysLLip1Wq5XC4QCORyOUVRtbW1ZrO5qqqqpKSkoqICAIfDiY6OHjBgQN++faVSKdoBBgTRhSUmJuJe+vXr16dPHzTU3r3YswcvvIB+/XBTZiY+/BChoZg/H/8/VVU4dAi7diE9HU4nfHwwYQLGj4eXFygKDTRmzBi9Xm8wGHBXiYmJ6JjsDmfSpazfTqYeSUqvNtcA4HI5S58bQ9MUWoVCoxj9zGiegMcT8QBwBdzYKbEuh4sv5uMWD2jjthkP2Zx2NJPnQyf6i7zQNCKOKFwaEi4NgZuDdRTYigxmo8FsNJiNN8xZta5atB2b05ZWlZ5WlQ43DkWrBWq9WKcVavyEvqHSYCkjwe2cK8kptFbjFhyKuk8bBuIWdrs9ISHhp59+ysvLCwgI6N+//7PPPqvX61E/Dofj0qVLiYmJX375ZXl5eZ8+fSZNmtS9e3e0HQYE0VXZ7faCggLcy+TJk9FyXC789hu2bkVsLJYvh0iEX37B9u1gWTzyCCQSNBBN05MnT37//fdxVzk5OehQHE5X0qWsQ4mpCafTq8w2/MkTD/TXa1VoLQyPkaqk+BOhVIg7kHHF96n77so9ieYQq4qY6DcAzY2hGK1QoxVqBnsOBOBiXSW1pTmWPIPZaDAbM803KuyVaDtO1pVrzcu15qGOnCvTi3V6sU4v1mlFGm++F9z2Zafidvp5BagEYhB/cunSpY0bN+bn5w8fPnzRokVarRYNxzBMbzcALMueO3du586dy5cvHzRo0MyZM728vNDqGBBEV1VWVsayLO6lX79+aDnV1fj1VwQE4PHH4e+Pm6ZPR0YGEhPRrx+6d0fDxcbG4l4qKirsdjuXy0X75nKxl9LyDiWmHTxxrbzCglsEB3jOeCAW7dgjAUN35yW6WBZNI2GEL0c+TIFCC6Mp2pvv5c33ilH0hFt5rclgNuZa83OseQazMc+az4JF2zHZK86bks+bkuEm4oi0Ik2gWPeTMRe3M9Y/HB3HwcLDsco+HlwpWgDLsj///POWLVvCw8Pnz58fFBSEZkJRVB83AAkJCa+88gpN0y+99FJkZCRaEQOC6KpKSkpQDxqNBo2Tn489e3DlCm7Kz4fBgNBQ/P8UFKCoCHFx8PXFH7hcREYiPR1lZWgUX19f3AvLsqWlpWq1Gu2Sy8Weu5L928nUhFPXTVVW3AFNU4ufuY/LcNCOaUWeAz2jjhenoGkWRDzoxZehLSh4cgVPHqPoCTer05plyTWYjbnWvBxrnsF8w+5yoO1YnJa0qvRzJdmlNg1uQVPUGP8IdBxHS07uK/htaeQCJU+BZrV///5PPvlk5MiR27Zt4/P5aDFD3fLy8latWmU2mxcvXhwSEoJWwYAguiqWZVEPFEWhcaqqkJ6OqircVFaGigrcimXBsqBpUBT+h6ZxE8uiUWiaRj24XC60My4Xe+Fqzm8nUw+fvl5eYcG9PHJ/THSIL9q9RwOGHS9OQROM9Ok9wqcX2gchRxguDQmXhsDNyTrzbYUGs9FgNuZa826Ys6odZrS6UrMYtyMW2P6V+o6f0Fcv1unFuhBJkAdXivbKxbqyLbk1rpp/Xlm1NGKhj8ALzcFoNC5ZsiQmJmbbtm1CoRCtQqPRrFu3Lisr680339RoNEuWLBEIBGhhDAiiq1KpVKiHoqKi6OhoNEJwMObMQe/euCktDZ9+iptMJpw5g4wMyGSIjYWnJ5RK5OSguBhqNW5yOJCeDpEIcjkapbCwEPWgUqnQzry86oeTFwyoH42PbM6j8egIesj1kR4BVyuz0CiefNn8iClorzgURyvUaIWawZ4D4VZeazKYjQaz0WA2GsxGk70CLa+0WozbUYnMRTUVRTXF503JcJNzZXqxTivS+Ak1erHOT+hLgUL7kG8rrHHVACipKX3jyqolkQu0Qg2agGXZ999//8yZM6tWrfL390erCwgI2Lhx46FDhx566KFXXnllyJAhaEkMCKKrUqlUFEWxLIu7SkpKGj58OBqBw4FIBA8P3CQWg8vFTQ4HuFx4euLaNdw0fjwGD8aPP+KHHzB5MgQCHDuGU6dw333Q6dAoSUlJuBeZTMbn89HOLHxy5OwlX1ZW23AvFIVFc0YL+Vx0EI8EDP3n5S/QGNREvwFSRoiOQ8GTK3jyGEVPuJkdlhxrnsFsNJiNBrMxz5rPgkWzMtfyaxwMboNVis34K5O94rwp+bwpGW5CjtBf5KcX67RCjZ9QEyQO5NIM2ojRko06JnvF21ffWxLxYoDIH41SXl7+3HPPTZw48euvv0abGjFiRFxc3OLFi48fP7548WKKotAyGBBEV8Xj8VQqVUlJCe5q7969L7/8MpqLTIa4ODAMtm1DZSVqazF2LOx2HD+OI0dwE0Vh6FBMmAC5HI2yZ88e3Iuvry/aH423bMW8cS+v+sHFsrircUO79euuQ8cx1Lu7RqjKs5aiwdgtmQdKairmhk4ScHjogMSMKFwaEi4NgZvNWZNvK8ix5hnMRoPZeMNsrHXZ0TSl1SLcjoRfy2ccuCur05pWlZ5WlQ43DsVRC3z0Yp1erNMKNYHiAAkjRmsxmrPxJ5X2qreuvvdK+PwQiR4NdOHChWXLlr377rtRUVFoBwQCwfvvv799+/bHHnts/fr1MpkMLYABQXRhsbGxe/fuxV0lJCSkpqaGh4ejQYYMQUQEdDr8wd8fzz0HsRhcLm4qKUFhIdRqeHiAx8OUKejTB8XFcLkgl0Ovh0oFikLDHTt2LCUlBfcSGxuLdmlgb/3MBwds+vYk7kwlF//j70PRodAUPcV/0IdpP6HhWLA/5yZeNGUui5oW7uGPDk7A4evFOr1YN9hzIAAn68q3FeRa83IseQazMcNsqLRXoYHKzGLcjlJsQQM5WWeuNS/Xmnes5CTc5FyZXqzTi3V6sS5IEijnytBijJYs/JXZYVl5bfXCsHlRHhGot4SEhA8//HDHjh0SiQTtydSpU7t16/b444//97//9fb2RnNjQBBdWFxc3N69e3FXLMsuX758586daBBfX/j64n8kEnTrhj9YrfjlF3C5GDIEPB5uksshl6M5rFixAvUQHx+P9mrahL67Dl4qMVXjDhbOHikVC9DRTND0/9zwa6XdgkbJMhc9n/TBowFDZwWN5dIcdBYcitYKNVqhpr8SfyivNRnMRoPZmGvNz7Hm5VnzWbC4M0stz2rn4nZUYjOazGSvOG9KPm9KhpuYEfkJNXqxTi/W6cU6P6EvBQrNxGjJxi1szpp3Uz9YEDa3uywK9bBr167vvvvuq6++4vF4aH+6dev2wQcfzJo16+OPP9bpdGhWDAiiCxs0aBDq4bvvvtuzZ8/48ePRdE4n9uxBYSEmT4ZGg2a1devWQ4cOoR7i4+PRLmXlly9dvavEVI07GBobOqx/KDogAYc3QdP/a+PvaCwn6/ra+Pu58vSlUdMCxN7opBQ8uYInj1H0hJvFac225BrMRoPZmGvNy7bkOlgH/qTMLMbtiHk1Aq4dzc3ssKRVpadVpcNNwBH4Cnz8hBq9WKcX6/RiHY/molHKa02V9ircTq2rdnXaB/NCnu6r6I27+v3333ft2rV582aaptFeBQYGbtq0afbs2Vu3bvX09ETzYUAQXdigQYO0Wm1OTg7uimXZWbNmnT171t/fH0107Rr27sWVK0hMxMiRmDIFPj5oDlevXp03bx7qoXv37tHR0Wh/Dp+6/vYn+8zWWtyBRMRfMGsEOqwp/oN2Zh+xu5xogmuV2XNOr30mZPzf/OMpUOjsRBxhuDQkXBoCNyfrzLcVGsxGg9loMBuN5uxSswi3o5JY0PJsTpvBbDSYjcdKTgLgULRaoNYKNX5CX71YFyIJ8uBKUT83LFm4M7vL8Z/rG+aGPNVf2Rd3kJKS8sEHH2zbto2mabRvPj4+H3zwwaxZs7Zv3y4Wi9FMGBBEF8bhcJ544om3334b91JcXDxy5Mhjx455e3ujKaKisH49XC5QFDgccDhoDrm5uffff391dTXq4cknn0Q743Kx67cf+2rXaZbFH2RS4ZjBUd/sPYs/mff4EC+lBB2WJ1823LvXgYKzaJoal/0/aT8eL0lZFPmot0COzm7m4e1BUtW4gIg+Xv4ciqMVarRCzWDPgQAMVWUj09fjdpRiM1qdk3XlWvNyrXmoI+fK9GKdXqzTijR+Qo2f0JcChdsxmrNxV07W+WH6xtog+2DPgbhFWVnZokWLvv76az6fj44gKCjotddee+GFFzZt2oRmwoAgurZZs2atXLnS5XLhXq5fvz527Ng9e/b4+vqi0SgKPB6aVWZm5tixY41GI+pBIBA8/vjjaE9MldYV/9lz5pIRdcICvd9ZOEnjLbNYa3b/fhluMdH+E0f0QAc3VTfs14JzLFg02dmy67NOvfdsyISJfgPQqQkZ7pa0M1vSzviKPMZow8cFRPTx8qfw//ol6xpux1csGu3b12A25lnzWbBoOyZ7xXlT8nlTMtxEHKFW5KcX6/RinVao8Rf5MRQDtxuWLNyLi3VtyNhscVjGqEfirxYsWLBy5UoPDw80Vl5e3v79+48dO1ZVVaVWq0eOHDlkyJBffvmlpqbm/vvvV6vVAC5fvvztt99Onz49NDQUTdavX7/ExMQtW7bMnDkTzYEBQXRtwcHBjz/++Oeff456OH/+fFxc3E8//dSjRw+0DydOnJgyZUphYSHqZ+7cuSqVCu1Gcmru8rW7S8qrUWfskKhFc0bzeQyAl54cmW4svpZZyOcxi5++j6LQ0QVJfGOUIWfLruMOeimC+ykjthj22V1O3IvZYVt97duksrQFEQ/KuGJ0UiEenvuRCiDfUrkl7cyWtDO+Io8x2vBxARG/ZF/D7Tyi7/Nc8GAAVqc1y5Kba83LseYZzEaD2Wh32dF2LE5rWlV6WlU63DgURy3w0Yt1erEuvSoT9cCC/cK4w8k6x/nehzobN26Mi4vr3r07GuvGjRubNm26fv16fHy8VqutrKy8evWqr69vWlqa1WodOnQo3EpLS0+fPj1+/Hg0k3nz5k2fPn3QoEEhISFoMgYE0eW9+eab33zzjc1mQz3cuHGjf//+q1evfu655yiKQttxuVyrVq167bXXHA4H6kehUCxduhTtxk8Hk9dsPmR3OOHG5XIWzhoxaWQP1OFxmXcWTJq95MvHJ8dq1XJ0Co8GDD1bdh23I2YES6Km+ggUcZ6Rb1/5Or0qD/WQUJScbDK8FPlQvGc0OqMQDxX+Kt9SuSXtzJa0M7iDsf7hcBNyhOHSkHBpCNwcrCPHkme0ZBkt2TfM2VmWHKvTirbjZJ251rxca96xkpOoNxbsV1k7ba6aKX4TAZSWlh44cGDnzp1oLKfTeeLEieTk5OnTp48ePVokEtXU1JSXl3t4eOzduxctiaKoNWvWvPjii9u2bUOTMSCILi8gIGD+/Pn/+te/UD82m23u3Lk7duz46KOPunXrhrZw5syZ559/PikpCQ2xbNkypVKJdsBqs6/ccODgiWuo46OSvr1gUlSIGn+l9vJ4b/GUcL03OotYVUSwRJNRnYdb/CPsAR+BAoBeov647z+2ZO7fnpXgYl24l/LaqmUXN9+n7vNixBQhh4/OJVjmiYYIlCrD5d64HYZiAsUBgeIA1CmvNRnMRoPZaDAbc635RTXF6CC+y9lV46yZFvDQG2+88eqrr6IJysvLU1JSVCrVyJEj5XI5AB6PJ5FI0CrUanXPnj337ds3duxYNA0DgiCAFStW7N27Nzk5GfV25MiRmJiY2bNnL1myRKfTobWkpqa+9dZbX3/9tcvlQkMMHjx4/vz5aAey8suXrt6VmV2COgN761fMG+chEeB2okLU6FweChi86soO/FW8V/QY376ow6OZp0PGx3lFr0zZnmstQT0cKDibbDIsiZ7aUx6ETiRIqqIpysWyqB8Jl3eqKKuvlz+HonAvCp5cwZPHKHrCzeK0ZFvyDGajwWw0mI35tgIX60J7tTt/f0FZYa29tkePHmgCi8VSWVmpUCjkcjnqUBQFt927dx85ckQoFAIwmUxWqxXNbf78+Q8//PCYMWMoikITMCAIAhAIBNu2bevbt6/VakW92e32DRs2bN68efr06c8991y/fv3Qko4ePfrxxx/v3LnT6XSigZRK5VdffcXhcNDWjiZlvPnxL9XmGrhRFKZPin122iCaotBljPLp/VnGL6U1lagj50leingIt+gmC/w0dv769N0/5yaiHgpsZS+e++Rv2vhnQyZwaQadgojh+oo8cs0VqJ/LZQXTfvtSwRcO8w0eFxA51DeYoWnUj4gjCpeGhEtD4OZgHQW2IoPZaDAbDWbjDXNWrasW7UlSzYVec7q7WBdN0WgshmG4XK7NZrPb7Xw+H38VExMzbtw4X19fABcvXvz+++/R3AQCwahRo3799df77rsPTcCAIAi3qKiojz/+ePbs2SzLoiFqa2s3u8XExEyfPn3KlCmBgYFoPmlpad9///0XX3xx5coVNAqHw9m6dau/vz/alNPp2rDj+Fe7TrMs/iCTClfMGzegVyC6GC7N/E0b/1nGL6izIPxBBU+K2xEzgoURDw326vbvq9+U1FTiXlws+132sXPl6UujpoVK/dAphHiocs0VaIjyGusPNy7/cOOySiAeow0bFxDZ31vHoSg0BEMxWqFGK9QM9hwIwMm68m0Fuda8HEuewWzMMBsq7VVoaxdqL32U8dnzwU9yKA4aRaVSBQYG/v7771evXu3VqxfcWJaFm1qt7tu3r16vB+Byufbt2wfg6tWrH330UVFRUURExIIFC+RyOZpm9uzZzzzzzH333YcmYEAQRJ2ZM2fm5eUtW7YMjXLObeHChb179x4+fPjQoUPj4+NVKhUarrCw8NixY0eOHDl06NDly5fRBBRFrV+/fsKECWhTpkrra+t2J13OQp2wQO93Fk7SeMvQJU3Wxn1145DVWQNgvKb/EO/uuKtYVcRnsQtWX/v2aPFl1IOhuuC5M/95PHDk3/WjaIpGBxfs4ZmQn4lGKbWZv0DDddYAACAASURBVE4//3X6eSVftHX4tGiFDxqLQ9FaoUYr1PRX4g/ltSaD2Zhrzc+x5hnMxjxrPgsWrS6x9IzdZX8h5BkuzaDheDzeoEGDEhMT16xZ89xzz4WFheXm5h49ejQmJgYATdMcDodhGAAcDoeiKAAKheKVV17hcrlvv/32tWvX+vTpw+Vy0QRSqVSlUmVnZ/v7+6OxGBAE8SdLly4tKipat24dmuC825o1awBotdpoN39/f19fXz8/P6FQKJVKGYYBUFtba3bLyckpLCy8cePGlStXLl++XFBQgGby1ltvPfXUU2hTyam5y9fuLimvRp2xQ6IWzRnN5zHoqqSMcKxv3x9yjvsKlXPDJqEe5DzJmz1mHi66uPrqt1UOK+7FwTq3GA6cKUtdEjVNK/JERxYi80TTUMDz0XHRCh80KwVPruDJYxQ94WZxWrMtuQazMdeal2PNM5hv2F0OtIqz5RdWp324IOx5Hs1DA1EU1aNHj5dffvmLL7547rnnqqurtVrt5MmT/f39cQfe3t4AKIricDhOpxPN4YEHHti1a9fcuXPRWAwIgvirtWvXyuXyf/7zn2gOOW779+9Hq6MoauXKlYsWLUKb+ulg8prNh+wOJ9x4XGbBrOGTRvZAl/dIwNCfcxMXRz4q4vBRb8O8e0Z66P51Zfv58nTUQ0qF8anTq58KHveg/yAKFDqmEA8VmoAC/tl3zOOhfdDCRBxhuDQkXBoCNyfrzLcVGsxGg9loMBuzLNk2Zw1azKWKlH9de//l8BeEHCEaiGGYHj16vPXWW7W1tSzL0jTN5/N5PN6iRYtYluXz+XCLi4vbsWOHUCikaRrAlStXysrK9Ho9wzBosiFDhmzcuHHu3LloLAYEQfwVRVGvv/56QEDAM88843A40DHxeLwtW7ZMmzYNbcdqs6/csP/giVTU8fH0ePvFiVEhahCAr1D5r15P9lQEo4F8BPI1Mc/szj310fWfbE477sXmtH+Y9tOp0muLIh/15HugAwr28ERj0RT1dr/7Hw3uhVbHoThaoUYr1Az2HAi38lqTwWw0mI0Gs9FgNprsFWhWqVXX3766enHEfAkjQUOwLEtRlMgNfyIUCvEnXDe4lZeXr1q1at68ed7e3hRFocm4XC6Hw7Hb7VwuF43CgCCI25k9e7a/v/+MGTMKCwvR0eh0um3btg0cOBBtJyu/fOnqXZnZJagzsLd+xbxxHhIBiDp9lWFoFArURL8B3eX6d1K2pVXloB7OlKbOTHx3fviUUere6GgUfKFKIC61mdFAHIpa1X/CFH13tA8KnlzBk8coesLN7LDkWPPWZ2wqqilGMzGYjRsytywIm0uBQr1ZLJYNGzbYbLalS5euXr3abrfPmzdPIpHgDux2+/Llyx955JEePXpwOBw0k4iIiNTU1G7duqFRGBAEcQejR4++dOnSE0888csvv6DjeOCBB/773/8qlUq0naNJGW9+9Eu1pQZuFIXpk2KfnTaIpigQzSdQ7PNJv3/syErYlLHPwTpxL9UO61spXx0rvrwg4kEPrggdSrCHqtRmRkNwKHrNwIkTddFor8SMKEwaXOWoRnOgQEXLIkZ4D+mriKFAoYFYlnW5XABcbrirAwcOnDp16tKlS++///7ChQtHjBjB4/HQZD169EhOTu7WrRsahQFBEHfm5eW1e/fu9evXL1u2zGQyoX3z9vZ+9913//73v6PtOJ2uDTuOf7XrNMviDzKpcMW8cQN6BYJoARyKfkw3vLci+J2UbdmWYtTD4aKLVyuNi6KmxihC0HGEeKhOF2Wh3hia/k/cA2P9I9C+FdlKrE4rmsaDKx3iGT/SZ4g33wutYrwbmlt4ePiOHTvQWAwIgrgrmqaff/75qVOnLlmyZOPGjSzLov2haXr69Olr165VqVRoO6ZK62vrdiddzkKdsEDvdxZO0njLQLSkSI+Az/ov2Jp5YHvWYRfL4l4KbaaF5zZM8Os/N3SSgMNDRxDkoUK9cWnOf+IfGKMNR7t3w2JEE+jFuhHeQwZ5DuTRXHR8SqWyvLwcjcWAIIh6UCqVGzZseOaZZ954441du3axLIv2gabpqVOnLl++PDIyEm3q4rXcV9/fXVJejTpjh0QtmjOaz2NAtDw+zX06ZHyMMnTVlR3FNRW4Fxbsz7mJySbD0qip4R7+aPdCPDxRPzya8+GgKaP8QtERGM3ZaDgBR2C7WL1y2hsBIn90InK5vKKiAo3FgCCIeouJifnxxx/Pnz+/cuXKH3/80W63o+0IBIJHH3108eLFERERaGs/HUxes/mQ3eGEG4/LLJg1fNLIHiBaV19l2JYBL69P3/1zbiLqwWgufD7pg0cDhs4OHstQHLRjoTJP1IOQw90w5KFBaj06iCxLDhpCJ/If6TM0XjXgybWzA570R+fC4/Fqa2vRWAwIgmig3r17f/PNNwUFBZs3b964caPBYEDrioiIePrpp5944gmlUom2ZrXZV27Yf/BEKur4eHq8/eLEqBA1iLYgZgQLIx7qowxdc+27SrsF9+JkXV8bfz9Xnr40alqA2BvtlVrkIWJ4Fkct7kzI4W4c+nCcTyA6DoPZiHrg0kyMvNcI7yHdZJFwY1kWnY7ZbBaJRGgsBgRBNIparV7ilpKSsnPnzu3bt6empqIlBQUFTZgw4eGHH46Pj6coCu1AVn750tW7MrNLUGdgb/2KeeM8JAIQbWqYd8+e8qB3r+48UXIF9XCtMnvO6bVPBN03NWAYTVFofyggyEN5uawAdyBiuBuHPDLQR4eOo9JeZbJX4K58BN7DvQYP8x4kZSTo7Ewmk1wuR2MxIAiiaaLdXn/99ZSUlISEhKNHjyYkJOTn56M56HS6IW5Dhw4NDQ1Fe3I0Kf3Nj/ZVW2rgRlGYPin22WmDaIoC0Q4oeNK3e87anXvq4+s/W501uJcal/3T9D1ny9IWRT7qLZCj/Qn18LxcVoDb8eAJNg99tLenHzqUG5Ys3AEFKloWMcZnZG9FDwoUbuFyudDplJaWKhQKNBYDgiCaSbTb888/DyAnJyclJeXSpUtXrlzJyMgoKCjIycmxWCy4M4lE4u/vr1arg4ODo6Oju3Xr1r17dx8fH7Q/Tqdrw47jX+06zbL4g0wqXDFv3IBegSDaEwrURL8BfZVhK69sSzYZUA9ny67POvXesyETJvoNQDsT7OGJ2/HgCbYMm9pLpUFHc8OchVvIubLBXgNHeQ/z5KtwZx4eHpWVlR4eHuhELl++HB0djcZiQBBEC9C6jRkzBn9SXV1dXFzMsmx5eTnLspSbXC6nadrLy0ssFqMjMFVaX1u3O+lyFuqE633eXjBR4y0D0S75CpXvxzy3PSthc+Y+u8uJezE7bKuvfZtUlrYg4kEZV4x2I1imwi1kPMHnw6d1V/qiAzJasvEnYdKQseqRfRW9ORQHd+VkXdrekZcuXYqPj0dzoGlao9HU1tYC8PPzczgcNE2j1V26dOnpp59GYzEgCKK1SNzQkV28lvvq+7tLyqtRZ+yQqEVzRvN5DIh2jKbox3TDB6gi3rmyLb0qD/WQUJScbDK8FPlQvGc02ocQD0/8lUog/nL4tHC5NzomozkLgIgjHKDqN0Y9UivU4K7KasxnSm8cLkg7XJBW62f3OHc2Pj4ezUEgEEydOpWiKACPPfYYy7JoCxkZGYGBgWgsBgRBEPXz08Hk1Zt+czhdcONxmQWzR0wa0R1EBxEk8f247z+2ZO7fnpXgYl24l/LaqmUXN9+n7vNixBQhh4+2ppMouDTH7nLCzVMg/mrEY6EyL3RMNa4aIUf4pH7GIM8BPJqHO3CyrmsVBYcL0hIK066Y8lj8f367fmE+mgHrYitLKq1VVoVawRfzWRdbnl/udDjlPnKugIvWUl1dLZFIKIpCYzEgCIK4F6vNvnLD/oMnUlHHx9PjnQUTI4PVIDoUHs08HTI+zit6Zcr2XGsJ6uFAwdlkk2FJ9NSe8iC0KYamdRJFemUJAF+Rx1cjHguUKtFh8Wn+m92W4Q5KaqqPF2UkFKSdKM6osttwOxatR0VFhUwmQ9OwLJt/Pf/asWtRQ6JCYkOqS6vP7j7LE/BiJsRwBVy0lr179953331oAgYEQRB3lZVfvnT1rszsEtQZ2Fu/Yt44D4kARMfUTRb4aez89em7f85NRD0U2MpePPfJ37Txz4ZM4NIM2k6wTJVeWaIReXw9cnqARIGWd6Esu5fSH63CybouluUcLkxLLM68YspjcS9h6l27ds2YMQNNQ3PogG4BJVklGUkZMm9ZztWcWktt5OBIqUqKVrR79+7//Oc/aAIGBEEQd3Y0Kf3Nj/ZVW2rgRlGYPin22WmDaIoC0ZGJGcHCiIcGeXX799VvSmsqcS8ulv0u+9i58vRlUY+FSDVoIyEeninigq9GTPeXyNHy/nv92OcZiYfHLqRAocXkmMtPFmeeLM48XpRe7ahBvRVSth2/7JoxYwaaTCQThfQLOb/3/MmdJyma0nXXqUPUaEW5ubkSiUQul6MJGBAEQdyO0+nasOP4V7tOsyz+IJMKX39hXP+egSA6i/6qiP/GLlh97dujxZdRD4bqgmfPrHs8cOTf9aNoikarG+IbND0kRi2SouV9dO3wx6mHAVyrKIiU+aJZ2Zz282XZJ4szDxekZlQVo1FYwGdQj+PHj8fHx6PJvAK9vHReR746EjYgLLB3IMNj0Io++OCDZ555Bk3DgCAI4hamSutr63YnXc5CnXC9z9sLJmq8ZSA6FzlP8maPmYeLLq6++m2Vw4p7cbDOLYYDZ8pSl0ZP8xN6onX18/JHq/jw2u+fpCbA7VhReqTMF80hx1x+sjjz98LUxKLMGpcDTSbuFbzu/XXx8fFoslprrb3WLpQKGR7DsixaUVFRkcFg6NmzJ5qGAUEQxF9dvJa7/P2fS8vNqDN2SNSiOaP5PAZEJzXMu2eEh/+/ruy4UJ6BekipMM45tXZu2OTxmlh0Oh9c+319agLqHCtMnxM6GI1ldtQkFhuOFaUfK0rPs5jQrC5XF4zrH7t79+4JEyagCVxOV86VnBJjSdiAMGuVNSMpo8eoHjwhD63i9ddfX758OZqMAUEQxJ/8dDB59abfHE4X3HhcZsHsEZNGdAfR2akFyrUxz+7OPfXR9Z9sTjvuxeKsSa3MHq+JRefywdVD69OO4E/Ol2VX2W1SrgANkWMu/70wNaEg7WxpVq3LgWalFSsGegUN8wkb6B1MDXM9+OCDo0eP5vP5aKzy/PIbF27IfGS9x/XOOJORnZLtpfMK6B5AURRa2Pnz53k8Xvfu3dFkDAiCINysNvvKDfsPnkhFHR9Pj3cWTIwMVoPoGihQE/0GdJfr30nZllaVg7vyFSqfDZ2AzuU/Vw9tSDuCv3KyrsTizNGaKNyLxVF7usRwuDDtaGF6gbUCzUrI4fVSaoeqw0aqIzQiOf6Hh1deeWXZsmXvvfceGsVWbcs8m1ljqek+srtUJQ3qG1SWU2Y4a5Cr5TJvGVqSzWZ79dVXv/jiCzQHBgRBEEBWfvnS1bsys0tQZ2Bv/esvjJOKBSC6mECxzyf9/rEjK2FTxj4H68Tt0BS1OGqqiMNHJ/Kfq4c2pB3B7RwryhiticIdpFcVJRSknSzOPFNqdLicaFZasWKYT9gwdXhflY5Lc3A7gwcPPnDgwM8//zxx4kQ0ilKjVGlVXoFeADw8PSKHRFYWV1IUhRb28ssvL126VKFQoDkwIAiiyzualP7mR/uqLTVwoyhMnxT77LRBNEWB6JI4FP2YbnhvRfA7KduyLcW4xVTd8J7yINxdYSFSUxEeDh8f3GSxICMDNhv69cNNFgsyMmAwwGaDRIKgIAQHg8tFG3kv5cDm9BO4g6NF1/FXplrLqRLDyeLMIwXXC22VaFYihtfPM3C4T/gQn1AfoQfqYcWKFY888khERERoaCgaSCARBPcLxp/4hvn6hvmihX3++ecajSYuLg7NhAFBEF2Y0+nasOP4V7tOsyz+IJMKX39hXP+egSC6vEiPgM/6L9iaeWB71mEXy6JOoFg9U38f7unKFaxbh/nz4eODm8rL8f33KChAv36orsbx4/jxR1RVgaLAsvDxweTJGDQINI1W9+/L+7dmnMSdFVorr1cWBUu9rlbkJxZnnizOPF1yw8m60KyCpV7D1OEDvYL6qXQMzUFDMAzz2WefzZgx47///a9arUa7d+jQocTExI8//hjNhwFBEF2VqdL62rrdSZezUCdc7/P2gokabxkIwo1Pc58OGR+jDF11ZUdxTQUALs282m06j2bQaCyLtDR8/jk8PbFsGfz8kJqKL77Ap59Cp4NOh9a19srBrRkncS+vXdiVZzGV1FSjWSl4olhP/UCvoKHqMG+BFE2gVCo/+uijOXPmbN26ValUoh07efLkp59++uWXX6JZMSAIoku6eC13+fs/l5abUWfskKhFc0bzeQwI4q/6KsO2DHh5XeoPBwrOPhk0Nljii6aw2ZCcjPx8LFmCyEjc1KcPqquxdi2OHYNOh9bCgl11af8XmYmoh+TyHDQTDkV3V/gN9gkd7B0SKfOlKQrNJDAwcN26dU888cQnn3yi1WrRLv3+++8bN27cvHkzwzBoVgwIguh6fjqYvHrTbw6nC248LrNg9ohJI7qDIO5AzAiWRk8bpe7dVxmG+ispwe7dSEvDTSYTLl6Ejw+qq5GTA6kUYWH4A03DywtqNTIz0VpYsP+6tO/LzFNoLUq+uJ8qcKg6bJhPmIwnRMsICgr65JNPnnnmmdWrV0dERKCd2b59+6+//vr5558zDIPmxoAgiK7EarOv3LD/4IlU1PHx9HhnwcTIYDUI4l5iVRFokJoaZGXB5cJN1dUoK4OPD1gWLhdoGhSF/6EoUBRcLrQKFuy/Lu37MvMUWhiHoiNk6qE+YcPUYVFyXwoUWp5Wq/3iiy+ef/75v/3tb48++ijah9ra2sWLFyuVyo0bN9I0jRbAgCCILiMrv3zp6l2Z2SWoExcTtGLe/VKxAATREtRqPPEEBg3CTfn5+PxzlJdDLIavLxISYDAgLAw3uVwoLUVREQYMQMtjwa68tO+rzFNoMSq+JN47eJg6LM4rWMoVoNUplcpt27atXLny//7v/9555x2xWIw2lZaW9vLLL//jH/8YOXIkWgwDgiC6hqNJ6W9+tK/aUgM3isL0SbHPThtEUxQIooVwOBCLIZPhpupq8Pm4SShEt25QKPDll5g1C15eMBqxbx8YBgMHAnC5XLW1tSzLCoVCNDcW7FvJe7cbzqC5cSi6h0I7XB02wCsoSu5LgUKboihq6dKliYmJU6dOffbZZ8ePH4+2UFtb++9//zszM/PTTz/18fFBS2JAEERn53S6Nuw4/tWu0yyLP8ikwtdfGNe/ZyAIovXRNCIj8cgj+OUXrF0LgQDV1XC58PjjCA0FYLPZzpw5c+7cueHDh3fv3p3D4aCZsGDfuLjnmxtJaD5asWKgV9BAr6B47xAJw0c7M2DAgO+///69997btm3b4sWLu3XrhtbCsuwPP/ywadOmuXPnLl++HC2PAUEQnZqp0vrqut1nL2ehTrje5+0FEzXeMhBEiwoOxhNPICgIf/DwwKhRMJtxk1yO+++Hnx9SUmA2QyZD9+7o0QMcDgCapvl8fmFh4eeffx4dHT1y5MjAwEA0GQv27eS939xIQpMJONzeSv+BXkEDvIKi5Rq0b1wud8mSJYWFhatWrSovL1+4cGG3bt3Qklwu1+7duz/77LP777//+++/5/F4aBUMCILovC5ey13+/s+l5WbUGTskatGc0XweA4JoaQEBCAjA/0iliI/H/0iliI9HfDxuIRAI+vTp4+Xldfz48YsXL169ejU+Pn7o0KFKpRKN5WLZf178+VvjOTSNWujxSrcxg71DRQwPHYqPj8+aNWtyc3PXrVuXkZHx0EMPTZkyhc/no1kVFRVt2rTpxIkT999//zfffCMQCNCKGBAE0Un9dDB59abfHE4X3HhcZsHsEZNGdAdBtHtcLjc4OFij0fTo0ePEiRNHjhxJSkoaOXLkwIEDhUIhGsjFsq9f/Pk74zk0manWOtQnTMDhomPy8/P797//XVNT8+23386YMUMikYwbN27MmDFSqRRNkJWVtWvXriNHjnh4eMycOXPx4sVoCwwIguh0rDb7O+v3/3YyFXV8PD3eWTAxMlgNgug4hEJhz549g4KCkpOTExMTv/vuu+PHj0+cOLFHjx40TaN+WLBvJe/5zngOzcHmtCeVGgd5h6Aj4/P5093Ky8t/+eWXF154wWKx+Pr6DhgwoGfPnnq9XigU4q7KysoyMjLOnDmTlJRUXV2t0WgmTpz4zDPPcLlctB0GBEF0Lll5ZUtW7zLklKJOXEzQinn3S8UCEERHQ1GUh4dHXFxcWFhYUlLSmTNnNm7cGBkZOWHChMDAQNTD4YK048UZaD5HC68P8g5Bp6BQKB5zA5Cfn3/q1Klvv/3WYDDYbDa4URTF5/N5PJ7ZbKYoqqamhsPhAFAqlUFBQX369Pn73/8ukUjQPjAgCKITOZqU/uZH+6otNXCjKEyfFPvstEE0RYEgOiyapr29vUePHt2tW7dTp06dPHly5cqVo0aNGj58uEAgEIlENE3jDoarw4erw4tsVedKs86VZZ0rzUqrLHSyLjTWsaJ0dEa+vr4PuOGvHA5HdXW1XC5Hu8eAIIhOwel0bdhx/Ktdp1kWf5BJha+/MK5/z0AQRKfA5XIDAgK8vLycTufatWu9vb3LysooihoxYkRISAjuylsgHesXPdYvGkC1o+ZiWfa5suyzpcZL5bk2px0NcaO6NMdcrhUr0DUwDCOXy9ERMCAIolMoLqv+6WAyy+IPkcHqdxZM9PH0AEF0LkKhUKlUqtXqCRMm5ObmHj58uFevXmgICcOP9w6J9w4B4GRd1yoKzpVlnS/NPlN6o6zGjHo4WpQ+Td8PRDvDgCCITkHt5fHavPsX/ftHF8uOHRK1aM5oPo8BQXRSIpEoJCSEoijWDY3FoehouSZarpkRNABAjrn8bFnW+bKsc6VZmVXFLG7vWFH6NH0/EO0MA4IgmlttbW1SUpKfn59Wq+VwOGgt8TFBTz4c5+MpHTc0GgRBNJxWrNCKFZP9ewIoqam+XJ57riz7XGnWZVOu3eVEnVPFhlqXg0czINoTBgRBNDebzfbZZ58FBAQMGzYsKirKy8uLoii0ilkPDgBBEM3Bky8Zpg4fpg4HYHXWXjUVnC/LOluWda40q8puO1eaNcArCER7woAgiOYmkUhWrFjxxRdffPrpp/379x8yZEhoaKhEIgFBEB2TkMOLUQXEqAKeBBwu55WKfAGHC6KdYUAQRHOjaVqn073yyitJSUnbt2+/cuXK4MGDBwwYoNPpuFwuCILoyBia00OhBdH+MCAIomXweLyBAwdGRUXt2bPn4MGDqamp8fHxPXv29PHxoWkaBEEQRLNiQBBEi6EoSi6XT5s2LT4+/ttvv922bVtKSsqgQYMiIiJkMhkIgiCI5sOAIIgWRtN0YGDg3Llzz58//9NPP23dujU2NjYuLk6n0/H5fBAEQRDNgQFBEK1CKBTGxcVFREQcOHDgyJEjGRkZDz74YI8ePWiaxk3FxUhLQ1ERKAo+PujeHWIxKAoEQRBE/TAgCKIVKZXKRx55JDY2ds+ePUVFRSzL4qaCAuzcibNnYbPhJg4HY8fiwQchFIKiQBAEQdQDA4IgWhdN00FBQc8++yxFURwOBy4Xdu/Gr7/ioYdw//1wOvHdd1i3DiEhiI0FhwOCIAiiHhgQBNEWuFwu/lBRgQMHMGAAxo+HSoWb5szBvn34+WfExIDDAUEQBFEPDAiCaFt5eSgrQ3g45HL8gcdDv344dw5OJwiCIIj6YUAQRNtyOnETw4Ci8D9cLhwOsCwIgrhFZGTk7NmzxWKxTqd7+OGHAwICQBAAA4Ig2panJ0QiZGfDbIZUipscDly7Bp0OHA4IgriF1g2AtxsIwo0BQRBty9sb/fohMRGRkYiNBcvi9Glcvoxly8AwIAjiT1xOV/rp9NM/no6fFh/YM9DldF1PvH5299khjw/x7+YPomtjQBBE22IYPPggNmzADz/gwgWwLC5cwIgRGD4cHA4IgvgTmkP7RfrpjfqkH5N89D4VRRWpx1MDewX6d/MH0eUxIAiizUVFYe5c/PYb0tJAURg6FJMnQyYDRYEgiL8Sy8XB/YJLjCVHvzoqkokcNY4+4/uAIAAGBEG0B2Fhdr3eZrOJRCIOhwOCIO7MS+cVHhe+5/09Kq1q2KxhAqkABAEwIAiifcjPzz99+vTw4cNVKhUIgrgziqL4Er5EKRF4CLz13iAINwYEQbQP+fn5+/bt69Wrl0qlAkEQd8CyrKnAlH46XSAV8EX8C/su9H+wP4fhgOjyGBAEQRBEx1FrrTVeNJbnlo+dO7Yst+zC/gvaaK1/tD9FUSC6NgYEQRAE0UG4nK78tPzMc5kRgyN8gn1EMlGxsfjC3gue/p4imQhE18aAIAiCIDoIW7WtJKtE5i2LHBIJQOopDRsYdvHAxZyUnLC4MBBdGwOCIAiC6CBEMlHfSX3xJ+oQtTpEDYIAGBAEQRAEQXR8DAiCIAiCIDo+BgRBtA9yubx79+5isRgEQRBEwzEgCKJ98PPzmzx5skKhAEEQBNFwDAiCaFMupyv9dDpXwNWEawIDA51254V9F7z13uoQNc2hQRAEQdQPA4Ig2pq53Jx1KYsv5KvD1MZkY0pCikKjAEEQBNEQDAiCaFM0hw4dGJqfnp9+Jp1m6Av7LgTFBKlD1PT/0x78x8ac53Ecf03nrbqjGbNbFN3msiL9Urud7FDqSJtFGv7Y4w+SwYlBCbmGP/wm/EETkm4JDk1IjERQiftLRLa9mz/konsi1O0q0j/4o36VaCebkbvtyCWTNGnTk61zif20z8fDnyUAwICZAHxsuZ/mfvnN/zzvrQAABr9JREFUlz/85YeOxx1ZWVlFM4uyc7IFAHgfJgC/AQWTCnJG5Nz/+/35f5ofHB30ZfkEAHgfJgC/AV0dXb/865fcvNyfX/+c7k4PGz5MAID3YQLwsXX/u/unv/30SfCT0j+UPmx+ON4b/3nx537zCwAwYCYAH9vjfz7ueNzx1byvCqcUdnV0/fjXH0cVjgqEAj6fTwCAgTEB+Ki6XnTdv35/7MSx473xObk5X8//+vuT37f9o23KN1Ms2wQAGBgTgI/KhtnE6RNH/250IBiQ9FnBZ9MXTbds8/l8AgAMmAnARzXi0xHe7z31MmHaBAEA3pMJAADAfSYAAAD3mQAAANxnAgAAcJ8JAADAfSYAAAD3mQAAANxnAgAAcJ8JAADAfSYAAAD3mQAAANxnAgAAcJ8JAADAfSYAAAD3mQAAANxnAgAAcJ8JAADAfSYAAAD3mQAAANxnAgAAcJ8JAADAfSYAAAD3mQAAANxnAgAAcJ8JAADAfSYAAAD3mQAAANxnAgAAcJ8JAADAfSYAAAD3mQAAANxnAgAAcJ8JAADAfSYAAAD3mQAAANxnAgAAcJ8JAADAfSYAAAD3mQAAANxnAgAAcJ8JAADAfSYAAAD3mQAAANxnAgAAcJ8JAADAfSYAAAD3mQAAANxnAgAAcJ8JAADAfSYAAAD3mQAAANxnAgAAcJ8JAADAfSYAAAD3mQAAANxnAgAAcJ8JAADAfSYAAAD3mQAMAdOmTauuro7FYvow1dXVx48fl+T3+7u7u9UjnU7v2LEjHo+nUqnKysr6+vr8/Hz1sm7dulOnTu3bt2/Pnj16t7a2tr179zY2NkqaM2fOoUOHCgoK1Fc6nd6xY0c8Hk+lUpWVlfX19fn5+QIw5JkAYMD+nHHlypVFixaplwMHDjQ0NDQ1NY0ZM2bNmjXRaDSRSKjHwYMHL1++fPz48a1bt06YMGH58uV6h5MnTy5ZsuTEiRPJZHLDhg3RaPT69evq68CBAw0NDU1NTWPGjFmzZk00Gk0kEgIw5JkADHbRaPTWrVurMmbMmNHc3Kz/t/r6+u3bt4fDYUl1dXXFxcUPHjzwPE/SpUuXamtrGxsbI5FIUVHR4sWLCwsLy8vL9d/U1dUpIxQKVVVVLVu2TP3U19dv3749HA5LqqurKy4ufvDgged56uXo0aOHDx9+8eJFJBI5cuRIJBIRgMHOBGCwu3jxYltbW3V1dSwWUz+xWOzs2bPqZ/fu3TU1NRqAV69etbe3l5aWKmPy5MmBQKClpcXzvBs3bmzcuPHatWuRSETSvHnzLl68GI1GE4mE53l6tydPnsTj8YULF6qvV69etbe3l5aWKmPy5MmBQKClpcXzPPV4+PDhli1bEonE1KlT79y5c+HChUgkIgCDnQnA0BbP0AdIJpOSRo4cqR6hUCiZTEqaOXPms2fP1Mv8+fOfPHmid4vH46tWrZJUUlJy9epV9ZVMJiWNHDlSPUKhUDKZVC/Dhg3Lzs4OBoM5OTllGQIwBJgA4MMEg0FJXV1d6tHZ2RkMBvVrzp07t2LFCmW8fv06FApJisViK1eufPbsWU1NzaxZs+7duxcIBNQjGAxK6urqUo/Ozs5gMKhevvjiiwsXLmzduvXly5clJSWbNm0Kh8MCMNiZAAwBWVlZeodYLHb27Fn1s3v37pqaGg1AXl5eQUHBzZs3y8rKJLW2tqZSqXA4rF/zxwz14/P5xo0bt2vXrhMnTrS1tZWUlKhHXl5eQUHBzZs3y8rKJLW2tqZSqXA4rL6+zXj79u358+fLy8ufPn0aCAQEYFAzARgCxo0bd/fu3e7ubjNTX/EMfZj169fX1taWl5fn5+dv3ry5oqLC8zy9p3Q6vXTp0l27dk2aNOn58+f79+8fO3as53mSqqqqHj161NTUJGn9+vW1tbXl5eX5+fmbN2+uqKjwPE+9NDY2JhKJ1atXFxYWptPpN2/evH37VgAGOxOAIWDbtm1VVVXHjh2bOnVqc3Oz/lenT59eu3atMnw+n6SOjo5Ro0bt3Lmzs7Nz7ty5qVSqsrLyzJkzen9+v3/FihUbNmxoaWkJhUKzZ89OJBLDhw9XXzt37uzs7Jw7d24qlaqsrDxz5oz6qqiouH379oIFC9rb24uKii5dupSbmysAg50JwBAwa9as1tZWfbCqDPXj9/u/y9CH+TZD/Zw+fVo9/H7/dxl6h+zs7G0ZAjCUmAAAANxnAgAAcJ8JAADAfSYAAAD3mQAAANxnAgAAcJ8JAADAfSYAAAD3mQAAANxnAgAAcJ8JAADAfSYAAAD3mQAAANxnAgAAcN9/AOzaWUPzjtukAAAAAElFTkSuQmCC", - "text/plain": [ - "883×753 Array{RGB{N0f8},2} with eltype ColorTypes.RGB{FixedPointNumbers.N0f8}:\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fd6 = getfluxdiagram(ssys6,1e-3;speciesratetolerance=1e-4)" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "d82e3be4", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plot_composition_comparison (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# function plot_composition_comparison(solutions, t, tol, exclude, x_labels)\n", - "# # Prepare data storage\n", - "# species_dict = Dict{String, Vector{Float64}}() # To collect mole fractions for each species\n", - "\n", - "# # Iterate through each solution\n", - "# for (idx, bsol) in enumerate(solutions)\n", - "# # Get mole fractions and species at the specified time\n", - "# mole_fractions = molefractions(bsol, t)\n", - "# species = bsol.domain.phase.species\n", - "\n", - "# # Filter species based on threshold and exclusion list\n", - "# for (i, mf) in enumerate(mole_fractions)\n", - "# species_name = species[i].name\n", - "# if mf > tol && !(species_name in exclude)\n", - "# # Initialize vector for each species if not already present\n", - "# if !haskey(species_dict, species_name)\n", - "# species_dict[species_name] = zeros(length(solutions))\n", - "# end\n", - "# # Assign the mole fraction for the current solution\n", - "# species_dict[species_name][idx] = mf\n", - "# end\n", - "# end\n", - "# end\n", - "\n", - "# # Convert species data to arrays for plotting\n", - "# species_names = collect(keys(species_dict))\n", - "# num_solutions = length(solutions)\n", - "\n", - "# # Sort species for each solution based on mole fractions (descending order)\n", - "# sorted_species = sort(species_names, by=name -> -maximum(species_dict[name]))\n", - "\n", - "# # Plotting each solution individually\n", - "# clf() # Clear the current figure\n", - "# bar_positions = 1:num_solutions\n", - "# width = 0.35 # Width of each bar\n", - "# color_cycle = get_cmap(\"tab20\", length(sorted_species))\n", - "\n", - "# # Initialize bottom values for stacked bars\n", - "# bottoms = zeros(num_solutions)\n", - "\n", - "# # Plot each species, stacking from the highest mole fraction down\n", - "# for (color_idx, species_name) in enumerate(sorted_species)\n", - "# # Get the mole fractions for the current species across solutions\n", - "# current_data = species_dict[species_name]\n", - "\n", - "# # Plot bars for the current species\n", - "# bar(bar_positions, current_data, width, bottom=bottoms, color=color_cycle(color_idx), label=species_name)\n", - "\n", - "# # Update the bottom values for stacking\n", - "# bottoms .+= current_data\n", - "# end\n", - "\n", - "# # Formatting the plot\n", - "# xticks(bar_positions, x_labels)\n", - "# ylabel(\"Mole Fraction\")\n", - "# legend(title=\"Species\", loc=\"upper right\", bbox_to_anchor=(1.2, 1))\n", - "# title(\"Liquid Phase Composition at t = $t\")\n", - "# tight_layout() # Adjust layout for better appearance\n", - "# end\n" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "id": "b1829469", - "metadata": {}, - "outputs": [ - { - "ename": "MethodError", - "evalue": "MethodError: no method matching plot_composition_comparison(::Vector{Simulation{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, SparseArrays.SparseMatrixCSC{Float64, Int64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Sundials.CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}, Vector{String}, ReactionMechanismSimulator.var\"#F#675\"{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, SparseArrays.SparseMatrixCSC{Float64, Int64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Sundials.CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Matrix{Float64}, Matrix{Float64}}}, Matrix{Float64}, Vector{Species}, Vector{ElementaryReaction}, Vector{Float64}}}, ::Float64, ::Float64, ::Vector{String})\n\nClosest candidates are:\n plot_composition_comparison(::Any, ::Any, ::Any, ::Any, !Matched::Any)\n @ Main ~/Work/Electrocat/CO2_RR_RMG/CO2_Reduction_Ag/jl_notebook_cell_df34fa98e69747e1a8f8a730347b8e2f_X26sdnNjb2RlLXJlbW90ZQ==.jl:1\n", - "output_type": "error", - "traceback": [ - "MethodError: no method matching plot_composition_comparison(::Vector{Simulation{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, SparseArrays.SparseMatrixCSC{Float64, Int64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Sundials.CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}, Vector{String}, ReactionMechanismSimulator.var\"#F#675\"{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, SparseArrays.SparseMatrixCSC{Float64, Int64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Sundials.CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Matrix{Float64}, Matrix{Float64}}}, Matrix{Float64}, Vector{Species}, Vector{ElementaryReaction}, Vector{Float64}}}, ::Float64, ::Float64, ::Vector{String})\n", - "\n", - "Closest candidates are:\n", - " plot_composition_comparison(::Any, ::Any, ::Any, ::Any, !Matched::Any)\n", - " @ Main ~/Work/Electrocat/CO2_RR_RMG/CO2_Reduction_Ag/jl_notebook_cell_df34fa98e69747e1a8f8a730347b8e2f_X26sdnNjb2RlLXJlbW90ZQ==.jl:1\n", - "\n", - "\n", - "Stacktrace:\n", - " [1] top-level scope\n", - " @ ~/Work/Electrocat/CO2_RR_RMG/CO2_Reduction_Ag/jl_notebook_cell_df34fa98e69747e1a8f8a730347b8e2f_X30sdnNjb2RlLXJlbW90ZQ==.jl:3" - ] - } - ], - "source": [ - "# sims_collection = [ssys1.sims[1], ssys2.sims[1], ssys3.sims[1]]\n", - "# x_labels = [\"Ag111@-2.0V\", \"Ag111@-1.5V\", \"Ag111@-1.0V\"]\n", - "# plot_composition_comparison(sims_collection, 1e-3, 1e-3, [\"H2O\"])" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "id": "51c99d48", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.9.1", - "language": "julia", - "name": "julia-1.9" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.9.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/CO2_Reduction_Ag/CO2RR_RMS.jl b/CO2_Reduction_Ag/CO2RR_RMS.jl new file mode 100644 index 0000000..7976657 --- /dev/null +++ b/CO2_Reduction_Ag/CO2RR_RMS.jl @@ -0,0 +1,397 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,jl:percent +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.17.2 +# kernelspec: +# display_name: Julia 1.9.1 +# language: julia +# name: julia-1.9 +# --- + +# %% +using DifferentialEquations +using ReactionMechanismSimulator +using PyPlot + +# %% +outdict1 = readinput("chem43_Ag.rms"); +outdict2 = readinput("chem43_Cu.rms") + + +# %% +liqspcs1 = outdict1["gas"]["Species"]; +liqrxns1 = outdict1["gas"]["Reactions"]; +surfspcs1 = outdict1["surface"]["Species"]; +surfrxns1 = outdict1["surface"]["Reactions"]; +interfacerxns1 = outdict1[Set(["surface", "gas"])]["Reactions"]; +solv1 = outdict1["Solvents"][1]; + +# %% +liqspcs2 = outdict2["gas"]["Species"]; +liqrxns2 = outdict2["gas"]["Reactions"]; +surfspcs2 = outdict2["surface"]["Species"]; +surfrxns2 = outdict2["surface"]["Reactions"]; +interfacerxns2 = outdict2[Set(["surface", "gas"])]["Reactions"]; +solv2 = outdict2["Solvents"][1]; + +# %% +sitedensity1 = 2.292e-5; # Ag111 +sitedensity2 = 2.943e-5; # Cu111 +AVratio = 1.0e5 + +# %% +initialcondsliq = Dict(["proton"=>10.0^-4,"CO2"=>10.0^-3*10^3, + "V"=>1.0,"T"=>298.15,"Phi"=>0.0,"d"=>0.0]); +initialcondssurf1 = Dict(["CO2X"=>0.4*sitedensity1*AVratio, + "CHO2X"=>0.1*sitedensity1*AVratio, + "CO2HX"=>0.1*sitedensity1*AVratio, + "OX"=>0.1*sitedensity1*AVratio, + "OCX"=>0.1*sitedensity1*AVratio, + "vacantX"=>0.1*sitedensity1*AVratio, + "CH2O2X"=>0.05*sitedensity1*AVratio, + "CHOX"=>0.04*sitedensity1*AVratio, + "CH2OX"=>0.01*sitedensity1*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-1.5]); +initialcondssurf2 = Dict(["CO2X"=>0.4*sitedensity1*AVratio, + "CHO2X"=>0.1*sitedensity1*AVratio, + "CO2HX"=>0.1*sitedensity1*AVratio, + "OX"=>0.1*sitedensity1*AVratio, + "OCX"=>0.1*sitedensity1*AVratio, + "vacantX"=>0.1*sitedensity1*AVratio, + "CH2O2X"=>0.05*sitedensity1*AVratio, + "CHOX"=>0.04*sitedensity1*AVratio, + "CH2OX"=>0.01*sitedensity1*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-1.0]); +initialcondssurf3 = Dict(["CO2X"=>0.4*sitedensity1*AVratio, + "CHO2X"=>0.1*sitedensity1*AVratio, + "CO2HX"=>0.1*sitedensity1*AVratio, + "OX"=>0.1*sitedensity1*AVratio, + "OCX"=>0.1*sitedensity1*AVratio, + "vacantX"=>0.1*sitedensity1*AVratio, + "CH2O2X"=>0.05*sitedensity1*AVratio, + "CHOX"=>0.04*sitedensity1*AVratio, + "CH2OX"=>0.01*sitedensity1*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-2.0]); +initialcondssurf4 = Dict(["CO2X"=>0.4*sitedensity2*AVratio, + "CHO2X"=>0.1*sitedensity2*AVratio, + "CO2HX"=>0.1*sitedensity2*AVratio, + "OX"=>0.1*sitedensity2*AVratio, + "OCX"=>0.1*sitedensity2*AVratio, + "vacantX"=>0.1*sitedensity2*AVratio, + "CH2O2X"=>0.05*sitedensity2*AVratio, + "CHOX"=>0.04*sitedensity2*AVratio, + "CH2OX"=>0.01*sitedensity2*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-1.5]); +initialcondssurf5 = Dict(["CO2X"=>0.4*sitedensity2*AVratio, + "CHO2X"=>0.1*sitedensity2*AVratio, + "CO2HX"=>0.1*sitedensity2*AVratio, + "OX"=>0.1*sitedensity2*AVratio, + "OCX"=>0.1*sitedensity2*AVratio, + "vacantX"=>0.1*sitedensity2*AVratio, + "CH2O2X"=>0.05*sitedensity2*AVratio, + "CHOX"=>0.04*sitedensity2*AVratio, + "CH2OX"=>0.01*sitedensity2*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-1.0]); +initialcondssurf6 = Dict(["CO2X"=>0.4*sitedensity2*AVratio, + "CHO2X"=>0.1*sitedensity2*AVratio, + "CO2HX"=>0.1*sitedensity2*AVratio, + "OX"=>0.1*sitedensity2*AVratio, + "OCX"=>0.1*sitedensity2*AVratio, + "vacantX"=>0.1*sitedensity2*AVratio, + "CH2O2X"=>0.05*sitedensity2*AVratio, + "CHOX"=>0.04*sitedensity2*AVratio, + "CH2OX"=>0.01*sitedensity2*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-2.0]); + +# %% +liq1 = IdealDiluteSolution(liqspcs1,liqrxns1,solv1,name="liquid",diffusionlimited=true); + +liq2 = IdealDiluteSolution(liqspcs2,liqrxns2,solv2,name="liquid",diffusionlimited=true); + +surf1 = IdealSurface(surfspcs1,surfrxns1,sitedensity1,name="surface"); + +surf2 = IdealSurface(surfspcs2,surfrxns2,sitedensity2,name="surface"); + +domainliq1,y0liq1,pliq1 = ConstantTVDomain(phase=liq1, + initialconds=initialcondsliq,constantspecies=["proton","CO2"]); + +domainliq2,y0liq2,pliq2 = ConstantTVDomain(phase=liq2, + initialconds=initialcondsliq,constantspecies=["proton","CO2"]); + +# %% +domaincat1,y0cat1,pcat1 = ConstantTAPhiDomain(phase=surf1, + initialconds=initialcondssurf1); + +inter1,pinter1 = ReactiveInternalInterfaceConstantTPhi(domainliq1, + domaincat1,interfacerxns1,298.15,AVratio*1.0); + +# %% +domaincat2,y0cat2,pcat2 = ConstantTAPhiDomain(phase=surf1, + initialconds=initialcondssurf2); + +inter2,pinter2 = ReactiveInternalInterfaceConstantTPhi(domainliq1, + domaincat2,interfacerxns1,298.15,AVratio*1.0); + +# %% +domaincat3,y0cat3,pcat3 = ConstantTAPhiDomain(phase=surf1, + initialconds=initialcondssurf3); + +inter3,pinter3 = ReactiveInternalInterfaceConstantTPhi(domainliq1, + domaincat3,interfacerxns1,298.15,AVratio*1.0); + +# %% +domaincat4,y0cat4,pcat4 = ConstantTAPhiDomain(phase=surf2, + initialconds=initialcondssurf4); + +inter4,pinter4 = ReactiveInternalInterfaceConstantTPhi(domainliq2, + domaincat4,interfacerxns2,298.15,AVratio*1.0); + +# %% +domaincat5,y0cat5,pcat5 = ConstantTAPhiDomain(phase=surf2, + initialconds=initialcondssurf5); + +inter5,pinter5 = ReactiveInternalInterfaceConstantTPhi(domainliq2, + domaincat5,interfacerxns2,298.15,AVratio*1.0); + +# %% +domaincat6,y0cat6,pcat6 = ConstantTAPhiDomain(phase=surf2, + initialconds=initialcondssurf6); + +inter6,pinter6 = ReactiveInternalInterfaceConstantTPhi(domainliq2, + domaincat6,interfacerxns2,298.15,AVratio*1.0); + +# %% +@time react1,y01,p1 = Reactor((domainliq1,domaincat1), (y0liq1,y0cat1), (0.0, 1.0e2), [inter1], (pliq1,pcat1,pinter1)); + +@time sol1 = solve(react1.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +ssys1 = SystemSimulation(sol1,(domainliq1,domaincat1,),(inter1,),p1); + + +# %% +@time react2,y02,p2 = Reactor((domainliq1,domaincat2), (y0liq1,y0cat2), (0.0, 1.0e2), [inter2], (pliq1,pcat2,pinter2)); + +@time sol2 = solve(react2.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +ssys2 = SystemSimulation(sol2,(domainliq1,domaincat2,),(inter2,),p2); + +# %% +@time react3,y03,p3 = Reactor((domainliq1,domaincat3), (y0liq1,y0cat3), (0.0, 1.0e2), [inter3], (pliq1,pcat3,pinter3)); + +@time sol3 = solve(react3.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +ssys3 = SystemSimulation(sol3,(domainliq1,domaincat3,),(inter3,),p3); + +# %% +@time react4,y04,p4 = Reactor((domainliq2,domaincat4), (y0liq2,y0cat4), (0.0, 1.0e2), [inter4], (pliq2,pcat4,pinter4)); + +@time sol4 = solve(react4.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +ssys4 = SystemSimulation(sol4,(domainliq2,domaincat4,),(inter4,),p4); + +# %% +@time react5,y05,p5 = Reactor((domainliq2,domaincat5), (y0liq2,y0cat5), (0.0, 1.0e2), [inter5], (pliq2,pcat5,pinter5)); + +@time sol5 = solve(react5.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +ssys5 = SystemSimulation(sol5,(domainliq2,domaincat5,),(inter5,),p5); + +# %% +@time react6,y06,p6 = Reactor((domainliq2,domaincat6), (y0liq2,y0cat6), (0.0, 1.0e2), [inter6], (pliq2,pcat6,pinter6)); + +@time sol6 = solve(react6.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +ssys6 = SystemSimulation(sol6,(domainliq2,domaincat6,),(inter6,),p6); + +# %% +# Helper function +function plotX(sim, tol, t_end, exclude) + clf() + xs = molefractions(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Mole Fraction") +end + +# %% +exclude_species = ["H2O"] +plotX(ssys1.sims[1], 1e-10, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e-3) +ylim(1e-12, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V") +gcf() +savefig("Ag111@-1.5V_X.png") + +# %% +exclude_species = ["H2O"] +plotX(ssys2.sims[1], 1e-10, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e-3) +ylim(1e-12, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.0V") +gcf() +savefig("Ag111@-1.0V_X.png") + +# %% +exclude_species = ["H2O"] +plotX(ssys3.sims[1], 1e-10, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e-3) +ylim(1e-12, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-2.0V") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys4.sims[1], 1e-10, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e-3) +ylim(1e-12, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Cu111@-1.5V") +gcf() +savefig("Cu111@-1.5V_X.png") + +# %% +exclude_species = ["H2O"] +plotX(ssys5.sims[1], 1e-10, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e-3) +ylim(1e-12, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Cu111@-1.0V") +gcf() +savefig("Cu111@-1.0V_X.png") + +# %% +exclude_species = ["H2O"] +plotX(ssys6.sims[1], 1e-10, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e-3) +ylim(1e-12, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Cu111@-2.0V") +gcf() +savefig("Cu111@-2.0V_X.png") + +# %% +exclude_species = ["H2O"] +plotX(ssys1.sims[2], 0.1, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e-3) +ylim(1e-12, 5) +title("Evolution of Solid-phase Mole Fractions vs. Time at phi = -1.5V on Ag111") +gcf() + +# %% +Dict([ssys1.sims[1].names[i]=>molefractions(ssys1.sims[1],1)[i] for i in 1:length(ssys1.sims[1].names)]) + +# %% +fd1 = getfluxdiagram(ssys1,1e-3;speciesratetolerance=1e-4) + +# %% +fd2 = getfluxdiagram(ssys2,1e-3;speciesratetolerance=1e-4) + +# %% +fd3 = getfluxdiagram(ssys3,1e-3;speciesratetolerance=1e-4) + +# %% +fd4 = getfluxdiagram(ssys4,1e-3;speciesratetolerance=1e-4) + +# %% +fd5 = getfluxdiagram(ssys5,1e-3;speciesratetolerance=1e-4) + +# %% +fd6 = getfluxdiagram(ssys6,1e-3;speciesratetolerance=1e-4) + +# %% +# function plot_composition_comparison(solutions, t, tol, exclude, x_labels) +# # Prepare data storage +# species_dict = Dict{String, Vector{Float64}}() # To collect mole fractions for each species + +# # Iterate through each solution +# for (idx, bsol) in enumerate(solutions) +# # Get mole fractions and species at the specified time +# mole_fractions = molefractions(bsol, t) +# species = bsol.domain.phase.species + +# # Filter species based on threshold and exclusion list +# for (i, mf) in enumerate(mole_fractions) +# species_name = species[i].name +# if mf > tol && !(species_name in exclude) +# # Initialize vector for each species if not already present +# if !haskey(species_dict, species_name) +# species_dict[species_name] = zeros(length(solutions)) +# end +# # Assign the mole fraction for the current solution +# species_dict[species_name][idx] = mf +# end +# end +# end + +# # Convert species data to arrays for plotting +# species_names = collect(keys(species_dict)) +# num_solutions = length(solutions) + +# # Sort species for each solution based on mole fractions (descending order) +# sorted_species = sort(species_names, by=name -> -maximum(species_dict[name])) + +# # Plotting each solution individually +# clf() # Clear the current figure +# bar_positions = 1:num_solutions +# width = 0.35 # Width of each bar +# color_cycle = get_cmap("tab20", length(sorted_species)) + +# # Initialize bottom values for stacked bars +# bottoms = zeros(num_solutions) + +# # Plot each species, stacking from the highest mole fraction down +# for (color_idx, species_name) in enumerate(sorted_species) +# # Get the mole fractions for the current species across solutions +# current_data = species_dict[species_name] + +# # Plot bars for the current species +# bar(bar_positions, current_data, width, bottom=bottoms, color=color_cycle(color_idx), label=species_name) + +# # Update the bottom values for stacking +# bottoms .+= current_data +# end + +# # Formatting the plot +# xticks(bar_positions, x_labels) +# ylabel("Mole Fraction") +# legend(title="Species", loc="upper right", bbox_to_anchor=(1.2, 1)) +# title("Liquid Phase Composition at t = $t") +# tight_layout() # Adjust layout for better appearance +# end + + +# %% +# sims_collection = [ssys1.sims[1], ssys2.sims[1], ssys3.sims[1]] +# x_labels = ["Ag111@-2.0V", "Ag111@-1.5V", "Ag111@-1.0V"] +# plot_composition_comparison(sims_collection, 1e-3, 1e-3, ["H2O"]) + +# %% diff --git a/CO2_Reduction_Ag/CO2RR_RMS_2.ipynb b/CO2_Reduction_Ag/CO2RR_RMS_2.ipynb deleted file mode 100644 index f6c86d7..0000000 --- a/CO2_Reduction_Ag/CO2RR_RMS_2.ipynb +++ /dev/null @@ -1,695 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 133, - "id": "8a590634", - "metadata": {}, - "outputs": [], - "source": [ - "using DifferentialEquations\n", - "using ReactionMechanismSimulator\n", - "using PyPlot" - ] - }, - { - "cell_type": "code", - "execution_count": 134, - "id": "e941d4fb", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Dict{Any, Any} with 4 entries:\n", - " \"Solvents\" => Solvent[Solvent(\"water\", RiedelViscosity{Float64}(…\n", - " Set([\"surface\", \"gas\"]) => Dict{Any, Any}(\"Reactions\"=>ElementaryReaction[vac…\n", - " \"gas\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…\n", - " \"surface\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "outdict = readinput(\"chem300.rms\")" - ] - }, - { - "cell_type": "code", - "execution_count": 135, - "id": "fe2767e9", - "metadata": {}, - "outputs": [], - "source": [ - "liqspcs = outdict[\"gas\"][\"Species\"]\n", - "liqrxns = outdict[\"gas\"][\"Reactions\"]\n", - "surfspcs = outdict[\"surface\"][\"Species\"]\n", - "surfrxns = outdict[\"surface\"][\"Reactions\"]\n", - "interfacerxns = outdict[Set([\"surface\", \"gas\"])][\"Reactions\"]\n", - "solv = outdict[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 136, - "id": "c54ee65e", - "metadata": {}, - "outputs": [], - "source": [ - "sitedensity = 2.292e-5; # Ag111\n", - "liq = IdealDiluteSolution(liqspcs,liqrxns,solv,name=\"liquid\",diffusionlimited=true);\n", - "surf = IdealSurface(surfspcs,surfrxns,sitedensity,name=\"surface\");" - ] - }, - { - "cell_type": "code", - "execution_count": 137, - "id": "8894c84d", - "metadata": {}, - "outputs": [], - "source": [ - "initialcondsliq = Dict([\"proton\"=>10.0^-4,\n", - " \"CO2\"=>10.0^-3*10^6,\n", - " \"V\"=>1.0,\"T\"=>300,\"Phi\"=>0.0,\"d\"=>0.0]);\n", - "AVratio = 1e5;\n", - "initialcondssurf = Dict([\"CO2X\"=>0.4*sitedensity*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity*AVratio,\n", - " \"OX\"=>0.1*sitedensity*AVratio,\n", - " \"OCX\"=>0.1*sitedensity*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>300,\"Phi\"=>-1.5]);" - ] - }, - { - "cell_type": "code", - "execution_count": 138, - "id": "ddb39b3d", - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "domainliq,y0liq,pliq = ConstantTVDomain(phase=liq,\n", - " initialconds=initialcondsliq,constantspecies=[\"proton\",\"CO2\"]);\n", - "domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf,\n", - " initialconds=initialcondssurf);" - ] - }, - { - "cell_type": "code", - "execution_count": 139, - "id": "ed49d2b4", - "metadata": {}, - "outputs": [], - "source": [ - "inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainliq,\n", - " domaincat,interfacerxns,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 140, - "id": "244f0912", - "metadata": {}, - "outputs": [], - "source": [ - "@time react,y0,p = Reactor((domainliq,domaincat), (y0liq,y0cat), (0.0, 1.0e3), [inter], (pliq,pcat,pinter));\n" - ] - }, - { - "cell_type": "code", - "execution_count": 141, - "id": "962f838c", - "metadata": {}, - "outputs": [], - "source": [ - "@time sol = solve(react.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-8);" - ] - }, - { - "cell_type": "code", - "execution_count": 142, - "id": "56b6f906", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "retcode: Success\n", - "Interpolation: 3rd order Hermite\n", - "t: 7135-element Vector{Float64}:\n", - " 0.0\n", - " 4.786910423176204e-20\n", - " 9.573820846352407e-20\n", - " 1.4360731269528611e-19\n", - " 3.136209658750193e-19\n", - " 4.836346190547525e-19\n", - " 6.536482722344857e-19\n", - " 9.290855160451293e-19\n", - " 1.393701587359254e-18\n", - " 2.1962591531694716e-18\n", - " ⋮\n", - " 879.5546091455969\n", - " 894.8998163040148\n", - " 910.2450234624328\n", - " 925.5902306208507\n", - " 940.9354377792686\n", - " 956.2806449376865\n", - " 971.6258520961044\n", - " 986.9710592545223\n", - " 1000.0\n", - "u: 7135-element Vector{Vector{Float64}}:\n", - " [0.0, 0.0, 0.0, 0.0, 1000.0, 0.0001, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]\n", - " [0.0, 0.0, 0.0, 0.0, 1000.0, 0.0001, 3.612374328324481e-148, 4.385132164362883e-19, 1.633795305695168e-19, 2.7428996724663614e-14 … 1.1203467421629118e-45, 1.8994249591181796e-72, 1.2800354014369318e-87, -3.879530191351059e-178, 1.3708129609046892e-77, 1.3213726871771316e-91, 1.5496805651867354e-69, 1.0657739381929874e-102, 7.799295861017468e-45, 1.5199781543354013e-65]\n", - " [0.0, 0.0, 0.0, 0.0, 1000.0, 0.0001, 3.2510159530929195e-147, 8.770264328726898e-19, 3.26901310954359e-19, 5.4857993449194225e-14 … 5.601733429675485e-45, 9.500781840630999e-72, 6.405079675989712e-87, 1.5792657431109165e-170, 9.579979641605759e-77, 9.249204609701657e-91, 7.747910452426376e-69, 5.3288687302123504e-102, 3.900398940032122e-44, 9.121693519206351e-65]\n", - " [0.0, 0.0, 0.0, 0.0, 1000.0, 0.0001, 1.914390693681754e-146, 1.3155396493092048e-18, 4.905653411229998e-19, 8.228699017359486e-14 … 1.5684852403090184e-44, 2.851514493402545e-71, 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3.008904767648952e-17]\n", - " [0.0, 0.0, 0.0, 0.0, 1000.0, 0.0001, 8.662001320737534e-59, 0.0006520781082836139, 1478.8029142762553, 620.9199458002881 … 1.6349225099682997e-30, 7.817281395042703e-18, 8.634034542102559e-16, 1.182646490629931e-70, 3.7649709371881814e-19, 7.801481961734099e-37, 6.350172148918026e-21, 8.274974497752408e-28, 4.009308604716525e-6, 3.007906462317097e-17]\n", - " [0.0, 0.0, 0.0, 0.0, 1000.0, 0.0001, 8.946827697111488e-59, 0.0006525467920031325, 1491.9399043216488, 626.2664659162169 … 1.6269066676192027e-30, 7.73620747200259e-18, 8.561602493564738e-16, 1.1836665222347363e-70, 3.733177555052834e-19, 7.736656031780808e-37, 6.307719612670948e-21, 8.294648908547076e-28, 4.0350703196569055e-6, 3.0070696513014354e-17]" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sol" - ] - }, - { - "cell_type": "code", - "execution_count": 143, - "id": "4714593e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ReturnCode.Success = 1" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sol.retcode" - ] - }, - { - "cell_type": "code", - "execution_count": 144, - "id": "6667bb5a", - "metadata": {}, - "outputs": [], - "source": [ - "ssys = SystemSimulation(sol,(domainliq,domaincat,),(inter,),p);" - ] - }, - { - "cell_type": "code", - "execution_count": 145, - "id": "87dcaf99", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotX (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotX(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = molefractions(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Mole Fraction\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 146, - "id": "ddf6da6b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotC (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotC(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = concentrations(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Concentration\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 147, - "id": "e719a85d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys.sims[1], 1e-3, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-9, 1e3)\n", - "ylim(1e-6, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 148, - "id": "1ef78267", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotC(ssys.sims[1], 1, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-9, 1e3)\n", - "ylim(1e-3, 1e4)\n", - "title(\"Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 149, - "id": "1f7d8918", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "1186×1435 Array{RGBA{N0f8},2} with eltype ColorTypes.RGBA{FixedPointNumbers.N0f8}:\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " ⋮ ⋱ \n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.71)\n", - " RGBA{N0f8}(1.0,1.0,1.0,0.8) … RGBA{N0f8}(1.0,1.0,1.0,0.569)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "getfluxdiagram(ssys,1e3;speciesratetolerance=1e-6)" - ] - }, - { - "cell_type": "code", - "execution_count": 150, - "id": "36206466", - "metadata": {}, - "outputs": [], - "source": [ - "println(ssys.names)" - ] - }, - { - "cell_type": "code", - "execution_count": 151, - "id": "44de0eb2", - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "for (i,rxn) in enumerate(inter.reactions)\n", - " str = getrxnstr(rxn)\n", - " kf = inter.kfs[i]\n", - " krev = inter.krevs[i]\n", - " Kc = kf/krev\n", - " println(str)\n", - " println(\"kf = $kf\")\n", - " println(\"krev = $krev\")\n", - " println(\"Kc = $Kc\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 152, - "id": "dd1b08a5", - "metadata": {}, - "outputs": [], - "source": [ - "for (i,rxn) in enumerate(inter.reactions)\n", - " str = getrxnstr(rxn)\n", - " kf = inter.kfs[i]\n", - " krev = inter.krevs[i]\n", - " Kc = kf/krev\n", - " println(str)\n", - " println(\"kf = $kf\")\n", - " println(\"krev = $krev\")\n", - " println(\"Kc = $Kc\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 203, - "id": "11333da0", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "10962-element SparseArrays.SparseVector{Float64, Int64} with 18 stored entries:\n", - " [11 ] = -6.62794e-112\n", - " [10253] = 5.62284\n", - " [10254] = 8950.06\n", - " [10255] = -8.57104e-20\n", - " [10256] = -7.59582e-24\n", - " [10265] = 8.69249e-8\n", - " [10268] = 5.42172e-14\n", - " ⋮\n", - " [10310] = 7.39712e-51\n", - " [10352] = 7.94894e-27\n", - " [10540] = 1.733e-29\n", - " [10555] = 6.69799e-34\n", - " [10835] = 1.03174e-24\n", - " [10865] = 5.4537e-26\n", - " [10867] = 1.78878e-45\n", - " [10908] = 1.48135e-12" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "rops(ssys, \"O=CO\", 1e-12)" - ] - }, - { - "cell_type": "code", - "execution_count": 190, - "id": "ef575a57", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotROP (generic function with 2 methods)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "function plotROP(bsol,name,t;N=0,tol=0.01)\n", - " clf()\n", - " rop = rops(bsol,name,t)\n", - " inds = rop.nzind[reverse(sortperm(abs.(rop.nzval)))]\n", - " if N == 0\n", - " N = length(inds)\n", - " elseif N > length(inds)\n", - " N = length(inds)\n", - " end\n", - " inds = inds[1:N]\n", - " mval = abs(rop[inds[1]])\n", - " minval = mval*tol\n", - " k = 1\n", - " while k < length(inds) && abs(rop[inds[k]]) >= minval\n", - " k += 1\n", - " end\n", - " inds = inds[1:k]\n", - " xs = Array{Float64,1}(1:length(inds))\n", - " barh(xs,reverse(rop[inds]))\n", - " yticks(xs,reverse(getrxnstr.(bsol.domain.phase.reactions[inds])))\n", - " xlabel(\"Production/Loss Rate mol/s\")\n", - " return\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 199, - "id": "e004c9af", - "metadata": {}, - "outputs": [ - { - "ename": "UndefVarError", - "evalue": "UndefVarError: `getphasespecies` not defined", - "output_type": "error", - "traceback": [ - "UndefVarError: `getphasespecies` not defined\n", - "\n", - "Stacktrace:\n", - " [1] plotROP(bsol::Simulation{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, SparseArrays.SparseMatrixCSC{Float64, Int64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Sundials.CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}, Vector{String}, ReactionMechanismSimulator.var\"#F#675\"{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, SparseArrays.SparseMatrixCSC{Float64, Int64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Sundials.CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Matrix{Float64}, Matrix{Float64}}}, Matrix{Float64}, Vector{Species}, Vector{ElementaryReaction}, Vector{Float64}}, name::String, t::Int64; N::Int64, tol::Float64)\n", - " @ Main ~/Work/Electrocat/CO2_RR_RMG/CO2_Reduction_Ag/jl_notebook_cell_df34fa98e69747e1a8f8a730347b8e2f_X30sdnNjb2RlLXJlbW90ZQ==.jl:3\n", - " [2] top-level scope\n", - " @ ~/Work/Electrocat/CO2_RR_RMG/CO2_Reduction_Ag/jl_notebook_cell_df34fa98e69747e1a8f8a730347b8e2f_X32sdnNjb2RlLXJlbW90ZQ==.jl:1" - ] - } - ], - "source": [ - "plotROP(ssys.sims[2], \"CH2O2X\",1;N=15,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 206, - "id": "b5b12ce0", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "10962-element SparseArrays.SparseVector{Float64, Int64} with 528 stored entries:\n", - " [47 ] = 2.35221e10\n", - " [48 ] = 1.82944e6\n", - " [49 ] = 1.82944e6\n", - " [50 ] = 0.93615\n", - " [53 ] = 1.82944e6\n", - " [54 ] = 1.82944e6\n", - " [56 ] = 21.6762\n", - " ⋮\n", - " [10084] = 5.29789e-29\n", - " [10087] = 6.68217e-37\n", - " [10088] = 1.51366e-30\n", - " [10242] = 1.87538e5\n", - " [10243] = 5.37857e5\n", - " [10253] = -5.62284\n", - " [10264] = -6.26487e-6\n", - " [10266] = -4.38995e-6" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "rops(ssys, \"CH2O2X\", 1e-12)" - ] - }, - { - "cell_type": "code", - "execution_count": 207, - "id": "16031f6f", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "10962-element SparseArrays.SparseVector{Float64, Int64} with 18 stored entries:\n", - " [11 ] = -6.62794e-112\n", - " [10253] = 5.62284\n", - " [10254] = 8950.06\n", - " [10255] = -8.57104e-20\n", - " [10256] = -7.59582e-24\n", - " [10265] = 8.69249e-8\n", - " [10268] = 5.42172e-14\n", - " ⋮\n", - " [10310] = 7.39712e-51\n", - " [10352] = 7.94894e-27\n", - " [10540] = 1.733e-29\n", - " [10555] = 6.69799e-34\n", - " [10835] = 1.03174e-24\n", - " [10865] = 5.4537e-26\n", - " [10867] = 1.78878e-45\n", - " [10908] = 1.48135e-12" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "rops(ssys, \"O=CO\", 1e-12)" - ] - }, - { - "cell_type": "code", - "execution_count": 194, - "id": "36b9ee55", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ConstantTVDomain{IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}(IdealDiluteSolution{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}\n", - " name: String \"liquid\"\n", - " species: Array{Species}((108,))\n", - " reactions: Array{ElementaryReaction}((43,))\n", - " solvent: Solvent\n", - " stoichmatrix: SparseArrays.SparseMatrixCSC{Float64, Int64}\n", - " Nrp: Array{Float64}((43,)) [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]\n", - " rxnarray: Array{Int64}((8, 43)) [7 7 … 7 15; 33 34 … 106 106; … ; 0 0 … 0 0; 0 0 … 0 0]\n", - " veckinetics: Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}\n", - " veckineticsinds: Array{Int64}((1,)) [43]\n", - " vecthermo: ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}\n", - " otherreactions: Array{ElementaryReaction}((0,))\n", - " electronchange: Array{Float64}((43,)) [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]\n", - " spcdict: Dict{String, Int64}\n", - " reversibility: Array{Bool}((43,)) Bool[1, 1, 1, 1, 1, 1, 1, 1, 1, 1 … 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]\n", - " forwardability: Array{Bool}((43,)) Bool[1, 1, 1, 1, 1, 1, 1, 1, 1, 1 … 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]\n", - " diffusionlimited: Bool true\n", - ", [1, 108], [1, 151], [6, 5], 300.0, 1.0, 0.0, 0.0, [8.30171982998078e6, 8.30171982998078e6, 7.945759617446088e6, 7.653861670370603e6, 7.990621761684466e6, 8.365589466005936e6, 7.486079195303395e6, 8.270053435737545e6, 7.325293273850048e6, 6.575646985634498e6 … 1.6449236157225358e-7, 975439.053875451, 421244.0828356318, 2.176624091649817e6, 1.105301411839168e6, 2.8662557808254304e-8, 3.1372973385333555e-9, 13.337843555354022, 1047.7426603355002, 3.854912483633202e-17], [2.5056634928273256e-132, 1.1613793480197979e-83, 1.0469602316081974e-111, 4.674409174722625e-63, 2.502310768518533e-105, 9.12325565337589e-115, 4.7546927811598384e-60, 1.8292328198366333e-69, 2.8349643752073253e-57, 4.807881163872417e-54 … 9.023066186355352e-17, 1.563105995258598e-44, 1.2753070140440015e-41, 1.5114569550525903e-45, 1.450059162715292e-42, 9.416249033124735e-16, 1.94720339830407e-13, 1.3370990092106833e-28, 2.48776775159488e-34, 4.535122728660089e-5], [5.536169735269627e9, 5.536169735269627e9, 5.536169735269627e9, 2.0078948710112387e8, 5.536169735269627e9, 5.536169735269627e9, 1.1607394475819142e8, 6.403973080115937e8, 5.828649368272015e7, 3.0562704051882233e7 … 1.6449236157225734e-7, 1.1153325173493526e6, 445367.8774444417, 3.034988664382294e6, 1.290665553097012e6, 2.8662557808254476e-8, 3.137297338533386e-9, 13.337865786615048, 1047.8737022624825, 3.8549124836554075e-17], Integer[], [-40043.126583650024, -32840.77588912651, -38671.7008403984, -51458.45101465355, -457938.94362207263, -12274.741585447891, 186629.03260505645, -188530.14716098696, -483402.40421594173, -325852.7281740505 … -601433.0819126703, -530752.7596515524, -297771.61210395163, -179638.08529880646, -280902.1348595971, 40897.63410455966, -175190.9596661942, -17841.765925695272, -462309.04129866365, -510468.6853220258], [7 7 … 7 15; 33 34 … 106 106; … ; 0 0 … 0 0; 0 0 … 0 0], 0.0008764544014047555, [1.2791698254820209e-9, 1.8057956542205799e-9, 1.6715781069123858e-9, 1.2139156476242518e-9, 1.122671285175347e-9, 1.6586845884779859e-9, 1.6586845884779859e-9, 1.14440221020022e-9, 1.0706139020926982e-9, 1.3343544679270026e-9 … 8.493536585469772e-10, 8.493536585469772e-10, 8.493536585469772e-10, 9.077994650831605e-10, 8.493536585469772e-10, 8.905894704051347e-10, 8.689951179730577e-10, 8.795273391843891e-10, 8.493536585469772e-10, 8.493536585469772e-10], [0.0 0.0 … 0.0 0.0; 0.0 0.0 … 0.0 0.0; … ; 0.0 0.0 … 0.0 0.0; 0.0 0.0 … 0.0 0.0], false, false, Bool[0], [0.0], [-40043.126583650024, -32840.77588912651, -38671.7008403984, -51458.45101465355, -457938.94362207263, -12274.741585447891, 186629.03260505645, -188530.14716098696, -483402.40421594173, -325852.7281740505 … 1.6449236157225734e-7, 1.1153325173493526e6, 445367.8774444417, 3.034988664382294e6, 1.290665553097012e6, 2.8662557808254476e-8, 3.137297338533386e-9, 13.337865786615048, 1047.8737022624825, 3.8549124836554075e-17], Dict{String, Int64}())" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "ssys.sims[1].domain" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "733fcc2d", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.9.1", - "language": "julia", - "name": "julia-1.9" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.9.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/CO2_Reduction_Ag/CO2RR_RMS_2.jl b/CO2_Reduction_Ag/CO2RR_RMS_2.jl new file mode 100644 index 0000000..ad797a8 --- /dev/null +++ b/CO2_Reduction_Ag/CO2RR_RMS_2.jl @@ -0,0 +1,215 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,jl:percent +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.17.2 +# kernelspec: +# display_name: Julia 1.9.1 +# language: julia +# name: julia-1.9 +# --- + +# %% +using DifferentialEquations +using ReactionMechanismSimulator +using PyPlot + +# %% +outdict = readinput("chem300.rms") + +# %% +liqspcs = outdict["gas"]["Species"] +liqrxns = outdict["gas"]["Reactions"] +surfspcs = outdict["surface"]["Species"] +surfrxns = outdict["surface"]["Reactions"] +interfacerxns = outdict[Set(["surface", "gas"])]["Reactions"] +solv = outdict["Solvents"][1]; + +# %% +sitedensity = 2.292e-5; # Ag111 +liq = IdealDiluteSolution(liqspcs,liqrxns,solv,name="liquid",diffusionlimited=true); +surf = IdealSurface(surfspcs,surfrxns,sitedensity,name="surface"); + +# %% +initialcondsliq = Dict(["proton"=>10.0^-4, + "CO2"=>10.0^-3*10^6, + "V"=>1.0,"T"=>300,"Phi"=>0.0,"d"=>0.0]); +AVratio = 1e5; +initialcondssurf = Dict(["CO2X"=>0.4*sitedensity*AVratio, + "CHO2X"=>0.1*sitedensity*AVratio, + "CO2HX"=>0.1*sitedensity*AVratio, + "OX"=>0.1*sitedensity*AVratio, + "OCX"=>0.1*sitedensity*AVratio, + "vacantX"=>0.1*sitedensity*AVratio, + "CH2O2X"=>0.05*sitedensity*AVratio, + "CHOX"=>0.04*sitedensity*AVratio, + "CH2OX"=>0.01*sitedensity*AVratio, + "A"=>1.0*AVratio,"T"=>300,"Phi"=>-1.5]); + +# %% +domainliq,y0liq,pliq = ConstantTVDomain(phase=liq, + initialconds=initialcondsliq,constantspecies=["proton","CO2"]); +domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf, + initialconds=initialcondssurf); + +# %% +inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainliq, + domaincat,interfacerxns,298.15,AVratio*1.0); + +# %% +@time react,y0,p = Reactor((domainliq,domaincat), (y0liq,y0cat), (0.0, 1.0e3), [inter], (pliq,pcat,pinter)); + + +# %% +@time sol = solve(react.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-8); + +# %% +sol + +# %% +sol.retcode + +# %% +ssys = SystemSimulation(sol,(domainliq,domaincat,),(inter,),p); + +# %% +# Helper function +function plotX(sim, tol, t_end, exclude) + clf() + xs = molefractions(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Mole Fraction") +end + +# %% +# Helper function +function plotC(sim, tol, t_end, exclude) + clf() + xs = concentrations(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Concentration") +end + +# %% +exclude_species = ["H2O"] +plotX(ssys.sims[1], 1e-3, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-9, 1e3) +ylim(1e-6, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V") +gcf() + +# %% +exclude_species = ["H2O"] +plotC(ssys.sims[1], 1, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-9, 1e3) +ylim(1e-3, 1e4) +title("Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V") +gcf() + +# %% +getfluxdiagram(ssys,1e3;speciesratetolerance=1e-6) + +# %% +println(ssys.names) + +# %% +for (i,rxn) in enumerate(inter.reactions) + str = getrxnstr(rxn) + kf = inter.kfs[i] + krev = inter.krevs[i] + Kc = kf/krev + println(str) + println("kf = $kf") + println("krev = $krev") + println("Kc = $Kc") +end + +# %% +for (i,rxn) in enumerate(inter.reactions) + str = getrxnstr(rxn) + kf = inter.kfs[i] + krev = inter.krevs[i] + Kc = kf/krev + println(str) + println("kf = $kf") + println("krev = $krev") + println("Kc = $Kc") +end + +# %% +rops(ssys, "O=CO", 1e-12) + +# %% +function plotROP(bsol,name,t;N=0,tol=0.01) + clf() + rop = rops(bsol,name,t) + inds = rop.nzind[reverse(sortperm(abs.(rop.nzval)))] + if N == 0 + N = length(inds) + elseif N > length(inds) + N = length(inds) + end + inds = inds[1:N] + mval = abs(rop[inds[1]]) + minval = mval*tol + k = 1 + while k < length(inds) && abs(rop[inds[k]]) >= minval + k += 1 + end + inds = inds[1:k] + xs = Array{Float64,1}(1:length(inds)) + barh(xs,reverse(rop[inds])) + yticks(xs,reverse(getrxnstr.(bsol.domain.phase.reactions[inds]))) + xlabel("Production/Loss Rate mol/s") + return +end + +# %% +plotROP(ssys.sims[2], "CH2O2X",1;N=15,tol=0.0) + +# %% +rops(ssys, "CH2O2X", 1e-12) + +# %% +rops(ssys, "O=CO", 1e-12) + +# %% +ssys.sims[1].domain + +# %% diff --git a/CO2_Reduction_Ag/CO2RR_RMS_3.ipynb b/CO2_Reduction_Ag/CO2RR_RMS_3.ipynb deleted file mode 100644 index d677065..0000000 --- a/CO2_Reduction_Ag/CO2RR_RMS_3.ipynb +++ /dev/null @@ -1,1458 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 45, - "id": "8a590634", - "metadata": {}, - "outputs": [], - "source": [ - "using DifferentialEquations\n", - "using ReactionMechanismSimulator\n", - "using PyPlot" - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "id": "e941d4fb", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[12:12:02] WARNING: not removing hydrogen atom without neighbors\n", - "[12:12:02] WARNING: not removing hydrogen atom without neighbors\n", - "┌ Warning: failed to generate StokesDiffusivity model for species vacantX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2O2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species H2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(C[Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]COO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(=[Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC([Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C([Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH3X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [H][H].[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(C=[Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(C#[Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]=C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)([Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=[Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]C#CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]OC#CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n" - ] - }, - { - "data": { - "text/plain": [ - "Dict{Any, Any} with 4 entries:\n", - " \"Solvents\" => Solvent[Solvent(\"water\", RiedelViscosity{Float64}(…\n", - " Set([\"surface\", \"gas\"]) => Dict{Any, Any}(\"Reactions\"=>ElementaryReaction[vac…\n", - " \"gas\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…\n", - " \"surface\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "outdict = readinput(\"Ag_C2_042925.rms\")" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "id": "fe2767e9", - "metadata": {}, - "outputs": [], - "source": [ - "liqspcs = outdict[\"gas\"][\"Species\"]\n", - "liqrxns = outdict[\"gas\"][\"Reactions\"]\n", - "surfspcs = outdict[\"surface\"][\"Species\"]\n", - "surfrxns = outdict[\"surface\"][\"Reactions\"]\n", - "interfacerxns = outdict[Set([\"surface\", \"gas\"])][\"Reactions\"]\n", - "solv = outdict[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "id": "c54ee65e", - "metadata": {}, - "outputs": [], - "source": [ - "sitedensity = 2.292e-5; # Ag111\n", - "liq = IdealDiluteSolution(liqspcs,liqrxns,solv,name=\"liquid\",diffusionlimited=true);\n", - "surf = IdealSurface(surfspcs,surfrxns,sitedensity,name=\"surface\");" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8894c84d", - "metadata": {}, - "outputs": [], - "source": [ - "# Reservoir is a 100 mL (100e-6 m^3) cell\n", - "# Proton concentration is 10^-7 mol/L (10^-4 mol/m^3)\n", - "# CO2 concentration is 0.01 mol/L (10 mol/m^3), saturation solubility ~0.03 mol/L\n", - "# Solvent concentration (water) is 55.6 mol/L (5.56e4 mol/m^3)\n", - "# AVratio in experiments is 36 m^-1 but is measured by surface area/reservoir volume\n", - "# Area of the electrode is therefore 3.6e1 m^-1 * 1e2*1e-6 m^3 = 3.6e-3 m^2 = 36 cm^2\n", - "# Assume boundary layer thickness d_bl = 1 mm or 1e-3 m\n", - "# Volume of the boundary layer V_bl = 3.6e-3 m^2 * 1e-3 m = 3.6e-6 m^3\n", - "# Actual AVratio is therefore 3.6e-3 m^2 / 3.6e-6 m^3 = 1e3 m^-1 (reciprocal of d_bl)\n", - "# Amount of sites is 2.292e-5 mol/m^2 * 1e3 m^-1 = 2.292e-2 mol/m^-3\n", - "\n", - "C_proton = 1.0e-7*1.0e3;\n", - "C_co2 = 1.0e-2*1.0e3;\n", - "C_h2o = 5.56e4;\n", - "C_default = 1e-12;\n", - "V_res = 1.0e3;\n", - "AVratio = 1.0e3;\n", - "A_surf = V_res*36;\n", - "V_bl = A_surf/AVratio;\n", - "sites = sitedensity*A_surf;\n", - "\n", - "initialcondsliq = Dict([\"proton\"=>C_proton * V_res,\n", - " \"CO2\"=>C_co2 * V_res,\n", - " \"H2O\"=>C_h2o * V_res,\n", - " \"V\"=>V_res,\"T\"=>300,\"Phi\"=>0.0,\"d\"=>0.0]);\n", - "\n", - "initialcondssurf = Dict([\"CO2X\"=>0.4*sites,\n", - " \"CHO2X\"=>0.1*sites,\n", - " \"CO2HX\"=>0.1*sites,\n", - " \"OX\"=>0.1*sites,\n", - " \"OCX\"=>0.1*sites,\n", - " \"vacantX\"=>0.1*sites,\n", - " \"CH2O2X\"=>0.05*sites,\n", - " \"CHOX\"=>0.04*sites,\n", - " \"CH2OX\"=>0.01*sites,\n", - " \"A\"=>A_surf,\"T\"=>300,\"Phi\"=>-1.414]);" - ] - }, - { - "cell_type": "code", - "execution_count": 50, - "id": "ddb39b3d", - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "domainliq,y0liq,pliq = ConstantTVDomain(phase=liq,\n", - " initialconds=initialcondsliq,constantspecies=[\"proton\",\"CO2\",\"H2O\"]);\n", - "domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf,\n", - " initialconds=initialcondssurf);" - ] - }, - { - "cell_type": "code", - "execution_count": 51, - "id": "ed49d2b4", - "metadata": {}, - "outputs": [], - "source": [ - "inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainliq,\n", - " domaincat,interfacerxns,298.15,A_surf);" - ] - }, - { - "cell_type": "code", - "execution_count": 52, - "id": "244f0912", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.003065 seconds (8.83 k allocations: 7.948 MiB)\n" - ] - } - ], - "source": [ - "@time react,y0,p = Reactor((domainliq,domaincat), (y0liq,y0cat), (0.0, 1.8e3), [inter], (pliq,pcat,pinter));\n" - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "id": "962f838c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.550028 seconds (1.50 M allocations: 876.191 MiB, 17.04% gc time)\n", - "1800.0\n", - "Success\n" - ] - } - ], - "source": [ - "@time sol = solve(react.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-22,reltol=1e-8);\n", - "println(sol.t[end]);\n", - "println(sol.retcode);" - ] - }, - { - "cell_type": "code", - "execution_count": 54, - "id": "6667bb5a", - "metadata": {}, - "outputs": [], - "source": [ - "ssys = SystemSimulation(sol,(domainliq,domaincat,),(inter,),p);" - ] - }, - { - "cell_type": "code", - "execution_count": 55, - "id": "87dcaf99", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotX (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotX(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = molefractions(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Mole Fraction\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 56, - "id": "ddf6da6b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotC (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotC(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = concentrations(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Concentration\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 57, - "id": "e719a85d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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FqWkoLdu3b6dLly4EBATkiyk9PT1frVu/fv3yPM4dJXLp0qVbXiMtLY0DBw4wcOBAXFxczNttbGwYOnQoV65cKXLTaGnYsWMH9evXp3Hjxnm230nfipulpaVx8OBBHn744TwdanNrC29kMpluWSsL3DLW5ORkDh8+nGd7Ud6f6Ohoxo0bR0BAALa2tuh0OoKCggA4efKkuVzLli1ZvHgx77zzDvv378/XXLN3717i4+MZPnx4nvhNJhM9evTg4MGDRa7pcHFx4dFHH2XhwoUYDAaWLl3KiBEjChyluWPHDoB8zc0tW7akbt26hf4e/frrr2g0Gp588sk8MVeuXJnGjRsXeYRjQfeEG/uUPfLIIwUe98UXX9CsWTMcHBzMr/22bdvyvO6///47Dg4Ot20iLKrTp09z7do1hg4dmqcpxsXFhUceeYT9+/eTnp6e55iCPkeZmZlER0cDcN999wEwaNAgVq1axdWrV4sUS1HvlS1btiQxMZHHHnuMX3755ba1oWWtT58+eR7XrVsXyBlwcPP2G3/Xfv31Vzw8POjbt2+ez1uTJk2oXLlyoZ+3snjfbiU1NZVVq1bRtm1b80CXjh07EhISwuLFi83vFfyvFcTHx8e8TavVMmjQoEKvcbedOHGCq1ev8sQTTwCQkZFB9+7dcXR0ZN26dbz33ntMnz6da9eumY/p27cv27dvNz++uXZcKVUqsVWpUoWvvvqKRx99lPvvv5/HH3+cXbt20bRpU1566aU8NdAuLi4MGjSI3377zVyzf/z4cf7++2+eeuqpYjevVqjkrG7durRo0SLPT/PmzfOUGTlyJFevXmXLli0ALF++nKysrDxfIHFxcVSuXDnfF46vry+2trZ5movulri4OKpUqZJve+7Is5tjurltO3eUU2HV8wkJCSilinWdspT7PtysoG0llZCQgMlkKtJ1Ro4ciU6nM//cPBCisHMU9/0xmUx069aNNWvW8MILL7Bt2zb++usv9u/fn6cc5HTIHz58ON988w1t2rTBy8uLYcOGERUVBWC+UQwcODBP/Dqdjvfffx+llLkpryhGjRplbh6JiYm55fQnuc/5Vp+nwj5L169fRymFn59fvpj3799f5CSgoHvCjQqK7YMPPuCZZ56hVatWrF69mv3793Pw4EF69OiR53WPiYnB39+/1Pq03O71MplM5ubkXLf7HHXo0IGff/4Zg8HAsGHDqFatGg0aNCjSyLmi3CuHDh3KwoULuXTpEo888gi+vr60atXKfMzd5uXlleexnZ3dLbdnZmaaH1+/fp3ExETs7Ozyfd6ioqIK/byVxft2KytXriQ1NZVBgwaRmJhIYmIiSUlJDBo0iIiIiDyve1xcHH5+fvnOUdA2Szpz5gwhISE4OzsDOYlyamoqq1evplu3bgwePJhFixbl+aPTz88vT1/Am9+zm/tilyadTsfgwYOJi4vL1+w/atQoDAYD3333HZDTN1Cj0Zi7ARRHhRqtWRTdu3fH39+fRYsW0b17dxYtWkSrVq3yDH/19vbmwIEDKKXyJGjR0dEYDIY8f4ncLLf25eaBA3f6F6W3tzeRkZH5tuf+NVFYTEXl6emJVqst8+sUlbe3tznBuFFB2xwcHAocrBEbG1tozJ6enmg0miJd580338zT383V1fW2ceVuK05HUMj5i+vff/9l8eLFDB8+3Lz93Llz+cr6+Pjw0Ucf8dFHH3H58mXWrVvHSy+9RHR0NBs3bjQ//08//fSWI46Kc8Nu164dtWvXZsaMGXTt2jVfbW6u3OccGRmZb9qDa9euFfq++Pj4oNFo2L17t/mL60YFbSuJgmr8li1bRqdOnViwYEGe7SkpKXkeV6pUiT179mAymUolQbvx9brZtWvX0Gq1eHp6Fvu8/fv3p3///mRlZbF//35mzZrF448/TnBwMG3atLnlcUW5V0JO/7QRI0aQlpbGrl27mD59On369OHMmTPmmt7yzsfHB29vbzZu3Fjg/pt/129UVu9bQb799lsAJk+eXOAUTN9++y3du3c3x1VQ38yC7lOWpNfr87RahIeHExoamqf1JrcGONeVK1fy3D9u7n9WvXr1Moo2R27N3M2/923btqVu3bosWrSI5557jmXLlvHAAw+UKJ4KVXNWFLlNdD///DO7d+/m0KFD+ZolunTpQmpqar6JI5cuXWrefyu5oxaPHj2aZ3tBHQjt7e1v+5fSjTFt3749T9VubkxOTk6lMrTc2dmZVq1asWbNmjxxmUwmli1bRrVq1Yo9x8yd6Ny5MydOnODff//Ns/2HH37IVzY4ODjfa37mzJnbNsM6OzvTsmVL1qxZk+cv6ZSUlHxz4gQHB+epgbl5Xrdbxerq6kqzZs0KjeNmuUnDzUnIl19+WehxgYGBTJw4ka5du5qbUtu1a4eHhwdhYWH5apFyf3JrGIrqtddeo2/fvoXO2/PAAw8A5Jte4+DBg5w8ebLQ36M+ffqglOLq1asFxtuwYcNixVscGo0m3+t+9OjRfF0HevbsSWZm5m0n1izq73nt2rWpWrUqP/zwQ55mmbS0NFavXm0eCVhS9vb2dOzYkffffx+Af/75p9DyRblX3sjZ2ZmePXvy6quvkp2dzYkTJ0oc693Wp08f4uLiMBqNBX7eCpvDsazft1wnT55k3759PPLII+zYsSPfT5cuXfjll1/MNXkdO3Zk+/bteSoGTCYTP/744x3HUpoCAwM5f/68uZuIn58fERERebqN3DzYYfHixeYkFMj3fhX3j+Hi0Ov1rFy5Eh8fH2rWrJlv/8iRIwkLC+O1114jJiamxN0eKlTN2fHjxwschRQSEpJnDp2RI0fy/vvv8/jjj+Po6MjgwYPzlB82bBiff/45w4cP5+LFizRs2JA9e/bw7rvv0qtXLx588MFbxnDfffdRu3Ztpk2bhsFgwNPTk7Vr1xY4Yqdhw4asWbOGBQsW0Lx5c7Ra7S3nZJo+fTq//vornTt35o033sDLy4vvv/+eDRs2MHv27AKnMSiJWbNm0bVrVzp37sy0adOws7Nj/vz5HD9+nOXLl9/RjPnHjh0rcGb8++67r8C/sCdPnszChQvp3bs377zzDn5+fnz//fecOnUqX9mhQ4fy5JNPMn78eB555BEuXbrE7NmzC5w76WZvv/02PXr0oGvXrkydOhWj0cj777+Ps7NzsZr7/P396devH2+++SZVqlRh2bJlbNmyhffff7/YN+c6deoQEhLCSy+9hFIKLy8v1q9fn6+5KCkpic6dO/P4449Tp04dXF1dOXjwIBs3bjSPLHZxceHTTz9l+PDhxMfHM3DgQHx9fYmJieHff/8lJiYmXy3R7Tz55JO3nbOndu3ajBkzhk8//RStVkvPnj25ePEir7/+OgEBAYWOTmvXrh1jxoxhxIgRHDp0iA4dOuDs7ExkZCR79uyhYcOGPPPMM8WKuaj69OnD22+/zfTp0+nYsSOnT59mxowZVK9ePc/95bHHHmPRokWMGzeO06dP07lzZ0wmEwcOHKBu3boMGTIEyPk937lzJ+vXr6dKlSq4uroW+GWv1WqZPXs2TzzxBH369GHs2LFkZWUxZ84cEhMTee+994r9XN544w2uXLlCly5dqFatGomJiXz88cfodDo6dux42+Nvd68cPXo0jo6OtGvXjipVqhAVFcWsWbNwd3c313ZcunSJkJAQhg8fbq75KW+GDBnC999/T69evXjuuedo2bIlOp2OK1eusGPHDvr3789DDz1U4LFl8b4VJPe1e+GFF2jZsmW+/SkpKWzbto1ly5bx3HPP8eqrr7J+/Xq6dOnCq6++iqOjI1988YW5f+mNtT4xMTH88ccfQM59GnL6VObOP3fjZ+XQoUPmaTiSk5NRSpnv6zffy3O3505/c+jQIXONWG6f7tzvvC1bttCjRw969uzJpEmTmDp1Kq+88gopKSlMmDABgKtXrzJt2jR+//13Dh06VKTXrajxLl26lJEjR7Jw4UKGDRsGwJQpU9Dr9eaZFSIiIvj00085cuQIixYtwsbGJt/1hg0bxiuvvMKcOXPw8PAo+QwPxRo+UE4VNjKLW4ymatu2rQLUE088UeA54+Li1Lhx41SVKlWUra2tCgoKUi+//LLKzMzMU66gUYJnzpxR3bp1U25ubqpSpUpq0qRJasOGDflGGMbHx6uBAwcqDw8PpdFo8ox046bRSEopdezYMdW3b1/l7u6u7OzsVOPGjfONfskdufPjjz/m2V7QKMVb2b17t3rggQeUs7OzcnR0VK1bt1br168v8HzFGa15q5/cmAp6LcPCwlTXrl2Vg4OD8vLyUqNGjVK//PJLvtfSZDKp2bNnqxo1aigHBwfVokULtX379iKN1lRKqXXr1qlGjRopOzs7FRgYqN577z3zyKqiCAoKUr1791Y//fSTql+/vrKzs1PBwcH5RokV5/3Jfe6urq7K09NTPfroo+ry5ct5PhuZmZlq3LhxqlGjRsrNzU05Ojqq2rVrq+nTp5tHiOb6448/VO/evZWXl5fS6XSqatWqqnfv3vliuVlR3+ubR2sqlTM67P3331ehoaFKp9MpHx8f9eSTT6qIiIg85W4erZlr4cKFqlWrVubPYkhIiBo2bJg6dOhQobHk3hMOHjxY4P5bvQ9KKZWVlaWmTZumqlatqhwcHFSzZs3Uzz//XGCMGRkZ6o033lC1atVSdnZ2ytvbWz3wwANq79695jJHjhxR7dq1U05OTgowfx4LGsGtlFI///yzatWqlXJwcFDOzs6qS5cu6s8//8xTJvezeeNIvBufd+5Iu19//VX17NlTVa1aVdnZ2SlfX1/Vq1cvtXv37kJfvxsVdq9csmSJ6ty5s/Lz81N2dnbK399fDRo0SB09etRcJvfzU9CI1cJQgtGaN7/ft3qdhg8frpydnfNs0+v1au7cuapx48bKwcFBubi4qDp16qixY8eqs2fP3jbe0nzfbpadna18fX1VkyZNbnl9g8GgqlWrpho2bGjetnv3btWqVStlb2+vKleurJ5//nnzrAM3juDN/SwW9HPz6Mbhw4ff9l6eq7D7/o3efPNN1aBBA5WamqqUUmr9+vXK09PTPOPCSy+9pIKCgpRWq1XdunVTp0+fvuXrcLOixpv7Hty47dtvv1UtW7ZUXl5eytbWVnl6eqru3burTZs2FXrNhx56qMCR6sWhUaqUhjUIcZfs3LmTzp07s2PHjmKtk1aWgoODadCggXlJFSGEKI+6devGxYsXOXPmjKVDMcvIyKBTp064urqa52A0GAycPXsWPz8/vLy8OHPmDH5+fqXWSlTe3XN9zoQQQoh7wZQpU/juu+/YuXMna9as4ZFHHmHLli289NJLlg4tD0dHRzZs2IDJZKJu3bq8++67hIWFUa1aNXQ6Hf/++y8//vgjzZs3t8hUVpZQofqcFUdERARDhw4lOjoaW1tbXn/9dR599FFLhyWEEEKUCqPRyBtvvEFUVBQajYZ69erx3XffFWuNx7vFx8eHrVu3smzZMj799FNee+018wALW1tb7r//fj744INSW8u5vLtnmzUjIyO5fv06TZo0ITo6mmbNmnH69GnzXCtCCCGEsIykpCTz7ARBQUGlMuLVmtyzNWdVqlQxTxro6+uLl5cX8fHxkpwJIYQQFubu7n7P9C8rSLntc7Zr1y769u2Lv78/Go0m35xjkLN4ePXq1XFwcKB58+bs3r27RNc6dOgQJpPplpNpCiGEEELcLeU2OUtLS6Nx48Z89tlnBe5fuXIlkydP5tVXX+Wff/6hffv29OzZk8uXL5vLNG/enAYNGuT7uXEi17i4OIYNG8ZXX31V5s9JCCGEEOJ2rKLPmUajYe3atQwYMMC8rVWrVjRr1izP5Jl169ZlwIABzJo1q0jnzcrKomvXrowePZqhQ4fetuyNywOZTCbi4+Px9va+o4lZhRBCCHH3KKVISUkp1bVxS5tV9jnLzs7m77//zjccuFu3buzdu7dI51BK8dRTT/HAAw/cNjGDnJnz33rrrRLFK4QQQojyJSIiIt+6v+WFVSZnsbGxGI3GfIs1+/n5FXlR1z///JOVK1fSqFEjc3+277777pZr9r388stMmTLF/DgpKYnAwEAiIiJwc3Mr2RMRQgghxF2VnJxMQEBAoQvaW5pVJme5bm5OVEoVuYnx/vvvx2QyFfla9vb2+RZDBnBzc5PkTAghhLAy5blLUvlsbL0NHx8fbGxs8tWSRUdH56tNE0IIIYSwJlaZnNnZ2dG8eXO2bNmSZ/uWLVto27athaISQgghhLhz5bZZMzU1lXPnzpkfh4eHc+TIEby8vAgMDGTKlCkMHTqUFi1a0KZNG7766isuX77MuHHjLBi1EPcWo9GIXq+3dBiimHQ6HTY2NpYOQwhxC+U2OTt06BCdO3c2P87tjD98+HAWL17M4MGDiYuLY8aMGURGRtKgQQN+++03goKCLBWyEPcMpRRRUVEkJiZaOhRRQh4eHlSuXLlc97sR4l5lFfOclUfJycm4u7uTlJQkAwLEPScyMpLExER8fX1xcnKSL3gropQiPT2d6OhoPDw8zMvYCXGvsIbv73JbcyaEKJ+MRqM5MfP29rZ0OKIEHB0dgZxBVL6+vtLEKUQ5Y5UDAoQQlpPbx8zJycnCkYg7kfv+SZ9BIcofSc6EECUiTZnWTd4/IcovSc6EEEIIIcoRSc6EEEIIIcoRSc6EEEIIIcoRSc6EEPeUqKgoJk2aRI0aNbC3tycgIIC+ffuybds2c5m9e/fSq1cvPD09cXBwoGHDhsybNw+j0Wguc/HiRUaNGkX16tVxdHQkJCSE6dOnk52dbYmnJYSoQGQqDSHEPePixYu0a9cODw8PZs+eTaNGjdDr9WzatIkJEyZw6tQp1q5dy6BBgxgxYgQ7duzAw8ODrVu38sILL7B//35WrVqFRqPh1KlTmEwmvvzyS2rWrMnx48cZPXo0aWlpzJ0719JPVQhhxWQS2hKyhknshCgLmZmZhIeHU716dRwcHICciU0z9MbbHFn6HHU2xRp12KtXL44ePcrp06dxdnbOsy8xMRGdTkdQUBAdO3Zk9erVefavX7+efv36sWLFCgYPHlzg+efMmcOCBQu4cOFC8Z/MXVbQ+yjEvcAavr+l5kwIcccy9EbqvbHprl83bEZ3nOyKdhuLj49n48aNzJw5M19iBjnLGa1du5a4uDimTZuWb3/fvn0JDQ1l+fLlt0zOkpKS8PLyKt6TEEKIm0ifMyHEPeHcuXMopahTp84ty5w5cwaAunXrFri/Tp065jI3O3/+PJ9++injxo2782CFEPc0qTkTQtwxR50NYTO6W+S6RZXbg6MozaC36u2hlCrw+GvXrtGjRw8effRRnn766SLHJIQQBZHkTAhxxzQaTZGbFy2lVq1aaDQaTp48yYABAwosExoaCsDJkydp27Ztvv2nTp2iXr16ebZdu3aNzp0706ZNG7766qtSj1sIce+RZk0hxD3By8uL7t278/nnn5OWlpZvf2JiIt26dcPLy4t58+bl279u3TrOnj3LY489Zt529epVOnXqRLNmzVi0aBFardxShRB3Tu4kQoh7xvz58zEajbRs2ZLVq1dz9uxZTp48ySeffEKbNm1wdnbmyy+/5JdffmHMmDEcPXqUixcv8u233/LUU08xcOBABg0aBOTUmHXq1ImAgADmzp1LTEwMUVFRREVFWfhZCiGsXfluhxBCiFJUvXp1Dh8+zMyZM5k6dSqRkZFUqlSJ5s2bs2DBAgAGDhzIjh07ePfdd+nQoQMZGRnUrFmTV199lcmTJ5v7nG3evJlz585x7tw5qlWrluc6MkOREOJOyDxnJWQN86QIURZkfqyKQd5Hca+yhu9vadYUQgghhChHJDkTQgghhChHJDkTQgghhChHJDkTQgghhChHJDkTQgghhChHJDkTQgghhChHJDkTQgghhChHJDkTQgghhChHJDkTQgghhChHJDkTQgghhChHJDkTQog7FBwczEcffWTpMIQQFYQkZ0IIcQvZ2dmWDkEIcQ+S5EwIceeUguy0u/+jVLHC7NSpExMnTmTixIl4eHjg7e3Na6+9hvrvPMHBwbzzzjs89dRTuLu7M3r0aABWr15N/fr1sbe3Jzg4mHnz5uU556VLl/i///s/NBoNGo3GvK+w43Kv9+677zJy5EhcXV0JDAzkq6++Kum7IISoIGwtHYAQogLQp8O7/nf/uq9cAzvnYh2yZMkSRo0axYEDBzh06BBjxowhKCjInIjNmTOH119/nddeew2Av//+m0GDBvHmm28yePBg9u7dy/jx4/H29uapp55izZo1NG7cmDFjxpjPUZTjcs2bN4+3336bV155hZ9++olnnnmGDh06UKdOnTt/fYQQVkmSMyHEPSUgIIAPP/wQjUZD7dq1OXbsGB9++KE5sXrggQeYNm2aufwTTzxBly5deP311wEIDQ0lLCyMOXPm8NRTT+Hl5YWNjQ2urq5UrlzZfNwHH3xQ6HG5evXqxfjx4wF48cUX+fDDD9m5c6ckZ0LcwyQ5E0LcOZ1TTi2WJa5bTK1bt87T9NimTRvmzZuH0WgEoEWLFnnKnzx5kv79++fZ1q5dOz766COMRiM2NjYFXqeoxzVq1Mi8X6PRULlyZaKjo4v9vIQQFYckZ0KIO6fRFLt5sbxyds77PJRSeZK53G23U9TjdDpdnscajQaTyVTUcIUQFZAMCBBC3FP279+f73GtWrVuWQNWr1499uzZk2fb3r17CQ0NNR9jZ2dnrnkrznFCCFEQSc6EEPeUiIgIpkyZwunTp1m+fDmffvopzz333C3LT506lW3btvH2229z5swZlixZwmeffZanX1pwcDC7du3i6tWrxMbGFvk4IYQoiDRrCiHuKcOGDSMjI4OWLVtiY2PDpEmTGDNmzC3LN2vWjFWrVvHGG2/w9ttvU6VKFWbMmJGnU/+MGTMYO3YsISEhZGVloZQq0nFCCFEQjSpK5wmRT3JyMu7u7iQlJeHm5mbpcIS4azIzMwkPD6d69eo4ODhYOpxi6dSpE02aNJHZ/LHu91GIO2EN39/SrCmEEEIIUY5IciaEEEIIUY5InzMhxD1j586dlg5BCCFuS2rOhBBCCCHKEUnOhBBCCCHKEUnOhBBCCCHKEUnOhBBCCCHKEUnOhBBCCCHKEUnOhBBCCCHKEUnOhBBCCCHKEUnOhBD3lKioKCZNmkSNGjWwt7cnICCAvn37sm3bthKfc8mSJbRs2RJnZ2dcXV3p0KEDv/76aylGLYS4l0hyJoS4Z1y8eJHmzZuzfft2Zs+ezbFjx9i4cSOdO3dmwoQJJTrntGnTGDt2LIMGDeLff//lr7/+on379vTv35/PPvuslJ+BEOJeICsECCHumFKKDEPGXb+uo60jGo2myOXHjx+PRqPhr7/+wtnZ2by9fv36jBw5stjX379/P/PmzeOTTz5h0qRJ5u0zZ84kMzOTKVOm0L9/fwICAop9biHEvUuSMyHEHcswZNDqh1Z3/boHHj+Ak86pSGXj4+PZuHEjM2fOzJOY5fLw8ACgZ8+e7N69u9BzpaamArB8+XJcXFwYO3ZsvjJTp07lgw8+YPXq1UyePLlIMQohBEhyJoS4R5w7dw6lFHXq1Cm03DfffENGRtFqAc+cOUNISAh2dnb59vn7++Pu7s6ZM2dKFK8Q4t4lyZkQ4o452jpy4PEDFrluUSmlAG7bDFq1atU7iunmaxan2VUIIUCSszumN5rQG02WDkOIu0ZvNKGUwvTfTy6HYiRKpUXxv6TrdkJq1kSj0RAWFka//v1vWa5Xr17suU2zZnJKCgC1atViz549ZGZl5as9u3btGsnJydSsWTPP61RemJRCKYXeaMJG7mFClCsaVdQ7m8gjOTkZd3d3AiavQmtftD4vQlQEVV1teLOzL77+1dDY5m/OK8/GDx3I2VMn+eWPv3ByytvvLDkpCTd3d65HXiMrM7PQ8wRWrwHAv3//xbAB3Xlxxvs8PmJMnjJz3nqVFUu+ZsOew1T2r1a6T6QUKEM20deu8OaOaK6mGC0djhB3haPOhgPPt8Xd3Z2kpCTc3NwsHVKBpOZMCHHPeGXmPIY/1J0n+j7IhKkvU6tufYwGA/t27+TH7xby844D+FXxL/L5GjdvyROjxvHhzDfQZ2fzQPfeGAx6NqxZxQ8Lv+D5N2eVy8RMCFG+Sc1ZCeXWnF2OjC23mbcQZSE7K5PoaxEEBQfj4OBg6XCKLTIyklmz3uW3DRuIjIykUqVKNGvWjOeem0zHTp1KdM5Fixby5ZdfEnbiBBqNhqZNmzFt2jT69O1busGXoszMTC5dvIivfwB29tb3PgpRUhpDRrmvOZPkrIRyk7Py/OYKURYyMzMJDw+nevXqVpmciRzyPop7lTV8f8sKAUIIIYQQ5cg9n5ylp6cTFBTEtGnTLB2KEEIIIYQkZzNnzqRVq7s/s7kQQgghREHu6eTs7NmznDp1il69elk6FCGEEEIIoBwnZ7t27aJv3774+/uj0Wj4+eef85WZP3++uTNr8+bNb7se3s2mTZvGrFmzSiliIYQQQog7V27nOUtLS6Nx48aMGDGCRx55JN/+lStXMnnyZObPn0+7du348ssv6dmzJ2FhYQQGBgLQvHlzsrKy8h27efNmDh48SGhoKKGhoezdu/e28WRlZeU5V3Jy8h08OyGEEEKIgpXb5Kxnz5707Nnzlvs/+OADRo0axdNPPw3ARx99xKZNm1iwYIG5Nuzvv/++5fH79+9nxYoV/Pjjj6SmpqLX63Fzc+ONN94osPysWbN466237uAZCSGEEELcXrlt1ixMdnY2f//9N926dcuzvVu3bkWqBYOcZCsiIoKLFy8yd+5cRo8efcvEDODll18mKSnJ/BMREXFHz0EIIYQQoiDltuasMLGxsRiNRvz8/PJs9/PzIyoqqkyuaW9vj729fZmcWwghhBAil1UmZ7k0Gk2ex0qpfNuK4qmnniqliIQQQggh7oxVNmv6+PhgY2OTr5YsOjo6X22aEELcKCIiglGjRuHv74+dnR1BQUE899xzxMXF3dF5d+zYQa9evfD29sbJyYl69eoxdepUrl69ai5jNBr58MMPadSoEQ4ODnh4eNCzZ0/+/PPPO31aQogKxCqTMzs7O5o3b86WLVvybN+yZQtt27a1UFRCiPLuwoULtGjRgjNnzrB8+XLOnTvHF198wbZt22jTpg3x8fElOu+XX37Jgw8+SOXKlVm9ejVhYWF88cUXJCUlMW/ePCCnZn/IkCHMmDGDZ599lpMnT/LHH38QEBBAp06dCpwuSAhxbyq3zZqpqamcO3fO/Dg8PJwjR47g5eVFYGAgU6ZMYejQobRo0YI2bdrw1VdfcfnyZcaNG2fBqIW4NymlUBkZd/26GkfHYnVlmDBhAnZ2dmzevBlHR0cAAgMDadq0KSEhIbz66qssWLCgWDFcuXKFZ599lmeffZYPP/zQvD04OJgOHTqQmJgIwKpVq/jpp59Yt24dffv2NZf76quviIuL4+mnn6Zr1644OzsX6/pCiIqn3CZnhw4donPnzubHU6ZMAWD48OEsXryYwYMHExcXx4wZM4iMjKRBgwb89ttvBAUFWSpkIe5ZKiOD082a3/Xr1j78NxonpyKVjY+PZ9OmTcycOdOcmOWqXLkyTzzxBCtXrmT+/Pk888wzLFu2rNDz5c6p+OOPP5Kdnc0LL7xQYDkPDw8AfvjhB0JDQ/MkZrmmTp3KmjVr2LJlCwMGDCjS8xFCVFzlNjnr1KkTSqlCy4wfP57x48ffpYiEENbs7NmzKKWoW7dugfvr1q1LQkICMTExzJgxg2nTphV6Pn9/f/N53dzcqFKlSqHlz5w5U+i1c8sIIUS5Tc6EENZD4+hI7cO3nvS5LK9bWnL/GNRoNFSqVAlfX98iH1eSUeIFKa3zCCGsmyRnQog7ptFoity8aCk1a9ZEo9EQFhZWYNPhqVOn8PT0xMfHh3HjxhW5WTM0NJSkpCQiIyMLrT0LDQ0lLCyswH0nT54EoFatWkV/QkKICssqR2sKIURxeXt707VrV+bPn0/GTYMXoqKi+P777xk8eDAajYYZM2Zw5MiRQn9ymzUHDhyInZ0ds2fPLvC6uQMChgwZwtmzZ1m/fn2+MvPmzTPHJ4QQUnMmhLhnfPbZZ7Rt25bu3bvzzjvvUL16dU6cOMHzzz9P1apVmTlzJgC+vr5FbtYMCAjgww8/ZOLEiSQnJzNs2DCCg4O5cuUKS5cuxcXFhXnz5jFkyBB+/PFHhg8fzpw5c+jSpQvJycl8/vnnrFu3jh9//FFGagohAKk5E0LcQ2rVqsWhQ4cICQlh8ODBhISEMGbMGDp37sy+ffvw8vIq0XnHjx/P5s2buXr1Kg899BB16tTh6aefxs3NzTywQKPRsGrVKl599VU+/PBD6tSpQ/v27bl06RI7duyQUZpCCDONut2QSFGg5ORk3N3dSUpKws3NzdLhCHHXZGZmEh4eTvXq1XFwcLB0OKKE5H0U9yJTZiap2dnl/vtbmjWFEEIIUWEppUjft4+4b74BjRaPDz+wdEi3JcmZEEIIISocZTSSsmULcV9/Q+aJEzkbbW1xjoy0bGBFIMmZEEIIISoMU3Y2SWt/Jm7ht+gvXQZA4+CAx8CBeD31FJlurhaO8PYkORNCCCGE1TNlZJD440/EffsthuvXAbBxd8fziSfwfPIJbP8b8JOZnGzJMItEkjMhhBBCWC1jahqJK5YTt2gxxrg4AGx9ffEaOQLPRx9Fa4VT1EhyJoQQQgirY0xKIn7ZMuKXfocpKQkAXdWqeI8ejfvDD6G1s7NwhCUnyZkQQgghrIYhPp74xUtI+P57TGlpANgFBeE9dizuffug0eksHOGdk+RMCCGEEOWeIT6euG++JWH5ctR/S7DZ16qF97ixuPXogcbGxsIRlh5JzoQQQghRbhkTE4lbuIj4ZctQ6ekAONSvj88z43B54AE02oq32JEkZ0IIIYQod4zJycQvXkL8kiXm5kuH+vXxmTQRl44d0Wg0Fo6w7FS8dFMIIQoRFRXFpEmTqFGjBvb29gQEBNC3b1+2bdtmLrN371569eqFp6cnDg4ONGzYkHnz5mE0GvOdb8eOHfTq1Qtvb2+cnJyoV68eU6dO5erVqyWOMT4+nsmTJxMcHIydnR1VqlRhxIgRXL58ucTnFMJaGFPTiF2wgHMPdiV2/nxMaWnY165Ntc8/I/inH3Ht1KlCJ2YgyZkQ4h5y8eJFmjdvzvbt25k9ezbHjh1j48aNdO7cmQkTJgCwdu1aOnbsSLVq1dixYwenTp3iueeeY+bMmQwZMoQblyP+8ssvefDBB6lcuTKrV68mLCyML774gqSkJObNm1eiGOPj42ndujVbt25l/vz5nDt3jpUrV3L+/Hnuu+8+Lly4UCqvhRDljSk9nbhvvuH8gw8S8/EnmJKTsasZQtWPPqL62jW4dulS4ZOyXLLweQnJwufiXlXQgtlKKQzZprsei62dtlg36169enH06FFOnz6N801zHyUmJqLT6QgKCqJjx46sXr06z/7169fTr18/VqxYweDBg7ly5QohISGMHz+eDz/8MN+1EhMT8fDwKPZzeuaZZ/juu+84d+4clStXNm/PyMigVq1aNGzYkN9//73Y572ZLHwuygul15O4ejUxn3+OMSYWALvgYHwmTMCtV89S7+hvDd/f0udMCHHHDNkmvnruj7t+3TEfd0RnX7Qbd3x8PBs3bmTmzJn5EjMADw8P1q5dS1xcHNOmTcu3v2/fvoSGhrJ8+XIGDx7Mjz/+SHZ2Ni+88EKB18tNzC5fvky9evUKje3JJ5/kiy++wGQysWLFCp544ok8iRmAo6Mj48eP57XXXiM+Ph6v/2Y7F8JaKaVI2bSZmA8/JPvSJQB01arhM2FCzpQYtvduinLvPnMhxD3l3LlzKKWoU6fOLcucOXMGgLp16xa4v06dOuYyZ8+exc3NjSpVqhR6XX9/f44cOVJomdy/3mNiYkhMTLzl9evWrYtSinPnztGyZctCzylEeZa2/wDRH3xA5tGjANh4eeEzfjyegx5FY8WTx5YWSc6EEHfM1k7LmI87WuS6RZXbg6MozaC36u2hlDIff+P/C43R1paaNWsWOc6ixHWv9LsRFU/mqVNEz/uAtN27AdA4OeE9YgReI0Zg42J9yyyVFUnOhBB3TKPRFLl50VJq1aqFRqPh5MmTDBgwoMAyoaGhAJw8eZK2bdvm23/q1ClzE2VoaChJSUlERkYWWntWnGbNSpUq4eHhQVhYWIHlTp06hUajISQkpNDzCVHe6K9eJfrjj0le/ysoBba2eA4ahM/4Z7D18bF0eOWODAgoIWvoUChEWbDmjuQ9e/bk2LFjhQ4ICAwMpFOnTvkGBKxbt47+/fubBwRERERQs2bN2w4IMBgMXLx4sdC43Nzc8PX1BWDs2LF8//33MiBAVAimtDRiv/6a+EWLUVlZALj16kWl557FLijIIjFZw/e3JGclZA1vrhBlwZq/1MPDw2nbti1eXl7MmDGDRo0aYTAY2LJlCwsWLODkyZP89NNPDBkyhJEjRzJx4kTc3NzYtm0bzz//PF26dGHVqlXmZsX58+czceJERowYwbBhwwgODubKlSssXboUFxeXEk2nERsbS+vWrXF0dGT27Nk0aNCA8PBwXnvtNU6fPs2+ffuoUaPGHb8W1vw+ivJPmUwkrf2Z6I8+NI/AdGrZEt/nn8exYQOLxmYN39/SrCmEuGdUr16dw4cPM3PmTKZOnUpkZCSVKlWiefPmLFiwAICBAweyY8cO3n33XTp06EBGRgY1a9bk1VdfZfLkyXn6e40fP57Q0FDmzp3LQw89REZGBsHBwfTp04cpU6aUKEYfHx/279/PjBkzGDt2LJGRkXh7e9OjRw+WLVtGYGBgqbwWQpSVtL/+4vp775EVdhIAXWAgfi88j8s9NE/ZnZKasxKyhsxbiLIgNS4Vg7yPorRlX75M9Jy5pGzZAoDWxQWfZ57Bc+iTaMvRCExr+P6WmjMhhBBClJgpLY3YL74gfvESlF4PWi0egwdRadIkbGU+vhKR5EwIIYQQxZYziewmrr/3PoaoKACc27bF96UXcfhv5LMoGUnOhBBCCFEsWefPE/XOO6Tv2w+ArmpV/F59BZfOnaVfWSmQ5EwIIYQQRWJKSyN2wQLiFi8BgwGNnR3eo0fjPfpptNJ3sdRIciaEEEKIQimlSNm4MacJ8/p1AFw6d8bvlZexCwiwcHQVjyRnQgghhLil7MuXiXrzTdL27gNyFif3e/UVXDt3tnBkFZckZ0IIIYTIR+n1xC1aTOznn6OysnKaMMeMwfvpUdKEWcYkORNCCCFEHhlHjhD5xnSyzpwBwKlNa6q8+abFlly610hyJoQQQggAjKmpxHz4EQk//ABKYePhge9LL+Lev7+MwryLtJYOQAghrNXrr7/OmDFjyvw60dHRVKpUiatXr5b5tcS9K2XrVi707kPC99+DUrj370+N33/DY8CACpOYKYPJ0iEUiSRnQoh7SlRUFJMmTaJGjRrY29sTEBBA37592bZtm7nMP//8w6OPPoqfnx8ODg6EhoYyevRozvzXxANw/fp1Pv74Y1555ZU7imfv3r306tULT09PHBwcaNiwIfPmzcNoNJrL+Pr6MnToUKZPn57v+IiICEaNGoW/vz92dnYEBQXx3HPPERcXd0dxiXuHITaWK5Oe5crESRiuX0cXGEjgwm/xf/89bD09LR1eqdBfTyN2aRjxy09ZOpQikeRMCHHPuHjxIs2bN2f79u3Mnj2bY8eOsXHjRjp37syECRMA+PXXX2ndujVZWVl8//33nDx5ku+++w53d3def/1187m+/fZb2rRpQ3BwcInjWbt2LR07dqRatWrs2LGDU6dO8dxzzzFz5kyGDBnCjUsfjxgxgu+//56EhATztgsXLtCiRQvOnDnD8uXLOXfuHF988QXbtm2jTZs2xMfHlzg2UfEppUj6dQMXevfJWQ/T1hbvMWOose4XnNu2tXR4pcKQlEX8j2e4/tFhMsPiyDgZhyE+09Jh3ZYsfF5C1rBwqhBloaAFs5VSGLKy7nostvb2xWpu6dWrF0ePHuX06dM4Ozvn2ZeYmGiuebr//vtZu3ZtvuMTExPx8PAAoFGjRowdO9ac1BVXWloaQUFBdOzYkdWrV+fZt379evr168eKFSsYPHiweXv16tV5/fXXGTlyJAA9e/bk+PHjnDlzBkdHR3O5qKgoQkJCGDZsGAsWLCjw+rLw+b3NEBND5Ftvkbo1p8bYvk4d/Ge9i0PduhaOrHSYMgyk/BFByp5r8F9TpibYjaw6Xvg0cy/3398yIEAIcccMWVl8MnzgXb/us0t+QlfExCI+Pp6NGzcyc+bMfIkZgIeHB2vXriU2NpYXXnihwHPkJmYJCQkcP36cFi1a5Nn/7rvv8u677xYax++//0779u3ZvHkzcXFxTJs2LV+Zvn37EhoayvLly/MkZy1btmT37t2MHDmS+Ph4Nm3axMyZM/MkZgCVK1fmiSeeYOXKlcyfP7/C9BcSd04pRfKvvxL1zkxMSUmg0+Ezbiw+Y8ag0eksHd4dUwYTqfsjSdl+GVO6IWebnxOnsk2cORKH4/lk+jdoYOEob0+SMyHEPeHcuXMopahTp84ty5w9exag0DIAly5dQimFv79/nu3jxo1j0KBBhR5btWpVAHP/tbq3qKmoU6dOnj5uucf+888/5liVUrc8vm7duiQkJBATE4Ovr2+hMYl7gz46mqg33yJ1+3YAHOrVo8qsd3GoXdvCkd05ZVJkHI0hafMljP81Wyo3O04b4fTpJAC0Wg1BDX0wZBkLO1W5IMmZEOKO2drb8+ySnyxy3aLK7cFRWC1SUXt5ZGRkAORrDvTy8sLLy6vIMRV2TaVUvlgdHR1JT08v1nml1kwopUhet46ome9iSk4GnY5KE8bjPWpUhagtyzyfSNJv4eivpgJgcrDhvAlOXk5DATY6LfXa+dO0WyCuXg4kJydbNuAikORMCHHHNBpNkZsXLaVWrVpoNBpOnjzJgAEDCiwTGhoKwKlTp2jTps0tz+Xj4wPkNG9WqlTJvL04zZq51zp58iRtC+h8ferUKerVq5dnW3x8vPl6NWvWRKPREBYWVuDzOXXqFJ6enuZYxb3JEB9P1PTppGzZCoBD/fpUefddHGqHWjiyO6ePSiPp93AyT+cMklG2Gi6aNJyIysQI6BxsaNixGo27BODkZmfZYItJBgSUkAwIEPcqa+5I3rNnT44dO3bLAQE6nY7g4ODbDggwmUx4enqyZMmSPIlRfHz8bUdIVq1aFUdHR9LS0ggMDKRTp075BgSsW7eO/v375xsQ0L59ezp16sTbb78NQPfu3Tlx4gRnz56VAQEin5SdO4l87XWMsbH/1ZZNwPvpUWhsrbtexpiURdLmS6Qfvg4KlAauajQcS8gmW4GDs47GXarRoGM1HJzz1wxaw/e3JGclZA1vrhBlwZq/1MPDw2nbti1eXl7MmDGDRo0aYTAY2LJlCwsWLODkyZP88ssvPProo/To0YNnn32WmjVrEhsby6pVq7h8+TIrVqwA4JFHHqF69erMnTu3xPH89NNPDBkyhJEjRzJx4kTc3NzYtm0bzz//PF26dGHVqlXmZsn09HR8fHzYtGkT7du3B3L6nbVt25a6devyzjvvUL16dU6cOMHzzz9PVlYW+/fvv2UzqzW/j6JwpvR0rs+eTeKKlQDY1Qyh6uzZONxUE2ttTNlGUnddIeWPKyh9zgjMaI2Go0nZpJnA0VVHk66BNOhQFTuHWyeg1vD9LfOcCSHuGdWrV+fw4cN07tyZqVOn0qBBA7p27cq2bdvMNUz9+/dn79696HQ6Hn/8cerUqcNjjz1GUlIS77zzjvlcY8aMYcWKFZhMJZ9xfODAgezYsYOIiAg6dOhA7dq1+eCDD3j11VdZsWJFnv5iv/zyC4GBgebEDHKaag8dOkRISAiDBw8mJCSEMWPG0LlzZ/bt21fs/m/C+mX8+y8XHnrInJh5DR9O9dWrrToxUyZF2j/RXJ97iOStl1F6E4nArhQD+xKyMTnraPtwTYa+05Zm3YIKTcyshdSclZA1ZN5ClAWpccmhlKJ169ZMnjyZxx57rMyv17JlSyZPnszjjz9eKueT97FiUXo9sQu+IPbLL8FoxLZyZfxnvYtzIX0nrUHWpWQS159HfyWns38GcDzNwDW9wtFVR9NuQTToUBWdvU2Rz2kN39/Wn14KIYQFaDQavvrqK44ePVrm14qOjmbgwIF3JQkU1ifrQjjXXniBzOPHAXDr25fKr7+GTTlNPIrCkJBJ0u/hZByNzXkMnMkwcj7LhL2rjnb9g6jfoSo6u6InZdZEkjMhhCihxo0b07hx4zK/jq+v7y0nxhX3LqUUiStWcP392ajMTLRublR5czpuvXpZOrQSM2UZSNlxhZQ9V8CgUMClLBOnMo1oXXS06VujQidluSQ5E0IIIayMISGByFdfM08o69y2DVVmzULn52fhyEpGmRTph6+TtPEiplQ9ADF6E8czjGQ52NK0fw0adQ4oVvOlNZPkTAghhLAiaQf+4toLL2C4fh2NTofvtKl4Dh2KRmudY/yyI1JIWHcefUQKAKlGxYkMI7FaDY27BdGka2CBU2JUZJKcCSGEEFZA6fXEfP45cV9+BUphV706VefNtdqRmMbUbJI3XSLtYBQAeqU4nWniokFRr0NVevQIwtm96KuAVCSSnAkhhBDlXPaVq1ybNo2MI0cAcB/4CJVfeQWtk5NlAysBZVSk/RVJ0qaLqMycdS4jsk2EZRoJblWZx3tXx83H8TZnqdgkORNCCCHKseTffiNy+puYUlLQurhQZcZbVtvpPys8iYSfz2G4nrNGbKJBcSzDiEdDHx7qVwMvf+fbnOHeIMmZEEIIUQ6Z0tOJmjmTpNVrAHBs0gT/uXOxq1bVwpEVnzE5i8Tfwsk4EgNAtklxMtNEhr8zHQfWwr+mh2UDLGckORNCCCHKmcywMK5OnUZ2eDhoNHiPG0ulCROsbl1MZVSk7r1K4qZLaAwmlFJcyjZxxUlH80G1qdncN89KGCKHdb3LQgghRAWmlCJh6VKi585D6fXY+vnhP3s2zq1aWjq0Ysu6nEzsqjOo2Aw0QLzBxCmlIbR3DR7tWA0bnXWOLr0b5JURQtxToqKimDRpEjVq1MDe3p6AgAD69u3Ltm3bzGX27t1Lr1698PT0xMHBgYYNGzJv3jyMRmOh59br9bz44os0bNgQZ2dn/P39GTZsGNeuXSvrpyUqAENcHBHjxnF91nsovR6XLl2o/vNaq0vMTBkGYn86Q/T8f1GxGWSbFP9mGkluVYV+M9rQ5MFAScxuo9g1Z0ajkcWLF7Nt2zaio6PzLfq7/b8J8YQQory5ePEi7dq1w8PDg9mzZ9OoUSP0ej2bNm1iwoQJnDp1irVr1zJo0CBGjBjBjh078PDwYOvWrbzwwgvs37+fVatW3bIZJj09ncOHD/P666/TuHFjEhISmDx5Mv369ePQoUN3+dkKa5L6559ce+kljDGxaOzs8H3pRTwfe8yqmvyUUqQfiSHu53Nos4xogMvZJlJDPLh/UCjule7tEZjFUeyFzydOnMjixYvp3bs3VapUyffB+fDDD0s1wLIUHh7OyJEjuX79OjY2Nuzfvx9n56KNFLGGhVOFKAsFLZitlELpTbc5svRpdNpifXn16tWLo0ePcvr06Xy/64mJieh0OoKCgujYsSOrV6/Os3/9+vX069ePFStWMHjw4CJf8+DBg7Rs2ZJLly4RGBhY5OPKmix8Xj4ovZ6Yjz8m7ptvAbCvVRP/ufNwqB1q4ciKxxCXQdQPp+BqzgLlKUbFBQdbGj1eh4C6XhaOLi9r+P4uds3ZihUrWLVqFb2sdBjvjZ566ineeecd2rdvT3x8PPb29+Zkd0LcKaU3ce2NvXf9uv4z2qIp4hp78fHxbNy4kZkzZxb4R5iHhwdr164lLi6OadOm5dvft29fQkNDWb58ebGSs6SkJDQaDR4eHkU+RtwbsiMiuDp1GplHjwLgMWQwfi++iNbRemqYlMFE3KZLpO+5glaBUSnOG8G7ezA9HqiGjY00X5ZEsZMzOzs7atasWRax3FUnTpxAp9PRvn17ALy8yldmL4QoXefOnUMpRZ06dW5Z5syZMwDUrVu3wP116tQxlymKzMxMXnrpJR5//PFy+xe6sIzk334j8o3pmFJTcxYsf+dt3Lp1s3RYxZIRnsT1ZSexTdOjBaL1JtLretN6UChObnaWDs+qFTs5mzp1Kh9//DGfffZZmbaF79q1izlz5vD3338TGRnJ2rVrGTBgQJ4y8+fPZ86cOURGRlK/fn0++ugjc7J1O2fPnsXFxYV+/fpx5coVBg4cyCuvvFIGz0SIik+j0+I/o61FrltUuT04inLfulVvD6WU+fjvv/+esWPHmvf9/vvvee4/er2eIUOGYDKZmD9/fpHjFBWbKT2dqHffJemnnGZzx2bNqDpnNrqq1jN3mSnbSOSqM5iOx2ILZJoUV1ztqDu0Ln7B7pYOr0IodnK2Z88eduzYwe+//079+vXR6fIuRrpmzZpSCSwtLY3GjRszYsQIHnnkkXz7V65cyeTJk5k/fz7t2rXjyy+/pGfPnoSFhZn7dTRv3pysrKx8x27evBm9Xs/u3bs5cuQIvr6+9OjRg/vuu4+uXbsWGE9WVlaecyUnJ5fK8xSiItBoNEVuXrSUWrVqodFoOHnyZL4/9HKFhub08zl58iRt2+ZPNk+dOkW9/9Yx7NevH61atTLvq3rDl6ter2fQoEGEh4ezfft2qTUTAGSePs3V/5tC9oULVjt3WfLxWOJWnkanN6EBrpoUrj2r07FjNTRa6xm8UN4V+xPh4eHBQw89VBax5NGzZ0969ux5y/0ffPABo0aN4umnnwbgo48+YtOmTSxYsIBZs2YB8Pfff9/y+GrVqnHfffcREBAA5HQUPnLkyC2Ts1mzZvHWW2+V9OkIISzMy8uL7t278/nnn/Pss88WOCCgW7dueHl5MW/evHzJ2bp16zh79ixvv/02AK6urri6uua7Tm5idvbsWXbs2IG3t3fZPSlhFZRSJCxfTvR776Oys7H19c2Zu6x1q9sfXE4Y0/VcXhKG7lIyOiDdpIgPdqfxsLo4ukgTZmkrdnK2aNGisoijWLKzs/n777956aWX8mzv1q0be/cWrVPyfffdx/Xr10lISMDd3Z1du3blaaK42csvv8yUKVPMj5OTk82JnRDCOsyfP5+2bdvSsmVLZsyYQaNGjTAYDGzZsoUFCxZw8uRJvvzyS4YMGcKYMWOYOHEibm5ubNu2jeeff56BAwcyaNCgW57fYDAwcOBADh8+zK+//orRaCQqKgrISQ7t7ORL7F5jTEwk8vXXSdmyFQCXjh2pMutdbK2on3PMn1dJ2RCOnSmnuf+qjZZqQ2sTWt/HwpFVXCWuS42JieH06dNoNBpCQ0OpVKlSacZVqNjYWIxGI35+fnm2+/n5mW+Et2Nra8u7775Lhw4dUErRrVs3+vTpc8vy9vb2MppTCCtXvXp1Dh8+zMyZM5k6dSqRkZFUqlSJ5s2bs2DBAgAGDhzIjh07zPeHjIwMatasyauvvsrkyZML7bN25coV1q1bB0CTJk3y7NuxYwedOnUqq6cmyqH0v//m6rTnMURGgk6H37SpeA4bZjVzl2UnZXLpm+M4xmRgB6SaFNnN/GgxsBY2tjIKsywVOzlLS0tj0qRJLF261DwBrY2NDcOGDePTTz/Fycmp1IO8lZs/4Dd21i2K2zWdCiEqnipVqvDZZ5/x2Wef3bJM+/bt+f3334t97uDg4FsOJhD3DmU0EvvFF8R+Ph9MJuyCgvD/YB6O9etbOrQii9oRQcamizgCJqWIdrWn1tMNcK9ctLlAxZ0pduo7ZcoU/vjjD9avX09iYiKJiYn88ssv/PHHH0ydOrUsYszHx8cHGxubfLVk0dHR+WrThBBCiLtFHxXF5adGEPvpZ2Ay4d6/H8GrV1tNYpadmMnpOQcxbLqIDkhWkPVAIM1fbSmJ2V1U7Jqz1atX89NPP+Wpnu/VqxeOjo4MGjTI3DRQluzs7GjevDlbtmzJMzhhy5Yt9O/fv8yvL4QQQtwsZft2Il95FWNiIlonJypPfwN3K/pOurr9MpmbL+FMTm1ZnJcjoWMa4uwpK0jcbcVOztLT0wusnfL19SU9Pb1UggJITU3l3Llz5sfh4eEcOXIELy8vAgMDmTJlCkOHDqVFixa0adOGr776isuXLzNu3LhSi0EIIYS4HVN6OtdnvUfijz8C4FCvHlU/mIddcLBlAyuizMRMLnx1DLf4TOyBVAX23YJp2qX8LDd2ryl2ctamTRumT5/O0qVLzeuxZWRk8NZbb9GmTZtSC+zQoUN07tzZ/Dh3pOTw4cNZvHgxgwcPJi4ujhkzZhAZGUmDBg347bffCAoKKrUYhBC3Jn2rrJu8f6Uj49gxrk17nuxLl0CjwWvECCpNfg6tlYzMvbIzgsyNF3Hjvyk/fBwJHdMIB3cZAGdJxV74/Pjx4/To0YPMzEwaN26MRqPhyJEjODg4sGnTJupbSbv6nbKGhVOFKAtGo5EzZ87g6+src3hZsbi4OKKjowkNDcXGpnxPIFweKaORuK+/Juazz8FgwNbPD//338O5dWtLh1Yk+rRszn55DLfonBavDMChezABnSv+FFHW8P1d7JqzBg0acPbsWZYtW8apU6dQSjFkyBCeeOIJHK1osVYhRMnY2Njg4eFBdHQ0AE5OTlYzNYDIqR1JT08nOjoaDw8PScxKIPvKVa69+CIZ/0107tqjB1XenI6NlSxuH3UwiuQ1Z3H7r2om0dOBmuOktqw8KXbNmchhDZm3EGVFKUVUVBSJiYmWDkWUkIeHB5UrV5bEupiS1q8n6q0ZOQuWOznh9/rruA/obxWvo0Fv5My3x3EJT0Kr0ZCpQNc5gKAewZYO7a6yhu/vItWcrVu3jp49e6LT6cwTLN5Kv379SiUwIUT5pdFoqFKlCr6+vuj1ekuHI4pJp9NJjVkxGRISuP72OyT/9hsAjk2a4D9nNnZWslJM3JkEri85gZtRgUZDkrOO4HGNcK509+YmFUVXpJozrVZLVFQUvr6+aLW3nhpNo9FgNBpLNcDyyhoybyGEEHcuZfsOIqe/gTEmFmxs8Bn/DD5jx1rFguVKKU4vP439v9HoNBoMSmFsUZnqj9Qs9Pu8IrOG7+8ifbJyVwK4+f9CCCFERWVMTub6u7NI+vlnAOxq1MD/vVk4Nmpk2cCKKC02nfPzj+KVrgeNhjSdlsoj6uNew8PSoYnbKHbavHTpUrKysvJtz87OZunSpaUSlBBCCGFJqbt3c6Fvv5zETKPBa+RIqq9dYzWJWcQfV7g652+80vU5g0BquFNremtJzKxEsQcE2NjYEBkZia+vb57tcXFx+Pr6SrOmEEIIq2VMTSX6/fdJ/PEnAOyCgqgyaxZOzZpaOLKiMWQZOf3lUdyupqDRaMjUgNvDtfC9r7KlQys3rOH7u9gN5rdaXPzKlSu4u7uXSlBCCCHE3ZayfTtRM97G8N+6zZ7DhuL7f/+H1kqmiYo/m0jU4uO4/9fpP9nDnpDxjbF3kykyrE2Rk7OmTZui0WjQaDR06dIF2xs6QhqNRsLDw+nRo0eZBCmEEEKUFX10NNffmUnK5s0A6AICqDLzHZxbtrRwZEWjlOLs2nPYHojETaNBrxSaNlWpNyDE0qGJEipycjZgwAAAjhw5Qvfu3XFxcTHvs7OzIzg4mEceeaTUAxRCCCHKgjKZSFy1iuh5H2BKSQEbG7xHjsBn/HirqS3LSs3m1GdH8E7Myun0b6ul8qgGuFeXlixrVuTkbPr06QAEBwczZMgQ7O2lmlQIIYR1yjp3jsg3ppNx+DAADg0bUuXtGTjUqWPhyIouOiyO2O9O4v1f1/G0ai7UHNMIGzuZw87aFbvPWb169Thy5AitWrXKs/3AgQPY2NjQokWLUgtOCCGEKE3GlBRiP/uc+O+/B4MBrZMTlSZPxvOJx9FYycS8SinOrj6L7mBUTjMmYN8tiNoPBFo6NFFKij2VxoQJE4iIiMi3/erVq0yYMKFUghJCCCFKkzKZSFy9hvM9ehK/ZAkYDLh06UKNDb/iNWyo1SRm2Wl6jr9/CKdD19FpNKTpbKg0sQn+kphVKMWuOQsLC6NZs2b5tjdt2pSwsLBSCUoIIYQoLRnHjhH1zjtk/nsUALvq1fF75WVc2re3cGTFExsWT8x3YXjmNmMGuFJrTEO0OutILEXRFTs5s7e35/r169SoUSPP9sjIyDwjOIUQQghLyr5yhZiPPyF5/XoAtE5O+EyYgNfQJ9HY2Vk4uuI5u/ostn9F4qrRkK3+a8bsIrVlFVWxs6muXbvy8ssv88svv5jnNUtMTOSVV16ha9eupR6gEEIIURyGhATivviChB+Wo/R6ANz796PS1KnobppAvbzTp+k5/dkRPBIyQaMhRaclYGwjXKq5Wjo0q2IyGUm4dpXU+Hg8g2vc/gALK3ZyNm/ePDp06EBQUBBNm+bMmHzkyBH8/Pz47rvvSj1AIYQQoihMGRnEL/2OuK+/xpSaCoBz2zZUmjoVx/r1LRxd8SWcSeD64hN4mHKaMVMDXAkd0wgb3b25YHlRKaVIiYsl6vwZos7l/FwPP0d2RgZO7h48PudzS4d4W8VOzqpWrcrRo0f5/vvv+ffff3F0dGTEiBE89thj6HS6sohRCCGEuCVTZiaJq34k7uuvMcTEAGBfty6+06bi0q6dhaMrmcu/XsC0+wou/zVj6roFUUeaMQtkMhmJvXyJKydPcPXUCa6eDiMtIT5fOVt7e7z8q5GdkWGBKIun2GtrihzWsDaXEEJUZKbMTBJXriT2m28wxsQCoPP3p9L/Tcatd280WuurYTJmGjj/xVGcotIASLLVUm10Q9yD5Hsml9FgIOr8Wa6cPM7Vk8e5duYUWelpecpotFp8AoOpEhJK5Zo5P95VA9Da2FjF93eJe/CHhYVx+fJlsrOz82zv16/fHQclhBBC3IopI4OEFSuJ+/ZbjLE5SZmtfxV8xozF/eGH0FpZZ/9caZeTufb1MZz0JpRSxPs5U39CE2zt7+3RmEopEiKvcenoYS4dO0LEiaP5ar90Do74h9ahWp36VK1bn8ohtdDZO1go4jtX7OTswoULPPTQQxw7dgyNRkNuxVvuYuhGo7F0IxRCCCEAU3o6CctXELdwIca4OAB0VaviPXYMHgMGWN0IzBtFb7tMxpZLOAKZJoWxrT+NB9S0dFgWk5WezqWjh7n4b05ClhwTnWe/g6sbAXUbULVOfarVrU+loOporWSuuqIodnL23HPPUb16dbZu3UqNGjX466+/iIuLY+rUqcydO7csYhRCCHEPM6WlkbBiBXHfLsQYn9OXSFe1Kj7PjMO9f380Vtzf2ZRt5PLC49heTMYGiAd8n6pP5Xrelg7trkuOjeb8339x/tABIk4cw2Q0mPfZ2NpStU49Ahs2JbhRU3yDa1hls3VRFTs527dvH9u3b6dSpUpotVq0Wi33338/s2bN4tlnn+Wff/4piziFEELcY4ypaST88APxixZhTEgAQBcQgM+4sbj362fVSRlA1rUUrn51HLtMA0oprrna03BSE5zc7421q5VSxFwK59zBfZw7dICYixfy7Pf0r0aNps0JatSManXqo3Ow3mbK4ip2cmY0GnFxcQHAx8eHa9euUbt2bYKCgjh9+nSpByiEEOLeYkxJIWHZMuIXL8GYlASALjAQn3HjcO/bx+qTMqUUSXuukbzhAnbkNGMm1fPmvqF10dpU3NqgXHFXLnNq725O79tNwrUr5u0ajRb/2nUIad6KkBat8PKvZsEoLavYyVmDBg04evQoNWrUoFWrVsyePRs7Ozu++uqrfKsGCCGEEEVlTEoiful3xC9diiklBchZasnnmXG49eqFpgKsQmPKMnL9h5MYTyegBaKNCrcBNWnezt/SoZWpxKhITu3dxel9u4m9fNG83Uano3qT5tS8rw3Vm7bAyc3dckGWI8X+pL/22mukpeUMWX3nnXfo06cP7du3x9vbm5UrV5Z6gEIIISo2Y1IScYsXk/DdMvPksXYhIfg88wxuPXtYzaLkt5N9LZXri06gScnGpBThNlrqT2yCTwWd7T87I53T+/dwYudWrp7639rbWhtbghs3pXab9oS0aI29k5MFoyyfSmWes/j4eDw9Pc0jNu8F1jBPihBClGem9HTiv1tG3DffmGvK7GvVwmfCeFy7daswHb6VUqQdiCThl/NoFGSYFJe8Hbl/QhMcXKy7ifZmymQiIuw4J/7YypkDf2LIygJymiwDGzamdtv21LqvLQ7/dY+yBGv4/i5WzZnBYMDBwYEjR47QoEED83YvL69SD0wIIUTFpLKzSfjxR2IXfGGep8y+Vi18Jk3E9cEHK0xSBmDKNBD30xmyjsehAaL0JjKb+tH5sVBsKlD/svTkJI7v2MLRrb+TFH3dvN3Tvxr1O3ahXofOuHr5WDBC61Ks5MzW1pagoCCZy0wIIUSxKZOJ5A0biPn4E/RXcjqC66pVo9Jzz+b0KasgzZe5sq+kELvsJKbELExKcTLLRLWHa9KiQ8Xo6K6UIvLsaY5s3sCZfbsxGnKmvrBzdKJ22/Y06PQgVWrVuada1UpLifqcvfzyyyxbtkxqzIQQQhRJ+j//cP3dWWQeOwaAjY8PPuOfwXPgQKuePLYgSilS914jaUM4mBTpJsUxpaHNxCb41/SwdHh3TJ+dxak9f3Bk0waiL543b/erUZMm3XpTu217q56dvzwodnL2ySefcO7cOfz9/QkKCsLZ2TnP/sOHD5dacEIIIaybPjKS6HkfkPzrrwBonZzwHjMGr2FD0VbAjuCmdD3xP50lMyxnBYNr2SYueznQfXxjXL2sO2FJT07iyKYNHNn0KxkpyUDOaMs6bTvQpFtvKtcMtXCEFUexk7MBAwaUQRhCCCEqElNGBnHfLiTum29QmZmg0eD+8EP4Tp6MbaVKlg6vTGRdSib+h1MYk7IwKsWJDBPa+t70f6oeOiteHzMh8ip/b/iFEzu3YtDnrKftVsmXJt370KDTgzi6ls9O9dasyKM1Fy5cyBNPPIG9/b0xc/HtWMNoDyGEsITUP/4g6q0Z6K9dA8CxeXP8XnkZx/r1LRxZ2VAmRcquKyRvuggKUo2KQ+kGaveqTotewVbb5yry7GkOrlvN2YP74L9Uwa9GTVr0fZjQVu2sdi1La/j+LnJyZmNjQ2RkJL6+vgD4+/uzd+9egoODyzK+cssa3lwhhLib9NejuT5rFikbNwJgW6UKfi88j2uPHlaboNyOMTWb+FVnyDqTs7zUlWwTx/SKTsPrUquFn4WjK5mrp0+y76cfuHT0f8sx1mh2Hy36PES1eg2t/r20hu/vIjdr3pzDpaSkYDKZSj0gIYQQ1kUZjSSsWEHMhx/lTCJrY4PX8OFUmjihQvYry5V5PpH4FacxpWRjVHA0w0CMgy19JzWicnXrm+n+yqkT7PtpOZePHQFAo9VSr31nWvR9GJ+AIMsGd4+x/rUwhBBCWEzm6TNEvv46mUePAuDQuBFV3noLhzp1LBxZ2VFGE8nbLpOyIwIUpJgUB1MN2FVxZuD4Rrh5O1o6xGK5EnacvT/9QMSJnPdQa2ND/Y5daDlgEB5+lS0c3b2pyMmZRqPJU5V582MhhBD3DmUwEPfNN8R8Ph/0erQuLlSa8n94Dh5c4eYru5EhLoP4FafJjshZ0eBSloljGUaqNfCm26j62DlaT53H9fDz7Fm+hIv/5syyoLWxpUHnB2nZ/1Hcfa2zSbaiKFazZmhoqDkhS01NpWnTpmhvmsk5Pj6+dCMUQghRrmSdPcu1l14m88QJAFy6dKHy9DfQ/dcnuSJSSpF+OJrEX86jso0YtRoOp+i5plc06lyNdgNrorWSGf8Toq7x58plnN67C8ipKWv4QDdaDngUN5+K+x5akyInZ4sWLSrLOIQQQpRzymAgbtEiYj/5FKXXo3V3p/Jrr+LWp0+FbkkxZRhIWHuWjKM5S02l6LTsi80iE+gwJJSGnaxjxv+0xAT2/bScY9s3YfpvpZ867TrSbtCTeFSuYuHoxI2KnJwNHz68LOMQQghRjmWFh3PtpZfI/DenX5JLp05UfustdH4Vu6Yl60IS8atOY0zMAg2Ea7UcjclC52BD79ENCKrvbekQbys7M4OD61Zz6Ne15oXIqzdpzv2PDcc3uIaFoxMFsZ7GcSGEEHedUoqkNWuIemcmKiMDrasrfq+8gvuA/hW6tkwZTSRvvUzKzpxO/7jZsT8hm+spWbh42tNnYmO8q7pYOsxCKZOJE7u2s2fFUtIScrocValVm/aPP0VAvYYWjk4URpIzIYQQBTImJRH5xnRSNm0CwKlVK/zffw9d5Yo9gk8flUb8qtPor6UBYKrhzubj8WRlm/AJcKHPhMY4e5TvCdmvnDzOzqXfcP3COQDc/SrT8YmR1GzZpkIn1RWFJGdCCCHyST94kKsvvIghMhJsban03LN4jxxZoUdimmf633IJjAqtky0pdbzYtuMqSkFAPS96jGmAnUP5/epMio5i1/eLObN/DwB2jk60fmQITXv0xVans3B0oqjK7ydMCCHEXaf0emI+/5y4L78CpdAFBVJ17lwcG1bsZjB9TDoJP54h+3LOFBkOdb244Kjj4PYrANRpW4VOT9TGppyOyMzOSOfAzz/y94afMer1aDRaGnbpRrtBT+Lk7mHp8EQxlTg5y87OJjw8nJCQEGxtJccTQghrp4+M5Or/TSHjyBEA3B95mMqvvILW2dmygZUhZVKk7r1G8qaLKL0Jjb0Nbr1rsP94LGf+S8zu61Od+3qXzzUylVKc2f8nO5d+TWp8HAAB9RvRefhoKgVVt3B0oqSKnVWlp6czadIklixZAsCZM2eoUaMGzz77LP7+/rz00kulHqQQQoiylbprF9deeBFjYiJaV1eqzHgLt549LR1WmdLHpJOw5izZ4ckA2Nf0wLlPDbasOMOVUwlotBo6PVGbeu38LRxpweKvXWX7oi/Ma2C6+/rRadhoQlq0KpeJpCi6YidnL7/8Mv/++y87d+6kR48e5u0PPvgg06dPl+RMCCGsiDIYiPn0M+K+/BIAh/r1qfrRh9gFBFg4srKjDKacvmXbL4NBodFpce9dHep4se7To8RdTUVnb0OPMQ0ILIdTZeizMjmw9kcOrV+N0WDARqejZf+B3Nd/IDq78j1QQRRNsZOzn3/+mZUrV9K6des8mXm9evU4f/58qQYnhBCi7Oijo7k27XnS//oLAM/HH8P3pZfQ2tlZOLKyk3U5mYTVZzFcTwfAPtQTzwE1STWYWDfnMClxmTi52dFnYmMqBbpaONr8zv99gO2LviI55joAwU2a88CIsXhWLp+1e6Jkip2cxcTE4FvAEh1paWlSjSqEEFYibf8Brk6bhjE2Fq2TE5XfnoF7796WDqvMmLIMJG+6ROq+a6BA62yLR98QHBtXIjYilfWfHiEjRY9bJUf6P9cEN5/ytXh5UnQU2xd/xYW/cxJpV+9KdB4+WqbGqKCKnZzdd999bNiwgUmTJgGYPxRff/01bdq0Kd3ohBBClCplMhH31dfEfPIJmEzY16pF1Y8/xr5Gxew8rpQi42gMSRvCMSZnA+DUzBf33jWwcdZx9UwCv80/SnamEZ8AF/pOaoKTW/mpOTTo9Rxav4YDa1Zi0GejtbGheZ+HaPPwEHQODpYOT5SRYidns2bNokePHoSFhWEwGPj44485ceIE+/bt448//iiLGIUQQpQCY2oakS+/RMqWrQC4P/QQld94Ha1j+aolKi36qDQSfjlPdngSADZeDng+VBOHWp4AXDgSw+ZvTmA0mPCv5UGv8Y2wdyw/sw9cPPoP2xd+QULkVQAC6jWky6hn8K4WaOHIRFkr9qewbdu2/Pnnn8ydO5eQkBA2b95Ms2bN2LdvHw0r+Dw4QghhrbIuhHNl0iSyz59Ho9Ph98breD76qKXDKhOmDAPJWy6Ruv8amECj0+LaKQDXDtXQ6HLmKQv78xo7l51CKaje2IduT9fHVlc+JthNiY9l59JvObNvNwBO7h50GvY0ddp1lCbMe4RGKaUsHYQ1Sk5Oxt3dnaSkJNzc3CwdjhBC3FLKjh1ce/4FTKmp2Pr6Uu3TT3Bs3NjSYZU6ZTSRdug6yZsvYUrTA+DY0Af3XtWx9fxfE+DhTZfYtzZnAFvddlXo9HhttOVgclmjwcA/v69j70/L0WdmoNFoadKjN+0GPYm9U8Wda+5us4bv7yLVnCUnJxf5hOX1iQohxL1GmUzELlhA7KefAeDYvDnVPvoQ20qVLBxZ6VImRcaxWJK3XMIQmwGAra8jHv1CcKjp+b9ySvHX+nAO/XYRgGbdA2k9IKRc1EZdOXmcbd8uIDbiEgBVQuvw4Kjx+AbXsHBkwhKKlJx5eHjc9sOrlEKj0WA0GkslMCGEECVnTE3l2osvkbptG5AzTYbfSy+hqUDTZCilyDqbSNLGcPMi5VpnHa4PBODSugqaG2rDlFLsXX2OI1sjAGjzUAjNugdZJO4bpScl8seyhYTt2g6Ag6sbHR5/igadHkSjtXxtnrCMIiVnO3bsKOs4hBBClJKsC+FcmTiR7AsX0Oh0VH5zOh6PPGLpsEpV1uVkkjdeJOtCTmd/jb0Nrh2q4XK/P1r7vF9tyqTYteIMx3fldKxvP7gWjTpbdpJdk8nI0a2b2LNiCVlpaaDR0OiB7tz/2DAcXaUF6l5XpOSsY8eOZR2HEEKIUpD6559cnfx/mFJSsPXzy+lf1qiRpcMqNfrraSRtukRmWM46kthqcGntj2vnAGycdfnKm0yKHd+d5NS+KNBA5yfqUO9+y07YGnXuDFu/XcD1C2cB8A0O4cGnx1OlVm2LxiXKjxKNGU5MTOTbb7/l5MmTaDQa6tWrx8iRI3F3dy/t+IQQQhRR/A8/cH3mu2A04ti0KdU+/QRbHx9Lh1UqDPGZJG+9RPo/0aAADTg198PtwUBsPQqe78toNLF1URjnDkWj0WroMrwutVtVvruB3yAzNZU9K5bw79aNoBR2jk7cP2Qojbv1QqstHyNFRflQ7NGahw4donv37jg6OtKyZUuUUhw6dIiMjAzztBr3AmsY7SGEuDcog4Hr784i4YcfAHDv34/KM2agtbf+dRaNqdmkbI8g9UAkGHO+rhwbeOPWLRidr9OtjzOY2PT1ccL/jUVro6HbqPqENMu/us3doJQibNd2/li2kIzknGbYuu070/HJkTh7eN7maFHarOH7u9jJWfv27alZsyZff/01trY5FW8Gg4Gnn36aCxcusGvXrjIJtLyxhjdXCFHxGZOTuTr5/0jbuxc0GipN+T+8n366XIxAvBOmTAMpu6+SuvsKKtsEgH1ND9y7B2MXUPial0ajiU1f5SRmNrZaeoxtQHBDy9QgRp07w/YlXxF55hQA3tUC6TJyHAH1K05Ts7Wxhu/vYidnjo6O/PPPP9SpUyfP9rCwMFq0aEF6enqpBliWPvzwQ7755huUUjz44IN8/PHHRb6hWcObK4So2LIvXSJi3DNkh4ejcXSk6pzZuD74oKXDuiNKbyJ1/zVSdkRgSjcAoKvmgnv3YPPM/oUxGk1s+eYE5/+JwcZWS6/xDQms513WYeeTlpjA7h+WcOKPnNUYdPYOtH5kCM1798fGNn/fOHH3WMP3d7H7nLm5uXH58uV8yVlERASuroX/NVOexMTE8Nlnn3HixAl0Oh0dOnRg//79sj6oEMIqpO0/wJXnnsOUlIRt5coELJiPQ926lg6rxJRRkX74OslbL2NMygLAtpIjbt2CcWzgXaQ/nE3/9TE7/08MWlsNPcfd/cTMoNdz+Ldf2L9mJfrMnDnX6nV4gPaPDcfF6+4nicI6FTs5Gzx4MKNGjWLu3Lm0bdsWjUbDnj17eP7553nsscfKIsYyYzAYyMzMBECv1+Pra5n+CEIIURyJP/1E5JtvgcGAQ+NGBHz2mdVOLKuUIjMsjqSNFzHE5CQzNu52uD0YhFMzPzQ2RWvNMJkUWxef5NyhaLQ2GnqOaUhQg7uXDCmlOP/3X/yx9BsSr0cCULlmKA88NVZGYYpiK3ZyNnfuXDQaDcOGDcNg+K/KWafjmWee4b333iu1wHbt2sWcOXP4+++/iYyMZO3atQwYMCBPmfnz5zNnzhwiIyOpX78+H330Ee3bty/S+StVqsS0adMIDAzE1taWcePGERISUmrxCyFEaVNKEfPRx8R9+SUAbr17U2XmO2gdCh6tWN5lhSeR9Hs42ZdTANA62eLaOQCX1v7mNTCLwmRSbF9ykrMHr6PVaug+ugHBje5eH7Ooc2fY9cNiIk4cBcDZ04sOjz9F3fs7yUSyokSKnZzZ2dnx8ccfM2vWLM6fP49Sipo1a+LkdOtRMyWRlpZG48aNGTFiBI8UMHniypUrmTx5MvPnz6ddu3Z8+eWX9OzZk7CwMAIDAwFo3rw5WVlZ+Y7dvHkzjo6O/Prrr1y8eBFHR0d69uzJrl276NChQ4HxZGVl5TlXcZa0EkKIO2XKzibylVdJ/vVXAHzGj8dn0kSr7Pivj0ojaeNFMk/FAzkLk7vcXxXXjtXQOhTva0kpxR/fn+L0gSg0Wg3dRtenRpO7U4uYEHmVPSu+48z+PQDY6HQ07z2AVgMexc6xdL8Txb3FKhY+12g0+WrOWrVqRbNmzViwYIF5W926dRkwYACzZs267Tl//PFHdu7cyeeffw7AnDlzUErxwgsvFFj+zTff5K233sq3vTx3KBRCVAzGpCSuTJxE+sGDYGtLlbfewuORhy0dVrEZEjNJ3nzDXGVacL6vMm5dgrBxK/6yUkop9q45z5Etl9FooOuo+tRq4Vf6gd8kLTGBfT8t59j2TZiMRtBoqN+hC20HPY6bj3SPKe8q1ICAkSNHFqncwoULSxxMUWVnZ/P333/z0ksv5dnerVs39u7dW6RzBAQEsHfvXjIzM9HpdOzcuZMxY8bcsvzLL7/MlClTzI+Tk5MJCLDs8h9CiIov+8pVIsaOJfv8ebTOzlT79BOc27a1dFjFYsoykrIzgpTdV8Dw31xlDX1w6xaErlLJa5gOb7rEkS2XAej0ZJ0yT8zSkxI5uH4NRzZvwPBfS0qNZvdx/2PDqRQYXKbXFveWIidnixcvJigoiKZNm2LpyrbY2FiMRiN+fnl/Ef38/IiKiirSOVq3bk2vXr1o2rQpWq2WLl260K9fv1uWt7e3x74CTOgohLAeGceOE/HMMxhjY7H18yPgqy9xqG09ncuVSZH+TzRJGy9iSskGwK66O+49g7EPvLMai+O7rrL/5wsAtBtYk3rtym5JprTEBA6uX8O/W34zJ2VVatam/RNPEVCvYZldV9y7ipycjRs3jhUrVnDhwgVGjhzJk08+iZeXV1nGdls397VQShWr/8XMmTOZOXNmaYclhBB3LGX7Dq5OnYrKyMC+dm0CvvwCXWXLLT1UXFkXk0j89QL6K6kA2Hg54NGrOg71izYtRmHOHrzOH8tPA9C8ZxBNHgy843gLkhofx6Ff1/Lvlt8xZOckZZVDatHm0cep3qSFVfb3E9ahyMnZ/Pnz+fDDD1mzZg0LFy7k5Zdfpnfv3owaNYpu3brd1Q+pj48PNjY2+WrJoqOj89WmCSGEtUlYvpyot98Bkwnndu2o+vFH2Li4WDqsIjEkZpL0+0Uy/o0BQGNvg9sDAbi0q4rG9s5HLl46HsfWRWGgoEGHqrTqV+OOz3mzmMsX+fvXtZzc8wcmY86sBJVrhtJ24OMEN2kuSZkoc8UaFmNvb89jjz3GY489xqVLl1i8eDHjx49Hr9cTFhaGy126edjZ2dG8eXO2bNnCQw89ZN6+ZcsW+vfvf1diEEKI0qaUIuaTT4hb8AUA7gMfocr06Wh05X9GeWUwkfLHFZJ3RIDBZF6Y3L17MDauxe/sX5DrF5PZ+NUxTCZFrfv86DAktNQSJaUUl44d4e9f13Lx38Pm7f6169H64cEEN24mSZm4a4o9lUYujUaDRqNBKYXJZCrNmABITU3l3Llz5sfh4eEcOXIELy8vAgMDmTJlCkOHDqVFixa0adOGr776isuXLzNu3LhSj0UIIcqaMhiIeustEn/8CQCfiRPxmTDeKhKCzLMJJP5yHkNsziSydtXd8OgTgl3V0vuDPSkmgw2f/4sh20RAPS+6PFUXjfbOX5uM1BTC/tjO0W0bib8aAYBGo6VWq7a06POQTCArLKJYyVlWVpa5WXPPnj306dOHzz77jB49eqAt5Yn2Dh06ROfOnc2Pc0dKDh8+nMWLFzN48GDi4uKYMWMGkZGRNGjQgN9++42goKBSjUMIIcqaKTOTq9Omkbp1G2i1VH7jDTyHDLZ0WLdlTM4i8dcLZByNBUDrqsOjTw0cG1Uq1aQyM1XPr5/9S0aKHp8AF3qMaYCNTcm/c5RSXDt9kqNbf+fM/j8x6HMGK+jsHWjwQFea9+qPu6/19O8TFU+R5zkbP348K1asIDAwkBEjRvDkk0/i7X3vrhNmDfOkCCHKP2NyMhHjx5Nx6G80dnb4z52DW7dulg6rUMqoSN13jeQtl1BZRtCASxt/3LoFFXsS2dsx6I2s++gIkeeTcPG0Z+CLLXD2KNnI+YTIq5zcs5OTe3aSGBVp3l4pqDqNHuxJ3fs7YV/KE6qL8scavr+LnJxptVoCAwNp2rRpoX8RrVmzptSCK8+s4c0VQpRv+uvRRIweTdaZM2hdXKg2/3OcW7a0dFiFyrqcTOLac+gj0wCwC3DFY0DNUm3CzKVMik3fnOD84WjsHG15+PlmePsX7zrJsdGc+2sfJ/fsJOr8WfN2W3t7ardpT+MHe1K5Zun1XRPlnzV8fxf5T5xhw4bJh1cIIUpJVng4EaOeRn/tGjaVfAj8+msc6tSxdFi3ZEzTk7zpIml/5YyS1zja4t4jGOf7KpdK36+C7F17nvOH/1vIfFzDIiVmSiliLoVz7uB+zh86QPTF8+Z9Gq2WoEZNqXt/J2re1xo7B8cyiVuIO1WsSWiFEELcuYxjx4gYMxZjQgK6oEACv/0Wu2rVLB1WgZRJkX74Okm/h2NKy5lWwqm5H+49g7FxKZ1RmAUJ23PNPPt/l+F1qVbb85ZlM1NTiThxlEvHjhB+5BDJMdHmfRqNFv/adQht3Z7abe7H2ePW5xGivCjdzgFCCCEKlbrnT648+ywqPR2H+vUJ+OpLbMtp/93syDQSfz5H9qVkAGz9nPAcUBP76u5let1rZxPMk8y27Fud0JZ5O+cbsrO5duYUl479w+VjR7h+4TxK/W/WAFs7e4IbNyWkRWtqNLsPJ7eyjVeI0ibJmRBC3CVJ63/l2ssvg8GAc9s2VP3kU2xcnC0dVj6mLAPJWy6TuvcqmEBjp8XtwSBc2vmjuYNRkkWRHJvB718cx2RU1GzhS4tewRgNBq5fOEvEiWNEhB3j6qkw84z9ubyqBhDUqAlBDZsS2LAxOjtZbk9YL0nOhBDiLohfupTr784CwK1XL/zfm4XGruyaBUtCKUXG8TiS1p/HmJwzvYRjA2/c+4RgW8IRksWRnWFgw/yjZKRm4lEpBTePGFa/u5Jrp0+iz8rMU9bZ04ugBo0JbNiEwIaNcfXyKfP4hLhbJDkTQogydPOs/55PPonfKy+jKeW5Ie+UITaDhHXnyTqTAPy3Fmb/EBxrl/0aykaDgajzZ9m2cAtxV05jMl7jeqKe6/8bXImDqxsB9RoQUK8hAfUb4V0tUAapiQpLkjMhhCgjymgk6p13SFy+AoBKzz2L97hx5SqpUHoTKX9EkLwzAgwKbDS4dqyGW+cANDqbMrtu4vUoLv57mIv/HibixL9kZ2Tk2e/g4kq1ug0IqN+IgPoN8akWWO4SWiHKiiRnQghRBlR2Ntdeeonk334HjYbKb7yO52OPWTqsPDLPJJD4yzkMcTlNhva1PPDoXxOdT+lPMZGdmUHEiaPmhOzGSWAB0Nijta1GvfYtadajLT4BQZKMiXuWJGdCCFHKTOnpXHluMmm7d4OtLf7vv4d7796WDsvMmPTfskvHcpddssOjbw0cG/qUaq1eSnws5w/9xbmD+4g4cQyT0WDep7WxoUqtOlQKrs+pA3YoVYkWvYJp3T+k1K4vhLWS5EwIIUqRMSmJiHHPkPHPP2gcHan2yce4tG9v6bAAUEYTqXuvkbzlMirbCFpwaVsVtwcDS23ZpbgrEZw7uI9zh/YTde5Mnn3ufpUJbtSM4MbNCKjfCKV0rHr3IJBJcENvWvWtUSoxCGHtJDkTQohSoo+OJmLU02SdPYvWzY2AL77AqVlTS4cFQOa5RBLXn8dwPR0Au8D/ll0q5nJIN1MmE5HnznDu0H7OHdxPwrUr/9up0eBfqw4172tNSIvWePlXNe8ymRQbPvuXlLhM3HwceHBEvTJbaUAIayPJmRBClILsy5e5PHIU+itXcpZj+uZbHGqHWjosDHEZJP4WTuaJOAC0Tra496yOU3O/EidDBr2eiBNHOXdwH+cPHSAtMcG8z8bWlsAGjal5XxtCWrS65Yz8f62/wOWweGx1WnqOa4SDs65EsQhREUlyJoQQdyjz9GkuP/00xphYdAEBBC78FruAAIvGZMoykrIzgpTdV3JGYWrBpbV/ThOmU/EToaz0NML/OcS5g/sJP3Ioz+hKO0cnajS7j5r3tSa4cXPsnZwKPdeFIzH8/fslADo9WQefaqW/aLoQ1kySMyGEuAPphw8TMe4ZTMnJ2IeGEvDN1+h8fS0WjzIp0v+NyVkL87+JZO1reuDRtwY6v+KtRlBYh35nTy9qtmhFzRatCWjQCBvboiV8CVFpbF0cBkCjB6pRu1Xl2xwhxL1HkjMhhCih1F27uPLsc6jMTBybNSNgwXxs3C23jmPmuUSSNoajv5IK/DeRbO8aONTzKtIoTKUUcVcuc+7gfs4f2k/U+bN59nv6V6PWfa2peV8bKofUKvZUF9mZBn7/8jj6TCNVarrT9pGaxTpeiHuFJGdCCFECSb9u4NpLL+Wsk9mhPdU+/hitY+nPD1YU2ddSSdp40Ty7v8bOBtcHAnBtVxWNrvAEypCdzZWTx7n479+cP/QXiddvmH9Mo6FKrdrUbNGamve1xsu/WoljVEqxY9kpEiLTcHK3o/voBtiU8TqdQlgrSc7u1JW/wVX6SwhxL0lYv42oT5eCUrh1bo3/8yPQxB6/63EYkk0kHzCQfsaUs0ELLvVtcG1hi41TFERF5TtGKUVCbDwXT53j4ulzRJy/iEH/v+ZKG1sbgmrVIKR+bULq1cbZ7b/7mzESIiLzna+ojh/K5tyhLLRa6DHAFufko5Bc4tMJUTIaLbjVsnQUt6VRSilLB2GNkpOTcXd3J+klV9zsZfi3EPcCpSD2hAuxx90A8KyZhl/zJO72akwG5UOKYSBpxu5ATl8vR+0fuNt+h602f0KWrLcnIs2dK+nuRKS7k6TPW8PnYptFsHMC1V3iCXZJwE5rKtV4Y/Q1+CnuPUzoaOe6kCbO60v1/EIUmc6J5Emnc76/k5Jwc3OzdEQFkpqzO+URCA5lt/6cEKJ8UEpx/U8jCcdzEhef5lp87vNAoyl4qoiyYDB6kpLajbT01uQmZfZ2p3F3/QU7u8uAAyYVTEKGLddS7LmSbE9Ekj0p2Xlv9TYaRVW3LII9MqnukYm3k/6/BNP1v5/Sk2V0YGP4FEzoCHY5RuOqx0ATXKrXEKLIbC3T9aC4JDm7U8/shXKaeQshSofS64l87TWSjq0DwO+Vl/EaNuyuXd+QkEnKzgjSDl0HY05jh30Nd1y7BJDlGkr4+TpEnT9D1PkzXL9wHn1m3kXENVotlWvUolq9Bjk/dRtg51D2X1JKKXZ8fYJkfTSuXg50eXU8Gufnyvy6QhQqufy3p0tyJoQQhTBlZnL1/6aQumMH2Njg/+5M3Pv3vyvXzr6WSuruq6T/GwOmnKQs20NPpOMlLkeEEfv2JbIz0vMdZ2tvT+Uatahapz7V6jXAP7TOXUnGbnb8j6ucPxyN1kZDt9H1ZaJZIYpIkjMhhLgFY0oKV54ZT/qhQ2js7an64Ye4PtC5TK6llCI9KZGEqEjSjkehPW3AMeV/CVVUxkVOJPxJbPiVPMdpbWyoFFSdyiG18AupRZWQULyqBaDVWra7RfSlZPb8lDMVR9uHa1K5uuWmGBHC2khyJoQQBTDExXF59Giywk6idXEhYMF8nO67r8Tny85IJyUujpT4WFLiYkg1/z+W1LhYUmLiqGIbTG23+/Cw9wV0mJSJiLRTnE46SIL+Oh6+lQkJaI1PQBA+AYH4BATh6V+1yBPA3i1ZGQY2fX0ck0FRvbEPjR4o+RQcQtyLJDkTQoibZEdEcPnpp9FfuoyNlxeB33yNQ716+copk4mM1BTSEhNIT0wkPSmBtKTEnMf//ZsaH0dqfBxZ6WkFXsvZ1p0Q16bU8O2HvU3OskdGDCS6JWAIgUrBDajl1xXPyv7oHBzK9HmXBqUUO747SXJsJq5eDjwwrG6RJsAVQvyPJGdCCAGYTEay0tJIOnKES2+8QWZqCqYaATg//hixJ/4h88BuMlNTSE9OIj0pMecnOQllKvq0E/ZOzrh4eePqXYkqjtWplOGPQ7IDGnKSF627HS5t/HFpWZmgEqx/WR7k9DOLQWujofvoBtLPTIgSkORMCGEVlFKYjAYM2XqM+mwM+uw8/zdm63O26XO26TMzyc7MIDsjw/yv/obH+hu2Z2ek563Z8nXJ+QFYv/q2sTm4uuHs7oGTuwfOHp445f7f3QMXbx9cvXxw9fZGm2VD+t/XSTsYhfF6lvl4+1BPXFpXwaGOFxqt9dYy3dzPzK+6jGQXoiQkOROinDAaDKQnJ5KdnkF2Zvp/yUUmRn02JqMRk9GIMpkwmf771/zYhFIKledfE8qkUEqBun0ZZTL+969CKRMolXNMbvncMrnllemmcxVwztwy/53TXObmc95w3VuVMeoNGPTZObPAljFbowk7G1ucAwNxdPfAwcUVRxcXHFxccXB2yZeIObq5Y2N761up0pvICIsladN5ss4lwn9PQeNoi3MLP1xaVcHWxzrmXipMVrpe+pkJUUokORPiLlJKkXQ9iuvh54m7com4iMskRkeRGh9HenLSXUk+KgpbnR02drqcf3U6bHR22Op05u06O3t0jk7YOThi5+iInYMDOgdH7Byd/nucs13n4EDGtu0kf/o5OoMR965d8Z87B629fYljU0qhv5pK2qHrpB+JQWX+b3kku+ruOLfww6mRDxpdxZjAOqef2amcfmbe0s9MiDslyZkQZSwjJZlzh/Zz6egRrp48TmpC/C3LarRa7J2c0Tk45CQPDo7Y2OnQam3Q2uT8aLRatNqcf3P+n/OvRqNFo9Wg0Whueqz93zbtf//XaNBobf5XXnPDvtuVKfScNz7+r2xuLPm23aJMAefITcBs7eyw0dlhY2tbKl/+SiliP/2UrPkLsAc8Bg+m8huvo7EpWdJkiMsg/WgM6UdiMFz/3/xjNu72ODX3xbm5H7be1l9LdrNjO69y/h/pZyZEaZHkTIgyoM/K5PTe3Zzcs5OIsGN5Oo3b2NpSKbgGPgFBeFcLxLNKVVy9fXDx9MLR1Q2NVmvByO8dymAgasbbJK5aBYDPxIn4TBhf7KTPmJxN+tEYMv6NITsi5X87bDU41vfBuYUf9iEeVt2XrDDRl5L5c/V//cweqYlfsPQzE+JOSXImRClKio7in43rOb5zK1lp/+tgXim4BjVbtCKgXkMq16qNzq7kTWbizpkyM7k6bRqpW7eBRkPl6W/gOWRIkY83pmaTERZHxpEYssKTzP3I0IB9iAdOjSvh2MAHrWPFvsXe2M+sRpNKNOos/cyEKA0V+84hxF2SeD2KA2tXEbZrGyajEQB3Xz8aPtCd2m3a41G5ioUjFLmMyclEjB9PxqG/0eh0+M+di1v3brc9zhCXkZOQnYgj+1Ly/xIywC7QNScha1QJG1e7Moy+/FBKsf2/fmZuPg48MKyO9DMTopRIcibEHchITWHvqmUc3brRnJQFNWpKs179CG7czOJL6Ii89NejiRg9mqwzZ9C6uFDt889xbtWywLLKpNBfSyXjZDyZJ+LQR+WdRFZX1QXHBj44Na6ErVf5nxy2tB3beYULN/Qzs7fSedmEKI8kOROiBEwmI8e2bWLPiu/ITM3pZxTcuBltBj6Gf2hdC0cnCpJ1IZyIp59Gf+0aNpV8CPz6a/6/vfuOb6peHzj+ye7eeyJljwJFEERAHCCITPe9CCpXEBUR0YvX30X0Oq4LNwqCol4HLlCGAiIIMgTZe2MnLd1t2sxzfn8Eq8hqS9Ok7fN+vfJKcnLOyZNv0+TJd/q0aXPaPs4yG5aDRVgOFmE9XIRi/mOUJVowNQvGt304Pu3D0Yc0vYTsd7nHS1n35WHA1c8sKln6mQlRlyQ5E6KGCjIz+P7tVzhx+CAAEYnJ9BszjqQOqR6OTJxL5fbtZNw7AWdREcbkZBLnzsGYkIDTbMd2vBTr8RKsh4ux55xeO6Yx6TC1CMG3XTg+bcLQySjEP/qZOVWad5F+ZkK4gyRnQlSTojjZsuQb1s3/CKfdjsnPn163/J1O1w5CW8upF4T7la1cSdbDU1AtFnw69SBi4r8x/2qh8Istp0138TtDfAA+rULxaRWKMSkQjU5Gz/5OVVV+/HA/ZQWn+pmNkn5mQriDJGdCVENZQT5LXn+BrP17Abikc1euHfcAgWERHo5MnI2qqiilNgo+WULZ8k34dLkHXWQLNFofShZlnbavPtIX0yXBrkvLEHQBTaNDf23s/DGTo9tPotVLPzMh3EmSMyEu4Nj2LXz35stUlpVi9PXlyjv+QYd+10qNgRdQVRWlzIY9twJ7XgWOvArsua5rpcIBRGJqff0fB2g1GGL9MTULwnRJMMZmQZKMVVPusVLWf+3qZ9ZrZEvpZyaEG0lyJsQ5KIqTDV98wsYFn4OqEtUshRsemirTYtQjVVVRKx04S204Ci04iiw4Cy04Ci04iyw4Cq2oNufZj1WcKGXZGOL8Cby6G6bEQAwx/mgM0kxZUxaznWVzXP3MUtIi6XhlvKdDEqJRk+RMiLOwVphZ/NoLHN++BYBO1w7iyjvGojdKLcvFUBUVpdKBWulA+eul3Iaz3I6z1IZSZsNZZsNZbgPHBdYb1YA+3Bd9lB+6EB1lSz6ncvtalMp8Yqf/m5ARQ+vnxTVSrn5m+6r6mfUbJetmCuFukpwJ8RfFuSdY+MJTFGSmozea6D/uAdpecaVHY1IV1bUouuL6sqy6/ft2FVBU12PKn27/vl35yz6nbf/zY67rM/b703bUUzEoKqpNQbU7UWwKqs2Jaj/9Wvn9vtXpSsqsZ6/luhCNrx59mA/6UBO6MB/0oT5V1/pQHzQGLfacHDLuGYf10CG0fn4kznyDgCt61c0foAnb+WMmx3bk/9HPrJGveiCEN5D/MiH+JHPfbr59+Vkqy0oJCA1j2KPTiG7eolrHKjYnjgKLq9an1FXro5TZUMz2P5IXmxPF6kpeOJUYqcqphEpVUZ2/b+NU0nTqsUZGY9Sh9dWj9dWjOXWt8zegDTSgCzSiCzSiDTKiC3DdvlBTpOXAATLuGYcjNxd9ZCSJs2fh01bmm7tYf+5ndsWN0s9MiPoiyZkQp+xfv4bv3pyB4nQQ3bwlwx75PwLCws/YT6mwY8s2Y88pd3U+L7DgKKhEKbV5IOpTNIBGA1pcTU5aDWg0aLRn2w5oNafuc2q/v27XVJ1To+VP5/vTdp0GjUHruhh1Vdfa3+8btWgMp67/lIxpffV1Oj2FecMGMh+YiFJejjElhaTZszDES5+oi2Ux/zGfWUpaFB36SpkKUV8kORMC2L5sCSvffwdUlVaX9eK6+x7CYPJBtTuxppdhO16KLbsce3Y5ziLrOc+j9dOjCzJV1QBpA43o/A1oTDq0Rp0raTGdSlq0fyRBVbe1GjSnkqSq25q/bD8t6Tp1fBPtA1Ty7bdkP/5/YLfjd+mlJLz1JrrgYE+H1eCpisrKeXspK7QQFOlLP5nPTIh6JcmZaNJUVWXDl5+w4ctPAehy7Q30uGIkFatOYD1Wgi2zDJxndkjXhZowxgWgj/HHEOGLPsIXfbgPWpn3qV6oqkrB7Hc5+corAAQOvI64//4Xrcnk4cgahy3fH+f4rgJ0Bi3XST8zIeqd/MeJJktRnKyeM5fcDXvpHNaPZrGdMR0xUnh432n7aYOMrjmxEgIwxAVgjPWXJMyDVIeDE08/TfFn8wEIu/NOoh6ZgkYrU2TUhfQ9Bfyy6BgAfW9rTWRSoIcjEqLpkeRMNCnOMhvWYyVYjhZTsOUorextaRV9quP4qZV8dGE+p2aMd01UqgvzkSYdL6FUVpI1+WHKV60CjYbox6YSdscdng6r0SjNr2T5e3tAhXa942h7uczpJ4QnSHImGiVVVVHMdhwFFuzZ5djSy7Cll+IosFTt44sfAEqASmD72FMzxgejD5GmMW/kOHmSjHsnYNm9G43JRNwLLxA0oL+nw2o0HHYn38/ejdXsICo5kD43t/J0SEI0WZKciQZLVVWcRVbsuWbXrPFFVtcM8gWuGeTPOnO8Bip0ZjIL9pFvy6Lz6GG06tO7/oMXNWI9dIj0ceNwZOegCwkhYeZb+KWleTqsRmXtZwc5mV6Gj7+B68Z1RCcrKQjhMZKciQZFqbBTubeQyr0F2I6XnFo/8Rw0oAs2oY/yw5QUiD7en9VL32ffpp/Q6vQMfuiftOzWs/6CF7ViXr+ezIkPuqbKSE4mcdY7GJs183RYjcren7PZuy4HjQb6j21PYJiPp0MSokmT5Ew0CI5CC2U/ZWDekgeOP83KqtNgiPL702zxJnThrpGT+lAfNHrXr3/F6WTxa89zaNN6dHo9N0x+jJSul3no1YjqKv7qK3KemA4OB75du5Lw5hvoQ0M9HVajkn24mJ8+PQBA9yHNSWwb5uGIhBCSnAmvpjoVylZlULo6syop00f74dcxAp/WYRhi/asSsHOeQ1H4/u1XOfSLKzEbMuVxmnfpVh/hi1pSFYWTr71OwaxZAARdfz2xzz4jU2XUsdKCSr6ftatqotmu1yV7OiQhBJKcCS/mLLFS8Ml+bL+VAmBqHkzQNckYLwmq9uhJVVVZ+d7b7Fu7Cq1Oxw2TH5PEzMspVis5j/2L0qVLAQi/dzyREyfKiNk6Zrc6Wfr2LirL7EQkBnD1aFnQXAhvIcmZ8Er2kxXkv7sLZ6kNjUlH6PAW+HaKrNGXh6qqrPn4fXas+A40GgbeN1maMr2co6iIzPvup3LrVtDriX3ySUJGjvB0WI3O7ysAFGSW4xtoYNC9qRhMOk+HJYQ4RZIz4XXseRWcnL0TpdyOPsqXiDvao4/wrfF5flnwOb8u+hqAa/9xP2169a3rUEUdsh0/Tvq4cdh/S0cbGEjCG6/j36OHp8NqlDYvOcaRbSfR6jQMHNdRBgAI4WUkORNexVlmI/+93Sjldgyx/kTc3QFdgLHG59m9+gfWzf8IgCvvGEvq1QPqOlRRhyp+/ZXM++7HWVKCIT6exFnvYGrRwtNhNUqHNueyeclxAPre3prYFiEejUcIcSaZyEZ4DdXuJP+DPTiLregjfIkY27FWidlvO7ezYvYbAHQfdhNdrx9Wx5GKulSyaDHpd96Fs6QEn9RUms3/TBIzN8k6WMQPH+wFoNPVibTrFefhiIQQZyM1Z8JrFC85hj2zHK2fnogx7dH513z9ypO/HePbGc+gOJ206dWXK26VpX28laqqFLzzDidfex2AwGuvJe6F59H61rwJW1xYYbaZ797ZheJQad4lkstHSgIshLeS5Ex4hcrd+Zg35gAQdmubWvUxKy8q5Ovnn8RWWUlCuw4MuHeSjD7zUqrNRs4T0ylZsACAsLvuImrKw7J4uZuYS6wsenM71goHMc2DufbOdmi18r8hhLdqEp+Ew4cPJzQ0lBtvvPGMxxYvXkzr1q1p2bIlc+bM8UB0wllmo/CrQwAE9E3Ap1XNJxl1OuwsmvEc5QX5hMUlMPTh/0NvqHnNm3A/Z2kp6feMcyVmWi0xT0wj+tFHJDFzE5vFweI3d1BeaCU4ypdBEzqiN8rITCG8WZP4NJw4cSIffvjhGdsdDgeTJ0/mxx9/ZOvWrTz//PMUFhZ6IMKmrXjREdRKB4b4AIL7124SzFXz3iX74D5Mfv4M++c0fAIC6jhKURdsmZkcv+12KjZuROvnR+I7bxN6222eDqvRstucLHlrJ/kZrikzbnigE7616McphKhfTSI569evH4GBgWds37RpE+3btyc+Pp7AwEAGDRrEsmXLPBBh01W5v5DKnfmghdARLdHoav6W3PXjcnasWAoaDYMemEJojHRy9kaVO3Zw/JZbsR05gj46muRPPiagTx9Ph9VoOR0K38/aTfahYgw+Ogbf34ngSD9PhyVEvbIrdoosRWSUZrCnYA/b8rZ5OqRq8XifszVr1vDiiy+yZcsWcnJyWLBgAcOGDTttn5kzZ/Liiy+Sk5ND+/btefXVV+ndu/dFP3d2djbx8fFV9xMSEsjKyrro84rqUWxOihceBiDginiM8TWv7co9epiVc2cC0Oumv9E8TWb/90aly5eT/cijqFYrprZtSXznbQzR0Z4Oq9FSnAor5u4hfU8BeoOWwfd3Iio5yNNhCVErDsVBibWEEmsJxdZiiq3FVbdLrCWU28sptZVSZiuj3FZOma3MdbGXUemoPO1cgYZAvh/8vYdeSfV5PDkzm8106tSJO++8k5EjR57x+Pz585k0aRIzZ86kV69ezJo1i4EDB7J3716SkpIA6Nq1K1ar9Yxjly9fTlzcuWtRVFU9Y9u5OpBbrdbTnqO0tPSCr02cX/m6LJzFVnShJoKuqXlzpq2ygsWvPY/T4SDl0su4bPjNbohSXAxVVSl8fx55L74Iqop/3z7EvzwDXYC/p0NrtBRF5ccP97smmdVrGHRvKnEyl5nwQlanlezybPIq8siryONk5UlOVpysup1fmU+xpZgye9lFP5ev3pdAYyBBxqCzfvd7G48nZwMHDmTgwIHnfHzGjBncfffdjB07FoBXX32VZcuW8fbbb/Pcc88BsGXLllo9d3x8/Gk1ZZmZmVx22dmX93nuued48skna/U84kxKhZ2ynzIBCB7QDG0tOij/+P4sik/kEBAe4RqZKR3KvYrqcHDimWco/vQzAEJvv53ofz2GRu/xj51GS3Eq/DBvH4c256LRahgwtgOJ7cI8HZZowhyKg99Kf+NQ8SHSS9PJLMskoyyDjLIM8iryUKl+ohRoDCTEFEKIKYRgU3DVdZAxiABDQFXyFWB03Q40BBJoDMTf6I9B+8cAsYZQueLVn5I2m40tW7YwderU07b379+f9evXX/T5u3fvzu7du8nKyiIoKIilS5cybdq0s+772GOPMXny5Kr7paWlJCYmXnQMTVXZT5moFieGGH98UyNrfPy+dT+x56eVaDRarr9/Cr4BZ/YpFJ7jLDeTNfkhzGvWgkZD1D8fJWz0aJnaxI2cDoXlc/dwdNtJtFoN197dnuada/6/JURtVdgr2FOwh935uzlYdJBDRYc4WnIUu2I/5zF+ej9i/GOI9Isk0jeSSL9IonyjiPSLJMI3glBTKCE+IQQZg9BrvTplqVNe/Urz8/NxOp1E/6VvSnR0NCdOnKj2eQYMGMDWrVsxm80kJCSwYMECunXrhl6v5+WXX6Zfv34oisKjjz5KeHj4Wc9hMpkwmUwX9XqEi7PUStm6bACCBiSjqeF8SyV5J/jh3bcAuGzELSS061DnMYras584Qcb4e7Hu34/Gx4e4F18g6NprPR1Wo+awO/l+9m5+21WAVq/huns6cklqhKfDEo1crjmXTSc2sePkDnae3MnBooM4VecZ+/np/WgR0oJmwc1ICEwgMTCx6hJqCpUfbWfh1cnZ7/76h1NVtUZ/zPONwBwyZAhDhgypdWyi5kpXpoNDwZgchE+bmjW5qIrCsrdfw1ZZQVyrtvQceaubohS1Ydm3j4xx43Hk5aELDyfx7Zn4pqZ6OqxGzVJuZ+nbO8k5UoLeoGXgvR1Janf2H5lCXAyz3cymnE1szNnIxpyNHC05esY+Ub5RpEam0iasDS1DW9IytCXxAfFoNdLtpCa8OjmLiIhAp9OdUUuWl5d3Rm2aaBgc+ZWYN+cCEHxdsxr/Ytrxw/dk7N2F3mhi4H2T0epkMk1vUf7TT2Q+NBm1ogJjixQS35mFMSH+wgeKWis5WcniN3dQnFuB0VfP9RM6Etey5pM4C3Eu+ZX5rMpYxcr0lfyS8wsOxVH1mFajpV1YO9Ki00iNTKVTZCdi/GM8GG3j4dXJmdFopGvXrqxYsYLhw4dXbV+xYgVDhw71YGSitkpW/AaKik/rUEyXBNfs2Lxc1vzvPQB63z6akJhYd4QoaqHwk0/IffoZUBT8evYg4bXX0AXJ1A3udOJYCUtn7qSyzE5AmInB93ciPE4mXxYXr6CygO+Pf8/3x75nx8kdp3XaTwpMomdcT3rE9qBbTDeCTTX7HBfV4/HkrLy8nMOHD1fdP3bsGNu3bycsLIykpCQmT57MqFGjuPTSS+nZsyezZ88mPT2d8ePHezBqURu27HIqd5wEIKh/sxodq6oqy2e9jt1qIb5Ne7oMGOyGCEVNqU4neS+8SOEHHwAQPGIEsdOfQGOUWejdRVVV9v6czZr5B1EcKhGJAQy+rxP+IdInVtSe1WlldcZqFh1ZxLqsdTjUP2rIOkZ05Kqkq7gq6SqaBzf3XJBNiMeTs19//ZV+/fpV3f99ROTo0aOZN28et9xyCwUFBTz11FPk5OTQoUMHli5dSnJy7Zb5EZ5Tuvw3AHw7RdZ4wtldK5eRvnsHeqOJAeMnyrQZXkCpqCBryiOU//gjAJEPPUT4Pf+Qzr1u5LA7WfPpQfatzwGgeedIrh7TFqOPxz/KRQN1tOQonx/4nG8Pf3vafGIdwjswOGUwVyddLU2VHqBRG8JsbF6otLSU4OBgSkpKCJLmmwuyHi/h5Ds7QQvRky/FEOFb7WPNxUW8/9B4rBVmrrxjLF2vH+a+QEW12HPzyLz3Xix796IxGon773MEDRrk6bAatcJsMyve30N+RjkaDfQYlkKX/kmSDIsacygOVmes5rP9n/HLiV+qtsf6xzK4+WAGpwxu1DVkDeH7W35uCbdTVZWS748D4H9pTI0SM4DVH87BWmEmunkLugy8wQ0RipqwHDhAxvh7ceTkoAsNJeGtt/BL6+LpsBotVVHZuTqTDQuO4LQr+Pgb6D+2PYltZXJZUTNmu5kvD37JR3s/IrfCNTBLq9HSN6Evt7a+lR5xPWRUpZeQ5Ey4neVAEbbjpaDXEnR1Uo2O/W3Xdvav+wk0Gq4Zex9arYzO9KTytWvJmvQQitmMsXlzEme9g1EmY3ab4twKVn9ygKwDRQAktQ/jqjva4h8s/ctE9RVUFvDxvo/57MBnlNlcTZdhPmGMbDmSm1rdRGyADK7yNpKcCbdSFZXSZccBCLg8Dl0NvlQcdjsr574NQOf+g4hJaemOEEU1FX32GSf+8zQ4nfhddhkJr7+GLlhGarmDw+5ky/e/sXXZbygOFb1By+UjW9Chb7w0Y4pqyzXnMnf3XL4+9DVWp2tt6GZBzRjTfgw3pNyAUScDd7yVJGfCrSp3nsSeY0Zj0hHYN6FGx/767VcU5WThFxxCr1tGuSlCcSGq00neSy9T+P77AAQPH07sk9NlRKYbqIrKwc25bFp0lNJ8C+CqLetzayuCI/08HJ1oKAoqC5i7ey7z98/HptgA14jLuzrcRb/EfuikBcLrSXIm3EZ1Kq55zYDAvgno/A0XOOIPxbkn+GXB5wBcecdYfPxl/iZPUCoqyHr0Ucp/WAlA5KQHCR83Tmpv6piqqvy2u4CN3xylILMcAP9gI1fc3IqUtEgpb1EtJdYS5u2Zx8f7PqbSUQlAWlQaEzpPoHtMd3kfNSCSnAm3Mf+ai7PAgjbAQECvms0Uv2reLBx2G0kdOtGmV183RSjOx3HyJBn3TsCyezcag4HY554jePD1ng6rUXE6FA79msv2FekUZJkBMPro6DIgmU5XJWIwSQ2HuDCr08rH+z5mzs45VdNhtA9vzwNdHuDyuMslKWuAJDkTbqHYnJT+kA5AUL9EtDX4kjm2fQtHt25Gq9Nx1V3j5YPFAywHD5IxfjyO7Bx0ISEkzHwLv7Q0T4fVaJScrGT/hhz2rc/BXOzqC6Q36ejQJ56uA5LxCah+LbNoulRVZdnxZby69VWyyrMAaBXaivs738+ViVfKZ2cDJsmZcIvy9dkoZTZ0ISb8L6v+SCCnw8HqD94FoMt1gwmPl5GA9a3853VkTZqEUl6OsVkz14hMmfT5olWW2zi2I5+Dm3KrRl8C+AUZSb0qgfa94/GpQdO/aNp2nNzBi5tfZMfJHQBE+UXxYNqDDG4+WKbDaAQkORN1TqmwU7Y6A4CgAc3Q6Kv/QbFjxVIKszPxDQyix8jb3BWiOIei+Z9z4qmnXCMyL72UhDffQBcS4umwGiRVVSnMMZO5r4hjO06SfaiYqim/NZDYNoy2l8fSvFMkOoN8mYrqyavI46VfX+K7Y98B4Kv35c4OdzK63Wj8DDJopLGQ5EzUudLVGagWJ4ZYf/w6RVb7uMqyUjZ88QkAvW4ZJYMA6pGqKOS9/DKFc10LywcPHULMf/6DVkZkVpvTrlCQXU7e8VKyDhaTdbCIyjL7aftEJAaQ0iWSVpfFEBRes8mYRdPmUBx8su8TZu6YidluRoOGoS2G8kCXB4jyi/J0eKKOSXIm6pSj2EL5+mwAgq5rhkZb/T4P67/4GIu5nMikZnS8ur+7QhR/oVRWkv3PqZQtXw5AxAP3EzFhgvRXOQdFUSkrsFCcW0FxbgWFOWZOppdRkFWO4jx9NTy9QUtsi2CS2ofTvHMkQTVcHUMIgG1523h649McLDoIQGpEKv/q8S/ah7f3cGTCXSQ5E3WqdEU6OFRMzYPxaRVa7ePy04+zY7mrmv7K0ffISgD1xJGfT8aE+7Ds3OkakfnsMwTf0HSXyFKcCtYKBxWlNsqLrZiLrZQXua7NxVZK8yspya9EcZx9SWKTv56opEBiW4QQ3yqU6GZB0mQpaq3QUsgrW15h4eGFAASbgpmUNokRLUdIv7JGTpIzUWfsJ8xUbHWt1xY88JJq17yoqsqqD+egqgotuvUkqUOqO8MUp1gPHybjnnHYs7PRBQeT8Nab+F16qafDuiBVVVGcKk6HguJUT10UnA7Xtd3qxGFzYrf++bYTu82Jw+rEbnNtt1bYsZTbsVY4sJjtWM12bBZntWLQ6bUER/kSGu1HSLQfkUmBRCYFEhjuIzWO4qKpqsrCwwt56deXKLWVAjCy5UgeTHuQUJ/q/+gVDZckZ6LOlHx3DFTw7RiBMTGw2scd2bKJ9F3b0en19B11txsjFL8rX7eOX5/6kGL/3tA1mIBeV5C51x91z15QQQXXtaq6OrGfuv7j/h+3VVU9976K6/n+uH3qMUWt6hx/tscU5VTS5VBQFNWVeP2ejClnr7WqSz7+BvxDTPiHmAgIMbquQ30ICDMREuVHYJhPjZrshaiunPIcpm+Yzvrs9QC0CWvD45c9Tueozp4NTNQrSc5Enag8UIjlQBFoNQT1r/60C06HgzX/c3VC73r9MEKiY9wVojil+Msv+eXdNRy+5JY/Nu4sA8o8FtPF0uo0aPVadDoNeqMOg0mH3qjFYNJhMOrQn3atRW/S4eNnwMdfj8nfgM+pi8lfj8nPgFYSL1HPVFXly0Nf8vKvL2O2mzHpTNzf+X7+3u7v6LXyVd3UyF9cXDTVoVCy+CgAAb3iMNRgDcDdq1ZQlJOFb2AQ3Yfd7K4QBa4P/5OvvkbOe59wtMdTALTqHkVoTABoQKPhjyY5DWjQoNGe2nbqMc2p/ai6/afHtKDh1GPaP871x2On9tW6joU/bmvQwKljNIBGp0Gn055Kuv50W6dFp9dUJWNanQatViNNiaJByyrPYvr66WzM2QhAl6guPHX5UzQLbubZwITHSHImLlr5hhwcJyvR+hsIujqp2sfZLRY2fOmaOqPHyFsx+ckcPe6i2GzkPP5/lC5aRGaz61F0RqKaBXLNne0lsRHCQxRV4YsDXzBjywwqHBX46HyYmDaR29vcLouTN3GSnImL4iy3UbrStbh58IBmaH2q/5basmQh5uIigqNj6HTtQHeF2OQ5S0rIfGAiFZs24TT6ktPyOrBD52uSJDETwkMyyjKYvn46m05sAlwLlP+n139ICqr+D1zReElyJi5K6fLfXBPOxvnjd2l0tY+rKC1h86KvALjillHo9LJsjTvYs7JIHzcO2+EjaP39qbx/BtZfHASEmUjpUv0JgoUQdUNRFT7b/xmvbn2VSkclvnpfHkx7kNva3CbTY4gqkpyJWrNll2PefAKAkBtSajR6bePXn2GrrCS6eQta9+ztrhCbtMo9e8gYPx7nyXz00dEkvPM2Cz4vBRx0uioRrU6+CISoT+ml6UxbP40tuVsA6BbTjScvf5LEQFlDWJxOkjNRK6qiUrzgsGvqjNQITJcEV/vY4twTVRPO9r59DBqtJAl1rXzNGjInPYRaUYGpVSsSZ88ip8BAUU4OBpOOtr3iPB2iEE2Goip8su8TXtv6GhanBV+9L5O7Tubm1jdLbZk4K0nORK2YN5/AllGGxqQj5PrmNTp23fyPUJwOklO7kNyxs3sCbML+vHi5/+U9iX/tNXSBgWz/fDsA7XrFYfKVf30h6sPxkuNMWz+NbXnbALgs5jKmXz6dhMAED0cmvJl8Qosac5bZKPnuOABB/ZPRBZuqfWzu0cPsX/cTAH3+dqc7wmuyfp8qo2DWLACChw0j9qkn0RiNFGSVk7G3EI0GUq+SLwUh3M2pOPnfvv/xxrY3sDqt+On9mNJtCje2vFEG4ogLkuRM1FjJkqOoFgeG+AACetaseWzNJ/MAaHvFlUQ1q1mNmzg3xWYj51+PU7p4MQAR991HxP33VX0J7PgxA0AW3xaiHhwtOcq/1/2bnSd3AtAztifTL59OXIB0JxDVI8mZqBHLoSIqtp8EDYQOb1GjQQDHd26rWqap1y2j3Bhl0/LnqTLQ64l98klCRo6oeryi1MbBX1xrnna6WjoeC+EuDsXBh3s/5K1tb2FTbPgb/Hnk0kcY0XKE1JaJGpHkTFSbalco/uYIAP49YjEmVH/9TFVRWPvxPAA69b+e4KjqT7shzs2enU36PfdUTZUR/9prBFzR67R9dq/JwulQiGoWRExK9QduCCGq70jxEf697t/syt8FQK/4XkzvOZ0Yf1mSTtScJGei2kpXZ+DIr0QbaCR4QLMaHbt//Rryjh/B6OvHZcNlmaa6YDlwkIx//ANHXh766GgSZ72DT5s2p+3jsDvZ/VMmAJ2vTpRf70LUMYfiYN6eeczcPhO7YifQEMij3R9laMpQ+X8TtSbJmagWW46ZstWufkshNzSv0UoADrudnz/7CIDuQ2/EL0hqby5WxebNZEy4D6WsDGOLFJLefRdDbOwZ+x3anEtlmZ2AUBPN02TSWSHq0qGiQ/x73b/ZU7AHgD4JfZjWYxrR/tIyIC6OJGfiglSnQtGXB8Gp4tMuHN+OETU6fueKpZSezMU/NIy0QUPcFGXTUbpiBdkPT0G12fBNSyNx5lvoQkLO2E9RVLYtTwegY78EdDLprBB1wq7YeW/Xe7yz8x0cioNAYyBTu0/lhuY3SG2ZqBOSnIkLKludiT2rHI2v3jUIoAYfPtYKMxu+ng/A5TfdjsHk464wm4Sizz7jxFP/AUUh4KqriJ/xMlqfs5fpka15FJ2owOSnp33v+HqOVIjGaW/BXqatm8aBogMAXJl4JdN6TCPST2qmRd2R5Eycl/2EmdIfXbUvoUNS0AUaa3T85m+/xlJWSlhcAh2uvNYdITYJqqqS/8ab5M+cCUDITTcR88Q0NPqz/wsrisrmJccB1whNmXRWiItjdVp5Z8c7vL/7fZyqkxBTCFO7T2XQJYOktkzUOfnEFuekOhUKvzjVnNk2DN/ONftlWF5YwJYlCwHXMk1anc4NUTZ+qsPBiaf+Q/HnnwMQMWECEQ/cf94vhL0/Z1OUY8bkpyf1Kpk+Q4iLsT1vO9PWT+NYyTEABjQbwGPdHyPcN9zDkYnGSpIzcU5la/7cnNmyxr8ON3z5KQ6blbhWbUm59DI3Rdm4KRYLWQ9PoXzlStBoiHliGqG33nreY8wlVjYudE150v2GS6TWTIhaqnRU8sa2N/jf3v+hohLuE86/e/ybq5Ov9nRoopGTT21xVvYTZkp/cDVnhgxJQRdUs+bMgqwMdq1aDriWaZJq/5pzlpSQce8EKrduRWM0EvfSiwT173/eYxx2J8vn7MFa4SAiMYAOfaSvmRC1sSlnE9M3TCejzDVKfUjKEB7t9ijBJhltLtxPkjNxBtWpntac6VfD5kyAnz/9EFVRSLm0B/Ft2rkhysbD6VAoyaukotSKqp7aVlxM3oxXsGVWoom/lPAJE8iPasHJrXkoigqqq1+ZqqqoioqquBKzAxtPkPdbGQaTjv53t0crIzSFqJFCSyEvbX6JRUcXARDtF80TPZ+gd0JvD0cmmhJJzsQZqpozfWo+OhMg68A+Dm/egEajpfdto90UZcNmq3RweEsex3bmk3mgCIfVeeZO4cPh9y4tKyphxa5qndvgo+P6e1MJjfGvu4CFaOQUVWHh4YW8/OvLlNpK0aDh5tY3MyltEgHGAE+HJ5oYSc7Eaey5Zkp/+A1wTTarCzLV6HhVVVn7yfsAdOh3DeEJ0hn9z/Izy9ixMoPDW/Jw2JSq7QYfHQEhJnDYsWdmgsMOBgPGxER0PiY0GtBoNWi1GjRaDRotaDR/vu+6HRbnT/vecQSEypQlQlTX4aLD/Gfjf9iatxWA1qGtmdZzGqmRqR6OTDRVkpyJKqc1Z7YJwy8tqsbnOLJlE1n796I3muh50+1uiLJhOplexuYlxzi2I79qW2iMH626x5DcIZyIhAAs+/aSMfYfOIuKMKakkPTeXAzRMtO4EO5SYa/g3V3vMm/3PByqA1+9L/d1vo+/tf0beq18PQrPkXefqFK2NhN75qnmzBE1b85UnE7WfjIPgLRBQwgMq9lKAo1RRamNjd8cYd+6HNcGDbToGkVqv0RimgdVlXHF5s1k3DsBpbwcnw4dSHx3NvrQUA9GLkTjpaoqS48tZcaWGeRV5AHQL7Efj3V/jNiAM5dBE6K+SXImgFPNmStq35wJsHv1DxRmZeATGET3oTfWdYgNiqqq7FmbzYYFR7BVOgBo2S2abtc3O6MvWPlPP5E58UFUqxW/bt1IeHsmugDp4yKEO+wp2MPzm55nW942AOID4nmk2yNcnSTTYwjvIcmZqJPmTLvFwvovPgag54hbMPk13c7o5mIrP364j/S9hQBEJAbQ59bWxKacOQS/9LvvyHrkUXA4CLjySuJffeWcyzEJIWqvoLKA17e9zoJDC1BR8dX7MrbjWEa3H41JV/Mfo0K4kyRn4k/Nmbpajc4E2LL0G8xFhQRHRZN67SA3RNkwHN6Sx+qP92OtcKAzaOk5LIWO/RLQas8s05JFi8j+51RQFIIGDybuuWfRGAweiFqIxqvCXsFHez/i/T3vY7abARh0ySAe6voQMf4xHo5OiLOT5KyJO605c3AKuuCa/4KsKC1h87dfAtDr1jvQN8EEw+lU2PD1EXasdE1YGZkUyDV3tiMs9uw1iMULFpLzr3+BqhI8cgSxTz2FRpa3EqLO2BU7Xx38ind2vEOBpQCAduHtmNp9Kl2iung4OiHOT5KzJkx1qhR+ecjVnNk6FL+uNW/OBNj41WfYKiuJbt6CNj2b3kSNFaU2lr27m+xDxQB06Z/EZUObozvHBLDFX35Jzr+ngaoScsstrgXMtTJZrBB1QVEVlh1fxhvb3qia3T8hIIEHujzAdZdch1Yj/2vC+0ly1oSV/5yJPaMMjY+OkBE1XzsToOhENjtWLAVOLdPUxJKMvN9KWTpzJ+YSGwaTjqvHtCWly7mT3KLPPuPE9CcBCP3b34j+v8dlaSsh6oBDcbD8+HLm7p7LwaKDAIT5hDG+03hubHkjBl3Tq9EXDZckZ02UPa+CkqrmzOboa9GcCfDzZx+hOJ0069yVpA6d6jJEr3dsZz7L5+zGYVMIjfFj4PiO552Vv/B/H5P79NMAhI0eTdTUf0piJsRFsjqtfHP4G97f/T6Z5ZkA+Bv8GdN+DHe0uwM/g5+HIxSi5iQ5a4JURaXoi4PgUDG1CsWva+0mOs05fICDG9aCRkOf28fUbZBebueqTH7+/CCqContwrjuHx0w+p7736lg3jzy/vs8AOFj7yby4YclMRPiIpjtZj4/8Dkf7v2Q/ErX5M4hphD+3vbv3NrmVlmgXDRokpw1QeU/Z2HLKENj0hFay+ZMVVVZ87Frmab2fa4iMvmSug7TK6mKyrqvDld1/G/XK5Y+t7c+Z/8ygMKP/vdHYjZ+HJEPPiiJmRC1VGgp5ON9H/Pp/k8ps5UBEOMfw5j2YxjeYrjUlIlGQZKzJsaeV0HJ8uPAqebMkNo1Zx7b9iuZe3ejMxi4/Oa/1WGE3svpVFg5bx+HNucC0GNYc9IGJJ830Sqa/zm5zzwDQPi944mcOFESMyFqIac8hw/2fsBXB7/C4rQA0CyoGXd3vJvrL7le+pSJRkWSsyZEVVSKvvxTc+altWvOVBRnVa1Z2sAhBEXUbpRnQ+KwOVn27m6O7ypAq9Vw9Zi2tOp+/jmSihcs5MT06QCE3X2XJGZC1MLRkqO8t+s9lhxdgkN1rbbRLrwdYzuO5arEq9BpZQoa0fhIctaElK/LwpZ+cc2ZALtX/UBBZjo+/gF0H3pTHUfpfWyVDpbM3En2oWJ0Bi3X3dOBZh3Pv25oyZIl5Dz+OKgqoX//O1FTpkhiJkQN7Mnfw5xdc1iZvhIVFYDuMd25u+Pd9IztKf9PolGT5KyJsOdXUrLMNTozeNAltW7OtFVWsG7+RwD0GHkbPo18DcjKchuL39hB3m9lGHx0DL4vlbiW51+QvHT5crIf/ScoCiE330z04/+SLxIhqkFVVTad2MScXXPYmLOxanu/xH6M7TiW1MhUD0YnRP2R5KwJ+KM5U8HUIgT/CzTHnc8vC7+goqSY0Ng4Og9o3Ms0mYutfPPadopyzPgEGLjhgU5EJQed95iyVavIengKOJ0EDxtGzPQnJDET4gIUVWFVxirm7prLrvxdAOg0OgZdMoi7OtxFi9AWHo5QiPolyVkTUL4hG9vxUjRG7UU1Z5bk5bJlyUIA+vz9bnT6xtsBt6zQwsJXtlF6shL/EBNDHux8zqWYfmfe+AtZD04Cu52gQYOIfebpJjcprxA14VAcLDu+jDm75nC4+DAAJp2J4S2GM6bDGOID4j0coRCeIclZI+coqKT0++PAqebMMJ9an2vNJ/Nw2u0kdUglpWv3OorQ+5QVWlg4Yyul+RaCInwYOqkLQRG+5z2mctduMidMQLXZCLjmauKe/6+slSnEOdiddr498i1zd8+tWmIpwBDArW1u5W9t/0aE7/n7dArR2Ely1oipikrRV4dQ7Qqm5sH4d4+t9bmy9u+tmnC276ixjbap7q+J2bDJaQReIKG1Hj1Gxj33oFRU4HfZZcS//DKaJrj4uxAXYnFY+OrQV7y/+31yK1xT0oSYQhjVbhS3trmVIOP5uw0I0VRIctaImX/JwXq0BI1BS+jIlmi0tUuoVEVh9YfvAtCx37VENWtel2F6jdKCSr55ZZsrMYv0ZdhDXS6YmNlPnCD97rtxFhXh0749CW+9idZUu8EWQjRWFfYKPjvwGR/s+YBCSyEAkb6RjG4/mpta3SQTxwrxF5KcNVKOQgsl3x0DIPi6ZujDz98sdz771v3EiSOHMPj40uuWUXUVolcpza9k4SvbKCuwEBzpy7DJXQgIPX9i5igqIv3usThycjA2a0biu7PRNfLRq0LUhM1p44uDXzB75+yqpCzOP467O97N0BZDMenkh4wQZyPJWSOkqipFXx9CtSkYmwXh3zOu1ueyWy2s/fQDAC4bdhP+IeefRqIhKs2vZOGMbZQVWgiO8mXYQ2kEhJ7/S0Mxm8kYNx7bkSPoY2JIem8u+rCweopYCO/mUBwsOrKIt3e8TY45B4CEgATGdRrH9c2vx6CVZn8hzkeSs0bIvOkE1sPFrubMG1vVujkT4NdFCygvyCcwIpK064fWYZTeoeRkBQtnbKO8yEpItB9DJ3W5cGJms5H5wEQsO3eiCwkhae4cDHG1T4CFaCwUVWHFbyt4c9ubHC89DkCUbxTjOo1jeMvhkpQJUU1NYpz/8OHDCQ0N5cYbbzxte0ZGBldeeSXt2rUjNTWVL774wkMR1h1HsYWSpa7mzKD+zTBcYJTh+ZQV5rPp2y8B6HP7GAzGxtUEUZxbwYKXXYlZaIwfwx66cGKmKgo5j/0L8/r1aPz8SJw9C1NKSj1FLIR3UlWVtZlruXXxrUz5aQrHS48TYgphyqVTWDJiCTe3vlkSMyFqoEnUnE2cOJG77rqLDz744LTter2eV199lc6dO5OXl0daWhqDBg3C3//881l5K1dz5mFUqxNjchABvS6uNmfdZx/hsFqJbdWG1pf3qaMovUPRCTMLX9lGRYmN0Fh/hk7qjH/whZPPk6+9TumSJaDXk/DG6/imyozlomnbkruF17e+zta8rQD4G/wZ3W40o9qNIsAofTCFqI0mkZz169eP1atXn7E9NjaW2FjX9BJRUVGEhYVRWFjYYJOziu0nsR4sAr2G0BtrPzoTIPvgPvb8tBKAfnf8o1FNnVGYbWbhq9uoLLURFufP0Eld8AsyXvC44i+/pGDWLABin3qKgF693B2qEF5rb8FeXt/2Ouuy1gGuyWNva3Mbd3W4i1Cfxtc3VYj65PFmzTVr1nDDDTcQFxeHRqNh4cKFZ+wzc+ZMLrnkEnx8fOjatStr166t8zh+/fVXFEUhMTGxzs9dH5zlNkoWHQEg6OpkDJG1H5quKE5WvvcOAO2vvIbYlq3rJEZvUJBVzsJXtlJZaiM8IYBhk6uXmJX/vI6cJ6YDEDFhAiEjhrs5UiG809Hio0xePZlbFt/Cuqx16DV6bm51M0uGL+HhSx+WxEyIOuDxmjOz2UynTp248847GTly5BmPz58/n0mTJjFz5kx69erFrFmzGDhwIHv37iUpKQmArl27YrVazzh2+fLlxFWjo3ZBQQF33HEHc+bMOec+Vqv1tOcoKSkBoLS09ILnrw+FXx6ksqgEQ7QfgZ0DLyqunSuXk35wP0Y/fzoPHuE1r/FiFWSVs2TmTixmO+Hx/lx1Vwp2xYK91HLe4yyHDpNx//0oNhuBgwZiHH1HoykTIaorpzyHObvm8N3x71BUBQ0aBjQbwNgOY0kISgCn93weCnE+v79PVVX1cCTnoXoRQF2wYMFp27p3766OHz/+tG1t2rRRp06dWqNzr1q1Sh05cuQZ2y0Wi9q7d2/1ww8/PO/xTzzxhArIRS5ykYtc5CKXRnDJyMioUR5Rnzxec3Y+NpuNLVu2MHXq1NO29+/fn/Xr11/0+VVVZcyYMVx11VWMGnX+yVUfe+wxJk+eXHW/uLiY5ORk0tPTCQ4OvuhYxOlKS0tJTEwkIyODoCBZ0qUuSdm6l5Sve0n5uldTKF9VVSkrK6tWy5qneHVylp+fj9PpJDo6+rTt0dHRnDhxotrnGTBgAFu3bsVsNpOQkMCCBQvo1q0b69atY/78+aSmplb1dfvoo4/o2LHjGecwmUyYzrIsT3BwcKN9A3uDoKAgKV83kbJ1Lylf95Lyda/GXr7eXqni1cnZ7/46UlBV1RqNHly2bNlZt19xxRUoinJRsQkhhBBC1CWPj9Y8n4iICHQ63Rm1ZHl5eWfUpgkhhBBCNAZenZwZjUa6du3KihUrTtu+YsUKLr/8cg9F5WIymXjiiSfO2tQpLp6Ur/tI2bqXlK97Sfm6l5Svd9CoqmfHkpaXl3P48GEAunTpwowZM+jXrx9hYWEkJSUxf/58Ro0axTvvvEPPnj2ZPXs27777Lnv27CE5OdmToQshhBBC1DmPJ2erV6+mX79+Z2wfPXo08+bNA1yT0L7wwgvk5OTQoUMHXnnlFfr0aVzLCQkhhBBCgBckZ0IIIYQQ4g9e3edMCCGEEKKpkeRMCCGEEMKLSHImhBBCCOFFJDmrB6+88grt27enXbt2TJw40bsXW22Ajh07Rr9+/WjXrh0dO3bEbDZ7OqRGp6KiguTkZKZMmeLpUBqVjIwMrrzyStq1a0dqaipffPGFp0Nq0BYvXkzr1q1p2bIlc+bM8XQ4jYq8V+uXDAhws5MnT9KjRw/27NmDwWCgT58+vPTSS/Ts2dPToTUaffv25emnn6Z3794UFhYSFBSEXt8gFr9oMB5//HEOHTpEUlISL730kqfDaTRycnLIzc2lc+fO5OXlkZaWxoEDB/D39/d0aA2Ow+GgXbt2rFq1iqCgINLS0vjll18ICwvzdGiNgrxX65fUnNUDh8OBxWLBbrdjt9uJiorydEiNxu9Jb+/evQEICwuTxKyOHTp0iP379zNo0CBPh9LoxMbG0rlzZwCioqIICwujsLDQs0E1UJs2baJ9+/bEx8cTGBjIoEGDzrl0n6g5ea/WryafnK1Zs4YbbriBuLg4NBpN1QLofzZz5kwuueQSfHx86Nq1K2vXrq32+SMjI5kyZQpJSUnExcVxzTXXkJKSUoevwLu5u3wPHTpEQEAAQ4YMIS0tjWeffbYOo/d+7i5fgClTpvDcc8/VUcQNS32U7+9+/fVXFEUhMTHxIqNumC62rLOzs4mPj6+6n5CQQFZWVn2E3iDU5Xu5qb9X60OTT87MZjOdOnXizTffPOvj8+fPZ9KkSTz++ONs27aN3r17M3DgQNLT06v26dq1Kx06dDjjkp2dTVFREYsXL+b48eNkZWWxfv161qxZU18vz+PcXb52u521a9fy1ltvsWHDBlasWHHGcl+NmbvL95tvvqFVq1a0atWqvl6SV3F3+f6uoKCAO+64g9mzZ7v9NXmriy3rs/XQ0Wg0bo25IamL9zLIe7XeqKIKoC5YsOC0bd27d1fHjx9/2rY2bdqoU6dOrdY5P//8c3XChAlV91944QX1+eefv+hYGyJ3lO/69evVAQMGVN1/4YUX1BdeeOGiY22I3FG+U6dOVRMSEtTk5GQ1PDxcDQoKUp988sm6CrlBcUf5qqqqWiwWtXfv3uqHH35YF2E2CrUp63Xr1qnDhg2remzixInqxx9/7PZYG6LavpflvVp/mnzN2fnYbDa2bNlC//79T9vev39/1q9fX61zJCYmsn79eiwWC06nk9WrV9O6dWt3hNvg1EX5duvWjdzcXIqKilAUhTVr1tC2bVt3hNvg1EX5Pvfcc2RkZHD8+HFeeukl/vGPfzBt2jR3hNvg1EX5qqrKmDFjuOqqqxg1apQ7wmwUqlPW3bt3Z/fu3WRlZVFWVsbSpUsZMGCAJ8JtcKpTvvJerV+SnJ1Hfn4+TqeT6Ojo07ZHR0dz4sSJap2jR48eDBo0iC5dupCamkpKSgpDhgxxR7gNTl2Ur16v59lnn6VPnz6kpqbSsmVLBg8e7I5wG5y6KF9xbnVRvuvWrWP+/PksXLiQzp0707lzZ3bt2uWOcBu06pS1Xq/n5Zdfpl+/fnTp0oVHHnmE8PBwT4Tb4FSnfOW9Wr9kWFs1/LXfgqqqNerL8Mwzz/DMM8/UdViNxsWW78CBAxk4cGBdh9VoXGz5/m7MmDF1FFHjcjHle8UVV6AoijvCapQuVNZDhgyRH78X4XzlK+/V+iU1Z+cRERGBTqc741dwXl7eGb8wRM1J+bqXlK97SfnWHylr95Ly9T6SnJ2H0Wika9euZ4z+W7FiBZdffrmHomo8pHzdS8rXvaR864+UtXtJ+XqfJt+sWV5ezuHDh6vuHzt2jO3btxMWFkZSUhKTJ09m1KhRXHrppfTs2ZPZs2eTnp7O+PHjPRh1wyHl615Svu4l5Vt/pKzdS8q3gfHcQFHvsGrVKhU44zJ69Oiqfd566y01OTlZNRqNalpamvrTTz95LuAGRsrXvaR83UvKt/5IWbuXlG/DImtrCiGEEEJ4EelzJoQQQgjhRSQ5E0IIIYTwIpKcCSGEEEJ4EUnOhBBCCCG8iCRnQgghhBBeRJIzIYQQQggvIsmZEEIIIYQXkeRMCCGEEMKLSHImhBBCCOFFJDkTQnit6dOn07lz53p/3tWrV6PRaCguLq735xZCCEnOhBAeodFoznsZM2YMU6ZMYeXKlfUe2+WXX05OTg7BwcEXdZ6vvvqKyy67jODgYAIDA2nfvj0PP/xwHUUphGis9J4OQAjRNOXk5FTdnj9/PtOmTePAgQNV23x9fQkICCAgIKDeYzMajcTExFzUOX744QduvfVWnn32WYYMGYJGo2Hv3r0eSTaFEA2L1JwJITwiJiam6hIcHIxGozlj21+bNceMGcOwYcN49tlniY6OJiQkhCeffBKHw8EjjzxCWFgYCQkJvPfee6c9V1ZWFrfccguhoaGEh4czdOhQjh8/fs7Y/tqsOW/ePEJCQli2bBlt27YlICCA66677rQE868WL17MFVdcwSOPPELr1q1p1aoVw4YN44033jhtv0WLFtG1a1d8fHxo3rx51ev5XXFxMffccw/R0dH4+PjQoUMHFi9eXP2CFkI0OJKcCSEalB9//JHs7GzWrFnDjBkzmD59OoMHDyY0NJRffvmF8ePHM378eDIyMgCoqKigX79+BAQEsGbNGn7++eeq5Mpms1X7eSsqKnjppZf46KOPWLNmDenp6UyZMuWc+8fExLBnzx527959zn2WLVvG3//+dyZOnMjevXuZNWsW8+bN45lnngFAURQGDhzI+vXr+d///sfevXv573//i06nq3bcQogGSBVCCA97//331eDg4DO2P/HEE2qnTp2q7o8ePVpNTk5WnU5n1bbWrVurvXv3rrrvcDhUf39/9dNPP1VVVVXnzp2rtm7dWlUUpWofq9Wq+vr6qsuWLTtrPKtWrVIBtaioqCo+QD18+HDVPm+99ZYaHR19ztdUXl6uDho0SAXU5ORk9ZZbblHnzp2rWiyWqn169+6tPvvss6cd99FHH6mxsbGqqqrqsmXLVK1Wqx44cOCczyOEaHykz5kQokFp3749Wu0flf7R0dF06NCh6r5OpyM8PJy8vDwAtmzZwuHDhwkMDDztPBaLhSNHjlT7ef38/EhJSam6HxsbW/UcZ+Pv78+SJUs4cuQIq1atYuPGjTz88MO89tprbNiwAT8/P7Zs2cLmzZurasoAnE4nFouFiooKtm/fTkJCAq1atap2nEKIhk+SMyFEg2IwGE67r9FozrpNURTA1TTYtWtXPv744zPOFRkZeVHPq6rqBY9LSUkhJSWFsWPH8vjjj9OqVSvmz5/PnXfeiaIoPPnkk4wYMeKM43x8fPD19a12fEKIxkOSMyFEo5aWlsb8+fOJiooiKCjIo7E0a9YMPz8/zGZzVWwHDhygRYsWZ90/NTWVzMxMDh48KLVnQjQhkpwJIRq1v/3tb7z44osMHTqUp556ioSEBNLT0/n666955JFHSEhIcMvzTp8+nYqKCgYNGkRycjLFxcW8/vrr2O12rr32WgCmTZvG4MGDSUxM5KabbkKr1bJz50527drF008/Td++fenTpw8jR45kxowZtGjRgv3796PRaLjuuuvcErcQwvNktKYQolHz8/NjzZo1JCUlMWLECNq2bctdd91FZWWlW2vS+vbty9GjR7njjjto06YNAwcO5MSJEyxfvpzWrVsDMGDAABYvXsyKFSvo1q0bPXr0YMaMGSQnJ1ed56uvvqJbt27cdttttGvXjkcffRSn0+m2uIUQnqdRq9NpQgghhBBC1AupORNCCCGE8CKSnAkhhBBCeBFJzoQQQgghvIgkZ0IIIYQQXkSSMyGEEEIILyLJmRBCCCGEF5HkTAghhBDCi0hyJoQQQgjhRSQ5E0IIIYTwIpKcCSGEEEJ4EUnOhBBCCCG8yP8DI6meeR5VsHAAAAAASUVORK5CYII=", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys.sims[1], 1e-10, 1.8e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-8, 2e3)\n", - "ylim(1e-12, 1e-2)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 58, - "id": "1ef78267", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotC(ssys.sims[1], 1e-5, 1.8e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-8, 2e3)\n", - "ylim(1e-6, 1e2)\n", - "title(\"Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 59, - "id": "9ca4df51", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys.sims[2], 1e-2, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-6, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 60, - "id": "1f7d8918", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "1377×1298 Array{RGB{N0f8},2} with eltype ColorTypes.RGB{FixedPointNumbers.N0f8}:\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "getfluxdiagram(ssys,1.8e3;speciesratetolerance=1e-6)" - ] - }, - { - "cell_type": "code", - "execution_count": 61, - "id": "36206466", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[\"Ar\", \"He\", \"Ne\", \"N2\", \"CO2\", \"proton\", \"H\", \"C=O\", \"O=CO\", \"O2\", \"O=C=C=O\", \"H2O\", \"CO\", \"C=C=O\", \"O=C=CO\", \"H2\", \"O=CC=O\", \"O=CCO\", \"COC=O\", \"CC(=O)O\", \"CO-2\", \"CC=O\", \"OCO\", \"OCCO\", \"C=C\", \"vacantX\", \"CO2X\", \"CHO2X\", \"CO2HX\", \"OCX\", \"OX\", \"CH2O2X\", \"CHOX\", \"CH2OX\", \"HOX\", \"O=C([Pt])C(=O)[Pt]\", \"HX\", \"H2OX\", \"O=CC(=O)[Pt]\", \"CX\", \"O=O.[Pt]\", \"O=C=C=O.[Pt]\", \"OC#[Pt]\", \"O=C([Pt])C#[Pt]\", \"CH2X\", \"O=C([Pt])C[Pt]\", \"[Pt]CO[Pt]\", \"O=C([Pt])OC[Pt]\", \"C=C=O.[Pt]\", \"O=C(C[Pt])O[Pt]\", \"O=C([Pt])C=[Pt]\", \"[Pt]OC=[Pt]\", \"O=C=C=[Pt]\", \"CHX\", \"O=C([Pt])CO[Pt]\", \"[Pt]OCO[Pt]\", \"O=C=C[Pt]\", \"[Pt]COO[Pt]\", \"O=C=CO[Pt]\", \"OO[Pt]\", \"O=C([Pt])C(O)=[Pt]\", \"OC(=[Pt])O[Pt]\", \"OC=[Pt]\", \"OC([Pt])O[Pt]\", \"O=C([Pt])C(O)[Pt]\", \"O=C=CO.[Pt]\", \"O=C=C([Pt])O[Pt]\", \"CO[Pt]\", \"COC(=O)[Pt]\", \"CC(=O)[Pt]\", \"CC(=O)O[Pt]\", \"CH3X\", \"OC[Pt]\", \"O=C([Pt])CO\", \"OCO[Pt]\", \"O=C([Pt])OC=[Pt]\", \"COO[Pt]\", \"[H][H].[Pt]\", \"O=C(C=[Pt])O[Pt]\", \"CO.[Pt]\", \"O=C(C#[Pt])O[Pt]\", \"O=C=C(O)[Pt]\", \"OC(O)[Pt]\", \"OC(O)=[Pt]\", \"CC(=O)O.[Pt]\", \"O=C(O)C[Pt]\", \"O=C(O)C=[Pt]\", \"O=C(O)C#[Pt]\", \"CC(O)=[Pt]\", \"[Pt]=C=C=[Pt]\", \"CC(O)([Pt])O[Pt]\", \"CC(=[Pt])O[Pt]\", \"CC#[Pt]\", \"[Pt]C#CO[Pt]\", \"[Pt]OC#CO[Pt]\", \"COC=O.[Pt]\", \"O=COC[Pt]\", \"O=COC=[Pt]\", \"O=COC#[Pt]\", \"[Pt]C=C=[Pt]\", \"[Pt]=CC=[Pt]\"]\n" - ] - } - ], - "source": [ - "println(ssys.names)" - ] - }, - { - "cell_type": "code", - "execution_count": 62, - "id": "44de0eb2", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "vacantX+CO2<=>CO2X\n", - "kf = 20654.615923781494\n", - "krev = 11189.298480848476\n", - "Kc = 1.8459259049290524\n", - "proton+CO2X<=>CHO2X\n", - "kf = 2.901741644670854e9\n", - "krev = 1899.6670255179733\n", - "Kc = 1.5275001385464643e6\n", - "proton+CO2X<=>CO2HX\n", - "kf = 1.4635836812024672e9\n", - "krev = 3.811669269961144e-9\n", - "Kc = 3.839744682826029e17\n", - "proton+CHO2X<=>CH2O2X\n", - "kf = 2.5e10\n", - "krev = 9.141528182057173e-33\n", - "Kc = 2.734772513097925e42\n", - "proton+CO2HX<=>CH2O2X\n", - "kf = 2.5e10\n", - "krev = 2.2979463860055554e-21\n", - "Kc = 1.0879279060751577e31\n", - "proton+OCX<=>CHOX\n", - "kf = 2.5e10\n", - "krev = 2.6138381923072832e-17\n", - "Kc = 9.564478808817174e26\n", - "proton+CHOX<=>CH2OX\n", - "kf = 2.5e10\n", - "krev = 6.953217448005557e-17\n", - "Kc = 3.5954578131553956e26\n", - "vacantX+vacantX+CO2<=>OX+OCX\n", - "kf = 3.0109478093912387e-24\n", - "krev = 3.0371562968883405e15\n", - "Kc = 9.913707149270016e-40\n", - "OX+proton<=>HOX\n", - "kf = 2.5e10\n", - "krev = 4.7718507938688055e-21\n", - "Kc = 5.239057355297378e30\n", - "vacantX+C=O<=>CH2OX\n", - "kf = 500114.13488002896\n", - "krev = 399.68032800366484\n", - "Kc = 1251.2853394061547\n", - "proton+CHO2X<=>OX+C=O\n", - "kf = 4.478925490216818e-5\n", - "krev = 4.6352602661777355e-10\n", - "Kc = 96627.27081148709\n", - "proton+O=C([Pt])C(=O)[Pt]<=>OCX+CHOX\n", - "kf = 349570.53490526683\n", - "krev = 2.4823507835261012e-29\n", - "Kc = 1.4082237580005227e34\n", - "vacantX+O=CO<=>CH2O2X\n", - "kf = 403943.82249737746\n", - "krev = 29.756334576372204\n", - "Kc = 13575.053118878628\n", - "vacantX+vacantX+O=CO<=>HOX+CHOX\n", - "kf = 8.486192390111035e-15\n", - "krev = 9.703703473931064e11\n", - "Kc = 8.745312975514075e-27\n", - "HX+CO2<=>CHO2X\n", - "kf = 6.542996392927688e-8\n", - "krev = 15.579156394921906\n", - "Kc = 4.199839983030407e-9\n", - "HX+CO2<=>CO2HX\n", - "kf = 6.542996392927688e-8\n", - "krev = 6.197590078871038e-11\n", - "Kc = 1055.732358813826\n", - "vacantX+vacantX+C=O<=>HX+CHOX\n", - "kf = 2.0718885766149143e-11\n", - "krev = 0.008867505326420184\n", - "Kc = 2.3364954407660184e-9\n", - "vacantX+vacantX+O=CO<=>HX+CHO2X\n", - "kf = 2.533669358619512e-21\n", - "krev = 760.2682056541253\n", - "Kc = 3.3325993902896074e-24\n", - "vacantX+vacantX+O=CO<=>HX+CO2HX\n", - "kf = 1.9680342311574e-14\n", - "krev = 0.02349245741111688\n", - "Kc = 8.377302538925132e-13\n", - "vacantX+vacantX+O2<=>OX+OX\n", - "kf = 1.0945721587141857e10\n", - "krev = 4.2193250079705054e-16\n", - "Kc = 2.5941878301540814e25\n", - "proton+HOX<=>H2OX\n", - "kf = 2.5e10\n", - "krev = 1.2669484290742183e-38\n", - "Kc = 1.9732452739428346e48\n", - "vacantX+vacantX+O=C=C=O<=>OCX+OCX\n", - "kf = 74.64023007210145\n", - "krev = 2.9534396659358314e-39\n", - "Kc = 2.5272305689187265e40\n", - "vacantX+H2O<=>H2OX\n", - "kf = 4.842414926683719e6\n", - "krev = 2.0721934489390883e8\n", - "Kc = 0.023368546643957957\n", - "proton+CO2HX<=>H2O+OCX\n", - "kf = 2.5e10\n", - "krev = 4.0403409398101914e-14\n", - "Kc = 6.187596634152973e23\n", - "vacantX+vacantX+H2O<=>HX+HOX\n", - "kf = 1.7047654949014593e-31\n", - "krev = 21441.30602993661\n", - "Kc = 7.950847268917505e-36\n", - "proton+O=CC(=O)[Pt]<=>OCX+C=O\n", - "kf = 1.2933642508640456e9\n", - "krev = 1.4498655439123794e-14\n", - "Kc = 8.920580644836735e22\n", - "HX+O=C=C=O<=>O=CC(=O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 5.0006650398005155e-61\n", - "Kc = 1.1597065597251546e53\n", - "OCX<=>vacantX+CO\n", - "kf = 2.010168305725754e-19\n", - "krev = 2.6176079382198975e-25\n", - "Kc = 767940.9419474666\n", - "vacantX+O=C=C=O<=>O=C=C=O.[Pt]\n", - "kf = 366139.2749661925\n", - "krev = 442.0652198786663\n", - "Kc = 828.2471872966771\n", - "proton+O=C=C=O.[Pt]<=>O=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.6594331967618788e-55\n", - "Kc = 9.400499335888545e64\n", - "proton+OCX<=>OC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.448446458236348e10\n", - "Kc = 0.264593762694259\n", - "proton+OC#[Pt]<=>H2O+CX\n", - "kf = 0.001840934017187436\n", - "krev = 5.2389566412922466e-9\n", - "Kc = 351393.2531293768\n", - "proton+O=C([Pt])C#[Pt]<=>CX+CHOX\n", - "kf = 1.567863889740614e6\n", - "krev = 480.1043675114013\n", - "Kc = 3265.673040775621\n", - "vacantX+vacantX+C=O<=>OX+CH2X\n", - "kf = 4.560831679646634e-28\n", - "krev = 3.8841510055710957e17\n", - "Kc = 1.1742158513160188e-45\n", - "vacantX+vacantX+C=C=O<=>OCX+CH2X\n", - "kf = 2.4823885573383586e-14\n", - "krev = 9.35113251070281e15\n", - "Kc = 2.6546394829686654e-30\n", - "proton+O=C([Pt])C[Pt]<=>CHOX+CH2X\n", - "kf = 125.41367268854671\n", - "krev = 111.34632647709498\n", - "Kc = 1.126338664745671\n", - "proton+[Pt]CO[Pt]<=>HOX+CH2X\n", - "kf = 427.3265444516916\n", - "krev = 3602.159459069811\n", - "Kc = 0.11863065733409828\n", - "proton+O=C([Pt])OC[Pt]<=>CO2HX+CH2X\n", - "kf = 2.5e10\n", - "krev = 0.00018606563291677844\n", - "Kc = 1.3436119076961272e14\n", - "vacantX+C=C=O<=>C=C=O.[Pt]\n", - "kf = 422670.5724931744\n", - "krev = 9.809802437351828e-11\n", - "Kc = 4.3086552985390705e15\n", - "proton+O=C(C[Pt])O[Pt]<=>CHO2X+CH2X\n", - "kf = 4.62207026560703e-6\n", - "krev = 4.538375929369704e7\n", - "Kc = 1.0184414727955226e-13\n", - "proton+O=C([Pt])C#[Pt]<=>O=C([Pt])C=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3210558555678669e-37\n", - "Kc = 1.892425660476978e47\n", - "proton+O=C([Pt])C=[Pt]<=>O=C([Pt])C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0627192300645304e-27\n", - "Kc = 2.352455784439127e37\n", - "proton+O=C([Pt])C=[Pt]<=>OCX+CH2X\n", - "kf = 2.5e10\n", - "krev = 0.9024244549013938\n", - "Kc = 2.7703149958111122e10\n", - "proton+[Pt]OC=[Pt]<=>[Pt]CO[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.5399557273620522e-20\n", - "Kc = 9.842691244844849e29\n", - "proton+[Pt]OC=[Pt]<=>OX+CH2X\n", - "kf = 296724.5058712665\n", - "krev = 1.3313608118035294e7\n", - "Kc = 0.022287309588849044\n", - "vacantX+vacantX+O=C=C=O<=>OX+O=C=C=[Pt]\n", - "kf = 149.2804601441562\n", - "krev = 1.2008902564546813e-12\n", - "Kc = 1.243081616673852e14\n", - "proton+CX<=>CHX\n", - "kf = 2.5e10\n", - "krev = 6.039944774662586e-40\n", - "Kc = 4.139110692679569e49\n", - "proton+O=C([Pt])C#[Pt]<=>OCX+CHX\n", - "kf = 1.746753626001255e7\n", - "krev = 1.2359850586917588e-19\n", - "Kc = 1.413248172959408e26\n", - "proton+CHX<=>CH2X\n", - "kf = 2.5e10\n", - "krev = 6.739232820388986e-22\n", - "Kc = 3.709621060184267e31\n", - "proton+O=C([Pt])C=[Pt]<=>CHX+CHOX\n", - "kf = 2.3817231579990697e8\n", - "krev = 333.44972665024386\n", - "Kc = 714267.5394954707\n", - "proton+[Pt]OC=[Pt]<=>HOX+CHX\n", - "kf = 1733.0864157787125\n", - "krev = 550603.5001889854\n", - "Kc = 0.003147612420160533\n", - "vacantX+vacantX+C=C=O<=>HX+O=C=C[Pt]\n", - "kf = 3.6584912239485734e-16\n", - "krev = 0.32395775784833547\n", - "Kc = 1.1293111942271616e-15\n", - "proton+O=C=C[Pt]<=>C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.759984133779286e-36\n", - "Kc = 2.561479573872979e45\n", - "proton+O=C=C=[Pt]<=>O=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.013708774394374e-22\n", - "Kc = 4.157168386079303e31\n", - "HX+O=C=C=O<=>O=C=CO[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.1302052975692196e-55\n", - "Kc = 2.722415560726707e47\n", - "proton+O=C=C=O.[Pt]<=>O=C=CO[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 2.2657541103771886e-49\n", - "Kc = 2.2067707952508713e59\n", - "proton+O=C=CO[Pt]<=>OX+C=C=O\n", - "kf = 2.673147452357666\n", - "krev = 1.5903536390399585e-13\n", - "Kc = 1.680850967192022e13\n", - "proton+OO[Pt]<=>OX+H2O\n", - "kf = 969.569442920103\n", - "krev = 3.5164838724414706e-68\n", - "Kc = 2.757212824203677e70\n", - "O=O.[Pt]+proton<=>OO[Pt]\n", - "kf = 5.0e10\n", - "krev = 7.117454684215303e-35\n", - "Kc = 7.02498325853584e44\n", - "proton+[Pt]COO[Pt]<=>OO[Pt]+CH2X\n", - "kf = 5.010993055207674e-10\n", - "krev = 177.88704533555924\n", - "Kc = 2.8169522101821023e-12\n", - "proton+O=C([Pt])C(=O)[Pt]<=>O=C([Pt])C(O)=[Pt]\n", - "kf = 5.0e10\n", - "krev = 8.622067229210218e-5\n", - "Kc = 5.799073316270118e14\n", - "proton+O=C([Pt])C(O)=[Pt]<=>H2O+O=C([Pt])C#[Pt]\n", - "kf = 5.795174679515367e8\n", - "krev = 8.382105904506003e-13\n", - "Kc = 6.913745478209755e20\n", - "proton+O=C([Pt])C(O)=[Pt]<=>CHOX+OC#[Pt]\n", - "kf = 1.1965126741588843e9\n", - "krev = 1.8621927584543355e-10\n", - "Kc = 6.425289050914463e18\n", - "proton+OC(=[Pt])O[Pt]<=>HOX+OC#[Pt]\n", - "kf = 2083.817981390467\n", - "krev = 29245.126965181986\n", - "Kc = 0.07125351118739792\n", - "proton+CHOX<=>OC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 23770.987687012675\n", - "Kc = 1.0517021980394528e6\n", - "vacantX+vacantX+O=CO<=>OX+OC=[Pt]\n", - "kf = 1.399500608042703e-36\n", - "krev = 7.971831424044634e14\n", - "Kc = 1.755557203356722e-51\n", - "proton+OC#[Pt]<=>OC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.576056260658294e-24\n", - "Kc = 3.801670638002933e33\n", - "proton+OC=[Pt]<=>H2O+CHX\n", - "kf = 2.5e10\n", - "krev = 6.534525208012436e-12\n", - "Kc = 3.825832666365073e21\n", - "proton+O=C([Pt])C(O)=[Pt]<=>OCX+OC=[Pt]\n", - "kf = 2.679139607443752e7\n", - "krev = 1.0490338346020113e-18\n", - "Kc = 2.5539115318050537e25\n", - "proton+OC(=[Pt])O[Pt]<=>OX+OC=[Pt]\n", - "kf = 61382.66930820151\n", - "krev = 1187.1843548522681\n", - "Kc = 51.704412256881454\n", - "proton+OC([Pt])O[Pt]<=>H2O+[Pt]OC=[Pt]\n", - "kf = 606573.2626910724\n", - "krev = 1.4273376264812929e-13\n", - "Kc = 4.24968312638413e18\n", - "proton+OC(=[Pt])O[Pt]<=>OC([Pt])O[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.2267927894970754e-28\n", - "Kc = 7.747631047575409e37\n", - "proton+OC([Pt])O[Pt]<=>HOX+OC=[Pt]\n", - "kf = 0.0001733046729443134\n", - "krev = 49.56766321132819\n", - "Kc = 3.4963252595838807e-6\n", - "vacantX+vacantX+O=C=CO<=>HOX+O=C=C[Pt]\n", - "kf = 1.5660475358156177e8\n", - "krev = 2.9097856260811068e7\n", - "Kc = 5.382003133766137\n", - "vacantX+vacantX+O=C=CO<=>HX+O=C=CO[Pt]\n", - "kf = 0.00035356443313081133\n", - "krev = 1.4494227063046492e-5\n", - "Kc = 24.393465866988898\n", - "vacantX+vacantX+O=C=CO<=>OCX+OC=[Pt]\n", - "kf = 73.33238091278024\n", - "krev = 14511.198913245214\n", - "Kc = 0.005053502563860903\n", - "proton+O=C([Pt])C(O)[Pt]<=>H2O+O=C([Pt])C=[Pt]\n", - "kf = 7.47304251282773e8\n", - "krev = 9.706293860582836e-32\n", - "Kc = 7.699171918929513e39\n", - "proton+O=C([Pt])C(O)=[Pt]<=>O=C([Pt])C(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4711325689645158e-18\n", - "Kc = 1.6993709831056707e28\n", - "proton+O=C([Pt])C(O)[Pt]<=>CHOX+OC=[Pt]\n", - "kf = 5.500723345616163e7\n", - "krev = 3.826844742690272e-17\n", - "Kc = 1.437404367167808e24\n", - "proton+O=C=CO[Pt]<=>O=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.237321276009296e-9\n", - "Kc = 2.020493826844385e19\n", - "vacantX+O=C=CO<=>O=C=CO.[Pt]\n", - "kf = 359723.7676387533\n", - "krev = 0.49000540957808064\n", - "Kc = 734122.0333638635\n", - "proton+O=C=C([Pt])O[Pt]<=>OX+O=C=C[Pt]\n", - "kf = 2832.720789616565\n", - "krev = 1.3891029050632516e-38\n", - "Kc = 2.0392447379465954e41\n", - "proton+O=C=C([Pt])O[Pt]<=>HOX+O=C=C=[Pt]\n", - "kf = 1.517560538428898e7\n", - "krev = 5.905016800821827e-34\n", - "Kc = 2.5699512628273853e40\n", - "vacantX+vacantX+H2<=>HX+HX\n", - "kf = 1.4751196915392066e-5\n", - "krev = 1.9009061341557055e13\n", - "Kc = 7.760086966074137e-19\n", - "H2+CX<=>CH2X\n", - "kf = 4.832014059685671\n", - "krev = 1.8278921581743624e-33\n", - "Kc = 2.643489681859418e33\n", - "proton+CH2OX<=>CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 0.004917587151469905\n", - "Kc = 5.083793988791291e12\n", - "HX+C=O<=>CO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.180104845142552e-9\n", - "Kc = 9.475050217697259\n", - "proton+O=C([Pt])CO[Pt]<=>OCX+CO[Pt]\n", - "kf = 4.126026049117007e9\n", - "krev = 9.0777008417621e-8\n", - "Kc = 4.545232455926683e16\n", - "proton+[Pt]OCO[Pt]<=>OX+CO[Pt]\n", - "kf = 2.8370216580227352e10\n", - "krev = 8.717411206626125e-5\n", - "Kc = 3.2544313796581125e14\n", - "HX+C=C=O<=>CC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.331078557756203e-33\n", - "Kc = 2.514767798289312e25\n", - "proton+C=C=O.[Pt]<=>CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.380006042553017e-15\n", - "Kc = 3.918491586568469e24\n", - "proton+O=C([Pt])CO[Pt]<=>OX+CC(=O)[Pt]\n", - "kf = 2.228376401388972e7\n", - "krev = 4.1761269462661204e-19\n", - "Kc = 5.33598817770941e25\n", - "proton+CH2X<=>CH3X\n", - "kf = 2.5e10\n", - "krev = 7.756475460671835e-35\n", - "Kc = 3.223113400765481e44\n", - "proton+O=C([Pt])C[Pt]<=>OCX+CH3X\n", - "kf = 2.427096762561667e9\n", - "krev = 6.394459214254184e-9\n", - "Kc = 3.79562474517206e17\n", - "proton+[Pt]CO[Pt]<=>OX+CH3X\n", - "kf = 2.5e10\n", - "krev = 0.003425473711991056\n", - "Kc = 7.298260650048531e12\n", - "CO2+CH3X<=>COC(=O)[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.004021716329375409\n", - "Kc = 1.626916434940066e-5\n", - "CO2+CH3X<=>CC(=O)O[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 3.3286101922667594e-7\n", - "Kc = 0.19656841789792018\n", - "vacantX+vacantX+O=CC=O<=>CHOX+CHOX\n", - "kf = 3.132095071630788e8\n", - "krev = 159.05427896337946\n", - "Kc = 1.9691988747765278e6\n", - "vacantX+vacantX+O=CC=O<=>HX+O=CC(=O)[Pt]\n", - "kf = 7.18568300467857e-10\n", - "krev = 0.00016138838968382215\n", - "Kc = 4.4524163223613075e-6\n", - "proton+CH2OX<=>OC[Pt]\n", - "kf = 3.92777210948067e9\n", - "krev = 3.4866635432857413e-10\n", - "Kc = 1.126513086427387e19\n", - "HX+C=O<=>OC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.8864221055476343e-15\n", - "Kc = 2.0995673877277512e7\n", - "proton+OC[Pt]<=>H2O+CH2X\n", - "kf = 404871.8642501109\n", - "krev = 1.0986509482895068e-8\n", - "Kc = 3.685172846575677e13\n", - "proton+O=C([Pt])OC[Pt]<=>OCX+OC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.1081588840505863e-14\n", - "Kc = 2.2559941863768676e24\n", - "proton+[Pt]COO[Pt]<=>OX+OC[Pt]\n", - "kf = 5.0656037426688395e7\n", - "krev = 2.403473330996825e-38\n", - "Kc = 2.1076180365054905e45\n", - "proton+OC=[Pt]<=>OC[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.49145949711522e-30\n", - "Kc = 3.85121404687342e39\n", - "proton+OC([Pt])O[Pt]<=>OX+OC[Pt]\n", - "kf = 444548.43010662886\n", - "krev = 172.96679933407768\n", - "Kc = 2570.137343225062\n", - "proton+O=C([Pt])C(O)[Pt]<=>OCX+OC[Pt]\n", - "kf = 38815.645706286836\n", - "krev = 6.706431722264065e-33\n", - "Kc = 5.787823885155849e36\n", - "HOX+C=C=O<=>O=C([Pt])CO\n", - "kf = 3.3473534940386794e-8\n", - "krev = 9.042590347803399e-30\n", - "Kc = 3.701763947375775e21\n", - "HX+O=C=CO<=>O=C([Pt])CO\n", - "kf = 2.8488442036348548e-8\n", - "krev = 1.6148406184190954e-45\n", - "Kc = 1.7641643213209675e37\n", - "proton+O=C=CO.[Pt]<=>O=C([Pt])CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.5495530665233894e-36\n", - "Kc = 1.6133684312012967e46\n", - "proton+CH2O2X<=>OCO[Pt]\n", - "kf = 0.04356390724635915\n", - "krev = 1.1663677924118434\n", - "Kc = 0.037350060186655744\n", - "HOX+C=O<=>OCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.9629491497429454e-13\n", - "Kc = 201771.41791040247\n", - "HX+O=CO<=>OCO[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 42359.46557800482\n", - "Kc = 7.552140562111307e-13\n", - "proton+O=C([Pt])OC=[Pt]<=>O=C([Pt])OC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.9681021610090853e-70\n", - "Kc = 1.270259262719472e80\n", - "proton+O=C([Pt])OC=[Pt]<=>OCX+OC=[Pt]\n", - "kf = 11.624436009512083\n", - "krev = 1.5622092374063505e-64\n", - "Kc = 7.441023731757911e64\n", - "proton+O=C([Pt])OC=[Pt]<=>CHX+CO2HX\n", - "kf = 41.457417606802025\n", - "krev = 9.010846264436114e-62\n", - "Kc = 4.600835081431319e62\n", - "vacantX+vacantX+O=CCO<=>CHOX+OC[Pt]\n", - "kf = 9001.813049527467\n", - "krev = 8.180569890870994e12\n", - "Kc = 1.1003894801477009e-9\n", - "vacantX+vacantX+O=CCO<=>HX+O=C([Pt])CO\n", - "kf = 1.2718474027465032e-10\n", - "krev = 0.00027056738325432323\n", - "Kc = 4.7006678611775395e-7\n", - "proton+HX<=>[H][H].[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.1992592361828559e-22\n", - "Kc = 2.0846201759990566e32\n", - "vacantX+H2<=>[H][H].[Pt]\n", - "kf = 2338.960705507055\n", - "krev = 9707.159813767565\n", - "Kc = 0.24095211682718268\n", - "vacantX+vacantX+COC=O<=>CHOX+CO[Pt]\n", - "kf = 5.858305523872122e-8\n", - "krev = 9.372228401444236e12\n", - "Kc = 6.250707166898933e-21\n", - "vacantX+vacantX+COC=O<=>HX+COC(=O)[Pt]\n", - "kf = 3.1523562447166925e-16\n", - "krev = 0.07358618391849557\n", - "Kc = 4.2838968904927294e-15\n", - "vacantX+vacantX+COC=O<=>CHO2X+CH3X\n", - "kf = 0.02794975184381862\n", - "krev = 2.527385267967585e16\n", - "Kc = 1.1058761874597226e-18\n", - "proton+O=C(C=[Pt])O[Pt]<=>O=C(C[Pt])O[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.0143585209679346e-67\n", - "Kc = 4.985682594385809e76\n", - "proton+O=C(C=[Pt])O[Pt]<=>CHX+CHO2X\n", - "kf = 556696.5278801522\n", - "krev = 4.0671234839602046e-27\n", - "Kc = 1.3687721311527293e32\n", - "vacantX+vacantX+CC(=O)O<=>HOX+CC(=O)[Pt]\n", - "kf = 3.661873055903954e-12\n", - "krev = 2.1682718088467175e11\n", - "Kc = 1.6888441020001398e-23\n", - "vacantX+vacantX+CC(=O)O<=>HX+CC(=O)O[Pt]\n", - "kf = 1.2376771395919924e-22\n", - "krev = 5691.281403266516\n", - "Kc = 2.174689761222537e-26\n", - "vacantX+vacantX+CC(=O)O<=>CO2HX+CH3X\n", - "kf = 1.1977509649483996e-8\n", - "krev = 1.0254845667255739e14\n", - "Kc = 1.1679853640049224e-22\n", - "proton+CO[Pt]<=>CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.496528240366098e-32\n", - "Kc = 1.001390635033791e42\n", - "proton+OC[Pt]<=>CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.532033240545627e-26\n", - "Kc = 4.519134089211336e35\n", - "proton+O=C(C#[Pt])O[Pt]<=>O=C(C=[Pt])O[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.72805599022829e-40\n", - "Kc = 3.2349662103394635e49\n", - "proton+O=C(C#[Pt])O[Pt]<=>CX+CHO2X\n", - "kf = 592078.5871076054\n", - "krev = 5.534590494038509e-27\n", - "Kc = 1.0697784917336755e32\n", - "vacantX+vacantX+CO-2<=>HX+CO[Pt]\n", - "kf = 3.6896065237788656e-26\n", - "krev = 1200.259790503812\n", - "Kc = 3.074006605045183e-29\n", - "proton+COC(=O)[Pt]<=>OCX+CO-2\n", - "kf = 2.5e10\n", - "krev = 1.1176103415271093e-15\n", - "Kc = 2.236915593125226e25\n", - "vacantX+vacantX+CO-2<=>HOX+CH3X\n", - "kf = 4.936438467893006e-16\n", - "krev = 3.4589105625985625e13\n", - "Kc = 1.4271656865809293e-29\n", - "vacantX+vacantX+CO-2<=>HX+OC[Pt]\n", - "kf = 1.1691860289045307e-22\n", - "krev = 1.716447493938648\n", - "Kc = 6.811662069671917e-23\n", - "proton+O=C([Pt])CO<=>OCX+CO-2\n", - "kf = 1.1103452526178925e9\n", - "krev = 6.855829706868127e-14\n", - "Kc = 1.6195636415903908e22\n", - "proton+OCO[Pt]<=>OX+CO-2\n", - "kf = 3.6444391032421975e9\n", - "krev = 2.7729447368992822e-14\n", - "Kc = 1.314284794336516e23\n", - "proton+COO[Pt]<=>OX+CO-2\n", - "kf = 7291.5478906770195\n", - "krev = 8.455002154274134e-64\n", - "Kc = 8.623945633167023e66\n", - "vacantX+CO-2<=>CO.[Pt]\n", - "kf = 484125.61468448705\n", - "krev = 1.055875027717377e7\n", - "Kc = 0.045850654857429916\n", - "vacantX+vacantX+CC=O<=>HX+CC(=O)[Pt]\n", - "kf = 4.3209399543319175e-11\n", - "krev = 0.00036152969853917976\n", - "Kc = 1.1951825733242348e-7\n", - "proton+CC(=O)O[Pt]<=>OX+CC=O\n", - "kf = 0.00037297722687802974\n", - "krev = 6.671936601170958e-13\n", - "Kc = 5.590239373865908e8\n", - "vacantX+vacantX+CC=O<=>CHOX+CH3X\n", - "kf = 6.063283190982672e-6\n", - "krev = 7.026751657908356e14\n", - "Kc = 8.628856527409311e-21\n", - "HX+O=C=C=O<=>O=C=C(O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 7.390785994818602e-44\n", - "Kc = 7.846667531316127e35\n", - "proton+O=C=C=O.[Pt]<=>O=C=C(O)[Pt]\n", - "kf = 5.0e10\n", - "krev = 7.861075064354598e-38\n", - "Kc = 6.360453193828528e47\n", - "proton+O=C=C(O)[Pt]<=>H2O+O=C=C=[Pt]\n", - "kf = 6.924465813920446e7\n", - "krev = 6.633338213957667e-37\n", - "Kc = 1.0438885506169724e44\n", - "vacantX+vacantX+O=C=CO<=>HX+O=C=C(O)[Pt]\n", - "kf = 2.870717564260776e-12\n", - "krev = 0.04083063397663767\n", - "Kc = 7.030793511321262e-11\n", - "proton+O=C=C(O)[Pt]<=>O=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.5662625582691334e-21\n", - "Kc = 7.010140053214033e30\n", - "proton+CH2O2X<=>OC(O)[Pt]\n", - "kf = 138.11636056439383\n", - "krev = 1.1610434185578788\n", - "Kc = 118.95882475777424\n", - "HX+O=CO<=>OC(O)[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 13.299800094987546\n", - "Kc = 2.405334184696311e-9\n", - "proton+OC(O)[Pt]<=>H2O+OC=[Pt]\n", - "kf = 6.447651758284203e9\n", - "krev = 1.3406711668276781e-14\n", - "Kc = 4.809271593078831e23\n", - "proton+CO2HX<=>OC(O)=[Pt]\n", - "kf = 4.281864353491569e-21\n", - "krev = 1.0085447542339753e12\n", - "Kc = 4.245586857217649e-33\n", - "proton+OC(O)=[Pt]<=>H2O+OC#[Pt]\n", - "kf = 88786.03578634068\n", - "krev = 2.3024001185433386e-51\n", - "Kc = 3.856238325878519e55\n", - "proton+OC(O)=[Pt]<=>OC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.201267114803314e-56\n", - "Kc = 3.048309444143688e65\n", - "vacantX+vacantX+OCO<=>HOX+OC[Pt]\n", - "kf = 1.6531073270072772e-12\n", - "krev = 3.4923103786877673e11\n", - "Kc = 4.733563594735331e-24\n", - "vacantX+vacantX+OCO<=>HX+OCO[Pt]\n", - "kf = 1.1281154422531037e-23\n", - "krev = 247.99076044555108\n", - "Kc = 4.549022069315333e-26\n", - "vacantX+vacantX+OCO<=>HX+OC(O)[Pt]\n", - "kf = 1.7561639713628244e-21\n", - "krev = 12.121089565849744\n", - "Kc = 1.4488499254313605e-22\n", - "proton+CC(=O)O[Pt]<=>CC(=O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.1487876512561545e-31\n", - "Kc = 6.025856732491622e40\n", - "vacantX+CC(=O)O<=>CC(=O)O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 181176.0549943608\n", - "Kc = 1.9518809820199483\n", - "proton+O=C(O)C[Pt]<=>CH2X+O=CO\n", - "kf = 2.8308298186665873e-7\n", - "krev = 4.4416030881885286e-10\n", - "Kc = 637.344166612852\n", - "HOX+C=C=O<=>O=C(O)C[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.348252838149528e-29\n", - "Kc = 4.555305278365498e20\n", - "vacantX+vacantX+CC(=O)O<=>HX+O=C(O)C[Pt]\n", - "kf = 1.1112170024966199e-23\n", - "krev = 36323.669871347265\n", - "Kc = 3.059209067895331e-28\n", - "proton+O=C(O)C[Pt]<=>CC(=O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.8362388188925276e-33\n", - "Kc = 4.2835807059629454e42\n", - "proton+O=C(O)C=[Pt]<=>CHX+O=CO\n", - "kf = 2.29560706613987e8\n", - "krev = 1.2779660484176362e-12\n", - "Kc = 1.7962973812819722e20\n", - "proton+O=C(O)C=[Pt]<=>O=C(O)C[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.3911467946667624e-39\n", - "Kc = 1.0455234306718537e49\n", - "proton+O=C(O)C#[Pt]<=>CX+O=CO\n", - "kf = 3.430344707960619e-7\n", - "krev = 6.243805158089141e-10\n", - "Kc = 549.3997043640043\n", - "proton+O=C(O)C#[Pt]<=>O=C(O)C=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.974798474705005e-22\n", - "Kc = 1.2659519601732776e32\n", - "proton+CC(=O)[Pt]<=>CC(O)=[Pt]\n", - "kf = 2.5e10\n", - "krev = 256072.6251484693\n", - "Kc = 97628.55356172944\n", - "vacantX+vacantX+CC(=O)O<=>OX+CC(O)=[Pt]\n", - "kf = 1.1829749543886283e-33\n", - "krev = 3.758913107218073e15\n", - "Kc = 3.1471197142520116e-49\n", - "proton+[Pt]=C=C=[Pt]<=>CX+CHX\n", - "kf = 9.604845727350947e6\n", - "krev = 4.263637187402111e7\n", - "Kc = 0.2252735236415203\n", - "proton+CC(O)([Pt])O[Pt]<=>HOX+CC(O)=[Pt]\n", - "kf = 0.010152527963617899\n", - "krev = 120.24516425575311\n", - "Kc = 8.443190232601934e-5\n", - "proton+CC(O)([Pt])O[Pt]<=>H2O+CC(=[Pt])O[Pt]\n", - "kf = 313070.20677152026\n", - "krev = 6.925505920879168e-13\n", - "Kc = 4.5205391540807046e17\n", - "proton+CC(O)=[Pt]<=>H2O+CC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.933382365919395e-13\n", - "Kc = 2.516766100313717e22\n", - "proton+CC(=[Pt])O[Pt]<=>HOX+CC#[Pt]\n", - "kf = 13217.132617099685\n", - "krev = 2811.7587337436053\n", - "Kc = 4.700663843765235\n", - "vacantX+vacantX+OCCO<=>OC[Pt]+OC[Pt]\n", - "kf = 2.961131444344567e-9\n", - "krev = 1.2992063226984979e13\n", - "Kc = 2.2791849089790384e-22\n", - "proton+COC(=O)[Pt]<=>COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.888135117564328e-25\n", - "Kc = 6.429817700281189e34\n", - "vacantX+COC=O<=>COC=O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.8619443782792543\n", - "Kc = 410274.8449347414\n", - "CHOX+C=O<=>O=COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 7.563806299923095e-5\n", - "Kc = 0.0005236345531927227\n", - "proton+O=COC[Pt]<=>CH2X+O=CO\n", - "kf = 111313.58403871658\n", - "krev = 8.286110635972536e-11\n", - "Kc = 1.343375546489451e15\n", - "vacantX+vacantX+COC=O<=>HX+O=COC[Pt]\n", - "kf = 1.744941649320221e-22\n", - "krev = 505.1321128993354\n", - "Kc = 3.4544262872235156e-25\n", - "proton+O=COC[Pt]<=>COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.135293986229989e-35\n", - "Kc = 7.973733917711833e44\n", - "proton+O=COC=[Pt]<=>CHX+O=CO\n", - "kf = 2.2907256913575046e7\n", - "krev = 2.628907383857028e-39\n", - "Kc = 8.713603626448959e45\n", - "proton+O=COC=[Pt]<=>O=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0389869635026436e-52\n", - "Kc = 2.406189959854717e62\n", - "proton+O=COC#[Pt]<=>CX+O=CO\n", - "kf = 3.475004449141671e9\n", - "krev = 2.1095578217424777e-28\n", - "Kc = 1.647266746294418e37\n", - "proton+O=COC#[Pt]<=>O=COC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.194970384149552e-31\n", - "Kc = 7.824798666061684e40\n", - "proton+[Pt]=C=C=[Pt]<=>[Pt]C=C=[Pt]\n", - "kf = 5.0e10\n", - "krev = 3.4547136706130488e-40\n", - "Kc = 1.4472979461457759e50\n", - "proton+[Pt]C=C=[Pt]<=>CHX+CHX\n", - "kf = 1.3644962633061858e6\n", - "krev = 2.1179373214223165e7\n", - "Kc = 0.06442571503437355\n", - "proton+[Pt]C=C=[Pt]<=>CX+CH2X\n", - "kf = 2.4069361700997183e-9\n", - "krev = 4.168528916469651e10\n", - "Kc = 5.77406614738843e-20\n", - "proton+[Pt]C=C=[Pt]<=>[Pt]=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.1480167012343258e-15\n", - "Kc = 2.1776686674610635e25\n", - "proton+[Pt]=CC=[Pt]<=>CHX+CH2X\n", - "kf = 7.64911197878265e8\n", - "krev = 6969.6990461017285\n", - "Kc = 109748.09569519259\n", - "vacantX+vacantX+C=C<=>CH2X+CH2X\n", - "kf = 9.387035392808428e-46\n", - "krev = 5.259242712872442e15\n", - "Kc = 1.7848644577351152e-61\n" - ] - } - ], - "source": [ - "for (i,rxn) in enumerate(inter.reactions)\n", - " str = getrxnstr(rxn)\n", - " kf = inter.kfs[i]\n", - " krev = inter.krevs[i]\n", - " Kc = kf/krev\n", - " println(str)\n", - " println(\"kf = $kf\")\n", - " println(\"krev = $krev\")\n", - " println(\"Kc = $Kc\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 63, - "id": "dd1b08a5", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(:index, :reactants, :reactantinds, :products, :productinds, :kinetics, :electronchange, :radicalchange, :reversible, :forwardable, :pairs, :fragmentbasedreactants, :fragmentbasedproducts, :fragmentbasedreactantinds, :fragmentbasedproductinds, :comment)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fieldnames(typeof(domaincat.phase.reactions[124]))" - ] - }, - { - "cell_type": "code", - "execution_count": 64, - "id": "09d93523", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "OX+CHX<=>[Pt]OC=[Pt]" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "r = domaincat.phase.reactions[124]" - ] - }, - { - "cell_type": "code", - "execution_count": 65, - "id": "30bd457b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "2-element StaticArraysCore.SVector{2, Species{NASA{EmptyThermoUncertainty}, EmptyDiffusivity, EmptyHenryLawConstant, EmptyLiquidVolumetricMassTransferCoefficient}} with indices SOneTo(2):\n", - " Species{NASA{EmptyThermoUncertainty}, EmptyDiffusivity, EmptyHenryLawConstant, EmptyLiquidVolumetricMassTransferCoefficient}(\"OX\", 6, \"\", \"O=[Pt]\", \"1 O u0 p2 c0 {2,D}\\n\\n2 X u0 p0 c0 {1,D}\\n\\n\", NASA{EmptyThermoUncertainty}\n", - " polys: Array{NASApolynomial}((2,))\n", - " unc: EmptyThermoUncertainty EmptyThermoUncertainty()\n", - ", Dict(\"X\" => 1, \"O\" => 1), 1, EmptyDiffusivity(), 0.0, 0, 0.01599939912557602, EmptyHenryLawConstant(), EmptyLiquidVolumetricMassTransferCoefficient(), \"Thermo library corrected for liquid phase: surfaceThermoPt111 Binding\\nenergy corrected by LSR (1.00O) from Pt111 + Solvation correction with water\\nas solvent and solute estimated using Solute library: water\", false, false)\n", - " Species{NASA{EmptyThermoUncertainty}, EmptyDiffusivity, EmptyHenryLawConstant, EmptyLiquidVolumetricMassTransferCoefficient}(\"CHX\", 29, \"\", \"C#[Pt]\", \"1 C u0 p0 c0 {2,S} {3,T}\\n\\n2 H u0 p0 c0 {1,S}\\n\\n3 X u0 p0 c0 {1,T}\\n\\n\", NASA{EmptyThermoUncertainty}\n", - " polys: Array{NASApolynomial}((2,))\n", - " unc: EmptyThermoUncertainty EmptyThermoUncertainty()\n", - ", Dict(\"X\" => 1, \"C\" => 1, \"H\" => 1), 2, EmptyDiffusivity(), 0.0, 0, 0.013018611469306052, EmptyHenryLawConstant(), EmptyLiquidVolumetricMassTransferCoefficient(), \"Thermo library corrected for liquid phase: surfaceThermoPt111 Binding\\nenergy corrected by LSR (0.75C) from Pt111 + Solvation correction with water\\nas solvent and solute estimated using group(Cs-CsCsCsCs)\", false, false)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "r.reactants" - ] - }, - { - "cell_type": "code", - "execution_count": 66, - "id": "bcbc831e", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.9.1", - "language": "julia", - "name": "julia-1.9" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.9.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/CO2_Reduction_Ag/CO2RR_RMS_3.jl b/CO2_Reduction_Ag/CO2RR_RMS_3.jl new file mode 100644 index 0000000..bc1f723 --- /dev/null +++ b/CO2_Reduction_Ag/CO2RR_RMS_3.jl @@ -0,0 +1,200 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,jl:percent +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.17.2 +# kernelspec: +# display_name: Julia 1.9.1 +# language: julia +# name: julia-1.9 +# --- + +# %% +using DifferentialEquations +using ReactionMechanismSimulator +using PyPlot + +# %% +outdict = readinput("Ag_C2_042925.rms") + +# %% +liqspcs = outdict["gas"]["Species"] +liqrxns = outdict["gas"]["Reactions"] +surfspcs = outdict["surface"]["Species"] +surfrxns = outdict["surface"]["Reactions"] +interfacerxns = outdict[Set(["surface", "gas"])]["Reactions"] +solv = outdict["Solvents"][1]; + +# %% +sitedensity = 2.292e-5; # Ag111 +liq = IdealDiluteSolution(liqspcs,liqrxns,solv,name="liquid",diffusionlimited=true); +surf = IdealSurface(surfspcs,surfrxns,sitedensity,name="surface"); + +# %% +# Reservoir is a 100 mL (100e-6 m^3) cell +# Proton concentration is 10^-7 mol/L (10^-4 mol/m^3) +# CO2 concentration is 0.01 mol/L (10 mol/m^3), saturation solubility ~0.03 mol/L +# Solvent concentration (water) is 55.6 mol/L (5.56e4 mol/m^3) +# AVratio in experiments is 36 m^-1 but is measured by surface area/reservoir volume +# Area of the electrode is therefore 3.6e1 m^-1 * 1e2*1e-6 m^3 = 3.6e-3 m^2 = 36 cm^2 +# Assume boundary layer thickness d_bl = 1 mm or 1e-3 m +# Volume of the boundary layer V_bl = 3.6e-3 m^2 * 1e-3 m = 3.6e-6 m^3 +# Actual AVratio is therefore 3.6e-3 m^2 / 3.6e-6 m^3 = 1e3 m^-1 (reciprocal of d_bl) +# Amount of sites is 2.292e-5 mol/m^2 * 1e3 m^-1 = 2.292e-2 mol/m^-3 + +C_proton = 1.0e-7*1.0e3; +C_co2 = 1.0e-2*1.0e3; +C_h2o = 5.56e4; +C_default = 1e-12; +V_res = 1.0e3; +AVratio = 1.0e3; +A_surf = V_res*36; +V_bl = A_surf/AVratio; +sites = sitedensity*A_surf; + +initialcondsliq = Dict(["proton"=>C_proton * V_res, + "CO2"=>C_co2 * V_res, + "H2O"=>C_h2o * V_res, + "V"=>V_res,"T"=>300,"Phi"=>0.0,"d"=>0.0]); + +initialcondssurf = Dict(["CO2X"=>0.4*sites, + "CHO2X"=>0.1*sites, + "CO2HX"=>0.1*sites, + "OX"=>0.1*sites, + "OCX"=>0.1*sites, + "vacantX"=>0.1*sites, + "CH2O2X"=>0.05*sites, + "CHOX"=>0.04*sites, + "CH2OX"=>0.01*sites, + "A"=>A_surf,"T"=>300,"Phi"=>-1.414]); + +# %% +domainliq,y0liq,pliq = ConstantTVDomain(phase=liq, + initialconds=initialcondsliq,constantspecies=["proton","CO2","H2O"]); +domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf, + initialconds=initialcondssurf); + +# %% +inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainliq, + domaincat,interfacerxns,298.15,A_surf); + +# %% +@time react,y0,p = Reactor((domainliq,domaincat), (y0liq,y0cat), (0.0, 1.8e3), [inter], (pliq,pcat,pinter)); + + +# %% +@time sol = solve(react.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-22,reltol=1e-8); +println(sol.t[end]); +println(sol.retcode); + +# %% +ssys = SystemSimulation(sol,(domainliq,domaincat,),(inter,),p); + +# %% +# Helper function +function plotX(sim, tol, t_end, exclude) + clf() + xs = molefractions(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Mole Fraction") +end + +# %% +# Helper function +function plotC(sim, tol, t_end, exclude) + clf() + xs = concentrations(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Concentration") +end + +# %% +exclude_species = ["H2O"] +plotX(ssys.sims[1], 1e-10, 1.8e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-8, 2e3) +ylim(1e-12, 1e-2) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V") +gcf() + +# %% +exclude_species = ["H2O"] +plotC(ssys.sims[1], 1e-5, 1.8e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-8, 2e3) +ylim(1e-6, 1e2) +title("Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys.sims[2], 1e-2, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e3) +ylim(1e-6, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V") +gcf() + +# %% +getfluxdiagram(ssys,1.8e3;speciesratetolerance=1e-6) + +# %% +println(ssys.names) + +# %% +for (i,rxn) in enumerate(inter.reactions) + str = getrxnstr(rxn) + kf = inter.kfs[i] + krev = inter.krevs[i] + Kc = kf/krev + println(str) + println("kf = $kf") + println("krev = $krev") + println("Kc = $Kc") +end + +# %% +fieldnames(typeof(domaincat.phase.reactions[124])) + +# %% +r = domaincat.phase.reactions[124] + +# %% +r.reactants + +# %% diff --git a/CO2_Reduction_Ag/CO2RR_RMS_4.ipynb b/CO2_Reduction_Ag/CO2RR_RMS_4.ipynb deleted file mode 100644 index d7395fd..0000000 --- a/CO2_Reduction_Ag/CO2RR_RMS_4.ipynb +++ /dev/null @@ -1,875 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 52, - "id": "8a590634", - "metadata": {}, - "outputs": [], - "source": [ - "using ReactionMechanismSimulator\n", - "using PyPlot\n", - "using DifferentialEquations\n", - "using Sundials\n", - "using SciMLBase\n", - "using QuadGK" - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "id": "e941d4fb", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[13:13:23] WARNING: not removing hydrogen atom without neighbors\n", - "[13:13:23] WARNING: not removing hydrogen atom without neighbors\n", - "┌ Warning: failed to generate StokesDiffusivity model for species vacantX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2O2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species H2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(C[Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]COO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(=[Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC([Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C([Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH3X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [H][H].[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(C=[Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(C#[Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]=C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)([Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=[Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]C#CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]OC#CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n" - ] - }, - { - "data": { - "text/plain": [ - "Dict{Any, Any} with 4 entries:\n", - " \"Solvents\" => Solvent[Solvent(\"water\", RiedelViscosity{Float64}(…\n", - " Set([\"surface\", \"gas\"]) => Dict{Any, Any}(\"Reactions\"=>ElementaryReaction[vac…\n", - " \"gas\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…\n", - " \"surface\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "outdict = readinput(\"Ag_C2_042925.rms\")" - ] - }, - { - "cell_type": "code", - "execution_count": 54, - "id": "fe2767e9", - "metadata": {}, - "outputs": [], - "source": [ - "liqspcs = outdict[\"gas\"][\"Species\"]\n", - "liqrxns = outdict[\"gas\"][\"Reactions\"]\n", - "surfspcs = outdict[\"surface\"][\"Species\"]\n", - "surfrxns = outdict[\"surface\"][\"Reactions\"]\n", - "interfacerxns = outdict[Set([\"surface\", \"gas\"])][\"Reactions\"]\n", - "solv = outdict[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 55, - "id": "c54ee65e", - "metadata": {}, - "outputs": [], - "source": [ - "sitedensity = 2.292e-5; # Ag111\n", - "liq = IdealDiluteSolution(liqspcs,liqrxns,solv,name=\"liquid\",diffusionlimited=true);\n", - "surf = IdealSurface(surfspcs,surfrxns,sitedensity,name=\"surface\");" - ] - }, - { - "cell_type": "code", - "execution_count": 56, - "id": "8894c84d", - "metadata": {}, - "outputs": [], - "source": [ - "# Reservoir is a 100 mL (100e-6 m^3) cell\n", - "# Proton concentration is 10^-7 mol/L (10^-4 mol/m^3)\n", - "# CO2 concentration is 0.01 mol/L (10 mol/m^3), saturation solubility ~0.03 mol/L\n", - "# Solvent concentration (water) is 55.6 mol/L (5.56e4 mol/m^3)\n", - "# AVratio in experiments is 36 m^-1 but is measured by surface area/reservoir volume\n", - "# Area of the electrode is therefore 3.6e1 m^-1 * 1e2*1e-6 m^3 = 3.6e-3 m^2 = 36 cm^2\n", - "# Assume boundary layer thickness d_bl = 1 mm or 1e-3 m\n", - "# Volume of the boundary layer V_bl = 3.6e-3 m^2 * 1e-3 m = 3.6e-6 m^3\n", - "# Actual AVratio is therefore 3.6e-3 m^2 / 3.6e-6 m^3 = 1e3 m^-1 (reciprocal of d_bl)\n", - "# Amount of sites is 2.292e-5 mol/m^2 * 1e3 m^-1 = 2.292e-2 mol/m^-3\n", - "\n", - "C_proton = 1.0e-7*1.0e3;\n", - "C_co2 = 1.0e-2*1.0e3;\n", - "C_h2o = 5.56e4;\n", - "C_default = 1e-12;\n", - "V_res = 1.0e3;\n", - "AVratio = 1.0e3;\n", - "A_surf = V_res*36;\n", - "V_bl = V_res;\n", - "sites = sitedensity*A_surf;\n", - "\n", - "initialcondsliq = Dict([\"proton\"=>C_proton * V_res,\n", - " \"CO2\"=>C_co2 * V_res,\n", - " \"H2O\"=>C_h2o * V_res,\n", - " \"V\"=>V_res,\"T\"=>300,\"Phi\"=>0.0,\"d\"=>0.0]);\n", - "\n", - "initialcondssurf = Dict([\"CO2X\"=>0.4*sites,\n", - " # \"CHO2X\"=>0.1*sites,\n", - " # \"CO2HX\"=>0.1*sites,\n", - " # \"OX\"=>0.1*sites,\n", - " # \"OCX\"=>0.1*sites,\n", - " \"vacantX\"=>0.6*sites,\n", - " # \"CH2O2X\"=>0.05*sites,\n", - " # \"CHOX\"=>0.04*sites,\n", - " # \"CH2OX\"=>0.01*sites,\n", - " \"A\"=>A_surf,\"T\"=>300,\"Phi\"=>-1.414]);" - ] - }, - { - "cell_type": "code", - "execution_count": 57, - "id": "ddb39b3d", - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "domainliq,y0liq,pliq = ConstantTVDomain(phase=liq,\n", - " initialconds=initialcondsliq,constantspecies=[\"proton\",\"CO2\",\"H2O\"]);\n", - "domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf,\n", - " initialconds=initialcondssurf);" - ] - }, - { - "cell_type": "code", - "execution_count": 58, - "id": "ed49d2b4", - "metadata": {}, - "outputs": [], - "source": [ - "inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainliq,\n", - " domaincat,interfacerxns,298.15,A_surf);" - ] - }, - { - "cell_type": "code", - "execution_count": 59, - "id": "244f0912", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.003364 seconds (8.83 k allocations: 7.921 MiB)\n" - ] - } - ], - "source": [ - "@time react,y0,p = Reactor((domainliq,domaincat), (y0liq,y0cat), (0.0, 1.0e3), [inter], (pliq,pcat,pinter));\n" - ] - }, - { - "cell_type": "code", - "execution_count": 60, - "id": "962f838c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.324096 seconds (893.95 k allocations: 518.367 MiB, 19.53% gc time)\n", - "1000.0\n", - "Success\n" - ] - } - ], - "source": [ - "@time sol = solve(react.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-22,reltol=1e-8);\n", - "println(sol.t[end]);\n", - "println(sol.retcode);" - ] - }, - { - "cell_type": "code", - "execution_count": 61, - "id": "6667bb5a", - "metadata": {}, - "outputs": [], - "source": [ - "ssys = SystemSimulation(sol,(domainliq,domaincat,),(inter,),p);" - ] - }, - { - "cell_type": "code", - "execution_count": 62, - "id": "87dcaf99", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotX (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotX(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = molefractions(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Mole Fraction\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 63, - "id": "ddf6da6b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotC (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotC(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = concentrations(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Concentration\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 64, - "id": "e719a85d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys.sims[1], 1e-10, 1.8e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-8, 2e3)\n", - "ylim(1e-12, 1e-2)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 75, - "id": "1ef78267", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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dnepaw4YNU1ZWVioiIiLDWPPivmUkNjZW2dvbq0aNGum39e3bV2k0Gv2PEaX+d6969OiR6vhjx44poEAldUeOHFG2trYqPDxcv23ZsmWqbNmyytzcXLVq1Up99913+s9KYmKicnV1fe4P1ReJN8WaNWvU9OnT1fbt29W+ffvU119/rZycnJSLi4u6d+9eqrIp78uNGzfqt128ePG532sZeWmaX9esWcOpU6dS/Ttx4oR+f7FixejUqRM//vgjOp0OgMjISP7880/69OmDmdmT7of79u3D1tY2TZNSStNLVpqsctu+ffto1aoVbm5uaWJ6/Phxmqatzp07p3rs5eUFkKoJ6FmxsbGcOHGCbt26UaRIEf12U1NTevfuzb1797LchJsb9u/fT/Xq1alVq1aq7b169cq1a8TGxnLq1CnefPPNVJ1s7ezs6NSpU6qyOp2O5ORk/T+tVptqf0axxsTEcPbs2VTbs3J/QkJCGDRoEG5ubpiZmWFubo6HhwcAV65c0Zdr0KABq1evZtq0aRw/fpykpKRU5z569CgRERH07ds3Vfw6nY527dpx6tQpYmNjs/R6Pc+1a9e4f/8+vXv3TtW8UaRIEd566y2OHz/O48ePn/taxMfHExISAjxp1gMYOnRohtfdtWsXycnJ9OnTJ9VztLKyokWLFmlGsGo0mjT318vLK9PPR3reeuutNNsePXrE2LFjqVChAmZmZpiZmVGkSBFiY2NT3bfs2LdvH0CaLgZvv/02tra2ab6Tateujbu7u/6xlZUVlSpVSvX8GjRowI4dOxg3bhwHDhwgLi4uS7G8++67WFpapurCsHbtWhISEnj//fdTnT+z92V+cnV1xdvbW//YyckJZ2dnateuTalSpfTbq1atCvzvcxgfH8/evXt54403sLGxSfXe6tChA/Hx8Rw/fjzD6+bFfcvI+vXriYmJSdWU179/f5RSqZr+jh8/TkJCAt27d091fKNGjQrciOvNmzfTrVs3nJycgCfdOoYPH06/fv3YvXs3zZo14+OPP9aXNzc3p127dvrXXSmV6p4lJyfnWmy9e/fm888/p3379vj4+DB27Fh27NhBaGgos2fPTlW2e/fu2NnZpWpK/+GHH9BoNKk+M1n10iR1VatWpV69eqn+Pf1Bhidv8sDAQPz8/ID/fRk9/aELDw+nZMmSaYZZOzs7Y2ZmRnh4eJ4/l2eFh4enO6Ir5Qvp2ZiKFSuW6rGlpSVApl/ckZGRKKWydZ28lHIfnpXetpyKjIxEp9Nl6Tr9+/fH3Nxc/+/ZASKZnSO790en09GmTRs2btzIZ599xt69ezl58qT+D8jT93HdunX07duX7777jsaNG+Pk5ESfPn0IDg4GnkxFAk/6vT0dv7m5ObNmzUIpRURERIavkbu7O6GhoVlK/FKeZ0bvIZ1Ol2aU7PNei9DQUExNTTO97ynPsX79+mme47p169L0Q7SxsUkzUs7S0pL4+PjnPsenpfc8e/XqxZIlSxgwYAC7du3i5MmTnDp1ihIlSmQ5cXpWeHg4ZmZmaTpTazQaSpYs+dz3Fzx5fk9f/5tvvmHs2LFs3rwZHx8fnJyc6Nq163Onp3FycqJz586sWbNG/8Nm9erVNGjQgOrVq+vLPe99mZ9SkoKnWVhYpNluYWEBoH8fhIeHk5yczOLFi9O8rzp06ACQ5r31tLy4bxn5/vvvsbKyol27dkRFRREVFYWXlxeenp6sXr1af69Sruni4pLmHOltM6Tr16/rf/ACrFixgn79+jFx4kRatmzJpEmT6NGjR6pjXFxc9AMgfvzxxzT3LS81aNCASpUqpUn0bWxs6NmzJzt37iQ4OJjk5GR+/vlnWrRokaNBUS/N6NesaNu2LaVKlWLVqlW0bduWVatW0bBhw1QjrIoVK8aJEydQSqVK7EJCQkhOTs5wpAug/0Px7ICKzD74WVGsWDGCgoLSbL9//z5ApjFllaOjIyYmJnl+nawqVqxYun8A0ttmZWWV7iCWsLCwTGN2dHREo9Fk6TqTJ09m2LBh+sd2dnbPjStlW3pf1pm5ePEi//zzD6tXr6Zv37767f7+/mnKFi9enIULF7Jw4ULu3LnDli1bGDduHCEhIezcuVP//BcvXpzhyN/Mvszbtm3L7t27+euvv+jZs2emcac8z4zeQyYmJjg6OmZ6jmeVKFECrVZLcHBwhlNVpDzHP/74Q1+bmR+e/eEXHR3N1q1bmTRpEuPGjdNvT0hIyDRxfp5ixYqRnJxMaGhoqgRBKUVwcDD169fP9jltbW2ZMmUKU6ZM4cGDB/pau06dOulHmGbk/fff5/fff8fPzw93d3dOnTrFsmXLUpV53vvSGDg6OupbKjKqKS5btmyGx+fFfUvP9evXOXLkCECqmr6n7dq1iw4dOug/oyk/hJ4WHBxcoGrrkpKSUv34CggIoGPHjqnK1K9fX18zB0/mn0tp0erUqROnTp3Kn2D/n1Iq3UEYH3zwAd9++y1r1qyhUqVKhISEMG/evBxd46WpqcuKlA/o5s2bOXz4MKdPn04z8qRVq1Y8evQozWS6a9as0e/PSMoH4t9//021/dlRepD1X2Ap19y3b58+uXo6Jhsbm1yZpsPW1paGDRuycePGVHHpdDp+/vlnypQpQ6VKlV74Olnl4+PDpUuX+Oeff1Jt//XXX9OU9fT0TPOaX79+/bnNxba2tjRo0ICNGzemqqV5+PBhmjmZPD09U9UCPzsvX0ax2tnZUbdu3UzjeFZKspBSa5VixYoVmR7n7u7OsGHDaN26tb7Jt2nTpjg4OHD58uU0Ndkp/1JqKNLzwQcfULJkST777DMCAwPTLbNx40YAKleuTOnSpfn1119RSun3x8bGsmHDBv2I2Oxo3749QJqk4Wlt27bFzMyM//77L8PnmF1Zqd1+lkajQSmV5r599913aZrrs3P+lO+cn3/+OdX2DRs2EBsb+8LTCrm4uNCvXz/eeecdrl27lqaJ/Flt2rShdOnSrFq1ilWrVmFlZcU777yTYfn03pfGwMbGBh8fH86dO4eXl1e676vMfrDl9X1LkTIa+dtvv2X//v2p/m3fvh1zc3N901/Dhg2xtLRk3bp1qc5x/PjxbHc/yGvu7u5cv35d/9jFxSXNzBIBAQH6/0dERLBlyxbatm0LPEmqX/R7IDuOHz/OjRs30v173LBhQ2rUqKH/zBQtWjTd7htZ8dLU1F28eDHdNvPy5cun+pXUv39/Zs2aRa9evbC2tk5TfdunTx98fX3p27cvt27dombNmhw5coQZM2bQoUMHXnvttQxjqF+/PpUrV2b06NEkJyfj6OjIpk2b9L+inlazZk02btzIsmXL8Pb2xsTEJMM33aRJk9i6dSs+Pj5MnDgRJycnfvnlF7Zt28bs2bNTTX74ImbOnEnr1q3x8fFh9OjRWFhYsHTpUi5evMjatWtfaObvCxcupDufWf369dOtXRkxYgQ//PADr7/+OtOmTcPFxYVffvkl3VqE3r1789577zFkyBDeeustbt++zezZs7M0989XX31Fu3btaN26NaNGjUKr1TJr1ixsbW2zVbtSqlQpOnfuzOTJk3F1deXnn3/Gz8+PWbNmZTuRqVKlCuXLl2fcuHEopXBycuKvv/7SdxtIER0djY+PD7169aJKlSrY2dlx6tQpdu7cqZ+ip0iRIixevJi+ffsSERFBt27dcHZ2JjQ0lH/++YfQ0NBME6aiRYvy559/0rFjR+rUqZNq8uEbN27w888/888///Dmm29iYmLC7Nmzeffdd+nYsSMDBw4kISGBOXPmEBUVxddff52t1wGgWbNm9O7dm2nTpvHgwQM6duyIpaUl586dw8bGhuHDh+Pp6cnUqVP54osvuHnzJu3atcPR0ZEHDx5w8uRJfa1UdtjZ2eHh4cGff/5Jq1atcHJyonjx4pnWZNjb29O8eXPmzJmjL3vw4EG+//57HBwcUpVNmbNq5cqV2NnZYWVlRdmyZdNNElq3bk3btm0ZO3YsMTExNG3alH///ZdJkyZRp06dbE1cmqJhw4Z07NgRLy8vHB0duXLlCj/99FOWEm9TU1P69OnD/Pnzsbe3580330z1HZSV9yXA1KlTmTp1Knv37qVFixbZfg75YdGiRbzyyis0a9aMwYMH4+npycOHD/H39+evv/5KVUv0rLy4b89KTk5mzZo1VK1alQEDBqRbplOnTmzZskVfYzhy5EhmzpyJo6Mjb7zxBvfu3WPKlCm4urqmqWU6ffq0PpGKiYlBKaX/Hn/2uztl+82bN/XHpvTPfrqP+u3bt/U1aP/991+qY1N+PMOTHw8jRoxg9uzZWFhY0L17d8aNG0ezZs1o1qwZf//9NytWrMDBwYFjx44xfPhwXnvttSy/l7Iab6tWrTh48GCq/KJWrVq89957VK1aFSsrK06ePMmcOXP0P4DT079/f0aOHMm1a9cYOHBgzucPzPbQCiOT2ehXQH377bdpjmnSpIkC1LvvvpvuOcPDw9WgQYOUq6urMjMzUx4eHmr8+PGphqArlf6oy+vXr6s2bdooe3t7VaJECTV8+HC1bdu2NCPdIiIiVLdu3ZSDg4PSaDSpRgCRzqi7CxcuqE6dOqmiRYsqCwsLVatWrTSjdVJGV/7++++ptqc36jMjhw8fVq+++qqytbVV1tbWqlGjRuqvv/5K93zZGf2a0b+UmNJ7LS9fvqxat26trKyslJOTk/rggw/Un3/+mea11Ol0avbs2apcuXLKyspK1atXT+3bty9Lo1+VUmrLli3Ky8tLWVhYKHd3d/X111/rRzhmhYeHh3r99dfVH3/8oapXr64sLCyUp6enmj9/fqpy2bk/Kc/dzs5OOTo6qrffflvduXMn1XsjPj5eDRo0SHl5eSl7e3tlbW2tKleurCZNmqQfcZvi4MGD6vXXX1dOTk7K3NxclS5dWr3++utpYslIcHCwGjt2rKpevbqysbFRlpaWqkKFCmrgwIHqwoULqcpu3rxZNWzYUFlZWSlbW1vVqlUr9ffff6cqk/L6pkzzkSK9EYxarVYtWLBA1ahRQ1lYWKiiRYuqxo0bp3lfbt68Wfn4+Ch7e3tlaWmpPDw8VLdu3VKNhuvbt6+ytbVN8/zSu9979uxRderUUZaWlgrQvz8zil0ppe7du6feeust5ejoqOzs7FS7du3UxYsX031/L1y4UJUtW1aZmpqmuv/Pjn5V6slIyLFjxyoPDw9lbm6uXF1d1eDBg1VkZGSqcinvxWc9+1kYN26cqlevnnJ0dFSWlpaqXLly6tNPP1VhYWFpjk3P9evX9Z9hPz+/VPuy+r5MeR3TGwGckZyMfq1evXqashm9ToAaOnRoqm0BAQGqf//+qnTp0src3FyVKFFCNWnSRE2bNu258eb2fXvW5s2bFaAWLlyYYZmUUbjz5s1TSj35vpw2bZoqU6aMsrCwUF5eXmrr1q2qVq1a6o033kh1bMpo8cy+u1Nk9j3/tMz+Zj/9GUlKSlKVKlXSTx2TnJysBg4cqP976erqqqZOnaoAVbRoUTV+/HiVkJCQ4evwrKzGmzKC+mk9e/ZUFSpUULa2tsrc3Fx5eHioQYMGqfv372d4vdDQUGVhYaEAdfLkySzH+SzN/wcvRKFw4MABfHx82L9/f54s35QTnp6e1KhRg61btxo6FCGEyLaAgACqVKnCpEmT+Pzzzw0djt7Ro0d57bXXmDFjhn5JzaioKO7fv0/FihVJSEggKCiIcuXKYWpqathg88lL0/wqhBBCiMz9888/rF27liZNmmBvb8+1a9eYPXs29vb2+hUQCoomTZrw559/0rNnT/744w+GDRtG06ZNKVeuHJGRkZw/f55ffvmFCxcu8Pfff7/QkmjGotAPlLh79y4tW7akWrVqeHl58fvvvxs6JCGEEKJAsrW15fTp03zwwQe0bt2aL774gjp16nDkyJECN60JPOmbeOXKFRo2bMioUaNwd3fH2toaFxcX3nnnHaysrPjjjz9eioQOoNA3vwYFBfHgwQNq165NSEgIdevW5dq1a9ja2ho6NCGEEELkosDAQMLDw7G3t8fDw+OFBvAZo0Kf1D3Ly8uLbdu2pVl9QQghhBDCmBX45tdDhw7RqVMnSpUqhUajSTM/HMDSpUspW7YsVlZWeHt7c/jw4XTPdfr0aXQ6nSR0QgghhCh0CnxSFxsbS61atViyZEm6+9etW8eIESP44osvOHfuHM2aNaN9+/bcuXMnVbnw8HD69OnDypUr8yNsIYQQQoh8ZVTNrxqNhk2bNtG1a1f9toYNG1K3bt1UE6RWrVqVrl27MnPmTODJMjytW7fmww8/fO6EjgkJCamWlNLpdERERFCsWLGXrm1eCCGEEDmnlOLhw4eUKlUq3SXCcptRT2mSmJjImTNnUq2jCE9mmj569Cjw5AXt168fr776apZm6J45c2a2Z5cXQgghhMjI3bt3KVOmTJ5fx6iTurCwMLRabZph1i4uLvrF0v/++2/WrVuHl5eXvj/eTz/9RM2aNdM95/jx4xk5cqT+cXR0NO7u7ty9exd7e/u8eSJCCCGEKHRiYmJwc3PDzs4uX65n1EldimebRZVS+m2vvPIKOp0uy+eytLRMs+A2PFm3UZI6IYQQQmRXfnXfKvADJTJTvHhxTE1N9bVyKUJCQl54kkRfX1+qVatG/fr1X+g8QgghhBD5waiTOgsLC7y9vfHz80u13c/PjyZNmrzQuYcOHcrly5c5derUC51HCCGEECI/FPjm10ePHuHv769/HBAQwPnz53FycsLd3Z2RI0fSu3dv6tWrR+PGjVm5ciV37txh0KBBL3RdX19ffH190Wq1L/oUhBBCCCHyXIGf0uTAgQP4+Pik2d63b19Wr14NPJl8ePbs2QQFBVGjRg0WLFhA8+bNc+X6MTExFC1alOjoaOlTJ4QQQogsy+8cosAndYYmSZ0QQgghciK/cwij7lOXl2SghBBCCCGMidTUPYfU1AkhhBAiJ6SmTgghhBBCZJskdRmQ5lchhBBCGBNpfn0OaX4VQgghRE5I86sQQgghhMg2SeqEEEIIIQoBSeoyIH3qhBBCCGFMpE/dc0ifOiGEEELkhPSpE0IIIYQQ2SZJnRBCCCFEISBJXQakT50QQgghjIn0qXsO6VMnhBBCiJyQPnVCCCGEECLbJKkTQgghhCgEJKkTQgghhCgEJKkTQgghhCgEJKnLgIx+FUIIIYQxkdGvzyGjX4UQQgiREzL6VQghhBBCZJskdUIIIYQQhYAkdUIIIYQQhYAkdUIIIYQQhYAkdUIIIYQQhYAkdUIIIYQQhYAkdUIIIYQQhYAkdRmQyYeFEEIIYUxk8uHnkMmHhRBCCJETMvmwEEIIIYTINknqhBBCCCEKAUnqhBBCCCEKAUnqhBBCCCEKAUnqhBBCCCEKAUnqhBBCCCEKgZciqXvjjTdwdHSkW7duhg5FCCGEECJPvBRJ3ccff8yaNWsMHYYQQgghRJ55KZI6Hx8f7OzsDB2GEEIIIUSeKfBJ3aFDh+jUqROlSpVCo9GwefPmNGWWLl1K2bJlsbKywtvbm8OHD+d/oEIIIYQQBlTgk7rY2Fhq1arFkiVL0t2/bt06RowYwRdffMG5c+do1qwZ7du3586dO/kcqRBCCCGE4ZgZOoDnad++Pe3bt89w//z58/nggw8YMGAAAAsXLmTXrl0sW7aMmTNnZvt6CQkJJCQk6B/HxMQAUGvKbkwsbbJ9PiGEEEK8nHQJj/P1egU+qctMYmIiZ86cYdy4cam2t2nThqNHj+bonDNnzmTKlClptmt1CqVTOTqnEEIIIV4+unzOG4w6qQsLC0Or1eLi4pJqu4uLC8HBwfrHbdu25ezZs8TGxlKmTBk2bdpE/fr10z3n+PHjGTlypP5xTEwMbm5u7B/VAjt7+7x5IkIIIYQodB7GxFBhYf5dz6iTuhQajSbVY6VUqm27du3K8rksLS2xtLTE19cXX19ftFotACXsrbC3t8qdgIUQQghR6FmRmK/XK/ADJTJTvHhxTE1NU9XKAYSEhKSpvcuuoUOHcvnyZU6dOvVC5xFCCCGEyA9GndRZWFjg7e2Nn59fqu1+fn40adLEQFEJIYQQQuS/At/8+ujRI/z9/fWPAwICOH/+PE5OTri7uzNy5Eh69+5NvXr1aNy4MStXruTOnTsMGjToha77bPOrEEIIIURBplFKFeghnQcOHMDHxyfN9r59+7J69WrgyeTDs2fPJigoiBo1arBgwQKaN2+eK9ePiYmhaNGiREdHYy8DJYQQQgiRRfmdQxT4pM5Qnq6pu379uiR1QgghhMgWSeoKGKmpE0IIIURO5HcOYdQDJYQQQgghxBOS1AkhhBBCFAKS1GXA19eXatWqZbjyhBBCCCFEQSJ96p5D+tQJIYQQIiekT50QQgghhMg2SeoyIM2vQgghhDAm0vz6HNL8KoQQQoickOZXIYQQQgiRbZLUCSGEEEIUApLUCSGEEEIUApLUZUAGSgghhBDCmMhAieeQgRJCCCGEyAkZKCGEEEIIIbJNkjohhBBCiEJAkjohhBBCiEJAkjohhBBCiEJAkroMyOhXIYQQQhgTGf36HDL6VQghhBA5IaNfhRBCCCFEtklSJ4QQQghRCEhSJ4QQQghRCEhSJ4QQQghRCEhSJ4QQQghRCEhSJ4QQQghRCEhSlwGZp04IIYQQxkTmqXsOmadOCCGEEDkh89QJIYQQQohsk6ROCCGEEKIQkKROCCGEEKIQkKROCCGEECKX3Yi8wfC9w/P1mmb5ejUhhBBCiEIsOiGaJeeWsP76epIeJ+XrtSWpE0IIIYR4QVqdlg03NvDNuW+ITogGwMfNhytcybcYJKkTQgghhHgB/4T+w4wTM7gcfhmAio4VGVd/HFVsq7CUpfkWx0vRp27r1q1UrlyZihUr8t133xk6HCGEEEIUAhHxEUz8eyLvbX+Py+GXsTO3Y3yD8azvuJ4Grg3yPZ5CX1OXnJzMyJEj2b9/P/b29tStW5c333wTJycnQ4cmhBBCCCOk1WlZf309i88t5mHiQwC6VujKiLojKGZdzGBxFfqk7uTJk1SvXp3SpUsD0KFDB3bt2sU777xj4MiEEEIIYWzOhZxjxokZXI24CkBVp6p83vBzajvXNmxgGEHz66FDh+jUqROlSpVCo9GwefPmNGWWLl1K2bJlsbKywtvbm8OHD+v33b9/X5/QAZQpU4bAwMD8CF0IIYQQhUR4XDhfHPmCPjv6cDXiKnYWdnzR8AvWvr62QCR0YARJXWxsLLVq1WLJkiXp7l+3bh0jRozgiy++4Ny5czRr1oz27dtz584dANJb2laj0eRpzEIIIYQoHJRSbLyxkc6bO7Plvy0AvFnxTba+sZWeVXpiamJq4Aj/p8A3v7Zv35727dtnuH/+/Pl88MEHDBgwAICFCxeya9culi1bxsyZMyldunSqmrl79+7RsGHDDM+XkJBAQkKC/nFMTEwuPAshhBBCGJubUTeZenwqZx6cAaCyY2UmNJ5ArRK1DBxZ+gp8TV1mEhMTOXPmDG3atEm1vU2bNhw9ehSABg0acPHiRQIDA3n48CHbt2+nbdu2GZ5z5syZFC1aVP/Pzc0tT5+DEEIIIQqWBG0Cvud9eeuvtzjz4AzWZtaMrjea3zr+VmATOjCCmrrMhIWFodVqcXFxSbXdxcWF4OBgAMzMzJg3bx4+Pj7odDo+++wzihXLeGTK+PHjGTlypP5xTEyMJHZCCCHES+Jk0Em+Ov4Vt2JuAdCsdDO+aPQFpYuUzvzAAsCok7oUz/aRU0ql2ta5c2c6d+6cpXNZWlpiaWmJr68vvr6+aLXaXI1VCCGEEAVPZHwkc0/P1febK25dnHENxtHGo43R9MU36qSuePHimJqa6mvlUoSEhKSpvcuuoUOHMnToUGJiYihatOgLnUsIIYQQBZNSil23djHjxAwiEyLRoKF75e58UvcT7CzsDB1ethh1nzoLCwu8vb3x8/NLtd3Pz48mTZq80Ll9fX2pVq0a9evXf6HzCCGEEKJgCn0cyoj9IxhzaAyRCZFUcKjAmvZr+LLRl0aX0IER1NQ9evQIf39//eOAgADOnz+Pk5MT7u7ujBw5kt69e1OvXj0aN27MypUruXPnDoMGDXqh60pNnRBCCFE4KaX46+ZfzDo5i5jEGMw0Znzk9REDag7A3NTc0OHlWIFP6k6fPo2Pj4/+ccoghr59+7J69Wp69OhBeHg4U6dOJSgoiBo1arB9+3Y8PDwMFbIQQgghCqjg2GCmHJvCkcAjAFQrVo2pTaZS2amygSN7cRqV3uy8ItVAievXrxMdHY29vb2hwxJCCCFEDiil2HBjA3NPzyU2KRYLEwsG1x5Mv+r9MDPJmzqulNa+/MohJKl7jvy+IUIIIYTIXUGPgphwdAIngk4A4FXCi6+afEU5h3J5et38ziEKfPOrEEIIIUROKKXY8t8Wvj75NY+SHmFlasXwOsN5t+q7BWp5r9wiSV0GZJ46IYQQwnhFxEcw9dhU9t7ZC0CtErWY/sp0POwLb597aX59Dml+FUIIIYzLwbsHmXR0EuHx4ZiZmDG09tA87TuXEWl+FUIIIYTIgdikWOacmsOGGxsAqOBQgZnNZlLFqYqBI8sfktQJIYQQwuidfXCWz498TuCjQDRo6FOtD8PrDsfS1NLQoeUbSeoyIH3qhBBCiIIvSZfEsvPL+O7CdygUpWxLMe2VadQv+fKtCCV96p5D+tQJIYQQBVPgo0DGHhrLP6H/ANClfBfGNRhHEYsiBo7sCelTJ4QQQgjxHDsCdjD12FQeJT3CztyOiU0m0s6znaHDMihJ6oQQQghhNB4nPWbmyZls9t8MPJmqZFbzWZQuUtqwgRUAktQJIYQQwihcDr/M2ENjuRVzCxONCR/W/JBBtQbl+1QlBZW8ChmQgRJCCCFEwaBTOn6+/DMLzi4gWZeMi40LM5vNfCkHQ2RGBko8hwyUEEIIIQwnOiGaL458wcF7BwFo5d6KKU2mUNSyqIEjez4ZKCGEEEIIAVwMu8ioA6O4H3sfCxMLPqv/Gd0rd0ej0Rg6tAJJkjohhBBCFChKKdZeXcuc03NI1iXjZufGvBbzqFqsqqFDK9AkqRNCCCFEgRGbFMuko5PYdWsX8KS59aumX2FnYWfgyAo+SeqEEEIIUSBci7jG6IOjuRVzCzONGSPrjeS9qu9Jc2sWSVKXARn9KoQQQuSfTTc2Mf3EdBK0CbjYuDC3xVxqO9c2dFhGRUa/PoeMfhVCCCHyTqI2kRknZrDhxgYAmpZuysxXZuJo5WjgyF6cjH4VQgghxEshODaYkQdGciHsAiYaE4bWHsqAmgMw0ZgYOjSjJEmdEEIIIfLd6eDTjDo4ioj4COwt7JnTfA5NSjcxdFhGTZK6XKLVaklKSjJ0GCKbzM3NMTU1NXQYQgjx0lBK8evVX5l7ai7JKpnKjpVZ4LMANzs3Q4dm9CSpe0FKKYKDg4mKijJ0KCKHHBwcKFmypIyuEkKIPBafHM/UY1P56+ZfAHQo24HJTSZjbWZt4MgKB0nqXlBKQufs7IyNjY0kBkZEKcXjx48JCQkBwNXV1cARCSFE4RX4KJBP93/KlYgrmGpMGVVvVKGeruRRRDg7VizO12tKUvcCtFqtPqErVqyYocMROWBt/eTXYUhICM7OztIUK4QQeeDY/WN8dugzohKicLJyYm6LudQvWd/QYeUJpRQXD/hxcM33REdH5eu1JanLQFbmqUvpQ2djY5NfYYk8kHL/kpKSJKkTQohcpJTilyu/MOf0HHRKR/Vi1Vnos5CStiUNHVqeiAkLYfeKxdz+9xwAxYs55+v1JanLwNChQxk6dKh+jpnMFNaq45eF3D8hhMh9Sdokpp+Yrp9/rnP5zkxsPBFLU0sDR5b7lFJc2LeLgz99T2JcHKZm5lQ3scL+wIl8jUOSOiGEEELkqsj4SD498ClnHpzBRGPCSO+R9KnWp1D+iI4JC2X3im/0tXMlihSl6vkrFImNI9bcPF9jkaROCCGEELnmRuQNhu8bTuCjQIqYF2FW81k0L9Pc0GHlOqUUF/f7cWDNdyTGPcbU1JQqUY9x/+csGsC2RXNKDB8ONWvmW0wyZfNLLDg4mOHDh1OuXDksLS1xc3OjU6dO7N27V1/m6NGjdOjQAUdHR6ysrKhZsybz5s1L1dfw1q1bfPDBB5QtWxZra2vKly/PpEmTSExMNMTTEkIIYSD77+znve3vEfgoEDc7N37u8HOhTOgehoex8evJ7F7xDYlxjylmYkbTSwF43LyHRenSlFnqi9vy5Vi4u+drXFJT95K6desWTZs2xcHBgdmzZ+Pl5UVSUhK7du1i6NChXL16lU2bNtG9e3fef/999u/fj4ODA3v27OGzzz7j+PHjrF+/Ho1Gw9WrV9HpdKxYsYIKFSpw8eJFPvzwQ2JjY5k7d66hn6oQQog8ppTih4s/sOjsIhSKhiUbMrfFXBysHAwdWq5SSnHpwB72//gtiXGPMdGYUCk4nLLBEZhYWFBs6FCKfTgAEysrg8SnUUopg1zZSGS2GG98fDwBAQGULVsWKwPdwJzq0KED//77L9euXcPW1jbVvqioKMzNzfHw8KBFixZs2LAh1f6//vqLzp0789tvv9GjR490zz9nzhyWLVvGzZs38+w55BZjvo9CCGFoCdoEJh+dzNabWwHoUbkHYxuMxdwkf/uT5bWHEWH4rVxCwLnTADgmaql5M5AiCUkUadkSl8/Hp6mZyyyHyAtSU5eLlFLEJWU8BUpesjY3zXIH1IiICHbu3Mn06dPTJHTwZIWFTZs2ER4ezujRo9Ps79SpE5UqVWLt2rUZJnXR0dE4OTll70kIIYQwKmFxYXyy7xP+DfsXU40p4xqMo2eVnoYOK1cppbhyeD/7Vq0g4XEsJkDF++GUC43CokwZXL74HDsfH0OHCbwkSd0bb7zBgQMHaNWqFX/88UeeXScuSUu1ibvy7PyZuTy1LTYWWbud/v7+KKWoUqVKhmWuX78OQNWqVdPdX6VKFX2ZZ/33338sXryYefPmZSkeIYQQxud65HWG7h1KcGww9hb2zGs5j0aujQwdVq6KexjDnm99uX7ibwAc4hLxuh1MER0UHzKYYh99ZLCm1vS8FEndxx9/TP/+/fnxxx8NHUqBkNLinpWavYxa55VS6R5///592rVrx9tvv82AAQNeLFAhhBAF0t+BfzPq4Chik2LxtPfEt5Uv7vb5OyggrwWcP8Ou5YuIjYxAo6BicDjlQqKwreeN65QpWJYvb+gQ03gpkjofHx8OHDiQ59exNjfl8tS2eX6djK6dVRUrVkSj0XDlyhW6du2abplKlSoBcOXKFZo0aZJm/9WrV6lWrVqqbffv38fHx4fGjRuzcuXKrAcvhBDCaKy/tp4ZJ2agVVrql6zPgpYLKGqZ+ST9xiQpIZ6DP6/in93bALCNT6T2nQc4WljjMu0rir75JhqTgjl5iMGjOnToEJ06daJUqVJoNBo2b96cpszSpUv1ndi9vb05fPhw/geaBRqNBhsLM4P8y86Ejk5OTrRt2xZfX19iY2PT7I+KiqJNmzY4OTml24S6ZcsWbty4wTvvvKPfFhgYSMuWLalbty6rVq3CpIC+4YUQQuSMTumYd3oeXx3/Cq3S0rl8Z1a8tqJQJXRB/tf4aewn+oTOMzSKV67fw+21tpTfvg2Hbt0KbEIHBaCmLjY2llq1avH+++/z1ltvpdm/bt06RowYwdKlS2natCkrVqygffv2XL58Gff/H2Xi7e1NQkJCmmN3795NqVKl8vw5GKOlS5fSpEkTGjRowNSpU/Hy8iI5ORk/Pz+WLVvGlStXWLFiBT179uSjjz5i2LBh2Nvbs3fvXsaMGUO3bt3o3r078KSGrmXLlri7uzN37lxCQ0P11ylZsnCu7yeEEC+TuOQ4Pj/8OXvu7AFgWO1hfOT1UaFZIUKn1XJi03qObViL0umwTErG604IpRyLU/LbWRR5pamhQ8wSgyd17du3p3379hnunz9/Ph988IG+f9bChQvZtWsXy5YtY+bMmQCcOXMmX2ItTMqWLcvZs2eZPn06o0aNIigoiBIlSuDt7c2yZcsA6NatG/v372fGjBk0b96cuLg4KlSowBdffMGIESP0H+bdu3fj7++Pv78/ZcqUSXUdmTFHCCGMW1hcGMP3Dudi+EXMTcz5qulXvF7udUOHlWsi7geyY8k8gv97MvjPNfIh1YMjce3bj+JDBmNibW3gCLPO4EldZhITEzlz5gzjxo1Ltb1NmzYcPXo0T66ZkJCQqtYvJiYmT65TELi6urJkyRKWLFmSYZlmzZqxY8eOTM/Tr18/+vXrl8vRCSGEMDT/SH+G7h3K/dj7OFg6sMhnEXVd6ho6rFyRsszXvlXLSU5MxCxZS43AMMqWLEOp35Zh9Uy/cWOQ46ROp9Ph7+9PSEgIOp0u1b7mzXNnSZCwsDC0Wi0uLi6ptru4uBAcHJzl87Rt25azZ88SGxtLmTJl2LRpE/Xr10+37MyZM5kyZcoLxS2EEEIYu6P3jzLqwCgeJT3Cw94D31a+eNh7GDqsXBEf+wi/lYu5fvzJVCXFHj7GKygStw8/pPiAAWgsLAwcYc7kKKk7fvw4vXr14vbt22ma1zQaTap1QXPDs232GU2nkZFdu7I+d9z48eMZOXKk/nFMTAxubm5ZPl4IIYQwdn9c/4Npx6ehVVrqOtdlkc+iQrPkV+C1K2xb8DUPI8PRKEWloAiquZSm1G/LsapcydDhvZAcJXWDBg2iXr16bNu2DVdX1zzrKFm8eHFMTU3T1MqFhISkqb3LLZaWllhaWuLr64uvr2+uJ6hCCCFEQaVTOhadXcQPF38A4PVyrzO1yVQsTI2z5uppOp2WExvXc+yPX1FKYZOQRJ37EVT48COKvf8+GrMC3SMtS3L0DG7cuMEff/xBhQoVcjueVCwsLPD29sbPz4833nhDv93Pz48uXbrk6bWHDh3K0KFD9eu2CSGEEIVZfHI8nx/5HL/bfgAMrjWYwbUGF4oRrjFhoWxf8DWB/tcAKB3xEG8nV9x/W4ZluXIGji735Cipa9iwIf7+/rmS1D169Ah/f3/944CAAM6fP4+TkxPu7u6MHDmS3r17U69ePf2ktnfu3GHQoEEvfO3MSE2dEEKIl0V4XDgf7/uYf8P+xczEjKlNptKpfCdDh5Urbpw8yq4l80hISMBUq6NGcAR13v8Qp3790JhmfeJ+Y5CjpG748OGMGjWK4OBgatasibm5ear9Xl5eWT7X6dOn8XlqIdyU/mx9+/Zl9erV9OjRg/DwcKZOnUpQUBA1atRg+/bteHjkbWdNqakTQgjxMvgv6j+G7h1K4KNA7C3sWeizkPol0x9MaEySEhPY//0yLhx4Mrde0cfxNDC1pdL3P2JVubKBo8sbGpWDicTSWy1Ao9HoBzAUptqtlKQuOjoae3v7VPvi4+MJCAjQr3YhjJPcRyHEy+p40HFG7h/Jw6SHuNu549vKF8+inoYO64VF3L/Hn9MnEhEWAkC5kCgadeiCyyefYJKPI1szyyHyQo5q6gICAnI7jgJHml+FEEIUZptubGLqsakkq2TqONdhkc8iHK0cDR3WC7t8cC9+y78hWafFIikZ7zgdtecuwsbb29Ch5bkcJXV53fRZEEjzqxBCiMJIKcXic4v59sK3ALQv256vmn6FpamlgSN7McmJiexdPI+LJ5/MPef0KI7mNevh+eVETIvYGji6/JHj8bv//fcfCxcu5MqVK2g0GqpWrconn3xC+fLlczM+IYQQQuSSBG0CE/6ewI6AJysFfeT1EcNqDzP6Ea4RQYFsmTye8KgIUIqKMfG0GD2eoq+9ZujQ8lXaznFZsGvXLqpVq8bJkyfx8vKiRo0anDhxgurVq+Pn55fbMRqEr68v1apVy3DlCZGWp6cnCxcuNHQYQggh0hEZH8lHuz9iR8AOzDRPRrgOrzPc6BO6q/v38POngwmPisAiWUszKwfar1n70iV0kMOaunHjxvHpp5/y9ddfp9k+duxYWrdunSvBGZI0v/5PYmIiFka6ZIoQQgi4HXObIXuGcOfhHezM7ZjvM59Gro0MHdYLSU5KYt+CWVw4cxwAx9h4XmvfFbfBQ9CkM6DzZZCjZ33lyhU++OCDNNv79+/P5cuXXzgokbdatmzJsGHDGDZsGA4ODhQrVowvv/xSv+Sbp6cn06ZNo1+/fhQtWpQPP/wQgA0bNlC9enUsLS3x9PRk3rx5qc55+/ZtPv30UzQaTapffpkdl3K9GTNm0L9/f+zs7HB3d2flypX58EoIIUThd/bBWd7d/i53Ht6hlG0pfurwk9EndNHBQfw8uJ8+oasQr6X7V3NwHzrspU3oIIdJXYkSJTh//nya7efPn8fZ2flFYzJeSkFirGH+ZXNmmh9//BEzMzNOnDjBN998w4IFC/juu+/0++fMmUONGjU4c+YMEyZM4MyZM3Tv3p2ePXty4cIFJk+ezIQJE1i9ejUAGzdupEyZMvr5BIOCggCee1yKefPmUa9ePc6dO8eQIUMYPHgwV69efaHbIYQQL7vtN7czYPcAohOiqVGsBr+8/gvlHYy77/t/B/ez5pOPCH8YjXmylmYl3Oj4y+8UqVPH0KEZXI6aXz/88EM++ugjbt68SZMmTdBoNBw5coRZs2YxatSo3I7RIHI0pUnSY5hRKu+Cyszn98Ei66N73NzcWLBgARqNhsqVK3PhwgUWLFigr5V79dVXGT16tL78u+++S6tWrZgwYQIAlSpV4vLly8yZM4d+/frh5OSEqakpdnZ2lCxZUn/c/PnzMz0uRYcOHRgyZAgAY8eOZcGCBRw4cIAqVark+CURQoiXlVKKby98y+JziwFo5d6Kmc1mYm1mbeDIck4pxd+L53PiyD7QaCgan0i7Hn0o0+s9Q4dWYOQoqZswYQJ2dnbMmzeP8ePHA1CqVCkmT57Mxx9/nKsBGkph71PXqFGjVE2kjRs3Zt68efoktl69eqnKX7lyJc16u02bNmXhwoVotVpMM1hqJavHPb0KiUajoWTJkoSEhOT8CQohxEsqSZfEV8e+YpP/JgD6VuvLp96fYmpivEtixT96xF9jP+FO2APQaPBI1tB+zhJsK1UydGgFSo6SOo1Gw6effsqnn37Kw4cPAbCzs8vVwIySuc2TGjNDXTsX2dqmrvVLWS3k2W3Pk9Xjnl1qTqPRoNPpshquEEIIICYxhpEHRnIi6AQmGhM+b/A5Par0MHRYLyTk8kU2f/UlD3XJmOgU3i5uNJ2zAFNr4611zCs5nqcuhSRzT9FostUEakjHjx9P87hixYoZ1rhVq1aNI0eOpNp29OhRKlWqpD/GwsIiTXN1Vo4TQgjx4gIfBTJ0z1D+i/4PGzMb5rSYQ/MyzQ0d1gu5+Nsv7NnwK1oTDVZJybRu15VKHw0ydFgFVpaTurp167J3714cHR2pU6dOpvPanD17NleCM6TCvkzY3bt3GTlyJAMHDuTs2bMsXrw4zajUp40aNYr69evz1Vdf0aNHD44dO8aSJUtYunSpvoynpyeHDh2iZ8+eWFpaUrx48SwdJ4QQ4sVcDLvIsL3DCI8Px9nGGd9WvlRxMt4+ydrkZPZOHMeF/66CiYbiSTo6fTENJ+96zz/4JZblpK5Lly5YWlrq/2/skxU+T2HvU9enTx/i4uJo0KABpqamDB8+nI8++ijD8nXr1mX9+vVMnDiRr776CldXV6ZOnZpqsMPUqVMZOHAg5cuXJyEhAaVUlo4TQgiRcztv7eTLI1+SoE2gsmNllrRaQknbks8/sICKfRDMptHDeZAYB0BlWwfaLvDFvBD+Lc5tGpWVjlEvsZSkLjo6Gnt7+1T74uPjCQgIoGzZslhZWRkowuxr2bIltWvXltUf/p+x3kchxMtNKcXyf5az9J8nLR/NyzRndvPZ2JobRzeg9ASdOMbmudN5bAKmOh2v1HsF78/GG21FUmY5RF7IUZ+6cuXKcerUKYoVK5Zqe1RUFHXr1uXmzZu5EpwQQggh0opPjmfC3xPYeWsnUDhGuF788Qf2bP0DrYkJNsk6On40HLe27Q0dllHJUVJ369atdPuaJSQkcO/evRcOSgghhBDpC30cysf7PuZi+EXMNGZMaDyBNyu+aeiwckyn03Hgi884d/MqmJhQAlO6zvkG+3LlDB2a0clWUrdlyxb9/3ft2pWqr5lWq2Xv3r2ULVs296ITeeLAgQOGDkEIIUQOXAm/wrB9wwh5HEJRy6IsaLmA+iXrGzqsHEuIiODPT4dwN/4RAJUcStBugS/mNrk7TdfLIltJXdeuXYEnc4j17ds31T5zc/N01/U0VoV99KsQQgjjsuf2Hj4/8jlxyXGULVoW31d9cbN3M3RYORZ+/hybpk8g2gQ0StG4bmMaj/vS0GEZtWwldSmTwZYtW5ZTp05RvHjxPAmqICjso1+FEEIYB6UU3134jm/OfQNA01JNmdNiDnYWxjtPrP/639ixfg2JpiZYaHW07/MhFTq/YeiwjF6O+tQFBATkdhxCCCGEeMbjpMdMPDqRXbd2AfBu1XcZXW80ZiYvvHaAQSilODF9Kkf/OYkyNaEoJrzx1WyKVa1m6NAKhRy/K2JjYzl48CB37twhMTEx1b7Csv6rEEIIYSh3H97lk/2fcCPyBmYmZoxvMJ7ulbsbOqwc0ybEs+OToVyLfAAmGtxsi9Jl4TIs82Gqj5dFjpK6c+fO0aFDBx4/fkxsbCxOTk6EhYVhY2ODs7OzJHVCCCHECzgaeJQxh8YQkxhDMatiLPBZQB3nOoYOK8figoPZ9OkQgnRPKoFql6+Gz7SvMTExMXBkhUuOXs1PP/2UTp06ERERgbW1NcePH+f27dt4e3szd+7c3I5RCCGEeCkopVh1cRWD9w4mJjGGmsVrsq7jOqNO6MLPn+WXoR8QpEvERKdo9VpHWs2YLQldHshRTd358+dZsWIFpqammJqakpCQQLly5Zg9ezZ9+/blzTeNd74cIYQQwhAeJz1m8tHJ7Li1A4A3KrzBF42+wNLU0sCR5dytzRvZ+tO3JJiZYqlTdBz4CZ6vtTF0WIVWjtJkc3Nz/ZIdLi4u3LlzB4CiRYvq/y8Kvrt37/LBBx9QqlQpLCws8PDw4JNPPiE8PPyFzrt//346dOhAsWLFsLGxoVq1aowaNYrAwEB9Ga1Wy4IFC/Dy8sLKygoHBwfat2/P33///aJPSwghjM7tmNv03tGbHbd2YKYx4/OGnzOlyRSjTujOz5/D5l++I8HMFHtM6DV9niR0eSxHSV2dOnU4ffo0AD4+PkycOJFffvmFESNGULNmzVwNUOSNmzdvUq9ePa5fv87atWvx9/dn+fLl7N27l8aNGxMREZGj865YsYLXXnuNkiVLsmHDBi5fvszy5cuJjo7Wz2GolKJnz55MnTqVjz/+mCtXrnDw4EHc3Nxo2bIlmzdvzsVnKoQQBduuW7vosbUH1yOv42TlxLdtvuWdKu8Y7XqnuuRk9o0Yyt7jB9CamFDSypb3lq/GqVIVQ4dW6GmUUiq7B50+fZqHDx/i4+NDaGgoffv25ciRI1SoUIFVq1ZRq1atvIg1Xz09+fD169fTXYzXmBeCb9++PRcvXuT69etYW1vrtwcHB1O+fHn69OnDsmXLsnXOe/fuUb58eYYMGcKCBQvS7I+KisLBwYF169bRs2dPtmzZQqdOnVKVeeuttzh48CC3b9/G1jZ/FqU25vsohDBeSdok5p6ey69XfwWgrnNdZjefjYuti4Ejy7mkhw/ZOuxDbv7/ChGVS3nQfs4iTM2McwqWF5Uy1216OUReyHZSp5Tizp07ODs7p0oGCqvMbsizyYBSirjkOIPEaW1mneVfdRERERQvXpzp06czfvz4NPs/+ugj/vjjD8LDwxk8eDA///xzpue7fPky7u7uLFiwgJEjR3L//n1cXV0zLN+lSxeuXr3KtWvX0uw7evQoTZs2ZdOmTfoVTPKaJHVCiPx2/9F9Rh8czYWwCwD0r9Gf4XWGG+38cwCP7t5l4+ihhKIDpWjcsBmNR4412hrH3JDfSV223z1KKSpWrMilS5eoWLFiXsRktOKS42j4a0ODXPtErxPYmGdtrbwbN26glKJq1arp7q9atSqRkZGEhoYydepURo8enen5SpUqpT+vvb19pgkdwPXr1zO9dkoZIYQojA7dO8T4w+OJSYzB3sKe6a9Mp6VbS0OH9UJCTp9i09eTeWSqwVSnaNPtXar16GXosF462U7qTExMqFixIuHh4ZLUFVIplbcajYYSJUrg7Oyc5eNy6xfZy/zLTghROCVoE1hwZgG/XPkFgBrFajC35VxKFylt4MheTMDWv9i6ehmJpiZYaRVdRoyjzCvNDB3WSylH9byzZ89mzJgxLFu2jBo1auR2TEbL2syaE71OGOzaWVWhQgU0Gg2XL19Ot4nz6tWrODo6Urx4cQYNGpTl5tdKlSoRHR1NUFBQprV1lSpV4vLly+nuu3LlCoD8YBBCFCo3Im8w9vBYbkTeAKBXlV6MqjcKC1MLA0f2Yi58u5w9u7egMzWhqNLQ7esFOFSQ729DydFACUdHRx4/fkxycjIWFhZp+tbldORkQZSdPnXGpG3btly6dIkbN25kOlAiJCSEmJiYTM/l6emJmZkZd+/epUKFCs8dKLF27Vp69eolAyWEEIWeUoq1V9cy/8x8ErQJOFk58VXTr2heprmhQ3shSimOfjWR4xfPgkZDSXMr3lq0AqtixQwdWoFS4PvUASxYsECax4zckiVLaNKkCW3btmXatGmULVuWS5cuMWbMGEqXLs306dMBcHZ2znLzq5ubGwsWLGDYsGHExMTQp08fPD09uXfvHmvWrKFIkSLMmzePnj178vvvv9O3b1/mzJlDq1atiImJwdfXly1btvD777/nW0InhBB5JTwunElHJ3Hw3kEAXin9Cl81/Yri1sUNHNmL0SUns3vEUC6FBoJGQ3mHEnT8ZjlmlsY7p15hkaOaupdJYa2pA7h9+zaTJ09m586dhIeHU7JkSbp27cqkSZMo9gK/tvbs2cPcuXM5efIkcXFxeHp60rFjR0aOHKlvlk1OTmbRokWsWrUKf39/LC0tady4MV9++SWvvPJKbj3FLDH2+yiEKHh23trJjOMziEyIxMLEgpH1RtKrSi+jrxBJehzLn0MGcDvuIQC1y1fFZ9osWfIrAwV+ShMAU1NTgoKC0tTghIeH4+zsjFarzbUAX9Tdu3fp3bs3ISEhmJmZMWHCBN5+++0sH1+YkzrxhNxHIURuCY8LZ/qJ6fjd9gOgomNFvm72NZUcKxk4shf3OCSEDZ8MJESXhEYpmjV9lfqfjDJ0WAWaUTS/ZpQHJiQkYGFRsDp9mpmZsXDhQmrXrk1ISAh169alQ4cO0rwnhBAi1yil2HVrF9NPTCcqIQozjRkDvAbwUc2PMDc1N3R4LyzyxnX++GIUMRqFqU5Huzd7UeWd9wwdlnhGtpK6b775Bngy3cR3331HkSJF9Pu0Wi2HDh2iSpWCtQyIq6urvsnP2dkZJycnIiIiJKkTQgiRK4Jjg5l1chZ77uwBoLJjZb5q+hVVi6U/H6exuX/yOJvmfEW8iQZLrY7OA0fg3lrWcC2IspXUpYxoVEqxfPlyTE1N9fssLCzw9PRk+fLl2Qrg0KFDzJkzhzNnzhAUFJTuSgJLly5lzpw5BAUFUb16dRYuXEizZtmfA+f06dPodDrc3NyyfawQQgjxtERtImsur2HlvyuJS47DTGPGR14fMaDmgEJROwfgv/0vtq1aTrKJhiLJOt764iuK1/U2dFgiA9lK6gICAgDw8fFh48aNODo6vnAAsbGx1KpVi/fff5+33norzf5169YxYsQIli5dStOmTVmxYgXt27fXz40G4O3tTUJCQppjd+/erV/tIDw8nD59+vDdd9+9cMxCCCFebkcCj/D1ya+5HXMbgNolavNloy+p7FTZwJHlnnM/fs/+bRtRJhqK6eCtuUuwK1vO0GGJTBSo0a8ajSZNTV3Dhg2pW7duqsXlq1atSteuXZk5c2aWzpuQkEDr1q358MMP6d2793PLPp0gxsTE4ObmJgMlCjG5j0KIrLr38B6zT81m/939ABSzKsaoeqPoWK6j0Y9sTaGU4vC8mZw6dRSAMhpzuvp+i2Ux456KJb8lJWi5fOo2tZuVL9gDJbRaLatXr2bv3r2EhISg0+lS7d+3b1+uBJeYmMiZM2cYN25cqu1t2rTh6NGjWTqHUop+/frx6quvPjehA5g5cyZTpkzJUbxCCCEKp/jkeH64+APfX/ieRF0iZhozelXtxeBagyliUeT5JzASOp2WHV+M4erNJ+tvV7K2p8PS7zC1ydra4i+72OgEbv0bxq1/w7h7NZJHsQ/z9fo5Suo++eQTVq9ezeuvv06NGjXy7NdJWFgYWq0WFxeXVNtdXFwIDg7O0jn+/vtv1q1bh5eXF5s3bwbgp59+ombNmumWHz9+PCNHjtQ/TqmpE0II8fJRSrHvzj7mnJ5D4KNAABqWbMj4huMp71DewNHlrqSEeDaNGsbd0GBQirrOZWi50BeNWY5ShZdGRFAsAf+EEvBPGA9uxcBT7Z92Tvnb+pOjO/Xbb7+xfv16OnTokNvxpOvZpDE7C8e/8soraWoSM2NpaYmlpSW+vr74+voWqDn3hBBC5J+A6AC+Pvk1R+8/aRkqaVuSMfXG0NqjdaFpak0RGx3FHyOHEPYoBhOdjlcqeVFv2sxC9zxzS1TIY/xPh+B/5gHhgbGp9jl72FG2VgnK1iqOWREtg+blX1w5SuosLCyoUKFCbseSRvHixTE1NU1TKxcSEpKm9i63DR06lKFDh+onDhRCCPFyiE2KZcW/K/jp8k8k65IxNzGnX/V+DKg5ABvzwtcMGXH/Hr+P/YRHiQmYJ2t5rWELqn027vkHvmQeRsTrE7mQ2/9rVjUx1VCmihNlaxWnrFdxbB3+t1za89ZOz205SupGjRrFokWLWLJkSZ5m8RYWFnh7e+Pn58cbb7yh3+7n50eXLl3y7LpCCCFePkopdgTsYN7peYTEhQDQrHQzxjUYh7u9u4Gjyxv3r15m45TxJOi0WCck0a59V8oNHGzosAqMxPhk/jsbytVjQdy/EaXfrjHRUKaKIxXrOVO2VgmsbAvGFDY5SuqOHDnC/v372bFjB9WrV8fcPPWT2bhxY5bP9ejRI/z9/fWPAwICOH/+PE5OTri7uzNy5Eh69+5NvXr1aNy4MStXruTOnTsMGjQoJ6Fn2cvQ/BocHMz06dPZtm0bgYGBODs7U7t2bUaMGEGrVq0AOHr0KNOmTePYsWPExcVRsWJF+vXrx4gRI1LNUwiwf/9+5syZw4kTJ/RrvrZv356RI0dSunTpHMUYERHB1KlT2bx5M/fv36dYsWK0a9eOKVOm6Ke0EUKIF3U98jozTszgzIMzAJQpUoZxDcbRwq2FgSPLOzeOH2HbglloUdjHJdCxV39ce75j6LAMTilFkH80V44F4X8mhOSE/88DNFCqggMV6zlTro4zNvYFawUtyGFS5+DgkKrm7EWcPn0aHx8f/eOUQQp9+/Zl9erV9OjRg/DwcKZOnUpQUBA1atRg+/bteHh45Mr1M1LYm19v3bpF06ZNcXBwYPbs2Xh5eZGUlMSuXbsYOnQoV69eZdOmTXTv3p3333+f/fv34+DgwJ49e/jss884fvw469ev19fUrlixgiFDhtC3b182bNiAp6cnd+7cYc2aNcybN4/58+dnO8aIiAgaNWqEhYUFS5cupUaNGty6dYsvv/yS+vXrc+zYMcqVkzmThBA5F5MYw9LzS/nt6m9olRYrUysG1BxAvxr9sDS1fP4JjNS5rZvZ99OTeVtLPIzj9WEjKdbhdQNHZViPYxK5cvQ+V44GER0Sp99etIQ1VZq4UqVRSYo4FuxprwrUPHUFUWaL8Rrz/GYdOnTg33//5dq1a2mWTIuKisLc3BwPDw9atGjBhg0bUu3/66+/6Ny5M7/99hs9evTg3r17lC9fniFDhuhXHXn2fA4ODtmOcfDgwfz000/4+/tTsmRJ/faUGsOaNWuyY8eObJ/3WcZ8H4UQOaNTOv70/5OFZxcSER8BQGuP1oyuN5pSRUoZOLq8o3Q6Dv34Had3bgHALTqWdl9MxT4HqzQVBkopgm/GcOHAPf47G4JO+yQlMrc0pYK3M1WauOJavmiOu5pllkPkhRyPU05OTubAgQP8999/9OrVCzs7O+7fv4+9vX2qNWGNVU6aX5VSqLi45xfMAxpr6yy/6SIiIti5cyfTp09Pdw1cBwcHNm3aRHh4OKNHj06zv1OnTlSqVIm1a9fSo0cPfv/9dxITE/nss8/SvV5KQnfnzh2qVauWaWzvvfcey5cvR6fT8dtvv/Huu++mSugArK2tGTJkCF9++SURERE4OTll6XkLIQTA1YirTD8+nfOh5wEoW7Qs4xqMo0mpJoYNLI9pk5PYsWgO104+Gc1bKeIRr349D1vvl2/Zr6RELTdOPuDCwXuE3X2k3+5S1p7qzUpTvm4JLKyMbyqXHEV8+/Zt2rVrx507d/SrNdjZ2TF79mzi4+Ozvf5rQZST5lcVF8c1A62JV/nsGTRZnBzS398fpRRVqlTJsMz1608mnqxaNf0FqatUqaIvc+PGDezt7XF1dc30uqVKleL8+fOZlkn5JRMaGkpUVFSG169atSpKKfz9/WnQoEGm5xRCCICHiQ/xPe/L2qtr0Skd1mbWDK41mPeqvldo1mrNSHzsI/6cOZl7N66iUYpaEbE0/WYpVs/5oV3YxEYn8O++e1w6HEjC42QATM1NqFTfhZoty1DC3c7AEb6YHE8+XK9ePf755x+KFSum3/7GG28wYMCAXAtO5I2UFves1Oxl1Dr/9FyBWZ030MzMLNemwsnOcxBCvNyUUmwL2Ma80/MIiwsDoI1HG8bUH0NJ25LPOdr4xYSFsnHal4QHBWKq1VE/OoF6K77Hsnzhmjw5M5HBsZzzu8O1E8Hokp/8/bAvbkWNFmWo2sS1wIxefVE5Hv36999/Y2GReuSHh4cHgYGBuRKYoeWk+VVjbU3ls2fyMKrMr51VFStWRKPRcOXKlVTr7D6tUqVKAFy5coUmTdI2SVy9elXflFqpUiWio6MJCgrKtLYuO82vJUqUwMHBgcuXL6db7urVq2g0Gsq/RF9KQojsux1zmynHpnAq+BQAnvaejG8wnialC3dTa4rQ2wFsmD6B2OgoLJOSafxIS81VP2JRpoyhQ8tzSimC/ovm3O473Po3TL/dtXxRard2p6xXcTQmhatiIEcDJZycnDhy5AjVqlXDzs6Of/75h3LlynHkyBHeeustHjx4kBexGkRhHSjRvn17Lly4kOlACXd3d1q2bJlmoMSWLVvo0qWLfqDE3bt3qVChwnMHSiQnJ3Pr1q1M47K3t8fZ2RmAgQMH8ssvv8hACSFEtiXrkvnp8k/4nvclQZuAlakVH3l9RN/qfbEwLXhTUeSF2xfO8+ecaSQlxFMkPpHG8Rqqrl6N+XO6yhg7pRSB16M4tTXgf3PLaaCsV3HqtPHAtXz+zWiR3wMlcpTU9ejRg6JFi7Jy5Urs7Oz4999/KVGiBF26dMHd3Z1Vq1blRawGUViTuoCAAJo0aYKTkxNTp07Fy8uL5ORk/Pz8WLZsGVeuXOGPP/6gZ8+e9O/fn2HDhmFvb8/evXsZM2YMrVq1SjWlydKlSxk2bBjvv/8+ffr0wdPTk3v37rFmzRqKFCnCvHnZXyclLCyMRo0aYW1tzezZs6lRowYBAQF8+eWXXLt2LdemNDHm+yiESOtaxDUmHZ3EpfBLADRybcSkxpMoY1f4a6dSXD60j13LFqLT6XB6FEcjnSUVVq/CPI9XYzIkpRSB1yI5uTWAIP9oAEzMNFRp7ErtVm44lkw7MDCvGUVSd//+fXx8fDA1NeXGjRvUq1ePGzduULx4cQ4dOqSvaSkMCmtSBxAUFMT06dPZunUrQUFBlChRAm9vbz799FNatmwJwOHDh5kxY4Z+8uEKFSrQv3//dCcf3rNnD3PnzuXkyZP6yYc7duzIyJEjnzuIIiNhYWH6yYeDgoL0kw9PnTo11yYfNvb7KIR4IlGbyMp/V/L9he9JVsnYWdgxpt4Yulbo+tL0v1VKcXLz7xz5bQ0ArpEPqWdhR7lVqzArUcLA0eUNpRT3rkVy6plkrvorpanb1t2gc8sZRVIHT5rAfvvtN86cOYNOp6Nu3bq8++67WGejb1dB9nSfuuvXrxfKpE48IfdRCON3PfI64w+P53rkk1H5rdxb8UXDLyhhUzgTmfTotFr2/rCMf/fsBKBcSCRe9sXxWLUKs0I69dODWzEc2+RP4LUoAEzNTKjWrBR123hQxNHwk0cbTVL3sijMNXXiCbmPQhgvndLx0+WfWHR2EUm6JBwtHfmy0Ze09mj90tTOASTFx7N10Sxunj0FSlEtMIwqLmVw+/47zBwdDR1erosKecyJP2/if+bJGr0mZhqqNyuNd1sPbB0Mn8ylMIrJh2fOnImLiwv9+/dPtf2HH34gNDSUsWPH5kpwQgghREaCY4P58siXnAg+AUDzMs2Z0mQKxa2LGziy/BUbFcmmWVN5cPMGJjpF7dvBeHpWwP27bzHNh0QiPz2OSeTUtgAuH76PTqdAA5UblqRBp7LYFyscLYUvIkdJ3YoVK/j111/TbK9evTo9e/aUpE4IIUSe2nlrJ1OPTeVh4kOszawZXW80b1d6+6WqnQOIuB/IxpkTiQ55gLlWR72b9ylVuRpuK1dgamfcE+k+LTlJy3m/u5zZdZvkhCdTjXnUKEajruUpXsb4V7HKLTlK6oKDg9Pt+F6iRAmCgoJeOKiCICfz1AkhhMhbCdoEZp+czfrr6wGoWbwmM16ZgWdRT8MGZgD3rl7iz7nTiX8Yg01iMvX/u08Jr1qUWb4c0yL5P9IzLyilCDgfxt8bbhATFg+As6c9Td4oT+nKha9Z+UXlKKlzc3Pj77//pmzZsqm2//3335QqVTgWQs7JMmFCCCHyzu2Y24w+OJqrEVfRoGFAzQEMrj0Yc5PCsRpAdlw5vJ9dyxehTU7GIT4R7//u41ivPm5LfTHJ4pKRBV34/UccWX+De1cjAbB1sKTJm+WpWN/lpauRzaocJXUDBgxgxIgRJCUl8eqrrwKwd+9ePvvsM0aNGpWrAQohhBA7b+1k8tHJxCbF4mjpyNfNvn5pVoV4mlKKY3/8yrE/1gJQ8lE8tW7ex65hQ9yWLcWkEMxAER+bxMmtAVw8GIjSKUzNTKjTxp26bT0wtzR9/gleYjlK6j777DMiIiIYMmQIiYmJAFhZWTF27FjGjx+fqwEKIYR4eSVqE5l9ajbrrq0DoK5zXWY3n42LbeGdRDcjyUlJ7F6+iCtHDgBQPjKWSneCsW3QoFAkdEopbpx+wJH1N4h7mARAuTolaPpWBeyLG/dzyy85Suo0Gg2zZs1iwoQJXLlyBWtraypWrIilZcEZRiyEEMK4hTwO4dMDn/Jv6L8AfFjzQ4bUHoKZSY7+dBm1xzHRbJk3ncCrlzExMaHGgyjK3A/Fpl493JYvM/qELjr0MQd/vcbdK0+aWh1L2tCsZyXcqhTO+fXyygt9MooUKUL9+vVzKxYhhBACgPMh5/n0wKeExYVhZ2HHrGazaFammaHDMoiI+/fY9PUUoh4EYWFpRZ1bQRQLicC6njduK5YbdR86bbKOc353OL39FtokHaZmJtTr4EmdNu6YmpkYOjyjk6OkLjY2lq+//pq9e/cSEhKCTqdLtf/mzZu5EpwhyejX7JkwYQIPHjxg5cqVeXqdkJAQqlevzvnz5yldunSeXksIYRgbrm9g2olpJOuSqeBQgW98vsHN3s3QYRnE3Uv/smXeDOJjH2Hn4Ejdi/9hGx6Jdd26uK9YgYmt8Y5yve8fxYFfrhEZFAtAmSqOtOhVGQdn401SDS1HK0q88847HDx4kN69e+Pq6ppmFMonn3ySawEaWmFeUSI4OJjp06ezbds2AgMDcXZ2pnbt2owYMYJWrVoBcO7cOWbMmMGhQ4eIjo7G3d2dFi1aMGbMGCpVqgTAgwcPqFixIv/++y+enp45jufo0aNMmzZNv85sxYoV6devX5p1ZkeOHElMTAzfffddquPv3r3L5MmT2bFjB2FhYbi6utK1a1cmTpxIsWLFMryusd9HIQqLJG0Ss07N0vefa+3RmmlNp2Fj/nL+kb+wbzd7vluKTpuMSxl3vI6ewzwyCus6dXD79lujnbYkKUHLsc3/cWH/PQCs7cxp2q0ilRoUvlGtRrGixI4dO9i2bRtNmzbN7XhEPrl16xZNmzbFwcGB2bNn4+XlRVJSErt27WLo0KFcvXqVrVu38tZbb9G2bVt++eUXypcvT0hICL///jsTJkxg3bonX7zff/89jRs3fqGEbtOmTXTv3p3333+f/fv34+DgwJ49e/jss884fvw469ev13/Y33//fRo0aMCcOXNw/P/lb27evEnjxo2pVKkSa9eupWzZsly6dIkxY8awY8cOjh8/jlMhXftQiMIgIj6CT/d/ytmQs2jQMLzOcAbUHFDo/shnhU6r5cBP33Fux18AVKhRm0rb9kBUNNa1auH27UqjTegCr0Wy76cr+jnnqjZ1pcmbFbCyffmmpckLOaqpK1u2LNu3b6dq1ap5EVOBUlhr6jp06MC///7LtWvXsH2m+j4qKgoLCws8PDx45ZVX2LRpU5rjo6KicHBwAMDLy4uBAwcydOjQHMUSGxuLh4cHLVq0YMOGDan2/fXXX3Tu3JnffvuNHj166LeXLVuWCRMm6Jeqa9++PRcvXuT69etYP9VhODg4mPLly9OnTx+WLVuW7vWN+T4KURjcjL7J0D1DuffoHnbmdnzd/Gual2lu6LAMIu7RQ7YunMWdC+cBaPBqO5xX/YIuKgorLy/cv//OKFeKSIxP5vjmm1w48KR2roijJT69q+BeLeNWlMIgv2vqctQL8auvvmLixIk8fvw4t+MxakopkhK0BvmXndw8IiKCnTt3MnTo0DQJHYCDgwO7du0iLCyMzz77LN1zpCR0kZGRXLx4kXr16qXaP2PGDIoUKZLpv8OHDwOwe/duwsPDGT16dJrrdOrUSV/79rQGDRroj4+IiGDXrl0MGTIkVUIHULJkSd59913WrVuXrddICJE/TgSd4L3t73Hv0T3KFCnDz6///NImdOH37vDr5yO5c+E85pZWtH9vAC4/rXuS0NWo8WQtVyNM6AKvRbJu2kl9QletWSnemdiw0Cd0hpCj5td58+bx33//4eLigqenJ+bmqatNz549myvBGZvkRB0rPzlokGt/tKhFlidl9Pf3RylFlSpVMixz48YNgEzLANy+fRulVJqVRAYNGkT37t0zPTZloMP169cBMqz5rVKlir7M08eeO3dOH6tSKsPjq1atSmRkJKGhoTg7O2cakxAi/2y6sYmpx6aSrJKpXaI2i15dhJPVy9lN4r8zJ9m+eA6JcXHYl3Dh9b4DiR0zluSwMCwrV36S0OVDTU9uSk7UcnTjf/+rnXOy5NX3quJW7eW8x/khR0ld165dczkMkZ9Saqwy66uS1VqtuLg4gDTNlk5OTtnuw5bRNZVSaWK1trbOck1xVp6vECL/6JSORWcX8cPFHwBoX7Y9XzX9CkvTl2+uU6UUp7Zs4PDaH0EpylSrQfv3BhAyaAjJwcFYlCuH+w/fY/r/rSPGIjzwEbu/v0TE/ScjW6s1K0XTNytgYf3yzTGYn3L06k6aNCm34ygUzCxM+GhRC4NdO6sqVqyIRqPhypUrGSboKSNbr169SuPGjTM8V/HixYEnzbAlSpTQb58xYwYzZszINI4dO3bQrFkz/bWuXLlCkyZpl/25evUq1apVS7UtIiJCf70KFSqg0Wi4fPlyus/n6tWrODo66mMVQhhOfHI8nx/5HL/bfgAMqjWIIbWGvJQ/uhLjHrNrxWKuH3vSlaRW6w406/wW9/r1J+nuXczd3HBf9QNmmYzeL2iUUlw6fJ8jv99Am6TD2t6C1/pWxb268TwHY5ajgRIpzpw5w5UrV9BoNFSrVo06derkZmwFQmEdKNG+fXsuXLiQ4UAJc3NzPD09nztQQqfT4ejoyI8//pgqoYqIiCAiIiLTGEqXLo21tTWxsbG4u7vTsmXLNAMltmzZQpcuXdIMlGjWrBktW7bkq6++AqBt27ZcunSJGzduyEAJIQqo6IRoPt73MWdDzmJmYsbUJlPpVL6TocMyiPB7d9kyfwYRgXcxMTXFp99AajZowu1+75Nw9SpmJUvi8fPPWJQxnvk442OT2P/zVW6eCwXAvboTrfpWw8bewsCRGU5+D5RA5cCDBw+Uj4+P0mg0ytHRUTk4OCiNRqNeffVVFRISkpNTFjhLlixRVatWVZUqVVKAio6OTlMmLi5OXb58WcXFxRkgwhdz8+ZNVbJkSVWtWjX1xx9/qOvXr6vLly+rRYsWqSpVqiillNq8ebMyNzdXnTp1Un5+fiogIECdOnVKjRkzRvXo0UN/rjfffFONGjXqheL5/ffflampqfrwww/VP//8owICAtR3332nHB0dVbdu3ZROp9OXjY2NVdbW1urQoUP6bdevX1fFixdXzZo1UwcPHlR37txRO3bsUDVq1FAVK1ZU4eHhGV7bmO+jEMYi6FGQ6rq5q6qxuoZq/EtjdTLopKFDMphrxw6rRX26qbndX1fLB/ZWgdcuq+SHD9XNbm+ry5WrqGtNX1HxN28aOsxsCbweqVaPO6KWDNyrlg7Zp8753VY6re75BxZy0dHRGeYQeSFHSV337t2Vt7e3unz5sn7bpUuXVL169VTPnj1zLbiCILMbYuzJwP3799XQoUOVh4eHsrCwUKVLl1adO3dW+/fv15c5deqUevPNN1WJEiWUpaWlqlChgvroo4/UjRs39GV27typSpcurbRa7QvFc+jQIdWuXTtVtGhRZWFhoapVq6bmzp2rkpOTU5X79ddfVeXKldMcf+vWLdWvXz9VsmRJZW5urtzc3NTw4cNVWFhYptc19vsoREHnH+mvXvv9NVVjdQ316rpX1bWIa4YOySCSk5LU/h+/VXO7v67mdn9drZs8Tj2KjFDa2FgV8O67TxK6ho1U3DXjeX20yVp14q+bynfQXrVk4F7105dH1YNb+ZPAGIP8Tupy1PxatGhR9uzZk2bd15MnT9KmTRuioqJyoxKxQCisza+5SSlFo0aNGDFiBO+8806eX69BgwaMGDGCXr165cr55D4KkXfOh5xn6N6hxCTG4GnvyYrWKyhVpNTzDyxkYqMi2bpwFveuXASgfue3eKVnH0hO5t7gIcQePYqJnR3uq1dhXb26gaPNmocR8fj9cIkg/2gAqjQqSbOelbCwksEQKYxiRQmdTpdmGhMAc3PzNOvAisJPo9GwcuVK/v333zy/VkhICN26dcuX5FEI8WIO3D3AmINjiNfG41XCC99XfXGwcjB0WPnu1vkz7Fi6gMfRUVhYW9Nu8KdUbNgElZxM4OjRxB49isbGBreVK4wmobt5LpR9P10h4XEy5pamtOhVmcoNSxo6rJdejmrqunTpQlRUFGvXrtXPTxYYGMi7776Lo6Njuh3rjZXU1BV+ch+FyH1/+v/JpKOT0Cotzcs0Z07zOS/dGq7a5CSO/PYTp//aCEBxd086fToOp1JlUEoRNGEC0X9sQGNujtu3K7Ft1MjAET9fcqKWv//w5+KhQACcPexoM6A6RUu8XPc2q4yipm7JkiV06dIFT09P3Nzc0Gg03Llzh5o1a/Lzzz/ndoxCCCGMyK9XfmXmyZkAdCnfhUlNJmFu8nKt7Rn1IJht38wm2P/JxOm12rxOi979Mbd4Mhdf6Pz5RP+xAUxMKDVvrlEkdOH3H7H7u//NPVenjTsNO5fD1CxHi1OJPJCjpM7NzY2zZ8/i5+fH1atXUUpRrVo1XnvttdyOTwghhBH57sJ3LDq7CIDe1Xozpt6Yl24OuqtHD+G3cgmJcY+xtLWl7aBPqNjgf3Nwhn//PeHffgeA69Qp2LdpY6hQs0SlN/dcv6qyzFcBlK2kbt++fQwbNozjx49jb29P69atad26NQDR0dFUr16d5cuX06xZszwJVgghRMGklGLR2UV8f/F74OWcVDjhcSz7V6/k0sG9AJSqXI3XPx6NffH/LU8YtWEjIXPmAuA8ehQO3boZJNaskrnnjEu2krqFCxfy4YcfptsuXLRoUQYOHMj8+fMLVFL38OFDXn31VZKSktBqtXz88cd8+OGHhg5LCCEKDZ3S8fXJr1l7dS0Ao7xH0a9GP8MGlc9uXzjPrmWLeBgeikZjQoOub9Pk7V6YmP5vTe6He/YQNGECAE4f9KfYgAGGCjdL7t+Iwu+HSzyKTMDEVEPjN8pT61U3NCYvT6JubLKV1P3zzz/MmjUrw/1t2rRh7ty5LxxUbrKxseHgwYPY2Njw+PFjatSowZtvvkkxI1p2RQghCqpkXTKTjk5iy39b0KDhy0Zf0r1yd0OHlW+SEuI59Mtqzu/aCoCDiyvthnxK6SqplzaMPXGSwJGjQKej6Ftv4jx6tCHCzRKdTnFmxy1ObQ1AKShawpo2A6rj7JEPKyKIF5KtpO7BgwfpTmWiP5mZGaGhoS8cVG4yNTXFxubJqJz4+Hi0Wm2WF6sXQgiRsSRtEmMPj8Xvth+mGlOmvTKNjuU6GjqsfHP/+lV2Lp1PZNB94Mnarc3fex8LK+tU5eKvXOHekCGoxESKvNYK1ylTCmyz9MOIePasusz9G1GAzD1nbLI1ZKV06dJcuHAhw/3//vsvrq6u2Qrg0KFDdOrUiVKlSqHRaNi8eXOaMkuXLtVPN+Ht7c3hw4ezdY2oqChq1apFmTJl+Oyzz2RhdyGEeEFJ2iRGHxyN320/zE3Mmddy3kuT0CXGx3FgzXf8NvEzIoPuU8TRibfGT+G1AUPSJHRJgYHc/WgguthYbBo0oPS8eWjMCmaCdPNcKOumneT+jSjMLU157f1qtOpXTRI6I5KtO9WhQwcmTpxI+/bt08znFRcXx6RJk+jYMXsf6tjYWGrVqsX777/PW2+9lWb/unXrGDFiBEuXLqVp06asWLGC9u3bc/nyZdzd3QHw9vYmISEhzbG7d++mVKlSODg48M8///DgwQPefPNNunXrhouLS7biFEII8USSNomRB0dy4O4BLEwsWPTqIl4p/Yqhw8oX/505wd7vl/Mw/EmrVJWmLWjVfzBWRYqkKauNjubORwNJDg3FslIlyvguwcTSMr9Dfi6Ze67wyNbkww8ePKBu3bqYmpoybNgwKleujEaj4cqVK/j6+qLVajl79myOEyaNRsOmTZvo2rWrflvDhg2pW7cuy5Yt02+rWrUqXbt2ZebMmdm+xuDBg3n11Vd5++23092fkJCQKkGMiYnBzc2tUE4+HBwczPTp09m2bRuBgYE4OztTu3ZtRowYQatWrQA4evQo06ZN49ixY8TFxVGxYkX69evHiBEjMH2qA/CzkpKS+PLLL9m+fTs3b96kaNGivPbaa3z99df6CasLCmO/j0Lkp0RtIqMOjOLAvQNYmlryjc83NCnd5PkHGrmHEWHsX7WSGyePAmBfwplWHwymXJ366ZbXJSRw94MBPD59GjMXFzzX/YZ5yYK34oLMPZe3CvTkwy4uLhw9epTBgwczfvx4fd80jUZD27ZtWbp0aa7WgCUmJnLmzBnGjRuXanubNm04evRols7x4MEDrK2tsbe3JyYmhkOHDjF48OAMy8+cOZMpU6a8UNzG4NatWzRt2hQHBwdmz56Nl5cXSUlJ7Nq1i6FDh3L16lU2bdpE9+7def/999m/fz8ODg7s2bOHzz77jOPHj7N+/foM+4U8fvyYs2fPMmHCBGrVqkVkZCQjRoygc+fOnD59Op+frRAiNyRqE/n0wKccunfoSUL36jc0KVW4EzqdTsv5Xdv5e90aEuPi0JiYUK/jGzR+6x3MM/gRqHQ67o8bx+PTpzEpUgS3lSsLXEInc88VTtluKPfw8GD79u1ERkbi7++PUoqKFSvi6OiY68GFhYWh1WrTJIouLi4EBwdn6Rz37t3jgw8+QCmFUophw4bh5eWVYfnx48czcuRI/eOUmrrCZsiQJ/NHnTx5EltbW/326tWr079/f2JjY/nwww/p3LkzK1eu1O8fMGAALi4udO7cmfXr19OjR490z1+0aFH8/PxSbVu8eDENGjTgzp07+qZzIYRxSNAm8On+TzkceBgrUysWt1pMI9eCvwrCi3gQ8B9+K5fw4OYNAFwrVKb1R8Mo4VE20+NC5szl4Y6dYG5OmSWLsapcKT/CzTKZe67wynHvR0dHR+rXT7/aObc9WxuklMryyCFvb2/Onz+f5WtZWlpiaWmJr6+vvkk5q5RSJKfTty8/mFlaZvk1iYiIYOfOnUyfPj1VQpfCwcGBTZs2ER4ezuh0ht136tSJSpUqsXbt2gyTuvRER0ej0WhwcHDI8jFCCMNL0Cbwyf5P+Dvwb6xMrVjSagkNXRsaOqw8kxgfx9H1v3B2+xaU0mFpY0uzXn3xatUOjUnmzZIRa9YQsWoVAKVmTC9wy3/J3HOFW4Ee0lK8eHFMTU3T1MqFhITk+UCHoUOHMnToUH17eFYkJyTwTV/DzA7+8Y9/ZNgU8KyUGtYqVapkWOb69SfrFVatWjXd/VWqVNGXyYr4+HjGjRtHr1698qVfgRAidyRqE1MldL6tfGng2sDQYeWZZwdCVG7cjJZ9P6SIo9Nzj43x8+PBzK8BKDFyJEU7dcrTWLNDp9VxZudtmXuukCvQSZ2FhQXe3t74+fnxxhtv6Lf7+fnRpUsXA0Zm3J7uC5nVsultTzn+l19+YeDAgfp9O3bsSLWqSFJSEj179kSn07F06dIXCV0IkY+SdEmMOTiGvwP/xtrMGt9WvtQvmT8tNPkt7UAIF177YDBl69TL0vFxly5x/7OxoBQOPXtQ7MOCs1pETHgce364TNB/0YDMPVeYGfyOPnr0CH9/f/3jgIAAzp8/j5OTE+7u7owcOZLevXtTr149GjduzMqVK7lz5w6DBg3K07hy0vxqZmnJxz/+kYdRZX7trKpYsaJ+1PLTI42fVqnSkz4gV65coUmTtB2hr169SrVqT2ZM79y5Mw0b/q8ppnTp0vr/JyUl0b17dwICAti3b5/U0glhJLQ6LV8c/oJ9d/c9mbbEZ1GhTOieHQhhYmqKd8c3aPxWT8wts9b6kfQghHuDh6Di4rB95RVKfvllgZlc+MapBxz49RqJccmYW5nS4p3KVG5YsAZtiNyTrSlN8sKBAwfw8fFJs71v376sXr0aeDL58OzZswkKCqJGjRosWLCA5s2b50t8mQ1HNuapMNq3b8+FCxe4du1amn51UVFRmJub4+7uTsuWLdmwYUOq/Vu2bKFLly789ttvmfapS0nobty4wf79+ylRokSePJcXZcz3UYi8oFM6Jv49kT//+xMzEzMW+SyieZn8+c7NT2kGQlSqQusPh1HC3TPL59DFxXH7vd7EX7qERfnyeP62FlM7uzyKOOsS45M5/Nt1rh5/0n3Jpaw9rftXp2gJ6+ccKXJTfk9pYvCkrqB6uqbu+vXrhS6pCwgIoEmTJjg5OTF16lS8vLxITk7Gz8+PZcuWceXKFf744w969uxJ//79GTZsGPb29uzdu5cxY8bQqlWrTKc0SU5O5q233uLs2bNs3bo1VR9IJycnLCwKzigrY76PQuQ2pRTTT0xn3bV1mGhMmNtiLq09Whs6rFyV/kCIfni1avvcgRBPUzodgZ+O5OGuXZg6OOC5fh0WBWBk/4OAGHb/cImY0Dg0GvBu70n91z0xMZW55/KbJHUFTGGtqQMICgpi+vTpbN26laCgIEqUKIG3tzeffvopLVu2BODw4cPMmDFDP/lwhQoV6N+//3MnH7516xZly6Y/7H///v368xcExn4fhcgtSinmnZ7Hj5d/RIOG6a9Mp1P5gtPZPzfcPHeKPd8t5WHY/w+EaNIcn74fYuuQ/Wm5Qr/5hrCly8DcHI8fvscmn2aEyIhOpzi3+zYntwSg0ymKOFnS+v3qlKroYNC4XmaS1BUwhTmpE0/IfRTiCd/zviz/ZzkAkxpPolslw4zmzwuxUZHsX72Sa8eerB2e3YEQz4r+ayv3x4wBwHX6dBzeejPXYs2JmLA49v54hfs3ogCo4O1My3crY2ljbtC4XnYFekUJIYQQhdPqi6v1Cd24BuMKTUKndDou7Pfj0C8/kBAbi8bEBO/Xu9KkW68sTwP1rLgLFwj64gsAnD7ob9CETinFlb+DOPL7DZIStJhZmtK8R0WqNHYtMIM1RP6RpC4DORn9KoQQxmiz/2bmnZkHwCd1P+Hdqu8aOKLcER54F7+VSwi8egkAl3IVaP3RcFzKls/xOZPDwrg3bDgqMZEiPj44P7UCUX6LjUpg/89XuX0xHADXCkVp1bcqRUvYGCwmYViS1GUgJ5MPCyGEsdl/Zz+Tj04GoF/1fgyoWXDmV8spbXIyJ//8nRMb16FNTsbc0oqmPXpTp11HTDLpC/w8KimJwBGfkvzgARZly1Jqzmw0L3C+HMehFDdOP+DQ2uskPE7G1MyEhl3KUauVGyayMsRLTZI6IYR4SZ0OPs2YQ2PQKi1dyndhpLfhap1yS+jtAHYuXUjIrf8AKFe3Pq36D8a+hPMLn/vB7Dk8Pn0aE1tbyvguwbRIkRc+Z3bFRidweN11/jv7ZKBHCXc7XutXDadSaZd8FC8fSeoykJ3mVxlrYtzk/omX0bWIawzfN5wEbQIt3Voyuclko+6DlVI7d3zDOnTaZKyK2PFq/0FUadI8V55X1ObNRP70EwClZs/Csly5Fz5ndiiluHI0iKMb/El4nIyJiYZ6r3tSt50HpjJVifh/ktRlICvNr+bmT0YVPX78GGtrmdDRWD1+/Bj43/0UorC7+/AuA/0G8ijpEXWd6zKn+RzMTIz3z0HonVvsXLqAkIAntXMV6jfmtQFDcjRNSXriLl4ieNJkAIoPGYxdq1a5ct6sinrwmAO/XCXwehTwpHbOp3cVSrgZfpJjUbAY76e4ADA1NcXBwYGQkBAAbGxsjPqX7stGKcXjx48JCQnBwcEh03n3hCgswuLC+Gj3R4THh1PZsTKLWy3Gysw4p/LRJidz6s8/OLbht//Vzr0/kCpNW+Tad3FyZCT3Ph6OSkjAtkVzig8blivnzQqtVsd5vzuc2noLbbIOM/Mnfee8fMrIRMIiXZLUvaCSJZ+soZeS2Anj4+DgoL+PQhRmsUmxDNkzhHuP7lGmSBmWt16OvYVxrscccf8e2xfP5cHNJ2uHl6/XiNYfDs212jl4Mh3K/TGfkXw/CHMPd0rPmZOtFSdeROC1SA6tu07E/VgA3Ko60qJXFVnmS2RKkroXpNFocHV1xdnZmaSkJEOHI7LJ3NxcaujESyFZl8yog6O4EnEFJysnVrZeSXHr4oYOK9uUUlw84Me+VStITkjAyrbIk9q5V1rmektJ+MqVxB45gsbKijLfLMY0HyaPfRgRz9EN/vifeVJRYGVrzitvV6BSw5LSEiSeS5K6DGR3njpTU1NJDoQQBZJSimnHp/F34N9YmVrh28oXN3s3Q4eVbfGxj/D71pfr/78qhHsNL9oNHYmdU+4np7EnThL6zWIASk6YgFXlSrl+jadpk3Sc33uH09tvkZyoQ6OBGs1L06BzOaxspb+vyBpZJuw58nuJDyGEyG3f/vst35z7BhONCQtbLsTH3cfQIWVb4LUrbF88h5jQEExMTWnS/T3qd34TE5Pc/zGdHBbGzTfeQBsaRtGuXSn19cxcv0YKpXsy59yJLTeJCYsHnkwi3KxHJRkIUQjIMmFCCCFyzV///cU3574Bniz/ZWwJnU6n5cSm9Rz7Yy1Kp6OoS0le/3gMrhUq58n1lFZL4JgxaEPDsKhQnpITJ+TJdQDuXong2Kb/CL3zEACbohY0ebMClRq4SFOryBFJ6oQQopA6EXSCiUcnAvB+9fd5p8o7Bo4oe2LCQtmxZB73rlwEoGozH1r1H4ylTd4tgxW2dBmPjx1HY21NmYULMcmDa4XcjuH4nze5ezkCAHMrU+q28aBWKzfMLaUbj8g5SeqEEKIQuhF5g0/3f0qyLpm2nm0Z4T3C0CFly40TR9m94hviYx9hbmXNax8MplrzV/P0mrHHjhG2dCkArlMmY1mhQq6ePzggmtPbb3H7wpO1Wk1MNdRoXpp6HTyxtrPI1WuJl5MkdUIIUciEPA5hyN4hPEx6SF3nukx/ZTomGuOY1ywpIZ4DP37Hv3t3AlCyfEU6fDwGx5Kl8vS6yZGR3P9sLCiFw9vdKNq5c66dO8g/ilPbb+lr5jQaqNjAhQYdy8kUJSJXSVKXgeyOfhVCiIIgPjmej/d9THBsMJ72nnzz6jdYmloaOqwsCbl1k23fzCEi8C5oNNTv/BZNu7+LqVnejv5UShH0xZckh4ZiUb48Lp9//sLn1OkUAedD+WfvXYL+iwZAY6KhcqOSeLf1wMEl75qQxctLRr8+h4x+FUIYC6UU44+MZ9vNbRS1LMra19fiZlfwpy5RSnFu51YO/fID2qQkbB2daD90JB41a+fL9SN/+43gyVPQmJvj+ft6rKpUyfG5EuKSufL3ff7df4+H4U9Gs5qYaqjS2JW6bT2kZu4lI6NfhRBC5MiqS6vYdnMbphpT5reYbxQJ3eOYaHYtW8jNs6cAKFe3Pm0Hj8DGPv01t3Nbgr8/D2Z+DUCJUSNzlNAppQi985DLfwdx/WQwSfFPWnisbM2p3rwUNVuUwdbBOGpLhXGTpE4IIQqBQ/cOsfDMQgDGNhhLA9cGhg0oC25fOM8O3/nERkZgam5Oi/f6U7ttx3ybzkOXmEjg6DFP1nVt2hSnPn2ydXx8bBI3Tj3g8t/3Cbv7SL/d0dWWWq+WoXLDkphZyGhWkX8kqRNCCCN3M+omYw+NRaHoVqkbPSv3NHRImdImJ/P3+p85tWUDKIVTaTc6fvIZJTzK5mscofPmk3D1KqaOjrjOnJGldV21STruXA7nxukQbp4PRZukA8DUzIRydUpQrakrpSs7yjxzwiAkqRNCCCMWnRDNx/s/5lHSI+o61+XzBp8X6IQiKjiIbd/MJvi/GwB4vdaOln0GYG5pla9xPDryNxE//giA64zpmDs7Z1hWq9Vx72ok/qcecPOfMBLjkvX7nErZUu2VUlRuWFKW8xIGJ0mdEEIYqWRdMp8d+ozbMbdxtXVlfsv5mJsW3MTi8qF97Pl+GUnxcVjZFqHNwI+p2LBJvseRHBnJ/fHjAHDs1Qs7n7SrbOh0ivvXI7lxJoSbZ0OJj03S77MtakGFei5UrO+Cs4ddgU6ixctFkjohhDBSC84s4Oj9o1ibWfPNq99QzLqYoUNKV8Ljx+z9filXjhwAoEzVGrQfNgr74iUMEs+Dr756sgxY+fI4fzZGv13pFEE3o/E/HYL/2RDiYhL1+6ztzClf15mK9VxwLV8UjYkkcqLgkaQuAzJPnRCiIPvT/0/WXF4DwFdNv6KKU86n4chLQTeusW3xHKIfBKMxMaFxt3do+EZ3TEwMM4AgZvt2YrbvAFNTSn39NRpLS0Jux3Dj1AP8z4TwKDJBX9bSxozydUpQob4LpSs6YGJqHBM4i5eXzFP3HDJPnRCioPkn9B/e3/k+SbokBnoNZFidYYYOKQ2dTsupLRs5uv5ndFot9iWc6TB8DKUrVzVYTMmhodzs2AltdDTm/T8lrHIrbpwOISY0Tl/G3MqUcrVLUMHbGbeqTpiaSSInck7mqRNCCJGhB7EPGLF/BEm6JF51e5UhtYcYOqQ0HoaHsWPJPO5evgBA5cbNeO3DoVjZFjFYTEopbkyYRYBDY0JrNuHRzWJw8zYAZuYmeNYqTkVvF9xrOGFmLtOQCOMkSZ0QQhiJ+OR4Ptn/CWFxYVRwqMDMZjML3Jqu10/8jd+KxcTHPsLc0gqf9z+iRsvWBhtMkBCXzI1TD7i47RLhdID/nzXFxEyDR/ViVKzngkfNYlhYyZ9DYfzkXSyEEEZAKcWko5O4FH4JB0sHFr+6GBvzgrN+aGJ8HPtXf8vF/bsBcClXkdc/Ho2ja+l8j0XpFPeuRXLlaNBTc8mZoVFaXIomUK2rN+VqF8fSpuCOFBYiJySpE0III7Dq0iq2B2zHVGPKvBbzKGNXxtAh6QX/d4Pti+cQGXQfNBoadOlGk7ffxdQsf//EPIpM4PKRQK4cC+JRxP8GPNjponC5uQ/PEo+ptPRbNKbSvCoKJ0nqhBCigHt6CbBxDcYVmCXAnh0MUaRYcToMHYlbda98i0Epxf0bUVw4cI+b58NQuidj/yyszahY34XSMf+QtHASJlZWlP1ukyR0olCTpE4IIQqwZ5cA61G5h6FDAiA65AG7li3UD4ao1LApr300DOsidvly/cT4ZK6fCObCwUAi7sfqt7tWKEqN5qUpV7sEugf3udn5azSA8+jRWHh65ktsQhjKS5PUPX78mKpVq/L2228zd+5cQ4cjhBDPVRCXAFNKcWHfbg6s+Y6k+Lh8HwzxKDKef/be5dKR+yTFP5lH1MzChEoNS1KzRRmKlymijzNw4kRUXBw29evj2OudPI9NCEN7aZK66dOn07BhQ0OHIYQQWVIQlwB7GBGG34rFBJw/A0DpKtVoO3gEjiVL5fm1wwMfcd7vDtdPPkD3/02sDi421GhemiqNS6YZ9BC9YQOPjx1HY2mJ67Sv0JgUrFHCQuSFlyKpu3HjBlevXqVTp05cvHjR0OEIIcRzFaQlwJRSXD1ygL2rlpMQG4upuTmv9OxD3Q6d83RliJT+cud23+H2xXD99tKVHKjd2h2P6sXSXa4r6UEID2bNBqDExx9j4eGRZzEKUZAY/KfLoUOH6NSpE6VKlUKj0bB58+Y0ZZYuXUrZsmWxsrLC29ubw4cPZ+sao0ePZubMmbkUsRBC5K2nlwCb/sp0gy4BFhsVyV/zZ7J9yTwSYmNxKVeR3l9/Q72Ob+RZQqfTKf47G8Ifs86wef45bl8MR6OB8nWd6TauHl1H1sWzZvF0E7r/a+++w6Mq04ePf6dlkknvhRRqQugQkJogCGgQEeV1lXURdC38llVZLKvLSlmaIoINFFaUXUUXXRVXVoWsgIAgIBpaaAFCSE9IL5NMOe8fwQgGJMAkJ8zcn+uaazLnnDnnnuek3Hmqoijk/e1v2CsqcO/enYBJ9zVLjEK0RqrX1FVVVdGzZ0/uv/9+xo8f32j/2rVrmTZtGsuXL2fw4MGsWLGC5ORk0tLSiI6OBiAhIYHa2tpG7924cSN79uwhNjaW2NhYduzY0eyfRwghrsW+wn3M2TkHgCk9pzAyZqQqcSiKwsHNKXzz3ipqq6rQ6nQMHD+BG8bdhbaZRpBa62wc+S6P1JRMys4t3aUzaIkfGE7PEVH4hVx+Xr6Kr76i8uuvwWAgfN48NC08rYoQampVa79qNBo+/fRTxo0b17Ctf//+9OnThzfeeKNhW3x8POPGjWtS7duzzz7Le++9h06no7KyEovFwhNPPMHMmTObFFPDum3b3sLHq/VM9CmEcD75lgruOfY2RdYqbvKNZUnMeLQqDIwoPltOyle7yMosACA0LIBRo/sTEhrQLNczmzUcPGRi/wETNeb6BiSj0U73btV071aNyaNpf6asFdWcfGI5tvJqgsYnEXzXjc0SrxBNVV5ZjW/igy229murTurq6uowmUx89NFH3HHHHQ3HPf7446SmpvLNN99c0flXr17NwYMHf3X0a21t7QW1fuXl5URFRVH2jDc+RnVHnQkhnJdZo2FyeAiHjEY61dXxXk4+phb+9WxTNOw5G8l3RdHYFC16jY3BwafpE5DNRVo6r1m5LZh9VbeRVjMCq+IBgLe2gJ6e/yHe42vctOYrOl/2Tj/KT5sw+lpoN6oQjUxJJ1RWXqvg+3xFiyV1rbpeuqioCJvNRmho6AXbQ0NDycvLa5ZrLly4kDlz5jTe0f5G8JAlZYQQjqcoCrOUPA4pFfih5VX3OEwdurVoDFln7Xx9wEpRRX0i2TZYw4geHvia4oF4h16rsDKIH7N7k17YEeVc1+4gz0J6R/5Ix6B0tBoFGHJF56xMr6D89BnQQPidsWja9HRozEJclRoL8HmLXa5VJ3U/+eXcR4qiXNV8SJMnT77sMc8++yzTp09veP1TTR13vwctkGULIVzPOwff5ou9S9Fr9CwZtZLIsH4tdu3KkmK2rnmHwzs2A+Dh7cOwSQ/ReciNDp13TlEUsg6X8GPKac4cLmnYHtnZnz6jYoiM90ejubqJlW2VleSOuQ2AgEmT8fjznx0SsxDXrLwcHvZtscu16qQuKCgInU7XqFauoKCgUe2doxiNRoxGI8uWLWPZsmXYbLZmuY4QQkDjJcD6tVBCZ7Na+OHLz9n57w+wmGtAo6H78FEMuec+TD6O+yNkt9lJ/6GAHzdmUnSmEgCNVkPHhBB6j4wmOPraV6AoeOklrHl5GKKiCH78sWs+nxDXq1ad1Lm5uZGQkEBKSsoFfepSUlK4/fbbm/XaU6dOZerUqQ0DJYQQwtHOXwLsrti7uLtzyywBdnp/KpveeZPinCwAwjvGMfyBKYR16OSwa9TVWDm8I5d9X5+hori+b5zeTUuXwRH0vCkKnyAPh1ynJjWV0n+tBSB87t/QejjmvEJcj1RP6iorK0lPT294ferUKVJTUwkICCA6Oprp06czceJE+vbty8CBA1m5ciWZmZlMmTKlWeOSmjohRHMqqy3j0U2PUmmpJCE0gWdveLbZr3k2K5Ot76/m5N7dAHj4+JL028l0HXqTw1ZcKMmr4sCWbI7szMVSW//708PbQI9hkXRLisTdy3F9kxWLhdxZs0FR8L3jDjwHDHDYuYW4Hqk++nXLli0MGzas0fZJkyaxevVqoH7y4UWLFpGbm0u3bt1YunQpSUlJLRJfw5QmLTRyRQjh/Kx2K3/43x/YmbuTCM8IPhjzAQHuzTNdCNT3m9vx0RoObkpBUexotFp63Xwrg+66F3dPr2s+v2JXOH3oLAc2Z5GZVtyw3T/MRI/hUXQeEIbezfFDUc+uWkXBi4vR+fnR/ssv0Pv7O/waQlyLls4hVE/qWjtJ6oQQjrZozyLeTXsXD70H7ya/S1xAXLNcp85cw/eff8L3n3+Kpba+CbRjv4Ek/nYSARGR13z+qrJajn6Xx6HtOZSfmywYDbTtHkSPYZFEdvZ36GCL81myszkx5jaUmhrC58/Hb/ydzXIdIa5FS+cQqje/tlbS/CqEaA7r0tfxbtq7QP0SYM2R0NltNg5s2sCOj96nuqwUgPBOcST97gEiO3e9xnPbyUwrJm17DhkHzqLY6+sFjCY98YPC6TY0Et/g5u3XpigKeXPnodTUYOrbF98777j8m4RwAVJTdxlSUyeEcJTUglQe2PAAFruF/+v5f/yh1x8cen5FUTixdzfb1rzTMAjCLyycxAmT6NR/8DXVmhXnVHFsdx5HduZSVVbXsD20nQ9dBkfQqV8oBmPLzPZbvnEj2Y89DgYD7T9bh7F9+xa5rhBXSmrqhBDCCeVV5fGnLX/CYrdwU/RNTOnp2MFeuelH2freO2QdPgjUzzc3YPwEeo68BZ3+6gYnlBXWkL43n+N7CjibXdmw3d3TQNyAMOIHhxMYce198q6ErbKS/HnzAQh88PeS0AlxHknqLkGaX4UQjmK2mnl88+MU1RTRyb8TC4YsQKtxzGjT0rxctv3rnxzbuQ0AvcGNhDHj6Dd2PEaT5xWfr6ywmlP7ikjfW0D+qfKG7VqdhuguAcT2D6N9z2B0BsfEf6UKX3kVa0EBhuhogh55RJUYhGitpPn1MqT5VQhxLRRF4c9b/8yXGV/iZ/Tjg1s/INL72gcp1FSU893H/yJ14xfYbVbQaOiadBOD7/4d3oFBTT6P3a5QkFHOqX1FnNpfREluVcM+jQbaxPnTqW8o7XsH4+6p7lKJNQcPkfGb34DdTtSqt/AaPFjVeIS4HGl+FUIIJ/LWgbf4MuPL+iXAblxyzQmdpa6WH7/8nN3rPqK2uj4Ba9uzD0n33k9wTLsmnaOqrJasIyVkHS7m9KGz1FRYGvZptBoiOvnRrmcQHRNC8PQ1XlO8jqLYbOTNmgV2Oz5jxkhCJ8RFSFInhBDNZFPmJl798VUA/jLgL9e0BJhit5O2bTPfrn2PirOFAAS3bU/SvffTtkfvX31vndlKzvFSsg6XcOZIMcU5VRfsd/PQE9M1gLY9g4juEqh6jdzFlKx5H/OhQ2h9fAh9RtZ2FeJiJKm7BOlTJ4S4FkeLj/LMtmcAmNB5AnfF3nXV58rY/yNb33ubwtOnAPAODGbIPROJH3LjRVeCsNbZyDtVTs6xErKOlpB/shy7/byeNhoIjvImKt6fqPgAwjv5odOp00euKSx5eRS+/DIAIdOnow9qevOyEK5E+tRdhvSpE0JcqWJzMRPWTyCnKof+4f15c8Sb6LVX/j90QcZJtr2/mox9PwBgNHlyw7i76J18Gwa3n5tFLXU28k6WkXOslOxjJeRnlGO3Xvir3SfIncj4AKI6B9Amzg8PL7dr+5AtKOvRx6hIScGjVy9i3l/jsCXNhGhu0qdOCCGuYxabhT9t/hM5VTlEe0fz0tCXrjihqzhbxLdr3+XQ1k2gKGh1enrdfCv97/gNJh9fLLU2zqQVk32shJzjpfVJnO3CJM7k60abWH/axPoR2Tmg2ScEbi4VmzdTkZICej1hc+ZIQifEr5CkTgghHERRFObvms8PBT/gZfDitZtew9fo2+T311ZXsfuzf/PDfz/Daqmf4DduYCL97/gtNZUm9n1dRM7x4xRkVFzYnAp4+RuJ6ORHm1h/Ijr54Rvi0WxLdLUUe3U1eXPnAhA4eRLucbEqRyRE6yZJnRBCOMj7R97n4+Mfo9VoWZS0iPa+TZsY12a1si/lS777+ANqKurnhguKiiUsbjTlZ/346IX0huW4fuIVYGxI4NrE+uMT5H7dJ3G/VLhsGdacXAwREQT9wbGrbwjhjCSpuwQZKCGEuBI7snewaM8iAKYnTCcxMvGy71EUhRPf7+Kb996mNC8HAL0xCK1hMBUV7ancqwHqkzyfIHciOvkR0am+SdUn6PpsTm0q85EjFK/+BwChM59DazKpHJEQrZ8MlLgMGSghhLicjLIMfvvFb6moq+D2Drczd/DcX601M1dZSNueyvefr6GiML1+o8YDvccgdG7d0Wi0+AR70KaTH21i/YiI9cc7wL2FPo36FLud0xN+S82+fXjffDORr7ysdkhCXBUZKCGEENeRstoyHt30KBV1FfQK7sXMgTMbJXQ1FXXkppeRfbyEzEOZFJzciL0u7dxeHTr3BAIik4iKDzvXnOqHl7/rJHG/VPrhh9Ts24fW05PQv/xF7XCEuG5IUieEEFfJYrfwxJYnyCjPIMwzjKXDlmLQGijJqyL3RFn9I72UsoIaFKUOq3kPNvNewApAQJve9B59D536dsTTr3Ws3KA2a2EhBS8tASB42jQMoSEqRyTE9UOSOiGEuAqKojDvu3n8kJ1KW3MX/uj7FLtX55B74jDmSst5x9mx1R3CXrcTu7USgLCO8Qy//0HCO8apFX6rlb/weewVFbh364b/byeoHY4Q1xVJ6oQQoomsdTaKsiopOF3OjtQf0WfG8UBNIhq0pO8vbzhOp9cS2s4Hd1MuWWmfU16aBYBfaDhJ995PxxsGOt1IVUeo3P4t5V98AVotYXNmo9Hp1A5JiOuKJHWXIKNfhXBdil2hotjM2ZwqinMqOZtd/1ycW33e1CJeBOBV/5W/keBob8I7+BHe0RetpoTt/3qHtN17AXD39GLA+HvodfOt6PStb13V1sBuNpM3Zw4AARN/h0fXripHJMT1R0a/XoaMfhXCedXVWCkrrKG0oJqyghrKCqopzqumOLcKa+3F/6EzeGo46ZZGvmcG8Z3bMXXk7/H0re8PV15UyI6P1pD2zSYUxd6wEsSA8ffg4eXdkh/tulPw8sucfXMF+rAw2q9fj87LU+2QhLhmMvpVCCEcQLErVFfUUVlSS1VJLRUlZqpKaqksMVNRXEtZYTU1FZZLvl+r1+Af5klghCcBEZ4ERnhhC6jmwW8nUWQuYkibIUwf/jB6rZ6ainJ2rfuI1A3rsVnqz9mx30CS7p2Mf3iblvrI163a9HTOrnobgNAZf5GEToirJEmdEKLVUxQFm8VOndlGXY0Vc5WFmkoLNRV1mM8917+2YK6so6bCQlVZbaP1UC/Gw9uAX4gJ32APfENM+IWaCIjwxC/EA63u53VGK+sque+rhykyF9HJvxMvJr2IUmdl15efsPuzf1NXUw1AZJduJE6YTERs52YrD2ei2O3kzp4NFgtew4bhPWKE2iEJcd2SpE4I8asURUFR6mu+FLuC/YJnLtxmU1CUn1/brAo2iw1rnR2rxY71p6/r6r+2WX7+2mqxY62zUVdTn7jVma31zzU26szWJiVov6TRgMnXiJf/uYefO14BRrz83euTuGAP3Dwu/2vQarfy1NanOF5ynCCPIF5LeoUT32xl578/oKq0BIDgmHYkTphE214JMgjiCpR9+ik13+9FYzIR9txfpeyEuAaS1AlxnbBabFQW11Jx1kxFiZnaKiu1NRbqqq3Umq3YLAp2mx27rf7ZZq1Psuy/SMYum5g1HEfD162GBtyMOowmAx7eBty93PDwNuDhZcDD2w33c88eXgY8/YyYfN3QnVfbdrUW7VnE9uztmDTuPG2cyBd/nU15YT4AviGhDP7N7+g8eCga7bVfy5VYi4spWPQiAMF//COGiAiVIxLi+iZJnRCtkGJXKMqqJOtICYWZ5RRkVlBWUKN2WBel1WrQaDVotD9/rdVp0Gjqn/VuOvRuWvQGLTrDz1/rDTp0531dv12Hm4cONw89bh56jB56DO46jB563Nz1GIw6NNqWrclZc3gNa9M+IDbLi6HZbUkr+QQAk68f/e+4m54jb5ERrVepYNGL2MrKMHbuTMB9E9UOR4jrniR1QrQSiqKQe6KMoztzOXXgLDXldY2O0Rt1eAe44x1gxN3LgNHDgNFUn/DoDFp0+vpESqvTotVp0Om0aHQaNBrqEy2t5ufE6xfPFyRlF33movuc2dcn/8en/17Gnelt8DLrsVCBp58//caOp8eIWzAYXXcpr2tV9d0uytatA42G8Dmz0ejlz5EQ10p+ii5B5qkTLcVaZ+Pwjlz2fX2GssKfa+P0Rh2Rcf6EtfchONqboEhvPLwN0ueoBdRWV7Hhs3fY99V/GWgOAMDTP4Abxo6n+4hbMLjJkl7Xwl5XR97s2QD4T7gHj5491Q1ICCch89RdhsxTJ5qLzWrnwJYsfthwumFqDYNRR8eEEDrdEEpERz90eumj1ZLKiwr54YvP2Pf1V1jNZgCsJh3D75pMrxGjJZlzkMLXl1H0+uvogoPo8MUX6LxlDj/hnGSeOiFcQOahs2z78Dil+fXTYHgHutN7ZDSdB4ZjMMrSSC1JURRyjh0hdcN6jn23Hfu52vkSrzqKu3vxwsPv4G3yVTlK51F78hRnV6wAIGzGDEnohHAgSeqEaEF1ZivbPzrO4W9zgfo50gbc3oG4gWEOGaUpmq62uprD27ewL+ULijIzGraXh+nYFZkD7QJ579aVeHtIQucoiqKQN3s2isWCZ1Ii3jffrHZIQjgVSeqEaCH5p8rZuOog5UVm0EDPYVH0u60dxibMkyYcQ1EU8k4c4+DmFA5v/waLub4Po97NSNygRFIC0tho3omv0Zd3R75BkEeQyhE7l7LPPqN692407u6EzZwp/UOFcDD5ayJECzjyXS5b3juKzWrHO8CdmybH0ybWX+2wXEZpfh6Ht23m8PbNlOTmNGwPiIik56jRxCcO46WDr7Dx6E7ctG68Nvw12vm2UzFi52MtKaHg+RcACP7jVNwiI1WOSAjnI0mdEM1IsSvs+PQEqSmZALTtEcSI+7tI7VwLKC8qIH3PdxzdsY2cY4cbtuuNRjr1G0j34aOI7NIdjUbDqgOrWHt0LRo0PJ/0PL1DeqsYuXMqeHExttJSjLGxBEyapHY4Qjgl+csiRDOx2+xs+ucRju7KA6Dv6LbcMKad08/tphZFUTh75jTpe77j+J6dFJw60bBPo9ES3b0n8UNupNMNA3HzMDXsW39yPS//8DIAf77hz4yMGdnSoTu9qt27KfukftLmsDmz0RhksmYhmoNLJHV6vZ5u3boB0LdvX9566y2VIxLOzmqxsfGtQ5zaV4RGq+GmSfHE9Q9TOyynU1NRTubBfZze/yOnD6RSXljw806NhjZxXejYbwCdByXhFRDY6P27cnfx3LfPATCpyyTujb+3pUJ3GfVz0s0BwO+euzH1llpQIZqLSyR1fn5+pKamqh2GcBE2m50Nfz9Exv4idHotNz/cjXY9pMO9I1SVlpBz/Ag5Rw9z5tB+8k+dgPOm2tQZDMR070XHfgPpkHADJl+/S57r8NnDPL75cax2Kze3vZnpfae3wCdwPcWrVlF38iS6oCBCpksZC9GcXCKpE6Kl2O0KX68+XJ/QGbSMmdqDyM4Baod1XbLUminKPE3+qRPkHDtM7rEjlObnNjouKCqGmB69iO7ei8j4bri5e1z23GfKz/B///s/qixV9A3ty/wh89FqZEoZR6vLyKDojTcBCH32GXQygbsQzUr1pG7r1q28+OKL7N27l9zcXD799FPGjRt3wTHLly/nxRdfJDc3l65du/Lyyy+TmJjY5GuUl5eTkJCAh4cH8+fPZ+jQoQ7+FELU9+n65oOjHN+Tj1ar4ZaHu0lC1wQ2q4WygnxKcrMpyjxNwelTFJ4+RUlu9gW1cABoNARFRhMRG0+bzl2I7t4LL/8rK+OimiIeTnmYs+azxPnH8erwVzHqZKUIR1MUhdw5c1Dq6vAcMgSf0aPVDkkIp6d6UldVVUXPnj25//77GT9+fKP9a9euZdq0aSxfvpzBgwezYsUKkpOTSUtLIzo6GoCEhARqa2sbvXfjxo1ERESQkZFBREQEBw8e5NZbb+XAgQOy5JdwuB82nCZtWw4aDYx4oAttu0uTK9T/ca+pKKfibNG5RyGlebmU5GZTkptNWUE+it1+0feafP0IjmlHRGxnImLjCe8Uh9HkedWxVNRVMCVlClmVWUR6RfLmyDfxdpMVDZpD+fr1VO/8Do3RSNgsmZNOiJbQqtZ+1Wg0jWrq+vfvT58+fXjjjTcatsXHxzNu3DgWLlx4xddITk5m7ty59O3b96L7a2trL0gQy8vLiYqKkrVfxa86+WMhX644AEDi3bH0GObcc3ApioKl1kxNeRnVZWVUl5dRXV5KTXk51eVl1JSVUllaQkVRIRVni7DWNf6n63wGozv+4W0IaBNJcEw7QmLaEdy2PZ5+jpvLr9ZWy5SUKXyf/z2B7oG8m/wuUT5RDju/+Jm1pISTo2/FVlJC8LRpBE15RO2QhFCFrP16nrq6Ovbu3cszzzxzwfZRo0axY8eOJp2jpKQEk8mE0WgkKyuLtLQ02rdvf8njFy5cyJw5c64pbuFaCjMrSHnnEADdhrZpkYROURQUux2bzYrdasVmPe/Z9tOzDZvVcm6fDbvVgs1mqz/up/dd9P02rHW11FZXU1dTTW1NNXXV555rquu3V1djt1mvKGaTrx/egcF4BwbhGxpGQHgb/MMj8A9vg6d/QLPW5NjsNv689c98n/89ngZP3hjxhiR0zSh/4UJsJSUYY2MJfOB+tcMRwmW06qSuqKgIm81GaGjoBdtDQ0PJy8tr0jkOHz7MI488glarRaPR8MorrxAQcOk+OM8++yzTzxuh9VNNnRAXY66y8OWbB7DW2YmK9yfxN52a/F5FUagqLaEsP4+ywnzKC/KprijDXFGBubICc2Ul1rparBYLVksdNosFa10dNksdNputcX8zFegNbnj4+mLyqX94nHuYfHzx9POvT+KCgvAOCELv5qZKjIqiMPe7uXyd+TUGrYFXh71KfGC8KrG4gspt2yj/z+eg1RI+by4ale67EK6oVSd1P/nlf/CKojT5v/pBgwZx4MCBJl/LaDRiNEqnaXF5iqLw9T8OU1FsxifInZsf6oZWd+kRlBazmazDB8k6coj8k+nknzqBuaLcYfFotFp0Oj1aff1Dd+6h1enQ6Q3nnvVo9QZ0Ol3DMVrduefzjtcb3HAzeWL08Kh/NpkwephwM5lw8zBhNHli9PTEYHRv9X2lXk99nY+Pf4wGDS8kvcAN4TeoHZLTsldVkTtrFgABEyfi0aOHyhEJ4VpadVIXFBSETqdrVCtXUFDQqPbO0ZYtW8ayZcvqa0SEuIjUlDNk7C9Cq9dwy8PdMZoaz5JfXVbK0Z3bSN+zk+wjadisFzZZajRavIOC8A0OxSckFE8/f9y9vPHw8sbo5YXB6I7eYEBvcEPn5oZOb0BvMKAznJek6fRo9Tq0Wl1LffTrxprDa1i5fyUAfx3wV1ktopkVvPwK1pxcDG3aEPz4Y2qHI4TLadVJnZubGwkJCaSkpHDHHXc0bE9JSeH2229v1mtPnTqVqVOnNnRyFOJ8eSfL2LmufhmqxN/EEhz98whKu93Gie93sf/rDZze/+MFIzt9gkOI7taTsA6dCG3XkaDotqo1Szq7r059xQu76xeQn9prKr+J+43KETm3mtRUSt57D4CwOXPQmkyXeYcQwtFUT+oqKytJT09veH3q1ClSU1MJCAggOjqa6dOnM3HiRPr27cvAgQNZuXIlmZmZTJkypVnjkpo6cSl1Zispbx9CsSt06htC18SI+u011RzYtJEfvvyc8sL8huPDOnSi8+ChtOvdD//wiFbfXOkMtmVt49ntz6KgcE/cPTzSQ0ZfNielro7c554DRcF33Di8hgxWOyQhXJLqU5ps2bKFYcOGNdo+adIkVq9eDdRPPrxo0SJyc3Pp1q0bS5cuJSkpqUXia+nhyKL12/L+UQ5tzcYrwMiE5/qj0dnYt/ELdq/7iJpzfeTcvbzpcdPNdL1xJAERbVSO2LXszd/LlJQpmG1mbml7C88nPo9OmqabVeHryyh6/XV0AQG0/+969P6Om4pGiOtZS+cQqid1rZ0kdeJ8mYfO8vlr+wAY+3hPygtS2f6vf1JZfBYAv7Bw+o0dT/yQGzEY3dUM1SUdOnuI32/4PVWWKpIik3h52MsYtI37OgrHqU1P5+Qdd4LFQpslL8nKEUKcR+apayWk+VX8krnKwqZ/HgagYx8t2z94gZyjaQB4BwUzcPwEug69Ca1OaoXUcLL0JP+X8vN6ri8NfUkSumam2Gzk/vU5sFjwuvFGvJOT1Q5JCJcmNXWXITV14ieb/nmYtG/PoNPupqZ0N4rdjsHozoDx99Bn9O3oDZJAqCWrIotJX06ioKaAroFdeWvUW3i5eakdltMrfm8N+fPmofX0pP1/12MIC1M7JCFaFampE6IVyjlewqGtqViqvkKx1ze1xvYfzND7HsQnKFjl6FxbYXUhD6c8TEFNAR18O/DmiDcloWsBdVlZFCxZAkDwE9MloROiFZCk7hKk+VX8xFpr5fNXVlFXsRWwY/L1Y9Qjj9EhQSaxVVupuZSHUx7mTMUZ2ni1YeWolfi5+6kdltNT7HZyZ/wVpboaj74J+N9zj9ohCSGQ5tfLkuZX11ZTUc4Hs+ZSkl3fl65DwkBGTfkjJh+Zu1BtVZYqHtr4EAeKDhDiEcLq5NVEecuSfi2h+P33yf/bXDTu7rT/bB1uMTFqhyREqyTNr0K0EnknjvPZ4gVUFhcCenrdMpHhk++UeeZaAbPVzKObHuVA0QH8jH6sHLVSEroWUpeVRcHilwAImT5dEjohWhFJ6oS4iMPbt7DhjZexWa1otL5Edf8dwyffIgldK2CxW3jqm6fYk7cHT4Mnb454kw5+HdQOyyUodju5f5mBUl2NqW9f/H93r9ohCSHOI0ndJUifOtekKAq7PlnLtx/WL3ekNbTHzSuZEQ8kSULXCtjsNmZsn8GWrC0YdUZeG/4aXYO6qh2Wyyj54AOqd+9G4+FB+IL5aLRatUMSQpxH+tRdhvSpcx02q4WUlcs49M3/APAMHIjVNoCew6NIvDtW5eiEoijM+24eHx77EL1GzyvDXyEpsmVWlhFQd+YMJ8fejlJTQ+iMGQRM/J3aIQnR6kmfOiFUUFtdzX9emkfmwf1oNFo6J93Dqf1huHvp6TemndrhuTxFUVj6w1I+PPYhGjQsTFwoCV0Lamh2ranB1K8f/vf+Vu2QhBAXIXXnwuXVVJTz0dwZZB7cj8HdgzHT/kLuyfpO9zeMaY+7p0wqrLY3973JOwffAWDmwJnc0u4WlSNyLSXvf0D1nj1oTCZpdhWiFZOfzEtYtmwZXbp0oV+/fmqHIppRZfFZ1s5+hvyTx/Hw9uHuWQs5mxuEudKCf5iJrkkRaofo8t4++DbL9y0H4Ol+T/P/Yv+fyhG5lrrTpyl46dxo1yem4xYlo4yFaK0kqbuEqVOnkpaWxp49e9QORTST0vw8/jXrac5mZeIVEMjds1/AKzCK/ZuyABh0Z0d0OvkRUdOaw2tYuncpAI/3eZyJXSaqHJFrUaxWsp9+ur7ZtX9//CdMUDskIcSvkL9YwiWVFeSxds4zlBXk4xcazj1zFhEYGcX3X2RgtdgJa+9LTPdAtcN0aR8d+4jndz8PwCM9HuHB7g+qHJHrKVqxAvO+/Wi9vYlYuECaXYVo5WSghHA55UUFfPi3GVSeLSKgTRR3PTcfL/8AygprSNuWA8CAce1lChMV/efEf5i7cy4Ak7tOZmqvqSpH5HpqDhygaPkbAITNfA5DhHRFEKK1k3+7hEupLD7LR3NnUF6Yj394RENCB7Bn/SnsdoWoLgG0ifVXOVLX9dWpr3ju2+dQUJjQeQLTE6ZLgt3C7NXV5Dz1NNhs+IxOxmfMGLVDEkI0gSR1wmXUVlfzycJZlObl4hsSyl3PLWhI6M7mVHJ0dx4AA25vr2aYLm1T5iae2fYMdsXO+E7jeeaGZyShU0HB4sXUZWSgDw0lbOZMuQdCXCckqbsEGf3qXGxWK+tffp7CzAxMvn7c9dx8vAODGvZ//98MUKB972BCYmSSaTVsz97Ok988iU2xMab9GJ4b8BxajfyKammVW7dS8v4HAEQsXIDOz0/dgIQQTSa/MS9BRr86l82rV5Cx7wf0RiN3/HkWviFhDftK8qpI/6EAgH63ykTDatiVu4tpm6dhsVsYFTOKuYPnotPq1A7L5VhLSsiZMQMA//sm4jlokMoRCSGuhCR1wukd3PI/9qV8CRoNtz72NGEdOl2w/4cNp0GBtj2CCIr0UilK1/VD/g88uulRam213Bh5I88nPY9eK2O4WpqiKOTNnIWtsAi3jh0ImT5d7ZCEEFdIkjrh1AozM/h6Vf0IvsF33UvHvv0v2F9eVMPRXfkAJCTHtHh8ru5A4QH+8PUfqLHWMChiEItvXIxBKyt4qKH0w4+oSEkBg4E2ixahdXdXOyQhxBWSpE44LUutmc+XPo+1rpa2PfvQ/47fNDrmx42ZKHaFyM7+hLXzVSFK13Wk+AiP/O8RqixV9Avrx8vDXsaoM6odlksyHztG/oIFAIRMm4Z7ly4qRySEuBqS1Amn9e3adynJycLLP4DkPz7RaOLUqtJaDu/IBaDv6LYqROi60kvSeXjjw1TUVdAruBevD38dD72H2mG5JHtNDTlPPIFSW4tnYiIB909WOyQhxFWSpE44pewjaez94j8AjHrkMUw+jWvh9m8+g81qJ7yDLxGd/Fo4QteVUZbBQykPUVJbQtfAriwfsRyTwaR2WC4rf+Hz1B5PRxccRMTzC2XVCCGuY/LTK5yOta6ODW++AopC16EjaNe7b6NjLLU2Dp1bPaLXyGiZh6uFZFVk8eDGBymqKSLWP5YVI1fg7eatdlguq/yrryj98EPQaGizaBH6QFkaT4jrmSR1wuns/e86SnKz8fQP4Mb7Lr5e6JGdudRWW/EJ9qBtj6CLHiMcK68qjwc3Pkh+dT7tfduzcuRKfI3Sj1EtdVlZ5D43E4DAhx/Gc+BAlSMSQlwrSeouQSYfvj5VFBex69MPAUi6937cvRpPUaLYFfZvzgKg5/BItFqppWtuhdWFPLjxQbIrs4nyjuLvo/5OoIfUCqlFsVjIfuIJ7BUVePTuTfAfZW1dIZyBJHWXIJMPX5+2vf8PLLVmwmM7Ez/kxosec/rQWUrzq3Hz0NN5YHjLBuiCis3FPLTxIU6XnybCM4JVo1YRYgpROyyXVrBkKeZ9+9H6+NBm8YtoDDKNjBDOQJI64TTyThzn8LbNAAyf9PAl+8nt+/oMAF2GRODmLpPcNqey2jIeSXmEE2UnCDGF8Naotwj3kkRaTeUbNlL8zjsAhM+fh6FNG5UjEkI4iiR1wml8++F7AMQnDiOsY+xFjzmbXUnWkRI0Wg09hkW2ZHgup6KugikpUzhSfIRA90DeGvUWUT5Raofl0mpPnSL3L38BIOD3D+AzcqTKEQkhHEmSOuEUso8eJiN1LxqtloH/b8Iljzu0NRuAdj2D8A6QGfObS7WlmqlfT+Xg2YP4Gf34+6i/085X1tVVk726muzHHsdeVYWpb19C/vQntUMSQjiYJHXCKew4V0vXdegI/MMiLnqMpdbG0V15AHRLkian5mK2mnl006P8WPAj3gZvVoxcQSf/Tpd/o2g2iqKQO3s2tceP189Ht+QlNHrpeiCEs5GkTlz3sg4fJPPgPrQ6PQPH33PJ445/n0+d2YZPsAeRcf4tGKHrqLPVMW3LNHbn7cakN/HGyDfoEihLTqmtdO1ayv/zOeh0RC5ZgiFEBqoI4YwkqRPXvT3/+RiAbjeOwCf40n+sfmp67TokAo1MY+JwFruFJ795km+zv8Vd586ym5bRM7in2mG5vJr9+8mff25d1+nTMck0TUI4LZdI6k6dOsWwYcPo0qUL3bt3p6qqSu2QhIOczTrDyR/2gEZD39vuuORxhZkVFJyuQKvTED9IRl86mtVu5dltz7L5zGbctG68OvxV+oY1XslDtCxLQQFZf3wUxWLBe+QIAh64X+2QhBDNyCU6VUyePJl58+aRmJhIcXExRqNR7ZCEg3y//lMAOvYdgH/4pfvJHdxWX0vXoXcwHt5uLRKbq7ArdmbtmMWGjA3otXqWDlvKwAhZnUBt9tpash59FGtBAW4dOxC+cKEshyeEk3P6pO7QoUMYDAYSExMBCAgIUDki4SiVJcUc3rYJgL633XnJ4yy1No7vzgega6IMkHAkRVGY+91c/nPiP+g0OhYnLSYpMkntsFyeoijkzZpdP8Gwry9Ry5eju8jqKkII56J68+vWrVu57bbbiIiIQKPRsG7dukbHLF++nHbt2uHu7k5CQgLbtm1r8vmPHz+Ol5cXY8eOpU+fPixYsMCB0Qs1pW74LzarlYjYeNrExV/yuJM/FmCprR8gERHr13IBOjlFUXhhzwv8+9i/0aBhwZAF3BRzk9phCaD4H/+gbN26+oERS5fgFh2tdkhCiBagek1dVVUVPXv25P7772f8+PGN9q9du5Zp06axfPlyBg8ezIoVK0hOTiYtLY3oc7+oEhISqK2tbfTejRs3YrFY2LZtG6mpqYSEhHDLLbfQr18/Rsqkm9c1m9XCgU0bAEgYM+5Xjz3yXf00Jp0HhEnzk4MoisLSH5ay5vAaAP42+G+Mbj9a5agEQOX2bylY9CIAoX9+Gs9Bg1SOSAjRUlRP6pKTk0lOTr7k/iVLlvD73/+eBx98EICXX36ZDRs28MYbb7Bw4UIA9u7de8n3R0ZG0q9fP6Ki6meyHz16NKmpqZdM6mpray9IEMvKygAoLy+/sg8mmtXx3TsoLirE5OdPcKf4S96fyhIzxw9kgQLhXUxyHx3k7/v/zqqDqwB4ut/TDA8ZLmXbCtSeOEHm449jt1jwGTsW3e23y30RQkU//fwpitIyF1RaEUD59NNPG17X1tYqOp1O+eSTTy447rHHHlOSkpKadE6LxaL06tVLKS4uVmw2mzJmzBjl888/v+Txs2bNUgB5yEMe8pCHPOQhD4c8zpw5c1V50ZVSvabu1xQVFWGz2QgNDb1ge2hoKHl5eU06h16vZ8GCBSQlJaEoCqNGjWLMmDGXPP7ZZ59l+vTpDa9LS0uJiYkhMzMTX1/fq/sg4qqVl5cTFRXFmTNn8PHxUTsclyPlry4pf3VJ+avLGcpfURQqKiqIiLj4SkeO1qqTup/8sh+UoihX1Dfqck285zMajRed8sTX1/e6/aZyBj4+PlL+KpLyV5eUv7qk/NV1vZd/S1YIqT769dcEBQWh0+ka1coVFBQ0qr0TQgghhHBlrTqpc3NzIyEhgZSUlAu2p6SkMEhGdAkhhBBCNFC9+bWyspL09PSG16dOnSI1NZWAgACio6OZPn06EydOpG/fvgwcOJCVK1eSmZnJlClTWiQ+o9HIrFmzZBUKlUj5q0vKX11S/uqS8leXlP+V0yhKS42zvbgtW7YwbNiwRtsnTZrE6tWrgfrJhxctWkRubi7dunVj6dKlJCXJrPVCCCGEED9RPakTQgghhBDXrlX3qRNCCCGEEE0jSZ0QQgghhBOQpE4IIYQQwglIUudAS5cupWvXrnTp0oXHHnus5dZ6E0D9yOlhw4bRpUsXunfvTlVVldohuZzq6mpiYmJ48skn1Q7F5Zw5c4Ybb7yRLl260KNHDz766CO1Q3J669evJy4ujk6dOvHWW2+pHY5Lke/3i5OBEg5SWFjIgAEDOHToEAaDgaSkJBYvXszAgQPVDs1lDB06lHnz5pGYmEhxcTE+Pj7o9arP2uNSZsyYwfHjx4mOjmbx4sVqh+NScnNzyc/Pp1evXhQUFNCnTx+OHj2Kp6en2qE5JavVSpcuXdi8eTM+Pj706dOHXbt2ERAQoHZoLkG+3y9OauocyGq1YjabsVgsWCwWQkJC1A7JZfyUTCcmJgIQEBAgCV0LO378OEeOHGH06NFqh+KSwsPD6dWrFwAhISEEBARQXFysblBObPfu3XTt2pU2bdrg7e3N6NGj2bBhg9phuQz5fr84l0nqtm7dym233UZERAQajYZ169Y1Omb58uW0a9cOd3d3EhIS2LZtW5PPHxwczJNPPkl0dDQRERGMGDGCDh06OPATXN+au/yPHz+Ol5cXY8eOpU+fPixYsMCB0V//mrv8AZ588kkWLlzooIidT0vcg598//332O12oqKirjFq53Wt9yMnJ4c2bdo0vI6MjCQ7O7slQncKjvx5kO/3n7lMUldVVUXPnj15/fXXL7p/7dq1TJs2jRkzZvDjjz+SmJhIcnIymZmZDcckJCTQrVu3Ro+cnBxKSkpYv349GRkZZGdns2PHDrZu3dpSH6/Va+7yt1gsbNu2jWXLlrFz505SUlIaLS/nypq7/D/77DNiY2OJjY1tqY903Wnue/CTs2fPct9997Fy5cpm/0zXs2u9HxfruaTRaJo1ZmfiiJ8HkO/3RhQXBCiffvrpBdtuuOEGZcqUKRds69y5s/LMM8806Zwffvih8oc//KHh9aJFi5QXXnjhmmN1Rs1R/jt27FBuvvnmhteLFi1SFi1adM2xOqPmKP9nnnlGiYyMVGJiYpTAwEDFx8dHmTNnjqNCdjrNcQ8URVHMZrOSmJio/POf/3REmC7jau7Ht99+q4wbN65h32OPPaasWbOm2WN1Rlf78yDf7425TE3dr6mrq2Pv3r2MGjXqgu2jRo1ix44dTTpHVFQUO3bswGw2Y7PZ2LJlC3Fxcc0RrtNxRPn369eP/Px8SkpKsNvtbN26lfj4+OYI1+k4ovwXLlzImTNnyMjIYPHixTz00EPMnDmzOcJ1So64B4qiMHnyZIYPH87EiRObI0yX0ZT7ccMNN3Dw4EGys7OpqKjgiy++4Oabb1YjXKfTlPKX7/eLk6QOKCoqwmazERoaesH20NBQ8vLymnSOAQMGMHr0aHr37k2PHj3o0KEDY8eObY5wnY4jyl+v17NgwQKSkpLo0aMHnTp1YsyYMc0RrtNxRPmLa+OIe/Dtt9+ydu1a1q1bR69evejVqxcHDhxojnCdXlPuh16v56WXXmLYsGH07t2bp556isDAQDXCdTpNKX/5fr84GR54nl/2h1AU5Yr6SMyfP5/58+c7OiyXca3ln5ycTHJysqPDchnXWv4/mTx5soMicj3Xcg+GDBmC3W5vjrBc1uXux9ixY+Wf92b0a+Uv3+8XJzV1QFBQEDqdrtF/xAUFBY3+UxCOJ+WvLil/9ck9aF3kfqhLyv/qSVIHuLm5kZCQ0Gi0ZEpKCoMGDVIpKtch5a8uKX/1yT1oXeR+qEvK/+q5TPNrZWUl6enpDa9PnTpFamoqAQEBREdHM336dCZOnEjfvn0ZOHAgK1euJDMzkylTpqgYtfOQ8leXlL/65B60LnI/1CXl30zUG3jbsjZv3qwAjR6TJk1qOGbZsmVKTEyM4ubmpvTp00f55ptv1AvYyUj5q0vKX31yD1oXuR/qkvJvHrL2qxBCCCGEE5A+dUIIIYQQTkCSOiGEEEIIJyBJnRBCCCGEE5CkTgghhBDCCUhSJ4QQQgjhBCSpE0IIIYRwApLUCSGEEEI4AUnqhBBCCCGcgCR1QgghhBBOQJI6IcR1b/bs2fTq1avFr7tlyxY0Gg2lpaUtfm0hhPglSeqEEK2aRqP51cfkyZN58skn+frrr1s8tkGDBpGbm4uvr+81nefjjz+mf//++Pr64u3tTdeuXXniiSccFKUQwlXo1Q5ACCF+TW5ubsPXa9euZebMmRw9erRhm4eHB15eXnh5ebV4bG5uboSFhV3TOf73v/9xzz33sGDBAsaOHYtGoyEtLU2VJFUIcX2TmjohRKsWFhbW8PD19UWj0TTa9svm18mTJzNu3DgWLFhAaGgofn5+zJkzB6vVylNPPUVAQACRkZG8/fbbF1wrOzubu+++G39/fwIDA7n99tvJyMi4ZGy/bH5dvXo1fn5+bNiwgfj4eLy8vLjlllsuSEx/af369QwZMoSnnnqKuLg4YmNjGTduHK+99toFx33++eckJCTg7u5O+/btGz7PT0pLS3n44YcJDQ3F3d2dbt26sX79+qYXtBDiuidJnRDCKW3atImcnBy2bt3KkiVLmD17NmPGjMHf359du3YxZcoUpkyZwpkzZwCorq5m2LBheHl5sXXrVrZv396QlNXV1TX5utXV1SxevJh3332XrVu3kpmZyZNPPnnJ48PCwjh06BAHDx685DEbNmzgd7/7HY899hhpaWmsWLGC1atXM3/+fADsdjvJycns2LGD9957j7S0NJ5//nl0Ol2T4xZCOAFFCCGuE++8847i6+vbaPusWbOUnj17NryeNGmSEhMTo9hstoZtcXFxSmJiYsNrq9WqeHp6Kh988IGiKIqyatUqJS4uTrHb7Q3H1NbWKh4eHsqGDRsuGs/mzZsVQCkpKWmID1DS09Mbjlm2bJkSGhp6yc9UWVmpjB49WgGUmJgY5e6771ZWrVqlmM3mhmMSExOVBQsWXPC+d999VwkPD1cURVE2bNigaLVa5ejRo5e8jhDC+UmfOiGEU+ratSta7c+NEaGhoXTr1q3htU6nIzAwkIKCAgD27t1Leno63t7eF5zHbDZz4sSJJl/XZDLRoUOHhtfh4eEN17gYT09P/vvf/3LixAk2b97Md999xxNPPMErr7zCzp07MZlM7N27lz179jTUzAHYbDbMZjPV1dWkpqYSGRlJbGxsk+MUQjgfSeqEEE7JYDBc8Fqj0Vx0m91uB+qbMBMSElizZk2jcwUHB1/TdRVFuez7OnToQIcOHXjwwQeZMWMGsbGxrF27lvvvvx+73c6cOXO48847G73P3d0dDw+PJscnhHBektQJIQTQp08f1q5dS0hICD4+PqrG0rZtW0wmE1VVVQ2xHT16lI4dO170+B49epCVlcWxY8ektk4IFyZJnRBCAPfeey8vvvgit99+O3/729+IjIwkMzOTTz75hKeeeorIyMhmue7s2bOprq5m9OjRxMTEUFpayquvvorFYmHkyJEAzJw5kzFjxhAVFcVdd92FVqtl//79HDhwgHnz5jF06FCSkpIYP348S5YsoWPHjhw5cgSNRsMtt9zSLHELIVofGf0qhBDU94XbunUr0dHR3HnnncTHx/PAAw9QU1PTrDV3Q4cO5eTJk9x333107tyZ5ORk8vLy2LhxI3FxcQDcfPPNrF+/npSUFPr168eAAQNYsmQJMTExDef5+OOP6devHxMmTKBLly48/fTT2Gy2ZotbCNH6aJSmdPYQQgghhBCtmtTUCSGEEEI4AUnqhBBCCCGcgCR1QgghhBBOQJI6IYQQQggnIEmdEEIIIYQTkKROCCGEEMIJSFInhBBCCOEEJKkTQgghhHACktQJIYQQQjgBSeqEEEIIIZyAJHVCCCGEEE5AkjohhBBCCCfw/wG8/8lpiGFQIAAAAABJRU5ErkJggg==", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotC(ssys.sims[1], 1e-5, 1.0e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-8, 1e3)\n", - "ylim(1e-6, 1e2)\n", - "title(\"Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 66, - "id": "9ca4df51", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys.sims[2], 1e-2, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-6, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 67, - "id": "1f7d8918", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "1305×1279 Array{RGBA{N0f8},2} with eltype ColorTypes.RGBA{FixedPointNumbers.N0f8}:\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,0.812)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.812)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.812)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.812)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.812)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,0.812)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.812)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.812)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.812)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.812)\n", - " ⋮ ⋱ \n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.812)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.812)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.812)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.812)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,0.812)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.812)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.812)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.812)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,0.812)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "getfluxdiagram(ssys,1e3;speciesratetolerance=1e-6)" - ] - }, - { - "cell_type": "code", - "execution_count": 68, - "id": "44de0eb2", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "plotROP (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "function plotROP(ssys,name,t;N=0,tol=0.01)\n", - " clf()\n", - " rop = rops(ssys, name, t)\n", - " inds = rop.nzind[reverse(sortperm(abs.(rop.nzval)))]\n", - " if N == 0\n", - " N = length(inds)\n", - " elseif N > length(inds)\n", - " N = length(inds)\n", - " end\n", - " inds = inds[1:N]\n", - " mval = abs(rop[inds[1]])\n", - " minval = mval*tol\n", - " k = 1\n", - " while k < length(inds) && abs(rop[inds[k]]) >= minval\n", - " k += 1\n", - " end\n", - " inds = inds[1:k]\n", - " net_rops = sum(rop[inds])\n", - " println(\"Net ROPs for species $name is: $net_rops\")\n", - "\n", - " for (i, j) in enumerate(inds)\n", - " println(\"Showing the reaction with $i th highest ROP for species $name:\")\n", - " println(getrxnstr(ssys.reactions[j]))\n", - " println(\"ROP = \", rop[inds[i]])\n", - " println(ssys.reactions[j].kinetics)\n", - " end\n", - "\n", - " xs = Array{Float64,1}(1:length(inds))\n", - " barh(xs,reverse(rop[inds]))\n", - " yticks(xs,reverse(getrxnstr.(ssys.reactions[inds])))\n", - " xlabel(\"Production/Loss Rate mol/s\")\n", - " gcf()\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 69, - "id": "bcbc831e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "get_boundary_layer_concentration" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "\"\"\"\n", - "Integrates the ROP in the boundary layer and computes the concentration\n", - "\"\"\"\n", - "function get_boundary_layer_concentration(sim,t,spc,Vbl,C_0)\n", - " intg,err = quadgk(x -> sum(rops(sim,spc,t)), 0, t);\n", - " return C_0 + intg ./ Vbl;\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "5c16efa0", - "metadata": {}, - "outputs": [], - "source": [ - "# Logarithmic time scale\n", - "t_vals = 10 .^ range(-12, stop=3, length=1000);\n", - "\n", - "# Compute ROP over time\n", - "ROP_vals = [sum(rops(ssys, \"O=CO\", t)) for t in t_vals];\n", - "# Compute boundary layer accumulation by integration\n", - "Cbl_vals = [get_boundary_layer_concentration(ssys, t, \"O=CO\", V_bl, C_default) for t in t_vals];" - ] - }, - { - "cell_type": "code", - "execution_count": 71, - "id": "f5b0f5bb", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Plots the ROP of O=CO\n", - "clf()\n", - "\n", - "plot(t_vals, ROP_vals)\n", - "\n", - "xscale(\"log\")\n", - "xlim(1e-11,1e3)\n", - "yscale(\"log\")\n", - "ylim(1e-8,1e2)\n", - "xlabel(\"Time (s)\")\n", - "ylabel(\"Rate of Progress (mol/s)\")\n", - "legend()\n", - "tight_layout()\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1a201c28", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n" - ] - }, - { - "data": { - "image/png": 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T/PPPPwKAmDZt2hPna9OmjbCxsXniPBV95su2b493Z/7111/lbvfWrVsnAIiVK1cq23x9fYWNjY1Kd2ViYqIAIOrUqaOyl3HTpk0CePqx0GXbt3Xr1omSkhJRUFAgDh48KAICAkRQUJDK3sKy7vHly5c/cZmenp4iMDBQeb8s1JWF77t374pFixYJiUQiWrVqpVF95YW6p31XCFFx9+s777wjatWqpfLZF+L/9/CWhb8lS5YIAGL79u1qjy8v1GmyPS3bFty8eVMAUDlk5Undr4+HOk2/h4V4+Bn19PQUMplM2Zaeni7MzMyeuOdc33j2axVYs2YNjh07hmPHjmH79u2Ijo7G2LFjsXjxYuU8u3fvhp2dHQYOHKjy2LKz9Hbt2lXp53/xxRdV7oeEhKCwsBAZGRkAgD179gAAXnvtNZX5hgwZoras0tJSzJ49G0FBQbC0tIS5uTksLS1x5coVXLhwQW3+AQMGqLV17twZoaGhWLJkibJt+fLlkEgkGDlypPYvsBwnT57Eiy++CFdXV0ilUlhYWOCNN96AXC7H5cuXlfNNnDgRGRkZ+O233wAACoUCy5YtQ69eveDn5wcA2LFjB0pLS/HGG2+gtLRUebO2tkanTp2wd+9ejV73syr7Oz1+5mbr1q0RGBio9h6pXbs2WrdurdIWEhKCmzdvKu9v374djRs3xgsvvFDh8/75559wcnJCnz59VF5/8+bNUbt2bbXX37x5c/j4+CjvW1tbo3HjxirP+zTOzs7o0qWLWvv169cxZMgQ1K5dW/l37dSpEwCU+/7TxO7duxEUFKS2rt58800IIbB7926V9l69ekEqlSrvh4SEAMBTX9/u3bvRtWtXeHt7qz1PQUEBDh8+XKn6n+bh98/DM9nLbNmyRblNetJNV5/HJ9X2aF2V8fhnrezv9fjnZNCgQbCzs1P7nDRv3hx169ZV3g8MDATwcDtla2ur1q7p+3jw4MGwsLCAra0tOnToAJlMhq1bt8LJyUmjxz+qvPWUn58PCwsLWFhYwN3dHZMmTUJUVBQ2btyo9fLLPO274kn+/PNPREREwMvLS2U7ERUVBQDYt2+f8l97e3v06NFD5fGvvvpqhcsub3uakZGBUaNGwdvbG+bm5rCwsICvry+AZ9sWaPM9HBERAXt7e+V9T09PeHh4aLWt0zVzgz1zDRIYGIjw8HDl/R49euDmzZuYMmUKXn/9dTg5OSErKwu1a9dW++B6eHjA3NwcWVlZlX5+V1dXlftWVlYAgAcPHgB4OByCubm52ny1a9dWW1ZMTAyWLFmCqVOnolOnTnB2doaZmRlGjBihXN6j6tSpU25NEyZMwIgRI3Dp0iXUr18f3377LQYOHFjuc2orOTkZHTt2REBAABYtWgQ/Pz9YW1vj6NGjGDt2rEqdLVq0QMeOHbFkyRK89tpr+PPPP3Hjxg2sWLFCOc+dO3cAAK1atSr3+czMVH8blQ0p8TRubm6wtbVFUlKSRq+r7D1Q3jr18vJS25A8/vcEHv7tH339d+/eVQlg5blz5w6ys7NhaWlZ7vTMzEytn/dpynuNeXl56NixI6ytrfH555+jcePGsLW1xa1bt/DSSy9ptfxHZWVlKQP8o7y8vJTTH/W0z9OTnqeiv115z6OJsr9dUlISmjRpUu48ZcPGPBomg4KClGHvSR59b/v4+ODKlSvIz8+HnZ2dxnU9yc2bN9VCrrYeX6dl2zN3d3eVdolEgtq1a6utZxcXF5X7Ze/zitqfNmRImTlz5qBLly4oKCjAzp07ERsbi379+uHIkSPK94wm6yk/Px+ZmZlo0aKFSruNjQ3i4+MBPHwP+vr6arTdeZLKvreBh9uJLVu2wMLCotzpZduJrKwseHp6qk0vrw0of3uqUCgQGRmJ1NRUfPTRR2jWrBns7OygUCjQtm3bZ9oWaPM9rIttna4x1BlISEgIduzYgcuXL6N169ZwdXXFkSNH1H6RZWRkoLS0FG5ubgAe7vUAgKKiIpXlPWvoKy0tRVZWlsqbND09XW3eH3/8EW+88QZmz56t0p6ZmVnuL9CKfoUPGTIEU6dOxZIlS9C2bVukp6dj7NixlX4Nj9q0aRPy8/OxYcMG5S83AEhMTCx3/gkTJmDQoEE4ceIEFi9ejMaNG6Nbt27K6WXrfv369SrLq4imex6kUim6du2K7du3IyUlBfXq1Xvi/GV/m7S0NLV5U1NTlXVqw93dHSkpKU+cx83NDa6urvjrr7/Knf7oL1VdKW8d7t69G6mpqdi7d69y7xyAcsef0oarqyvS0tLU2lNTUwGgUuu1qp6nW7duWLlyJTZt2oRp06aVO8+mTZtgbm6uMh5XgwYNNNqbMHPmTOV4f927d8fOnTuxZcsWvPLKK098XJ06ddC0aVPs3LkTBQUFKnu8yhw+fBh37tzBoEGDnlrHkzz+Xinbnt29e1cl2AkhkJ6eXuGPM12rX7++8sf8888/DxsbG3z44Yf45ptv8N577wEAwsLC4OzsjM2bNyM2Nrbc9/3mzZuhUChUtknAw8D96M4CQ3Nzc0NISAi++OKLcqeX/XhxdXXF0aNH1aaX930DlL8tOHv2LE6dOoXVq1cjOjpa2X716tXKlK6k6fewMWP3q4GUBYyyjU7Xrl2Rl5enNqjjmjVrlNOBh79mrK2tcfr0aZX5/vjjj0rXEhERAQD46aefVNp//vlntXnLBrp81NatW3H79m2tntPa2hojR47EDz/8gPnz56N58+bo0KGDlpWXr+zD+GidQgh8++235c7fv39/+Pj44N1338Xff/+NMWPGqHygu3fvDnNzc1y7dg3h4eHl3ipr+vTpEELg7bffRnFxsdr0kpISbNmyBQCU3ZE//vijyjzHjh3DhQsXlO8RbURFReHy5ctqXYyP6t27N7KysiCXy8t97QEBAVo/rzZ7AMqU93cFoLJXtTLL79q1K86fP48TJ06otK9ZswYSiUT5+XhWXbt2VQbTx5/H1tYWbdu21XqZ/fv3R1BQEL788kuVwwrKrFu3Djt37sSIESNU9oJXpvt1+PDhqF27NqZMmVLh533Dhg3K/8+YMQP3799XBphH5efnY8KECbC1tcXkyZO1ft1PUvY5ePxz8vvvvyM/P79SnxNdmDJlCho2bIgvv/wSubm5AB7u/Xv//fdx4cIFzJ07V+0xGRkZmD59Ojw9PTFixIiqLrlcFe2J6t27N86ePYsGDRqUu50oC3WdOnVCbm4utm/frvL4tWvXalyDPrcFmnwPGzPuqasCZ8+eRWlpKYCHe9Q2bNiAuLg49O/fH/7+/gCAN954A0uWLEF0dDRu3LiBZs2a4cCBA5g9ezZ69uypPOZJIpHg9ddfx/fff48GDRogNDQUR48eLTeAaSoyMhLPP/88pkyZgvz8fISHh+PgwYP43//+pzZv7969sXr1ajRp0gQhISFISEjA3Llzn7qXqTxjxozBV199hYSEBHz33XdaPfbMmTPljojeqlUrdOvWDZaWlnj11VcxZcoUFBYWYtmyZbh//365y5JKpRg7diymTp0KOzs7tWNx/Pz8MGvWLMyYMQPXr19Hjx494OzsjDt37uDo0aOws7PDp59+qlX9Zdq1a4dly5ZhzJgxCAsLw+jRo9G0aVOUlJTg5MmTWLlyJYKDg9GnTx8EBARg5MiR+Oabb2BmZoaoqCjcuHEDH330Eby9vSv15Thp0iSsW7cOffv2xbRp09C6dWs8ePAA+/btQ+/evREREYFXXnkFP/30E3r27ImJEyeidevWsLCwQEpKCvbs2YO+ffuif//+Wj1vcHAwAGDlypWwt7eHtbU1/P39y+3OKNO+fXs4Oztj1KhRmDlzJiwsLPDTTz/h1KlTavM2a9YMwMMusKioKEilUoSEhJTbhTx58mSsWbMGvXr1wqxZs+Dr64utW7di6dKlGD16NBo3bqzVa6vIzJkzlccdffzxx3BxccFPP/2ErVu34quvvoKjo6PWy5RKpfj999/RrVs3tGvXDu+++y7atWuHoqIibNmyBStXrkSnTp3w9ddfqzyubP1ow9HREX/88Qd69+6NFi1aYNy4cWjXrp3ymNoff/wRp06dwksvvQTg4TFSJ06cwLx583Djxg289dZb8PT0xKVLl7BgwQJcu3YNP//8M+rXr691LU/SrVs3dO/eHVOnToVMJkOHDh1w+vRpzJw5Ey1atMDQoUN1+nyasrCwwOzZs/Hyyy9j0aJF+PDDDwEAU6dOxalTp5T/Dh48GI6Ojjh9+jTmzp2L3Nxc/Pnnn5V6f+hDs2bNsHfvXmzZsgV16tSBvb09AgICMGvWLMTFxaF9+/aYMGECAgICUFhYiBs3bmDbtm1Yvnw56tWrh+joaCxYsACvv/46Pv/8czRs2BDbt2/Hjh07AKgfzlKeJk2aoEGDBpg2bRqEEHBxccGWLVsQFxdXbr0AsGjRIkRHR8PCwgIBAQHl9jBo+j1s1Ax0gkaNUN7Zr46OjqJ58+Zi/vz5amesZWVliVGjRok6deoIc3Nz4evrK6ZPn642X9mYcp6ensLOzk706dNH3Lhxo8KzXx8d6uLRuh49Gyg7O1u89dZbwsnJSdja2opu3bqJixcvqi3z/v37Yvjw4cLDw0PY2tqK5557Tuzfv1/tLCJNB7js3LmzcHFxeeowAWXKzoSr6FZ25tSWLVtEaGiosLa2FnXr1hXvv/++8izA8s64LFt/o0aNqvC5N23aJCIiIoSDg4OwsrISvr6+YuDAgeLvv/9WzlPRUANPk5iYKKKjo4WPj4+wtLRUDr/w8ccfq4wFVzZOXePGjYWFhYVwc3MTr7/+eoXj1D0uOjpaOc5Xmfv374uJEycKHx8fYWFhITw8PESvXr1UhqgpKSkR8+bNU67TWrVqiSZNmoh33nlHXLlyRTlf2bhfjytvPKiFCxcKf39/IZVKVf52FdUuxMMhINq1aydsbW2Fu7u7GDFihDhx4oTaWXNFRUVixIgRwt3dXUgkEpX3e0Xj1A0ZMkS4uroKCwsLERAQIObOnVvhOHWPe/xzUpEzZ86IPn36CEdHR2FpaSlCQ0MrPJNdk7Nfy2RmZopp06aJJk2aKP8+rVu3FosXL1YZm1EX0tPTxdSpU0XTpk2Fra2tsLKyEg0bNhTvvPOOOHPmjNr827ZtEz179lSu27p164qhQ4dqPJL/085+fXz7JsTDM66nTp0qfH19hYWFhahTp44YPXp0hePUPa689a/pmfdP2/a1adNGbQgchUIhfvrpJ9G5c2fh5OQkLC0thb+/vxg9erTa2aRCVH47U1F92nxXJCYmig4dOghbW1sBqI5Td/fuXTFhwgTh7+8vLCwshIuLiwgLCxMzZsxQGQonOTlZvPTSS6JWrVrC3t5eDBgwQGzbtk3tzNUnvc7z58+Lbt26CXt7e+Hs7CwGDRokkpOTy/0sTp8+XXh5eQkzMzOV74CKxqnT5Hu4os9oeduXqiQRQoOjZYn0ICMjA76+vhg/fjy++uorg9byzTffYMKECTh79iyaNm1q0FqIiGqa2bNn48MPP0RycnKlen7oIXa/UpVLSUnB9evXMXfuXJiZmWHixIkGq+XkyZNISkrCrFmz0LdvXwY6IiI9KxvOq0mTJigpKcHu3bvxn//8B6+//joD3TOq0aGuf//+2Lt3L7p27Vru8VmkH9999x1mzZoFPz8//PTTTypjRFW1/v37Iz09HR07dsTy5csNVgcRUU1ha2uLBQsW4MaNGygqKoKPjw+mTp2qPM6QKq9Gd7/u2bMHeXl5+OGHHxjqiIiIqFqr0UOaPD4aNBEREVF1VW1DXXx8PPr06QMvLy9IJBK1cWUAYOnSpfD394e1tTXCwsKwf//+qi+UiIiIqApU21CXn5+P0NBQleunPmrdunWYNGkSZsyYgZMnT6Jjx46IiopCcnJyFVdKREREpH/V9kSJqKgo5YWCyzN//nwMHz5cOQr3woULsWPHDixbtgyxsbFaP19RUZHKpbkUCgXu3bsHV1fXZ74gNREREdUMQgjk5ubCy8tLo8GWtVFtQ92TFBcXIyEhQe1aiJGRkTh06FCllhkbG1vpqwYQERERPerWrVs6H8LFJENdZmYm5HI5PD09Vdo9PT1VLhrcvXt3nDhxAvn5+ahXrx42btxY4cWep0+fjpiYGOX9nJwc+Pj44NatW3BwcNDPCyEiIiKTIpPJ4O3trZcTNU0y1JV5vFtUCKHSVnatOU1YWVmpXTwYABwcHBjqiIiISCv6OHSr2p4o8SRubm6QSqUqe+WAh5elenzvHREREZEpMMlQZ2lpibCwMMTFxam0x8XFoX379gaqioiIiEh/qm33a15eHq5evaq8n5SUhMTERLi4uMDHxwcxMTEYOnQowsPD0a5dO6xcuRLJyckYNWqUAasmIiIi0o9qG+qOHz+OiIgI5f2ykxiio6OxevVqDB48GFlZWZg1axbS0tIQHByMbdu2wdfX11AlExERkQmQy+UoKSmpcLqlpaXOhyvRRI2+9uuzkMlkcHR0RE5ODk+UICIiqgGEEEhPT0d2dvYT5zMzM4O/vz8sLS3VpukzP1TbPXVEREREVaks0Hl4eMDW1rbcM1gVCgVSU1ORlpYGHx+fKr1AAUMdERER0VPI5XJloHN1dX3ivO7u7khNTUVpaSksLCyqqEITPfuViIiISJfKjqGztbV96rxl3a5yuVyvNT2OoY6IiIhIQ5p0pxrqmvAMdUREREQmgKGOiIiIyAQw1BERERGZAIY6IiIiIhPAUEdERESkIYVC8dR5DHVdB45TR0RERPQUZZf+Sk1Nhbu7OywtLcs9y1UIgbt370IikVTpGHUAQx0RERHRU5Vd+istLQ2pqalPnFcikaBevXqQSqVVVN1DDHVEREREGrC0tISPjw9KS0ufOLCwhYVFlQc6gKGOiIiISGNl3apV3bWqCZ4oQURERGQCGOqIiIiITABDHREREZEJYKgjIiIiMgEMdUREREQmgKGOiIiIyAQw1BERERGZAI5TR0RERFQFrt/Nw2+Hrult+Qx1RERERHpyN7cIW06lYlPibZxOyYGiqEBvz8VQR0RERKRD+UWl2Hk+HZtOpuLA1UzIFQIAIDWToF1DV6zV0/My1BERERE9o1K5AgeuZmLTydvYce4OHpT8/7Vhm3s7oX+LuugVUgeWiiKsHaefGhjqiIiIiCrp7O0crE9IwZ+nU5GZV6xs93O1Rb8WddG3eV34u9kp22WyIr3VwlBHREREpIX7+cXYlHgbvx1Pwfk0mbLd1c4SfUK90Le5F5p7O0EikVRpXQx1RERERE8hVwjsv3IXvx1PQdz5OyiWKwAAllIzdGvqiYEt6+G5Rm6wkBputDiGOiIiIqIK3MjMx28Jt/B7wm2kywqV7cF1HfByuDdeDPWCk62lASv8fwx1RERERI8okSuw89wd/PjPTRy+nqVsd7K1QL/mdTEovB6aejkasMLyMdQRERERAbid/QC/HEnGuuO3cDf34QkNZhLg+cbueDncG10DPWBlLjVwlRVjqCMiIqIaS64QiL98Fz/+cxN7LmXg3yHl4G5vhVdaeeOV1j6o62Rj2CI1xFBHRERENU7OgxKsO5aMNYdvIuX+A2V7+waueL2tL7oFeRr0pIfKYKgjIiKiGiMpMx+rDybht4QUFBQ/HCDY0cYCA8PqYUgbHzRwr2XgCiuPoY6IiIhMmhACh69l4b8HkrD7UgbEv12sAZ72eOs5P/RtXhfWFsZ7rJymGOqIiIjIJJXIFfgjMRXf7b+Oi+m5yvYuTTww/Dl/tG/gWuUDBOsTQx0RERGZlAfFcqw7loxv9yfhdvbD4+VsLKQYGFYPwzr4oX417mJ9EoY6IiIiMgk5D0rwv8M3sOrgDWTlP7wOq1stK7z1nB9ea+0LR1sLA1eoXwx1REREVK1l5hXhu/1J+PGfm8grKgUAeLvYYOTzDTAorJ5JHC+nCYY6IiIiqpbu5RdjZfx1/HDoBh6UPDyTNcDTHqM7N0DvkDowr2ZDkjwrhjoiIiKqVnIKSvDdgev4/kAS8v8dliTU2wnjIxqiSxMPmJmZzskP2mCoIyIiompBVliCVQdu4LsD15Fb+LCbtamXA2K6NUaXJh4mdSZrZdToUNe/f3/s3bsXXbt2xfr16w1dDhEREZWjsESONYdvYOnea8guKAHwsJt1crfG6N7Us8aHuTI1OtRNmDABb731Fn744QdDl0JERESPUSgEtpxOxVd/XVIOTdLA3Q6TXmiMXs3q1Nhu1orU6FAXERGBvXv3GroMIiIiesyha5mI3XYRZ27nAAA8HazwbmQABrSsBynDXLmM9rSQ+Ph49OnTB15eXpBIJNi0aZPaPEuXLoW/vz+sra0RFhaG/fv3V32hREREpDOX7+TirdXHMOTbIzhzOwe1rMzxfvcA7H0vAi+HezPQPYHR7qnLz89HaGgohg0bhgEDBqhNX7duHSZNmoSlS5eiQ4cOWLFiBaKionD+/Hn4+PgAAMLCwlBUVKT22J07d8LLy0vvr4GIiIg0k11QjPlxl/HjPzehEIC5mQSvtfHB+K6N4FbLytDlVQtGG+qioqIQFRVV4fT58+dj+PDhGDFiBABg4cKF2LFjB5YtW4bY2FgAQEJCgs7qKSoqUgmIMplMZ8smIiKqqeQKgbXHkjFvxyXc//ckiB5Na2NKjwCTvZyXvhhtqHuS4uJiJCQkYNq0aSrtkZGROHTokF6eMzY2Fp9++qlelk1ERFQTHb9xDzM3n8O51Ic7SgI87THzxSC0b+Bm4Mqqp2oZ6jIzMyGXy+Hp6anS7unpifT0dI2X0717d5w4cQL5+fmoV68eNm7ciFatWpU77/Tp0xETE6O8L5PJ4O3tXbkXQEREVIPdkRUidtsFbEpMBQA4WJsjpltjvN7Wt8ZdBUKXqmWoK/P4uDRCCK3GqtmxY4fG81pZWcHKin36RERElVUiV2DVwSQs/PsKCorlkEiAweHeeL97AFx53Nwzq5ahzs3NDVKpVG2vXEZGhtreOyIiIjK8k8n38cHGs7iQ9rCrtYWPEz59sSlC6jkZtjATUi1DnaWlJcLCwhAXF4f+/fsr2+Pi4tC3b18DVkZERESPkhWWYN6OS/jfPzchBOBka4HpUU0wKMybgwfrmNGGury8PFy9elV5PykpCYmJiXBxcYGPjw9iYmIwdOhQhIeHo127dli5ciWSk5MxatQoA1ZNREREwMNDorafTccnm88hI/fh6BEvtayLGT0D2dWqJ0Yb6o4fP46IiAjl/bKTFKKjo7F69WoMHjwYWVlZmDVrFtLS0hAcHIxt27bB19fXUCUTERERgFv3CjBz8znsvpgBAPB3s8MX/YLRviHPatUniRBCGLqI6kgmk8HR0RE5OTlwcHAwdDlEREQGJ1cIrDqYhK93XsaDEjkspBKM7twQYzo3gLWF1NDlGQV95gej3VNHRERE1cfVjFy8v/40TiZnAwBa+7tgdv9maOjBAYSrCkMdERERVVqpXIEV8dex6O8rKJYrUMvKHDN6BeKVVt5aDTNGz46hjoiIiCrlQpoM768/hbO3Hw5T0jnAHbP7N4OXk42BK6uZGOqIiIhIK8WlCizZcxVL9lxFqULAwdocM/s0xUst63LvnAEx1BEREZHGzqTk4P31p3AxPRcAEBnkic/7BcPDwdrAlRFDHRERET1VUakci/6+ghXx1yFXCLjYWeLTF5uid0gd7p0zEgx1RERE9EQX0mSYvC5RuXeud0gdfPpiUw4ibGQY6oiIiKhccoXAyvjrmB93CSVyAVc7S3zRPxg9gusYujQqB0MdERERqUnOKkDMr4k4fvM+AOCFQE98OaAZ3Lh3zmgx1BEREZGSEAJrj93CZ3+eR0GxHLWszPFxnyAMCqvHY+eMHEMdERERAQAycgsx7fczymu2tvZ3wdeDQuHtYmvgykgTDHVERESE7WfS8MHGM7hfUAJLqRne7x6A4c/5w8yMe+eqC4Y6IiKiGiznQQk+3XwOG07eBgAE1XHAgsHNEVDb3sCVkbYY6oiIiGqog1cz8f5vp5CaUwgzCTC6cwNM7NoYluZmhi6NKoGhjoiIqIYpLJFjzl8XsergDQCAr6st5r8cijBfF8MWRs+EoY6IiKgGOZ2SjcnrEnHtbj4A4LU2PvigZyDsrBgJqjv+BYmIiGqAErkCS/dcwze7r6BUIeBhb4U5A0MQEeBh6NJIRxjqiIiITNy1u3mIWZeIUyk5AIBeIXXwed9gONtZGrgy0iWGOiIiIhOlUAj875+biN1+AYUlCjhYm+OzfsF4MdSLAwmbIIY6IiIiE5RyvwBT1p/GoWtZAICOjdzw1cAQ1HG0MXBlpC8MdURERCZECIHfjqdg1p/nkVdUCmsLM0yPCsTQtr4cSNjEMdQRERGZiAxZIaZvOINd/17mK8zXGfMGhcLfzc7AlVFVYKgjIiKq5oQQ2JR4G59uOY/sfy/z9W5kY4zoWB9S7p2rMRjqiIiIqrGkzHx8uOkMDl59eOxcUy8HzH+Zl/mqiRjqiIiIqqEHxXKsjL+OJXuvorhUAStzM0zo2ggjn68PCykv81UTMdQRERFVI3KFwIYTKfh652WkywoBPDyz9fN+wfB15bFzNRlDHRERUTVQIldgy6lULNt7DVcy8gAAdZ1sMC2qCXqH1OG4c8RQR0REZMyy8oqw4cRtrD50A7ezHwAA7K3NMb5LQ7zRzg/WFlIDV0jGgqGOiIjIyGQXFCP+Sib+OpuGuPN3UCIXAAC3WpYY1sEfQ9v5wsHawsBVkrFhqCMiIjIwhULgfJoMey5mYO/luziZfB8K8f/TQ+s5YnArH7zUsi73zFGFGOqIiIgMIOdBCQ5cycSeSxnYe+kuMvOKVKYHeNqjc4A7+javiyAvBwNVSdUJQx0REVEVEELg8p087Lp4B3sv3kVC8n3IH9kdZ2spRYeGbogI8EDnAHd4OfEaraQdhjoiIiI9KS5V4EhSFnZdyMDfF+4g5f4DlekNPWqhc2N3RDTxQLifM6zM2bVKlcdQR0REpEMKhcDxm/exKfE2tp1JQ3ZBiXKapbkZOjRwRZcmHugc4AFvF1sDVkqmhqGOiIhIB1KzH2Dt0WT8fuK2cugRAHCrZYWuTTzQNdADzzVyg60lv3pJP/jOIiIiqiSFQiD+yl38+E8ydl+8ozxj1d7KHD2Ca6Nv87po18AVUjMODEz6x1BHRESkpeJSBTYl3saKfddw7W6+sr1tfRe81sYX3YI8OfQIVTmGOiIiIg3lF5Xil6PJ+G5/kvK6q/ZW5hgQVg+vt/VBQw97A1dINRlDHRER0VMUFJfih0M3sSL+mvLEBw97K4zo6I9XW/vAnld3ICPAUEdERFSB4lIF1h5Lxje7r+Ju7sPBgf3d7PDO8/XRv2VdDkFCRqXGhrrc3Fx06dIFJSUlkMvlmDBhAt5++21Dl0VEREZArhDYePI2Fv59WTm2nLeLDSa/0Bh9m9fliQ9klLQKdZcuXcIvv/yC/fv348aNGygoKIC7uztatGiB7t27Y8CAAbCystJXrTpla2uLffv2wdbWFgUFBQgODsZLL70EV1dXQ5dGREQG9M/1LMzach7n02QAHnazju/aCIPDvWFpbmbg6ogqplGoO3nyJKZMmYL9+/ejffv2aN26Nfr16wcbGxvcu3cPZ8+exYwZMzB+/HhMmTIFkyZNMvpwJ5VKYWv7cNDHwsJCyOVyCCGe8igiIjJVt+4VYPa2C9h+Nh0AYG9tjrERDRHdzg82luxmJeOnUajr168f3n//faxbtw4uLi4Vznf48GEsWLAAX3/9NT744INnKiw+Ph5z585FQkIC0tLSsHHjRvTr109lnqVLl2Lu3LlIS0tD06ZNsXDhQnTs2FHj58jOzkanTp1w5coVzJ07F25ubs9UMxERVT95RaVYuucqvjuQhOJSBcwkwJA2PojpFgAXO0tDl0ekMY1C3ZUrV2Bp+fQ3drt27dCuXTsUFxc/c2H5+fkIDQ3FsGHDMGDAALXp69atw6RJk7B06VJ06NABK1asQFRUFM6fPw8fHx8AQFhYGIqKitQeu3PnTnh5ecHJyQmnTp3CnTt38NJLL2HgwIHw9PR85tqJiMj4CSGw9UwaZm05j4x/T4Lo0NAVH/UOQpPaDgaujkh7ElEN+hwlEonanro2bdqgZcuWWLZsmbItMDAQ/fr1Q2xsrNbPMXr0aHTp0gWDBg0qd3pRUZFKQJTJZPD29kZOTg4cHPjhJyKqTm5m5ePjP85h3+W7AAAfF1t82CsQ3YI8IZHwJAjSH5lMBkdHR73kB62O+MzKysKePXtw7949AEBmZibmzJmDWbNm4cKFCzot7EmKi4uRkJCAyMhIlfbIyEgcOnRIo2XcuXMHMtnDg2BlMhni4+MREBBQ4fyxsbFwdHRU3ry9vSv/AoiIyCCKSuVYvPsKIhfEY9/lu7CUmmFi10bYOfl5RDatzUBH1ZrGZ78ePXoUkZGRkMlkcHJyQlxcHAYNGgRzc3MIIfDll1/iwIEDaNmypT7rBfAwTMrlcrWuUk9PT6Snp2u0jJSUFAwfPhxCCAghMG7cOISEhFQ4//Tp0xETE6O8X7anjoiIqod/rmdhxsYzyst6dWjois/6BqO+ey0DV0akGxqHuhkzZmDQoEGYP38+VqxYgX79+qFHjx749ttvAQAjRozAZ599ho0bN+qt2Mc9/otKCKHxr6ywsDAkJiZq/FxWVlZGf0YvERGpkxWWIHbbBfxy9BYAwK2WJT7qHYQXQ724Z45MisbdrwkJCYiJiYG9vT0mTpyI1NRUlcF6x44di2PHjumlyMe5ublBKpWq7ZXLyMjgiQ5ERKS0++IdRM6PVwa619r4YFdMZ/RtXpeBjkyOxqGuuLgYNjY2AAALCwvY2tqqDAHi6uqKrKws3VdYDktLS4SFhSEuLk6lPS4uDu3bt6+SGoiIyHhlFxQjZl0i3lp9HOmyQvi52mLdyLb4on8zONryOq1kmjTufvX29sb169fh5+cHAFi7di3q1KmjnJ6WlqbTcd7y8vJw9epV5f2kpCQkJibCxcUFPj4+iImJwdChQxEeHo527dph5cqVSE5OxqhRo3RWAxERVT9/nU3Dh5vOITOvCGYSYPhz/ojpFsABhMnkaRzqXnnlFWRkZCjv9+rVS2X65s2b0bp1a50Vdvz4cURERCjvl52kEB0djdWrV2Pw4MHIysrCrFmzkJaWhuDgYGzbtg2+vr46q4GIiKqPnAcl+PiPs/gjMRUA0MijFr4aGIIWPs4GroyoauhsnLqCggJIpdIaczKBPseZISIi7Ry6lon3fj2F1JxCSM0kGN2pAcZ3bQgrc+6dI+Oiz/yg8Z66pym7jioREVFVKSqVY96OS/juQBKEAPxcbbFgcHPunaMaSetQl5GRAQ8PD33UQkREpLGL6TJMWpuIi+m5AIBXW/vgw16BsLPS2f4KompFq3d+UlISunfvjsuXL+urHiIioicSQuCnI8mY9ed5FJcq4GpniS8HhKBbEIe0oppN41B39uxZ9OjRA2PGjNFnPURERBXKKyrF9A1nsOXUw5MhIgLc8dXAULjb14zjuYmeRKNQd+jQIfTu3RujR4/GBx98oO+aiIiI1JxPlWHszyeQlJkPczMJpvZoghEd/TmIMNG/NAp1kZGRGD58OL744gt910NERKRCCIF1x25h5uZzKCpVwMvRGt8MaYkwX54MQfQojUKdnZ0d0tLStLq2KhER0bMqKpXj403nsO74w8t8RQS4Y/7LzeFsZ2ngyoiMj0aXCTtw4ACOHz+OYcOG6bseIiIiAECGrBCvrvwH647fgpkEmNqjCf4b3YqBjqgCGoW6Ro0a4cCBA0hISMDYsWP1XRMREdVwibey0WfxAZxIzoaDtTlWDWuN0Z0bwMyMvUVEFdH47FcvLy/Ex8erXR6MiIhIl9YnpOCDjWdQXKpAQ49a+O6NcPi52Rm6LCKjp9U4dc7Ozti1a5e+aiEiohpMoRCYs+MiVuy7DgB4IdATCwaHwt7awsCVEVUPWg+7bWNjo486iIioBisskSPm10RsO5MOAJjQpSEmvdCY3a1EWnima6nk5eVBoVCotPHi9kREpI2svCKMWHMcJ5OzYSGVYM6AELzUsp6hyyKqdrQOdUlJSRg3bhz27t2LwsJCZXvZcCdyuVynBRIRkem6djcPw1YdQ/K9AjhYm2PF0HC0a+Bq6LKIqiWtQ91rr70GAPj+++/h6enJceuIiKhSjlzPwsj/JSDnQQm8XWyw6s3WaOhRy9BlEVVbWoe606dPIyEhAQEBAfqoh4iIaoDtZ9IwcW0iiuUKNPd2wnfR4XCrxeu3Ej0Ljcape1SrVq1w69YtfdRCREQ1wM9HkjHm5xMolivQvakn1o5sy0BHpANa76n77rvvMGrUKNy+fRvBwcGwsFA91TwkJERnxRERkekQQmDp3muYu+MSAODV1t74vF8zSHmGK5FOaB3q7t69i2vXrqlcMkwikfBECSIiqpBCIfD51gv4/mASAGBsRAO8FxnA47KJdEjrUPfWW2+hRYsW+OWXX3iiBBERPVWJXIEp609j48nbAIAPewViRMf6Bq6KyPRoHepu3ryJzZs3o2HDhvqoh4iITMiDYjnG/nwCuy9mQGomwVcDQjAgjGPQEemD1idKdOnSBadOndJHLUREZEJyCkow9L9HsPtiBqzMzbByaBgDHZEeab2nrk+fPpg8eTLOnDmDZs2aqZ0o8eKLL+qsOCIiqp7uyAoR/f1RXEzPhYO1Of77Ziu08nMxdFlEJk0ihBDaPMDMrOKdezXpRAmZTAZHR0fk5OTw0mhERI+4kZmP1/97BCn3H8DD3go/vNUagXW4nSQC9JsftN5T9/i1XomIiMqcvZ2DN1cdRWZeMXxdbfHj8DbwdrE1dFlENYLGx9QNGTIEv/76K3Jzc/VZDxERVVP/XM/Cqyv/QWZeMQLrOGD9qPYMdERVSONQFxAQgDlz5sDd3R2RkZFYsmQJryxBREQAgJ3n0vHG90eRW1SK1v4uWPdOW7jb8yoRRFVJ62PqUlJSsHnzZvzxxx/Yt28fgoKC8OKLL6Jv375o0aKFvuo0OjymjojooV+P38K0309DIYAXAj2xeEgLWFtIDV0WkVHSZ37QOtQ9Kjc3F9u3b8cff/yB7du3w97eHn369MHo0aPRtGlTXdZpdBjqiIiA5fuu4cvtFwEAg8LqIfalZjCXaj1aFlGNoc/88EyfPHt7e7z88sv46aefcPfuXXz//feQSqU4fPiwruojIiIjJITA7G0XlIHunefr46uBIQx0RAb0THvqajLuqSOimqpUrsDU38/g9xMpAIDpUU3wTqcGBq6KqHow+JAmLVq00PgarydOnHimgoiIyHgVlsgx9qcT2PXvZb++fKkZBoV7G7osIoKGoa5fv356LoOIiIxdzoMSjPjhGI7duA8rczMsHtIS3YI8DV0WEf2L3a+VxO5XIqpJMmSFeOPfy37ZW5vjv9Gt0Nqfl/0i0pbBu1/Lk5CQgAsXLkAikSAoKKhGDWdCRFST3MjMx9Dvj+DWvQdwt7fCD8NaI8iLP2aJjI3WoS4jIwOvvPIK9u7dCycnJwghkJOTg4iICKxduxbu7u76qJOIiAzgXGoOor8/hsy8Ivi62uJ/b7WBjyuvEkFkjLQ+93z8+PGQyWQ4d+4c7t27h/v37+Ps2bOQyWSYMGGCPmokIiID2H/lLgav+AeZeUUIrOOA30a1Y6AjMmJaH1Pn6OiIv//+G61atVJpP3r0KCIjI5Gdna3L+owWj6kjIlO2PiEF034/jVKFQNv6Llj5RjgcrC0MXRZRtWdUx9QpFApYWKh/sC0sLKBQKHRSFBERGYYQAt/svor5cZcBAH2be+GrgSGwMudlv4iMndbdr126dMHEiRORmpqqbLt9+zYmT56Mrl276rQ4IiKqOqVyBaZvOKMMdKM7N8CCl5sz0BFVE1qHusWLFyM3Nxd+fn5o0KABGjZsCH9/f+Tm5uKbb77RR41ERKRn+UWlGLHmONYeuwUzCfBZ36aY2qMJzMw0G3ieiAxP6+5Xb29vnDhxAnFxcbh48SKEEAgKCsILL7ygj/r0ytzcHMHBwQCA8PBwfPfddwauiIio6mXkFuKt1cdw9rYM1hZm+OZVDipMVB3V6MGH3dzckJmZWanH8kQJIjIFVzPy8Oaqo0i5/wAudpb4b3Q4Wvg4G7osIpNlVCdKAA/PdN27dy8yMjLUTo6YP3++TgojIiL9Ong1E6N/TICssBR+rrZYPaw1/NzsDF0WEVWS1sfUzZ49G23btsWqVatw/PhxnDx5UnlLTEzUWWHx8fHo06cPvLy8IJFIsGnTJrV5li5dCn9/f1hbWyMsLAz79+/X6jlkMhnCwsLw3HPPYd++fTqqnIjI+P105Cbe+P4oZIWlCPN1xu+j2zPQEVVzWu+pW7RoEb7//nu8+eabeijn/+Xn5yM0NBTDhg3DgAED1KavW7cOkyZNwtKlS9GhQwesWLECUVFROH/+PHx8fAAAYWFhKCoqUnvszp074eXlhRs3bsDLywtnz55Fr169cObMGXalEpFJkysEvth6Ad8fTAIA9G9RF7EvNYO1Bc9wJarutD6mrk6dOoiPj0ejRo30VZMaiUSCjRs3ol+/fsq2Nm3aoGXLlli2bJmyLTAwEP369UNsbKzWzxEVFYXPPvsM4eHh5U4vKipSCYgymQze3t48po6Iqo3cwhJMXJuI3RczAADvdmuMcV0aQiLhGa5EVUWfx9Rp3f06efJkLFmyRKdFaKu4uBgJCQmIjIxUaY+MjMShQ4c0Wsb9+/eVIS0lJQXnz59H/fr1K5w/NjYWjo6Oypu3t3flXwARURVLuV+AgcsOY/fFDFiZm2HJkJYY37URAx2RCdG6+/W9995Dr1690KBBAwQFBaldXWLDhg06K64imZmZkMvl8PRUPeXe09MT6enpGi3jwoULeOedd2BmZgaJRIJFixbBxcWlwvmnT5+OmJgY5f2yPXVERMbuRPJ9jFxzHJl5xXC3t8J3b4Qj1NvJ0GURkY5pHerGjx+PPXv2ICIiAq6urgb9lff4cwshNK6nffv2OHPmjMbPZWVlBSsrK63qIyIytE0nb2PK76dRXKpAUB0HfBcdDi8nG0OXRUR6oHWoW7NmDX7//Xf06tVLH/VoxM3NDVKpVG2vXEZGhtreOyKimqhUrsCcvy7i2/0PT4joFuSJhYObw86qUiNZEVE1oPUxdS4uLmjQoIE+atGYpaUlwsLCEBcXp9IeFxeH9u3bG6gqIiLjkF1QjGGrjykD3biIhlj+ehgDHZGJ0/oT/sknn2DmzJlYtWoVbG1t9VETACAvLw9Xr15V3k9KSkJiYiJcXFzg4+ODmJgYDB06FOHh4WjXrh1WrlyJ5ORkjBo1Sm81EREZu4vpMoxck4DkewWwtZRi3qBQ9GxWx9BlEVEV0HpIkxYtWuDatWsQQsDPz0/tRIkTJ07opLC9e/ciIiJCrT06OhqrV68G8HDw4a+++gppaWkIDg7GggUL8Pzzz+vk+Z+GlwkjImOz7Uwa3vvtFAqK5fB2scG3b4SjSW1un4iMiVFdJuzRseL0qXPnznha3hwzZgzGjBlTJfUQERkruUJgftwlLNlzDQDwXEM3LB7SAk62lgaujIiqktZ76ugh7qkjImMgKyzBpEcGFH67oz+m9mgCc6nWh0wTURUwqj11mtBmaBEiIqqcy3dyMep/CbiemQ8rczPMGRCCfi3qGrosIjIQjX7KBQYG4ueff0ZxcfET57ty5QpGjx6NOXPm6KQ4IiIq3x+Jt9F38UFcz8yHl6M11o9qz0BHVMNptKduyZIlmDp1KsaOHYvIyEiEh4fDy8sL1tbWuH//Ps6fP48DBw7g/PnzGDduHI9zIyLSk+JSBb7Yeh4/HL4J4OHxc4teaQ7XWhwcnaim0+qYukOHDmHdunWIj4/HjRs38ODBA7i5uaFFixbo3r07Xn/9dTg5OemxXOPBY+qIqKqlZj/A2J9P4GRyNoCH489N7tYYUjMe7kJUXRjNMXXt27fn4L5ERAZw8Gomxv9yEvfyi+FgbY4Fg5ujayCvoENE/4/DixMRGTGFQmDZvmv4euclKAQQVMcBy18Pg4+r/gZ/J6LqiaGOiMhI5RSUIObXROz6d7iSQWH18Fm/YFhbSA1cGREZI4Y6IiIjdPZ2Dkb/lIBb9x7A0twMn/VtisGtfAxdFhEZMYY6IiIjIoTAumO3MHPzORSVKlDP2QbLXgtDs3qOhi6NiIwcQx0RkZHIKyrFjI1n8EdiKgAgIsAdCwY35+W+iEgjlQp1CoUCV69eRUZGBhQKhcq0559/XieFERHVJBfSZBj70wlcz8yH1EyC9yID8M7z9WHG4UqISENah7p//vkHQ4YMwc2bN/H4EHcSiQRyuVxnxRERmTohBNYeu4VP/u1ure1gjW+GtEArPxdDl0ZE1YzWoW7UqFEIDw/H1q1bUadOHV7jlYiokh7vbu0c4I75LzeHix27W4lIe1qHuitXrmD9+vVo2LChPuohIqoRzqfKMO5ndrcSke5oHeratGmDq1evMtQREVWCEAK/HL2FT7acQ3GpAnUcrfHNqy0Qzu5WInpGWoe68ePH491330V6ejqaNWsGCwsLlekhISE6K46IyJTkFZXigw1nsPnU/5/d+jW7W4lIRyTi8bMdnsLMzEx9IRIJhBA16kQJfV6Ql4hMz/lUGcb+fAJJ/3a3TukegLc7sruVqKbRZ37Qek9dUlKSTgsgIjJlQgj8fDQZn245j+JSBbwcH57dGubL7lYi0i2tQ52vr68+6iAiMjm5hSX4YONZbPm3u7VLEw98PSgUzuxuJSI9qNTgw9euXcPChQtx4cIFSCQSBAYGYuLEiWjQoIGu6yMiqpZO3crGhLUncTOrAFIzCab2CMCI59jdSkT6o36A3FPs2LEDQUFBOHr0KEJCQhAcHIwjR46gadOmiIuL00eNRETVhkIhsDL+GgYsO4SbWQWo62SDX99pi5HPN2CgIyK90vpEiRYtWqB79+748ssvVdqnTZuGnTt34sSJEzot0FjxRAkietzd3CK8+9spxF++CwCICq6NL18KgaOtxVMeSUQ1hT7zg9ahztraGmfOnEGjRo1U2i9fvoyQkBAUFhbqtEBjxVBHRI/af+UuJq87hcy8IliZm+HjPkEY0tqHV90hIhVGdfaru7s7EhMT1UJdYmIiPDw8dFYYEVF1UCJXYN7OS1ix7zoAoLFnLSwe0hKNPe0NXBkR1TRah7q3334bI0eOxPXr19G+fXtIJBIcOHAAc+bMwbvvvquPGomIjFJyVgHGrz2JU7eyAQCvtfHBR72DYG0hNWxhRFQjad39KoTAwoUL8fXXXyM19eFp+l5eXnj//fcxYcKEGtPVwO5Xoppt86lUzNhwBrlFpXCwNsecASGIalbH0GURkZEzqmPqHpWbmwsAsLeved0MDHVENVNBcSlm/nEOvyWkAADCfZ2x6NUWqOtkY+DKiKg6MKpj6h5VE8McEdVc51JzMP6Xk7h+Nx8SCTA+oiEmdG0Ec6nWo0MREemcRqGuZcuW2LVrF5ydndGiRYsndrHWlCFNiKjmEEJg9aEbiN12EcVyBWo7WGPB4OZo18DV0KURESlpFOr69u0LKysr5f9rynFzRET38osxZf0p/H0hAwDwQqAHvhoYChde6ouIjMwzHVNXk/GYOiLTd/haFiatO4k7siJYSs3wQc8miG7vxx+2RFRp+swPWh8IUr9+fWRlZam1Z2dno379+jopiojIkErlCszfeQlDvvsHd2RFqO9uh01jO+DNDv4MdERktLQ+UeLGjRuQy+Vq7UVFRUhJSdFJUUREhnI7+wEmrT2JYzfuAwBeDq+HT15sClvLZzqvjIhI7zTeSm3evFn5/x07dsDR0VF5Xy6XY9euXfD399dtdUREVWj7mTRM/f00ZIWlqGVlji/6B6Nv87qGLouISCMah7p+/foBACQSCaKjo1WmWVhYwM/PD19//bVOiyMiqgoPiuX4bOt5/HwkGQAQ6u2Eb15pAR9XWwNXRkSkOY1DnUKhAAD4+/vj2LFjcHNz01tRRERV5VJ6Lsb/cgKX7+QBAEZ1aoB3IxvDgmPPEVE1o/VBIklJSfqog4ioSgkh8OORZHz+53kUlSrgbm+F+S+HomMjd0OXRkRUKZU68jc/Px/79u1DcnIyiouLVaZNmDBBJ4UREelLdkExpqw/jZ3n7wAAOge4Y96gULjVsjJwZURElad1qDt58iR69uyJgoIC5Ofnw8XFBZmZmbC1tYWHhwdDHREZtSPXszBpXSLScgphIZVgWlQghrX3g5kZhyohoupN64NGJk+ejD59+uDevXuwsbHBP//8g5s3byIsLAzz5s3TR416cenSJTRv3lx5s7GxwaZNmwxdFhHpSalcgQVxl/Hqt/8gLacQ/m522DimA4Y/589AR0QmQesrSjg5OeHIkSMICAiAk5MTDh8+jMDAQBw5cgTR0dG4ePGivmrVm7y8PPj5+eHmzZuws7PT6DG8ogRR9ZGa/QCT1ibi6I17AIABLethVt+msLPi2HNEVLX0mR+03qJZWFgoR1T39PREcnIyAgMD4ejoiOTkZJ0WV1U2b96Mrl27ahzoiKj62HspA5PXJeJ+QQlqWZnj837B6NeCY88RkenRuvu1RYsWOH78OAAgIiICH3/8MX766SdMmjQJzZo101lh8fHx6NOnD7y8vCCRSMrtGl26dCn8/f1hbW2NsLAw7N+/v1LP9euvv2Lw4MHPWDERGRO5QuDrnZcwbPUx3C8oQXBdB2yd8BwDHRGZLK1D3ezZs1GnTh0AwGeffQZXV1eMHj0aGRkZWLlypc4Ky8/PR2hoKBYvXlzu9HXr1mHSpEmYMWMGTp48iY4dOyIqKkplb2FYWBiCg4PVbqmpqcp5ZDIZDh48iJ49e+qsdiIyrLu5RXjj+yP4ZvdVCAG83tYH60e1h68r98YTkenS6pg6IQSSk5Ph4eEBGxsbfdalQiKRYOPGjcqrWgBAmzZt0LJlSyxbtkzZFhgYiH79+iE2NlbjZf/vf//Djh078OOPPz5xvqKiIhQVFSnvy2QyeHt785g6IiNzNOkexv18Ahm5RbC1lCL2pWa81BcRGQ19HlOn1Z46IQQaNWqElJQUnRahreLiYiQkJCAyMlKlPTIyEocOHdJqWZp2vcbGxsLR0VF58/b21up5iEi/hBBYfTAJr377DzJyi9DIoxY2j+vAQEdENYZWoc7MzAyNGjVCVlaWvurRSGZmJuRyOTw9PVXaPT09kZ6ervFycnJycPToUXTv3v2p806fPh05OTnK261bt7Sum4j0o6hUjmm/n8EnW85DrhDo19wLf4zrgIYe9oYujYioymh9TN1XX32F999/H2fPntVHPVopOwu3jBBCre1JHB0dcefOHVhaWj51XisrKzg4OKjciMjw7uYWYci3R7Du+C2YSYAPewViweDmsLXkcCVEVLNovdV7/fXXUVBQgNDQUFhaWqodW3fv3j2dFVcRNzc3SKVStb1yGRkZanvviMh0nb2dg7fXHEdaTiHsrc2xeEhLdGrMa7cSUc2kdahbsGCBVnvD9MHS0hJhYWGIi4tD//79le1xcXHo27evASsjoqqy52IGxv58AgXFctR3t8N3b4SjvnstQ5dFRGQwWoe6N998Uw9lqMvLy8PVq1eV95OSkpCYmAgXFxf4+PggJiYGQ4cORXh4ONq1a4eVK1ciOTkZo0aNqpL6iMhw1h5NxoxNZyFXCHRs5IYlr7WEg7WFocsiIjIorUOdVCpFWloaPDw8VNqzsrLg4eEBuVyuk8KOHz+OiIgI5f2YmBgAQHR0NFavXo3BgwcjKysLs2bNQlpaGoKDg7Ft2zb4+vrq5PmJyPgIIbDg7yv4z64rAB5e7uvLAc1gIdX68GAiIpOj9bVfzczMkJ6erhbqUlNT0aBBAzx48ECnBRorXvuVqGrJFQIfbDiDdccfnnk+oWsjTH6hkcEPByEi0oZRXPv1P//5D4CHZ5x+9913qFXr/49dkcvliI+PR5MmTXRaHBERAJTIFZi8LhF/nk6DmQT4on8zvNrax9BlEREZFY1D3YIFCwA87P5Yvnw5pFKpcpqlpSX8/PywfPly3VdIRDVaYYkc434+gb8vZMBCKsF/XmmBqGZ1DF0WEZHR0TjUJSUlAQAiIiKwYcMGODs7660oIiIAKCguxcg1CThwNRNW5mZYPjQMEQEeT38gEVENpPWJEnv27NFHHUREKgqKSzFs1TEcSboHW0sp/hvdCu0auBq6LCIio6V1qJPL5Vi9ejV27dqFjIwMKBQKlem7d+/WWXFEVDMVlsjx9prjOJJ0D/ZW5vhheGu09GHvABHRk2gd6iZOnIjVq1ejV69eCA4O5plnRKRThSVyjPxfAg5ezYKdpRSr32KgIyLShNahbu3atfj111/Rs2dPfdRDRDVYcakCY386gfjLd2FjIcWqYa0R5stAR0SkCa1H7LS0tETDhg31UQsR1WByhcCkdSex62IGrMzN8N83w9Ha38XQZRERVRtah7p3330XixYtgpZjFhMRVUgIgY//OIttZ9JhKTXDt2+Eo30DN0OXRURUrWjd/XrgwAHs2bMH27dvR9OmTWFhoXq9xQ0bNuisOCKqGRbtuoKfjiRDIgEWvtIczzd2N3RJRETVjtahzsnJCf3799dHLURUA/34z00s/PvhtVxn9Q1GTw4sTERUKVqHulWrVumjDiKqgbadScNHf5wF8PBarkPb+hq4IiKi6kvrY+oAoLS0FH///TdWrFiB3NxcAEBqairy8vJ0WhwRma6jSfcwaW0ihACGtPHB5BcaGbokIqJqTes9dTdv3kSPHj2QnJyMoqIidOvWDfb29vjqq69QWFjI678S0VPdyMzHO/87jmK5At2beuKzvhzzkojoWWm9p27ixIkIDw/H/fv3YWNjo2zv378/du3apdPiiMj05BSU4K3Vx3C/oASh9RyxcHALSM0Y6IiInlWlzn49ePAgLC0tVdp9fX1x+/ZtnRVGRKanuFSBUT8m4HpmPuo62eDb6HDYWEoNXRYRkUnQek+dQqGAXC5Xa09JSYG9vb1OiiIi0yOEwIebzuDw9SzUsjLHf98Mh4e9taHLIiIyGVqHum7dumHhwoXK+xKJBHl5eZg5cyYvHUZEFVq+7zp+PZ4CMwnwzZAWaFLbwdAlERGZFK27XxcsWICIiAgEBQWhsLAQQ4YMwZUrV+Dm5oZffvlFHzUSUTW341w65vx1EQAws09TRAR4GLgiIiLTo3Wo8/LyQmJiItauXYuEhAQoFAoMHz4cr732msqJE0REAHD5Ti5i1iUCAKLb+SK6vZ9B6yEiMlUSwYu4VopMJoOjoyNycnLg4MBuJKLy5BSUoO+SA7iRVYB29V2xZnhrWEgrNTwmEZFJ0Gd+0HrrGhsbi++//16t/fvvv8ecOXN0UhQRVX9yhcCEtSdxI6sAdZ1ssOS1lgx0RER6pPUWdsWKFWjSpIlae9OmTTnwMBEpzd1xCfsu34W1hRlWvhEGFzvLpz+IiIgqTetQl56ejjp11C+47e7ujrS0NJ0URUTV2+ZTqVi+7xoAYO7AUDT1cjRwRUREpk/rUOft7Y2DBw+qtR88eBBeXl46KYqIqq9zqTmYsv4UAGBUpwboE8rtAhFRVdD67NcRI0Zg0qRJKCkpQZcuXQAAu3btwpQpU/Duu+/qvEAiqj6yC4oxck0CCksUeL6xO97vHmDokoiIagytQ92UKVNw7949jBkzBsXFxQAAa2trTJ06FdOnT9d5gURUPSgUApPXJeJ29gP4utrim1d4TVcioqpU6SFN8vLycOHCBdjY2KBRo0awsrLSdW1GjUOaEKlasucq5u64BCtzM2wY057H0RERlUOf+UHrPXVlatWqhVatWumyFiKqpg5dzcTXOy8BAD7rG8xAR0RkAFqHuvz8fHz55ZfYtWsXMjIyoFAoVKZfv35dZ8URkfG7IyvEhLUnoRDAoLB6eLmVt6FLIiKqkSp1osS+ffswdOhQ1KlTBxIJj5khqqlK5AqM+/kEMvOK0aS2PWb1DTZ0SURENZbWoW779u3YunUrOnTooI96iKgambfjEo7duA97K3Msez0MNpZSQ5dERFRjaT1OnbOzM1xcXPRRCxFVI7sv3sGK+IeHW8wdFAJ/NzsDV0REVLNpHeo+++wzfPzxxygoKNBHPURUDWTICvHeb6cBAG+290OPYPWrzBARUdXSuvv166+/xrVr1+Dp6Qk/Pz9YWFioTD9x4oTOiiMi46NQCEz+NRH38osRVMcB03uqXwuaiIiqntahrl+/fnoog4iqixXx13HwahZsLKT4ZkgLWJnzODoiImOgdaibOXOmPuogomrgZPJ95Xh0n/ZtigbutQxcERERlan04MMJCQm4cOECJBIJgoKC0KJFC13WRURGRlZYgglrT6JUIdAn1AuDwuoZuiQiInqE1qEuIyMDr7zyCvbu3QsnJycIIZCTk4OIiAisXbsW7u7u+qiTiAxICIEPN57FrXsPUM/ZBl/0D+YYlURERkbrs1/Hjx8PmUyGc+fO4d69e7h//z7Onj0LmUyGCRMm6KNGIjKw30/cxuZTqZCaSfCfV1vAwdri6Q8iIqIqpfWeur/++gt///03AgMDlW1BQUFYsmQJIiMjdVocERleyv0CfLL5HAAgpltjtPRxNnBFRERUHq331CkUCrVhTADAwsJC7Tqwxm7evHlo2rQpgoOD8eOPPxq6HCKjo1AITFl/GnlFpQj3dcaoTg0MXRIREVVA61DXpUsXTJw4Eampqcq227dvY/LkyejatatOi9OnM2fO4Oeff0ZCQgKOHz+OZcuWITs729BlERmVn47cxKFrWbC2MMO8QaGQmvE4OiIiY6V1qFu8eDFyc3Ph5+eHBg0aoGHDhvD390dubi6++eYbfdSoFxcuXED79u1hbW0Na2trNG/eHH/99ZehyyIyGslZBZi97SIAYFqPJvDjZcCIiIya1qHO29sbJ06cwNatWzFp0iRMmDAB27ZtQ0JCAurV090QB/Hx8ejTpw+8vLwgkUiwadMmtXmWLl0Kf39/WFtbIywsDPv379d4+cHBwdizZw+ys7ORnZ2N3bt34/bt2zqrn6g6UygE3lt/Cg9K5Ghb3wVvtPMzdElERPQUlR6nrlu3bujWrZsua1GRn5+P0NBQDBs2DAMGDFCbvm7dOkyaNAlLly5Fhw4dsGLFCkRFReH8+fPw8fEBAISFhaGoqEjtsTt37kRQUBAmTJiALl26wNHREa1atYK5eaVXB5FJWX3oBo4m3YOtpRRzB4bCjN2uRERGTyKEEJrMuHv3bowbNw7//PMPHBwcVKbl5OSgffv2WL58OTp27Kj7IiUSbNy4UeUSZW3atEHLli2xbNkyZVtgYCD69euH2NhYrZ9jxIgR6N+/P3r16lXu9KKiIpWAKJPJ4O3tjZycHLX1QVSdXb+bh57/2Y/CEgU+7xeM19v6GrokIiKTIZPJ4OjoqJf8oHH368KFC/H222+XW4CjoyPeeecdzJ8/X6fFVaS4uBgJCQlqQ6hERkbi0KFDGi8nIyMDAHDp0iUcPXoU3bt3r3De2NhYODo6Km/e3t6VK57IiMkVAu/9dgqFJQo819ANr7XxMXRJRESkIY1D3alTp9CjR48Kp0dGRiIhIUEnRT1NZmYm5HI5PD09Vdo9PT2Rnp6u8XL69euHoKAgvP7661i1atUTu1+nT5+OnJwc5e3WrVuVrp/IWP33wHWcSM6GvZU55gwM4VUjiIiqEY0PIrtz506549MpF2Rujrt37+qkKE09/oUjhNDqS0ibvXpWVlawsrLSeH6i6ubKnVzM23kZAPBR7yDUdbIxcEVERKQNjffU1a1bF2fOnKlw+unTp1GnTh2dFPU0bm5ukEqlanvlMjIy1PbeEdHTlcoVeO+3UyguVSAiwB2DwnV3JjsREVUNjUNdz5498fHHH6OwsFBt2oMHDzBz5kz07t1bp8VVxNLSEmFhYYiLi1Npj4uLQ/v27aukBiJTsiL+Ok6l5MDB2hyxL7HblYioOtK4+/XDDz/Ehg0b0LhxY4wbNw4BAQGQSCS4cOEClixZArlcjhkzZuissLy8PFy9elV5PykpCYmJiXBxcYGPjw9iYmIwdOhQhIeHo127dli5ciWSk5MxatQondVAVBNcTJdh4d8Pu10/ebEpajtaG7giIiKqDI1DnaenJw4dOoTRo0dj+vTpKBsJRSKRoHv37li6dKlOuz6PHz+OiIgI5f2YmBgAQHR0NFavXo3BgwcjKysLs2bNQlpaGoKDg7Ft2zb4+nL4BSJNlcgVePfXUyiRC3QL8kT/FnUNXRIREVWSxuPUPer+/fu4evUqhBBo1KgRnJ2d9VGbUdPnODNEVWXh35ex8O8rcLK1wM7Jz8PDnnvpiIj0SZ/5oVKXUHB2dkarVq10WggRVa2zt3OwePfDQxxm9Q1moCMiqua0vvYrEVV/RaVyvPfbKZQqBHo2q40+IVVz5joREekPQx1RDfSfXVdwMT0XrnaW+KxvMM92JSIyAQx1RDXMqVvZWLb3GgDg837BcK3FQbWJiEwBQx1RDVJYIse7v52CQgAvhnohqhm7XYmITAVDHVENsiDuMq5m5MHd3gqfvtjU0OUQEZEOMdQR1RAJN+9h5f7rAIDY/s3gbGdp4IqIiEiXGOqIaoAHxXK899tpCAEMaFkPLwTxGslERKaGoY6oBvhqx0UkZebD08EKH/cJMnQ5RESkBwx1RCbun+tZWHXwBgBgzoAQONpYGLYgIiLSC4Y6IhOWX1SKKetPAwBeaeWNzgEeBq6IiIj0haGOyIR9uf0iku8VoK6TDWb0CjR0OUREpEcMdUQm6uDVTPzvn5sAHna72luz25WIyJQx1BGZoNzCEmW36+ttffBcIzcDV0RERPrGUEdkgmZvu4Db2Q/g7WKD6VHsdiUiqgkY6ohMzN5LGfjl6C0AwNyBobCzMjdwRUREVBUY6ohMSM6DEkz7/QwAYFgHP7St72rgioiIqKow1BGZkFlbziNdVgh/NztM6d7E0OUQEVEVYqgjMhF/n7+D30+kQCIB5g0KgY2l1NAlERFRFWKoIzIB9/OLMX3jw27XtzvWR5ivi4ErIiKiqsZQR2QCPtlyDndzi9DA3Q4x3RobuhwiIjIAhjqiau6vs2n4IzEVZhLg65ebw9qC3a5ERDURQx1RNZaVV4QZG88CAEZ1aoDm3k6GLYiIiAyGoY6omhJC4KM/ziIrvxgBnvaY+EIjQ5dEREQGxFBHVE1tPpWKbWfSYW4mwdcvh8LKnN2uREQ1GUMdUTV0R1aIj/84BwAY16Uhgus6GrgiIiIyNIY6ompGCIFpv59GzoMSNKvriLERDQ1dEhERGQGGOqJq5tfjt7Dn0l1Ympvh65dDYSHlx5iIiBjqiKqVW/cKMGvLeQDAe5GN0djT3sAVERGRsWCoI6omFAqBKetPI79YjnBfZwx/rr6hSyIiIiPCUEdUTfxw+AYOX8+CjYUU8waFQmomMXRJRERkRBjqiKqBa3fz8OX2iwCAD3o2gZ+bnYErIiIiY8NQR2TkSuUKvPfbKRSVKtCxkRteb+tr6JKIiMgIMdQRGbmV+6/jZHI27K3MMWdACCQSdrsSEZE6hjoiI3YxXYYFcZcBADNfbAovJxsDV0RERMaKoY7ISBWVyjF53SmUyAVeCPTEgJZ1DV0SEREZMYY6IiM1b8clXEiTwcXOErNfCma3KxERPRFDHZEROng1E9/uTwIAfDUgBB721gauiIiIjB1DHZGRyS4oxru/ngIADGnjgxeCPA1cERERVQcMdURGRAiB6RvOIF1WiPpudviwV6ChSyIiomqiRoS6/v37w9nZGQMHDtRqGlFV+y0hBdvPpsPcTIJFr7SAraW5oUsiIqJqokaEugkTJmDNmjVaTyOqSjez8vHp5nMAgJjIxmhWz9HAFRERUXVSI0JdREQE7O3ttZ5GVFVK5QpMWpeI/GI5Wvu74J3nGxi6JCIiqmYMHuri4+PRp08feHl5QSKRYNOmTWrzLF26FP7+/rC2tkZYWBj2799f9YUS6dGiXVceXjXC2hwLBjeH1IzDlxARkXYMHury8/MRGhqKxYsXlzt93bp1mDRpEmbMmIGTJ0+iY8eOiIqKQnJysnKesLAwBAcHq91SU1Or6mUQVdr+K3exeM9VAMAX/ZuhLq8aQURElWDwo7CjoqIQFRVV4fT58+dj+PDhGDFiBABg4cKF2LFjB5YtW4bY2FgAQEJCQpXUSqRrGbJCTFqbCCGAV1v74MVQL0OXRERE1ZTB99Q9SXFxMRISEhAZGanSHhkZiUOHDlVpLUVFRZDJZCo3omchVwhMXJuIrPxiNKltj5l9ggxdEhERVWNGHeoyMzMhl8vh6ak6+KqnpyfS09M1Xk737t0xaNAgbNu2DfXq1cOxY8c0mvao2NhYODo6Km/e3t6Ve1FE//rPris4fD0LtpZSLHmtJawtpIYuiYiIqjGDd79q4vFrXgohtLoO5o4dOyo17VHTp09HTEyM8r5MJmOwo0o7eDUT/9l9BQAwu38zNHCvZeCKiIioujPqUOfm5gapVKq2Vy4jI0Nt752+WVlZwcrKqkqfk0xTek4hJv57HN0rrbzRr0VdQ5dEREQmwKi7Xy0tLREWFoa4uDiV9ri4OLRv395AVRFVXlGpHKN+TEBmXtG/x9E1NXRJRERkIgy+py4vLw9Xr15V3k9KSkJiYiJcXFzg4+ODmJgYDB06FOHh4WjXrh1WrlyJ5ORkjBo1yoBVE2lPCIGPN51D4q1sONpYYOXQcNhY8jg6IiLSDYOHuuPHjyMiIkJ5v+y4tejoaKxevRqDBw9GVlYWZs2ahbS0NAQHB2Pbtm3w9fU1VMlElfLTkWSsO34LZhLgm1dbwMfV1tAlERGRCZEIIYShi6iOZDIZHB0dkZOTAwcHB0OXQ0buaNI9vPbdPyiRC0zt0QSjO/MyYERENZE+84NRH1NHZAqu3c3DyP8dR4lcoFezOhjVqb6hSyIiIhPEUEekR1l5RRi26hiyC0oQ6u2EeYNCtRqOh4iISFMMdUR6Ulgix4g1x5F8rwDeLjb4bzRPjCAiIv1hqCPSg1K5AhN+OYmTyQ/PdF31Zmu41eI4h0REpD8MdUQ6JlcIxPx6CjvP34Gl1Awrh4ahoQevGEFERPrFUEekQwqFwLTfT2PzqVSYm0mw9LWWaFPf1dBlERFRDcBQR6QjcoXABxvP4LeEFJhJgP+82gIvBFXt5eyIiKjmMvjgw0SmoKhUjklrE7H9bDrMJMDXL4eiZ7M6hi6LiIhqEIY6omeUW1iCd/6XgEPXsmApNcOiV5ojioGOiIiqGEMd0TO4fjcPI/+XgKsZebCzlOLbN8LRvqGbocsiIqIaiKGOqJL+Pn8Hk39NRG5hKTwdrPDtG+EIqedk6LKIiKiGYqgj0lJBcSm+2HoBPx1JBgCE+Tpj2est4WFvbeDKiIioJmOoI9LCnksZ+GTzOdzMKgAAvNXBH1OjAmBlzitFEBGRYTHUEWng8p1czN1xCXHn7wAAPB2s8PWg5niuEY+fIyIi48BQR/QEp25lY+X+69h2Jg1CAFIzCYa198PEFxrB3trC0OUREREpMdQRPSYjtxA7zt3Bb8dv4XRKjrI9Krg2Yro1RiNPewNWR0REVD6GOqrxCkvkOJ2SgyPXsxB/5S6O37wPIR5Os5SaoWez2ninUwME1nEwbKFERERPwFBHNYJCIZCVX4y0nAdIzS7Ejax8XErPxcX0XFzLyEOxXKEyf3NvJ/RqVgcvtawL11pWBqqaiIhIcwx1z+hk8n3Uspf/e0+oTRfqTeXMVcF85TRq8lhR3lzPUkclX5em9Zdfm3qjQgGUyBUolitQVKpAcdlNrkDJv//mF8khKyxBbmEJZA9KISssQc6DEmTIitSC26Pcalmhjb8L2tZ3QddAT3g52VQ4LxERkTFiqHtGQ/97FGZWtoYugzQgkQAe9lao7WgDb2cbBHjaI6C2PZrUdoC3iw0kEomhSyQiIqo0hrpn5O1iA3Pr/w915cWC8sJCufGhnMbKLq+8fCIpZ2ma5hhNX8Pjsz1LHWpNEgkspRJYmpvBUmoGS3MzWPz7r9W/bTaW5nCwMYeDtQUcbCxgb/3w/54OVvB0sIaF1KzC10hERFSdMdQ9o+0Tn4eDAw+gJyIiIsPibgsiIiIiE8BQR0RERGQCGOqIiIiITABDHREREZEJYKgjIiIiMgEMdUREREQmgKGOiIiIyAQw1BERERGZAIY6IiIiIhPAUEdERERkAhjqiIiIiEwAQx0RERGRCWCoIyIiIjIBDHVEREREJoChjoiIiMgEMNQRERERmQCGOiIiIiITwFBHREREZAIY6oiIiIhMQI0Idf3794ezszMGDhyo0p6bm4tWrVqhefPmaNasGb799lsDVUhERET0bCRCCGHoIvRtz549yMvLww8//ID169cr2+VyOYqKimBra4uCggIEBwfj2LFjcHV1feoyZTIZHB0dkZOTAwcHB32WT0RERCZCn/mhRuypi4iIgL29vVq7VCqFra0tAKCwsBByuRw1IOMSERGRCTJ4qIuPj0efPn3g5eUFiUSCTZs2qc2zdOlS+Pv7w9raGmFhYdi/f7/Onj87OxuhoaGoV68epkyZAjc3N50tm4iIiKiqGDzU5efnIzQ0FIsXLy53+rp16zBp0iTMmDEDJ0+eRMeOHREVFYXk5GTlPGFhYQgODla7paamPvX5nZyccOrUKSQlJeHnn3/GnTt3dPbaiIiIiKqKuaELiIqKQlRUVIXT58+fj+HDh2PEiBEAgIULF2LHjh1YtmwZYmNjAQAJCQnPXIenpydCQkIQHx+PQYMGqU0vKipCUVGR8n5OTg6Ah33jRERERJooyw36ONzL4KHuSYqLi5GQkIBp06aptEdGRuLQoUPPvPw7d+7AxsYGDg4OkMlkiI+Px+jRo8udNzY2Fp9++qlau7e39zPXQURERDVLVlYWHB0ddbpMow51mZmZkMvl8PT0VGn39PREenq6xsvp3r07Tpw4gfz8fNSrVw8bN25Eq1atkJKSguHDh0MIASEExo0bh5CQkHKXMX36dMTExCjvZ2dnw9fXF8nJyTr/o5gamUwGb29v3Lp1i2cKa4DrS3NcV9rh+tIc15V2uL40l5OTAx8fH7i4uOh82UYd6spIJBKV+0IItbYn2bFjR7ntYWFhSExM1GgZVlZWsLKyUmt3dHTkG1hDDg4OXFda4PrSHNeVdri+NMd1pR2uL82Zmen+tAaDnyjxJG5ubpBKpWp75TIyMtT23hERERHVZEYd6iwtLREWFoa4uDiV9ri4OLRv395AVREREREZH4N3v+bl5eHq1avK+0lJSUhMTISLiwt8fHwQExODoUOHIjw8HO3atcPKlSuRnJyMUaNGGbDqh92xM2fOLLdLllRxXWmH60tzXFfa4frSHNeVdri+NKfPdWXwy4Tt3bsXERERau3R0dFYvXo1gIeDD3/11VdIS0tDcHAwFixYgOeff76KKyUiIiIyXgYPdURERET07Iz6mDoiIiIi0gxDHREREZEJYKgjIiIiMgEMdXrSv39/ODs7Y+DAgVpNI2DevHlo2rQpgoOD8eOPPxq6HKN16dIlNG/eXHmzsbHBpk2bDF2WUTM3N1eur7LrSZO63NxctGrVCs2bN0ezZs3w7bffGroko8ftesW4bjT3rJ89niihJ3v27EFeXh5++OEHrF+/XuNpNd2ZM2cQHR2tvLZv165dsXXrVjg5ORm2MCOXl5cHPz8/3Lx5E3Z2doYux2i5ubkhMzPT0GUYPblcjqKiItja2qKgoADBwcE4duwYXF1dDV2a0eJ2vWJcN5p71s8e99TpSUREBOzt7bWeVtNduHAB7du3h7W1NaytrdG8eXP89ddfhi7L6G3evBldu3ZloCOdkEqlsLW1BQAUFhZCLpeDv/+fjNv1inHdaO5ZP3s1MtTFx8ejT58+8PLygkQiKbfLaunSpfD394e1tTXCwsKwf//+qi/UCOl73QUHB2PPnj3Izs5GdnY2du/ejdu3b+vwFVSdqnyf/frrrxg8ePAzVmxYVbG+ZDIZwsLC8Nxzz2Hfvn06qrzqVcW6ys7ORmhoKOrVq4cpU6bAzc1NR9VXPW7zK4/rTju6WF/P8tmrkaEuPz8foaGhWLx4cbnT161bh0mTJmHGjBk4efIkOnbsiKioKCQnJyvnCQsLQ3BwsNotNTW1ql6GQeh73QUFBWHChAno0qUL+vfvj1atWsHc3OAXPqmUqnqfyWQyHDx4ED179tT7a9KnqlhfN27cQEJCApYvX4433ngDMpmsSl6brlXFunJycsKpU6eQlJSEn3/+GXfu3KmS16YP3OZXni7WXU2ii/X1TJ89UcMBEBs3blRpa926tRg1apRKW5MmTcS0adO0WvaePXvEgAEDtJ5WXehz3ZUZPny4+PPPPytbotHQ57pas2aNeO211561RKNSFe+tHj16iGPHjlW2RKNRFetq1KhR4tdff61siUbFUNt8U/As687U1015dPFe0/azVyP31D1JcXExEhISEBkZqdIeGRmpPHifyqerdZeRkQHg4dmdR48eRffu3XVapzHQ5fvMFLpen0YX6+v+/fsoKioCAKSkpOD8+fOoX7++zms1NF2sqzt37ij3YspkMsTHxyMgIEDntRoDbvMrj+tOO5qsr2f97FXPfi09yszMhFwuh6enp0q7p6cn0tPTNV5O9+7dceLECeTn56NevXrYuHEjWrVq9dRp1Zmu1l2/fv2QnZ0NOzs7rFq1qtp2vz6JrtZVTk4Ojh49it9//13XJRoVXayvCxcu4J133oGZmRkkEgkWLVoEFxcXfZRrULpYVykpKRg+fDiEEBBCYNy4cQgJCdFHuQZXFdt8U6XpuquJ66Y8mqyvZ/3smd63pY5IJBKV+0IItbYn2bFjR6WmmYJnXXc16Rfes64rR0fHan2sk7aeZX21b98eZ86c0UdZRulZ1lVYWBgSExP1UJXx0uc239Q9bd3V5HVTnietr2f97LH79TFubm6QSqVqv9AyMjLU0jWp4rrTHNeVdri+NMd1pR2ur8rjutNOVawvhrrHWFpaIiwsDHFxcSrtcXFxaN++vYGqqh647jTHdaUdri/NcV1ph+ur8rjutFMV66tGdr/m5eXh6tWryvtJSUlITEyEi4sLfHx8EBMTg6FDhyI8PBzt2rXDypUrkZycjFGjRhmwauPAdac5rivtcH1pjutKO1xflcd1px2Dry+Nz5M1IXv27BEA1G7R0dHKeZYsWSJ8fX2FpaWlaNmypdi3b5/hCjYiXHea47rSDteX5riutMP1VXlcd9ox9PritV+JiIiITACPqSMiIiIyAQx1RERERCaAoY6IiIjIBDDUEREREZkAhjoiIiIiE8BQR0RERGQCGOqIiIiITABDHREREZEJYKgjIiIiMgEMdURE//rkk0/QvHlzgz3/Rx99hJEjR2o073vvvYcJEybouSIiqk54mTAiqhEkEskTp0dHR2Px4sUoKiqCq6trFVX1/+7cuYNGjRrh9OnT8PPze+r8GRkZaNCgAU6fPg1/f3/9F0hERo+hjohqhPT0dOX/161bh48//hiXLl1SttnY2MDR0dEQpQEAZs+ejX379mHHjh0aP2bAgAFo2LAh5syZo8fKiKi6YPcrEdUItWvXVt4cHR0hkUjU2h7vfn3zzTfRr18/zJ49G56ennBycsKnn36K0tJSvP/++3BxcUG9evXw/fffqzzX7du3MXjwYDg7O8PV1RV9+/bFjRs3nljf2rVr8eKLL6q0rV+/Hs2aNYONjQ1cXV3xwgsvID8/Xzn9xRdfxC+//PLM64aITANDHRHRE+zevRupqamIj4/H/Pnz8cknn6B3795wdnbGkSNHMGrUKIwaNQq3bt0CABQUFCAiIgK1atVCfHw8Dhw4gFq1aqFHjx4oLi4u9znu37+Ps2fPIjw8XNmWlpaGV199FW+99RYuXLiAvXv34qWXXsKjnSutW7fGrVu3cPPmTf2uBCKqFhjqiIiewMXFBf/5z38QEBCAt956CwEBASgoKMAHH3yARo0aYfr06bC0tMTBgwcBPNzjZmZmhu+++w7NmjVDYGAgVq1aheTkZOzdu7fc57h58yaEEPDy8lK2paWlobS0FC+99BL8/PzQrFkzjBkzBrVq1VLOU7duXQB46l5AIqoZzA1dABGRMWvatCnMzP7/96+npyeCg4OV96VSKVxdXZGRkQEASEhIwNWrV2Fvb6+ynMLCQly7dq3c53jw4AEAwNraWtkWGhqKrl27olmzZujevTsiIyMxcOBAODs7K+exsbEB8HDvIBERQx0R0RNYWFio3JdIJOW2KRQKAIBCoUBYWBh++ukntWW5u7uX+xxubm4AHnbDls0jlUoRFxeHQ4cOYefOnfjmm28wY8YMHDlyRHm267179564XCKqWdj9SkSkQy1btsSVK1fg4eGBhg0bqtwqOru2QYMGcHBwwPnz51XaJRIJOnTogE8//RQnT56EpaUlNm7cqJx+9uxZWFhYoGnTpnp9TURUPTDUERHp0GuvvQY3Nzf07dsX+/fvR1JSEvbt24eJEyciJSWl3MeYmZnhhRdewIEDB5RtR44cwezZs3H8+HEkJydjw4YNuHv3LgIDA5Xz7N+/Hx07dlR2wxJRzcZQR0SkQ7a2toiPj4ePjw9eeuklBAYG4q233sKDBw/g4OBQ4eNGjhyJtWvXKrtxHRwcEB8fj549e6Jx48b48MMP8fXXXyMqKkr5mF9++QVvv/223l8TEVUPHHyYiMgICCHQtm1bTJo0Ca+++upT59+6dSvef/99nD59GubmPDyaiLinjojIKEgkEqxcuRKlpaUazZ+fn49Vq1Yx0BGREvfUEREREZkA7qkjIiIiMgEMdUREREQmgKGOiIiIyAQw1BERERGZAIY6IiIiIhPAUEdERERkAhjqiIiIiEwAQx0RERGRCWCoIyIiIjIBDHVEREREJuD/AM339j3Bv6jkAAAAAElFTkSuQmCC", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Plots the Boundary Layer Concentration of O=CO from ROP Integration WITHOUT Diffusion Flux Into Reservoir\n", - "clf()\n", - "\n", - "plot(t_vals, Cbl_vals)\n", - "\n", - "xscale(\"log\")\n", - "xlim(1e-11,1e3)\n", - "yscale(\"log\")\n", - "ylim(1e-13,1e1)\n", - "xlabel(\"Time (s)\")\n", - "ylabel(\"Concentration (mol/m^3)\")\n", - "title(\"Boundary Layer Accumulation of O=CO from ROP Integration\")\n", - "legend()\n", - "tight_layout()\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 73, - "id": "2c9dc48d", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "1507-element SparseArrays.SparseVector{Float64, Int64} with 13 stored entries:\n", - " [1329] = 4.93052\n", - " [1330] = 2.47097e-18\n", - " [1334] = 1.90726e-20\n", - " [1335] = 8.41519e-25\n", - " [1382] = 5.09286e-16\n", - " [1429] = 1.11637e-9\n", - " [1466] = 2.47701e-9\n", - " [1476] = -3.97882e-23\n", - " [1480] = 2.23586e-21\n", - " [1482] = -4.77469e-32\n", - " [1495] = 3.0577e-7\n", - " [1498] = 8.25581e-21\n", - " [1500] = 5.02641e-30" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "rops(ssys,\"O=CO\",1)" - ] - }, - { - "cell_type": "code", - "execution_count": 82, - "id": "4697b3d4", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "1.4953198336508606" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "concentrations(ssys,\"O=CO\",1e3)" - ] - }, - { - "cell_type": "code", - "execution_count": 83, - "id": "338b79c3", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.8667719072294274" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "Cbl_vals[end]" - ] - }, - { - "cell_type": "code", - "execution_count": 80, - "id": "979f34c5", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "101-element Vector{Float64}:\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 10.0\n", - " 9.999999999999999e-5\n", - " 0.0\n", - " 5.8044933978456105e-6\n", - " 1.4953198336508606\n", - " 1.326212079687479e-53\n", - " ⋮\n", - " 2.101831965253404e-6\n", - " 4.989543828025639e-27\n", - " 2.944554505137183e-28\n", - " 1.6334751634574246e-5\n", - " 3.2907339687809483e-13\n", - " 1.5851318841390273e-29\n", - " 2.0754716608442726e-40\n", - " 6.7655561558769405e-15\n", - " 2.2024084677739304e-11" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "concentrations(ssys,1e3)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "816d05fc", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.9.1", - "language": "julia", - "name": "julia-1.9" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.9.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/CO2_Reduction_Ag/CO2RR_RMS_4.jl b/CO2_Reduction_Ag/CO2RR_RMS_4.jl new file mode 100644 index 0000000..119fe40 --- /dev/null +++ b/CO2_Reduction_Ag/CO2RR_RMS_4.jl @@ -0,0 +1,277 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,jl:percent +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.17.2 +# kernelspec: +# display_name: Julia 1.9.1 +# language: julia +# name: julia-1.9 +# --- + +# %% +using ReactionMechanismSimulator +using PyPlot +using DifferentialEquations +using Sundials +using SciMLBase +using QuadGK + +# %% +outdict = readinput("Ag_C2_042925.rms") + +# %% +liqspcs = outdict["gas"]["Species"] +liqrxns = outdict["gas"]["Reactions"] +surfspcs = outdict["surface"]["Species"] +surfrxns = outdict["surface"]["Reactions"] +interfacerxns = outdict[Set(["surface", "gas"])]["Reactions"] +solv = outdict["Solvents"][1]; + +# %% +sitedensity = 2.292e-5; # Ag111 +liq = IdealDiluteSolution(liqspcs,liqrxns,solv,name="liquid",diffusionlimited=true); +surf = IdealSurface(surfspcs,surfrxns,sitedensity,name="surface"); + +# %% +# Reservoir is a 100 mL (100e-6 m^3) cell +# Proton concentration is 10^-7 mol/L (10^-4 mol/m^3) +# CO2 concentration is 0.01 mol/L (10 mol/m^3), saturation solubility ~0.03 mol/L +# Solvent concentration (water) is 55.6 mol/L (5.56e4 mol/m^3) +# AVratio in experiments is 36 m^-1 but is measured by surface area/reservoir volume +# Area of the electrode is therefore 3.6e1 m^-1 * 1e2*1e-6 m^3 = 3.6e-3 m^2 = 36 cm^2 +# Assume boundary layer thickness d_bl = 1 mm or 1e-3 m +# Volume of the boundary layer V_bl = 3.6e-3 m^2 * 1e-3 m = 3.6e-6 m^3 +# Actual AVratio is therefore 3.6e-3 m^2 / 3.6e-6 m^3 = 1e3 m^-1 (reciprocal of d_bl) +# Amount of sites is 2.292e-5 mol/m^2 * 1e3 m^-1 = 2.292e-2 mol/m^-3 + +C_proton = 1.0e-7*1.0e3; +C_co2 = 1.0e-2*1.0e3; +C_h2o = 5.56e4; +C_default = 1e-12; +V_res = 1.0e3; +AVratio = 1.0e3; +A_surf = V_res*36; +V_bl = V_res; +sites = sitedensity*A_surf; + +initialcondsliq = Dict(["proton"=>C_proton * V_res, + "CO2"=>C_co2 * V_res, + "H2O"=>C_h2o * V_res, + "V"=>V_res,"T"=>300,"Phi"=>0.0,"d"=>0.0]); + +initialcondssurf = Dict(["CO2X"=>0.4*sites, + # "CHO2X"=>0.1*sites, + # "CO2HX"=>0.1*sites, + # "OX"=>0.1*sites, + # "OCX"=>0.1*sites, + "vacantX"=>0.6*sites, + # "CH2O2X"=>0.05*sites, + # "CHOX"=>0.04*sites, + # "CH2OX"=>0.01*sites, + "A"=>A_surf,"T"=>300,"Phi"=>-1.414]); + +# %% +domainliq,y0liq,pliq = ConstantTVDomain(phase=liq, + initialconds=initialcondsliq,constantspecies=["proton","CO2","H2O"]); +domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf, + initialconds=initialcondssurf); + +# %% +inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainliq, + domaincat,interfacerxns,298.15,A_surf); + +# %% +@time react,y0,p = Reactor((domainliq,domaincat), (y0liq,y0cat), (0.0, 1.0e3), [inter], (pliq,pcat,pinter)); + + +# %% +@time sol = solve(react.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-22,reltol=1e-8); +println(sol.t[end]); +println(sol.retcode); + +# %% +ssys = SystemSimulation(sol,(domainliq,domaincat,),(inter,),p); + +# %% +# Helper function +function plotX(sim, tol, t_end, exclude) + clf() + xs = molefractions(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Mole Fraction") +end + +# %% +# Helper function +function plotC(sim, tol, t_end, exclude) + clf() + xs = concentrations(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Concentration") +end + +# %% +exclude_species = ["H2O"] +plotX(ssys.sims[1], 1e-10, 1.8e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-8, 2e3) +ylim(1e-12, 1e-2) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V") +gcf() + +# %% +exclude_species = ["H2O"] +plotC(ssys.sims[1], 1e-5, 1.0e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-8, 1e3) +ylim(1e-6, 1e2) +title("Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys.sims[2], 1e-2, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e3) +ylim(1e-6, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V") +gcf() + +# %% +getfluxdiagram(ssys,1e3;speciesratetolerance=1e-6) + +# %% +function plotROP(ssys,name,t;N=0,tol=0.01) + clf() + rop = rops(ssys, name, t) + inds = rop.nzind[reverse(sortperm(abs.(rop.nzval)))] + if N == 0 + N = length(inds) + elseif N > length(inds) + N = length(inds) + end + inds = inds[1:N] + mval = abs(rop[inds[1]]) + minval = mval*tol + k = 1 + while k < length(inds) && abs(rop[inds[k]]) >= minval + k += 1 + end + inds = inds[1:k] + net_rops = sum(rop[inds]) + println("Net ROPs for species $name is: $net_rops") + + for (i, j) in enumerate(inds) + println("Showing the reaction with $i th highest ROP for species $name:") + println(getrxnstr(ssys.reactions[j])) + println("ROP = ", rop[inds[i]]) + println(ssys.reactions[j].kinetics) + end + + xs = Array{Float64,1}(1:length(inds)) + barh(xs,reverse(rop[inds])) + yticks(xs,reverse(getrxnstr.(ssys.reactions[inds]))) + xlabel("Production/Loss Rate mol/s") + gcf() +end + +# %% +""" +Integrates the ROP in the boundary layer and computes the concentration +""" +function get_boundary_layer_concentration(sim,t,spc,Vbl,C_0) + intg,err = quadgk(x -> sum(rops(sim,spc,t)), 0, t); + return C_0 + intg ./ Vbl; +end + +# %% +# Logarithmic time scale +t_vals = 10 .^ range(-12, stop=3, length=1000); + +# Compute ROP over time +ROP_vals = [sum(rops(ssys, "O=CO", t)) for t in t_vals]; +# Compute boundary layer accumulation by integration +Cbl_vals = [get_boundary_layer_concentration(ssys, t, "O=CO", V_bl, C_default) for t in t_vals]; + +# %% +# Plots the ROP of O=CO +clf() + +plot(t_vals, ROP_vals) + +xscale("log") +xlim(1e-11,1e3) +yscale("log") +ylim(1e-8,1e2) +xlabel("Time (s)") +ylabel("Rate of Progress (mol/s)") +legend() +tight_layout() +gcf() + +# %% +# Plots the Boundary Layer Concentration of O=CO from ROP Integration WITHOUT Diffusion Flux Into Reservoir +clf() + +plot(t_vals, Cbl_vals) + +xscale("log") +xlim(1e-11,1e3) +yscale("log") +ylim(1e-13,1e1) +xlabel("Time (s)") +ylabel("Concentration (mol/m^3)") +title("Boundary Layer Accumulation of O=CO from ROP Integration") +legend() +tight_layout() +gcf() + +# %% +rops(ssys,"O=CO",1) + +# %% +concentrations(ssys,"O=CO",1e3) + +# %% +Cbl_vals[end] + +# %% +concentrations(ssys,1e3) + +# %% diff --git a/CO2_Reduction_Ag/CO2RR_RMS_AIChE.ipynb b/CO2_Reduction_Ag/CO2RR_RMS_AIChE.ipynb deleted file mode 100644 index 1b2ed55..0000000 --- a/CO2_Reduction_Ag/CO2RR_RMS_AIChE.ipynb +++ /dev/null @@ -1,1212 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 82, - "id": "8a590634", - "metadata": {}, - "outputs": [], - "source": [ - "using DifferentialEquations\n", - "using ReactionMechanismSimulator\n", - "using PyPlot" - ] - }, - { - "cell_type": "code", - "execution_count": 83, - "id": "e941d4fb", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[17:10:35] WARNING: not removing hydrogen atom without neighbors\n", - "[17:10:36] WARNING: not removing hydrogen atom without neighbors\n", - "┌ Warning: failed to generate StokesDiffusivity model for species vacantX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2O2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC([Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species H2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "[17:10:36] WARNING: not removing hydrogen atom without neighbors\n", - "[17:10:36] WARNING: not removing hydrogen atom without neighbors\n", - "┌ Warning: failed to generate StokesDiffusivity model for species vacantX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2O2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species H2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [H][H].[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n" - ] - }, - { - "data": { - "text/plain": [ - "Dict{Any, Any} with 4 entries:\n", - " \"Solvents\" => Solvent[Solvent(\"water\", RiedelViscosity{Float64}(…\n", - " Set([\"surface\", \"gas\"]) => Dict{Any, Any}(\"Reactions\"=>ElementaryReaction[vac…\n", - " \"gas\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…\n", - " \"surface\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "outdict1 = readinput(\"chem43_Ag.rms\");\n", - "outdict2 = readinput(\"chem43_Cu.rms\")\n" - ] - }, - { - "cell_type": "code", - "execution_count": 84, - "id": "fe2767e9", - "metadata": {}, - "outputs": [], - "source": [ - "liqspcs1 = outdict1[\"gas\"][\"Species\"];\n", - "liqrxns1 = outdict1[\"gas\"][\"Reactions\"];\n", - "surfspcs1 = outdict1[\"surface\"][\"Species\"];\n", - "surfrxns1 = outdict1[\"surface\"][\"Reactions\"];\n", - "interfacerxns1 = outdict1[Set([\"surface\", \"gas\"])][\"Reactions\"];\n", - "solv1 = outdict1[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 85, - "id": "2e3c1e9a", - "metadata": {}, - "outputs": [], - "source": [ - "liqspcs2 = outdict2[\"gas\"][\"Species\"];\n", - "liqrxns2 = outdict2[\"gas\"][\"Reactions\"];\n", - "surfspcs2 = outdict2[\"surface\"][\"Species\"];\n", - "surfrxns2 = outdict2[\"surface\"][\"Reactions\"];\n", - "interfacerxns2 = outdict2[Set([\"surface\", \"gas\"])][\"Reactions\"];\n", - "solv2 = outdict2[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 86, - "id": "711d8a69", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "100000.0" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sitedensity1 = 2.292e-5; # Ag111\n", - "sitedensity2 = 2.943e-5; # Cu111\n", - "AVratio = 1.0e5" - ] - }, - { - "cell_type": "code", - "execution_count": 87, - "id": "8894c84d", - "metadata": {}, - "outputs": [], - "source": [ - "initialcondsliq = Dict([\"proton\"=>10.0^-4,\"CO2\"=>10.0^-3*10^3,\n", - " \"V\"=>1.0,\"T\"=>298.15,\"Phi\"=>0.0,\"d\"=>0.0]);\n", - "initialcondssurf1 = Dict([\"CO2X\"=>0.4*sitedensity1*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity1*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity1*AVratio,\n", - " \"OX\"=>0.1*sitedensity1*AVratio,\n", - " \"OCX\"=>0.1*sitedensity1*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity1*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity1*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity1*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity1*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-1.5]);\n", - "initialcondssurf2 = Dict([\"CO2X\"=>0.4*sitedensity1*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity1*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity1*AVratio,\n", - " \"OX\"=>0.1*sitedensity1*AVratio,\n", - " \"OCX\"=>0.1*sitedensity1*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity1*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity1*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity1*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity1*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-1.0]);\n", - "initialcondssurf3 = Dict([\"CO2X\"=>0.4*sitedensity1*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity1*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity1*AVratio,\n", - " \"OX\"=>0.1*sitedensity1*AVratio,\n", - " \"OCX\"=>0.1*sitedensity1*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity1*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity1*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity1*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity1*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-2.0]);\n", - "initialcondssurf4 = Dict([\"CO2X\"=>0.4*sitedensity2*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity2*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity2*AVratio,\n", - " \"OX\"=>0.1*sitedensity2*AVratio,\n", - " \"OCX\"=>0.1*sitedensity2*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity2*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity2*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity2*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity2*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-1.5]);\n", - "initialcondssurf5 = Dict([\"CO2X\"=>0.4*sitedensity2*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity2*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity2*AVratio,\n", - " \"OX\"=>0.1*sitedensity2*AVratio,\n", - " \"OCX\"=>0.1*sitedensity2*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity2*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity2*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity2*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity2*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-1.0]);\n", - "initialcondssurf6 = Dict([\"CO2X\"=>0.4*sitedensity2*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity2*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity2*AVratio,\n", - " \"OX\"=>0.1*sitedensity2*AVratio,\n", - " \"OCX\"=>0.1*sitedensity2*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity2*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity2*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity2*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity2*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>-2.0]);" - ] - }, - { - "cell_type": "code", - "execution_count": 88, - "id": "ddb39b3d", - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "liq1 = IdealDiluteSolution(liqspcs1,liqrxns1,solv1,name=\"liquid\",diffusionlimited=true);\n", - "\n", - "liq2 = IdealDiluteSolution(liqspcs2,liqrxns2,solv2,name=\"liquid\",diffusionlimited=true);\n", - "\n", - "surf1 = IdealSurface(surfspcs1,surfrxns1,sitedensity1,name=\"surface\");\n", - "\n", - "surf2 = IdealSurface(surfspcs2,surfrxns2,sitedensity2,name=\"surface\");\n", - "\n", - "domainliq1,y0liq1,pliq1 = ConstantTVDomain(phase=liq1,\n", - " initialconds=initialcondsliq,constantspecies=[\"proton\",\"CO2\"]);\n", - "\n", - "domainliq2,y0liq2,pliq2 = ConstantTVDomain(phase=liq2,\n", - " initialconds=initialcondsliq,constantspecies=[\"proton\",\"CO2\"]);" - ] - }, - { - "cell_type": "code", - "execution_count": 89, - "id": "29ec7f86", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat1,y0cat1,pcat1 = ConstantTAPhiDomain(phase=surf1,\n", - " initialconds=initialcondssurf1);\n", - "\n", - "inter1,pinter1 = ReactiveInternalInterfaceConstantTPhi(domainliq1,\n", - " domaincat1,interfacerxns1,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 90, - "id": "02daf794", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat2,y0cat2,pcat2 = ConstantTAPhiDomain(phase=surf1,\n", - " initialconds=initialcondssurf2);\n", - "\n", - "inter2,pinter2 = ReactiveInternalInterfaceConstantTPhi(domainliq1,\n", - " domaincat2,interfacerxns1,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 91, - "id": "b6bac559", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat3,y0cat3,pcat3 = ConstantTAPhiDomain(phase=surf1,\n", - " initialconds=initialcondssurf3);\n", - " \n", - "inter3,pinter3 = ReactiveInternalInterfaceConstantTPhi(domainliq1,\n", - " domaincat3,interfacerxns1,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 92, - "id": "5ed60871", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat4,y0cat4,pcat4 = ConstantTAPhiDomain(phase=surf2,\n", - " initialconds=initialcondssurf4);\n", - " \n", - "inter4,pinter4 = ReactiveInternalInterfaceConstantTPhi(domainliq2,\n", - " domaincat4,interfacerxns2,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 93, - "id": "5b589c3f", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat5,y0cat5,pcat5 = ConstantTAPhiDomain(phase=surf2,\n", - " initialconds=initialcondssurf5);\n", - " \n", - "inter5,pinter5 = ReactiveInternalInterfaceConstantTPhi(domainliq2,\n", - " domaincat5,interfacerxns2,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 94, - "id": "8eaa5eaf", - "metadata": {}, - "outputs": [], - "source": [ - "domaincat6,y0cat6,pcat6 = ConstantTAPhiDomain(phase=surf2,\n", - " initialconds=initialcondssurf6);\n", - " \n", - "inter6,pinter6 = ReactiveInternalInterfaceConstantTPhi(domainliq2,\n", - " domaincat6,interfacerxns2,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 95, - "id": "244f0912", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.001202 seconds (3.31 k allocations: 960.234 KiB)\n", - " 0.105116 seconds (462.72 k allocations: 65.158 MiB, 18.36% gc time)\n" - ] - } - ], - "source": [ - "@time react1,y01,p1 = Reactor((domainliq1,domaincat1), (y0liq1,y0cat1), (0.0, 1.0e2), [inter1], (pliq1,pcat1,pinter1));\n", - "\n", - "@time sol1 = solve(react1.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6);\n", - "\n", - "ssys1 = SystemSimulation(sol1,(domainliq1,domaincat1,),(inter1,),p1);\n" - ] - }, - { - "cell_type": "code", - "execution_count": 96, - "id": "3b06f7a9", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.001183 seconds (3.31 k allocations: 960.234 KiB)\n", - " 0.033939 seconds (133.51 k allocations: 19.993 MiB, 23.54% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "[CVODES ERROR] CVode\n", - " At t = 1.71566e-13 and h = 2.74651e-20, the error test failed repeatedly or with |h| = hmin.\n", - "\n" - ] - } - ], - "source": [ - "@time react2,y02,p2 = Reactor((domainliq1,domaincat2), (y0liq1,y0cat2), (0.0, 1.0e2), [inter2], (pliq1,pcat2,pinter2));\n", - "\n", - "@time sol2 = solve(react2.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-12,reltol=1e-6);\n", - "\n", - "ssys2 = SystemSimulation(sol2,(domainliq1,domaincat2,),(inter2,),p2);" - ] - }, - { - "cell_type": "code", - "execution_count": 97, - "id": "ab03df14", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.001498 seconds (3.31 k allocations: 960.234 KiB)\n", - " 0.074664 seconds (341.64 k allocations: 46.424 MiB, 11.17% gc time)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "[CVODES ERROR] CVode\n", - " At t = 15.6322 and h = 5.60371e-09, the error test failed repeatedly or with |h| = hmin.\n", - "\n" - ] - } - ], - "source": [ - "@time react3,y03,p3 = Reactor((domainliq1,domaincat3), (y0liq1,y0cat3), (0.0, 1.0e2), [inter3], (pliq1,pcat3,pinter3));\n", - "\n", - "@time sol3 = solve(react3.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6);\n", - "\n", - "ssys3 = SystemSimulation(sol3,(domainliq1,domaincat3,),(inter3,),p3);" - ] - }, - { - "cell_type": "code", - "execution_count": 98, - "id": "9b238da8", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.001587 seconds (3.66 k allocations: 865.812 KiB)\n", - " 0.056727 seconds (266.76 k allocations: 31.517 MiB, 15.80% gc time)\n" - ] - } - ], - "source": [ - "@time react4,y04,p4 = Reactor((domainliq2,domaincat4), (y0liq2,y0cat4), (0.0, 1.0e2), [inter4], (pliq2,pcat4,pinter4));\n", - "\n", - "@time sol4 = solve(react4.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6);\n", - "\n", - "ssys4 = SystemSimulation(sol4,(domainliq2,domaincat4,),(inter4,),p4);" - ] - }, - { - "cell_type": "code", - "execution_count": 99, - "id": "b7c78e37", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.001386 seconds (3.66 k allocations: 865.812 KiB)\n", - " 0.047519 seconds (288.60 k allocations: 33.380 MiB)\n" - ] - } - ], - "source": [ - "@time react5,y05,p5 = Reactor((domainliq2,domaincat5), (y0liq2,y0cat5), (0.0, 1.0e2), [inter5], (pliq2,pcat5,pinter5));\n", - "\n", - "@time sol5 = solve(react5.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6);\n", - "\n", - "ssys5 = SystemSimulation(sol5,(domainliq2,domaincat5,),(inter5,),p5);" - ] - }, - { - "cell_type": "code", - "execution_count": 100, - "id": "8498a9b3", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.001202 seconds (3.66 k allocations: 865.812 KiB)\n", - " 0.053374 seconds (254.13 k allocations: 30.542 MiB, 19.28% gc time)\n" - ] - } - ], - "source": [ - "@time react6,y06,p6 = Reactor((domainliq2,domaincat6), (y0liq2,y0cat6), (0.0, 1.0e2), [inter6], (pliq2,pcat6,pinter6));\n", - "\n", - "@time sol6 = solve(react6.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6);\n", - "\n", - "ssys6 = SystemSimulation(sol6,(domainliq2,domaincat6,),(inter6,),p6);" - ] - }, - { - "cell_type": "code", - "execution_count": 101, - "id": "39632165", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotX1 (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotX1(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = molefractions(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Mole Fraction\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 130, - "id": "63bd3256", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotX (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "function plotX(bsol, tol, t_end, exclude)\n", - " # Species order and corresponding colors for the main species\n", - " species_order = [\"CO2\", \"proton\", \"H2\", \"O=CO\", \"C=O\", \"O=CC=O\", \"O=CCO\"]\n", - " color_map = Dict(\"CO2\" => \"blue\", \"proton\" => \"orange\", \"H2\" => \"purple\",\n", - " \"O=CO\" => \"red\", \"C=O\" => \"green\", \"O=CC=O\" => \"magenta\",\n", - " \"O=CCO\" => \"brown\")\n", - " # Replacement map for species labels\n", - " replacement_map = Dict(\"C=O\" => \"CH2=O\", \"O=CO\" => \"HCOOH\",\n", - " \"O=CC=O\" => \"O=CH-CH=O\", \"O=CCO\" => \"O=CH-CH2OH\")\n", - "\n", - " clf()\n", - " \n", - " xs = molefractions(bsol)\n", - " maxes = maximum(xs, dims=2)\n", - " spnames = []\n", - " plotted_species = Set{String}()\n", - "\n", - " # Filter data to the specified time range\n", - " if t_end !== nothing\n", - " t_mask = bsol.sol.t .<= t_end\n", - " ts = bsol.sol.t[t_mask]\n", - " xs = xs[:, t_mask]\n", - " else\n", - " ts = bsol.sol.t\n", - " end\n", - "\n", - " # Plot species in the specified order with custom colors and labels\n", - " for sp in species_order\n", - " # Find the species index in the phase\n", - " species_index = findfirst(x -> x.name == sp, bsol.domain.phase.species)\n", - " if species_index === nothing || maxes[species_index] <= tol || sp in exclude\n", - " continue\n", - " end\n", - "\n", - " # Apply replacement for display name if available\n", - " display_name = get(replacement_map, sp, sp)\n", - "\n", - " # Plot the species with the specified color\n", - " plot(ts, xs[species_index, :], label=display_name, color=color_map[sp])\n", - " push!(spnames, display_name)\n", - " push!(plotted_species, sp)\n", - " end\n", - "\n", - " # Plot any remaining species that are above the tolerance and not already plotted\n", - " for i = 1:length(bsol.domain.phase.species)\n", - " sp = bsol.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(sp in exclude) && !(sp in plotted_species)\n", - " plot(ts, xs[i, :], label=sp)\n", - " push!(spnames, sp)\n", - " end\n", - " end\n", - "\n", - " # Configure the legend and labels\n", - " xlabel(\"Time in sec\", fontsize=16)\n", - " ylabel(\"Mole Fraction\", fontsize=16)\n", - " xticks(fontsize=14)\n", - " yticks(fontsize=14)\n", - " legend(spnames, loc=\"upper left\", bbox_to_anchor=(0, 0.93), fontsize=12, ncol=2)\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 132, - "id": "6ef159b3", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys1.sims[1], 1e-12, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1)\n", - "ylim(1e-12, 5)\n", - "title(\"Ag111@-1.5 V\", fontsize=16, fontweight=\"bold\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 133, - "id": "bce46a3f", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys2.sims[1], 1e-10, 10, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 10)\n", - "ylim(1e-12, 5)\n", - "title(\"Ag111@-1.0 V\", fontsize=16, fontweight=\"bold\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 134, - "id": "78344a8c", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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hhBB5TE41i5LODkIIIYQQeZQkckIIIYQQeZQkckIIIYQQeZQkckIIIYQQeZQkckIIIYQQeZQkckIIIYQQeZQkckIIIYQQeZQkckIIIYQQeZQkckIIIYQQeZQkctlk1qxZlC5dGltbW9q0acO1a9dMHZIQQggh8hlJ5LLBihUr+PLLL/n+++85ceIErq6udOzYkZiYGFOHJoQQQoh8RBK5bDBr1izGjRvHoEGDqFGjBosWLeLhw4ds3LjR1KEJIYQQIh8psIncsmXLGDNmDA0aNMDa2hqNRsOiRYtSPefEiRN07twZV1dX7O3tadSoEStWrDA6JjY2ljNnztCmTRvDNkdHRxo3bszRo0ez46UIIYQQooCyMHUApjJx4kRu376Nm5sb7u7u3L59O9Xj9+7dS4cOHbCysmLAgAE4Ozvj4+PD4MGD8ff358svvwQgMDAQnU5H0aJFjc4vWrQojx8/zrbXI4QQQoiCp8CWyHl7e+Pv709AQABjx45N9VitVsuoUaPQaDTs37+f+fPnM3PmTM6dO4eHhwdeXl5cv349hyIXQgghhFAV2ETu9ddfp2zZsmk6dvfu3dy8eZNBgwZRt25dw3ZHR0cmTZqEVqtl4cKFALi5uWFubs6TJ0+MrvHkyROKFSuWdS9ACCGEEAVega1aTY+9e/cC0L59+yT74rft27cPACsrK+rWrcuePXvo0qULAOHh4Rw7doxx48al+94//gg2NupzjebF9pSep/W4/HZOVl/b3FxdzMxePE+4ZGS7hQVYWYG19YtHC/kfKIQQIhPkayQN4qtNK1eunGSfq6srbm5uRlWrH374IaNHj6ZBgwbUqFGDr7/+Gnd3d7p3757iPWJiYoyGJwkNDQVgypSsehUiNzIzS5rcJffcxgbs7MDeXl0SPk+4JLfdweHFPrMCWwYvhBD5kyRyaRASEgKAs7NzsvudnJy4d++eYX3w4ME8efKE8ePHExgYSJMmTdi2bRs28UVryZg+fTpff/11ku1vvKF+kSvKi20pPU9tX34+JzuurdOpi17/4nlyS3r2a7UQG2scg14P0dHqkhPs7F4kdlnxGF+qaGEBlpbqoySLQgiRcySRyyYfffQRH330UZqPnzBhAh9//LFhPTQ0lNKlS/Pbb+DklB0RClNQFDWhi4lRl9jY5B8Tb4uOhogIiIxUHxMvKW2PX+JFRqpLdtJojBO7xMldeqvA01pNnh3bcuo+eSGegnDv+KYRFhbJN5FIbntatllZvVjiS9nTux5fKm9llfLfSBRMksilQXxJXHzJXGKhoaEpltallbW1NdbW1pm6hsj9NBo1wbG0VEu0coJeD1FRakIXHp6xx5T26XRJ76coEBenLkKIrGVmpiZ08c0o4p8nXhI2tXByUhdn5xePCZ87OEhJel4miVwaxLeNu379OvXr1zfaFxwcTGBgIE2bNjVFaEK8lJnZi/ZyiYY3zDS9Xk3YtNoXS3Lr8VXX6a0CT2s1eXZsy6n75IV4Csq9EzeFSNxUIiPb4v8fxJeuxy/pXY//0aTXqz+iwsOT/1tlhEYDjo5qYufiAoULg5vbi8eUnjs5SelgbiCJXBq0bNmS6dOn4+vry4ABA4z2+fr6Go4RoqAxM3vRKUMIkX3i4l40jUhpiW9mkXAJD4fQUAgJSfoYEvLih1ZoqLokaO79UtbW4O5uvJQokXS9cGEp8ctOksilQdu2balQoQIrVqzg/fffp06dOgCEhYUxdepULCwsGDZsmEljFEIIkX9ZWr6oEs1K0dHGid2zZxAUBIGBLx4TPo9/jIhQSw39/dUlNdbWULasupQr9+Ix/rm7u9qWUGRMgU3kvL29OXjwIAAXLlwwbIsfM87T0xNPT08ALCws8Pb2pkOHDrRo0YKBAwfi5OSEj48Pfn5+TJs2jSpVqpjiZQghhBAZZmOjLultdhEVBY8fw8OH6vLgwYvnCdcDAtSE79o1dUmOpSVUqABVqkDVqupj/FK8uFTfvoxGUVJqlZC/DRs2jMWLF6e438vLi8mTJxttO378OF5eXhw5coTY2Fg8PDz48MMPGTx4cJbHF9+BIiQkBCfptiqEECIPio2F+/fh9m215C7x4927ahvClDg6vkjqatZUl1q1oHTp3Jvg5fT3d4FN5HI7SeSEEELkdzqdmuhdv66W2F29+qL0zs9P7dyRHGdnqFFDTerik7tatdTEL1PCw+HpU7WOOTjY+PHZM7VOOSpKrZOOijJ+HhsLWi2hMTE4nzsniVxBJ4mcEEKIgiwmBm7dUpO6K1fgwgV1uXIl+VI8jQZeeQUaNoQGDdSlTh2wtUXNCB8+VC/o75+0Ljh+STjwZgaFAs4giVxBJ4mcEEIIkVRsrFpyd/78i+Tu3Dm4f1+hFPeozmWqc5lK3KAit6hq7UcprT+WupiXXxzURnuururi4vLi0cVFHcfJ1vbFYmPz4rmVFVhYqCVyffvm2Pd3ge3sIIQQQoi8x8oKahZ5RE3X01D4EhS9DCUvo392GbOIZAbYe56/aTHnDmW4Z1EebfGS2Fd0p0htd0o1cMeq7PPxUooXV0dIzkwDvOdzpecUSeTyibi4OHTJDbMvhBB5iKWlJeYyFoWIpyhqNeipU3D6tPp46pRaDZqIGajzo1WpAtWro1SqTLBrBS5FV+DIw/Jsv1SaIycs1Lmt7z1f9qmJYYMG0Lw5tGqlPma6rV0OkqrVXCqtVauhoaEEBgYSE5PGImMhhMjFNBoNzs7OFC9eHE1u7ZYosk9MjJqwHTqkLkeOqOOcJBbfIK52bahe/cVSqZJaNZqC2Fg4cwYOHlQvf/CgOkRKQubmaju71q2hTRto2lSd7iytpNeqANL2RggNDeX+/fs4ODjg7OyMpaWlfPAJIfIsRVGIiIggICAAd3d3XFxcTB2SyG5Pn75I2g4dghMn1GQuITMzNUmrXx/q1VMfa9fOkgmrFQVu3FBvvX8/7NmTdIBjS0t49dUXid2rr6Y+m40kcgJI2xvh1q1bWFpaUqpUKUnghBD5xv3794mIiKBy5cry2ZbfRESoxWC7dqnLmTNJJ791c4NmzdSisGbNoG7d9BWJZZK/v5rQxS+Jpy2zsVHDattWXerXN56ZQhI5Abz8jRAXF8eNGzcoWbKk9GoVQuQrYWFh3Lt3j8qVK2NhIU258zSdDo4dg5071cTtyBF1gteEqlZVG6Y1a6YulSvnmtF+FQVu3jRO7B49Mj7G2VltWxef2JUsGYqLS84lcvI/JI+K79hgmUpbACGEyIvikzetViuJXF4UGAj//gtbt6qPT58a7y9T5kXW06aN2ls0l9Jo1GZ3lSrB6NFqYvfff7B7t5qb7tmjzlG7caO6ABQrlrMxyv+QPE6qHYQQ+Y18ruUxiqIO5LZ1q7ocO2Y8JYOrK7z++ovkrWLFXFPill4aDVSrpi7vvKMWOJ4+rRY27typ1hon1zcjO0kiJ4QQQoj00enUalIfH3W5fdt4f61a0KULdO6s9g7IpyWr8T1cGzaEL75QZ+vasQO6d8+5GMxy7lZCpN/58+cZPnw45cuXx8bGBgcHB+rVq8eMGTN4mqC4Pi4ujjlz5tCkSROcnZ2xtbWlWrVqfPHFFwQFBRldU6fT8dNPP9GxY0dKlSqFnZ2d4dhnz57l8CsU6bVo0SI0Gg0nT55Mdn/Xrl0pV66c0baYmBh+++03mjdvjqurK1ZWVpQsWZJ+/fqxb9++JNe4cuUKw4YNo0yZMlhZWeHm5kbnzp3Ztm1binGl55y9e/ei0Wj4+++/k73Wu+++K6VSIveJiwNfXxg7FkqWhBYtYNYsNYmzs1Ozlz//hDt31BK6b79V277l0yQuOTY20LJlzt5TEjmRa82fP5/69etz4sQJPv30U7Zv38769evp27cvc+fOZeTIkQBERkbSrl073nvvPerWrcvKlSv5559/eOONN5g3bx5169bl6tWrhutGRUUxefJkypYty88//8w///zD6NGjmTdvHs2aNSMqKspUL1lkg8DAQJo1a8bHH39MjRo1WLRoEbt27eLHH3/E3Nyctm3bcu7cOcPxPj4+1K1bl+PHjzNp0iR27tzJnDlzAOjcuTOfffZZkntk5Bwh8oS4ONi+HYYOhaJFoUMHNVl7/Fht5f/GG7B+vToY28aN8NZbULq0qaMuWBSRK4WEhCiAEhISkuz+qKgo5fLly0pUVFQOR5YzDh8+rJibmysdO3ZUoqOjk+yPiYlRNm7cqCiKorz11lsKoKxatSrJcVevXlWcnZ0VDw8PRavVKoqiKFqtVgkMDExy7Nq1axVAWbp0aRa/GpGVFi5cqADKiRMnkt3fpUsXpWzZsob1Tp06KRYWFsquXbuSPf748ePK7du3FUVRlBs3bih2dnZKgwYNlPDw8CTHjh07VgGUlStXGrZl5Jw9e/YogLJ27dpkY3rnnXeUgvzxnN8/33I9vV5RDh1SlHfeUZQiRRRFbQWnLkWLKspbbynK9u2KEhNj6khzpZd9f2c1KZETudK3336LRqNh3rx5WCcz8qKVlRXdu3fn0aNHLFiwgA4dOtC/f/8kx1WpUoXPP/+cS5cusWHDBgDMzc0pXLhwkmMbNWoEwN27d7P2xQiTOXXqFNu2bWPkyJG0adMm2WMaNmxImTJlAJg1axaRkZHMnj0be3v7JMf++OOPuLi48M033xi2ZeQcIXKlixfhyy+hQgV1GJDff1dL2ooUUVv279unTpf1559qyZyVlakjFkhnh3xHUSAy0tRRvGBnl/7OSTqdjt27d1O/fn1Kv6SIfs+ePWi1Wjw9PVM8xtPTky+//JIdO3bQu3fvFI/bvXs3AB4eHukLOC/IbW8MyNibIwGdTodWq02yXUkwNKavry9Aqu+PhHbs2EGxYsV49dVXk91vZ2dH+/btWbNmDY8ePaJ48eIZOieeXq9/6WsQIlsFBcHy5bBggdquLZ6DA/TsCYMGqT1NZairXEsSuXwmMjJLZi3JMuHhkEwhRaoCAwOJjIykfPnyLz32zp07AKkeG78v/tjk3L9/ny+++IIGDRrQtWvX9AWcF+S2NwZk7M2RQEqJE0DZsmWBtL0/Erpz5w516tRJ9ZiE76fixYtn6Jx4yZUiC5HtdDq1a+WCBWq7tthYdbulpdrLdNAg6No1R2dTEBkniZwoMFLqBfj06VM6d+6MoiisXr0aMzNpcZAXLFmyhGrVqiXZ/tFHH2Vr9Xh8aVl6epWmdM7333+fbJXvDz/8wJo1azIRpRDJuHkTFi6ERYvg/v0X2+vVgxEjYOBAKFTIZOGJjJFELp+xs1MLOnKLjPygc3Nzw87ODj8/v5ceG9+2KbVj4/clV00bHBxMu3btuH//Prt376ZChQrpDzgvyG1vDMj0r/1q1arRoEGDJNudnZ0NiVzC90fVqlVfes0yZcq89H3n/3xG7fj3U0bOiVehQoVkX0ORIkVeGqsQaaLVwpYtanu3nTtfbC9UCIYMgeHD4SUlyiJ3k6KHfEajUWurcsuSkSZQ8UNCnDp1inuJZytOpHXr1lhYWBg6MiQnfl+7du2MtgcHB/P666/j5+fHjh07qFWrVvqDzSty2xsjo2+OdOrQoQNAqu+PhNq1a8fjx485evRosvsjIyPZsWMHNWrUMFSRZuQcIbLd48fwzTdqx4WePdUkTqOBjh1hzRq108Ivv0gSlw9IIidypQkTJqAoCqNHjyY2vv1GAnFxcWzevJnixYszYsQI/v33X1avXp3kuGvXrvH999/j4eFh1OA9Pom7desWvr6+1K1bNztfjjCRevXq0alTJ/766y9DZ5bETp48aWhL99FHH2Fra8t7771HREREkmPHjx9PcHAwEydONGzLyDlCZAtFUeeIGjRIHctt4kS4exfc3NRpB27dgm3boG9fSGY0AJE3SdWqyJWaNGnCnDlzGDduHPXr1+ftt9/Gw8ODuLg4zpw5w7x586hRowbdunXjp59+4urVqwwZMoT9+/fTrVs3rK2tOXr0KDNnzsTR0ZF169Zhbm4OqAMCd+jQgTNnzvDzzz+j1WqNSlOKFClCxYoVTfXSRRZbsmQJHTt2pFOnTowYMYJOnTrh6urKw4cP2bx5MytXruTUqVOUKVOGihUrsnTpUgYPHkzDhg35+OOPqVq1Ko8fP2bBggVs27aN8ePHG3VSyMg5QmSpuDhYvRp+/BHOnn2x/dVX1WFD+vRRpxwQ+VOOjFYn0q2gDwgc7+zZs8rQoUOVMmXKKFZWVoq9vb1St25d5X//+5/y5MkTw3GxsbHK77//rjRu3FhxcHBQrK2tlapVqyqfffZZksF//fz8FCDFZejQoTn8KkV6pHdAYEVR/7/8+uuvSpMmTRQnJyfFwsJCKVGihNKrVy9l69atSa5x6dIlZejQoUqpUqUUS0tLpVChQkrHjh2TPTYj58iAwKkrKJ9vmfbsmaLMmKEopUq9GLDX1lZRRo5UlFOnTB1dgZXTAwJrFEUGLMqNQkNDcXZ2JiQkBCcnpyT7o6Oj8fPzM8xBKoQQ+YV8vr3E7dtq+7b58190YipWDN57T50HNZkBz0XOeeT/CPfy7il+f2c1qVoVQggh8oKrV9WJ6JcvV8eCA6heHT75BAYPlnZvJqLX6Xlw4gE3tt/gxvYb3Dx2M0fvL4mcEEIIkZtduKD2QF2zRq1ABWjTBj79VJ0qKwd6gAtjcVFx3Np5i//W/8e1zdeIDDTdzDmSyAkhhBC50alTMG0aJBw+p0cP+OoraNjQZGEVVDGhMVzddJX/NvzHje03iIuIM+yzdramYruKVOxYkaJNi/Jd9e9yLC5J5IQQQojc5OJFdeiQjRvVdY1G7Xn61VdQu7ZpYytgtDFabmy/wYXlF7i2+Rra6BdzIzuVduIVz1d4xfMVyrQog7mlOjJCaGhojsYoiZwQQgiRG/j5gZcXLFumVqGamaljwn35JSQzHZ3IHope4fb+25xffp4rf18h+lm0YV/hqoWp3qc6r/R8Bfd67umaqi+7SCInhBBCmNKjR2oV6rx56phwoJbATZ0Kr7xi2tgKkLAHYZxddJYzf50h+FawYbtjCUdqDKxBzcE1KV6neK5I3hKSRE4IIYQwhYgImDEDZs6EyOeN5du1U3umJjMHr8h6eq2eG9tvcHr+aa5tvYaiUzuTWDtZU71fdWoOqknZ18piZp57J8KSRE4IIYTISXo9rFihTpt1/766rXFjmD4dWrc2bWwFRNjDME7OPcmZv84Qdj/MsL1M8zLUG12P6n2qY2lnacII004SOSGEECKnHD0KH34Ix46p6+XKwQ8/QO/eMoxIDrh//D7HfjnGpTWX0Gv1ANgWtqX20NrUG1WPItWKmDjC9JNETgghhMhuT56o474tWaKuOziovVA//FDmQc1mujgdV9Zd4dgvx7h39J5he5nmZWj4bkNe8XwFC+u8mw7l3ciFEEKI3E6vh7/+gs8/h+BgtdRt+HC1c4O7u6mjy9eiQ6I5Ofckx2cfN1SfmluZU2NADRq934gS9UuYOMKskXtb7wmRAx48eMDkyZM5e/asqUMR6XT+/HmGDx9umI/TwcGBevXqMWPGDJ4+fQpAq1atqFGjRrLnBwYGotFomDx5smHbqVOneOedd6hZsyaOjo4UK1aM119/nd27d2dp7HFxccyZM4cmTZrg7OyMra0t1apV44svviAoKChL7yVM6OJFeO01eOstNYmrU0etWv3rL0nislH443B2fbmLn8v8zK4vdhF2Pwz7Yva0nNySD29/iOdiz3yTxIGUyIkC7sGDB3z99deUK1eOOnXqmDockUbz589n3LhxVK1alU8//ZTq1asTFxfHyZMnmTt3LkeOHGH9+vXpvu7KlSs5fvw4I0aMoHbt2kRERDB37lzatm3L4sWLefPNNzMde2RkJJ07d+bgwYO89dZbTJo0CVtbW44cOcLMmTNZsWIFO3bsoGrVqpm+lzCR2Fh16JDvvgOtFuzt1fX33gML+drNLsF+wRyeeZizC84aBu51q+ZGs8+bUWNAjTxdfZqa/PmqRIEWFRWFra2tqcMQ2eTIkSO8/fbbtGvXjg0bNmCdYKLwdu3a8cknn7B9+/YMXfuzzz5j5syZRts6d+5MvXr1mDJlSpYkch999BH79u1j1apV9O/f37C9devW9OnTh0aNGtG7d2/OnTuHubl5pu8ncti5c/Dmm3D+vLru6Qm//gqlS5s0rPzsyaUnHJx+kIurLhqGDynZuCTNJzSnareqaMzydycSqVoVudLkyZPRaDScOXOGXr164eTkhLOzM0OGDCEgIMBwXLly5ejatSs+Pj7UrVsXGxsbvv76awAuXrxIjx49cHV1xcbGhjp16rB48WLDuXv37qXh8/kKhw8fjkajSVLVtmnTJpo0aYKdnR2Ojo60a9eOI0eOJBvrpUuXGDhwIM7OzhQrVowRI0YQEhKSjX+lgunbb79Fo9Ewb948oyQunpWVFd27d8/QtYsWLZpkm7m5OfXr1+fu3bsZumZCjx49YsGCBXTo0MEoiYtXpUoVPv/8cy5dusSGhPNritxPq1XbvTVsqCZxbm6wdi2sXy9JXDYJuBLA3wP+Zk7NOVxYfgFFp1CxfUWG7hnKyCMjeaXHK/k+iQMpkct/FAV0kaaO4gVzu0x1qe/Zsyf9+vVj7NixXLp0iUmTJnH58mWOHTuGpaU6xs/p06e5cuUKEydOpHz58tjb23P16lWaNm1K0aJF+fXXXylcuDDLli1j2LBhPH78mM8++4x69eqxcOFChg8fzsSJE+nSpQsApUqVAmDFihUMHjyY9u3bs3LlSmJiYpgxYwatWrVi165dNG/e3CjW3r17079/f0aOHMmFCxeYMGECAAsWLMjw688qiqIQGZeL3heAnaVdukdI1+l07N69m/r161M6HV+OWq02yTadTpfmcw8cOICHh4fRdr1ej16vf+n5Go3GULK2Z88etFotnp6eKR7v6enJl19+yY4dO+jdu3eaYhQmdusWDBwIx4+r6z17wty5kMwPA5F5gVcD2T9lPxdWXgC1AI5qvavR4ssWuNcreG0PJZHLJtOnT2fdunVcvXoVOzs7WrZsyYwZMyhXrlz23lgXCWscsvce6dEvHCzsM3x6r169mDFjBgDt27enWLFiDB48mDVr1jB48GAAnjx5wuXLl6lSpYrhvIEDBxIbG8uePXsMX/idO3fm2bNnfP3114wZMwZnZ2dDQ/iKFSvy6quvGs7X6/V8+umn1KxZk23btmFmZma4RsWKFfn88885dOiQUawjR47k008/BeD111/nxo0bLFiwgL/++svkU7pExkXiMD0XvS+A8Anh2Ful770RGBhIZGQk5cuXT/M5ly5dMiT9GTF58mRu3LiRpIRsypQphtLf1JQtWxZ/f38A7ty5A5Bq/PH74o8VudyaNTB6NISGgosL/PabOj+qjAmX5YKuB7F/6n619E2vZnCv9HyFVpNbUaxWMRNHZzqSyGWTffv28d5779GwYUNiYmL4/PPP6dSpExcuXMBCGrumWXyyFq9fv34MHTqUPXv2GPbVqlXLKIkD2L17N23btk1SajNs2DC2bdvGkSNH6NixY4r3vXr1Kg8ePODDDz80JHEADg4O9O7dmz///JPIyEjs7OwM+xJX59WqVYvo6GiePHlCsWIF90PG1CpWrMiqVauSbA8JCeH1119P9Vxvb2+++eYbPvnkE3r06GG076233qJr164vvX9y1b9pYerkX7xEVBR89BH8+ae63qyZOltDmTKmjSsfeub/jH1f7+Pc0nOGNnBVu1el5eSWuNcteCVwiUlGkU0SN7b+66+/KFOmDJcvX6ZWrVrZd2NzO7UULLcwt3v5MakoXry40bqFhQWFCxc2GqLBPZlu/EFBQcluL1GihGF/auL3p3QNvV5PcHCwUSJXuHBho+Piv8CjoqJSvVdOsLO0I3xCLnpfoMaUXm5ubtjZ2eHn55fmc2xsbGiQzLyVgYGBqZ63cOFCxowZw1tvvcUPP/yQZH/x4sWTbVOXWMKErMzzL/nU4o/fl56qY5HDbt1Sq0/Pn1dL3iZMgK+/lh6pWSwyMJL93+zn5B8n0cWqTSEqd6lMq8mtKNEg/wwfkln56l23bNkyDhw4wKlTp7hw4QKxsbEsXLiQYcOGpXjOiRMn8PLy4siRI8TGxuLh4cGHH37IoEGDsjS2+EbvhQoVytLrJqHRZKoqM7d59OgRJUuWNKxrtVqCgoKMkqbkSi4KFy7Mw4cPk2x/8OABoCYEqYm/fkrXMDMzw9XVNW0vIhfQaDTprsbMjczNzWnbti3btm3j3r17hvaMWW3hwoWMGjWKoUOHMnfu3GTfYxmpWm3dujUWFhZs2LCBsWPHJnt8fBVuu3btMhy/yEa7dkG/fvD0qdoGbulSaN/e1FHlK7ERsRz9+SiHZxwmJjQGgPJty9PmmzaUapw9/+fzsnyVyE2cOJHbt2/j5uaGu7s7t2/fTvX4vXv30qFDB6ysrBgwYADOzs74+PgwePBg/P39+fLLL7MkLr1ezyeffELnzp2z7Ysnv1q+fDn169c3rK9ZswatVkurVq1SPa9t27asX7+eBw8eGErhAJYsWYKdnZ2hPVxKpWZVq1alZMmSrFixgvHjxxu+yCMiIli3bp2hJ6vIeRMmTOCff/5h9OjRbNy4ESsrK6P9cXFxbN++nW7dumXo+osWLWLUqFEMGTIEb2/vFKs4M1K1Wrx4cUaMGMG8efNYvXp1kp6r165d4/vvv8fDwyPVDhHCBBRFHUbkk09Ap4NGjcDHBxL80BSZo9fqObPgDHsn7yX8oVqDULxucV7//nUqtqto4uhyr3yVyHl7e1O5cmXKli3Ld999Z+g1mBytVsuoUaPQaDTs37+funXrAuDl5UWTJk3w8vKib9++VK5cGVCTxG+++SbV+yuKkuy2MWPG4Ofnl6RxvHg5Hx8fLCwsaNeunaHXau3atenXr1+q53l5ebFlyxZat27N//73PwoVKsTy5cvZunUrM2bMwNnZGVDbT9na2rJ8+XKqVauGg4MDJUqUoESJEsyYMYPBgwfTtWtXxowZQ0xMDD/88APPnj3ju+++y4mXL5LRpEkT5syZw7hx46hfvz5vv/02Hh4exMXFcebMGebNm0eNGjUylMitXbuWkSNHUqdOHcaMGcPx+F6Iz9WtW9eQmMW/T9Lrp59+4urVqwwZMoT9+/fTrVs3rK2tOXr0KDNnzsTR0ZF169bJGHK5iU6nDuY7Z466/uabats4mSM1SyiKwn8b/mPXhF0EXVWbtbiUc6HNN22oMaBGgRhCJFOUfGr69OkKoCxcuDDZ/f/++68CKMOHD0+yb9WqVQqgTJgwwbAtODhY8fPzS3VJTK/XK2PHjlXKlSun3LlzJ13xh4SEKIASEhKS7P6oqCjl8uXLSlRUVLqum1d4eXkpgHLq1CmlW7duioODg+Lo6KgMHDhQefz4seG4smXLKl26dEn2GhcuXFC6deumODs7K1ZWVkrt2rWTfT+sXLlSeeWVVxRLS0sFULy8vAz7NmzYoDRu3FixsbFR7O3tlbZt2yqHDh1KNtaAgACj7QsXLlSAZN8bIvPOnj2rDB06VClTpoxiZWWl2NvbK3Xr1lX+97//KU+ePFEURVFatmypeHh4JHt+QEBAkn/voUOHKqgDGiS7ZNW/ZWxsrPL7778rjRs3VhwcHBRra2ulatWqymeffaYEBgZmyT3yslz1+RYZqSienooCiqLRKMqPPyqKXm/qqPKNe8fvKX81+0uZzGRlMpOVGW4zlKO/HFXiouNMHVqGvez7O6sV2ERuwoQJCqCsXLkyyb6nT58qgNK0adMM31+v1ytvv/22Urp0aeXWrVvpPl8SueSTIyFE/pdrPt+CghSlaVM1ibO2VpS1a00bTz4Sej9UWf/mekMCN812mrJr4i4lOiTa1KFlWk4ncvmqajU9rl+/DmCoOk3I1dUVNzc3wzEZMW7cOFatWsXmzZuxtbXl0aNHgNrZIXGbHoCYmBhiYmIM66GhoRm+txBCiEx68gTatlUnvndxgY0b4bXXTB1VnhcXFceRH49wcPpB4iLjAKj1Ri3aftsWp1JOJo4ubyqwiVx8L9L4tlKJOTk5ce/evQxff+7cuQC0aNHCaPuePXuSbag/ffr0NPWAE0IIkc0eP4Y2beDyZXB3hx07INHMHiJ9FEXh0upL7Px8JyF31O/fUk1K0fHnjpRsJB1GMqPAJnLZTUmm40NqJkyYwMcff2xYDw0NLdDjSE2ePNlozlMhhMgRDx+qSdx//6k9UvfsgWRqbkTa3T9xn38//Je7h9X5ip1KO9FuRjs8+nvIwNdZoMAmcvElcSlNah4aGppiaV12sLa2zvAI8EIIIbLAkyfQqhVcu6ZOdL9nD1SUYS8yKvxxODs/38m5xecAsLSzpPmE5jT5uAmWdhmfNk8YK7CJXHzbuOvXrxuNUwYQHBxMYGAgTZs2NUVoQgghclpUFHTvriZxZcqoSVyFCqaOKk/Sa/WcmHOCPZP2EBOitv2u/WZt2nzbBqeS0g4uq5m9/JD8qWXLlgD4+vom2Re/Lf4YIYQQ+ZheD2+8AceOQaFCaps4SeIy5M7BO8yrP4/t728nJiQG9/rujDw6Es/FnpLEZZMCm8i1bduWChUqsGLFCs6ePWvYHhYWxtSpU7GwsEh1ai8hhBD5xOefw7p1YGUFGzZAlSqmjijPCX8czoahG1jYYiGPzz/GxtWGLnO7MOrYKJlWK5vlq6pVb29vDh48CMCFCxcM2/bu3QuAp6enYdobCwsLvL296dChAy1atGDgwIE4OTnh4+ODn58f06ZNo4r8ZxZCiPxtzhyYOVN9vnAhJBppQKROr9Vz4o/n1aihMaCBeqPq0fbbtti5yTSGOSFfJXIHDx5k8eLFRtsOHTpkmBqrXLlyRvMXtm7dmoMHD+Ll5cWaNWuIjY3Fw8ODqVOnMnjw4JwMXQghRE775x949131+bRpMGiQaePJY+4cvMM/7/zD4/OPASjRoASdf+8sw4nkMI2S3nEyRI6I7zUbEhKCk1PSdgXR0dH4+flRvnx5bGS+PyFEPpIjn29nzqilbxERMGIEeHuDDIWRJpFBkez4dAdnF54FwLaQLW2+bUO9UfUwMy+wLbYMXvb9ndXkLy5ypUWLFqHRaDh58mSy+7t27Uq5cuUA9T/NN998Q6tWrShevDgODg7UrFmT77//nujo6ByMWuSko0eP0rdvX9zd3bGysqJ48eL06dOHI0eOZOl9Dhw4QL9+/ShZsiRWVlY4OzvTtGlT5syZQ0REhOG4cuXK0bVr12SvcfLkSTQaDYsWLUrzfW/dusW7775LlSpVsLW1xc7ODg8PDyZOnMj9+/cNxw0bNgwHB4cUr+Pg4GDU3vfatWuMHz+e+vXr4+LiQqFChWjWrBl///13itfYvn07Xbp0oUiRIlhbW1O6dGmGDh3K5cuXkxw7efJkNBoNgYGByV6rRo0ayQ6KnqPu3YOuXdUkrm1bmDtXkrg0UBSFc0vO8fsrvxuSuHqj6/Hu1XdpMKaBJHEmIn91kefduXOHn3/+mXr16jFv3jw2bdpEnz59mDx5Ml27dk334Mwi95s9ezbNmjXj3r17zJgxg507dzJz5kzu379P8+bN+e2337LkPl5eXrz22mvcv3+fqVOnsmPHDlatWkXbtm2ZPHkyEydOzJL7JLZlyxZq1arFli1beOutt9iyZYvh+ebNm1NMGNPC19eXrVu30rt3b9auXcvy5cupXLkyffv2ZcqUKUmO/+yzz+jUqRN6vZ4//viDHTt24OXlxYkTJ6hXrx4+Pj6Zeak5LzQUunSBBw/U2Rr+/hssZUyzlwm6FsSStkvYMHQDkYGRFK1ZlBGHR9BtXjdpC2dqOTKjq0i3l026m2smlc4mCxcuVADlxIkTye7v0qWLUrZsWUVRFCU8PFwJDw9PcswPP/ygAMqBAweyM1SRww4ePKiYmZkpXbt2VeLi4oz2xcXFKV27dlXMzMyUgwcPZuo+a9asUQBl5MiRil6vT7I/NDRU+ffffw3rZcuWVbp06ZLstU6cOKEAysKFC19631u3bin29vZK3bp1lWfPniXZr9frlXXr1hnWhw4dqtjb26d4PXt7e2Xo0KGG9YCAgGRfT5cuXRQ7OzslOvrFpOUrVqxQAOXtt99Ocnx4eLhSv359xc7OTrl586Zhu5eXlwIoAQEBycbj4eGhtGzZMsV4FSUbP99iYxWlQwdFAUUpXlxR/P2z9vr5UFx0nLL3673KVKuphsntD3x3QNHGak0dWq71su/vrCYlciLPs7e3x97ePsn2Ro0aAXD37t2cDklko+nTp6PRaJgzZw4WFsb9tSwsLPjjjz/QaDR89913mbrPlClTcHV15ddff012GiFHR0fat2+fqXsk56effiIiIoI//vgj2dllNBoNvXr1yvD13dzckn09jRo1IjIykqdPnxq2ffPNN7i6ujIzvldnAvb29syePZvIyEhmzZqV4XhyjKKoHRv+/Rfs7GDzZihb1tRR5Wr++/yZW3sue732oovVUaljJcZdHEfzz5tjbmlu6vDEc/mq16pQ2zDERcaZOgwDSzvLTM2lp9Pp0Gq1SbYraagu3b17NwAeMtk1iqKgi4oydRhGzG1t0/3e0Ol07NmzhwYNGlCqVPJjU5UuXZr69euze/dudDodZmZm6HS6NF0/PjF8+PAhFy9epH///tjZpb3aSFGUZN+vab0/qFWfxYoV49VXX03zOUCy902PPXv2UKRIEYoWLQqof4NLly6l+jdo0qQJRYsWZceOHUn2pfR/12R++AHmzVPbwq1cCQ0amDqiXCsy8HlnhkVnAXAo7kDHXzpSvW91mRs1F5JELp+Ji4xjusN0U4dhMCF8Alb2Vhk+P7Uvs7Kp/Jo+f/48M2bMoGfPntSqVSvD988vdFFRrGnY0NRhGOl34gQW6UiSAAIDA4mMjKR8+fKpHle+fHmOHz9OUFAQly9fpnXr1mm6vp+fH+XKlePOnTuG66THP//8g2Um21vduXOHOnXqpOuciIiITN03frzNX375BXNzc0Mc8PK/Qfny5Tl//nyS7cWLF0/xnByfNWfNGnXQX4Cff1an4hJJKM87M/h+4ktUUBRooMHYBrT9ti02LjI6Qm4liZzI1ZYsWUK1atWSbP/oo49SrDL19/ena9eulC5dGm9v7+wOUeRC8SW2Go2G+vXrc+LEiTSdV6JEiUzdt3nz5slWM165coU333zTaFvi0ipzc/MMl3bY2tqyf//+ZPe99tprqZ67bds23nnnHfr06cN7772X7nsripJs3Dt37ky2anjAgAHpvkemHD4M8X/7999XF5FE8K1gNr+1Gb9dfgAUrVmUrn92pXST0iaOTLyMJHL5jKWdJRPCJ5g6DANLu8yVTlSrVo0GyVSBODs7J5vI3b59m9atW2NhYcGuXbsoVKhQpu6fX5jb2tIvjclMTjG3tU33OW5ubtjZ2eHn55fqcf7+/tjZ2VGoUCHMzMzSXMIVX7VapkwZgJfeJzFnZ+dk36/JxZe4pGvPnj20atWKMmXKpPu+ZmZmKd7XzCzlptD//vsvvXr1ol27dixfvtwoIUvr3+D27duULp30y7527dq4ubkl2Z6j417euAE9ekBMjFoK99NPOXfvPEKv03Psl2PsnrgbbZQWC1sLWnq1pMnHTaQdXB4hiVw+o9FoMlWVmZfdvn2bVq1aoSgKe/fuTbENVUGk0WjSXY2ZG5mbm9O6dWu2b9/OvXv3kv03vnfvHqdOnaJTp06Ym5uzd+/edFeturu7U7NmTXx9fYmMjExXO7m0KFGiRJJSwqpVqwLQoUMHZs+ezdGjR9PdTi49/v33Xzw9PWnZsiXr1q3Dysr4c8Pd3R0PD49U/wZHjhzh8ePH9O3bN9vizLCgIOjcGQID1fZwK1aAuSQmCT25+IRNIzdx/7g6LmG51uXoNr8bhSrKD+C8RHqtinzhzp07tGrVCp1Ox+7du1NtPyfytgkTJqAoCuPGjUvSiUCn0/H222+jKAoTJqgl0/FVq2lZElatTpo0ieDgYN5///1kO9eEh4fj6+uboddgZWVFgwYNjBZHR0dAbTZgb2/PuHHjCAkJSXKuoiisX78+Q/eN5+vri6enJ82bN2fDhg1YW1sne9xXX31FcHAw48ePT7IvIiKC999/Hzs7Oz766KNMxZPloqOhZ0+4fh3KlFF7qCbTs72g0sZo2Tt5L3/W+5P7x+9j7WRNt/ndeHPXm5LE5UFSIifyvCdPntC6dWsePnzIX3/9xZMnT3jy5Ilhf6lSpaR0Lh9p1qwZP//8Mx9++CHNmzfn3XffpUyZMty5c4fff/+dY8eO8fPPP9O0aVNAHSYkLdWdifXt25dJkyYxdepU/vvvP0aOHEnFihWJjIzk2LFj/Pnnn/Tv3z/LhyApX748q1aton///tSpU4d3332XunXrAnD58mUWLFiAoij07NkzQ9c/ePAgnp6eFC9enC+//JKzZ88a7a9evbphWqGBAwdy+vRpZs6cib+/PyNGjKBYsWJcvXqVWbNmcfPmTVasWEGFChUy9ZqzlF4PQ4fCgQPg5KTOp5pKx4uC5t6xe2wauYmASwEAVO1elc5/dMapZPZPJSWyhyRyIs+7fPkyt27dAmDIkCFJ9nt5eTF58uQcjkpkp/fee4+GDRvy448/8sknnxAUFEShQoVo3rw5Bw8epEmTJllynylTpvD6668ze/ZsvvrqKwIDA7G1tcXDw4OPP/6YMWPGZMl9EuvatSsXLlzgxx9/ZO7cudy9exczMzPKly9Px44dM9QpId7OnTuJiorC39+fNm3aJNkf31Yv3g8//ECbNm347bffGDt2LKGhoRQtWpQ2bdqwdu1aqlevnuFYssWnn6q9VC0tYf16dfYGQWxELLsn7ubYL8dAAfui9nSa3UmGFMkHNEpaBuQSOe5lk+7myKTSQghhAhn+fPv5Z4iv5l2+HAYNypb48ppbO2+xefRmnvk/A6D2m7Vp/1N77Arn/XazudHLvr+zmpTICSGEyPv+/hs+/lh9/t13ksQBUcFR+I735eyCswA4l3Gm659dqdSxkmkDE1lKEjkhhBB527//wuDB6jRc48bBZ5+ZOiKT+2/Df2x9eyvhj8JBAw3faUjbb9ti7Zh8xxaRd0kiJ4QQIu/av1/toRobC717w6+/qtNwFVCRQZFse28bF1deBKBw1cJ0/6s7ZZqVMXFkIrtIIieEECJvOn4cunSBqCj1sYCPFfffhv/YMnYLEY8j0JhpaPpZU1p5tcLCRr7q8zP51xVCCJH3nD4NHTpAeDi0aQNr14JVwRwMPTIoku3vb+fCigsAuFVzw3ORJyUblTRxZCInSCKXx0mnYyFEfvPSz7VDh9RZG0JDoWlT2LgRMjDlW37w38b/2DImQSncp01pNVlK4QoS+ZfOoywtLdFoNERERGBbQD/AhBD5U2RkJKB+ziWxYwd4ekJkJLz2mjprg4NDzgaYC0Q9jWL7B9s5v+w8AG6vuNFjUQ9KNZbBzwsaSeTyKHNzc5ydnQkICCAmJgYnJycsLCxkYEchRJ6lKAqRkZE8efIEFxcXzBO3d9uwAfr3Vzs2dOwI69ZBPphDOL2ubr7Klre2EP4oHI2Zhibjm9D669ZSCldAyb96Hla8eHFsbW158uQJoaGhpg5HCCGyhIuLC8UTTqulKDBrFowfrz7v3Vsd8DeFOWLzq6jg56VwS6UUTrwgiVweptFocHFxwdnZGZ1Oh1arNXVIQgiRKZaWlsYlcXFx8M47MH++uj5mDPz2G1gUrK+vq5uvsmXMFsIfPi+F+6QJradIKZyQRC5f0Gg0WFhYYFHAPtiEEPlcYKBalbp7tzo23E8/wQcfFKhx4qKCo/j3w385t+QcoI4L57nIk1KvSimcUMk3vxBCiNzn4EEYMADu31c7M6xcCV27mjqqHHX9n+tsHr2ZsAdhhlK4Vl+3wtI2mU4gosDKdCLn6+vLtm3buHXrFuHh4Sl2G9doNOzatSuztxNCCJGf6fUwYwZMnAg6HVStqo4RV7OmqSPLMTFhMfh+4svp+acBKFylMD0W9aB0k9ImjkzkRhlO5CIjI+nVqxc7duwAXj7uj/SmFEIIkaobN2DECDhwQF0fMgTmzClQw4vcPnCbDUM38MzvGWjg1Q9fpc03baQUTqQow4ncpEmT8PX1xcnJiVGjRtGwYUOKFi2KmZlZVsYnhBAiv9PpYPZs+PJLdbote3v45Rc1qSsghQDaaC27J+3myI9HQAHnss54LvKkXKtypg5N5HIZTuTWrl2Lubk5vr6+NGrUKCtjEkIIUVAcOADvvQfn1Mb8tGkD3t5Qvrxp48pBD08/ZP2b6wm4FABAnRF16DirI9ZOBWt4FZExGU7kAgICqFy5siRxQggh0u/GDZg0CVatUtddXOC77+CttwpMKZxeq+fA9APsn7IfvVaPfTF7us3vRtVuVU0dmshDMpzIlSpVSoa7EEIIkT63b8PUqbBokVqlqtGoydu0aeDmZurockzg1UA2vLmB+8fvA1CtdzW6zu2KnVvBm6lCZE6GG7QNHjyYy5cvc/PmzayMRwghRH509iwMGwaVK8Nff6lJXKdOcOoUzJ1bYJI4Ra9w7Ndj/FnnT+4fv4+1szU9l/Wk79q+ksSJDNEoL+tumoLY2Fjat29PUFAQS5YsoW7dulkdW4EWGhqKs7MzISEhODk5mTocIYRIv7g42LIFfv0V9u59sf3112HKFGjSxGShmULInRA2DNuA/x5/ACq0q0CPBT1wKiWf8flJTn9/Z7hudOzYsZQuXZojR47QsGFD6tSpQ8WKFbG3t0/2eI1Gw19//ZXhQIUQQuQBigKnT8OyZep8qAFqA37MzaFvX/jwQ2jc2KQh5jRFUTi3+BzbP9hOTGgMFrYWtJ/ZngZvN5ChuUSmZbhEzszMDI1G89Lx4ww30mjQ6XQZuVWBJCVyQog8Q6eDI0fAx0ddbt9+sa94cbVKddw4KF3wBrSNeBLB5rc2c3XjVQBKvVoKzyWeFK5c2MSRieySZ0rkFi5cmJVxCCGEyEv8/GDnTti1S10CA1/ss7ODzp1h6FDo2LHATXAf77+N/7F59GYiAyIxszSj1detaPZpM8wsZLxVkXUy/L9r6NChWRmHEEKI3Co2Fs6fh6NH1eXwYTWRS8jZGbp1g169oEMHNZkroGLDY/n3438NU2wVrVGUnkt7UrxOcRNHJvKjgvkzSQghRPL0erh+Xe1NevIkHDumPo+JMT7OwkJt6/b669C2rfrcyso0Meci947dY/2Q9Ty98RSAJuOb0GZaGyys5etWZI8se2ddu3aNa9euERYWhqOjI1WqVKFKlSpZdXkhhBBZTa+HmzfVhC0+cTt9GsLCkh7r6gqvvqoujRtD06bg6JjzMedSeq2eA98eYN+UfSg6BceSjvRc0pPybQrODBXCNDKdyP355598//333E7YuPW5cuXK8cUXXzB69OjM3kYIIURmhYSo1aIHDqhVpKdOQWho0uNsbKBuXahfHxo2VJO3ypULzIwL6fX05lPWD1nPvaP3APDo70GXOV2wdbU1cWSiIMhUIjd8+HCWLFmCoihYW1tTunRpihUrxuPHj7l79y5+fn6MHTuWw4cPF9jOEW+//TZz585l9uzZvPvuu6YORwhRkISGqh0R9uxRk7fz59VSuIRsbKB2bWjQQE3cGjSAatUKbAeF9FAUhbMLz7L9g+3Ehsdi7WRN5z86U3NQTRlWROSYDP9PXbFiBYsXL8be3h4vLy/Gjh2Lg4ODYX94eDhz585lypQpLFmyhPbt2zNw4MAsCTqv2LJlC0eOHKFEiRKmDkUIURAoCly+DP/8A9u2qcmbVmt8TMWK0KIFNGumlrZVrw6WlqaJNw+LDIxky5gtXPG5AkDZ18riucQTl7Iupg1MFDgZTuTmz5+PRqNh3bp1tG/fPsl+BwcHxo8fT61atejYsSPz588vUInc48ePefvtt/nnn3/o1q2bqcMRQuRnly7B6tWwZg1cvWq8r1IlaN8eWraE5s1Bflhm2o1/b7Bx+EbCH4ZjZmlG66mtaTq+KWbmMqyIyHkZTuTOnTtHhQoVkk3iEmrfvj2VKlXizJkzGb1VmixbtowDBw5w6tQpLly4QGxsLAsXLmTYsGEpnnPixAm8vLw4cuQIsbGxeHh48OGHHzJo0KBMxzN8+HDef/99atasmelrCSFEEo8fw+LF6nL58ovt1tbQpo06j2mnTmoiJ7JEXFQcO7/YyfFfjwPgVs2NXst64V7P3cSRiYIsw4lcdHQ0Li4uaTrWycmJe/fuZfRWaTJx4kRu376Nm5sb7u7uyXa+SGjv3r106NABKysrBgwYgLOzMz4+PgwePBh/f3++/PLLDMfy22+/ER4ezieffJLhawghRBJ6vToI77x5sHHji2pTKyt17Lb+/dWx3GQ2mCz38MxD1g9ZT8Bldcqxhu82pN2MdljaSrW0MK0MlwOXKVOGixcvEphwNO9kBAQEcOnSJcqUKZPRW6WJt7c3/v7+BAQEMHbs2FSP1Wq1jBo1Co1Gw/79+5k/fz4zZ87k3LlzeHh44OXlxfXr1w3HT5w4EY1Gk+oS77///mPq1KksWbIEMzMpZhdCZIGgIPj2W7V9W4cOsG6dmsQ1bgze3mrp3KZNMHiwJHFZTNErHP7xMN6NvQm4HIBDcQcG/TOIzrM7SxIncoUMZxrdu3cnJiaG/v37ExA/KXIiT548oX///sTGxtKjR48MB5kWr7/+OmXLlk3Tsbt37+bmzZsMGjSIunXrGrY7OjoyadIktFqtUS/b8ePH4+fnl+oS7+jRowQEBFCpUiUsLCywsLDg9u3bfPDBB9SpUyfLXq8QogC4dQveew/KlIGvvgJ/f3UGhXffhXPn1CFERo6ENNaOiPQJfxTO8k7L2TF+B/o4Pa94vsLY82Op3KmyqUMTwiDDVatffPEFq1atYu/evZQtW5a+fftSvXp1ihYtypMnT7h8+TJr164lOjqa0qVL8/nnn2dl3Jmyd+9egGTb98Vv27dvn2Gbi4tLmquRPT09adCggdG2Dh06MGzYMIYPH57+YONCIS5+JWF39gTPk3RzT8txqZyT4nGJzknpOOl2L0TmnDwJM2aoJW/xw4XUqQMffgh9+xbo6a9yyvV/rrNh2AYiAyKxsLWgw6wO1H+rvgwrInKdDCdyhQoVYvfu3QwcOJBTp06xdOlSoze4oigANGzYkBUrVlCoUKHMR5tF4qtNK1dO+qvK1dUVNzc3o6rV9Egu6bO0tMTd3Z1KqTQ6jomJISbBFDih8YN0ri8N+eozOwsTxowcl+ak1xzMzAEz9Xnixez5Y3L7zRKtxx9jZgFmVmBmDebPH82swNz6xXbDeqJ95jZgbgcW9uqS8LmFvXptkfedOgVeXrB164ttHTvC+PFqBwZJIrKdNkbLzi92cuznYwAUq1WM3it7U6R6ERNHJkTyMvXpX6lSJU6cOMGuXbvw9fXl2rVrhIeH4+DgQJUqVejQoQNt2rTJqlizTEhICADOzs7J7s+JzhmJTZ8+na+//jpH72kaSoKnSsqHpXCKSIGZVfIJnoU9WDik8vj8uaUDmD9/THiMuZ0kDznhzBmYPFlt5wZgZqa2d/v0U5Ce7zkm4EoA6wau4/G5xwA0er8R7b5vh4WN/FASuVeWvDvbtm1L27Zts+JS+ZK/v/9Lj5kwYQIff/yxYT00NJTSpUtD7yfPGy+nlAAlznLSclyic9JyXJKkywT3yfRx6XgNiu75ok/wPLkllf16HZBgv14L+tjnSwzoYhI8f/6oj32+PeHzWNBFgy4CtJGgjVAXXYR6f1CPiY0FgslaGrCwSz75s3BQSww1FmqJoOb5YmZpvM3MAqPmuOkuOU1r84AUtiWbiKZ1WybPf9m5tx7DrK2w84K6bqaBrvXh7Q5QviiwB67uyZ57p/e4TJ+fe++tKAqnV4exfUoQ2mgFu0Lm9JhZmirt4iDo3wSl7RbJlNAnsy3xcWZWL0rYNRby40hkqQL5MyO+JC6+ZC6x0NDQFEvrsou1tTXW1tZJd5hbq4sQiSmKmvBpEyR4uogXiZ7REv7yx7hw9fy4cNBFxt/kxTVE1gkFfIBdgB41z2gC9FSgxEl4ehKemjLAgiMqwoYt3t24fNwDgAo1buI5dj2O1uGwP5tumjCxi39ulvB5on3m1mBmo/6oMrczfjTaZp/MPnuwdFKbZ0gCmS8VyEQuvm3c9evXqV+/vtG+4OBgAgMDadq0qSlCEyLtNJrnbedswLpw1l5b0Sco/Usl+dPHqiWNStzzR+2Lx/jn+jhelH4+f3xZ6Wyy+19WLZ/Wbek4P8Xq/wyeH6ODtVdh6SWIeN6LqVlJGFsbyqcwbEhOvVZTn5/Vf+s0nH/7vCM+31Ym9Ik1ZuZ62oy8TdM+99Bo6j1/Hycuade+KG1PvM2oNF5rvD+x+JJ5bXgKMWcDM0s1obN0TvDobLzN6vk2azf1M8XaTV2sCqvtekWulKZErkKFCoDaJs7X19doW1ppNBpu3ryZzvCyR8uWLZk+fTq+vr4MGDDAaF/862vZsqUpQhMid9CYqe3lLB2AYqaOJu/T62HVKpgwAe7cUbfVrQs//gitW5s2tgJIr9Ozf+p+9k/dj6JXKFSpEL1X9qZEg2yavkyve9FcImGTCaOmFbHGxyQ+Thel/rjSRabyGJH8NlB/UMUEqUtGWDgmSO7iH4uCXQmwcQfb+KWEmhRK6V+OSVMiF9/Gy8bGJsm2tMpNXbbbtm1LhQoVWLFiBe+//75hfLewsDCmTp2KhYVFqlN7CSFEmh0+rA4bcuKEul6ypDq475AhaqcGkaPCHoSxbtA6bu9TZ/+pPbQ2nWZ3wtoxG5uwmJmDmR0mGYJA0aslf7Ehz4ezSuExNuT582fPE75A9TE26Pk1wtQlwv/l9zS3NU7sbEuBQzmwLwv2zx+tXLL1ZRckaUrk4ge8tbS0TLItt/D29ubgwYMAXLhwwbAtfsw4T09PPD09AbCwsMDb25sOHTrQokULBg4ciJOTEz4+Pvj5+TFt2jSqVKliipchhMgvnjyBL76A+MHFHRzU9Y8+knHgTOSm7018hvgQGRCJlYMVXeZ2odbgWqYOK3tpzJ5Xn2Zwxg9FryZ40YFqUhef4MUEQPRjiHr4fHmgPsaFqKWH4bfUJSWWzi+SOvty4FgJHKuAU1WwK/18+CeRFhpFSesYELnbsGHDWLx4cYr7vby8mDx5stG248eP4+XlxZEjR4iNjcXDw4MPP/yQwYMHZ3O0Lxff4SIkJAQnmXJHiLxDp4M//1RnYnj2TN02YgR88w0UL27S0AoqvVbPHq89HJx+EBQoVrsYfdf0pXCVLG5bKtQqXaPk7gFE3oWI288XfzUZTI2ZtXFi51gFnKqAcw21HV8ul9Pf3xlO5Pbv34+zszO1a9d+6bHnz5/n2bNnvPbaaxm5VYEkiZwQedDRo/DOO3D6tLpety78/js0aWLauAqw0PuhrBu4jjsH1LaJ9cfWp+OsjjI2nClpI4wTu3B/CLsOYdfUR31syufalQGXWuBS8/lSS03yzHLPvLd5JpEzMzOjRYsWRlNZpaR169YcOHAArTaZ3jsiWZLICZGHBAWp1abe3uq6s7NaAjd2LJhLFZGp3Nh+g/VvrCcyMBIrRyu6ze9Gjf41TB2WSI1eB5F3IPSamtiFXn3+eAUiUxio38wKnKqBax0o3BAKNQTXWmqPfhPI6e/vTP0kSU8OmE9qcIUQ4gVFgRUr1M4Mgc+ri4YNg++/h6JFTRlZgabX6tk9aTeHvjsEQPG6xem7pi+FKuWeqSJFCszMwaG8utDBeF9sMDy7CM/Ow7MLzx8vqp0wnp1TF7/nTazMLMG5JhRuoCZ2hRuoVbP5cDrDHHlFQUFB2Nra5sSthBAiZ/j5wdtvw7//quseHjB3LjRvbtq4CriQuyGsG7iOu4fuAtDwnYa0n9leqlLzAytXKNpCXeIpilpF++wcPD0FQSfh6Qm1HV7waXVhnnqshT0UfhWKNFMXt1cz3gkkF0nzOzs0NJRn8Q13n4uJieHu3bsplrZFRUWxb98+Ll68mKa2dEIIketptfDzz/C//0FUFFhbw6RJ6ryoVjJoqild/+c6699cT1RQFNZO1nT/qzvV+1Q3dVgiO2k06tAmDuWgVA91m6Ko1bNBJ9RZUuIf40Lh8S51AbVHr0stcHue2BVpDvalTfVKMizNidysWbOYMmWK0baTJ09Srly5NJ0/cuTIdAUmhBC5zqlTMHq0Osk9QKtWag9VGa7IpHRxOnZ/tZvDPxwGwL2+O31W96FQRalKLZA0mufDmpSFMn3UbYoeQi5BwKEXS4QfBJ9Vl+u/q8c5VIBiraFoa/XRLpsGic5CaU7kXFxcKFOmjGH9zp07WFlZUTyF7vQajQZbW1sqVKhA//79GTJkSOajFUIIU4iOBi8vmDlTnaXB1VV9Pny4jGBvYiF3Qvh7wN/cO6I2hG/0XiPa/dAOC2upShUJaMxe9HStPFbdFvkAAhMkdsFnXox/d/Mv9RjHKmpCV6wNFGsFNrmv7Wumeq02b96c/fuza1bhgk16rQqRSxw9qiZs//2nrvfvD7/8AsVk6jJTu7blGhuGbiDqaRTWztb0WNCDar2qmToskVfFhcGTA/BkDzzeA09Pk2SuXmcP48TOyjXJZfJMr9WFCxdSTD7IhBD5VVSUWgr3449qKVzx4mo1avfupo6swEtclVqiYQn6rO6Da/mkX6pCpJmlI5TsrC4Asc/gyX54vFtN7J6dV6tnQy7Btd/UUj7XelD8dSjeVm1rZ5HzHTvzzcwO+Y2UyAlhQkeOqKVwV6+q62+8oXZwKCRtrkwt9F4ofw/429ArtfEHjWk3ox3mVjJen8hm0YHwZN/zxG43hP5nvN/MGoo0JdShOc6vTs39AwKfPXuWX3/9lXbt2jFw4MAUj1uxYgU7d+7ko48+ombNmhkOtKCRRE4IE4iKUnug/vST2vPN3V0thevWzdSRCYwH+LV2sqb7gu5U7y29UoWJRN6HR897wT7aBVH3AQiNBOfR5P6q1T///JPFixe/tDdq2bJlWbRoEfb29syePTujtxNCiOx1+LBaCnftmrr+5ptqKZyrVNeZml6rZ+/kvRz45gDwfIDftX2lV6owLbuSUOFNdVEUdQaKR7vg1nZgc46FkeESuerVq/Pw4UOCg4NfeqyrqyslS5bk4sWLGblVgSQlckLkkMSlcCVKqKVwXbuaOjIBhD0MY93AddzedxuABm83oMNPHWSAX5Fr5ZnODnfv3qVKGsdOKl++PLdu3crorYQQInscOgQjRrwohRs2TE3opBQuV7i16xY+g3yIeBKBlcPzuVIHyFypQiSU4UTOzMyM2NjYNB0bFxeHTqfL6K2EECJrRUXBxIkwa9aLUrj586FzZ1NHJgC9Ts+Bbw6wd/JeUKBozaL0XdsXt6pupg5NiFwnw4lcxYoVuXDhAg8fPsTd3T3F4x48eMCVK1eoXl0apAohcoHTp9VeqJcvq+vDh6ulcC4uJg1LqCKeROAz2IdbO9VanLqj6tLp105Y2lqaODIhciezjJ7YrVs3dDodo0ePJi4uLtljtFotY8aMQVEUusvYS0IIU9JqYdo0aNxYTeKKF4ctW2DBAkniconb+28zt85cbu28haWdJZ6LPek+v7skcUKkIsOdHYKDg6lRowaPHj2ievXqfPDBBzRu3BgXFxeePXvG0aNHmT17NhcvXsTd3Z2LFy/iKu1O0kw6OwiRha5fV3uhHj2qrvfpA3PmgJtU1eUGil7h4PcH2TNxD4pewa2aG/3+7keR6kVMHZoQ6ZbT39+ZGhD43LlzdO/enbt376JJZr5BRVEoW7YsGzdupFatWpkKtKCRRE6ILKAoasL26acQGQnOzvDbbzB4sMyRmktEBkay/s313Nh2A4Bab9Siy5wuWNlbmTgyITImz/RaBahduzYXL15k7ty5bNq0iStXrhAaGoqjoyMeHh54enry1ltv4eDgkFXxCiFE2jx4oPZI/fdfdb1NG1i0CEqXNmlY4oW7h+/yd/+/Cb0XioWNBZ1+60TdEXWTLRgQQiRPpujKpaRETohMWL0a3n4bgoPBxga+/x7efRfMMtwsWGQhRVE48uMRdk3YhV6rp3CVwvRd25ditWT+bpH35akSOSGEyFWePlUTtpUr1fX69WHpUqhWzbRxCYOo4Cg2DtvI1U3qPLY1BtSg67yuWDtamzgyIfImSeSEEPmDr686lMiDB2BuDl99pY4VZyk9HnOLu0fusm7AOkLuhGBuZU7HXzpSf0x9qUoVIhMyncj5+fmxevVqzp07x9OnT1McikSj0bBr167M3k4IIYxFR8OECeq8qABVqqilcI0amTQs8YKiVzg04xC7J+5G0Sm4VnCl79q+uNdLeQxSIUTaZCqR++GHH/jqq6/QarWGX1QJm9wl3Ca/uIQQWe7CBbUH6oUL6vq4cfDDD2BnZ9q4hEH443A2vLmBm743gedVqX92xdpJqlKFyAoZbvn7zz//8Pnnn1OkSBG8vb3x8PAAYMeOHSxYsIAPPvgAe3t7bGxs+OWXX9i9e3eWBS2EKOAUBX79FRo2VJO4okXVwX1//12SuFzk1q5b/FnnT2763sTC1oJu87vRa0UvSeKEyEIZ7rXaqVMnfH192b9/P82aNaNFixYcPnzYaE7VoKAgevfuzdmzZzlx4gSVK1fOssDzO+m1KkQKHj1S28Jt366ud+6szs5QTHo85hZ6rZ69X+/lwDcHQIEi1YvQZ00finoUNXVoQmS7nP7+znCJ3KlTp3B3d6dZs2YpHlO4cGFWrlxJZGQkX3/9dUZvJYQQqk2boGZNNYmzsVEH992yRZK4XCT0XiiL2yzmwDQ1ias7qi6jT4yWJE6IbJLhNnKhoaHUrl3bsG5jY2PYnjADdXd3p0aNGuzZsycTYQohCrTISPjkE5g7V12vXRtWrIDq1U0blzBydfNVNg7bSNTTKKwcrej6Z1dqDqxp6rCEyNcyXCJXtGhRQkNDjdYBrl69muTY8PBwgoKCMnorIURBdvo01Kv3Ion75BM4dkySuFxEF6tj+0fbWdV9FVFPo3Cv786Y02MkiRMiB2Q4katYsSIPHjwwrDdu3BhFUZgzZ47Rcbt27eLGjRuULFky41EKIQoevV7tgfrqq3D1Kri7w44dMHMmWEtj+dzi6c2n/NX0L479fAyAxh82ZsShERSqVMjEkQlRMGS4arVjx47s37+fEydO0LBhQwYNGoSXlxeLFy/m2rVrNGnShMePH7NmzRo0Gg1vvPFGVsYthMjP7t+HN9+E+N7uPXvC/PlQuLBp4xJGLq66yOa3NhMbFottIVt6LOxB1e5VTR2WEAVKhhO5fv36cePGDZ4+fQqAm5sbq1evZsCAARw+fJjDhw8bju3Tpw8TJ07MfLRCiPzvn39g6FAIDFSHEvn1VxgxAmQsylwjLjKO7R9u5/T80wCUblaa3it741za2cSRCVHwZHj4kZSEhISwbds2/P39sbW1pUWLFtSrVy8rb1EgyPAjosCJjVWn1Zo5U12vWxdWrVJnahC5xuPzj1k3cB0BlwNAAy2+bEGrya0ws8hwSx0h8pWc/v7O8rlWnZ2dGTBgQFZfVgiRn/n5wYABcPy4uv7ee2r7OGkLl2soisLx2cfZ8dkOdDE6HIo70HNpTyq8XsHUoQlRoGU4kTMzM6NQoULcv38fa/mwFUJk1Lp1MHIkhISAi4s6uG/PnqaOSiQQERDBxuEbub71OgCVu1Smx8Ie2BexN3FkQogMJ3IODg5UrFhRkjghRMZER8PHH0N8T/dXX1WrUsuWNW1cwshN35tsGLqB8EfhmFub0+6HdjR6t5HMny1ELpHhRO6VV17h8ePHWRmLEKKguHoV+veHc+fU9c8/h6lTwdLStHEJA12sjl1f7eLIzCOAOs1W75W9KVZLZtEQIjfJcOvU0aNHc+fOHbZu3ZqV8Qgh8rulS6F+fTWJK1IEtm2D776TJC4XCboWxF9N/jIkcQ3ebsDok6MliRMiF8pwidzo0aM5c+YMAwcOZOrUqbzxxhsUKiQDQAohUhAeDu++C4sXq+utW8OyZVCihGnjEgaKonB24Vm2vbeNuMg4bAvZ0n1Bd17p8YqpQxNCpCDDw49UqKD2VLp79y56vR5Qx5Kzt0++8atGo+HmzZsZDLPgkeFHRL5y/rxalfrff2BmBl5e6lAj5uamjkw8F/0smi1jtnBpzSUAyrUuR8+lPXEqKZ8/QqRHnhl+xN/fP8m2gIAAAgICkj2+oDWMvXPnDuPHj2fHjh3ExsZSvXp1NmzYIFOViYJFUeDPP+HDDyEmRi19W7ECWrY0dWQigTsH7+Az2IeQOyGYWZjRemprmn7aFDNzGRtOiNwuw4mcn59fVsaRrwQFBdG8eXM6duzIzp07cXFx4dKlS9LDVxQsISEwejSsXauud+4Mixap7eJErqDX6tk/bT/7p+5H0Su4VnSl94relGwkPziFyCvSnMidP38eBwcHQ5VqWRkiIEXff/895cuXZ968eYZtFStWNGFEQuSwEyfUqlQ/P7CwUDszfPSRWq0qcoVnt5/hM9iHu4fuAlD7zdp0+q0T1o7yg1OIvCTNn6p16tRh+PDhye6bMmUKixYtyqqYMmTZsmWMGTOGBg0aYG1tjUajeWlMJ06coHPnzri6umJvb0+jRo1YsWJFpmPZvHkz9erVo3fv3hQtWpSGDRvi4+OT6esKkespCvz0EzRrpiZx5crBwYPwySeSxOUil9ZcYm7tudw9dBcrRyt6Le+F52JPSeKEyIPS9cmaUr+IyZMns2DBgiwJKKMmTpzIvHnzuH37Nu7u7i89fu/evTRv3pwDBw7Qp08f3n77bQIDAxk8eDDffvttpmLx8/Pjjz/+wMPDg3///Zf+/fvTt29f9u/fn6nrCpGrBQZCt25q0hYXB336wJkz0LixqSMTz8WGx7Jx5Eb+7v83MSExlGxckrFnx1JzUE1ThyaEyKB88xPZ29sbf39/AgICGDt2bKrHarVaRo0ahUajYf/+/cyfP5+ZM2dy7tw5PDw88PLy4vr164bjJ06ciEajSXVJSK/X07BhQ6ZMmULdunUZP348Xbt2NapqFSJfOXAA6tSBrVvV+VH/+APWrFGn3BK5woNTD/iz3p+cXXBWnex+YguGHxiOawVXU4cmhMiEDHd2yG1ef/31NB+7e/dubt68yfDhw6lbt65hu6OjI5MmTWLAgAEsXLjQUDI3fvx4Ro0alebrFy9enFdeMR53qVq1ahw+fDjN1xAiT9DpYPp0dTgRvR6qVFETuNq1TR2ZeE7RKxz+8TC7v9qNPk6PUyknei7rSbmW5UwdmhAiC+SbRC499u7dC0D79u2T7Ivftm/fPsM2FxcXXNJRstC0aVOjEj2Aa9euSQcRkb88fAhDhsDu3er6m2/C77+Dg4Np4xIGIXdD2PDmBvz3+gNQrVc1us3vhm0hW9MGJoTIMgUykYtPsipXrpxkn6urK25ubkkSsfT46KOPaNasGT/88AM9e/Zk586dbN682ZBAJicmJoaYmBjDemhoaIbvL0S28/WFN96AJ0/Azk6tSh061NRRiQQurr7I1rFbiX4WjaW9JR1/6UjdEXUL3JieQuR36UrkYmJiuHPnTrr3xStTpkx6bpdtQkJCAHB2dk52v5OTE/fu3cvw9Rs3bszatWv56quv+N///keVKlVYu3YtzZo1S/Gc6dOn8/XXX2f4nkLkiLg4+N//1OFEAGrVgtWr4RWZwim3iAmN4Z93/+H80vMAlGxUkp7LelK4cmETRyaEyA7pSuROnjxJ+fLlk2zXaDQp7kt4jFarTX+EeVTPnj3p2bNnmo+fMGECH3/8sWE9NDSU0qVLZ0doQmTMnTswcCDEt/UcO1YdasRWqulyizsH77D+jfU883+GxkxDi69a8Nqk1zC3lKnQhMiv0pXIZXBa1kyfm9XiS+LiS+YSi58nLSdZW1vLzA8i99qwAUaMgOBgcHICb2/o29fUUYnndHE69n29j4PTD6LoFVzKu9BzaU/KNMsdtSBCiOyT5kQuP03JFd827vr169SvX99oX3BwMIGBgTRt2tQUoQmRu0RHw6efwm+/qesNG8KqVfB8hhdhekHXg/AZ7MODEw+A5zM0zO6EtZP8MBSiIEhzIpefely2bNmS6dOn4+vry4ABA4z2+fr6Go4RokC7ehUGDICzZ9X18ePhm2/AysqkYQmVoiic9j7Nvx/+S1xkHDYuNnT9syse/TxMHZoQIgflmwGB06Nt27ZUqFCBFStWcDb+SwoICwtj6tSpWFhYMGzYMJPFJ4TJLVkC9eurSZybG/zzD/zwgyRxuURkYCSre65my1tbiIuMo3yb8rx94W1J4oQogPLN8CPe3t4cPHgQgAsXLhi2xQ/54enpiaenJwAWFhZ4e3vToUMHWrRowcCBA3FycsLHxwc/Pz+mTZtGlSpVTPEyhDCtsDB45x1YulRdb90ali2DEiVMG5cwuPHvDTYO20j4o3DMLM1o+21bmnzcBI2ZDCsiREGUbxK5gwcPsnjxYqNthw4d4tChQwCUK1fOkMgBtG7dmoMHD+Ll5cWaNWuIjY3Fw8ODqVOnMnjw4JwMXYjc4cwZ6N8frl9XJ7j/+muYMAHMpcdjbhAXFcfOL3Zy/NfjABSpXoRey3tRvE5xE0cmhDAljZKbupMKg/iesyEhITg5OZk6HJGfKQrMnq12aoiNhVKlYOVKaN7c1JGJ5x6de4TPYB8CLgUA0Oi9Rrz+/etY2lqaODIhRGI5/f2db0rkhBAZEBSkDiuyaZO63qMHLFgAhQqZNi4BqPOkHpl1hN1f7kYXq8O+mD09Fvagcqeks9IIIQomSeSEKKgOHIBBg+DePbUTw8yZ8O67IFM45Qqh90LZMHQDfrvVoZ+qdq9KN+9u2BexN3FkQojcRBI5IQoanQ6mTwcvL9DroXJldZqtunVNHZl47vLfl9n81maig6OxtLOkw6wO1BtdT+ZJFUIkIYmcEAXJgwcwZAjs2aOuv/EG/P47ODqaNi4BqPOkbv9gO2cXnQWgRIMS9Frei8JVZJ5UIUTysiSRu3v3LgcOHOD+/ftERUXxv//9z7AvLi4ORVGwkvGnhDCtbdtg6FAICAB7e/jjD3jzTVNHJZ67e/guPkN8eOanzpPafEJzWnq1lHlShRCpylSv1cDAQN555x3WrVtnNJeqTqczPB8yZAgrV67k+PHjSabDEimTXqsiy8TGwldfqW3gAOrUUafZqlrVpGEJlV6rZ9/UfRyYdgBFr+Bc1pmeS3tStkX+mU1HiIIkp7+/MzyzQ1hYGC1btmTt2rWULFmSYcOGUbJkySTHjRo1CkVR8PHxyVSgQogMuH4dmjZ9kcS9+y4cOSJJXC7x9MZTFjRfwP4p+1H0CrWG1GLsubGSxAkh0izDVaszZszgypUr9O7dmyVLlmBra0uLFi24f/++0XGvvfYatra27IlvkyOEyBlLl8K4cRAerg4nsmCBOryIMDlFUTiz4AzbP9hOXEQc1s7WdJ3blRoDapg6NCFEHpPhRO7vv//G2toab29vbG1tUzzOzMyMSpUqcefOnYzeSgiRHqGh6jRby5ap6y1bqs9LlTJtXAKAyKBItry1hSs+VwAo27IsPZf0xLmMs4kjE0LkRRlO5Pz9/alSpQrOzi//8LGzs+Pq1asZvZUQIq1OnICBA+HmTXVqrcmTZZqtXOTmjptsGLqB8IfqPKltprWhySdNMDPPcCsXIUQBl+FEzsbGhrCwsDQd+/DhwzQlfEKIDNLr4ccf4csvQauFMmVgxQpo1szUkQlAG61l54SdHPv5GABur7jRa3kv3Ou5mzgyIURel+FEzsPDg2PHjnH79m3Klk25Ye7Zs2e5c+cOHTt2zOithBCpefRIHUZkxw51vU8fmDcPXF1NG5cA4PGFx/gM9uHJhScANBjXgPY/tMfSTuZJFUJkXobL84cMGYJOp+Ott94iMjIy2WOCg4MZOXIkGo2GN2W8KiGy3vbtULu2msTZ2qoJ3Jo1ksTlAvHzpM5vMJ8nF55gX9SegVsG0uX3LpLECSGyTIZL5EaPHs3KlSvZsWMHNWvWpG/fvjx+/BiABQsWcPHiRZYtW0ZgYCDt27dnwIABWRa0EAVebKxajfrjj+p6zZrq2HDVq5s2LgFA2IMwNgzbwK0dtwCo3KUyPRb0wL6ozJMqhMhamRoQOCwsjLfeeovVq1ej0WgMgwInfN6vXz/++usv7O3lAyw9ZEBgkaLr19UODadOqevvvgs//AA2NqaNSwBwxecKm0dvJuppFBa2FnT4qQP1x9SXeVKFKCBy+vs7U4lcvAsXLrB+/XouXLhASEgIDg4OVK9enZ49e8psDhkkiZxIQlFejA0XESFjw+UyseGxbPtgG2cXnAXAvZ47vZb3wu0VN9MGJoTIUTn9/Z0lc63WrFmTmjVrZsWlhBDJCQ1VE7jly9X1Vq3UseGSmU1F5Lx7R+/hM8SH4JvBoIFmnzej9detMbeSYV+EENkrSxI5IUQ2On5crUq9dUsdD+7rr+GLL2RsuFxAr9Wz/5v97J+6H0Wn4FzGGc8lnpRrWc7UoQkhCghJ5ITIrfR6dY7Ur75Sx4YrW1YdG65pU1NHJoDgW8H4DPHh3pF7ANQcVJPOv3fGxkXaKgohck6aErkKFSpk+kYajYabN29m+jpCFAiJx4br21cdWsTFxaRhCXWe1HOLz7HtvW3Ehsdi7WRN5z86U2twLVOHJoQogNKUyPn7+2f6RtJjS4g02rEDhgyBJ0/UseF+/RVGjgT5P2RyUU+j2DJmC5f/vgxAmRZl6Lm0Jy5lXUwbmBCiwEpTIufn55fdcQghtFrw8oLp09UeqjVrwurVUK2aqSMTwK1dt9gwdANh98MwszCj1ZRWNPusmcyTKoQwqTQlcqlNwSWEyAJ376odGg4dUtfHjoWfflJL5IRJaWO07P5qN0d+PAJA4SqF6bW8FyUalDBxZEIIIZ0dhDC9rVvV9nBPn4KjI3h7Q79+po5KAE8uPcFnkA+Pz6uz1tQfW5/2M9tjZW9l4siEEEKVJYlcREQEhw4d4tq1a4SFheHo6EiVKlVo1qyZzOggREoST7NVv75alVqxomnjEih6heO/HWfHZzvQxeiwK2JH97+6U7VbVVOHJoQQRjKVyMXGxuLl5cXvv/9OREREkv329va89957eHl5YWUlv2CFMPDzgwED1DHiAD74AL7/HqytTRuXIOxhGBuHb+Tmv2ov+8qdK9P9r+44FHcwcWRCCJFUhhM5nU5H9+7d2bFjB4qiUKpUKV555RWKFSvG48eP+e+//7h37x7fffcdp06dYuvWrZjLAKZCgI8PjBgBISHqcCILF4Knp6mjEsB/G/5j06hNRAVFYWFjQbuZ7Wg4rqH0uhdC5FoZTuT+/PNPfH19KVasGLNnz6Z3795GH3aKorBu3To++OADduzYwbx583j77bezJGgh8qToaPj0U/jtN3X91Vdh1Sp1oF9hUrHhsWz/aDtnvM8AULxOcXot70WR6kVMHJkQQqROoyiKkpETX331VU6cOMGJEyeoV69eisedPn2aBg0a0KhRI44ePZrhQAuanJ50V2QzPz/o0wdOn1bXP/sMpk0DS0vTxiW4f/w+PoN9eHrjKWig6adNaT2lNRbW0hdMCJF+Of39neFPqitXrlCtWrVUkziAevXqUb16dS5fvpzRWwmRt23dqg7w++wZFC4MS5ZA586mjqrA0+v0HJx+kL2T96LoFJxKOeG5xJPyrcubOjQhhEizTLWRs0xjaYKlpSV6vT6jtxIib9Lp4H//g2+/VdcbN4a1a6F0adPGJQj2C2b9G+u5e+guAB79Pegypwu2rjJunxAib8lwIlexYkUuXryIv78/5cqVS/E4Pz8/Ll68SPXq1TN6KyHynidPYNAg2LVLXX/vPZg5E6T3tkkpisL5pef5591/iA2LxcrRis6/d6bWkFrSoUEIkSdleG6Zvn37otPp6NGjB+fPn0/2mHPnzuHp6Yler6efDHAqCorDh6FePTWJs7eHlSvV+VIliTOpqOAo1g1Yx4ahG4gNi6V0s9KMPTeW2m/UliROCJFnZbizQ2RkJK+++ioXL15Eo9HQvHlzqlevTtGiRXny5AmXL1/m4MGDKIpCrVq1OHLkCLYy3VCaSWeHPEhRYPZs+OQTdd7UV16BdetASqNNzm+PHxve3EDovVDMLMxoObklzT9vjpmFzJMqhMhaOf39neFEDiAwMJCxY8eyfv164i+j0WiMnvfq1Ys5c+bg5uaWNREXEJLI5THh4TBqlDozA6hTbHl7q1NuCZPRxmjZM2kPh2ceBgUKVS5Er+W9KNmwpKlDE0LkU3mm1yqAm5sbf//9Nzdu3GDHjh1cu3aN8PBwHBwcqFKlCu3bt6eiTDck8rtbt9QBfS9cAAsLdcqt994Dqa4zqYDLAfgM9uHR2UcA1Btdjw4/dcDKQaq4hRD5R5YMlFSpUiUqVaqUFZcSIm/ZuVMtfQsOhuLF4e+/oVkzU0dVoCmKwonfT7Dj0x1oo7XYFralu3d3XvF8xdShCSFElpMRL4XICEWBWbPUmRr0emjUSJ16q6RU2ZlS+KNwNo7YyI1tNwCo2KEiPRb2wNFdqriFEPmTJHJCpFdUFLz1Fixbpq4PGwZz5oCNjUnDKuiubr7KppGbiAyIxNzanHY/tKPRO43QmEkVtxAi/0pzIpfZCe81Gg1arTZT1xDC5O7ehZ494dQpMDeHn36S9nAmFhsRi+8nvpz68xQAxWoVo9eKXhT1KGriyIQQIvulOZHLROfWLDlfCJM7eBB691YH+y1cWJ2loXVrU0dVoD04+QCfwT4EXQsCoMknTWjzTRuZJ1UIUWCk69NOo9FQtWpV3njjDXr16oWDg0N2xZWnhYWF8emnn7Jp0yZCQkKoUqUKX331FX369DF1aCKjVq2CoUMhNhZq14YNGyCVGU1E9tLr9Bz6/hB7vfai1+pxLOmI52JPKrStYOrQhBAiR6V5HLlffvmF5cuXc/LkSTQaDba2tvTs2ZM33niD119/HTMzGVgz3qhRozh48CDe3t6UKFGC1atXM2nSJE6fPk2tWrXSdA0ZRy6XUBR1aq3PPlPXe/aEpUvVGRuESTy7/Yz1b6znzoE7AFTvW52uc7tiW0gGHBdCmF6uHxD42rVrLFmyhBUrVuDv749Go6Fo0aIMGjSIwYMHU69eveyKNc+oUaMGQ4YM4YsvvjBsK1y4MD/++CPDhg1L0zUkkcsFdDp4/3344w91/f331TZxmWwvKjLu/PLz/DPuH2JCY7BysKLTb52o/aZMsSWEyD1y+vs73cVoVapUYdq0ady6dYv9+/czcuRIYmJimDVrFg0bNsTDw4Pvv/+eu3fvZke8KVq2bBljxoyhQYMGWFtbo9FoWLRoUarnnDhxgs6dO+Pq6oq9vT2NGjVixYoVmY6ladOmbNy4kUePHqEoCmvXriUmJoaWLVtm+toih0REqKVvf/yhdmT46Sf45RdJ4kwk+lk06watY/2Q9cSExlCqSSnGnhtLnaF1JIkTQhRomZqiK15sbCybN29m6dKlbN++nbi4ODQaDWPHjuW3337Lijhfqly5cty+fRs3Nzfs7e25ffs2CxcuTLEEbO/evXTo0AErKysGDBiAs7MzPj4++Pn58c033/Dll19mOJbo6GhGjBjBypUrsbCwwNbWlr///pv27dun+RpSImdCjx9Dt25w4gRYW6vDjEj7RpPx3+fPhjc3EHInBI25hpb/a0mLL1vIPKlCiFwp15fIJcfKyorevXuzYcMGduzYQenSpdHr9Vy7di0rLp8m3t7e+Pv7ExAQwNixY1M9VqvVMmrUKDQaDfv372f+/PnMnDmTc+fO4eHhgZeXF9evXzccP3HiRDQaTapLQr/88gvnz59n27ZtnDx5ks8++4z+/ftz+fLlbHntIgtdvQpNmqhJXOHCsGuXJHEmoovVsXPCTha3XkzInRBcK7oy4uAIWv6vpSRxQgjxXJb00X/8+DErV65k6dKlnD17FkVRcHBwoHnz5llx+TR5/fXX03zs7t27uXnzJsOHD6du3bqG7Y6OjkyaNIkBAwawcOFCvv32WwDGjx/PqFGj0nTtqKgoJk2axJYtWwwlcLVr12bfvn388ccfOVZCKTLg0CHo3h2ePoUKFWDbNqhSxdRRFUiB/wXiM9iHh6cfAlB3ZF06/txR5kkVQohEMpzIRUVFsX79epYuXcquXbvQarWYm5vTvn173njjDXr27Imtbe7sRbZ3716AZKs647ft27fPsM3FxQUXF5c0XTsuLo64uLgkAyibm5uj1+tTPC8mJoaYmBjDemhoaJruJ7LI33/DkCEQE6NOt7V5MxSVAWVzmqIonJx7Et9PfNFGabEtZEu3+d2o1quaqUMTQohcKV2JnKIo7Ny5k2XLlrF+/XoiIiJQFIW6devyxhtvMHDgQIoVK5ZdsWaZ+GrTypUrJ9nn6uqKm5ubUdVqejg5OdGiRQs+/fRTZs+ejbu7O5s2bWLHjh1s3bo1xfOmT5/O119/naF7ikyInzN1/Hj1eY8esGIF2NmZOrICJ/xROJtGbuL6P+r/vQrtKuC5yBPHEjJPqhBCpCTNidynn37KihUrDD0xS5cuzbvvvssbb7xBtWp569dySEgIAM7Ozsnud3Jy4t69exm+/qpVq/j888/p06cPISEhVKpUiUWLFtGxY8cUz5kwYQIff/yxYT00NJTSpUtnOAaRBjodfPwx/Pqruv7OO9Iz1UT+2/gfm0dtJjJQnSf19e9ep/H7jWWeVCGEeIk0J3I//vijYWaHIUOG0LJlSzQaDcHBwRw+fDhN12jatGmGA81LSpQowdKlS9N1jrW1NdbW1tkUkUgiMlKtSl2/Xl2fOVNN6mQoixwVGx7L9o+2c8b7DADFahej17JeFK0h1dpCCJEW6W4jd/XqVSZNmpTuG2k0GrRabbrPyw7xJXHxJXOJxXcdFvlUQIDaqeHoUbCyUmdq6NfP1FEVOPeO3sNniA/BN4NBA03HN6X11NYyT6oQQqRDmj8xy5Qpk28G3oxvG3f9+nXq169vtC84OJjAwMACU3pY4Fy/Dp06wc2b4OoKGzdCixamjqpA0cXpOPDNAfZP24+iU3Aq7UTPJT0p16qcqUMTQog8J82JnL+/fzaGkbNatmzJ9OnT8fX1ZcCAAUb7fH19DceIfObIEbUkLjBQnfB+2zZ45RVTR1WgBF0PYv2Q9dw/fh+AmoNq0vn3zti42Jg4MiGEyJsK5Kiabdu2pUKFCqxYsYKzZ88atoeFhTF16lQsLCzSPCeqyCPWr4c2bdQkrkEDtVpVkrgcoygKp+ad4s86f3L/+H2sna3ptaIXvZb3kiROCCEyId80RvH29ubgwYMAXLhwwbAtfsw4T09PPD09AbCwsMDb25sOHTrQokULBg4ciJOTk2GKrmnTplFFBoLNP379FT78UB1epGtXWLUK7O1NHVWBEfEkgk0jN3FtizrTS7nW5fBc7IlzaWmHKoQQmZVvErmDBw+yePFio22HDh3i0KFDgDoXa3wiB9C6dWsOHjyIl5cXa9asITY2Fg8PD6ZOncrgwYNzMnSRXfR6dXy4WbPU9bFjYfZssMg3b/tc79qWa2wauYmIJxGYW5nT5ts2NPmoiQwrIoQQWUSjKIpi6iBEUjk96W6+ExUFb7wB69ap6999B599JsOL5JDYiFh8P/Hl1J+nAChaoyi9lveiWK3cP2C4EEJkRk5/f0vRhMh/AgPVGRoOH1aHF1m0CAYONHVUBcb94/fxGeLD0+tPAXj141dp+01bLGzk40YIIbKafLKK/OXmTXV4kevXwcUFNmwA6YGcI7QxWvZN2ceh7w+h6BQcSzriudiTCm0rmDo0IYTItySRE/nHsWPQrZs64G+ZMurwItWrmzqqAuHBqQdsHLaRJxefAFBjQA06/9EZW1dbE0cmhBD5myRyIn/YuFGtPo2Kgrp1YetWcHc3dVT5ni5Wx76p+zg4/SCKTsGuiB1d53alWq+8Nf+yEELkVZLIibzvt9/g/ffV4UU6dYI1a8DBwdRR5XsPTz9kw7ANPLmglsJ59Peg82+dsXOzM3FkQghRcEgiJ/IuvR4+/1yd8B5g1CiYM0eGF8lmulgd+7/Zz8FvD6LX6rFzs6PLnC5U7yPV2EIIkdPkG0/kTdHRMHSoWvoG8M03MGGCDC+SzR6dfcSGYRt4fO4xANX7VKfz752xLyoDLAshhClIIifynqAg6NkTDhwAS0tYsACGDDF1VPmaLk7HgW8PcGDaAfRaPbaFbenyRxc8+nmYOjQhhCjQJJETecuNG9C5szq8iJPTizlURbZ5fP4xG4Zt4NGZRwBU61WNzn90xqGYtEMUQghTk0RO5B2HD6sD/QYGqsOLbN0KNWqYOqp8Sxen4+B3B9k/dT/6OD22hWzp/HtnPPp7oJEqbCGEyBUkkRN5w5o18OabEBMD9evD5s0yvEg2enLxCRuGbuDh6YcAvOL5Cl3mdMGhuJTCCSFEbiKJnMjdFAW+/17tyADQvTusWAH20rg+O+i1eg5+f5B9X+9DH6fHxtWGzr91psbAGlIKJ4QQuZAkciL3iouDcePA21td/+AD+PFHMDc3bVz51JNLT9g4bCMPTj4AoGr3qnSZ2wVHd0cTRyaEECIlksiJ3CkkBPr1A19fMDODn3+G994zdVT5kl6r5/DMw+z12osuVoeNiw2dZnei5uCaUgonhBC5nCRyIve5cwe6dIGLF8HODlatUudQFVku4HIAG4dv5P7x+wBU6VqFrn92xbGElMIJIUReIImcyF1OnFB7pj58CMWLw5YtaucGkaX0Oj1HfjzCnv/tQRejw9rZmk6/dqLWG7WkFE4IIfIQSeRE7rF6NQwbps7aUKOGOrxImTKmjirfCfwvkI3DN3Lv6D0AKneuTNd5XXEq6WTiyIQQQqSXJHLC9PR6mDwZpk5V17t0UXumOklikZX0Oj1Hfz7K7q92q6VwTtZ0/KUjtYfWllI4IYTIoySRE6YVEaHOmbpunbo+fjx89530TM1iQdeC2Dh8I3cP3wWgUsdKdJvfDadSkiwLIUReJomcMJ27d9X2cGfOqHOmzpunVq2KLKPX6Tn26zF2f7kbbbQWaydr2v/Unroj6kopnBBC5AOSyAnTOHZMTeIeP4YiRdQ5U5s1M3VU+UrQ9eelcIfUUriK7SvSzbsbzqWdTRyZEEKIrCKJnMh5y5fDyJHqdFs1a8KmTVCunKmjyjcUvcLx346z84udaKO0WDla0f7H9tQbVU9K4YQQIp+RRE7kHK0WPv8cfvpJXe/RA5YtAweZvzOrBPsFs2nEJvz3+gNQvm15uv/VHZeyLiaNSwghRPaQRE7kjMBA6N8fdu9W17/8Uu2lamZm2rjyCUVRODXvFDvG7yA2PBZLe0va/dCOBmMbSCmcEELkY5LIiex35gz07Am3b6uT3S9eDL17mzqqfCPkbgibRm7i1o5bAJR9rSw9FvbAtYKriSMTQgiR3SSRE9lr+XIYNUod5LdSJdiwATw8TB1VvqAoCmcXneXfD/8lJjQGCxsL2k5vS+P3G6Mxk1I4IYQoCCSRE9lDq4XPPoNZs9T1zp3VpM7FxaRh5RdhD8PY8tYWrm25BkCpV0vRY1EP3Kq6mTgyIYQQOUkSOZH1AgLU9nB79qjrEyeqMzfIIL+ZpigKF1de5J93/yE6OBpzK3NaTWlF0/FNMTOX9oZCCFHQSCInstbx49C3L9y5o/ZGXbwYevUydVT5QkRABFvf3sqVdVcAcK/njudiT4rWKGriyIQQQpiKJHK53OkffsDBxkZdSdj7MFFPRKO11I5L676UrpfSNRRF7dSwc6c6d2rVqmj69FFnb/jll1SvmVpMKR6X1uul514JTzE3R2Nmpi7xz5N71GhS3G/2/JHn1zGzsMDM0hIzKyvMLC0xf/7cPME2M4vk/0te/+c6G0dsJOJxBGYWZrw26TWaT2iOuaWUcgohREGmURRFMXUQIqnQ0FCcnZ2ZX7UqdlIlWWBozMxeJHpWVmgsLIkJiSPqWRyKYoG5rS3F65TCvpgLFra2mNvaYhG/2NlhYWOTdJud3Yvnz7enlDAKIYTInPjv75CQEJycsn8+a/k0z+WqjxiBg60tRvl2Krl3iscleJ4kd0/heqnd07Dv6VPYsgWCgtQSrhYtoG5d9ZikF3x5PKnEpqSwPV3XS+41JBObXq9H0elAr0d5/lzR69E/f4xfT7hfn2B74v16nU49Ji4OfVwcuthY9LGx6OPijGPS69FFR6OLjibhHmubF8+Dzt4nKMVXlTZmVlZY2tlhbmub7KNR8pc4EUzwaG5lpZZAWlioJZDm5phZWCRZT7ZUNIXS0eT2y1h4QgiRPCmRy6VyOqPPkNWr1am2IiKgRAl1vXlzU0eVpyiKYkju4pe4yGhO/H6Ek78fQ9FrsS9iQ/MvXqVINRd00dFoo6LUJTLS8Dzxdl3880THKjqdqV9y1kkmuUs24UvjthRTxbSen9X3TmNTh5y8d6buk9Zk3IT3TtJEIplmE2ZmZmgsLFJsbmGW3DZLS0Mpe/zzhItR84pkjjW3ssLM2lotcbexUUvjbWwwk9qaXElK5ETuFxsL48fD7NnqeuvWsHIlFCtm2rjyII1Gg7mVFeZWVgA8vfmU9W/4cu/IPcAJj34edJnTBdtCtpm+l6Io6GNjXyR2kZHEPU/64uKTwpQeE5yTcJ8+Lg69VquWNup0KFoteq021ZLQLJPMPTLzu1R+0Yq8xszK6kVzikRJnsXzbRZ2dljY22Pp4ICVgwOW8Yuj44vnz/eZ29pK6XceJImcSJ+7d6FfPzh6VF2fMAGmTAFpc5UpiqJwduFZtn+wndjwWKydrOn8e2dqDq6ZZR+sGo0Gc2trzK2tsc7m8fwUvf5FgpcwsUutij+57WltHpD42NRiS8+5aU0Ws/reafnbpHJssmen9dx0/C3y272VhE0pEjWTMPxYSbxdq03a/CLhMc//DxiaVcSXvj9vWmHU3CK19ZgYtNHR6KKiDDHrY2OJjY2F0NDk/27ppDE3x9LBAWsXF6xcXLB2ccHG1dXw3NrFBWtXV8NzGzc3rJydJfkzMfn2FWnn6wuDB6vzprq4wNKl0LWrqaPK8yKDItk8ejP/rf8PUKfY8lzimacnuteYmRlKGYUQWUdRFHQxMYbmFLroaEOCp42KevH8eVtbbWQkceHhxIaHE5dwCQsjLiJCfQwPNySesSEhxIaEqFMqpoGZpSU2bm7YFi2KbZEi2CZ8/nyxK15cEr5sJImceDmtFry8YPp09ZdsvXrw999QvrypI8vzbu+/jc9gH0LvhWJmaUabaW1o8kkTGdxXCJEsjUajVpna2GRZybqiKOiiotRkLzSUmJAQYoKDiXn2zPAY++wZ0cHBxD7fFx0cTFxoKPq4OCIfPiTy4cNU72FhZ4d9iRLYlyyJvbs79iVL4lCyJHbu7jiULIl1oUKS6GWQJHIidffuwcCBcPCguj5mDPz8M9jYpHqaSJ1eq2f/tP3sn7ofRa9QuEpheq/sjXs9d1OHJoQoYDQajaGHOkXTPsC4LjaW6MBAogICiHryRH0MCCAqMNBoPebpU7SRkYTcuEHIjRvJXsvC3h6ncuVwLFdOfSxb1rBuaW+fVS81X5Jeq7lUrui1unUrDB2qDi3i6Ajz56tTb4lMCbkTgs8QH+4cuANAnWF16DS7E1YOUhUphMh/dDExRDx8SMT9+0Q8ePBiuX+f8AcPiHryJNV2prZFiuBYrhwulSurS9WqOFeqlGsTvJz+/pZELpcyaSIXGwtffgk//qiu16+vDi1SsWLOxpEPXVl/hU0jNxEdHI2VoxVd53al5qCapg5LCCFMRhcbS/jdu4Tdvk2on5/66O9PmL8/0UEpj5ppX6oUrlWq4Fy5Mq5Vq+Lyyis4lilj8ipaSeTyAB8fH+bMmcOpU6cIDg7Gz8+PcuXKJTlu1qxZ/PTTTwQGBtKkSRPmzp1LlSpV0nQPkyVyfn4wYIA6ZyrABx/A99+DtXXOxZAPxUXF4fuJLyfnnASgRMMS9F7Zm0IVC5k4MiGEyL1iQ0MJu32bkFu3CLl+nWfXrvHs2jWiAgKSPd7SyYnCHh4Uer4UrlEDO3f3HE3uJJHLA5YuXYqfnx9FihRh3LhxySZyK1asYOTIkfz111/UqlULLy8vzpw5w5UrV7BOQ1JkkkTOxwdGjICQELVX6sKF4OmZM/fOxwKuBPB3v795cvEJAE0/a8r/27vzuKrq/PHjrwuXy74paLgAiuaCSxC4hIrmhlamVqTSTFg6Ns6vxsweLWrUmFlj21SPmSYtdIZIraEx8+uaQJJr7vsWizsiAgKyXPj8/rhyR2QR4cK9F97Px+M87r2fc+457/P26nl7ls/nwQUPYquTzjyFEKI+iq5dI/fkSXJuFnfXTpwg5+RJyktKqixr36oVrXv1onWfPngHBeHVp4/hfsBGIoWcFTl+/Dg9evSotpALDQ1lyJAhfHDz8uT169dp06YNy5cvJzIy8o7rbtIfQlERvPwyfPaZ4fPAgYYOfv38Gne7LcDBrw/y4x9+pLSwFOe2zkz41wQCRsklaiGEMLXy0lJyTp8m+/Bhrh4+TPaRI+ScOoXS6ystp7G1xbN7d7yDgvAODsYrKAinu3jI406kkKtBXFwcW7duZc+ePRw6dIiSkhJiY2OJjo6u8Tu7d+8mJiaG7du3U1JSQmBgILNmzWLKlCkmiammQq6kpAQnJydWr17NQw89ZGwfOnQowcHBfPjhh3dcd5P9EE6dMjzAsG+f4fMrr8CCBWBn13jbbAH0RXrWv7iePZ/vAaDT8E5M/HoiLm1dzByZEEK0HPqiInJOnuTqoUNk7dvHlX37KLx0qcpyzu3b4x0cTNvQUNr264dzhw71vhwrQ3TVYN68eaSnp+Pl5YWPjw/pd+isMCkpidGjR6PT6Zg0aRLu7u4kJCQQFRVFWloar7/+eqPFmpWVRVlZGW1uq/DbtGnD5cuXG227dy0+3tCdSH4+eHkZOviNiDB3VFbvWuo1vn38Wy7uvQgaGDJvCOEx4dI3nBBCNDGtgwNeffrg1acP3aKiACi4cIErN4u6rH37yDl50vBE7fnzpK1ZA4CTjw9t+/Wjbf/+hsLOx3K7hrKaQm7p0qV07doVPz8/3n33XV577bUal9Xr9UybNg2NRsPPP/9MUFAQADExMQwcOJCYmBieeOIJunbtChiKxIULF9a6fSs5cVk3BQWGhxi+/NLwecgQQ1HXvr1542oGTvxwgv8+/V+KcopwbO3IxLiJdInoYu6whBBC3OTcrh3O7drhf/OKWWl+PlkHDpC5Zw+Zu3aRdegQhRcvkrp6NamrVwPg0rFjpcLO0dvbnLtQidUUciNGjKjzslu2bOHMmTNMnTrVWMQBuLq6Mn/+fCZNmkRsbCzvvPMOAHPmzGHatGkmi9XLywtbW1syMzMrtWdmZhIcHGyy7dTL3r2GDn5PngSNBubPN0wyVmqDlOvL+WnuT2z76zYAOgzowOOrHse9o7uZIxNCCFEbOxcXfMLC8AkLA6C0oIAr+/aRuWsXl3ftIvvIEfLPniX/7FnO/Oc/ALh17sw9AwbQdsAA2oaGojNXf69YUSF3N5KSkgAYNWpUlXkVbcnJycY2Dw8PPEw4iLhOpyMoKIjExETjPXL5+fns3LmTmTNnmmw7d6W83DAiw6uvQmmp4exbXBwMHWqeeJqR/Mv5fBf5Hek/Gy7395/Vn5HvjZSnUoUQwgrZOTvTbtAg2g0aBBjO2GXu2cPlXbu4vHMn144fJ++338j77TdOxsejsbHBs2dP7hkwgHsGDEDXxH2uNstC7tSpUwDGS6e38vT0xMvLy7hMfWRnZ5ORkUFaWhoAR48eJScnB19fX1q1MvQLNmvWLKZPn05ISAi9evXirbfewsfHh3HjxlW7zuLiYoqLi42f8/Ly6h1fFZcvG0Zo2LDB8Hn8eFi6FFq3Nt02Wqjzu8+zauIq8s7loXPV8Wjso/R8rKe5wxJCCGEidi4utA8Pp314OADFOTlk/vorl7Zv5/LOneSlppJ9+DDZhw9zdOlSimyb9j/xzbKQy83NBcDdvfrLWm5ubpw7d67e6//hhx+YOnWq8XPFWbdbn6KNiooiMzOTOXPmGDsEXrduHQ41jFG6aNEi3nrrrXrHVKP16w1FXGamYXzUjz+GP/zBcFlVNMj+5fv5ccaPlBWX0bpbayatnoRXNy9zhyWEEKIR2Xt40HHECDrevOWr8NIlLu3cyaUdO7i8YweFFy82aTxW0/3IrSoedqip+5FRo0axadMmTp06RZcuVW80DwgI4Ny5c5XOgJlbdWfkOnbsWP/Hl4uLDZdRP/7Y8Ll3b1ixAnrK2aKGKistY+Ocjez6xDD6xb2P3MuEf0/Awb36Il0IIUTLoJTi3MGD+N53n3Q/0hAVZ+IqzszdrqKPF0tib29fpxEf6uT4ccMDDfv3Gz6/8IJhmK0azgaKuivILODbyG9JTzbcDxceE074G+FobOQMpxBCtHQajQb3Tp2adJvNsmOrinvjqrsP7tq1a2RlZVV7/5zVU8pw79v99xuKOC8v+PFH+NvfpIgzgYt7L/JFyBekJ6ejc9Hx5PdPMvTNoVLECSGEMJtmWciF37whcePGjVXmVbRVLNNsXLsGkZEwfToUFsKIEXDwINwysoSov2MJx/hq0Ffknc2jVddWTNs5je7ju5s7LCGEEC1csyzkhg8fTufOnYmPj2d/xeVFDOOdLliwAK1WW+vQXlZn61bo2xe++87QH9xf/2p4QtWCe6K2FkopUt5NYdVjq9Df0BMwOoDpu6bj3dNyOoMUQgjRclnNPXJLly4lJSUFgEOHDhnbKvqMGz9+POPHjwdAq9WydOlSRo8ezeDBg5k8eTJubm4kJCSQmprK22+/zb333muO3TAtvR7+8hdYuNDQT1zXroYRGkJCzB1Zs1BWUsaPz/3I/tj9AIT+v1AiPorARtss//8jhBDCCllNIZeSksLy5csrtf3yyy/88ssvAPj7+xsLOYBhw4aRkpJCTEwMq1atoqSkhMDAQBYsWEDUzfHWrFpaGkRFwTbDSAJER8Onn4KLDMpuCoVXC1k1cRXpP6ejsdEQ8bcI+v2/fuYOSwghhKjEKrsfaQkqnqyt9vHllSsNg93n5oKbG/zznzBpknkCbYayTmTxzcPfkH06G52rjidWPSHjpQohhKiTWo/fjcBqzsgJID8fnn8eli0zfB440HAp1d/fnFE1K6mJqayauIqinCI8/D2YvGYybXq1MXdYQgghRLWkkLMWe/YY+oY7dQpsbGDuXHjjDRns3oQOfn2Q1dGrKdeX02FgByb9dxLObZzNHZYQQghRI6kCLF15Obz/Prz+umGw+w4d4OuvYciQahfPK84j9Voqlwsuk1WYxZWCK2QVZpFTlMMN/Q3DVGp4LdIXoS/Xo5SiXJVTrspRGN5XtCkUt19919wc3kuDpk5tt7bXta0+26n3thXkpueSfTIbzZMa3H3caXdfO9YmrsXWxhYbjQ22mpuvt3/W2N55GRtbdLY642Rva1/pc6V52qrzHLWOONk54axzxs7GrtJ+CCGEaNmkkLN0EydCYuL/3i9ZAq1akX0jm/2X9rPv4j72X97PyasnOZN9hqs3rpo3Xmt2y21we07vMV8ctbDV2OKsc8bJzslQ3Nk5G4u829tcdC442znjrHM2vnfRueCsc670vmKek52TFIlCCGFl5GEHC2W8WRJwc3Tk8ocLSB7UgaT0ZJLSkjiWdazG77Z2bI2Pqw/eTt54O3vj7eSNh4MHTnZOOGodcbRzxFHriIPWAa2NFhuNDRqNBhuNjeE9mkptt57pUhh+Lrf+bGpru7W9rm312U59tq0v1bPnn3s4u/0sSqPoNbkXnSM6U1ZeRrkqp0zdfK3mc23zKj7f+r60rJTismJKykqqTDW264spLivmRukNylRZNX/Spnd74VelCKyhMHTUOqK10aK10WJrY2t41djW2HbrWUtbG9tKZy9vf1/TslJ0CiEsUVM/7CCFnIWq+CHMndCG9UO92XPtSJVlOnt2JuieIO675z56evckwDOATp6dcLNv/B+OtSvOK2blhJWkbknFxs6GR2MfpU9UH3OHVaOSshIKSwspLC2koKTA8FpaUGNbQUkBBaUF5JfkU1BaQEHJ/97nl+RXml9YWmju3asXDZo7FoQV87U2Wuxt7bHX2mNva4+D1sH4/tZXJ63hTKaLzgVXe1fDq8610ueKtlaOrbDXmmh8ZCFEsyFPrYpKFnbLhGuZaNDQ956+DPUbSrh/OIN9B9PaqbW5w7NK1y9eJ35sPJf2X0LnoiMyIZKAkQHmDqtWFffLeTh4mHzd5aq8avF32/saC8KbbYWlhcazkPpyPWXK8Kov11fbduuZzdvPYlac3bwThUJfrjd5Pu6Gq84VLycvvJy88Hb2Nrx39OIel3vwdfc1Tj6uPthopCNpIYTpSSFn4UZ3Gc0TQU/wSLdHaOMs3WA0VNaJLL6O+JqctByc2zoT9X9R+AS37KHMbDQ2xjNNlqS6S9W3X96u6VL27cuWlpcaL1XX9FqkL+JG6Q3yS/K5XnK90mt+ST7Xi295X3KdclXO9ZLrXC+5TmpOaq37YmdjRwe3Dvi6+9LJsxM9vHrQ07snPbx64O/hj62NbRNlVQjR3MilVQvV1KdmW4JzO88R/1A8N67eoFWXVjy14Sk8O3uaOyxhhZRS5BTlkFWYZXg6vPDK/94XXOFi/kXSc9PJyM3gfN75Wu9xdNA60LdtX/q170f/9v3p174fXVp1kXsAhbBSco+cAKSQM7WTa0/yXeR3lBaW0i60HVN+nCJ9xIkmoS/Xc+H6BTJyM8jIzeB09mmOZR3j6JWjnMg6QXFZcZXveDp4MrDjQIb5D+Ohrg/R3au7FHZCWAkp5AQghZwp7Yvdx5rpa1Blii4RXXji2yfQuejMHZYQlJWX8du13/j1wq/sOr+Lned3svfi3irFXZdWXRh37zjGdRtHmG8YWhu5K0YISyWFnACkkDMFpRRb39lK4jxDP3x9n+7LI0sewdZO7kcSlqu0rJSDlw+yNWMrG89s5KfUnygpKzHO93TwZGKPiTwT9AwDOwyUM3VCWBgp5AQghVxDlZeVs+6Fdfz6918BGPTaIB5c+KAc9ITVyS/JZ+OZjfxw4gd+PPljpU6/u3t159mgZ3k26Fk8HeV+TyEsgRRyApBCriH0RXoSohI4lnAMNBDxtwj6P9/f3GEJ0WBl5WWkZKSw7MAyVh1ZZewD0NnOmenB03lx4Iv4uvuaOUohWjYp5AQghVx93bh2g5XjV5L+czq2OlsmxE0g8IlAc4clhMnlFeex4vAKPtv1GYcyDwGgtdEyLWga88Pn0861nZkjFKJlkkJOAFLI1UfeuTziIuK4cuQK9m72TFo9Cf+h/uYOS4hGpZRiw5kNLN62mC2pWwBw1Doye+BsXh/8Ok52TmaOUIiWRQo5AUghd7euHL1C3Og48s7l4drOlah1UbTt09bcYQnRpH5O/5nXfnqNbWe3AeDv4c+nYz7l4XsfNnNkQrQcTX38ljFjhNXL+CWDrwZ9Rd65PLy6e/HMtmekiBMt0hC/IaRMTeH7J7/H192XtJw0HvnmESaunEhmQaa5wxNCNAIp5IRVO/7f4/x7xL8pulZEh4EdmJoyFQ8/D3OHJYTZaDQaxncfz9GZR3kl7BW0Nlq+P/49ff7Rh3Wn1pk7PCGEiUkhJ6zWr5//yqrHVqEv0tNtXDd+v/n3OLWW+4GEAHDWOfPuiHfZ84c99GrTi8sFlxkbP5bZG2ajL9ebOzwhhIlIISesjlKKxJhE1v5xLapcETw9mMj/RGLnZGfu0ISwOH3a9mHXtF280O8FAD7a8RGj40aTVZhl5siEEKYghZywKuX6ctb8YQ0//+VnAMJjwnn4nw9jo5WfshA1cbRz5G9j/kZCZAIuOhe2pG4hdEkoJ7JOmDs0IUQDydFPWI3SwlJWTlzJvqX70NhoeOjzhxj65lAZrUGIOprQYwI7nt1BgGcAaTlpDIodxJ4Le8wdlhCiAaSQE1ah8Goh/xr+L06uOYnWQUtkQiQhM0LMHZYQViewTSDbn93O/T73k1WYxdDlQ0lMTTR3WEKIepJCTli8nPQcvgr7inM7zuHg6cDvNv+O7o92N3dYQlgtb2dvtjy9hWH+w8gvySfi6wg2nN5g7rCEEPUghZywaJcPXubLgV9y9cRV3Dq68UzKM/iGyViSQjSUm70b/xf1f4zvPp6SshImrJxASkaKucMSQtwlKeSExUpLSiN2cCz5F/Np06sNz257Fu+e3uYOS4hmw0HrwMrHVzKmyxhu6G/wUPxDcs+cEFZGCjlhkY6sOkLc6DiK84rxG+LH1K1TcesgQ5UJYWo6Wx3/ifwP4X7h5BXnEfF1BKnXUs0dlhCijqSQExZn56c7+W7Sd5SVlNHjsR48teEpHDwczB2WEM2Wo50jayavIdgnmKzCLB7+5mFyi3LNHZYQog6kkBMWQynF5tc2s/6F9aAg9E+hPL7ycbQOWnOHJkSz52rvyg+TfqCdazuOXjnKk989KSNACGEFpJATFqGstIzV0av55d1fAHhw4YOM+XQMNrbyExWiqbR3a8+ayWtwsnNiw5kNvJn0prlDEkLcgRwlhdmV5JfwzSPfcOBfB9DYang09lEGvz5YOvoVwgyCfYL5ctyXALyz9R3plkQICyeFnDCrgswClg9bzpkNZ7BzsmPyD5O5L/o+c4clRIs2qdcknrv/ORSKp75/inN558wdkhCiBlLICbPJPpPNV2FfceHXCzi2duT3W35P17FdzR2WEAL4KOIjgu4JIqswi8n/mUxZeZm5QxJCVEMKOWEWF/Zc4KsHviL7dDYe/h48u+1ZOvTvYO6whBA3OWgdWPXEKlx1rqRkpPDxjo/NHZIQohpSyIkmd2bTGZYPXU5BZgH33HcPz25/ltb3tjZ3WEKI23Rp1YUPRn0AwLzEeZzIOmHmiIQQt5NCTjSpg18fJH5sPCX5JXQa3ono5Ghc7nExd1hCiBpMC57GqIBRFOmLmLp6qlxiFcLCSCEnmoRSim3vb+P7p76nXF9Or8m9iPq/KOzd7M0dmhCiFhqNhiWPLMFV58r2c9v5aMdH5g5JCHELKeREo1Plio0vbWTTy5sAGDB7ABPjJmKrszVzZEKIuvB19+XD0R8C8EbiG6TnpJs5IiFEBSnkRKPSF+tJiEpgx0c7ABj5/khGfzAajY30ESeENXk26FnC/cK5ob/BixteNHc4QoibpJCrh4SEBEaOHEmrVq3QaDSkpaVVWWbRokWEhITg6upK27ZtiYyMrHa55qw4r5j4sfEcXnEYGzsbJsRN4IGXHjB3WEKIetBoNHw29jNsNbZ8f/x76ShYCAshhVw9FBQUMHjwYBYuXFjjMsnJyTz//PPs3LmT9evXk5OTw5gxY9DrW8bYhfmX8lkWvozULanoXHRMWTuFPlF9zB2WEKIBerXpxfP9ngfghfUvUKwvNnNEQgiNUkqZOwhrdfz4cXr06EFqair+/v61Lnv27Fl8fX05cOAAffrcuaDJy8vD3d2d3Nxc3NzcTBRx08g+k03cqDiu/XYN5zbORK2LwifYx9xhCSFMILcol26fdeNywWUWj1zMnAfmmDskISxKUx+/reaMXFxcHDNmzCAkJAR7e3s0Gg3Lli2r9Tu7d+9m7NixeHp64uzsTL9+/YiPj2+agG+Tm5sLQKtWrcyy/aZy6cAlvgr7imu/XcOzsyfPbHtGijghmhF3B3cWDV8EGMZizSnKMW9AQrRwVlPIzZs3jy+++IL09HR8fO5cGCQlJTFo0CC2bt3K448/zh//+EeysrKIiorinXfeaYKI/6e8vJyXXnqJsWPH0qFD8x29IH1rOsvCl1FwuYC2fdvyzC/P0CqgeReuQrREv+/7ewK9A7lWdI33Ut4zdzhCtGhWU8gtXbqUtLQ0rly5wnPPPVfrsnq9nmnTpqHRaPj5559ZsmQJ77//PgcOHCAwMJCYmBhOnTplXH7evHloNJpap/pSSjFjxgxSU1PveAbRmp1Yc4K4UXEU5xbjO9iX6CTp6FeI5srWxtZ4Vu7jnR9zPu+8mSMSouWymkJuxIgR+Pn51WnZLVu2cObMGaZMmUJQUJCx3dXVlfnz56PX64mNjTW2z5kzh9TU1Fqn+lBKMXPmTDZv3sxPP/2Et7d3vdZj6fYv28/KCSvRF+npNq4bT214CgcPB3OHJYRoRA/f+zBhHcMo0hfxVvJb5g5HiBZLa+4AGkNSUhIAo0aNqjKvoi05OdnY5uHhgYeHh0ljUErxpz/9ibVr15KcnEzHjh1Nun5Lse2DbWyaY+jo977o+3hkySPYaK3m/wdCiHrSaDS8N+I9BsUO4st9XzJ74Gy6e3U3d1hCtDjNspCruGzatWvXKvM8PT3x8vKqdGn1bmVnZ5ORkWHsF+7o0aPk5OTg6+trfJhh5syZrFixgjVr1uDo6MilS5cAw8MOOp2uyjqLi4spLv7fo/wVD0fk5eXVO87GpJQi5d0UUt5NAaDf8/0YumAo+YX5Zo5MCNFUenv0ZkzHMaw7tY43N7zJF498Ye6QhDC7iuN2k3UKoqzQokWLFKBiY2OrnT9y5EgFqFOnTlU7v3Pnzkqn09V7+7GxsQqoMt0aT3XzAZWYmFjtOmNiYmr8jkwyySSTTDLJZF3TmTNn6l1n3I1meUausUVHRxMdHV3rMuouK/HXXnuN2bNnGz/n5OTg5+dHRkYG7u7u9QlT3JSXl0fHjh05e/as1fXJZ0kkj6YjuTQdyaVpSB5NJzc3t9IVusbWLAu5isKn4vLk7So667Mk9vb22NvbV2l3d3eXv1Qm4ubmJrk0Acmj6UguTUdyaRqSR9OxsWma+8Wb5V3pFffGVXcf3LVr18jKyqr2/jkhhBBCCGvSLAu58PBwADZu3FhlXkVbxTJCCCGEENaqWRZyw4cPp3PnzsTHx7N//35j+/Xr11mwYAFarfaO97iZm729PTExMdVebhV3R3JpGpJH05Fcmo7k0jQkj6bT1LnUqLu9K99Mli5dSkqKoauLQ4cOsXfvXsLCwujSpQsA48ePZ/z48cblExMTGT16NPb29kyePBk3NzcSEhJITU3l7bffZu7cuebYDSGEEEIIk7GaQi46Oprly5fXOD8mJoY333yzUtuuXbuIiYlh+/btlJSUEBgYyKxZs4iKimrkaIUQQgghGp/VFHJCCCGEEKKyZnmPnBBCCCFESyCFXDORkJDAyJEjadWqFRqNxjh82K0WLVpESEgIrq6utG3blsjIyGqXa8nqkkeAjz76iI4dO+Lo6MiDDz7IyZMnmzZQK3T9+nWee+452rVrh7OzM0FBQXz33XfmDstqZWRkEBkZiaenJ87OzoSGhnL+/Hlzh2XV/vjHP6LRaPjss8/MHYrVkeNL/ZjiWCKFXDNRUFDA4MGDWbhwYY3LJCcn8/zzz7Nz507Wr19PTk4OY8aMQa/XN2Gklq0ueYyPj+f111/nvffeY/fu3Xh6ehIREVFprFxR1YsvvkhSUhKrVq3i0KFDREZGMmnSJA4ePGju0KzO1atXGTRoEB4eHmzevJmDBw8yf/58eeKwAX788Ue2b99Ou3btzB2KVZLjy90z2bGkSQYCE03m2LFjClCpqal3XDYjI0MB6sCBA40fmJWpLY8hISFq9uzZxs95eXnKwcFBrVy5sgkjtD6BgYFq0aJFldpatWpV45jJomYvv/yyGjJkiLnDaDYuXbqkOnTooA4ePKj8/PzUp59+au6QrJ4cX+7MVMcSOSPXAHFxccyYMYOQkBDs7e3RaDQsW7as1u/s3r2bsWPHGi+H9OvXj/j4+KYJ+DYVQ5g11XhwNbGmPJaUlLBv3z4efPBBY5urqyv9+/dnx44djb79u2VJuX3ggQdYvXo1ly5dQinFt99+S3FxsdV0zm1JuVyzZg3BwcE89thjtGnThtDQUBISEhq83qZiSbkEmDp1Ki+88AK9e/c2yfqaiqXl8VaWcnxpqMbKsUmPJSYuMFsUPz8/BSgvLy/j+9rOLiQmJiqdTqdcXFzUtGnT1EsvvaQ6deqkALVw4UKTxFTXM3JlZWVq1KhRauzYsSbZbkNYUx7Pnz+vALVr165K7U888YSaMmWKSbZtSpaU2xs3bqjJkycrQGm1WuXq6qo2bNjQoHU2JUvKpb29vdLpdGr+/Plq7969avHixcrGxkYlJyc3aL1NxZJy+emnn6rBgwersrIyY2zWckbOkvJ4K0s6vjRUY+XYlMcSKeQaYNOmTSotLU0ppdSiRYtq/QMuLS1VAQEByt7eXu3du9fYnpeXpwIDA5VWq1UnT540ts+dO1cBtU7VqUshV15erqZNm6a6du2qMjMz737HTcya8mhthZwl5fbdd99VgYGBat26dWr//v1qwYIFysPDQx05csT0O94ILCmXdnZ2KiwsrFLbuHHjVFRUlIn2tnFZSi6PHTum2rRpU+nvuTUVcpaSx1tZ2vGloRorx6Y8lsil1QYYMWIEfn5+dVp2y5YtnDlzhilTphAUFGRsd3V1Zf78+ej1emJjY43tc+bMITU1tdapPpRSzJw5k82bN/PTTz/h7e1dr/WYkjXl0cvLC1tbWzIzMyu1Z2Zm0rZt27taV1OwlNzeuHGD+fPn8+GHHxIREUHfvn2ZN28eISEh/P3vfzfdDjciS8klwD333EP37t0rtfXo0YOMjIwG7GHTsZRc7tixgytXrtClSxe0Wi1arZb09HT+/Oc/c99995lsfxuLpeSxgiUeXxqqsXJsymOJ9q6WFvWWlJQEwKhRo6rMq2hLTk42tnl4eODh4WHSGJRS/OlPf2Lt2rUkJyfTsWNHk66/KZg7jzqdjqCgIBITE3nooYcAyM/PZ+fOncycOdNk2zGHxsxtaWkppaWl2NraVmq3tbWlvLy8fgFbsMb+nT7wwAOcOnWqUtvJkyfrfMCxJo2Zy/HjxxMSElKpbfTo0URHRzN16tT6BWyhGvs32RyOLw11Nzk25bFECrkmUvGPbteuXavM8/T0xMvLq8o/zHcjOzubjIwMY789R48eJScnB19fX+PNpjNnzmTFihWsWbMGR0dHLl26BBhuRtXpdPXedlOyhDzOmjWL6dOnExISQq9evXjrrbfw8fFh3Lhx9d6uJWjM3Lq5uTF48GBefvllPv30U3x8fPjhhx/YtGkTa9eubVDclqixf6cvvvgiYWFhLF68mAkTJrB582bWrFljPJA0J42Zy+qKFTs7O3x8fIzjeDcXjf2bbA7Hl4a62xyb6lgihVwTqXiCx93dvdr5bm5unDt3rt7r/+GHHyr9D7Kiwo+NjSU6OhqAzz//HIDBgwdX+m5iYiJDhw6t97abkiXkMSoqiszMTObMmUNWVhYDBw5k3bp1ODg41Hu7lqCxc7tixQpeeeUVHn/8cXJzc+nSpQvLli0jIiKi3uu0VI2dy/79+/Ptt98yd+5c3njjDe69916+/fZbwsLC6r1OS9XYuWwpGjuPzeH40lB3m2NTHUukkGsmoqOjjYVGTZQMq3tHdckjGM6IvPjii40fUDPSrl07/v3vf5s7jGZjwoQJTJgwwdxhNDsyGkH9yPGlfkxxLJGHHZpIRYVeUbHfLi8vr8YqXvyP5LHxSG5NR3JpOpJL05A8Nj5z5VgKuSZScc28unsQrl27RlZWVrXX1UVlksfGI7k1Hcml6UguTUPy2PjMlWMp5JpIRe/1GzdurDKvos1aerg3J8lj45Hcmo7k0nQkl6YheWx85sqxFHJNZPjw4XTu3Jn4+Hj2799vbL9+/ToLFixAq9XW6d6slk7y2Hgkt6YjuTQdyaVpSB4bn7lyrFFyh2K9LV26lJSUFAAOHTrE3r17CQsLMz62Pn78eMaPH29cPjExkdGjR2Nvb8/kyZNxc3MjISGB1NRU3n77bebOnWuO3TA7yWPjkdyajuTSdCSXpiF5bHxWkeO7GgdCVPL000/XOnxJTExMle/s3LlTRUREKHd3d+Xo6KhCQkJUXFxc0wdvQSSPjUdyazqSS9ORXJqG5LHxWUOO5YycEEIIIYSVknvkhBBCCCGslBRyQgghhBBWSgo5IYQQQggrJYWcEEIIIYSVkkJOCCGEEMJKSSEnhBBCCGGlpJATQgghhLBSUsgJIYQQQlgpKeSEEEIIIayUFHJCCKs0dOhQNBoNSUlJ5g6lXtLS0tBoNPj7+5s7FCGEFZNCTghhNhqN5q6noUOHmjtsIYSwGFpzByCEaLnCwsKqtOXm5nL48OEa5/fu3RsAX19funXrhpOTU+MG2Ujs7Ozo1q0b7du3N3coQggrplFKKXMHIYQQFZKSkhg2bBgA8s+TEELUTi6tCiGEEEJYKSnkhBBWqaaHHaKjo9FoNCxbtoz09HSeeuop2rZti4uLCwMHDmTTpk3GZQ8dOsRjjz1GmzZtcHJyYsiQIezYsaPGber1ej7//HMGDRqEh4cHDg4OdO/enXnz5pGXl3dX8df2sEPF/YAA69atY8iQIbi6uuLu7s6YMWPYt2/fXW0L4OrVq8yZM4fu3bvj4OCAs7Mz/v7+RERE8Pe//73a72RnZzN37lx69eqFs7Mzrq6uDBgwgCVLllBeXl7jtnbv3s1TTz2Fr68v9vb2tG3blgceeIC//vWv5Obm3nXsQohaKCGEsCCJiYkKUHf65yk8PFwBKjExsVL7008/rQD1xhtvKC8vL+Xs7Kzuv/9+5eXlpQCl1WrVTz/9pLZu3aqcnZ2Vh4eHuv/++5W7u7sClJOTkzp8+HCV7eXm5qohQ4YoQNnY2Cg/Pz/Vq1cvpdPpFKB69OihLl++XOf9TE1NVYDy8/OrMq9i///xj38ojUajfHx8VHBwsHJ2dlaAcnFxUceOHavztnJyclRAQIAClE6nUz179lTBwcGqTZs2SqPRKHd39yrfOXz4sGrfvn2l7wQEBCiNRqMA9fjjj6vy8vIq33vvvfeMy7i5uan7779fBQQEKDs7u2r/vIQQDSOFnBDCopiqkLOzs1OTJk1SeXl5SimlysrK1MyZMxWg+vbtq/z9/dXs2bNVcXGxUkqpoqIi9cgjjyhARUZGVtnepEmTFKCGDx+uzpw5Y2zPzs5WEydONBY3dVWXQs7JyUnFxsYa2/Py8tTw4cMVoJ588sk6b+v9999XgBo1apS6evVqpXnp6enqo48+qtSWn59vLPxeeOEFlZuba5x35MgRFRgYqAD12WefVfref//7XwUoW1tb9cEHH6iSkhLjvIKCAvXFF1+oo0eP1jluIcSdSSEnhLAopirkfHx8VEFBQaV5OTk5ysHBQQEqKCioyhml48ePG88k3erAgQPGoquiMLxVQUGB6tixo9JoNCotLa1O+1mXQu7555+vMu/gwYMKqPYsWk1mzJihALV69eo6Lf/JJ58oQE2YMKHa+QcOHFAajUZ17ty5UnvPnj0VoP7yl7/UOTYhRMPIPXJCiGZp8uTJVbomcXd3p1OnTgBMnTrVeB9ahW7duuHo6EheXh5Xr141tn///fcAREZG4urqWmVbTk5OjBgxAqUUW7duNdk+TJs2rUpb7969cXBwIDc3t1KMtenYsSNg2A+9Xn/H5RMSEmrcPkCfPn3w9/fnt99+49y5cwCcPn2ao0ePotPpmDVrVp3iEkI0nPQjJ4RolgICAqpt9/b25tixY7XOz8jIID8/n9atWwOGhyLAUAht27at2u+lp6cDcP78+YaGblRbjGfPnq0UY22mTp3K4sWLWbZsGevWrSMiIoLBgwczbNgwOnfuXGX5iv194403eOedd6pdZ1ZWFmDY3w4dOnDs2DEAevbsWW2xK4RoHFLICSGapZo6Cq44C3en+eqWPuwqnrQ8ffo0p0+frnW7N27cuOtYa+Ls7Fxtu42N4WKKqmM/e+3atWP79u3Mnz+ftWvXsnz5cpYvXw7AgAED+PDDDxk4cKBx+Yr93bNnzx3XXbG/FU/tenh41CkmIYRpSCEnhBB34OLiAsCSJUtqvNxo6Xr06MF3331HcXEx27dvJzk5mRUrVrBjxw5GjRrFoUOHjF2huLi4kJOTw6lTp+jSpUud1l9xFi4nJ6eR9kAIUR25R04IIe6gZ8+eAMahw6yZvb09Q4cOJSYmhsOHDxMWFkZ+fj7ffPONcZn67G9gYCAAR48e5fr166YNWghRIynkhBDiDiZMmABAXFxcnR8wsAa2traEhoYCcOHCBWP7xIkTAfjkk0/qfPk2ICCAXr16UVJSwieffGL6YIUQ1ZJCTggh7iAkJITIyEiuXr3KyJEjq4ysUFZWRlJSElFRURQXF5spyprNnTuXL7/8ssplz8OHD7Nq1SoAgoODje0zZsygc+fOJCYmEhUVxcWLFyt9Lz8/n1WrVjF79uxK7W+//TYAb775Jp988gmlpaXGeYWFhSxdutT4UIQQwjSkkBNCiDr48ssvjUVccHAwfn5+DBgwgD59+uDq6sqwYcOIj4+v8xmspnTkyBGmTZtG69at6dq1K/3796dr16707t2bCxcuMGzYMH73u98Zl3dxcWHt2rV06tSJb775hg4dOtCzZ08GDBhAt27d8PDw4Mknn6zyBO+jjz7KokWLKCsr489//jPe3t6EhoZy77334uHhwfTp07l8+XJT774QzZoUckIIUQcuLi6sX7+er7/+mtGjR1NYWMjevXvJysqiT58+vPLKK+zatQsHBwdzh1rFvHnzePXVVwkNDSU/P5/9+/dz48YNwsPD+de//sXGjRvRais/+9a9e3cOHDjAu+++S2hoKOfPn2f//v2UlJQQHh7O+++/z4oVK6ps69VXX2Xbtm1ERkbi5OTEgQMHyMvLIzQ0lMWLF1c68yeEaDiNssT/PgohhBBCiDuSM3JCCCGEEFZKCjkhhBBCCCslhZwQQgghhJWSQk4IIYQQwkpJISeEEEIIYaWkkBNCCCGEsFJSyAkhhBBCWCkp5IQQQgghrJQUckIIIYQQVkoKOSGEEEIIKyWFnBBCCCGElZJCTgghhBDCSkkhJ4QQQghhpaSQE0IIIYSwUv8fF/O6sc8PpLQAAAAASUVORK5CYII=", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys3.sims[1], 1e-12, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1)\n", - "ylim(1e-12, 5)\n", - "title(\"Ag111@-2.0 V\", fontsize=16, fontweight=\"bold\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 135, - "id": "a5b06177", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys4.sims[1], 1e-12, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1)\n", - "ylim(1e-12, 5)\n", - "title(\"Cu111@-1.5 V\", fontsize=16, fontweight=\"bold\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 136, - "id": "a15be1a0", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys5.sims[1], 1e-12, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1)\n", - "ylim(1e-12, 5)\n", - "title(\"Cu111@-1.0 V\", fontsize=16, fontweight=\"bold\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 137, - "id": "076638f2", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys6.sims[1], 1e-12, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1)\n", - "ylim(1e-12, 5)\n", - "title(\"Cu111@-2.0 V\", fontsize=16, fontweight=\"bold\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 109, - "id": "87dcaf99", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys1.sims[2], 0.1, 1, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1)\n", - "ylim(1e-12, 5)\n", - "title(\"Solid-phase Mole Fractions on Ag111@-1.5 V\", fontsize=16, fontweight=\"bold\")\n", - "legend(loc=\"lower left\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 110, - "id": "4dfc055c", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Dict{String, Float64} with 17 entries:\n", - " \"O=CC=O\" => 3.45197e-29\n", - " \"proton\" => 2.7869e-5\n", - " \"O=CO\" => 0.646063\n", - " \"Ne\" => 0.0\n", - " \"COC=O\" => 1.65034e-15\n", - " \"[O]C=O\" => 2.21457e-42\n", - " \"C=O\" => 1.79e-10\n", - " \"[CH]=O\" => 2.77632e-32\n", - " \"CO2\" => 0.27869\n", - " \"O=[C]O\" => 4.57006e-35\n", - " \"N2\" => 0.0\n", - " \"O=CCO\" => 2.01266e-6\n", - " \"Ar\" => 0.0\n", - " \"H2O\" => 0.0752102\n", - " \"He\" => 0.0\n", - " \"H\" => 5.33777e-37\n", - " \"H2\" => 6.18658e-6" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "Dict([ssys1.sims[1].names[i]=>molefractions(ssys1.sims[1],1)[i] for i in 1:length(ssys1.sims[1].names)])" - ] - }, - { - "cell_type": "code", - "execution_count": 121, - "id": "1f7d8918", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "842×1012 Array{RGBA{N0f8},2} with eltype ColorTypes.RGBA{FixedPointNumbers.N0f8}:\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,1.0) … RGBA{N0f8}(1.0,1.0,1.0,1.0)\n", - " RGBA{N0f8}(1.0,1.0,1.0,0.733) RGBA{N0f8}(1.0,1.0,1.0,0.733)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fd1 = getfluxdiagram(ssys1,1;speciesratetolerance=1e-4)" - ] - }, - { - "cell_type": "code", - "execution_count": 122, - "id": "379c4050", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "1322×1036 Array{RGB{N0f8},2} with eltype ColorTypes.RGB{FixedPointNumbers.N0f8}:\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " ⋮ ⋱ ⋮\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fd3 = getfluxdiagram(ssys3,1;speciesratetolerance=1e-4)" - ] - }, - { - "cell_type": "code", - "execution_count": 123, - "id": "007de25f", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "879×750 Array{RGB{N0f8},2} with eltype ColorTypes.RGB{FixedPointNumbers.N0f8}:\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fd4 = getfluxdiagram(ssys4,1;speciesratetolerance=1e-4)" - ] - }, - { - "cell_type": "code", - "execution_count": 124, - "id": "977f11cd", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "884×750 Array{RGB{N0f8},2} with eltype ColorTypes.RGB{FixedPointNumbers.N0f8}:\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fd5 = getfluxdiagram(ssys5,1;speciesratetolerance=1e-4)" - ] - }, - { - "cell_type": "code", - "execution_count": 125, - "id": "6eaab3dd", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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Dict{String, Vector{Float64}}() # To collect mole fractions for each species\n", - "\n", - "# # Iterate through each solution\n", - "# for (idx, bsol) in enumerate(solutions)\n", - "# # Get mole fractions and species at the specified time\n", - "# mole_fractions = molefractions(bsol, t)\n", - "# species = bsol.domain.phase.species\n", - "\n", - "# # Filter species based on threshold and exclusion list\n", - "# for (i, mf) in enumerate(mole_fractions)\n", - "# species_name = species[i].name\n", - "# if mf > tol && !(species_name in exclude)\n", - "# # Initialize vector for each species if not already present\n", - "# if !haskey(species_dict, species_name)\n", - "# species_dict[species_name] = zeros(length(solutions))\n", - "# end\n", - "# # Assign the mole fraction for the current solution\n", - "# species_dict[species_name][idx] = mf\n", - "# end\n", - "# end\n", - "# end\n", - "\n", - "# # Convert species data to arrays for plotting\n", - "# species_names = collect(keys(species_dict))\n", - "# num_solutions = length(solutions)\n", - "\n", - "# # Sort species for each solution based on mole fractions (descending order)\n", - "# sorted_species = sort(species_names, by=name -> -maximum(species_dict[name]))\n", - "\n", - "# # Plotting each solution individually\n", - "# clf() # Clear the current figure\n", - "# bar_positions = 1:num_solutions\n", - "# width = 0.35 # Width of each bar\n", - "# color_cycle = get_cmap(\"tab20\", length(sorted_species))\n", - "\n", - "# # Initialize bottom values for stacked bars\n", - "# bottoms = zeros(num_solutions)\n", - "\n", - "# # Plot each species, stacking from the highest mole fraction down\n", - "# for (color_idx, species_name) in enumerate(sorted_species)\n", - "# # Get the mole fractions for the current species across solutions\n", - "# current_data = species_dict[species_name]\n", - "\n", - "# # Plot bars for the current species\n", - "# bar(bar_positions, current_data, width, bottom=bottoms, color=color_cycle(color_idx), label=species_name)\n", - "\n", - "# # Update the bottom values for stacking\n", - "# bottoms .+= current_data\n", - "# end\n", - "\n", - "# # Formatting the plot\n", - "# xticks(bar_positions, x_labels)\n", - "# ylabel(\"Mole Fraction\")\n", - "# legend(title=\"Species\", loc=\"upper right\", bbox_to_anchor=(1.2, 1))\n", - "# title(\"Liquid Phase Composition at t = $t\")\n", - "# tight_layout() # Adjust layout for better appearance\n", - "# end\n" - ] - }, - { - "cell_type": "code", - "execution_count": 117, - "id": "b1829469", - "metadata": {}, - "outputs": [], - "source": [ - "# sims_collection = [ssys1.sims[1], ssys2.sims[1], ssys3.sims[1]]\n", - "# x_labels = [\"Ag111@-2.0V\", \"Ag111@-1.5V\", \"Ag111@-1.0V\"]\n", - "# plot_composition_comparison(sims_collection, 1e-3, 1e-3, [\"H2O\"])" - ] - }, - { - "cell_type": "code", - "execution_count": 118, - "id": "51c99d48", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.9.1", - "language": "julia", - "name": "julia-1.9" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.9.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/CO2_Reduction_Ag/CO2RR_RMS_AIChE.jl b/CO2_Reduction_Ag/CO2RR_RMS_AIChE.jl new file mode 100644 index 0000000..61098d9 --- /dev/null +++ b/CO2_Reduction_Ag/CO2RR_RMS_AIChE.jl @@ -0,0 +1,451 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,jl:percent +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.17.2 +# kernelspec: +# display_name: Julia 1.9.1 +# language: julia +# name: julia-1.9 +# --- + +# %% +using DifferentialEquations +using ReactionMechanismSimulator +using PyPlot + +# %% +outdict1 = readinput("chem43_Ag.rms"); +outdict2 = readinput("chem43_Cu.rms") + + +# %% +liqspcs1 = outdict1["gas"]["Species"]; +liqrxns1 = outdict1["gas"]["Reactions"]; +surfspcs1 = outdict1["surface"]["Species"]; +surfrxns1 = outdict1["surface"]["Reactions"]; +interfacerxns1 = outdict1[Set(["surface", "gas"])]["Reactions"]; +solv1 = outdict1["Solvents"][1]; + +# %% +liqspcs2 = outdict2["gas"]["Species"]; +liqrxns2 = outdict2["gas"]["Reactions"]; +surfspcs2 = outdict2["surface"]["Species"]; +surfrxns2 = outdict2["surface"]["Reactions"]; +interfacerxns2 = outdict2[Set(["surface", "gas"])]["Reactions"]; +solv2 = outdict2["Solvents"][1]; + +# %% +sitedensity1 = 2.292e-5; # Ag111 +sitedensity2 = 2.943e-5; # Cu111 +AVratio = 1.0e5 + +# %% +initialcondsliq = Dict(["proton"=>10.0^-4,"CO2"=>10.0^-3*10^3, + "V"=>1.0,"T"=>298.15,"Phi"=>0.0,"d"=>0.0]); +initialcondssurf1 = Dict(["CO2X"=>0.4*sitedensity1*AVratio, + "CHO2X"=>0.1*sitedensity1*AVratio, + "CO2HX"=>0.1*sitedensity1*AVratio, + "OX"=>0.1*sitedensity1*AVratio, + "OCX"=>0.1*sitedensity1*AVratio, + "vacantX"=>0.1*sitedensity1*AVratio, + "CH2O2X"=>0.05*sitedensity1*AVratio, + "CHOX"=>0.04*sitedensity1*AVratio, + "CH2OX"=>0.01*sitedensity1*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-1.5]); +initialcondssurf2 = Dict(["CO2X"=>0.4*sitedensity1*AVratio, + "CHO2X"=>0.1*sitedensity1*AVratio, + "CO2HX"=>0.1*sitedensity1*AVratio, + "OX"=>0.1*sitedensity1*AVratio, + "OCX"=>0.1*sitedensity1*AVratio, + "vacantX"=>0.1*sitedensity1*AVratio, + "CH2O2X"=>0.05*sitedensity1*AVratio, + "CHOX"=>0.04*sitedensity1*AVratio, + "CH2OX"=>0.01*sitedensity1*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-1.0]); +initialcondssurf3 = Dict(["CO2X"=>0.4*sitedensity1*AVratio, + "CHO2X"=>0.1*sitedensity1*AVratio, + "CO2HX"=>0.1*sitedensity1*AVratio, + "OX"=>0.1*sitedensity1*AVratio, + "OCX"=>0.1*sitedensity1*AVratio, + "vacantX"=>0.1*sitedensity1*AVratio, + "CH2O2X"=>0.05*sitedensity1*AVratio, + "CHOX"=>0.04*sitedensity1*AVratio, + "CH2OX"=>0.01*sitedensity1*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-2.0]); +initialcondssurf4 = Dict(["CO2X"=>0.4*sitedensity2*AVratio, + "CHO2X"=>0.1*sitedensity2*AVratio, + "CO2HX"=>0.1*sitedensity2*AVratio, + "OX"=>0.1*sitedensity2*AVratio, + "OCX"=>0.1*sitedensity2*AVratio, + "vacantX"=>0.1*sitedensity2*AVratio, + "CH2O2X"=>0.05*sitedensity2*AVratio, + "CHOX"=>0.04*sitedensity2*AVratio, + "CH2OX"=>0.01*sitedensity2*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-1.5]); +initialcondssurf5 = Dict(["CO2X"=>0.4*sitedensity2*AVratio, + "CHO2X"=>0.1*sitedensity2*AVratio, + "CO2HX"=>0.1*sitedensity2*AVratio, + "OX"=>0.1*sitedensity2*AVratio, + "OCX"=>0.1*sitedensity2*AVratio, + "vacantX"=>0.1*sitedensity2*AVratio, + "CH2O2X"=>0.05*sitedensity2*AVratio, + "CHOX"=>0.04*sitedensity2*AVratio, + "CH2OX"=>0.01*sitedensity2*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-1.0]); +initialcondssurf6 = Dict(["CO2X"=>0.4*sitedensity2*AVratio, + "CHO2X"=>0.1*sitedensity2*AVratio, + "CO2HX"=>0.1*sitedensity2*AVratio, + "OX"=>0.1*sitedensity2*AVratio, + "OCX"=>0.1*sitedensity2*AVratio, + "vacantX"=>0.1*sitedensity2*AVratio, + "CH2O2X"=>0.05*sitedensity2*AVratio, + "CHOX"=>0.04*sitedensity2*AVratio, + "CH2OX"=>0.01*sitedensity2*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>-2.0]); + +# %% +liq1 = IdealDiluteSolution(liqspcs1,liqrxns1,solv1,name="liquid",diffusionlimited=true); + +liq2 = IdealDiluteSolution(liqspcs2,liqrxns2,solv2,name="liquid",diffusionlimited=true); + +surf1 = IdealSurface(surfspcs1,surfrxns1,sitedensity1,name="surface"); + +surf2 = IdealSurface(surfspcs2,surfrxns2,sitedensity2,name="surface"); + +domainliq1,y0liq1,pliq1 = ConstantTVDomain(phase=liq1, + initialconds=initialcondsliq,constantspecies=["proton","CO2"]); + +domainliq2,y0liq2,pliq2 = ConstantTVDomain(phase=liq2, + initialconds=initialcondsliq,constantspecies=["proton","CO2"]); + +# %% +domaincat1,y0cat1,pcat1 = ConstantTAPhiDomain(phase=surf1, + initialconds=initialcondssurf1); + +inter1,pinter1 = ReactiveInternalInterfaceConstantTPhi(domainliq1, + domaincat1,interfacerxns1,298.15,AVratio*1.0); + +# %% +domaincat2,y0cat2,pcat2 = ConstantTAPhiDomain(phase=surf1, + initialconds=initialcondssurf2); + +inter2,pinter2 = ReactiveInternalInterfaceConstantTPhi(domainliq1, + domaincat2,interfacerxns1,298.15,AVratio*1.0); + +# %% +domaincat3,y0cat3,pcat3 = ConstantTAPhiDomain(phase=surf1, + initialconds=initialcondssurf3); + +inter3,pinter3 = ReactiveInternalInterfaceConstantTPhi(domainliq1, + domaincat3,interfacerxns1,298.15,AVratio*1.0); + +# %% +domaincat4,y0cat4,pcat4 = ConstantTAPhiDomain(phase=surf2, + initialconds=initialcondssurf4); + +inter4,pinter4 = ReactiveInternalInterfaceConstantTPhi(domainliq2, + domaincat4,interfacerxns2,298.15,AVratio*1.0); + +# %% +domaincat5,y0cat5,pcat5 = ConstantTAPhiDomain(phase=surf2, + initialconds=initialcondssurf5); + +inter5,pinter5 = ReactiveInternalInterfaceConstantTPhi(domainliq2, + domaincat5,interfacerxns2,298.15,AVratio*1.0); + +# %% +domaincat6,y0cat6,pcat6 = ConstantTAPhiDomain(phase=surf2, + initialconds=initialcondssurf6); + +inter6,pinter6 = ReactiveInternalInterfaceConstantTPhi(domainliq2, + domaincat6,interfacerxns2,298.15,AVratio*1.0); + +# %% +@time react1,y01,p1 = Reactor((domainliq1,domaincat1), (y0liq1,y0cat1), (0.0, 1.0e2), [inter1], (pliq1,pcat1,pinter1)); + +@time sol1 = solve(react1.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +ssys1 = SystemSimulation(sol1,(domainliq1,domaincat1,),(inter1,),p1); + + +# %% +@time react2,y02,p2 = Reactor((domainliq1,domaincat2), (y0liq1,y0cat2), (0.0, 1.0e2), [inter2], (pliq1,pcat2,pinter2)); + +@time sol2 = solve(react2.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-12,reltol=1e-6); + +ssys2 = SystemSimulation(sol2,(domainliq1,domaincat2,),(inter2,),p2); + +# %% +@time react3,y03,p3 = Reactor((domainliq1,domaincat3), (y0liq1,y0cat3), (0.0, 1.0e2), [inter3], (pliq1,pcat3,pinter3)); + +@time sol3 = solve(react3.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +ssys3 = SystemSimulation(sol3,(domainliq1,domaincat3,),(inter3,),p3); + +# %% +@time react4,y04,p4 = Reactor((domainliq2,domaincat4), (y0liq2,y0cat4), (0.0, 1.0e2), [inter4], (pliq2,pcat4,pinter4)); + +@time sol4 = solve(react4.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +ssys4 = SystemSimulation(sol4,(domainliq2,domaincat4,),(inter4,),p4); + +# %% +@time react5,y05,p5 = Reactor((domainliq2,domaincat5), (y0liq2,y0cat5), (0.0, 1.0e2), [inter5], (pliq2,pcat5,pinter5)); + +@time sol5 = solve(react5.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +ssys5 = SystemSimulation(sol5,(domainliq2,domaincat5,),(inter5,),p5); + +# %% +@time react6,y06,p6 = Reactor((domainliq2,domaincat6), (y0liq2,y0cat6), (0.0, 1.0e2), [inter6], (pliq2,pcat6,pinter6)); + +@time sol6 = solve(react6.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +ssys6 = SystemSimulation(sol6,(domainliq2,domaincat6,),(inter6,),p6); + +# %% +# Helper function +function plotX1(sim, tol, t_end, exclude) + clf() + xs = molefractions(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Mole Fraction") +end + +# %% +function plotX(bsol, tol, t_end, exclude) + # Species order and corresponding colors for the main species + species_order = ["CO2", "proton", "H2", "O=CO", "C=O", "O=CC=O", "O=CCO"] + color_map = Dict("CO2" => "blue", "proton" => "orange", "H2" => "purple", + "O=CO" => "red", "C=O" => "green", "O=CC=O" => "magenta", + "O=CCO" => "brown") + # Replacement map for species labels + replacement_map = Dict("C=O" => "CH2=O", "O=CO" => "HCOOH", + "O=CC=O" => "O=CH-CH=O", "O=CCO" => "O=CH-CH2OH") + + clf() + + xs = molefractions(bsol) + maxes = maximum(xs, dims=2) + spnames = [] + plotted_species = Set{String}() + + # Filter data to the specified time range + if t_end !== nothing + t_mask = bsol.sol.t .<= t_end + ts = bsol.sol.t[t_mask] + xs = xs[:, t_mask] + else + ts = bsol.sol.t + end + + # Plot species in the specified order with custom colors and labels + for sp in species_order + # Find the species index in the phase + species_index = findfirst(x -> x.name == sp, bsol.domain.phase.species) + if species_index === nothing || maxes[species_index] <= tol || sp in exclude + continue + end + + # Apply replacement for display name if available + display_name = get(replacement_map, sp, sp) + + # Plot the species with the specified color + plot(ts, xs[species_index, :], label=display_name, color=color_map[sp]) + push!(spnames, display_name) + push!(plotted_species, sp) + end + + # Plot any remaining species that are above the tolerance and not already plotted + for i = 1:length(bsol.domain.phase.species) + sp = bsol.domain.phase.species[i].name + if maxes[i] > tol && !(sp in exclude) && !(sp in plotted_species) + plot(ts, xs[i, :], label=sp) + push!(spnames, sp) + end + end + + # Configure the legend and labels + xlabel("Time in sec", fontsize=16) + ylabel("Mole Fraction", fontsize=16) + xticks(fontsize=14) + yticks(fontsize=14) + legend(spnames, loc="upper left", bbox_to_anchor=(0, 0.93), fontsize=12, ncol=2) +end + +# %% +exclude_species = ["H2O"] +plotX(ssys1.sims[1], 1e-12, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1) +ylim(1e-12, 5) +title("Ag111@-1.5 V", fontsize=16, fontweight="bold") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys2.sims[1], 1e-10, 10, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 10) +ylim(1e-12, 5) +title("Ag111@-1.0 V", fontsize=16, fontweight="bold") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys3.sims[1], 1e-12, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1) +ylim(1e-12, 5) +title("Ag111@-2.0 V", fontsize=16, fontweight="bold") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys4.sims[1], 1e-12, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1) +ylim(1e-12, 5) +title("Cu111@-1.5 V", fontsize=16, fontweight="bold") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys5.sims[1], 1e-12, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1) +ylim(1e-12, 5) +title("Cu111@-1.0 V", fontsize=16, fontweight="bold") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys6.sims[1], 1e-12, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1) +ylim(1e-12, 5) +title("Cu111@-2.0 V", fontsize=16, fontweight="bold") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys1.sims[2], 0.1, 1, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1) +ylim(1e-12, 5) +title("Solid-phase Mole Fractions on Ag111@-1.5 V", fontsize=16, fontweight="bold") +legend(loc="lower left") +gcf() + +# %% +Dict([ssys1.sims[1].names[i]=>molefractions(ssys1.sims[1],1)[i] for i in 1:length(ssys1.sims[1].names)]) + +# %% +fd1 = getfluxdiagram(ssys1,1;speciesratetolerance=1e-4) + +# %% +fd3 = getfluxdiagram(ssys3,1;speciesratetolerance=1e-4) + +# %% +fd4 = getfluxdiagram(ssys4,1;speciesratetolerance=1e-4) + +# %% +fd5 = getfluxdiagram(ssys5,1;speciesratetolerance=1e-4) + +# %% +fd6 = getfluxdiagram(ssys6,1;speciesratetolerance=1e-4) + +# %% +# function plot_composition_comparison(solutions, t, tol, exclude, x_labels) +# # Prepare data storage +# species_dict = Dict{String, Vector{Float64}}() # To collect mole fractions for each species + +# # Iterate through each solution +# for (idx, bsol) in enumerate(solutions) +# # Get mole fractions and species at the specified time +# mole_fractions = molefractions(bsol, t) +# species = bsol.domain.phase.species + +# # Filter species based on threshold and exclusion list +# for (i, mf) in enumerate(mole_fractions) +# species_name = species[i].name +# if mf > tol && !(species_name in exclude) +# # Initialize vector for each species if not already present +# if !haskey(species_dict, species_name) +# species_dict[species_name] = zeros(length(solutions)) +# end +# # Assign the mole fraction for the current solution +# species_dict[species_name][idx] = mf +# end +# end +# end + +# # Convert species data to arrays for plotting +# species_names = collect(keys(species_dict)) +# num_solutions = length(solutions) + +# # Sort species for each solution based on mole fractions (descending order) +# sorted_species = sort(species_names, by=name -> -maximum(species_dict[name])) + +# # Plotting each solution individually +# clf() # Clear the current figure +# bar_positions = 1:num_solutions +# width = 0.35 # Width of each bar +# color_cycle = get_cmap("tab20", length(sorted_species)) + +# # Initialize bottom values for stacked bars +# bottoms = zeros(num_solutions) + +# # Plot each species, stacking from the highest mole fraction down +# for (color_idx, species_name) in enumerate(sorted_species) +# # Get the mole fractions for the current species across solutions +# current_data = species_dict[species_name] + +# # Plot bars for the current species +# bar(bar_positions, current_data, width, bottom=bottoms, color=color_cycle(color_idx), label=species_name) + +# # Update the bottom values for stacking +# bottoms .+= current_data +# end + +# # Formatting the plot +# xticks(bar_positions, x_labels) +# ylabel("Mole Fraction") +# legend(title="Species", loc="upper right", bbox_to_anchor=(1.2, 1)) +# title("Liquid Phase Composition at t = $t") +# tight_layout() # Adjust layout for better appearance +# end + + +# %% +# sims_collection = [ssys1.sims[1], ssys2.sims[1], ssys3.sims[1]] +# x_labels = ["Ag111@-2.0V", "Ag111@-1.5V", "Ag111@-1.0V"] +# plot_composition_comparison(sims_collection, 1e-3, 1e-3, ["H2O"]) + +# %% diff --git a/CO2_Reduction_Ag/CO2RR_RMS_Diffusion_Interface.ipynb b/CO2_Reduction_Ag/CO2RR_RMS_Diffusion_Interface.ipynb deleted file mode 100644 index b089263..0000000 --- a/CO2_Reduction_Ag/CO2RR_RMS_Diffusion_Interface.ipynb +++ /dev/null @@ -1,6894 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "8a590634", - "metadata": {}, - "outputs": [], - "source": [ - "using DifferentialEquations\n", - "using ReactionMechanismSimulator\n", - "using PyPlot" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "e941d4fb", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[14:28:08] WARNING: not removing hydrogen atom without neighbors\n", - "[14:28:08] WARNING: not removing hydrogen atom without neighbors\n", - "┌ Warning: failed to generate StokesDiffusivity model for species vacantX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2O2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species H2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [H][H].[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(=O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH3X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(C#[Pt])CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)C(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C([Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C([Pt])CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC([Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=[Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC([Pt])=C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=C=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC(=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCOC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCC(=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC([Pt])=C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=COC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCOO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C=CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])CCO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)C(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)C(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC([Pt])OC=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=[Pt])OC=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC([Pt])=CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C([Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(C=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n" - ] - }, - { - "data": { - "text/plain": [ - "Dict{Any, Any} with 4 entries:\n", - " \"Solvents\" => Solvent[Solvent(\"water\", RiedelViscosity{Float64}(…\n", - " Set([\"surface\", \"gas\"]) => Dict{Any, Any}(\"Reactions\"=>ElementaryReaction[vac…\n", - " \"gas\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…\n", - " \"surface\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "outdict = readinput(\"chem300.rms\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "fe2767e9", - "metadata": {}, - "outputs": [], - "source": [ - "boundarylayerspcs = outdict[\"gas\"][\"Species\"]\n", - "boundarylayerrxns = outdict[\"gas\"][\"Reactions\"]\n", - "surfspcs = outdict[\"surface\"][\"Species\"]\n", - "surfrxns = outdict[\"surface\"][\"Reactions\"]\n", - "interfacerxns = outdict[Set([\"surface\", \"gas\"])][\"Reactions\"]\n", - "solv = outdict[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "c54ee65e", - "metadata": {}, - "outputs": [], - "source": [ - "sitedensity = 2.292e-5; # Ag111\n", - "boundarylayer = IdealDiluteSolution(boundarylayerspcs,boundarylayerrxns,solv,name=\"boundarylayeruid\",diffusionlimited=true);\n", - "surf = IdealSurface(surfspcs,surfrxns,sitedensity,name=\"surface\");" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "8894c84d", - "metadata": {}, - "outputs": [], - "source": [ - "initialcondsboundarylayer = Dict([\"proton\"=>10.0^-4,\n", - " \"CO2\"=>10.0^-3*10^6,\n", - " \"V\"=>1.0e-3,\"T\"=>300,\"Phi\"=>0.0,\"d\"=>0.0]);\n", - "initialcondsreservoir = Dict([\"proton\"=>10.0^-4,\n", - " \"CO2\"=>10.0^-3*10^6,\n", - " \"V\"=>1.0,\"T\"=>300]);\n", - "AVratio = 1e5;\n", - "initialcondssurf = Dict([\"CO2X\"=>0.4*sitedensity*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity*AVratio,\n", - " \"OX\"=>0.1*sitedensity*AVratio,\n", - " \"OCX\"=>0.1*sitedensity*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>300,\"Phi\"=>-1.0]);" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "ddb39b3d", - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "domainboundarylayer, y0boundarylayer, pboundarylayer = ConstantTVDomain(phase=boundarylayer, initialconds=initialcondsboundarylayer);\n", - "domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf,\n", - " initialconds=initialcondssurf);" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "ed49d2b4", - "metadata": {}, - "outputs": [], - "source": [ - "inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainboundarylayer,\n", - " domaincat,interfacerxns,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "dee14906", - "metadata": {}, - "outputs": [], - "source": [ - "# start with 1mm layer thickness\n", - "diffusionlayer = ConstantReservoirDiffusion(domainboundarylayer, initialcondsreservoir, AVratio*1.0, 1e-3);" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "e70ac4b0", - "metadata": {}, - "outputs": [], - "source": [ - "interfaces = [inter, diffusionlayer];" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "244f0912", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 17.594306 seconds (76.53 M allocations: 4.854 GiB, 7.88% gc time, 99.49% compilation time: <1% of which was recompilation)\n" - ] - } - ], - "source": [ - "@time react,y0,p = Reactor((domainboundarylayer,domaincat), (y0boundarylayer,y0cat), (0.0, 1.0e2), interfaces, (pboundarylayer,pcat,pinter));\n" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "962f838c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 14.018329 seconds (45.39 M allocations: 14.701 GiB, 8.17% gc time, 63.16% compilation time)\n" - ] - } - ], - "source": [ - "@time sol = solve(react.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-8);" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "56b6f906", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "retcode: Success\n", - "Interpolation: 3rd order Hermite\n", - "t: 7378-element Vector{Float64}:\n", - " 0.0\n", - " 5.637182922368118e-20\n", - " 1.1274365844736235e-19\n", - " 2.8910211211279163e-19\n", - " 4.654605657782209e-19\n", - " 6.418190194436502e-19\n", - " 9.195383720242527e-19\n", - " 1.3841882991386121e-18\n", - " 2.1843751517941395e-18\n", - " 3.563281809146959e-18\n", - " ⋮\n", - " 34.585534778618225\n", - " 37.972824443061896\n", - " 41.36011410750557\n", - " 48.6159125226287\n", - " 55.87171093775183\n", - " 63.12750935287496\n", - " 70.38330776799809\n", - " 83.73929891807829\n", - " 100.0\n", - "u: 7378-element Vector{Vector{Float64}}:\n", - " [0.0, 0.0, 0.0, 0.0, 1000.0, 0.0001, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]\n", - " [0.0, 0.0, 0.0, 0.0, 1000.0, 0.0001, 0.0, 0.0, 0.0, 0.0 … 3.616585260471062e-48, 1.250284183589301e-66, 3.3559035931055214e-86, -2.930822829419953e-183, 9.11712362429275e-74, 4.972280466767057e-91, 1.6800515466000932e-93, 8.919271365980456e-98, 5.278931575090823e-45, 1.995290567657646e-61]\n", - " [0.0, 0.0, 0.0, 0.0, 1000.0, 0.0001, 0.0, 0.0, 0.0, 0.0 … 1.8082925133540044e-47, 8.741481198944129e-66, 1.9747951911527822e-85, 3.215917908275869e-175, 4.558751536742425e-73, 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- "sol.retcode" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "6667bb5a", - "metadata": {}, - "outputs": [], - "source": [ - "ssys = SystemSimulation(sol,(domainboundarylayer,domaincat,), interfaces,p);" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "87dcaf99", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotX (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotX(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = molefractions(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Mole Fraction\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "ddf6da6b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotC (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotC(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = concentrations(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Concentration\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "386a52a2", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "108×7378 Matrix{Float64}:\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 … 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 1.0e6 1.0e6 1.0e6 1.0e6 1.0e6 1.0e6 1000.0 1000.0\n", - " 0.1 0.1 0.1 0.1 0.1 0.1 … 0.0001 0.0001\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 1.26634e-25 -3.37894e-24\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 -3.85013e-25 3.87315e-23\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 4.98977e-32 5.14795e-31\n", - " ⋮ ⋮ ⋱ \n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 … 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 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5.85419e-9\n", - " 0.0 3.93893e-14 7.87785e-14 7.35377e-19 7.35366e-19\n", - " ⋮ ⋱ \n", - " 0.0 1.25028e-71 8.74148e-71 1.11796e-24 1.11613e-24\n", - " 0.0 3.3559e-91 1.9748e-90 3.87397e-29 3.86904e-29\n", - " 0.0 -2.93082e-188 3.21592e-180 … -1.60967e-81 -1.50788e-81\n", - " 0.0 9.11712e-79 4.55875e-78 9.86869e-27 9.85295e-27\n", - " 0.0 4.97228e-96 3.90346e-95 2.11012e-43 2.10736e-43\n", - " 0.0 1.68005e-98 9.82947e-98 2.73081e-48 -3.29903e-48\n", - " 0.0 8.91927e-103 4.45963e-102 7.2535e-39 7.24499e-39\n", - " 0.0 5.27893e-50 3.0284e-49 … 6.33888e-19 6.33473e-19\n", - " 0.0 1.99529e-66 1.39664e-65 3.5683e-24 3.5682e-24" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "concentrations(ssys.sims[2])" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "e719a85d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys.sims[1], 1e-6, 1e2, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e2)\n", - "ylim(1e-9, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "1ef78267", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotC(ssys.sims[1], 1e-6, 1e2, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 10)\n", - "ylim(1e-6, 1e8)\n", - "title(\"Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "1ee8224d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotC(ssys.sims[2], 1e-6, 1e2, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 10)\n", - "ylim(1e-6, 1e-4)\n", - "title(\"Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "1f7d8918", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "1406×1462 Array{RGB{N0f8},2} with eltype ColorTypes.RGB{FixedPointNumbers.N0f8}:\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "getfluxdiagram(ssys,1e2;speciesratetolerance=1e-6)" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "36206466", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[\"Ar\", \"He\", \"Ne\", \"N2\", \"CO2\", \"proton\", \"H\", \"C=O\", \"O=CO\", \"H2O\", \"O=CC=O\", \"H2\", \"OO\", \"CO\", \"O2\", \"O=C=C=O\", \"C=C=O\", \"O=C=CO\", \"CH4\", \"COC=O\", \"COO\", \"CO-2\", \"COOC\", \"O=CCO\", \"OCO\", \"COCO\", \"OCCO\", \"OC=CO\", \"O=O\", \"C=CO\", \"C=C\", \"O=C=C=C=O\", \"C#COO[CH2]\", \"C#COC[O]\", \"CC=O\", \"O=C=CC=O\", \"C=C(O)O\", \"CC(=O)O\", \"[OH]\", \"CC(=O)C=O\", \"COC(C)=O\", \"CC(=O)CO\", \"O=CCC=O\", \"COC=C=O\", \"O=C=CCO\", \"[CH2]OOC=C\", \"C=COC[O]\", \"C=CC=O\", \"C=COC=O\", \"O=CC=CO\", \"COC\", \"CCO\", \"CC(O)O\", \"CCOC=O\", \"COCC=O\", \"CCOO\", \"CC(C)=O\", \"C=C=C=O\", \"CC=C=O\", \"CC\", \"O=C=C=CO\", \"[CH2]OCC=O\", \"[O]CCC=O\", \"[CH2]COC=O\", \"[CH3]\", \"O=CCCO\", \"CCC=O\", \"CC(O)=C=O\", \"[CH]=O\", \"C[O]\", \"CC(O)C=O\", \"[CH2]O\", \"C=C(O)C=O\", \"OC=CCO\", \"C=CCO\", \"[CH]=C\", \"C[CH2]\", \"C=C=CO\", \"C=C=C\", \"C=C=C(O)O\", \"C=CC(=O)O\", \"CC=CO\", \"C=CC\", \"CC=C(O)O\", \"CCC(=O)O\", \"C=COO\", \"C#C\", \"C=COC\", \"C=CC(O)O\", \"C=COCO\", \"C=CCOO\", \"C=COOC\", \"CC(O)=CO\", \"C=C(C)O\", \"C#CC=O\", \"OC=C=CO\", \"CCOC\", \"CCCO\", \"CCC(O)O\", \"CCOCO\", \"CCCOO\", \"CCC\", \"CCOOC\", \"C=C=COO\", \"CC=COO\", \"C=CCO[O]\", \"COCOC\", \"COCCO\", \"vacantX\", \"CO2X\", \"CHO2X\", \"CO2HX\", \"OCX\", \"OX\", \"CH2O2X\", \"CHOX\", \"CH2OX\", \"HOX\", \"HX\", \"CO[Pt]\", \"OC[Pt]\", \"OC(O)[Pt]\", \"OCO[Pt]\", \"H2OX\", \"OC=[Pt]\", \"O=CC(=O)[Pt]\", \"OC#[Pt]\", \"O=CC=O.[Pt]\", \"[H][H].[Pt]\", \"O=COC[Pt]\", \"OO[Pt]\", \"CX\", \"CHX\", \"CH2X\", \"O=COC#[Pt]\", \"O=CCO[Pt]\", \"O=O.[Pt]\", \"O=CC#[Pt]\", \"OC(O)=[Pt]\", \"O=C(O)C#[Pt]\", \"O=C=C=O.[Pt]\", \"OOC[Pt]\", \"C=C=O.[Pt]\", \"COC(=O)[Pt]\", \"CC(=O)[Pt]\", \"O=COCC#[Pt]\", \"O=C([Pt])CO\", \"O=CCC(=O)[Pt]\", \"OCC#[Pt]\", \"OC(O)C#[Pt]\", \"OCOC#[Pt]\", \"O=CCOC#[Pt]\", \"O=C=C[Pt]\", \"COC#[Pt]\", \"O=CC(=O)C#[Pt]\", \"O=COC=[Pt]\", \"O=C=CC#[Pt]\", \"CC#[Pt]\", \"O=C=CO[Pt]\", \"COC(=O)C#[Pt]\", \"O=C=CC(=O)[Pt]\", \"O=CCC#[Pt]\", \"CH3X\", \"O=C=CO.[Pt]\", \"O=C=C=[Pt]\", \"CC(=O)C#[Pt]\", \"O=C(C#[Pt])CO\", \"COC=O.[Pt]\", \"CC(=O)C(=O)[Pt]\", \"OOC#[Pt]\", \"O=CC[Pt]\", \"O=CC=[Pt]\", \"C.[Pt]\", \"O=C=CC=O.[Pt]\", \"CC(=O)O[Pt]\", \"CC(=O)OC#[Pt]\", \"O=C=C([Pt])C=O\", \"O=C=COC#[Pt]\", \"COO[Pt]\", \"CO.[Pt]\", \"O=C=C(O)[Pt]\", \"O=C=C(O)C#[Pt]\", \"COOC#[Pt]\", \"O=CC(O)[Pt]\", \"O=CC(O)C#[Pt]\", \"O=CC(O)=[Pt]\", \"OCO.[Pt]\", \"O=C=C=C=O.[Pt]\", \"O=CCO.[Pt]\", \"OCC=[Pt]\", \"O=C=CCO.[Pt]\", \"O=C=CC(O)[Pt]\", \"O=C=CC=[Pt]\", \"O=C=C([Pt])CO\", \"O=C=CC[Pt]\", \"O=C=CC(O)=[Pt]\", \"O=C=CCO[Pt]\", \"O=CC([Pt])C=O\", \"O=CC(=[Pt])C=O\", \"O=CCC=O.[Pt]\", \"O=CCC=[Pt]\", \"OOCC#[Pt]\", \"C=C=[Pt]\", \"O=C(O)C=[Pt]\", \"CC=O.[Pt]\", \"CC=[Pt]\", \"CC=C=O.[Pt]\", \"O=C(O)C[Pt]\", \"O=C(O)CC#[Pt]\", \"CC([Pt])=C=O\", \"CC(=C=O)O[Pt]\", \"C=C.[Pt]\", \"C=C[Pt]\", \"C=CC#[Pt]\", \"CC(=O)O.[Pt]\", \"C=CC(=O)[Pt]\", \"O=CC=CO[Pt]\", \"C=CO[Pt]\", \"C=COC(=O)[Pt]\", \"C=COC#[Pt]\", \"CC(O)=[Pt]\", \"O=CC=C[Pt]\", \"C=CC(=O)O[Pt]\", \"OC=C=[Pt]\", \"CC[Pt]\", \"CCC#[Pt]\", \"CCO[Pt]\", \"CCOC(=O)[Pt]\", \"CCC(=O)[Pt]\", \"CCOC#[Pt]\", \"CCC(=O)O[Pt]\", \"CC(O)=C=O.[Pt]\", \"OOC=[Pt]\", \"OO.[Pt]\", \"COCO[Pt]\", \"COCC(=O)[Pt]\", \"COCOC#[Pt]\", \"COCC#[Pt]\", \"COC[Pt]\", \"COC=[Pt]\", \"COC=C=O.[Pt]\", \"O=C=COC[Pt]\", \"COC([Pt])=C=O\", \"O=C=COC=[Pt]\", \"CCOO[Pt]\", \"O=C=C=CO.[Pt]\", \"O=C=C=C(O)[Pt]\", \"O=C=C=C[Pt]\", \"OC=CO.[Pt]\", \"OC=C(O)[Pt]\", \"OC=C[Pt]\", \"OC=CO[Pt]\", \"OC=COC#[Pt]\", \"O=C([Pt])C=CO\", \"OC=C(O)C#[Pt]\", \"OC=CC#[Pt]\", \"OCC[Pt]\", \"OCCC#[Pt]\", \"O=C([Pt])CCO\", \"OCCO[Pt]\", \"OCCOC#[Pt]\", \"O=C=C=C=[Pt]\", \"C=CO.[Pt]\", \"C=C(O)[Pt]\", \"C=C(O)O[Pt]\", \"C=C(O)OC#[Pt]\", \"C=C(O)C#[Pt]\", \"C=C(O)C(=O)[Pt]\", \"C=COO[Pt]\", \"O=CC=C=[Pt]\", \"C=C=C=O.[Pt]\", \"O=C=C=CO[Pt]\", \"CC(O)[Pt]\", \"CC(O)C#[Pt]\", \"CC(O)O[Pt]\", \"CC(O)C(=O)[Pt]\", \"CC(O)OC#[Pt]\", \"O=C=C(O)C[Pt]\", \"O=C=C(O)C=[Pt]\", \"CC([Pt])OC=O\", \"CC(=[Pt])OC=O\", \"O=CC=CO.[Pt]\", \"O=CC=C(O)[Pt]\", \"O=CC([Pt])=CO\", \"OC=CC=[Pt]\", \"OCC(O)[Pt]\", \"OCC(O)C#[Pt]\", \"OCC(O)=[Pt]\", \"COC(O)[Pt]\", \"COC(O)C#[Pt]\", \"COC(O)=[Pt]\", \"O=CCCO[Pt]\", \"O=CCC[Pt]\", \"C=COOC#[Pt]\", \"C=CC=O.[Pt]\", \"C=C([Pt])C=O\", \"C=C(C=O)O[Pt]\", \"C=CC=[Pt]\", \"CC(O)O.[Pt]\", \"OC(O)C[Pt]\"]\n" - ] - } - ], - "source": [ - "println(ssys.names)" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "64238bc0", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"CH2O2X\",1;N=15,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "e8bb3c43", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"CHO2X\",1;N=10,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "0bb84a7f", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"CO2HX\",1;N=10,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "1044d2b9", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"OX\",1;N=10,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "7086e403", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"OCX\",1.0e-6)" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "44de0eb2", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "vacantX+CO2<=>CO2X\n", - "kf = 20654.615923781494\n", - "krev = 11189.298481041604\n", - "Kc = 1.8459259048971917\n", - "proton+CO2X<=>CHO2X\n", - "kf = 5.164749496653815e7\n", - "krev = 3.369038128826839e8\n", - "Kc = 0.1533004168893831\n", - "proton+CO2X<=>CO2HX\n", - "kf = 463658.8965294065\n", - "krev = 1.20318988446587e-5\n", - "Kc = 3.853580407511801e10\n", - "proton+CHO2X<=>CH2O2X\n", - "kf = 2.5e10\n", - "krev = 9.108706843764319e-26\n", - "Kc = 2.7446266993557504e35\n", - "proton+CO2HX<=>CH2O2X\n", - "kf = 1.9190551016885178e10\n", - "krev = 1.757621070775451e-14\n", - "Kc = 1.0918480289052538e24\n", - "proton+OCX<=>CHOX\n", - "kf = 2.5e10\n", - "krev = 2.604453583293511e-10\n", - "Kc = 9.59894242706594e19\n", - "proton+CHOX<=>CH2OX\n", - "kf = 1.7890196451453958e9\n", - "krev = 4.957912234830633e-11\n", - "Kc = 3.608413300616868e19\n", - "vacantX+vacantX+CO2<=>OX+OCX\n", - "kf = 3.0109478093923404e-24\n", - "krev = 3.037156297092479e15\n", - "Kc = 9.913707148607306e-40\n", - "OX+proton<=>HOX\n", - "kf = 2.5e10\n", - "krev = 4.7547181516587526e-14\n", - "Kc = 5.25793521352646e23\n", - "vacantX+C=O<=>CH2OX\n", - "kf = 500114.13488002896\n", - "krev = 399.6803280141717\n", - "Kc = 1251.2853393732605\n", - "proton+CHO2X<=>OX+C=O\n", - "kf = 7.971946163368602e-7\n", - "krev = 8.220582009654122e-5\n", - "Kc = 0.009697544716428197\n", - "HX+CO2<=>CHO2X\n", - "kf = 6.542996392927688e-8\n", - "krev = 15.579156394796986\n", - "Kc = 4.199839983064083e-9\n", - "HX+CO2<=>CO2HX\n", - "kf = 6.542996392927688e-8\n", - "krev = 6.197590078701277e-11\n", - "Kc = 1055.7323588427441\n", - "vacantX+vacantX+C=O<=>HX+CHOX\n", - "kf = 2.0718885766149262e-11\n", - "krev = 0.008867505326838887\n", - "Kc = 2.336495440655708e-9\n", - "vacantX+O=CO<=>CH2O2X\n", - "kf = 403943.82249737746\n", - "krev = 29.756334575496034\n", - "Kc = 13575.053119278344\n", - "vacantX+vacantX+O=CO<=>HOX+CHOX\n", - "kf = 8.486192390111145e-15\n", - "krev = 9.7037034735699e11\n", - "Kc = 8.745312975839684e-27\n", - "vacantX+vacantX+O=CO<=>HX+CHO2X\n", - "kf = 1.2668346793097018e-21\n", - "krev = 380.13410282264914\n", - "Kc = 3.332599390328158e-24\n", - "vacantX+vacantX+O=CO<=>HX+CO2HX\n", - "kf = 9.840171155787102e-15\n", - "krev = 0.011746228705195169\n", - "Kc = 8.377302539184302e-13\n", - "proton+CH2OX<=>CO[Pt]\n", - "kf = 4.612846333154699e7\n", - "krev = 90.4105198560361\n", - "Kc = 510211.23874742666\n", - "HX+C=O<=>CO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.180104845075902e-9\n", - "Kc = 9.475050217848336\n", - "proton+CO2HX<=>H2O+OCX\n", - "kf = 2.5e10\n", - "krev = 4.0258346788129556e-7\n", - "Kc = 6.20989235637749e16\n", - "vacantX+vacantX+H2O<=>HX+HOX\n", - "kf = 1.7047654949014593e-31\n", - "krev = 21441.30602897437\n", - "Kc = 7.950847269274322e-36\n", - "proton+CH2OX<=>OC[Pt]\n", - "kf = 1.2443063594454413e6\n", - "krev = 1.1005987164187474e-6\n", - "Kc = 1.1305722429827158e12\n", - "HX+C=O<=>OC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.886422105564557e-15\n", - "Kc = 2.099567387708916e7\n", - "vacantX+vacantX+O=CC=O<=>CHOX+CHOX\n", - "kf = 3.132095071630788e8\n", - "krev = 159.05427897483804\n", - "Kc = 1.9691988746346629e6\n", - "proton+CH2O2X<=>OC(O)[Pt]\n", - "kf = 1.9695177200694968e-5\n", - "krev = 3718.799864740736\n", - "Kc = 5.296111088803661e-9\n", - "HX+O=CO<=>OC(O)[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 29981.045237801853\n", - "Kc = 1.0670229661561413e-12\n", - "proton+CH2O2X<=>OCO[Pt]\n", - "kf = 1.3800914441571782e-5\n", - "krev = 3681.751563599994\n", - "Kc = 3.748464339097702e-9\n", - "HOX+C=O<=>OCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.962949149852605e-13\n", - "Kc = 201771.41789913058\n", - "HX+O=CO<=>OCO[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 42359.465576793365\n", - "Kc = 7.552140562327293e-13\n", - "vacantX+H2O<=>H2OX\n", - "kf = 4.842414926683719e6\n", - "krev = 2.0721934488233277e8\n", - "Kc = 0.023368546645263413\n", - "proton+HOX<=>H2OX\n", - "kf = 2.5e10\n", - "krev = 1.2623996335027457e-31\n", - "Kc = 1.9803554545269617e41\n", - "vacantX+vacantX+H2<=>HX+HX\n", - "kf = 3.8736093818093735e10\n", - "krev = 4.9917087254698525e28\n", - "Kc = 7.760086965901168e-19\n", - "proton+CHOX<=>OC=[Pt]\n", - "kf = 3.6460821201937575e9\n", - "krev = 3.454391742229775e10\n", - "Kc = 0.10554917890812951\n", - "vacantX+vacantX+O=CO<=>OX+OC=[Pt]\n", - "kf = 1.3995006080437096e-36\n", - "krev = 7.971831424002446e14\n", - "Kc = 1.755557203367275e-51\n", - "proton+OC=[Pt]<=>OC[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.468152848309303e-23\n", - "Kc = 3.8650910988497585e32\n", - "proton+OC(O)[Pt]<=>H2O+OC=[Pt]\n", - "kf = 6.989877198043828e9\n", - "krev = 6.424310280494338e-11\n", - "Kc = 1.0880354299303816e20\n", - "proton+O=CC(=O)[Pt]<=>OCX+C=O\n", - "kf = 2.302032083373261e7\n", - "krev = 2.5713202543754838e-9\n", - "Kc = 8.952724109165363e15\n", - "vacantX+vacantX+O=CC=O<=>HX+O=CC(=O)[Pt]\n", - "kf = 1.43713660093583e-9\n", - "krev = 0.00032277677938391324\n", - "Kc = 4.452416322137251e-6\n", - "proton+OCX<=>OC#[Pt]\n", - "kf = 26781.620683797883\n", - "krev = 1.0085447542339806e12\n", - "Kc = 2.6554717151981333e-8\n", - "proton+OC#[Pt]<=>OC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.552445879282663e-17\n", - "Kc = 3.815369170624406e26\n", - "vacantX+O=CC=O<=>O=CC=O.[Pt]\n", - "kf = 359723.7676387533\n", - "krev = 0.32068189796600394\n", - "Kc = 1.121746409511672e6\n", - "proton+O=CC(=O)[Pt]<=>O=CC=O.[Pt]\n", - "kf = 1.508798479649927e9\n", - "krev = 8.88806985342612e-11\n", - "Kc = 1.6975547048252826e19\n", - "vacantX+vacantX+OO<=>HOX+HOX\n", - "kf = 4.0912386971316826e8\n", - "krev = 1.7763617117679594e-6\n", - "Kc = 2.3031563166601894e14\n", - "OCX<=>vacantX+CO\n", - "kf = 2.010168305725754e-19\n", - "krev = 2.61760793808642e-25\n", - "Kc = 767940.9419866255\n", - "vacantX+vacantX+O2<=>OX+OX\n", - "kf = 1.0945721587141857e10\n", - "krev = 4.219325007995329e-16\n", - "Kc = 2.594187830138819e25\n", - "proton+HX<=>[H][H].[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.1949534688419614e-15\n", - "Kc = 2.0921316730623565e25\n", - "vacantX+H2<=>[H][H].[Pt]\n", - "kf = 2338.960705505517\n", - "krev = 9707.159813448116\n", - "Kc = 0.24095211683495363\n", - "CHOX+C=O<=>O=COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 7.563806299311394e-5\n", - "Kc = 0.0005236345532350701\n", - "proton+OO[Pt]<=>OX+H2O\n", - "kf = 17.257164508221003\n", - "krev = 6.236444643145301e-63\n", - "Kc = 2.767147869610126e63\n", - "vacantX+vacantX+OO<=>HX+OO[Pt]\n", - "kf = 4.980245005159166e-22\n", - "krev = 5.509834949091977\n", - "Kc = 9.038827934364735e-23\n", - "proton+OC#[Pt]<=>H2O+CX\n", - "kf = 3.276640102032806e-5\n", - "krev = 0.0009291230748795855\n", - "Kc = 0.03526594259277716\n", - "vacantX+vacantX+O=C=C=O<=>OCX+OCX\n", - "kf = 74.64023007210145\n", - "krev = 2.953439666185894e-39\n", - "Kc = 2.52723056870475e40\n", - "HX+O=C=C=O<=>O=CC(=O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 5.0006650398424424e-61\n", - "Kc = 1.1597065597154312e53\n", - "proton+OC=[Pt]<=>H2O+CHX\n", - "kf = 2.5e10\n", - "krev = 6.511063937864271e-5\n", - "Kc = 3.839618261865876e14\n", - "proton+CX<=>CHX\n", - "kf = 2.5e10\n", - "krev = 6.018259224258551e-33\n", - "Kc = 4.1540251206244773e42\n", - "H2+CX<=>CH2X\n", - "kf = 4.832014059685671\n", - "krev = 1.8278921581756875e-33\n", - "Kc = 2.643489681857502e33\n", - "vacantX+vacantX+C=O<=>OX+CH2X\n", - "kf = 4.5608316796485725e-28\n", - "krev = 3.884151005592286e17\n", - "Kc = 1.1742158513101117e-45\n", - "proton+OC[Pt]<=>H2O+CH2X\n", - "kf = 7206.229958253159\n", - "krev = 0.0019484451144913943\n", - "Kc = 3.6984516036184127e6\n", - "proton+O=COC[Pt]<=>CH2X+O=CO\n", - "kf = 1981.2472905766488\n", - "krev = 1.4695324127813272e-5\n", - "Kc = 1.3482161219069803e8\n", - "proton+CHX<=>CH2X\n", - "kf = 2.5e10\n", - "krev = 6.715036577093663e-15\n", - "Kc = 3.722987911231938e24\n", - "proton+O=COC#[Pt]<=>CX+O=CO\n", - "kf = 6.185088018779624e7\n", - "krev = 3.741277098492221e-23\n", - "Kc = 1.6532023306352497e30\n", - "vacantX+vacantX+C=C=O<=>OCX+CH2X\n", - "kf = 2.4823885573387985e-14\n", - "krev = 9.351132511056354e15\n", - "Kc = 2.6546394828687704e-30\n", - "CHOX+C=O<=>O=CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.4949222028864902e7\n", - "Kc = 2.6494156850764662e-15\n", - "HX+O=CC=O<=>O=CCO[Pt]\n", - "kf = 5.6976884072695144e-8\n", - "krev = 2.551666729065355e-8\n", - "Kc = 2.23292812590636\n", - "proton+O=CC=O.[Pt]<=>O=CCO[Pt]\n", - "kf = 957581.7759153218\n", - "krev = 7139.55197608848\n", - "Kc = 134.12351070801344\n", - "O=O.[Pt]+proton<=>OO[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.545950245153839e-28\n", - "Kc = 7.050296330064662e37\n", - "proton+O=CC#[Pt]<=>CX+C=O\n", - "kf = 5.731900626219973e-17\n", - "krev = 16.634660991475336\n", - "Kc = 3.4457574032662074e-18\n", - "proton+CO2HX<=>OC(O)=[Pt]\n", - "kf = 8.313674902647437e-22\n", - "krev = 1.0085447542339753e12\n", - "Kc = 8.243238455949296e-34\n", - "proton+OC(O)=[Pt]<=>OC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.563843227039955e-39\n", - "Kc = 7.014898918762039e48\n", - "proton+OC(O)=[Pt]<=>H2O+OC#[Pt]\n", - "kf = 58948.65819613129\n", - "krev = 2.9467686111082447e-38\n", - "Kc = 2.0004508658710534e42\n", - "proton+O=C(O)C#[Pt]<=>CX+O=CO\n", - "kf = 1.2163309452954808e-9\n", - "krev = 0.00037997676558546045\n", - "Kc = 3.201066632117316e-6\n", - "proton+O=C=C=O.[Pt]<=>O=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.649884885591097e-48\n", - "Kc = 9.434372087609898e57\n", - "vacantX+O=C=C=O<=>O=C=C=O.[Pt]\n", - "kf = 366139.2749661925\n", - "krev = 442.06521987276346\n", - "Kc = 828.2471873077366\n", - "HOX+C=O<=>OOC[Pt]\n", - "kf = 1.5395975576095126e-29\n", - "krev = 2.622153295712258e16\n", - "Kc = 5.871500953537159e-46\n", - "proton+OOC[Pt]<=>OO+CH2X\n", - "kf = 15.535579749933543\n", - "krev = 3.4028033042152773e-9\n", - "Kc = 4.5655238816444645e9\n", - "vacantX+vacantX+O=C=CO<=>OCX+OC=[Pt]\n", - "kf = 73.33238091278024\n", - "krev = 14511.198914062346\n", - "Kc = 0.005053502563576338\n", - "vacantX+C=C=O<=>C=C=O.[Pt]\n", - "kf = 422670.5724931744\n", - "krev = 9.80980243728561e-11\n", - "Kc = 4.3086552985681545e15\n", - "proton+CO[Pt]<=>OX+CH4\n", - "kf = 541698.6744405399\n", - "krev = 1.9995135619129721e-19\n", - "Kc = 2.7091522896313173e24\n", - "HX+C=C=O<=>CC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.3310785577331067e-33\n", - "Kc = 2.514767798332947e25\n", - "proton+C=C=O.[Pt]<=>CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.357099551204697e-8\n", - "Kc = 3.9326110592781875e17\n", - "proton+CC(=O)[Pt]<=>OCX+CH4\n", - "kf = 1.0030005882936613e8\n", - "krev = 4.3463683404291294e-8\n", - "Kc = 2.3076750743003805e15\n", - "vacantX+vacantX+COC=O<=>CHOX+CO[Pt]\n", - "kf = 5.858305523872122e-8\n", - "krev = 9.372228401924443e12\n", - "Kc = 6.250707166578664e-21\n", - "vacantX+vacantX+COC=O<=>HX+O=COC[Pt]\n", - "kf = 8.724708246600757e-23\n", - "krev = 252.56605644619947\n", - "Kc = 3.454426287270814e-25\n", - "vacantX+vacantX+COC=O<=>HX+COC(=O)[Pt]\n", - "kf = 7.165711269221808e-16\n", - "krev = 0.1859922027934253\n", - "Kc = 3.852694447186316e-15\n", - "proton+O=COCC#[Pt]<=>CX+COC=O\n", - "kf = 0.8132675549526747\n", - "krev = 2.165706403032533e-5\n", - "Kc = 37552.06863746147\n", - "HOX+C=C=O<=>O=C([Pt])CO\n", - "kf = 3.3473534940386794e-8\n", - "krev = 9.042590347389556e-30\n", - "Kc = 3.70176394754519e21\n", - "HX+O=C=CO<=>O=C([Pt])CO\n", - "kf = 2.8488442036348548e-8\n", - "krev = 1.614840618256874e-45\n", - "Kc = 1.7641643214981894e37\n", - "vacantX+vacantX+COO<=>HOX+CO[Pt]\n", - "kf = 3.442529358831723e8\n", - "krev = 2.6586367586035048e-11\n", - "Kc = 1.294847574679578e19\n", - "vacantX+vacantX+COO<=>HX+OOC[Pt]\n", - "kf = 1.3336211820914592e-23\n", - "krev = 16620.58178963317\n", - "Kc = 8.023913957833202e-28\n", - "CHOX+C=C=O<=>O=CCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 2.6714659015861004e-16\n", - "Kc = 1.2530025152300434e8\n", - "vacantX+vacantX+CO-2<=>HX+CO[Pt]\n", - "kf = 3.6896065237788346e-26\n", - "krev = 1200.2597905170037\n", - "Kc = 3.0740066050113714e-29\n", - "vacantX+vacantX+CO-2<=>HX+OC[Pt]\n", - "kf = 1.1691860289045307e-22\n", - "krev = 1.716447494000275\n", - "Kc = 6.811662069427353e-23\n", - "proton+OCO[Pt]<=>OX+CO-2\n", - "kf = 6.4866612293733e7\n", - "krev = 4.917786339628338e-9\n", - "Kc = 1.319020547335029e16\n", - "proton+COC(=O)[Pt]<=>OCX+CO-2\n", - "kf = 5.096893185474306e9\n", - "krev = 2.041829224680708e-9\n", - "Kc = 2.49623872744369e18\n", - "proton+O=C([Pt])CO<=>OCX+CO-2\n", - "kf = 1.9762803815844387e7\n", - "krev = 1.2158736968776066e-8\n", - "Kc = 1.6253994034574272e15\n", - "proton+OCC#[Pt]<=>CX+CO-2\n", - "kf = 1.8515947729382765e-10\n", - "krev = 0.16959607683462066\n", - "Kc = 1.091767455649245e-9\n", - "vacantX+vacantX+COOC<=>CO[Pt]+CO[Pt]\n", - "kf = 3.028654941635431e8\n", - "krev = 1.0392777770118965e-11\n", - "Kc = 2.914191959673513e19\n", - "vacantX+vacantX+C=C=O<=>HX+O=C=C[Pt]\n", - "kf = 3.6584912239485734e-16\n", - "krev = 0.32395775785233605\n", - "Kc = 1.1293111942132156e-15\n", - "vacantX+vacantX+O=C=CO<=>HOX+O=C=C[Pt]\n", - "kf = 3.132095071630788e8\n", - "krev = 5.819571251914923e7\n", - "Kc = 5.382003133994065\n", - "proton+O=C=C[Pt]<=>C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.724942318590629e-29\n", - "Kc = 2.570709334924167e38\n", - "vacantX+vacantX+O=CCO<=>CHOX+OC[Pt]\n", - "kf = 9001.813049524091\n", - "krev = 8.180569891408677e12\n", - "Kc = 1.1003894800749632e-9\n", - "vacantX+vacantX+O=CCO<=>HX+O=CCO[Pt]\n", - "kf = 3.705974451661604e-28\n", - "krev = 2668.9209237076484\n", - "Kc = 1.3885665996103351e-31\n", - "vacantX+vacantX+O=CCO<=>HX+O=C([Pt])CO\n", - "kf = 1.2718474027465153e-10\n", - "krev = 0.0002705673832361486\n", - "Kc = 4.7006678614933393e-7\n", - "proton+O=CCOC#[Pt]<=>CX+O=CCO\n", - "kf = 3.8625888100004036e-23\n", - "krev = 1.5059302822169408e-12\n", - "Kc = 2.564918745318097e-11\n", - "proton+COC#[Pt]<=>CX+CO-2\n", - "kf = 3.5797175052253717e-22\n", - "krev = 9.770006712968626e-20\n", - "Kc = 0.0036639867406372244\n", - "proton+O=CC(=O)C#[Pt]<=>CX+O=CC=O\n", - "kf = 5.9931479699583235e-12\n", - "krev = 0.0016900056192162703\n", - "Kc = 3.546229611199523e-9\n", - "vacantX+vacantX+OCO<=>HOX+OC[Pt]\n", - "kf = 1.653107374238179e-12\n", - "krev = 3.492310477620836e11\n", - "Kc = 4.7335635958815765e-24\n", - "vacantX+vacantX+OCO<=>HX+OC(O)[Pt]\n", - "kf = 4.0412190145177725e-23\n", - "krev = 628.7683045605482\n", - "Kc = 6.427198993979533e-26\n", - "vacantX+vacantX+OCO<=>HX+OCO[Pt]\n", - "kf = 1.1281154422531313e-23\n", - "krev = 247.99076039714222\n", - "Kc = 4.5490220702034325e-26\n", - "proton+OC(O)C#[Pt]<=>CX+OCO\n", - "kf = 0.005562206988621036\n", - "krev = 0.025459246171787766\n", - "Kc = 0.21847492856189518\n", - "proton+OCOC#[Pt]<=>CX+OCO\n", - "kf = 2.2993090387825977e-18\n", - "krev = 1.7767009384663083e-12\n", - "Kc = 1.2941452266960681e-6\n", - "proton+O=COC=[Pt]<=>O=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.03525663068036e-45\n", - "Kc = 2.4148601669491608e55\n", - "proton+O=COC=[Pt]<=>CHX+O=CO\n", - "kf = 407721.49317133107\n", - "krev = 4.66233771243883e-34\n", - "Kc = 8.745001291595743e38\n", - "proton+O=COC#[Pt]<=>O=COC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.1834993039887084e-24\n", - "Kc = 7.852993706854812e33\n", - "proton+O=C=CC#[Pt]<=>CX+C=C=O\n", - "kf = 1.255896512556004e-15\n", - "krev = 0.016900821436021087\n", - "Kc = 7.430979123176135e-14\n", - "vacantX+vacantX+COCO<=>CO[Pt]+OC[Pt]\n", - "kf = 3.0636862331912886e-9\n", - "krev = 3.008499680951675e11\n", - "Kc = 1.0183435459837431e-20\n", - "proton+CC#[Pt]<=>CX+CH4\n", - "kf = 3.172314510568854e-8\n", - "krev = 0.363285670785801\n", - "Kc = 8.732286367659409e-8\n", - "HX+O=C=C=O<=>O=C=CO[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.1302052975227224e-55\n", - "Kc = 2.7224155607861307e47\n", - "proton+O=C=CO[Pt]<=>OX+C=C=O\n", - "kf = 0.047578794564636824\n", - "krev = 2.8204743128358057e-8\n", - "Kc = 1.6869075654441754e6\n", - "proton+O=C=C=O.[Pt]<=>O=C=CO[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 2.257619247094878e-42\n", - "Kc = 2.2147224366704162e52\n", - "vacantX+vacantX+O=C=CO<=>HX+O=C=CO[Pt]\n", - "kf = 0.0007071288662616175\n", - "krev = 2.8988454126647536e-5\n", - "Kc = 24.393465866522067\n", - "vacantX+vacantX+OCCO<=>OC[Pt]+OC[Pt]\n", - "kf = 2.961131444342359e-9\n", - "krev = 1.299206322752899e13\n", - "Kc = 2.2791849088819035e-22\n", - "proton+COC(=O)C#[Pt]<=>CX+COC=O\n", - "kf = 2.520547604265173e-10\n", - "krev = 3.828537658551766e-5\n", - "Kc = 6.583577932517004e-6\n", - "proton+O=C=CC(=O)[Pt]<=>OCX+C=C=O\n", - "kf = 2.14881300259784e7\n", - "krev = 1.9623010758881652e-11\n", - "Kc = 1.0950475587061772e18\n", - "vacantX+vacantX+OC=CO<=>OC=[Pt]+OC=[Pt]\n", - "kf = 1.351949923589269e-23\n", - "krev = 7.975137957191956e11\n", - "Kc = 1.6952056890377485e-35\n", - "vacantX+OX+CH4<=>HOX+CH3X\n", - "kf = 1181.9069662995785\n", - "krev = 1.0235810933777192e20\n", - "Kc = 1.1546783874244874e-17\n", - "vacantX+HOX+CH4<=>H2OX+CH3X\n", - "kf = 5.28370763875636e9\n", - "krev = 1.2149259925984929e9\n", - "Kc = 4.348995470461149\n", - "HX+CH3X<=>vacantX+vacantX+CH4\n", - "kf = 5.733311120080377e8\n", - "krev = 8.483521653048543e-25\n", - "Kc = 6.758173497465076e32\n", - "proton+CH2X<=>CH3X\n", - "kf = 2.5e10\n", - "krev = 7.728626954425352e-28\n", - "Kc = 3.2347272222377345e37\n", - "CO2+CH3X<=>COC(=O)[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.00447183609125585\n", - "Kc = 1.463156578060128e-5\n", - "vacantX+vacantX+COC=O<=>CHO2X+CH3X\n", - "kf = 0.05589950368763065\n", - "krev = 5.054770535995559e16\n", - "Kc = 1.1058761874463802e-18\n", - "vacantX+vacantX+COO<=>OO[Pt]+CH3X\n", - "kf = 9.385776922831516e-7\n", - "krev = 3.9782610412247473e11\n", - "Kc = 2.359266228528335e-18\n", - "vacantX+vacantX+CO-2<=>HOX+CH3X\n", - "kf = 9.872876935778847e-16\n", - "krev = 6.917821124819518e13\n", - "Kc = 1.427165686657795e-29\n", - "vacantX+vacantX+COCO<=>CH3X+OCO[Pt]\n", - "kf = 3.9072411322938125e-9\n", - "krev = 8.599564777209447e13\n", - "Kc = 4.543533578174534e-23\n", - "O=O+HX<=>OO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 8.854082166234876e-41\n", - "Kc = 8.666474551788235e32\n", - "vacantX+O=O<=>O=O.[Pt]\n", - "kf = 484458.3574999593\n", - "krev = 584.920039726471\n", - "Kc = 828.247152767255\n", - "vacantX+O=C=CO<=>O=C=CO.[Pt]\n", - "kf = 359723.7676387533\n", - "krev = 0.4900054095759742\n", - "Kc = 734122.0333670193\n", - "proton+O=C=CO.[Pt]<=>O=C([Pt])CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.543989619636675e-29\n", - "Kc = 1.6191818702694958e39\n", - "proton+O=C=CO[Pt]<=>O=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.012328788524416852\n", - "Kc = 2.0277742578265605e12\n", - "vacantX+vacantX+O=C=C=O<=>OX+O=C=C=[Pt]\n", - "kf = 149.2804601441562\n", - "krev = 1.2008902564793325e-12\n", - "Kc = 1.2430816166483347e14\n", - "proton+O=C=C=[Pt]<=>O=CC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 728325.7738813914\n", - "Kc = 34325.299057824195\n", - "proton+O=C=C=[Pt]<=>O=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.992117420427329e-15\n", - "Kc = 4.1721478812771864e24\n", - "vacantX+vacantX+C=CO<=>CH2X+OC=[Pt]\n", - "kf = 3.7510196251812924e-36\n", - "krev = 6.624293894020312e13\n", - "Kc = 5.662519938264367e-50\n", - "proton+O=C(C#[Pt])CO<=>CX+O=CCO\n", - "kf = 2.1150580786972557e-17\n", - "krev = 1.2236788896896236\n", - "Kc = 1.728442074565594e-17\n", - "vacantX+vacantX+C=C<=>CH2X+CH2X\n", - "kf = 9.387035392806688e-46\n", - "krev = 5.259242712748897e15\n", - "Kc = 1.784864457776713e-61\n", - "proton+O=COC[Pt]<=>COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.124037165592671e-28\n", - "Kc = 8.002465615756261e37\n", - "proton+COC(=O)[Pt]<=>COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.484214060387906e-18\n", - "Kc = 7.175219308200797e27\n", - "vacantX+COC=O<=>COC=O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.8619443782965007\n", - "Kc = 410274.8449265323\n", - "HX+O=C=C=C=O<=>O=C=CC(=O)[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 3.561089909521239e-25\n", - "Kc = 1.4777843564830474e17\n", - "vacantX+vacantX+O=C=C=C=O<=>OCX+O=C=C=[Pt]\n", - "kf = 135.4631249389026\n", - "krev = 3.092595390223456e6\n", - "Kc = 4.3802407960361956e-5\n", - "CH3X+O=C=C=O<=>CC(=O)C(=O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 3.5093718907449027e-71\n", - "Kc = 1.6525190917893694e63\n", - "proton+OOC#[Pt]<=>OO+CX\n", - "kf = 3.959382254258936e-52\n", - "krev = 4.505410128222608e6\n", - "Kc = 8.78806177812034e-59\n", - "proton+O=CC[Pt]<=>CH2X+C=O\n", - "kf = 9.847553463617368e-13\n", - "krev = 0.8193686811731042\n", - "Kc = 1.2018464568987987e-12\n", - "HX+C=C=O<=>O=CC[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 3.6888123831707493e-19\n", - "Kc = 9.074339235332521e10\n", - "proton+C=C=O.[Pt]<=>O=CC[Pt]\n", - "kf = 4.477750650627013e6\n", - "krev = 3155.453532604055\n", - "Kc = 1419.0513675324908\n", - "vacantX+vacantX+O=CCO<=>HOX+O=CC[Pt]\n", - "kf = 3.3834985622063113e-5\n", - "krev = 2.9362980773683545e12\n", - "Kc = 1.1523007790948657e-17\n", - "vacantX+vacantX+O=CC=O<=>OX+O=CC=[Pt]\n", - "kf = 6.170227811474367e-18\n", - "krev = 2.1467268001769245e15\n", - "Kc = 2.874249210922341e-33\n", - "proton+O=CC=[Pt]<=>CHX+C=O\n", - "kf = 0.3518802014338951\n", - "krev = 0.0019581841163396926\n", - "Kc = 179.69719930710195\n", - "proton+O=CC#[Pt]<=>O=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.1385387905668107e-13\n", - "Kc = 7.9654902068249e22\n", - "proton+O=C=C[Pt]<=>O=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.814809579170971e7\n", - "Kc = 655.3407052478085\n", - "proton+O=CC=[Pt]<=>O=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.4911345025101916e-29\n", - "Kc = 5.566522219725765e38\n", - "proton+O=CCO[Pt]<=>OX+CC=O\n", - "kf = 108844.3774855493\n", - "krev = 6.551243603618761e-23\n", - "Kc = 1.6614307766761425e27\n", - "vacantX+vacantX+CC=O<=>HX+CC(=O)[Pt]\n", - "kf = 4.3209399543319175e-11\n", - "krev = 0.0003615296985530135\n", - "Kc = 1.195182573278502e-7\n", - "proton+O=CCC(=O)[Pt]<=>OCX+CC=O\n", - "kf = 7.362850070977087e6\n", - "krev = 9.270601965584902e-14\n", - "Kc = 7.94214884676321e19\n", - "proton+O=CCC#[Pt]<=>CX+CC=O\n", - "kf = 0.11748380587607415\n", - "krev = 6.387097627333538e-5\n", - "Kc = 1839.3926745898334\n", - "vacantX+vacantX+CC=O<=>CHOX+CH3X\n", - "kf = 6.063283190982672e-6\n", - "krev = 7.026751658283665e14\n", - "Kc = 8.628856526948432e-21\n", - "proton+CC(=O)C#[Pt]<=>CX+CC=O\n", - "kf = 8.247683071468342e-18\n", - "krev = 0.06355423283679383\n", - "Kc = 1.2977393799478706e-16\n", - "proton+CC(=O)C(=O)[Pt]<=>OCX+CC=O\n", - "kf = 3.422758172577326e7\n", - "krev = 2.0119060511296993e-10\n", - "Kc = 1.7012514926606157e17\n", - "vacantX+vacantX+CC=O<=>HX+O=CC[Pt]\n", - "kf = 3.2094062904328744e-20\n", - "krev = 74.41720028073364\n", - "Kc = 4.312721089110603e-22\n", - "vacantX+CH4<=>C.[Pt]\n", - "kf = 11983.404197457203\n", - "krev = 27576.843954134933\n", - "Kc = 0.4345458899280744\n", - "proton+CH3X<=>C.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.2634270430964172e-30\n", - "Kc = 1.9787450440137642e40\n", - "HX+O=C=CC=O<=>O=CCC(=O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 3.8194581898791103e-32\n", - "Kc = 6.789235995427004e23\n", - "vacantX+vacantX+O=C=CC=O<=>CHOX+O=C=C[Pt]\n", - "kf = 2.850945414803626e8\n", - "krev = 4.6591458607721776e7\n", - "Kc = 6.119030182779314\n", - "vacantX+vacantX+O=C=CC=O<=>HX+O=C=CC(=O)[Pt]\n", - "kf = 1.1776167531898308e-10\n", - "krev = 0.0005032011998508361\n", - "Kc = 2.3402502886298994e-7\n", - "vacantX+vacantX+O=C=CC=O<=>OCX+O=CC=[Pt]\n", - "kf = 0.006845452357086415\n", - "krev = 1.638610749190394e14\n", - "Kc = 4.177595173514284e-17\n", - "vacantX+vacantX+C=C(O)O<=>CH2X+OC(O)=[Pt]\n", - "kf = 1.3631835715271243e-51\n", - "krev = 1.0974745099569602e16\n", - "Kc = 1.242109551665655e-67\n", - "proton+O=C=CC=O.[Pt]<=>O=CCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.130402878837127e-16\n", - "Kc = 4.078035407151288e25\n", - "proton+O=C=CC(=O)[Pt]<=>O=C=CC=O.[Pt]\n", - "kf = 2.964275004938465e9\n", - "krev = 9.178277268525813e-12\n", - "Kc = 3.229663822756335e20\n", - "vacantX+O=C=CC=O<=>O=C=CC=O.[Pt]\n", - "kf = 327433.4917974331\n", - "krev = 0.29189612518083846\n", - "Kc = 1.1217466199476891e6\n", - "vacantX+vacantX+CC(=O)O<=>HOX+CC(=O)[Pt]\n", - "kf = 3.661873055903852e-12\n", - "krev = 2.1682718089028445e11\n", - "Kc = 1.6888441019563762e-23\n", - "vacantX+vacantX+CC(=O)O<=>CO2HX+CH3X\n", - "kf = 1.1977509649486271e-8\n", - "krev = 1.0254845667743408e14\n", - "Kc = 1.1679853639496008e-22\n", - "CO2+CH3X<=>CC(=O)O[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 3.3286101924403974e-7\n", - "Kc = 0.19656841788766613\n", - "proton+CC(=O)O[Pt]<=>OX+CC=O\n", - "kf = 6.638543952734307e-6\n", - "krev = 1.1832604608796647e-7\n", - "Kc = 56.10382643732599\n", - "vacantX+vacantX+CC(=O)O<=>HX+CC(=O)O[Pt]\n", - "kf = 2.4753542791841756e-22\n", - "krev = 11382.562807978633\n", - "Kc = 2.1746897609465158e-26\n", - "proton+CC(=O)OC#[Pt]<=>CX+CC(=O)O\n", - "kf = 3.5372794201475537e8\n", - "krev = 2.288049006228874e-19\n", - "Kc = 1.5459806195224992e27\n", - "vacantX+vacantX+CC(=O)C=O<=>CHOX+CC(=O)[Pt]\n", - "kf = 2.810784197367395e8\n", - "krev = 8.682228189641076\n", - "Kc = 3.237399589106622e7\n", - "vacantX+vacantX+CC(=O)C=O<=>CH3X+O=CC(=O)[Pt]\n", - "kf = 0.010756441693245073\n", - "krev = 2.0353876594794328e15\n", - "Kc = 5.284714016589902e-18\n", - "vacantX+vacantX+CC(=O)C=O<=>HX+CC(=O)C(=O)[Pt]\n", - "kf = 2.426386880233808e-11\n", - "krev = 0.0003222108693910823\n", - "Kc = 7.530431499158364e-8\n", - "proton+O=C=C([Pt])C=O<=>C=O+O=C=C=[Pt]\n", - "kf = 13308.622034460761\n", - "krev = 4.6234228919871786e-9\n", - "Kc = 2.8785214645897607e12\n", - "HX+O=C=C=C=O<=>O=C=C([Pt])C=O\n", - "kf = 5.262522960320117e-8\n", - "krev = 8.417963556232881e-20\n", - "Kc = 6.251539253129229e11\n", - "vacantX+vacantX+O=C=CC=O<=>HX+O=C=C([Pt])C=O\n", - "kf = 3.109950102720783e-13\n", - "krev = 0.31413419650430946\n", - "Kc = 9.900068624582613e-13\n", - "proton+O=C=C([Pt])C=O<=>O=C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.274602487927107e-16\n", - "Kc = 7.6345144463093386e25\n", - "proton+O=C=COC#[Pt]<=>CX+O=C=CO\n", - "kf = 3.333143073629419e-24\n", - "krev = 2.9895559923107984e-13\n", - "Kc = 1.1149291340260339e-11\n", - "vacantX+vacantX+COC(C)=O<=>CO[Pt]+CC(=O)[Pt]\n", - "kf = 6.614441053978493e-6\n", - "krev = 7.629970776987544e11\n", - "Kc = 8.669025409544227e-18\n", - "vacantX+vacantX+COC(C)=O<=>CH3X+COC(=O)[Pt]\n", - "kf = 1.5563360867242215e-10\n", - "krev = 4.0343976517667425e14\n", - "Kc = 3.857666549162974e-25\n", - "vacantX+vacantX+COC(C)=O<=>CH3X+CC(=O)O[Pt]\n", - "kf = 0.0003463783354588583\n", - "krev = 6.683486846094463e16\n", - "Kc = 5.182599194629471e-21\n", - "vacantX+vacantX+COO<=>HX+COO[Pt]\n", - "kf = 1.175900379595729e-21\n", - "krev = 0.27982743013843664\n", - "Kc = 4.2022341377111815e-21\n", - "proton+COO[Pt]<=>OX+CO-2\n", - "kf = 129.78074174016686\n", - "krev = 1.499485133709293e-58\n", - "Kc = 8.65502023478731e59\n", - "vacantX+vacantX+COOC<=>CH3X+COO[Pt]\n", - "kf = 1.8186835430204133e-8\n", - "krev = 4.141977957602716e12\n", - "Kc = 4.39085760869917e-21\n", - "O=O+CH3X<=>COO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 4.970959816815508e-38\n", - "Kc = 1.543639067721808e30\n", - "proton+CO[Pt]<=>CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.487564815762018e-25\n", - "Kc = 1.0049989387851077e35\n", - "proton+OC[Pt]<=>CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.512171272873819e-19\n", - "Kc = 4.535417853038886e28\n", - "vacantX+CO-2<=>CO.[Pt]\n", - "kf = 484125.61468448705\n", - "krev = 1.0558750276780043e7\n", - "Kc = 0.04585065485913965\n", - "vacantX+vacantX+CC(=O)CO<=>OC[Pt]+CC(=O)[Pt]\n", - "kf = 4.324183911493771e7\n", - "krev = 7.8667392573421875e12\n", - "Kc = 5.496793232924203e-6\n", - "vacantX+vacantX+CC(=O)CO<=>CH3X+O=C([Pt])CO\n", - "kf = 0.43146252134138535\n", - "krev = 2.5450806210309695e15\n", - "Kc = 1.695280368629765e-16\n", - "HX+O=C=C=O<=>O=C=C(O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 7.390785994602033e-44\n", - "Kc = 7.846667531546056e35\n", - "proton+O=C=C=O.[Pt]<=>O=C=C(O)[Pt]\n", - "kf = 5.0e10\n", - "krev = 7.832851008293297e-31\n", - "Kc = 6.383371769367348e40\n", - "vacantX+vacantX+O=C=CO<=>HX+O=C=C(O)[Pt]\n", - "kf = 2.8707175642480555e-12\n", - "krev = 0.04083063397693327\n", - "Kc = 7.030793511239207e-11\n", - "proton+O=C=C(O)[Pt]<=>O=C=CO.[Pt]\n", - "kf = 1.7351014576291664e10\n", - "krev = 2.4662443446341767e-14\n", - "Kc = 7.03539964077054e23\n", - "proton+O=C=C(O)[Pt]<=>H2O+O=C=C=[Pt]\n", - "kf = 1.2324712433709262e6\n", - "krev = 1.176415080398485e-31\n", - "Kc = 1.0476499867321094e37\n", - "vacantX+vacantX+O=CCC=O<=>HX+O=CCC(=O)[Pt]\n", - "kf = 3.286584099620913e-11\n", - "krev = 0.0009472638388816695\n", - "Kc = 3.469555117295539e-8\n", - "vacantX+vacantX+O=CCC=O<=>CHOX+O=CC[Pt]\n", - "kf = 5.621568394735124e8\n", - "krev = 2.2372815421494465e13\n", - "Kc = 2.51267812692642e-5\n", - "proton+O=C=C(O)C#[Pt]<=>CX+O=C=CO\n", - "kf = 3.0900625689798e-31\n", - "krev = 97363.75326657317\n", - "Kc = 3.1737299203323514e-36\n", - "proton+COOC#[Pt]<=>CX+COO\n", - "kf = 1.3396315820930446e-65\n", - "krev = 2.5e10\n", - "Kc = 5.3585263283721787e-76\n", - "vacantX+vacantX+COC=C=O<=>CO[Pt]+O=C=C[Pt]\n", - "kf = 1.4053920986837533e8\n", - "krev = 2.5815645207863396e8\n", - "Kc = 0.5443954963619013\n", - "vacantX+vacantX+COC=C=O<=>CH3X+O=C=CO[Pt]\n", - "kf = 1.4053920986837533e8\n", - "krev = 1.2268284001067661e8\n", - "Kc = 1.1455490421981163\n", - "HX+O=CC=O<=>O=CC(O)[Pt]\n", - "kf = 5.6976884072695144e-8\n", - "krev = 1.248882373151946e-25\n", - "Kc = 4.562229822244678e17\n", - "proton+O=CC(O)[Pt]<=>C=O+OC=[Pt]\n", - "kf = 1.4979350850413518e-9\n", - "krev = 7.682289195925664e-6\n", - "Kc = 0.00019498551106820976\n", - "proton+O=CC=O.[Pt]<=>O=CC(O)[Pt]\n", - "kf = 3.43386635836783e8\n", - "krev = 1.2530721027853126e-11\n", - "Kc = 2.7403581571523903e19\n", - "HX+O=C=CO<=>O=CC(O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 2.6755933088589045e-38\n", - "Kc = 1.0647523277182356e30\n", - "vacantX+vacantX+O=CCO<=>HX+O=CC(O)[Pt]\n", - "kf = 5.743984385098034e-15\n", - "krev = 0.20246227896672986\n", - "Kc = 2.8370639777506056e-14\n", - "proton+O=C=CO.[Pt]<=>O=CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.5582018736355307e-22\n", - "Kc = 9.77248912904274e31\n", - "proton+O=CC(O)[Pt]<=>H2O+O=CC=[Pt]\n", - "kf = 459.6019775429135\n", - "krev = 1.1031455244918085e-6\n", - "Kc = 4.166286018833649e8\n", - "proton+O=CC(O)C#[Pt]<=>CX+O=CCO\n", - "kf = 0.2097860124056399\n", - "krev = 0.0024507024511013467\n", - "Kc = 85.60240036947854\n", - "vacantX+vacantX+O=C=CCO<=>OC[Pt]+O=C=C[Pt]\n", - "kf = 4067.906517801298\n", - "krev = 9.581534474143486e11\n", - "Kc = 4.245568941779481e-9\n", - "proton+O=CC(=O)[Pt]<=>O=CC(O)=[Pt]\n", - "kf = 1.4625119078213113e-5\n", - "krev = 1.0085447542339824e12\n", - "Kc = 1.4501209804339615e-17\n", - "proton+O=CC(O)=[Pt]<=>OC#[Pt]+C=O\n", - "kf = 345367.8200620121\n", - "krev = 2.1066346546856475e-20\n", - "Kc = 1.6394291211996983e25\n", - "proton+O=CC(O)=[Pt]<=>H2O+O=CC#[Pt]\n", - "kf = 109541.91076063467\n", - "krev = 6.52855201530546e-37\n", - "Kc = 1.6778898368861259e41\n", - "proton+O=C=C(O)[Pt]<=>O=CC(O)=[Pt]\n", - "kf = 266253.7431100425\n", - "krev = 124230.61178859882\n", - "Kc = 2.1432217009695007\n", - "proton+O=CC(O)=[Pt]<=>O=CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.793151847783197e-46\n", - "Kc = 3.207944678649035e55\n", - "proton+OC(O)[Pt]<=>OCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.3128823116835e-26\n", - "Kc = 5.796587570283467e35\n", - "proton+OCO[Pt]<=>OCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.052557862362137e-26\n", - "Kc = 8.189852945376913e35\n", - "vacantX+OCO<=>OCO.[Pt]\n", - "kf = 395377.4080430906\n", - "krev = 715.0601225795458\n", - "Kc = 552.9289014422803\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.079525546868e-12\n", - "Kc = 1.2021973010936467e22\n", - "vacantX+O=C=C=C=O<=>O=C=C=C=O.[Pt]\n", - "kf = 332249.5811031886\n", - "krev = 401.14766551623046\n", - "Kc = 828.2475748067037\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 4.91573386591171e-7\n", - "Kc = 5.08571063485824e16\n", - "proton+O=CCO[Pt]<=>O=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.8816895227328687e-31\n", - "Kc = 1.3285932507978942e41\n", - "proton+O=C([Pt])CO<=>O=CCO.[Pt]\n", - "kf = 3.74256001789537e8\n", - "krev = 9.536073355505413e-9\n", - "Kc = 3.9246342581191416e16\n", - "vacantX+O=CCO<=>O=CCO.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 1291.5767888759226\n", - "Kc = 273.8002875141987\n", - "proton+O=CC(O)[Pt]<=>O=CCO.[Pt]\n", - "kf = 1.712472301799593e10\n", - "krev = 2.6335036754646568e-14\n", - "Kc = 6.5026387384762e23\n", - "proton+OCC#[Pt]<=>OCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.6468663797080987e-6\n", - "Kc = 6.855200437039605e15\n", - "proton+OCC=[Pt]<=>CHX+CO-2\n", - "kf = 2.437334851076409e7\n", - "krev = 3.684139726492616e-11\n", - "Kc = 6.615750302708541e17\n", - "vacantX+vacantX+O=CCO<=>OX+OCC=[Pt]\n", - "kf = 3.3881471741726223e-34\n", - "krev = 2.264159139077055e16\n", - "Kc = 1.4964262518904662e-50\n", - "vacantX+vacantX+O=C=CCO<=>OCX+OCC=[Pt]\n", - "kf = 1.8009876630720204e-13\n", - "krev = 6.668943472119082e14\n", - "Kc = 2.7005591974222413e-28\n", - "vacantX+vacantX+C=CC=O<=>CH2X+O=CC=[Pt]\n", - "kf = 3.2830355290077765e-39\n", - "krev = 2.9277080237249806e14\n", - "Kc = 1.121367124864694e-53\n", - "vacantX+vacantX+C=COC=O<=>CH2X+O=COC=[Pt]\n", - "kf = 1.0242943870290668e-63\n", - "krev = 2.920849603333263e13\n", - "Kc = 3.5068371403311754e-77\n", - "vacantX+O=C=CCO<=>O=C=CCO.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 1179.037991138623\n", - "Kc = 273.8002884035305\n", - "vacantX+vacantX+O=CC=CO<=>OC=[Pt]+O=CC=[Pt]\n", - "kf = 6.284377773759944e-35\n", - "krev = 2.1623088290446475e12\n", - "Kc = 2.90632757418676e-47\n", - "vacantX+vacantX+COC<=>CH3X+CO[Pt]\n", - "kf = 3.3416169046706564e-11\n", - "krev = 3.110510590664853e12\n", - "Kc = 1.0742985137872191e-23\n", - "proton+O=C=CC(O)[Pt]<=>OC=[Pt]+C=C=O\n", - "kf = 7.886335155622577e-9\n", - "krev = 1.1676117437495351e-7\n", - "Kc = 0.0675424446340125\n", - "HX+O=C=CC=O<=>O=C=CC(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 3.0624966294759025e-24\n", - "Kc = 8.467340919226885e15\n", - "proton+O=C=CC=O.[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 5.4417257022505686e7\n", - "krev = 1.0699402207865258e-10\n", - "Kc = 5.086009102686402e17\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=CC(O)[Pt]\n", - "kf = 2.2665619116480148e-11\n", - "krev = 0.03466826587817799\n", - "Kc = 6.537857761944495e-10\n", - "proton+O=C=CC(O)[Pt]<=>O=C=CCO.[Pt]\n", - "kf = 1.693513701515947e9\n", - "krev = 6.001577582317764e-11\n", - "Kc = 2.8217809039168078e19\n", - "proton+O=C=CC=[Pt]<=>CHX+C=C=O\n", - "kf = 181.35768264661723\n", - "krev = 8.307531938850336e-7\n", - "Kc = 2.183051283841528e8\n", - "proton+O=C=CC#[Pt]<=>O=C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.768026569342988e-11\n", - "Kc = 1.4140058997693788e21\n", - "vacantX+vacantX+O=C=CC=O<=>OX+O=C=CC=[Pt]\n", - "kf = 3.709849833927781e-21\n", - "krev = 2.4389911159903437e17\n", - "Kc = 1.5210591828750508e-38\n", - "proton+O=C=CC(O)[Pt]<=>H2O+O=C=CC=[Pt]\n", - "kf = 4.694863820330143\n", - "krev = 3.9520471176425216e-5\n", - "Kc = 118795.74510565875\n", - "vacantX+vacantX+CCO<=>CH3X+OC[Pt]\n", - "kf = 1.5510087911871897e-15\n", - "krev = 9.749013808701775e13\n", - "Kc = 1.5909391674086975e-29\n", - "proton+O=C=C([Pt])CO<=>CO-2+O=C=C=[Pt]\n", - "kf = 259142.28390262663\n", - "krev = 5.010713983419634e-21\n", - "Kc = 5.171763640074528e25\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=C([Pt])CO\n", - "kf = 4.040764431615523e-20\n", - "krev = 30.812673220085827\n", - "Kc = 1.3113969056672023e-21\n", - "proton+O=C=C([Pt])CO<=>O=C=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.777114479215893e-21\n", - "Kc = 1.4067748753603438e31\n", - "proton+O=C=CC[Pt]<=>CH2X+C=C=O\n", - "kf = 6.0148104045883e-8\n", - "krev = 8.74545093406659e-6\n", - "Kc = 0.006877644674854341\n", - "vacantX+vacantX+O=C=CCO<=>HOX+O=C=CC[Pt]\n", - "kf = 8.032715739528718e-6\n", - "krev = 4.997427676480693e14\n", - "Kc = 1.6073700830795308e-20\n", - "proton+O=C=CC=[Pt]<=>O=C=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.1155543114237032e-25\n", - "Kc = 1.1817233840324226e35\n", - "vacantX+vacantX+CC(O)O<=>CH3X+OC(O)[Pt]\n", - "kf = 1.0212279299691738e-21\n", - "krev = 4.839386960246169e15\n", - "Kc = 2.1102423475497943e-37\n", - "proton+O=C=CC(O)=[Pt]<=>OC#[Pt]+C=C=O\n", - "kf = 1.5097720767202745e6\n", - "krev = 3.361950781834918e-17\n", - "Kc = 4.490761985207459e22\n", - "proton+O=C=CC(O)=[Pt]<=>H2O+O=C=CC#[Pt]\n", - "kf = 5.803789817126122e6\n", - "krev = 2.7232165859221153e-28\n", - "Kc = 2.1312259359498893e34\n", - "proton+O=C=CC(=O)[Pt]<=>O=C=CC(O)=[Pt]\n", - "kf = 0.6530550593549805\n", - "krev = 1.0085447542339824e12\n", - "Kc = 6.475221417923034e-13\n", - "proton+O=C=CC(O)=[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.85508059604632e-41\n", - "Kc = 2.5367626125786886e50\n", - "C=O+O=C=C[Pt]<=>O=C=CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 80798.59947863563\n", - "Kc = 4.901904683810505e-13\n", - "HX+O=C=CC=O<=>O=C=CCO[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 2.019947796444839e-5\n", - "Kc = 0.0012837560986177624\n", - "proton+O=C=CC=O.[Pt]<=>O=C=CCO[Pt]\n", - "kf = 278.5863350248319\n", - "krev = 3612.827309769227\n", - "Kc = 0.07711033800910536\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=CCO[Pt]\n", - "kf = 7.342900678318069e-26\n", - "krev = 740.7927312780465\n", - "Kc = 9.912220204496055e-29\n", - "proton+O=C=CCO[Pt]<=>O=C=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3432355963676785e-28\n", - "Kc = 1.861177597407629e38\n", - "vacantX+vacantX+CCOC=O<=>CH3X+O=COC[Pt]\n", - "kf = 1.714178070740009e-17\n", - "krev = 1.2983121019578911e14\n", - "Kc = 1.3203127877765141e-31\n", - "proton+O=CC([Pt])C=O<=>C=O+O=CC=[Pt]\n", - "kf = 1.0131844482393167e-10\n", - "krev = 2.9534786470384583e-7\n", - "Kc = 0.00034304783251277847\n", - "HX+O=C=CC=O<=>O=CC([Pt])C=O\n", - "kf = 2.5931203025755725e-8\n", - "krev = 5.183135272095574e-24\n", - "Kc = 5.002995612590211e15\n", - "proton+O=C=CC=O.[Pt]<=>O=CC([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 8.319166178505196e-8\n", - "Kc = 3.005108861101275e17\n", - "vacantX+vacantX+O=CCC=O<=>HX+O=CC([Pt])C=O\n", - "kf = 6.269624738894468e-15\n", - "krev = 24.522149705338403\n", - "Kc = 2.556719053684591e-16\n", - "proton+O=CC(=[Pt])C=O<=>C=O+O=CC#[Pt]\n", - "kf = 0.04202179791424184\n", - "krev = 2.102387409121332e-9\n", - "Kc = 1.9987656761987723e7\n", - "proton+O=C=C([Pt])C=O<=>O=CC(=[Pt])C=O\n", - "kf = 2.5e10\n", - "krev = 5.057292696382588\n", - "Kc = 4.943356357025204e9\n", - "proton+O=CC(=[Pt])C=O<=>O=CC([Pt])C=O\n", - "kf = 2.5e10\n", - "krev = 5.3866690937421086e-24\n", - "Kc = 4.641087017771969e33\n", - "vacantX+vacantX+COCC=O<=>CH3X+O=CCO[Pt]\n", - "kf = 1.7650043109029407e-12\n", - "krev = 1.4735149295451475e13\n", - "Kc = 1.1978190892492496e-25\n", - "vacantX+vacantX+COCC=O<=>CO[Pt]+O=CC[Pt]\n", - "kf = 10.947009513309483\n", - "krev = 5.112987413682155e11\n", - "Kc = 2.1410202348661592e-11\n", - "proton+O=CCC(=O)[Pt]<=>O=CCC=O.[Pt]\n", - "kf = 2.1814901321970692e8\n", - "krev = 5.7550523540318155e-8\n", - "Kc = 3.7905652251256815e15\n", - "vacantX+O=CCC=O<=>O=CCC=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 165389.8266532618\n", - "Kc = 1.951879075907524\n", - "proton+O=CC([Pt])C=O<=>O=CCC=O.[Pt]\n", - "kf = 1.6062704929440186e10\n", - "krev = 3.122654421781107e-14\n", - "Kc = 5.1439265316711864e23\n", - "proton+O=CCC#[Pt]<=>O=CCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.03648176110191e-17\n", - "Kc = 4.141485220927174e26\n", - "proton+O=CCC=[Pt]<=>CHX+CC=O\n", - "kf = 1.0605779567215914e7\n", - "krev = 5.748508015003e-13\n", - "Kc = 1.8449621257439228e19\n", - "vacantX+vacantX+O=CCC=O<=>OX+O=CCC=[Pt]\n", - "kf = 1.2771337705277995e-31\n", - "krev = 6.599290845791489e16\n", - "Kc = 1.935259106426951e-48\n", - "vacantX+vacantX+CCOO<=>CH3X+OOC[Pt]\n", - "kf = 1.1728434846364774e-18\n", - "krev = 2.6840450809869076e16\n", - "Kc = 4.3696862356918e-35\n", - "proton+OOCC#[Pt]<=>CX+COO\n", - "kf = 0.24698833297799483\n", - "krev = 0.0004336424509567548\n", - "Kc = 569.5667765760919\n", - "vacantX+vacantX+C=C=O<=>OX+C=C=[Pt]\n", - "kf = 5.2796000958546504e-37\n", - "krev = 1.4614931014553018e17\n", - "Kc = 3.612470076387919e-54\n", - "proton+C=C=[Pt]<=>CC#[Pt]\n", - "kf = 10.738937415423795\n", - "krev = 4.122167482176662e-33\n", - "Kc = 2.60516766042539e33\n", - "vacantX+vacantX+CC(C)=O<=>CH3X+CC(=O)[Pt]\n", - "kf = 0.0015322757193851075\n", - "krev = 1.9084257758101816e14\n", - "Kc = 8.029003479239911e-18\n", - "vacantX+vacantX+C=C=C=O<=>CH2X+O=C=C=[Pt]\n", - "kf = 0.014873013888318402\n", - "krev = 6.520037160662236e15\n", - "Kc = 2.2811240981957472e-18\n", - "HOX+C=C=C=O<=>O=C=C([Pt])CO\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.9529365102554657e-31\n", - "Kc = 9.99708792916859e22\n", - "HX+C=C=C=O<=>O=C=CC[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.4091973858076736e-32\n", - "Kc = 1.225336127134283e24\n", - "vacantX+vacantX+C=C=C=O<=>OCX+C=C=[Pt]\n", - "kf = 0.8504584217531632\n", - "krev = 1.347597642765549e15\n", - "Kc = 6.310922450174717e-16\n", - "proton+O=C(O)C=[Pt]<=>CHX+O=CO\n", - "kf = 7.88145235948431e7\n", - "krev = 1.995696153847229e-7\n", - "Kc = 3.949224607308452e14\n", - "proton+O=C(O)C#[Pt]<=>O=C(O)C=[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.424855572557093e-13\n", - "Kc = 3.3670688615684534e22\n", - "vacantX+vacantX+CC=C=O<=>CH3X+O=C=C[Pt]\n", - "kf = 0.0008567749561878586\n", - "krev = 1.2359860589695025e13\n", - "Kc = 6.931914401220598e-17\n", - "vacantX+vacantX+CC=C=O<=>HX+O=C=CC[Pt]\n", - "kf = 2.2773385768535307e-19\n", - "krev = 181.8091471864856\n", - "Kc = 1.2525984594810374e-21\n", - "proton+O=C=CCO[Pt]<=>OX+CC=C=O\n", - "kf = 3.801213612232799e6\n", - "krev = 3.4005935521726275e-15\n", - "Kc = 1.1178088630451637e21\n", - "proton+CC(=O)[Pt]<=>CC=O.[Pt]\n", - "kf = 2.2108223076011086e9\n", - "krev = 2.493722128340101e-11\n", - "Kc = 8.865551949337277e19\n", - "proton+O=CC[Pt]<=>CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0175396707648368e-24\n", - "Kc = 2.456906665978799e34\n", - "vacantX+CC=O<=>CC=O.[Pt]\n", - "kf = 412885.969273148\n", - "krev = 2.625517699834265\n", - "Kc = 157258.8786200951\n", - "proton+CC=[Pt]<=>CHX+CH4\n", - "kf = 3.754229088708618e7\n", - "krev = 3.193900280463504e-10\n", - "Kc = 1.1754371642948722e17\n", - "proton+CC#[Pt]<=>CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.101069134371629e-9\n", - "Kc = 3.086012424450092e18\n", - "vacantX+vacantX+CC=O<=>OX+CC=[Pt]\n", - "kf = 6.186864182993887e-31\n", - "krev = 2.034915252803989e19\n", - "Kc = 3.04035471475717e-50\n", - "vacantX+vacantX+CC=C=O<=>OCX+CC=[Pt]\n", - "kf = 5.619880038277716e-8\n", - "krev = 4.919193785592355e16\n", - "Kc = 1.14243924578405e-24\n", - "vacantX+vacantX+CC<=>CH3X+CH3X\n", - "kf = 1.6866972609475142e-22\n", - "krev = 6.547125244410207e13\n", - "Kc = 2.576241018739606e-36\n", - "proton+O=C=CC[Pt]<=>CC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.381078389100095e-19\n", - "Kc = 1.0499444333476355e29\n", - "vacantX+CC=C=O<=>CC=C=O.[Pt]\n", - "kf = 365995.57053717994\n", - "krev = 187509.1639624155\n", - "Kc = 1.9518809790573244\n", - "proton+O=C(O)C[Pt]<=>CH2X+O=CO\n", - "kf = 5.038535015011119e-9\n", - "krev = 7.877133180076684e-5\n", - "Kc = 6.396407042799381e-5\n", - "HOX+C=C=O<=>O=C(O)C[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.348252838458729e-29\n", - "Kc = 4.5553052781738184e20\n", - "vacantX+vacantX+CC(=O)O<=>HX+O=C(O)C[Pt]\n", - "kf = 1.1112170024966995e-23\n", - "krev = 36323.66987445037\n", - "Kc = 3.0592090676342045e-28\n", - "proton+O=C(O)C=[Pt]<=>O=C(O)C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0876086200539217e-33\n", - "Kc = 2.2986209872776243e43\n", - "vacantX+vacantX+O=C=C=CO<=>OC=[Pt]+O=C=C=[Pt]\n", - "kf = 0.004371453552681894\n", - "krev = 1.2572855491392857e13\n", - "Kc = 3.476897953431907e-16\n", - "HX+O=C=C=CO<=>O=C=CC(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.3635197599529065e-33\n", - "Kc = 1.9017841755847633e25\n", - "HX+O=C=C=CO<=>O=C=C([Pt])CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 6.797711819853139e-22\n", - "Kc = 3.814695843684052e13\n", - "proton+O=C(O)CC#[Pt]<=>CX+CC(=O)O\n", - "kf = 0.12574987603391333\n", - "krev = 9.921358720719502e-5\n", - "Kc = 1267.4662772882168\n", - "proton+CC([Pt])=C=O<=>CH4+O=C=C=[Pt]\n", - "kf = 49487.72961177987\n", - "krev = 1.2730900614037961e-24\n", - "Kc = 3.8872135689451003e28\n", - "HX+C=C=C=O<=>CC([Pt])=C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.301177455844525e-32\n", - "Kc = 1.2828548214436644e24\n", - "vacantX+vacantX+CC=C=O<=>HX+CC([Pt])=C=O\n", - "kf = 4.581183222917958e-20\n", - "krev = 34.93361388628861\n", - "Kc = 1.3113968791863429e-21\n", - "proton+CC([Pt])=C=O<=>CC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.492848961236613e-19\n", - "Kc = 1.0028686209532082e29\n", - "CH3X+O=C=C=O<=>CC(=C=O)O[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.951682102619952e-64\n", - "Kc = 1.9647454732667077e56\n", - "proton+CC(=C=O)O[Pt]<=>OX+CC=C=O\n", - "kf = 1.920567374031219e-6\n", - "krev = 5.0434729686975995e-5\n", - "Kc = 0.03808025513274787\n", - "vacantX+C=C<=>C=C.[Pt]\n", - "kf = 36.21750369826068\n", - "krev = 0.32335117013731834\n", - "Kc = 112.00671914340097\n", - "vacantX+vacantX+C=CO<=>HOX+C=C[Pt]\n", - "kf = 1.7018617233469498e-12\n", - "krev = 4.164837143763027e13\n", - "Kc = 4.086262354568991e-26\n", - "vacantX+vacantX+C=C<=>HX+C=C[Pt]\n", - "kf = 6.071347272542775e-23\n", - "krev = 1180.067101472276\n", - "Kc = 5.144916983930861e-26\n", - "vacantX+vacantX+C=CC=O<=>CHOX+C=C[Pt]\n", - "kf = 0.3274906030624493\n", - "krev = 2.9425898600264806e14\n", - "Kc = 1.1129332276687114e-15\n", - "vacantX+vacantX+C=COC=O<=>CHO2X+C=C[Pt]\n", - "kf = 0.2513917911405871\n", - "krev = 1.0405847657707406e16\n", - "Kc = 2.4158703779829617e-17\n", - "proton+C=C=[Pt]<=>C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.446578752089028e-33\n", - "Kc = 1.0218350820979533e43\n", - "proton+C=C[Pt]<=>CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 31.775139733809926\n", - "Kc = 7.867786014296917e8\n", - "proton+C=C[Pt]<=>C=C.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.7043133558442046e-25\n", - "Kc = 1.4668664019015827e35\n", - "proton+C=CC#[Pt]<=>CX+C=C\n", - "kf = 1.0856530221273585e-15\n", - "krev = 0.12983129718682296\n", - "Kc = 8.36202861444987e-15\n", - "vacantX+CC(=O)O<=>CC(=O)O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 181176.05501028927\n", - "Kc = 1.9518809818483447\n", - "proton+CC(=O)O[Pt]<=>CC(=O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.133892027559991e-24\n", - "Kc = 6.04756965913213e33\n", - "proton+O=C(O)C[Pt]<=>CC(=O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.815284645396005e-26\n", - "Kc = 4.2990157016290936e35\n", - "proton+C=CC(=O)[Pt]<=>OCX+C=C\n", - "kf = 7.087170621400232e6\n", - "krev = 2.9783308105065206e-7\n", - "Kc = 2.3795780496911715e13\n", - "vacantX+vacantX+C=CC=O<=>HX+C=CC(=O)[Pt]\n", - "kf = 3.052485738368744e-11\n", - "krev = 0.0007099643372969683\n", - "Kc = 4.29949164769375e-8\n", - "HX+C=C=C=O<=>C=CC(=O)[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 5.604440911093213e-48\n", - "Kc = 5.267388203494818e39\n", - "HX+O=C=CC=O<=>O=CC=CO[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 5.6159867257682645e-34\n", - "Kc = 4.61739037002591e25\n", - "proton+O=C=CC=O.[Pt]<=>O=CC=CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 9.013912308921113e-18\n", - "Kc = 2.7734904826239954e27\n", - "proton+O=CC=CO[Pt]<=>OX+C=CC=O\n", - "kf = 3.6615493516163485e-10\n", - "krev = 9.407550626549198e-5\n", - "Kc = 3.892138875429521e-6\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC=CO[Pt]\n", - "kf = 4.135805741920728e-10\n", - "krev = 0.028732529553568358\n", - "Kc = 1.4394158141245496e-8\n", - "HX+C=C=O<=>C=CO[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.272169613200064e-8\n", - "Kc = 0.46029640012283785\n", - "proton+C=C=O.[Pt]<=>C=CO[Pt]\n", - "kf = 2.7021695253394946e-5\n", - "krev = 3753.979595717479\n", - "Kc = 7.19814654406251e-9\n", - "vacantX+vacantX+C=CO<=>HX+C=CO[Pt]\n", - "kf = 1.5839272910037507e-20\n", - "krev = 3600.161649580889\n", - "Kc = 4.399600476795654e-24\n", - "proton+C=CO[Pt]<=>OX+C=C\n", - "kf = 6.694428008398142e6\n", - "krev = 4.294813980591457e-9\n", - "Kc = 1.5587236231070068e15\n", - "vacantX+vacantX+C=COC=O<=>CHOX+C=CO[Pt]\n", - "kf = 0.024290856013790354\n", - "krev = 3.5586883050271985e15\n", - "Kc = 6.825789148062155e-18\n", - "vacantX+vacantX+O=CCCO<=>OC[Pt]+O=CC[Pt]\n", - "kf = 2.162232232095232e-5\n", - "krev = 5.66671683371172e13\n", - "Kc = 3.815670158833332e-19\n", - "proton+C=COC(=O)[Pt]<=>OCX+C=CO\n", - "kf = 8.547694380469097e6\n", - "krev = 5.219823560516419e-10\n", - "Kc = 1.637544695020963e16\n", - "vacantX+vacantX+C=COC=O<=>HX+C=COC(=O)[Pt]\n", - "kf = 3.5117597357119104e-15\n", - "krev = 0.7837038908782975\n", - "Kc = 4.480977798612533e-15\n", - "CO2+C=C[Pt]<=>C=COC(=O)[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.08399332498323721\n", - "Kc = 7.789900440580834e-7\n", - "proton+C=COC#[Pt]<=>CX+C=CO\n", - "kf = 3.59319568894763e-23\n", - "krev = 3.7552909398960855e-5\n", - "Kc = 9.568355012853036e-19\n", - "vacantX+vacantX+CCC=O<=>CH3X+O=CC[Pt]\n", - "kf = 1.2257627381394946e-12\n", - "krev = 3.270257576074817e14\n", - "Kc = 3.748214657790771e-27\n", - "proton+CC(O)=[Pt]<=>OC#[Pt]+CH4\n", - "kf = 7.023325690411809e6\n", - "krev = 0.001122962882704699\n", - "Kc = 6.254281239906934e9\n", - "proton+CC(=O)[Pt]<=>CC(O)=[Pt]\n", - "kf = 9.881755573608883e9\n", - "krev = 1.0085447542339819e12\n", - "Kc = 0.009798033782957261\n", - "proton+CC(O)=[Pt]<=>H2O+CC#[Pt]\n", - "kf = 7.254296675241664e9\n", - "krev = 2.8720393080667615e-6\n", - "Kc = 2.5258347456688205e15\n", - "vacantX+vacantX+CC(=O)O<=>OX+CC(O)=[Pt]\n", - "kf = 1.1829749543892744e-33\n", - "krev = 3.758913107590896e15\n", - "Kc = 3.1471197139415875e-49\n", - "vacantX+vacantX+CC(O)=C=O<=>CH3X+O=C=C(O)[Pt]\n", - "kf = 1.049990631922765e-6\n", - "krev = 1.7955210884029898e15\n", - "Kc = 5.847832357439309e-22\n", - "vacantX+vacantX+CC(O)=C=O<=>HOX+CC([Pt])=C=O\n", - "kf = 0.0029164033711847528\n", - "krev = 3.4437539939134434e12\n", - "Kc = 8.468675103794464e-16\n", - "vacantX+vacantX+CC(O)=C=O<=>HX+CC(=C=O)O[Pt]\n", - "kf = 1.7528367761452354e-6\n", - "krev = 1.1970864565480504e-5\n", - "Kc = 0.14642524494009906\n", - "vacantX+vacantX+CC(O)=C=O<=>OCX+CC(O)=[Pt]\n", - "kf = 65.80946386077328\n", - "krev = 1217.699742052305\n", - "Kc = 0.054044081301896585\n", - "vacantX+vacantX+C=CC=O<=>HX+O=CC=C[Pt]\n", - "kf = 6.342176392543457e-21\n", - "krev = 776.2437464870187\n", - "Kc = 8.170341366672147e-24\n", - "vacantX+vacantX+O=CC=CO<=>HOX+O=CC=C[Pt]\n", - "kf = 4.672349699632388e-15\n", - "krev = 8.81363422062413e13\n", - "Kc = 5.301274800693419e-29\n", - "proton+O=CC=C[Pt]<=>O=CCC=[Pt]\n", - "kf = 1.2673656466904085e10\n", - "krev = 1.0824082827935274e8\n", - "Kc = 117.08757839689983\n", - "proton+C=CC(=O)O[Pt]<=>OX+C=CC=O\n", - "kf = 4.524546416801015\n", - "krev = 7.68227583414659e-9\n", - "Kc = 5.889591202505473e8\n", - "CO2+C=C[Pt]<=>C=CC(=O)O[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 450683.30306117237\n", - "Kc = 1.4517947189269602e-13\n", - "vacantX+vacantX+O=C=CO<=>OX+OC=C=[Pt]\n", - "kf = 7.548264554696059e-34\n", - "krev = 5.749061160710156e15\n", - "Kc = 1.3129560364189368e-49\n", - "proton+OC=C=[Pt]<=>OCC#[Pt]\n", - "kf = 0.00032547344886471076\n", - "krev = 1.1489507349403094e-46\n", - "Kc = 2.832788551909668e42\n", - "vacantX+vacantX+O=C=C=CO<=>OCX+OC=C=[Pt]\n", - "kf = 1.463392220587488e-22\n", - "krev = 7.968303762369095e13\n", - "Kc = 1.8365166090912173e-36\n", - "proton+CC[Pt]<=>CH2X+CH4\n", - "kf = 1.4846524062695914\n", - "krev = 9.859129077434927e-6\n", - "Kc = 150586.56749586415\n", - "HX+C=C<=>CC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 3.1627439012977165e-12\n", - "Kc = 25911.109388377805\n", - "vacantX+vacantX+CCO<=>HOX+CC[Pt]\n", - "kf = 2.1035625708276702e-15\n", - "krev = 1.0019023766861524e15\n", - "Kc = 2.099568400850909e-30\n", - "vacantX+vacantX+CCOC=O<=>CHO2X+CC[Pt]\n", - "kf = 0.08561452397466171\n", - "krev = 3.215769317238553e17\n", - "Kc = 2.6623341268826044e-19\n", - "vacantX+vacantX+CCOO<=>OO[Pt]+CC[Pt]\n", - "kf = 1.262172875849309e-6\n", - "krev = 1.5596341944506717e13\n", - "Kc = 8.092749443044025e-20\n", - "proton+CC=[Pt]<=>CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.602708332438123e-27\n", - "Kc = 2.9060615603731233e36\n", - "vacantX+vacantX+CC<=>HX+CC[Pt]\n", - "kf = 8.697106954471648e-14\n", - "krev = 5.359609736165605e16\n", - "Kc = 1.6227127314485718e-30\n", - "proton+C=C.[Pt]<=>CC[Pt]\n", - "kf = 5.504599623053448e9\n", - "krev = 0.3531497863658743\n", - "Kc = 1.558715263486103e10\n", - "vacantX+vacantX+CCC=O<=>CHOX+CC[Pt]\n", - "kf = 0.0004422945453165714\n", - "krev = 9.363325052982716e15\n", - "Kc = 4.723691026572629e-20\n", - "vacantX+vacantX+CC(O)C=O<=>CH3X+O=CC(O)[Pt]\n", - "kf = 9.477814531468979e-7\n", - "krev = 7.52142668687151e15\n", - "Kc = 1.2601086105129898e-22\n", - "proton+CCC#[Pt]<=>CX+CC\n", - "kf = 3.73018742862406e-11\n", - "krev = 0.075105066117345\n", - "Kc = 4.966625583946592e-10\n", - "C=O+CH3X<=>CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.1808191230067762e-17\n", - "Kc = 3.354171909251678e9\n", - "HX+CC=O<=>CCO[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 2.639709061724686e-6\n", - "Kc = 0.012387213631168494\n", - "vacantX+vacantX+CCO<=>HX+CCO[Pt]\n", - "kf = 5.372480262216755e-24\n", - "krev = 2113.809062877283\n", - "Kc = 2.5416109508508876e-27\n", - "vacantX+vacantX+CCOC=O<=>CHOX+CCO[Pt]\n", - "kf = 4.80530366959931e-5\n", - "krev = 5.681813674074216e13\n", - "Kc = 8.457341168235823e-19\n", - "vacantX+vacantX+CCOO<=>HOX+CCO[Pt]\n", - "kf = 3.028654941635431e8\n", - "krev = 1.2132864881112858e-12\n", - "Kc = 2.496240559268171e20\n", - "proton+CC=O.[Pt]<=>CCO[Pt]\n", - "kf = 19418.796323941955\n", - "krev = 3658.802750537776\n", - "Kc = 5.30741820424393\n", - "proton+CCO[Pt]<=>OX+CC\n", - "kf = 1.5180806810718186e7\n", - "krev = 3.4536717602694347e-12\n", - "Kc = 4.395555763392486e18\n", - "proton+CCOC(=O)[Pt]<=>OCX+CCO\n", - "kf = 1.100364657251968e9\n", - "krev = 4.5302115405928314e-10\n", - "Kc = 2.4289476272623954e18\n", - "vacantX+vacantX+CCOC=O<=>HX+CCOC(=O)[Pt]\n", - "kf = 2.5742212027881315e-15\n", - "krev = 0.39729482671494754\n", - "Kc = 6.479372570927264e-15\n", - "CO2+CC[Pt]<=>CCOC(=O)[Pt]\n", - "kf = 3.860701485876577e-7\n", - "krev = 0.0037771400241392917\n", - "Kc = 0.00010221229451921966\n", - "CH3X+C=C=O<=>CCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.9339597186194493e-34\n", - "Kc = 1.7308289628845924e26\n", - "HX+CC=C=O<=>CCC(=O)[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 2.728234417234893e-33\n", - "Kc = 1.0624138213938816e25\n", - "proton+CCC(=O)[Pt]<=>OCX+CC\n", - "kf = 3.3183098775357734e7\n", - "krev = 1.723115430616528e-10\n", - "Kc = 1.9257618024745373e17\n", - "proton+CC=C=O.[Pt]<=>CCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.816709270833084e-23\n", - "Kc = 3.667458740974689e32\n", - "vacantX+vacantX+CCC=O<=>HX+CCC(=O)[Pt]\n", - "kf = 1.3037608552158366e-12\n", - "krev = 0.18236199715464047\n", - "Kc = 7.149301255514685e-12\n", - "vacantX+vacantX+C=C(O)C=O<=>CH2X+O=CC(O)=[Pt]\n", - "kf = 3.506980389191063e-59\n", - "krev = 1.6121784785918364e12\n", - "Kc = 2.1753053001019147e-71\n", - "proton+CCOC#[Pt]<=>CX+CCO\n", - "kf = 1.6403573057503937e-22\n", - "krev = 1.0480859144262605e-13\n", - "Kc = 1.5650981309565184e-9\n", - "proton+CCC(=O)O[Pt]<=>OX+CCC=O\n", - "kf = 5.622114816602621e-8\n", - "krev = 4.785365563630673e-7\n", - "Kc = 0.11748558687619057\n", - "CO2+CC[Pt]<=>CCC(=O)O[Pt]\n", - "kf = 3.860701485876577e-7\n", - "krev = 2.2515045234693432e-8\n", - "Kc = 17.147207325738\n", - "vacantX+vacantX+OC=CCO<=>OC=[Pt]+OCC=[Pt]\n", - "kf = 3.6700973989487563e-44\n", - "krev = 3.0504263460080312e13\n", - "Kc = 1.203142440646588e-57\n", - "proton+CC(=C=O)O[Pt]<=>CC(O)=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 27.83415070046663\n", - "Kc = 8.981772165076653e8\n", - "vacantX+CC(O)=C=O<=>CC(O)=C=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 165389.73964983693\n", - "Kc = 1.9518801026953096\n", - "proton+OOC=[Pt]<=>OO+CHX\n", - "kf = 2.8719882764673755e7\n", - "krev = 8.077545633440945e-25\n", - "Kc = 3.555520955000709e31\n", - "proton+OOC=[Pt]<=>OOC[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.62255074484058e-37\n", - "Kc = 2.899374064566577e46\n", - "proton+OOC#[Pt]<=>OOC=[Pt]\n", - "kf = 3.432151727081939e-44\n", - "krev = 3342.777740155216\n", - "Kc = 1.0267364431242663e-47\n", - "vacantX+vacantX+C=CCO<=>CH2X+OCC=[Pt]\n", - "kf = 3.3256293066300124e-48\n", - "krev = 2.638642223210571e15\n", - "Kc = 1.2603562837645906e-63\n", - "vacantX+vacantX+C=CCO<=>OC[Pt]+C=C[Pt]\n", - "kf = 1.4930923415267688e-9\n", - "krev = 1.1121057711212152e14\n", - "Kc = 1.3425812366942817e-23\n", - "vacantX+OO<=>OO.[Pt]\n", - "kf = 469882.2241291155\n", - "krev = 15.560302693769444\n", - "Kc = 30197.498941795184\n", - "proton+OO[Pt]<=>OO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.110596489625074e-24\n", - "Kc = 2.251042591395165e34\n", - "C=O+CO[Pt]<=>COCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 9.545218685674386e-14\n", - "Kc = 414937.62088874576\n", - "HX+COC=O<=>COCO[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 0.02522938529859348\n", - "Kc = 1.1100614687459063e-6\n", - "vacantX+vacantX+COCO<=>HX+COCO[Pt]\n", - "kf = 1.0488506310161173e-19\n", - "krev = 521.1543106644776\n", - "Kc = 2.0125529225284944e-22\n", - "proton+COC=O.[Pt]<=>COCO[Pt]\n", - "kf = 0.6792883990466445\n", - "krev = 3726.123137157573\n", - "Kc = 0.00018230433457033608\n", - "proton+COCO[Pt]<=>OX+COC\n", - "kf = 5093.375621150868\n", - "krev = 5.977614318003391e-7\n", - "Kc = 8.520749834613165e9\n", - "CO[Pt]+C=C=O<=>COCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.680149232421768e-23\n", - "Kc = 1.9922953446306685e15\n", - "HX+COC=C=O<=>COCC(=O)[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 2.661991446097411e-38\n", - "Kc = 9.604054388173769e29\n", - "proton+COCC(=O)[Pt]<=>OCX+COC\n", - "kf = 8.734746675052269e7\n", - "krev = 2.1771371890779743e-8\n", - "Kc = 4.012033196103488e15\n", - "vacantX+vacantX+COCC=O<=>HX+COCC(=O)[Pt]\n", - "kf = 2.290241001822749e-10\n", - "krev = 0.0004872161822843353\n", - "Kc = 4.7006669423105973e-7\n", - "proton+COCOC#[Pt]<=>CX+COCO\n", - "kf = 3.2770328923262016e-17\n", - "krev = 2.1864147814239428e-13\n", - "Kc = 0.0001498815741719407\n", - "proton+COCC#[Pt]<=>CX+COC\n", - "kf = 1.433200340176918\n", - "krev = 0.00041586763423335837\n", - "Kc = 3446.289689792732\n", - "proton+COC[Pt]<=>CH2X+CO-2\n", - "kf = 0.2769010105768301\n", - "krev = 3.0099119392563808e-6\n", - "Kc = 91996.38267332179\n", - "vacantX+vacantX+COCO<=>HOX+COC[Pt]\n", - "kf = 8.90444501639475e-13\n", - "krev = 8.409201083164982e12\n", - "Kc = 1.0588931015362724e-25\n", - "C=O+CH3X<=>COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 8.422687202008296e-11\n", - "Kc = 470.23832623775377\n", - "vacantX+vacantX+COC<=>HX+COC[Pt]\n", - "kf = 2.786306429788959e-20\n", - "krev = 52.25975865319748\n", - "Kc = 5.3316481009398625e-22\n", - "vacantX+vacantX+COCC=O<=>CHOX+COC[Pt]\n", - "kf = 1.4060776479118306e6\n", - "krev = 6.613786245273692e13\n", - "Kc = 2.1259798786461146e-8\n", - "vacantX+vacantX+C=C=CO<=>OC=[Pt]+C=C=[Pt]\n", - "kf = 1.5975335437882445e-34\n", - "krev = 2.2957840869759923e8\n", - "Kc = 6.958553083676594e-43\n", - "vacantX+vacantX+C=C=CO<=>CH2X+OC=C=[Pt]\n", - "kf = 9.363402027600756e-56\n", - "krev = 7.047835211144391e9\n", - "Kc = 1.328550079149818e-65\n", - "vacantX+vacantX+COC=O<=>OX+COC=[Pt]\n", - "kf = 1.1797200153280936e-59\n", - "krev = 4.3408253155831816e16\n", - "Kc = 2.7177320660497494e-76\n", - "proton+COC=[Pt]<=>CHX+CO-2\n", - "kf = 479145.9852086257\n", - "krev = 1.0449825701778588e-33\n", - "Kc = 4.5852055228736854e38\n", - "proton+COC#[Pt]<=>COC=[Pt]\n", - "kf = 90933.51053402986\n", - "krev = 2739.427130274527\n", - "Kc = 33.194352764155155\n", - "vacantX+vacantX+COC=C=O<=>OCX+COC=[Pt]\n", - "kf = 2.7777170398864307e-21\n", - "krev = 2.5089215324603047e13\n", - "Kc = 1.107135876490541e-34\n", - "proton+COC=[Pt]<=>COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3472876439887766e-48\n", - "Kc = 1.8555799952254487e58\n", - "vacantX+COC=C=O<=>COC=C=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 1179.0380002145982\n", - "Kc = 273.8002862958761\n", - "proton+COC=C=O.[Pt]<=>COCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.0577777781824875e-25\n", - "Kc = 2.3634453772469967e35\n", - "vacantX+vacantX+C=C=C<=>CH2X+C=C=[Pt]\n", - "kf = 4.78083312177258e-41\n", - "krev = 4.774618642094983e15\n", - "Kc = 1.0013015656628172e-56\n", - "proton+O=C=COC[Pt]<=>CH2X+O=C=CO\n", - "kf = 4.988523456059943e-5\n", - "krev = 0.0009299241102698363\n", - "Kc = 0.05364441464596958\n", - "C=O+O=C=C[Pt]<=>O=C=COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.852140732586457e13\n", - "Kc = 2.1384283940268284e-21\n", - "vacantX+vacantX+COC=C=O<=>HX+O=C=COC[Pt]\n", - "kf = 3.256466928453685e-21\n", - "krev = 26.50445975246776\n", - "Kc = 1.2286486722863626e-22\n", - "proton+O=C=COC[Pt]<=>COC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.6649798034152577e-22\n", - "Kc = 1.5015197150571575e32\n", - "CH3X+O=C=C=O<=>COC([Pt])=C=O\n", - "kf = 5.799304049644909e-8\n", - "krev = 3.1615249923835833e-35\n", - "Kc = 1.8343375629216876e27\n", - "proton+COC([Pt])=C=O<=>CO-2+O=C=C=[Pt]\n", - "kf = 313658.31445379555\n", - "krev = 1.256306436150439e-34\n", - "Kc = 2.496670441448219e39\n", - "vacantX+vacantX+COC=C=O<=>HX+COC([Pt])=C=O\n", - "kf = 2.779636780044878e-20\n", - "krev = 3.601218910546807\n", - "Kc = 7.718599866018197e-21\n", - "proton+COC([Pt])=C=O<=>COC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0459713323621888e-20\n", - "Kc = 2.390122867281724e30\n", - "vacantX+vacantX+C=C=C(O)O<=>OC(O)=[Pt]+C=C=[Pt]\n", - "kf = 2.937512138355157e-45\n", - "krev = 8.778136400287878e10\n", - "Kc = 3.34639609639561e-56\n", - "proton+O=C=COC=[Pt]<=>CHX+O=C=CO\n", - "kf = 2.102599834403735e7\n", - "krev = 1.6989476123058672e-25\n", - "Kc = 1.237589563782969e32\n", - "proton+O=C=COC#[Pt]<=>O=C=COC=[Pt]\n", - "kf = 1080.8801129554665\n", - "krev = 2888.2699525834805\n", - "Kc = 0.37423098626520285\n", - "proton+O=C=COC=[Pt]<=>O=C=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.9106920181466426e-48\n", - "Kc = 8.589022763019266e57\n", - "proton+CCOO[Pt]<=>OX+CCO\n", - "kf = 169.16425212622386\n", - "krev = 5.6416707126946964e-58\n", - "Kc = 2.9984779463568512e59\n", - "vacantX+vacantX+CCOO<=>HX+CCOO[Pt]\n", - "kf = 1.893449523720139e-21\n", - "krev = 0.6694879211592951\n", - "Kc = 2.8282056537202555e-21\n", - "O=O+CC[Pt]<=>CCOO[Pt]\n", - "kf = 4.5276782379965965e-7\n", - "krev = 1.4949208469184493e-38\n", - "Kc = 3.0287076719344122e31\n", - "vacantX+vacantX+C=CC(=O)O<=>CH2X+O=C(O)C=[Pt]\n", - "kf = 4.72289540105198e-39\n", - "krev = 9.498795808374404e14\n", - "Kc = 4.9720990916429044e-54\n", - "vacantX+vacantX+C=CC(=O)O<=>CO2HX+C=C[Pt]\n", - "kf = 5.354197885861111e7\n", - "krev = 1.376967106369583e14\n", - "Kc = 3.888399266107105e-7\n", - "vacantX+vacantX+C=CC(=O)O<=>HOX+C=CC(=O)[Pt]\n", - "kf = 0.03947248649742643\n", - "krev = 2.5171232142616846e11\n", - "Kc = 1.5681586929785789e-13\n", - "vacantX+vacantX+C=CC(=O)O<=>HX+C=CC(=O)O[Pt]\n", - "kf = 2.4490000178339845e-20\n", - "krev = 458.0011375503109\n", - "Kc = 5.3471483300955e-23\n", - "proton+O=C=C=CO.[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.4322611471299928e-17\n", - "Kc = 1.7454917387164855e27\n", - "proton+O=C=C=CO.[Pt]<=>O=C=C([Pt])CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 7.140416160377535e-6\n", - "Kc = 3.5011964903006675e15\n", - "vacantX+O=C=C=CO<=>O=C=C=CO.[Pt]\n", - "kf = 327433.4917974331\n", - "krev = 0.4460204906723957\n", - "Kc = 734122.0832787583\n", - "HX+O=C=C=C=O<=>O=C=C=C(O)[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 1.3048903398306852e-5\n", - "Kc = 0.004032923533638046\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C=C(O)[Pt]\n", - "kf = 4235.342411204313\n", - "krev = 12.909334546967292\n", - "Kc = 328.0837130523738\n", - "proton+O=C=C=C(O)[Pt]<=>O=C=CC(O)=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1053.6449933824201\n", - "Kc = 2.3727156828928486e7\n", - "vacantX+vacantX+O=C=C=CO<=>HX+O=C=C=C(O)[Pt]\n", - "kf = 8.233814429551885e-18\n", - "krev = 0.5740049812746953\n", - "Kc = 1.434449995759099e-17\n", - "proton+O=C=C=C(O)[Pt]<=>O=C=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.249904355928212e-21\n", - "Kc = 3.4483213533096645e30\n", - "vacantX+vacantX+CC=CO<=>OC=[Pt]+CC=[Pt]\n", - "kf = 1.6816353348966163e-33\n", - "krev = 8.021148128032321e14\n", - "Kc = 2.0965020319468163e-48\n", - "proton+O=C=C=C[Pt]<=>O=C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.0269882986128818\n", - "Kc = 9.263273820479827e11\n", - "vacantX+vacantX+C=C=C=O<=>HX+O=C=C=C[Pt]\n", - "kf = 3.6772489817592154e-10\n", - "krev = 0.00723599763490509\n", - "Kc = 5.081882509221477e-8\n", - "vacantX+vacantX+O=C=C=CO<=>HOX+O=C=C=C[Pt]\n", - "kf = 0.00020826365169953766\n", - "krev = 1.0739954827079557e13\n", - "Kc = 1.939148302322696e-17\n", - "vacantX+OC=CO<=>OC=CO.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.48171019889246675\n", - "Kc = 734122.0861712244\n", - "vacantX+vacantX+C=CC<=>CH2X+CC=[Pt]\n", - "kf = 3.8695500910369183e-44\n", - "krev = 2.1644248520711738e17\n", - "Kc = 1.787795999169979e-61\n", - "vacantX+vacantX+C=CC<=>CH3X+C=C[Pt]\n", - "kf = 1.1726078415532691e-17\n", - "krev = 1.59532697721828e15\n", - "Kc = 7.350266486422159e-33\n", - "HX+O=C=CO<=>OC=C(O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 2.762063581333058e-24\n", - "Kc = 1.0314187634521844e16\n", - "vacantX+vacantX+OC=CO<=>HX+OC=C(O)[Pt]\n", - "kf = 6.089904416870865e-20\n", - "krev = 3.928023437111271\n", - "Kc = 1.550373747604081e-20\n", - "proton+O=C=CO.[Pt]<=>OC=C(O)[Pt]\n", - "kf = 6.4368819183992445e7\n", - "krev = 6.799608634080986e-11\n", - "Kc = 9.466547657075904e17\n", - "proton+OC=C(O)[Pt]<=>H2O+OC=C=[Pt]\n", - "kf = 5.262467142275111e-7\n", - "krev = 0.6251329939834178\n", - "Kc = 8.418156125054411e-7\n", - "proton+OC=C(O)[Pt]<=>OC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.835798651062412e-24\n", - "Kc = 3.190485247679302e33\n", - "vacantX+vacantX+OC=CO<=>HOX+OC=C[Pt]\n", - "kf = 1.882970379851619e-8\n", - "krev = 6.2613640604613945e13\n", - "Kc = 3.0072846134950095e-22\n", - "vacantX+vacantX+C=CO<=>HX+OC=C[Pt]\n", - "kf = 5.986889507133711e-22\n", - "krev = 1492.047811549125\n", - "Kc = 4.0125319448830507e-25\n", - "proton+OC=C[Pt]<=>OCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.693803965028289e7\n", - "Kc = 1475.967733939179\n", - "vacantX+vacantX+O=CC=CO<=>CHOX+OC=C[Pt]\n", - "kf = 3.6404040231768274e-5\n", - "krev = 5.1339082800935775e14\n", - "Kc = 7.090901949480236e-20\n", - "proton+OC=C=[Pt]<=>OC=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.9001266800545872e-45\n", - "Kc = 1.3157017509633512e55\n", - "vacantX+vacantX+OC=CCO<=>OC[Pt]+OC=C[Pt]\n", - "kf = 1.39754480380523e-13\n", - "krev = 4.435737343310229e14\n", - "Kc = 3.1506482364492156e-28\n", - "vacantX+vacantX+CC=CO<=>CH3X+OC=C[Pt]\n", - "kf = 3.0518560755450534e-15\n", - "krev = 1.440283576497463e15\n", - "Kc = 2.1189272205454667e-30\n", - "vacantX+vacantX+CC=C(O)O<=>OC(O)=[Pt]+CC=[Pt]\n", - "kf = 3.314404876424973e-50\n", - "krev = 3.298291971460818e17\n", - "Kc = 1.0048852269912959e-67\n", - "HX+O=C=CO<=>OC=CO[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 5.830973747204281e-42\n", - "Kc = 4.885709192226705e33\n", - "vacantX+vacantX+OC=CO<=>HX+OC=CO[Pt]\n", - "kf = 6.3392542923960805e-6\n", - "krev = 0.0008631955285686626\n", - "Kc = 0.007343937824733329\n", - "proton+O=C=CO.[Pt]<=>OC=CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.575140256117379e-26\n", - "Kc = 4.4841921192150256e35\n", - "proton+OC=CO[Pt]<=>OX+C=CO\n", - "kf = 2.262727495050209e-8\n", - "krev = 2.5678564004292932e-5\n", - "Kc = 0.0008811736881672694\n", - "proton+OC=CO[Pt]<=>OC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.711725523568878e-6\n", - "Kc = 6.73541182968781e15\n", - "proton+OC=COC#[Pt]<=>CX+OC=CO\n", - "kf = 2.2492341197526439e-29\n", - "krev = 0.00020529518482061674\n", - "Kc = 1.0956097785332785e-25\n", - "vacantX+vacantX+CCC(=O)O<=>CH3X+O=C(O)C[Pt]\n", - "kf = 8.997747599742267e-17\n", - "krev = 6.572577910715489e15\n", - "Kc = 1.368983026442782e-32\n", - "vacantX+vacantX+CCC(=O)O<=>CO2HX+CC[Pt]\n", - "kf = 3.388822996448631e-6\n", - "krev = 1.0293603282987281e15\n", - "Kc = 3.292163981148853e-21\n", - "vacantX+vacantX+CCC(=O)O<=>HOX+CCC(=O)[Pt]\n", - "kf = 2.1491486919570496e-14\n", - "krev = 4.131728096070369e12\n", - "Kc = 5.201573390081201e-27\n", - "vacantX+vacantX+CCC(=O)O<=>HX+CCC(=O)O[Pt]\n", - "kf = 2.415446383235281e-20\n", - "krev = 451.7273406124814\n", - "Kc = 5.347133472063615e-23\n", - "proton+O=C([Pt])C=CO<=>OCX+C=CO\n", - "kf = 224.18396606543615\n", - "krev = 8.215700647740584e-7\n", - "Kc = 2.728726078001508e8\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=C([Pt])C=CO\n", - "kf = 2.859565189776071e-11\n", - "krev = 0.000933578065584948\n", - "Kc = 3.06301668300697e-8\n", - "HX+O=C=C=CO<=>O=C([Pt])C=CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.1750295723598082e-43\n", - "Kc = 2.206855353748942e35\n", - "proton+O=C=C=CO.[Pt]<=>O=C([Pt])C=CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.234268290529092e-27\n", - "Kc = 2.0254915557527025e37\n", - "proton+OC=C(O)C#[Pt]<=>CX+OC=CO\n", - "kf = 2.8680661830740045e-24\n", - "krev = 729.307267106125\n", - "Kc = 3.932589612680575e-27\n", - "vacantX+vacantX+C=COO<=>OO[Pt]+C=C[Pt]\n", - "kf = 0.00256837059370255\n", - "krev = 1.2695573429161084e13\n", - "Kc = 2.0230441799526235e-16\n", - "vacantX+vacantX+C=COO<=>HOX+C=CO[Pt]\n", - "kf = 3.07907263663438e8\n", - "krev = 5.547742278067932e-15\n", - "Kc = 5.5501364019864025e22\n", - "vacantX+vacantX+C=COO<=>CH2X+OOC=[Pt]\n", - "kf = 7.483948884590266e-53\n", - "krev = 2.8103204909201245e17\n", - "Kc = 2.6630232775123643e-70\n", - "proton+OC=CC#[Pt]<=>CX+C=CO\n", - "kf = 1.0593841984272302e-19\n", - "krev = 13.369077699035607\n", - "Kc = 7.924138241066921e-21\n", - "proton+OCC[Pt]<=>CH2X+CO-2\n", - "kf = 3.9799160772985795e-6\n", - "krev = 0.00035437522440524626\n", - "Kc = 0.011230796633647675\n", - "vacantX+vacantX+OCCO<=>HOX+OCC[Pt]\n", - "kf = 2.110093084979835e-12\n", - "krev = 2.4085316622580622e14\n", - "Kc = 8.760910716040024e-27\n", - "HX+C=CO<=>OCC[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 1.1429411507382647e-15\n", - "Kc = 2.8609207088741057e7\n", - "HOX+C=C<=>OCC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 2.2750559854988554e-15\n", - "Kc = 3.602118089238167e7\n", - "proton+OCC=[Pt]<=>OCC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.1399343496076094e-34\n", - "Kc = 2.1931087530264836e44\n", - "vacantX+vacantX+CCO<=>HX+OCC[Pt]\n", - "kf = 4.51610258482867e-23\n", - "krev = 15472.547765874588\n", - "Kc = 2.918784063985339e-27\n", - "vacantX+vacantX+O=CCCO<=>CHOX+OCC[Pt]\n", - "kf = 2.0496526220764064\n", - "krev = 1.4633869198921762e15\n", - "Kc = 1.4006224835106677e-15\n", - "HX+C#C<=>C=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 2.375601900047824e-24\n", - "Kc = 3.580716650609497e16\n", - "CHOX+C#C<=>O=CC=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 3.2359557228060194e-16\n", - "Kc = 2.6287001452988416e8\n", - "HOX+C#C<=>OC=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 2.419253665005007e-25\n", - "Kc = 3.516108046777805e17\n", - "proton+OCCC#[Pt]<=>CX+CCO\n", - "kf = 0.036583470766554806\n", - "krev = 0.0005754138836916786\n", - "Kc = 63.577664361948486\n", - "OC[Pt]+C=C=O<=>O=C([Pt])CCO\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.869121889511259e-30\n", - "Kc = 1.7908695590280368e22\n", - "HX+O=C=CCO<=>O=C([Pt])CCO\n", - "kf = 2.5565910629172877e-8\n", - "krev = 3.7973012083800085e-37\n", - "Kc = 6.732652804247709e28\n", - "proton+O=C=CCO.[Pt]<=>O=C([Pt])CCO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.5089082544191712e-24\n", - "Kc = 1.6568270421201532e34\n", - "proton+O=C([Pt])CCO<=>OCX+CCO\n", - "kf = 9.600816617542319e7\n", - "krev = 3.185535798116408e-7\n", - "Kc = 3.0138781121904944e14\n", - "vacantX+vacantX+O=CCCO<=>HX+O=C([Pt])CCO\n", - "kf = 4.786286134347495e-11\n", - "krev = 0.0006355926831038164\n", - "Kc = 7.530429883135883e-8\n", - "vacantX+vacantX+C=COC<=>CO[Pt]+C=C[Pt]\n", - "kf = 1.9108708710628152e-14\n", - "krev = 5.750545812867103e12\n", - "Kc = 3.322938262290088e-27\n", - "vacantX+vacantX+C=COC<=>CH3X+C=CO[Pt]\n", - "kf = 8.809048609670953e-10\n", - "krev = 5.30334818480063e15\n", - "Kc = 1.6610353125441853e-25\n", - "vacantX+vacantX+C=COC<=>CH2X+COC=[Pt]\n", - "kf = 2.00333233616492e-67\n", - "krev = 2.0086736136424638e14\n", - "Kc = 9.973408932933319e-82\n", - "C=O+OC[Pt]<=>OCCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.726586049973397e-6\n", - "Kc = 0.00837955829095468\n", - "HX+O=CCO<=>OCCO[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 7.096612291679358e-6\n", - "Kc = 0.003946413774492056\n", - "vacantX+vacantX+OCCO<=>HX+OCCO[Pt]\n", - "kf = 1.0265256602604584e-26\n", - "krev = 112849.3186381155\n", - "Kc = 9.09642763154215e-32\n", - "proton+O=CCO.[Pt]<=>OCCO[Pt]\n", - "kf = 3.478307222117794e6\n", - "krev = 3581.5775849412535\n", - "Kc = 971.1662360023528\n", - "proton+OCCO[Pt]<=>OX+CCO\n", - "kf = 951266.6788585404\n", - "krev = 3.3388075163598663e-18\n", - "Kc = 2.8491210535420697e23\n", - "proton+OCCOC#[Pt]<=>CX+OCCO\n", - "kf = 6.336022152476698e-22\n", - "krev = 5.125095889500872e-13\n", - "Kc = 1.2362738744959868e-9\n", - "vacantX+vacantX+C=CC(O)O<=>OC(O)[Pt]+C=C[Pt]\n", - "kf = 1.3588265576828814e-16\n", - "krev = 6.093754170226661e16\n", - "Kc = 2.2298676968656565e-33\n", - "proton+O=C=C=C=[Pt]<=>O=C=CC#[Pt]\n", - "kf = 8.597534639917141e-9\n", - "krev = 2.1202950562509243e-60\n", - "Kc = 4.0548765204023916e51\n", - "vacantX+vacantX+O=C=C=C=O<=>OX+O=C=C=C=[Pt]\n", - "kf = 6.451439297868635e-57\n", - "krev = 8.482832416110645e14\n", - "Kc = 7.60528910793525e-72\n", - "proton+O=C=C=C(O)[Pt]<=>H2O+O=C=C=C=[Pt]\n", - "kf = 1.6149902683641734e-11\n", - "krev = 0.12950076972214764\n", - "Kc = 1.2470893198775887e-10\n", - "proton+O=C=C=C=[Pt]<=>O=C=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.039016761990757e-51\n", - "Kc = 6.189625216528679e60\n", - "vacantX+C=CO<=>C=CO.[Pt]\n", - "kf = 412885.969273148\n", - "krev = 1.1342794009872417\n", - "Kc = 364007.288604364\n", - "proton+C=CO[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.484544240591893e-27\n", - "Kc = 5.574702502366298e36\n", - "proton+OC=C[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.090002516938126e-28\n", - "Kc = 6.112465676112982e37\n", - "proton+C=CO.[Pt]<=>OCC[Pt]\n", - "kf = 1.7684909297990441e9\n", - "krev = 0.3339506079512917\n", - "Kc = 5.295666148501179e9\n", - "vacantX+vacantX+C=COCO<=>OCO[Pt]+C=C[Pt]\n", - "kf = 1.4197397308458187e-12\n", - "krev = 3.0290185667479297e13\n", - "Kc = 4.6871278586123213e-26\n", - "vacantX+vacantX+C=COCO<=>OC[Pt]+C=CO[Pt]\n", - "kf = 1.0263854075463885e-7\n", - "krev = 1.9545487277553856e14\n", - "Kc = 5.251265384031101e-22\n", - "HX+C=C=O<=>C=C(O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 3.2362559658776053e-12\n", - "Kc = 10343.290300064218\n", - "proton+C=C=O.[Pt]<=>C=C(O)[Pt]\n", - "kf = 0.5863133386822127\n", - "krev = 3624.832599039063\n", - "Kc = 0.00016174908017480404\n", - "vacantX+vacantX+C=CO<=>HX+C=C(O)[Pt]\n", - "kf = 4.00965787691315e-19\n", - "krev = 4.055766485027893\n", - "Kc = 9.886313454472895e-20\n", - "vacantX+vacantX+C=C(O)O<=>HOX+C=C(O)[Pt]\n", - "kf = 3.9452234947489745e-7\n", - "krev = 1.361002505571871e12\n", - "Kc = 2.8987628447394044e-19\n", - "proton+C=C(O)[Pt]<=>H2O+C=C=[Pt]\n", - "kf = 0.1408093188614318\n", - "krev = 0.006096548509334685\n", - "Kc = 23.09656334987455\n", - "proton+C=C(O)[Pt]<=>CC(O)=[Pt]\n", - "kf = 1.124057689749841e8\n", - "krev = 4.718570974473911e-12\n", - "Kc = 2.382199390092179e19\n", - "vacantX+vacantX+C=C(O)C=O<=>CHOX+C=C(O)[Pt]\n", - "kf = 2.8052009086647103\n", - "krev = 2.294429327232502e13\n", - "Kc = 1.2226137782366527e-13\n", - "proton+C=C(O)[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0077190030498644e-22\n", - "Kc = 2.4808503088993487e32\n", - "HOX+C=C=O<=>C=C(O)O[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.6625343699967689e-31\n", - "Kc = 2.0134040862236038e23\n", - "proton+C=C(O)O[Pt]<=>OX+C=CO\n", - "kf = 7.621772041144703e-10\n", - "krev = 0.16987445654378072\n", - "Kc = 4.4867087119601115e-9\n", - "vacantX+vacantX+C=C(O)O<=>HX+C=C(O)O[Pt]\n", - "kf = 8.7276566297004e-6\n", - "krev = 1.546723677424112e-6\n", - "Kc = 5.6426734503963205\n", - "vacantX+vacantX+C=CCOO<=>OOC[Pt]+C=C[Pt]\n", - "kf = 2.5331825038162864e-12\n", - "krev = 1.769892843246248e17\n", - "Kc = 1.4312632052740838e-29\n", - "proton+C=C(O)OC#[Pt]<=>CX+C=C(O)O\n", - "kf = 1.0744261387122509e-22\n", - "krev = 181.85749301564874\n", - "Kc = 5.908066370516815e-25\n", - "proton+C=C(O)C#[Pt]<=>CX+C=CO\n", - "kf = 3.691417083839596e-20\n", - "krev = 61.67110810051338\n", - "Kc = 5.985650651555046e-22\n", - "vacantX+vacantX+C=COOC<=>COO[Pt]+C=C[Pt]\n", - "kf = 0.0009962735751002543\n", - "krev = 4.495422962203487e13\n", - "Kc = 2.21619541359445e-17\n", - "vacantX+vacantX+C=COOC<=>CO[Pt]+C=CO[Pt]\n", - "kf = 2.772273774659678e8\n", - "krev = 3.7705323383409334e-17\n", - "Kc = 7.352473141443741e24\n", - "proton+C=C(O)C(=O)[Pt]<=>OCX+C=CO\n", - "kf = 985.1540455146012\n", - "krev = 5.159085449148215e-7\n", - "Kc = 1.9095517126533618e9\n", - "HOX+C=C=C=O<=>C=C(O)C(=O)[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 3.5720015577500406e-52\n", - "Kc = 8.264488540948707e43\n", - "vacantX+vacantX+C=C(O)C=O<=>HX+C=C(O)C(=O)[Pt]\n", - "kf = 2.8595651897765786e-11\n", - "krev = 0.000933577098423846\n", - "Kc = 3.063019856211522e-8\n", - "proton+C=COO[Pt]<=>OX+C=CO\n", - "kf = 43.93537738533433\n", - "krev = 6.669135249611683e-61\n", - "Kc = 6.587867203306832e61\n", - "O=O+C=C[Pt]<=>C=COO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 1.0833501613715598e-32\n", - "Kc = 7.082998693235901e24\n", - "vacantX+vacantX+C=COO<=>HX+C=COO[Pt]\n", - "kf = 4.552726448583842e-23\n", - "krev = 27.53540659037694\n", - "Kc = 1.6534081069915729e-24\n", - "vacantX+vacantX+C=COOC<=>CH3X+C=COO[Pt]\n", - "kf = 2.287071149777874e-9\n", - "krev = 2.2490557638427473e13\n", - "Kc = 1.0169028205286352e-22\n", - "vacantX+vacantX+CC(O)=CO<=>OC=[Pt]+CC(O)=[Pt]\n", - "kf = 7.128045206079291e-31\n", - "krev = 1.6024698052635947e11\n", - "Kc = 4.4481619451835966e-42\n", - "vacantX+vacantX+CC(O)=CO<=>CH3X+OC=C(O)[Pt]\n", - "kf = 1.2021042471738558e-26\n", - "krev = 3.79937896614338e12\n", - "Kc = 3.163949313521812e-39\n", - "proton+O=CC=C=[Pt]<=>O=CCC#[Pt]\n", - "kf = 62.9877146015209\n", - "krev = 8.316144406521062e-31\n", - "Kc = 7.574148730766316e31\n", - "vacantX+vacantX+O=C=CC=O<=>OX+O=CC=C=[Pt]\n", - "kf = 1.1758489216219413e-43\n", - "krev = 2.1453863988577092e16\n", - "Kc = 5.480825842132732e-60\n", - "proton+O=CC=C=[Pt]<=>O=CC=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.331702565774384e-47\n", - "Kc = 2.6790395240083815e56\n", - "proton+C=C=C=O.[Pt]<=>O=C=CC[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.2229421483387703e-16\n", - "Kc = 1.1246356554390213e26\n", - "vacantX+C=C=C=O<=>C=C=C=O.[Pt]\n", - "kf = 372758.92921022984\n", - "krev = 0.5077615475124772\n", - "Kc = 734122.012658058\n", - "proton+C=C=C=O.[Pt]<=>CC([Pt])=C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.123273247571115e-16\n", - "Kc = 1.1774273531962195e26\n", - "proton+C=C=C=O.[Pt]<=>C=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.171161147913428e-32\n", - "Kc = 4.834504144216726e41\n", - "proton+O=C=C=C[Pt]<=>C=C=C=O.[Pt]\n", - "kf = 3.820491632517615e9\n", - "krev = 3.925100397444825e-12\n", - "Kc = 9.733487670798667e20\n", - "vacantX+vacantX+C=C(C)O<=>CH2X+CC(O)=[Pt]\n", - "kf = 1.2526307828427685e-31\n", - "krev = 1.8291181793687947e14\n", - "Kc = 6.848276929132241e-46\n", - "vacantX+vacantX+C=C(C)O<=>CH3X+C=C(O)[Pt]\n", - "kf = 6.412809230790006e-14\n", - "krev = 6.896161957802356e13\n", - "Kc = 9.299098933624258e-28\n", - "HX+O=C=C=C=O<=>O=C=C=CO[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 6.474039280394542e-15\n", - "Kc = 8.128654665807662e6\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C=CO[Pt]\n", - "kf = 2.4048564698523636e10\n", - "krev = 0.03636685994081414\n", - "Kc = 6.612769080877996e11\n", - "proton+O=C=C=CO[Pt]<=>OX+C=C=C=O\n", - "kf = 7.675790818902377e-14\n", - "krev = 0.0006735755949001122\n", - "Kc = 1.1395589265731426e-10\n", - "vacantX+vacantX+O=C=C=CO<=>HX+O=C=C=CO[Pt]\n", - "kf = 4.194899212644372e-10\n", - "krev = 0.014508998351933198\n", - "Kc = 2.891239705796395e-8\n", - "proton+O=C=C=CO[Pt]<=>O=C=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4612716650323904e-11\n", - "Kc = 1.71083862078759e21\n", - "proton+CC(O)[Pt]<=>OC=[Pt]+CH4\n", - "kf = 59.397807135376084\n", - "krev = 1.2803453253139382e-6\n", - "Kc = 4.639202093451769e7\n", - "HX+C=CO<=>CC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 1.2254518112062234e-21\n", - "Kc = 2.668292606261641e13\n", - "HX+CC=O<=>CC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 2.4645381117653586e-12\n", - "Kc = 13267.654460532101\n", - "vacantX+vacantX+CCO<=>HX+CC(O)[Pt]\n", - "kf = 1.7361137032745595e-19\n", - "krev = 63.774720976875884\n", - "Kc = 2.72225997492652e-21\n", - "vacantX+vacantX+CC(O)O<=>HOX+CC(O)[Pt]\n", - "kf = 7.380915652046712e-14\n", - "krev = 2.775462823415347e13\n", - "Kc = 2.6593458899096773e-27\n", - "proton+CC=O.[Pt]<=>CC(O)[Pt]\n", - "kf = 36132.65188770086\n", - "krev = 0.006356177292382113\n", - "Kc = 5.68465135971048e6\n", - "proton+CC(O)[Pt]<=>H2O+CC=[Pt]\n", - "kf = 2964.0563969386994\n", - "krev = 0.019559355499681682\n", - "Kc = 151541.61889367664\n", - "proton+CC(O)=[Pt]<=>CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.860369956892034e-19\n", - "Kc = 5.143641373338227e28\n", - "vacantX+vacantX+CC(O)C=O<=>CHOX+CC(O)[Pt]\n", - "kf = 753631.9525109725\n", - "krev = 9.011518944421836e14\n", - "Kc = 8.362984721654206e-10\n", - "proton+C=CO.[Pt]<=>CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.061646123775542e-6\n", - "Kc = 4.939104668453628e15\n", - "HX+C#CC=O<=>O=CC=C[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 1.9866745274914506e-30\n", - "Kc = 1.4859387148609413e22\n", - "proton+CC(O)C#[Pt]<=>CX+CCO\n", - "kf = 1.3617819786307934\n", - "krev = 4.084110860281074e-5\n", - "Kc = 33343.413663777814\n", - "O=CO+CH3X<=>CC(O)O[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 7.324156308451427e-7\n", - "Kc = 0.043678018970166745\n", - "HOX+CC=O<=>CC(O)O[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 7.587328136505701e-13\n", - "Kc = 43096.38318446866\n", - "HX+CC(=O)O<=>CC(O)O[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 4598.938099177113\n", - "Kc = 6.089703295881323e-12\n", - "proton+CC(O)O[Pt]<=>OX+CCO\n", - "kf = 1.6583777607664147e6\n", - "krev = 1.6983423991371652e-6\n", - "Kc = 9.764684445309413e11\n", - "vacantX+vacantX+CC(O)O<=>HX+CC(O)O[Pt]\n", - "kf = 4.052122584605618e-24\n", - "krev = 469.09529347560436\n", - "Kc = 8.638165082797514e-27\n", - "proton+CC(=O)O.[Pt]<=>CC(O)O[Pt]\n", - "kf = 0.7475019896975738\n", - "krev = 3555.8603422114556\n", - "Kc = 0.00021021691454639312\n", - "vacantX+vacantX+OC=C=CO<=>OC=[Pt]+OC=C=[Pt]\n", - "kf = 3.0449395213240036e-51\n", - "krev = 1.4315520101841116e12\n", - "Kc = 2.1270198355785863e-63\n", - "CH3X+O=C=CO<=>CC(O)C(=O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 4.477216581188038e-53\n", - "Kc = 6.362980552705156e44\n", - "proton+CC(O)C(=O)[Pt]<=>OCX+CCO\n", - "kf = 9.570476890072168e7\n", - "krev = 4.96015815008412e-7\n", - "Kc = 1.929470109720163e14\n", - "HOX+CC=C=O<=>CC(O)C(=O)[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 3.536759710167166e-36\n", - "Kc = 8.195394062368554e27\n", - "HX+CC(O)=C=O<=>CC(O)C(=O)[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 4.830700359768998e-42\n", - "Kc = 5.292381792522405e33\n", - "vacantX+vacantX+CC(O)C=O<=>HX+CC(O)C(=O)[Pt]\n", - "kf = 4.786286134353719e-11\n", - "krev = 0.0006355923790078162\n", - "Kc = 7.530433486042254e-8\n", - "proton+CC(O)=C=O.[Pt]<=>CC(O)C(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.368412782384192e-31\n", - "Kc = 1.8269341182594315e41\n", - "proton+CC(O)OC#[Pt]<=>CX+CC(O)O\n", - "kf = 2.7873525673015004e-16\n", - "krev = 1.8374709107747412e-8\n", - "Kc = 1.516950581887719e-8\n", - "vacantX+vacantX+CCOC<=>CO[Pt]+CC[Pt]\n", - "kf = 2.3627317133785774e-11\n", - "krev = 3.856091265609508e13\n", - "Kc = 6.127271246016828e-25\n", - "vacantX+vacantX+CCOC<=>CH3X+CCO[Pt]\n", - "kf = 6.326940367296449e-9\n", - "krev = 1.8372911814097844e13\n", - "Kc = 3.443624195943553e-22\n", - "vacantX+vacantX+CCOC<=>CH3X+COC[Pt]\n", - "kf = 1.3389399016858639e-14\n", - "krev = 2.773400746132106e14\n", - "Kc = 4.8277909478217395e-29\n", - "proton+O=C=C(O)C[Pt]<=>CH2X+O=C=CO\n", - "kf = 4.2042874371743854e-22\n", - "krev = 1.1101526849597185\n", - "Kc = 3.787125405481442e-22\n", - "HOX+C=C=C=O<=>O=C=C(O)C[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 6.322264310888409e-36\n", - "Kc = 4.669334354059592e27\n", - "vacantX+vacantX+CC(O)=C=O<=>HX+O=C=C(O)C[Pt]\n", - "kf = 6.004181315465852e-13\n", - "krev = 0.19478740167193392\n", - "Kc = 3.082427951669201e-12\n", - "proton+O=C=C(O)C[Pt]<=>CC(O)=C=O.[Pt]\n", - "kf = 1.859235052213257e9\n", - "krev = 4.357618832801525e-11\n", - "Kc = 4.266630753057283e19\n", - "proton+O=C=C(O)C=[Pt]<=>CHX+O=C=CO\n", - "kf = 1.807627844430322e-6\n", - "krev = 0.0010238577171457239\n", - "Kc = 0.0017655068806528764\n", - "proton+O=C=C(O)C#[Pt]<=>O=C=C(O)C=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.347883511420028\n", - "Kc = 7.467404380923659e9\n", - "proton+O=C=C(O)C=[Pt]<=>O=C=C(O)C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4404183806094484e-33\n", - "Kc = 1.735606844271341e43\n", - "vacantX+vacantX+CCCO<=>OC[Pt]+CC[Pt]\n", - "kf = 4.648157058598011e-13\n", - "krev = 1.3999921584371802e15\n", - "Kc = 3.3201307811515004e-28\n", - "vacantX+vacantX+CCCO<=>CH3X+OCC[Pt]\n", - "kf = 1.2211065235504926e-16\n", - "krev = 1.2627143633797795e15\n", - "Kc = 9.670488900451568e-32\n", - "proton+CC([Pt])OC=O<=>CH4+O=COC=[Pt]\n", - "kf = 1.0679856406424377e-15\n", - "krev = 0.2905260385078575\n", - "Kc = 3.6760410396521245e-15\n", - "CHOX+CC=O<=>CC([Pt])OC=O\n", - "kf = 3.269864007171502e-8\n", - "krev = 0.48922244404245907\n", - "Kc = 6.68379802887317e-8\n", - "HX+C=COC=O<=>CC([Pt])OC=O\n", - "kf = 2.5565910629172877e-8\n", - "krev = 1.2259112200812889e-16\n", - "Kc = 2.0854618352769157e8\n", - "vacantX+vacantX+CCOC=O<=>HX+CC([Pt])OC=O\n", - "kf = 6.519502059052115e-22\n", - "krev = 142.86665816232104\n", - "Kc = 4.563347489828482e-24\n", - "proton+CC([Pt])OC=O<=>O=CO+CC=[Pt]\n", - "kf = 8049.244255788158\n", - "krev = 0.00029431628636694825\n", - "Kc = 2.7348959703006394e7\n", - "proton+CC(=[Pt])OC=O<=>CH4+O=COC#[Pt]\n", - "kf = 4.771264023974434e9\n", - "krev = 10.578082715743388\n", - "Kc = 4.510518732164335e8\n", - "proton+CC(=[Pt])OC=O<=>O=CO+CC#[Pt]\n", - "kf = 7292.02651577905\n", - "krev = 8.53932827082491e-43\n", - "Kc = 8.539344412712957e45\n", - "proton+CC(=[Pt])OC=O<=>CC([Pt])OC=O\n", - "kf = 2.5e10\n", - "krev = 2.5945295399651927e-47\n", - "Kc = 9.635658262860014e56\n", - "vacantX+vacantX+CCC(O)O<=>OC(O)[Pt]+CC[Pt]\n", - "kf = 3.712816041087776e-19\n", - "krev = 9.367983662004229e16\n", - "Kc = 3.9633032838716965e-36\n", - "vacantX+O=CC=CO<=>O=CC=CO.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 0.8868529608572997\n", - "Kc = 364007.2889878057\n", - "proton+O=CC=CO[Pt]<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.467206835324098e-11\n", - "Kc = 1.703917907012588e21\n", - "proton+O=C([Pt])C=CO<=>O=CC=CO.[Pt]\n", - "kf = 3.672999120067293e9\n", - "krev = 4.587068754429701e-12\n", - "Kc = 8.00729031262133e20\n", - "HX+O=C=CC=O<=>O=CC=C(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.0473065138531246e-21\n", - "Kc = 2.475989854235963e13\n", - "proton+O=C=CC=O.[Pt]<=>O=CC=C(O)[Pt]\n", - "kf = 9.946079261837086e6\n", - "krev = 6.687641252513296e-9\n", - "Kc = 1.4872327755468685e15\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC=C(O)[Pt]\n", - "kf = 2.77963678004065e-20\n", - "krev = 3.601218827022036\n", - "Kc = 7.718600045027592e-21\n", - "proton+O=CC=C(O)[Pt]<=>H2O+O=CC=C=[Pt]\n", - "kf = 2.367383825493301e-13\n", - "krev = 16.1722227709439\n", - "Kc = 1.463858035487058e-14\n", - "proton+O=CC=C(O)[Pt]<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.867624236214861e-24\n", - "Kc = 3.177579311035777e33\n", - "vacantX+vacantX+CCOCO<=>OCO[Pt]+CC[Pt]\n", - "kf = 2.4512530384253315e-9\n", - "krev = 3.614837695546209e14\n", - "Kc = 6.781087409389048e-24\n", - "vacantX+vacantX+CCOCO<=>OC[Pt]+CCO[Pt]\n", - "kf = 1.0293700832173347e-6\n", - "krev = 1.2050997101819434e12\n", - "Kc = 8.541783509863451e-19\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC([Pt])=CO\n", - "kf = 4.3007284274917255e-15\n", - "krev = 1.9561961334382385\n", - "Kc = 2.1985159636997663e-15\n", - "HX+O=C=C=CO<=>O=CC([Pt])=CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.6370748462102965e-36\n", - "Kc = 1.5839961798805036e28\n", - "proton+O=CC([Pt])=CO<=>C=O+OC=C=[Pt]\n", - "kf = 4.3296354594819855e-33\n", - "krev = 908.9754469679581\n", - "Kc = 4.76320397203711e-36\n", - "proton+O=C=C=CO.[Pt]<=>O=CC([Pt])=CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.7196074204687593e-20\n", - "Kc = 1.4538201977044896e30\n", - "HOX+C#CC=O<=>O=CC([Pt])=CO\n", - "kf = 2.952076594227614e-8\n", - "krev = 4.790462195255654e-44\n", - "Kc = 6.162404531970363e35\n", - "proton+O=CC([Pt])=CO<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.2409630475480663e-18\n", - "Kc = 1.1155918000233681e28\n", - "proton+OC=CC=[Pt]<=>CHX+C=CO\n", - "kf = 0.3708119772368373\n", - "krev = 1.9743851754031655e-5\n", - "Kc = 18781.136621992628\n", - "vacantX+vacantX+O=CC=CO<=>OX+OC=CC=[Pt]\n", - "kf = 8.803023976547135e-28\n", - "krev = 1.526615583505237e17\n", - "Kc = 5.766365856383213e-45\n", - "proton+OC=CC#[Pt]<=>OC=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4263979915391943e-8\n", - "Kc = 1.7526665172195773e18\n", - "vacantX+vacantX+CCCOO<=>OOC[Pt]+CC[Pt]\n", - "kf = 5.56726706794292e-16\n", - "krev = 4.282042054393877e17\n", - "Kc = 1.3001430152303739e-33\n", - "proton+OCC(O)[Pt]<=>OC=[Pt]+CO-2\n", - "kf = 0.16339719354915763\n", - "krev = 6.17359485423602e-8\n", - "Kc = 2.6467106670766133e6\n", - "HX+O=CCO<=>OCC(O)[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 4.347223516290618e-14\n", - "Kc = 644231.1603064304\n", - "vacantX+vacantX+OCCO<=>HX+OCC(O)[Pt]\n", - "kf = 7.314142036323851e-21\n", - "krev = 492.5535033039904\n", - "Kc = 1.4849436634317805e-23\n", - "HX+OC=CO<=>OCC(O)[Pt]\n", - "kf = 5.6012337000223925e-8\n", - "krev = 1.5412075197181771e-21\n", - "Kc = 3.634315060340885e13\n", - "HOX+C=CO<=>OCC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 6.743155058263278e-19\n", - "Kc = 4.8491603395127426e10\n", - "proton+O=CCO.[Pt]<=>OCC(O)[Pt]\n", - "kf = 698182.0065765544\n", - "krev = 4.403884986144656e-6\n", - "Kc = 1.5853774764171848e11\n", - "proton+OCC(O)[Pt]<=>H2O+OCC=[Pt]\n", - "kf = 0.7285659975205578\n", - "krev = 0.0004743003964980969\n", - "Kc = 1536.0855755124403\n", - "proton+OC=CO.[Pt]<=>OCC(O)[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 1.4989628309182922e-5\n", - "Kc = 3.3356397482764175e15\n", - "proton+OCC(O)C#[Pt]<=>CX+OCCO\n", - "kf = 5.26000051169577\n", - "krev = 0.00019971123776726528\n", - "Kc = 26338.02969978857\n", - "vacantX+vacantX+CCC<=>CH3X+CC[Pt]\n", - "kf = 7.798842461270165e-20\n", - "krev = 4.754727023110295e15\n", - "Kc = 1.640229275700578e-35\n", - "proton+O=C([Pt])CO<=>OCC(O)=[Pt]\n", - "kf = 4.019918430047713e-18\n", - "krev = 1.0085447542339827e12\n", - "Kc = 3.9858602339377106e-30\n", - "proton+OCC(O)=[Pt]<=>H2O+OCC#[Pt]\n", - "kf = 16209.61875952926\n", - "krev = 4.634124941714537e-41\n", - "Kc = 3.4978812533984058e44\n", - "proton+OCC(O)=[Pt]<=>OC#[Pt]+CO-2\n", - "kf = 382.95023851607715\n", - "krev = 3.536410198453644e-35\n", - "Kc = 1.0828784474253827e37\n", - "proton+OC=C(O)[Pt]<=>OCC(O)=[Pt]\n", - "kf = 6875.768524790738\n", - "krev = 1.0085447542339824e12\n", - "Kc = 6.8175145385720384e-9\n", - "proton+OCC(O)=[Pt]<=>OCC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.6015120113778689e-47\n", - "Kc = 1.5610248204439706e57\n", - "HX+COC=O<=>COC(O)[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 224.3395816271696\n", - "Kc = 1.2483828443014824e-10\n", - "proton+COC(O)[Pt]<=>OC=[Pt]+CO-2\n", - "kf = 564390.3708916149\n", - "krev = 3.282828318007529e-12\n", - "Kc = 1.7192198806002883e17\n", - "vacantX+vacantX+COCO<=>HX+COC(O)[Pt]\n", - "kf = 6.183244140051347e-23\n", - "krev = 2731.92216309053\n", - "Kc = 2.2633310068601865e-26\n", - "O=CO+CH3X<=>COC(O)[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 8.503469161971292e7\n", - "Kc = 3.7620485485108396e-16\n", - "proton+COC=O.[Pt]<=>COC(O)[Pt]\n", - "kf = 7.49969185016536e-5\n", - "krev = 3658.0165064396892\n", - "Kc = 2.0502072193940793e-8\n", - "proton+COC(O)[Pt]<=>H2O+COC=[Pt]\n", - "kf = 5.10646151413012e-10\n", - "krev = 0.003546985366877098\n", - "Kc = 1.439662413557134e-7\n", - "vacantX+vacantX+CCOOC<=>COO[Pt]+CC[Pt]\n", - "kf = 1.4778859852656565e-10\n", - "krev = 2.404289853338368e13\n", - "Kc = 6.146871115450596e-24\n", - "vacantX+vacantX+CCOOC<=>CO[Pt]+CCO[Pt]\n", - "kf = 2.735304068777078e8\n", - "krev = 1.1929824589169815e-11\n", - "Kc = 2.2928284052560617e19\n", - "vacantX+vacantX+CCOOC<=>CH3X+CCOO[Pt]\n", - "kf = 1.542530561493995e-10\n", - "krev = 1.2789927244807063e12\n", - "Kc = 1.2060510837700736e-22\n", - "proton+COC(O)C#[Pt]<=>CX+COCO\n", - "kf = 0.03928313633337953\n", - "krev = 0.002914319669063903\n", - "Kc = 13.479350515448948\n", - "proton+COC(=O)[Pt]<=>COC(O)=[Pt]\n", - "kf = 6.005930457604258e-17\n", - "krev = 1.0085447542339825e12\n", - "Kc = 5.955046052632466e-29\n", - "proton+COC(O)=[Pt]<=>OC#[Pt]+CO-2\n", - "kf = 383854.3090963643\n", - "krev = 3.448448528690976e-34\n", - "Kc = 1.113121758677009e39\n", - "proton+COC(O)=[Pt]<=>H2O+COC#[Pt]\n", - "kf = 217922.49486435574\n", - "krev = 2.0340320286285714e-35\n", - "Kc = 1.0713818258372662e40\n", - "proton+COC(O)=[Pt]<=>COC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0120272229346644e-38\n", - "Kc = 2.4702892801149458e48\n", - "vacantX+vacantX+C=C=COO<=>OOC=[Pt]+C=C=[Pt]\n", - "kf = 1.9145907695639512e-44\n", - "krev = 1.1771971588384226e12\n", - "Kc = 1.626397715275781e-56\n", - "C=O+O=CC[Pt]<=>O=CCCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 0.0025285011306884937\n", - "Kc = 1.5664103465194285e-5\n", - "HX+O=CCC=O<=>O=CCCO[Pt]\n", - "kf = 5.113182125834635e-8\n", - "krev = 3.03538509820146e-7\n", - "Kc = 0.16845250142607343\n", - "proton+O=CCC=O.[Pt]<=>O=CCCO[Pt]\n", - "kf = 2.3901708430508703e8\n", - "krev = 41.103568870106145\n", - "Kc = 5.814995896351951e6\n", - "vacantX+vacantX+O=CCCO<=>HX+O=CCCO[Pt]\n", - "kf = 2.5157725911236352e-27\n", - "krev = 8837.406478086354\n", - "Kc = 2.84673178421957e-31\n", - "proton+O=CCCO[Pt]<=>OX+CCC=O\n", - "kf = 774927.4661784222\n", - "krev = 1.1978583087682196e-18\n", - "Kc = 6.469274875884902e23\n", - "CHOX+C=C<=>O=CCC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 0.4688595936220698\n", - "Kc = 1.7478623517301195e-7\n", - "proton+O=CCC[Pt]<=>CH2X+CC=O\n", - "kf = 0.0016740956920828355\n", - "krev = 4.373185000711893e-7\n", - "Kc = 3828.0925499614495\n", - "HX+C=CC=O<=>O=CCC[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 7.666152073113618e-12\n", - "Kc = 3780.924152337611\n", - "proton+O=CCC=[Pt]<=>O=CCC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3932958912707058e-30\n", - "Kc = 1.794306590339518e40\n", - "vacantX+vacantX+O=CCCO<=>HOX+O=CCC[Pt]\n", - "kf = 8.901266563864654e-15\n", - "krev = 1.309728963703428e15\n", - "Kc = 6.79626610584771e-30\n", - "vacantX+vacantX+CCC=O<=>HX+O=CCC[Pt]\n", - "kf = 1.6716561102658422e-25\n", - "krev = 524619.2678123232\n", - "Kc = 3.186417680076247e-31\n", - "vacantX+vacantX+CC=COO<=>OOC=[Pt]+CC=[Pt]\n", - "kf = 3.7147962989308654e-50\n", - "krev = 4.0636001726377395e18\n", - "Kc = 9.141638303749602e-69\n", - "proton+C=COOC#[Pt]<=>CX+C=COO\n", - "kf = 8.811176921711816e-67\n", - "krev = 2.5e10\n", - "Kc = 3.5244707686847265e-77\n", - "vacantX+C=CC=O<=>C=CC=O.[Pt]\n", - "kf = 365995.57053717994\n", - "krev = 1.0054621985249468\n", - "Kc = 364007.290452202\n", - "proton+C=CC(=O)[Pt]<=>C=CC=O.[Pt]\n", - "kf = 3.399604827397095e9\n", - "krev = 5.959510760846119e-12\n", - "Kc = 5.704503211458966e20\n", - "proton+O=CC=C[Pt]<=>C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.32808736312024e-27\n", - "Kc = 3.00188973889839e36\n", - "proton+C=CC=O.[Pt]<=>O=CCC[Pt]\n", - "kf = 5.197601136262071e7\n", - "krev = 74.26603000820454\n", - "Kc = 699862.5260684955\n", - "vacantX+vacantX+C=CC=O<=>HX+C=C([Pt])C=O\n", - "kf = 1.2784478936507186e-21\n", - "krev = 132.59733776930153\n", - "Kc = 9.641580405445367e-24\n", - "proton+C=C([Pt])C=O<=>C=O+C=C=[Pt]\n", - "kf = 2.4079500300331376e-13\n", - "krev = 0.010970404022735962\n", - "Kc = 2.194951092997765e-11\n", - "HX+C=C=C=O<=>C=C([Pt])C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.4992009477647154e-32\n", - "Kc = 1.1812081765045545e24\n", - "vacantX+vacantX+C=C(O)C=O<=>HOX+C=C([Pt])C=O\n", - "kf = 1.107119853181277e-14\n", - "krev = 2.5289157654010746e13\n", - "Kc = 4.377843929513773e-28\n", - "proton+C=C=C=O.[Pt]<=>C=C([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.305987527913534e-16\n", - "Kc = 1.0841342243780513e26\n", - "HX+C#CC=O<=>C=C([Pt])C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 1.683521621093348e-30\n", - "Kc = 1.753512730243651e22\n", - "proton+C=C([Pt])C=O<=>C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.827731832923639e-27\n", - "Kc = 2.5438219545478565e36\n", - "CHOX+C=C=O<=>C=C(C=O)O[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.906984656058423e-6\n", - "Kc = 0.017553122325364576\n", - "proton+C=C(C=O)O[Pt]<=>OX+C=CC=O\n", - "kf = 13.565263195704604\n", - "krev = 7.179044500174065e-6\n", - "Kc = 1.8895638821260543e6\n", - "vacantX+vacantX+C=C(O)C=O<=>HX+C=C(C=O)O[Pt]\n", - "kf = 8.336773502217888e-19\n", - "krev = 4.018028855986407\n", - "Kc = 2.0748416203624424e-19\n", - "vacantX+vacantX+COCOC<=>CH3X+COCO[Pt]\n", - "kf = 0.24675966205104702\n", - "krev = 5.277017405064255e15\n", - "Kc = 4.6761199198288865e-17\n", - "vacantX+vacantX+COCOC<=>CO[Pt]+COC[Pt]\n", - "kf = 4.1241018831024145e-7\n", - "krev = 7.782310155024181e12\n", - "Kc = 5.2993286067375974e-20\n", - "proton+C=CC=[Pt]<=>CHX+C=C\n", - "kf = 1.3385165927063483e6\n", - "krev = 9.028119675350497e-7\n", - "Kc = 1.4826083845132273e12\n", - "vacantX+vacantX+C=CC=O<=>OX+C=CC=[Pt]\n", - "kf = 1.438969400016978e-30\n", - "krev = 1.6093339940290013e17\n", - "Kc = 8.941396909254915e-48\n", - "proton+C=CC#[Pt]<=>C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.067052266556579e-6\n", - "Kc = 2.342903040792558e16\n", - "vacantX+CC(O)O<=>CC(O)O.[Pt]\n", - "kf = 347843.58123444836\n", - "krev = 178209.4487483253\n", - "Kc = 1.9518806868971765\n", - "proton+CC(O)O[Pt]<=>CC(O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.64203868551119e-24\n", - "Kc = 1.5224976257010135e34\n", - "vacantX+vacantX+COCCO<=>OC[Pt]+COC[Pt]\n", - "kf = 1.3358759661274015e-7\n", - "krev = 3.1165281946439875e14\n", - "Kc = 4.286423490161954e-22\n", - "vacantX+vacantX+COCCO<=>CO[Pt]+OCC[Pt]\n", - "kf = 6.192873660096324e-8\n", - "krev = 3.90827625278604e13\n", - "Kc = 1.584553716150872e-21\n", - "vacantX+vacantX+COCCO<=>CH3X+OCCO[Pt]\n", - "kf = 4.52195120819324e-12\n", - "krev = 5.920081591014324e14\n", - "Kc = 7.638325821483257e-27\n", - "proton+OC(O)C[Pt]<=>CH2X+OCO\n", - "kf = 2.252975678309519e-7\n", - "krev = 0.002613777215265548\n", - "Kc = 8.619616335895816e-5\n", - "HOX+C=CO<=>OC(O)C[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 6.095879365149742e-19\n", - "Kc = 5.364056293281289e10\n", - "HX+C=C(O)O<=>OC(O)C[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 1.7806643358524245e-19\n", - "Kc = 1.572793251160735e11\n", - "vacantX+vacantX+CC(O)O<=>HX+OC(O)C[Pt]\n", - "kf = 2.610914590914038e-25\n", - "krev = 48838.0104312493\n", - "Kc = 5.3460707507516085e-30\n", - "vacantX+vacantX+CCC(O)O<=>CH3X+OC(O)C[Pt]\n", - "kf = 2.73273606062798e-19\n", - "krev = 1.7143250273592365e15\n", - "Kc = 1.594059479396106e-34\n", - "proton+OC(O)C[Pt]<=>CC(O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0162407066861682e-27\n", - "Kc = 2.4600470966688416e37\n" - ] - } - ], - "source": [ - "for (i,rxn) in enumerate(inter.reactions)\n", - " str = getrxnstr(rxn)\n", - " kf = inter.kfs[i]\n", - " krev = inter.krevs[i]\n", - " Kc = kf/krev\n", - " println(str)\n", - " println(\"kf = $kf\")\n", - " println(\"krev = $krev\")\n", - " println(\"Kc = $Kc\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "dd1b08a5", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "vacantX+CO2<=>CO2X\n", - "kf = 20654.615923781494\n", - "krev = 11189.298481041604\n", - "Kc = 1.8459259048971917\n", - "proton+CO2X<=>CHO2X\n", - "kf = 5.164749496653815e7\n", - "krev = 3.369038128826839e8\n", - "Kc = 0.1533004168893831\n", - "proton+CO2X<=>CO2HX\n", - "kf = 463658.8965294065\n", - "krev = 1.20318988446587e-5\n", - "Kc = 3.853580407511801e10\n", - "proton+CHO2X<=>CH2O2X\n", - "kf = 2.5e10\n", - "krev = 9.108706843764319e-26\n", - "Kc = 2.7446266993557504e35\n", - "proton+CO2HX<=>CH2O2X\n", - "kf = 1.9190551016885178e10\n", - "krev = 1.757621070775451e-14\n", - "Kc = 1.0918480289052538e24\n", - "proton+OCX<=>CHOX\n", - "kf = 2.5e10\n", - "krev = 2.604453583293511e-10\n", - "Kc = 9.59894242706594e19\n", - "proton+CHOX<=>CH2OX\n", - "kf = 1.7890196451453958e9\n", - "krev = 4.957912234830633e-11\n", - "Kc = 3.608413300616868e19\n", - "vacantX+vacantX+CO2<=>OX+OCX\n", - "kf = 3.0109478093923404e-24\n", - "krev = 3.037156297092479e15\n", - "Kc = 9.913707148607306e-40\n", - "OX+proton<=>HOX\n", - "kf = 2.5e10\n", - "krev = 4.7547181516587526e-14\n", - "Kc = 5.25793521352646e23\n", - "vacantX+C=O<=>CH2OX\n", - "kf = 500114.13488002896\n", - "krev = 399.6803280141717\n", - "Kc = 1251.2853393732605\n", - "proton+CHO2X<=>OX+C=O\n", - "kf = 7.971946163368602e-7\n", - "krev = 8.220582009654122e-5\n", - "Kc = 0.009697544716428197\n", - "HX+CO2<=>CHO2X\n", - "kf = 6.542996392927688e-8\n", - "krev = 15.579156394796986\n", - "Kc = 4.199839983064083e-9\n", - "HX+CO2<=>CO2HX\n", - "kf = 6.542996392927688e-8\n", - "krev = 6.197590078701277e-11\n", - "Kc = 1055.7323588427441\n", - "vacantX+vacantX+C=O<=>HX+CHOX\n", - "kf = 2.0718885766149262e-11\n", - "krev = 0.008867505326838887\n", - "Kc = 2.336495440655708e-9\n", - "vacantX+O=CO<=>CH2O2X\n", - "kf = 403943.82249737746\n", - "krev = 29.756334575496034\n", - "Kc = 13575.053119278344\n", - "vacantX+vacantX+O=CO<=>HOX+CHOX\n", - "kf = 8.486192390111145e-15\n", - "krev = 9.7037034735699e11\n", - "Kc = 8.745312975839684e-27\n", - "vacantX+vacantX+O=CO<=>HX+CHO2X\n", - "kf = 1.2668346793097018e-21\n", - "krev = 380.13410282264914\n", - "Kc = 3.332599390328158e-24\n", - "vacantX+vacantX+O=CO<=>HX+CO2HX\n", - "kf = 9.840171155787102e-15\n", - "krev = 0.011746228705195169\n", - "Kc = 8.377302539184302e-13\n", - "proton+CH2OX<=>CO[Pt]\n", - "kf = 4.612846333154699e7\n", - "krev = 90.4105198560361\n", - "Kc = 510211.23874742666\n", - "HX+C=O<=>CO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.180104845075902e-9\n", - "Kc = 9.475050217848336\n", - "proton+CO2HX<=>H2O+OCX\n", - "kf = 2.5e10\n", - "krev = 4.0258346788129556e-7\n", - "Kc = 6.20989235637749e16\n", - "vacantX+vacantX+H2O<=>HX+HOX\n", - "kf = 1.7047654949014593e-31\n", - "krev = 21441.30602897437\n", - "Kc = 7.950847269274322e-36\n", - "proton+CH2OX<=>OC[Pt]\n", - "kf = 1.2443063594454413e6\n", - "krev = 1.1005987164187474e-6\n", - "Kc = 1.1305722429827158e12\n", - "HX+C=O<=>OC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.886422105564557e-15\n", - "Kc = 2.099567387708916e7\n", - "vacantX+vacantX+O=CC=O<=>CHOX+CHOX\n", - "kf = 3.132095071630788e8\n", - "krev = 159.05427897483804\n", - "Kc = 1.9691988746346629e6\n", - "proton+CH2O2X<=>OC(O)[Pt]\n", - "kf = 1.9695177200694968e-5\n", - "krev = 3718.799864740736\n", - "Kc = 5.296111088803661e-9\n", - "HX+O=CO<=>OC(O)[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 29981.045237801853\n", - "Kc = 1.0670229661561413e-12\n", - "proton+CH2O2X<=>OCO[Pt]\n", - "kf = 1.3800914441571782e-5\n", - "krev = 3681.751563599994\n", - "Kc = 3.748464339097702e-9\n", - "HOX+C=O<=>OCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.962949149852605e-13\n", - "Kc = 201771.41789913058\n", - "HX+O=CO<=>OCO[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 42359.465576793365\n", - "Kc = 7.552140562327293e-13\n", - "vacantX+H2O<=>H2OX\n", - "kf = 4.842414926683719e6\n", - "krev = 2.0721934488233277e8\n", - "Kc = 0.023368546645263413\n", - "proton+HOX<=>H2OX\n", - "kf = 2.5e10\n", - "krev = 1.2623996335027457e-31\n", - "Kc = 1.9803554545269617e41\n", - "vacantX+vacantX+H2<=>HX+HX\n", - "kf = 3.8736093818093735e10\n", - "krev = 4.9917087254698525e28\n", - "Kc = 7.760086965901168e-19\n", - "proton+CHOX<=>OC=[Pt]\n", - "kf = 3.6460821201937575e9\n", - "krev = 3.454391742229775e10\n", - "Kc = 0.10554917890812951\n", - "vacantX+vacantX+O=CO<=>OX+OC=[Pt]\n", - "kf = 1.3995006080437096e-36\n", - "krev = 7.971831424002446e14\n", - "Kc = 1.755557203367275e-51\n", - "proton+OC=[Pt]<=>OC[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.468152848309303e-23\n", - "Kc = 3.8650910988497585e32\n", - "proton+OC(O)[Pt]<=>H2O+OC=[Pt]\n", - "kf = 6.989877198043828e9\n", - "krev = 6.424310280494338e-11\n", - "Kc = 1.0880354299303816e20\n", - "proton+O=CC(=O)[Pt]<=>OCX+C=O\n", - "kf = 2.302032083373261e7\n", - "krev = 2.5713202543754838e-9\n", - "Kc = 8.952724109165363e15\n", - "vacantX+vacantX+O=CC=O<=>HX+O=CC(=O)[Pt]\n", - "kf = 1.43713660093583e-9\n", - "krev = 0.00032277677938391324\n", - "Kc = 4.452416322137251e-6\n", - "proton+OCX<=>OC#[Pt]\n", - "kf = 26781.620683797883\n", - "krev = 1.0085447542339806e12\n", - "Kc = 2.6554717151981333e-8\n", - "proton+OC#[Pt]<=>OC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.552445879282663e-17\n", - "Kc = 3.815369170624406e26\n", - "vacantX+O=CC=O<=>O=CC=O.[Pt]\n", - "kf = 359723.7676387533\n", - "krev = 0.32068189796600394\n", - "Kc = 1.121746409511672e6\n", - "proton+O=CC(=O)[Pt]<=>O=CC=O.[Pt]\n", - "kf = 1.508798479649927e9\n", - "krev = 8.88806985342612e-11\n", - "Kc = 1.6975547048252826e19\n", - "vacantX+vacantX+OO<=>HOX+HOX\n", - "kf = 4.0912386971316826e8\n", - "krev = 1.7763617117679594e-6\n", - "Kc = 2.3031563166601894e14\n", - "OCX<=>vacantX+CO\n", - "kf = 2.010168305725754e-19\n", - "krev = 2.61760793808642e-25\n", - "Kc = 767940.9419866255\n", - "vacantX+vacantX+O2<=>OX+OX\n", - "kf = 1.0945721587141857e10\n", - "krev = 4.219325007995329e-16\n", - "Kc = 2.594187830138819e25\n", - "proton+HX<=>[H][H].[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.1949534688419614e-15\n", - "Kc = 2.0921316730623565e25\n", - "vacantX+H2<=>[H][H].[Pt]\n", - "kf = 2338.960705505517\n", - "krev = 9707.159813448116\n", - "Kc = 0.24095211683495363\n", - "CHOX+C=O<=>O=COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 7.563806299311394e-5\n", - "Kc = 0.0005236345532350701\n", - "proton+OO[Pt]<=>OX+H2O\n", - "kf = 17.257164508221003\n", - "krev = 6.236444643145301e-63\n", - "Kc = 2.767147869610126e63\n", - "vacantX+vacantX+OO<=>HX+OO[Pt]\n", - "kf = 4.980245005159166e-22\n", - "krev = 5.509834949091977\n", - "Kc = 9.038827934364735e-23\n", - "proton+OC#[Pt]<=>H2O+CX\n", - "kf = 3.276640102032806e-5\n", - "krev = 0.0009291230748795855\n", - "Kc = 0.03526594259277716\n", - "vacantX+vacantX+O=C=C=O<=>OCX+OCX\n", - "kf = 74.64023007210145\n", - "krev = 2.953439666185894e-39\n", - "Kc = 2.52723056870475e40\n", - "HX+O=C=C=O<=>O=CC(=O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 5.0006650398424424e-61\n", - "Kc = 1.1597065597154312e53\n", - "proton+OC=[Pt]<=>H2O+CHX\n", - "kf = 2.5e10\n", - "krev = 6.511063937864271e-5\n", - "Kc = 3.839618261865876e14\n", - "proton+CX<=>CHX\n", - "kf = 2.5e10\n", - "krev = 6.018259224258551e-33\n", - "Kc = 4.1540251206244773e42\n", - "H2+CX<=>CH2X\n", - "kf = 4.832014059685671\n", - "krev = 1.8278921581756875e-33\n", - "Kc = 2.643489681857502e33\n", - "vacantX+vacantX+C=O<=>OX+CH2X\n", - "kf = 4.5608316796485725e-28\n", - "krev = 3.884151005592286e17\n", - "Kc = 1.1742158513101117e-45\n", - "proton+OC[Pt]<=>H2O+CH2X\n", - "kf = 7206.229958253159\n", - "krev = 0.0019484451144913943\n", - "Kc = 3.6984516036184127e6\n", - "proton+O=COC[Pt]<=>CH2X+O=CO\n", - "kf = 1981.2472905766488\n", - "krev = 1.4695324127813272e-5\n", - "Kc = 1.3482161219069803e8\n", - "proton+CHX<=>CH2X\n", - "kf = 2.5e10\n", - "krev = 6.715036577093663e-15\n", - "Kc = 3.722987911231938e24\n", - "proton+O=COC#[Pt]<=>CX+O=CO\n", - "kf = 6.185088018779624e7\n", - "krev = 3.741277098492221e-23\n", - "Kc = 1.6532023306352497e30\n", - "vacantX+vacantX+C=C=O<=>OCX+CH2X\n", - "kf = 2.4823885573387985e-14\n", - "krev = 9.351132511056354e15\n", - "Kc = 2.6546394828687704e-30\n", - "CHOX+C=O<=>O=CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.4949222028864902e7\n", - "Kc = 2.6494156850764662e-15\n", - "HX+O=CC=O<=>O=CCO[Pt]\n", - "kf = 5.6976884072695144e-8\n", - "krev = 2.551666729065355e-8\n", - "Kc = 2.23292812590636\n", - "proton+O=CC=O.[Pt]<=>O=CCO[Pt]\n", - "kf = 957581.7759153218\n", - "krev = 7139.55197608848\n", - "Kc = 134.12351070801344\n", - "O=O.[Pt]+proton<=>OO[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.545950245153839e-28\n", - "Kc = 7.050296330064662e37\n", - "proton+O=CC#[Pt]<=>CX+C=O\n", - "kf = 5.731900626219973e-17\n", - "krev = 16.634660991475336\n", - "Kc = 3.4457574032662074e-18\n", - "proton+CO2HX<=>OC(O)=[Pt]\n", - "kf = 8.313674902647437e-22\n", - "krev = 1.0085447542339753e12\n", - "Kc = 8.243238455949296e-34\n", - "proton+OC(O)=[Pt]<=>OC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.563843227039955e-39\n", - "Kc = 7.014898918762039e48\n", - "proton+OC(O)=[Pt]<=>H2O+OC#[Pt]\n", - "kf = 58948.65819613129\n", - "krev = 2.9467686111082447e-38\n", - "Kc = 2.0004508658710534e42\n", - "proton+O=C(O)C#[Pt]<=>CX+O=CO\n", - "kf = 1.2163309452954808e-9\n", - "krev = 0.00037997676558546045\n", - "Kc = 3.201066632117316e-6\n", - "proton+O=C=C=O.[Pt]<=>O=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.649884885591097e-48\n", - "Kc = 9.434372087609898e57\n", - "vacantX+O=C=C=O<=>O=C=C=O.[Pt]\n", - "kf = 366139.2749661925\n", - "krev = 442.06521987276346\n", - "Kc = 828.2471873077366\n", - "HOX+C=O<=>OOC[Pt]\n", - "kf = 1.5395975576095126e-29\n", - "krev = 2.622153295712258e16\n", - "Kc = 5.871500953537159e-46\n", - "proton+OOC[Pt]<=>OO+CH2X\n", - "kf = 15.535579749933543\n", - "krev = 3.4028033042152773e-9\n", - "Kc = 4.5655238816444645e9\n", - "vacantX+vacantX+O=C=CO<=>OCX+OC=[Pt]\n", - "kf = 73.33238091278024\n", - "krev = 14511.198914062346\n", - "Kc = 0.005053502563576338\n", - "vacantX+C=C=O<=>C=C=O.[Pt]\n", - "kf = 422670.5724931744\n", - "krev = 9.80980243728561e-11\n", - "Kc = 4.3086552985681545e15\n", - "proton+CO[Pt]<=>OX+CH4\n", - "kf = 541698.6744405399\n", - "krev = 1.9995135619129721e-19\n", - "Kc = 2.7091522896313173e24\n", - "HX+C=C=O<=>CC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.3310785577331067e-33\n", - "Kc = 2.514767798332947e25\n", - "proton+C=C=O.[Pt]<=>CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.357099551204697e-8\n", - "Kc = 3.9326110592781875e17\n", - "proton+CC(=O)[Pt]<=>OCX+CH4\n", - "kf = 1.0030005882936613e8\n", - "krev = 4.3463683404291294e-8\n", - "Kc = 2.3076750743003805e15\n", - "vacantX+vacantX+COC=O<=>CHOX+CO[Pt]\n", - "kf = 5.858305523872122e-8\n", - "krev = 9.372228401924443e12\n", - "Kc = 6.250707166578664e-21\n", - "vacantX+vacantX+COC=O<=>HX+O=COC[Pt]\n", - "kf = 8.724708246600757e-23\n", - "krev = 252.56605644619947\n", - "Kc = 3.454426287270814e-25\n", - "vacantX+vacantX+COC=O<=>HX+COC(=O)[Pt]\n", - "kf = 7.165711269221808e-16\n", - "krev = 0.1859922027934253\n", - "Kc = 3.852694447186316e-15\n", - "proton+O=COCC#[Pt]<=>CX+COC=O\n", - "kf = 0.8132675549526747\n", - "krev = 2.165706403032533e-5\n", - "Kc = 37552.06863746147\n", - "HOX+C=C=O<=>O=C([Pt])CO\n", - "kf = 3.3473534940386794e-8\n", - "krev = 9.042590347389556e-30\n", - "Kc = 3.70176394754519e21\n", - "HX+O=C=CO<=>O=C([Pt])CO\n", - "kf = 2.8488442036348548e-8\n", - "krev = 1.614840618256874e-45\n", - "Kc = 1.7641643214981894e37\n", - "vacantX+vacantX+COO<=>HOX+CO[Pt]\n", - "kf = 3.442529358831723e8\n", - "krev = 2.6586367586035048e-11\n", - "Kc = 1.294847574679578e19\n", - "vacantX+vacantX+COO<=>HX+OOC[Pt]\n", - "kf = 1.3336211820914592e-23\n", - "krev = 16620.58178963317\n", - "Kc = 8.023913957833202e-28\n", - "CHOX+C=C=O<=>O=CCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 2.6714659015861004e-16\n", - "Kc = 1.2530025152300434e8\n", - "vacantX+vacantX+CO-2<=>HX+CO[Pt]\n", - "kf = 3.6896065237788346e-26\n", - "krev = 1200.2597905170037\n", - "Kc = 3.0740066050113714e-29\n", - "vacantX+vacantX+CO-2<=>HX+OC[Pt]\n", - "kf = 1.1691860289045307e-22\n", - "krev = 1.716447494000275\n", - "Kc = 6.811662069427353e-23\n", - "proton+OCO[Pt]<=>OX+CO-2\n", - "kf = 6.4866612293733e7\n", - "krev = 4.917786339628338e-9\n", - "Kc = 1.319020547335029e16\n", - "proton+COC(=O)[Pt]<=>OCX+CO-2\n", - "kf = 5.096893185474306e9\n", - "krev = 2.041829224680708e-9\n", - "Kc = 2.49623872744369e18\n", - "proton+O=C([Pt])CO<=>OCX+CO-2\n", - "kf = 1.9762803815844387e7\n", - "krev = 1.2158736968776066e-8\n", - "Kc = 1.6253994034574272e15\n", - "proton+OCC#[Pt]<=>CX+CO-2\n", - "kf = 1.8515947729382765e-10\n", - "krev = 0.16959607683462066\n", - "Kc = 1.091767455649245e-9\n", - "vacantX+vacantX+COOC<=>CO[Pt]+CO[Pt]\n", - "kf = 3.028654941635431e8\n", - "krev = 1.0392777770118965e-11\n", - "Kc = 2.914191959673513e19\n", - "vacantX+vacantX+C=C=O<=>HX+O=C=C[Pt]\n", - "kf = 3.6584912239485734e-16\n", - "krev = 0.32395775785233605\n", - "Kc = 1.1293111942132156e-15\n", - "vacantX+vacantX+O=C=CO<=>HOX+O=C=C[Pt]\n", - "kf = 3.132095071630788e8\n", - "krev = 5.819571251914923e7\n", - "Kc = 5.382003133994065\n", - "proton+O=C=C[Pt]<=>C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.724942318590629e-29\n", - "Kc = 2.570709334924167e38\n", - "vacantX+vacantX+O=CCO<=>CHOX+OC[Pt]\n", - "kf = 9001.813049524091\n", - "krev = 8.180569891408677e12\n", - "Kc = 1.1003894800749632e-9\n", - "vacantX+vacantX+O=CCO<=>HX+O=CCO[Pt]\n", - "kf = 3.705974451661604e-28\n", - "krev = 2668.9209237076484\n", - "Kc = 1.3885665996103351e-31\n", - "vacantX+vacantX+O=CCO<=>HX+O=C([Pt])CO\n", - "kf = 1.2718474027465153e-10\n", - "krev = 0.0002705673832361486\n", - "Kc = 4.7006678614933393e-7\n", - "proton+O=CCOC#[Pt]<=>CX+O=CCO\n", - "kf = 3.8625888100004036e-23\n", - "krev = 1.5059302822169408e-12\n", - "Kc = 2.564918745318097e-11\n", - "proton+COC#[Pt]<=>CX+CO-2\n", - "kf = 3.5797175052253717e-22\n", - "krev = 9.770006712968626e-20\n", - "Kc = 0.0036639867406372244\n", - "proton+O=CC(=O)C#[Pt]<=>CX+O=CC=O\n", - "kf = 5.9931479699583235e-12\n", - "krev = 0.0016900056192162703\n", - "Kc = 3.546229611199523e-9\n", - "vacantX+vacantX+OCO<=>HOX+OC[Pt]\n", - "kf = 1.653107374238179e-12\n", - "krev = 3.492310477620836e11\n", - "Kc = 4.7335635958815765e-24\n", - "vacantX+vacantX+OCO<=>HX+OC(O)[Pt]\n", - "kf = 4.0412190145177725e-23\n", - "krev = 628.7683045605482\n", - "Kc = 6.427198993979533e-26\n", - "vacantX+vacantX+OCO<=>HX+OCO[Pt]\n", - "kf = 1.1281154422531313e-23\n", - "krev = 247.99076039714222\n", - "Kc = 4.5490220702034325e-26\n", - "proton+OC(O)C#[Pt]<=>CX+OCO\n", - "kf = 0.005562206988621036\n", - "krev = 0.025459246171787766\n", - "Kc = 0.21847492856189518\n", - "proton+OCOC#[Pt]<=>CX+OCO\n", - "kf = 2.2993090387825977e-18\n", - "krev = 1.7767009384663083e-12\n", - "Kc = 1.2941452266960681e-6\n", - "proton+O=COC=[Pt]<=>O=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.03525663068036e-45\n", - "Kc = 2.4148601669491608e55\n", - "proton+O=COC=[Pt]<=>CHX+O=CO\n", - "kf = 407721.49317133107\n", - "krev = 4.66233771243883e-34\n", - "Kc = 8.745001291595743e38\n", - "proton+O=COC#[Pt]<=>O=COC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.1834993039887084e-24\n", - "Kc = 7.852993706854812e33\n", - "proton+O=C=CC#[Pt]<=>CX+C=C=O\n", - "kf = 1.255896512556004e-15\n", - "krev = 0.016900821436021087\n", - "Kc = 7.430979123176135e-14\n", - "vacantX+vacantX+COCO<=>CO[Pt]+OC[Pt]\n", - "kf = 3.0636862331912886e-9\n", - "krev = 3.008499680951675e11\n", - "Kc = 1.0183435459837431e-20\n", - "proton+CC#[Pt]<=>CX+CH4\n", - "kf = 3.172314510568854e-8\n", - "krev = 0.363285670785801\n", - "Kc = 8.732286367659409e-8\n", - "HX+O=C=C=O<=>O=C=CO[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.1302052975227224e-55\n", - "Kc = 2.7224155607861307e47\n", - "proton+O=C=CO[Pt]<=>OX+C=C=O\n", - "kf = 0.047578794564636824\n", - "krev = 2.8204743128358057e-8\n", - "Kc = 1.6869075654441754e6\n", - "proton+O=C=C=O.[Pt]<=>O=C=CO[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 2.257619247094878e-42\n", - "Kc = 2.2147224366704162e52\n", - "vacantX+vacantX+O=C=CO<=>HX+O=C=CO[Pt]\n", - "kf = 0.0007071288662616175\n", - "krev = 2.8988454126647536e-5\n", - "Kc = 24.393465866522067\n", - "vacantX+vacantX+OCCO<=>OC[Pt]+OC[Pt]\n", - "kf = 2.961131444342359e-9\n", - "krev = 1.299206322752899e13\n", - "Kc = 2.2791849088819035e-22\n", - "proton+COC(=O)C#[Pt]<=>CX+COC=O\n", - "kf = 2.520547604265173e-10\n", - "krev = 3.828537658551766e-5\n", - "Kc = 6.583577932517004e-6\n", - "proton+O=C=CC(=O)[Pt]<=>OCX+C=C=O\n", - "kf = 2.14881300259784e7\n", - "krev = 1.9623010758881652e-11\n", - "Kc = 1.0950475587061772e18\n", - "vacantX+vacantX+OC=CO<=>OC=[Pt]+OC=[Pt]\n", - "kf = 1.351949923589269e-23\n", - "krev = 7.975137957191956e11\n", - "Kc = 1.6952056890377485e-35\n", - "vacantX+OX+CH4<=>HOX+CH3X\n", - "kf = 1181.9069662995785\n", - "krev = 1.0235810933777192e20\n", - "Kc = 1.1546783874244874e-17\n", - "vacantX+HOX+CH4<=>H2OX+CH3X\n", - "kf = 5.28370763875636e9\n", - "krev = 1.2149259925984929e9\n", - "Kc = 4.348995470461149\n", - "HX+CH3X<=>vacantX+vacantX+CH4\n", - "kf = 5.733311120080377e8\n", - "krev = 8.483521653048543e-25\n", - "Kc = 6.758173497465076e32\n", - "proton+CH2X<=>CH3X\n", - "kf = 2.5e10\n", - "krev = 7.728626954425352e-28\n", - "Kc = 3.2347272222377345e37\n", - "CO2+CH3X<=>COC(=O)[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.00447183609125585\n", - "Kc = 1.463156578060128e-5\n", - "vacantX+vacantX+COC=O<=>CHO2X+CH3X\n", - "kf = 0.05589950368763065\n", - "krev = 5.054770535995559e16\n", - "Kc = 1.1058761874463802e-18\n", - "vacantX+vacantX+COO<=>OO[Pt]+CH3X\n", - "kf = 9.385776922831516e-7\n", - "krev = 3.9782610412247473e11\n", - "Kc = 2.359266228528335e-18\n", - "vacantX+vacantX+CO-2<=>HOX+CH3X\n", - "kf = 9.872876935778847e-16\n", - "krev = 6.917821124819518e13\n", - "Kc = 1.427165686657795e-29\n", - "vacantX+vacantX+COCO<=>CH3X+OCO[Pt]\n", - "kf = 3.9072411322938125e-9\n", - "krev = 8.599564777209447e13\n", - "Kc = 4.543533578174534e-23\n", - "O=O+HX<=>OO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 8.854082166234876e-41\n", - "Kc = 8.666474551788235e32\n", - "vacantX+O=O<=>O=O.[Pt]\n", - "kf = 484458.3574999593\n", - "krev = 584.920039726471\n", - "Kc = 828.247152767255\n", - "vacantX+O=C=CO<=>O=C=CO.[Pt]\n", - "kf = 359723.7676387533\n", - "krev = 0.4900054095759742\n", - "Kc = 734122.0333670193\n", - "proton+O=C=CO.[Pt]<=>O=C([Pt])CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.543989619636675e-29\n", - "Kc = 1.6191818702694958e39\n", - "proton+O=C=CO[Pt]<=>O=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.012328788524416852\n", - "Kc = 2.0277742578265605e12\n", - "vacantX+vacantX+O=C=C=O<=>OX+O=C=C=[Pt]\n", - "kf = 149.2804601441562\n", - "krev = 1.2008902564793325e-12\n", - "Kc = 1.2430816166483347e14\n", - "proton+O=C=C=[Pt]<=>O=CC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 728325.7738813914\n", - "Kc = 34325.299057824195\n", - "proton+O=C=C=[Pt]<=>O=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.992117420427329e-15\n", - "Kc = 4.1721478812771864e24\n", - "vacantX+vacantX+C=CO<=>CH2X+OC=[Pt]\n", - "kf = 3.7510196251812924e-36\n", - "krev = 6.624293894020312e13\n", - "Kc = 5.662519938264367e-50\n", - "proton+O=C(C#[Pt])CO<=>CX+O=CCO\n", - "kf = 2.1150580786972557e-17\n", - "krev = 1.2236788896896236\n", - "Kc = 1.728442074565594e-17\n", - "vacantX+vacantX+C=C<=>CH2X+CH2X\n", - "kf = 9.387035392806688e-46\n", - "krev = 5.259242712748897e15\n", - "Kc = 1.784864457776713e-61\n", - "proton+O=COC[Pt]<=>COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.124037165592671e-28\n", - "Kc = 8.002465615756261e37\n", - "proton+COC(=O)[Pt]<=>COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.484214060387906e-18\n", - "Kc = 7.175219308200797e27\n", - "vacantX+COC=O<=>COC=O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.8619443782965007\n", - "Kc = 410274.8449265323\n", - "HX+O=C=C=C=O<=>O=C=CC(=O)[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 3.561089909521239e-25\n", - "Kc = 1.4777843564830474e17\n", - "vacantX+vacantX+O=C=C=C=O<=>OCX+O=C=C=[Pt]\n", - "kf = 135.4631249389026\n", - "krev = 3.092595390223456e6\n", - "Kc = 4.3802407960361956e-5\n", - "CH3X+O=C=C=O<=>CC(=O)C(=O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 3.5093718907449027e-71\n", - "Kc = 1.6525190917893694e63\n", - "proton+OOC#[Pt]<=>OO+CX\n", - "kf = 3.959382254258936e-52\n", - "krev = 4.505410128222608e6\n", - "Kc = 8.78806177812034e-59\n", - "proton+O=CC[Pt]<=>CH2X+C=O\n", - "kf = 9.847553463617368e-13\n", - "krev = 0.8193686811731042\n", - "Kc = 1.2018464568987987e-12\n", - "HX+C=C=O<=>O=CC[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 3.6888123831707493e-19\n", - "Kc = 9.074339235332521e10\n", - "proton+C=C=O.[Pt]<=>O=CC[Pt]\n", - "kf = 4.477750650627013e6\n", - "krev = 3155.453532604055\n", - "Kc = 1419.0513675324908\n", - "vacantX+vacantX+O=CCO<=>HOX+O=CC[Pt]\n", - "kf = 3.3834985622063113e-5\n", - "krev = 2.9362980773683545e12\n", - "Kc = 1.1523007790948657e-17\n", - "vacantX+vacantX+O=CC=O<=>OX+O=CC=[Pt]\n", - "kf = 6.170227811474367e-18\n", - "krev = 2.1467268001769245e15\n", - "Kc = 2.874249210922341e-33\n", - "proton+O=CC=[Pt]<=>CHX+C=O\n", - "kf = 0.3518802014338951\n", - "krev = 0.0019581841163396926\n", - "Kc = 179.69719930710195\n", - "proton+O=CC#[Pt]<=>O=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.1385387905668107e-13\n", - "Kc = 7.9654902068249e22\n", - "proton+O=C=C[Pt]<=>O=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.814809579170971e7\n", - "Kc = 655.3407052478085\n", - "proton+O=CC=[Pt]<=>O=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.4911345025101916e-29\n", - "Kc = 5.566522219725765e38\n", - "proton+O=CCO[Pt]<=>OX+CC=O\n", - "kf = 108844.3774855493\n", - "krev = 6.551243603618761e-23\n", - "Kc = 1.6614307766761425e27\n", - "vacantX+vacantX+CC=O<=>HX+CC(=O)[Pt]\n", - "kf = 4.3209399543319175e-11\n", - "krev = 0.0003615296985530135\n", - "Kc = 1.195182573278502e-7\n", - "proton+O=CCC(=O)[Pt]<=>OCX+CC=O\n", - "kf = 7.362850070977087e6\n", - "krev = 9.270601965584902e-14\n", - "Kc = 7.94214884676321e19\n", - "proton+O=CCC#[Pt]<=>CX+CC=O\n", - "kf = 0.11748380587607415\n", - "krev = 6.387097627333538e-5\n", - "Kc = 1839.3926745898334\n", - "vacantX+vacantX+CC=O<=>CHOX+CH3X\n", - "kf = 6.063283190982672e-6\n", - "krev = 7.026751658283665e14\n", - "Kc = 8.628856526948432e-21\n", - "proton+CC(=O)C#[Pt]<=>CX+CC=O\n", - "kf = 8.247683071468342e-18\n", - "krev = 0.06355423283679383\n", - "Kc = 1.2977393799478706e-16\n", - "proton+CC(=O)C(=O)[Pt]<=>OCX+CC=O\n", - "kf = 3.422758172577326e7\n", - "krev = 2.0119060511296993e-10\n", - "Kc = 1.7012514926606157e17\n", - "vacantX+vacantX+CC=O<=>HX+O=CC[Pt]\n", - "kf = 3.2094062904328744e-20\n", - "krev = 74.41720028073364\n", - "Kc = 4.312721089110603e-22\n", - "vacantX+CH4<=>C.[Pt]\n", - "kf = 11983.404197457203\n", - "krev = 27576.843954134933\n", - "Kc = 0.4345458899280744\n", - "proton+CH3X<=>C.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.2634270430964172e-30\n", - "Kc = 1.9787450440137642e40\n", - "HX+O=C=CC=O<=>O=CCC(=O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 3.8194581898791103e-32\n", - "Kc = 6.789235995427004e23\n", - "vacantX+vacantX+O=C=CC=O<=>CHOX+O=C=C[Pt]\n", - "kf = 2.850945414803626e8\n", - "krev = 4.6591458607721776e7\n", - "Kc = 6.119030182779314\n", - "vacantX+vacantX+O=C=CC=O<=>HX+O=C=CC(=O)[Pt]\n", - "kf = 1.1776167531898308e-10\n", - "krev = 0.0005032011998508361\n", - "Kc = 2.3402502886298994e-7\n", - "vacantX+vacantX+O=C=CC=O<=>OCX+O=CC=[Pt]\n", - "kf = 0.006845452357086415\n", - "krev = 1.638610749190394e14\n", - "Kc = 4.177595173514284e-17\n", - "vacantX+vacantX+C=C(O)O<=>CH2X+OC(O)=[Pt]\n", - "kf = 1.3631835715271243e-51\n", - "krev = 1.0974745099569602e16\n", - "Kc = 1.242109551665655e-67\n", - "proton+O=C=CC=O.[Pt]<=>O=CCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.130402878837127e-16\n", - "Kc = 4.078035407151288e25\n", - "proton+O=C=CC(=O)[Pt]<=>O=C=CC=O.[Pt]\n", - "kf = 2.964275004938465e9\n", - "krev = 9.178277268525813e-12\n", - "Kc = 3.229663822756335e20\n", - "vacantX+O=C=CC=O<=>O=C=CC=O.[Pt]\n", - "kf = 327433.4917974331\n", - "krev = 0.29189612518083846\n", - "Kc = 1.1217466199476891e6\n", - "vacantX+vacantX+CC(=O)O<=>HOX+CC(=O)[Pt]\n", - "kf = 3.661873055903852e-12\n", - "krev = 2.1682718089028445e11\n", - "Kc = 1.6888441019563762e-23\n", - "vacantX+vacantX+CC(=O)O<=>CO2HX+CH3X\n", - "kf = 1.1977509649486271e-8\n", - "krev = 1.0254845667743408e14\n", - "Kc = 1.1679853639496008e-22\n", - "CO2+CH3X<=>CC(=O)O[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 3.3286101924403974e-7\n", - "Kc = 0.19656841788766613\n", - "proton+CC(=O)O[Pt]<=>OX+CC=O\n", - "kf = 6.638543952734307e-6\n", - "krev = 1.1832604608796647e-7\n", - "Kc = 56.10382643732599\n", - "vacantX+vacantX+CC(=O)O<=>HX+CC(=O)O[Pt]\n", - "kf = 2.4753542791841756e-22\n", - "krev = 11382.562807978633\n", - "Kc = 2.1746897609465158e-26\n", - "proton+CC(=O)OC#[Pt]<=>CX+CC(=O)O\n", - "kf = 3.5372794201475537e8\n", - "krev = 2.288049006228874e-19\n", - "Kc = 1.5459806195224992e27\n", - "vacantX+vacantX+CC(=O)C=O<=>CHOX+CC(=O)[Pt]\n", - "kf = 2.810784197367395e8\n", - "krev = 8.682228189641076\n", - "Kc = 3.237399589106622e7\n", - "vacantX+vacantX+CC(=O)C=O<=>CH3X+O=CC(=O)[Pt]\n", - "kf = 0.010756441693245073\n", - "krev = 2.0353876594794328e15\n", - "Kc = 5.284714016589902e-18\n", - "vacantX+vacantX+CC(=O)C=O<=>HX+CC(=O)C(=O)[Pt]\n", - "kf = 2.426386880233808e-11\n", - "krev = 0.0003222108693910823\n", - "Kc = 7.530431499158364e-8\n", - "proton+O=C=C([Pt])C=O<=>C=O+O=C=C=[Pt]\n", - "kf = 13308.622034460761\n", - "krev = 4.6234228919871786e-9\n", - "Kc = 2.8785214645897607e12\n", - "HX+O=C=C=C=O<=>O=C=C([Pt])C=O\n", - "kf = 5.262522960320117e-8\n", - "krev = 8.417963556232881e-20\n", - "Kc = 6.251539253129229e11\n", - "vacantX+vacantX+O=C=CC=O<=>HX+O=C=C([Pt])C=O\n", - "kf = 3.109950102720783e-13\n", - "krev = 0.31413419650430946\n", - "Kc = 9.900068624582613e-13\n", - "proton+O=C=C([Pt])C=O<=>O=C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.274602487927107e-16\n", - "Kc = 7.6345144463093386e25\n", - "proton+O=C=COC#[Pt]<=>CX+O=C=CO\n", - "kf = 3.333143073629419e-24\n", - "krev = 2.9895559923107984e-13\n", - "Kc = 1.1149291340260339e-11\n", - "vacantX+vacantX+COC(C)=O<=>CO[Pt]+CC(=O)[Pt]\n", - "kf = 6.614441053978493e-6\n", - "krev = 7.629970776987544e11\n", - "Kc = 8.669025409544227e-18\n", - "vacantX+vacantX+COC(C)=O<=>CH3X+COC(=O)[Pt]\n", - "kf = 1.5563360867242215e-10\n", - "krev = 4.0343976517667425e14\n", - "Kc = 3.857666549162974e-25\n", - "vacantX+vacantX+COC(C)=O<=>CH3X+CC(=O)O[Pt]\n", - "kf = 0.0003463783354588583\n", - "krev = 6.683486846094463e16\n", - "Kc = 5.182599194629471e-21\n", - "vacantX+vacantX+COO<=>HX+COO[Pt]\n", - "kf = 1.175900379595729e-21\n", - "krev = 0.27982743013843664\n", - "Kc = 4.2022341377111815e-21\n", - "proton+COO[Pt]<=>OX+CO-2\n", - "kf = 129.78074174016686\n", - "krev = 1.499485133709293e-58\n", - "Kc = 8.65502023478731e59\n", - "vacantX+vacantX+COOC<=>CH3X+COO[Pt]\n", - "kf = 1.8186835430204133e-8\n", - "krev = 4.141977957602716e12\n", - "Kc = 4.39085760869917e-21\n", - "O=O+CH3X<=>COO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 4.970959816815508e-38\n", - "Kc = 1.543639067721808e30\n", - "proton+CO[Pt]<=>CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.487564815762018e-25\n", - "Kc = 1.0049989387851077e35\n", - "proton+OC[Pt]<=>CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.512171272873819e-19\n", - "Kc = 4.535417853038886e28\n", - "vacantX+CO-2<=>CO.[Pt]\n", - "kf = 484125.61468448705\n", - "krev = 1.0558750276780043e7\n", - "Kc = 0.04585065485913965\n", - "vacantX+vacantX+CC(=O)CO<=>OC[Pt]+CC(=O)[Pt]\n", - "kf = 4.324183911493771e7\n", - "krev = 7.8667392573421875e12\n", - "Kc = 5.496793232924203e-6\n", - "vacantX+vacantX+CC(=O)CO<=>CH3X+O=C([Pt])CO\n", - "kf = 0.43146252134138535\n", - "krev = 2.5450806210309695e15\n", - "Kc = 1.695280368629765e-16\n", - "HX+O=C=C=O<=>O=C=C(O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 7.390785994602033e-44\n", - "Kc = 7.846667531546056e35\n", - "proton+O=C=C=O.[Pt]<=>O=C=C(O)[Pt]\n", - "kf = 5.0e10\n", - "krev = 7.832851008293297e-31\n", - "Kc = 6.383371769367348e40\n", - "vacantX+vacantX+O=C=CO<=>HX+O=C=C(O)[Pt]\n", - "kf = 2.8707175642480555e-12\n", - "krev = 0.04083063397693327\n", - "Kc = 7.030793511239207e-11\n", - "proton+O=C=C(O)[Pt]<=>O=C=CO.[Pt]\n", - "kf = 1.7351014576291664e10\n", - "krev = 2.4662443446341767e-14\n", - "Kc = 7.03539964077054e23\n", - "proton+O=C=C(O)[Pt]<=>H2O+O=C=C=[Pt]\n", - "kf = 1.2324712433709262e6\n", - "krev = 1.176415080398485e-31\n", - "Kc = 1.0476499867321094e37\n", - "vacantX+vacantX+O=CCC=O<=>HX+O=CCC(=O)[Pt]\n", - "kf = 3.286584099620913e-11\n", - "krev = 0.0009472638388816695\n", - "Kc = 3.469555117295539e-8\n", - "vacantX+vacantX+O=CCC=O<=>CHOX+O=CC[Pt]\n", - "kf = 5.621568394735124e8\n", - "krev = 2.2372815421494465e13\n", - "Kc = 2.51267812692642e-5\n", - "proton+O=C=C(O)C#[Pt]<=>CX+O=C=CO\n", - "kf = 3.0900625689798e-31\n", - "krev = 97363.75326657317\n", - "Kc = 3.1737299203323514e-36\n", - "proton+COOC#[Pt]<=>CX+COO\n", - "kf = 1.3396315820930446e-65\n", - "krev = 2.5e10\n", - "Kc = 5.3585263283721787e-76\n", - "vacantX+vacantX+COC=C=O<=>CO[Pt]+O=C=C[Pt]\n", - "kf = 1.4053920986837533e8\n", - "krev = 2.5815645207863396e8\n", - "Kc = 0.5443954963619013\n", - "vacantX+vacantX+COC=C=O<=>CH3X+O=C=CO[Pt]\n", - "kf = 1.4053920986837533e8\n", - "krev = 1.2268284001067661e8\n", - "Kc = 1.1455490421981163\n", - "HX+O=CC=O<=>O=CC(O)[Pt]\n", - "kf = 5.6976884072695144e-8\n", - "krev = 1.248882373151946e-25\n", - "Kc = 4.562229822244678e17\n", - "proton+O=CC(O)[Pt]<=>C=O+OC=[Pt]\n", - "kf = 1.4979350850413518e-9\n", - "krev = 7.682289195925664e-6\n", - "Kc = 0.00019498551106820976\n", - "proton+O=CC=O.[Pt]<=>O=CC(O)[Pt]\n", - "kf = 3.43386635836783e8\n", - "krev = 1.2530721027853126e-11\n", - "Kc = 2.7403581571523903e19\n", - "HX+O=C=CO<=>O=CC(O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 2.6755933088589045e-38\n", - "Kc = 1.0647523277182356e30\n", - "vacantX+vacantX+O=CCO<=>HX+O=CC(O)[Pt]\n", - "kf = 5.743984385098034e-15\n", - "krev = 0.20246227896672986\n", - "Kc = 2.8370639777506056e-14\n", - "proton+O=C=CO.[Pt]<=>O=CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.5582018736355307e-22\n", - "Kc = 9.77248912904274e31\n", - "proton+O=CC(O)[Pt]<=>H2O+O=CC=[Pt]\n", - "kf = 459.6019775429135\n", - "krev = 1.1031455244918085e-6\n", - "Kc = 4.166286018833649e8\n", - "proton+O=CC(O)C#[Pt]<=>CX+O=CCO\n", - "kf = 0.2097860124056399\n", - "krev = 0.0024507024511013467\n", - "Kc = 85.60240036947854\n", - "vacantX+vacantX+O=C=CCO<=>OC[Pt]+O=C=C[Pt]\n", - "kf = 4067.906517801298\n", - "krev = 9.581534474143486e11\n", - "Kc = 4.245568941779481e-9\n", - "proton+O=CC(=O)[Pt]<=>O=CC(O)=[Pt]\n", - "kf = 1.4625119078213113e-5\n", - "krev = 1.0085447542339824e12\n", - "Kc = 1.4501209804339615e-17\n", - "proton+O=CC(O)=[Pt]<=>OC#[Pt]+C=O\n", - "kf = 345367.8200620121\n", - "krev = 2.1066346546856475e-20\n", - "Kc = 1.6394291211996983e25\n", - "proton+O=CC(O)=[Pt]<=>H2O+O=CC#[Pt]\n", - "kf = 109541.91076063467\n", - "krev = 6.52855201530546e-37\n", - "Kc = 1.6778898368861259e41\n", - "proton+O=C=C(O)[Pt]<=>O=CC(O)=[Pt]\n", - "kf = 266253.7431100425\n", - "krev = 124230.61178859882\n", - "Kc = 2.1432217009695007\n", - "proton+O=CC(O)=[Pt]<=>O=CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.793151847783197e-46\n", - "Kc = 3.207944678649035e55\n", - "proton+OC(O)[Pt]<=>OCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.3128823116835e-26\n", - "Kc = 5.796587570283467e35\n", - "proton+OCO[Pt]<=>OCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.052557862362137e-26\n", - "Kc = 8.189852945376913e35\n", - "vacantX+OCO<=>OCO.[Pt]\n", - "kf = 395377.4080430906\n", - "krev = 715.0601225795458\n", - "Kc = 552.9289014422803\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.079525546868e-12\n", - "Kc = 1.2021973010936467e22\n", - "vacantX+O=C=C=C=O<=>O=C=C=C=O.[Pt]\n", - "kf = 332249.5811031886\n", - "krev = 401.14766551623046\n", - "Kc = 828.2475748067037\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 4.91573386591171e-7\n", - "Kc = 5.08571063485824e16\n", - "proton+O=CCO[Pt]<=>O=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.8816895227328687e-31\n", - "Kc = 1.3285932507978942e41\n", - "proton+O=C([Pt])CO<=>O=CCO.[Pt]\n", - "kf = 3.74256001789537e8\n", - "krev = 9.536073355505413e-9\n", - "Kc = 3.9246342581191416e16\n", - "vacantX+O=CCO<=>O=CCO.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 1291.5767888759226\n", - "Kc = 273.8002875141987\n", - "proton+O=CC(O)[Pt]<=>O=CCO.[Pt]\n", - "kf = 1.712472301799593e10\n", - "krev = 2.6335036754646568e-14\n", - "Kc = 6.5026387384762e23\n", - "proton+OCC#[Pt]<=>OCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.6468663797080987e-6\n", - "Kc = 6.855200437039605e15\n", - "proton+OCC=[Pt]<=>CHX+CO-2\n", - "kf = 2.437334851076409e7\n", - "krev = 3.684139726492616e-11\n", - "Kc = 6.615750302708541e17\n", - "vacantX+vacantX+O=CCO<=>OX+OCC=[Pt]\n", - "kf = 3.3881471741726223e-34\n", - "krev = 2.264159139077055e16\n", - "Kc = 1.4964262518904662e-50\n", - "vacantX+vacantX+O=C=CCO<=>OCX+OCC=[Pt]\n", - "kf = 1.8009876630720204e-13\n", - "krev = 6.668943472119082e14\n", - "Kc = 2.7005591974222413e-28\n", - "vacantX+vacantX+C=CC=O<=>CH2X+O=CC=[Pt]\n", - "kf = 3.2830355290077765e-39\n", - "krev = 2.9277080237249806e14\n", - "Kc = 1.121367124864694e-53\n", - "vacantX+vacantX+C=COC=O<=>CH2X+O=COC=[Pt]\n", - "kf = 1.0242943870290668e-63\n", - "krev = 2.920849603333263e13\n", - "Kc = 3.5068371403311754e-77\n", - "vacantX+O=C=CCO<=>O=C=CCO.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 1179.037991138623\n", - "Kc = 273.8002884035305\n", - "vacantX+vacantX+O=CC=CO<=>OC=[Pt]+O=CC=[Pt]\n", - "kf = 6.284377773759944e-35\n", - "krev = 2.1623088290446475e12\n", - "Kc = 2.90632757418676e-47\n", - "vacantX+vacantX+COC<=>CH3X+CO[Pt]\n", - "kf = 3.3416169046706564e-11\n", - "krev = 3.110510590664853e12\n", - "Kc = 1.0742985137872191e-23\n", - "proton+O=C=CC(O)[Pt]<=>OC=[Pt]+C=C=O\n", - "kf = 7.886335155622577e-9\n", - "krev = 1.1676117437495351e-7\n", - "Kc = 0.0675424446340125\n", - "HX+O=C=CC=O<=>O=C=CC(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 3.0624966294759025e-24\n", - "Kc = 8.467340919226885e15\n", - "proton+O=C=CC=O.[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 5.4417257022505686e7\n", - "krev = 1.0699402207865258e-10\n", - "Kc = 5.086009102686402e17\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=CC(O)[Pt]\n", - "kf = 2.2665619116480148e-11\n", - "krev = 0.03466826587817799\n", - "Kc = 6.537857761944495e-10\n", - "proton+O=C=CC(O)[Pt]<=>O=C=CCO.[Pt]\n", - "kf = 1.693513701515947e9\n", - "krev = 6.001577582317764e-11\n", - "Kc = 2.8217809039168078e19\n", - "proton+O=C=CC=[Pt]<=>CHX+C=C=O\n", - "kf = 181.35768264661723\n", - "krev = 8.307531938850336e-7\n", - "Kc = 2.183051283841528e8\n", - "proton+O=C=CC#[Pt]<=>O=C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.768026569342988e-11\n", - "Kc = 1.4140058997693788e21\n", - "vacantX+vacantX+O=C=CC=O<=>OX+O=C=CC=[Pt]\n", - "kf = 3.709849833927781e-21\n", - "krev = 2.4389911159903437e17\n", - "Kc = 1.5210591828750508e-38\n", - "proton+O=C=CC(O)[Pt]<=>H2O+O=C=CC=[Pt]\n", - "kf = 4.694863820330143\n", - "krev = 3.9520471176425216e-5\n", - "Kc = 118795.74510565875\n", - "vacantX+vacantX+CCO<=>CH3X+OC[Pt]\n", - "kf = 1.5510087911871897e-15\n", - "krev = 9.749013808701775e13\n", - "Kc = 1.5909391674086975e-29\n", - "proton+O=C=C([Pt])CO<=>CO-2+O=C=C=[Pt]\n", - "kf = 259142.28390262663\n", - "krev = 5.010713983419634e-21\n", - "Kc = 5.171763640074528e25\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=C([Pt])CO\n", - "kf = 4.040764431615523e-20\n", - "krev = 30.812673220085827\n", - "Kc = 1.3113969056672023e-21\n", - "proton+O=C=C([Pt])CO<=>O=C=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.777114479215893e-21\n", - "Kc = 1.4067748753603438e31\n", - "proton+O=C=CC[Pt]<=>CH2X+C=C=O\n", - "kf = 6.0148104045883e-8\n", - "krev = 8.74545093406659e-6\n", - "Kc = 0.006877644674854341\n", - "vacantX+vacantX+O=C=CCO<=>HOX+O=C=CC[Pt]\n", - "kf = 8.032715739528718e-6\n", - "krev = 4.997427676480693e14\n", - "Kc = 1.6073700830795308e-20\n", - "proton+O=C=CC=[Pt]<=>O=C=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.1155543114237032e-25\n", - "Kc = 1.1817233840324226e35\n", - "vacantX+vacantX+CC(O)O<=>CH3X+OC(O)[Pt]\n", - "kf = 1.0212279299691738e-21\n", - "krev = 4.839386960246169e15\n", - "Kc = 2.1102423475497943e-37\n", - "proton+O=C=CC(O)=[Pt]<=>OC#[Pt]+C=C=O\n", - "kf = 1.5097720767202745e6\n", - "krev = 3.361950781834918e-17\n", - "Kc = 4.490761985207459e22\n", - "proton+O=C=CC(O)=[Pt]<=>H2O+O=C=CC#[Pt]\n", - "kf = 5.803789817126122e6\n", - "krev = 2.7232165859221153e-28\n", - "Kc = 2.1312259359498893e34\n", - "proton+O=C=CC(=O)[Pt]<=>O=C=CC(O)=[Pt]\n", - "kf = 0.6530550593549805\n", - "krev = 1.0085447542339824e12\n", - "Kc = 6.475221417923034e-13\n", - "proton+O=C=CC(O)=[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.85508059604632e-41\n", - "Kc = 2.5367626125786886e50\n", - "C=O+O=C=C[Pt]<=>O=C=CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 80798.59947863563\n", - "Kc = 4.901904683810505e-13\n", - "HX+O=C=CC=O<=>O=C=CCO[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 2.019947796444839e-5\n", - "Kc = 0.0012837560986177624\n", - "proton+O=C=CC=O.[Pt]<=>O=C=CCO[Pt]\n", - "kf = 278.5863350248319\n", - "krev = 3612.827309769227\n", - "Kc = 0.07711033800910536\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=CCO[Pt]\n", - "kf = 7.342900678318069e-26\n", - "krev = 740.7927312780465\n", - "Kc = 9.912220204496055e-29\n", - "proton+O=C=CCO[Pt]<=>O=C=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3432355963676785e-28\n", - "Kc = 1.861177597407629e38\n", - "vacantX+vacantX+CCOC=O<=>CH3X+O=COC[Pt]\n", - "kf = 1.714178070740009e-17\n", - "krev = 1.2983121019578911e14\n", - "Kc = 1.3203127877765141e-31\n", - "proton+O=CC([Pt])C=O<=>C=O+O=CC=[Pt]\n", - "kf = 1.0131844482393167e-10\n", - "krev = 2.9534786470384583e-7\n", - "Kc = 0.00034304783251277847\n", - "HX+O=C=CC=O<=>O=CC([Pt])C=O\n", - "kf = 2.5931203025755725e-8\n", - "krev = 5.183135272095574e-24\n", - "Kc = 5.002995612590211e15\n", - "proton+O=C=CC=O.[Pt]<=>O=CC([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 8.319166178505196e-8\n", - "Kc = 3.005108861101275e17\n", - "vacantX+vacantX+O=CCC=O<=>HX+O=CC([Pt])C=O\n", - "kf = 6.269624738894468e-15\n", - "krev = 24.522149705338403\n", - "Kc = 2.556719053684591e-16\n", - "proton+O=CC(=[Pt])C=O<=>C=O+O=CC#[Pt]\n", - "kf = 0.04202179791424184\n", - "krev = 2.102387409121332e-9\n", - "Kc = 1.9987656761987723e7\n", - "proton+O=C=C([Pt])C=O<=>O=CC(=[Pt])C=O\n", - "kf = 2.5e10\n", - "krev = 5.057292696382588\n", - "Kc = 4.943356357025204e9\n", - "proton+O=CC(=[Pt])C=O<=>O=CC([Pt])C=O\n", - "kf = 2.5e10\n", - "krev = 5.3866690937421086e-24\n", - "Kc = 4.641087017771969e33\n", - "vacantX+vacantX+COCC=O<=>CH3X+O=CCO[Pt]\n", - "kf = 1.7650043109029407e-12\n", - "krev = 1.4735149295451475e13\n", - "Kc = 1.1978190892492496e-25\n", - "vacantX+vacantX+COCC=O<=>CO[Pt]+O=CC[Pt]\n", - "kf = 10.947009513309483\n", - "krev = 5.112987413682155e11\n", - "Kc = 2.1410202348661592e-11\n", - "proton+O=CCC(=O)[Pt]<=>O=CCC=O.[Pt]\n", - "kf = 2.1814901321970692e8\n", - "krev = 5.7550523540318155e-8\n", - "Kc = 3.7905652251256815e15\n", - "vacantX+O=CCC=O<=>O=CCC=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 165389.8266532618\n", - "Kc = 1.951879075907524\n", - "proton+O=CC([Pt])C=O<=>O=CCC=O.[Pt]\n", - "kf = 1.6062704929440186e10\n", - "krev = 3.122654421781107e-14\n", - "Kc = 5.1439265316711864e23\n", - "proton+O=CCC#[Pt]<=>O=CCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.03648176110191e-17\n", - "Kc = 4.141485220927174e26\n", - "proton+O=CCC=[Pt]<=>CHX+CC=O\n", - "kf = 1.0605779567215914e7\n", - "krev = 5.748508015003e-13\n", - "Kc = 1.8449621257439228e19\n", - "vacantX+vacantX+O=CCC=O<=>OX+O=CCC=[Pt]\n", - "kf = 1.2771337705277995e-31\n", - "krev = 6.599290845791489e16\n", - "Kc = 1.935259106426951e-48\n", - "vacantX+vacantX+CCOO<=>CH3X+OOC[Pt]\n", - "kf = 1.1728434846364774e-18\n", - "krev = 2.6840450809869076e16\n", - "Kc = 4.3696862356918e-35\n", - "proton+OOCC#[Pt]<=>CX+COO\n", - "kf = 0.24698833297799483\n", - "krev = 0.0004336424509567548\n", - "Kc = 569.5667765760919\n", - "vacantX+vacantX+C=C=O<=>OX+C=C=[Pt]\n", - "kf = 5.2796000958546504e-37\n", - "krev = 1.4614931014553018e17\n", - "Kc = 3.612470076387919e-54\n", - "proton+C=C=[Pt]<=>CC#[Pt]\n", - "kf = 10.738937415423795\n", - "krev = 4.122167482176662e-33\n", - "Kc = 2.60516766042539e33\n", - "vacantX+vacantX+CC(C)=O<=>CH3X+CC(=O)[Pt]\n", - "kf = 0.0015322757193851075\n", - "krev = 1.9084257758101816e14\n", - "Kc = 8.029003479239911e-18\n", - "vacantX+vacantX+C=C=C=O<=>CH2X+O=C=C=[Pt]\n", - "kf = 0.014873013888318402\n", - "krev = 6.520037160662236e15\n", - "Kc = 2.2811240981957472e-18\n", - "HOX+C=C=C=O<=>O=C=C([Pt])CO\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.9529365102554657e-31\n", - "Kc = 9.99708792916859e22\n", - "HX+C=C=C=O<=>O=C=CC[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.4091973858076736e-32\n", - "Kc = 1.225336127134283e24\n", - "vacantX+vacantX+C=C=C=O<=>OCX+C=C=[Pt]\n", - "kf = 0.8504584217531632\n", - "krev = 1.347597642765549e15\n", - "Kc = 6.310922450174717e-16\n", - "proton+O=C(O)C=[Pt]<=>CHX+O=CO\n", - "kf = 7.88145235948431e7\n", - "krev = 1.995696153847229e-7\n", - "Kc = 3.949224607308452e14\n", - "proton+O=C(O)C#[Pt]<=>O=C(O)C=[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.424855572557093e-13\n", - "Kc = 3.3670688615684534e22\n", - "vacantX+vacantX+CC=C=O<=>CH3X+O=C=C[Pt]\n", - "kf = 0.0008567749561878586\n", - "krev = 1.2359860589695025e13\n", - "Kc = 6.931914401220598e-17\n", - "vacantX+vacantX+CC=C=O<=>HX+O=C=CC[Pt]\n", - "kf = 2.2773385768535307e-19\n", - "krev = 181.8091471864856\n", - "Kc = 1.2525984594810374e-21\n", - "proton+O=C=CCO[Pt]<=>OX+CC=C=O\n", - "kf = 3.801213612232799e6\n", - "krev = 3.4005935521726275e-15\n", - "Kc = 1.1178088630451637e21\n", - "proton+CC(=O)[Pt]<=>CC=O.[Pt]\n", - "kf = 2.2108223076011086e9\n", - "krev = 2.493722128340101e-11\n", - "Kc = 8.865551949337277e19\n", - "proton+O=CC[Pt]<=>CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0175396707648368e-24\n", - "Kc = 2.456906665978799e34\n", - "vacantX+CC=O<=>CC=O.[Pt]\n", - "kf = 412885.969273148\n", - "krev = 2.625517699834265\n", - "Kc = 157258.8786200951\n", - "proton+CC=[Pt]<=>CHX+CH4\n", - "kf = 3.754229088708618e7\n", - "krev = 3.193900280463504e-10\n", - "Kc = 1.1754371642948722e17\n", - "proton+CC#[Pt]<=>CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.101069134371629e-9\n", - "Kc = 3.086012424450092e18\n", - "vacantX+vacantX+CC=O<=>OX+CC=[Pt]\n", - "kf = 6.186864182993887e-31\n", - "krev = 2.034915252803989e19\n", - "Kc = 3.04035471475717e-50\n", - "vacantX+vacantX+CC=C=O<=>OCX+CC=[Pt]\n", - "kf = 5.619880038277716e-8\n", - "krev = 4.919193785592355e16\n", - "Kc = 1.14243924578405e-24\n", - "vacantX+vacantX+CC<=>CH3X+CH3X\n", - "kf = 1.6866972609475142e-22\n", - "krev = 6.547125244410207e13\n", - "Kc = 2.576241018739606e-36\n", - "proton+O=C=CC[Pt]<=>CC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.381078389100095e-19\n", - "Kc = 1.0499444333476355e29\n", - "vacantX+CC=C=O<=>CC=C=O.[Pt]\n", - "kf = 365995.57053717994\n", - "krev = 187509.1639624155\n", - "Kc = 1.9518809790573244\n", - "proton+O=C(O)C[Pt]<=>CH2X+O=CO\n", - "kf = 5.038535015011119e-9\n", - "krev = 7.877133180076684e-5\n", - "Kc = 6.396407042799381e-5\n", - "HOX+C=C=O<=>O=C(O)C[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.348252838458729e-29\n", - "Kc = 4.5553052781738184e20\n", - "vacantX+vacantX+CC(=O)O<=>HX+O=C(O)C[Pt]\n", - "kf = 1.1112170024966995e-23\n", - "krev = 36323.66987445037\n", - "Kc = 3.0592090676342045e-28\n", - "proton+O=C(O)C=[Pt]<=>O=C(O)C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0876086200539217e-33\n", - "Kc = 2.2986209872776243e43\n", - "vacantX+vacantX+O=C=C=CO<=>OC=[Pt]+O=C=C=[Pt]\n", - "kf = 0.004371453552681894\n", - "krev = 1.2572855491392857e13\n", - "Kc = 3.476897953431907e-16\n", - "HX+O=C=C=CO<=>O=C=CC(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.3635197599529065e-33\n", - "Kc = 1.9017841755847633e25\n", - "HX+O=C=C=CO<=>O=C=C([Pt])CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 6.797711819853139e-22\n", - "Kc = 3.814695843684052e13\n", - "proton+O=C(O)CC#[Pt]<=>CX+CC(=O)O\n", - "kf = 0.12574987603391333\n", - "krev = 9.921358720719502e-5\n", - "Kc = 1267.4662772882168\n", - "proton+CC([Pt])=C=O<=>CH4+O=C=C=[Pt]\n", - "kf = 49487.72961177987\n", - "krev = 1.2730900614037961e-24\n", - "Kc = 3.8872135689451003e28\n", - "HX+C=C=C=O<=>CC([Pt])=C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.301177455844525e-32\n", - "Kc = 1.2828548214436644e24\n", - "vacantX+vacantX+CC=C=O<=>HX+CC([Pt])=C=O\n", - "kf = 4.581183222917958e-20\n", - "krev = 34.93361388628861\n", - "Kc = 1.3113968791863429e-21\n", - "proton+CC([Pt])=C=O<=>CC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.492848961236613e-19\n", - "Kc = 1.0028686209532082e29\n", - "CH3X+O=C=C=O<=>CC(=C=O)O[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.951682102619952e-64\n", - "Kc = 1.9647454732667077e56\n", - "proton+CC(=C=O)O[Pt]<=>OX+CC=C=O\n", - "kf = 1.920567374031219e-6\n", - "krev = 5.0434729686975995e-5\n", - "Kc = 0.03808025513274787\n", - "vacantX+C=C<=>C=C.[Pt]\n", - "kf = 36.21750369826068\n", - "krev = 0.32335117013731834\n", - "Kc = 112.00671914340097\n", - "vacantX+vacantX+C=CO<=>HOX+C=C[Pt]\n", - "kf = 1.7018617233469498e-12\n", - "krev = 4.164837143763027e13\n", - "Kc = 4.086262354568991e-26\n", - "vacantX+vacantX+C=C<=>HX+C=C[Pt]\n", - "kf = 6.071347272542775e-23\n", - "krev = 1180.067101472276\n", - "Kc = 5.144916983930861e-26\n", - "vacantX+vacantX+C=CC=O<=>CHOX+C=C[Pt]\n", - "kf = 0.3274906030624493\n", - "krev = 2.9425898600264806e14\n", - "Kc = 1.1129332276687114e-15\n", - "vacantX+vacantX+C=COC=O<=>CHO2X+C=C[Pt]\n", - "kf = 0.2513917911405871\n", - "krev = 1.0405847657707406e16\n", - "Kc = 2.4158703779829617e-17\n", - "proton+C=C=[Pt]<=>C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.446578752089028e-33\n", - "Kc = 1.0218350820979533e43\n", - "proton+C=C[Pt]<=>CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 31.775139733809926\n", - "Kc = 7.867786014296917e8\n", - "proton+C=C[Pt]<=>C=C.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.7043133558442046e-25\n", - "Kc = 1.4668664019015827e35\n", - "proton+C=CC#[Pt]<=>CX+C=C\n", - "kf = 1.0856530221273585e-15\n", - "krev = 0.12983129718682296\n", - "Kc = 8.36202861444987e-15\n", - "vacantX+CC(=O)O<=>CC(=O)O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 181176.05501028927\n", - "Kc = 1.9518809818483447\n", - "proton+CC(=O)O[Pt]<=>CC(=O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.133892027559991e-24\n", - "Kc = 6.04756965913213e33\n", - "proton+O=C(O)C[Pt]<=>CC(=O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.815284645396005e-26\n", - "Kc = 4.2990157016290936e35\n", - "proton+C=CC(=O)[Pt]<=>OCX+C=C\n", - "kf = 7.087170621400232e6\n", - "krev = 2.9783308105065206e-7\n", - "Kc = 2.3795780496911715e13\n", - "vacantX+vacantX+C=CC=O<=>HX+C=CC(=O)[Pt]\n", - "kf = 3.052485738368744e-11\n", - "krev = 0.0007099643372969683\n", - "Kc = 4.29949164769375e-8\n", - "HX+C=C=C=O<=>C=CC(=O)[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 5.604440911093213e-48\n", - "Kc = 5.267388203494818e39\n", - "HX+O=C=CC=O<=>O=CC=CO[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 5.6159867257682645e-34\n", - "Kc = 4.61739037002591e25\n", - "proton+O=C=CC=O.[Pt]<=>O=CC=CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 9.013912308921113e-18\n", - "Kc = 2.7734904826239954e27\n", - "proton+O=CC=CO[Pt]<=>OX+C=CC=O\n", - "kf = 3.6615493516163485e-10\n", - "krev = 9.407550626549198e-5\n", - "Kc = 3.892138875429521e-6\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC=CO[Pt]\n", - "kf = 4.135805741920728e-10\n", - "krev = 0.028732529553568358\n", - "Kc = 1.4394158141245496e-8\n", - "HX+C=C=O<=>C=CO[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.272169613200064e-8\n", - "Kc = 0.46029640012283785\n", - "proton+C=C=O.[Pt]<=>C=CO[Pt]\n", - "kf = 2.7021695253394946e-5\n", - "krev = 3753.979595717479\n", - "Kc = 7.19814654406251e-9\n", - "vacantX+vacantX+C=CO<=>HX+C=CO[Pt]\n", - "kf = 1.5839272910037507e-20\n", - "krev = 3600.161649580889\n", - "Kc = 4.399600476795654e-24\n", - "proton+C=CO[Pt]<=>OX+C=C\n", - "kf = 6.694428008398142e6\n", - "krev = 4.294813980591457e-9\n", - "Kc = 1.5587236231070068e15\n", - "vacantX+vacantX+C=COC=O<=>CHOX+C=CO[Pt]\n", - "kf = 0.024290856013790354\n", - "krev = 3.5586883050271985e15\n", - "Kc = 6.825789148062155e-18\n", - "vacantX+vacantX+O=CCCO<=>OC[Pt]+O=CC[Pt]\n", - "kf = 2.162232232095232e-5\n", - "krev = 5.66671683371172e13\n", - "Kc = 3.815670158833332e-19\n", - "proton+C=COC(=O)[Pt]<=>OCX+C=CO\n", - "kf = 8.547694380469097e6\n", - "krev = 5.219823560516419e-10\n", - "Kc = 1.637544695020963e16\n", - "vacantX+vacantX+C=COC=O<=>HX+C=COC(=O)[Pt]\n", - "kf = 3.5117597357119104e-15\n", - "krev = 0.7837038908782975\n", - "Kc = 4.480977798612533e-15\n", - "CO2+C=C[Pt]<=>C=COC(=O)[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.08399332498323721\n", - "Kc = 7.789900440580834e-7\n", - "proton+C=COC#[Pt]<=>CX+C=CO\n", - "kf = 3.59319568894763e-23\n", - "krev = 3.7552909398960855e-5\n", - "Kc = 9.568355012853036e-19\n", - "vacantX+vacantX+CCC=O<=>CH3X+O=CC[Pt]\n", - "kf = 1.2257627381394946e-12\n", - "krev = 3.270257576074817e14\n", - "Kc = 3.748214657790771e-27\n", - "proton+CC(O)=[Pt]<=>OC#[Pt]+CH4\n", - "kf = 7.023325690411809e6\n", - "krev = 0.001122962882704699\n", - "Kc = 6.254281239906934e9\n", - "proton+CC(=O)[Pt]<=>CC(O)=[Pt]\n", - "kf = 9.881755573608883e9\n", - "krev = 1.0085447542339819e12\n", - "Kc = 0.009798033782957261\n", - "proton+CC(O)=[Pt]<=>H2O+CC#[Pt]\n", - "kf = 7.254296675241664e9\n", - "krev = 2.8720393080667615e-6\n", - "Kc = 2.5258347456688205e15\n", - "vacantX+vacantX+CC(=O)O<=>OX+CC(O)=[Pt]\n", - "kf = 1.1829749543892744e-33\n", - "krev = 3.758913107590896e15\n", - "Kc = 3.1471197139415875e-49\n", - "vacantX+vacantX+CC(O)=C=O<=>CH3X+O=C=C(O)[Pt]\n", - "kf = 1.049990631922765e-6\n", - "krev = 1.7955210884029898e15\n", - "Kc = 5.847832357439309e-22\n", - "vacantX+vacantX+CC(O)=C=O<=>HOX+CC([Pt])=C=O\n", - "kf = 0.0029164033711847528\n", - "krev = 3.4437539939134434e12\n", - "Kc = 8.468675103794464e-16\n", - "vacantX+vacantX+CC(O)=C=O<=>HX+CC(=C=O)O[Pt]\n", - "kf = 1.7528367761452354e-6\n", - "krev = 1.1970864565480504e-5\n", - "Kc = 0.14642524494009906\n", - "vacantX+vacantX+CC(O)=C=O<=>OCX+CC(O)=[Pt]\n", - "kf = 65.80946386077328\n", - "krev = 1217.699742052305\n", - "Kc = 0.054044081301896585\n", - "vacantX+vacantX+C=CC=O<=>HX+O=CC=C[Pt]\n", - "kf = 6.342176392543457e-21\n", - "krev = 776.2437464870187\n", - "Kc = 8.170341366672147e-24\n", - "vacantX+vacantX+O=CC=CO<=>HOX+O=CC=C[Pt]\n", - "kf = 4.672349699632388e-15\n", - "krev = 8.81363422062413e13\n", - "Kc = 5.301274800693419e-29\n", - "proton+O=CC=C[Pt]<=>O=CCC=[Pt]\n", - "kf = 1.2673656466904085e10\n", - "krev = 1.0824082827935274e8\n", - "Kc = 117.08757839689983\n", - "proton+C=CC(=O)O[Pt]<=>OX+C=CC=O\n", - "kf = 4.524546416801015\n", - "krev = 7.68227583414659e-9\n", - "Kc = 5.889591202505473e8\n", - "CO2+C=C[Pt]<=>C=CC(=O)O[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 450683.30306117237\n", - "Kc = 1.4517947189269602e-13\n", - "vacantX+vacantX+O=C=CO<=>OX+OC=C=[Pt]\n", - "kf = 7.548264554696059e-34\n", - "krev = 5.749061160710156e15\n", - "Kc = 1.3129560364189368e-49\n", - "proton+OC=C=[Pt]<=>OCC#[Pt]\n", - "kf = 0.00032547344886471076\n", - "krev = 1.1489507349403094e-46\n", - "Kc = 2.832788551909668e42\n", - "vacantX+vacantX+O=C=C=CO<=>OCX+OC=C=[Pt]\n", - "kf = 1.463392220587488e-22\n", - "krev = 7.968303762369095e13\n", - "Kc = 1.8365166090912173e-36\n", - "proton+CC[Pt]<=>CH2X+CH4\n", - "kf = 1.4846524062695914\n", - "krev = 9.859129077434927e-6\n", - "Kc = 150586.56749586415\n", - "HX+C=C<=>CC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 3.1627439012977165e-12\n", - "Kc = 25911.109388377805\n", - "vacantX+vacantX+CCO<=>HOX+CC[Pt]\n", - "kf = 2.1035625708276702e-15\n", - "krev = 1.0019023766861524e15\n", - "Kc = 2.099568400850909e-30\n", - "vacantX+vacantX+CCOC=O<=>CHO2X+CC[Pt]\n", - "kf = 0.08561452397466171\n", - "krev = 3.215769317238553e17\n", - "Kc = 2.6623341268826044e-19\n", - "vacantX+vacantX+CCOO<=>OO[Pt]+CC[Pt]\n", - "kf = 1.262172875849309e-6\n", - "krev = 1.5596341944506717e13\n", - "Kc = 8.092749443044025e-20\n", - "proton+CC=[Pt]<=>CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.602708332438123e-27\n", - "Kc = 2.9060615603731233e36\n", - "vacantX+vacantX+CC<=>HX+CC[Pt]\n", - "kf = 8.697106954471648e-14\n", - "krev = 5.359609736165605e16\n", - "Kc = 1.6227127314485718e-30\n", - "proton+C=C.[Pt]<=>CC[Pt]\n", - "kf = 5.504599623053448e9\n", - "krev = 0.3531497863658743\n", - "Kc = 1.558715263486103e10\n", - "vacantX+vacantX+CCC=O<=>CHOX+CC[Pt]\n", - "kf = 0.0004422945453165714\n", - "krev = 9.363325052982716e15\n", - "Kc = 4.723691026572629e-20\n", - "vacantX+vacantX+CC(O)C=O<=>CH3X+O=CC(O)[Pt]\n", - "kf = 9.477814531468979e-7\n", - "krev = 7.52142668687151e15\n", - "Kc = 1.2601086105129898e-22\n", - "proton+CCC#[Pt]<=>CX+CC\n", - "kf = 3.73018742862406e-11\n", - "krev = 0.075105066117345\n", - "Kc = 4.966625583946592e-10\n", - "C=O+CH3X<=>CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.1808191230067762e-17\n", - "Kc = 3.354171909251678e9\n", - "HX+CC=O<=>CCO[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 2.639709061724686e-6\n", - "Kc = 0.012387213631168494\n", - "vacantX+vacantX+CCO<=>HX+CCO[Pt]\n", - "kf = 5.372480262216755e-24\n", - "krev = 2113.809062877283\n", - "Kc = 2.5416109508508876e-27\n", - "vacantX+vacantX+CCOC=O<=>CHOX+CCO[Pt]\n", - "kf = 4.80530366959931e-5\n", - "krev = 5.681813674074216e13\n", - "Kc = 8.457341168235823e-19\n", - "vacantX+vacantX+CCOO<=>HOX+CCO[Pt]\n", - "kf = 3.028654941635431e8\n", - "krev = 1.2132864881112858e-12\n", - "Kc = 2.496240559268171e20\n", - "proton+CC=O.[Pt]<=>CCO[Pt]\n", - "kf = 19418.796323941955\n", - "krev = 3658.802750537776\n", - "Kc = 5.30741820424393\n", - "proton+CCO[Pt]<=>OX+CC\n", - "kf = 1.5180806810718186e7\n", - "krev = 3.4536717602694347e-12\n", - "Kc = 4.395555763392486e18\n", - "proton+CCOC(=O)[Pt]<=>OCX+CCO\n", - "kf = 1.100364657251968e9\n", - "krev = 4.5302115405928314e-10\n", - "Kc = 2.4289476272623954e18\n", - "vacantX+vacantX+CCOC=O<=>HX+CCOC(=O)[Pt]\n", - "kf = 2.5742212027881315e-15\n", - "krev = 0.39729482671494754\n", - "Kc = 6.479372570927264e-15\n", - "CO2+CC[Pt]<=>CCOC(=O)[Pt]\n", - "kf = 3.860701485876577e-7\n", - "krev = 0.0037771400241392917\n", - "Kc = 0.00010221229451921966\n", - "CH3X+C=C=O<=>CCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.9339597186194493e-34\n", - "Kc = 1.7308289628845924e26\n", - "HX+CC=C=O<=>CCC(=O)[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 2.728234417234893e-33\n", - "Kc = 1.0624138213938816e25\n", - "proton+CCC(=O)[Pt]<=>OCX+CC\n", - "kf = 3.3183098775357734e7\n", - "krev = 1.723115430616528e-10\n", - "Kc = 1.9257618024745373e17\n", - "proton+CC=C=O.[Pt]<=>CCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.816709270833084e-23\n", - "Kc = 3.667458740974689e32\n", - "vacantX+vacantX+CCC=O<=>HX+CCC(=O)[Pt]\n", - "kf = 1.3037608552158366e-12\n", - "krev = 0.18236199715464047\n", - "Kc = 7.149301255514685e-12\n", - "vacantX+vacantX+C=C(O)C=O<=>CH2X+O=CC(O)=[Pt]\n", - "kf = 3.506980389191063e-59\n", - "krev = 1.6121784785918364e12\n", - "Kc = 2.1753053001019147e-71\n", - "proton+CCOC#[Pt]<=>CX+CCO\n", - "kf = 1.6403573057503937e-22\n", - "krev = 1.0480859144262605e-13\n", - "Kc = 1.5650981309565184e-9\n", - "proton+CCC(=O)O[Pt]<=>OX+CCC=O\n", - "kf = 5.622114816602621e-8\n", - "krev = 4.785365563630673e-7\n", - "Kc = 0.11748558687619057\n", - "CO2+CC[Pt]<=>CCC(=O)O[Pt]\n", - "kf = 3.860701485876577e-7\n", - "krev = 2.2515045234693432e-8\n", - "Kc = 17.147207325738\n", - "vacantX+vacantX+OC=CCO<=>OC=[Pt]+OCC=[Pt]\n", - "kf = 3.6700973989487563e-44\n", - "krev = 3.0504263460080312e13\n", - "Kc = 1.203142440646588e-57\n", - "proton+CC(=C=O)O[Pt]<=>CC(O)=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 27.83415070046663\n", - "Kc = 8.981772165076653e8\n", - "vacantX+CC(O)=C=O<=>CC(O)=C=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 165389.73964983693\n", - "Kc = 1.9518801026953096\n", - "proton+OOC=[Pt]<=>OO+CHX\n", - "kf = 2.8719882764673755e7\n", - "krev = 8.077545633440945e-25\n", - "Kc = 3.555520955000709e31\n", - "proton+OOC=[Pt]<=>OOC[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.62255074484058e-37\n", - "Kc = 2.899374064566577e46\n", - "proton+OOC#[Pt]<=>OOC=[Pt]\n", - "kf = 3.432151727081939e-44\n", - "krev = 3342.777740155216\n", - "Kc = 1.0267364431242663e-47\n", - "vacantX+vacantX+C=CCO<=>CH2X+OCC=[Pt]\n", - "kf = 3.3256293066300124e-48\n", - "krev = 2.638642223210571e15\n", - "Kc = 1.2603562837645906e-63\n", - "vacantX+vacantX+C=CCO<=>OC[Pt]+C=C[Pt]\n", - "kf = 1.4930923415267688e-9\n", - "krev = 1.1121057711212152e14\n", - "Kc = 1.3425812366942817e-23\n", - "vacantX+OO<=>OO.[Pt]\n", - "kf = 469882.2241291155\n", - "krev = 15.560302693769444\n", - "Kc = 30197.498941795184\n", - "proton+OO[Pt]<=>OO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.110596489625074e-24\n", - "Kc = 2.251042591395165e34\n", - "C=O+CO[Pt]<=>COCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 9.545218685674386e-14\n", - "Kc = 414937.62088874576\n", - "HX+COC=O<=>COCO[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 0.02522938529859348\n", - "Kc = 1.1100614687459063e-6\n", - "vacantX+vacantX+COCO<=>HX+COCO[Pt]\n", - "kf = 1.0488506310161173e-19\n", - "krev = 521.1543106644776\n", - "Kc = 2.0125529225284944e-22\n", - "proton+COC=O.[Pt]<=>COCO[Pt]\n", - "kf = 0.6792883990466445\n", - "krev = 3726.123137157573\n", - "Kc = 0.00018230433457033608\n", - "proton+COCO[Pt]<=>OX+COC\n", - "kf = 5093.375621150868\n", - "krev = 5.977614318003391e-7\n", - "Kc = 8.520749834613165e9\n", - "CO[Pt]+C=C=O<=>COCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.680149232421768e-23\n", - "Kc = 1.9922953446306685e15\n", - "HX+COC=C=O<=>COCC(=O)[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 2.661991446097411e-38\n", - "Kc = 9.604054388173769e29\n", - "proton+COCC(=O)[Pt]<=>OCX+COC\n", - "kf = 8.734746675052269e7\n", - "krev = 2.1771371890779743e-8\n", - "Kc = 4.012033196103488e15\n", - "vacantX+vacantX+COCC=O<=>HX+COCC(=O)[Pt]\n", - "kf = 2.290241001822749e-10\n", - "krev = 0.0004872161822843353\n", - "Kc = 4.7006669423105973e-7\n", - "proton+COCOC#[Pt]<=>CX+COCO\n", - "kf = 3.2770328923262016e-17\n", - "krev = 2.1864147814239428e-13\n", - "Kc = 0.0001498815741719407\n", - "proton+COCC#[Pt]<=>CX+COC\n", - "kf = 1.433200340176918\n", - "krev = 0.00041586763423335837\n", - "Kc = 3446.289689792732\n", - "proton+COC[Pt]<=>CH2X+CO-2\n", - "kf = 0.2769010105768301\n", - "krev = 3.0099119392563808e-6\n", - "Kc = 91996.38267332179\n", - "vacantX+vacantX+COCO<=>HOX+COC[Pt]\n", - "kf = 8.90444501639475e-13\n", - "krev = 8.409201083164982e12\n", - "Kc = 1.0588931015362724e-25\n", - "C=O+CH3X<=>COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 8.422687202008296e-11\n", - "Kc = 470.23832623775377\n", - "vacantX+vacantX+COC<=>HX+COC[Pt]\n", - "kf = 2.786306429788959e-20\n", - "krev = 52.25975865319748\n", - "Kc = 5.3316481009398625e-22\n", - "vacantX+vacantX+COCC=O<=>CHOX+COC[Pt]\n", - "kf = 1.4060776479118306e6\n", - "krev = 6.613786245273692e13\n", - "Kc = 2.1259798786461146e-8\n", - "vacantX+vacantX+C=C=CO<=>OC=[Pt]+C=C=[Pt]\n", - "kf = 1.5975335437882445e-34\n", - "krev = 2.2957840869759923e8\n", - "Kc = 6.958553083676594e-43\n", - "vacantX+vacantX+C=C=CO<=>CH2X+OC=C=[Pt]\n", - "kf = 9.363402027600756e-56\n", - "krev = 7.047835211144391e9\n", - "Kc = 1.328550079149818e-65\n", - "vacantX+vacantX+COC=O<=>OX+COC=[Pt]\n", - "kf = 1.1797200153280936e-59\n", - "krev = 4.3408253155831816e16\n", - "Kc = 2.7177320660497494e-76\n", - "proton+COC=[Pt]<=>CHX+CO-2\n", - "kf = 479145.9852086257\n", - "krev = 1.0449825701778588e-33\n", - "Kc = 4.5852055228736854e38\n", - "proton+COC#[Pt]<=>COC=[Pt]\n", - "kf = 90933.51053402986\n", - "krev = 2739.427130274527\n", - "Kc = 33.194352764155155\n", - "vacantX+vacantX+COC=C=O<=>OCX+COC=[Pt]\n", - "kf = 2.7777170398864307e-21\n", - "krev = 2.5089215324603047e13\n", - "Kc = 1.107135876490541e-34\n", - "proton+COC=[Pt]<=>COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3472876439887766e-48\n", - "Kc = 1.8555799952254487e58\n", - "vacantX+COC=C=O<=>COC=C=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 1179.0380002145982\n", - "Kc = 273.8002862958761\n", - "proton+COC=C=O.[Pt]<=>COCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.0577777781824875e-25\n", - "Kc = 2.3634453772469967e35\n", - "vacantX+vacantX+C=C=C<=>CH2X+C=C=[Pt]\n", - "kf = 4.78083312177258e-41\n", - "krev = 4.774618642094983e15\n", - "Kc = 1.0013015656628172e-56\n", - "proton+O=C=COC[Pt]<=>CH2X+O=C=CO\n", - "kf = 4.988523456059943e-5\n", - "krev = 0.0009299241102698363\n", - "Kc = 0.05364441464596958\n", - "C=O+O=C=C[Pt]<=>O=C=COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.852140732586457e13\n", - "Kc = 2.1384283940268284e-21\n", - "vacantX+vacantX+COC=C=O<=>HX+O=C=COC[Pt]\n", - "kf = 3.256466928453685e-21\n", - "krev = 26.50445975246776\n", - "Kc = 1.2286486722863626e-22\n", - "proton+O=C=COC[Pt]<=>COC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.6649798034152577e-22\n", - "Kc = 1.5015197150571575e32\n", - "CH3X+O=C=C=O<=>COC([Pt])=C=O\n", - "kf = 5.799304049644909e-8\n", - "krev = 3.1615249923835833e-35\n", - "Kc = 1.8343375629216876e27\n", - "proton+COC([Pt])=C=O<=>CO-2+O=C=C=[Pt]\n", - "kf = 313658.31445379555\n", - "krev = 1.256306436150439e-34\n", - "Kc = 2.496670441448219e39\n", - "vacantX+vacantX+COC=C=O<=>HX+COC([Pt])=C=O\n", - "kf = 2.779636780044878e-20\n", - "krev = 3.601218910546807\n", - "Kc = 7.718599866018197e-21\n", - "proton+COC([Pt])=C=O<=>COC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0459713323621888e-20\n", - "Kc = 2.390122867281724e30\n", - "vacantX+vacantX+C=C=C(O)O<=>OC(O)=[Pt]+C=C=[Pt]\n", - "kf = 2.937512138355157e-45\n", - "krev = 8.778136400287878e10\n", - "Kc = 3.34639609639561e-56\n", - "proton+O=C=COC=[Pt]<=>CHX+O=C=CO\n", - "kf = 2.102599834403735e7\n", - "krev = 1.6989476123058672e-25\n", - "Kc = 1.237589563782969e32\n", - "proton+O=C=COC#[Pt]<=>O=C=COC=[Pt]\n", - "kf = 1080.8801129554665\n", - "krev = 2888.2699525834805\n", - "Kc = 0.37423098626520285\n", - "proton+O=C=COC=[Pt]<=>O=C=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.9106920181466426e-48\n", - "Kc = 8.589022763019266e57\n", - "proton+CCOO[Pt]<=>OX+CCO\n", - "kf = 169.16425212622386\n", - "krev = 5.6416707126946964e-58\n", - "Kc = 2.9984779463568512e59\n", - "vacantX+vacantX+CCOO<=>HX+CCOO[Pt]\n", - "kf = 1.893449523720139e-21\n", - "krev = 0.6694879211592951\n", - "Kc = 2.8282056537202555e-21\n", - "O=O+CC[Pt]<=>CCOO[Pt]\n", - "kf = 4.5276782379965965e-7\n", - "krev = 1.4949208469184493e-38\n", - "Kc = 3.0287076719344122e31\n", - "vacantX+vacantX+C=CC(=O)O<=>CH2X+O=C(O)C=[Pt]\n", - "kf = 4.72289540105198e-39\n", - "krev = 9.498795808374404e14\n", - "Kc = 4.9720990916429044e-54\n", - "vacantX+vacantX+C=CC(=O)O<=>CO2HX+C=C[Pt]\n", - "kf = 5.354197885861111e7\n", - "krev = 1.376967106369583e14\n", - "Kc = 3.888399266107105e-7\n", - "vacantX+vacantX+C=CC(=O)O<=>HOX+C=CC(=O)[Pt]\n", - "kf = 0.03947248649742643\n", - "krev = 2.5171232142616846e11\n", - "Kc = 1.5681586929785789e-13\n", - "vacantX+vacantX+C=CC(=O)O<=>HX+C=CC(=O)O[Pt]\n", - "kf = 2.4490000178339845e-20\n", - "krev = 458.0011375503109\n", - "Kc = 5.3471483300955e-23\n", - "proton+O=C=C=CO.[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.4322611471299928e-17\n", - "Kc = 1.7454917387164855e27\n", - "proton+O=C=C=CO.[Pt]<=>O=C=C([Pt])CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 7.140416160377535e-6\n", - "Kc = 3.5011964903006675e15\n", - "vacantX+O=C=C=CO<=>O=C=C=CO.[Pt]\n", - "kf = 327433.4917974331\n", - "krev = 0.4460204906723957\n", - "Kc = 734122.0832787583\n", - "HX+O=C=C=C=O<=>O=C=C=C(O)[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 1.3048903398306852e-5\n", - "Kc = 0.004032923533638046\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C=C(O)[Pt]\n", - "kf = 4235.342411204313\n", - "krev = 12.909334546967292\n", - "Kc = 328.0837130523738\n", - "proton+O=C=C=C(O)[Pt]<=>O=C=CC(O)=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1053.6449933824201\n", - "Kc = 2.3727156828928486e7\n", - "vacantX+vacantX+O=C=C=CO<=>HX+O=C=C=C(O)[Pt]\n", - "kf = 8.233814429551885e-18\n", - "krev = 0.5740049812746953\n", - "Kc = 1.434449995759099e-17\n", - "proton+O=C=C=C(O)[Pt]<=>O=C=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.249904355928212e-21\n", - "Kc = 3.4483213533096645e30\n", - "vacantX+vacantX+CC=CO<=>OC=[Pt]+CC=[Pt]\n", - "kf = 1.6816353348966163e-33\n", - "krev = 8.021148128032321e14\n", - "Kc = 2.0965020319468163e-48\n", - "proton+O=C=C=C[Pt]<=>O=C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.0269882986128818\n", - "Kc = 9.263273820479827e11\n", - "vacantX+vacantX+C=C=C=O<=>HX+O=C=C=C[Pt]\n", - "kf = 3.6772489817592154e-10\n", - "krev = 0.00723599763490509\n", - "Kc = 5.081882509221477e-8\n", - "vacantX+vacantX+O=C=C=CO<=>HOX+O=C=C=C[Pt]\n", - "kf = 0.00020826365169953766\n", - "krev = 1.0739954827079557e13\n", - "Kc = 1.939148302322696e-17\n", - "vacantX+OC=CO<=>OC=CO.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.48171019889246675\n", - "Kc = 734122.0861712244\n", - "vacantX+vacantX+C=CC<=>CH2X+CC=[Pt]\n", - "kf = 3.8695500910369183e-44\n", - "krev = 2.1644248520711738e17\n", - "Kc = 1.787795999169979e-61\n", - "vacantX+vacantX+C=CC<=>CH3X+C=C[Pt]\n", - "kf = 1.1726078415532691e-17\n", - "krev = 1.59532697721828e15\n", - "Kc = 7.350266486422159e-33\n", - "HX+O=C=CO<=>OC=C(O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 2.762063581333058e-24\n", - "Kc = 1.0314187634521844e16\n", - "vacantX+vacantX+OC=CO<=>HX+OC=C(O)[Pt]\n", - "kf = 6.089904416870865e-20\n", - "krev = 3.928023437111271\n", - "Kc = 1.550373747604081e-20\n", - "proton+O=C=CO.[Pt]<=>OC=C(O)[Pt]\n", - "kf = 6.4368819183992445e7\n", - "krev = 6.799608634080986e-11\n", - "Kc = 9.466547657075904e17\n", - "proton+OC=C(O)[Pt]<=>H2O+OC=C=[Pt]\n", - "kf = 5.262467142275111e-7\n", - "krev = 0.6251329939834178\n", - "Kc = 8.418156125054411e-7\n", - "proton+OC=C(O)[Pt]<=>OC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.835798651062412e-24\n", - "Kc = 3.190485247679302e33\n", - "vacantX+vacantX+OC=CO<=>HOX+OC=C[Pt]\n", - "kf = 1.882970379851619e-8\n", - "krev = 6.2613640604613945e13\n", - "Kc = 3.0072846134950095e-22\n", - "vacantX+vacantX+C=CO<=>HX+OC=C[Pt]\n", - "kf = 5.986889507133711e-22\n", - "krev = 1492.047811549125\n", - "Kc = 4.0125319448830507e-25\n", - "proton+OC=C[Pt]<=>OCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.693803965028289e7\n", - "Kc = 1475.967733939179\n", - "vacantX+vacantX+O=CC=CO<=>CHOX+OC=C[Pt]\n", - "kf = 3.6404040231768274e-5\n", - "krev = 5.1339082800935775e14\n", - "Kc = 7.090901949480236e-20\n", - "proton+OC=C=[Pt]<=>OC=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.9001266800545872e-45\n", - "Kc = 1.3157017509633512e55\n", - "vacantX+vacantX+OC=CCO<=>OC[Pt]+OC=C[Pt]\n", - "kf = 1.39754480380523e-13\n", - "krev = 4.435737343310229e14\n", - "Kc = 3.1506482364492156e-28\n", - "vacantX+vacantX+CC=CO<=>CH3X+OC=C[Pt]\n", - "kf = 3.0518560755450534e-15\n", - "krev = 1.440283576497463e15\n", - "Kc = 2.1189272205454667e-30\n", - "vacantX+vacantX+CC=C(O)O<=>OC(O)=[Pt]+CC=[Pt]\n", - "kf = 3.314404876424973e-50\n", - "krev = 3.298291971460818e17\n", - "Kc = 1.0048852269912959e-67\n", - "HX+O=C=CO<=>OC=CO[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 5.830973747204281e-42\n", - "Kc = 4.885709192226705e33\n", - "vacantX+vacantX+OC=CO<=>HX+OC=CO[Pt]\n", - "kf = 6.3392542923960805e-6\n", - "krev = 0.0008631955285686626\n", - "Kc = 0.007343937824733329\n", - "proton+O=C=CO.[Pt]<=>OC=CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.575140256117379e-26\n", - "Kc = 4.4841921192150256e35\n", - "proton+OC=CO[Pt]<=>OX+C=CO\n", - "kf = 2.262727495050209e-8\n", - "krev = 2.5678564004292932e-5\n", - "Kc = 0.0008811736881672694\n", - "proton+OC=CO[Pt]<=>OC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.711725523568878e-6\n", - "Kc = 6.73541182968781e15\n", - "proton+OC=COC#[Pt]<=>CX+OC=CO\n", - "kf = 2.2492341197526439e-29\n", - "krev = 0.00020529518482061674\n", - "Kc = 1.0956097785332785e-25\n", - "vacantX+vacantX+CCC(=O)O<=>CH3X+O=C(O)C[Pt]\n", - "kf = 8.997747599742267e-17\n", - "krev = 6.572577910715489e15\n", - "Kc = 1.368983026442782e-32\n", - "vacantX+vacantX+CCC(=O)O<=>CO2HX+CC[Pt]\n", - "kf = 3.388822996448631e-6\n", - "krev = 1.0293603282987281e15\n", - "Kc = 3.292163981148853e-21\n", - "vacantX+vacantX+CCC(=O)O<=>HOX+CCC(=O)[Pt]\n", - "kf = 2.1491486919570496e-14\n", - "krev = 4.131728096070369e12\n", - "Kc = 5.201573390081201e-27\n", - "vacantX+vacantX+CCC(=O)O<=>HX+CCC(=O)O[Pt]\n", - "kf = 2.415446383235281e-20\n", - "krev = 451.7273406124814\n", - "Kc = 5.347133472063615e-23\n", - "proton+O=C([Pt])C=CO<=>OCX+C=CO\n", - "kf = 224.18396606543615\n", - "krev = 8.215700647740584e-7\n", - "Kc = 2.728726078001508e8\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=C([Pt])C=CO\n", - "kf = 2.859565189776071e-11\n", - "krev = 0.000933578065584948\n", - "Kc = 3.06301668300697e-8\n", - "HX+O=C=C=CO<=>O=C([Pt])C=CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.1750295723598082e-43\n", - "Kc = 2.206855353748942e35\n", - "proton+O=C=C=CO.[Pt]<=>O=C([Pt])C=CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.234268290529092e-27\n", - "Kc = 2.0254915557527025e37\n", - "proton+OC=C(O)C#[Pt]<=>CX+OC=CO\n", - "kf = 2.8680661830740045e-24\n", - "krev = 729.307267106125\n", - "Kc = 3.932589612680575e-27\n", - "vacantX+vacantX+C=COO<=>OO[Pt]+C=C[Pt]\n", - "kf = 0.00256837059370255\n", - "krev = 1.2695573429161084e13\n", - "Kc = 2.0230441799526235e-16\n", - "vacantX+vacantX+C=COO<=>HOX+C=CO[Pt]\n", - "kf = 3.07907263663438e8\n", - "krev = 5.547742278067932e-15\n", - "Kc = 5.5501364019864025e22\n", - "vacantX+vacantX+C=COO<=>CH2X+OOC=[Pt]\n", - "kf = 7.483948884590266e-53\n", - "krev = 2.8103204909201245e17\n", - "Kc = 2.6630232775123643e-70\n", - "proton+OC=CC#[Pt]<=>CX+C=CO\n", - "kf = 1.0593841984272302e-19\n", - "krev = 13.369077699035607\n", - "Kc = 7.924138241066921e-21\n", - "proton+OCC[Pt]<=>CH2X+CO-2\n", - "kf = 3.9799160772985795e-6\n", - "krev = 0.00035437522440524626\n", - "Kc = 0.011230796633647675\n", - "vacantX+vacantX+OCCO<=>HOX+OCC[Pt]\n", - "kf = 2.110093084979835e-12\n", - "krev = 2.4085316622580622e14\n", - "Kc = 8.760910716040024e-27\n", - "HX+C=CO<=>OCC[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 1.1429411507382647e-15\n", - "Kc = 2.8609207088741057e7\n", - "HOX+C=C<=>OCC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 2.2750559854988554e-15\n", - "Kc = 3.602118089238167e7\n", - "proton+OCC=[Pt]<=>OCC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.1399343496076094e-34\n", - "Kc = 2.1931087530264836e44\n", - "vacantX+vacantX+CCO<=>HX+OCC[Pt]\n", - "kf = 4.51610258482867e-23\n", - "krev = 15472.547765874588\n", - "Kc = 2.918784063985339e-27\n", - "vacantX+vacantX+O=CCCO<=>CHOX+OCC[Pt]\n", - "kf = 2.0496526220764064\n", - "krev = 1.4633869198921762e15\n", - "Kc = 1.4006224835106677e-15\n", - "HX+C#C<=>C=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 2.375601900047824e-24\n", - "Kc = 3.580716650609497e16\n", - "CHOX+C#C<=>O=CC=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 3.2359557228060194e-16\n", - "Kc = 2.6287001452988416e8\n", - "HOX+C#C<=>OC=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 2.419253665005007e-25\n", - "Kc = 3.516108046777805e17\n", - "proton+OCCC#[Pt]<=>CX+CCO\n", - "kf = 0.036583470766554806\n", - "krev = 0.0005754138836916786\n", - "Kc = 63.577664361948486\n", - "OC[Pt]+C=C=O<=>O=C([Pt])CCO\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.869121889511259e-30\n", - "Kc = 1.7908695590280368e22\n", - "HX+O=C=CCO<=>O=C([Pt])CCO\n", - "kf = 2.5565910629172877e-8\n", - "krev = 3.7973012083800085e-37\n", - "Kc = 6.732652804247709e28\n", - "proton+O=C=CCO.[Pt]<=>O=C([Pt])CCO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.5089082544191712e-24\n", - "Kc = 1.6568270421201532e34\n", - "proton+O=C([Pt])CCO<=>OCX+CCO\n", - "kf = 9.600816617542319e7\n", - "krev = 3.185535798116408e-7\n", - "Kc = 3.0138781121904944e14\n", - "vacantX+vacantX+O=CCCO<=>HX+O=C([Pt])CCO\n", - "kf = 4.786286134347495e-11\n", - "krev = 0.0006355926831038164\n", - "Kc = 7.530429883135883e-8\n", - "vacantX+vacantX+C=COC<=>CO[Pt]+C=C[Pt]\n", - "kf = 1.9108708710628152e-14\n", - "krev = 5.750545812867103e12\n", - "Kc = 3.322938262290088e-27\n", - "vacantX+vacantX+C=COC<=>CH3X+C=CO[Pt]\n", - "kf = 8.809048609670953e-10\n", - "krev = 5.30334818480063e15\n", - "Kc = 1.6610353125441853e-25\n", - "vacantX+vacantX+C=COC<=>CH2X+COC=[Pt]\n", - "kf = 2.00333233616492e-67\n", - "krev = 2.0086736136424638e14\n", - "Kc = 9.973408932933319e-82\n", - "C=O+OC[Pt]<=>OCCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.726586049973397e-6\n", - "Kc = 0.00837955829095468\n", - "HX+O=CCO<=>OCCO[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 7.096612291679358e-6\n", - "Kc = 0.003946413774492056\n", - "vacantX+vacantX+OCCO<=>HX+OCCO[Pt]\n", - "kf = 1.0265256602604584e-26\n", - "krev = 112849.3186381155\n", - "Kc = 9.09642763154215e-32\n", - "proton+O=CCO.[Pt]<=>OCCO[Pt]\n", - "kf = 3.478307222117794e6\n", - "krev = 3581.5775849412535\n", - "Kc = 971.1662360023528\n", - "proton+OCCO[Pt]<=>OX+CCO\n", - "kf = 951266.6788585404\n", - "krev = 3.3388075163598663e-18\n", - "Kc = 2.8491210535420697e23\n", - "proton+OCCOC#[Pt]<=>CX+OCCO\n", - "kf = 6.336022152476698e-22\n", - "krev = 5.125095889500872e-13\n", - "Kc = 1.2362738744959868e-9\n", - "vacantX+vacantX+C=CC(O)O<=>OC(O)[Pt]+C=C[Pt]\n", - "kf = 1.3588265576828814e-16\n", - "krev = 6.093754170226661e16\n", - "Kc = 2.2298676968656565e-33\n", - "proton+O=C=C=C=[Pt]<=>O=C=CC#[Pt]\n", - "kf = 8.597534639917141e-9\n", - "krev = 2.1202950562509243e-60\n", - "Kc = 4.0548765204023916e51\n", - "vacantX+vacantX+O=C=C=C=O<=>OX+O=C=C=C=[Pt]\n", - "kf = 6.451439297868635e-57\n", - "krev = 8.482832416110645e14\n", - "Kc = 7.60528910793525e-72\n", - "proton+O=C=C=C(O)[Pt]<=>H2O+O=C=C=C=[Pt]\n", - "kf = 1.6149902683641734e-11\n", - "krev = 0.12950076972214764\n", - "Kc = 1.2470893198775887e-10\n", - "proton+O=C=C=C=[Pt]<=>O=C=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.039016761990757e-51\n", - "Kc = 6.189625216528679e60\n", - "vacantX+C=CO<=>C=CO.[Pt]\n", - "kf = 412885.969273148\n", - "krev = 1.1342794009872417\n", - "Kc = 364007.288604364\n", - "proton+C=CO[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.484544240591893e-27\n", - "Kc = 5.574702502366298e36\n", - "proton+OC=C[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.090002516938126e-28\n", - "Kc = 6.112465676112982e37\n", - "proton+C=CO.[Pt]<=>OCC[Pt]\n", - "kf = 1.7684909297990441e9\n", - "krev = 0.3339506079512917\n", - "Kc = 5.295666148501179e9\n", - "vacantX+vacantX+C=COCO<=>OCO[Pt]+C=C[Pt]\n", - "kf = 1.4197397308458187e-12\n", - "krev = 3.0290185667479297e13\n", - "Kc = 4.6871278586123213e-26\n", - "vacantX+vacantX+C=COCO<=>OC[Pt]+C=CO[Pt]\n", - "kf = 1.0263854075463885e-7\n", - "krev = 1.9545487277553856e14\n", - "Kc = 5.251265384031101e-22\n", - "HX+C=C=O<=>C=C(O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 3.2362559658776053e-12\n", - "Kc = 10343.290300064218\n", - "proton+C=C=O.[Pt]<=>C=C(O)[Pt]\n", - "kf = 0.5863133386822127\n", - "krev = 3624.832599039063\n", - "Kc = 0.00016174908017480404\n", - "vacantX+vacantX+C=CO<=>HX+C=C(O)[Pt]\n", - "kf = 4.00965787691315e-19\n", - "krev = 4.055766485027893\n", - "Kc = 9.886313454472895e-20\n", - "vacantX+vacantX+C=C(O)O<=>HOX+C=C(O)[Pt]\n", - "kf = 3.9452234947489745e-7\n", - "krev = 1.361002505571871e12\n", - "Kc = 2.8987628447394044e-19\n", - "proton+C=C(O)[Pt]<=>H2O+C=C=[Pt]\n", - "kf = 0.1408093188614318\n", - "krev = 0.006096548509334685\n", - "Kc = 23.09656334987455\n", - "proton+C=C(O)[Pt]<=>CC(O)=[Pt]\n", - "kf = 1.124057689749841e8\n", - "krev = 4.718570974473911e-12\n", - "Kc = 2.382199390092179e19\n", - "vacantX+vacantX+C=C(O)C=O<=>CHOX+C=C(O)[Pt]\n", - "kf = 2.8052009086647103\n", - "krev = 2.294429327232502e13\n", - "Kc = 1.2226137782366527e-13\n", - "proton+C=C(O)[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0077190030498644e-22\n", - "Kc = 2.4808503088993487e32\n", - "HOX+C=C=O<=>C=C(O)O[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.6625343699967689e-31\n", - "Kc = 2.0134040862236038e23\n", - "proton+C=C(O)O[Pt]<=>OX+C=CO\n", - "kf = 7.621772041144703e-10\n", - "krev = 0.16987445654378072\n", - "Kc = 4.4867087119601115e-9\n", - "vacantX+vacantX+C=C(O)O<=>HX+C=C(O)O[Pt]\n", - "kf = 8.7276566297004e-6\n", - "krev = 1.546723677424112e-6\n", - "Kc = 5.6426734503963205\n", - "vacantX+vacantX+C=CCOO<=>OOC[Pt]+C=C[Pt]\n", - "kf = 2.5331825038162864e-12\n", - "krev = 1.769892843246248e17\n", - "Kc = 1.4312632052740838e-29\n", - "proton+C=C(O)OC#[Pt]<=>CX+C=C(O)O\n", - "kf = 1.0744261387122509e-22\n", - "krev = 181.85749301564874\n", - "Kc = 5.908066370516815e-25\n", - "proton+C=C(O)C#[Pt]<=>CX+C=CO\n", - "kf = 3.691417083839596e-20\n", - "krev = 61.67110810051338\n", - "Kc = 5.985650651555046e-22\n", - "vacantX+vacantX+C=COOC<=>COO[Pt]+C=C[Pt]\n", - "kf = 0.0009962735751002543\n", - "krev = 4.495422962203487e13\n", - "Kc = 2.21619541359445e-17\n", - "vacantX+vacantX+C=COOC<=>CO[Pt]+C=CO[Pt]\n", - "kf = 2.772273774659678e8\n", - "krev = 3.7705323383409334e-17\n", - "Kc = 7.352473141443741e24\n", - "proton+C=C(O)C(=O)[Pt]<=>OCX+C=CO\n", - "kf = 985.1540455146012\n", - "krev = 5.159085449148215e-7\n", - "Kc = 1.9095517126533618e9\n", - "HOX+C=C=C=O<=>C=C(O)C(=O)[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 3.5720015577500406e-52\n", - "Kc = 8.264488540948707e43\n", - "vacantX+vacantX+C=C(O)C=O<=>HX+C=C(O)C(=O)[Pt]\n", - "kf = 2.8595651897765786e-11\n", - "krev = 0.000933577098423846\n", - "Kc = 3.063019856211522e-8\n", - "proton+C=COO[Pt]<=>OX+C=CO\n", - "kf = 43.93537738533433\n", - "krev = 6.669135249611683e-61\n", - "Kc = 6.587867203306832e61\n", - "O=O+C=C[Pt]<=>C=COO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 1.0833501613715598e-32\n", - "Kc = 7.082998693235901e24\n", - "vacantX+vacantX+C=COO<=>HX+C=COO[Pt]\n", - "kf = 4.552726448583842e-23\n", - "krev = 27.53540659037694\n", - "Kc = 1.6534081069915729e-24\n", - "vacantX+vacantX+C=COOC<=>CH3X+C=COO[Pt]\n", - "kf = 2.287071149777874e-9\n", - "krev = 2.2490557638427473e13\n", - "Kc = 1.0169028205286352e-22\n", - "vacantX+vacantX+CC(O)=CO<=>OC=[Pt]+CC(O)=[Pt]\n", - "kf = 7.128045206079291e-31\n", - "krev = 1.6024698052635947e11\n", - "Kc = 4.4481619451835966e-42\n", - "vacantX+vacantX+CC(O)=CO<=>CH3X+OC=C(O)[Pt]\n", - "kf = 1.2021042471738558e-26\n", - "krev = 3.79937896614338e12\n", - "Kc = 3.163949313521812e-39\n", - "proton+O=CC=C=[Pt]<=>O=CCC#[Pt]\n", - "kf = 62.9877146015209\n", - "krev = 8.316144406521062e-31\n", - "Kc = 7.574148730766316e31\n", - "vacantX+vacantX+O=C=CC=O<=>OX+O=CC=C=[Pt]\n", - "kf = 1.1758489216219413e-43\n", - "krev = 2.1453863988577092e16\n", - "Kc = 5.480825842132732e-60\n", - "proton+O=CC=C=[Pt]<=>O=CC=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.331702565774384e-47\n", - "Kc = 2.6790395240083815e56\n", - "proton+C=C=C=O.[Pt]<=>O=C=CC[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.2229421483387703e-16\n", - "Kc = 1.1246356554390213e26\n", - "vacantX+C=C=C=O<=>C=C=C=O.[Pt]\n", - "kf = 372758.92921022984\n", - "krev = 0.5077615475124772\n", - "Kc = 734122.012658058\n", - "proton+C=C=C=O.[Pt]<=>CC([Pt])=C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.123273247571115e-16\n", - "Kc = 1.1774273531962195e26\n", - "proton+C=C=C=O.[Pt]<=>C=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.171161147913428e-32\n", - "Kc = 4.834504144216726e41\n", - "proton+O=C=C=C[Pt]<=>C=C=C=O.[Pt]\n", - "kf = 3.820491632517615e9\n", - "krev = 3.925100397444825e-12\n", - "Kc = 9.733487670798667e20\n", - "vacantX+vacantX+C=C(C)O<=>CH2X+CC(O)=[Pt]\n", - "kf = 1.2526307828427685e-31\n", - "krev = 1.8291181793687947e14\n", - "Kc = 6.848276929132241e-46\n", - "vacantX+vacantX+C=C(C)O<=>CH3X+C=C(O)[Pt]\n", - "kf = 6.412809230790006e-14\n", - "krev = 6.896161957802356e13\n", - "Kc = 9.299098933624258e-28\n", - "HX+O=C=C=C=O<=>O=C=C=CO[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 6.474039280394542e-15\n", - "Kc = 8.128654665807662e6\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C=CO[Pt]\n", - "kf = 2.4048564698523636e10\n", - "krev = 0.03636685994081414\n", - "Kc = 6.612769080877996e11\n", - "proton+O=C=C=CO[Pt]<=>OX+C=C=C=O\n", - "kf = 7.675790818902377e-14\n", - "krev = 0.0006735755949001122\n", - "Kc = 1.1395589265731426e-10\n", - "vacantX+vacantX+O=C=C=CO<=>HX+O=C=C=CO[Pt]\n", - "kf = 4.194899212644372e-10\n", - "krev = 0.014508998351933198\n", - "Kc = 2.891239705796395e-8\n", - "proton+O=C=C=CO[Pt]<=>O=C=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4612716650323904e-11\n", - "Kc = 1.71083862078759e21\n", - "proton+CC(O)[Pt]<=>OC=[Pt]+CH4\n", - "kf = 59.397807135376084\n", - "krev = 1.2803453253139382e-6\n", - "Kc = 4.639202093451769e7\n", - "HX+C=CO<=>CC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 1.2254518112062234e-21\n", - "Kc = 2.668292606261641e13\n", - "HX+CC=O<=>CC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 2.4645381117653586e-12\n", - "Kc = 13267.654460532101\n", - "vacantX+vacantX+CCO<=>HX+CC(O)[Pt]\n", - "kf = 1.7361137032745595e-19\n", - "krev = 63.774720976875884\n", - "Kc = 2.72225997492652e-21\n", - "vacantX+vacantX+CC(O)O<=>HOX+CC(O)[Pt]\n", - "kf = 7.380915652046712e-14\n", - "krev = 2.775462823415347e13\n", - "Kc = 2.6593458899096773e-27\n", - "proton+CC=O.[Pt]<=>CC(O)[Pt]\n", - "kf = 36132.65188770086\n", - "krev = 0.006356177292382113\n", - "Kc = 5.68465135971048e6\n", - "proton+CC(O)[Pt]<=>H2O+CC=[Pt]\n", - "kf = 2964.0563969386994\n", - "krev = 0.019559355499681682\n", - "Kc = 151541.61889367664\n", - "proton+CC(O)=[Pt]<=>CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.860369956892034e-19\n", - "Kc = 5.143641373338227e28\n", - "vacantX+vacantX+CC(O)C=O<=>CHOX+CC(O)[Pt]\n", - "kf = 753631.9525109725\n", - "krev = 9.011518944421836e14\n", - "Kc = 8.362984721654206e-10\n", - "proton+C=CO.[Pt]<=>CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.061646123775542e-6\n", - "Kc = 4.939104668453628e15\n", - "HX+C#CC=O<=>O=CC=C[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 1.9866745274914506e-30\n", - "Kc = 1.4859387148609413e22\n", - "proton+CC(O)C#[Pt]<=>CX+CCO\n", - "kf = 1.3617819786307934\n", - "krev = 4.084110860281074e-5\n", - "Kc = 33343.413663777814\n", - "O=CO+CH3X<=>CC(O)O[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 7.324156308451427e-7\n", - "Kc = 0.043678018970166745\n", - "HOX+CC=O<=>CC(O)O[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 7.587328136505701e-13\n", - "Kc = 43096.38318446866\n", - "HX+CC(=O)O<=>CC(O)O[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 4598.938099177113\n", - "Kc = 6.089703295881323e-12\n", - "proton+CC(O)O[Pt]<=>OX+CCO\n", - "kf = 1.6583777607664147e6\n", - "krev = 1.6983423991371652e-6\n", - "Kc = 9.764684445309413e11\n", - "vacantX+vacantX+CC(O)O<=>HX+CC(O)O[Pt]\n", - "kf = 4.052122584605618e-24\n", - "krev = 469.09529347560436\n", - "Kc = 8.638165082797514e-27\n", - "proton+CC(=O)O.[Pt]<=>CC(O)O[Pt]\n", - "kf = 0.7475019896975738\n", - "krev = 3555.8603422114556\n", - "Kc = 0.00021021691454639312\n", - "vacantX+vacantX+OC=C=CO<=>OC=[Pt]+OC=C=[Pt]\n", - "kf = 3.0449395213240036e-51\n", - "krev = 1.4315520101841116e12\n", - "Kc = 2.1270198355785863e-63\n", - "CH3X+O=C=CO<=>CC(O)C(=O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 4.477216581188038e-53\n", - "Kc = 6.362980552705156e44\n", - "proton+CC(O)C(=O)[Pt]<=>OCX+CCO\n", - "kf = 9.570476890072168e7\n", - "krev = 4.96015815008412e-7\n", - "Kc = 1.929470109720163e14\n", - "HOX+CC=C=O<=>CC(O)C(=O)[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 3.536759710167166e-36\n", - "Kc = 8.195394062368554e27\n", - "HX+CC(O)=C=O<=>CC(O)C(=O)[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 4.830700359768998e-42\n", - "Kc = 5.292381792522405e33\n", - "vacantX+vacantX+CC(O)C=O<=>HX+CC(O)C(=O)[Pt]\n", - "kf = 4.786286134353719e-11\n", - "krev = 0.0006355923790078162\n", - "Kc = 7.530433486042254e-8\n", - "proton+CC(O)=C=O.[Pt]<=>CC(O)C(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.368412782384192e-31\n", - "Kc = 1.8269341182594315e41\n", - "proton+CC(O)OC#[Pt]<=>CX+CC(O)O\n", - "kf = 2.7873525673015004e-16\n", - "krev = 1.8374709107747412e-8\n", - "Kc = 1.516950581887719e-8\n", - "vacantX+vacantX+CCOC<=>CO[Pt]+CC[Pt]\n", - "kf = 2.3627317133785774e-11\n", - "krev = 3.856091265609508e13\n", - "Kc = 6.127271246016828e-25\n", - "vacantX+vacantX+CCOC<=>CH3X+CCO[Pt]\n", - "kf = 6.326940367296449e-9\n", - "krev = 1.8372911814097844e13\n", - "Kc = 3.443624195943553e-22\n", - "vacantX+vacantX+CCOC<=>CH3X+COC[Pt]\n", - "kf = 1.3389399016858639e-14\n", - "krev = 2.773400746132106e14\n", - "Kc = 4.8277909478217395e-29\n", - "proton+O=C=C(O)C[Pt]<=>CH2X+O=C=CO\n", - "kf = 4.2042874371743854e-22\n", - "krev = 1.1101526849597185\n", - "Kc = 3.787125405481442e-22\n", - "HOX+C=C=C=O<=>O=C=C(O)C[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 6.322264310888409e-36\n", - "Kc = 4.669334354059592e27\n", - "vacantX+vacantX+CC(O)=C=O<=>HX+O=C=C(O)C[Pt]\n", - "kf = 6.004181315465852e-13\n", - "krev = 0.19478740167193392\n", - "Kc = 3.082427951669201e-12\n", - "proton+O=C=C(O)C[Pt]<=>CC(O)=C=O.[Pt]\n", - "kf = 1.859235052213257e9\n", - "krev = 4.357618832801525e-11\n", - "Kc = 4.266630753057283e19\n", - "proton+O=C=C(O)C=[Pt]<=>CHX+O=C=CO\n", - "kf = 1.807627844430322e-6\n", - "krev = 0.0010238577171457239\n", - "Kc = 0.0017655068806528764\n", - "proton+O=C=C(O)C#[Pt]<=>O=C=C(O)C=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.347883511420028\n", - "Kc = 7.467404380923659e9\n", - "proton+O=C=C(O)C=[Pt]<=>O=C=C(O)C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4404183806094484e-33\n", - "Kc = 1.735606844271341e43\n", - "vacantX+vacantX+CCCO<=>OC[Pt]+CC[Pt]\n", - "kf = 4.648157058598011e-13\n", - "krev = 1.3999921584371802e15\n", - "Kc = 3.3201307811515004e-28\n", - "vacantX+vacantX+CCCO<=>CH3X+OCC[Pt]\n", - "kf = 1.2211065235504926e-16\n", - "krev = 1.2627143633797795e15\n", - "Kc = 9.670488900451568e-32\n", - "proton+CC([Pt])OC=O<=>CH4+O=COC=[Pt]\n", - "kf = 1.0679856406424377e-15\n", - "krev = 0.2905260385078575\n", - "Kc = 3.6760410396521245e-15\n", - "CHOX+CC=O<=>CC([Pt])OC=O\n", - "kf = 3.269864007171502e-8\n", - "krev = 0.48922244404245907\n", - "Kc = 6.68379802887317e-8\n", - "HX+C=COC=O<=>CC([Pt])OC=O\n", - "kf = 2.5565910629172877e-8\n", - "krev = 1.2259112200812889e-16\n", - "Kc = 2.0854618352769157e8\n", - "vacantX+vacantX+CCOC=O<=>HX+CC([Pt])OC=O\n", - "kf = 6.519502059052115e-22\n", - "krev = 142.86665816232104\n", - "Kc = 4.563347489828482e-24\n", - "proton+CC([Pt])OC=O<=>O=CO+CC=[Pt]\n", - "kf = 8049.244255788158\n", - "krev = 0.00029431628636694825\n", - "Kc = 2.7348959703006394e7\n", - "proton+CC(=[Pt])OC=O<=>CH4+O=COC#[Pt]\n", - "kf = 4.771264023974434e9\n", - "krev = 10.578082715743388\n", - "Kc = 4.510518732164335e8\n", - "proton+CC(=[Pt])OC=O<=>O=CO+CC#[Pt]\n", - "kf = 7292.02651577905\n", - "krev = 8.53932827082491e-43\n", - "Kc = 8.539344412712957e45\n", - "proton+CC(=[Pt])OC=O<=>CC([Pt])OC=O\n", - "kf = 2.5e10\n", - "krev = 2.5945295399651927e-47\n", - "Kc = 9.635658262860014e56\n", - "vacantX+vacantX+CCC(O)O<=>OC(O)[Pt]+CC[Pt]\n", - "kf = 3.712816041087776e-19\n", - "krev = 9.367983662004229e16\n", - "Kc = 3.9633032838716965e-36\n", - "vacantX+O=CC=CO<=>O=CC=CO.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 0.8868529608572997\n", - "Kc = 364007.2889878057\n", - "proton+O=CC=CO[Pt]<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.467206835324098e-11\n", - "Kc = 1.703917907012588e21\n", - "proton+O=C([Pt])C=CO<=>O=CC=CO.[Pt]\n", - "kf = 3.672999120067293e9\n", - "krev = 4.587068754429701e-12\n", - "Kc = 8.00729031262133e20\n", - "HX+O=C=CC=O<=>O=CC=C(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.0473065138531246e-21\n", - "Kc = 2.475989854235963e13\n", - "proton+O=C=CC=O.[Pt]<=>O=CC=C(O)[Pt]\n", - "kf = 9.946079261837086e6\n", - "krev = 6.687641252513296e-9\n", - "Kc = 1.4872327755468685e15\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC=C(O)[Pt]\n", - "kf = 2.77963678004065e-20\n", - "krev = 3.601218827022036\n", - "Kc = 7.718600045027592e-21\n", - "proton+O=CC=C(O)[Pt]<=>H2O+O=CC=C=[Pt]\n", - "kf = 2.367383825493301e-13\n", - "krev = 16.1722227709439\n", - "Kc = 1.463858035487058e-14\n", - "proton+O=CC=C(O)[Pt]<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.867624236214861e-24\n", - "Kc = 3.177579311035777e33\n", - "vacantX+vacantX+CCOCO<=>OCO[Pt]+CC[Pt]\n", - "kf = 2.4512530384253315e-9\n", - "krev = 3.614837695546209e14\n", - "Kc = 6.781087409389048e-24\n", - "vacantX+vacantX+CCOCO<=>OC[Pt]+CCO[Pt]\n", - "kf = 1.0293700832173347e-6\n", - "krev = 1.2050997101819434e12\n", - "Kc = 8.541783509863451e-19\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC([Pt])=CO\n", - "kf = 4.3007284274917255e-15\n", - "krev = 1.9561961334382385\n", - "Kc = 2.1985159636997663e-15\n", - "HX+O=C=C=CO<=>O=CC([Pt])=CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.6370748462102965e-36\n", - "Kc = 1.5839961798805036e28\n", - "proton+O=CC([Pt])=CO<=>C=O+OC=C=[Pt]\n", - "kf = 4.3296354594819855e-33\n", - "krev = 908.9754469679581\n", - "Kc = 4.76320397203711e-36\n", - "proton+O=C=C=CO.[Pt]<=>O=CC([Pt])=CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.7196074204687593e-20\n", - "Kc = 1.4538201977044896e30\n", - "HOX+C#CC=O<=>O=CC([Pt])=CO\n", - "kf = 2.952076594227614e-8\n", - "krev = 4.790462195255654e-44\n", - "Kc = 6.162404531970363e35\n", - "proton+O=CC([Pt])=CO<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.2409630475480663e-18\n", - "Kc = 1.1155918000233681e28\n", - "proton+OC=CC=[Pt]<=>CHX+C=CO\n", - "kf = 0.3708119772368373\n", - "krev = 1.9743851754031655e-5\n", - "Kc = 18781.136621992628\n", - "vacantX+vacantX+O=CC=CO<=>OX+OC=CC=[Pt]\n", - "kf = 8.803023976547135e-28\n", - "krev = 1.526615583505237e17\n", - "Kc = 5.766365856383213e-45\n", - "proton+OC=CC#[Pt]<=>OC=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4263979915391943e-8\n", - "Kc = 1.7526665172195773e18\n", - "vacantX+vacantX+CCCOO<=>OOC[Pt]+CC[Pt]\n", - "kf = 5.56726706794292e-16\n", - "krev = 4.282042054393877e17\n", - "Kc = 1.3001430152303739e-33\n", - "proton+OCC(O)[Pt]<=>OC=[Pt]+CO-2\n", - "kf = 0.16339719354915763\n", - "krev = 6.17359485423602e-8\n", - "Kc = 2.6467106670766133e6\n", - "HX+O=CCO<=>OCC(O)[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 4.347223516290618e-14\n", - "Kc = 644231.1603064304\n", - "vacantX+vacantX+OCCO<=>HX+OCC(O)[Pt]\n", - "kf = 7.314142036323851e-21\n", - "krev = 492.5535033039904\n", - "Kc = 1.4849436634317805e-23\n", - "HX+OC=CO<=>OCC(O)[Pt]\n", - "kf = 5.6012337000223925e-8\n", - "krev = 1.5412075197181771e-21\n", - "Kc = 3.634315060340885e13\n", - "HOX+C=CO<=>OCC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 6.743155058263278e-19\n", - "Kc = 4.8491603395127426e10\n", - "proton+O=CCO.[Pt]<=>OCC(O)[Pt]\n", - "kf = 698182.0065765544\n", - "krev = 4.403884986144656e-6\n", - "Kc = 1.5853774764171848e11\n", - "proton+OCC(O)[Pt]<=>H2O+OCC=[Pt]\n", - "kf = 0.7285659975205578\n", - "krev = 0.0004743003964980969\n", - "Kc = 1536.0855755124403\n", - "proton+OC=CO.[Pt]<=>OCC(O)[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 1.4989628309182922e-5\n", - "Kc = 3.3356397482764175e15\n", - "proton+OCC(O)C#[Pt]<=>CX+OCCO\n", - "kf = 5.26000051169577\n", - "krev = 0.00019971123776726528\n", - "Kc = 26338.02969978857\n", - "vacantX+vacantX+CCC<=>CH3X+CC[Pt]\n", - "kf = 7.798842461270165e-20\n", - "krev = 4.754727023110295e15\n", - "Kc = 1.640229275700578e-35\n", - "proton+O=C([Pt])CO<=>OCC(O)=[Pt]\n", - "kf = 4.019918430047713e-18\n", - "krev = 1.0085447542339827e12\n", - "Kc = 3.9858602339377106e-30\n", - "proton+OCC(O)=[Pt]<=>H2O+OCC#[Pt]\n", - "kf = 16209.61875952926\n", - "krev = 4.634124941714537e-41\n", - "Kc = 3.4978812533984058e44\n", - "proton+OCC(O)=[Pt]<=>OC#[Pt]+CO-2\n", - "kf = 382.95023851607715\n", - "krev = 3.536410198453644e-35\n", - "Kc = 1.0828784474253827e37\n", - "proton+OC=C(O)[Pt]<=>OCC(O)=[Pt]\n", - "kf = 6875.768524790738\n", - "krev = 1.0085447542339824e12\n", - "Kc = 6.8175145385720384e-9\n", - "proton+OCC(O)=[Pt]<=>OCC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.6015120113778689e-47\n", - "Kc = 1.5610248204439706e57\n", - "HX+COC=O<=>COC(O)[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 224.3395816271696\n", - "Kc = 1.2483828443014824e-10\n", - "proton+COC(O)[Pt]<=>OC=[Pt]+CO-2\n", - "kf = 564390.3708916149\n", - "krev = 3.282828318007529e-12\n", - "Kc = 1.7192198806002883e17\n", - "vacantX+vacantX+COCO<=>HX+COC(O)[Pt]\n", - "kf = 6.183244140051347e-23\n", - "krev = 2731.92216309053\n", - "Kc = 2.2633310068601865e-26\n", - "O=CO+CH3X<=>COC(O)[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 8.503469161971292e7\n", - "Kc = 3.7620485485108396e-16\n", - "proton+COC=O.[Pt]<=>COC(O)[Pt]\n", - "kf = 7.49969185016536e-5\n", - "krev = 3658.0165064396892\n", - "Kc = 2.0502072193940793e-8\n", - "proton+COC(O)[Pt]<=>H2O+COC=[Pt]\n", - "kf = 5.10646151413012e-10\n", - "krev = 0.003546985366877098\n", - "Kc = 1.439662413557134e-7\n", - "vacantX+vacantX+CCOOC<=>COO[Pt]+CC[Pt]\n", - "kf = 1.4778859852656565e-10\n", - "krev = 2.404289853338368e13\n", - "Kc = 6.146871115450596e-24\n", - "vacantX+vacantX+CCOOC<=>CO[Pt]+CCO[Pt]\n", - "kf = 2.735304068777078e8\n", - "krev = 1.1929824589169815e-11\n", - "Kc = 2.2928284052560617e19\n", - "vacantX+vacantX+CCOOC<=>CH3X+CCOO[Pt]\n", - "kf = 1.542530561493995e-10\n", - "krev = 1.2789927244807063e12\n", - "Kc = 1.2060510837700736e-22\n", - "proton+COC(O)C#[Pt]<=>CX+COCO\n", - "kf = 0.03928313633337953\n", - "krev = 0.002914319669063903\n", - "Kc = 13.479350515448948\n", - "proton+COC(=O)[Pt]<=>COC(O)=[Pt]\n", - "kf = 6.005930457604258e-17\n", - "krev = 1.0085447542339825e12\n", - "Kc = 5.955046052632466e-29\n", - "proton+COC(O)=[Pt]<=>OC#[Pt]+CO-2\n", - "kf = 383854.3090963643\n", - "krev = 3.448448528690976e-34\n", - "Kc = 1.113121758677009e39\n", - "proton+COC(O)=[Pt]<=>H2O+COC#[Pt]\n", - "kf = 217922.49486435574\n", - "krev = 2.0340320286285714e-35\n", - "Kc = 1.0713818258372662e40\n", - "proton+COC(O)=[Pt]<=>COC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0120272229346644e-38\n", - "Kc = 2.4702892801149458e48\n", - "vacantX+vacantX+C=C=COO<=>OOC=[Pt]+C=C=[Pt]\n", - "kf = 1.9145907695639512e-44\n", - "krev = 1.1771971588384226e12\n", - "Kc = 1.626397715275781e-56\n", - "C=O+O=CC[Pt]<=>O=CCCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 0.0025285011306884937\n", - "Kc = 1.5664103465194285e-5\n", - "HX+O=CCC=O<=>O=CCCO[Pt]\n", - "kf = 5.113182125834635e-8\n", - "krev = 3.03538509820146e-7\n", - "Kc = 0.16845250142607343\n", - "proton+O=CCC=O.[Pt]<=>O=CCCO[Pt]\n", - "kf = 2.3901708430508703e8\n", - "krev = 41.103568870106145\n", - "Kc = 5.814995896351951e6\n", - "vacantX+vacantX+O=CCCO<=>HX+O=CCCO[Pt]\n", - "kf = 2.5157725911236352e-27\n", - "krev = 8837.406478086354\n", - "Kc = 2.84673178421957e-31\n", - "proton+O=CCCO[Pt]<=>OX+CCC=O\n", - "kf = 774927.4661784222\n", - "krev = 1.1978583087682196e-18\n", - "Kc = 6.469274875884902e23\n", - "CHOX+C=C<=>O=CCC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 0.4688595936220698\n", - "Kc = 1.7478623517301195e-7\n", - "proton+O=CCC[Pt]<=>CH2X+CC=O\n", - "kf = 0.0016740956920828355\n", - "krev = 4.373185000711893e-7\n", - "Kc = 3828.0925499614495\n", - "HX+C=CC=O<=>O=CCC[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 7.666152073113618e-12\n", - "Kc = 3780.924152337611\n", - "proton+O=CCC=[Pt]<=>O=CCC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3932958912707058e-30\n", - "Kc = 1.794306590339518e40\n", - "vacantX+vacantX+O=CCCO<=>HOX+O=CCC[Pt]\n", - "kf = 8.901266563864654e-15\n", - "krev = 1.309728963703428e15\n", - "Kc = 6.79626610584771e-30\n", - "vacantX+vacantX+CCC=O<=>HX+O=CCC[Pt]\n", - "kf = 1.6716561102658422e-25\n", - "krev = 524619.2678123232\n", - "Kc = 3.186417680076247e-31\n", - "vacantX+vacantX+CC=COO<=>OOC=[Pt]+CC=[Pt]\n", - "kf = 3.7147962989308654e-50\n", - "krev = 4.0636001726377395e18\n", - "Kc = 9.141638303749602e-69\n", - "proton+C=COOC#[Pt]<=>CX+C=COO\n", - "kf = 8.811176921711816e-67\n", - "krev = 2.5e10\n", - "Kc = 3.5244707686847265e-77\n", - "vacantX+C=CC=O<=>C=CC=O.[Pt]\n", - "kf = 365995.57053717994\n", - "krev = 1.0054621985249468\n", - "Kc = 364007.290452202\n", - "proton+C=CC(=O)[Pt]<=>C=CC=O.[Pt]\n", - "kf = 3.399604827397095e9\n", - "krev = 5.959510760846119e-12\n", - "Kc = 5.704503211458966e20\n", - "proton+O=CC=C[Pt]<=>C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.32808736312024e-27\n", - "Kc = 3.00188973889839e36\n", - "proton+C=CC=O.[Pt]<=>O=CCC[Pt]\n", - "kf = 5.197601136262071e7\n", - "krev = 74.26603000820454\n", - "Kc = 699862.5260684955\n", - "vacantX+vacantX+C=CC=O<=>HX+C=C([Pt])C=O\n", - "kf = 1.2784478936507186e-21\n", - "krev = 132.59733776930153\n", - "Kc = 9.641580405445367e-24\n", - "proton+C=C([Pt])C=O<=>C=O+C=C=[Pt]\n", - "kf = 2.4079500300331376e-13\n", - "krev = 0.010970404022735962\n", - "Kc = 2.194951092997765e-11\n", - "HX+C=C=C=O<=>C=C([Pt])C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.4992009477647154e-32\n", - "Kc = 1.1812081765045545e24\n", - "vacantX+vacantX+C=C(O)C=O<=>HOX+C=C([Pt])C=O\n", - "kf = 1.107119853181277e-14\n", - "krev = 2.5289157654010746e13\n", - "Kc = 4.377843929513773e-28\n", - "proton+C=C=C=O.[Pt]<=>C=C([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.305987527913534e-16\n", - "Kc = 1.0841342243780513e26\n", - "HX+C#CC=O<=>C=C([Pt])C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 1.683521621093348e-30\n", - "Kc = 1.753512730243651e22\n", - "proton+C=C([Pt])C=O<=>C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.827731832923639e-27\n", - "Kc = 2.5438219545478565e36\n", - "CHOX+C=C=O<=>C=C(C=O)O[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.906984656058423e-6\n", - "Kc = 0.017553122325364576\n", - "proton+C=C(C=O)O[Pt]<=>OX+C=CC=O\n", - "kf = 13.565263195704604\n", - "krev = 7.179044500174065e-6\n", - "Kc = 1.8895638821260543e6\n", - "vacantX+vacantX+C=C(O)C=O<=>HX+C=C(C=O)O[Pt]\n", - "kf = 8.336773502217888e-19\n", - "krev = 4.018028855986407\n", - "Kc = 2.0748416203624424e-19\n", - "vacantX+vacantX+COCOC<=>CH3X+COCO[Pt]\n", - "kf = 0.24675966205104702\n", - "krev = 5.277017405064255e15\n", - "Kc = 4.6761199198288865e-17\n", - "vacantX+vacantX+COCOC<=>CO[Pt]+COC[Pt]\n", - "kf = 4.1241018831024145e-7\n", - "krev = 7.782310155024181e12\n", - "Kc = 5.2993286067375974e-20\n", - "proton+C=CC=[Pt]<=>CHX+C=C\n", - "kf = 1.3385165927063483e6\n", - "krev = 9.028119675350497e-7\n", - "Kc = 1.4826083845132273e12\n", - "vacantX+vacantX+C=CC=O<=>OX+C=CC=[Pt]\n", - "kf = 1.438969400016978e-30\n", - "krev = 1.6093339940290013e17\n", - "Kc = 8.941396909254915e-48\n", - "proton+C=CC#[Pt]<=>C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.067052266556579e-6\n", - "Kc = 2.342903040792558e16\n", - "vacantX+CC(O)O<=>CC(O)O.[Pt]\n", - "kf = 347843.58123444836\n", - "krev = 178209.4487483253\n", - "Kc = 1.9518806868971765\n", - "proton+CC(O)O[Pt]<=>CC(O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.64203868551119e-24\n", - "Kc = 1.5224976257010135e34\n", - "vacantX+vacantX+COCCO<=>OC[Pt]+COC[Pt]\n", - "kf = 1.3358759661274015e-7\n", - "krev = 3.1165281946439875e14\n", - "Kc = 4.286423490161954e-22\n", - "vacantX+vacantX+COCCO<=>CO[Pt]+OCC[Pt]\n", - "kf = 6.192873660096324e-8\n", - "krev = 3.90827625278604e13\n", - "Kc = 1.584553716150872e-21\n", - "vacantX+vacantX+COCCO<=>CH3X+OCCO[Pt]\n", - "kf = 4.52195120819324e-12\n", - "krev = 5.920081591014324e14\n", - "Kc = 7.638325821483257e-27\n", - "proton+OC(O)C[Pt]<=>CH2X+OCO\n", - "kf = 2.252975678309519e-7\n", - "krev = 0.002613777215265548\n", - "Kc = 8.619616335895816e-5\n", - "HOX+C=CO<=>OC(O)C[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 6.095879365149742e-19\n", - "Kc = 5.364056293281289e10\n", - "HX+C=C(O)O<=>OC(O)C[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 1.7806643358524245e-19\n", - "Kc = 1.572793251160735e11\n", - "vacantX+vacantX+CC(O)O<=>HX+OC(O)C[Pt]\n", - "kf = 2.610914590914038e-25\n", - "krev = 48838.0104312493\n", - "Kc = 5.3460707507516085e-30\n", - "vacantX+vacantX+CCC(O)O<=>CH3X+OC(O)C[Pt]\n", - "kf = 2.73273606062798e-19\n", - "krev = 1.7143250273592365e15\n", - "Kc = 1.594059479396106e-34\n", - "proton+OC(O)C[Pt]<=>CC(O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0162407066861682e-27\n", - "Kc = 2.4600470966688416e37\n" - ] - } - ], - "source": [ - "for (i,rxn) in enumerate(inter.reactions)\n", - " str = getrxnstr(rxn)\n", - " kf = inter.kfs[i]\n", - " krev = inter.krevs[i]\n", - " Kc = kf/krev\n", - " println(str)\n", - " println(\"kf = $kf\")\n", - " println(\"krev = $krev\")\n", - " println(\"Kc = $Kc\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "id": "11333da0", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "ef575a57", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.9.1", - "language": "julia", - "name": "julia-1.9" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.9.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/CO2_Reduction_Ag/CO2RR_RMS_Diffusion_Interface.jl b/CO2_Reduction_Ag/CO2RR_RMS_Diffusion_Interface.jl new file mode 100644 index 0000000..fe10d60 --- /dev/null +++ b/CO2_Reduction_Ag/CO2RR_RMS_Diffusion_Interface.jl @@ -0,0 +1,217 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,jl:percent +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.17.2 +# kernelspec: +# display_name: Julia 1.9.1 +# language: julia +# name: julia-1.9 +# --- + +# %% +using DifferentialEquations +using ReactionMechanismSimulator +using PyPlot + +# %% +outdict = readinput("chem300.rms") + +# %% +boundarylayerspcs = outdict["gas"]["Species"] +boundarylayerrxns = outdict["gas"]["Reactions"] +surfspcs = outdict["surface"]["Species"] +surfrxns = outdict["surface"]["Reactions"] +interfacerxns = outdict[Set(["surface", "gas"])]["Reactions"] +solv = outdict["Solvents"][1]; + +# %% +sitedensity = 2.292e-5; # Ag111 +boundarylayer = IdealDiluteSolution(boundarylayerspcs,boundarylayerrxns,solv,name="boundarylayeruid",diffusionlimited=true); +surf = IdealSurface(surfspcs,surfrxns,sitedensity,name="surface"); + +# %% +initialcondsboundarylayer = Dict(["proton"=>10.0^-4, + "CO2"=>10.0^-3*10^6, + "V"=>1.0e-3,"T"=>300,"Phi"=>0.0,"d"=>0.0]); +initialcondsreservoir = Dict(["proton"=>10.0^-4, + "CO2"=>10.0^-3*10^6, + "V"=>1.0,"T"=>300]); +AVratio = 1e5; +initialcondssurf = Dict(["CO2X"=>0.4*sitedensity*AVratio, + "CHO2X"=>0.1*sitedensity*AVratio, + "CO2HX"=>0.1*sitedensity*AVratio, + "OX"=>0.1*sitedensity*AVratio, + "OCX"=>0.1*sitedensity*AVratio, + "vacantX"=>0.1*sitedensity*AVratio, + "CH2O2X"=>0.05*sitedensity*AVratio, + "CHOX"=>0.04*sitedensity*AVratio, + "CH2OX"=>0.01*sitedensity*AVratio, + "A"=>1.0*AVratio,"T"=>300,"Phi"=>-1.0]); + +# %% +domainboundarylayer, y0boundarylayer, pboundarylayer = ConstantTVDomain(phase=boundarylayer, initialconds=initialcondsboundarylayer); +domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf, + initialconds=initialcondssurf); + +# %% +inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainboundarylayer, + domaincat,interfacerxns,298.15,AVratio*1.0); + +# %% +# start with 1mm layer thickness +diffusionlayer = ConstantReservoirDiffusion(domainboundarylayer, initialcondsreservoir, AVratio*1.0, 1e-3); + +# %% +interfaces = [inter, diffusionlayer]; + +# %% +@time react,y0,p = Reactor((domainboundarylayer,domaincat), (y0boundarylayer,y0cat), (0.0, 1.0e2), interfaces, (pboundarylayer,pcat,pinter)); + + +# %% +@time sol = solve(react.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-8); + +# %% +sol + +# %% +sol.retcode + +# %% +ssys = SystemSimulation(sol,(domainboundarylayer,domaincat,), interfaces,p); + +# %% +# Helper function +function plotX(sim, tol, t_end, exclude) + clf() + xs = molefractions(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Mole Fraction") +end + +# %% +# Helper function +function plotC(sim, tol, t_end, exclude) + clf() + xs = concentrations(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Concentration") +end + +# %% +concentrations(ssys.sims[1]) + +# %% +concentrations(ssys.sims[2]) + +# %% +exclude_species = ["H2O"] +plotX(ssys.sims[1], 1e-6, 1e2, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e2) +ylim(1e-9, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V") +gcf() + +# %% +exclude_species = ["H2O"] +plotC(ssys.sims[1], 1e-6, 1e2, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 10) +ylim(1e-6, 1e8) +title("Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V") +gcf() + +# %% +exclude_species = ["H2O"] +plotC(ssys.sims[2], 1e-6, 1e2, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 10) +ylim(1e-6, 1e-4) +title("Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V") +gcf() + +# %% +getfluxdiagram(ssys,1e2;speciesratetolerance=1e-6) + +# %% +println(ssys.names) + +# %% +plotrops(ssys,"CH2O2X",1;N=15,tol=0.0) + +# %% +plotrops(ssys,"CHO2X",1;N=10,tol=0.0) + +# %% +plotrops(ssys,"CO2HX",1;N=10,tol=0.0) + +# %% +plotrops(ssys,"OX",1;N=10,tol=0.0) + +# %% +plotrops(ssys,"OCX",1.0e-6) + +# %% +for (i,rxn) in enumerate(inter.reactions) + str = getrxnstr(rxn) + kf = inter.kfs[i] + krev = inter.krevs[i] + Kc = kf/krev + println(str) + println("kf = $kf") + println("krev = $krev") + println("Kc = $Kc") +end + +# %% +for (i,rxn) in enumerate(inter.reactions) + str = getrxnstr(rxn) + kf = inter.kfs[i] + krev = inter.krevs[i] + Kc = kf/krev + println(str) + println("kf = $kf") + println("krev = $krev") + println("Kc = $Kc") +end + +# %% + +# %% diff --git a/CO2_Reduction_Ag/CO2RR_RMS_Diffusion_Interface_1.ipynb b/CO2_Reduction_Ag/CO2RR_RMS_Diffusion_Interface_1.ipynb deleted file mode 100644 index a90c268..0000000 --- a/CO2_Reduction_Ag/CO2RR_RMS_Diffusion_Interface_1.ipynb +++ /dev/null @@ -1,2776 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "8a590634", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\u001b[32m\u001b[1m Activating\u001b[22m\u001b[39m project at `~/miniforge3/envs/rmg_electrocat_2/julia_env`\n" - ] - } - ], - "source": [ - "using Pkg\n", - "Pkg.activate(ENV[\"PYTHON_JULIAPKG_PROJECT\"])" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "2dd97e53", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "WARNING: Method definition getGibbs(P, N) where {N<:Number, P<:ReactionMechanismSimulator.AbstractThermo} in module ReactionMechanismSimulator at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Calculators/Thermo.jl:6 overwritten on the same line (check for duplicate calls to `include`).\n", - "ERROR: Method overwriting is not permitted during Module precompilation. Use `__precompile__(false)` to opt-out of precompilation.\n", - "┌ Warning: Replacing docs for `ReactionMechanismSimulator.getpairs :: Tuple{T} where T<:ReactionMechanismSimulator.AbstractReaction` in module `ReactionMechanismSimulator`\n", - "└ @ Base.Docs docs/Docs.jl:243\n", - "┌ Warning: Replacing docs for `ReactionMechanismSimulator.getsimilarity :: Union{Tuple{T2}, Tuple{T}, Tuple{T, T2}} where {T<:ReactionMechanismSimulator.AbstractSpecies, T2<:ReactionMechanismSimulator.AbstractSpecies}` in module `ReactionMechanismSimulator`\n", - "└ @ Base.Docs docs/Docs.jl:243\n", - "WARNING: method definition for getreactionindices at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Phase.jl:316 declares type variable Q but does not use it.\n", - "WARNING: method definition for Inlet at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Interface.jl:255 declares type variable B but does not use it.\n", - "WARNING: method definition for #ConstantTPDomain#338 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:43 declares type variable W but does not use it.\n", - "WARNING: method definition for #ConstantTPDomain#338 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:43 declares type variable Q but does not use it.\n", - "WARNING: method definition for #ConstantTPDomain#338 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:43 declares type variable E but does not use it.\n", - "WARNING: method definition for #ConstantVDomain#349 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:121 declares type variable Q but does not use it.\n", - "WARNING: method definition for #ConstantPDomain#358 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:189 declares type variable Q but does not use it.\n", - "WARNING: method definition for #ParametrizedTPDomain#367 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:258 declares type variable Q but does not use it.\n", - "WARNING: method definition for #ParametrizedVDomain#376 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:338 declares type variable Q but does not use it.\n", - "WARNING: method definition for #ParametrizedVDomain#376 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:338 declares type variable E but does not use it.\n", - "WARNING: method definition for #ParametrizedPDomain#385 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:415 declares type variable Q but does not use it.\n", - "WARNING: method definition for #ParametrizedPDomain#385 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:415 declares type variable E but does not use it.\n", - "WARNING: method definition for #ConstantTVDomain#394 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:502 declares type variable W but does not use it.\n", - "WARNING: method definition for #ConstantTVDomain#394 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:502 declares type variable Q but does not use it.\n", - "WARNING: method definition for #ParametrizedTConstantVDomain#405 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:587 declares type variable Q but does not use it.\n", - "WARNING: method definition for #ConstantTAPhiDomain#414 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:671 declares type variable W but does not use it.\n", - "WARNING: method definition for #ConstantTAPhiDomain#414 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:671 declares type variable E but does not use it.\n", - "WARNING: method definition for #FragmentBasedConstantTrhoDomain#423 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:763 declares type variable X3 but does not use it.\n", - "WARNING: method definition for #FragmentBasedConstantTrhoDomain#423 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:763 declares type variable E1 but does not use it.\n", - "WARNING: method definition for #FragmentBasedConstantTrhoDomain#423 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:763 declares type variable X1 but does not use it.\n", - "WARNING: method definition for #ConstantTLiqFilmDomain#432 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:871 declares type variable W but does not use it.\n", - "WARNING: method definition for #ConstantTLiqFilmDomain#432 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:871 declares type variable Q but does not use it.\n", - "WARNING: method definition for calcthermo at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:1591 declares type variable J but does not use it.\n", - "WARNING: method definition for calcthermo at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:1663 declares type variable J but does not use it.\n", - "WARNING: method definition for calcthermo at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:1750 declares type variable J but does not use it.\n", - "WARNING: method definition for calcthermo at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:1829 declares type variable J but does not use it.\n", - "WARNING: method definition for #calcdomainderivatives!#487 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:1866 declares type variable Y but does not use it.\n", - "WARNING: method definition for #calcdomainderivatives!#487 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:1866 declares type variable W but does not use it.\n", - "WARNING: method definition for #calcdomainderivatives!#488 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:1892 declares type variable Y but does not use it.\n", - "WARNING: method definition for #calcdomainderivatives!#488 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:1892 declares type variable W but does not use it.\n", - "WARNING: method definition for jacobianpnsderiv! at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:3130 declares type variable Q3 but does not use it.\n", - "WARNING: method definition for jacobianpnsderiv! at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:3239 declares type variable Q3 but does not use it.\n", - "WARNING: method definition for jacobianpnsderiv! at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Domain.jl:3325 declares type variable Q3 but does not use it.\n", - "WARNING: Method definition isapprox(IntervalSets.AbstractInterval{T} where T, IntervalSets.AbstractInterval{T} where T) in module IntervalSets at /home/ssun30/.julia/packages/IntervalSets/CFJJK/src/IntervalSets.jl:297 overwritten in module DomainSets at /home/ssun30/.julia/packages/DomainSets/aafhp/src/domains/interval.jl:52.\n", - "ERROR: Method overwriting is not permitted during Module precompilation. Use `__precompile__(false)` to opt-out of precompilation.\n", - "WARNING: Method definition isapprox(IntervalSets.AbstractInterval{T} where T, IntervalSets.AbstractInterval{T} where T) in module IntervalSets at /home/ssun30/.julia/packages/IntervalSets/CFJJK/src/IntervalSets.jl:297 overwritten in module DomainSets at /home/ssun30/.julia/packages/DomainSets/aafhp/src/domains/interval.jl:52.\n", - "ERROR: Method overwriting is not permitted during Module precompilation. Use `__precompile__(false)` to opt-out of precompilation.\n", - "\u001b[33m\u001b[1m┌ \u001b[22m\u001b[39m\u001b[33m\u001b[1mWarning: \u001b[22m\u001b[39mModule Symbolics with build ID ffffffff-ffff-ffff-da52-b0f537dfbdbc is missing from the cache.\n", - "\u001b[33m\u001b[1m│ \u001b[22m\u001b[39mThis may mean Symbolics [0c5d862f-8b57-4792-8d23-62f2024744c7] does not support precompilation but is imported by a module that does.\n", - "\u001b[33m\u001b[1m└ \u001b[22m\u001b[39m\u001b[90m@ Base loading.jl:2018\u001b[39m\n", - "WARNING: method definition for #Reactor#622 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Reactor.jl:267 declares type variable F but does not use it.\n", - "WARNING: method definition for addreactionratecontributions! at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Reactor.jl:465 declares type variable T but does not use it.\n", - "WARNING: method definition for addreactionratecontributions! at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Reactor.jl:509 declares type variable W2 but does not use it.\n", - "WARNING: method definition for addreactionratecontributions! at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Reactor.jl:509 declares type variable T but does not use it.\n", - "WARNING: method definition for addreactionratecontributions! at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Reactor.jl:556 declares type variable T but does not use it.\n", - "WARNING: method definition for addreactionratecontributionsforwardreverse! at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Reactor.jl:601 declares type variable T but does not use it.\n", - "WARNING: method definition for jacobianyforwarddiff at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Reactor.jl:789 declares type variable Q but does not use it.\n", - "WARNING: method definition for jacobianpforwarddiff at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Reactor.jl:841 declares type variable Q but does not use it.\n", - "WARNING: Method definition (::ChainRulesCore.ProjectTo{var\"#s1108\"<:(ChainRulesCore.Tangent{var\"#s1107\", T} where T where var\"#s1107\"<:Tuple), D<:(NamedTuple{names, T} where T<:Tuple where names)})(StaticArraysCore.SArray{S, T, N, L} where L where N where T where S<:Tuple) in module StaticArraysChainRulesCoreExt at /home/ssun30/.julia/packages/StaticArrays/LSPcF/ext/StaticArraysChainRulesCoreExt.jl:10 overwritten in module SciMLSensitivity at /home/ssun30/.julia/packages/SciMLSensitivity/VumeD/src/staticarrays.jl:2.\n", - "ERROR: Method overwriting is not permitted during Module precompilation. Use `__precompile__(false)` to opt-out of precompilation.\n", - "WARNING: method definition for sensg at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:554 declares type variable V but does not use it.\n", - "WARNING: method definition for sensg at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:554 declares type variable Q but does not use it.\n", - "WARNING: method definition for sensg at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:560 declares type variable V but does not use it.\n", - "WARNING: method definition for sensg at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:560 declares type variable Q but does not use it.\n", - "WARNING: method definition for sensg at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:566 declares type variable V but does not use it.\n", - "WARNING: method definition for sensg at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:566 declares type variable Q but does not use it.\n", - "WARNING: method definition for sensg at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:572 declares type variable V but does not use it.\n", - "WARNING: method definition for sensg at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:572 declares type variable Q but does not use it.\n", - "WARNING: method definition for g at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:579 declares type variable V but does not use it.\n", - "WARNING: method definition for g at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:579 declares type variable Q but does not use it.\n", - "WARNING: method definition for g at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:583 declares type variable V but does not use it.\n", - "WARNING: method definition for g at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:583 declares type variable Q but does not use it.\n", - "WARNING: method definition for g at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:587 declares type variable V but does not use it.\n", - "WARNING: method definition for g at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:587 declares type variable Q but does not use it.\n", - "WARNING: method definition for g at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:591 declares type variable V but does not use it.\n", - "WARNING: method definition for g at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:591 declares type variable Q but does not use it.\n", - "WARNING: method definition for g at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:646 declares type variable V but does not use it.\n", - "WARNING: method definition for g at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:646 declares type variable Q but does not use it.\n", - "WARNING: method definition for g at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:650 declares type variable V but does not use it.\n", - "WARNING: method definition for g at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:650 declares type variable Q but does not use it.\n", - "WARNING: method definition for g at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:654 declares type variable V but does not use it.\n", - "WARNING: method definition for g at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:654 declares type variable Q but does not use it.\n", - "WARNING: method definition for g at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:658 declares type variable V but does not use it.\n", - "WARNING: method definition for g at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Simulation.jl:658 declares type variable Q but does not use it.\n", - "┌ Warning: Replacing docs for `ReactionMechanismSimulator.plotrops :: Union{Tuple{X}, Tuple{Y}, Tuple{Y, X}} where {Y<:ReactionMechanismSimulator.Simulation, X<:AbstractString}` in module `ReactionMechanismSimulator`\n", - "└ @ Base.Docs docs/Docs.jl:243\n", - "┌ Warning: Replacing docs for `ReactionMechanismSimulator.plotrops :: Union{Tuple{X}, Tuple{Y}, Tuple{Y, X}} where {Y<:ReactionMechanismSimulator.Simulation, X<:AbstractString}` in module `ReactionMechanismSimulator`\n", - "└ @ Base.Docs docs/Docs.jl:243\n", - "WARNING: method definition for #plotradicalrops#952 at /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Plotting.jl:371 declares type variable X but does not use it.\n" - ] - } - ], - "source": [ - "using ReactionMechanismSimulator" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "ab36978b", - "metadata": {}, - "outputs": [], - "source": [ - "using PythonPlot\n", - "using DifferentialEquations\n", - "using Sundials\n", - "using SciMLBase\n", - "using QuadGK" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "e941d4fb", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[18:17:43] WARNING: not removing hydrogen atom without neighbors\n", - "[18:17:43] WARNING: not removing hydrogen atom without neighbors\n", - "┌ Warning: failed to generate StokesDiffusivity model for species vacantX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2O2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species H2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(C[Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]COO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(=[Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC([Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C([Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH3X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [H][H].[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(C=[Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(C#[Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]=C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)([Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=[Pt])O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]C#CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]OC#CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [Pt]=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n" - ] - }, - { - "data": { - "text/plain": [ - "Dict{Any, Any} with 4 entries:\n", - " \"Solvents\" => Solvent[Solvent(\"water\", RiedelViscosity{Float64}(…\n", - " Set([\"surface\", \"gas\"]) => Dict{Any, Any}(\"Reactions\"=>ElementaryReaction[vac…\n", - " \"gas\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…\n", - " \"surface\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "outdict = readinput(\"Ag_C2_042925.rms\")" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "fe2767e9", - "metadata": {}, - "outputs": [], - "source": [ - "boundarylayerspcs = outdict[\"gas\"][\"Species\"]\n", - "boundarylayerrxns = outdict[\"gas\"][\"Reactions\"]\n", - "surfspcs = outdict[\"surface\"][\"Species\"]\n", - "surfrxns = outdict[\"surface\"][\"Reactions\"]\n", - "interfacerxns = outdict[Set([\"surface\", \"gas\"])][\"Reactions\"]\n", - "solv = outdict[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "c54ee65e", - "metadata": {}, - "outputs": [], - "source": [ - "sitedensity = 2.294e-5; # Ag111 site density is 2.294e-9 mol/cm^2 or 2.294e-5 mol/m^2\n", - "boundarylayer = IdealDiluteSolution(boundarylayerspcs,boundarylayerrxns,solv,name=\"boundarylayeruid\",diffusionlimited=true);\n", - "surf = IdealSurface(surfspcs,surfrxns,sitedensity,name=\"surface\");" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "8894c84d", - "metadata": {}, - "outputs": [], - "source": [ - "# Reservoir is a 100 mL (100e-6 m^3) cell\n", - "# Proton concentration is 10^-7 mol/L (10^-4 mol/m^3)\n", - "# CO2 concentration is 0.01 mol/L (10 mol/m^3), saturation solubility ~0.03 mol/L\n", - "# AVratio in experiments is 36 m^-1 but is measured by surface area/reservoir volume\n", - "# Area of the electrode is therefore 3.6e1 m^-1 * 1e2 * 1e-6 m^3 = 3.6e-3 m^2 = 36 cm^2\n", - "# Assume boundary layer thickness d_bl = 1 mm or 1e-3 m\n", - "# Volume of the boundary layer V_bl = 3.6e-3 m^2 * 1e-3 m = 3.6e-6 m^3\n", - "# Actual AVratio is therefore 3.6e-3 m^2 / 3.6e-6 m^3 = 1e3 m^-1 (reciprocal of d_bl)\n", - "# Amount of sites is 2.943e-5 mol/m^2 * 3.6e-3 m^2 = 10.595e-8 mol\n", - "\n", - "C_proton = 1e-7*1e3;\n", - "C_co2 = 1e-2*1e3;\n", - "C_default = 1e-12;\n", - "V_res = 1e3;\n", - "layer_thickness = 1e-3;\n", - "A_surf = V_res*36;\n", - "V_bl = A_surf*layer_thickness;\n", - "# V_bl = V_res;\n", - "sites = sitedensity*A_surf;\n", - "\n", - "# The initial conditions for individual species are moles not concentration, so we need to multiply concentration by boundary layer volume\n", - "initialcondsboundarylayer = Dict([\"proton\"=>C_proton*V_bl,\n", - " \"CO2\"=>C_co2*V_bl,\n", - " # \"H2\"=>C_default*10*V_bl,\n", - " # \"O=CO\"=>C_default*V_bl,\n", - " \"V\"=>V_bl,\"T\"=>300,\"Phi\"=>0.0,\"d\"=>0.0]);\n", - "initialcondsreservoir = Dict([\"proton\"=>C_proton,\n", - " \"CO2\"=>C_co2,\n", - " \"V\"=>V_res,\"T\"=>300]);\n", - "\n", - "\n", - "# Assume voltage is -1.0 V vs. R.H.E. which equates to -1.414 V vs. S.H.E. at pH=7\n", - "initialcondssurf = Dict([\"CO2X\"=>0.4*sites,\n", - " # \"CHO2X\"=>0.1*sites,\n", - " # \"CO2HX\"=>0.1*sites,\n", - " # \"OX\"=>0.1*sites,\n", - " # \"OCX\"=>0.1*sites,\n", - " \"vacantX\"=>0.6*sites,\n", - " # \"CH2O2X\"=>0.05*sites,\n", - " # \"CHOX\"=>0.04*sites,\n", - " # \"CH2OX\"=>0.01*sites,\n", - " \"A\"=>A_surf,\"T\"=>300,\"Phi\"=>-1.414]);" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "ddb39b3d", - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "domainboundarylayer, y0boundarylayer, pboundarylayer = ConstantTVDomain(phase=boundarylayer, initialconds=initialcondsboundarylayer);\n", - "domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf,\n", - " initialconds=initialcondssurf);" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "ed49d2b4", - "metadata": {}, - "outputs": [], - "source": [ - "inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainboundarylayer,\n", - " domaincat,interfacerxns,298.15,A_surf);" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "dee14906", - "metadata": {}, - "outputs": [], - "source": [ - "# start with 1mm layer thickness\n", - "diffusionlayer = ConstantReservoirDiffusion(domainboundarylayer, initialcondsreservoir, A_surf, layer_thickness);" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "e70ac4b0", - "metadata": {}, - "outputs": [], - "source": [ - "interfaces = [inter,diffusionlayer];" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "244f0912", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 10.585216 seconds (18.03 M allocations: 1.160 GiB, 4.27% gc time, 99.87% compilation time: <1% of which was recompilation)\n" - ] - } - ], - "source": [ - "@time react,y0,p = Reactor((domainboundarylayer,domaincat), (y0boundarylayer,y0cat), (0.0, 1e3), interfaces, (pboundarylayer,pcat,pinter));" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "7cbec36e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(:f, :u0, :tspan, :p, :kwargs, :problem_type)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fieldnames(typeof(react.ode))" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "2aec7241", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(:domains, :interfaces)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fieldnames(typeof(react.ode.f.f))" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "437675db", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(::ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}) (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "react.ode.f.f" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "962f838c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 5.706378 seconds (5.22 M allocations: 595.831 MiB, 2.44% gc time, 93.39% compilation time)\n", - "1000.0\n", - "Success\n" - ] - } - ], - "source": [ - "@time sol = solve(react.ode,Sundials.CVODE_BDF(),abstol=1e-20,reltol=1e-8);\n", - "println(sol.t[end]);\n", - "println(sol.retcode);" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "6667bb5a", - "metadata": {}, - "outputs": [], - "source": [ - "ssys = SystemSimulation(sol,(domainboundarylayer,domaincat,), interfaces,p);" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "d55a5466", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "25-element Vector{Float64}:\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 9.995894322983263\n", - " 1.9009994446410727e-15\n", - " 0.0\n", - " 3.2837017585781954e-9\n", - " 7.457566298864922e-6\n", - " 5.088457912314128e-31\n", - " ⋮\n", - " 1.0146040082645551e-15\n", - " 8.751521312671633e-12\n", - " 6.433071959568614e-16\n", - " 7.881294843165944e-11\n", - " 7.705460739893599e-11\n", - " 2.467809485838953e-15\n", - " 1.5818822088345775e-28\n", - " 1.4563077738483654e-20\n", - " 2.9286296106950514e-32" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "concentrations(ssys.sims[1], 1e3)" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "d4939a87", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "get_reservoir_concentration" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "\"\"\"\n", - "diffusive flux to the reservoir\n", - "\"\"\"\n", - "function flux_to_reservoir(sim,t,reservoirinterface)\n", - " cs = concentrations(sim,t)\n", - " # println(reservoirinterface.A);\n", - " # println(reservoirinterface.layer_thickness);\n", - " # println(sim.domain.diffusivity);\n", - " # println(cs);\n", - " # println(reservoirinterface.c);\n", - " return reservoirinterface.A .* sim.domain.diffusivity .* (cs - reservoirinterface.c) / reservoirinterface.layer_thickness\n", - "end\n", - "\n", - "\"\"\"\n", - "Integrates the flux to the reservoir and computes the concentration assuming\n", - "there is no prior concentration of that species in the reservoir\n", - "\"\"\"\n", - "function get_reservoir_concentration(sim,t,reservoirinterface,Vres)\n", - " intg,err = quadgk(x -> flux_to_reservoir(sim,x,reservoirinterface), 0, t);\n", - " return intg./Vres\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "411d79d6", - "metadata": {}, - "outputs": [], - "source": [ - "# Logarithmic time scale\n", - "t_vals = 10 .^ range(-12, stop=3, length=100);\n", - "\n", - "# Compute reservoir concentrations\n", - "flux_vals = [flux_to_reservoir(ssys.sims[1], t, diffusionlayer) for t in t_vals]\n", - "# conc_vals = [get_reservoir_concentration(ssys.sims[1], t, diffusionlayer, V_res) for t in t_vals]\n", - "conc_vals_bl = [concentrations(ssys.sims[1], t) for t in t_vals]\n", - "flux_matrix = hcat(flux_vals...);\n", - "# conc_matrix = hcat(conc_vals...);\n", - "conc_matrix_bl = hcat(conc_vals_bl...);\n" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "e4448a7b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "25×100 Matrix{Float64}:\n", - " 0.0 0.0 0.0 … 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0\n", - " -1.10653e-10 -1.56848e-10 -2.22328e-10 -0.000230735 -0.000165936\n", - " -2.39182e-10 -3.39032e-10 -4.80563e-10 … -5.97126e-6 -5.97126e-6\n", - " 0.0 0.0 0.0 0.0 0.0\n", - " 2.45652e-31 4.93562e-31 9.91657e-31 8.72626e-11 1.35284e-10\n", - " 2.19873e-27 6.59934e-27 2.01542e-26 2.36514e-7 2.8743e-7\n", - " 1.45136e-91 8.2261e-91 4.67978e-90 -5.82143e-30 2.37233e-32\n", - " ⋮ ⋱ \n", - " 1.78663e-57 1.96363e-56 2.24754e-55 2.47709e-17 3.58097e-17\n", - " 5.28216e-59 1.08752e-57 2.63488e-56 1.62428e-13 2.99043e-13\n", - " 4.31419e-56 8.9391e-55 2.31362e-53 2.12449e-17 2.19821e-17\n", - " 5.37499e-58 8.52858e-57 1.56712e-55 1.3642e-12 2.69307e-12\n", - " 2.94888e-41 1.23994e-40 5.29375e-40 … 2.00577e-12 3.01944e-12\n", - " 6.48488e-70 2.49199e-68 1.38155e-66 6.2986e-17 8.82077e-17\n", - " 4.3849e-65 3.63337e-64 3.12281e-63 3.8522e-30 5.84876e-30\n", - " 5.30136e-71 2.00446e-69 1.06264e-67 2.5714e-22 4.83164e-22\n", - " 3.74989e-81 2.63431e-79 3.25053e-77 1.50052e-33 1.10271e-33" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "flux_matrix" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "6df160b6", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "25×100 Matrix{Float64}:\n", - " 0.0 0.0 0.0 … 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0\n", - " 10.0 10.0 10.0 9.99429 9.99589\n", - " 9.9996e-5 9.99943e-5 9.9992e-5 … 1.89928e-15 1.901e-15\n", - " 0.0 0.0 0.0 0.0 0.0\n", - " 5.96264e-30 1.19801e-29 2.40702e-29 2.1181e-9 3.2837e-9\n", - " 5.70475e-26 1.71224e-25 5.22913e-25 6.13652e-6 7.45757e-6\n", - " 3.11306e-90 1.76443e-89 1.00378e-88 -1.24865e-28 5.08846e-31\n", - " ⋮ ⋱ \n", - " 5.06209e-56 5.56359e-55 6.368e-54 7.01839e-16 1.0146e-15\n", - " 1.54583e-57 3.18264e-56 7.71101e-55 4.75348e-12 8.75152e-12\n", - " 1.26255e-54 2.61604e-53 6.77083e-52 6.21734e-16 6.43307e-16\n", - " 1.57299e-56 2.4959e-55 4.58618e-54 3.99235e-11 7.88129e-11\n", - " 7.52538e-40 3.16427e-39 1.35094e-38 … 5.11862e-11 7.70546e-11\n", - " 1.81429e-68 6.97192e-67 3.86521e-65 1.76218e-15 2.46781e-15\n", - " 1.18596e-63 9.82699e-63 8.44609e-62 1.04188e-28 1.58188e-28\n", - " 1.59789e-69 6.04166e-68 3.20292e-66 7.75047e-21 1.45631e-20\n", - " 9.95915e-80 6.99635e-78 8.63293e-76 3.98515e-32 2.92863e-32" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "conc_matrix_bl" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "d68e0335", - "metadata": {}, - "outputs": [], - "source": [ - "# clf()\n", - "\n", - "# for i in 1:size(conc_matrix, 1)\n", - "# if maximum(conc_matrix[i, :]) > 1e-12\n", - "# plot(t_vals, conc_matrix[i, :], label=ssys.sims[1].domain.phase.species[i].name)\n", - "\n", - "# end\n", - "# end\n", - "\n", - "# xscale(\"log\")\n", - "# yscale(\"log\")\n", - "# xlabel(\"Time (s)\")\n", - "# ylabel(\"Reservoir Concentration\")\n", - "# legend()\n", - "# tight_layout()\n", - "# gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "53cf7fe2", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "clf()\n", - "\n", - "for i in 1:size(flux_matrix, 1)\n", - " if abs(maximum(flux_matrix[i, :])) > 1e-12\n", - " plot(t_vals, flux_matrix[i, :], label=ssys.sims[1].domain.phase.species[i].name)\n", - "\n", - " end\n", - "end\n", - "\n", - "xscale(\"log\")\n", - "# yscale(\"log\")\n", - "xlabel(\"Time (s)\")\n", - "ylabel(\"Diffusive Flux (mol/s)\")\n", - "legend()\n", - "tight_layout()\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "a88347b2", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "clf()\n", - "for i in 1:size(conc_matrix_bl, 1)\n", - " if maximum(conc_matrix_bl[i, :]) > 1e-16\n", - " plot(t_vals, conc_matrix_bl[i, :], label=ssys.sims[1].domain.phase.species[i].name)\n", - "\n", - " end\n", - "end\n", - "\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlabel(\"Time (s)\")\n", - "ylabel(\"Boundary Layer Concentrations (mol/m^3)\")\n", - "legend()\n", - "tight_layout()\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "4d4dfc9c", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "25-element Vector{Float64}:\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " -1.1065307558934541e-10\n", - " -2.391819083649919e-10\n", - " 0.0\n", - " 2.456515040239678e-31\n", - " 2.1987305985554648e-27\n", - " 1.4513644535895097e-91\n", - " ⋮\n", - " 1.786626313652337e-57\n", - " 5.282160782532602e-59\n", - " 4.314185572755859e-56\n", - " 5.374985999598471e-58\n", - " 2.9488771690448566e-41\n", - " 6.484884569806172e-70\n", - " 4.38489673445632e-65\n", - " 5.301357962680641e-71\n", - " 3.749885553130054e-81" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "flux_to_reservoir(ssys.sims[1],1e-12,diffusionlayer)" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "782dc215", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 1.568176 seconds (808.83 k allocations: 53.710 MiB, 99.99% compilation time)\n" - ] - }, - { - "data": { - "text/plain": [ - "25-element Vector{Float64}:\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " -0.000305933766239202\n", - " -5.971264518408162e-6\n", - " 0.0\n", - " 6.061356878812117e-11\n", - " 1.994776218890955e-7\n", - " 3.6506732267198526e-28\n", - " ⋮\n", - " 1.8530468439250678e-17\n", - " 1.0892828492137514e-13\n", - " 2.1047306379836483e-17\n", - " 9.40818406475637e-13\n", - " 1.3923059994803368e-12\n", - " 4.236901789426139e-17\n", - " 2.5738223985740063e-30\n", - " 1.7268159892614905e-22\n", - " 1.9462281666180405e-33" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "@time res_cs = get_reservoir_concentration(ssys.sims[1],1e3,diffusionlayer,V_res)" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "e8885c97", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "25-element Vector{Float64}:\n", - " -0.000305933766239202\n", - " -5.971264518408162e-6\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 1.5871699271786366e-53\n", - " 1.9462281666180405e-33\n", - " 2.5738223985740063e-30\n", - " ⋮\n", - " 2.1047306379836483e-17\n", - " 4.236901789426139e-17\n", - " 1.0892828492137514e-13\n", - " 9.40818406475637e-13\n", - " 1.3923059994803368e-12\n", - " 6.061356878812117e-11\n", - " 8.320806506357228e-10\n", - " 2.614714710578341e-8\n", - " 1.994776218890955e-7" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sort(res_cs)" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "9606a8ed", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "25-element Vector{String}:\n", - " \"Ar\"\n", - " \"He\"\n", - " \"Ne\"\n", - " \"N2\"\n", - " \"CO2\"\n", - " \"proton\"\n", - " \"H\"\n", - " \"C=O\"\n", - " \"O=CO\"\n", - " \"O2\"\n", - " ⋮\n", - " \"O=CC=O\"\n", - " \"O=CCO\"\n", - " \"COC=O\"\n", - " \"CC(=O)O\"\n", - " \"CO-2\"\n", - " \"CC=O\"\n", - " \"OCO\"\n", - " \"OCCO\"\n", - " \"C=C\"" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "getfield.(ssys.sims[1].domain.phase.species,:name)" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "9be02a3e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "76-element Vector{String}:\n", - " \"vacantX\"\n", - " \"CO2X\"\n", - " \"CHO2X\"\n", - " \"CO2HX\"\n", - " \"OCX\"\n", - " \"OX\"\n", - " \"CH2O2X\"\n", - " \"CHOX\"\n", - " \"CH2OX\"\n", - " \"HOX\"\n", - " ⋮\n", - " \"CC#[Pt]\"\n", - " \"[Pt]C#CO[Pt]\"\n", - " \"[Pt]OC#CO[Pt]\"\n", - " \"COC=O.[Pt]\"\n", - " \"O=COC[Pt]\"\n", - " \"O=COC=[Pt]\"\n", - " \"O=COC#[Pt]\"\n", - " \"[Pt]C=C=[Pt]\"\n", - " \"[Pt]=CC=[Pt]\"" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "getfield.(ssys.sims[2].domain.phase.species,:name)" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "id": "87dcaf99", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotX (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotX(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = molefractions(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Mole Fraction\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "ddf6da6b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotC (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotC(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = concentrations(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Concentration\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "id": "e719a85d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys.sims[1], 1e-10, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-8, 1e3)\n", - "ylim(1e-16, 5)\n", - "title(\"Liquid-phase Mole Fractions vs. Time on Ag111@-1.0V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "id": "1ef78267", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotC(ssys.sims[1], 1e-12, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-8, 1e3)\n", - "ylim(1e-16, 1e2)\n", - "title(\"Liquid-phase Concentrations vs. Time on Ag111@-1.0V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "id": "a1e338ce", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys.sims[2], 1e-4, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-6, 5)\n", - "title(\"Surface Mole Fractions vs. Time on Ag111@-0.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "id": "1f7d8918", - "metadata": {}, - "outputs": [ - { - "ename": "PythonCall.Core.PyException", - "evalue": "Python: TypeError: cannot use a string pattern on a bytes-like object", - "output_type": "error", - "traceback": [ - "Python: TypeError: cannot use a string pattern on a bytes-like object\n", - "\n", - "Stacktrace:\n", - " [1] pythrow()\n", - " @ PythonCall.Core ~/.julia/packages/PythonCall/L4cjh/src/Core/err.jl:92\n", - " [2] errcheck(val::Ptr{PythonCall.C.PyObject})\n", - " @ PythonCall.Core ~/.julia/packages/PythonCall/L4cjh/src/Core/err.jl:10\n", - " [3] pycallargs(f::PythonCall.Core.Py, args::PythonCall.Core.Py)\n", - " @ PythonCall.Core ~/.julia/packages/PythonCall/L4cjh/src/Core/builtins.jl:220\n", - " [4] pycall(f::PythonCall.Core.Py, args::PythonCall.Core.Py; kwargs::@Kwargs{})\n", - " @ PythonCall.Core ~/.julia/packages/PythonCall/L4cjh/src/Core/builtins.jl:243\n", - " [5] pycall\n", - " @ ~/.julia/packages/PythonCall/L4cjh/src/Core/builtins.jl:233 [inlined]\n", - " [6] Py\n", - " @ ~/.julia/packages/PythonCall/L4cjh/src/Core/Py.jl:357 [inlined]\n", - " [7] makefluxdiagrams(bsol::SystemSimulation{Tuple{Simulation{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Vector{Any}, Vector{String}, ReactionMechanismSimulator.var\"#F#675\"{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Matrix{Float64}, Matrix{Float64}}}, Matrix{Float64}, Vector{Species}, Vector{ElementaryReaction}, Vector{Float64}}, Simulation{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}, Vector{String}, ReactionMechanismSimulator.var\"#F#675\"{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Matrix{Float64}, Matrix{Float64}}}, Matrix{Float64}, Vector{Species}, Vector{ElementaryReaction}, Vector{Float64}}}, ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, Vector{Any}, ElementaryReaction, Species}, ts::Vector{Float64}; centralspecieslist::Vector{String}, superimpose::Bool, maximumnodecount::Int64, maximumedgecount::Int64, concentrationtol::Float64, speciesratetolerance::Float64, maximumnodepenwidth::Float64, maximumedgepenwidth::Float64, radius::Int64, centralreactioncount::Int64, outputdirectory::String, colorscheme::String, removeunconnectednodes::Bool)\n", - " @ ReactionMechanismSimulator ~/RMG-Electrocat/ReactionMechanismSimulator.jl/src/fluxdiagrams.jl:346\n", - " [8] makefluxdiagrams\n", - " @ ~/RMG-Electrocat/ReactionMechanismSimulator.jl/src/fluxdiagrams.jl:139 [inlined]\n", - " [9] getfluxdiagram(bsol::SystemSimulation{Tuple{Simulation{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Vector{Any}, Vector{String}, ReactionMechanismSimulator.var\"#F#675\"{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Matrix{Float64}, Matrix{Float64}}}, Matrix{Float64}, Vector{Species}, Vector{ElementaryReaction}, Vector{Float64}}, Simulation{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}, Vector{String}, ReactionMechanismSimulator.var\"#F#675\"{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Matrix{Float64}, Matrix{Float64}}}, Matrix{Float64}, Vector{Species}, Vector{ElementaryReaction}, Vector{Float64}}}, ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, Vector{Any}, ElementaryReaction, Species}, t::Float64; centralspecieslist::Vector{String}, superimpose::Bool, maximumnodecount::Int64, maximumedgecount::Int64, concentrationtol::Float64, speciesratetolerance::Float64, maximumnodepenwidth::Float64, maximumedgepenwidth::Float64, radius::Int64, centralreactioncount::Int64, outputdirectory::String, colorscheme::String, removeunconnectednodes::Bool)\n", - " @ ReactionMechanismSimulator ~/RMG-Electrocat/ReactionMechanismSimulator.jl/src/fluxdiagrams.jl:85\n", - " [10] top-level scope\n", - " @ ~/Work/CO2_RR_RMG/CO2_Reduction_Ag/jl_notebook_cell_df34fa98e69747e1a8f8a730347b8e2f_X50sdnNjb2RlLXJlbW90ZQ==.jl:1" - ] - } - ], - "source": [ - "getfluxdiagram(ssys,1e3;speciesratetolerance=1e-8)" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "id": "2c73bc58", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotROP (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "function plotROP(ssys,name,t;N=0,tol=0.01)\n", - " clf()\n", - " rop = rops(ssys, name, t)\n", - " inds = rop.nzind[reverse(sortperm(abs.(rop.nzval)))]\n", - " if N == 0\n", - " N = length(inds)\n", - " elseif N > length(inds)\n", - " N = length(inds)\n", - " end\n", - " inds = inds[1:N]\n", - " mval = abs(rop[inds[1]])\n", - " minval = mval*tol\n", - " k = 1\n", - " while k < length(inds) && abs(rop[inds[k]]) >= minval\n", - " k += 1\n", - " end\n", - " inds = inds[1:k]\n", - " net_rops = sum(rop[inds])\n", - " println(\"Net ROPs for species $name is: $net_rops\")\n", - "\n", - " for (i, j) in enumerate(inds)\n", - " println(\"Showing the reaction with $i th highest ROP for species $name:\")\n", - " println(getrxnstr(ssys.reactions[j]))\n", - " println(\"ROP = \", rop[inds[i]])\n", - " println(ssys.reactions[j].kinetics)\n", - " end\n", - "\n", - " xs = Array{Float64,1}(1:length(inds))\n", - " barh(xs,reverse(rop[inds]))\n", - " yticks(xs,reverse(getrxnstr.(ssys.reactions[inds])))\n", - " xlabel(\"Production/Loss Rate mol/s\")\n", - " gcf()\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "id": "61a903c0", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "PrintKinDetail (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "function PrintKinDetail(inter, speciesname)\n", - " println(\"Showing Kinetics details for reactions involving species $speciesname\\n\")\n", - " for (i,rxn) in enumerate(inter.reactions)\n", - " flag = false\n", - " for j = 1:length(rxn.reactants)\n", - " if rxn.reactants[j].name == speciesname\n", - " flag = true\n", - " end\n", - " end\n", - " for j = 1:length(rxn.products)\n", - " if rxn.products[j].name == speciesname\n", - " flag = true\n", - " end\n", - " end\n", - " if flag\n", - " println(getrxnstr(rxn))\n", - " println(rxn.kinetics)\n", - " kf = inter.kfs[i]\n", - " krev = inter.krevs[i]\n", - " kc = kf/krev\n", - " println(\"kf = $kf\")\n", - " println(\"krev = $krev\")\n", - " println(\"Kc = $kc\\n\")\n", - " end\n", - " end\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "id": "ae7ceaad", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "get_boundary_layer_concentration" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "\"\"\"\n", - "Integrates the ROP in the boundary layer and computes the concentration\n", - "\"\"\"\n", - "function get_boundary_layer_concentration(sim,t,spc,Vbl,C_0)\n", - " intg,err = quadgk(x -> sum(rops(sim,spc,t)), 0, t);\n", - " return C_0 + intg ./ Vbl;\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "id": "482a542d", - "metadata": {}, - "outputs": [], - "source": [ - "# Logarithmic time scale\n", - "t_vals = 10 .^ range(-12, stop=3, length=1000);\n", - "\n", - "# Compute ROP over time\n", - "ROP_vals = [sum(rops(ssys, \"O=CO\", t)) for t in t_vals];\n", - "# Compute boundary layer accumulation by integration\n", - "Cbl_vals = [get_boundary_layer_concentration(ssys, t, \"O=CO\", V_bl, C_default) for t in t_vals];" - ] - }, - { - "cell_type": "code", - "execution_count": 41, - "id": "a9b1bfda", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "sys:1: UserWarning: No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n" - ] - }, - { - "data": { - "image/png": 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PbyjC0PRaseVrRfzxHn/e15ariEUR0IkiqjQ6VGl0t/9GjRQC4OPqCH93FfzdHeHr1vA1wNMJId4uCPF2hq+bI0cLiei2GRXs/uzChQtYtWoVTp06BUEQ0KdPHyxcuBDdu3c3d31ENqNGq8PPJwrx7dFcHLx4BfprRuIUAtDT3w19u7gjzNcFoT6uCPJyho+bAzo5O0BlL58lgqyR2BQcxT/CIdAyJIoAREPrUKg3iKir16O2catr3Gq1hhaPa7R6VNbVQ11bj4paXcPXxsfq2npU1ulgEIHiSg2KKzU4nnf9Wp3slQj2dkZ3X1f0DXBH3wB39OviDj93VbudLyKyXSYHu507d2LixImIjo7G8OHDIYoiUlJS0K9fP/z444+Ii4uzRJ1EVutCSRU+2ZeFrWl5qNb+cY1pT39XjO7th5HhvogO8oSr4239HUVmIAgClI0jnVLR6Q24Uq1FUYUGRRV1KK5s+FpUUYe88lpcKqtG3tVa1NbrcbqwEqcLK7H9eEHz631cHTEgyBNDQ70wNNQbfQPc2dYlolZMXu5kwIABGDduHF5//fUW+5cuXYpdu3bh6NGjZi1QalzuhG4kPaccq3efx6+ni5rbfUFezngopiseiA5EkLeztAWSzdHqDMi9WoNLZdU4V1SFzIIKnMyvwMWSKvz5Ukw3RzvEhnsjrm9n3N3bD14uDtIUTUQmsXSuMDnYqVQqHD9+HD169Gix/+zZs+jfvz/q6urMWqDUGOzoz84WVeKtnWewK7Ooed+YPn54fEQohoV58/ooMrtarR6ZBRU4cukKDmVdwe9ZV1B5zTV/CgEYHOKFKQO7Ynz/LhwdJrJiVrGO3bV8fX2Rnp7eKtilp6fDz8/PbIURWZvyGi3e3HkGXxzOhig2/DJ9cEBX/P2u7gj3c5W6PJIxJwclYoI7ISa4E/42qjv0BhEn89X45VQxfsksQmZBBQ5lNYS+l344ifjIznhsWAiiu3lKXToRtTOTg93cuXMxb948XLx4EbGxsRAEAfv27cMbb7yBp59+2hI1EknKYBDxTWouXv/5NK5UawEA9/brjKfH9kQPfzeJq6OOSKkQ0L+rJ/p39cTiuJ7IvVqDH47l45sjubhYWo3vjubhu6N5GBLihXl3huHu3n5Q8Ho8og7B5FasKIpYtWoV3n77beTn5wMAAgIC8Mwzz2DBggWya0OxFduxXS6rxpKvj+H3S1cBNEyIeHVSBIaGeUtcGVFroijiaHY5Nh26jB+P5aNe3/DPe/+uHlga3xux3X0krpCIrO4au2tVVlYCANzc5DtqwWDXMYmiiE2HsrFixynUaPVwdlBi0ZgemDU8FPZKhdTlEd1SoboOG1Ky8N8Dl5tna4/q6YuXJ/ZDqI+LxNURdVxWHew6Aga7jqe4sg5Lvs5A0tkSAMDQUC+89ZcodPPiLFeyPaVVGvz713PYdCgbOoMIRzsFFo3pibkjQ2HHP1KI2p3VBbuysjK8+OKL2LNnD4qLi2FoWia+0ZUrV8xaoNQY7DqWAxfK8OQXaSit0sDRToFn7+2NWbEhvD6JbN6l0mq88P0JJJ8rBQBEBLrjX/8zAN19OfGHqD1ZXbCLj4/HhQsXMHv2bPj7+7e6pm7GjBlmLVBqDHYdg8Eg4oO9F/D2rjMwiEAvfze8P20Awv3ke5kBdTyiKOLbo3l4dVsm1LX1cHFQYsXkSEyKDpS6NKIOw+qCnZubG/bt24eoqCizF2ONGOzkr7xGi6c2p2PPmYbW60MxXfHqpAg4OfA2XyRPxRV1WPBlGg5ebOiwPD48FM/f14d3siBqB5bOFSZfYNG7d2/U1t78huZEtuJCSRUeXJOCPWdK4GinwJtT+uOtv0Qx1JGs+bmrsGnOHVhwdzgA4JP9WUj4bypqtLpbvJKIrJ3JwW7NmjV4/vnnsXfvXpSVlaGioqLFRmQrks+V4MH39yOrtBqBnk74bn4sHh7cTeqyiNqFUiFg8dhe+PcjA+Bgp0BiZhGmrT+Eirp6qUsjojYweYFiT09PqNVq3H333S32i6IIQRCg1+tv8Eoi6/GfA5fw8o+Z0BtExAR3wtrpMfBxdZS6LKJ2NyEqAF08VJj96RGkZZdj+seH8dnjQ+DhZC91aUR0G0wOdtOmTYODgwM+//zz606esDY5OTmYPn06iouLYWdnhxdeeAF/+ctfpC6LJGIwiFix4xTW78sCAEweEIgVkyOhsmfrlTquQSFe+HzuUExbfwjHcsrx2MeHsGnuHbznLJENMnnyhLOzM9LS0tCrVy9L1WRWBQUFKCoqQnR0NIqLizFw4ECcOXMGLi7GLdDJyRPyodUZ8Ow3x7A1veGOKc+M64X5d3W3+j9OiNpLZn4Fpq0/iKs19RjV0xfrZwzigtxEZmZ1kycGDRqEnJwcsxdiKV26dEF0dDQAwM/PD15eXrJba49urVqjw5zPjmBrej6UCgFv/yUK/xgdzlBHdI2+Ae7YMGsIVPYK7D1bghe2ngDXsCeyLSYHuyeffBILFy7Exo0bkZqaioyMjBabqZKSkjBhwgQEBARAEARs3bq11TFr1qxBaGgoVCoVYmJikJycbPLnAMCRI0dgMBjQrRsvkO9IrlRr8ej6Q0g6WwIneyXWPzYIU2K6Sl0WkVWK7uaJfz8yEAoB+PL3HHzceNkCEdkGky+gmDp1KgDg8ccfb94nCMJtT56orq5GVFQUZs2ahSlTprR6fvPmzVi0aBHWrFmD4cOHY+3atYiPj0dmZiaCgoIAADExMdBoNK1eu2vXLgQEBABouGPGY489hvXr15tUH9m2QnUdpq0/iAsl1fB0tscnMwdjYFAnqcsismpxff3xwv198cqPmVj502lEdfPE4BAvqcsiIiOYfI3d5cuXb/p8cHDw7RcjCNiyZQseeOCB5n1Dhw7FwIED8cEHHzTv69OnDx544AGsXLnSqPfVaDSIi4vD3LlzMX369Fsee21IrKioQLdu3XiNnQ3KK6/Fox8dxOWyGgR4qPDZ7CG8kwSRkURRxMIv0/HDsXz4uzti+4KRnDlOZAaWvsbO5BG7tgQ3U2m1WqSmpmLp0qUt9o8dOxYpKSlGvYcoipg5cybuvvvuW4Y6AFi5ciVeeeWV26qXrEfOlRo88tFB5F6tRTcvJ3w+5w5083KWuiwimyEIAlZOjkRmQQXOF1dhydfHsGHmYF6XSmTljLrG7sCBA0a/YXV1NU6ePHnbBV2rtLQUer0e/v7+Lfb7+/ujsLDQqPfYv38/Nm/ejK1btyI6OhrR0dE4fvz4DY9ftmwZ1Gp182ZLE0WowaXSakxdewC5V2sR4u2MzfOGMdQR3QYXRzusmTYQDnYK/HamBF+n5kpdEhHdglHB7rHHHkNcXBy++uorVFVVXfeYzMxMPPfccwgPD8fRo0fNWuSf/0Jsup7PGCNGjIDBYEB6enrzFhkZecPjHR0d4e7u3mIj23GxpApT1x1AvroOYb4u2Py3YQjwdJK6LCKb1dPfDU/H9QQAvPpjJgrUvKUkkTUzKthlZmZi0qRJePHFF9GpUyf069cPcXFxmDBhAkaMGAEfHx/ExMTg8uXLSExMNKrlaQwfHx8olcpWo3PFxcWtRvGIcq7U4NGPDqGoQoOe/q7YPG8Y/N1VUpdFZPPmjAxDdDdPVGp0WPbdcS6BQmTFjAp29vb2eOKJJ3D69GkcOnQI8+bNQ0REBAIDA3HXXXdh7dq1yMvLw6ZNmxAREWG24hwcHBATE4PExMQW+xMTExEbG2u2zyHbV6CuxaPrD6Kwog49/Fzxxdw74OvGC72JzEGpEPDWX/rDQdnQkt2VWSR1SUR0AyZPnhg4cCAGDhxotgKqqqpw/vz55sdZWVlIT0+Hl5cXgoKCsHjxYkyfPh2DBg3CsGHDsG7dOmRnZyMhIcFsNZBtK6nUYNr6Q8i5Uotgb2dsmjMU3py9R2RW4X5umDMyFGt+u4DXtp/CqJ6+vBUfkRWS/EaAR44cwejRo5sfL168GAAwY8YMbNy4EVOnTkVZWRmWL1+OgoICREREYMeOHe06O5esV3mNFtM/PoSLJdUI8FBh05yh8GP7lcgi/jE6HN8ezUX2lRp8vC8L/xgdLnVJRPQnJq9j19HwXrHWq0qjw7SPDuJYrhq+bo746m/DEOpj3D2Aiej2bEnLxVObj8HZQYk9S+7idaxEJrK6e8USWYN6vQF//28qjuWq0cnZHpvmDGWoI2oHD0QHYkCQJ2q0eqzZc/7WLyCidsVgRzZHFEX877cZSD5XCid7JTbMGoKe/ryjBFF7EAQBz4ztBQD44nAO8su5/AmRNTFLsCsvLzfH2xAZ5f/tPIPvjuZBqRCwZtpARHfzlLokog5lWHdvDA31glZvwJrfOGpHZE1MDnZvvPEGNm/e3Pz44Ycfhre3NwIDA3Hs2DGzFkf0Z58duIQ1v10AAKx8MBKje/tJXBFRxyMIAp5qXLR48+85yOOoHZHVMDnYrV27Ft26dQPQsJ5cYmIifvrpJ8THx+OZZ54xe4FETX4+UYiXfmi4Xd3iuJ54eHA3iSsi6rjuCPPGsDBv1OtFfNj4xxYRSc/kYFdQUNAc7LZt24aHH34YY8eOxbPPPovff//d7AUSAcCJPDUWbU6DKAKPDAnCk3dzmQUiqT15T8PP4depObharZW4GiICbiPYderUCTk5OQCAn3/+GWPGjAHQcEG7Xq83b3VEAIor6jD3syOoqzfgzp6+eHVSP6PvFUxEljMszBv9AtxRV2/ApkOXpS6HiHAbwW7y5Ml49NFHERcXh7KyMsTHxwMA0tPTER7OURQyr7p6Peb9JxUF6jp093XB6kcHwE7JydxE1kAQBMwZGQoA+PTAZWh0/OOeSGom/4Z899138cQTT6Bv375ITEyEq6srgIYW7fz5881eIHVcoihi2XfHkZ5TDg8ne6yfMRjuKnupyyKia9zfPwCd3VUoqdRge0aB1OUQdXi888Qt8M4T0vlw7wW8/tNpKBUC/vP4EMSG+0hdEhFdx79/PYe3E89iUHAnfPP3WKnLIbJqVnfniU8//RTbt29vfvzss8/C09MTsbGxuHyZ11iQeew/X4o3fz4NAHh5Ql+GOiIrNnVwNygVAo5cvoozhZVSl0PUoZkc7FasWAEnJycAwIEDB7B69Wq8+eab8PHxwVNPPWX2AqnjKVTXYcEXaTCIwMODumL6sBCpSyKim/BzVyGujz8A4HNOoiCSlMnBLicnp3mSxNatW/HQQw9h3rx5WLlyJZKTk81eIHUs9XoD/vH5UZRVa9G3izuWT4qQuiQiMsK0O4IAAN+l5aFWy0kURFIxOdi5urqirKwMALBr167m5U5UKhVqa7n6OLXNyh2nkXr5KtxUdvjgrwOhsldKXRIRGWF4dx907eSEyjodEk8VSV0OUYdlcrCLi4vDnDlzMGfOHJw9exb33XcfAODkyZMICQkxd33Ugew8WYhP9mcBAN7+SxSCvV0kroiIjKVQCHhwQCAAYMvRXImrIeq4TA5277//PoYNG4aSkhJ8++238Pb2BgCkpqbikUceMXuB1DEUVdRh6bcZAIB5d4ZhbL/OEldERKZqCnZJ50pRUqmRuBqijonLndwClzuxPINBxIwNh5F8rhQRge747u/D4WDHRYiJbNGk9/fjWE45Xry/Lx4fESp1OURWx+qWOwGA5ORk/PWvf0VsbCzy8vIAAP/5z3+wb98+sxZHHcMn+7OQfK4UKnsFVk0dwFBHZMMmN47afZ+eJ3ElRB2Tyb9Bv/32W4wbNw5OTk44evQoNJqG4fbKykqsWLHC7AWSvGXmV+DNn88AAP55X1+E+7lKXBERtcX4yC5QCMCxXDVyr9ZIXQ5Rh2NysPu///s/fPjhh/joo49gb//H7Z1iY2Nx9OhRsxZH8qbVGbD4q3Ro9QaM6eOHaUODpC6JiNrI180RQ0K9AAA/nyiUuBqijsfkYHfmzBnceeedrfa7u7ujvLzcHDVRB/HBbxdwurASXi4OeH1KfwiCIHVJRGQG4yO7AAB2HOe9Y4nam8nBrkuXLjh//nyr/fv27UNYWJhZiiL5O1NYidV7zgEAXprQFz6ujhJXRETmMq5fZwgCcDS7HAVqrm9K1J5MDnZ/+9vfsHDhQhw6dAiCICA/Px+bNm3CkiVLMH/+fEvUSDKjN4h49tsM1OtFjOnjh4lRAVKXRERm5O+uwqDgTgDYjiVqb3amvuDZZ5+FWq3G6NGjUVdXhzvvvBOOjo5YsmQJnnjiCUvUSDKzYX8WjuWUw01lh/97IJItWCIZGtevM36/dBW7Txdj1nAue0LUXkwasdPr9di7dy+efvpplJaW4vDhwzh48CBKSkrw6quvWqpGkpGiijq8m3gWAPDc+D7o7KGSuCIisoS7e/sBAA5eLEOVRidxNUQdh0nBTqlUYty4cVCr1XB2dsagQYMwZMgQuLpyiQoyzmvbT6Faq8eAIE9MHdRN6nKIyELCfF0R6uOCer2IfedKpC6HqMMw+Rq7yMhIXLx40RK1kMylXCjFD8fyoRCAVydFQKFgC5ZIzppG7X49VSxxJUQdh8nB7rXXXsOSJUuwbds2FBQUoKKiosVGdD31egNe+v4kAOCvdwQjItBD4oqIyNLuaQx2e84Uw2Dg3SuJ2oPJkyfuvfdeAMDEiRNbXPQuiiIEQYBerzdfdSQbnx24jHPFVfB2ccDTcb2kLoeI2sGgEC+4OdqhtEqL43lqRHXzlLokItkzOdjt2bPHEnWQjKlr6/Hv3Q1r1j0zrhc8nO1v8QoikgMHOwWGdffGrswi7DtfymBH1A5MDnajRo2yRB0kY2v2nEd5TT16+rviL5wwQdShjOjh0xDszpXiH6PDpS6HSPZMDnYZGRnX3S8IAlQqFYKCguDoyLsIUIPcqzXYkHIJALAsvg+UnDBB1KGMCPcBAKRevoparR5ODkqJKyKSN5ODXXR09E0XlLW3t8fUqVOxdu1aqFRco6yje3vXWWh1BsR298ZdvXylLoeI2lmojwsCPFTIV9fh8KUrGNWT/w4QWZLJs2K3bNmCHj16YN26dUhPT0daWhrWrVuHXr164fPPP8fHH3+M3bt345///Kcl6iUbcjJfjS1peQAaRut4hwmijkcQBIzo0TBqx/XsiCzP5BG71157Df/6178wbty45n39+/dH165d8cILL+Dw4cNwcXHB008/jbfeesusxZJteTexYcLExKgARHbl8iZEHdXwcB98dSQXyedKpS6FSPZMHrE7fvw4goODW+0PDg7G8ePHATS0awsKCtpeHdms47lq/HKqCAoBWDimh9TlEJGEhjdeZ3e6sBLlNVqJqyGSN5ODXe/evfH6669Dq/3jh7O+vh6vv/46evfuDQDIy8uDv7+/+aokm7Pql4b7wU6KDkR3X95yjqgj83F1RHdfFwDA75euSlwNkbyZ3Ip9//33MXHiRHTt2hX9+/eHIAjIyMiAXq/Htm3bAAAXL17E/PnzzV4s2YZjOeX49XQxFALw5N1c3oCIgCGh3rhQUo3DWWWI68s//IksxeRgFxsbi0uXLuG///0vzp49C1EU8dBDD+HRRx+Fm5sbAGD69OlmL5Rsx79+bbi27oEBgQjjaB0RARga6oUvDmfjcNYVqUshkjWTgx0AuLq6IiEhwdy1kAycyFNj9+liKBUCFtzNa+uIqMGQUC8AwIn8ClRpdHB1vK1fP0R0CyZfYwcAFy5cwJNPPokxY8YgLi4OCxcuxIULF8xdG9mgD/Y2/H8wMSoAIT4uEldDRNYiwNMJXTs5QW8QcfQyr7MjshSTg93OnTvRt29fHD58GP3790dERAQOHjyIfv36ITEx0RI1ko24XFaNn443zIb+26gwiashImvTNGrHdiyR5Zg8Fr506VI89dRTeP3111vt/9///V/ExcWZrTiyLR8lX4RBBO7q5Yvend2lLoeIrMzgEC98dzQPqRyxI7IYk0fsTp06hdmzZ7fa//jjjyMzM9MsRZHtKa3S4OsjuQCAhFHdJa6GiKzRwKBOAIBjueXQG0SJqyGSJ5ODna+vL9LT01vtT09Ph5+fnzlqIhv0acolaHQGRHXzxNDGdgsR0bXC/Vzh6miHGq0eZ4sqpS6HSJZMbsXOnTsX8+bNw8WLFxEbGwtBELBv3z688cYbePrppy1RI1m5Gq0Onx24DAD4+6gw3hOWiK5LqRAQ1c0D+8+XIS27HH268JINInMzOdi98MILcHNzw9tvv41ly5YBAAICAvDyyy9jwYIFZi+QrN+WtDyoa+sR7O2MuL6dpS6HiKzYgG6dGoPdVTw6NEjqcohkx6Rgp9PpsGnTJjzyyCN46qmnUFnZMJTetDAxdTyiKOLTlEsAgOl3BEOp4GgdEd3YgCBPAEBaTrmkdRDJlUnX2NnZ2eHvf/87NBoNgIZAx1DXsR24WIazRVVwdlDiL4O6SV0OEVm56G6eAIDzxVVQ19ZLWwyRDJk8eWLo0KFIS0uzRC1kgzbuvwQAmDwwEB5O9tIWQ0RWz9vVEcHezgCAdI7aEZmdydfYzZ8/H08//TRyc3MRExMDF5eWdxfo37+/2Yoj65Z7tQa/nCoCAMwYFiJtMURkM6K6euJyWQ1O5Kkxqqev1OUQyYrJwW7q1KkA0GKihCAIEEURgiBAr9ebrzqyav85eBkGERge7o0e/mzJE5FxIgLd8cOxfJzIU0tdCpHsmBzssrKyLFEH2Zi6ej02/54DgKN1RGSaiAAPAMCJfAY7InMzKdhVVlbi7NmzqK+vx5AhQ+Dj42OpusjK/ZCej/KaenTt5IR7+vhLXQ4R2ZB+gQ3BLudKLdQ19fBw5vW5ROZi9OSJjIwM9O7dG/feey/uv/9+hIeH45dffrFkbWTFNh3OBgD8lUucEJGJPJzsEeTVMIHiJEftiMzK6GC3dOlSBAUFITk5GUeOHMGoUaPwxBNPWLI2slKZ+RU4llMOe6WAh2K6Sl0OEdmgiMCGu06wHUtkXka3Yo8cOYIdO3Zg0KBBAIBPPvkEfn5+qKqqgqurq8UKJOvz5e8No3Vj+3aGj6ujxNUQkS3qF+CBHccLcSKvQupSiGTF6BG70tJSBAX9cfsXb29vODs7o6SkxCKFkXWq1eqxJS0PAPA/Q7ggMRHdnohATqAgsgSjR+wEQUBlZSVUKhUANC9vUllZiYqKP/7icnfnTZ3lbPvxAlTW6dDNywnDu3PyDBHdnn4BDb8rskqrUaXRwdXR5EUaiOg6jP5JEkURPXv2bLVvwIABzf/Ndezk78vGSRP/MzgICk6aIKLb5OPqiC4eKhSo63CqoAKDQ7ykLolIFowOdnv27LFkHWQDzhZV4sjlq1AqBPyFkyaIqI36BXigQF2HE3lqBjsiMzE62I0aNcqSdZAN+PJww4LE9/T2g5+7SuJqiMjWRQS645dTRZxAQWRGRk+eoI5No9Pju7RcAMAjQ4JucTQR0a316dJwnd2ZIgY7InNhsCOj7D5VjPKaevi7O+JO3rSbiMygV+M9ps8VVUFvECWuhkgeGOzIKN8ebRite3BAV95pgojMIsjLGSp7BTQ6Ay6XVUtdDpEsGBXsMjIyYDAYLF2LRdXU1CA4OBhLliyRuhSbU1KpwZ4zDesVPhQTKHE1RCQXCoWAno2jdmcKKyWuhkgejAp2AwYMQGlpKQAgLCwMZWVlFi3KEl577TUMHTpU6jJs0vfpedAbRER180S4n5vU5RCRjDS1Y88UMdgRmYNRwc7T0xNZWVkAgEuXLtnc6N25c+dw+vRpjB8/XupSbNK3RxvuNPHQQI7WEZF59erMETsiczIq2E2ZMgWjRo1CaGgoBEHAoEGDEBYWdt3NVElJSZgwYQICAgIgCAK2bt3a6pg1a9YgNDQUKpUKMTExSE5ONukzlixZgpUrV5pcGwEn89U4VVABB6UCE6ICpC6HiGSmOdhxxI7ILIxax27dunWYPHkyzp8/jwULFmDu3LlwczNPS666uhpRUVGYNWsWpkyZ0ur5zZs3Y9GiRVizZg2GDx+OtWvXIj4+HpmZmc33ro2JiYFGo2n12l27duH3339Hz5490bNnT6SkpNyyHo1G0+K9rr1dWkf0bWrDaN2Yvn7wdHaQuBoikpumVuyl0mrU1euhsldKXBGRbTN6geJ7770XAJCamoqFCxeaLdjFx8cjPj7+hs+/8847mD17NubMmQMAWLVqFXbu3IkPPvigeRQuNTX1hq8/ePAgvvzyS3z99deoqqpCfX093N3d8eKLL173+JUrV+KVV15pw3ckH/V6A75Pb2zD8k4TRGQBvm6O6ORsj6s19ThfXIWIQA+pSyKyaSYvd7Jhw4bmUJebm4u8vDyzF9VEq9UiNTUVY8eObbF/7NixRo2+AQ1BLScnB5cuXcJbb72FuXPn3jDUAcCyZcugVqubt5ycnDZ9D7bstzMlKKvWwsfVEXf24Np1RGR+gsCZsUTmZHKwMxgMWL58OTw8PBAcHIygoCB4enri1VdfNfukitLSUuj1evj7+7fY7+/vj8LCQrN+VhNHR0e4u7u32Dqqb1Mb1q57IDoAdkoueUhEltG78Tq7s7zOjqjNjG7FNnn++efx8ccf4/XXX8fw4cMhiiL279+Pl19+GXV1dXjttdfMXqQgtFwQVxTFVvuMMXPmTDNVJH/qmnrsPl0MAJjCNiwRWVDPxmB3miN2RG1mcrD79NNPsX79ekycOLF5X1RUFAIDAzF//nyzBjsfHx8olcpWo3PFxcWtRvHIvHacKIBWb0Dvzm7N93MkIrKE3lzyhMhsTO6vXblyBb179261v3fv3rhy5YpZimri4OCAmJgYJCYmttifmJiI2NhYs34WtdQ0aWJSNNeuIyLLalr4vLCiDpV19RJXQ2TbTA52UVFRWL16dav9q1evRlRUlMkFVFVVIT09Henp6QCArKwspKenIzs7GwCwePFirF+/Hp988glOnTqFp556CtnZ2UhISDD5s8g4BepaHMpqCOkTo7l2HRFZloeTPXzdHAEAF0p4z1iitjC5Ffvmm2/ivvvuwy+//IJhw4ZBEASkpKQgJycHO3bsMLmAI0eOYPTo0c2PFy9eDACYMWMGNm7ciKlTp6KsrAzLly9HQUEBIiIisGPHDgQHB5v8WWScH4/lQxSBISFeCPR0krocIuoAwn1dUVKpwYXiKkR385S6HCKbZXKwGzVqFM6ePYv3338fp0+fhiiKmDx5MubPn4+AANNHd+666y6IonjTY+bPn4/58+eb/N50e7am5QMAJg3gaB0RtY9wP1ccuFiG8yVVUpdCZNNMDnYAEBAQYJHZryS9c0WVyCyogL1SwPiILlKXQ0QdRHdfFwDA+WIGO6K24OJk1ML36Q2jdaN6+qKTC28hRkTto2kCxQWO2BG1CYMdNRNFEd8f42xYImp/4X6uAIDLZTXQ6sy72D1RR8JgR82OZpcj50otXByUGNOH6wQSUfvxd3eEq6Md9AYRl8s4M5bodjHYUbOmtevG9esMJwelxNUQUUciCELzdXZsxxLdvtsKdjqdDr/88gvWrl2LysqGlcLz8/NRVcUfRltVrzdge0YBAK5dR0TS6N7YjuUECqLbZ/Ks2MuXL+Pee+9FdnY2NBoN4uLi4ObmhjfffBN1dXX48MMPLVEnWdi+86Uoq9bCx9UBI8J9pC6HiDqg7r4MdkRtZfKI3cKFCzFo0CBcvXoVTk5/LF774IMP4tdffzVrcdR+fmicDXt//wDYKdmhJ6L21zSBgnefILp9Jo/Y7du3D/v374eDQ8ulMIKDg5GXl2e2wqj91Gr12HmyEADbsEQknT+CXRUMBhEKhSBxRUS2x+ShGYPBAL1e32p/bm4u3NzczFIUta89Z4pRo9Wjm5cTBvBWPkQkkSAvZ9gpBNRo9SioqJO6HCKbZHKwi4uLw6pVq5ofC4KAqqoqvPTSSxg/frw5a6N20jRpYnxkFwgC/0ImImnYKxUI8WmcGcvr7Ihui8nB7t1338XevXvRt29f1NXV4dFHH0VISAjy8vLwxhtvWKJGsqBarR67TxcDAO6PZBuWiKQVzgkURG1i8jV2AQEBSE9Px5dffonU1FQYDAbMnj0b06ZNazGZgmzDnjPFqK1vaMNGBLpLXQ4RdXDd/VyAk8B5rmVHdFtMDnZJSUmIjY3FrFmzMGvWrOb9Op0OSUlJuPPOO81aIFkW27BEZE2aJ1BwxI7otpjcih09ejSuXLnSar9arcbo0aPNUhS1D7ZhicjahPs2TMLj3SeIbo/JwU4UxeuO7JSVlcHFxcUsRVH7YBuWiKxNWONtxUqrtCiv0UpcDZHtMboVO3nyZAANs2BnzpwJR0fH5uf0ej0yMjIQGxtr/grJYtiGJSJr4+JohwAPFfLVdbhQUoWYYC+pSyKyKUYHOw8PDwANI3Zubm4tJko4ODjgjjvuwNy5c81fIVkE27BEZK26+7kiX12Hc0UMdkSmMjrYbdiwAQAQEhKCJUuWsO1q49iGJSJr1cPPDcnnSnGOEyiITGbyrNiXXnrJEnVQO2MbloisVU//hpmxZ4sqJa6EyPaYHOwA4JtvvsFXX32F7OxsaLUtL249evSoWQojy6nR6tiGJSKr1aMx2J0r4ogdkalMnhX73nvvYdasWfDz80NaWhqGDBkCb29vXLx4EfHx8Zaokcxsz+kStmGJyGqF+zUseVJYUQd1bb3E1RDZFpOD3Zo1a7Bu3TqsXr0aDg4OePbZZ5GYmIgFCxZArVZbokYysx3H2YYlIuvl4WSPzu4qALy1GJGpTA522dnZzcuaODk5obKy4RqI6dOn44svvjBvdWR2bMMSkS34ox3L6+yITGFysOvcuTPKysoAAMHBwTh48CAAICsrC6Iomrc6Mju2YYnIFvRobMee5XV2RCYxOdjdfffd+PHHHwEAs2fPxlNPPYW4uDhMnToVDz74oNkLJPNqasPeFxnANiwRWa2mmbHnijliR2QKk2fFrlu3DgaDAQCQkJAALy8v7Nu3DxMmTEBCQoLZCyTzubYNe19kF4mrISK6sR7+TSN2DHZEpjA52CkUCigUfwz0Pfzww3j44YcBAHl5eQgMDDRfdWRWbMMSka1ousauqEIDdU09PJztJa6IyDaY3Iq9nsLCQjz55JMIDw83x9uRhbANS0S2wl1lj0DPhltXZhZUSFwNke0wOtiVl5dj2rRp8PX1RUBAAN577z0YDAa8+OKLCAsLw8GDB/HJJ59YslZqgxqtDr+eLgLANiwR2YamzsKJPC6lRWQso1uxzz33HJKSkjBjxgz8/PPPeOqpp/Dzzz+jrq4OP/30E0aNGmXJOqmN9pwuQV29gW1YIrIZkYEe2HmyCCfyGeyIjGV0sNu+fTs2bNiAMWPGYP78+QgPD0fPnj2xatUqC5ZH5sI2LBHZmohADwDAcY7YERnN6FZsfn4++vbtCwAICwuDSqXCnDlzLFYYmQ/bsERki5qCXVZpNao0OomrIbINRgc7g8EAe/s/ZiUplUq4uLhYpCgyL7ZhicgW+bg6oouHCqLI6+yIjGV0K1YURcycOROOjo4AgLq6OiQkJLQKd9999515K6Q2YxuWiGzVwOBO2J5RgEMXr+COMG+pyyGyekYHuxkzZrR4/Ne//tXsxZD5sQ1LRLZsWJg3tmcU4MDFUixED6nLIbJ6Rge7DRs2WLIOshC2YYnIlsV2bxilO5pdjrp6PVT2SokrIrJuZlmgmKwX27BEZMtCfVzg7+4Irc6Ao5evSl0OkdVjsJMxtmGJyNYJgoAR4b4AgJ9PFkpcDZH1Y7CTsaY2bJCXM9uwRGSzJkUHAAB+OJYPjU4vcTVE1o3BTsa2H88HAIyP7MI2LBHZrOHhPujsrkJ5TT12nyqWuhwiq8ZgJ1M1Wh12n274B5BtWCKyZUqFgMkDAwEAa367AINBlLgiIuvFYCdTbMMSkZw8PiIUro52OJ6nxnu7z0ldDpHVYrCTKbZhiUhOfFwd8cL9fQAAq345hzmfHsHu00XNtxsTRY7iEQEmrGNHtoNtWCKSo6mDg3C1ph5v7TyDX04V4ZdTRS2et1MIsFcqYKcUYKcQYKdUwE4hQKkQrvmqaPiqbHhs/6fH1x5nrxSgsldesykavto1fHVyUMLRruGrm8oO7ip7uKvs4O5kD0c7Bf+oJkkw2MkQ27BEJFcJo7pjdC8/bEy5hEMXy1BUUYdqbcNMWZ1BhM6gB+olLhKAvVKAu8oebio7eDjZw8fVEb5u12yujvBxc4S/mwpdPFWwV7KBRubBYCdDbMMSkZz16uyGlZMjmx9Xa3SorddDpxdRrzegXm+A3iBCZxCv+WqATv/HY92fHrc4rvGxpt6Auno96nR61DX+d229vtX+Gq0elXX1qKitR6VGB1EE6vUiyqq1KKvW3vL7USoEdPFQIcjLGUFezujm5YwwHxf07uKOIC9nKBX8d5yMx2AnM2zDElFH4+JoBxdH6/h1ZjCIqNbqUFmnQ0VdPSrrdCivqUdplQYllX9spVUalFRpUKiug0ZnQO7VWuRerUXKhbIW76eyV6CXvxt6d3ZH3wB3xAR3Qu/ObrDjCB/dgHX8JJDZ7D5dzDYsEZFEFAoBbip7uKnsEQCnWx5vMIgoqdIg+0oNsstqGr5eqcH54iqcLapEXb0Bx3LVOJarbn6Ni4MS0UGeiAn2Qmx3b8QEd2Irl5ox2MlM071h2YYlIrJ+CoUAf3cV/N1VGBzi1eI5vUHEpbJqnC6oxOnCChzLVSPt8lVUanTYf74M+8+X4b1fz8HN0Q4jevjgrl6+uKePP3xcHSX6bsgaMNjJCNuwRETyoVQI6O7riu6+rrivf8O/6XqDiLNFlThy+Sp+z7qCfedLcaVai59OFOKnE4VQCMcxPNwHE6ICMK5fZ3g42Uv8XVB7E0Qu/nNTFRUV8PDwgFqthru7dbc2t2Xk44nP0xDk5Yy9z9zFETsiIpnTG0Rk5JbjtzMl2H26GMfz/mjZOigViOvnj78ODcYdYV78nWAlLJ0rOGInI2zDEhF1LEqFgAFBnTAgqBOeiuuJS6XV+PFYPn44lo9zxVXYnlGA7RkFCPdzxfQ7gvGXQV3h7MBf/XLGEbtbsJURuxqtDgNfTURdvQHbnhyBiEAPqUsiIiKJiKKIk/kV+PxwNram5aGmca0/LxcHPD48BNOHhbBNKxFL5wpOo5GJa2fD9guw3gBKRESWJwgCIgI9sOLBSBx87h68MrEfgryccaVai7d2ncXw13fjncSzqNLopC6VzIzBTibYhiUioutxV9ljRmwIdj89Cv/6n2j08ndDlUaH9349h7v+3x7858Al1OsNUpdJZsJgJwPXzoa9vz9nwxIRUWt2SgUmRQfip4UjsWbaQIR4O6O0SosXvj+Jce8mYd+5UqlLJDNgsJMBtmGJiMhYCoWA8ZFdkLh4FJZP6gdvFwdcLK3GXz8+hAVfpKG4sk7qEqkNGOxkgG1YIiIylb1SgceGhWDPM3dhZmwIFALww7F83PP2Xnx5OBucW2mbGOxsHNuwRETUFu4qe7w8sR++/8cIRHX1QGWdDku/O47Znx5BcQVH72wNg52NYxuWiIjMIbKrB76bPxzPj+8DBzsFdp8uxthVSdieUSB1aWQCBjsbxzYsERGZi1IhYO6dYY3robqjvKYe//j8KJ7fchx19XqpyyMjMNjZMLZhiYjIEnr6u2HL/OF4YnQ4BAHYdCgbD65JQVZptdSl0S0w2NkwtmGJiMhS7JUKLBnXC589PgTeLg44VVCB+99Lxo/H8qUujW6Cwc6GsQ1LRESWNrKHL3YsHImhoV6o1urx5BdpWPnTKegNnDVrjTpEsMvKysLo0aPRt29fREZGorra9oeS2YYlIqL24u+uwqY5Q/H3u7oDANbuvYjHN/4OdW29xJXRn3WIYDdz5kwsX74cmZmZ2Lt3LxwdHaUuqc3YhiUiovZkp1Tgf+/tjX8/MgAqewX2ni3BA+/vx/niKqlLo2vIPtidPHkS9vb2GDlyJADAy8sLdnZ2ElfVdk3Tz+/rzzYsERG1nwlRAfgmIRaBnk7IKq3Gg+/vx+7TRVKXRY0kD3ZJSUmYMGECAgICIAgCtm7d2uqYNWvWIDQ0FCqVCjExMUhOTjb6/c+dOwdXV1dMnDgRAwcOxIoVK8xYvTRqtDrsOdPQhr0vkm1YIiJqXxGBHvj+ieEYEuKFSo0Osz89gnVJF3i3CisgebCrrq5GVFQUVq9efd3nN2/ejEWLFuH5559HWloaRo4cifj4eGRnZzcfExMTg4iIiFZbfn4+6uvrkZycjPfffx8HDhxAYmIiEhMTb1iPRqNBRUVFi83asA1LRERS83F1xH/nDMUjQ4IgisCKHaex5OsMaHRc705Kkvck4+PjER8ff8Pn33nnHcyePRtz5swBAKxatQo7d+7EBx98gJUrVwIAUlNTb/j6rl27YvDgwejWrRsAYPz48UhPT0dcXNx1j1+5ciVeeeWV2/122gXbsEREZA0c7BRY8WAEend2w/Jtmfj2aC4ulVXjw7/GwNfN9q9nt0WSj9jdjFarRWpqKsaOHdti/9ixY5GSkmLUewwePBhFRUW4evUqDAYDkpKS0KdPnxsev2zZMqjV6uYtJyenTd+DubENS0RE1kQQBMyIDcHGWYPhrrJD6uWreOD9/cjMt76OV0dg1cGutLQUer0e/v7+Lfb7+/ujsLDQqPews7PDihUrcOedd6J///7o0aMH7r///hse7+joCHd39xabNWEbloiIrNHIHr7Y+o/hCPNxQV55LaZ8kIKfTxj3u5rMx6qDXZM/txtFUTSpBRkfH4/jx4/jxIkTeOedd8xdXrtiG5aIiKxVmK8rtswfjpE9fFBbr0fCf1Oxevc5TqpoR1Yd7Hx8fKBUKluNzhUXF7caxesI2IYlIiJr5+Fsjw0zB2NmbAgA4K1dZ7Hgy3TU1XNSRXuw6mDn4OCAmJiYVrNYExMTERsbK1FV0mEbloiIbIGdUoGXJ/bDigcjYacQ8OOxfDy89gCKKuqkLk32JA92VVVVSE9PR3p6OoCG23+lp6c3L2eyePFirF+/Hp988glOnTqFp556CtnZ2UhISJCwammwDUtERLbk0aFB+O+coejkbI+MXDUmrt6HYznlUpcla5Ivd3LkyBGMHj26+fHixYsBADNmzMDGjRsxdepUlJWVYfny5SgoKEBERAR27NiB4OBgqUqWRLWGbVgiIrI9d4R54/t/jMCcz37H2aIqPLz2AF57MBJTBgZykMICBJFXNN5URUUFPDw8oFarJZ0h++OxfDz5RRqCvJyx95m7+MNAREQ2pbKuHou+TMevpxsGKSZFB+D/HoiAm8pe4sral6VzheStWDLOjuNswxIRke1yU9lj3WODsGRsTygVAr5Pz8f495JxNPuq1KXJCoOdDWAbloiI5ECpEPDE3T3w1d+GIdDTCTlXavHQBylYseMUarWcNWsODHY2oGk2bLA3Z8MSEZHtiwnuhB0LR2JSdAAMIrAu6SLGrUrC3rMlUpdm8xjsbEBTG3Z8JNuwREQkDx5O9vjX/wzAxzMGoYuHCtlXajDjk8OY8clhnC7k7chul+SzYunm2IYlIiI5u6ePP4aGeeOdXWfx2YFL2Hu2BMnnSjApOhDz7gxDny7y6FSV12ix/XgBvkk5Z9HPYbCzcmzDEhGR3Lk62uHFCX3x2LBgvLnzNHYcL8SWtDxsScvDnT19Mf2OYIzq6QsHO9tqNOaX1+KXU0VIzCzCwYtlqNeLMGhqLPqZDHZWjm1YIiLqKEJ8XLBmWgwycsuxNukifjpegKSzJUg6W4JOzvaYEBWAuL7+GBziBZW9UupyW9Ho9EjLLkfKhTLsPl2EE3ktW8p9u7hjXM9ALFpluRq4jt0tSLmOXbVGh4GvJkKjM2DbkyMQEejRrp9PREQkpeyyGnx24BK2puejtErTvN/RToEhoV6I7uaJfgEeiOzqgQAPVbsPgFTU1eNErhpHs6/iwMUyHLl0FRqdofl5QQBigjohrq8/4vr6I8zX1eK5giN2Vmz36WJodGzDEhFRxxTk7Yx/3t8XS+N7Y9/5UmzLKEDyuRIUVWiQfK4UyedKm4/1dLZH3y7u6NvFHaN6+SK2uw+UCvMEPVEUUVKpwfniKpwqrMTx3HJk5KpxsbS61bE+ro4Y1t0bI8N9cHcfP/i4OpqlBmMx2FkxtmGJiIgAO6UCd/Xyw129/CCKIs4WVeFQVhlO5KlxPK8C54oqUV5Tj5QLZUi5UIb1+7LQy98Nr0+JxICgTkZ9hk5vQHGlBnnltcgvr0Xu1VpcKq3G+ZIqXCiuQkWd7rqv69rJCVFdPTE0zAux3b3R3ddV0t/ZDHZWqlqjw+7TnA1LRER0LUEQ0KuzG3p1dmveV1evx/niKmTmVyAt5yq2ZxTgTFElpnyQgmlDg3FnT1/YKQRUa3Uoq9KirEqDsmotyqq0KK3SoEBdh8KKOugNN746TSEAQV7OCPdzQ/+uHujf1QORgR7wbucRuVvhNXa3INU1dk33hg32dsZvS3hvWCIiImNdrdZi+bZMbEnLM+l1dgoBXTxVCPR0QoCnU2OQc0W4nytCvF3MMmGD19h1UGzDEhER3Z5OLg54d2o0HhgQiK1peThXXAkBApzslfBxc4CXiwO8XRzh7drw3108VAj0dIavm6PZrsuTCoOdFWIbloiIqO1G9fTFqJ6+UpfRrmxrpb8OgrNhiYiI6HYw2FkhtmGJiIjodjDYWRm2YYmIiOh2MdhZmV8b27AhbMMSERGRiRjsrMz2jHwAwH392YYlIiIi0zDYWZEqjQ57zpQAaLi+joiIiMgUDHZW5NdTRdDqDAj1cUHfLmzDEhERkWkY7KzI9oyG2bD3cTYsERER3QYGOytRWVeP3842tGHv6882LBEREZmOwc5K/HqqGFqdAWG+Luh9zY2NiYiIiIzFYGcltjW2Ye9nG5aIiIhuE4OdFaioq0dScxs2QOJqiIiIyFYx2FmBX08VQas3oLuvC3r6u0pdDhEREdkoBjsr0Dwbtn8A27BERER02xjsJKaurUfS2VIAwP2cDUtERERtwGAnsV8yG9qwPfxc0dOfs2GJiIjo9jHYSWz78aY2LEfriIiIqG0Y7CSkrq1H8rnG2bC8NywRERG1EYOdhBIzi1CvF9HL3w092IYlIiKiNmKwk9D2jHwAwHiO1hEREZEZMNhJRF1Tj+RzDbNh7+vfWeJqiIiISA4Y7CSyM7MQOoOI3p3dEO7HNiwRERG1HYOdRJoXJWYbloiIiMyEwU4C5TVa7D/f0IYdz2VOiIiIyEwY7CSw62QRdAYRfbq4o7sv7w1LRERE5sFgJ4FtjYsS8xZiREREZE4Mdu3savU1bVheX0dERERmxGDXznaeLITeIKJvF3eE+rhIXQ4RERHJCINdO+O9YYmIiMhSGOza0ZVqLVIulAHgMidERERkfgx27aipDRsR6I4QtmGJiIjIzBjs2tEfixIHSFwJERERyRGDXTspq9Ig5ULjvWHZhiUiIiILYLBrJz+fLIRBBCIDPRDk7Sx1OURERCRDDHbtZNsxzoYlIiIiy2KwawfFFXU4mMXZsERERGRZDHbtYMfxAogiMCDIE9282IYlIiIiy2Cwawc/Ns6GndCfs2GJiIjIchjsLCz3ag1SL1+FIPD6OiIiIrIsBjsLa1q7bmioF/zdVRJXQ0RERHLGYGdhP2bkAwAmRLENS0RERJbFYGdBF0uqcCKvAkqFgPgItmGJiIjIshjsLGhbYxt2RLgPvFwcJK6GiIiI5I7BzkJEUcQPx9iGJSIiovbDYGchZ4oqcb64Cg5KBcb285e6HCIiIuoAGOws5MfG0bq7evnCXWUvcTVERETUETDYWYAois3X193PNiwRERG1EwY7Cziep8blsho42Ssxpo+f1OUQERFRB8FgZwFNbdh7+vjB2cFO4mqIiIioo2CwMzOD4Y82LGfDEhERUXtisDOz1OyrKFDXwc3RDqN6+kpdDhEREXUgHSLYvfvuu+jXrx/69u2LBQsWQBRFi31WUxt2bL/OUNkrLfY5RERERH8m+2BXUlKC1atXIzU1FcePH0dqaioOHjxokc/S6Q3YcbypDctbiBEREVH76hBX9ut0OtTV1QEA6uvr4ednmZmqBy9eQWmVFp2c7TE83Mcin0FERER0I5KP2CUlJWHChAkICAiAIAjYunVrq2PWrFmD0NBQqFQqxMTEIDk52ej39/X1xZIlSxAUFISAgACMGTMG3bt3N+N38IemNmx8ZBfYKyU/tURERNTBSD5iV11djaioKMyaNQtTpkxp9fzmzZuxaNEirFmzBsOHD8fatWsRHx+PzMxMBAUFAQBiYmKg0WhavXbXrl1wcnLCtm3bcOnSJTg5OSE+Ph5JSUm48847r1uPRqNp8V5qtRoAUFFRcdPvQ6szYFvqeRg0eowOdb3l8URERNTxNOUDi13vL1oRAOKWLVta7BsyZIiYkJDQYl/v3r3FpUuXGvWeX331lTh//vzmx2+++ab4xhtv3PD4l156SQTAjRs3bty4ceNmse3ChQvGByQTSD5idzNarRapqalYunRpi/1jx45FSkqKUe/RrVs3pKSkoK6uDvb29vjtt98wb968Gx6/bNkyLF68uPlxeXk5goODkZ2dDQ8Pj9v7RjqQiooKdOvWDTk5OXB3d5e6HJvAc2Yani/T8HyZjufMNDxfplGr1QgKCoKXl5dF3t+qg11paSn0ej38/f1b7Pf390dhYaFR73HHHXdg/PjxGDBgABQKBe655x5MnDjxhsc7OjrC0dGx1X4PDw/+D2sCd3d3ni8T8ZyZhufLNDxfpuM5Mw3Pl2kUCstci2/Vwa6JIAgtHoui2Grfzbz22mt47bXXzF0WERERkVWx6qmbPj4+UCqVrUbniouLW43iEREREXV0Vh3sHBwcEBMTg8TExBb7ExMTERsb2y41ODo64qWXXrpue5Za4/kyHc+ZaXi+TMPzZTqeM9PwfJnG0udLEEUL3l/LCFVVVTh//jwAYMCAAXjnnXcwevRoeHl5ISgoCJs3b8b06dPx4YcfYtiwYVi3bh0++ugjnDx5EsHBwVKWTkRERGRVJA92v/32G0aPHt1q/4wZM7Bx40YADQsUv/nmmygoKEBERATefffdG65DR0RERNRRSR7siIiIiMg8rPoaOyIiIiIyHoMdERERkUww2BERERHJBINdGz344IPo1KkTHnroIZOeI+Ctt95Cv379EBERgf/+979Sl2P1zpw5g+jo6ObNyckJW7dulbosq2ZnZ9d8vubMmSN1OVavsrISgwcPRnR0NCIjI/HRRx9JXZLV47/zt8ZzZDxz/Axy8kQb7dmzB1VVVfj000/xzTffGP1cR3f8+HHMmDGj+Z6/99xzD7Zv3w5PT09pC7MRVVVVCAkJweXLl+Hi4iJ1OVbLx8cHpaWlUpdhM/R6PTQaDZydnVFTU4OIiAj8/vvv8Pb2lro0q8V/52+N58h45vgZ5IhdG40ePRpubm4mP9fRnTp1CrGxsVCpVFCpVIiOjsbPP/8sdVk244cffsA999zDUEdmpVQq4ezsDACoq6uDXq8H//a/Of47f2s8R8Yzx8+grINdUlISJkyYgICAAAiCcN221Zo1axAaGgqVSoWYmBgkJye3f6FWyNLnLiIiAnv27EF5eTnKy8uxe/du5OXlmfE7aH/t+f/bV199halTp7axYmm1x/mqqKhATEwMRowYgb1795qpcum0xzkrLy9HVFQUunbtimeffRY+Pj5mqr798XdA2/EcmsYc56utP4OyDnbV1dWIiorC6tWrr/v85s2bsWjRIjz//PNIS0vDyJEjER8fj+zs7OZjYmJiEBER0WrLz89vr29DEpY+d3379sWCBQtw991348EHH8TgwYNhZ2fXXt+eRbTX/28VFRXYv38/xo8fb/HvyZLa43xdunQJqamp+PDDD/HYY4+hoqKiXb43S2mPc+bp6Yljx44hKysLn3/+OYqKitrle7ME/g5oO3Ocw47EHOerzT+DYgcBQNyyZUuLfUOGDBETEhJa7Ovdu7e4dOlSk957z5494pQpU0x+zlZY8tw1mT17trht27bbLdHqWPKcffbZZ+K0adPaWqJVaY//x+69917x999/v90SrU57nLOEhATxq6++ut0SrYpUvwPkpC3nsKOco2uZ4/+52/kZlPWI3c1otVqkpqZi7NixLfaPHTu2+YJ+uj5znbvi4mIADbM9Dx8+jHHjxpm1Tmtizv/f5NCGvRVznK+rV69Co9EAAHJzc5GZmYmwsDCz12otzHHOioqKmkc1KyoqkJSUhF69epm9VmvA3wFtx3NoGmPOlzl+Bm2799UGpaWl0Ov18Pf3b7Hf398fhYWFRr/PuHHjcPToUVRXV6Nr167YsmULBg8efMvnbJm5zt0DDzyA8vJyuLi4YMOGDTbfir0Zc50ztVqNw4cP49tvvzV3iVbFHOfr1KlT+Nvf/gaFQgFBEPCvf/0LXl5elijXKpjjnOXm5mL27NkQRRGiKOKJJ55A//79LVGu5Nrjd4DcGXsOO/I5upYx58scP4Py/U1qJEEQWjwWRbHVvpvZuXPnbT0nB209dx3xL7q2njMPDw+bvubJVG05X7GxsTh+/LglyrJqbTlnMTExSE9Pt0BV1suSvwM6iludQ56jlm52vszxM9hhW7E+Pj5QKpWt/jIrLi5ulaapJZ470/GcmYbny3Q8Z6bh+Wo7nkPTtNf56rDBzsHBATExMUhMTGyxPzExEbGxsRJVZRt47kzHc2Yani/T8ZyZhuer7XgOTdNe50vWrdiqqiqcP3+++XFWVhbS09Ph5eWFoKAgLF68GNOnT8egQYMwbNgwrFu3DtnZ2UhISJCwauvAc2c6njPT8HyZjufMNDxfbcdzaBqrOF8mzaG1MXv27BEBtNpmzJjRfMz7778vBgcHiw4ODuLAgQPFvXv3SlewFeG5Mx3PmWl4vkzHc2Yanq+24zk0jTWcL94rloiIiEgmOuw1dkRERERyw2BHREREJBMMdkREREQywWBHREREJBMMdkREREQywWBHREREJBMMdkREREQywWBHREREJBMMdkREREQywWBHRB3ayy+/jOjoaMk+/4UXXsC8efOMOnbJkiVYsGCBhSsiIlvGW4oRkWwJgnDT52fMmIHVq1dDo9HA29u7nar6Q1FREXr06IGMjAyEhITc8vji4mJ0794dGRkZCA0NtXyBRGRzGOyISLYKCwub/3vz5s148cUXcebMmeZ9Tk5O8PDwkKI0AMCKFSuwd+9e7Ny50+jXTJkyBeHh4XjjjTcsWBkR2Sq2YolItjp37ty8eXh4QBCEVvv+3IqdOXMmHnjgAaxYsQL+/v7w9PTEK6+8Ap1Oh2eeeQZeXl7o2rUrPvnkkxaflZeXh6lTp6JTp07w9vbGpEmTcOnSpZvW9+WXX2LixIkt9n3zzTeIjIyEk5MTvL29MWbMGFRXVzc/P3HiRHzxxRdtPjdEJE8MdkREf7J7927k5+cjKSkJ77zzDl5++WXcf//96NSpEw4dOoSEhAQkJCQgJycHAFBTU4PRo0fD1dUVSUlJ2LdvH1xdXXHvvfdCq9Ve9zOuXr2KEydOYNCgQc37CgoK8Mgjj+Dxxx/HqVOn8Ntvv2Hy5Mm4trEyZMgQ5OTk4PLly5Y9CURkkxjsiIj+xMvLC++99x569eqFxx9/HL169UJNTQ2ee+459OjRA8uWLYODgwP2798PoGHkTaFQYP369YiMjESfPn2wYcMGZGdn47fffrvuZ1y+fBmiKCIgIKB5X0FBAXQ6HSZPnoyQkBBERkZi/vz5cHV1bT4mMDAQAG45GkhEHZOd1AUQEVmbfv36QaH44+9ef39/REREND9WKpXw9vZGcXExACA1NRXnz5+Hm5tbi/epq6vDhQsXrvsZtbW1AACVStW8LyoqCvfccw8iIyMxbtw4jB07Fg899BA6derUfIyTkxOAhlFCIqI/Y7AjIvoTe3v7Fo8FQbjuPoPBAAAwGAyIiYnBpk2bWr2Xr6/vdT/Dx8cHQENLtukYpVKJxMREpKSkYNeuXfj3v/+N559/HocOHWqeBXvlypWbvi8RdWxsxRIRtdHAgQNx7tw5+Pn5ITw8vMV2o1m33bt3h7u7OzIzM1vsFwQBw4cPxyuvvIK0tDQ4ODhgy5Ytzc+fOHEC9vb26Nevn0W/JyKyTQx2RERtNG3aNPj4+GDSpElITk5GVlYW9u7di4ULFyI3N/e6r1EoFBgzZgz27dvXvO/QoUNYsWIFjhw5guzsbHz33XcoKSlBnz59mo9JTk7GyJEjm1uyRETXYrAjImojZ2dnJCUlISgoCJMnT0afPn3w+OOPo7a2Fu7u7jd83bx58/Dll182t3Td3d2RlJSE8ePHo2fPnvjnP/+Jt99+G/Hx8c2v+eKLLzB37lyLf09EZJu4QDERkUREUcQdd9yBRYsW4ZFHHrnl8du3b8czzzyDjIwM2NnxEmkiao0jdkREEhEEAevWrYNOpzPq+OrqamzYsIGhjohuiCN2RERERDLBETsiIiIimWCwIyIiIpIJBjsiIiIimWCwIyIiIpIJBjsiIiIimWCwIyIiIpIJBjsiIiIimWCwIyIiIpIJBjsiIiIimfj/1/XUs7gt7TAAAAAASUVORK5CYII=", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Plots the ROP of O=CO\n", - "clf()\n", - "\n", - "plot(t_vals, ROP_vals)\n", - "\n", - "xscale(\"log\")\n", - "xlim(1e-11,1e3)\n", - "yscale(\"log\")\n", - "ylim(1e-8,1e2)\n", - "xlabel(\"Time (s)\")\n", - "ylabel(\"Rate of Progress (mol/s)\")\n", - "legend()\n", - "tight_layout()\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "id": "23c409b5", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Plots the Boundary Layer Concentration of O=CO from ROP Integration WITHOUT Diffusion Flux Into Reservoir\n", - "clf()\n", - "\n", - "plot(t_vals, Cbl_vals)\n", - "\n", - "xscale(\"log\")\n", - "xlim(1e-11,1e3)\n", - "yscale(\"log\")\n", - "ylim(1e-13,1e1)\n", - "xlabel(\"Time (s)\")\n", - "ylabel(\"Concentration (mol/m^3)\")\n", - "title(\"Boundary Layer Accumulation of O=CO from ROP Integration\")\n", - "legend()\n", - "tight_layout()\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 43, - "id": "86b95521", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "1507-element SparseArrays.SparseVector{Float64, Int64} with 13 stored entries:\n", - " [1329] = 3.51883e-6\n", - " [1330] = 6.67508e-27\n", - " [1334] = 3.30016e-24\n", - " [1335] = 3.19117e-20\n", - " [1382] = 1.47424e-31\n", - " [1429] = -3.13886e-24\n", - " [1466] = 1.26125e-18\n", - " [1476] = -3.47548e-41\n", - " [1480] = 3.86781e-39\n", - " [1482] = -1.39325e-53\n", - " [1495] = 3.98532e-40\n", - " [1498] = -6.95737e-42\n", - " [1500] = 2.9296e-38" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "rops(ssys,\"O=CO\",1)" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "id": "8073b759", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(:sol, :sims, :interfaces, :names, :species, :reactions, :p)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fieldnames(typeof(ssys))" - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "id": "2eefe3c5", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Net ROPs for species O=CO is: 0.011081939249267675\n", - "Showing the reaction with 1 th highest ROP for species O=CO:\n", - "vacantX+O=CO<=>CH2O2X\n", - "ROP = 0.011081939247853978\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 23373.5545874235\n", - " n: Float64 0.49999999999977207\n", - " Ea: Float64 1.418358411610997e-9\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 2 th highest ROP for species O=CO:\n", - "HX+O=CO<=>OC(O)[Pt]\n", - "ROP = 1.405972317009418e-12\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 11686.777293693782\n", - " n: Float64 0.49999999999996975\n", - " Ea: Float64 73060.00000000019\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 3 th highest ROP for species O=CO:\n", - "HX+O=CO<=>OCO[Pt]\n", - "ROP = 4.472145402079929e-15\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 11686.777293693782\n", - " n: Float64 0.49999999999996975\n", - " Ea: Float64 73060.00000000019\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 4 th highest ROP for species O=CO:\n", - "proton+O=COC[Pt]<=>CH2X+O=CO\n", - "ROP = 2.9954118602407244e-15\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 64651.660819360055\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 5 th highest ROP for species O=CO:\n", - "proton+O=COC#[Pt]<=>CX+O=CO\n", - "ROP = 2.3506931460862857e-16\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 38998.96922048947\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 6 th highest ROP for species O=CO:\n", - "vacantX+vacantX+O=CO<=>OX+OC=[Pt]\n", - "ROP = 1.1314227975578065e-17\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 1.0188995025013964e8\n", - " n: Float64 0.5000000000000002\n", - " Ea: Float64 257417.66568750236\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 7 th highest ROP for species O=CO:\n", - "vacantX+vacantX+O=CO<=>HX+CHO2X\n", - "ROP = 9.550886293769898e-18\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 1.0188995025013927e9\n", - " n: Float64 0.5000000000000007\n", - " Ea: Float64 176038.66814912477\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 8 th highest ROP for species O=CO:\n", - "proton+O=COC=[Pt]<=>CHX+O=CO\n", - "ROP = -1.5015825455900762e-18\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 51447.34412179033\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 9 th highest ROP for species O=CO:\n", - "vacantX+vacantX+O=CO<=>HX+CO2HX\n", - "ROP = 2.1744577929659633e-21\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 1.0188995025013999e9\n", - " n: Float64 0.4999999999999998\n", - " Ea: Float64 136711.0572887129\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 10 th highest ROP for species O=CO:\n", - "vacantX+vacantX+O=CO<=>HOX+CHOX\n", - "ROP = 9.125423325019487e-22\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 7.641746268753779e7\n", - " n: Float64 0.5000000000001129\n", - " Ea: Float64 132375.38628664595\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 11 th highest ROP for species O=CO:\n", - "proton+O=C(O)C=[Pt]<=>CHX+O=CO\n", - "ROP = 5.988139025813965e-28\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 45734.37564534281\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 12 th highest ROP for species O=CO:\n", - "proton+O=C(O)C[Pt]<=>CH2X+O=CO\n", - "ROP = -1.8372826056198025e-40\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 130830.26178561061\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 13 th highest ROP for species O=CO:\n", - "proton+O=C(O)C#[Pt]<=>CX+O=CO\n", - "ROP = -3.7651155840160784e-45\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 130354.10328483029\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plotROP(ssys, \"O=CO\",1e-8;N=15,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "id": "03ec23c9", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Net ROPs for species proton is: -5.9712645183068285e-6\n", - "Showing the reaction with 1 th highest ROP for species proton:\n", - "proton+CO2X<=>CHO2X\n", - "ROP = -3.909658832227069e-6\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e14\n", - " n: Float64 0.0\n", - " Ea: Float64 62276.629849940306\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 2 th highest ROP for species proton:\n", - "proton+CO2X<=>CO2HX\n", - "ROP = -1.9749718464379574e-6\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 75249.98822394571\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 3 th highest ROP for species proton:\n", - "proton+CO2HX<=>H2O+OCX\n", - "ROP = -4.255653013520114e-8\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 22584.872508307497\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 4 th highest ROP for species proton:\n", - "proton+CO2HX<=>CH2O2X\n", - "ROP = -4.255653013520114e-8\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 48898.20910952611\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 5 th highest ROP for species proton:\n", - "proton+OCX<=>CHOX\n", - "ROP = -1.462152308106832e-9\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 34575.95926752735\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 6 th highest ROP for species proton:\n", - "proton+CHOX<=>CH2OX\n", - "ROP = -2.92605741806731e-11\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 54779.82771855402\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 7 th highest ROP for species proton:\n", - "proton+CHOX<=>OC=[Pt]\n", - "ROP = -2.9053023822973633e-11\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 53014.94467580053\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 8 th highest ROP for species proton:\n", - "proton+CH2OX<=>CO[Pt]\n", - "ROP = -2.6708368651046744e-13\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.4999999999999992e10\n", - " n: Float64 0.0\n", - " Ea: Float64 63847.33033518879\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 9 th highest ROP for species proton:\n", - "proton+CH2OX<=>OC[Pt]\n", - "ROP = -4.1961754190969024e-14\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 72802.9367584667\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 10 th highest ROP for species proton:\n", - "proton+HX<=>[H][H].[Pt]\n", - "ROP = -2.1463994768336997e-15\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.4999999999999992e10\n", - " n: Float64 0.0\n", - " Ea: Float64 26879.12942447813\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 11 th highest ROP for species proton:\n", - "proton+OCX<=>OC#[Pt]\n", - "ROP = -1.62730356787951e-15\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 59907.674739328526\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 12 th highest ROP for species proton:\n", - "proton+CH2O2X<=>OC(O)[Pt]\n", - "ROP = -2.8619989026153704e-16\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 115347.50806876807\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 13 th highest ROP for species proton:\n", - "proton+O=C([Pt])C[Pt]<=>OCX+CH3X\n", - "ROP = -1.747162463995665e-16\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 39888.61730671122\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 14 th highest ROP for species proton:\n", - "proton+CHO2X<=>CH2O2X\n", - "ROP = -1.3599177517494918e-16\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 3012.3559299445205\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 15 th highest ROP for species proton:\n", - "proton+[Pt]=CC=[Pt]<=>CHX+CH2X\n", - "ROP = -4.923843544206662e-17\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 5.0e10\n", - " n: Float64 0.0\n", - " Ea: Float64 44469.07469607376\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plotROP(ssys, \"proton\",1;N=15,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "id": "1ca256e1", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Net ROPs for species O=CO is: 3.5188331343763696e-6\n", - "Showing the reaction with 1 th highest ROP for species O=CO:\n", - "vacantX+O=CO<=>CH2O2X\n", - "ROP = 3.5188331343750766e-6\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 23373.5545874235\n", - " n: Float64 0.49999999999977207\n", - " Ea: Float64 1.418358411610997e-9\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 2 th highest ROP for species O=CO:\n", - "HX+O=CO<=>OC(O)[Pt]\n", - "ROP = 1.2612537663989518e-18\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 11686.777293693782\n", - " n: Float64 0.49999999999996975\n", - " Ea: Float64 73060.00000000019\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 3 th highest ROP for species O=CO:\n", - "vacantX+vacantX+O=CO<=>HX+CO2HX\n", - "ROP = 3.191170302971873e-20\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 1.0188995025013999e9\n", - " n: Float64 0.4999999999999998\n", - " Ea: Float64 136711.0572887129\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 4 th highest ROP for species O=CO:\n", - "vacantX+vacantX+O=CO<=>HX+CHO2X\n", - "ROP = 3.300158681985259e-24\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 1.0188995025013927e9\n", - " n: Float64 0.5000000000000007\n", - " Ea: Float64 176038.66814912477\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 5 th highest ROP for species O=CO:\n", - "HX+O=CO<=>OCO[Pt]\n", - "ROP = -3.1388645300997214e-24\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 11686.777293693782\n", - " n: Float64 0.49999999999996975\n", - " Ea: Float64 73060.00000000019\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 6 th highest ROP for species O=CO:\n", - "vacantX+vacantX+O=CO<=>HOX+CHOX\n", - "ROP = 6.675077863448035e-27\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 7.641746268753779e7\n", - " n: Float64 0.5000000000001129\n", - " Ea: Float64 132375.38628664595\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 7 th highest ROP for species O=CO:\n", - "vacantX+vacantX+O=CO<=>OX+OC=[Pt]\n", - "ROP = 1.474236414721233e-31\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 1.0188995025013964e8\n", - " n: Float64 0.5000000000000002\n", - " Ea: Float64 257417.66568750236\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 8 th highest ROP for species O=CO:\n", - "proton+O=COC#[Pt]<=>CX+O=CO\n", - "ROP = 2.929603640728949e-38\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 38998.96922048947\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 9 th highest ROP for species O=CO:\n", - "proton+O=C(O)C=[Pt]<=>CHX+O=CO\n", - "ROP = 3.8678114512138464e-39\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 45734.37564534281\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 10 th highest ROP for species O=CO:\n", - "proton+O=COC[Pt]<=>CH2X+O=CO\n", - "ROP = 3.985315295748389e-40\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 64651.660819360055\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 11 th highest ROP for species O=CO:\n", - "proton+O=C(O)C[Pt]<=>CH2X+O=CO\n", - "ROP = -3.475475922803838e-41\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 130830.26178561061\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 12 th highest ROP for species O=CO:\n", - "proton+O=COC=[Pt]<=>CHX+O=CO\n", - "ROP = -6.957372780235491e-42\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 51447.34412179033\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 13 th highest ROP for species O=CO:\n", - "proton+O=C(O)C#[Pt]<=>CX+O=CO\n", - "ROP = -1.3932460007596807e-53\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 130354.10328483029\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plotROP(ssys, \"O=CO\",1;N=15,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "id": "64238bc0", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Net ROPs for species CH2O2X is: 33256.74822959144\n", - "Showing the reaction with 1 th highest ROP for species CH2O2X:\n", - "CHO2X+CHO2X<=>CO2X+CH2O2X\n", - "ROP = 32491.88243204814\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 2 th highest ROP for species CH2O2X:\n", - "proton+CO2HX<=>CH2O2X\n", - "ROP = 650.6058223512374\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 48898.20910952611\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 3 th highest ROP for species CH2O2X:\n", - "proton+CHO2X<=>CH2O2X\n", - "ROP = 88.30234913296361\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 3012.3559299445205\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 4 th highest ROP for species CH2O2X:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = 6.492103842569652\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 26227.25171408696\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 5 th highest ROP for species CH2O2X:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = 6.492103842569652\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 26227.25171408696\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 6 th highest ROP for species CH2O2X:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = 6.492103842569652\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 26227.25171408696\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 7 th highest ROP for species CH2O2X:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = 6.492103842569652\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 26227.25171408696\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 8 th highest ROP for species CH2O2X:\n", - "vacantX+O=CO<=>CH2O2X\n", - "ROP = -0.011081939247853978\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 23373.5545874235\n", - " n: Float64 0.49999999999977207\n", - " Ea: Float64 1.418358411610997e-9\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 9 th highest ROP for species CH2O2X:\n", - "CHO2X+OC(O)[Pt]<=>CH2O2X+CH2O2X\n", - "ROP = 0.0002599529648578453\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 8.36e17\n", - " n: Float64 0.0\n", - " Ea: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 10 th highest ROP for species CH2O2X:\n", - "CO2HX+OC(O)[Pt]<=>CH2O2X+CH2O2X\n", - "ROP = 2.561777271497043e-5\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 8.36e17\n", - " n: Float64 0.0\n", - " Ea: Float64 10760.85577299056\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 11 th highest ROP for species CH2O2X:\n", - "CO2HX+CO2HX<=>CO2X+CH2O2X\n", - "ROP = 8.534574725738622e-6\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 64984.89719971026\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 12 th highest ROP for species CH2O2X:\n", - "proton+CH2O2X<=>OC(O)[Pt]\n", - "ROP = -3.4375883085779855e-6\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 115347.50806876807\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 13 th highest ROP for species CH2O2X:\n", - "CHO2X+CO[Pt]<=>CH2OX+CH2O2X\n", - "ROP = 1.933447621553195e-6\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 1.254e18\n", - " n: Float64 0.0\n", - " Ea: Float64 12479.425316287554\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 14 th highest ROP for species CH2O2X:\n", - "CHOX+CHO2X<=>OCX+CH2O2X\n", - "ROP = 2.4993542729921353e-8\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 7.475e18\n", - " n: Float64 0.0\n", - " Ea: Float64 57891.205417621124\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 15 th highest ROP for species CH2O2X:\n", - "CO2HX+OCO[Pt]<=>CH2O2X+CH2O2X\n", - "ROP = 1.912820642014731e-9\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 8.36e17\n", - " n: Float64 0.0\n", - " Ea: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plotROP(ssys,\"CH2O2X\",1e-8;N=15,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "id": "e8bb3c43", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Net ROPs for species CHO2X is: 3.72379849332553e-13\n", - "Showing the reaction with 1 th highest ROP for species CHO2X:\n", - "proton+CO2X<=>CHO2X\n", - "ROP = 3.909658832227069e-6\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e14\n", - " n: Float64 0.0\n", - " Ea: Float64 62276.629849940306\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 2 th highest ROP for species CHO2X:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = -9.772876922410774e-7\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 26227.25171408696\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 3 th highest ROP for species CHO2X:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = -9.772876922410774e-7\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 26227.25171408696\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 4 th highest ROP for species CHO2X:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = -9.772876922410774e-7\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 26227.25171408696\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 5 th highest ROP for species CHO2X:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = -9.772876922410774e-7\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 26227.25171408696\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 6 th highest ROP for species CHO2X:\n", - "CHO2X+CHO2X<=>CO2X+CH2O2X\n", - "ROP = -2.3032122461454962e-10\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 7 th highest ROP for species CHO2X:\n", - "CHO2X<=>CO2HX\n", - "ROP = -2.2755687003918355e-10\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 2.4999999999999995e12\n", - " n: Float64 0.0\n", - " Ea: Float64 60523.33333333338\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 8 th highest ROP for species CHO2X:\n", - "HX+CO2<=>CHO2X\n", - "ROP = -4.902074886718284e-11\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 23902.917479574127\n", - " n: Float64 0.49999999999971745\n", - " Ea: Float64 73060.00000000176\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 9 th highest ROP for species CHO2X:\n", - "CHOX+CHO2X<=>CO2X+CH2OX\n", - "ROP = -7.551936582822176e-13\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 43165.28869169279\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 10 th highest ROP for species CHO2X:\n", - "CHOX+CHO2X<=>OCX+CH2O2X\n", - "ROP = -3.6845731211385277e-14\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 7.475e18\n", - " n: Float64 0.0\n", - " Ea: Float64 57891.205417621124\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plotROP(ssys,\"CHO2X\",1;N=10,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 50, - "id": "0bb84a7f", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Net ROPs for species CO2HX is: -0.000111152266901548\n", - "Showing the reaction with 1 th highest ROP for species CO2HX:\n", - "CO2HX+CO2HX<=>CO2X+CH2O2X\n", - "ROP = -0.00010913316030959863\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 64984.89719971026\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 2 th highest ROP for species CO2HX:\n", - "proton+CO2X<=>CO2HX\n", - "ROP = 1.9749718464379574e-6\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 75249.98822394571\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 3 th highest ROP for species CO2HX:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = -9.772876922410774e-7\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 26227.25171408696\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 4 th highest ROP for species CO2HX:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = -9.772876922410774e-7\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 26227.25171408696\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 5 th highest ROP for species CO2HX:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = -9.772876922410774e-7\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 26227.25171408696\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 6 th highest ROP for species CO2HX:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = -9.772876922410774e-7\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 26227.25171408696\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 7 th highest ROP for species CO2HX:\n", - "proton+CO2HX<=>H2O+OCX\n", - "ROP = -4.255653013520114e-8\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 22584.872508307497\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 8 th highest ROP for species CO2HX:\n", - "proton+CO2HX<=>CH2O2X\n", - "ROP = -4.255653013520114e-8\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 48898.20910952611\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 9 th highest ROP for species CO2HX:\n", - "CHO2X<=>CO2HX\n", - "ROP = 2.2755687003918355e-10\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 2.4999999999999995e12\n", - " n: Float64 0.0\n", - " Ea: Float64 60523.33333333338\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 10 th highest ROP for species CO2HX:\n", - "CHOX+CO2HX<=>CO2X+CH2OX\n", - "ROP = -4.2166022610077696e-11\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 81922.93417731601\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plotROP(ssys,\"CO2HX\",1;N=10,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 51, - "id": "1044d2b9", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Net ROPs for species OX is: 3.82295046247797e-27\n", - "Showing the reaction with 1 th highest ROP for species OX:\n", - "OCX+CO[Pt]<=>OX+CC(=O)[Pt]\n", - "ROP = 6.911463830051847e-18\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 1.39e17\n", - " n: Float64 0.101\n", - " Ea: Float64 19000.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 2 th highest ROP for species OX:\n", - "OX+CHOX<=>HOX+OCX\n", - "ROP = -4.74159053410928e-18\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 3.298e17\n", - " n: Float64 0.0\n", - " Ea: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 3 th highest ROP for species OX:\n", - "vacantX+vacantX+CO2<=>OX+OCX\n", - "ROP = -2.178186060194617e-18\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 2.0839509572346687e8\n", - " n: Float64 0.500000000000215\n", - " Ea: Float64 188799.94201580161\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 4 th highest ROP for species OX:\n", - "OX+CC(=O)O.[Pt]<=>CO2HX+CO[Pt]\n", - "ROP = 8.621124346808134e-21\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 1.405e20\n", - " n: Float64 -0.101\n", - " Ea: Float64 92700.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 5 th highest ROP for species OX:\n", - "OX+O=CC(=O)[Pt]<=>OCX+CHO2X\n", - "ROP = 1.3656860450940751e-21\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 3.298e17\n", - " n: Float64 0.0\n", - " Ea: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 6 th highest ROP for species OX:\n", - "OX+[Pt]=CC=[Pt]<=>CHX+[Pt]OC=[Pt]\n", - "ROP = -5.2156291066219785e-22\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 6.596e17\n", - " n: Float64 0.0\n", - " Ea: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 7 th highest ROP for species OX:\n", - "OX+[Pt]=CC=[Pt]<=>HOX+[Pt]C=C=[Pt]\n", - "ROP = -5.215629106618754e-22\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 6.596e17\n", - " n: Float64 0.0\n", - " Ea: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 8 th highest ROP for species OX:\n", - "vacantX+HOX<=>OX+HX\n", - "ROP = -3.4037408170132824e-22\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 7.39e15\n", - " n: Float64 0.0\n", - " Ea: Float64 81288.40204872913\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 9 th highest ROP for species OX:\n", - "OX+O=C([Pt])C[Pt]<=>OCX+[Pt]CO[Pt]\n", - "ROP = -2.9162184960345253e-22\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 3.298e17\n", - " n: Float64 0.0\n", - " Ea: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 10 th highest ROP for species OX:\n", - "proton+OC([Pt])O[Pt]<=>OX+OC[Pt]\n", - "ROP = 1.0794357267545613e-24\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 61219.2209161558\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n" - ] - }, - { - "data": { - "image/png": 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33nijwrze3t4YO3YsJk2ahKKiIvTq1QvFxcVYt24dlixZgsWLF8PBwQE5OTmYMGECFi1aJO1oOHfuXOzatQtTpkzRaemjmZkZEhIS0LdvX/Ts2RNjxoyBi4sL7t27h82bNyMnJwcbN26El5cXJk+ejAkTJuDWrVv48MMPYWdnJ23j/84772Ds2LF48803UadOHfzf//0fPvjgA6kdbZb8aToeZU6cOAEjI6Nq+Z0oJycnHDx4EG+//TaMjIxgaWn5ynUSERERvQ6codKQq6srzpw5A2dnZ/Tv3x/Ozs4ICwtDhw4dcPz4cWkjhjZt2kj5hg8fjiZNmqBnz564ePGitM1zZGQkLCwslF6cr1GjBlavXo1Dhw6pLP3TlCZtA8C4ceOwbds2pKamwtPTE82bN8f69euxYsUKpfezdFW/fn3MmjULU6ZMQd26dZXeGdKUu7s75s+fj5ycHMybN0/nvkydOhW5ubn46quvKg2myixevBixsbHYuHEjWrRogVatWuHIkSPYvn07IiIiIITA0KFD0bZtW6X320xNTbF69Wq1S/805e/vj2PHjsHAwACDBg2Cu7s7Bg4cCIVCgc8//1zKt2DBAqxfvx4nT55E165d0axZM4wfPx5vvPEGgoKCALzYRXLo0KEVLn/UVFXjUd6GDRsQEBAAU1PTV2oTAKKjo3HgwAE4ODhoNONFRERE9Ffh71BRhSr6HapXpcnvUNGr+9///odmzZrhl19+gaOj42tt6+7du3B3d8eZM2eUfofsddxr/g4V0d8Xf4eKiP5M/B0q+sewt7fX6L2qqoSHh2u09I+qR926dbFy5Urk5OS89raysrIQGxur8qPOADBw4EDY29u/chtlG5Lo8jtXRERERK8LZ6ioQk+fPsWtW7cAAHK5XKffBCrv999/l35ktV69emo3I6B/l6tXrwJ4sQRRXbCljT/++AP/+9//ALz4jSpNf/eLM1REfx7OUBHRn+nvMkPFTSmoQiYmJnBxcam2+mxsbHTeWp3+marz+/Mqv0FGRERE9LpwyR8REREREZGOGFARERERERHpiAEVERERERGRjhhQERERERER6YgBFRERERERkY64yx8RERFVi9e5hTER0d8VZ6iIiIiIiIh0xICKiIiIiIhIRwyoiIiIiIiIdMSAioiIiIiISEcMqIiIiIiIiHTEgIqIiIiIiEhH3DadiOgVOU3Z9Vd3gehvgdumE9F/EWeoiIiIiIiIdMSAioiIiIiISEcMqIiIiIiIiHTEgIqIiIiIiEhHDKiIiIiIiIh0xICKiIiIiIhIRwyoiIiIiIiIdMSAioiIiIiISEcMqAg3b95EaGgo7OzsYGhoCEdHR4wdOxb3799HSUkJfHx80Lt3b6UyCoUCDg4OiIqK0rndoqIiLFy4EB4eHjA1NYW1tTXefvttrF69GsXFxQCA4OBg9OrVS6VsSkoKZDIZHj16JKWVlJQgJiYGb7zxBoyNjVGrVi10794d//d//yfliY2NRa1atXDz5k2l+kaPHg03Nzc8efJE5+t5Xfz8/BAZGamSnpiYiFq1aimlPX36FDNnzkTjxo1hZGQEa2tr9OnTBxcvXpTyTJ48GU5OTvjjjz+Uyvbo0QPt27dHaWmpzn1NSkpCmzZtYGZmBnNzc7Rv3x47d+5UySeEwDfffAMvLy/I5XLUqlULnp6eWLx4sXQP+vfvDy8vL5SUlEjliouL8dZbb2Hw4ME695GIiIioOjGg+o+7fv06PD09kZGRgQ0bNuDq1auIi4vDwYMH4e3tDYVCgaSkJOzduxfJyclSuYiICFhZWWHGjBlq601JSYGTk1OF7RYVFaFr166YP38+wsLCcOzYMZw6dQqjRo3CsmXLlAIATQghMGDAAMyePRtjxozB5cuXceTIETg4OMDPzw/bt28HAHz88cdo06YNQkNDpbKHDh1CfHw8EhMTYWpqqlF7eXl5eP78uVZ9LPPo0SPk5+frVLYyhYWF6NSpE1atWoU5c+YgIyMDu3fvRklJCby8vHDixAkAwJw5cyCXyzF+/Hip7KpVq3D48GGsXr0aNWqo/78FmUyG7OzsCtufOHEiRowYgX79+uHcuXM4deoU2rVrB39/fyxfvlwp75AhQxAZGQl/f38cPnwYaWlpmD59Onbs2IH9+/cDeBH83rhxA/Pnz5fKzZkzB3fu3MGyZct0HSYiIiKiaqX/V3eA/lqjRo2CoaEh9u/fDxMTEwBAgwYN8Oabb8LZ2RmffvopVqxYgXnz5iEiIgIdOnTA6dOnsXHjRpw6dQqGhoY6tbt48WIcPXoUZ86cwZtvvimlN2rUCH379kVRUZFW9W3evBnff/89fvjhB/To0UNK/+abb3D//n0MGzYMnTt3hpmZGVauXIkWLVogLi4OgwYNQkhICMaNGwcfH59K23j27Bl27NiBpKQk7N+/H/fv34eFhYV2Fw7g3Llz6N69Oz766CMEBQXh3XffrTCI0cbixYtx/PhxnD17Fh4eHgAAR0dHbNmyBV5eXggNDcVvv/0GIyMjJCUlwdvbG71790bTpk0xbtw4LFy4EM7Ozjq1feLECURHR2Pp0qWIiIiQ0r/44gs8e/YM48ePh7+/PxwcHLB582YkJydj+/bt8Pf3l/I6OTmhZ8+eUrBZu3ZtfPPNN+jbty969OiB4uJizJs3Dzt27IClpeUrjBQRERFR9eEM1X/YgwcPsG/fPowcOVIKpsrY2toiICAAmzZtghACERER8PDwQGBgIMLCwjBjxgy0bNlS57aTk5PRqVMnpWCqjIGBAczMzLSqb/369XBzc1MKpspMmDAB9+/fx4EDBwAADg4OiImJwaRJkzB48GDI5XLMmTOnwrqPHz+O8PBw1KtXD+PHj0ezZs2QlpamFEzJ5fJKj+7du0t527dvjz179sDIyAh9+vSBo6Mjpk2bhitXrmh1zerGoHPnzlIwVaZGjRoYN24cLl26hHPnzgEAWrVqhalTp2LYsGEYMmQIWrdujY8//ljntjds2AC5XI4RI0aonJswYQKKi4uxZcsWAC/ufePGjZWCqTIymUxpXHv27IkBAwYgMDAQgYGBCAoKwnvvvadzP4mIiIiqG2eo/sMyMzMhhECTJk3Unm/SpAkePnyIu3fvwsbGBitWrECTJk3QokULTJky5ZXb9vPz0yjvzp07IZfLldLKv1cDABkZGZVeR1meMiEhIfjmm2/w448/4uTJkzAyMlIqk5ubizVr1iApKQm5ubn48MMPsWnTJnTq1EntbFJaWlql11A+YJXJZPD19YWvry+WL1+O7du3Y82aNfjyyy/RqlUrBAUFYdCgQUqBRWxsLBISEpTqfP78OYyNjZXGoEOHDlWOQVkgHBUVhdWrV+PkyZPIyMiATCar9Boqk5GRAWdnZ7UzlnZ2drCwsJDGPzMzE40bN9a47iVLlsDOzg41a9bEV199VWX+wsJCFBYWSp9fx/JKIiIiojIMqKhCQggAkB60V61aBVNTU2RlZSE3N1flHanyQU9JSQkKCwuV0tq1a4c9e/ZIdWv6AN+hQwesWLFCKe3kyZNab0xQvr1z587hl19+gampKVJTU9GmTRulvFFRUUhKSsJHH32E48ePw8rKqtK6XVxctOpLGRMTEwwcOBADBw5ERkYGBg4ciJEjR6KwsFBpI4qAgAB8+umnSmW3bt2KuXPnatTOy/cSAA4cOIC8vDzUqFEDp0+fRoMGDZTKdO/eHampqUppzZo1U6qjoKBA4/bLymlz74EXM28ymQz37t1Denq6yr162bx58zBr1iyN6yciIiJ6FQyo/sNcXFwgk8lw6dIltTvppaenw9LSEtbW1jh+/DhiYmKwZ88eLFy4EKGhofjpp5+UHozLz9KcPHkSn3zyCVJSUqS08rM0bm5uuHz5skb9NDMzUwlYcnNzlT67ubnh0qVLasuXtePq6grgxYYYgYGBGDhwIDp37ozhw4ejR48ecHNzk8pERUWhXr16WLt2Ldzc3DBgwAAMGTIEXl5eatt4eQbtZeWDyfKeP3+OAwcOYM2aNdixYwcaNWqEBQsWICAgQCmfhYWFyhjY2NhoPAbp6elKY/Dw4UMMHz4c06ZNg4GBAUaOHAlfX19YW1tLZRISEvD06VPps6urK3bv3o369eur1O/m5oaff/4ZRUVFKrNUt2/fRn5+vtS2Nvf++vXrmDx5MpYvX47/+7//Q3BwMM6ePasyo1je1KlTlTbcyM/Ph4ODg0btEREREWmL71D9h9WuXRudO3dGbGys0oMzANy5cwfJycno378/nj17hqCgIIwYMQKdOnVCQkICTp8+jfj4eKUyLi4u0lG/fn3o6+urpJUZNGgQfvrpJ5w9e1alX8+fP8fjx4+1upYBAwYgMzMTP/74o8q56Oho6VoBYPbs2bh//z6WLFmCwYMHo2vXrggJCVHaLtzFxQXz5s1DTk4O1q9fj4cPH6JDhw5wc3PDnDlzkJWVpdRGWlpapcfLy/XOnj2LcePGwd7eHkOGDIG1tTWOHj2K3377DZMnT0adOnW0uv6yMfjpp5+k96TKlJaWIiYmBk2bNpXer4qIiICNjQ2ioqIwZcoUODg4YPTo0Url6tevr3T/gBebXLycVtZ2QUGByncCABYtWgQDAwNp6/1BgwYhIyMDO3bsUMkrhIBCoZD6HRISAj8/P4SEhOCrr75CQUEBZs6cWek4GBkZoWbNmkoHERER0evCgOo/bvny5SgsLETXrl1x9OhR3Lx5E3v37kXnzp1Rv359fPHFF5gyZQpKS0uxYMECAC92AYyOjsakSZMq3Ua7MpGRkXj77bfx7rvv4uuvv8a5c+dw/fp1bN68GV5eXsjMzNSqvgEDBuDDDz9EUFAQVq5ciezsbJw/fx4jRozADz/8gISEBJiZmeHMmTNYsGABEhISpN9wiouLQ3p6OmJiYlTqrVGjBrp06YLk5GTcuXMHkydPxv79++Hi4qL0bk75IEPdUT6YTE1NhZeXF65fv47Y2Fjcvn0by5Ytg6enp05jWWbcuHFo06YNevToge+++w45OTk4ffo0evfujcuXL2PlypWQyWTYtm0bvvvuOyQlJcHAwAD6+vpITEzEtm3bpI0jtOXt7Y2xY8di0qRJiI6OxrVr15Ceno6oqCgsWbIE0dHR0ixRv3790L9/fwwcOBDz5s3DmTNncOPGDezcuROdOnXC4cOHAbx4d+rChQv49ttvAQA1a9ZEQkICoqOjcerUqVcaKyIiIqLqwoDqP87V1RVnzpyBs7Mz+vfvD2dnZ4SFhaFDhw44fvw4Lly4gK+//hqJiYlKO+8NHz4cPj4+CA0Nld7P0YaRkREOHDiAyZMnIz4+Hm3btkXr1q2xdOlSjBkzBs2bN9eqPplMhs2bN+PTTz9FTEwM3N3d0a5dO9y4cQOHDx9Gr169UFhYiKCgIISEhKBbt25SWVtbWyxbtgxRUVGV7rRXs2ZNDBs2DKmpqcjIyFDZGVFTTZs2xa1bt7Bjxw589NFHOm89/zJjY2McOnQIQUFBmDZtGlxcXNCtWzfo6enhxIkTaNu2Le7du4fw8HDMnDkTb7zxhlS2efPmmDlzJkaOHIl79+7p1P7ixYsRGxuLjRs3okWLFmjVqhWOHDmC7du3K22lLpPJsH79enz11VfYtm0bfH198cYbb+Czzz6Dv78/unbtioyMDHz66adYvnw56tWrJ5Xt0qULQkJCEBwcrLTxBBEREdFfRSZ0eRomIvqHyM/Ph4WFBRQKxWtb/uc0ZddrqZfonyZ7/vt/dReIiKqFNs8PnKEiIiIiIiLSEQMqIiIiIiIiHTGgIiIiIiIi0hEDKiIiIiIiIh0xoCIiIiIiItIRAyoiIiIiIiIdMaAiIiIiIiLSEQMqIiIiIiIiHen/1R0gIvqn44+ZEhER/XdxhoqIiIiIiEhHDKiIiIiIiIh0xICKiIiIiIhIRwyoiIiIiIiIdMSAioiIiIiISEcMqIiIiIiIiHTEbdOJiOhfz2nKrr+6C/8J/AkBIvov4gwVERERERGRjhhQERERERER6YgBFRERERERkY4YUBEREREREemIARUREREREZGOGFARERERERHpiAEVERERERGRjhhQERERERER6YgBFRERERERkY4YUFUjJycnLF68WCktNjYWtWrVws2bN5XSR48eDTc3Nzx58uRP7OGfKyUlBTKZDI8ePZLSSkpK4OPjg969eyvlVSgUcHBwQFRUlM7tFRUVYeHChfDw8ICpqSmsra3x9ttvY/Xq1SguLpby3bx5E6GhobCzs4OhoSEcHR0xduxY3L9/X8pTXFyMTz75BC1atICZmRns7OwQGBiI27dv69y/P8OxY8fw3nvvwdLSEsbGxmjRogWio6NRUlICALh9+zasrKywdOlSpXInT56EgYEBDhw4oHPbmoxrmatXryIkJAT29vYwMjJCw4YNMXDgQJw5cwYAcO7cORgZGeGHH35QKrdlyxYYGxvjt99+07mfRERERNWJAdVr9vHHH6NNmzYIDQ2V0g4dOoT4+HgkJibC1NRUbTknJyekpKT8Sb388+jp6SEpKQl79+5FcnKylB4REQErKyvMmDFDbbmUlBQ4OTlVWG9RURG6du2K+fPnIywsDMeOHcOpU6cwatQoLFu2DBcvXgQAXL9+HZ6ensjIyMCGDRtw9epVxMXF4eDBg/D29saDBw8AAE+ePMGvv/6K6dOn49dff8XWrVuRkZGBnj17anW9OTk5WuUv7+7du3j27JnG+bdt2wZfX1/Y29vj8OHDSE9Px9ixY/HFF19gwIABEELAzs4OS5cuxdSpU5GZmQkAePr0KYKCgjBs2DB07txZbd2fffYZgoODK2xb03EFgDNnzqBVq1bIyMhAfHw8Ll26hG3btsHd3R0TJkwAAHh4eGD69OkICwuTArLff/8d4eHhmDVrFpo3b67xuBARERG9Tv+IgCo+Ph7169dHaWmpUnrPnj0RFBSEa9euwd/fH3Xr1oVcLkfr1q3x008/KeUtLCzE5MmT4eDgACMjI7i6umLlypUAXsyahIaGomHDhjAxMUHjxo2xZMkSpfLBwcHo1asXFi1ahHr16qF27doYNWqUNPPh5+eHGzduYNy4cZDJZJDJZAAAmUyGlStX4tSpU4iLi0N+fj5CQkIwbtw4+Pj46DQe3t7emDJlilLa3bt3YWBggMOHDwMA1q1bB09PT5ibm8PW1haDBg3C77//rlTm4sWLeP/991GzZk2Ym5ujXbt2uHbtGgDg9OnT6Ny5M6ytrWFhYQFfX1/8+uuvSuVlMhkSEhLw4YcfwtTUFK6urtKMQnZ2Njp06AAAsLS0hEwmkx7IXV1dMW/ePEREROD27dvYsWMHNm7ciKSkJBgaGuo0JosXL8bRo0dx8OBBjBo1Ci1btkSjRo0waNAgnDx5Eq6urgCAUaNGwdDQEPv374evry8aNGiA7t2746effsKtW7fw6aefAgAsLCxw4MAB9OvXD40bN0bbtm2xbNky/PLLL1UGSfn5+Vi5ciXat2+Pli1b6nQ9ALB7927Uq1cP4eHhOH78eKV5Hz9+jOHDh6Nnz5745ptv0LJlSzg5OWHYsGFISkrC999/j82bNwMABg8ejK5duyI4OBilpaWYOnUqioqK8OWXX+rcV03HVQiB4OBguLq6IjU1Fe+//z6cnZ3RsmVLzJw5Ezt27JDqnDp1Kho0aIBRo0YBAEaMGAFXV1dMnDhR534SERERVbd/REDVt29f3Lt3TwoWAODhw4fYt28fAgICUFBQgPfeew8//fQTzp49i65du6JHjx5KD76BgYHYuHEjli5disuXLyMuLg5yuRwAUFpaCnt7e2zevBmXLl3CjBkzMG3aNOkBtMzhw4dx7do1HD58GElJSUhMTERiYiIAYOvWrbC3t8fs2bORl5eHvLw8qZyDgwNiYmIwadIkDB48GHK5HHPmzNF5PAICArBhwwYIIaS0TZs2oW7duvD19QXwYsZmzpw5OHfuHLZv346srCylGYZbt26hffv2MDY2xqFDh/DLL79g6NCheP78OQDgjz/+QFBQEFJTU3HixAm4urrivffewx9//KHUl1mzZqFfv344f/483nvvPQQEBODBgwdwcHDAli1bAABXrlxBXl6eUpAaEREBDw8PBAYGIiwsDDNmzHil4CM5ORmdOnXCm2++qXLOwMAAZmZmePDgAfbt24eRI0fCxMREKY+trS0CAgKwadMmpXEtT6FQQCaToVatWirnSktLceDAAQwePBi2traYP38+3n33XWkJG/Bitkoul1d6hIeHS/kDAgKwbt06PHz4EB07dkTjxo3xxRdfqCwfBYD9+/fj/v37aoONHj16wM3NDRs2bJDS4uLikJmZiYCAACxfvhyJiYnSvwdtaTOuaWlpuHjxIiZMmIAaNVT/76f82JbNZu7YsQODBg3Cvn37kJiYCD09vUr7U1hYiPz8fKWDiIiI6HXR/6s7oAkrKyt069YN69evx7vvvgsA+O6772BlZYV3330Xenp68PDwkPJ//vnn2LZtG3744QeMHj0aGRkZ2Lx5Mw4cOIBOnToBABo1aiTlNzAwwKxZs6TPDRs2xLFjx7B582b069dPSre0tMTy5cuhp6cHd3d3vP/++zh48CCGDx8OKysr6OnpSTNCLwsJCcE333yDH3/8ESdPnoSRkZHO49G/f3+MGzcOP//8M9q1awcAWL9+PQYNGiQ9pA4dOlTK36hRIyxduhRt2rRBQUEB5HI5vv76a1hYWGDjxo0wMDAAALi5uUllOnbsqNRmfHw8LC0tceTIEXzwwQdSenBwMAYOHAgAmDt3LpYtW4ZTp06hW7dusLKyAgDY2NioBCEymQwrVqxAkyZN0KJFC5UZN21lZmbCz8+vyjxCCDRp0kTt+SZNmuDhw4e4e/cubGxslM49e/YMU6ZMwaBBg1CzZk0pPSMjA4mJiVi7di0eP36Mfv364cCBA3j77bdV6rezs0NaWlqlfSxft76+Pt5//328//77UCgU+O6777BmzRrMnDkTfn5+CAoKQp8+fWBiYoKMjAzpGtRxd3eX8gAv7smcOXMQHh6Ojz/+GO3bt6+0X5XRZlzLlhm6u7trVHeTJk0QGRmJ+fPnY8GCBUrf0YrMmzdP6d8zERER0ev0j5ihAl78tX7Lli0oLCwE8GJGYsCAAdDT08Pjx48xefJkNG3aFLVq1YJcLkd6ero0Q5WWlgY9PT1p9kaduLg4eHp6ok6dOpDL5fj2229VlnY1a9ZM6a/j9erVU1lGV5Fz587hl19+gampKVJTU1XOh4eHK81U5OTkoHv37ippAFCnTh107txZegcpKysLx48fR0BAgFTf2bNn4e/vD0dHR5ibm0vBRvkxadeunRRMvazsfRU3NzdYWFjAwsICBQUFKmPyxhtvSP9tZmYGc3Nzjcdk1apVMDU1RVZWFnJzc1XOl7/27t27q8zwdO/eXcorhJCWWeqqbGbq5XqKi4sxYMAAlJaWIjY2VulcWFgY5s2bhw8++AC3bt1CXFyc2mAKeBEgubi4VHq8HMiVsbCwwLBhw3D06FEcO3YMWVlZCAwMxL59+9Reg7prK39dJSUlSEpKgqmpKU6cOCHNTJZJTU1VGuu5c+ciOTlZJU0T5ce1ojGuSEFBATZt2lThvxt1pk6dCoVCIR3qZvSIiIiIqss/JqDq0aMHSktLsWvXLty8eROpqakYPHgwAGDSpEnYsmULvvjiC6SmpiItLQ0tWrRAUVERAKgsQ3rZ5s2bMW7cOAwdOhT79+9HWloaQkJCpPJlXg4+ZDKZyntd6hQVFSEwMBADBw5EfHw8oqKilGYLAGD27NlIS0uTDjs7OyQkJKiklQkICMD333+P4uJirF+/Hs2aNZNm6R4/fowuXbpALpdj3bp1OH36NLZt2yb1RZMxCQ4Oxi+//ILFixfj2LFjSEtLQ+3atattTI4fP46YmBjs2LED3t7eCA0NVQkGyl97QkKCNMNTPq2Mm5sbLl++XGmbLi4ukMlkuHTpktrz6enpsLS0hLW1tZRWXFyMfv36ISsrCwcOHFCaQQJevLs1evRofPfdd3Bzc8OUKVOkDTBepu2Sv/KePXuG7777Dj179sQ777wDa2trfP3119KMbdnMTUVjkJ6eLr1HBgCLFi1CZmYmTp8+jdu3b6sER56enkpjHR4ejp49e6qkaTuuVfXzZZMmTYKhoSGOHTuGgwcPYs2aNVWWMTIyQs2aNZUOIiIiotflH7HkD3gRAHz00UdITk7G1atX4ebmhlatWgF48df04OBgfPjhhwBe/FU7OztbKtuiRQuUlpbiyJEj0pK/8lJTU+Hj44ORI0dKaWWbM2jD0NBQ2p66vNmzZ+P+/ftYsmQJatWqhe+//x4hISFITU2VlujZ2NgozU7o6+ujfv36cHFxUdtWr169MGLECOzduxfr16/HkCFDpHPp6em4d+8e5s+fDwcHBwBQepcHeDGzlJSUhOLiYrWzVKmpqYiNjcV7770H4MWW2Pfu3dN6PACojEnZrnIjRoxAp06d4ObmhubNmyM+Pl4poCh/7bm5udIMjzqDBg3CtGnTcPbsWZX3qJ4/f47CwkLUrl0bnTt3RmxsLMaNG6cUVN65cwfJyckIDAyUZk/KgqnMzEwcPnwYtWvXVmm3ZcuWWLZsGaKjo7Fz504kJSXhzTffRPPmzTFkyBAMHDhQWgKq7ZI/IQR+/vlnrF27Fps3b4ZcLsfgwYOxcOFClSVzXbp0gZWVFaKjo1U2O/nhhx+QmZkpvbd38eJFzJw5E+vWrUPTpk0RFxeHfv36oVevXtKMo4mJidJYW1lZIT8/X+34azOuLVu2RNOmTREdHY3+/furvEf16NEjaXnogQMHkJCQgNTUVHh4eGDu3LmIjIxE586dUa9evUrHkYiIiOjP8o+ZoQJezMrs2rULq1atkmangBcP3lu3bkVaWhrOnTuHQYMGKc2SODk5ISgoCEOHDpU2aEhJSZE2nXBxccGZM2ewb98+ZGRkYPr06Th9+rTW/XNycsLRo0dx69YtKfg4c+YMFixYgISEBOlBMS4uDunp6YiJidF5LMzMzODv74/p06fj8uXLGDRokHSuQYMGMDQ0xLJly3D9+nX88MMPKptgjB49Gvn5+RgwYADOnDmDzMxMrF27FleuXAHwYkzWrl2Ly5cv4+TJkwgICKhyVutljo6OkMlk2LlzJ+7evYuCggIAwJQpU1BaWooFCxZI/Y2OjsakSZOUAmFtREZG4u2338a7776Lr7/+GufOncP169exefNmeHl5Se/uLF++HIWFhejatSuOHj2KmzdvYu/evejcuTPq16+PL774AsCLIKxPnz44c+YMkpOTUVJSgjt37uDOnTsqs3TAi+Dxo48+wo4dO3Dr1i0EBgZizZo1aNasmZRH2yV/69atQ9euXfH48WNs3rwZOTk5mD9/vtr3j8zMzBAfH48dO3YgLCwM58+fR3Z2NlauXIng4GD06dMH/fr1w/PnzxEUFIQPP/wQffr0AfAiOO/bty+Cg4NVlv5pStNxlclkWL16NTIyMtC+fXvs3r0b169fx/nz5/HFF1/A398fwIudEkNDQzFx4kS0bdsWADBmzBg0a9YMYWFhOvWRiIiI6HX4RwVUHTt2hJWVFa5cuaIUQMTExMDS0hI+Pj7o0aMHunbtirfeekup7IoVK9CnTx+MHDkS7u7uGD58OB4/fgzgxftLH330Efr37w8vLy/cv39fabZKU7Nnz0Z2djacnZ1Rp04dFBYWIigoCCEhIejWrZuUz9bWFsuWLUNUVJQUwOgiICAA586dQ7t27dCgQQMpvU6dOkhMTMR3332Hpk2bYv78+Vi0aJFS2dq1a+PQoUMoKCiAr68vWrVqhW+//VaarVq1ahUePnyIN998E0OGDMGYMWMqfL+nIvXr18esWbMwZcoU1K1bF6NHj8aRI0fw9ddfIzExEWZmZlLe4cOHw8fHR+3SP00YGRnhwIEDmDx5MuLj49G2bVu0bt0aS5cuxZgxY6TfLXJ1dcWZM2fg7OyM/v37w9nZGWFhYejQoQOOHz8ubaSRm5uLH374Abm5uWjZsiXq1asnHceOHau0L3Xq1EFkZCTOnj2L//u//9P6Wsq8++670gxPly5d1O6KV16fPn1w+PBh3Lx5E+3bt0fjxo3x1Vdf4dNPP8XGjRshk8kwd+5c3Lp1C8uXL1cqu2zZMuTl5Wn8XtTLNB1XAGjTpo2Ud/jw4WjSpAl69uyJixcvSj+MHRkZCQsLC6XNJWrUqIHVq1fj0KFDGi39IyIiIvozyIQuT69ERP8Q+fn5sLCwgEKh4PtU/2FOU3b91V34T8ie//5f3QUiomqhzfPDP2qGioiIiIiI6O+EARUREREREZGOGFARERERERHpiAEVERERERGRjhhQERERERER6YgBFRERERERkY4YUBEREREREelI/6/uABER0evG30ciIqLXhTNUREREREREOmJARUREREREpCMGVERERERERDpiQEVERERERKQjBlREREREREQ6YkBFRERERESkIwZUREREREREOmJARURERNXCacquv7oLRER/OgZUREREREREOmJARUREREREpCMGVERERERERDpiQEVERERERKQjBlREREREREQ6YkBFRERERESkIwZUREREREREOmJA9Sc6dOgQ3N3dUVpa+trbat26NbZu3Vpt9fn5+UEmk0EmkyEtLe2V6srOzpbqatmyZbX0j/6eyu5zrVq1XrmuxMREqb7IyMhXro+IiIioOvwjAqqbN28iNDQUdnZ2MDQ0hKOjI8aOHYv79++jpKQEPj4+6N27t1IZhUIBBwcHREVF6dxuUVERFi5cCA8PD5iamsLa2hpvv/02Vq9ejeLiYinfnTt3EBERgUaNGsHIyAgODg7o0aMHDh48qFTf5MmT8emnn6JGDd2HvbKxKG/69OmYMmWKSvD29OlTzJw5E40bN4aRkRGsra3Rp08fXLx4scq2hw8fjry8PDRv3hyAcmAkk8lgaWmJ9u3b48iRI1IZPz8/lYdfBwcH5OXlYcKECTqOwp9D0/t67NgxvPfee7C0tISxsTFatGiB6OholJSUSHmys7MRGhqKhg0bwsTEBM7Ozpg5cyaKioqU8lQUsJYfx4KCAjg7O2P8+PFKebKzs1GzZk0kJCTofM35+fn49NNP4e7uDmNjY9ja2qJTp07YunUrhBBSvosXL6Jfv36oU6cOjIyM4OrqiunTp+PJkycqda5evRoZGRnS5/KBkUwmQ7169dCvXz9kZWVJeWQyGbZv365UT//+/ZGXlwdvb2+dr4+IiIiouv3tA6rr16/D09MTGRkZ2LBhA65evYq4uDgcPHgQ3t7eUCgUSEpKwt69e5GcnCyVi4iIgJWVFWbMmKG23pSUFDg5OVXYblFREbp27Yr58+cjLCwMx44dw6lTpzBq1CgsW7ZMCkCys7PRqlUrHDp0CAsXLsSFCxewd+9edOjQAaNGjZLqO3bsGDIzM9G3b9/XNhYPHjyQ8r7//vtQKBTYt2+flFZYWIhOnTph1apVmDNnDjIyMrB7926UlJTAy8sLJ06cqLR9U1NT2NraQl9fXyn9p59+Ql5eHo4cOYKaNWvivffeU3o4fpmenh5sbW0hl8u1uv6HDx+ioKBAqzJlnj17hrt372qcX9P7um3bNvj6+sLe3h6HDx9Geno6xo4diy+++AIDBgyQgpD09HSUlpYiPj4eFy9eRExMDOLi4jBt2jStr0Uul2P16tVYtmwZUlNTAQBCCISEhODtt9/GsGHD1JZLTEyEn59fhfU+evQIPj4+WLNmDaZOnYpff/0VR48eRf/+/TF58mQoFAoAwIkTJ+Dl5YWioiLs2rULGRkZmDt3LpKSktC5c2elIBEAatWqBRsbG6W0mjVrIi8vD7dv38b69euRlpaGnj17KgWhLzMxMYGtrS0MDQ01GSYiIiKiP4f4m+vWrZuwt7cXT548UUrPy8sTpqamIjw8XAghxJIlS4SlpaW4deuW2L59uzAwMBBnz56tsN7Dhw8LR0fHCs8vWLBA1KhRQ/z6668q54qKikRBQYEQQoju3buL+vXrS5/Le/jwofTfERERok+fPpVcadU0HYsywcHBYsiQIdLn+fPnC5lMJtLS0pTylZSUCE9PT9G0aVNRWlqqtm1fX18xduxYpbSsrCwBQGmcc3NzBQARFxcngoKCBAClIysrS8o7c+ZM4eHhUek1FxcXi507d4q+ffsKIyMjlb5rKjs7WxgYGAh/f3+xdetWUVhYWGl+Te5rQUGBqF27tvjoo49U8vzwww8CgNi4cWOFbSxcuFA0bNhQ+qxuPMuoG/9x48YJZ2dnUVBQIGJiYkStWrVEbm5uhe2tXr1a+Pr6Vnj+448/FmZmZuLWrVsq5/744w9RXFwsSktLRdOmTYWnp6coKSlRypOWliZkMpmYP3++lAZAbNu2TaUfFhYWSmnr1q0TAER6erpwdHRU+s68/O9U3VhURqFQCABCoVBoXIaIdOP4yc6/ugtERNVCm+eHv/UM1YMHD7Bv3z6MHDkSJiYmSudsbW0REBCATZs2QQiBiIgIeHh4IDAwEGFhYZgxY8YrvZ+TnJyMTp064c0331Q5Z2BgADMzMzx48AB79+7FqFGjYGZmppKv/HsjR48ehaenp9L51NRUyOXySo+5c+dqPRZl2rRpI81gAMD69evRuXNneHh4KJWvUaMGxo0bh0uXLuHcuXOaD5IapqamAIDi4mIsWbIE3t7e0lLBvLw8ODg4aFTPhQsXMHHiRNjb2yMwMBC1a9fG4cOHlfrerFmzSseuWbNmUl5HR0ccP34cjo6OGDFiBOzs7DBmzBj88ssvKm1rel/379+P+/fvY+LEiSp5evToATc3N2zYsKHCa1QoFLCystJoPNSZO3cuDAwMMHjwYEybNg3Lli1D/fr1daqrtLQUGzduREBAAOzs7FTOy+Vy6OvrIy0tDZcuXcL48eNVlq56eHigU6dOlV5zRcq+08XFxTh9+jSAF0sF8/LypM9EREREf0f6VWf562RmZkIIgSZNmqg936RJEzx8+BB3796FjY0NVqxYgSZNmqBFixaYMmXKK7dd2fIoALh69SqEEHB3d6+yvuzsbJUHVU9Pzyo3eCh74NZ2LACgfv36yMnJQWlpKWrUqIGMjAx06NChwvIAkJGRoXMg+vjxY0ydOhV6enrw9fWFhYUFDA0NpaWCVbl//z6Sk5ORmJiIixcvonv37oiNjcUHH3ygdpnX7t27ld5le5mBgYHS51atWqFVq1aIjo7Gnj17sGbNGrz99ttwdXVFUFAQhgwZgrp162p8X8veC6ronri7uyu9O1TetWvXsGzZMkRHR6uc8/HxUQlWnj59qnJfjI2NsXjxYnTr1g3du3fH4MGDK+1vZe7du4eHDx++8jU3adIEP//8s1Zt5+bm4ssvv4S9vT3c3Nyke12rVi2NvjcvKywsRGFhofQ5Pz9f6zqIiIiINPW3DqiqUjYbI5PJAACrVq2CqakpsrKykJubq/KOVPl3dkpKSlBYWKiU1q5dO+zZs0equ6xeTduvzNOnT2FsbKyUZmJiAhcXlyrLakJdX0xMTFBaWorCwkKVWS1NymuqLAB48uQJ6tWrh8TERLRo0ULrepYtW4ZZs2ahXbt2uHr1apWzWY6Ojlq3AQD6+vro0aMHevTogTt37iAwMBCTJk1Cbm4uFi9erPVYlJ8VfDldXR23b99Gt27d0LdvX7XvO23atEklYAkICFDbxsqVK2FqaooLFy5AoVDAwsJCOpeTk4OmTZtKn58/f47i4mKl7/zgwYMRFxf3Sve/PE3+3QAvZufkcjmEEHjy5AneeustbN26tVrej5o3bx5mzZr1yvUQERERaeJvveTPxcUFMpkMly5dUns+PT0dlpaWsLa2xvHjxxETE4MdO3bA29sboaGhKg+6aWlp0pGQkAA7OzuVtDJubm64fPlypf1zdXWFTCarMh8AWFtb4+HDh0pp2iz502Ysyjx48ACmpqZSMOXm5lZp+bJr0tamTZtw7tw53L17F7du3dJ5piQsLAyff/457ty5g6ZNmyI4OBgHDx6scJt5bZb8lSeEwNGjRzF8+HC4u7sjMzMTM2bMkHbN0/S+urm5AUCF+dLT01XG8/bt2+jQoQO8vb3xzTffqC3n4OAAFxcXpUNdQLxp0yb88MMP+Pnnn2FhYYFx48YpnX/5+z179mxpVrR8GgDUqVMHlpaWGl9zZd8jTb5D5ubmSEtLw4ULF1BQUIBffvkFrVu3rrKcJqZOnQqFQiEdN2/erJZ6iYiIiNSq7he4qluXLl1E/fr1K92I4cmTJ8LV1VWMGjVKCCHEjRs3hLm5uVixYkWF9Va1KcX8+fMr3JSiuLhY2qygW7duGm1K8f7776u8SP/kyRORmZlZ6XH//n2txqK8qKgo8c4770if586d+9o3pXhZ586dxejRo9Weq2xTiv/7v/8TYWFhwsLCQtjb24tPPvlE/Pbbb0p5srOzKx277OxspfxXrlwRUVFRwsnJScjlchEcHCwOHz6s9po1ua8FBQXCyspK7aYUO3bsUNmUIjc3V7i6uooBAwaI58+fq5TRZlOKO3fuiNq1a4svv/xSCCHE6dOnhb6+vti9e7dK2TJVbUoRHh5e4aYUBQUF0qYU7u7u1b4pxcsMDAzE999/r/YcN6Ug+vviphRE9G+hzfPD3z6gysjIENbW1qJdu3biyJEjIicnR+zZs0c0b95cuLq6ivv374sxY8ZIu52V+eabb4RcLlfaVa68qgKqZ8+eiXbt2glLS0uxfPlykZaWJq5duyY2bdok3nrrLemh9/r168LW1lY0bdpUfP/99yIjI0NcunRJLFmyRLi7u0v1LV26VLRq1eq1j0V5vr6+Yvbs2dLnp0+fCi8vL+Hg4CA2b94sbty4IU6dOiV69eolzMzMxPHjx6W8HTt2FMuWLVOqS5eAavjw4aJ169YiKytL3L17V+khXJNd/p4+fSo2bNggunXrJvT09MT58+crzV+RGzduiBo1aoiOHTuKpKQktYFSeZre1++++07o6emJ4cOHi3PnzomsrCyRkJAgLC0tRZ8+faRg7datW8LFxUV07NhR5Obmiry8POkoo01A5e/vL3x8fJTGc9q0acLe3l48evRI7TVVFVA9ePBAuLu7C3t7e5GUlCQuXrwoMjIyxMqVK4WLi4sUSP7888/C1NRU9OrVS5w8eVLcuHFDbN68WTg4OAgfHx/x7NkzqU5dAypXV1fx8ccfi7y8PPHgwYNKx6IqDKiI/jwMqIjo3+JfFVAJ8WImIjg4WNja2goDAwPh4OAgIiIixL1790RKSorQ09MTqampKuW6dOkiOnbsqHYGoqqASogXQdW8efNEixYthLGxsbCyshJvv/22SExMFMXFxVK+27dvi1GjRglHR0dhaGgo6tevL3r27CkOHz4s5Xnw4IEwMTER6enpOo+DEJWPRXm5ubnCwMBA3Lx5Uyn98ePHIioqSri4uAgDAwNhZWUlevfuLS5cuKCUz9HRUcycOVP6rGtAdeXKFdG2bVthYmKi07bp5d26dUvnh+LHjx+LGzduaFVGk/sqhBBHjx4V3bp1ExYWFsLQ0FA0bdpULFq0SGkWavXq1SpbyJcdZTQNqJKSkoSpqanIyMhQylNYWCiaN28uQkJC1F5PVQGVEEI8evRITJkyRbi6ugpDQ0NRt25d0alTJ7Ft2zalf0fnz58XvXv3FrVr1xYGBgbC2dlZREVFicePHyvVp2tA9cMPPwgXFxehr6/PbdOJ/kEYUBHRv4U2zw8yISp4o56qXdmPo8bHx7/2tiZNmgSFQlHhezra8vPzQ8uWLbF48eJqqQ8APvvsM2zfvr3KnQ7pn0smk2Hbtm3o1atXtdWp7XcxPz8fFhYWUCgUqFmzZrX1g4hUOU3Zhez57//V3SAiemXaPD/8rTel+Lf59NNP4ejoiJKSktfelo2NDebMmVOtdcbGxkIul+PChQuvVE9OTo7Shhv07zZw4EDY29u/cj3JycmQy+VKv61GRERE9FfjDBVp5NatW3j69CkAoEGDBq+0vfXz58+RnZ0NADAyMtL4x37pn+fq1asAAD09PTRs2PCV6vrjjz/wv//9D8CL36gqv6NlZThDRfTn4QwVEf1baPP88I/+HSr689SvX7/a6tLX16+239+iv7fqvM/m5uYwNzevtvqIiIiIqgOX/BEREREREemIARUREREREZGOGFARERERERHpiAEVERERERGRjhhQERERERER6YgBFREREVULbplORP9FDKiIiIiIiIh0xICKiIiIiIhIRwyoiIiIiIiIdMSAioiIiIiISEcMqIiIiIiIiHTEgIqIiIiIiEhHDKiIiIiIiIh0xICKiIiIiIhIRwyoiIiIiIiIdMSAioiIiIiISEcMqIiIiIiIiHTEgIqIiIiIiEhHDKiIiIiIiIh0xICKiIiIiIhIRwyoiIiIiIiIdMSA6j9gyJAhmDt37mtv58KFC7C3t8fjx4+V0p2cnCCTySCTyfDo0aNXaiMlJUWqq1evXq9UFxERERHRq/rHB1Q3b95EaGgo7OzsYGhoCEdHR4wdOxb3799HSUkJfHx80Lt3b6UyCoUCDg4OiIqK0rndp0+fYubMmWjcuDGMjIxgbW2NPn364OLFi696Sbh69SpCQkJgb28PIyMjNGzYEAMHDsSZM2eU8h0+fBjvvfceateuDVNTUzRt2hQTJkzArVu3pDznz5/Hrl27EBER8Up92rlzJ/z8/GBubg5TU1O0bt0aiYmJSnlatGiBNm3aICYmRqX87NmzkZeXBwsLCwDKgZFMJkOdOnXQvXt3nDt3Tirj5OSExYsXK9Xj4+ODvLw89OvX75Wu53W7ePEi+vXrhzp16sDIyAiurq6YPn06njx5opL37Nmz6Nu3L+rWrQtjY2O4ublh+PDhyMjIAADs3r0bhoaG+PXXX5XKLVq0CNbW1rhz547O/ayq7ezsbMhkMqSlpamU9fPzQ2RkpNbX/eDBA0RERKBx48YwNTVFgwYNMGbMGCgUCinPuXPnYGRkhB9++EGp/i1btsDY2Bi//fabztdMREREVJ3+0QHV9evX4enpiYyMDGzYsAFXr15FXFwcDh48CG9vbygUCiQlJWHv3r1ITk6WykVERMDKygozZsxQW29KSgqcnJwqbLewsBCdOnXCqlWrMGfOHGRkZGD37t0oKSmBl5cXTpw4ofM1nTlzBq1atUJGRgbi4+Nx6dIlbNu2De7u7pgwYYKULz4+Hp06dYKtrS22bNmCS5cuIS4uDgqFAtHR0VK+5cuXo2/fvjA3N9e5T8uWLYO/vz98fHxw8uRJnD9/HgMGDEB4eDgmTpyolDckJAQrVqxASUmJUrq5uTlsbW0hk8mU0q9cuYK8vDzs2rULDx8+RLdu3ZQerF9maGgIW1tbmJiYaHUNeXl5eP78uVZlyjx69Aj5+fka5z9x4gS8vLxQVFSEXbt2ISMjA3PnzkVSUhI6d+6MoqIiKe/OnTvRtm1bFBYWIjk5GZcvX8batWthYWGB6dOnAwDee+89BAYGIjAwEIWFhQCAy5cvY/r06fj6669ha2urth9+fn4qQW95mrStDU2v+/bt27h9+zYWLVqECxcuIDExEXv37kVoaKhUl4eHB6ZPn46wsDDcv38fAPD7778jPDwcs2bNQvPmzbXuHxEREdFrIf7BunXrJuzt7cWTJ0+U0vPy8oSpqakIDw8XQgixZMkSYWlpKW7duiW2b98uDAwMxNmzZyus9/Dhw8LR0bHC8/PnzxcymUykpaUppZeUlAhPT0/RtGlTUVpaqvX1lJaWimbNmolWrVqJkpISlfMPHz4UQghx8+ZNYWhoKCIjI9XWU5avpKRE1KpVS+zcuVPrvpTJyckRBgYGYvz48Srnli5dKgCIEydOSGmFhYXCyMhIHDx4UEpzdHQUMTExSmUPHz4sAEh9FUKIn3/+WQAQe/fuFb6+vgKA0lFeUFCQ8Pf3r7TvT58+FRs3bhTdu3cXenp64tGjR5pfeDkpKSnCxMREBAQEiP3796u9N2VKS0tF06ZNhaenp0q+tLQ0IZPJxPz584UQQjx+/FhYW1uLXr16qa2r/Njk5+cLR0dH8cknn4ji4mLh6ekp+vbtW2m/fX19xerVq9We07TtrKwsAUDtvxdfX18xduxYIYR2163O5s2bhaGhoSguLpbSnj9/Llq3bi369+8vhBCiV69ewtvbWzx//rzCetRRKBQCgFAoFFqVIyIiov8ubZ4f/rEzVA8ePMC+ffswcuRIldkKW1tbBAQEYNOmTRBCICIiAh4eHggMDERYWBhmzJiBli1b6tz2+vXr0blzZ3h4eCil16hRA+PGjcOlS5ekpWvJycmQy+WVHmWzZ2lpabh48SImTJiAGjVUb02tWrUAAN999x2KioowefJktf0ry3f+/Hk8evQInp6eSufDw8Or7FNOTg4A4Pvvv0dxcbHKTBQAjBgxAnK5HBs2bJDSDA0N4eHhgdTUVA1GUlnZfSwuLsbWrVthb28vLRXMy8vTuJ7jx48jPDwc9erVw/jx49GsWTOkpaVJyw0BVHn93bt3l/K2b98ee/bsgZGREfr06QNHR0dMmzYNV65cUWk7LS0Nly5dwvjx41XuoYeHBzp16iSN1759+3Dv3r0q7yPwYoZv1apViI6ORkBAAG7evInY2FiNx+Rl2rStCW2uWx2FQoGaNWtCX19fStPT00NSUhJ27NiBQYMGYd++fUhMTISenl6lfSksLER+fr7SQURERPS66Fed5e8pMzMTQgg0adJE7fkmTZrg4cOHuHv3LmxsbLBixQo0adIELVq0wJQpU16p7YyMDHTo0KHCdsvytGzZEj179oSXl1el9dWtWxfAi2sCAHd390rzZ2ZmombNmqhXr16l+bKzs6GnpwcbGxul9NmzZ6sNkMqzs7OTrsPCwkJtW4aGhmjUqJH0vk2Z+vXrIzs7u9L6X3b//n3MmjUL5ubmaNOmDaysrKCnpyctFaxKbm4u1qxZg6SkJOTm5uLDDz/Epk2b0KlTJ7XBqbp3gsorH6TLZDL4+vrC19cXy5cvx/bt27FmzRp8+eWXaNWqFYKCgjBo0CBYWFhIY1HZ9/Lnn38GoPn9LtOxY0f06dMHGzduxKZNm2Btba1ROXW0bdvHx0dlHJ8+fSr9YUKb637Z/fv3MWfOHIwYMUJtucjISMyfPx8LFiyAm5tblX2dN28eZs2aVWU+IiIiourwjw2oqiKEAADpnZ1Vq1bB1NQUWVlZyM3NVXlHSi6XS/9dUlKCwsJCpbR27dphz549Wrdrbm6u8ftLL5etLF9VeYAXD7xGRkYqeW1sbFSCLF2p64uJiYnazRfUsbe3BwA8fvwYrq6u+O6773TqW1RUFJKSkvDRRx/h+PHjsLKyqjS/i4uL1m0AL65t4MCBGDhwIDIyMjBw4ECMHDkShYWFKhs0qFN+vMrut6Zu376NvXv3wtTUFKmpqSobc8ydO1dpN8enT5/ixIkTGD16tJS2Z88etGvXTuu2N23apBIsBQQEaFy+ou9sfn4+3n//fTRt2hQzZ85UOV9QUIBNmzZJ11zRjFp5U6dOxfjx45XacHBw0LivRERERNr4xy75c3FxgUwmw6VLl9SeT09Ph6WlJaytrXH8+HHExMRgx44d8Pb2RmhoqMoDZVpamnQkJCTAzs5OJa2Mm5tbpe0CgKurKwDtlvyV/fX98uXLlV67m5sbFApFlcvgrK2t8eTJE6VNEADtlvyVtXX79m2V+ouKinD9+nXpWss8ePAAderUqbRvZVJTU3Hu3DkoFApkZGSga9euGpV7WVRUFKZMmYKTJ0/Czc0No0ePxsmTJyvMr82Sv/KeP3+OPXv2YODAgWjZsiUKCwuxYMECKbgou4eVfT/Kxqssb9l3pirDhg2Dh4cHdu/ejRUrVuDIkSNK58PDw5W+s56enpg9e7ZKmi5tOzg4wMXFRekoP4unzXWX+eOPP9CtWzfI5XJs27YNBgYGKuUmTZoEQ0NDHDt2DAcPHsSaNWuq7KuRkRFq1qypdBARERG9Nq/pPa4/RZcuXUT9+vUr3ZTiyZMnwtXVVYwaNUoIIcSNGzeEubm5WLFiRYX1VrUpxdy5czXelCI/P19kZmZWeuTn5wsh/v+L/VVtSpGTk6PRphS///672g0F/ve//1XZp7LNAW7cuCH09fXVbkqxZMkSlU0phBDC3t5eJCQkSJ813ZTiZa6urmLRokVqz1W0KUVJSYnYt2+fGDRokDAxMRGurq5i9uzZ4vr160r5qrr+3Nxcpfy//vqriIyMFHXr1hW1a9cWo0ePFqdPn1Zpv7S0VLi7u2u0OUNBQYHGm1J8++23Qi6XS9cxduxY0ahRI1FQUKC2rBCVb0qhadvabEqh6XUL8eJFz7Zt2wpfX1/x+PFjtX3Yv3+/0NfXF8ePHxdCCBETEyMsLS3F7du3K7xmdbgpBREREWlLm+eHf3RAlZGRIaytrUW7du3EkSNHRE5OjtizZ49o3ry5cHV1Fffv3xdjxowRzs7OSg+e33zzjZDL5SIrK0ttvVUFVE+fPhVeXl7CwcFBbN68Wdy4cUOcOnVK9OrVS5iZmUkPgLo4efKkMDc3F2+//bbYtWuXuHbtmjh37pz4/PPPRfv27aV8X3/9tZDJZGLo0KEiJSVFZGdni59//lmEhYUpBT9vvfWWWLZsmc79EUKIr776StSoUUNMmzZNXL58WVy9elVER0cLIyMjMWHCBKW8WVlZQiaTiezsbClN14Cqc+fOomfPniI3N1fcvXtX6Zwmu/wpFArx7bffinfeeUfUqFFD5wfqo0ePCgMDA9GzZ0+xZcsWUVhYWGn+n3/+WZiamopevXqJkydPihs3bojNmzcLBwcH4ePjI549eyblLdt1skePHuLAgQMiKytLnD59WkyaNEna3e7GjRuiZs2aIi4uTir3+PFj4eLiIkaPHl1hPyoLqDRtW9OASpvrzs/PF15eXqJFixbi6tWrIi8vTzrKdvBTKBTCwcFBTJkyRaq/pKREvPPOO+KDDz6oePDVYEBFRERE2vrPBFRCCJGdnS2Cg4OFra2tMDAwEA4ODiIiIkLcu3dPpKSkCD09PZGamqpSrkuXLqJjx45qtzevKqAS4sUDbVRUlHBxcREGBgbCyspK9O7dW1y4cOGVr+nKlSsiMDBQ2NnZCUNDQ+Ho6CgGDhwofv31V6V8Bw4cEF27dhWWlpbC2NhYuLu7i4kTJyr9BT8uLk60bdv2lfu0Y8cO0a5dO2FmZiaMjY1Fq1atxKpVq1TyzZ07V3Tt2lUpTdeA6vjx4+KNN94QRkZGOm2bXt7Vq1dFUVGRxvnLu3fvnvj999+1KnP+/HnRu3dvUbt2bWFgYCCcnZ1FVFSU2tmY06dPi48++kjUqVNHGBkZCRcXFxEWFiYyMzNFaWmpePfdd0WXLl1UyqWmpgo9PT2RkpKitg9VBVRVtS2EdgGVptdddu/VHWV/5AgJCRHNmzdXCV4zMzOFqampSEpKqvS6ymNARURERNrS5vlBJoSWb6fTP8qzZ8/QuHFjbNy4Ed7e3q+1rcLCQri6umLDhg14++23pXQnJydERkZqtGmDpoKDg/Ho0SNs37692uqkf6f8/HxYWFhIW7MTERERVUWb54d/7KYUpBljY2OsWbMG9+7de+1t3bhxA59++qlSMFXmk08+gVwuh0KheKU2UlNTlTbyICIiIiL6K3GGil67GzduoLi4GADQqFEjtb8LpamnT5/i1q1bAF7s1KfJb1TRfxtnqIiIiEhb2jw//Gt/h4r+PhwdHautLhMTE51/Q4qIiIiIqLpxyR8REREREZGOGFARERERERHpiAEVERERERGRjhhQERERERER6YgBFRERERERkY4YUBEREREREemIARUREREREZGOGFARERERERHpiAEVERERERGRjhhQERERERER6YgBFRERERERkY4YUBEREREREemIARUREREREZGOGFARERERERHpiAEVERERERGRjhhQERERERER6YgBFRERERERkY4YUBEREREREemIARUREREREZGOGFARERERERHp6F8ZUH322WeQyWSQyWRYvHjxK9fn5OQk1ffo0aNXru/PxvH4+8nOzpbGsGXLlq9cX3Xf4+ri5+cn9SstLe2V6qruMSMiIiKqDq89oLp58yZCQ0NhZ2cHQ0NDODo6YuzYsbh//z5KSkrg4+OD3r17K5VRKBRwcHBAVFSUzu02a9YMeXl5CAsLk9LKBwKmpqZo3rw54uPjpfOfffaZ2ge106dPY8uWLTr3pcydO3cQERGBRo0awcjICA4ODujRowcOHjyolO/s2bPo27cv6tatC2NjY7i5uWH48OHIyMjQue2/43i8TkVFRVi4cCE8PDxgamoKa2trvP3221i9ejWKi4sBAMHBwejVq5dK2ZSUFKVgMTY2FrVq1cLNmzeV8o0ePRpubm548uSJzv386aeflO5/+cBIT08PDg4OGDZsGO7evQvg/wcVLwcnEydORF5eHuzt7VXa2LlzJ/z8/GBubg5TU1O0bt0aiYmJavuzZcsW+Pn5wcLCAnK5HG+88QZmz56NBw8e6HyNw4cPR15eHpo3b650DWWHpaUl2rdvjyNHjkhl/Pz8EBkZqVSPg4MD8vLyMGHCBJ37QkRERFTdXmtAdf36dXh6eiIjIwMbNmzA1atXERcXh4MHD8Lb2xsKhQJJSUnYu3cvkpOTpXIRERGwsrLCjBkz1NabkpICJyenStvW19eHra0tTE1NldJnz56NvLw8nD9/Hr169UJ4eDg2bdpUaV116tSBlZWVZhddgezsbLRq1QqHDh3CwoULceHCBezduxcdOnTAqFGjpHw7d+5E27ZtUVhYiOTkZFy+fBlr166FhYUFpk+frnP7f/V4FBUV4c6dO1r3u0xOTo5WbXXt2hXz589HWFgYjh07hlOnTmHUqFFYtmwZLl68qFXbH3/8Mdq0aYPQ0FAp7dChQ4iPj0diYqLKmJZxcnJCSkpKpXXXrl0btWvXVkorC35zcnKwYsUK/PjjjwgMDKy0HrlcDltbW+jp6SmlL1u2DP7+/vDx8cHJkydx/vx5DBgwAOHh4Zg4caJS3k8//RT9+/dH69atsWfPHvz222+Ijo7GuXPnsHbt2krbr4ypqSlsbW2hr6+vlP7TTz8hLy8PR44cQc2aNfHee+8hKyurwnr09PRga2sLuVyuc1+IiIiIqp14jbp16ybs7e3FkydPlNLz8vKEqampCA8PF0IIsWTJEmFpaSlu3boltm/fLgwMDMTZs2crrPfw4cPC0dGxwvMzZ84UHh4eKumOjo4iJiZGKc3V1VUMGDBArF69WgBQOlavXq3UJgDx8OHDKq5ave7du4v69euLgoIClXNldT5+/FhYW1uLXr16qa1D17b/yvE4c+aMiIiIELVr1xaLFy/Wqf9CCOHk5CS8vLxEbGysePDgQaV5FyxYIGrUqCF+/fVXlXNFRUXSPQgKChL+/v4qedRdW05OjrCwsBArVqwQCoVCNGjQQEyaNKnSfjg6OorDhw+rPZeVlSUAqHzP1d2rzz//XNSoUUM8efJE5Z74+vqqtFl2T3NycoSBgYEYP368SvtLly4VAMSJEyeEEEKcPHlSAKjwHun63fP19RVjx45VSlN37bm5uQKAiIuLE0FBQSrXmZWVJeWt6PtcEYVCIQAIhUKh0zUQERHRf482zw+vbYbqwYMH2LdvH0aOHAkTExOlc7a2tggICMCmTZsghEBERAQ8PDwQGBiIsLAwzJgx4097R8LY2BjFxcXo378/JkyYIM0O5OXloX///hWWS01NhVwur/SYO3cugBdjsXfvXowaNQpmZmYqddWqVQsAsG/fPty7dw+TJ09W22ZZPgBVtt29e/c/dTzKy8vLw5dffonmzZvDx8cHubm5SEhIwMiRI6U84eHhVV5D+Vmpo0ePomfPnli6dCnq1auHfv36YdeuXXj+/LlK+8nJyejUqRPefPNNlXMGBgZq70FVHBwcEBMTg0mTJmHw4MGQy+WYM2eO1vXowsTEBKWlpXj+/DlOnToF4P/P7mzdurXCct9//z2Ki4tVZqIAYMSIEZDL5diwYQOAF2Mml8uV7lF5Zd89bb732iib5SsuLsaSJUvg7e0tLRXMy8uDg4OD1nUSERER/Rn0q86im8zMTAgh0KRJE7XnmzRpgocPH+Lu3buwsbHBihUr0KRJE7Ro0QJTpkx5Xd2SPH/+HOvWrcOFCxfw8ccfw8TEBHK5XFoaVxVPT88qX7IvWxZ39epVCCHg7u5eaf7MzEwAqDIfgCrbfjmIrcqrjkdRURG2bduGpKQkHDhwAJ6enhg1ahT69++vdnng7Nmz1T7ol2dnZyf9t4ODA6ZNm4Zp06bh9OnTWLNmDYKDg6Gvr4+AgAAEBwdL7+hkZmbCz89Po+veuXOnyhKykpIStXlDQkLwzTff4Mcff8TJkydhZGSkURuvIj09HStWrECbNm1gbm6OOnXqAHixVLCq+5KRkQELCwvUq1dP5ZyhoSEaNWokvZeXmZmJRo0awcDAoNI6tfnea+rx48eYOnUq9PT04OvrCwsLCxgaGkpLBbVVWFiIwsJC6XN+fr7WdRARERFp6rUFVFURQgAAZDIZAGDVqlUwNTVFVlYWcnNzVd6RKv/QW1JSgsLCQqW0du3aYc+ePVW2+8knnyAqKgqFhYUwNDTEpEmTMGLECK37b2JiAhcXF43yvnytVeXThKZtV6W6xuPYsWMYMGAAHBwccOjQIbRr167S/DY2NrCxsdGpz61bt0br1q0RHR2NqVOn4quvvsJPP/0kPegLIaoc6zIdOnTAihUrlNJOnjyJwYMHq+Q9d+4cfvnlF5iamiI1NRVt2rRROh8eHo5169ZJn588eYLu3bsrvdd06dIlNGjQoNI+XbhwAXK5XPqe+/n54ZtvvtHoerRRfpw0HTNtvvdV8fHxQY0aNfDkyRPUq1cPiYmJaNGixSvXO2/ePMyaNasaekhERERUtde25M/FxQUymQyXLl1Sez49PR2WlpawtrbG8ePHERMTgx07dsDb2xuhoaEqwUVaWpp0JCQkwM7OTiVNE5MmTUJaWhpu3LiBgoICLFy4EDVqaD8M2ix9cnV1hUwmw+XLlyut083NTRqbqlTXkr/qGo82bdrg22+/haOjIzp27Iju3btj/fr1Fe6Ap+2Sv/KuXLmCqKgouLm5YdWqVRg+fLhSwOHm5lblWJcxMzODi4uL0lG/fn2VfEVFRQgMDMTAgQMRHx+PqKgolV0XZ8+erfSdtLOzQ0JCgkpaVRo3boy0tDRcunQJT58+xaFDh3QKYtzc3KBQKHD79m2113P9+nW4urpKea9duybtgFiR6lzyt2nTJpw7dw53797FrVu31Aaxupg6dSoUCoV0vLw7IxEREVF1em0zVLVr10bnzp0RGxuLcePGKS1Bu3PnDpKTkxEYGIhnz54hKCgII0aMQKdOneDm5iZt3x0eHi6VKf9AmZubC319fZ0eMq2trSssZ2hoWOFyr5dps/TJysoKXbt2xddff40xY8aovMPz6NEj1KpVC126dIG1tTUWLlyIbdu2qdRXlg+oviV/1TUepqamGDZsGIYNG4Zr164hKSkJn376KUaMGIHevXsjMDAQfn5+UrCm7ZK/e/fuYePGjVi7di1++eUXdO7cGfPnz0evXr1gbGysVG7QoEGYNm0azp49q/Ie1fPnz1FYWKj1e1SzZ8/G/fv3sWTJEtSqVQvff/89QkJCkJqaKl3Ty7Nu+vr6qF+/vtbfU0NDw0rvCVDxssTyevfujcmTJyM6OhrR0dFK5+Li4vD48WMMHDgQwIsxW7p0KWJjYzF27FiVusq+e9W55M/BwQHOzs5qz2nz3XuZkZHRn7Ick4iIiAh4zUv+li9fDh8fH3Tt2hWff/45GjZsiIsXL2LSpEmoX78+vvjiC0yZMgWlpaVYsGABAKBBgwaIjo7G+PHj0a1btyq3R69OTk5OyMrKQlpaGuzt7WFubl7hg5m2S59iY2Ph4+ODNm3aYPbs2XjjjTfw/PlzHDhwACtWrMDly5dhZmaGhIQE9O3bFz179sSYMWPg4uKCe/fuYfPmzcjJycHGjRsBVN+Sv8poMx7lOTs7Y/bs2Zg1axaOHDmCpKQk+Pv7Y+7cuYiIiACg/ZI/Ly8vGBsbIygoCNu3b1f7XlCZyMhI7Nq1C++++y7mzJmDd955B+bm5jhz5gwWLFiAlStXarXpSVm5H3/8UQpo4+Li0KxZM8TExPypv4tkY2MDExMT7N27F/b29jA2NoaFhYXavA0aNMDChQsxceJEGBsbY8iQITAwMMCOHTswbdo0TJgwAV5eXgBejO/kyZMxYcIE3Lp1Cx9++CHs7Oyknzp45513MHbs2Gpd8lcZJycnnDx5EtnZ2ZDL5bCystJp5pSIiIjodXutTyiurq44c+YMnJ2d0b9/fzg7OyMsLAwdOnTA8ePHceHCBXz99ddITExUmjEYPnw4fHx81C79e5169+6Nbt26oUOHDqhTp460A1p1aNiwIX799Vd06NABEyZMQPPmzdG5c2ccPHhQ6R0ef39/HDt2DAYGBhg0aBDc3d0xcOBAKBQKfP7559XWH0286njIZDL4+flh9erVuHPnjtof0dXUrl27cPHiRUyePLnSYAp4MUNx4MABTJ48GfHx8Wjbti1at26NpUuXYsyYMdLmFZooLCxEUFAQQkJC0K1bNynd1tYWy5YtQ1RUFK5cuaLzdWlLX18fS5cuRXx8POzs7ODv719p/nHjxmHbtm1ITU2Fp6cnmjdvjvXr12PFihVYtGiRUt4FCxZg/fr1OHnyJLp27YpmzZph/PjxeOONNxAUFPQ6L0vFxIkToaenh6ZNm6JOnTpa/Q4ZERER0Z9JJv7MiOVP8tlnn2H79u1VLk3SRkpKCjp06ICHDx8qbV/+T8Dx+PvJzs5Gw4YNcfbs2Wr9iQAnJydERkYiMjKy2up8FX5+fmjZsiUWL15cbXVq+33Oz8+HhYUFFAoFatasWW39ICIion8vbZ4f/rVraMp2SouNjX3lupo1a6bz7zr9XXA8/p58fHzg4+PzyvXMnTu30o08/kqxsbGQy+W4cOHCK9WTk5Oj8+9cEREREb0u/8oZqgcPHuDBgwcAgDp16lT4jommbty4Ie1+1qhRo3/cuxwcj7+f58+fIzs7G8CLJYqv+sO11X2Pq8utW7fw9OlTAC/e6SrbVEMXuo4ZZ6iIiIhIW9o8P/wrAyoiojIMqIiIiEhbXPJHRERERET0J2BARUREREREpCMGVERERERERDpiQEVERERERKQjBlREREREREQ6YkBFRERERESkIwZUREREREREOmJARUREREREpCMGVERERERERDpiQEVERERERKQjBlREREREREQ6YkBFRERERESkIwZUREREREREOmJARUREREREpCMGVERERERERDpiQEVERERERKQjBlREREREREQ6YkBFRERERESkIwZUREREREREOmJARUREREREpCMGVERERERERDr6xwRUn332GWQyGWQyGRYvXvzK9Tk5OUn1PXr06JXr+7NxPP6eqnMcU1JSpLp69epVLf37s3E8iIiI6N9Op4Dq5s2bCA0NhZ2dHQwNDeHo6IixY8fi/v37KCkpgY+PD3r37q1URqFQwMHBAVFRUTp3tlmzZsjLy0NYWJiUVv6BzdTUFM2bN0d8fLx0/rPPPkPLli1V6jp9+jS2bNmic1/K3LlzBxEREWjUqBGMjIzg4OCAHj164ODBg0r5zp49i759+6Ju3bowNjaGm5sbhg8fjoyMDJ3b/juOx+uSmJiIWrVqqT0nk8mwfft2pbSdO3fCz88P5ubmMDU1RevWrZGYmCidP3fuHIyMjPDDDz8olduyZQuMjY3x22+/6dzX2bNnIy8vDxYWFgCUAwGZTIY6deqge/fuOHfunFTGyclJJTD28fFBXl4e+vXrp9LG1atXERISAnt7exgZGaFhw4YYOHAgzpw5o3O/hRD45ptv4OXlBblcjlq1asHT0xOLFy/GkydPdK73zxgPIiIior+K1gHV9evX4enpiYyMDGzYsAFXr15FXFwcDh48CG9vbygUCiQlJWHv3r1ITk6WykVERMDKygozZsxQW29KSgqcnJwqbVtfXx+2trYwNTVVSi97YDt//jx69eqF8PBwbNq0qdK66tSpAysrK80uugLZ2dlo1aoVDh06hIULF+LChQvYu3cvOnTogFGjRkn5du7cibZt26KwsBDJycm4fPky1q5dCwsLC0yfPl3n9v/q8SgqKsKdO3e07neZnJwcnctWZtmyZfD394ePjw9OnjyJ8+fPY8CAAQgPD8fEiRMBAB4eHpg+fTrCwsJw//59AMDvv/+O8PBwzJo1C82bN1dbd3BwMD777LNK2zc3N4etrS1kMplS+pUrV5CXl4ddu3bh4cOH6NatGxQKRYX1GBoawtbWFiYmJkrpZ86cQatWrZCRkYH4+HhcunQJ27Ztg7u7OyZMmFDV8FRoyJAhiIyMhL+/Pw4fPoy0tDRMnz4dO3bswP79+3Wu93WPBxEREdFfSmipW7duwt7eXjx58kQpPS8vT5iamorw8HAhhBBLliwRlpaW4tatW2L79u3CwMBAnD17tsJ6Dx8+LBwdHSs8P3PmTOHh4aGS7ujoKGJiYpTSXF1dxYABA8Tq1asFAKVj9erVSm0CEA8fPqziqtXr3r27qF+/vigoKFA5V1bn48ePhbW1tejVq5faOnRt+68cjzNnzoiIiAhRu3ZtsXjxYp36L4QQTk5OwsvLS8TGxooHDx5Umnf16tXCwsJC7TkAYtu2bUIIIXJycoSBgYEYP368Sr6lS5cKAOLEiRNCCCGeP38uWrduLfr37y+EEKJXr17C29tbPH/+vMJ+BAUFiZkzZ1Z4Xt34qxvXn3/+WQAQe/fuFb6+vir35eU2/f39hRBClJaWimbNmolWrVqJkpISlfZ1/T5t2rRJABDbt29XOVdaWioePXqkU72vezw0oVAoBAChUCh0ugYiIiL679Hm+UGrGaoHDx5g3759GDlypMpfiW1tbREQEIBNmzZBCIGIiAh4eHggMDAQYWFhmDFjhtqlZq+DsbExiouL0b9/f0yYMEFaGpeXl4f+/ftXWC41NRVyubzSY+7cuQBejMXevXsxatQomJmZqdRVtjxt3759uHfvHiZPnqy2zfLL2Kpqu3v37n/qeJSXl5eHL7/8Es2bN4ePjw9yc3ORkJCAkSNHSnnCw8OrvIbys1JHjx5Fz549sXTpUtSrVw/9+vXDrl278Pz5c52uEwC+//57FBcXSzNR5Y0YMQJyuRwbNmwAAOjp6SEpKQk7duzAoEGDsG/fPiQmJkJPT0/n9jVV9u+nuLgYW7duhb29vTSzmJeXV2G5tLQ0XLx4ERMmTECNGqr/fMt/n5o1a1bpvWjWrJmUNzk5GY0bN4a/v79KnTKZTFqul5ycXOU9Lj8z/brHQ53CwkLk5+crHURERESvi742mTMzMyGEQJMmTdSeb9KkCR4+fIi7d+/CxsYGK1asQJMmTdCiRQtMmTKlWjpcmefPn2PdunW4cOECPv74Y5iYmEAul0tL46ri6emJtLS0SvOULYu7evUqhBBwd3evNH9mZiYAVJkPQJVta7vU6VXHo6ioCNu2bUNSUhIOHDgAT09PjBo1Cv3791e7PHD27NlqA5ny7OzspP92cHDAtGnTMG3aNJw+fRpr1qxBcHAw9PX1ERAQgODgYKWldwqFAnK5vNL6MzIyYGFhgXr16qmcMzQ0RKNGjZTeW2vSpAkiIyMxf/58LFiwAG5ubpXWXx3u37+PWbNmwdzcHG3atIGVlRX09PSkpXGV0eb7tHv3bhQXF1d43sDAQKnexo0bV1lnz5494eXlVWmeunXrVllPea8yHurMmzcPs2bN0rocERERkS60CqiqIoQAAOldiVWrVsHU1BRZWVnIzc1VeUeq/MNxSUkJCgsLldLatWuHPXv2VNnuJ598gqioKBQWFsLQ0BCTJk3CiBEjtO6/iYkJXFxcNMr78rVWlU8TmrZdleoaj2PHjmHAgAFwcHDAoUOH0K5du0rz29jYwMbGRqc+t27dGq1bt0Z0dDSmTp2Kr776Cj/99JNSkGlubo5ff/1Vpayrq6vG7QghlO5ZQUEBNm3aBFNTU6SmpqrMJCYnJyuNXWFhIWQyGRYtWiSlxcfHIyAgoMq27e3tAQCPHz+Gq6srvvvuO63HS9PvHQA4OjpqVa8mdZqbm8Pc3FzjeitTHeOhztSpUzF+/Hjpc35+PhwcHF65XiIiIiJ1tAqoXFxcIJPJcOnSJbXbFqenp8PS0hLW1tY4fvw4YmJisGfPHixcuBChoaH46aeflB7ayj8snzx5Ep988glSUlKkNE1nZCZNmoTg4GCYmpqiXr16Gj0YqpOamlrlsrqyGRVXV1fIZDJcvny50i2cy2Y80tPT4e3tXWndVc2+aBpgVtd4tGnTBt9++y2SkpLQsWNHdOrUCUOGDEGvXr1UNsIAXiz5W7duXaV1Xrp0CQ0aNFBJv3LlCtauXYt169ZBoVBg+PDhCA0NVcpTo0aNKoNONzc3KBQK3L59W2k2DHgx43b9+nV07NhRSps0aRIMDQ1x7NgxeHt7Y82aNQgMDJTOvzwj88knn6B+/foYM2aMlKbpjExqaipq1qyJOnXqoGbNmhqVUXd9AHD58uUql9A2a9YMN27cqPC8o6MjLl68KNV7+fLlKtt/OcBUR9MAszrGQx0jIyMYGRlVW31EREREldEqoKpduzY6d+6M2NhYjBs3TinguXPnDpKTkxEYGIhnz54hKCgII0aMQKdOneDm5iZt3x0eHi6VKf9wnJubC319fZ1maaytrSssZ2hoiJKSEo3q0WbJn5WVFbp27Yqvv/4aY8aMUXmP6tGjR6hVqxa6dOkCa2trLFy4ENu2bVOprywfUH1L/qprPExNTTFs2DAMGzYM165dQ1JSEj799FOMGDECvXv3RmBgIPz8/KR3ebRd8nfv3j1s3LgRa9euxS+//ILOnTtj/vz56NWrF4yNjTXq48t69+6NyZMnIzo6GtHR0Urn4uLi8PjxYwwcOBAAcODAASQkJCA1NRUeHh6YO3cuIiMj0blzZ2nJ4MszMubm5rCystLpe9qwYcMKt37X9L60bNkSTZs2RXR0NPr376/yHlX575M2S/4GDRqEAQMGYMeOHSrvUQkhkJ+fDwsLi2pd8lcd40FERET0V9N6yd/y5cvh4+ODrl274vPPP0fDhg1x8eJFTJo0CfXr18cXX3yBKVOmoLS0FAsWLAAANGjQANHR0Rg/fjy6detW5fbo1cnJyQlZWVlIS0uDvb09zM3NK/zrtTZL/gAgNjYWPj4+aNOmDWbPno033ngDz58/x4EDB7BixQpcvnwZZmZmSEhIQN++fdGzZ0+MGTMGLi4uuHfvHjZv3oycnBxs3LgRQPUt+auMNuNRnrOzM2bPno1Zs2bhyJEjSEpKgr+/P+bOnYuIiAgA2i/58/LygrGxMYKCgrB9+3a17z1pq0GDBli4cCEmTpwIY2NjDBkyBAYGBtixYwemTZuGCRMmwMvLC/n5+QgNDcXEiRPRtm1bAMCYMWOwZcsWhIWF4ccff3zlvmjDyckJR48exYABA2BkZARra2u1+WQyGVavXo1OnTqhffv2mDZtGtzd3VFQUIAff/wR+/fvx5EjRwBot+SvX79+2LZtGwYOHIjp06ejc+fOqFOnDi5cuICYmBhERESgV69e1brkrzKajgcRERHRX03r36FydXXFmTNn4OzsjP79+8PZ2RlhYWHo0KEDjh8/jgsXLuDrr79GYmKi0qzN8OHD4ePjg9DQUK3eK3pVvXv3Rrdu3dChQwfUqVNH2uGtOjRs2BC//vorOnTogAkTJqB58+bo3LkzDh48iBUrVkj5/P39cezYMRgYGGDQoEFwd3fHwIEDoVAo8Pnnn1dbfzTxquMhk8ng5+eH1atX486dO5Uud6zKrl27cPHiRUyePLlagqky48aNw7Zt25CamgpPT080b94c69evx4oVK6R3nyIjI2FhYaG0eUGNGjWwevVqHDp0CGvWrKm2/mhi9uzZyM7OhrOzM+rUqVNp3jZt2kj/BocPH44mTZqgZ8+euHjxosqP4WpKJpNh/fr1+Oqrr7Bt2zb4+vrijTfewGeffQZ/f3907dpVp3p1pc14EBEREf2VZOLPjG5ewWeffYbt27dXuSxOGykpKejQoQMePnxY4dKjvyuOx9+Tk5MTIiMjERkZWW11BgcH49GjR9i+fXu11fln+TuMR9lyRYVCUa3vahEREdG/lzbPD1rPUP2VLly4ALlcjtjY2Feuq1mzZjr/rtPfBcfj7+mTTz6BXC6HQqF4pXrKfhdNl991+jvheBAREdG/2T9mhurBgwd48OABAKBOnTrSD43q6saNG9IL+40aNVL7I6l/ZxyPv6fqHMenT5/i1q1bAF7sAKnLbzL91f4O48EZKiIiItKWNs8P/5iAiohIFwyoiIiISFv/2iV/REREREREfycMqIiIiIiIiHTEgIqIiIiIiEhHDKiIiIiIiIh0xICKiIiIiIhIRwyoiIiIiIiIdMSAioiIiIiISEcMqIiIiIiIiHTEgIqIiIiIiEhHDKiIiIiIiIh0xICKiIiIiIhIRwyoiIiIiIiIdMSAioiIiIiISEcMqIiIiIiIiHTEgIqIiIiIiEhHDKiIiIiIiIh0xICKiIiIiIhIRwyoiIiIiIiIdMSAioiIiIiISEcMqIiIiIiIiHTEgIqIiIiIiEhHDKjob8HJyQmLFy9WSouNjUWtWrVw8+ZNpfTRo0fDzc0NT5480aktmUyG7du3q6QHBwejV69eSmk3b95EaGgo7OzsYGhoCEdHR4wdOxb3798HAJSUlMDHxwe9e/dWKqdQKODg4ICoqCid+vhnSEpKQps2bWBmZgZzc3O0b98eO3fulM7v3r0bhoaG+PXXX5XKLVq0CNbW1rhz545O7aq71wDw2WefoWXLltLn/v37w8vLCyUlJVJacXEx3nrrLQwePFintomIiIiqGwMq+tv6+OOP0aZNG4SGhkpphw4dQnx8PBITE2Fqaqq2nJOTE1JSUl65/evXr8PT0xMZGRnYsGEDrl69iri4OBw8eBDe3t548OAB9PT0kJSUhL179yI5OVkqGxERASsrK8yYMUPj9l4OHLWRm5sLIYTG+SdOnIgRI0agX79+OHfuHE6dOoV27drB398fy5cvBwC89957CAwMRGBgIAoLCwEAly9fxvTp0/H111/D1tZWbd1+fn5ITEzU+VrKxMbG4saNG5g/f76UNmfOHNy5cwfLli175fqJiIiIqoWgf7W4uDhhZ2cnSkpKlNJ79OghAgMDxdWrV0XPnj2FjY2NMDMzE56enuLAgQNKeZ89eyYmTZok7O3thaGhoXBxcREJCQlCCCGeP38uhg4dKpycnISxsbFwc3MTixcvViofFBQk/P39xZdffilsbW2FlZWVGDlypCgqKhJCCOHr6ysAKB1lcnJyhIWFhVixYoVQKBSiQYMGYtKkSZVes6Ojozh8+HCF5wGIbdu2qaSX9bNMt27dhL29vXjy5IlSvry8PGFqairCw8OltCVLlghLS0tx69YtsX37dmFgYCDOnj1baT/Lru/zzz8Xrq6uolevXlXmr0hwcLBwcnISM2bMENeuXas07/HjxwUAsXTpUpVz48ePFwYGBiInJ0cIIUR+fr5wdHQUn3zyiSguLhaenp6ib9++ldbv6+srVq9eXeF5R0dHERMTo5I+c+ZM4eHhoZS2Y8cOYWhoKM6dOyfOnDkj9PX1xa5duypt/2UKhUIAEAqFQqtyRERE9N+lzfMDA6p/ufv37wtDQ0Px008/SWkPHjwQhoaGYt++fSItLU3ExcWJ8+fPi4yMDPHpp58KY2NjcePGDSl/v379hIODg9i6dau4du2a+Omnn8TGjRuFEEIUFRWJGTNmiFOnTonr16+LdevWCVNTU7Fp0yapfFBQkKhZs6YIDw8Xly9fFj/++KMwNTUV33zzjdRHe3t7MXv2bJGXlyfy8vKUrmHVqlVCLpeLHj16iKZNm4pnz55Ves3VEVDdv39fyGQyMXfuXLV1DB8+XFhaWorS0lIhhBClpaXCz89PvPvuu8LGxkbMmTOnwvYfP34s1qxZI959911Ro0YN4ePjI1asWCEePHgg5Vm3bp0wMzOr9Fi3bp2UPz8/X6xcuVL4+vqKGjVqiHbt2omEhASRn5+v0v6YMWOEXC4XhYWFKudu3bolACgFPAcPHhT6+vqiX79+om7duuLu3bsVXpsQ1RtQCSFEYGCg8PDwEE2bNhWhoaGVti3Eiz8AKBQK6bh58yYDKiIiItIKAypS0rNnTzF06FDpc3x8vLC1tRXPnz9Xm79p06Zi2bJlQgghrly5IgCozFpVZuTIkaJ3797S56CgIOHo6KjUXt++fUX//v2lzxU9ZJdp27atACBOnjxZZfuaBFTGxsYqAYq+vr4UUJ04caLCwEsIIb766isBQPzvf/+T0i5fviwAiBYtWoji4mKVMikpKSIkJETI5XLRqFEjMWPGDHH16lW19efn54vMzMxKD3XBkhBCZGdnizlz5gg3NzdhamoqAgICxP79+6Xgr1u3bmoDlzIWFhbi448/VkobMGCAAKAUKFdEk4DK0NBQZfwNDAzU9uvhw4fCxMRE1K1bV6P/U5s5c6bKjCcDKiIiItKGNgEV36H6DwgICMCWLVuk92CSk5MxYMAA6Onp4fHjx5g8eTKaNm2KWrVqQS6XIz09HTk5OQCAtLQ06OnpwdfXt8L64+Li4OnpiTp16kAul+Pbb7+Vypdp1qwZ9PT0pM/16tXD77//rlH/z507h19++QWmpqZITU1VOR8eHg65XC4dOTk56N69u0paeTExMUhLS1M6evbsqVF/AEjvK8lkMilt1apVMDU1RVZWFnJzc1XK+Pn5YePGjfjyyy9x7do1zJo1C87OzmrrNzc3h4uLS6WHubm52rKOjo6IiorClStXEBsbix07dqBLly5QKBQaX1v567p9+zb27t1b4fjPnTtXaaxTU1NV7snL5SZNmqQy/uHh4Wr7s379eshkMty7dw/p6elV9n/q1KlQKBTS8SrvphERERFVhQHVf0CPHj1QWlqKXbt24ebNm0hNTZV2SZs0aRK2bNmCL774AqmpqUhLS0OLFi1QVFQEADAxMam07s2bN2PcuHEYOnQo9u/fj7S0NISEhEjlyxgYGCh9lslkKC0trbLvRUVFCAwMxMCBAxEfH4+oqChkZGQo5Zk9e7bSg7mdnR0SEhJU0sqztbWtNEBxcXGBTCbDpUuX1PYrPT0dlpaWsLa2BgAcP34cMTEx2LFjB7y9vREaGqqyScSPP/6I999/H5GRkXjrrbcQExNT4U55ycnJSgGJuqP8Jhjl3bt3D8uXL0ebNm0wfPhwdOzYEVu2bIGFhQUAwM3NDdeuXVO5R8CL4Ck/Px+urq5S2rBhw+Dh4YHdu3djxYoVOHLkiFKZ8PBwpbH29PRUuSeenp5KZaytrVXG38rKSqU/169fx+TJk7F8+XIEBwcjODhY+sNARYyMjFCzZk2lg4iIiOh10f+rO0Cvn4mJCT766CMkJyfj6tWrcHNzQ6tWrQAAqampCA4OxocffggAKCgoQHZ2tlS2RYsWKC0txZEjR9CpUyeVulNTU+Hj44ORI0dKadeuXdO6j4aGhkrbY5eZPXs27t+/jyVLlqBWrVr4/vvvERISgtTUVNSo8eLvATY2NrCxsZHK6Ovro379+nBxcdG6H2Vq166Nzp07IzY2FuPGjVMKLO/cuYPk5GQEBgZCJpPh6dOnCAoKwogRI9CpUye4ubmhefPmiI+PV5p1+eCDD/DBBx/g4cOH2LBhA5KSkjBp0iR07twZQ4YMQa9evaSdC3v27AkvL69K+1i3bl3pvwsLC/Hjjz9izZo12Lt3L5o1a4agoCDs2rULderUUSo3YMAALF26FPHx8YiIiFA6t2jRIhgYGEjbwCckJCA1NRXnz59Hw4YNMXr0aAwdOhTnz5+HmZkZAMDKykopGDIxMYGNjc0rjT8AlJaWIiQkBH5+fggJCUHv3r3RvHlzzJw5U2nnPyIiIqK/Emeo/iMCAgKwa9curFq1Suk3fFxcXLB161akpaXh3LlzGDRokNLMkZOTE4KCgjB06FBs374dWVlZSElJwebNm6XyZ86cwb59+5CRkYHp06fj9OnTWvfPyckJR48exa1bt3Dv3j0AwJkzZ7BgwQIkJCSgVq1aAF4sL0xPT0dMTMwrjIZmli9fjsLCQnTt2hVHjx7FzZs3sXfvXnTu3Bn169fHF198AQCYMmUKSktLsWDBAgBAgwYNEB0djUmTJikFp2UsLS0xcuRInDx5Er/99hs8PDwwefJkDBkyRMqj7ZK/kSNHYvTo0dL9OHv2LCIjI1WCKQDw9vbG2LFjMWnSJERHR+PatWtIT09HVFQUlixZgujoaDg4OCAnJwcTJkzAokWL0LBhQwAvlvfVqFEDU6ZMqc6hVmvJkiW4cOECvv32WwBAzZo1kZCQgOjoaJw6deq1t09ERESkkdf9Qhf9PTx//lzUq1dPAFDaVjsrK0t06NBBmJiYCAcHB7F8+XLh6+srxo4dK+V5+vSpGDdunKhXr560bfqqVauEEC92VAsODhYWFhaiVq1a4uOPPxZTpkxR2lzg5e3IhRBi7NixwtfXV/p8/Phx8cYbbwgjIyMBQDx79kw0bdpUDB8+XOVakpOThbGxsUhPT1d7rdW1bboQLzZ4CA4OFra2tsLAwEA4ODiIiIgIce/ePSHEi40m9PT0RGpqqkp9Xbp0ER07dpQ2g6hMSUmJuHLlSpX5KpKZmal2I4zKrFy5Unh6egoTExNhamoq3nnnHfHDDz8IIV7sWvjuu++KLl26qJRLTU0Venp6IiUlRW291bHL35UrV4SJiYlITk5WyTd8+HDRpEmTKnd7LMNt04mIiEhb2jw/yITQ4tdAiYj+YfLz82FhYQGFQsH3qYiIiEgj2jw/cMkfERERERGRjhhQERERERER6YgBFRERERERkY4YUBEREREREemIARUREREREZGOGFARERERERHpiAEVERERERGRjhhQERERERER6YgBFRERERERkY4YUBEREREREemIARUREREREZGOGFARERERERHpiAEVERERERGRjhhQERERERER6YgBFRERERERkY4YUBEREREREemIARUREREREZGOGFARERERERHpiAEVERERERGRjhhQERERERER6YgBFRERERERkY4YUBEREREREemIARUREREREZGOGFC9ZitXrkSXLl2kz8HBwZDJZJDJZNi+ffsr119WV61ataS0iRMnYsyYMTrV99lnn0l1Ll68+JX75+TkJNX36NGjV67vv+rP+N68DtXZTmJiolRfZGTkK9dHREREVB3+lIDq5s2bCA0NhZ2dHQwNDeHo6IixY8fi/v37KCkpgY+PD3r37q1URqFQwMHBAVFRUTq3+/TpU8ycORONGzeGkZERrK2t0adPH1y8ePFVLwlXr15FSEgI7O3tYWRkhIYNG2LgwIE4c+aMlKewsBAzZszA9OnTlcp269YNeXl56N69u5RW9qAok8lgbm4OT09PbN26VTofHByMXr16qfQjLy9PJfCZPHkyVq9ejaysLJX8W7Zs+X/t3XlYFMfaNvB7gGEddsERwUEFVFCBiHLQqLii5nVJjIBBAT83ojHuRmOMBtdEORj1uJxoQMUtiaLELVEjYuK+EFRAMIoYxbghiAtrfX/4Mi/jsAyjiCT377rmuuzq6qqnazrn9EN118DX1xfm5uaQyWRo3bo1wsPD8eDBA2UdNzc3ZGVlYdSoUcqysomRsbExWrZsiTVr1ij3z5kzBx4eHmr9nT59Gtu3b1cfwDdIda6T3NxczJw5E82bN4ehoSHkcjm6d++OHTt2QAiBvLw8NG3aFJMmTVI5LiMjA2ZmZli7dq3Wcdb0daPJ+ZW6dOkS/P39YWNjAwMDAzg7O2PWrFl48uSJWptRUVFIS0tTbpdNjCQSCRo0aAB/f3+V67W8xDEgIABZWVnw8fHRZLiIiIiIXosaT6iuXr0KLy8vpKWlYcuWLbhy5QpWr16NQ4cOwcfHBzk5OVi/fj3279+PTZs2KY8bN24crKys8Pnnn5fbbnx8PBwdHSvsNz8/H927d8e3336LuXPnIi0tDXv37kVxcTG8vb1x4sQJrc/pzJkzaNOmDdLS0rBmzRokJycjNjYWzZs3x+TJk5X1tm/fDplMho4dO6ocb2BgALlcDgMDA5XyqKgoZGVl4fTp03B3d8egQYNw/PjxSmORy+UwNzdXKbO1tUXPnj2xevVqlfKZM2ciICAAbdu2xb59+3Dx4kVERETg999/x8aNG5X19PT0IJfLYWxsrHJ8eHg4srKykJSUhAEDBiAsLAzbtm2rND4bGxtYWVlVWudFBQUFuH37drWOKSszM1PjutW5Th4+fIj27dtjw4YNmDFjBs6dO4eEhAQEBARg2rRpyMnJgUwmQ1RUFJYvX46jR48CAIQQGDZsGDp06IARI0aUG0d0dDR8fX0rjbWmrxtNzg8ATpw4AW9vbxQUFGDPnj1IS0vDggULsH79evTo0QMFBQUq7VpYWMDW1lalzMzMDFlZWbh16xY2b96MxMRE9OvXD8XFxRXGbGRkBLlcDn19/UrPjYiIiOi1EjWsV69ewt7eXjx58kSlPCsrSxgbG4uwsDAhhBBff/21sLS0FDdv3hQ7d+4UUqlUnD9/vsJ2Dx8+LBQKRYX7Fy1aJCQSiUhMTFQpLy4uFl5eXsLV1VWUlJRU+3xKSkqEm5ubaNOmjSguLlbbn52drfx33759xZQpU1T2h4SEiP79+6sdB0DExsYqtwsKCoSxsbGYPn26mD17tgCg8jl8+LCyblRUlDA3N1dpLzo6Wjg4OCi3T548KQCIpUuXlntepXHPnj1buLu7q+1XKBQiMjJSpczZ2VkEBgaKqKgotfiioqKU9Q4fPiwAqIxNec6cOSPGjRsnrK2tK4xTE46OjsLb21usXLlSPHjwoNK61blOPvzwQ2FiYiJu3ryp1s6jR49EYWGhcnvixImiadOmIi8vT0RGRgoLCwvx559/VhhHVFSU6Ny5c4X7X8d1o8n5lZSUCFdXV+Hl5aV2/ScmJgqJRCIWLVpUYXzl9SuEEDExMQKASE1NFQqFQiXmF/8779y5sxg/fnx5w1SunJwcAUDk5ORofAwRERH9s1Xn/qFGZ6gePHiAn376CWPGjIGRkZHKPrlcjqCgIGzbtg1CCIwbNw7u7u4IDg7GqFGj8Pnnn5f7CJmmNm/ejB49esDd3V2lXEdHBxMnTkRycjJ+//13AMCmTZsgk8kq/ZTOniUmJuLSpUuYPHkydHTUh6/suyJHjx6Fl5eXVvFLpVLo6emhsLAQU6ZMgb+/v/KRr6ysLLRv377S49u1a4cbN27g+vXrKuc4ZsyYcutr846LoaEhCgsLERAQgMmTJysfFczKykJAQIBGbWRlZWHx4sVo2bIl2rdvjz///BNr165ViTMsLKzK76fsrFRCQgL69euHZcuWKR8n27NnD4qKitT61/Q6KSkpwdatWxEUFAQ7Ozu1dmQyGfT09JTbCxYsgFQqxZAhQ/Dpp59i+fLlaNiwoUZj8jK0vW40Pb/ExEQkJydj0qRJate/u7s7unfvji1btlQ77tL/fSgsLMTp06cBqM68EREREb2p9Kquor309HQIIdCiRYty97do0QLZ2dm4e/cubG1tsWrVKrRo0QKtWrXC9OnTX6rvtLQ0dOnSpcJ+S+t4eHigX79+8Pb2rrS9+vXrA3h+TgDQvHnzSus/fPgQDx8+LPfmtCr5+flYvHgxcnNz0a1bN8hkMhgZGSE/Px9yuVyjNkpv3jMyMqBQKJCeno4mTZpAKpVWO54XFRUVISYmBhcuXMCHH34IIyMj5Q23JvEVFBQgNjYW69evx4EDB+Dl5YWxY8ciICCg3McDw8PDMWXKlErbLDvODg4O+PTTT/Hpp5/i9OnT2LBhA0JDQ6Gnp4egoCCEhoaiZcuWADS/Tuzs7JCdnV3l917K0NAQS5cuRa9evdC7d28MGTJEo+NexstcN/fu3dPo/Erfharsv+lff/21WnH/+eefWLx4Mezt7eHi4qJ8pM/CwkLj672s/Px85OfnK7dzc3Or3QYRERGRpmo0oaqK+N+X3CUSCQDg22+/hbGxMa5du4Y///xT7R0pmUym/HdxcTHy8/NVyjp27Ih9+/ZVu19TU1OYmppqFXNFnj59CuD5jbWmBg8eDF1dXTx9+hTm5uZYsmSJygIE1VH6F//SRQKEEFXGXJVPPvkEn332GfLz86Gvr4+pU6di9OjR1W7n2LFjCAwMhIODA3755Re1d8xeZGtrq/YOjqbatm2Ltm3bIiIiAjNmzMC///1vHDx4EImJiVUeW/a71vR7L2vdunUwNjbGhQsXkJOTo/LOUmZmJlxdXZXbRUVFKCwsVLmehwwZovYeXHlexXWjzflV1I4mbZS+byaEwJMnT/DWW29hx44dr+T9qIULF+KLL7546XaIiIiINFGjCZWTkxMkEgmSk5PLXWksNTUVlpaWqFevHo4fP47IyEjs27cPX331FYYPH46DBw+q3JyVvQk+efIkPvnkE8THxyvLyj5W6OLiguTk5HLjSk1NBQA4OzsDeP44XFWJwZo1axAUFAQXFxcAQEpKSqWPJFpbW0MikSA7O7vSdsuKjIxE9+7dYWZmpnUCUap01T4bGxsAz8fj119/RWFhodazVFOnTkVoaCiMjY3RoEEDrW++27Vrh2+++Qbr169H165d0b17dwwdOhQDBgxQWwgDeP7IX0xMTKVtJicno1GjRmrlly9fxsaNGxETE4OcnByMHDkSw4cPV+7X9DqxsbGBpaUlUlJSNDrHbdu2IS4uDsePH8fQoUMxceJEfPvtt8r9dnZ2Ktfzjh07sH37dpWFWczMzDTq61VcN5qeX+n1n5ycXO71n5qaqvzvqjKmpqY4d+4cdHR0UL9+fZiYmGgVd3lmzJihsspibm4uHBwcXln7RERERGXV6DtU1tbW6NGjB1auXKmcsSl1+/ZtbNq0CQEBAXj27BlCQkIwevRodO/eHWvXrsXp06dVluUGnidopZ+GDRtCT09PraxUYGAgDh48qHxPqlRJSQkiIyPh6uqqfG+mX79+SExMrPTTr18/AICHhwdcXV0RERGBkpIStXMu/a0lfX19uLq6VnizXh65XA4nJ6dyb4r19fUrXQHtRRcvXoRUKoWbmxsA4IMPPkBeXh5WrlxZbn1NfiOqXr16cHJygp2dnVoyVZ34jI2NMWLECBw9ehSpqalo27YtZs6cifr16yM0NBS//PKLytiGh4dX+f2UfeTv3r17WLFiBby9veHm5oazZ89i0aJFyMrKwpo1a9CuXTtlXU2vEx0dHQQEBGDTpk24deuW2jk9fvxY+Y7WX3/9hbFjx2LevHnw9PREdHQ0Nm7cqDJ7+uK1a2trCyMjI7UyTbyK60bT8/Pw8EDz5s0RGRmpdv3//vvvOHjwIAYPHqxRf05OTmjSpEm5yZRUKq3W9V6WgYEBzMzMVD5ERERENaXGl01fsWIF8vPz4efnh4SEBNy4cQP79+9Hjx490LBhQ8yfPx/Tp09HSUkJvvzySwBAo0aNEBERgalTpyIjI0OrfidOnIh27dqhb9+++P7775GZmYnTp09j4MCBSElJwbp161Qe+St7I1vep/SRQIlEovxdnU6dOmHv3r24evUqkpKSMH/+fPTv318Zg5+fX7XfJ6mIo6MjkpKScPnyZdy7dw+FhYWV1j969Cg6duyonLXz9vbGtGnTMHnyZEybNg3Hjx/H9evXcejQIQwaNAjr169/6fiuXbuGxMRE3Lt3T+Udlso0bdoU4eHhuHr1Kn788UdIJBL0798f//nPf5R1bG1tq/x+yi4I4e3tjVWrVmHgwIG4ceMG9u3bh8DAwHIfv6zOdbJgwQI4ODjA29sbGzZsQHJyMtLT0/Htt9/Cw8MDeXl5AIDRo0ejWbNmylkSLy8vTJs2DaNGjVIuPf66VOe60eT8JBIJ1q5di+TkZAwcOBCnTp1CZmYmvv/+e/Tt2xc+Pj6v5Ed3HR0dcejQIdy+fbtas7xEREREr11NLTVYVkZGhggNDRVyuVxIpVLh4OAgxo0bJ+7duyfi4+OFrq6uOHr0qNpxPXv2FF27di13efOqlk0XQojHjx+Lzz77TDg5OQmpVCqsrKzEwIEDxYULF176nC5fviyCg4OFnZ2d0NfXFwqFQgwePFicO3dOWSclJUUYGRmJhw8fKss0Xf76RXfu3BE9evQQMplMo2XTXVxcxJYtW9Ta2bZtm+jUqZMwNTUVJiYmonXr1iI8PFyrZdPLevbsmRg4cKCwsLDQetn0Unl5eSIzM1OjuuVJSUmpVv3qXCcPHz4U06dPF87OzkJfX1/Ur19fdO/eXcTGxoqSkhKxfv16YWxsLNLS0lSOy8/PFy1bthTDhg0rN4ZXtWz6i6p73VR1fqWSkpLEwIEDhbW1tZBKpaJp06bis88+E48fP64yvvL6fVFcXJxwcnISenp6XDadiIiIXrvq3D9IhPjft9GpRvj7+8PT0xMzZswAAISGhuLhw4fYuXPnK+sjOjoaEyZMUD62t2fPHkydOhVJSUkqMzeamDNnDnbu3KnRog2aio+PR5cuXZCdna3V8uz0eq6bmiCRSBAbG1vuO5Ta8vX1hYeHB5YuXapR/dzcXJibmyMnJ4eP/xEREZFGqnP/UOOP/P3TLV68WGXlNgDYvXs3ZDIZdu/e/dLty2QyhIWFqZQ9fvwYUVFR1U6mSl24cAEymazC962qw83NTeuVCklVTV83NWXw4MGwt7d/6XZKf0vt6NGjryAqIiIioleDM1Sv2Z07d5S/i9OgQYOXXt3sypUrAABdXV00btz4peN78OCBygqBZZf61sb169eV7+00adKk3B9Dpqq96dfN6+jn0aNH+OuvvwA8/42qevXqaXQcZ6iIiIiouqpz/8CEioj+1phQERERUXXxkT8iIiIiIqLXgAkVERERERGRlphQERERERERaYkJFRERERERkZaYUBEREREREWmJCRUREREREZGWmFARERERERFpiQkVERERERGRlphQERERERERaYkJFRERERERkZaYUBEREREREWmJCRUREREREZGWmFARERERERFpiQkVERERERGRlphQERERERERaYkJFRERERERkZaYUBEREREREWmJCRUREREREZGWmFARERERERFpiQkVERERERGRlphQERERERERaYkJ1T/E/fv3YWtri4yMDABAfHw8JBIJJBIJBgwY8NLth4aGKtvbuXMnAODChQuwt7fH48ePtW63tE0LC4uXjjE6OlrZ3oQJE166PapcRkaGcrw9PDxeur05c+Yo21u6dOlLt0dERET0KjCh+l+Ojo5vzE1acXExIiMj0bp1axgaGsLCwgK9e/fGb7/9pla3oKAAX331Fdzd3WFsbIx69eqhQ4cOiIqKQmFhobLewoUL0bdvXzg6Oqocf/nyZURHRyu3yyZGUqkUTZo0wZQpU5RJUWki9vDhQ5V2vv76a2RlZamUtWrVCu3atUNkZKRa3JcuXYK/vz9sbGxgYGAAZ2dnzJo1C0+ePFGrGxUVhbS0NOV22cRIIpGgQYMG8Pf3x7Vr15R1yiZ2pQICApCVlQUfHx+1Pt4kx44dQ58+fWBpaQlDQ0O0atUKERERKC4uBgDcunULVlZWWLZsmcpxJ0+ehFQqxYEDB7Tu+8aNGxg+fDjs7Oygr68PhUKB8ePH4/79+2p1r1y5gmHDhsHe3h4GBgZo3LgxBg8ejDNnzqjUO3jwIA4dOqTcLpsY6erqwsHBASNGjMDdu3cB/F8ilpiYqNLOlClTkJWVBXt7e63Pj4iIiOhV+9snVAUFBbUdgorSm8WKCCEQGBiI8PBwfPzxx0hJScGRI0fg4OAAX19flSShoKAAfn5+WLRoEUaNGoVjx47h1KlTGDt2LJYvX45Lly4BAJ4+fYp169ZhxIgRav3Z2tqqzf706tULWVlZuHr1KubNm4eVK1diypQplZ6Xubk55HK5WvmwYcOwatUqZTIAACdOnIC3tzcKCgqwZ88epKWlYcGCBVi/fj169Oih9p1ZWFjA1tZWpczMzAxZWVm4desWNm/ejMTERPTr10+lnxcZGRlBLpdDX1+/0nN5UWZmZrXql3X37l08e/ZM4/qxsbHo3Lkz7O3tcfjwYaSmpmL8+PGYP38+AgMDIYSAnZ0dli1bhhkzZiA9PR3A8+84JCQEI0aMQI8ePcpte86cOQgNDa2w76tXr8LLywtpaWnYsmULrly5gtWrV+PQoUPw8fHBgwcPlHXPnDmDNm3aIC0tDWvWrEFycjJiY2PRvHlzTJ48WaVda2trWFtbq5S5ubkhKysLmZmZWLVqFX788UcEBwdXOjYymQxyuRy6urqV1iMiIiJ6rUQd07lzZzF27FgxduxYYW5uLqysrMTMmTNFSUmJEEIIhUIh5s6dK0JCQoSZmZkIDg4WQgjxww8/CFdXV6Gvry8UCoVYsmSJSpsAVD6lKjuutL/58+eLYcOGCZlMJhwcHMSaNWsqjP/atWuismHfunWrACDi4uLU9r333nvC2tpa5OXlCSGE+PLLL4WOjo44d+6cWt2CggJlve3bt4t69eqp7D98+LAAILKzs1XKQ0JCRP/+/VXKRowYIeRyuTL2sp+QkBCVugBEbGyscjs/P18YGBiIQ4cOCSGEKCkpEa6ursLLy0sUFxerHJuYmCgkEolYtGhRhe0JIURUVJQwNzdXKYuJiREARGpqqlAoFCoxKhQKlbqdO3cW48ePF5XJyckRa9euFR07dhSWlpaV1q1MdHS0sLCwEKNHjxbHjh2rtG5eXp6wtrYW7733ntq+uLg4AUBs3bpVWfbuu++K9u3bi+LiYjF+/HjRuHFj8ejRowrbnz17ttr3VVavXr2Evb29ePLkiUp5VlaWMDY2FmFhYUKI59+hm5ubaNOmjdp3KIRQXlOl18v58+fV4nB3d1cpmzdvntDR0RFPnjxRu8Y6d+6sUlehUIjIyMgKz+NFOTk5AoDIycnR+BgiIiL6Z6vO/UOdnKFav3499PT0cPLkSSxbtgyRkZFYu3atcv/ixYvRsmVLnD17FrNmzcLZs2fh7++PwMBAXLhwAXPmzMGsWbOUj7rt2LED9vb2CA8PR1ZWlvLRtaqOKxUREQEvLy+cP38eY8aMwYcffojU1FStzm3z5s1wcXFB37591fZNnjwZ9+/fVz7StWnTJnTv3h2enp5qdaVSKUxMTAAACQkJ8PLy0ioe4PnMTmFhIRwcHLB9+3YAzx8VzMrKwtdff13psfr6+nB3d8fRo0cBAImJiUhOTsakSZOgo6N6+bm7u6N79+7YsmWLVjECQGFhIU6fPg3g+aOCWVlZyu2qlJSU4MCBAxgyZAjkcjkWLVqEbt26qTzClpmZCZlMVuknLCxMWT8oKAgxMTHIzs5G165d0axZM8yfPx83btxQ6//nn3/G/fv3y50N7Nu3L1xcXFTGZvXq1UhPT0dQUBBWrFiB6OhoyGQyzQbsBQ8ePMBPP/2EMWPGKMeylFwuR1BQELZt2wYhBBITE3Hp0iVMnjxZ7TsEoNX7bkZGRigpKUFRURFOnToF4PmjgllZWdixY0e12srPz0dubq7Kh4iIiKim6NV2ANpwcHBAZGQkJBIJmjVrhgsXLiAyMhIjR44EAHTt2lXlpjQoKAjdunXDrFmzAAAuLi5ITk7G4sWLERoaCisrK+jq6sLU1FTlsbV///vflR5Xqk+fPhgzZgwA4JNPPkFkZCTi4+PRvHnzap9bWloaWrRoUe6+0vLS94nS09Ph6+tbZZsZGRmws7OrdiwAcOrUKWzevBndunWDrq4urKysAJT/qGBFGjZsqFwMozT2ys7x119/rVaMf/75JxYvXgx7e3u4uLgoH+mzsLAo9zHEF6WlpSE6OhobN27E48eP4e/vjwMHDqBDhw5qde3s7NTe7XmRmZmZ8t96enp455138M477yAnJwfff/89NmzYgNmzZ8PX1xchISF4//33YWRkVOXYNG/eXOVdMltbW8ydOxdhYWH48MMP0alTpyrPtSLp6ekQQlT6vWRnZ+Pu3bvKxwy1ub7Lk5qailWrVqFdu3YwNTWFjY0NgOePCmry/b1o4cKF+OKLL15JbERERERVqZMzVP/6179U3kPy8fFBenq68v2ZF2djUlJS1G6OO3TooHJMeTQ9rnXr1sp/SyQSyOVy3LlzR1nm5uamnL1wc3MDAJUZjdIyTZWeuxCi0vexSj19+hSGhoYat797927IZDIYGhrCx8cHnTp1wvLly6sVY1lGRkblLjZRHk3PKScnBzKZDCYmJnBwcEBBQQF27NhR7fejAGDUqFFYuHAh/ud//gc3b97E6tWry02mgOcJkpOTU6WfF9/3KmVubo4RI0YgISEBx44dw7Vr1xAcHIyffvpJbQzK8+LYFBcXY/369TA2NsaJEydQVFSkUv/o0aMq19mCBQuwadMmtTJNlMYkkUhU/q2tCxcuQCaTwcjICK6urnBwcMCmTZu0bq+sGTNmICcnR/kpbzaQiIiI6FWpkzNUVSl91K1UeTfpFd20anOcVCpV2ZZIJCgpKVFu7927V7ni3s2bN+Hr66syy1H2+NJZsPKkpKQAAJydnZV1S8sqU69ePWRnZ1dZr1SXLl2watUqSKVS2NnZqZ1fdT148ABNmzYF8DxmAEhOTi53Ke3U1FTl+VXG1NQU586dg46ODurXr6/2nVfH0qVLsW7dOmzZsgW7d+9GUFAQhg4dWm6im5mZCVdX10rbGzJkCFavXq1W/uzZM/z444/YuHEj9u/fD09PT0yePBndunUD8H9jk5KSgvbt26sdn5qaqtL3kiVLkJ6ejtOnT6Nr165YsGABPv/8c+V+Ly8vlets2bJluHnzJr788ktlWemMo5OTEyQSCZKTk8tdRj81NRWWlpaoV6+eSpzaLoferFkzxMXFQVdXF3Z2djAwMNCqnfIYGBi80vaIiIiIKlMnE6oTJ06obTs7O1e4+perq6vaY2THjh2Di4uL8hh9fX212SpNjtOEQqFQ/ltP7/mQOzk5lVs3MDAQH3zwAX788Ue196giIiJgbW2tXMXtgw8+wKefforz58+rvUdVVFSE/Px8mJiYwNPTEzExMRrHa2JiUmF8pTNAlc3svejixYt4//33AQAeHh5o3rw5IiMjERgYqPIOzu+//46DBw9i4cKFVbapo6NTYYzA8yRV0xg9PDywfPlyREREYPfu3Vi/fj08PT3RsmVLDB06FIMHD1Y+elbdR/6EEPj111+xceNGfPfdd5DJZBgyZAi++uortUfmevbsCSsrK0RERKglVHFxcUhPT8fcuXMBPF92fvbs2YiJiYGrqytWr14Nf39/DBgwQDljamRkpDJGVlZWyM3NLXfcSq+rlStXYuLEiSrvUd2+fRubNm1CcHCw8jelXF1dERERgYCAALX3qB4+fFjl46D6+vqv9BojIiIiqi118pG/GzduYNKkSbh8+TK2bNmC5cuXY/z48RXWnzx5Mg4dOoS5c+ciLS0N69evx4oVK1Tes3J0dERCQgJu3ryJe/fuaXzcqxYYGIh3330XISEhWLduHTIyMpCUlITRo0cjLi4Oa9euVc7GTJgwAR06dEC3bt3wn//8B7///juuXr2K7777Dt7e3sp3Xfz8/HDp0qVqzVJVRKFQQCKRYPfu3bh79y7y8vIqrZ+RkYGbN2+ie/fuAJ7P3q1duxbJyckYOHAgTp06hczMTHz//ffo27cvfHx8XsmP7jo6OuLQoUO4ffu2xuetr6+P9957D7t27cLNmzcRHByMDRs2qMxUVfeRv5iYGPj5+eHx48f47rvvkJmZiUWLFpX7/pGJiQnWrFmDXbt2YdSoUUhKSkJGRgbWrVuH0NBQvP/++/D390dRURFCQkLw7rvvKhPVAQMGYNCgQQgNDVV79E9TK1asQH5+Pvz8/JCQkIAbN25g//796NGjBxo2bIj58+cDeP4dlv42WKdOnbB3715cvXoVSUlJmD9/Pvr3769V/6VsbW1hZGSE/fv346+//kJOTs5LtUdERERUo2pmocGa07lzZzFmzBgRFhYmzMzMhKWlpZg+fbrKsunlLalcuvy5VCoVjRo1EosXL1bZf/z4cdG6dWthYGBQ7rLpFR1XXn/u7u5i9uzZ5cZf1bLpQghRWFgolixZItzc3ISBgYEwMzMTfn5+4ujRo2p1nz17JhYuXChatWolDA0NhZWVlejQoYOIjo4WhYWFynr/+te/xOrVq5Xb1Vk2/UXh4eFCLpcLiURS5bLpCxYsEH5+fmptJCUliYEDBwpra2shlUpF06ZNxWeffSYeP35caXtClL9s+ovi4uKEk5OT0NPT02rZ9LJSUlI0rvuimzdvVnu57oSEBNGrVy9hbm4u9PX1haurq1iyZIkoKioSQgjxxRdfCLlcLu7du6dy3P3794VcLhdffPFFue1WtWy6EEJkZGSI0NBQIZfLhVQqFQ4ODmLcuHFqfQkhxOXLl0VwcLCws7NT/qzA4MGDlcv4V2fZ9Bd98803wsHBQejo6HDZdCIiInrtqnP/IBFCg5eJ3iC+vr7w8PDA0qVLazuUOmXv3r2YMmUKLl68CB0dHcTHx6NLly7Izs7WapnrikgkEsTGxmLAgAHIz8+Hs7MztmzZUuEiD9Vp71XhNfR6ZGRkoHHjxjh//rzW71qVx9HRERMmTNB4JjM3Nxfm5ubIyclReRyTiIiIqCLVuX+ok4/8UfX16dMHo0ePxs2bN1XK7e3tMXjw4JduPywsTO03kK5fv46ZM2dqnUyVGjx4MOzt7V+qDQDKFe5KfxOLXo/27duXu8hGdS1YsAAymQyZmZmvICoiIiKiV4MzVP9QT58+VSZXMplMq9/7KevOnTvKH1Bt0KDBS626V9aVK1cAALq6umjcuPFLtfXo0SP89ddfAJ7/RlW9evVeOj6qWFFRkfL3xwwMDODg4PBS7T148AAPHjwAANjY2MDc3Fyj4zhDRURERNVVnfuHOpdQERFVBxMqIiIiqi4+8kdERERERPQaMKEiIiIiIiLSEhMqIiIiIiIiLTGhIiIiIiIi0hITKiIiIiIiIi0xoSIiIiIiItISEyoiIiIiIiItMaEiIiIiIiLSEhMqIiIiIiIiLTGhIiIiIiIi0hITKiIiIiIiIi0xoSIiIiIiItISEyoiIiIiIiItMaEiIiIiIiLSEhMqIiIiIiIiLTGhIiIiIiIi0hITKiIiIiIiIi0xoSIiIiIiItISEyoiIiIiIiItMaEiIiIiIiLSEhMqIiIiIiIiLenVdgBERDVJCAEAyM3NreVIiIiIqK4ovW8ovY+oDBMqIvpbe/ToEQDAwcGhliMhIiKiuubRo0cwNzevtI5EaJJ2ERHVUSUlJbh16xZMTU0hkUhqO5xXJjc3Fw4ODrhx4wbMzMxqO5w6jWP5anAcXx2O5avBcXx1/oljKYTAo0ePYGdnBx2dyt+S4gwVEf2t6ejowN7evrbDqDFmZmb/mP9zq2kcy1eD4/jqcCxfDY7jq/NPG8uqZqZKcVEKIiIiIiIiLTGhIiIiIiIi0hITKiKiOsjAwACzZ8+GgYFBbYdS53EsXw2O46vDsXw1OI6vDseyclyUgoiIiIiISEucoSIiIiIiItISEyoiIiIiIiItMaEiIiIiIiLSEhMqIiIiIiIiLTGhIiL6m8jPz4eHhwckEgkSExNrO5w6JyMjA8OHD0fjxo1hZGSEpk2bYvbs2SgoKKjt0OqElStXonHjxjA0NESbNm1w9OjR2g6pTlm4cCHatm0LU1NT2NraYsCAAbh8+XJth1XnLVy4EBKJBBMmTKjtUOqkmzdvYsiQIbC2toaxsTE8PDxw9uzZ2g7rjcOEiojob2LatGmws7Or7TDqrNTUVJSUlGDNmjW4dOkSIiMjsXr1anz66ae1Hdobb9u2bZgwYQJmzpyJ8+fPo2PHjujduzcyMzNrO7Q648iRIxg7dixOnDiBAwcOoKioCD179sTjx49rO7Q66/Tp0/jvf/+L1q1b13YodVJ2djY6dOgAqVSKffv2ITk5GREREbCwsKjt0N44XDadiOhvYN++fZg0aRK2b98ONzc3nD9/Hh4eHrUdVp23ePFirFq1ClevXq3tUN5o3t7eeOutt7Bq1SplWYsWLTBgwAAsXLiwFiOru+7evQtbW1scOXIEnTp1qu1w6py8vDy89dZbWLlyJebNmwcPDw8sXbq0tsOqU6ZPn47ffvuNs80a4AwVEVEd99dff2HkyJHYuHEjjI2Nazucv5WcnBxYWVnVdhhvtIKCApw9exY9e/ZUKe/ZsyeOHTtWS1HVfTk5OQDA609LY8eOxTvvvIPu3bvXdih1VlxcHLy8vDBo0CDY2trC09MT33zzTW2H9UZiQkVEVIcJIRAaGoqwsDB4eXnVdjh/K3/88QeWL1+OsLCw2g7ljXbv3j0UFxejfv36KuX169fH7du3aymquk0IgUmTJuHtt99Gy5YtazucOmfr1q04d+4cZ0df0tWrV7Fq1So4Ozvjp59+QlhYGD7++GNs2LChtkN74zChIiJ6A82ZMwcSiaTSz5kzZ7B8+XLk5uZixowZtR3yG0vTsSzr1q1b6NWrFwYNGoQRI0bUUuR1i0QiUdkWQqiVkWY++ugjJCUlYcuWLbUdSp1z48YNjB8/HjExMTA0NKztcOq0kpISvPXWW1iwYAE8PT0xevRojBw5UuXRXnpOr7YDICIidR999BECAwMrrePo6Ih58+bhxIkTMDAwUNnn5eWFoKAgrF+/vibDrBM0HctSt27dQpcuXeDj44P//ve/NRxd3VevXj3o6uqqzUbduXNHbdaKqjZu3DjExcUhISEB9vb2tR1OnXP27FncuXMHbdq0UZYVFxcjISEBK1asQH5+PnR1dWsxwrqjQYMGcHV1VSlr0aIFtm/fXksRvbmYUBERvYHq1auHevXqVVlv2bJlmDdvnnL71q1b8PPzw7Zt2+Dt7V2TIdYZmo4l8HyJ4C5duqBNmzaIioqCjg4f5KiKvr4+2rRpgwMHDuDdd99Vlh84cAD9+/evxcjqFiEExo0bh9jYWMTHx6Nx48a1HVKd1K1bN1y4cEGlbNiwYWjevDk++eQTJlPV0KFDB7Wl+9PS0qBQKGopojcXEyoiojqsUaNGKtsymQwA0LRpU/51u5pu3boFX19fNGrUCEuWLMHdu3eV++RyeS1G9uabNGkShg4dCi8vL+XMXmZmJt8/q4axY8di8+bN2LVrF0xNTZUzfubm5jAyMqrl6OoOU1NTtffOTExMYG1tzffRqmnixIlo3749FixYAH9/f5w6dQr//e9/OXNfDiZUREREAH7++WdcuXIFV65cUUtG+QsjlQsICMD9+/cRHh6OrKwstGzZEnv37uVfsquh9L0UX19flfKoqCiEhoa+/oDoH69t27aIjY3FjBkzEB4ejsaNG2Pp0qUICgqq7dDeOPwdKiIiIiIiIi3x4XAiIiIiIiItMaEiIiIiIiLSEhMqIiIiIiIiLTGhIiIiIiIi0hITKiIiIiIiIi0xoSIiIiIiItISEyoiIiIiIiItMaEiIiIiIqIalZCQgL59+8LOzg4SiQQ7d+6s9f7y8vLw0Ucfwd7eHkZGRmjRooXyR7argwkVERHRP9CcOXPg4eFR4/34+vpiwoQJNd4PvX6Ojo5YunRpbYdBdcTjx4/h7u6OFStWvDH9TZw4Efv370dMTAxSUlIwceJEjBs3Drt27apWX0yoiIiI3hChoaGQSCSQSCSQSqVo0qQJpkyZgsePH9d2aFWKj4+HRCLBw4cPVcp37NiBuXPn1kifc+bMQWBgIIA35+a+dBxKP9bW1ujatSt+++03rdp5cTzrgsaNG2P//v21HQa9YXr37o158+bhvffeK3d/QUEBpk2bhoYNG8LExATe3t6Ij4+vsf4A4Pjx4wgJCYGvry8cHR0xatQouLu748yZM9XqiwkVERHRG6RXr17IysrC1atXMW/ePKxcuRJTpkwpt25hYeFrjq76rKysYGpqWiNtx8XFoX///jXS9su6fPkysrKyEB8fDxsbG7zzzju4c+dObYdV45KSknD//n106dKltkOhOmbYsGH47bffsHXrViQlJWHQoEHo1asX0tPTa6zPt99+G3Fxcbh58yaEEDh8+DDS0tLg5+dXrXaYUBEREb1BDAwMIJfL4eDggA8++ABBQUHKZ/9LH9P79ttv0aRJExgYGEAIgczMTPTv3x8ymQxmZmbw9/fHX3/9pdLuokWLUL9+fZiammL48OF49uyZyv7yHs0bMGAAQkNDldv5+fmYNm0aHBwcYGBgAGdnZ6xbtw4ZGRnKG2hLS0tIJBLlcS+2m52djeDgYFhaWsLY2Bi9e/dWuWGKjo6GhYUFfvrpJ7Ro0QIymUyZZJZ148YNXLx4Eb1799ZoXFetWoWmTZtCX18fzZo1w8aNG1X2z5kzB40aNYKBgQHs7Ozw8ccfK/etXLkSzs7OMDQ0RP369fH+++9X2Z+trS3kcjlatWqFzz77DDk5OTh58qRyf0xMDLy8vGBqagq5XI4PPvhAmXBVNp5CCHz11Vdo0qQJjIyM4O7ujh9++KHSWBwdHTFv3jwEBwdDJpNBoVBg165duHv3rvK6adWqldpf5bdv3w43NzcYGBjA0dERERERVZ73rl274OfnBwMDA1y/fh19+/aFpaUlTExM4Obmhr1791bZBv3z/PHHH9iyZQu+//57dOzYEU2bNsWUKVPw9ttvIyoqqsb6XbZsGVxdXWFvbw99fX306tULK1euxNtvv12tdphQERERvcGMjIxUZqKuXLmC7777Dtu3b0diYiKA54nPgwcPcOTIERw4cAB//PEHAgIClMd89913mD17NubPn48zZ86gQYMGWLlyZbVjCQ4OxtatW7Fs2TKkpKRg9erVkMlkcHBwwPbt2wH838zM119/XW4boaGhOHPmDOLi4nD8+HEIIdCnTx+Vc3zy5AmWLFmCjRs3IiEhAZmZmWqzdHFxcejUqRMsLCyqjDs2Nhbjx4/H5MmTcfHiRYwePRrDhg3D4cOHAQA//PADIiMjsWbNGqSnp2Pnzp1o1aoVAODMmTP4+OOPER4ejsuXL2P//v3o1KmTxmP25MkT5Q2hVCpVlhcUFGDu3Ln4/fffsXPnTly7dk2ZNFU2np999hmioqKwatUqXLp0CRMnTsSQIUNw5MiRSuOIjIxEhw4dcP78ebzzzjsYOnQogoODMWTIEJw7dw5OTk4IDg6GEAIAcPbsWfj7+yMwMBAXLlzAnDlzMGvWLERHR1faT9lZw7FjxyI/Px8JCQm4cOECvvzyS8hkMo3Hjv45zp07ByEEXFxcIJPJlJ8jR47gjz/+APD8Dw1lH6ct7/PRRx9Vq99ly5bhxIkTiIuLw9mzZxEREYExY8bg4MGD1TsBQURERG+EkJAQ0b9/f+X2yZMnhbW1tfD39xdCCDF79mwhlUrFnTt3lHV+/vlnoaurKzIzM5Vlly5dEgDEqVOnhBBC+Pj4iLCwMJW+vL29hbu7u3K7c+fOYvz48Sp1+vfvL0JCQoQQQly+fFkAEAcOHCg39sOHDwsAIjs7W6W8bLtpaWkCgPjtt9+U++/duyeMjIzEd999J4QQIioqSgAQV65cUdb5z3/+I+rXr6/Sbo8ePcSyZcuU2wqFQkRGRpYbW/v27cXIkSNVygYNGiT69OkjhBAiIiJCuLi4iIKCArVjt2/fLszMzERubm65bb+odBxMTEyEiYmJkEgkAoBo06ZNue2XOnXqlAAgHj16pNJO2fHMy8sThoaG4tixYyrHDh8+XAwePLjCthUKhRgyZIhyOysrSwAQs2bNUpYdP35cABBZWVlCCCE++OAD0aNHD5V2pk6dKlxdXVXaLTvmf/75p5BKpeL+/ftCCCFatWol5syZU2Fc9M8FQMTGxiq3t27dKnR1dUVqaqpIT09X+ZRekwUFBSIlJaXSz+3btzXqTwghnjx5IqRSqdi9e7dK+fDhw4Wfn1+1zoczVERERG+Q3bt3QyaTwdDQED4+PujUqROWL1+u3K9QKGBjY6PcTklJgYODAxwcHJRlrq6usLCwQEpKirKOj4+PSj8vblclMTERurq66Ny5szanpYxDT08P3t7eyjJra2s0a9ZMGSsAGBsbo2nTpsrtBg0aqLx/lJubiyNHjqBfv34a99uhQweVsg4dOij7HDRoEJ4+fYomTZpg5MiRiI2NRVFREQCgR48eUCgUaNKkCYYOHYpNmzbhyZMnVfZ59OhRnDt3Dlu2bIFCoUB0dLTKDNX58+fRv39/KBQKmJqawtfXFwCQmZlZYZvJycl49uwZevToofJX/A0bNij/il+R1q1bK/9dv359AFDOwpUtKx3nisYsPT0dxcXF5fYRFxeHDh06wMrKCgDw8ccfY968eejQoQNmz56NpKSkSmOkfy5PT08UFxfjzp07cHJyUvnI5XIAz2d4mzdvXumn9DrWRGFhIQoLC6Gjo5oO6erqoqSkpFrx61WrNhEREdWoLl26YNWqVZBKpbCzs1O5CQcAExMTlW0hBCQSiVo7FZVXREdHR/m4V6myj+EZGRlp3FZFXmy/bHnZWF88Z4lEonLsvn370KJFCygUCo37fnEsyvbp4OCAy5cv48CBAzh48CDGjBmDxYsX48iRIzA1NcW5c+cQHx+Pn3/+GZ9//jnmzJmD06dPV/q4YePGjWFhYQEXFxc8e/YM7777Li5evAgDAwM8fvwYPXv2RM+ePRETEwMbGxtkZmbCz88PBQUFFbZZepO3Z88eNGzYUGWfgYFBpedfdkxLz7u8stI+yrt+Kvr+Sr24SMiIESPg5+eHPXv24Oeff8bChQsRERGBcePGVdoO/T3l5eXhypUryu1r164hMTERVlZWcHFxQVBQEIKDgxEREQFPT0/cu3cPv/zyC1q1aoU+ffq80v4aNWoEMzMzdO7cGVOnToWRkREUCgWOHDmCDRs24N///ne1+uIMFRER0RvExMQETk5OUCgUaolFeVxdXZGZmYkbN24oy5KTk5GTk4MWLVoAAFq0aIETJ06oHPfito2NjcrCD8XFxbh48aJyu1WrVigpKanwXR19fX3lcZXFWlRUpLI4w/3795GWlqaMVRO7du3SeHYKeH7+v/76q0rZsWPHVPo0MjJCv379sGzZMsTHx+P48eO4cOECAEBPTw/du3fHV199haSkJGRkZOCXX37RuP+hQ4eipKRE+d5aamoq7t27h0WLFqFjx45o3ry52gqA5Y2nq6srDAwMkJmZqfZX/LIzlK+Cq6truWPm4uICXV1dtfp5eXk4fPiw2vfi4OCAsLAw7NixA5MnT8Y333zzSuOkuuPMmTPw9PSEp6cnAGDSpEnw9PTE559/DgCIiopCcHAwJk+ejGbNmqFfv344efKk1td2Vf0BwNatW9G2bVsEBQXB1dUVixYtwvz58xEWFlatvjhDRUREVId1794drVu3RlBQEJYuXYqioiKMGTMGnTt3hpeXFwBg/PjxCAkJgZeXF95++21s2rQJly5dQpMmTZTtdO3aFZMmTcKePXvQtGlTREZGqvwGkqOjI0JCQvD//t//w7Jly+Du7o7r16/jzp078Pf3h0KhgEQiwe7du9GnTx8YGRmpLUDg7OyM/v37Y+TIkVizZg1MTU0xffp0NGzYUOPlz4uKirBv375yXxq/efOmcqGOUo0aNcLUqVPh7++Pt956C926dcOPP/6IHTt2KNuIjo5GcXExvL29YWxsjI0bNyr/Yr17925cvXoVnTp1gqWlJfbu3YuSkhI0a9ZMo3iB57N/EyZMwLx58zB69Gg0atQI+vr6WL58OcLCwnDx4kW13+oqbzxNTU0xZcoUTJw4ESUlJXj77beRm5uLY8eOQSaTISQkROOYqjJ58mS0bdsWc+fORUBAAI4fP44VK1ZUuJjJ/v374ezsrHJNTZgwAb1794aLiwuys7Pxyy+/VCtxpr8XX1/fSmc5pVIpvvjiC3zxxRevpT8AkMvlr2YVwWq9cUVEREQ15sVFKV40e/ZslYUkSl2/fl3069dPmJiYCFNTUzFo0CC1l7Pnz58v6tWrJ2QymQgJCRHTpk1TaaugoEB8+OGHwsrKStja2oqFCxeqLEohhBBPnz4VEydOFA0aNBD6+vrCyclJfPvtt8r94eHhQi6XC4lEojzuxcUuHjx4IIYOHSrMzc2FkZGR8PPzE2lpacr9UVFRwtzcXCX22NhYUXrLcvDgQWFvb682BgqFQgBQ+0RFRQkhhFi5cqVo0qSJkEqlwsXFRWzYsEGlfW9vb2FmZiZMTEzEv/71L3Hw4EEhhBBHjx4VnTt3FpaWlsLIyEi0bt1abNu2Ta3/UhUtzpGXlycsLS3Fl19+KYQQYvPmzcLR0VEYGBgIHx8fERcXJwCI8+fPVzqeJSUl4uuvvxbNmjUTUqlU2NjYCD8/P3HkyJEKYypvwQ688JL+tWvX1Pr/4YcfhKurq5BKpaJRo0Zi8eLFFbY7ZMgQMXPmTJX9H330kWjatKkwMDAQNjY2YujQoeLevXsVxklUV0mEqCJ1IyIiInpDfPzxxygqKtJq2XeqGcXFxbC1tcW+ffvQrl272g6H6LXjI39ERERUZ7Rs2bLaKxRSzbp//z4mTpyItm3b1nYoRLWCM1RERERERERa4ip/REREREREWmJCRUREREREpCUmVERERERERFpiQkVERERERKQlJlRERERERERaYkJFRERERESkJSZUREREREREWmJCRUREREREpCUmVERERERERFr6/x/4haBNSgp9AAAAAElFTkSuQmCC", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plotROP(ssys,\"OX\",1;N=10,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 52, - "id": "7086e403", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Net ROPs for species OCX is: 0.0010823432798137006\n", - "Showing the reaction with 1 th highest ROP for species OCX:\n", - "CO2HX+OC=[Pt]<=>OCX+OC(O)[Pt]\n", - "ROP = 0.0010852207068393384\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 1.39e17\n", - " n: Float64 0.101\n", - " Ea: Float64 19000.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 2 th highest ROP for species OCX:\n", - "O=C([Pt])C=[Pt]<=>OCX+CHX\n", - "ROP = -2.8774270256379165e-6\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.22e12\n", - " n: Float64 0.0\n", - " Ea: Float64 104000.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plotROP(ssys,\"OCX\",1.0e-6)" - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "id": "f558daa4", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "2.086079162408844e-6" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "concentrations(ssys,\"O=CO\",1)" - ] - }, - { - "cell_type": "code", - "execution_count": 54, - "id": "d7ea3b6e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "retcode: Success\n", - "Interpolation: 3rd order Hermite\n", - "t: 3402-element Vector{Float64}:\n", - " 0.0\n", - " 1.5219934681649523e-18\n", - " 8.633547368488198e-17\n", - " 9.344702758520521e-16\n", - " 1.7826050780192224e-15\n", - " 2.6307398801863927e-15\n", - " 3.920199324331331e-15\n", - " 6.027873627295679e-15\n", - " 9.528803114914393e-15\n", - " 1.498608205811249e-14\n", - " ⋮\n", - " 828.1715751387352\n", - " 850.638780346129\n", - " 873.1059855535228\n", - " 895.5731907609166\n", - " 918.0403959683105\n", - " 940.5076011757043\n", - " 962.9748063830981\n", - " 985.4420115904919\n", - " 1000.0\n", - "u: 3402-element Vector{Vector{Float64}}:\n", - " [0.0, 0.0, 0.0, 0.0, 360.0, 0.0036, 0.0, 0.0, 0.0, 0.0 … 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]\n", - " [0.0, 0.0, 0.0, 0.0, 359.99999999999983, 0.003599999999780525, 0.0, 9.945212408385767e-40, 3.77878100593239e-41, 1.1070000459093474e-122 … 1.8050027813578834e-182, 3.5814210458429026e-136, 0.0, 0.0, 6.44159813871022e-96, 1.689468624297892e-84, 7.453336270420498e-92, 9.825753070303532e-87, 0.0, 0.0]\n", - " [0.0, 0.0, 0.0, 0.0, 359.9999999999915, 0.0035999999875502165, 0.0, 3.144705728800497e-36, 6.658603121682767e-36, 9.830268759761564e-108 … 6.050335890580479e-141, 9.648208935673809e-98, 8.941030049866435e-156, 4.685412107603335e-201, 3.454333881602009e-80, 1.6283728164554078e-70, 1.2891466757494804e-79, 3.049745913400057e-76, 1.103615848204188e-102, 1.8830325097682767e-99]\n", - " [0.0, 0.0, 0.0, 0.0, 359.99999999990786, 0.0035999998652471365, 0.0, 2.4046788872744706e-34, 3.424084657525366e-33, 3.8324505425824124e-103 … 5.020535480617539e-125, 5.0022772082488694e-89, 2.7879850597977056e-140, 1.1698308564297704e-175, 2.535065560187501e-72, 1.7924952083872728e-63, 2.1285623910269682e-73, 7.551849313715483e-71, 5.777257817975247e-94, 6.572982712439977e-90]\n", - " [0.0, 0.0, 0.0, 0.0, 359.99999999982424, 0.00359999974294406, 0.0, 7.523058123385961e-34, 1.518685845421872e-32, 3.608525142014511e-102 … 6.1574199540862386e-120, 6.265521343967512e-88, 2.3019109049053397e-134, 5.116914522116296e-172, 2.130047320217106e-71, 1.2663712137922205e-62, 1.5031520954293265e-72, 5.326996189278033e-70, 5.962863509930395e-93, 6.790012840870803e-89]\n", - " [0.0, 0.0, 0.0, 0.0, 359.9999999997406, 0.003599999620640987, 0.0, 1.5615346786208654e-33, 4.1162329647735395e-32, 2.037273796982261e-101 … 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"lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.10.10", - "language": "julia", - "name": "julia-1.10" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.10.10" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/CO2_Reduction_Ag/CO2RR_RMS_Diffusion_Interface_1.jl b/CO2_Reduction_Ag/CO2RR_RMS_Diffusion_Interface_1.jl new file mode 100644 index 0000000..b2fab41 --- /dev/null +++ b/CO2_Reduction_Ag/CO2RR_RMS_Diffusion_Interface_1.jl @@ -0,0 +1,642 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,jl:percent +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.17.2 +# kernelspec: +# display_name: Julia rmg_env3 1.10 +# language: julia +# name: julia-rmg_env3-1.10 +# --- + +# %% +using Pkg +Pkg.activate(ENV["PYTHON_JULIAPKG_PROJECT"]) +using ReactionMechanismSimulator + +# %% +using PythonPlot +using DifferentialEquations +using Sundials +using SciMLBase +using QuadGK + +# %% +outdict = readinput("/home/danieltori/CO2_RR_RMG/CO2_Reduction_Ag/Ag_C2_042925.rms") + +# %% +boundarylayerspcs = outdict["gas"]["Species"] +boundarylayerrxns = outdict["gas"]["Reactions"] +surfspcs = outdict["surface"]["Species"] +surfrxns = outdict["surface"]["Reactions"] +interfacerxns = outdict[Set(["surface", "gas"])]["Reactions"] +solv = outdict["Solvents"][1]; + +# %% +sitedensity = 2.292e-5; # Ag111 site density is 2.294e-9 mol/cm^2 or 2.294e-5 mol/m^2 +boundarylayer = IdealDiluteSolution(boundarylayerspcs,boundarylayerrxns,solv,name="boundarylayeruid",diffusionlimited=true); +surf = IdealSurface(surfspcs,surfrxns,sitedensity,name="surface"); + +# %% +# Reservoir is a 100 mL (100e-6 m^3) cell +# Proton concentration is 10^-7 mol/L (10^-4 mol/m^3) +# CO2 concentration is 0.01 mol/L (10 mol/m^3), saturation solubility ~0.03 mol/L +# AVratio in experiments is 36 m^-1 but is measured by surface area/reservoir volume +# Area of the electrode is therefore 3.6e1 m^-1 * 1e2 * 1e-6 m^3 = 3.6e-3 m^2 = 36 cm^2 +# Assume boundary layer thickness d_bl = 1 mm or 1e-3 m +# Volume of the boundary layer V_bl = 3.6e-3 m^2 * 1e-3 m = 3.6e-6 m^3 +# Actual AVratio is therefore 3.6e-3 m^2 / 3.6e-6 m^3 = 1e3 m^-1 (reciprocal of d_bl) +# Amount of sites is 2.943e-5 mol/m^2 * 3.6e-3 m^2 = 10.595e-8 mol + +# For earlier simulations, a 100x linear scale factor is applied, +# so volume becomes 100e-6 m^3 * (1e2)^3 = 100 m^3, +# electrode area becomes 3.6e-3 * (1e2) ^2 = 3.6e1 m^2, +# AVratio becomes 3.6e1 m^2 / 1e2 m^3 = 0.36 m^-1 +# Volume of the boundary layer becomes 3.6e1 m^2 * 1e-3 m = 3.6e-2 m^3 + +C_proton = 1e-7*1e3; +C_co2 = 1e-2*1e3; +C_default = 1e-12; +V_res = 1e3; +layer_thickness = 1e-6; +AVratio = 36; +A_surf = V_res*AVratio; +V_bl = A_surf*layer_thickness; +# V_bl = V_res; +sites = sitedensity*A_surf; + +# The initial conditions for individual species are moles not concentration, so we need to multiply concentration by boundary layer volume +initialcondsboundarylayer = Dict(["proton"=>C_proton*V_bl, + "CO2"=>C_co2*V_bl, + # "H2"=>C_default*10*V_bl, + # "O=CO"=>C_default*V_bl, + "V"=>V_bl,"T"=>300,"Phi"=>0.0,"d"=>0.0]); +initialcondsreservoir = Dict(["proton"=>C_proton, + "CO2"=>C_co2, + "V"=>V_res,"T"=>300]); + + +# Assume voltage is -1.0 V vs. R.H.E. which equates to -1.414 V vs. S.H.E. at pH=7 +initialcondssurf = Dict(["CO2X"=>0.1*sites, + # "CHO2X"=>0.1*sites, + # "CO2HX"=>0.1*sites, + # "OX"=>0.1*sites, + # "OCX"=>0.1*sites, + "vacantX"=>0.9*sites, + # "CH2O2X"=>0.05*sites, + # "CHOX"=>0.04*sites, + # "CH2OX"=>0.01*sites, + "A"=>A_surf,"T"=>300,"Phi"=>-1.414]); + +# %% +domainboundarylayer, y0boundarylayer, pboundarylayer = ConstantTVDomain(phase=boundarylayer, initialconds=initialcondsboundarylayer); +domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf, + initialconds=initialcondssurf); + +# %% +# Set proton diffusivity to a higher value than calculated from Stokes Einstein equation +# The values are taken from DOI: 10.1039/C8SC01253A +# Values calculated from MD is 1.015 A^2/ps, experimental values are 0.932 A^2/ps. +# 1 A^2/ps = 1e-8 m^2/s +domainboundarylayer.diffusivity[6] = 0.932e-8 + +# %% +inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainboundarylayer, + domaincat,interfacerxns,298.15,A_surf); + +# %% +# start with 1mm layer thickness +diffusionlayer = ConstantReservoirDiffusion(domainboundarylayer, initialcondsreservoir, A_surf, layer_thickness); + +# %% +interfaces = [inter, diffusionlayer]; + +# %% +@time react,y0,p = Reactor((domainboundarylayer,domaincat), (y0boundarylayer,y0cat), (0.0, 1e3), interfaces, (pboundarylayer,pcat,pinter)); + +# %% +@time sol = solve(react.ode,Sundials.CVODE_BDF(),abstol=1e-22,reltol=1e-8); +println(sol.t[end]); +println(sol.retcode); + +# %% +ssys = SystemSimulation(sol,(domainboundarylayer,domaincat,), interfaces,p); + +# %% +""" +diffusive flux to the reservoir +""" +function flux_to_reservoir(sim,t,reservoirinterface) + cs = concentrations(sim,t) + return reservoirinterface.A .* sim.domain.diffusivity .* (cs - reservoirinterface.c) / reservoirinterface.layer_thickness +end + +""" +Integrates the flux to the reservoir and computes the concentration assuming +there is no prior concentration of that species in the reservoir +""" +function get_reservoir_concentration(sim,t,reservoirinterface,Vres,C0) + intg,err = quadgk(x -> flux_to_reservoir(sim,x,reservoirinterface), 0, t); + intg[5] = 0; + intg[6] = 0; + return C0 + intg./Vres +end + +# %% +# Logarithmic time scale +t_vals = 10 .^ range(-12, stop=3, length=160); + +# Compute reservoir concentrations +flux_vals = [flux_to_reservoir(ssys.sims[1], t, diffusionlayer) for t in t_vals] + +conc_vals_bl = [concentrations(ssys.sims[1], t) for t in t_vals] +flux_matrix = hcat(flux_vals...); +conc_matrix_bl = hcat(conc_vals_bl...); + + +# %% +conc_0 = concentrations(ssys.sims[1], 0) +t_vals_2 = 10 .^ range(-9, stop=3, length=130); +conc_vals = [get_reservoir_concentration(ssys.sims[1], t, diffusionlayer, V_res, conc_0) for t in t_vals_2] +conc_matrix = hcat(conc_vals...); + +# %% +function plotC_Reservoir(sim, cs, tvals, tol, exclude) + clf() + xs = cs + maxes = maximum(xs, dims=2) + + time_filtered = tvals + xs_filtered = xs + + # Custom species order and their corresponding names and color + species_order = ["CO2", "proton", "H2", "O=CO", "C=O", "CO-2", "CCO", "CH4", "OCO", "COC", "COCO", "CC(=O)O", "COC=O"] + color_map = Dict("CO2" => "black", "proton" => "grey", "H2" => "green", + "O=CO" => "red", "C=O" => "brown", "CO-2" => "blue", "CCO" => "magenta", + "CH4" => "brown", "OCO" => "orange", "COC" => "teal", "COCO" => "lime", "CC(=O)O" => "teal", "COC=O" => "lime") + # Replacement map for species labels + replacement_map = Dict("CO-2" => "CH3OH", "O=CO" => "HCOOH", "C=O" => "HCHO", + "CCO" => "C2H5OH", "OCO" => "CH2(OH)2", "COC" => "CH3OCH3", "COCO" => "CH3OCH2OH", "CC(=O)O" => "CH3COOH", "COC=O" => "CH3OCHO") + + # Build a map of species names to indices + name_to_index = Dict(sim.domain.phase.species[i].name => i for i in 1:length(sim.domain.phase.species)) + # Keep track of whether the species is plotted, used for later checks + plotted = falses(length(sim.domain.phase.species)) + + # Plot species from the custom species dictionary + for species_name in species_order + if species_name in exclude + continue + end + + if haskey(name_to_index, species_name) + i = name_to_index[species_name] + + if (maxes[i] > tol) || (species_name == "proton") || (species_name == "CCO") # Always plot proton and ethanol + plot_label = get(replacement_map, species_name, species_name) + plot_color = color_map[species_name] + + plot(time_filtered, xs_filtered[i, :]/1000, label=plot_label, color=plot_color) + plotted[i] = true # Mark as plotted + end + end + end + + # Plot any remaining species that passed tolerance but were not in species_order + for i in 1:length(sim.domain.phase.species) + if plotted[i] || sim.domain.phase.species[i].name in exclude + continue + end + + if maxes[i] > tol + species_name = sim.domain.phase.species[i].name + plot(time_filtered, xs_filtered[i, :]/1000, label=species_name) # Default color + end + end + + xlabel("Time (s)", fontsize=14) + ylabel("Bulk Concentration (mol/L)", fontsize=14) + xticks(fontsize=14) + yticks(fontsize=14) + legend(loc="upper left", bbox_to_anchor=(0, 0.9), fontsize=12, ncol=2) +end + +# %% +exclude_species = ["H2O", "O=CC=O", "O=CCO", "CC=O"] +plotC_Reservoir(ssys.sims[1], conc_matrix, t_vals_2, 1e-12, exclude_species) + +xscale("log") +yscale("log") +xlim(1e-9, 1e3) +ylim(1e-20, 1e-1) +legend(loc="upper left", bbox_to_anchor=(0, 0.9), fontsize=12, ncol=2) +title("Ag111@-1.0V vs. R.H.E., d = 10e-6 m") +gcf() + +# %% +clf() + +for i in 1:size(flux_matrix, 1) + if maximum(abs.(flux_matrix[i, :])) > 1e-10 + plot(t_vals, abs.(flux_matrix[i, :]), label=ssys.sims[1].domain.phase.species[i].name) + + end +end + +xscale("log") +yscale("log") +xlabel("Time (s)") +ylabel("Diffusive Flux (mol/s)") +xlim(1e-12, 1e3) +ylim(1e-9, 1e1) +legend() +tight_layout() +gcf() + +# %% +clf() + +# Define consistent color map for all species +color_map = Dict( + "CO2" => "black", + "proton" => "grey", + "H2" => "green", + "O=CO" => "red", + "C=O" => "brown", + "CO-2" => "blue", + "CCO" => "magenta", + "CH4" => "olive", + "OCO" => "orange", + "COC" => "teal", + "COCO" => "lime", + "CC(=O)O" => "purple", + "COC=O" => "cyan", + "H2O" => "lightblue", + "O=CC=O" => "pink", + "O=CCO" => "darkred", + "CC=O" => "gold" +) + +for i in 1:size(conc_matrix_bl, 1) + if maximum(conc_matrix_bl[i, :]) > 1e-10 + species_name = ssys.sims[1].domain.phase.species[i].name + # Get color from map, or use default if not found + plot_color = get(color_map, species_name, nothing) + plot(t_vals, conc_matrix_bl[i, :]/1e3, label=species_name, color=plot_color) + end +end + +xscale("log") +yscale("log") +xlabel("Time (s)", fontsize=12) +ylabel("Boundary Layer Concentrations (mol/L)", fontsize=12) +xlim(1e-12, 1e3) +ylim(1e-18, 1) +legend(fontsize=10) +tight_layout() +gcf() + +# %% +# Helper function +function plotX(sim, tol, t_end, exclude) + clf() + xs = molefractions(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time (s)") + ylabel("Concentration (mol/m^3)") +end + +# %% +function plotC(sim, tol, t_end, exclude) + clf() + xs = concentrations(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + # Custom species order and their corresponding names and color + species_order = ["CO2", "proton", "H2", "O=CO", "C=O", "CO-2", "CCO", "CH4", "OCO", "COC", "COCO", "CC(=O)O", "COC=O"] + color_map = Dict("CO2" => "black", "proton" => "grey", "H2" => "green", + "O=CO" => "red", "C=O" => "brown", "CO-2" => "blue", "CCO" => "magenta", + "CH4" => "brown", "OCO" => "orange", "COC" => "teal", "COCO" => "lime", "CC(=O)O" => "teal", "COC=O" => "lime") + # Replacement map for species labels + replacement_map = Dict("CO-2" => "CH3OH", "O=CO" => "HCOOH", "C=O" => "HCHO", + "CCO" => "C2H5OH", "OCO" => "CH2(OH)2", "COC" => "CH3OCH3", "COCO" => "CH3OCH2OH", "CC(=O)O" => "CH3COOH", "COC=O" => "CH3OCHO") + + # Build a map of species names to indices + name_to_index = Dict(sim.domain.phase.species[i].name => i for i in 1:length(sim.domain.phase.species)) + # Keep track of whether the species is plotted, used for later checks + plotted = falses(length(sim.domain.phase.species)) + + # Plot species from the custom species dictionary + for species_name in species_order + if species_name in exclude + continue + end + + if haskey(name_to_index, species_name) + i = name_to_index[species_name] + + if (maxes[i] > tol) || (species_name == "proton") || (species_name == "CCO") # Always plot proton and ethanol + plot_label = get(replacement_map, species_name, species_name) + plot_color = color_map[species_name] + + plot(time_filtered, xs_filtered[i, :]/1000, label=plot_label, color=plot_color) + plotted[i] = true # Mark as plotted + end + end + end + + # Plot any remaining species that passed tolerance but were not in species_order + for i in 1:length(sim.domain.phase.species) + if plotted[i] || sim.domain.phase.species[i].name in exclude + continue + end + + if maxes[i] > tol + species_name = sim.domain.phase.species[i].name + plot(time_filtered, xs_filtered[i, :]/1000, label=species_name) # Default color + end + end + + xlabel("Time (s)", fontsize=14) + ylabel("Boundary Layer Concentration (mol/L)", fontsize=14) + xticks(fontsize=14) + yticks(fontsize=14) + legend(loc="upper left", bbox_to_anchor=(0, 0.9), fontsize=12, ncol=2) +end + +# %% +exclude_species = ["H2O"] +plotX(ssys.sims[1], 1e-12, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-8, 1e3) +ylim(1e-16, 5) +title("Liquid-phase Mole Fractions vs. Time on Ag111@-1.0V") +gcf() + +# %% +exclude_species = ["H2O", "O=CC=O", "O=CCO", "CC=O"] +plotC(ssys.sims[1], 1e-10, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-9, 1e3) +ylim(1e-20, 1e-1) +title("Ag111@-1.0V vs. R.H.E., d = 1 mm") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys.sims[2], 1e-3, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e3) +ylim(1e-6, 5) +title("Surface Mole Fractions vs. Time on Ag111@-1.0V") +gcf() + +# %% +#fd1 = getfluxdiagram(ssys,1;speciesratetolerance=1e-4) + +# %% +#ts = 10.0 .^ range(-10, 3; step=1) +#fd1 = makefluxdiagrams(ssys, ts) + +# %% +species_list = ["CO2", "CO2X", "CO2HX", "CH2O2X", "O=CO"]; +spc_names = [s.name for s in ssys.species]; +G_val = Float64[]; +T = 300.0; + +for spc in species_list + ind = findfirst(==(spc), spc_names); + if isnothing(ind) + @warn "Species $spc not found" + push!(G_val, NaN); + else + sp = ssys.species[ind]; + G = getGibbs(sp.thermo, T); + push!(G_val, G); + end +end + +# %% +dG = G_val .- G_val[1]; + +clf() +for (i, name) in enumerate(species_list) + if !isnan(dG[i]) # Skip NaN values + hlines([dG[i]], xmin=i-0.4, xmax=i+0.4, label=name, linewidth=2) + end +end +xlim(0, length(species_list)+1) +xlabel("Species") +ylabel("Relative Gibbs Energy (J/mol)") +legend() +grid(true, alpha=0.3) +gcf() + +# %% +function plotROP(ssys,name,t;N=0,tol=0.01) + clf() + rop = rops(ssys, name, t) + inds = rop.nzind[reverse(sortperm(abs.(rop.nzval)))] + if N == 0 + N = length(inds) + elseif N > length(inds) + N = length(inds) + end + inds = inds[1:N] + mval = abs(rop[inds[1]]) + minval = mval*tol + k = 1 + while k < length(inds) && abs(rop[inds[k]]) >= minval + k += 1 + end + inds = inds[1:k] + net_rops = sum(rop[inds]) + println("Net ROPs for species $name is: $net_rops") + + for (i, j) in enumerate(inds) + println("Showing the reaction with $i th highest ROP for species $name:") + println(getrxnstr(ssys.reactions[j])) + println("ROP = ", rop[inds[i]]) + println(ssys.reactions[j].kinetics) + end + + xs = Array{Float64,1}(1:length(inds)) + barh(xs,reverse(rop[inds])) + yticks(xs,reverse(getrxnstr.(ssys.reactions[inds]))) + xlabel("Production/Loss Rate mol/s") + gcf() +end + +# %% +function PrintKinDetail(inter, speciesname) + println("Showing Kinetics details for reactions involving species $speciesname\n") + for (i,rxn) in enumerate(inter.reactions) + flag = false + for j = 1:length(rxn.reactants) + if rxn.reactants[j].name == speciesname + flag = true + end + end + for j = 1:length(rxn.products) + if rxn.products[j].name == speciesname + flag = true + end + end + if flag + println(getrxnstr(rxn)) + println(rxn.kinetics) + kf = inter.kfs[i] + krev = inter.krevs[i] + kc = kf/krev + println("kf = $kf") + println("krev = $krev") + println("Kc = $kc\n") + end + end +end + +# %% +""" +Integrates the ROP in the boundary layer and computes the concentration +""" +function get_boundary_layer_concentration(sim,t,spc,Vbl,C_0) + intg,err = quadgk(x -> sum(rops(sim,spc,t)), 0, t); + return C_0 + intg ./ Vbl; +end + +# %% +""" +diffusive flux to the reservoir using concentration from ROP integration +""" +function flux_to_reservoir_2(bsol,t,spc,Vbl,C_0,reservoirinterface) + cs = get_boundary_layer_concentration(bsol,t,spc,Vbl,C_0) + spc_idx = findfirst(s -> s.name == spc, bsol.sims[1].species) + d = bsol.sims[1].domain.diffusivity[spc_idx]; + c_res = reservoirinterface.c[spc_idx]; + return reservoirinterface.A * d * (cs - c_res) / reservoirinterface.layer_thickness +end + +# %% +# Compute ROP over time +ROP_vals = [sum(rops(ssys, "O=CO", t)) for t in t_vals]; +# Compute boundary layer accumulation by integration +Cbl_vals = [get_boundary_layer_concentration(ssys, t, "O=CO", V_bl, C_default) for t in t_vals]; +# Compute flux over time using Cbl_vals +F_vals = [flux_to_reservoir_2(ssys, t, "O=CO", V_bl, C_default, diffusionlayer) for t in t_vals]; + +# %% +# Plots the ROP of O=CO +clf() + +plot(t_vals, ROP_vals) + +xscale("log") +xlim(1e-11,1e3) +yscale("log") +ylim(1e-8,1e2) +xlabel("Time (s)") +ylabel("Rate of Progress (mol/s)") +legend() +tight_layout() +gcf() + +# %% +# Plots the Boundary Layer Concentration of O=CO from ROP Integration WITHOUT Diffusion Flux Into Reservoir +clf() + +plot(t_vals, Cbl_vals) + +xscale("log") +xlim(1e-11,1e3) +yscale("log") +ylim(1e-13,1e1) +xlabel("Time (s)") +ylabel("Concentration (mol/m^3)") +title("Boundary Layer Accumulation of O=CO from ROP Integration") +legend() +tight_layout() +gcf() + +# %% +# Plots the Diffusive Flux of O=CO using ROP Integration +clf() + +plot(t_vals, F_vals) + +xscale("log") +xlim(1e-11,1e3) +yscale("log") +ylim(1e-15,1e1) +xlabel("Time (s)") +ylabel("Diffusive Flux (mol/m^3)") +title("Diffusive Flux of O=CO from ROP Integration") +legend() +tight_layout() +gcf() + +# %% +# Plots the Diffusion Flux Into Reservoir Using Integrated Concentration from ROP Analysis +clf() + +plot(t_vals, F_vals) + +xscale("log") +yscale("log") +xlabel("Time (s)") +ylabel("Diffusive Flux") +title("Diffusive Flux of O=CO from ROP Integration") +legend() +tight_layout() +gcf() + +# %% +plotROP(ssys, "proton",1;N=15,tol=0.0) + +# %% +plotROP(ssys, "HX",sol.t[end];N=15,tol=0.0) + +# %% +plotROP(ssys, "OCX",sol.t[end];N=15,tol=0.0) + +# %% +plotROP(ssys, "O=CO",sol.t[end];N=15,tol=0.0) + +# %% +plotROP(ssys,"CH2O2X",sol.t[end];N=15,tol=0.0) + +# %% +plotROP(ssys,"CHO2X",sol.t[end];N=10,tol=0.0) + +# %% +plotROP(ssys,"CO2HX",sol.t[end];N=10,tol=0.0) + +# %% +plotROP(ssys,"OCX",sol.t[end]) + +# %% +plotROP(ssys,"H2",sol.t[end]) diff --git a/CO2_Reduction_Ag/CO2RR_RMS_Diffusion_Interface_Matt.ipynb b/CO2_Reduction_Ag/CO2RR_RMS_Diffusion_Interface_Matt.ipynb deleted file mode 100644 index 30c3917..0000000 --- a/CO2_Reduction_Ag/CO2RR_RMS_Diffusion_Interface_Matt.ipynb +++ /dev/null @@ -1,7147 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 41, - "id": "8a590634", - "metadata": {}, - "outputs": [], - "source": [ - "using ReactionMechanismSimulator\n", - "using PyPlot\n", - "using Sundials\n", - "using SciMLBase\n", - "using QuadGK" - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "id": "e941d4fb", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[06:16:05] WARNING: not removing hydrogen atom without neighbors\n", - "[06:16:05] WARNING: not removing hydrogen atom without neighbors\n", - "┌ Warning: failed to generate StokesDiffusivity model for species vacantX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2O2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species H2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [H][H].[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(=O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH3X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(C#[Pt])CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)C(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C([Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C([Pt])CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC([Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=[Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC([Pt])=C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=C=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC(=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCOC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCC(=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC([Pt])=C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=COC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CCOO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=COC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])C=CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCCC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C([Pt])CCO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCCOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(O)C(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)C(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C(O)C=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC([Pt])OC=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=[Pt])OC=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=C(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC([Pt])=CO\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(O)C#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=COOC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C([Pt])C=O\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C(C=O)O[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=CC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)C[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n" - ] - }, - { - "data": { - "text/plain": [ - "Dict{Any, Any} with 4 entries:\n", - " \"Solvents\" => Solvent[Solvent(\"water\", RiedelViscosity{Float64}(…\n", - " Set([\"surface\", \"gas\"]) => Dict{Any, Any}(\"Reactions\"=>ElementaryReaction[vac…\n", - " \"gas\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…\n", - " \"surface\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "outdict = readinput(\"chem300.rms\")\n" - ] - }, - { - "cell_type": "code", - "execution_count": 43, - "id": "fe2767e9", - "metadata": {}, - "outputs": [], - "source": [ - "boundarylayerspcs = outdict[\"gas\"][\"Species\"]\n", - "boundarylayerrxns = outdict[\"gas\"][\"Reactions\"]\n", - "surfspcs = outdict[\"surface\"][\"Species\"]\n", - "surfrxns = outdict[\"surface\"][\"Reactions\"]\n", - "interfacerxns = outdict[Set([\"surface\", \"gas\"])][\"Reactions\"]\n", - "solv = outdict[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "id": "c54ee65e", - "metadata": {}, - "outputs": [], - "source": [ - "sitedensity = 2.292e-5; # Ag111\n", - "boundarylayer = IdealDiluteSolution(boundarylayerspcs,boundarylayerrxns,solv,name=\"boundarylayeruid\",diffusionlimited=true);\n", - "surf = IdealSurface(surfspcs,surfrxns,sitedensity,name=\"surface\");" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8894c84d", - "metadata": {}, - "outputs": [], - "source": [ - "initialcondsboundarylayer = Dict([\"proton\"=>10.0^-4,\n", - " \"CO2\"=>10.0^-3*10^6,\n", - " \"V\"=>1.0e-3,\"T\"=>300,\"Phi\"=>0.0,\"d\"=>0.0]);\n", - "initialcondsreservoir = Dict([\"proton\"=>10.0^-4,\n", - " \"CO2\"=>10.0^-3*10^6,\n", - " \"V\"=>1.0,\"T\"=>300]);\n", - "AVratio = 1e5;\n", - "initialcondssurf = Dict([\"CO2X\"=>0.4*sitedensity*AVratio,\n", - "# \"CHO2X\"=>0.1*sitedensity*AVratio,\n", - "# \"CO2HX\"=>0.1*sitedensity*AVratio,\n", - "# \"OX\"=>0.1*sitedensity*AVratio,\n", - "# \"OCX\"=>0.1*sitedensity*AVratio,\n", - " \"vacantX\"=>1.0*sitedensity*AVratio,\n", - "# \"CH2O2X\"=>0.05*sitedensity*AVratio,\n", - "# \"CHOX\"=>0.04*sitedensity*AVratio,\n", - "# \"CH2OX\"=>0.01*sitedensity*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>300,\"Phi\"=>-1.0]);" - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "id": "ddb39b3d", - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "domainboundarylayer, y0boundarylayer, pboundarylayer = ConstantTVDomain(phase=boundarylayer, initialconds=initialcondsboundarylayer);\n", - "domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf,\n", - " initialconds=initialcondssurf);" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "id": "ed49d2b4", - "metadata": {}, - "outputs": [], - "source": [ - "inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainboundarylayer,\n", - " domaincat,interfacerxns,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "id": "dee14906", - "metadata": {}, - "outputs": [], - "source": [ - "# start with 1mm layer thickness\n", - "diffusionlayer = ConstantReservoirDiffusion(domainboundarylayer, initialcondsreservoir, AVratio*1.0, 1e-3);" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "id": "e70ac4b0", - "metadata": {}, - "outputs": [], - "source": [ - "interfaces = [inter, diffusionlayer];" - ] - }, - { - "cell_type": "code", - "execution_count": 50, - "id": "244f0912", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.067722 seconds (61.60 k allocations: 139.523 MiB, 21.90% gc time)\n" - ] - } - ], - "source": [ - "@time react,y0,p = Reactor((domainboundarylayer,domaincat), (y0boundarylayer,y0cat), (0.0, 100.0), interfaces, (pboundarylayer,pcat,pinter));\n" - ] - }, - { - "cell_type": "code", - "execution_count": 51, - "id": "962f838c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 4.182686 seconds (3.17 M allocations: 10.057 GiB, 23.77% gc time)\n" - ] - } - ], - "source": [ - "@time sol = solve(react.ode,Sundials.CVODE_BDF(),abstol=1e-16,reltol=1e-6);" - ] - }, - { - "cell_type": "code", - "execution_count": 52, - "id": "56b6f906", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "100.0" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sol.t[end]" - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "id": "4714593e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ReturnCode.Success = 1" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sol.retcode" - ] - }, - { - "cell_type": "code", - "execution_count": 54, - "id": "6667bb5a", - "metadata": {}, - "outputs": [], - "source": [ - "ssys = SystemSimulation(sol,(domainboundarylayer,domaincat,), interfaces,p);" - ] - }, - { - "cell_type": "code", - "execution_count": 55, - "id": "abcf6608", - "metadata": {}, - "outputs": [], - "source": [ - "plotmolefractions(ssys.sims[1], 0.99e2,tol=1e-25)\n", - "yscale(\"log\")\n", - "xscale(\"log\")" - ] - }, - { - "cell_type": "code", - "execution_count": 56, - "id": "afae3194", - "metadata": {}, - "outputs": [], - "source": [ - "plotmolefractions(ssys.sims[2], 0.99e2,tol=3e-2)\n", - "xscale(\"log\")" - ] - }, - { - "cell_type": "code", - "execution_count": 57, - "id": "d4939a87", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "get_reservoir_concentration" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "\"\"\"\n", - "diffusive flux to the reservoir\n", - "\"\"\"\n", - "function flux_to_reservoir(sim,t,reservoirinterface)\n", - " cs = concentrations(sim,t)\n", - " return reservoirinterface.A .* sim.domain.diffusivity .* (cs - reservoirinterface.c) / reservoirinterface.layer_thickness\n", - "end\n", - "\n", - "\"\"\"\n", - "Integrates the flux to the reservoir and computes the concentration assuming\n", - "there is no prior concentration of that species in the reservoir\n", - "\"\"\"\n", - "function get_reservoir_concentration(sim,t,reservoirinterface,Vres)\n", - " intg,err = quadgk(x -> flux_to_reservoir(sim,x,reservoirinterface), 0, t)\n", - " return intg./Vres\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 58, - "id": "4d4dfc9c", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "108-element Vector{Float64}:\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 2.127051950376656e-25\n", - " -3.510243060654668e-24\n", - " -8.96648312396144e-32\n", - " ⋮\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "flux_to_reservoir(ssys.sims[1],0.99e2,diffusionlayer)" - ] - }, - { - "cell_type": "code", - "execution_count": 59, - "id": "782dc215", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "108-element Vector{Float64}:\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 999.0002936231041\n", - " 9.990001587581694e-5\n", - " 0.0\n", - " -1.467825103225412e-21\n", - " -6.296704606711658e-22\n", - " -8.269101685197958e-22\n", - " ⋮\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0\n", - " 0.0" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "res_cs = get_reservoir_concentration(ssys.sims[1],0.99e2,diffusionlayer,1.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 60, - "id": "e8885c97", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "108-element Vector{Float64}:\n", - " -3.510028156283103e-20\n", - " -1.467825103225412e-21\n", - " -8.269101685197958e-22\n", - " -6.296704606711658e-22\n", - " -4.143209291884549e-22\n", - " -2.4664908632623496e-22\n", - " -1.4501328070805046e-22\n", - " -2.4297366095524073e-24\n", - " -4.26741575269268e-27\n", - " -1.7565743538985845e-30\n", - " ⋮\n", - " 2.9311480681523782e-24\n", - " 6.298841337396956e-23\n", - " 1.2552996666635814e-22\n", - " 3.8512926576472575e-22\n", - " 1.2001691194545139e-21\n", - " 1.9879062943569044e-21\n", - " 6.998718825476003e-21\n", - " 9.990001587581694e-5\n", - " 999.0002936231041" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sort(res_cs)" - ] - }, - { - "cell_type": "code", - "execution_count": 61, - "id": "9606a8ed", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "108-element Vector{String}:\n", - " \"Ar\"\n", - " \"He\"\n", - " \"Ne\"\n", - " \"N2\"\n", - " \"CO2\"\n", - " \"proton\"\n", - " \"H\"\n", - " \"C=O\"\n", - " \"O=CO\"\n", - " \"H2O\"\n", - " ⋮\n", - " \"CCOCO\"\n", - " \"CCCOO\"\n", - " \"CCC\"\n", - " \"CCOOC\"\n", - " \"C=C=COO\"\n", - " \"CC=COO\"\n", - " \"C=CCO[O]\"\n", - " \"COCOC\"\n", - " \"COCCO\"" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "getfield.(ssys.sims[1].domain.phase.species,:name)" - ] - }, - { - "cell_type": "code", - "execution_count": 62, - "id": "9be02a3e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "192-element Vector{String}:\n", - " \"vacantX\"\n", - " \"CO2X\"\n", - " \"CHO2X\"\n", - " \"CO2HX\"\n", - " \"OCX\"\n", - " \"OX\"\n", - " \"CH2O2X\"\n", - " \"CHOX\"\n", - " \"CH2OX\"\n", - " \"HOX\"\n", - " ⋮\n", - " \"O=CCCO[Pt]\"\n", - " \"O=CCC[Pt]\"\n", - " \"C=COOC#[Pt]\"\n", - " \"C=CC=O.[Pt]\"\n", - " \"C=C([Pt])C=O\"\n", - " \"C=C(C=O)O[Pt]\"\n", - " \"C=CC=[Pt]\"\n", - " \"CC(O)O.[Pt]\"\n", - " \"OC(O)C[Pt]\"" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "getfield.(ssys.sims[2].domain.phase.species,:name)" - ] - }, - { - "cell_type": "code", - "execution_count": 63, - "id": "87dcaf99", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotX (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotX(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = molefractions(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Mole Fraction\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 64, - "id": "ddf6da6b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotC (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotC(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = concentrations(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Concentration\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 65, - "id": "386a52a2", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "108×2718 Matrix{Float64}:\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 … 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 1.0e6 1.0e6 1.0e6 1.0e6 1.0e6 1.0e6 1000.0 1000.0\n", - " 0.1 0.1 0.1 0.1 0.1 0.1 … 0.0001 0.0001\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 1.26649e-24 1.70973e-24\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 -1.08044e-22 2.70162e-24\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 -2.08817e-30 -5.98544e-32\n", - " ⋮ ⋮ ⋱ \n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 … 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 … 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "concentrations(ssys.sims[1])" - ] - }, - { - "cell_type": "code", - "execution_count": 66, - "id": "da1def09", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "192×2718 Matrix{Float64}:\n", - " 2.292e-5 2.292e-5 2.292e-5 … 1.48811e-9 1.48778e-9\n", - " 9.168e-6 9.168e-6 9.16803e-6 2.67667e-6 2.67609e-6\n", - " 0.0 3.24252e-16 2.68962e-15 3.72688e-11 3.72614e-11\n", - " 0.0 2.91093e-18 2.41457e-17 2.79838e-11 2.79778e-11\n", - " 0.0 4.98345e-26 3.06528e-24 2.18384e-11 2.18338e-11\n", - " 0.0 1.77024e-40 1.0888e-38 … 3.77888e-17 3.7788e-17\n", - " 0.0 5.58937e-24 3.43799e-22 2.45322e-5 2.45235e-5\n", - " 0.0 8.53155e-34 3.83663e-31 2.05333e-10 2.05293e-10\n", - " 0.0 1.0452e-42 3.42982e-39 7.18635e-9 7.18497e-9\n", - " 0.0 3.03063e-48 1.36279e-45 7.40575e-19 7.40568e-19\n", - " ⋮ ⋱ \n", - " 0.0 7.44284e-106 7.87499e-97 1.84255e-24 1.84169e-24\n", - " 0.0 3.7116e-143 2.15143e-126 5.74841e-29 5.74626e-29\n", - " 0.0 0.0 8.02521e-256 … 3.6977e-80 3.69116e-80\n", - " 0.0 4.10532e-147 8.28194e-117 1.62355e-26 1.62278e-26\n", - " 0.0 7.16192e-143 1.43798e-127 3.20669e-43 3.20538e-43\n", - " 0.0 4.40393e-195 1.07731e-146 -3.82267e-47 9.8272e-48\n", - " 0.0 5.00958e-203 5.55362e-151 1.03891e-38 1.03856e-38\n", - " 0.0 5.74078e-104 4.36787e-89 … 7.76022e-19 7.75873e-19\n", - " 0.0 1.59781e-96 1.23158e-88 3.57634e-24 3.57635e-24" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "concentrations(ssys.sims[2])" - ] - }, - { - "cell_type": "code", - "execution_count": 67, - "id": "e719a85d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys.sims[1], 1e-6, 1e2, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e2)\n", - "ylim(1e-9, 5)\n", - "title(\"Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 68, - "id": "1ef78267", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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14osvCqVSKbKzsyuNtS4+t8rk5+cLJycn0b17d01ZTEyMkCRJ84+EEP9+VqNHj9Z6/6FDhwQAo0rIfv75Z2Fvby+ysrI0ZatXrxaBgYHCyspK9O/fX3z88ceav5Xi4mLh6el5338yaxNvuc8//1wsXLhQ7Ny5U/z444/irbfeEm5ubsLDw0NcuXJFq275frlp0yZN2cmTJ+97XKuIyVyy/Pzzz3H06FGt16+//qqZ36hRIwwZMgSfffYZ1Go1AODmzZvYunUrxo4dC0vLstvlfvzxR9jb2+tchim/XKHPZR5D+/HHH9G/f3/4+vrqxFRQUKBzOWjo0KFa0yEhIQCgddnkXvn5+fj1118xcuRIODg4aMoVCgWio6Nx5coVvS97GsL+/fvRrl07dOjQQav8iSeeMNg68vPzcfToUTz66KNaN4Q6OjpiyJAhWnXVajVKS0s1L5VKpTW/slhzc3Px22+/aZXr8/lkZGRg0qRJ8PX1haWlJaysrODv7w8AOHPmjKZe165dsX79erz55ps4fPgwSkpKtJadmJiI7OxsxMTEaMWvVqsxaNAgHD16FPn5+Xq11/2cO3cOaWlpiI6O1rok4ODggBEjRuDw4cMoKCi4b1sUFhYiIyMDQNmlMAB44YUXKl3v7t27UVpairFjx2pto1KpRN++fXWelJQkSefzDQkJqfLvoyIjRozQKcvLy8OMGTPQokULWFpawtLSEg4ODsjPz9f63Krjxx9/BACdy/KPPfYY7O3tdY5JHTt2hJ+fn2ZaqVQiKChIa/u6du2KH374ATNnzsSBAwdw584dvWJ58sknYWNjo3XZf8OGDSgqKsJTTz2ltfyq9sv65OnpidDQUM20m5sb3N3d0bFjR3h5eWnK27RpA+Dfv8PCwkLs27cPw4cPh52dnda+FRUVhcLCQhw+fLjS9dbF51aZb775Brm5uVqXv8aPHw8hhNblssOHD6OoqAijRo3Sen/37t2N7sneLVu2YOTIkXBzcwNQdivE5MmTMW7cOOzZswe9e/fGSy+9pKlvZWWFQYMGadpdCKH1mZWWlhostujoaLz22muIjIxEeHg4ZsyYgR9++AE3btxAbGysVt1Ro0bB0dFR6/Lzp59+CkmStP5m9GEyCVmbNm3QpUsXrdfdf4RA2Q569epVxMfHA/j3QHL3H0xWVhaaNm2q8yiuu7s7LC0tkZWVVefbcq+srKwKnxwqP5jcG1OjRo20pm1sbACgyoPuzZs3IYSo1nrqUvnncK+Kymrq5s2bUKvVeq1n/PjxsLKy0rzufZihqmVU9/NRq9WIiIjApk2b8Oqrr2Lfvn04cuSI5uB/9+cYFxeHmJgYfPzxx+jRowfc3NwwduxYpKenAygbrgIou8/r7vitrKywZMkSCCGQnZ1daRv5+fnhxo0beiVt5dtZ2T6kVqt1nsa8X1vcuHEDCoWiys+9fBvDwsJ0tjEuLk7nvjs7OzudJ7JsbGxQWFh43228W0Xb+cQTT+D999/H008/jd27d+PIkSM4evQomjRponfSc6+srCxYWlrq3PgrSRKaNm163/0LKNu+u9f/7rvvYsaMGdiyZQvCw8Ph5uaGYcOG3XcIEzc3NwwdOhSff/655p+S9evXo2vXrmjXrp2m3v32y/pUfkK/m7W1tU65tbU1AGj2g6ysLJSWluK9997T2a+ioqIAQGffultdfG6V+eSTT6BUKjFo0CDcunULt27dQkhICAICArB+/XrNZ1W+Tg8PD51lVFQmp/Pnz2v+WQWANWvWYNy4cZgzZw769euHuXPnYvTo0Vrv8fDw0Nys/9lnn+l8bnWpa9euCAoK0knS7ezsMGbMGOzatQvp6ekoLS3Fl19+ib59+1b7AR6TecpSHwMHDoSXlxfWrVuHgQMHYt26dejWrZvWkzyNGjXCr7/+CiGEVlKWkZGB0tLSSp+oAKA5yN97839Vf7T6aNSoEa5du6ZTnpaWBgBVxqQvV1dXWFhY1Pl69NWoUaMKD94VlSmVygofuMjMzKwyZldXV0iSpNd65s2bhxdffFEz7ejoeN+4yssqOtBW5eTJk/j999+xfv16xMTEaMqTk5N16jZu3BgrV67EypUrkZqaim3btmHmzJnIyMjArl27NNv/3nvvVfqEaVUH4oEDB2LPnj34/vvvMWbMmCrjLt/OyvYhCwsLuLq6VrmMezVp0gQqlQrp6emVDmdQvo3ffvutphexPtz7T1tOTg62b9+OuXPnYubMmZryoqKiKpPe+2nUqBFKS0tx48YNrZO7EALp6ekICwur9jLt7e0xf/58zJ8/H9evX9f0lg0ZMkTzJGNlnnrqKWzcuBHx8fHw8/PD0aNHsXr1aq0699svTYGrq6vmCkFlPbSBgYGVvr8uPreKnD9/Hj///DMAaPWw3W337t2IiorS/I2W/xNzt/T0dKPqJSspKdH6xyklJQWDBw/WqhMWFqbpEQPKxhcrv5I0ZMgQHD16tH6C/YcQosIHBiZMmICPPvoIn3/+OYKCgpCRkYFly5ZVe/km00Omj/I/ri1btuDgwYM4duyYzhMO/fv3R15ens5Ap59//rlmfmXKd+Y//vhDq/zep8EA/f/zKV/njz/+qEmM7o7Jzs7OIEM52Nvbo1u3bti0aZNWXGq1Gl9++SV8fHwQFBRU6/XoKzw8HKdOncLvv/+uVf6///1Pp25AQIBOm58/f/6+l1jt7e3RtWtXbNq0Sat35Pbt2zpj7gQEBGj1vt477lplsTo6OqJz585VxnGv8hN9eW9RuTVr1lT5Pj8/P7z44osYMGCA5jJpr1694OLigtOnT+v0IJe/ynsGKjJhwgQ0bdoUr776Kq5evVphnU2bNgEAWrVqBW9vb/zvf/+DEEIzPz8/H999953mycvqiIyMBACdE/7dBg4cCEtLS/z111+VbmN16dOrfC9JkiCE0PncPv74Y51L3NVZfvkx58svv9Qq/+6775Cfn1/roWc8PDwwbtw4PP744zh37pzOZeV7RUREwNvbG+vWrcO6deugVCrx+OOPV1q/ov3SFNjZ2SE8PBwnTpxASEhIhftVVf9s1fXnVq78qdePPvoI+/fv13rt3LkTVlZWmstl3bp1g42NDeLi4rSWcfjw4Wpfsq9rfn5+OH/+vGbaw8NDZwSDlJQUze/Z2dnYtm0bBg4cCKAsIa7tcaA6Dh8+jAsXLlR4Pu7WrRuCg4M1fzPOzs4V3vJwPybTQ3by5MkKrxE3b95c67+T8ePHY8mSJXjiiSdga2ur0+U5duxYfPDBB4iJicHFixfRvn17/Pzzz1i0aBGioqLw0EMPVRpDWFgYWrVqhenTp6O0tBSurq7YvHmz5r+Xu7Vv3x6bNm3C6tWrERoaCgsLi0p3mLlz52L79u0IDw/HnDlz4Obmhq+++go7duxAbGys1sB0tbF48WIMGDAA4eHhmD59OqytrbFq1SqcPHkSGzZsqNWIyn/++WeF41WFhYVV2KsxZcoUfPrpp3j44Yfx5ptvwsPDA1999VWF/71HR0fjP//5D55//nmMGDECly5dQmxsrF5ju7zxxhsYNGgQBgwYgGnTpkGlUmHJkiWwt7evVq+Gl5cXhg4dinnz5sHT0xNffvkl4uPjsWTJkmonIa1bt0bz5s0xc+ZMCCHg5uaG77//XnOpvVxOTg7Cw8PxxBNPoHXr1nB0dMTRo0exa9cuzTAuDg4OeO+99xATE4Ps7GyMHDkS7u7uuHHjBn7//XfcuHGjymTH2dkZW7duxeDBg9GpUyetgWEvXLiAL7/8Er///jseffRRWFhYIDY2Fk8++SQGDx6MiRMnoqioCG+//TZu3bqFt956q1rtAAC9e/dGdHQ03nzzTVy/fh2DBw+GjY0NTpw4ATs7O0yePBkBAQFYsGABZs+ejb///huDBg2Cq6srrl+/jiNHjmh6g6rD0dER/v7+2Lp1K/r37w83Nzc0bty4yh4EJycn9OnTB2+//bam7k8//YRPPvkELi4uWnXLxyRau3YtHB0doVQqERgYWOEJfsCAARg4cCBmzJiB3Nxc9OrVC3/88Qfmzp2LTp066T2o5N26deuGwYMHIyQkBK6urjhz5gy++OILvZJmhUKBsWPHYvny5XBycsKjjz6qdQzSZ78EgAULFmDBggXYt28f+vbtW+1tqA/vvPMOHnjgAfTu3RvPPfccAgICcPv2bSQnJ+P777/X6p25V118bvcqLS3F559/jjZt2uDpp5+usM6QIUOwbds2TU/d1KlTsXjxYri6umL48OG4cuUK5s+fD09PT53enWPHjmmSoNzcXAghNMfxe4/d5eV///235r3l9yPffU/2pUuXND1Xf/31l9Z7y//xBcoS/ylTpiA2NhbW1tYYNWoUZs6cid69e6N379745ZdfsGbNGri4uODQoUOYPHkyHnroIb33JX3j7d+/P3766Set/KJDhw74z3/+gzZt2kCpVOLIkSN4++23Nf+8VmT8+PGYOnUqzp07h4kTJ9ZsfLhqPQIgg6qesgQgPvroI5339OzZUwAQTz75ZIXLzMrKEpMmTRKenp7C0tJS+Pv7i1mzZmk9pixExU/3nT9/XkRERAgnJyfRpEkTMXnyZLFjxw6dJ6qys7PFyJEjhYuLi5AkSetJE1TwdNeff/4phgwZIpydnYW1tbXo0KGDzlMh5U/xbdy4Uau8oqcLK3Pw4EHx4IMPCnt7e2Frayu6d+8uvv/++wqXV52nLCt7lcdUUVuePn1aDBgwQCiVSuHm5iYmTJggtm7dqtOWarVaxMbGimbNmgmlUim6dOkifvzxR72eshRCiG3btomQkBBhbW0t/Pz8xFtvvaV5kk4f/v7+4uGHHxbffvutaNeunbC2thYBAQFi+fLlWvWq8/mUb7ujo6NwdXUVjz32mEhNTdXaNwoLC8WkSZNESEiIcHJyEra2tqJVq1Zi7ty5mic7y/3000/i4YcfFm5ubsLKykp4e3uLhx9+WCeWyqSnp4sZM2aIdu3aCTs7O2FjYyNatGghJk6cKP7880+tulu2bBHdunUTSqVS2Nvbi/79+4tffvlFq055+5YPBVGuoiflVCqVWLFihQgODhbW1tbC2dlZ9OjRQ2e/3LJliwgPDxdOTk7CxsZG+Pv7i5EjR2o9dRUTEyPs7e11tq+iz3vv3r2iU6dOwsbGRgDQ7J+VxS6EEFeuXBEjRowQrq6uwtHRUQwaNEicPHmywv175cqVIjAwUCgUCq3P/96nLIUoe+JuxowZwt/fX1hZWQlPT0/x3HPPiZs3b2rVK98X73Xv38LMmTNFly5dhKurq7CxsRHNmjUTr7zyisjMzNR5b0XOnz+v+RuOj4/XmqfvflnejhU9aVqZmjxl2a5dO526lbUTAPHCCy9olaWkpIjx48cLb29vYWVlJZo0aSJ69uwp3nzzzfvGa+jP7V5btmwRAMTKlSsrrVP+tOeyZcuEEGXHyzfffFP4+PgIa2trERISIrZv3y46dOgghg8frvXe8qeSqzp2l6vqOH+3qs7Zd/+NlJSUiKCgIM3wIqWlpWLixIma86Wnp6dYsGCBACCcnZ3FrFmzRFFRUaXtcC994y1/UvduY8aMES1atBD29vbCyspK+Pv7i0mTJom0tLRK13fjxg1hbW0tAIgjR47oHefdpH8CJzIKBw4cQHh4OPbv318nX2lTEwEBAQgODsb27dvlDoWIqNpSUlLQunVrzJ07F6+99prc4WgkJibioYcewqJFizRfM3jr1i2kpaWhZcuWKCoqwrVr19CsWTMoFAp5g60HJnPJkoiIiKr2+++/Y8OGDejZsyecnJxw7tw5xMbGwsnJSTOyvLHo2bMntm7dijFjxuDbb7/Fiy++iF69eqFZs2a4efMmkpKS8NVXX+HPP//EL7/8UquviTIFDeqm/sqsWLEC7dq1Q9u2bfHSSy+BnYJERNQQ2dvb49ixY5gwYQIGDBiA2bNno1OnTvj555+NbugLoOxevDNnzqBbt26YNm0a/Pz8YGtrCw8PDzz++ONQKpX49ttvG3wyBgAN/pLljRs30L17d5w6dQpWVlbo06cPli5dih49esgdGhEREd3l6tWryMrKgpOTE/z9/Wv1sJmpMYtLlqWlpZphD0pKSuDu7i5zRERERHQvb29veHt7yx2GLIz+kmVCQgKGDBkCLy8vSJKkM34YAKxatQqBgYFQKpUIDQ3FwYMHNfOaNGmC6dOnw8/PD15eXnjooYeqPXouERERUV0y+oQsPz8fHTp0wPvvv1/h/Li4OEyZMgWzZ8/GiRMn0Lt3b0RGRiI1NRVA2dfnbN++HRcvXsTVq1eRmJiIhISE+twEIiIioiqZ1D1kkiRh8+bNGDZsmKasW7du6Ny5s9bgl23atMGwYcOwePFibNy4EQcOHMAHH3wAAHj77bchhKh0cLeioiKtr+lRq9XIzs5Go0aNzOpaNhERkSkTQuD27dvw8vKq8CuPjI1J30NWXFyM48ePa32vHFA2AnBiYiIAwNfXF4mJiSgsLISVlRUOHDiAZ599ttJlLl68uNqjfhMREZFxunz5Mnx8fOQO475MOiHLzMyESqXSeZTXw8ND88XP3bt3R1RUFDp16gQLCwv0798fQ4cOrXSZs2bNwtSpUzXTOTk58PPzw+XLl+Hk5FQ3G0JEREQGlZubC19fXzg6Osodil5MOiErd++lRCGEVtnChQuxcOFCvZZlY2Oj8+XBQNn32DEhIyIiMi2mcruR8V9UrULjxo2hUCg0vWHlMjIyjHIAPCIiIqKKmHRCZm1tjdDQUMTHx2uVx8fHo2fPnjJFRURERFQ9Rn/JMi8vD8nJyZrplJQUJCUlwc3NDX5+fpg6dSqio6PRpUsX9OjRA2vXrkVqaiomTZokY9RERGRuVCoVSkpK5A7DbFhZWTWoLx03+oTs2LFjCA8P10yX33AfExOD9evXY/To0cjKysKCBQtw7do1BAcHY+fOnfD395crZCIiMiNCCKSnp+PWrVtyh2J2XFxc0LRpU5O5T6wqJjUOmRxyc3Ph7OyMnJwc3tRPREQ6rl27hlu3bsHd3R12dnYNIjkwdkIIFBQUICMjAy4uLvD09NSpY2rnb6PvISMiIjJWKpVKk4w1atRI7nDMiq2tLYCyB/nc3d1N/vKlSd/UT0REJKfye8bs7OxkjsQ8lbd7Q7h3jwkZERFRLfEypTwaUrszISMiIiKSGRMyIiIiIpkxISMiIiKSGRMyIiIiM5Weno7JkyejWbNmsLGxga+vL4YMGYJ9+/Zp6iQmJiIqKgqurq5QKpVo3749li1bBpVKpalz8eJFTJgwAYGBgbC1tUXz5s0xd+5cFBcXy7FZJonDXhAREZmhixcvolevXnBxcUFsbCxCQkJQUlKC3bt344UXXsDZs2exefNmjBo1Ck899RT2798PFxcX7N27F6+++ioOHz6Mb775BpIk4ezZs1Cr1VizZg1atGiBkydP4plnnkF+fj6WLl0q96aaBA4Mex+mNrAcERHVn8LCQqSkpCAwMBBKpRJA2aCld0pU93ln3bC1Uuj95GFUVBT++OMPnDt3Dvb29lrzbt26BSsrK/j7+6Nv37747rvvtOZ///33GDp0KL7++muMHj26wuW//fbbWL16Nf7++++abYweKmr/cqZ2/mYPGRERkQHdKVGh7Zzdsqz79IKBsLO+/6k9Ozsbu3btwsKFC3WSMaDsK4k2b96MrKwsTJ8+XWf+kCFDEBQUhA0bNlSakOXk5MDNza36G2GmeA8ZERGRmUlOToYQAq1bt660zvnz5wEAbdq0qXB+69atNXXu9ddff+G9997DpEmTah+smWAPGRERkQHZWilwesFA2datj/K7lfS5vFnZnU1CiArfn5aWhkGDBuGxxx7D008/rVc8xISMiIjIoCRJ0uuyoZxatmwJSZJw5swZDBs2rMI6QUFBAIAzZ86gZ8+eOvPPnj2Ltm3bapWlpaUhPDwcPXr0wNq1aw0ed0PGS5ZERERmxs3NDQMHDsQHH3yA/Px8nfm3bt1CREQE3NzcsGzZMp3527Ztw4ULF/D4449ryq5evYp+/fqhc+fOWLduHSwsmGJUB1uLiIjIDK1atQoqlQpdu3bFd999hwsXLuDMmTN499130aNHD9jb22PNmjXYunUrnn32Wfzxxx+4ePEiPvnkE4wbNw4jR47EqFGjAJT1jPXr1w++vr5YunQpbty4gfT0dKSnp8u8labDuPtUiYiIqE4EBgbit99+w8KFCzFt2jRcu3YNTZo0QWhoKFavXg0AGDlyJPbv349FixahT58+uHPnDlq0aIHZs2djypQpmnvI9uzZg+TkZCQnJ8PHx0drPRxdSz8ch+w+TG0cEyIiqj9VjYNFda8hjUPGS5ZEREREMmNCRkRERCQzJmREREREMmNCRkRERCQzJmREREREMmNCRkRERCQzJmREREREMmNCRkRERCQzJmREREREMmNCRkRERCQzJmRERERkMAEBAVi5cqXcYZgcJmRERER0X8XFxXKH0KAxISMiIjIkIYDifHleQugdZr9+/fDiiy/ixRdfhIuLCxo1aoT/+7//g/hnGQEBAXjzzTcxbtw4ODs745lnngEAfPfdd2jXrh1sbGwQEBCAZcuWaS3z0qVLeOWVVyBJEiRJ0syr6n3l61u0aBHGjx8PR0dH+Pn5Ye3atbX5JEyKpdwBEBERNSglBcAiL3nW/VoaYG2vd/XPPvsMEyZMwK+//opjx47h2Wefhb+/vyb5evvtt/H666/j//7v/wAAx48fx6hRozBv3jyMHj0aiYmJeP7559GoUSOMGzcOmzZtQocOHfDss89qlqHP+8otW7YMb7zxBl577TV8++23eO6559CnTx+0bt3aMO1jxJiQERERmSlfX1+sWLECkiShVatW+PPPP7FixQpNMvXggw9i+vTpmvpPPvkk+vfvj9dffx0AEBQUhNOnT+Ptt9/GuHHj4ObmBoVCAUdHRzRt2lTzvuXLl1f5vnJRUVF4/vnnAQAzZszAihUrcODAASZkREREVE1WdmU9VXKtuxq6d++udVmxR48eWLZsGVQqFQCgS5cuWvXPnDmDRx55RKusV69eWLlyJVQqFRQKRYXr0fd9ISEhmvmSJKFp06bIyMio1jaZKiZkREREhiRJ1bpsaMzs7bW3QwihlcCVl92Pvu+zsrLSmpYkCWq1Wt9wTRpv6iciIjJThw8f1plu2bJlpT1dbdu2xc8//6xVlpiYiKCgIM17rK2tNT1s1XmfuWNCRkREZKYuX76MqVOn4ty5c9iwYQPee+89vPzyy5XWnzZtGvbt24c33ngD58+fx2effYb3339f6z6zgIAAJCQk4OrVq8jMzNT7feaOlyyJiIjM1NixY3Hnzh107doVCoUCkydPxrPPPltp/c6dO+Obb77BnDlz8MYbb8DT0xMLFizQujF/wYIFmDhxIpo3b46ioiIIIfR6n7mThD4Xf81Ybm4unJ2dkZOTAycnJ7nDISIiI1JYWIiUlBQEBgZCqVTKHU619OvXDx07djTpUfWran9TO3/zkiURERGRzMwiIUtJSUF4eDjatm2L9u3bIz8/X+6QiIiIiDTM4h6ycePG4c0330Tv3r2RnZ0NGxsbuUMiIiKS1YEDB+QOge7S4BOyU6dOwcrKCr179wYAuLm5yRwRERERkTajv2SZkJCAIUOGwMvLC5IkYcuWLTp1Vq1apbmhLzQ0FAcPHtTMu3DhAhwcHDB06FB07twZixYtqsfoiYjIHPD5OHk0pHY3+h6y/Px8dOjQAU899RRGjBihMz8uLg5TpkzBqlWr0KtXL6xZswaRkZE4ffo0/Pz8UFJSgoMHDyIpKQnu7u4YNGgQwsLCMGDAgArXV1RUhKKiIs10bm4uAODZL47B2tbhvvFK963xTz09K+q/PP1qGjo+fZdo+O3Vd3kGjs/A6zVwNdn2A7ni07/9jHs/tZAkKCzuet07XV6m0J5naSHB4q76NlYK2FhawMbSAkrN7woorSw085RWCthaKaCw0LuVqQrlI8sXFBTA1tZW5mjMT0FBAQDdEf5NkdEnZJGRkYiMjKx0/vLlyzFhwgQ8/fTTAICVK1di9+7dWL16NRYvXgwfHx+EhYXB19cXQNkXlyYlJVWakC1evBjz58/XKU9MzoKFzR0DbBERkfzsrRVwVFrBUWn5z8tK89PVzgpNHG3QxNEGjR1sNL872ljqnVSbC4VCARcXF833LdrZ2bGN6oEQAgUFBcjIyICLi0uDGO3f6BOyqhQXF+P48eOYOXOmVnlERAQSExMBAGFhYbh+/Tpu3rwJZ2dnJCQkYOLEiZUuc9asWZg6dapmOjc3F76+vlg0PBh2Do6Vvk/fXlN9O1f1+m4wPZelb0WhR0XDb6c+y9JvaQaNTc+FGXQ7ZVinvssz9GUBY/3c9V+WYWNTqwVUQkCl/uclBFQq7TK1ECitpEwtBEpUAsWlahSVqlBUqkZhSdnPu38vLv33OwHzi1XIL1YhPVe/GAFAaWUBX1c7+LnZwa9R2c+ARvYIauoIL2el2SYiTZs2BQCz+RJsY+Li4qJpf1Nn0glZZmYmVCoVPDw8tMo9PDyQnp4OALC0tMSiRYvQp08fCCEQERGBwYMHV7pMGxubCp/CHNrR2yQGliMiqoxaLVCsUiO/qBS3C8tfJcj952d52c2CYty4XYQbeUXIvF2EG7eLcLuoFIUlalzIyMOFjDydZTvbWqF1U0e08XRCe29ndA10g4+rrVkkaZIkwdPTE+7u7igpKZE7HLNhZWXVIHrGypl0Qlauom+Qv7vsfpc9iYjMgYWFBKWFAkorBRo5VG/4nzvFKlzPLURqdgFSswtwObsAl7IKkJKZj79u5CHnTgl+TcnGrynZmvd4OisRFuCG3i0b48HW7tVep6lRKBQNKkGg+mXSCVnjxo2hUCg0vWHlMjIydHrNiIio5mytFQhobI+AxvY684pKVUjOyMOZa7dxOi0XJy7fxJ9XcnAtpxDbfk/Dtt/TIElAqJ8rBrT1wLBO3vBwMq2vGSKqayadkFlbWyM0NBTx8fEYPny4pjw+Ph6PPPKIjJEREZkPG0sF2nk5o52XMxBaVlZQXIqk1Fs4/HcW9p3NwKm0XBy7dBPHLt3Ekl1n0SeoCR4L9UVEOw9YKYx+BCaiOmf0CVleXh6Sk5M10ykpKUhKSoKbmxv8/PwwdepUREdHo0uXLujRowfWrl2L1NRUTJo0ScaoiYjMm521JXq2aIyeLRpjakQrpN26g31nrmPb72k4evEmDpy7gQPnbsDLWYnxDwRiTFc/ONgY/SmJqM5IwshHVTtw4ADCw8N1ymNiYrB+/XoAZQPDxsbG4tq1awgODsaKFSvQp08fg6zf1L4tnojI2KVk5uPb45cRd/QKMvPKxn10UlriuX4t8FSvACiteB8W1Z6pnb+NPiGTm6l9oEREpqKwRIXNJ67io4S/8XdmPgDA28UWrw5qhaEdvMziCU2qO6Z2/mZCdh+m9oESEZkalVpgy4mreHv3OaTnFgIA+rVqgkXD28PLhaPfU82Y2vmbd1ISEZGsFBYSRoT6YP/0fpg6IAjWCgscOHcDESsS8N3xK3KHR1QvmJAREZFRsLVW4KX+LbHz5QfQ2c8FeUWlmLbxd8za9AcKS1Ryh0dUp5iQERGRUWnh7oiNk3rilYeCIEnAhiOXMWrNIWTcLpQ7NKI6w4SMiIiMjsJCwssPtcTn47vCzd4af1zJwYjVifj7hu7XNhE1BEzIiIjIaPVu2QSbnusJ/0Z2uJx9ByNWJ+J0WjW+EZ3IRDAhIyIioxbQ2B7fPdcTIT7OuFlQgv988ivOX78td1hEBsWEjIiIjF5jBxt8MaEb2ns7Izu/GE989CtS/hm7jKghYEJGREQmwdnWCl9M6Io2nk7IzCvC+PVHcaugWO6wiAyCCRkREZkMFztrfDY+DN4utkjJzMdzX/6G4lK13GER1RoTMiIiMinujkp8HNMF9tYKHPo7Cwt3nJY7JKJaY0JGREQmp42nE94Z0wkA8NmhS9h1Ml3miIhqhwkZERGZpIfaeuDZPs0AAK9++zuu3CyQOSKimmNCRkREJmt6RCt09HVBbmEppm/8HUIIuUMiqhEmZEREZLKsLS3w7phOsLVS4PDf2fj66GW5QyKqESZkRERk0vwa2WH6wFYAgEU7zuBazh2ZIyKqPiZkRERk8sb1DEBHXxfcLirFgu/51CWZHiZkRERk8hQWEt4a0R4WEvDDyXQc/jtL7pCIqoUJGRERNQitmzrhiW5+AIA3tp+GSs0b/Ml0MCEjIqIG45WHguCotMSptFx8e5w3+JPpYEJGREQNRiMHG7zcvyUA4J29F1BUqpI5IiL9MCEjIqIG5T/d/eHhZIO0nEJ8c+yK3OEQ6YUJGRERNShKKwWe79cCALBqfzIKS9hLRsaPCRkRETU4o8N80dRJiWs5hfjmGO8lI+PHhIyIiBocpZUCz4c3BwB8dPBvPnFJRo8JGRERNUiPhfrCxc4Kl7PvYM+pdLnDIaoSEzIiImqQbK0V+E83fwDAxz+nyBwNUdWYkBERUYM1toc/rBUWOH7pJn5LvSl3OESVYkJGREQNlruTEkM7egEAPku8KG8wRFVgQkZERA3a2B5lly1/OJmOm/nFMkdDVDEmZERE1KC193ZGOy8nFJeqsenEVbnDIaoQEzIiImrQJEnCmK5lXzq+4UgqhOAQGGR8mJAREVGD90hHL9haKZCckYfjl3hzPxkfJmRERNTgOSmtMKSDJwAg7ihH7ifjw4SMiIjMwojOPgCAXSfT+f2WZHSYkBERkVkIC3CDl7MSt4tK8ePZDLnDIdLChIyIiMyChYWEIf+MSbaFT1uSkWFCRkREZmNYR28AwIFzN5BTUCJzNET/YkJGRERmo42nE1p5OKJYpcbOk9fkDodIw2wSsoKCAvj7+2P69Olyh0JERDJ6pFPZZcvtf6TJHAnRv8wmIVu4cCG6desmdxhERCSzqOCy4S8O/53Nr1Iio2EWCdmFCxdw9uxZREVFyR0KERHJLKCxPVo3dYRKLbD3zHW5wyECYAIJWUJCAoYMGQIvLy9IkoQtW7bo1Fm1ahUCAwOhVCoRGhqKgwcPas2fPn06Fi9eXE8RExGRsRsU3BQAsPtUusyREJUx+oQsPz8fHTp0wPvvv1/h/Li4OEyZMgWzZ8/GiRMn0Lt3b0RGRiI1NRUAsHXrVgQFBSEoKEiv9RUVFSE3N1frRUREDUvkP5ctEy5kIq+oVOZoiABLuQO4n8jISERGRlY6f/ny5ZgwYQKefvppAMDKlSuxe/durF69GosXL8bhw4fx9ddfY+PGjcjLy0NJSQmcnJwwZ86cCpe3ePFizJ8/v062hYiIjEOQhwMCG9sjJTMf+89mYEgHL7lDIjNn9D1kVSkuLsbx48cRERGhVR4REYHExEQAZQnW5cuXcfHiRSxduhTPPPNMpckYAMyaNQs5OTma1+XL/M4zIqKGRpIkDGxXdtlyFy9bkhEw6YQsMzMTKpUKHh4eWuUeHh5IT6/ZH5iNjQ2cnJy0XkRE1PBE/nMf2f6zGfxuS5Kd0V+y1IckSVrTQgidMgAYN25cPUVERETGLsTHGZ7OSlzLKcQvyZno38bj/m8iqiMm3UPWuHFjKBQKnd6wjIwMnV4zIiKiu0mShIi2ZecKPm1JcjPphMza2hqhoaGIj4/XKo+Pj0fPnj1lioqIiExF+X1ke89koFSlljkaMmdGf8kyLy8PycnJmumUlBQkJSXBzc0Nfn5+mDp1KqKjo9GlSxf06NEDa9euRWpqKiZNmiRj1EREZAq6BrrBxc4K2fnFOHbpJro3ayR3SGSmjD4hO3bsGMLDwzXTU6dOBQDExMRg/fr1GD16NLKysrBgwQJcu3YNwcHB2LlzJ/z9/eUKmYiITISlwgL9W3vgu9+uYPepdCZkJBtJCCHkDsKY5ebmwtnZGTk5OXzikoioAdpzKh3PfnEc3i62+HlGeIUPhZHpMbXzt0nfQ0ZERFRbfYKawNZKgau37uBUGr+dheTBhIyIiMya0kqBvkFNAPBpS5IPEzIiIjJ7Ee04/AXJiwkZERGZvf6tPWBpIeH89TykZObLHQ6ZISZkRERk9pztrDRPWLKXjOTAhIyIiAjAQF62JBkxISMiIgIwoG3ZqP0nUm/hem6hzNGQuWFCRkREBKCpsxIdfV0AAHtOX5c3GDI7TMiIiIj+Uf7dlt8npckcCZkbJmRERET/GN7JGwoLCUcuZuPC9dtyh0NmhAkZERHRP5o6K9G/tTsA4KtfU2WOhswJEzIiIqK7PNHNDwDw3fEruFVQLHM0ZC6YkBEREd2lT8smaN3UEbeLSvHRwb/lDofMBBMyIiKiu1hYSJg6IAgA8PHBFPx1I0/miMgcMCEjIiK6x4C2HujdsjGKStWY/L8TyC0skTskauCYkBEREd1DkiTEjgyBm701Tl/LxWOrD+HYxWwIIeQOjRooS7kDICIiMkaezrb4YkJXxHx6BOeu38bIDw/By1mJ1p5OaOxgDTtrSygsJM3LQpI7YrpbYb5pXWpmQkZERFSJdl7O+OHlPnh791lsSUpDWk4h0nL4tUqmQF1UIHcI1SIJ9r9WKTc3F87OzsjJyYGTk5Pc4RARkUzyi0rx++VbuJRdgKy8IhSWqFGqFlALgVKVgABPp8aksCAPb43pbjLnbyZk98GEjIiIyPSY2vmbN/UTERERyYwJGREREZHMmJARERERyYwJGREREZHMajzshVqtRnJyMjIyMqBWq7Xm9enTp9aBEREREZmLGiVkhw8fxhNPPIFLly7pjFosSRJUKpVBgiMiIiIyBzVKyCZNmoQuXbpgx44d8PT0hCRxeGIiIiKimqpRQnbhwgV8++23aNGihaHjISIiIjI7Nbqpv1u3bkhOTjZ0LERERERmqUY9ZJMnT8a0adOQnp6O9u3bw8rKSmt+SEiIQYIjIiIiMgc1+uokCwvdjjVJkiCEaHA39ZvaVy8QERGR6Z2/a9RDlpKSYug4iIiIiMxWjRIyf39/Q8dBREREZLZqPDDsX3/9hZUrV+LMmTOQJAlt2rTByy+/jObNmxsyPiIiIqIGr0ZPWe7evRtt27bFkSNHEBISguDgYPz6669o164d4uPjDR0jERERUYNWo5v6O3XqhIEDB+Ktt97SKp85cyb27NmD3377zWABys3UbgokIiIi0zt/16iH7MyZM5gwYYJO+fjx43H69OlaB0VERERkTmqUkDVp0gRJSUk65UlJSXB3d69tTERERERmpUY39T/zzDN49tln8ffff6Nnz56QJAk///wzlixZgmnTphk6RiIiIqIGrUb3kAkhsHLlSixbtgxpaWkAAC8vL/z3v//FSy+9ZFRfNn758mVER0cjIyMDlpaWeP311/HYY4/p/X5TuwZNREREpnf+rlFCdrfbt28DABwdHQ0SkKFdu3YN169fR8eOHZGRkYHOnTvj3LlzsLe31+v9pvaBEhERkemdv2s8Dlk5Y03Eynl6esLT0xMA4O7uDjc3N2RnZ+udkBERERHVNb1v6u/cuTNu3rwJoGzYi86dO1f6MqSEhAQMGTIEXl5ekCQJW7Zs0amzatUqBAYGQqlUIjQ0FAcPHqxwWceOHYNarYavr69BYyQiIiKqDb17yB555BHY2Nhofq+v+8Ty8/PRoUMHPPXUUxgxYoTO/Li4OEyZMgWrVq1Cr169sGbNGkRGRuL06dPw8/PT1MvKysLYsWPx8ccfV7m+oqIiFBUVaaZzc3MNtzFEREREFaj1PWT1SZIkbN68GcOGDdOUdevWDZ07d8bq1as1ZW3atMGwYcOwePFiAGVJ1oABA/DMM88gOjq6ynXMmzcP8+fP1yk3lWvQREREZHr3kNVoHLJmzZohKytLp/zWrVto1qxZrYPSV3FxMY4fP46IiAit8oiICCQmJgIoeyJ03LhxePDBB++bjAHArFmzkJOTo3ldvny5TmInIiIiKlejm/ovXrwIlUqlU15UVIQrV67UOih9ZWZmQqVSwcPDQ6vcw8MD6enpAIBffvkFcXFxCAkJ0dx/9sUXX6B9+/YVLtPGxkZzaZaIiIioPlQrIdu2bZvm9927d8PZ2VkzrVKpsG/fPgQGBhouOj3dez+bEEJT9sADD0CtVtd7TERERET6qlZCVn7vliRJiImJ0ZpnZWWFgIAALFu2zGDB3U/jxo2hUCg0vWHlMjIydHrNiIiIiIxVte4hU6vVUKvV8PPzQ0ZGhmZarVajqKgI586dw+DBg+sqVh3W1tYIDQ1FfHy8Vnl8fDx69uxZb3EQERER1UaN7iFLSUkxdByVysvLQ3Jysta6k5KS4ObmBj8/P0ydOhXR0dHo0qULevTogbVr1yI1NRWTJk2qtxiJiIiIaqPGI/Xn5+fjp59+QmpqKoqLi7XmvfTSS7UOrNyxY8cQHh6umZ46dSoAICYmBuvXr8fo0aORlZWFBQsW4Nq1awgODsbOnTvh7+9vsBiIiIiI6lKNxiE7ceIEoqKiUFBQgPz8fLi5uSEzMxN2dnZwd3fH33//XRexysLUxjEhIiIi0zt/12gcsldeeQVDhgxBdnY2bG1tcfjwYVy6dAmhoaFYunSpoWMkIiIiatBqlJAlJSVh2rRpUCgUUCgUKCoqgq+vL2JjY/Haa68ZOkYiIiKiBq1GCZmVlZVmnC8PDw+kpqYCAJydnTW/ExEREZF+anRTf6dOnXDs2DEEBQUhPDwcc+bMQWZmZpUj4BMRERFRxWrUQ7Zo0SJ4enoCAN544w00atQIzz33HDIyMrB27VqDBkhERETU0FW7h0wIgSZNmqBdu3YAgCZNmmDnzp0GD4yIiIjIXFS7h0wIgZYtW9brl4gTERERNWTVTsgsLCzQsmVLZGVl1UU8RERERGanRveQxcbG4r///S9Onjxp6HiIiIiIzE6NRup3dXVFQUEBSktLYW1tDVtbW6352dnZBgtQbqY20i8RERGZ3vm7RsNerFixQjMOGRERERHVTo0SsnHjxhk4DCIiIiLzVaN7yBQKBTIyMnTKs7KyoFAoah0UERERkTmpUUJW2W1nRUVFsLa2rlVAREREROamWpcs3333XQCAJEn4+OOP4eDgoJmnUqmQkJCA1q1bGzZCIiIiogauWgnZihUrAJT1kH344Ydalyetra0REBCADz/80LAREhERETVw1UrIUlJSAADh4eHYtGkTXF1d6yQoIiIiInNSo6cs9+/fb+g4iIiIiMxWjRIylUqF9evXY9++fcjIyIBardaa/+OPPxokOCIiIiJzUKOE7OWXX8b69evx8MMPIzg4mIPEEhEREdVCjRKyr7/+Gt988w2ioqIMHQ8RERGR2anROGTW1tZo0aKFoWMhIiIiMks1SsimTZuGd955p9IBYomIiIhIfzW6ZPnzzz9j//79+OGHH9CuXTtYWVlpzd+0aZNBgiMiIiIyBzVKyFxcXDB8+HBDx0JERERklmqUkK1bt87QcRARERGZrRrdQwYApaWl2Lt3L9asWYPbt28DANLS0pCXl2ew4IiIiIjMQY16yC5duoRBgwYhNTUVRUVFGDBgABwdHREbG4vCwkJ+nyURERFRNdSoh+zll19Gly5dcPPmTdja2mrKhw8fjn379hksOCIiIiJzUOOnLH/55RdYW1trlfv7++Pq1asGCYyIiIjIXNSoh0ytVkOlUumUX7lyBY6OjrUOioiIiMic1CghGzBgAFauXKmZliQJeXl5mDt3Lr9OiYiIiKiaJFGD4fbT0tIQHh4OhUKBCxcuoEuXLrhw4QIaN26MhIQEuLu710WsssjNzYWzszNycnLg5OQkdzhERESkB1M7f9foHjIvLy8kJSXh66+/xvHjx6FWqzFhwgQ8+eSTWjf5ExEREdH91aiHzJyYWoZNREREpnf+rtE9ZIsXL8ann36qU/7pp59iyZIltQ6KiIiIyJzUKCFbs2YNWrdurVPerl07DgpLREREVE01SsjS09Ph6empU96kSRNcu3at1kERERERmZMaJWS+vr745ZdfdMp/+eUXeHl51TooQ9u+fTtatWqFli1b4uOPP5Y7HCIiIiItNXrK8umnn8aUKVNQUlKCBx98EACwb98+vPrqq5g2bZpBA6yt0tJSTJ06Ffv374eTkxM6d+6MRx99FG5ubnKHRkRERASghgnZq6++iuzsbDz//PMoLi4GACiVSsyYMQOzZs0yaIC1deTIEbRr1w7e3t4AgKioKOzevRuPP/64zJERERERlanRJUtJkrBkyRLcuHEDhw8fxu+//47s7GzMmTPH0PEhISEBQ4YMgZeXFyRJwpYtW3TqrFq1CoGBgVAqlQgNDcXBgwc189LS0jTJGAD4+Pjw+zaJiIjIqNQoISvn4OCAsLAwBAcHw8bGxlAxacnPz0eHDh3w/vvvVzg/Li4OU6ZMwezZs3HixAn07t0bkZGRSE1NBQBUNMyaJEl1EisRERFRTdTokmV+fj7eeust7Nu3DxkZGVCr1Vrz//77b4MEBwCRkZGIjIysdP7y5csxYcIEPP300wCAlStXYvfu3Vi9ejUWL14Mb29vrR6xK1euoFu3bpUur6ioCEVFRZrp3NxcA2wFERERUeVqfFP/Tz/9hOjoaHh6esrW41RcXIzjx49j5syZWuURERFITEwEAHTt2hUnT57E1atX4eTkhJ07d1Z5aXXx4sWYP39+ncZNREREdLcaJWQ//PADduzYgV69ehk6nmrJzMyESqWCh4eHVrmHhwfS09MBAJaWlli2bBnCw8OhVqvx6quvolGjRpUuc9asWZg6dapmOjc3F76+vnWzAURERESoYULm6upqVMNG3NtDJ4TQKhs6dCiGDh2q17JsbGzq7H44IiIioorU6Kb+N954A3PmzEFBQYGh46mWxo0bQ6FQaHrDymVkZOj0mhEREREZqxr1kC1btgx//fUXPDw8EBAQACsrK635v/32m0GCux9ra2uEhoYiPj4ew4cP15THx8fjkUceqZcYiIiIiGqrRgnZsGHDDBxG5fLy8pCcnKyZTklJQVJSEtzc3ODn54epU6ciOjoaXbp0QY8ePbB27VqkpqZi0qRJ9RYjERERUW1IoqKBuozIgQMHEB4erlMeExOD9evXAygbGDY2NhbXrl1DcHAwVqxYgT59+hhk/bm5uXB2dkZOTg6cnJwMskwiIiKqW6Z2/q5VQnb8+HGcOXMGkiShbdu26NSpkyFjMwqm9oESERGR6Z2/a3TJMiMjA2PGjMGBAwfg4uICIQRycnIQHh6Or7/+Gk2aNDF0nEREREQNVo2espw8eTJyc3Nx6tQpZGdn4+bNmzh58iRyc3Px0ksvGTpGIiIiogatRpcsnZ2dsXfvXoSFhWmVHzlyBBEREbh165ah4pOdqXV5EhERkemdv2vUQ6ZWq3WGugAAKysrne+1JCIiIqKq1Sghe/DBB/Hyyy8jLS1NU3b16lW88sor6N+/v8GCIyIiIjIHNUrI3n//fdy+fRsBAQFo3rw5WrRogcDAQNy+fRvvvfeeoWMkIiIiatBq9JSlr68vfvvtN8THx+Ps2bMQQqBt27Z46KGHDB0fERERUYNXrR6yH3/8EW3btkVubi4AYMCAAZg8eTJeeuklhIWFoV27djh48GCdBEpERETUUFUrIVu5ciWeeeaZCp9WcHZ2xsSJE7F8+XKDBUdERERkDqqVkP3+++8YNGhQpfMjIiJw/PjxWgdFREREZE6qlZBdv369wuEuyllaWuLGjRu1DoqIiIjInFQrIfP29saff/5Z6fw//vgDnp6etQ6KiIiIyJxUKyGLiorCnDlzUFhYqDPvzp07mDt3LgYPHmyw4IiIiIjMQbW+Oun69evo3LkzFAoFXnzxRbRq1QqSJOHMmTP44IMPoFKp8Ntvv8HDw6MuY65XpvbVC0RERGR65+9qjUPm4eGBxMREPPfcc5g1axbKczlJkjBw4ECsWrWqQSVjRERERPWh2gPD+vv7Y+fOnbh58yaSk5MhhEDLli3h6upaF/ERERERNXg1GqkfAFxdXREWFmbIWIiIiIjMUo0TMrOzMgRQ3u8ZCEm/ZUl61pNjecYcm6GXp++ijHpbjTk2Qy/PmGPTc3mSBFhYAhYKQFL887tF2U/NtOKe+fdOWwKW1oClLWBpA1gqAStl2U+tlw1gZQconQAbp7KflspqbA8R1ScmZPq6kw2oeSAjIhNmYaWdoNk1AuzdAQd3wMHjn1cTwKEp4OIHWNvJHTGR2WBCpq+nfwQcHaqooOfDqno/1CrD8ow5NkMvT+9ni415W405NkMvz5hj03N5QvzzUgHqUkD9z0+hvuv3u+epKp5WlQCqIqC0CCi5U/aztPxnIVBSWPaztAgoKQAKc4Gi3LIY1SVAQVbZSx8OTQG3QMA1AHANBNzbAE2DAZeAsp49IjIYJmT6ahIEmMBjs0REOtRqoDivLDErT9AKc8oSs7yMf17Xgfx/fs+9BhTlAHnpZa/UQ9rLs3YAPNoBXp0B/x6AX4+yXjYiqrFqjUNmjkxtHBMiIoMoyAZupgA3LwLZKUD238D1k0DG2bIeuns1agE07w+0igT8e5Xd50YkI1M7fzMhuw9T+0CJiOqUqhTIugCk/wlc/hW4dAjIOKVdx8YJaPEQ0GFMWZKm4MUYqn+mdv5mQnYfpvaBEhHVuzs3gYs/A+d3Aed3A/k3/p3n4FGWmHV9FnD2kS9GMjumdv5mQnYfpvaBEhHJSq0Grh4HTn4H/PnNvw8QSAqg3XCg18uAZ4i8MZJZMLXzNxOy+zC1D5SIyGiUFgMX9gC/fghcPPhvefBI4MHZgFsz+WKjBs/Uzt9MyO7D1D5QIiKjdO134Jd3y3rOIMoGuO3+PNBvFsc7ozphaudvDiRDRER1z7MDMPITYGJC2Q3/6lIg8V1gdQ/gr/1yR0ckOyZkRERUfzxDgP98BzzxDeDkUzasxhfDgN2zyy5xEpkpJmRERFT/ggYCLxwGwp4pmz70PrBuEHDrsrxxEcmECRkREcnDxhF4eCkw+itA6Vz2dObH/YG0E3JHRlTvmJAREZG82gwGJh4E3NuVfYXTuqiy8cyIzAgTMiIikp+rPzB+F9D8wbIvRf/6SeDsTrmjIqo3TMiIiMg4KJ3KbvYPHgGoS4BvxjIpI7PBhIyIiIyHwgoYvvbfpGxjDHApUe6oiOocEzIiIjIuCsuypKzNEEBVDGx4HMi8IHdURHWKCRkRERkfhSXw6EeATxhQeAv4aiRQkC13VER1hgkZEREZJytbYMwGwMW/bADZLc+VfXk5UQPEhIyIiIyXQxNg9JeAwgY4v6vs65aIGqAGn5BdvnwZ/fr1Q9u2bRESEoKNGzfKHRIREVWHZwgQFVv2+74FwJVj8sZDVAcafEJmaWmJlStX4vTp09i7dy9eeeUV5Ofnyx0WERFVR+cYIHgkIFTAlueBkkK5IyIyqAafkHl6eqJjx44AAHd3d7i5uSE7mzeGEhGZFEkCot4G7N2BzHPAT2/JHRGRQcmekCUkJGDIkCHw8vKCJEnYsmWLTp1Vq1YhMDAQSqUSoaGhOHjwYI3WdezYMajVavj6+tYyaiIiqnd2bsCQlWW///IOkJYkZzREBiV7Qpafn48OHTrg/fffr3B+XFwcpkyZgtmzZ+PEiRPo3bs3IiMjkZqaqqkTGhqK4OBgnVdaWpqmTlZWFsaOHYu1a9fW+TYREVEdaf0w0O5RQKiBH2YAQsgdEZFBSEIYz94sSRI2b96MYcOGacq6deuGzp07Y/Xq1ZqyNm3aYNiwYVi8eLFeyy0qKsKAAQPwzDPPIDo6+r51i4qKNNO5ubnw9fVFTk4OnJycqrdBRERkeDlXgfe7lH3n5aMfAyGPyR0RGaHc3Fw4OzubzPlb9h6yqhQXF+P48eOIiIjQKo+IiEBion5fpSGEwLhx4/Dggw/eNxkDgMWLF8PZ2Vnz4uVNIiIj4+wN9J5a9nv860BRnrzxEBmAUSdkmZmZUKlU8PDw0Cr38PBAenq6Xsv45ZdfEBcXhy1btqBjx47o2LEj/vzzz0rrz5o1Czk5OZrX5cuXa7UNRERUB3pMLhsw9vY14NcP5Y6GqNYs5Q5AH5IkaU0LIXTKKvPAAw9AXY2RnW1sbGBjY1Ot+IiIqJ5ZKYEHXwc2PV02WGzY04Cti9xREdWYUfeQNW7cGAqFQqc3LCMjQ6fXjIiIzEzwo0CTNkBhDnDoA7mjIaoVo07IrK2tERoaivj4eK3y+Ph49OzZU6aoiIjIKFgogPDXyn4/vArIz5I3HqJakP2SZV5eHpKTkzXTKSkpSEpKgpubG/z8/DB16lRER0ejS5cu6NGjB9auXYvU1FRMmjRJxqiJiMgotBkCNA0B0v8Ajn4M9Jshd0RENSJ7Qnbs2DGEh4drpqdOLXtyJiYmBuvXr8fo0aORlZWFBQsW4Nq1awgODsbOnTvh7+8vV8hERGQsJAno9TLw3QTgyFqg10uAla3cURFVm1GNQ2aMTG0cEyIis6MqBd7rBNxKBR5eDoRNkDsiMgKmdv426nvIiIiI7kthCXR/oez3Q+8DapW88RDVABMyIiIyfZ3+AyhdgOy/gQt75I6GqNqYkBERkemzcShLygDg2Dp5YyGqASZkRETUMIQ+Vfbzwp6y+8mITAgTMiIiahgatwAC+wIQwPHP5I6GqFqYkBERUcPRZXzZzxNfAKoSeWMhqgYmZERE1HC0fhiwdwfyrvPmfjIpTMiIiKjhUFgBIaPKfv8jTt5YiKqBCRkRETUsIaPLfp7bBdy5JWsoRPpiQkZERA1L0/ZAkzaAqgg4vVXuaIj0woSMiIgaFkkCOvzTS/bHN/LGQqQnJmRERNTwtH8MgARc+pljkpFJYEJGREQNj7MPEPBA2e+ntsgaCpE+mJAREVHD1PaRsp+8j4xMABMyIiJqmNoMASABV48BOVfljoaoSkzIiIioYXJsCvh1L/v9zPfyxkJ0H0zIiIio4WoztOwnL1uSkWNCRkREDVebIWU/Uw8Bt6/LGwtRFZiQERFRw+XiC3iHAhDAWV62JOPFhIyIiBq28qcteR8ZGTEmZERE1LC1Hlz2M+UgUJAtbyxElWBCRkREDVuj5oB7O0CogPO75Y6GqEJMyIiIqOErv7mfly3JSDEhIyKihq/NP5ct/9oHFOfLGwtRBZiQERFRw+cRDLgGAKWFQPJeuaMh0sGEjIiIGj5J+vfmfl62JCPEhIyIiMxD+aj953cDpcXyxkJ0DyZkRERkHnzCAAcPoCgXSEmQOxoiLUzIiIjIPFhYAK0fLvudo/aTkWFCRkRE5qP8PrKzOwC1St5YiO7ChIyIiMxHQG9A6Qzk3wAu/yp3NEQaTMiIiMh8WFoDQYPKfj+zXd5YiO7ChIyIiMzL3aP2CyFvLET/YEJGRETmpXl/wNIWyEkF0v+QOxoiAEzIiIjI3FjbAS36l/3OQWLJSDAhIyIi81N+2fL0Nl62JKPAhIyIiMxP0CDAUglknuPTlmQUmJAREZH5sXUB2o8s+/3XNbKGQgQwISMiInPV9dmyn2e2AbdS5Y2FzJ7ZJGQFBQXw9/fH9OnT5Q6FiIiMgWeHsoFi1aXAjwvljobMnNkkZAsXLkS3bt3kDoOIiIzJgAVlP//4Grj4s7yxkFkzi4TswoULOHv2LKKiouQOhYiIjIl3Z6BTdNnv344HMpPljYfMluwJWUJCAoYMGQIvLy9IkoQtW7bo1Fm1ahUCAwOhVCoRGhqKgwcPVmsd06dPx+LFiw0UMRERNSiRSwD3tkDedeDj/sDhD4H8TLmjIjNjKXcA+fn56NChA5566imMGDFCZ35cXBymTJmCVatWoVevXlizZg0iIyNx+vRp+Pn5AQBCQ0NRVFSk8949e/bg6NGjCAoKQlBQEBITE+8bT1FRkdaycnNza7F1RERk9KztgbHbgP+NAtJ+A3bNKHs5NAXsGgE2joCFJSBJZS9IgGTx7+9knO6UyB1BtUhCGM+IeJIkYfPmzRg2bJimrFu3bujcuTNWr16tKWvTpg2GDRumV6/XrFmz8OWXX0KhUCAvLw8lJSWYNm0a5syZU2H9efPmYf78+TrlOTk5cHJyqv5GERGRaVCVAsfXAcc/A67/KXc0VEu5RQLOb902mfO3USdkxcXFsLOzw8aNGzF8+HBNvZdffhlJSUn46aefqrX89evX4+TJk1i6dGmldSrqIfP19TWZD5SIiAygMAfI+gsovAUU5gJC9e+I/kL9z+9Gc/qkCuTmFcD5gQkmc/6W/ZJlVTIzM6FSqeDh4aFV7uHhgfT09DpZp42NDWxsbOpk2UREZCKUzmU3/JPpys0FMEHuKPRm1AlZOUnSvkYvhNAp08e4ceMMFBERERGR4cj+lGVVGjduDIVCodMblpGRodNrRkRERGSqjDohs7a2RmhoKOLj47XK4+Pj0bNnT5miIiIiIjIs2S9Z5uXlITn534H4UlJSkJSUBDc3N/j5+WHq1KmIjo5Gly5d0KNHD6xduxapqamYNGmSjFETERERGY7sCdmxY8cQHh6umZ46dSoAICYmBuvXr8fo0aORlZWFBQsW4Nq1awgODsbOnTvh7+8vV8hEREREBmVUw14Yo9zcXDg7O5vMY7NERERkeudvo76HjIiIiMgcMCEjIiIikhkTMiIiIiKZMSEjIiIikhkTMiIiIiKZMSEjIiIikhkTMiIiIiKZMSEjIiIikhkTMiIiIiKZMSEjIiIikhkTMiIiIiKZMSEjIiIikhkTMiIiIiKZMSEjIiIikhkTMiIiIiKZMSEjIiIikhkTMiIiIiKZMSEjIiIikhkTMiIiIiKZMSEjIiIikhkTMiIiIiKZMSEjIiIikhkTMiIiIiKZMSEjIiIikhkTMiIiIiKZMSEjIiIikhkTMiIiIiKZMSEjIiIikhkTMiIiIiKZMSEjIiIikhkTMiIiIiKZMSEjIiIikhkTMiIiIiKZMSEjIiIikhkTMiIiIiKZMSEjIiIikhkTMiIiIiKZMSEjIiIikhkTMiIiIiKZmUVClpKSgvDwcLRt2xbt27dHfn6+3CERERERaVjKHUB9GDduHN5880307t0b2dnZsLGxkTskIiIiIo0Gn5CdOnUKVlZW6N27NwDAzc1N5oiIiIiItMl+yTIhIQFDhgyBl5cXJEnCli1bdOqsWrUKgYGBUCqVCA0NxcGDB/Ve/oULF+Dg4IChQ4eic+fOWLRokQGjJyIiIqo92XvI8vPz0aFDBzz11FMYMWKEzvy4uDhMmTIFq1atQq9evbBmzRpERkbi9OnT8PPzAwCEhoaiqKhI57179uxBSUkJDh48iKSkJLi7u2PQoEEICwvDgAEDKoynqKhIa1k5OTkAgNzcXENsLhEREdWD8vO2EELmSPQkjAgAsXnzZq2yrl27ikmTJmmVtW7dWsycOVOvZSYmJoqBAwdqpmNjY0VsbGyl9efOnSsA8MUXX3zxxRdfDeD1119/6Z+IyEj2HrKqFBcX4/jx45g5c6ZWeUREBBITE/VaRlhYGK5fv46bN2/C2dkZCQkJmDhxYqX1Z82ahalTp2qmb926BX9/f6SmpsLZ2blmG9JA5ebmwtfXF5cvX4aTk5Pc4RgVtk3F2C6VY9tUjm1TObZN5XJycuDn52cy944bdUKWmZkJlUoFDw8PrXIPDw+kp6frtQxLS0ssWrQIffr0gRACERERGDx4cKX1bWxsKnwK09nZmTt7JZycnNg2lWDbVIztUjm2TeXYNpVj21TOwkL22+X1YtQJWTlJkrSmhRA6ZVWJjIxEZGSkocMiIiIiMgijThsbN24MhUKh0xuWkZGh02tGREREZKqMOiGztrZGaGgo4uPjtcrj4+PRs2fPeonBxsYGc+fO5WCyFWDbVI5tUzG2S+XYNpVj21SObVM5U2sbSQh5nwfNy8tDcnIyAKBTp05Yvnw5wsPD4ebmBj8/P8TFxSE6OhoffvghevTogbVr1+Kjjz7CqVOn4O/vL2foRERERAYhe0J24MABhIeH65THxMRg/fr1AMoGho2NjcW1a9cQHByMFStWoE+fPvUcKREREVHdkD0hIyIiIjJ3Rn0PGREREZE5YEJGREREJDMmZEREREQyY0JWS8OHD4erqytGjhypVX758mX069cPbdu2RUhICDZu3ChThPKprG0AYPv27WjVqhVatmyJjz/+WIbojMeKFSvQrl07tG3bFi+99JLpfBFuPUhJSUF4eDjatm2L9u3bIz8/X+6QjEZBQQH8/f0xffp0uUMxGjzuauNxtmJGu5/I9i2aDcSPP/4otm3bJkaMGKFVnpaWJk6cOCGEEOL69evC29tb5OXlyRChfCprm5KSEtGyZUtx5coVkZubK1q0aCGysrJkilJeGRkZolmzZuLOnTuitLRU9OzZUyQmJsodltHo06ePSEhIEEIIkZWVJUpKSmSOyHi89tpr4rHHHhPTpk2TOxSjwePuv3icrZyx7ifsIaul8PBwODo66pR7enqiY8eOAAB3d3e4ubkhOzu7nqOTV2Vtc+TIEbRr1w7e3t5wdHREVFQUdu/eLUOExqG0tBSFhYUoKSlBSUkJ3N3d5Q7JKJw6dQpWVlbo3bs3AMDNzQ2WlibxbW917sKFCzh79iyioqLkDsWo8Lj7Lx5nK2es+0mDTsgSEhIwZMgQeHl5QZIkbNmyRafOqlWrEBgYCKVSidDQUBw8eNDgcRw7dgxqtRq+vr4GX3ZNydk2aWlp8Pb21kz7+Pjg6tWrBlm2odV1OzVp0gTTp0+Hn58fvLy88NBDD6F58+YG3IK6U9dtc+HCBTg4OGDo0KHo3LkzFi1aZMDo6059/G1Nnz4dixcvNlDE9ac+jzvGeNytjtq2lSkdZ6vLkPuRMe0nDTohy8/PR4cOHfD+++9XOD8uLg5TpkzB7NmzceLECfTu3RuRkZFITU3V1AkNDUVwcLDOKy0tTa8YsrKyMHbsWKxdu9Yg22QocraNqOAeqep8WXx9qut2unnzJrZv346LFy/i6tWrSExMREJCQn1tXq3UdduUlJTg4MGD+OCDD3Do0CHEx8frfI2aMarrdtm6dSuCgoIQFBRUX5tkMPV13DHW42511LatTOk4W12G2I8AI9xP5L5mWl8AiM2bN2uVde3aVUyaNEmrrHXr1mLmzJnVWvb+/ft17pMSQojCwkLRu3dv8fnnn1c73vpU323zyy+/iGHDhmmmX3rpJfHVV19VL2gZ1EU7ffPNN+L555/XTMfGxoolS5bUOtb6Vhdtk5iYKAYOHKiZjo2NFbGxsbWOtT7VRbvMnDlT+Pj4CH9/f9GoUSPh5OQk5s+fb6iQ601dHXdM5bhbHTVpK1M9zlZXTfcjY9xPGnQPWVWKi4tx/PhxREREaJVHREQgMTGx1ssXQmDcuHF48MEHER0dXevl1ae6bpuuXbvi5MmTuHr1Km7fvo2dO3di4MCBtV5ufTNEO/n6+iIxMRGFhYVQqVQ4cOAAWrVqVRfh1itDtE1YWBiuX7+OmzdvQq1WIyEhAW3atKmLcOuNIdpl8eLFuHz5Mi5evIilS5fimWeewZw5c+oi3HpliLYx5eNudejTVg3lOFtd+rSNse4nZnuHbGZmJlQqFTw8PLTKPTw8kJ6ervdyBg4ciN9++w35+fnw8fHB5s2bERYWhl9++QVxcXEICQnRXN/+4osv0L59e0NuRp2o67axtLTEsmXLEB4eDrVajVdffRWNGjUy9GbUOUO0U/fu3REVFYVOnTrBwsIC/fv3x9ChQ+si3HpliLaxtLTEokWL0KdPHwghEBERgcGDB9dFuPXGUH9bDZEh2saUj7vVoU9bNZTjbHXp0zbGup+YbUJW7t5r6kKIal1nr+yplQceeABqtbpWscmtrtoGAIYOHdogEg+g9u20cOFCLFy40NBhGYXatk1kZCQiIyMNHZbsatsu5caNG2egiIxHbdqmIRx3q+N+bdWQjrPVVVXbGOt+YraXLBs3bgyFQqHzn1dGRoZOZm1u2Db6YTtVjm1TMbZL5dg2+mNbVc6U28ZsEzJra2uEhobqPLUVHx+Pnj17yhSVcWDb6IftVDm2TcXYLpVj2+iPbVU5U26bBn3JMi8vD8nJyZrplJQUJCUlwc3NDX5+fpg6dSqio6PRpUsX9OjRA2vXrkVqaiomTZokY9T1g22jH7ZT5dg2FWO7VI5toz+2VeUabNvI83Bn/di/f78AoPOKiYnR1Pnggw+Ev7+/sLa2Fp07dxY//fSTfAHXI7aNfthOlWPbVIztUjm2jf7YVpVrqG0jCcFvMiYiIiKSk9neQ0ZERERkLJiQEREREcmMCRkRERGRzJiQEREREcmMCRkRERGRzJiQEREREcmMCRkRERGRzJiQEREREcmMCRkRERGRzJiQEZHs5s2bh44dO9b7eg8cOABJknDr1q16XzcR0d2YkBFRnZIkqcrXuHHjMH36dOzbt6/eY+vZsyeuXbsGZ2fnWi3nu+++Q7du3eDs7AxHR0e0a9cO06ZNM1CURGQOLOUOgIgatmvXrml+j4uLw5w5c3Du3DlNma2tLRwcHODg4FDvsVlbW6Np06a1WsbevXsxZswYLFq0CEOHDoUkSTh9+rQsCSYRmS72kBFRnWratKnm5ezsDEmSdMruvWQ5btw4DBs2DIsWLYKHhwdcXFwwf/58lJaW4r///S/c3Nzg4+ODTz/9VGtdV69exejRo+Hq6opGjRrhkUcewcWLFyuN7d5LluvXr4eLiwt2796NNm3awMHBAYMGDdJKKu+1fft2PPDAA/jvf/+LVq1aISgoCMOGDcN7772nVe/7779HaGgolEolmjVrptmecrdu3cKzzz4LDw8PKJVKBAcHY/v27fo3NBGZNCZkRGSUfvzxR6SlpSEhIQHLly/HvHnzMHjwYLi6uuLXX3/FpEmTMGnSJFy+fBkAUFBQgPDwcDg4OCAhIQE///yzJqEqLi7We70FBQVYunQpvvjiCyQkJCA1NRXTp0+vtH7Tpk1x6tQpnDx5stI6u3fvxn/+8x+89NJLOH36NNasWYP169dj4cKFAAC1Wo3IyEgkJibiyy+/xOnTp/HWW29BoVDoHTcRmThBRFRP1q1bJ5ydnXXK586dKzp06KCZjomJEf7+/kKlUmnKWrVqJXr37q2ZLi0tFfb29mLDhg1CCCE++eQT0apVK6FWqzV1ioqKhK2trdi9e3eF8ezfv18AEDdv3tTEB0AkJydr6nzwwQfCw8Oj0m3Ky8sTUVFRAoDw9/cXo0ePFp988okoLCzU1Ondu7dYtGiR1vu++OIL4enpKYQQYvfu3cLCwkKcO3eu0vUQUcPGe8iIyCi1a9cOFhb/duJ7eHggODhYM61QKNCoUSNkZGQAAI4fP47k5GQ4OjpqLaewsBB//fWX3uu1s7ND8+bNNdOenp6adVTE3t4eO3bswF9//YX9+/fj8OHDmDZtGt555x0cOnQIdnZ2OH78OI4eParpEQMAlUqFwsJCFBQUICkpCT4+PggKCtI7TiJqWJiQEZFRsrKy0pqWJKnCMrVaDaDssl9oaCi++uornWU1adKkVusVQtz3fc2bN0fz5s3x9NNPY/bs2QgKCkJcXByeeuopqNVqzJ8/H48++qjO+5RKJWxtbfWOj4gaJiZkRNQgdO7cGXFxcXB3d4eTk5OssQQEBMDOzg75+fma2M6dO4cWLVpUWD8kJARXrlzB+fPn2UtGZKaYkBFRg/Dkk0/i7bffxiOPPIIFCxbAx8cHqamp2LRpE/773//Cx8enTtY7b948FBQUICoqCv7+/rh16xbeffddlJSUYMCAAQCAOXPmYPDgwfD19cVjjz0GCwsL/PHHH/jzzz/x5ptvom/fvujTpw9GjBiB5cuXo0WLFjh79iwkScKgQYPqJG4iMi58ypKIGgQ7OzskJCTAz88Pjz76KNq0aYPx48fjzp07ddpj1rdvX/z9998YO3YsWrdujcjISKSnp2PPnj1o1aoVAGDgwIHYvn074uPjERYWhu7du2P58uXw9/fXLOe7775DWFgYHn/8cbRt2xavvvoqVCpVncVNRMZFEvrcHEFEREREdYY9ZEREREQyY0JGREREJDMmZEREREQyY0JGREREJDMmZEREREQyY0JGREREJDMmZEREREQyY0JGREREJDMmZEREREQyY0JGREREJDMmZEREREQy+3++5TBJADGc7wAAAABJRU5ErkJggg==", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotC(ssys.sims[1], 1e-6, 1e2, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e2)\n", - "ylim(1e-6, 1e8)\n", - "title(\"Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 69, - "id": "1ee8224d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotC(ssys.sims[2], 1e-6, 1e2, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e2)\n", - "ylim(1e-6, 1e-4)\n", - "title(\"Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 70, - "id": "1f7d8918", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "1406×1462 Array{RGB{N0f8},2} with eltype ColorTypes.RGB{FixedPointNumbers.N0f8}:\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " ⋮ ⋱ \n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0)\n", - " RGB{N0f8}(1.0,1.0,1.0) RGB{N0f8}(1.0,1.0,1.0) … RGB{N0f8}(1.0,1.0,1.0)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "getfluxdiagram(ssys,1e2;speciesratetolerance=1e-6)" - ] - }, - { - "cell_type": "code", - "execution_count": 71, - "id": "36206466", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[\"Ar\", \"He\", \"Ne\", \"N2\", \"CO2\", \"proton\", \"H\", \"C=O\", \"O=CO\", \"H2O\", \"O=CC=O\", \"H2\", \"OO\", \"CO\", \"O2\", \"O=C=C=O\", \"C=C=O\", \"O=C=CO\", \"CH4\", \"COC=O\", \"COO\", \"CO-2\", \"COOC\", \"O=CCO\", \"OCO\", \"COCO\", \"OCCO\", \"OC=CO\", \"O=O\", \"C=CO\", \"C=C\", \"O=C=C=C=O\", \"C#COO[CH2]\", \"C#COC[O]\", \"CC=O\", \"O=C=CC=O\", \"C=C(O)O\", \"CC(=O)O\", \"[OH]\", \"CC(=O)C=O\", \"COC(C)=O\", \"CC(=O)CO\", \"O=CCC=O\", \"COC=C=O\", \"O=C=CCO\", \"[CH2]OOC=C\", \"C=COC[O]\", \"C=CC=O\", \"C=COC=O\", \"O=CC=CO\", \"COC\", \"CCO\", \"CC(O)O\", \"CCOC=O\", \"COCC=O\", \"CCOO\", \"CC(C)=O\", \"C=C=C=O\", \"CC=C=O\", \"CC\", \"O=C=C=CO\", \"[CH2]OCC=O\", \"[O]CCC=O\", \"[CH2]COC=O\", \"[CH3]\", \"O=CCCO\", \"CCC=O\", \"CC(O)=C=O\", \"[CH]=O\", \"C[O]\", \"CC(O)C=O\", \"[CH2]O\", \"C=C(O)C=O\", \"OC=CCO\", \"C=CCO\", \"[CH]=C\", \"C[CH2]\", \"C=C=CO\", \"C=C=C\", \"C=C=C(O)O\", \"C=CC(=O)O\", \"CC=CO\", \"C=CC\", \"CC=C(O)O\", \"CCC(=O)O\", \"C=COO\", \"C#C\", \"C=COC\", \"C=CC(O)O\", \"C=COCO\", \"C=CCOO\", \"C=COOC\", \"CC(O)=CO\", \"C=C(C)O\", \"C#CC=O\", \"OC=C=CO\", \"CCOC\", \"CCCO\", \"CCC(O)O\", \"CCOCO\", \"CCCOO\", \"CCC\", \"CCOOC\", \"C=C=COO\", \"CC=COO\", \"C=CCO[O]\", \"COCOC\", \"COCCO\", \"vacantX\", \"CO2X\", \"CHO2X\", \"CO2HX\", \"OCX\", \"OX\", \"CH2O2X\", \"CHOX\", \"CH2OX\", \"HOX\", \"HX\", \"CO[Pt]\", \"OC[Pt]\", \"OC(O)[Pt]\", \"OCO[Pt]\", \"H2OX\", \"OC=[Pt]\", \"O=CC(=O)[Pt]\", \"OC#[Pt]\", \"O=CC=O.[Pt]\", \"[H][H].[Pt]\", \"O=COC[Pt]\", \"OO[Pt]\", \"CX\", \"CHX\", \"CH2X\", \"O=COC#[Pt]\", \"O=CCO[Pt]\", \"O=O.[Pt]\", \"O=CC#[Pt]\", \"OC(O)=[Pt]\", \"O=C(O)C#[Pt]\", \"O=C=C=O.[Pt]\", \"OOC[Pt]\", \"C=C=O.[Pt]\", \"COC(=O)[Pt]\", \"CC(=O)[Pt]\", \"O=COCC#[Pt]\", \"O=C([Pt])CO\", \"O=CCC(=O)[Pt]\", \"OCC#[Pt]\", \"OC(O)C#[Pt]\", \"OCOC#[Pt]\", \"O=CCOC#[Pt]\", \"O=C=C[Pt]\", \"COC#[Pt]\", \"O=CC(=O)C#[Pt]\", \"O=COC=[Pt]\", \"O=C=CC#[Pt]\", \"CC#[Pt]\", \"O=C=CO[Pt]\", \"COC(=O)C#[Pt]\", \"O=C=CC(=O)[Pt]\", \"O=CCC#[Pt]\", \"CH3X\", \"O=C=CO.[Pt]\", \"O=C=C=[Pt]\", \"CC(=O)C#[Pt]\", \"O=C(C#[Pt])CO\", \"COC=O.[Pt]\", \"CC(=O)C(=O)[Pt]\", \"OOC#[Pt]\", \"O=CC[Pt]\", \"O=CC=[Pt]\", \"C.[Pt]\", \"O=C=CC=O.[Pt]\", \"CC(=O)O[Pt]\", \"CC(=O)OC#[Pt]\", \"O=C=C([Pt])C=O\", \"O=C=COC#[Pt]\", \"COO[Pt]\", \"CO.[Pt]\", \"O=C=C(O)[Pt]\", \"O=C=C(O)C#[Pt]\", \"COOC#[Pt]\", \"O=CC(O)[Pt]\", \"O=CC(O)C#[Pt]\", \"O=CC(O)=[Pt]\", \"OCO.[Pt]\", \"O=C=C=C=O.[Pt]\", \"O=CCO.[Pt]\", \"OCC=[Pt]\", \"O=C=CCO.[Pt]\", \"O=C=CC(O)[Pt]\", \"O=C=CC=[Pt]\", \"O=C=C([Pt])CO\", \"O=C=CC[Pt]\", \"O=C=CC(O)=[Pt]\", \"O=C=CCO[Pt]\", \"O=CC([Pt])C=O\", \"O=CC(=[Pt])C=O\", \"O=CCC=O.[Pt]\", \"O=CCC=[Pt]\", \"OOCC#[Pt]\", \"C=C=[Pt]\", \"O=C(O)C=[Pt]\", \"CC=O.[Pt]\", \"CC=[Pt]\", \"CC=C=O.[Pt]\", \"O=C(O)C[Pt]\", \"O=C(O)CC#[Pt]\", \"CC([Pt])=C=O\", \"CC(=C=O)O[Pt]\", \"C=C.[Pt]\", \"C=C[Pt]\", \"C=CC#[Pt]\", \"CC(=O)O.[Pt]\", \"C=CC(=O)[Pt]\", \"O=CC=CO[Pt]\", \"C=CO[Pt]\", \"C=COC(=O)[Pt]\", \"C=COC#[Pt]\", \"CC(O)=[Pt]\", \"O=CC=C[Pt]\", \"C=CC(=O)O[Pt]\", \"OC=C=[Pt]\", \"CC[Pt]\", \"CCC#[Pt]\", \"CCO[Pt]\", \"CCOC(=O)[Pt]\", \"CCC(=O)[Pt]\", \"CCOC#[Pt]\", \"CCC(=O)O[Pt]\", \"CC(O)=C=O.[Pt]\", \"OOC=[Pt]\", \"OO.[Pt]\", \"COCO[Pt]\", \"COCC(=O)[Pt]\", \"COCOC#[Pt]\", \"COCC#[Pt]\", \"COC[Pt]\", \"COC=[Pt]\", \"COC=C=O.[Pt]\", \"O=C=COC[Pt]\", \"COC([Pt])=C=O\", \"O=C=COC=[Pt]\", \"CCOO[Pt]\", \"O=C=C=CO.[Pt]\", \"O=C=C=C(O)[Pt]\", \"O=C=C=C[Pt]\", \"OC=CO.[Pt]\", \"OC=C(O)[Pt]\", \"OC=C[Pt]\", \"OC=CO[Pt]\", \"OC=COC#[Pt]\", \"O=C([Pt])C=CO\", \"OC=C(O)C#[Pt]\", \"OC=CC#[Pt]\", \"OCC[Pt]\", \"OCCC#[Pt]\", \"O=C([Pt])CCO\", \"OCCO[Pt]\", \"OCCOC#[Pt]\", \"O=C=C=C=[Pt]\", \"C=CO.[Pt]\", \"C=C(O)[Pt]\", \"C=C(O)O[Pt]\", \"C=C(O)OC#[Pt]\", \"C=C(O)C#[Pt]\", \"C=C(O)C(=O)[Pt]\", \"C=COO[Pt]\", \"O=CC=C=[Pt]\", \"C=C=C=O.[Pt]\", \"O=C=C=CO[Pt]\", \"CC(O)[Pt]\", \"CC(O)C#[Pt]\", \"CC(O)O[Pt]\", \"CC(O)C(=O)[Pt]\", \"CC(O)OC#[Pt]\", \"O=C=C(O)C[Pt]\", \"O=C=C(O)C=[Pt]\", \"CC([Pt])OC=O\", \"CC(=[Pt])OC=O\", \"O=CC=CO.[Pt]\", \"O=CC=C(O)[Pt]\", \"O=CC([Pt])=CO\", \"OC=CC=[Pt]\", \"OCC(O)[Pt]\", \"OCC(O)C#[Pt]\", \"OCC(O)=[Pt]\", \"COC(O)[Pt]\", \"COC(O)C#[Pt]\", \"COC(O)=[Pt]\", \"O=CCCO[Pt]\", \"O=CCC[Pt]\", \"C=COOC#[Pt]\", \"C=CC=O.[Pt]\", \"C=C([Pt])C=O\", \"C=C(C=O)O[Pt]\", \"C=CC=[Pt]\", \"CC(O)O.[Pt]\", \"OC(O)C[Pt]\"]\n" - ] - } - ], - "source": [ - "println(ssys.names)" - ] - }, - { - "cell_type": "code", - "execution_count": 83, - "id": "8a278180", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "10962-element SparseArrays.SparseVector{Float64, Int64} with 17 stored entries:\n", - " [10253] = 1.81165e-7\n", - " [10254] = 2.86301e-26\n", - " [10255] = -2.17534e-23\n", - " [10256] = -6.02979e-30\n", - " [10265] = 1.19176e-22\n", - " [10268] = 1.18009e-22\n", - " [10273] = 2.99461e-24\n", - " ⋮\n", - " [10310] = -1.12058e-48\n", - " [10352] = -9.82087e-28\n", - " [10540] = -4.14154e-35\n", - " [10555] = 1.26353e-50\n", - " [10835] = 8.25969e-48\n", - " [10865] = 9.36983e-37\n", - " [10867] = -1.9707e-52\n", - " [10908] = 3.09459e-35" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "rops(ssys, \"O=CO\", 1e-12)" - ] - }, - { - "cell_type": "code", - "execution_count": 72, - "id": "64238bc0", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"CH2O2X\",1;N=15,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 73, - "id": "e8bb3c43", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"CHO2X\",1;N=10,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 74, - "id": "0bb84a7f", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"CO2HX\",1;N=10,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 75, - "id": "1044d2b9", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"OX\",1;N=10,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 76, - "id": "7086e403", - "metadata": {}, - "outputs": [], - "source": [ - "plotrops(ssys,\"OCX\",1.0e-6)" - ] - }, - { - "cell_type": "code", - "execution_count": 77, - "id": "44de0eb2", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "vacantX+CO2<=>CO2X\n", - "kf = 20654.615923781494\n", - "krev = 11189.298481041604\n", - "Kc = 1.8459259048971917\n", - "proton+CO2X<=>CHO2X\n", - "kf = 5.164749496653815e7\n", - "krev = 3.369038128826839e8\n", - "Kc = 0.1533004168893831\n", - "proton+CO2X<=>CO2HX\n", - "kf = 463658.8965294065\n", - "krev = 1.20318988446587e-5\n", - "Kc = 3.853580407511801e10\n", - "proton+CHO2X<=>CH2O2X\n", - "kf = 2.5e10\n", - "krev = 9.108706843764319e-26\n", - "Kc = 2.7446266993557504e35\n", - "proton+CO2HX<=>CH2O2X\n", - "kf = 1.9190551016885178e10\n", - "krev = 1.757621070775451e-14\n", - "Kc = 1.0918480289052538e24\n", - "proton+OCX<=>CHOX\n", - "kf = 2.5e10\n", - "krev = 2.604453583293511e-10\n", - "Kc = 9.59894242706594e19\n", - "proton+CHOX<=>CH2OX\n", - "kf = 1.7890196451453958e9\n", - "krev = 4.957912234830633e-11\n", - "Kc = 3.608413300616868e19\n", - "vacantX+vacantX+CO2<=>OX+OCX\n", - "kf = 3.0109478093923404e-24\n", - "krev = 3.037156297092479e15\n", - "Kc = 9.913707148607306e-40\n", - "OX+proton<=>HOX\n", - "kf = 2.5e10\n", - "krev = 4.7547181516587526e-14\n", - "Kc = 5.25793521352646e23\n", - "vacantX+C=O<=>CH2OX\n", - "kf = 500114.13488002896\n", - "krev = 399.6803280141717\n", - "Kc = 1251.2853393732605\n", - "proton+CHO2X<=>OX+C=O\n", - "kf = 7.971946163368602e-7\n", - "krev = 8.220582009654122e-5\n", - "Kc = 0.009697544716428197\n", - "HX+CO2<=>CHO2X\n", - "kf = 6.542996392927688e-8\n", - "krev = 15.579156394796986\n", - "Kc = 4.199839983064083e-9\n", - "HX+CO2<=>CO2HX\n", - "kf = 6.542996392927688e-8\n", - "krev = 6.197590078701277e-11\n", - "Kc = 1055.7323588427441\n", - "vacantX+vacantX+C=O<=>HX+CHOX\n", - "kf = 2.0718885766149262e-11\n", - "krev = 0.008867505326838887\n", - "Kc = 2.336495440655708e-9\n", - "vacantX+O=CO<=>CH2O2X\n", - "kf = 403943.82249737746\n", - "krev = 29.756334575496034\n", - "Kc = 13575.053119278344\n", - "vacantX+vacantX+O=CO<=>HOX+CHOX\n", - "kf = 8.486192390111145e-15\n", - "krev = 9.7037034735699e11\n", - "Kc = 8.745312975839684e-27\n", - "vacantX+vacantX+O=CO<=>HX+CHO2X\n", - "kf = 1.2668346793097018e-21\n", - "krev = 380.13410282264914\n", - "Kc = 3.332599390328158e-24\n", - "vacantX+vacantX+O=CO<=>HX+CO2HX\n", - "kf = 9.840171155787102e-15\n", - "krev = 0.011746228705195169\n", - "Kc = 8.377302539184302e-13\n", - "proton+CH2OX<=>CO[Pt]\n", - "kf = 4.612846333154699e7\n", - "krev = 90.4105198560361\n", - "Kc = 510211.23874742666\n", - "HX+C=O<=>CO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.180104845075902e-9\n", - "Kc = 9.475050217848336\n", - "proton+CO2HX<=>H2O+OCX\n", - "kf = 2.5e10\n", - "krev = 4.0258346788129556e-7\n", - "Kc = 6.20989235637749e16\n", - "vacantX+vacantX+H2O<=>HX+HOX\n", - "kf = 1.7047654949014593e-31\n", - "krev = 21441.30602897437\n", - "Kc = 7.950847269274322e-36\n", - "proton+CH2OX<=>OC[Pt]\n", - "kf = 1.2443063594454413e6\n", - "krev = 1.1005987164187474e-6\n", - "Kc = 1.1305722429827158e12\n", - "HX+C=O<=>OC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.886422105564557e-15\n", - "Kc = 2.099567387708916e7\n", - "vacantX+vacantX+O=CC=O<=>CHOX+CHOX\n", - "kf = 3.132095071630788e8\n", - "krev = 159.05427897483804\n", - "Kc = 1.9691988746346629e6\n", - "proton+CH2O2X<=>OC(O)[Pt]\n", - "kf = 1.9695177200694968e-5\n", - "krev = 3718.799864740736\n", - "Kc = 5.296111088803661e-9\n", - "HX+O=CO<=>OC(O)[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 29981.045237801853\n", - "Kc = 1.0670229661561413e-12\n", - "proton+CH2O2X<=>OCO[Pt]\n", - "kf = 1.3800914441571782e-5\n", - "krev = 3681.751563599994\n", - "Kc = 3.748464339097702e-9\n", - "HOX+C=O<=>OCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.962949149852605e-13\n", - "Kc = 201771.41789913058\n", - "HX+O=CO<=>OCO[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 42359.465576793365\n", - "Kc = 7.552140562327293e-13\n", - "vacantX+H2O<=>H2OX\n", - "kf = 4.842414926683719e6\n", - "krev = 2.0721934488233277e8\n", - "Kc = 0.023368546645263413\n", - "proton+HOX<=>H2OX\n", - "kf = 2.5e10\n", - "krev = 1.2623996335027457e-31\n", - "Kc = 1.9803554545269617e41\n", - "vacantX+vacantX+H2<=>HX+HX\n", - "kf = 3.8736093818093735e10\n", - "krev = 4.9917087254698525e28\n", - "Kc = 7.760086965901168e-19\n", - "proton+CHOX<=>OC=[Pt]\n", - "kf = 3.6460821201937575e9\n", - "krev = 3.454391742229775e10\n", - "Kc = 0.10554917890812951\n", - "vacantX+vacantX+O=CO<=>OX+OC=[Pt]\n", - "kf = 1.3995006080437096e-36\n", - "krev = 7.971831424002446e14\n", - "Kc = 1.755557203367275e-51\n", - "proton+OC=[Pt]<=>OC[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.468152848309303e-23\n", - "Kc = 3.8650910988497585e32\n", - "proton+OC(O)[Pt]<=>H2O+OC=[Pt]\n", - "kf = 6.989877198043828e9\n", - "krev = 6.424310280494338e-11\n", - "Kc = 1.0880354299303816e20\n", - "proton+O=CC(=O)[Pt]<=>OCX+C=O\n", - "kf = 2.302032083373261e7\n", - "krev = 2.5713202543754838e-9\n", - "Kc = 8.952724109165363e15\n", - "vacantX+vacantX+O=CC=O<=>HX+O=CC(=O)[Pt]\n", - "kf = 1.43713660093583e-9\n", - "krev = 0.00032277677938391324\n", - "Kc = 4.452416322137251e-6\n", - "proton+OCX<=>OC#[Pt]\n", - "kf = 26781.620683797883\n", - "krev = 1.0085447542339806e12\n", - "Kc = 2.6554717151981333e-8\n", - "proton+OC#[Pt]<=>OC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.552445879282663e-17\n", - "Kc = 3.815369170624406e26\n", - "vacantX+O=CC=O<=>O=CC=O.[Pt]\n", - "kf = 359723.7676387533\n", - "krev = 0.32068189796600394\n", - "Kc = 1.121746409511672e6\n", - "proton+O=CC(=O)[Pt]<=>O=CC=O.[Pt]\n", - "kf = 1.508798479649927e9\n", - "krev = 8.88806985342612e-11\n", - "Kc = 1.6975547048252826e19\n", - "vacantX+vacantX+OO<=>HOX+HOX\n", - "kf = 4.0912386971316826e8\n", - "krev = 1.7763617117679594e-6\n", - "Kc = 2.3031563166601894e14\n", - "OCX<=>vacantX+CO\n", - "kf = 2.010168305725754e-19\n", - "krev = 2.61760793808642e-25\n", - "Kc = 767940.9419866255\n", - "vacantX+vacantX+O2<=>OX+OX\n", - "kf = 1.0945721587141857e10\n", - "krev = 4.219325007995329e-16\n", - "Kc = 2.594187830138819e25\n", - "proton+HX<=>[H][H].[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.1949534688419614e-15\n", - "Kc = 2.0921316730623565e25\n", - "vacantX+H2<=>[H][H].[Pt]\n", - "kf = 2338.960705505517\n", - "krev = 9707.159813448116\n", - "Kc = 0.24095211683495363\n", - "CHOX+C=O<=>O=COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 7.563806299311394e-5\n", - "Kc = 0.0005236345532350701\n", - "proton+OO[Pt]<=>OX+H2O\n", - "kf = 17.257164508221003\n", - "krev = 6.236444643145301e-63\n", - "Kc = 2.767147869610126e63\n", - "vacantX+vacantX+OO<=>HX+OO[Pt]\n", - "kf = 4.980245005159166e-22\n", - "krev = 5.509834949091977\n", - "Kc = 9.038827934364735e-23\n", - "proton+OC#[Pt]<=>H2O+CX\n", - "kf = 3.276640102032806e-5\n", - "krev = 0.0009291230748795855\n", - "Kc = 0.03526594259277716\n", - "vacantX+vacantX+O=C=C=O<=>OCX+OCX\n", - "kf = 74.64023007210145\n", - "krev = 2.953439666185894e-39\n", - "Kc = 2.52723056870475e40\n", - "HX+O=C=C=O<=>O=CC(=O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 5.0006650398424424e-61\n", - "Kc = 1.1597065597154312e53\n", - "proton+OC=[Pt]<=>H2O+CHX\n", - "kf = 2.5e10\n", - "krev = 6.511063937864271e-5\n", - "Kc = 3.839618261865876e14\n", - "proton+CX<=>CHX\n", - "kf = 2.5e10\n", - "krev = 6.018259224258551e-33\n", - "Kc = 4.1540251206244773e42\n", - "H2+CX<=>CH2X\n", - "kf = 4.832014059685671\n", - "krev = 1.8278921581756875e-33\n", - "Kc = 2.643489681857502e33\n", - "vacantX+vacantX+C=O<=>OX+CH2X\n", - "kf = 4.5608316796485725e-28\n", - "krev = 3.884151005592286e17\n", - "Kc = 1.1742158513101117e-45\n", - "proton+OC[Pt]<=>H2O+CH2X\n", - "kf = 7206.229958253159\n", - "krev = 0.0019484451144913943\n", - "Kc = 3.6984516036184127e6\n", - "proton+O=COC[Pt]<=>CH2X+O=CO\n", - "kf = 1981.2472905766488\n", - "krev = 1.4695324127813272e-5\n", - "Kc = 1.3482161219069803e8\n", - "proton+CHX<=>CH2X\n", - "kf = 2.5e10\n", - "krev = 6.715036577093663e-15\n", - "Kc = 3.722987911231938e24\n", - "proton+O=COC#[Pt]<=>CX+O=CO\n", - "kf = 6.185088018779624e7\n", - "krev = 3.741277098492221e-23\n", - "Kc = 1.6532023306352497e30\n", - "vacantX+vacantX+C=C=O<=>OCX+CH2X\n", - "kf = 2.4823885573387985e-14\n", - "krev = 9.351132511056354e15\n", - "Kc = 2.6546394828687704e-30\n", - "CHOX+C=O<=>O=CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.4949222028864902e7\n", - "Kc = 2.6494156850764662e-15\n", - "HX+O=CC=O<=>O=CCO[Pt]\n", - "kf = 5.6976884072695144e-8\n", - "krev = 2.551666729065355e-8\n", - "Kc = 2.23292812590636\n", - "proton+O=CC=O.[Pt]<=>O=CCO[Pt]\n", - "kf = 957581.7759153218\n", - "krev = 7139.55197608848\n", - "Kc = 134.12351070801344\n", - "O=O.[Pt]+proton<=>OO[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.545950245153839e-28\n", - "Kc = 7.050296330064662e37\n", - "proton+O=CC#[Pt]<=>CX+C=O\n", - "kf = 5.731900626219973e-17\n", - "krev = 16.634660991475336\n", - "Kc = 3.4457574032662074e-18\n", - "proton+CO2HX<=>OC(O)=[Pt]\n", - "kf = 8.313674902647437e-22\n", - "krev = 1.0085447542339753e12\n", - "Kc = 8.243238455949296e-34\n", - "proton+OC(O)=[Pt]<=>OC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.563843227039955e-39\n", - "Kc = 7.014898918762039e48\n", - "proton+OC(O)=[Pt]<=>H2O+OC#[Pt]\n", - "kf = 58948.65819613129\n", - "krev = 2.9467686111082447e-38\n", - "Kc = 2.0004508658710534e42\n", - "proton+O=C(O)C#[Pt]<=>CX+O=CO\n", - "kf = 1.2163309452954808e-9\n", - "krev = 0.00037997676558546045\n", - "Kc = 3.201066632117316e-6\n", - "proton+O=C=C=O.[Pt]<=>O=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.649884885591097e-48\n", - "Kc = 9.434372087609898e57\n", - "vacantX+O=C=C=O<=>O=C=C=O.[Pt]\n", - "kf = 366139.2749661925\n", - "krev = 442.06521987276346\n", - "Kc = 828.2471873077366\n", - "HOX+C=O<=>OOC[Pt]\n", - "kf = 1.5395975576095126e-29\n", - "krev = 2.622153295712258e16\n", - "Kc = 5.871500953537159e-46\n", - "proton+OOC[Pt]<=>OO+CH2X\n", - "kf = 15.535579749933543\n", - "krev = 3.4028033042152773e-9\n", - "Kc = 4.5655238816444645e9\n", - "vacantX+vacantX+O=C=CO<=>OCX+OC=[Pt]\n", - "kf = 73.33238091278024\n", - "krev = 14511.198914062346\n", - "Kc = 0.005053502563576338\n", - "vacantX+C=C=O<=>C=C=O.[Pt]\n", - "kf = 422670.5724931744\n", - "krev = 9.80980243728561e-11\n", - "Kc = 4.3086552985681545e15\n", - "proton+CO[Pt]<=>OX+CH4\n", - "kf = 541698.6744405399\n", - "krev = 1.9995135619129721e-19\n", - "Kc = 2.7091522896313173e24\n", - "HX+C=C=O<=>CC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.3310785577331067e-33\n", - "Kc = 2.514767798332947e25\n", - "proton+C=C=O.[Pt]<=>CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.357099551204697e-8\n", - "Kc = 3.9326110592781875e17\n", - "proton+CC(=O)[Pt]<=>OCX+CH4\n", - "kf = 1.0030005882936613e8\n", - "krev = 4.3463683404291294e-8\n", - "Kc = 2.3076750743003805e15\n", - "vacantX+vacantX+COC=O<=>CHOX+CO[Pt]\n", - "kf = 5.858305523872122e-8\n", - "krev = 9.372228401924443e12\n", - "Kc = 6.250707166578664e-21\n", - "vacantX+vacantX+COC=O<=>HX+O=COC[Pt]\n", - "kf = 8.724708246600757e-23\n", - "krev = 252.56605644619947\n", - "Kc = 3.454426287270814e-25\n", - "vacantX+vacantX+COC=O<=>HX+COC(=O)[Pt]\n", - "kf = 7.165711269221808e-16\n", - "krev = 0.1859922027934253\n", - "Kc = 3.852694447186316e-15\n", - "proton+O=COCC#[Pt]<=>CX+COC=O\n", - "kf = 0.8132675549526747\n", - "krev = 2.165706403032533e-5\n", - "Kc = 37552.06863746147\n", - "HOX+C=C=O<=>O=C([Pt])CO\n", - "kf = 3.3473534940386794e-8\n", - "krev = 9.042590347389556e-30\n", - "Kc = 3.70176394754519e21\n", - "HX+O=C=CO<=>O=C([Pt])CO\n", - "kf = 2.8488442036348548e-8\n", - "krev = 1.614840618256874e-45\n", - "Kc = 1.7641643214981894e37\n", - "vacantX+vacantX+COO<=>HOX+CO[Pt]\n", - "kf = 3.442529358831723e8\n", - "krev = 2.6586367586035048e-11\n", - "Kc = 1.294847574679578e19\n", - "vacantX+vacantX+COO<=>HX+OOC[Pt]\n", - "kf = 1.3336211820914592e-23\n", - "krev = 16620.58178963317\n", - "Kc = 8.023913957833202e-28\n", - "CHOX+C=C=O<=>O=CCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 2.6714659015861004e-16\n", - "Kc = 1.2530025152300434e8\n", - "vacantX+vacantX+CO-2<=>HX+CO[Pt]\n", - "kf = 3.6896065237788346e-26\n", - "krev = 1200.2597905170037\n", - "Kc = 3.0740066050113714e-29\n", - "vacantX+vacantX+CO-2<=>HX+OC[Pt]\n", - "kf = 1.1691860289045307e-22\n", - "krev = 1.716447494000275\n", - "Kc = 6.811662069427353e-23\n", - "proton+OCO[Pt]<=>OX+CO-2\n", - "kf = 6.4866612293733e7\n", - "krev = 4.917786339628338e-9\n", - "Kc = 1.319020547335029e16\n", - "proton+COC(=O)[Pt]<=>OCX+CO-2\n", - "kf = 5.096893185474306e9\n", - "krev = 2.041829224680708e-9\n", - "Kc = 2.49623872744369e18\n", - "proton+O=C([Pt])CO<=>OCX+CO-2\n", - "kf = 1.9762803815844387e7\n", - "krev = 1.2158736968776066e-8\n", - "Kc = 1.6253994034574272e15\n", - "proton+OCC#[Pt]<=>CX+CO-2\n", - "kf = 1.8515947729382765e-10\n", - "krev = 0.16959607683462066\n", - "Kc = 1.091767455649245e-9\n", - "vacantX+vacantX+COOC<=>CO[Pt]+CO[Pt]\n", - "kf = 3.028654941635431e8\n", - "krev = 1.0392777770118965e-11\n", - "Kc = 2.914191959673513e19\n", - "vacantX+vacantX+C=C=O<=>HX+O=C=C[Pt]\n", - "kf = 3.6584912239485734e-16\n", - "krev = 0.32395775785233605\n", - "Kc = 1.1293111942132156e-15\n", - "vacantX+vacantX+O=C=CO<=>HOX+O=C=C[Pt]\n", - "kf = 3.132095071630788e8\n", - "krev = 5.819571251914923e7\n", - "Kc = 5.382003133994065\n", - "proton+O=C=C[Pt]<=>C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.724942318590629e-29\n", - "Kc = 2.570709334924167e38\n", - "vacantX+vacantX+O=CCO<=>CHOX+OC[Pt]\n", - "kf = 9001.813049524091\n", - "krev = 8.180569891408677e12\n", - "Kc = 1.1003894800749632e-9\n", - "vacantX+vacantX+O=CCO<=>HX+O=CCO[Pt]\n", - "kf = 3.705974451661604e-28\n", - "krev = 2668.9209237076484\n", - "Kc = 1.3885665996103351e-31\n", - "vacantX+vacantX+O=CCO<=>HX+O=C([Pt])CO\n", - "kf = 1.2718474027465153e-10\n", - "krev = 0.0002705673832361486\n", - "Kc = 4.7006678614933393e-7\n", - "proton+O=CCOC#[Pt]<=>CX+O=CCO\n", - "kf = 3.8625888100004036e-23\n", - "krev = 1.5059302822169408e-12\n", - "Kc = 2.564918745318097e-11\n", - "proton+COC#[Pt]<=>CX+CO-2\n", - "kf = 3.5797175052253717e-22\n", - "krev = 9.770006712968626e-20\n", - "Kc = 0.0036639867406372244\n", - "proton+O=CC(=O)C#[Pt]<=>CX+O=CC=O\n", - "kf = 5.9931479699583235e-12\n", - "krev = 0.0016900056192162703\n", - "Kc = 3.546229611199523e-9\n", - "vacantX+vacantX+OCO<=>HOX+OC[Pt]\n", - "kf = 1.653107374238179e-12\n", - "krev = 3.492310477620836e11\n", - "Kc = 4.7335635958815765e-24\n", - "vacantX+vacantX+OCO<=>HX+OC(O)[Pt]\n", - "kf = 4.0412190145177725e-23\n", - "krev = 628.7683045605482\n", - "Kc = 6.427198993979533e-26\n", - "vacantX+vacantX+OCO<=>HX+OCO[Pt]\n", - "kf = 1.1281154422531313e-23\n", - "krev = 247.99076039714222\n", - "Kc = 4.5490220702034325e-26\n", - "proton+OC(O)C#[Pt]<=>CX+OCO\n", - "kf = 0.005562206988621036\n", - "krev = 0.025459246171787766\n", - "Kc = 0.21847492856189518\n", - "proton+OCOC#[Pt]<=>CX+OCO\n", - "kf = 2.2993090387825977e-18\n", - "krev = 1.7767009384663083e-12\n", - "Kc = 1.2941452266960681e-6\n", - "proton+O=COC=[Pt]<=>O=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.03525663068036e-45\n", - "Kc = 2.4148601669491608e55\n", - "proton+O=COC=[Pt]<=>CHX+O=CO\n", - "kf = 407721.49317133107\n", - "krev = 4.66233771243883e-34\n", - "Kc = 8.745001291595743e38\n", - "proton+O=COC#[Pt]<=>O=COC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.1834993039887084e-24\n", - "Kc = 7.852993706854812e33\n", - "proton+O=C=CC#[Pt]<=>CX+C=C=O\n", - "kf = 1.255896512556004e-15\n", - "krev = 0.016900821436021087\n", - "Kc = 7.430979123176135e-14\n", - "vacantX+vacantX+COCO<=>CO[Pt]+OC[Pt]\n", - "kf = 3.0636862331912886e-9\n", - "krev = 3.008499680951675e11\n", - "Kc = 1.0183435459837431e-20\n", - "proton+CC#[Pt]<=>CX+CH4\n", - "kf = 3.172314510568854e-8\n", - "krev = 0.363285670785801\n", - "Kc = 8.732286367659409e-8\n", - "HX+O=C=C=O<=>O=C=CO[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.1302052975227224e-55\n", - "Kc = 2.7224155607861307e47\n", - "proton+O=C=CO[Pt]<=>OX+C=C=O\n", - "kf = 0.047578794564636824\n", - "krev = 2.8204743128358057e-8\n", - "Kc = 1.6869075654441754e6\n", - "proton+O=C=C=O.[Pt]<=>O=C=CO[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 2.257619247094878e-42\n", - "Kc = 2.2147224366704162e52\n", - "vacantX+vacantX+O=C=CO<=>HX+O=C=CO[Pt]\n", - "kf = 0.0007071288662616175\n", - "krev = 2.8988454126647536e-5\n", - "Kc = 24.393465866522067\n", - "vacantX+vacantX+OCCO<=>OC[Pt]+OC[Pt]\n", - "kf = 2.961131444342359e-9\n", - "krev = 1.299206322752899e13\n", - "Kc = 2.2791849088819035e-22\n", - "proton+COC(=O)C#[Pt]<=>CX+COC=O\n", - "kf = 2.520547604265173e-10\n", - "krev = 3.828537658551766e-5\n", - "Kc = 6.583577932517004e-6\n", - "proton+O=C=CC(=O)[Pt]<=>OCX+C=C=O\n", - "kf = 2.14881300259784e7\n", - "krev = 1.9623010758881652e-11\n", - "Kc = 1.0950475587061772e18\n", - "vacantX+vacantX+OC=CO<=>OC=[Pt]+OC=[Pt]\n", - "kf = 1.351949923589269e-23\n", - "krev = 7.975137957191956e11\n", - "Kc = 1.6952056890377485e-35\n", - "vacantX+OX+CH4<=>HOX+CH3X\n", - "kf = 1181.9069662995785\n", - "krev = 1.0235810933777192e20\n", - "Kc = 1.1546783874244874e-17\n", - "vacantX+HOX+CH4<=>H2OX+CH3X\n", - "kf = 5.28370763875636e9\n", - "krev = 1.2149259925984929e9\n", - "Kc = 4.348995470461149\n", - "HX+CH3X<=>vacantX+vacantX+CH4\n", - "kf = 5.733311120080377e8\n", - "krev = 8.483521653048543e-25\n", - "Kc = 6.758173497465076e32\n", - "proton+CH2X<=>CH3X\n", - "kf = 2.5e10\n", - "krev = 7.728626954425352e-28\n", - "Kc = 3.2347272222377345e37\n", - "CO2+CH3X<=>COC(=O)[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.00447183609125585\n", - "Kc = 1.463156578060128e-5\n", - "vacantX+vacantX+COC=O<=>CHO2X+CH3X\n", - "kf = 0.05589950368763065\n", - "krev = 5.054770535995559e16\n", - "Kc = 1.1058761874463802e-18\n", - "vacantX+vacantX+COO<=>OO[Pt]+CH3X\n", - "kf = 9.385776922831516e-7\n", - "krev = 3.9782610412247473e11\n", - "Kc = 2.359266228528335e-18\n", - "vacantX+vacantX+CO-2<=>HOX+CH3X\n", - "kf = 9.872876935778847e-16\n", - "krev = 6.917821124819518e13\n", - "Kc = 1.427165686657795e-29\n", - "vacantX+vacantX+COCO<=>CH3X+OCO[Pt]\n", - "kf = 3.9072411322938125e-9\n", - "krev = 8.599564777209447e13\n", - "Kc = 4.543533578174534e-23\n", - "O=O+HX<=>OO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 8.854082166234876e-41\n", - "Kc = 8.666474551788235e32\n", - "vacantX+O=O<=>O=O.[Pt]\n", - "kf = 484458.3574999593\n", - "krev = 584.920039726471\n", - "Kc = 828.247152767255\n", - "vacantX+O=C=CO<=>O=C=CO.[Pt]\n", - "kf = 359723.7676387533\n", - "krev = 0.4900054095759742\n", - "Kc = 734122.0333670193\n", - "proton+O=C=CO.[Pt]<=>O=C([Pt])CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.543989619636675e-29\n", - "Kc = 1.6191818702694958e39\n", - "proton+O=C=CO[Pt]<=>O=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.012328788524416852\n", - "Kc = 2.0277742578265605e12\n", - "vacantX+vacantX+O=C=C=O<=>OX+O=C=C=[Pt]\n", - "kf = 149.2804601441562\n", - "krev = 1.2008902564793325e-12\n", - "Kc = 1.2430816166483347e14\n", - "proton+O=C=C=[Pt]<=>O=CC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 728325.7738813914\n", - "Kc = 34325.299057824195\n", - "proton+O=C=C=[Pt]<=>O=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.992117420427329e-15\n", - "Kc = 4.1721478812771864e24\n", - "vacantX+vacantX+C=CO<=>CH2X+OC=[Pt]\n", - "kf = 3.7510196251812924e-36\n", - "krev = 6.624293894020312e13\n", - "Kc = 5.662519938264367e-50\n", - "proton+O=C(C#[Pt])CO<=>CX+O=CCO\n", - "kf = 2.1150580786972557e-17\n", - "krev = 1.2236788896896236\n", - "Kc = 1.728442074565594e-17\n", - "vacantX+vacantX+C=C<=>CH2X+CH2X\n", - "kf = 9.387035392806688e-46\n", - "krev = 5.259242712748897e15\n", - "Kc = 1.784864457776713e-61\n", - "proton+O=COC[Pt]<=>COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.124037165592671e-28\n", - "Kc = 8.002465615756261e37\n", - "proton+COC(=O)[Pt]<=>COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.484214060387906e-18\n", - "Kc = 7.175219308200797e27\n", - "vacantX+COC=O<=>COC=O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.8619443782965007\n", - "Kc = 410274.8449265323\n", - "HX+O=C=C=C=O<=>O=C=CC(=O)[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 3.561089909521239e-25\n", - "Kc = 1.4777843564830474e17\n", - "vacantX+vacantX+O=C=C=C=O<=>OCX+O=C=C=[Pt]\n", - "kf = 135.4631249389026\n", - "krev = 3.092595390223456e6\n", - "Kc = 4.3802407960361956e-5\n", - "CH3X+O=C=C=O<=>CC(=O)C(=O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 3.5093718907449027e-71\n", - "Kc = 1.6525190917893694e63\n", - "proton+OOC#[Pt]<=>OO+CX\n", - "kf = 3.959382254258936e-52\n", - "krev = 4.505410128222608e6\n", - "Kc = 8.78806177812034e-59\n", - "proton+O=CC[Pt]<=>CH2X+C=O\n", - "kf = 9.847553463617368e-13\n", - "krev = 0.8193686811731042\n", - "Kc = 1.2018464568987987e-12\n", - "HX+C=C=O<=>O=CC[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 3.6888123831707493e-19\n", - "Kc = 9.074339235332521e10\n", - "proton+C=C=O.[Pt]<=>O=CC[Pt]\n", - "kf = 4.477750650627013e6\n", - "krev = 3155.453532604055\n", - "Kc = 1419.0513675324908\n", - "vacantX+vacantX+O=CCO<=>HOX+O=CC[Pt]\n", - "kf = 3.3834985622063113e-5\n", - "krev = 2.9362980773683545e12\n", - "Kc = 1.1523007790948657e-17\n", - "vacantX+vacantX+O=CC=O<=>OX+O=CC=[Pt]\n", - "kf = 6.170227811474367e-18\n", - "krev = 2.1467268001769245e15\n", - "Kc = 2.874249210922341e-33\n", - "proton+O=CC=[Pt]<=>CHX+C=O\n", - "kf = 0.3518802014338951\n", - "krev = 0.0019581841163396926\n", - "Kc = 179.69719930710195\n", - "proton+O=CC#[Pt]<=>O=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.1385387905668107e-13\n", - "Kc = 7.9654902068249e22\n", - "proton+O=C=C[Pt]<=>O=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.814809579170971e7\n", - "Kc = 655.3407052478085\n", - "proton+O=CC=[Pt]<=>O=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.4911345025101916e-29\n", - "Kc = 5.566522219725765e38\n", - "proton+O=CCO[Pt]<=>OX+CC=O\n", - "kf = 108844.3774855493\n", - "krev = 6.551243603618761e-23\n", - "Kc = 1.6614307766761425e27\n", - "vacantX+vacantX+CC=O<=>HX+CC(=O)[Pt]\n", - "kf = 4.3209399543319175e-11\n", - "krev = 0.0003615296985530135\n", - "Kc = 1.195182573278502e-7\n", - "proton+O=CCC(=O)[Pt]<=>OCX+CC=O\n", - "kf = 7.362850070977087e6\n", - "krev = 9.270601965584902e-14\n", - "Kc = 7.94214884676321e19\n", - "proton+O=CCC#[Pt]<=>CX+CC=O\n", - "kf = 0.11748380587607415\n", - "krev = 6.387097627333538e-5\n", - "Kc = 1839.3926745898334\n", - "vacantX+vacantX+CC=O<=>CHOX+CH3X\n", - "kf = 6.063283190982672e-6\n", - "krev = 7.026751658283665e14\n", - "Kc = 8.628856526948432e-21\n", - "proton+CC(=O)C#[Pt]<=>CX+CC=O\n", - "kf = 8.247683071468342e-18\n", - "krev = 0.06355423283679383\n", - "Kc = 1.2977393799478706e-16\n", - "proton+CC(=O)C(=O)[Pt]<=>OCX+CC=O\n", - "kf = 3.422758172577326e7\n", - "krev = 2.0119060511296993e-10\n", - "Kc = 1.7012514926606157e17\n", - "vacantX+vacantX+CC=O<=>HX+O=CC[Pt]\n", - "kf = 3.2094062904328744e-20\n", - "krev = 74.41720028073364\n", - "Kc = 4.312721089110603e-22\n", - "vacantX+CH4<=>C.[Pt]\n", - "kf = 11983.404197457203\n", - "krev = 27576.843954134933\n", - "Kc = 0.4345458899280744\n", - "proton+CH3X<=>C.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.2634270430964172e-30\n", - "Kc = 1.9787450440137642e40\n", - "HX+O=C=CC=O<=>O=CCC(=O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 3.8194581898791103e-32\n", - "Kc = 6.789235995427004e23\n", - "vacantX+vacantX+O=C=CC=O<=>CHOX+O=C=C[Pt]\n", - "kf = 2.850945414803626e8\n", - "krev = 4.6591458607721776e7\n", - "Kc = 6.119030182779314\n", - "vacantX+vacantX+O=C=CC=O<=>HX+O=C=CC(=O)[Pt]\n", - "kf = 1.1776167531898308e-10\n", - "krev = 0.0005032011998508361\n", - "Kc = 2.3402502886298994e-7\n", - "vacantX+vacantX+O=C=CC=O<=>OCX+O=CC=[Pt]\n", - "kf = 0.006845452357086415\n", - "krev = 1.638610749190394e14\n", - "Kc = 4.177595173514284e-17\n", - "vacantX+vacantX+C=C(O)O<=>CH2X+OC(O)=[Pt]\n", - "kf = 1.3631835715271243e-51\n", - "krev = 1.0974745099569602e16\n", - "Kc = 1.242109551665655e-67\n", - "proton+O=C=CC=O.[Pt]<=>O=CCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.130402878837127e-16\n", - "Kc = 4.078035407151288e25\n", - "proton+O=C=CC(=O)[Pt]<=>O=C=CC=O.[Pt]\n", - "kf = 2.964275004938465e9\n", - "krev = 9.178277268525813e-12\n", - "Kc = 3.229663822756335e20\n", - "vacantX+O=C=CC=O<=>O=C=CC=O.[Pt]\n", - "kf = 327433.4917974331\n", - "krev = 0.29189612518083846\n", - "Kc = 1.1217466199476891e6\n", - "vacantX+vacantX+CC(=O)O<=>HOX+CC(=O)[Pt]\n", - "kf = 3.661873055903852e-12\n", - "krev = 2.1682718089028445e11\n", - "Kc = 1.6888441019563762e-23\n", - "vacantX+vacantX+CC(=O)O<=>CO2HX+CH3X\n", - "kf = 1.1977509649486271e-8\n", - "krev = 1.0254845667743408e14\n", - "Kc = 1.1679853639496008e-22\n", - "CO2+CH3X<=>CC(=O)O[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 3.3286101924403974e-7\n", - "Kc = 0.19656841788766613\n", - "proton+CC(=O)O[Pt]<=>OX+CC=O\n", - "kf = 6.638543952734307e-6\n", - "krev = 1.1832604608796647e-7\n", - "Kc = 56.10382643732599\n", - "vacantX+vacantX+CC(=O)O<=>HX+CC(=O)O[Pt]\n", - "kf = 2.4753542791841756e-22\n", - "krev = 11382.562807978633\n", - "Kc = 2.1746897609465158e-26\n", - "proton+CC(=O)OC#[Pt]<=>CX+CC(=O)O\n", - "kf = 3.5372794201475537e8\n", - "krev = 2.288049006228874e-19\n", - "Kc = 1.5459806195224992e27\n", - "vacantX+vacantX+CC(=O)C=O<=>CHOX+CC(=O)[Pt]\n", - "kf = 2.810784197367395e8\n", - "krev = 8.682228189641076\n", - "Kc = 3.237399589106622e7\n", - "vacantX+vacantX+CC(=O)C=O<=>CH3X+O=CC(=O)[Pt]\n", - "kf = 0.010756441693245073\n", - "krev = 2.0353876594794328e15\n", - "Kc = 5.284714016589902e-18\n", - "vacantX+vacantX+CC(=O)C=O<=>HX+CC(=O)C(=O)[Pt]\n", - "kf = 2.426386880233808e-11\n", - "krev = 0.0003222108693910823\n", - "Kc = 7.530431499158364e-8\n", - "proton+O=C=C([Pt])C=O<=>C=O+O=C=C=[Pt]\n", - "kf = 13308.622034460761\n", - "krev = 4.6234228919871786e-9\n", - "Kc = 2.8785214645897607e12\n", - "HX+O=C=C=C=O<=>O=C=C([Pt])C=O\n", - "kf = 5.262522960320117e-8\n", - "krev = 8.417963556232881e-20\n", - "Kc = 6.251539253129229e11\n", - "vacantX+vacantX+O=C=CC=O<=>HX+O=C=C([Pt])C=O\n", - "kf = 3.109950102720783e-13\n", - "krev = 0.31413419650430946\n", - "Kc = 9.900068624582613e-13\n", - "proton+O=C=C([Pt])C=O<=>O=C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.274602487927107e-16\n", - "Kc = 7.6345144463093386e25\n", - "proton+O=C=COC#[Pt]<=>CX+O=C=CO\n", - "kf = 3.333143073629419e-24\n", - "krev = 2.9895559923107984e-13\n", - "Kc = 1.1149291340260339e-11\n", - "vacantX+vacantX+COC(C)=O<=>CO[Pt]+CC(=O)[Pt]\n", - "kf = 6.614441053978493e-6\n", - "krev = 7.629970776987544e11\n", - "Kc = 8.669025409544227e-18\n", - "vacantX+vacantX+COC(C)=O<=>CH3X+COC(=O)[Pt]\n", - "kf = 1.5563360867242215e-10\n", - "krev = 4.0343976517667425e14\n", - "Kc = 3.857666549162974e-25\n", - "vacantX+vacantX+COC(C)=O<=>CH3X+CC(=O)O[Pt]\n", - "kf = 0.0003463783354588583\n", - "krev = 6.683486846094463e16\n", - "Kc = 5.182599194629471e-21\n", - "vacantX+vacantX+COO<=>HX+COO[Pt]\n", - "kf = 1.175900379595729e-21\n", - "krev = 0.27982743013843664\n", - "Kc = 4.2022341377111815e-21\n", - "proton+COO[Pt]<=>OX+CO-2\n", - "kf = 129.78074174016686\n", - "krev = 1.499485133709293e-58\n", - "Kc = 8.65502023478731e59\n", - "vacantX+vacantX+COOC<=>CH3X+COO[Pt]\n", - "kf = 1.8186835430204133e-8\n", - "krev = 4.141977957602716e12\n", - "Kc = 4.39085760869917e-21\n", - "O=O+CH3X<=>COO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 4.970959816815508e-38\n", - "Kc = 1.543639067721808e30\n", - "proton+CO[Pt]<=>CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.487564815762018e-25\n", - "Kc = 1.0049989387851077e35\n", - "proton+OC[Pt]<=>CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.512171272873819e-19\n", - "Kc = 4.535417853038886e28\n", - "vacantX+CO-2<=>CO.[Pt]\n", - "kf = 484125.61468448705\n", - "krev = 1.0558750276780043e7\n", - "Kc = 0.04585065485913965\n", - "vacantX+vacantX+CC(=O)CO<=>OC[Pt]+CC(=O)[Pt]\n", - "kf = 4.324183911493771e7\n", - "krev = 7.8667392573421875e12\n", - "Kc = 5.496793232924203e-6\n", - "vacantX+vacantX+CC(=O)CO<=>CH3X+O=C([Pt])CO\n", - "kf = 0.43146252134138535\n", - "krev = 2.5450806210309695e15\n", - "Kc = 1.695280368629765e-16\n", - "HX+O=C=C=O<=>O=C=C(O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 7.390785994602033e-44\n", - "Kc = 7.846667531546056e35\n", - "proton+O=C=C=O.[Pt]<=>O=C=C(O)[Pt]\n", - "kf = 5.0e10\n", - "krev = 7.832851008293297e-31\n", - "Kc = 6.383371769367348e40\n", - "vacantX+vacantX+O=C=CO<=>HX+O=C=C(O)[Pt]\n", - "kf = 2.8707175642480555e-12\n", - "krev = 0.04083063397693327\n", - "Kc = 7.030793511239207e-11\n", - "proton+O=C=C(O)[Pt]<=>O=C=CO.[Pt]\n", - "kf = 1.7351014576291664e10\n", - "krev = 2.4662443446341767e-14\n", - "Kc = 7.03539964077054e23\n", - "proton+O=C=C(O)[Pt]<=>H2O+O=C=C=[Pt]\n", - "kf = 1.2324712433709262e6\n", - "krev = 1.176415080398485e-31\n", - "Kc = 1.0476499867321094e37\n", - "vacantX+vacantX+O=CCC=O<=>HX+O=CCC(=O)[Pt]\n", - "kf = 3.286584099620913e-11\n", - "krev = 0.0009472638388816695\n", - "Kc = 3.469555117295539e-8\n", - "vacantX+vacantX+O=CCC=O<=>CHOX+O=CC[Pt]\n", - "kf = 5.621568394735124e8\n", - "krev = 2.2372815421494465e13\n", - "Kc = 2.51267812692642e-5\n", - "proton+O=C=C(O)C#[Pt]<=>CX+O=C=CO\n", - "kf = 3.0900625689798e-31\n", - "krev = 97363.75326657317\n", - "Kc = 3.1737299203323514e-36\n", - "proton+COOC#[Pt]<=>CX+COO\n", - "kf = 1.3396315820930446e-65\n", - "krev = 2.5e10\n", - "Kc = 5.3585263283721787e-76\n", - "vacantX+vacantX+COC=C=O<=>CO[Pt]+O=C=C[Pt]\n", - "kf = 1.4053920986837533e8\n", - "krev = 2.5815645207863396e8\n", - "Kc = 0.5443954963619013\n", - "vacantX+vacantX+COC=C=O<=>CH3X+O=C=CO[Pt]\n", - "kf = 1.4053920986837533e8\n", - "krev = 1.2268284001067661e8\n", - "Kc = 1.1455490421981163\n", - "HX+O=CC=O<=>O=CC(O)[Pt]\n", - "kf = 5.6976884072695144e-8\n", - "krev = 1.248882373151946e-25\n", - "Kc = 4.562229822244678e17\n", - "proton+O=CC(O)[Pt]<=>C=O+OC=[Pt]\n", - "kf = 1.4979350850413518e-9\n", - "krev = 7.682289195925664e-6\n", - "Kc = 0.00019498551106820976\n", - "proton+O=CC=O.[Pt]<=>O=CC(O)[Pt]\n", - "kf = 3.43386635836783e8\n", - "krev = 1.2530721027853126e-11\n", - "Kc = 2.7403581571523903e19\n", - "HX+O=C=CO<=>O=CC(O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 2.6755933088589045e-38\n", - "Kc = 1.0647523277182356e30\n", - "vacantX+vacantX+O=CCO<=>HX+O=CC(O)[Pt]\n", - "kf = 5.743984385098034e-15\n", - "krev = 0.20246227896672986\n", - "Kc = 2.8370639777506056e-14\n", - "proton+O=C=CO.[Pt]<=>O=CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.5582018736355307e-22\n", - "Kc = 9.77248912904274e31\n", - "proton+O=CC(O)[Pt]<=>H2O+O=CC=[Pt]\n", - "kf = 459.6019775429135\n", - "krev = 1.1031455244918085e-6\n", - "Kc = 4.166286018833649e8\n", - "proton+O=CC(O)C#[Pt]<=>CX+O=CCO\n", - "kf = 0.2097860124056399\n", - "krev = 0.0024507024511013467\n", - "Kc = 85.60240036947854\n", - "vacantX+vacantX+O=C=CCO<=>OC[Pt]+O=C=C[Pt]\n", - "kf = 4067.906517801298\n", - "krev = 9.581534474143486e11\n", - "Kc = 4.245568941779481e-9\n", - "proton+O=CC(=O)[Pt]<=>O=CC(O)=[Pt]\n", - "kf = 1.4625119078213113e-5\n", - "krev = 1.0085447542339824e12\n", - "Kc = 1.4501209804339615e-17\n", - "proton+O=CC(O)=[Pt]<=>OC#[Pt]+C=O\n", - "kf = 345367.8200620121\n", - "krev = 2.1066346546856475e-20\n", - "Kc = 1.6394291211996983e25\n", - "proton+O=CC(O)=[Pt]<=>H2O+O=CC#[Pt]\n", - "kf = 109541.91076063467\n", - "krev = 6.52855201530546e-37\n", - "Kc = 1.6778898368861259e41\n", - "proton+O=C=C(O)[Pt]<=>O=CC(O)=[Pt]\n", - "kf = 266253.7431100425\n", - "krev = 124230.61178859882\n", - "Kc = 2.1432217009695007\n", - "proton+O=CC(O)=[Pt]<=>O=CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.793151847783197e-46\n", - "Kc = 3.207944678649035e55\n", - "proton+OC(O)[Pt]<=>OCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.3128823116835e-26\n", - "Kc = 5.796587570283467e35\n", - "proton+OCO[Pt]<=>OCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.052557862362137e-26\n", - "Kc = 8.189852945376913e35\n", - "vacantX+OCO<=>OCO.[Pt]\n", - "kf = 395377.4080430906\n", - "krev = 715.0601225795458\n", - "Kc = 552.9289014422803\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.079525546868e-12\n", - "Kc = 1.2021973010936467e22\n", - "vacantX+O=C=C=C=O<=>O=C=C=C=O.[Pt]\n", - "kf = 332249.5811031886\n", - "krev = 401.14766551623046\n", - "Kc = 828.2475748067037\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 4.91573386591171e-7\n", - "Kc = 5.08571063485824e16\n", - "proton+O=CCO[Pt]<=>O=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.8816895227328687e-31\n", - "Kc = 1.3285932507978942e41\n", - "proton+O=C([Pt])CO<=>O=CCO.[Pt]\n", - "kf = 3.74256001789537e8\n", - "krev = 9.536073355505413e-9\n", - "Kc = 3.9246342581191416e16\n", - "vacantX+O=CCO<=>O=CCO.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 1291.5767888759226\n", - "Kc = 273.8002875141987\n", - "proton+O=CC(O)[Pt]<=>O=CCO.[Pt]\n", - "kf = 1.712472301799593e10\n", - "krev = 2.6335036754646568e-14\n", - "Kc = 6.5026387384762e23\n", - "proton+OCC#[Pt]<=>OCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.6468663797080987e-6\n", - "Kc = 6.855200437039605e15\n", - "proton+OCC=[Pt]<=>CHX+CO-2\n", - "kf = 2.437334851076409e7\n", - "krev = 3.684139726492616e-11\n", - "Kc = 6.615750302708541e17\n", - "vacantX+vacantX+O=CCO<=>OX+OCC=[Pt]\n", - "kf = 3.3881471741726223e-34\n", - "krev = 2.264159139077055e16\n", - "Kc = 1.4964262518904662e-50\n", - "vacantX+vacantX+O=C=CCO<=>OCX+OCC=[Pt]\n", - "kf = 1.8009876630720204e-13\n", - "krev = 6.668943472119082e14\n", - "Kc = 2.7005591974222413e-28\n", - "vacantX+vacantX+C=CC=O<=>CH2X+O=CC=[Pt]\n", - "kf = 3.2830355290077765e-39\n", - "krev = 2.9277080237249806e14\n", - "Kc = 1.121367124864694e-53\n", - "vacantX+vacantX+C=COC=O<=>CH2X+O=COC=[Pt]\n", - "kf = 1.0242943870290668e-63\n", - "krev = 2.920849603333263e13\n", - "Kc = 3.5068371403311754e-77\n", - "vacantX+O=C=CCO<=>O=C=CCO.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 1179.037991138623\n", - "Kc = 273.8002884035305\n", - "vacantX+vacantX+O=CC=CO<=>OC=[Pt]+O=CC=[Pt]\n", - "kf = 6.284377773759944e-35\n", - "krev = 2.1623088290446475e12\n", - "Kc = 2.90632757418676e-47\n", - "vacantX+vacantX+COC<=>CH3X+CO[Pt]\n", - "kf = 3.3416169046706564e-11\n", - "krev = 3.110510590664853e12\n", - "Kc = 1.0742985137872191e-23\n", - "proton+O=C=CC(O)[Pt]<=>OC=[Pt]+C=C=O\n", - "kf = 7.886335155622577e-9\n", - "krev = 1.1676117437495351e-7\n", - "Kc = 0.0675424446340125\n", - "HX+O=C=CC=O<=>O=C=CC(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 3.0624966294759025e-24\n", - "Kc = 8.467340919226885e15\n", - "proton+O=C=CC=O.[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 5.4417257022505686e7\n", - "krev = 1.0699402207865258e-10\n", - "Kc = 5.086009102686402e17\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=CC(O)[Pt]\n", - "kf = 2.2665619116480148e-11\n", - "krev = 0.03466826587817799\n", - "Kc = 6.537857761944495e-10\n", - "proton+O=C=CC(O)[Pt]<=>O=C=CCO.[Pt]\n", - "kf = 1.693513701515947e9\n", - "krev = 6.001577582317764e-11\n", - "Kc = 2.8217809039168078e19\n", - "proton+O=C=CC=[Pt]<=>CHX+C=C=O\n", - "kf = 181.35768264661723\n", - "krev = 8.307531938850336e-7\n", - "Kc = 2.183051283841528e8\n", - "proton+O=C=CC#[Pt]<=>O=C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.768026569342988e-11\n", - "Kc = 1.4140058997693788e21\n", - "vacantX+vacantX+O=C=CC=O<=>OX+O=C=CC=[Pt]\n", - "kf = 3.709849833927781e-21\n", - "krev = 2.4389911159903437e17\n", - "Kc = 1.5210591828750508e-38\n", - "proton+O=C=CC(O)[Pt]<=>H2O+O=C=CC=[Pt]\n", - "kf = 4.694863820330143\n", - "krev = 3.9520471176425216e-5\n", - "Kc = 118795.74510565875\n", - "vacantX+vacantX+CCO<=>CH3X+OC[Pt]\n", - "kf = 1.5510087911871897e-15\n", - "krev = 9.749013808701775e13\n", - "Kc = 1.5909391674086975e-29\n", - "proton+O=C=C([Pt])CO<=>CO-2+O=C=C=[Pt]\n", - "kf = 259142.28390262663\n", - "krev = 5.010713983419634e-21\n", - "Kc = 5.171763640074528e25\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=C([Pt])CO\n", - "kf = 4.040764431615523e-20\n", - "krev = 30.812673220085827\n", - "Kc = 1.3113969056672023e-21\n", - "proton+O=C=C([Pt])CO<=>O=C=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.777114479215893e-21\n", - "Kc = 1.4067748753603438e31\n", - "proton+O=C=CC[Pt]<=>CH2X+C=C=O\n", - "kf = 6.0148104045883e-8\n", - "krev = 8.74545093406659e-6\n", - "Kc = 0.006877644674854341\n", - "vacantX+vacantX+O=C=CCO<=>HOX+O=C=CC[Pt]\n", - "kf = 8.032715739528718e-6\n", - "krev = 4.997427676480693e14\n", - "Kc = 1.6073700830795308e-20\n", - "proton+O=C=CC=[Pt]<=>O=C=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.1155543114237032e-25\n", - "Kc = 1.1817233840324226e35\n", - "vacantX+vacantX+CC(O)O<=>CH3X+OC(O)[Pt]\n", - "kf = 1.0212279299691738e-21\n", - "krev = 4.839386960246169e15\n", - "Kc = 2.1102423475497943e-37\n", - "proton+O=C=CC(O)=[Pt]<=>OC#[Pt]+C=C=O\n", - "kf = 1.5097720767202745e6\n", - "krev = 3.361950781834918e-17\n", - "Kc = 4.490761985207459e22\n", - "proton+O=C=CC(O)=[Pt]<=>H2O+O=C=CC#[Pt]\n", - "kf = 5.803789817126122e6\n", - "krev = 2.7232165859221153e-28\n", - "Kc = 2.1312259359498893e34\n", - "proton+O=C=CC(=O)[Pt]<=>O=C=CC(O)=[Pt]\n", - "kf = 0.6530550593549805\n", - "krev = 1.0085447542339824e12\n", - "Kc = 6.475221417923034e-13\n", - "proton+O=C=CC(O)=[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.85508059604632e-41\n", - "Kc = 2.5367626125786886e50\n", - "C=O+O=C=C[Pt]<=>O=C=CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 80798.59947863563\n", - "Kc = 4.901904683810505e-13\n", - "HX+O=C=CC=O<=>O=C=CCO[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 2.019947796444839e-5\n", - "Kc = 0.0012837560986177624\n", - "proton+O=C=CC=O.[Pt]<=>O=C=CCO[Pt]\n", - "kf = 278.5863350248319\n", - "krev = 3612.827309769227\n", - "Kc = 0.07711033800910536\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=CCO[Pt]\n", - "kf = 7.342900678318069e-26\n", - "krev = 740.7927312780465\n", - "Kc = 9.912220204496055e-29\n", - "proton+O=C=CCO[Pt]<=>O=C=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3432355963676785e-28\n", - "Kc = 1.861177597407629e38\n", - "vacantX+vacantX+CCOC=O<=>CH3X+O=COC[Pt]\n", - "kf = 1.714178070740009e-17\n", - "krev = 1.2983121019578911e14\n", - "Kc = 1.3203127877765141e-31\n", - "proton+O=CC([Pt])C=O<=>C=O+O=CC=[Pt]\n", - "kf = 1.0131844482393167e-10\n", - "krev = 2.9534786470384583e-7\n", - "Kc = 0.00034304783251277847\n", - "HX+O=C=CC=O<=>O=CC([Pt])C=O\n", - "kf = 2.5931203025755725e-8\n", - "krev = 5.183135272095574e-24\n", - "Kc = 5.002995612590211e15\n", - "proton+O=C=CC=O.[Pt]<=>O=CC([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 8.319166178505196e-8\n", - "Kc = 3.005108861101275e17\n", - "vacantX+vacantX+O=CCC=O<=>HX+O=CC([Pt])C=O\n", - "kf = 6.269624738894468e-15\n", - "krev = 24.522149705338403\n", - "Kc = 2.556719053684591e-16\n", - "proton+O=CC(=[Pt])C=O<=>C=O+O=CC#[Pt]\n", - "kf = 0.04202179791424184\n", - "krev = 2.102387409121332e-9\n", - "Kc = 1.9987656761987723e7\n", - "proton+O=C=C([Pt])C=O<=>O=CC(=[Pt])C=O\n", - "kf = 2.5e10\n", - "krev = 5.057292696382588\n", - "Kc = 4.943356357025204e9\n", - "proton+O=CC(=[Pt])C=O<=>O=CC([Pt])C=O\n", - "kf = 2.5e10\n", - "krev = 5.3866690937421086e-24\n", - "Kc = 4.641087017771969e33\n", - "vacantX+vacantX+COCC=O<=>CH3X+O=CCO[Pt]\n", - "kf = 1.7650043109029407e-12\n", - "krev = 1.4735149295451475e13\n", - "Kc = 1.1978190892492496e-25\n", - "vacantX+vacantX+COCC=O<=>CO[Pt]+O=CC[Pt]\n", - "kf = 10.947009513309483\n", - "krev = 5.112987413682155e11\n", - "Kc = 2.1410202348661592e-11\n", - "proton+O=CCC(=O)[Pt]<=>O=CCC=O.[Pt]\n", - "kf = 2.1814901321970692e8\n", - "krev = 5.7550523540318155e-8\n", - "Kc = 3.7905652251256815e15\n", - "vacantX+O=CCC=O<=>O=CCC=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 165389.8266532618\n", - "Kc = 1.951879075907524\n", - "proton+O=CC([Pt])C=O<=>O=CCC=O.[Pt]\n", - "kf = 1.6062704929440186e10\n", - "krev = 3.122654421781107e-14\n", - "Kc = 5.1439265316711864e23\n", - "proton+O=CCC#[Pt]<=>O=CCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.03648176110191e-17\n", - "Kc = 4.141485220927174e26\n", - "proton+O=CCC=[Pt]<=>CHX+CC=O\n", - "kf = 1.0605779567215914e7\n", - "krev = 5.748508015003e-13\n", - "Kc = 1.8449621257439228e19\n", - "vacantX+vacantX+O=CCC=O<=>OX+O=CCC=[Pt]\n", - "kf = 1.2771337705277995e-31\n", - "krev = 6.599290845791489e16\n", - "Kc = 1.935259106426951e-48\n", - "vacantX+vacantX+CCOO<=>CH3X+OOC[Pt]\n", - "kf = 1.1728434846364774e-18\n", - "krev = 2.6840450809869076e16\n", - "Kc = 4.3696862356918e-35\n", - "proton+OOCC#[Pt]<=>CX+COO\n", - "kf = 0.24698833297799483\n", - "krev = 0.0004336424509567548\n", - "Kc = 569.5667765760919\n", - "vacantX+vacantX+C=C=O<=>OX+C=C=[Pt]\n", - "kf = 5.2796000958546504e-37\n", - "krev = 1.4614931014553018e17\n", - "Kc = 3.612470076387919e-54\n", - "proton+C=C=[Pt]<=>CC#[Pt]\n", - "kf = 10.738937415423795\n", - "krev = 4.122167482176662e-33\n", - "Kc = 2.60516766042539e33\n", - "vacantX+vacantX+CC(C)=O<=>CH3X+CC(=O)[Pt]\n", - "kf = 0.0015322757193851075\n", - "krev = 1.9084257758101816e14\n", - "Kc = 8.029003479239911e-18\n", - "vacantX+vacantX+C=C=C=O<=>CH2X+O=C=C=[Pt]\n", - "kf = 0.014873013888318402\n", - "krev = 6.520037160662236e15\n", - "Kc = 2.2811240981957472e-18\n", - "HOX+C=C=C=O<=>O=C=C([Pt])CO\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.9529365102554657e-31\n", - "Kc = 9.99708792916859e22\n", - "HX+C=C=C=O<=>O=C=CC[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.4091973858076736e-32\n", - "Kc = 1.225336127134283e24\n", - "vacantX+vacantX+C=C=C=O<=>OCX+C=C=[Pt]\n", - "kf = 0.8504584217531632\n", - "krev = 1.347597642765549e15\n", - "Kc = 6.310922450174717e-16\n", - "proton+O=C(O)C=[Pt]<=>CHX+O=CO\n", - "kf = 7.88145235948431e7\n", - "krev = 1.995696153847229e-7\n", - "Kc = 3.949224607308452e14\n", - "proton+O=C(O)C#[Pt]<=>O=C(O)C=[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.424855572557093e-13\n", - "Kc = 3.3670688615684534e22\n", - "vacantX+vacantX+CC=C=O<=>CH3X+O=C=C[Pt]\n", - "kf = 0.0008567749561878586\n", - "krev = 1.2359860589695025e13\n", - "Kc = 6.931914401220598e-17\n", - "vacantX+vacantX+CC=C=O<=>HX+O=C=CC[Pt]\n", - "kf = 2.2773385768535307e-19\n", - "krev = 181.8091471864856\n", - "Kc = 1.2525984594810374e-21\n", - "proton+O=C=CCO[Pt]<=>OX+CC=C=O\n", - "kf = 3.801213612232799e6\n", - "krev = 3.4005935521726275e-15\n", - "Kc = 1.1178088630451637e21\n", - "proton+CC(=O)[Pt]<=>CC=O.[Pt]\n", - "kf = 2.2108223076011086e9\n", - "krev = 2.493722128340101e-11\n", - "Kc = 8.865551949337277e19\n", - "proton+O=CC[Pt]<=>CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0175396707648368e-24\n", - "Kc = 2.456906665978799e34\n", - "vacantX+CC=O<=>CC=O.[Pt]\n", - "kf = 412885.969273148\n", - "krev = 2.625517699834265\n", - "Kc = 157258.8786200951\n", - "proton+CC=[Pt]<=>CHX+CH4\n", - "kf = 3.754229088708618e7\n", - "krev = 3.193900280463504e-10\n", - "Kc = 1.1754371642948722e17\n", - "proton+CC#[Pt]<=>CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.101069134371629e-9\n", - "Kc = 3.086012424450092e18\n", - "vacantX+vacantX+CC=O<=>OX+CC=[Pt]\n", - "kf = 6.186864182993887e-31\n", - "krev = 2.034915252803989e19\n", - "Kc = 3.04035471475717e-50\n", - "vacantX+vacantX+CC=C=O<=>OCX+CC=[Pt]\n", - "kf = 5.619880038277716e-8\n", - "krev = 4.919193785592355e16\n", - "Kc = 1.14243924578405e-24\n", - "vacantX+vacantX+CC<=>CH3X+CH3X\n", - "kf = 1.6866972609475142e-22\n", - "krev = 6.547125244410207e13\n", - "Kc = 2.576241018739606e-36\n", - "proton+O=C=CC[Pt]<=>CC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.381078389100095e-19\n", - "Kc = 1.0499444333476355e29\n", - "vacantX+CC=C=O<=>CC=C=O.[Pt]\n", - "kf = 365995.57053717994\n", - "krev = 187509.1639624155\n", - "Kc = 1.9518809790573244\n", - "proton+O=C(O)C[Pt]<=>CH2X+O=CO\n", - "kf = 5.038535015011119e-9\n", - "krev = 7.877133180076684e-5\n", - "Kc = 6.396407042799381e-5\n", - "HOX+C=C=O<=>O=C(O)C[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.348252838458729e-29\n", - "Kc = 4.5553052781738184e20\n", - "vacantX+vacantX+CC(=O)O<=>HX+O=C(O)C[Pt]\n", - "kf = 1.1112170024966995e-23\n", - "krev = 36323.66987445037\n", - "Kc = 3.0592090676342045e-28\n", - "proton+O=C(O)C=[Pt]<=>O=C(O)C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0876086200539217e-33\n", - "Kc = 2.2986209872776243e43\n", - "vacantX+vacantX+O=C=C=CO<=>OC=[Pt]+O=C=C=[Pt]\n", - "kf = 0.004371453552681894\n", - "krev = 1.2572855491392857e13\n", - "Kc = 3.476897953431907e-16\n", - "HX+O=C=C=CO<=>O=C=CC(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.3635197599529065e-33\n", - "Kc = 1.9017841755847633e25\n", - "HX+O=C=C=CO<=>O=C=C([Pt])CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 6.797711819853139e-22\n", - "Kc = 3.814695843684052e13\n", - "proton+O=C(O)CC#[Pt]<=>CX+CC(=O)O\n", - "kf = 0.12574987603391333\n", - "krev = 9.921358720719502e-5\n", - "Kc = 1267.4662772882168\n", - "proton+CC([Pt])=C=O<=>CH4+O=C=C=[Pt]\n", - "kf = 49487.72961177987\n", - "krev = 1.2730900614037961e-24\n", - "Kc = 3.8872135689451003e28\n", - "HX+C=C=C=O<=>CC([Pt])=C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.301177455844525e-32\n", - "Kc = 1.2828548214436644e24\n", - "vacantX+vacantX+CC=C=O<=>HX+CC([Pt])=C=O\n", - "kf = 4.581183222917958e-20\n", - "krev = 34.93361388628861\n", - "Kc = 1.3113968791863429e-21\n", - "proton+CC([Pt])=C=O<=>CC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.492848961236613e-19\n", - "Kc = 1.0028686209532082e29\n", - "CH3X+O=C=C=O<=>CC(=C=O)O[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.951682102619952e-64\n", - "Kc = 1.9647454732667077e56\n", - "proton+CC(=C=O)O[Pt]<=>OX+CC=C=O\n", - "kf = 1.920567374031219e-6\n", - "krev = 5.0434729686975995e-5\n", - "Kc = 0.03808025513274787\n", - "vacantX+C=C<=>C=C.[Pt]\n", - "kf = 36.21750369826068\n", - "krev = 0.32335117013731834\n", - "Kc = 112.00671914340097\n", - "vacantX+vacantX+C=CO<=>HOX+C=C[Pt]\n", - "kf = 1.7018617233469498e-12\n", - "krev = 4.164837143763027e13\n", - "Kc = 4.086262354568991e-26\n", - "vacantX+vacantX+C=C<=>HX+C=C[Pt]\n", - "kf = 6.071347272542775e-23\n", - "krev = 1180.067101472276\n", - "Kc = 5.144916983930861e-26\n", - "vacantX+vacantX+C=CC=O<=>CHOX+C=C[Pt]\n", - "kf = 0.3274906030624493\n", - "krev = 2.9425898600264806e14\n", - "Kc = 1.1129332276687114e-15\n", - "vacantX+vacantX+C=COC=O<=>CHO2X+C=C[Pt]\n", - "kf = 0.2513917911405871\n", - "krev = 1.0405847657707406e16\n", - "Kc = 2.4158703779829617e-17\n", - "proton+C=C=[Pt]<=>C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.446578752089028e-33\n", - "Kc = 1.0218350820979533e43\n", - "proton+C=C[Pt]<=>CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 31.775139733809926\n", - "Kc = 7.867786014296917e8\n", - "proton+C=C[Pt]<=>C=C.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.7043133558442046e-25\n", - "Kc = 1.4668664019015827e35\n", - "proton+C=CC#[Pt]<=>CX+C=C\n", - "kf = 1.0856530221273585e-15\n", - "krev = 0.12983129718682296\n", - "Kc = 8.36202861444987e-15\n", - "vacantX+CC(=O)O<=>CC(=O)O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 181176.05501028927\n", - "Kc = 1.9518809818483447\n", - "proton+CC(=O)O[Pt]<=>CC(=O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.133892027559991e-24\n", - "Kc = 6.04756965913213e33\n", - "proton+O=C(O)C[Pt]<=>CC(=O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.815284645396005e-26\n", - "Kc = 4.2990157016290936e35\n", - "proton+C=CC(=O)[Pt]<=>OCX+C=C\n", - "kf = 7.087170621400232e6\n", - "krev = 2.9783308105065206e-7\n", - "Kc = 2.3795780496911715e13\n", - "vacantX+vacantX+C=CC=O<=>HX+C=CC(=O)[Pt]\n", - "kf = 3.052485738368744e-11\n", - "krev = 0.0007099643372969683\n", - "Kc = 4.29949164769375e-8\n", - "HX+C=C=C=O<=>C=CC(=O)[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 5.604440911093213e-48\n", - "Kc = 5.267388203494818e39\n", - "HX+O=C=CC=O<=>O=CC=CO[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 5.6159867257682645e-34\n", - "Kc = 4.61739037002591e25\n", - "proton+O=C=CC=O.[Pt]<=>O=CC=CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 9.013912308921113e-18\n", - "Kc = 2.7734904826239954e27\n", - "proton+O=CC=CO[Pt]<=>OX+C=CC=O\n", - "kf = 3.6615493516163485e-10\n", - "krev = 9.407550626549198e-5\n", - "Kc = 3.892138875429521e-6\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC=CO[Pt]\n", - "kf = 4.135805741920728e-10\n", - "krev = 0.028732529553568358\n", - "Kc = 1.4394158141245496e-8\n", - "HX+C=C=O<=>C=CO[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.272169613200064e-8\n", - "Kc = 0.46029640012283785\n", - "proton+C=C=O.[Pt]<=>C=CO[Pt]\n", - "kf = 2.7021695253394946e-5\n", - "krev = 3753.979595717479\n", - "Kc = 7.19814654406251e-9\n", - "vacantX+vacantX+C=CO<=>HX+C=CO[Pt]\n", - "kf = 1.5839272910037507e-20\n", - "krev = 3600.161649580889\n", - "Kc = 4.399600476795654e-24\n", - "proton+C=CO[Pt]<=>OX+C=C\n", - "kf = 6.694428008398142e6\n", - "krev = 4.294813980591457e-9\n", - "Kc = 1.5587236231070068e15\n", - "vacantX+vacantX+C=COC=O<=>CHOX+C=CO[Pt]\n", - "kf = 0.024290856013790354\n", - "krev = 3.5586883050271985e15\n", - "Kc = 6.825789148062155e-18\n", - "vacantX+vacantX+O=CCCO<=>OC[Pt]+O=CC[Pt]\n", - "kf = 2.162232232095232e-5\n", - "krev = 5.66671683371172e13\n", - "Kc = 3.815670158833332e-19\n", - "proton+C=COC(=O)[Pt]<=>OCX+C=CO\n", - "kf = 8.547694380469097e6\n", - "krev = 5.219823560516419e-10\n", - "Kc = 1.637544695020963e16\n", - "vacantX+vacantX+C=COC=O<=>HX+C=COC(=O)[Pt]\n", - "kf = 3.5117597357119104e-15\n", - "krev = 0.7837038908782975\n", - "Kc = 4.480977798612533e-15\n", - "CO2+C=C[Pt]<=>C=COC(=O)[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.08399332498323721\n", - "Kc = 7.789900440580834e-7\n", - "proton+C=COC#[Pt]<=>CX+C=CO\n", - "kf = 3.59319568894763e-23\n", - "krev = 3.7552909398960855e-5\n", - "Kc = 9.568355012853036e-19\n", - "vacantX+vacantX+CCC=O<=>CH3X+O=CC[Pt]\n", - "kf = 1.2257627381394946e-12\n", - "krev = 3.270257576074817e14\n", - "Kc = 3.748214657790771e-27\n", - "proton+CC(O)=[Pt]<=>OC#[Pt]+CH4\n", - "kf = 7.023325690411809e6\n", - "krev = 0.001122962882704699\n", - "Kc = 6.254281239906934e9\n", - "proton+CC(=O)[Pt]<=>CC(O)=[Pt]\n", - "kf = 9.881755573608883e9\n", - "krev = 1.0085447542339819e12\n", - "Kc = 0.009798033782957261\n", - "proton+CC(O)=[Pt]<=>H2O+CC#[Pt]\n", - "kf = 7.254296675241664e9\n", - "krev = 2.8720393080667615e-6\n", - "Kc = 2.5258347456688205e15\n", - "vacantX+vacantX+CC(=O)O<=>OX+CC(O)=[Pt]\n", - "kf = 1.1829749543892744e-33\n", - "krev = 3.758913107590896e15\n", - "Kc = 3.1471197139415875e-49\n", - "vacantX+vacantX+CC(O)=C=O<=>CH3X+O=C=C(O)[Pt]\n", - "kf = 1.049990631922765e-6\n", - "krev = 1.7955210884029898e15\n", - "Kc = 5.847832357439309e-22\n", - "vacantX+vacantX+CC(O)=C=O<=>HOX+CC([Pt])=C=O\n", - "kf = 0.0029164033711847528\n", - "krev = 3.4437539939134434e12\n", - "Kc = 8.468675103794464e-16\n", - "vacantX+vacantX+CC(O)=C=O<=>HX+CC(=C=O)O[Pt]\n", - "kf = 1.7528367761452354e-6\n", - "krev = 1.1970864565480504e-5\n", - "Kc = 0.14642524494009906\n", - "vacantX+vacantX+CC(O)=C=O<=>OCX+CC(O)=[Pt]\n", - "kf = 65.80946386077328\n", - "krev = 1217.699742052305\n", - "Kc = 0.054044081301896585\n", - "vacantX+vacantX+C=CC=O<=>HX+O=CC=C[Pt]\n", - "kf = 6.342176392543457e-21\n", - "krev = 776.2437464870187\n", - "Kc = 8.170341366672147e-24\n", - "vacantX+vacantX+O=CC=CO<=>HOX+O=CC=C[Pt]\n", - "kf = 4.672349699632388e-15\n", - "krev = 8.81363422062413e13\n", - "Kc = 5.301274800693419e-29\n", - "proton+O=CC=C[Pt]<=>O=CCC=[Pt]\n", - "kf = 1.2673656466904085e10\n", - "krev = 1.0824082827935274e8\n", - "Kc = 117.08757839689983\n", - "proton+C=CC(=O)O[Pt]<=>OX+C=CC=O\n", - "kf = 4.524546416801015\n", - "krev = 7.68227583414659e-9\n", - "Kc = 5.889591202505473e8\n", - "CO2+C=C[Pt]<=>C=CC(=O)O[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 450683.30306117237\n", - "Kc = 1.4517947189269602e-13\n", - "vacantX+vacantX+O=C=CO<=>OX+OC=C=[Pt]\n", - "kf = 7.548264554696059e-34\n", - "krev = 5.749061160710156e15\n", - "Kc = 1.3129560364189368e-49\n", - "proton+OC=C=[Pt]<=>OCC#[Pt]\n", - "kf = 0.00032547344886471076\n", - "krev = 1.1489507349403094e-46\n", - "Kc = 2.832788551909668e42\n", - "vacantX+vacantX+O=C=C=CO<=>OCX+OC=C=[Pt]\n", - "kf = 1.463392220587488e-22\n", - "krev = 7.968303762369095e13\n", - "Kc = 1.8365166090912173e-36\n", - "proton+CC[Pt]<=>CH2X+CH4\n", - "kf = 1.4846524062695914\n", - "krev = 9.859129077434927e-6\n", - "Kc = 150586.56749586415\n", - "HX+C=C<=>CC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 3.1627439012977165e-12\n", - "Kc = 25911.109388377805\n", - "vacantX+vacantX+CCO<=>HOX+CC[Pt]\n", - "kf = 2.1035625708276702e-15\n", - "krev = 1.0019023766861524e15\n", - "Kc = 2.099568400850909e-30\n", - "vacantX+vacantX+CCOC=O<=>CHO2X+CC[Pt]\n", - "kf = 0.08561452397466171\n", - "krev = 3.215769317238553e17\n", - "Kc = 2.6623341268826044e-19\n", - "vacantX+vacantX+CCOO<=>OO[Pt]+CC[Pt]\n", - "kf = 1.262172875849309e-6\n", - "krev = 1.5596341944506717e13\n", - "Kc = 8.092749443044025e-20\n", - "proton+CC=[Pt]<=>CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.602708332438123e-27\n", - "Kc = 2.9060615603731233e36\n", - "vacantX+vacantX+CC<=>HX+CC[Pt]\n", - "kf = 8.697106954471648e-14\n", - "krev = 5.359609736165605e16\n", - "Kc = 1.6227127314485718e-30\n", - "proton+C=C.[Pt]<=>CC[Pt]\n", - "kf = 5.504599623053448e9\n", - "krev = 0.3531497863658743\n", - "Kc = 1.558715263486103e10\n", - "vacantX+vacantX+CCC=O<=>CHOX+CC[Pt]\n", - "kf = 0.0004422945453165714\n", - "krev = 9.363325052982716e15\n", - "Kc = 4.723691026572629e-20\n", - "vacantX+vacantX+CC(O)C=O<=>CH3X+O=CC(O)[Pt]\n", - "kf = 9.477814531468979e-7\n", - "krev = 7.52142668687151e15\n", - "Kc = 1.2601086105129898e-22\n", - "proton+CCC#[Pt]<=>CX+CC\n", - "kf = 3.73018742862406e-11\n", - "krev = 0.075105066117345\n", - "Kc = 4.966625583946592e-10\n", - "C=O+CH3X<=>CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.1808191230067762e-17\n", - "Kc = 3.354171909251678e9\n", - "HX+CC=O<=>CCO[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 2.639709061724686e-6\n", - "Kc = 0.012387213631168494\n", - "vacantX+vacantX+CCO<=>HX+CCO[Pt]\n", - "kf = 5.372480262216755e-24\n", - "krev = 2113.809062877283\n", - "Kc = 2.5416109508508876e-27\n", - "vacantX+vacantX+CCOC=O<=>CHOX+CCO[Pt]\n", - "kf = 4.80530366959931e-5\n", - "krev = 5.681813674074216e13\n", - "Kc = 8.457341168235823e-19\n", - "vacantX+vacantX+CCOO<=>HOX+CCO[Pt]\n", - "kf = 3.028654941635431e8\n", - "krev = 1.2132864881112858e-12\n", - "Kc = 2.496240559268171e20\n", - "proton+CC=O.[Pt]<=>CCO[Pt]\n", - "kf = 19418.796323941955\n", - "krev = 3658.802750537776\n", - "Kc = 5.30741820424393\n", - "proton+CCO[Pt]<=>OX+CC\n", - "kf = 1.5180806810718186e7\n", - "krev = 3.4536717602694347e-12\n", - "Kc = 4.395555763392486e18\n", - "proton+CCOC(=O)[Pt]<=>OCX+CCO\n", - "kf = 1.100364657251968e9\n", - "krev = 4.5302115405928314e-10\n", - "Kc = 2.4289476272623954e18\n", - "vacantX+vacantX+CCOC=O<=>HX+CCOC(=O)[Pt]\n", - "kf = 2.5742212027881315e-15\n", - "krev = 0.39729482671494754\n", - "Kc = 6.479372570927264e-15\n", - "CO2+CC[Pt]<=>CCOC(=O)[Pt]\n", - "kf = 3.860701485876577e-7\n", - "krev = 0.0037771400241392917\n", - "Kc = 0.00010221229451921966\n", - "CH3X+C=C=O<=>CCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.9339597186194493e-34\n", - "Kc = 1.7308289628845924e26\n", - "HX+CC=C=O<=>CCC(=O)[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 2.728234417234893e-33\n", - "Kc = 1.0624138213938816e25\n", - "proton+CCC(=O)[Pt]<=>OCX+CC\n", - "kf = 3.3183098775357734e7\n", - "krev = 1.723115430616528e-10\n", - "Kc = 1.9257618024745373e17\n", - "proton+CC=C=O.[Pt]<=>CCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.816709270833084e-23\n", - "Kc = 3.667458740974689e32\n", - "vacantX+vacantX+CCC=O<=>HX+CCC(=O)[Pt]\n", - "kf = 1.3037608552158366e-12\n", - "krev = 0.18236199715464047\n", - "Kc = 7.149301255514685e-12\n", - "vacantX+vacantX+C=C(O)C=O<=>CH2X+O=CC(O)=[Pt]\n", - "kf = 3.506980389191063e-59\n", - "krev = 1.6121784785918364e12\n", - "Kc = 2.1753053001019147e-71\n", - "proton+CCOC#[Pt]<=>CX+CCO\n", - "kf = 1.6403573057503937e-22\n", - "krev = 1.0480859144262605e-13\n", - "Kc = 1.5650981309565184e-9\n", - "proton+CCC(=O)O[Pt]<=>OX+CCC=O\n", - "kf = 5.622114816602621e-8\n", - "krev = 4.785365563630673e-7\n", - "Kc = 0.11748558687619057\n", - "CO2+CC[Pt]<=>CCC(=O)O[Pt]\n", - "kf = 3.860701485876577e-7\n", - "krev = 2.2515045234693432e-8\n", - "Kc = 17.147207325738\n", - "vacantX+vacantX+OC=CCO<=>OC=[Pt]+OCC=[Pt]\n", - "kf = 3.6700973989487563e-44\n", - "krev = 3.0504263460080312e13\n", - "Kc = 1.203142440646588e-57\n", - "proton+CC(=C=O)O[Pt]<=>CC(O)=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 27.83415070046663\n", - "Kc = 8.981772165076653e8\n", - "vacantX+CC(O)=C=O<=>CC(O)=C=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 165389.73964983693\n", - "Kc = 1.9518801026953096\n", - "proton+OOC=[Pt]<=>OO+CHX\n", - "kf = 2.8719882764673755e7\n", - "krev = 8.077545633440945e-25\n", - "Kc = 3.555520955000709e31\n", - "proton+OOC=[Pt]<=>OOC[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.62255074484058e-37\n", - "Kc = 2.899374064566577e46\n", - "proton+OOC#[Pt]<=>OOC=[Pt]\n", - "kf = 3.432151727081939e-44\n", - "krev = 3342.777740155216\n", - "Kc = 1.0267364431242663e-47\n", - "vacantX+vacantX+C=CCO<=>CH2X+OCC=[Pt]\n", - "kf = 3.3256293066300124e-48\n", - "krev = 2.638642223210571e15\n", - "Kc = 1.2603562837645906e-63\n", - "vacantX+vacantX+C=CCO<=>OC[Pt]+C=C[Pt]\n", - "kf = 1.4930923415267688e-9\n", - "krev = 1.1121057711212152e14\n", - "Kc = 1.3425812366942817e-23\n", - "vacantX+OO<=>OO.[Pt]\n", - "kf = 469882.2241291155\n", - "krev = 15.560302693769444\n", - "Kc = 30197.498941795184\n", - "proton+OO[Pt]<=>OO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.110596489625074e-24\n", - "Kc = 2.251042591395165e34\n", - "C=O+CO[Pt]<=>COCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 9.545218685674386e-14\n", - "Kc = 414937.62088874576\n", - "HX+COC=O<=>COCO[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 0.02522938529859348\n", - "Kc = 1.1100614687459063e-6\n", - "vacantX+vacantX+COCO<=>HX+COCO[Pt]\n", - "kf = 1.0488506310161173e-19\n", - "krev = 521.1543106644776\n", - "Kc = 2.0125529225284944e-22\n", - "proton+COC=O.[Pt]<=>COCO[Pt]\n", - "kf = 0.6792883990466445\n", - "krev = 3726.123137157573\n", - "Kc = 0.00018230433457033608\n", - "proton+COCO[Pt]<=>OX+COC\n", - "kf = 5093.375621150868\n", - "krev = 5.977614318003391e-7\n", - "Kc = 8.520749834613165e9\n", - "CO[Pt]+C=C=O<=>COCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.680149232421768e-23\n", - "Kc = 1.9922953446306685e15\n", - "HX+COC=C=O<=>COCC(=O)[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 2.661991446097411e-38\n", - "Kc = 9.604054388173769e29\n", - "proton+COCC(=O)[Pt]<=>OCX+COC\n", - "kf = 8.734746675052269e7\n", - "krev = 2.1771371890779743e-8\n", - "Kc = 4.012033196103488e15\n", - "vacantX+vacantX+COCC=O<=>HX+COCC(=O)[Pt]\n", - "kf = 2.290241001822749e-10\n", - "krev = 0.0004872161822843353\n", - "Kc = 4.7006669423105973e-7\n", - "proton+COCOC#[Pt]<=>CX+COCO\n", - "kf = 3.2770328923262016e-17\n", - "krev = 2.1864147814239428e-13\n", - "Kc = 0.0001498815741719407\n", - "proton+COCC#[Pt]<=>CX+COC\n", - "kf = 1.433200340176918\n", - "krev = 0.00041586763423335837\n", - "Kc = 3446.289689792732\n", - "proton+COC[Pt]<=>CH2X+CO-2\n", - "kf = 0.2769010105768301\n", - "krev = 3.0099119392563808e-6\n", - "Kc = 91996.38267332179\n", - "vacantX+vacantX+COCO<=>HOX+COC[Pt]\n", - "kf = 8.90444501639475e-13\n", - "krev = 8.409201083164982e12\n", - "Kc = 1.0588931015362724e-25\n", - "C=O+CH3X<=>COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 8.422687202008296e-11\n", - "Kc = 470.23832623775377\n", - "vacantX+vacantX+COC<=>HX+COC[Pt]\n", - "kf = 2.786306429788959e-20\n", - "krev = 52.25975865319748\n", - "Kc = 5.3316481009398625e-22\n", - "vacantX+vacantX+COCC=O<=>CHOX+COC[Pt]\n", - "kf = 1.4060776479118306e6\n", - "krev = 6.613786245273692e13\n", - "Kc = 2.1259798786461146e-8\n", - "vacantX+vacantX+C=C=CO<=>OC=[Pt]+C=C=[Pt]\n", - "kf = 1.5975335437882445e-34\n", - "krev = 2.2957840869759923e8\n", - "Kc = 6.958553083676594e-43\n", - "vacantX+vacantX+C=C=CO<=>CH2X+OC=C=[Pt]\n", - "kf = 9.363402027600756e-56\n", - "krev = 7.047835211144391e9\n", - "Kc = 1.328550079149818e-65\n", - "vacantX+vacantX+COC=O<=>OX+COC=[Pt]\n", - "kf = 1.1797200153280936e-59\n", - "krev = 4.3408253155831816e16\n", - "Kc = 2.7177320660497494e-76\n", - "proton+COC=[Pt]<=>CHX+CO-2\n", - "kf = 479145.9852086257\n", - "krev = 1.0449825701778588e-33\n", - "Kc = 4.5852055228736854e38\n", - "proton+COC#[Pt]<=>COC=[Pt]\n", - "kf = 90933.51053402986\n", - "krev = 2739.427130274527\n", - "Kc = 33.194352764155155\n", - "vacantX+vacantX+COC=C=O<=>OCX+COC=[Pt]\n", - "kf = 2.7777170398864307e-21\n", - "krev = 2.5089215324603047e13\n", - "Kc = 1.107135876490541e-34\n", - "proton+COC=[Pt]<=>COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3472876439887766e-48\n", - "Kc = 1.8555799952254487e58\n", - "vacantX+COC=C=O<=>COC=C=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 1179.0380002145982\n", - "Kc = 273.8002862958761\n", - "proton+COC=C=O.[Pt]<=>COCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.0577777781824875e-25\n", - "Kc = 2.3634453772469967e35\n", - "vacantX+vacantX+C=C=C<=>CH2X+C=C=[Pt]\n", - "kf = 4.78083312177258e-41\n", - "krev = 4.774618642094983e15\n", - "Kc = 1.0013015656628172e-56\n", - "proton+O=C=COC[Pt]<=>CH2X+O=C=CO\n", - "kf = 4.988523456059943e-5\n", - "krev = 0.0009299241102698363\n", - "Kc = 0.05364441464596958\n", - "C=O+O=C=C[Pt]<=>O=C=COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.852140732586457e13\n", - "Kc = 2.1384283940268284e-21\n", - "vacantX+vacantX+COC=C=O<=>HX+O=C=COC[Pt]\n", - "kf = 3.256466928453685e-21\n", - "krev = 26.50445975246776\n", - "Kc = 1.2286486722863626e-22\n", - "proton+O=C=COC[Pt]<=>COC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.6649798034152577e-22\n", - "Kc = 1.5015197150571575e32\n", - "CH3X+O=C=C=O<=>COC([Pt])=C=O\n", - "kf = 5.799304049644909e-8\n", - "krev = 3.1615249923835833e-35\n", - "Kc = 1.8343375629216876e27\n", - "proton+COC([Pt])=C=O<=>CO-2+O=C=C=[Pt]\n", - "kf = 313658.31445379555\n", - "krev = 1.256306436150439e-34\n", - "Kc = 2.496670441448219e39\n", - "vacantX+vacantX+COC=C=O<=>HX+COC([Pt])=C=O\n", - "kf = 2.779636780044878e-20\n", - "krev = 3.601218910546807\n", - "Kc = 7.718599866018197e-21\n", - "proton+COC([Pt])=C=O<=>COC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0459713323621888e-20\n", - "Kc = 2.390122867281724e30\n", - "vacantX+vacantX+C=C=C(O)O<=>OC(O)=[Pt]+C=C=[Pt]\n", - "kf = 2.937512138355157e-45\n", - "krev = 8.778136400287878e10\n", - "Kc = 3.34639609639561e-56\n", - "proton+O=C=COC=[Pt]<=>CHX+O=C=CO\n", - "kf = 2.102599834403735e7\n", - "krev = 1.6989476123058672e-25\n", - "Kc = 1.237589563782969e32\n", - "proton+O=C=COC#[Pt]<=>O=C=COC=[Pt]\n", - "kf = 1080.8801129554665\n", - "krev = 2888.2699525834805\n", - "Kc = 0.37423098626520285\n", - "proton+O=C=COC=[Pt]<=>O=C=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.9106920181466426e-48\n", - "Kc = 8.589022763019266e57\n", - "proton+CCOO[Pt]<=>OX+CCO\n", - "kf = 169.16425212622386\n", - "krev = 5.6416707126946964e-58\n", - "Kc = 2.9984779463568512e59\n", - "vacantX+vacantX+CCOO<=>HX+CCOO[Pt]\n", - "kf = 1.893449523720139e-21\n", - "krev = 0.6694879211592951\n", - "Kc = 2.8282056537202555e-21\n", - "O=O+CC[Pt]<=>CCOO[Pt]\n", - "kf = 4.5276782379965965e-7\n", - "krev = 1.4949208469184493e-38\n", - "Kc = 3.0287076719344122e31\n", - "vacantX+vacantX+C=CC(=O)O<=>CH2X+O=C(O)C=[Pt]\n", - "kf = 4.72289540105198e-39\n", - "krev = 9.498795808374404e14\n", - "Kc = 4.9720990916429044e-54\n", - "vacantX+vacantX+C=CC(=O)O<=>CO2HX+C=C[Pt]\n", - "kf = 5.354197885861111e7\n", - "krev = 1.376967106369583e14\n", - "Kc = 3.888399266107105e-7\n", - "vacantX+vacantX+C=CC(=O)O<=>HOX+C=CC(=O)[Pt]\n", - "kf = 0.03947248649742643\n", - "krev = 2.5171232142616846e11\n", - "Kc = 1.5681586929785789e-13\n", - "vacantX+vacantX+C=CC(=O)O<=>HX+C=CC(=O)O[Pt]\n", - "kf = 2.4490000178339845e-20\n", - "krev = 458.0011375503109\n", - "Kc = 5.3471483300955e-23\n", - "proton+O=C=C=CO.[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.4322611471299928e-17\n", - "Kc = 1.7454917387164855e27\n", - "proton+O=C=C=CO.[Pt]<=>O=C=C([Pt])CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 7.140416160377535e-6\n", - "Kc = 3.5011964903006675e15\n", - "vacantX+O=C=C=CO<=>O=C=C=CO.[Pt]\n", - "kf = 327433.4917974331\n", - "krev = 0.4460204906723957\n", - "Kc = 734122.0832787583\n", - "HX+O=C=C=C=O<=>O=C=C=C(O)[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 1.3048903398306852e-5\n", - "Kc = 0.004032923533638046\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C=C(O)[Pt]\n", - "kf = 4235.342411204313\n", - "krev = 12.909334546967292\n", - "Kc = 328.0837130523738\n", - "proton+O=C=C=C(O)[Pt]<=>O=C=CC(O)=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1053.6449933824201\n", - "Kc = 2.3727156828928486e7\n", - "vacantX+vacantX+O=C=C=CO<=>HX+O=C=C=C(O)[Pt]\n", - "kf = 8.233814429551885e-18\n", - "krev = 0.5740049812746953\n", - "Kc = 1.434449995759099e-17\n", - "proton+O=C=C=C(O)[Pt]<=>O=C=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.249904355928212e-21\n", - "Kc = 3.4483213533096645e30\n", - "vacantX+vacantX+CC=CO<=>OC=[Pt]+CC=[Pt]\n", - "kf = 1.6816353348966163e-33\n", - "krev = 8.021148128032321e14\n", - "Kc = 2.0965020319468163e-48\n", - "proton+O=C=C=C[Pt]<=>O=C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.0269882986128818\n", - "Kc = 9.263273820479827e11\n", - "vacantX+vacantX+C=C=C=O<=>HX+O=C=C=C[Pt]\n", - "kf = 3.6772489817592154e-10\n", - "krev = 0.00723599763490509\n", - "Kc = 5.081882509221477e-8\n", - "vacantX+vacantX+O=C=C=CO<=>HOX+O=C=C=C[Pt]\n", - "kf = 0.00020826365169953766\n", - "krev = 1.0739954827079557e13\n", - "Kc = 1.939148302322696e-17\n", - "vacantX+OC=CO<=>OC=CO.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.48171019889246675\n", - "Kc = 734122.0861712244\n", - "vacantX+vacantX+C=CC<=>CH2X+CC=[Pt]\n", - "kf = 3.8695500910369183e-44\n", - "krev = 2.1644248520711738e17\n", - "Kc = 1.787795999169979e-61\n", - "vacantX+vacantX+C=CC<=>CH3X+C=C[Pt]\n", - "kf = 1.1726078415532691e-17\n", - "krev = 1.59532697721828e15\n", - "Kc = 7.350266486422159e-33\n", - "HX+O=C=CO<=>OC=C(O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 2.762063581333058e-24\n", - "Kc = 1.0314187634521844e16\n", - "vacantX+vacantX+OC=CO<=>HX+OC=C(O)[Pt]\n", - "kf = 6.089904416870865e-20\n", - "krev = 3.928023437111271\n", - "Kc = 1.550373747604081e-20\n", - "proton+O=C=CO.[Pt]<=>OC=C(O)[Pt]\n", - "kf = 6.4368819183992445e7\n", - "krev = 6.799608634080986e-11\n", - "Kc = 9.466547657075904e17\n", - "proton+OC=C(O)[Pt]<=>H2O+OC=C=[Pt]\n", - "kf = 5.262467142275111e-7\n", - "krev = 0.6251329939834178\n", - "Kc = 8.418156125054411e-7\n", - "proton+OC=C(O)[Pt]<=>OC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.835798651062412e-24\n", - "Kc = 3.190485247679302e33\n", - "vacantX+vacantX+OC=CO<=>HOX+OC=C[Pt]\n", - "kf = 1.882970379851619e-8\n", - "krev = 6.2613640604613945e13\n", - "Kc = 3.0072846134950095e-22\n", - "vacantX+vacantX+C=CO<=>HX+OC=C[Pt]\n", - "kf = 5.986889507133711e-22\n", - "krev = 1492.047811549125\n", - "Kc = 4.0125319448830507e-25\n", - "proton+OC=C[Pt]<=>OCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.693803965028289e7\n", - "Kc = 1475.967733939179\n", - "vacantX+vacantX+O=CC=CO<=>CHOX+OC=C[Pt]\n", - "kf = 3.6404040231768274e-5\n", - "krev = 5.1339082800935775e14\n", - "Kc = 7.090901949480236e-20\n", - "proton+OC=C=[Pt]<=>OC=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.9001266800545872e-45\n", - "Kc = 1.3157017509633512e55\n", - "vacantX+vacantX+OC=CCO<=>OC[Pt]+OC=C[Pt]\n", - "kf = 1.39754480380523e-13\n", - "krev = 4.435737343310229e14\n", - "Kc = 3.1506482364492156e-28\n", - "vacantX+vacantX+CC=CO<=>CH3X+OC=C[Pt]\n", - "kf = 3.0518560755450534e-15\n", - "krev = 1.440283576497463e15\n", - "Kc = 2.1189272205454667e-30\n", - "vacantX+vacantX+CC=C(O)O<=>OC(O)=[Pt]+CC=[Pt]\n", - "kf = 3.314404876424973e-50\n", - "krev = 3.298291971460818e17\n", - "Kc = 1.0048852269912959e-67\n", - "HX+O=C=CO<=>OC=CO[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 5.830973747204281e-42\n", - "Kc = 4.885709192226705e33\n", - "vacantX+vacantX+OC=CO<=>HX+OC=CO[Pt]\n", - "kf = 6.3392542923960805e-6\n", - "krev = 0.0008631955285686626\n", - "Kc = 0.007343937824733329\n", - "proton+O=C=CO.[Pt]<=>OC=CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.575140256117379e-26\n", - "Kc = 4.4841921192150256e35\n", - "proton+OC=CO[Pt]<=>OX+C=CO\n", - "kf = 2.262727495050209e-8\n", - "krev = 2.5678564004292932e-5\n", - "Kc = 0.0008811736881672694\n", - "proton+OC=CO[Pt]<=>OC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.711725523568878e-6\n", - "Kc = 6.73541182968781e15\n", - "proton+OC=COC#[Pt]<=>CX+OC=CO\n", - "kf = 2.2492341197526439e-29\n", - "krev = 0.00020529518482061674\n", - "Kc = 1.0956097785332785e-25\n", - "vacantX+vacantX+CCC(=O)O<=>CH3X+O=C(O)C[Pt]\n", - "kf = 8.997747599742267e-17\n", - "krev = 6.572577910715489e15\n", - "Kc = 1.368983026442782e-32\n", - "vacantX+vacantX+CCC(=O)O<=>CO2HX+CC[Pt]\n", - "kf = 3.388822996448631e-6\n", - "krev = 1.0293603282987281e15\n", - "Kc = 3.292163981148853e-21\n", - "vacantX+vacantX+CCC(=O)O<=>HOX+CCC(=O)[Pt]\n", - "kf = 2.1491486919570496e-14\n", - "krev = 4.131728096070369e12\n", - "Kc = 5.201573390081201e-27\n", - "vacantX+vacantX+CCC(=O)O<=>HX+CCC(=O)O[Pt]\n", - "kf = 2.415446383235281e-20\n", - "krev = 451.7273406124814\n", - "Kc = 5.347133472063615e-23\n", - "proton+O=C([Pt])C=CO<=>OCX+C=CO\n", - "kf = 224.18396606543615\n", - "krev = 8.215700647740584e-7\n", - "Kc = 2.728726078001508e8\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=C([Pt])C=CO\n", - "kf = 2.859565189776071e-11\n", - "krev = 0.000933578065584948\n", - "Kc = 3.06301668300697e-8\n", - "HX+O=C=C=CO<=>O=C([Pt])C=CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.1750295723598082e-43\n", - "Kc = 2.206855353748942e35\n", - "proton+O=C=C=CO.[Pt]<=>O=C([Pt])C=CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.234268290529092e-27\n", - "Kc = 2.0254915557527025e37\n", - "proton+OC=C(O)C#[Pt]<=>CX+OC=CO\n", - "kf = 2.8680661830740045e-24\n", - "krev = 729.307267106125\n", - "Kc = 3.932589612680575e-27\n", - "vacantX+vacantX+C=COO<=>OO[Pt]+C=C[Pt]\n", - "kf = 0.00256837059370255\n", - "krev = 1.2695573429161084e13\n", - "Kc = 2.0230441799526235e-16\n", - "vacantX+vacantX+C=COO<=>HOX+C=CO[Pt]\n", - "kf = 3.07907263663438e8\n", - "krev = 5.547742278067932e-15\n", - "Kc = 5.5501364019864025e22\n", - "vacantX+vacantX+C=COO<=>CH2X+OOC=[Pt]\n", - "kf = 7.483948884590266e-53\n", - "krev = 2.8103204909201245e17\n", - "Kc = 2.6630232775123643e-70\n", - "proton+OC=CC#[Pt]<=>CX+C=CO\n", - "kf = 1.0593841984272302e-19\n", - "krev = 13.369077699035607\n", - "Kc = 7.924138241066921e-21\n", - "proton+OCC[Pt]<=>CH2X+CO-2\n", - "kf = 3.9799160772985795e-6\n", - "krev = 0.00035437522440524626\n", - "Kc = 0.011230796633647675\n", - "vacantX+vacantX+OCCO<=>HOX+OCC[Pt]\n", - "kf = 2.110093084979835e-12\n", - "krev = 2.4085316622580622e14\n", - "Kc = 8.760910716040024e-27\n", - "HX+C=CO<=>OCC[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 1.1429411507382647e-15\n", - "Kc = 2.8609207088741057e7\n", - "HOX+C=C<=>OCC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 2.2750559854988554e-15\n", - "Kc = 3.602118089238167e7\n", - "proton+OCC=[Pt]<=>OCC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.1399343496076094e-34\n", - "Kc = 2.1931087530264836e44\n", - "vacantX+vacantX+CCO<=>HX+OCC[Pt]\n", - "kf = 4.51610258482867e-23\n", - "krev = 15472.547765874588\n", - "Kc = 2.918784063985339e-27\n", - "vacantX+vacantX+O=CCCO<=>CHOX+OCC[Pt]\n", - "kf = 2.0496526220764064\n", - "krev = 1.4633869198921762e15\n", - "Kc = 1.4006224835106677e-15\n", - "HX+C#C<=>C=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 2.375601900047824e-24\n", - "Kc = 3.580716650609497e16\n", - "CHOX+C#C<=>O=CC=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 3.2359557228060194e-16\n", - "Kc = 2.6287001452988416e8\n", - "HOX+C#C<=>OC=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 2.419253665005007e-25\n", - "Kc = 3.516108046777805e17\n", - "proton+OCCC#[Pt]<=>CX+CCO\n", - "kf = 0.036583470766554806\n", - "krev = 0.0005754138836916786\n", - "Kc = 63.577664361948486\n", - "OC[Pt]+C=C=O<=>O=C([Pt])CCO\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.869121889511259e-30\n", - "Kc = 1.7908695590280368e22\n", - "HX+O=C=CCO<=>O=C([Pt])CCO\n", - "kf = 2.5565910629172877e-8\n", - "krev = 3.7973012083800085e-37\n", - "Kc = 6.732652804247709e28\n", - "proton+O=C=CCO.[Pt]<=>O=C([Pt])CCO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.5089082544191712e-24\n", - "Kc = 1.6568270421201532e34\n", - "proton+O=C([Pt])CCO<=>OCX+CCO\n", - "kf = 9.600816617542319e7\n", - "krev = 3.185535798116408e-7\n", - "Kc = 3.0138781121904944e14\n", - "vacantX+vacantX+O=CCCO<=>HX+O=C([Pt])CCO\n", - "kf = 4.786286134347495e-11\n", - "krev = 0.0006355926831038164\n", - "Kc = 7.530429883135883e-8\n", - "vacantX+vacantX+C=COC<=>CO[Pt]+C=C[Pt]\n", - "kf = 1.9108708710628152e-14\n", - "krev = 5.750545812867103e12\n", - "Kc = 3.322938262290088e-27\n", - "vacantX+vacantX+C=COC<=>CH3X+C=CO[Pt]\n", - "kf = 8.809048609670953e-10\n", - "krev = 5.30334818480063e15\n", - "Kc = 1.6610353125441853e-25\n", - "vacantX+vacantX+C=COC<=>CH2X+COC=[Pt]\n", - "kf = 2.00333233616492e-67\n", - "krev = 2.0086736136424638e14\n", - "Kc = 9.973408932933319e-82\n", - "C=O+OC[Pt]<=>OCCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.726586049973397e-6\n", - "Kc = 0.00837955829095468\n", - "HX+O=CCO<=>OCCO[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 7.096612291679358e-6\n", - "Kc = 0.003946413774492056\n", - "vacantX+vacantX+OCCO<=>HX+OCCO[Pt]\n", - "kf = 1.0265256602604584e-26\n", - "krev = 112849.3186381155\n", - "Kc = 9.09642763154215e-32\n", - "proton+O=CCO.[Pt]<=>OCCO[Pt]\n", - "kf = 3.478307222117794e6\n", - "krev = 3581.5775849412535\n", - "Kc = 971.1662360023528\n", - "proton+OCCO[Pt]<=>OX+CCO\n", - "kf = 951266.6788585404\n", - "krev = 3.3388075163598663e-18\n", - "Kc = 2.8491210535420697e23\n", - "proton+OCCOC#[Pt]<=>CX+OCCO\n", - "kf = 6.336022152476698e-22\n", - "krev = 5.125095889500872e-13\n", - "Kc = 1.2362738744959868e-9\n", - "vacantX+vacantX+C=CC(O)O<=>OC(O)[Pt]+C=C[Pt]\n", - "kf = 1.3588265576828814e-16\n", - "krev = 6.093754170226661e16\n", - "Kc = 2.2298676968656565e-33\n", - "proton+O=C=C=C=[Pt]<=>O=C=CC#[Pt]\n", - "kf = 8.597534639917141e-9\n", - "krev = 2.1202950562509243e-60\n", - "Kc = 4.0548765204023916e51\n", - "vacantX+vacantX+O=C=C=C=O<=>OX+O=C=C=C=[Pt]\n", - "kf = 6.451439297868635e-57\n", - "krev = 8.482832416110645e14\n", - "Kc = 7.60528910793525e-72\n", - "proton+O=C=C=C(O)[Pt]<=>H2O+O=C=C=C=[Pt]\n", - "kf = 1.6149902683641734e-11\n", - "krev = 0.12950076972214764\n", - "Kc = 1.2470893198775887e-10\n", - "proton+O=C=C=C=[Pt]<=>O=C=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.039016761990757e-51\n", - "Kc = 6.189625216528679e60\n", - "vacantX+C=CO<=>C=CO.[Pt]\n", - "kf = 412885.969273148\n", - "krev = 1.1342794009872417\n", - "Kc = 364007.288604364\n", - "proton+C=CO[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.484544240591893e-27\n", - "Kc = 5.574702502366298e36\n", - "proton+OC=C[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.090002516938126e-28\n", - "Kc = 6.112465676112982e37\n", - "proton+C=CO.[Pt]<=>OCC[Pt]\n", - "kf = 1.7684909297990441e9\n", - "krev = 0.3339506079512917\n", - "Kc = 5.295666148501179e9\n", - "vacantX+vacantX+C=COCO<=>OCO[Pt]+C=C[Pt]\n", - "kf = 1.4197397308458187e-12\n", - "krev = 3.0290185667479297e13\n", - "Kc = 4.6871278586123213e-26\n", - "vacantX+vacantX+C=COCO<=>OC[Pt]+C=CO[Pt]\n", - "kf = 1.0263854075463885e-7\n", - "krev = 1.9545487277553856e14\n", - "Kc = 5.251265384031101e-22\n", - "HX+C=C=O<=>C=C(O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 3.2362559658776053e-12\n", - "Kc = 10343.290300064218\n", - "proton+C=C=O.[Pt]<=>C=C(O)[Pt]\n", - "kf = 0.5863133386822127\n", - "krev = 3624.832599039063\n", - "Kc = 0.00016174908017480404\n", - "vacantX+vacantX+C=CO<=>HX+C=C(O)[Pt]\n", - "kf = 4.00965787691315e-19\n", - "krev = 4.055766485027893\n", - "Kc = 9.886313454472895e-20\n", - "vacantX+vacantX+C=C(O)O<=>HOX+C=C(O)[Pt]\n", - "kf = 3.9452234947489745e-7\n", - "krev = 1.361002505571871e12\n", - "Kc = 2.8987628447394044e-19\n", - "proton+C=C(O)[Pt]<=>H2O+C=C=[Pt]\n", - "kf = 0.1408093188614318\n", - "krev = 0.006096548509334685\n", - "Kc = 23.09656334987455\n", - "proton+C=C(O)[Pt]<=>CC(O)=[Pt]\n", - "kf = 1.124057689749841e8\n", - "krev = 4.718570974473911e-12\n", - "Kc = 2.382199390092179e19\n", - "vacantX+vacantX+C=C(O)C=O<=>CHOX+C=C(O)[Pt]\n", - "kf = 2.8052009086647103\n", - "krev = 2.294429327232502e13\n", - "Kc = 1.2226137782366527e-13\n", - "proton+C=C(O)[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0077190030498644e-22\n", - "Kc = 2.4808503088993487e32\n", - "HOX+C=C=O<=>C=C(O)O[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.6625343699967689e-31\n", - "Kc = 2.0134040862236038e23\n", - "proton+C=C(O)O[Pt]<=>OX+C=CO\n", - "kf = 7.621772041144703e-10\n", - "krev = 0.16987445654378072\n", - "Kc = 4.4867087119601115e-9\n", - "vacantX+vacantX+C=C(O)O<=>HX+C=C(O)O[Pt]\n", - "kf = 8.7276566297004e-6\n", - "krev = 1.546723677424112e-6\n", - "Kc = 5.6426734503963205\n", - "vacantX+vacantX+C=CCOO<=>OOC[Pt]+C=C[Pt]\n", - "kf = 2.5331825038162864e-12\n", - "krev = 1.769892843246248e17\n", - "Kc = 1.4312632052740838e-29\n", - "proton+C=C(O)OC#[Pt]<=>CX+C=C(O)O\n", - "kf = 1.0744261387122509e-22\n", - "krev = 181.85749301564874\n", - "Kc = 5.908066370516815e-25\n", - "proton+C=C(O)C#[Pt]<=>CX+C=CO\n", - "kf = 3.691417083839596e-20\n", - "krev = 61.67110810051338\n", - "Kc = 5.985650651555046e-22\n", - "vacantX+vacantX+C=COOC<=>COO[Pt]+C=C[Pt]\n", - "kf = 0.0009962735751002543\n", - "krev = 4.495422962203487e13\n", - "Kc = 2.21619541359445e-17\n", - "vacantX+vacantX+C=COOC<=>CO[Pt]+C=CO[Pt]\n", - "kf = 2.772273774659678e8\n", - "krev = 3.7705323383409334e-17\n", - "Kc = 7.352473141443741e24\n", - "proton+C=C(O)C(=O)[Pt]<=>OCX+C=CO\n", - "kf = 985.1540455146012\n", - "krev = 5.159085449148215e-7\n", - "Kc = 1.9095517126533618e9\n", - "HOX+C=C=C=O<=>C=C(O)C(=O)[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 3.5720015577500406e-52\n", - "Kc = 8.264488540948707e43\n", - "vacantX+vacantX+C=C(O)C=O<=>HX+C=C(O)C(=O)[Pt]\n", - "kf = 2.8595651897765786e-11\n", - "krev = 0.000933577098423846\n", - "Kc = 3.063019856211522e-8\n", - "proton+C=COO[Pt]<=>OX+C=CO\n", - "kf = 43.93537738533433\n", - "krev = 6.669135249611683e-61\n", - "Kc = 6.587867203306832e61\n", - "O=O+C=C[Pt]<=>C=COO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 1.0833501613715598e-32\n", - "Kc = 7.082998693235901e24\n", - "vacantX+vacantX+C=COO<=>HX+C=COO[Pt]\n", - "kf = 4.552726448583842e-23\n", - "krev = 27.53540659037694\n", - "Kc = 1.6534081069915729e-24\n", - "vacantX+vacantX+C=COOC<=>CH3X+C=COO[Pt]\n", - "kf = 2.287071149777874e-9\n", - "krev = 2.2490557638427473e13\n", - "Kc = 1.0169028205286352e-22\n", - "vacantX+vacantX+CC(O)=CO<=>OC=[Pt]+CC(O)=[Pt]\n", - "kf = 7.128045206079291e-31\n", - "krev = 1.6024698052635947e11\n", - "Kc = 4.4481619451835966e-42\n", - "vacantX+vacantX+CC(O)=CO<=>CH3X+OC=C(O)[Pt]\n", - "kf = 1.2021042471738558e-26\n", - "krev = 3.79937896614338e12\n", - "Kc = 3.163949313521812e-39\n", - "proton+O=CC=C=[Pt]<=>O=CCC#[Pt]\n", - "kf = 62.9877146015209\n", - "krev = 8.316144406521062e-31\n", - "Kc = 7.574148730766316e31\n", - "vacantX+vacantX+O=C=CC=O<=>OX+O=CC=C=[Pt]\n", - "kf = 1.1758489216219413e-43\n", - "krev = 2.1453863988577092e16\n", - "Kc = 5.480825842132732e-60\n", - "proton+O=CC=C=[Pt]<=>O=CC=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.331702565774384e-47\n", - "Kc = 2.6790395240083815e56\n", - "proton+C=C=C=O.[Pt]<=>O=C=CC[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.2229421483387703e-16\n", - "Kc = 1.1246356554390213e26\n", - "vacantX+C=C=C=O<=>C=C=C=O.[Pt]\n", - "kf = 372758.92921022984\n", - "krev = 0.5077615475124772\n", - "Kc = 734122.012658058\n", - "proton+C=C=C=O.[Pt]<=>CC([Pt])=C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.123273247571115e-16\n", - "Kc = 1.1774273531962195e26\n", - "proton+C=C=C=O.[Pt]<=>C=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.171161147913428e-32\n", - "Kc = 4.834504144216726e41\n", - "proton+O=C=C=C[Pt]<=>C=C=C=O.[Pt]\n", - "kf = 3.820491632517615e9\n", - "krev = 3.925100397444825e-12\n", - "Kc = 9.733487670798667e20\n", - "vacantX+vacantX+C=C(C)O<=>CH2X+CC(O)=[Pt]\n", - "kf = 1.2526307828427685e-31\n", - "krev = 1.8291181793687947e14\n", - "Kc = 6.848276929132241e-46\n", - "vacantX+vacantX+C=C(C)O<=>CH3X+C=C(O)[Pt]\n", - "kf = 6.412809230790006e-14\n", - "krev = 6.896161957802356e13\n", - "Kc = 9.299098933624258e-28\n", - "HX+O=C=C=C=O<=>O=C=C=CO[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 6.474039280394542e-15\n", - "Kc = 8.128654665807662e6\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C=CO[Pt]\n", - "kf = 2.4048564698523636e10\n", - "krev = 0.03636685994081414\n", - "Kc = 6.612769080877996e11\n", - "proton+O=C=C=CO[Pt]<=>OX+C=C=C=O\n", - "kf = 7.675790818902377e-14\n", - "krev = 0.0006735755949001122\n", - "Kc = 1.1395589265731426e-10\n", - "vacantX+vacantX+O=C=C=CO<=>HX+O=C=C=CO[Pt]\n", - "kf = 4.194899212644372e-10\n", - "krev = 0.014508998351933198\n", - "Kc = 2.891239705796395e-8\n", - "proton+O=C=C=CO[Pt]<=>O=C=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4612716650323904e-11\n", - "Kc = 1.71083862078759e21\n", - "proton+CC(O)[Pt]<=>OC=[Pt]+CH4\n", - "kf = 59.397807135376084\n", - "krev = 1.2803453253139382e-6\n", - "Kc = 4.639202093451769e7\n", - "HX+C=CO<=>CC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 1.2254518112062234e-21\n", - "Kc = 2.668292606261641e13\n", - "HX+CC=O<=>CC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 2.4645381117653586e-12\n", - "Kc = 13267.654460532101\n", - "vacantX+vacantX+CCO<=>HX+CC(O)[Pt]\n", - "kf = 1.7361137032745595e-19\n", - "krev = 63.774720976875884\n", - "Kc = 2.72225997492652e-21\n", - "vacantX+vacantX+CC(O)O<=>HOX+CC(O)[Pt]\n", - "kf = 7.380915652046712e-14\n", - "krev = 2.775462823415347e13\n", - "Kc = 2.6593458899096773e-27\n", - "proton+CC=O.[Pt]<=>CC(O)[Pt]\n", - "kf = 36132.65188770086\n", - "krev = 0.006356177292382113\n", - "Kc = 5.68465135971048e6\n", - "proton+CC(O)[Pt]<=>H2O+CC=[Pt]\n", - "kf = 2964.0563969386994\n", - "krev = 0.019559355499681682\n", - "Kc = 151541.61889367664\n", - "proton+CC(O)=[Pt]<=>CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.860369956892034e-19\n", - "Kc = 5.143641373338227e28\n", - "vacantX+vacantX+CC(O)C=O<=>CHOX+CC(O)[Pt]\n", - "kf = 753631.9525109725\n", - "krev = 9.011518944421836e14\n", - "Kc = 8.362984721654206e-10\n", - "proton+C=CO.[Pt]<=>CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.061646123775542e-6\n", - "Kc = 4.939104668453628e15\n", - "HX+C#CC=O<=>O=CC=C[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 1.9866745274914506e-30\n", - "Kc = 1.4859387148609413e22\n", - "proton+CC(O)C#[Pt]<=>CX+CCO\n", - "kf = 1.3617819786307934\n", - "krev = 4.084110860281074e-5\n", - "Kc = 33343.413663777814\n", - "O=CO+CH3X<=>CC(O)O[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 7.324156308451427e-7\n", - "Kc = 0.043678018970166745\n", - "HOX+CC=O<=>CC(O)O[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 7.587328136505701e-13\n", - "Kc = 43096.38318446866\n", - "HX+CC(=O)O<=>CC(O)O[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 4598.938099177113\n", - "Kc = 6.089703295881323e-12\n", - "proton+CC(O)O[Pt]<=>OX+CCO\n", - "kf = 1.6583777607664147e6\n", - "krev = 1.6983423991371652e-6\n", - "Kc = 9.764684445309413e11\n", - "vacantX+vacantX+CC(O)O<=>HX+CC(O)O[Pt]\n", - "kf = 4.052122584605618e-24\n", - "krev = 469.09529347560436\n", - "Kc = 8.638165082797514e-27\n", - "proton+CC(=O)O.[Pt]<=>CC(O)O[Pt]\n", - "kf = 0.7475019896975738\n", - "krev = 3555.8603422114556\n", - "Kc = 0.00021021691454639312\n", - "vacantX+vacantX+OC=C=CO<=>OC=[Pt]+OC=C=[Pt]\n", - "kf = 3.0449395213240036e-51\n", - "krev = 1.4315520101841116e12\n", - "Kc = 2.1270198355785863e-63\n", - "CH3X+O=C=CO<=>CC(O)C(=O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 4.477216581188038e-53\n", - "Kc = 6.362980552705156e44\n", - "proton+CC(O)C(=O)[Pt]<=>OCX+CCO\n", - "kf = 9.570476890072168e7\n", - "krev = 4.96015815008412e-7\n", - "Kc = 1.929470109720163e14\n", - "HOX+CC=C=O<=>CC(O)C(=O)[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 3.536759710167166e-36\n", - "Kc = 8.195394062368554e27\n", - "HX+CC(O)=C=O<=>CC(O)C(=O)[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 4.830700359768998e-42\n", - "Kc = 5.292381792522405e33\n", - "vacantX+vacantX+CC(O)C=O<=>HX+CC(O)C(=O)[Pt]\n", - "kf = 4.786286134353719e-11\n", - "krev = 0.0006355923790078162\n", - "Kc = 7.530433486042254e-8\n", - "proton+CC(O)=C=O.[Pt]<=>CC(O)C(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.368412782384192e-31\n", - "Kc = 1.8269341182594315e41\n", - "proton+CC(O)OC#[Pt]<=>CX+CC(O)O\n", - "kf = 2.7873525673015004e-16\n", - "krev = 1.8374709107747412e-8\n", - "Kc = 1.516950581887719e-8\n", - "vacantX+vacantX+CCOC<=>CO[Pt]+CC[Pt]\n", - "kf = 2.3627317133785774e-11\n", - "krev = 3.856091265609508e13\n", - "Kc = 6.127271246016828e-25\n", - "vacantX+vacantX+CCOC<=>CH3X+CCO[Pt]\n", - "kf = 6.326940367296449e-9\n", - "krev = 1.8372911814097844e13\n", - "Kc = 3.443624195943553e-22\n", - "vacantX+vacantX+CCOC<=>CH3X+COC[Pt]\n", - "kf = 1.3389399016858639e-14\n", - "krev = 2.773400746132106e14\n", - "Kc = 4.8277909478217395e-29\n", - "proton+O=C=C(O)C[Pt]<=>CH2X+O=C=CO\n", - "kf = 4.2042874371743854e-22\n", - "krev = 1.1101526849597185\n", - "Kc = 3.787125405481442e-22\n", - "HOX+C=C=C=O<=>O=C=C(O)C[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 6.322264310888409e-36\n", - "Kc = 4.669334354059592e27\n", - "vacantX+vacantX+CC(O)=C=O<=>HX+O=C=C(O)C[Pt]\n", - "kf = 6.004181315465852e-13\n", - "krev = 0.19478740167193392\n", - "Kc = 3.082427951669201e-12\n", - "proton+O=C=C(O)C[Pt]<=>CC(O)=C=O.[Pt]\n", - "kf = 1.859235052213257e9\n", - "krev = 4.357618832801525e-11\n", - "Kc = 4.266630753057283e19\n", - "proton+O=C=C(O)C=[Pt]<=>CHX+O=C=CO\n", - "kf = 1.807627844430322e-6\n", - "krev = 0.0010238577171457239\n", - "Kc = 0.0017655068806528764\n", - "proton+O=C=C(O)C#[Pt]<=>O=C=C(O)C=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.347883511420028\n", - "Kc = 7.467404380923659e9\n", - "proton+O=C=C(O)C=[Pt]<=>O=C=C(O)C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4404183806094484e-33\n", - "Kc = 1.735606844271341e43\n", - "vacantX+vacantX+CCCO<=>OC[Pt]+CC[Pt]\n", - "kf = 4.648157058598011e-13\n", - "krev = 1.3999921584371802e15\n", - "Kc = 3.3201307811515004e-28\n", - "vacantX+vacantX+CCCO<=>CH3X+OCC[Pt]\n", - "kf = 1.2211065235504926e-16\n", - "krev = 1.2627143633797795e15\n", - "Kc = 9.670488900451568e-32\n", - "proton+CC([Pt])OC=O<=>CH4+O=COC=[Pt]\n", - "kf = 1.0679856406424377e-15\n", - "krev = 0.2905260385078575\n", - "Kc = 3.6760410396521245e-15\n", - "CHOX+CC=O<=>CC([Pt])OC=O\n", - "kf = 3.269864007171502e-8\n", - "krev = 0.48922244404245907\n", - "Kc = 6.68379802887317e-8\n", - "HX+C=COC=O<=>CC([Pt])OC=O\n", - "kf = 2.5565910629172877e-8\n", - "krev = 1.2259112200812889e-16\n", - "Kc = 2.0854618352769157e8\n", - "vacantX+vacantX+CCOC=O<=>HX+CC([Pt])OC=O\n", - "kf = 6.519502059052115e-22\n", - "krev = 142.86665816232104\n", - "Kc = 4.563347489828482e-24\n", - "proton+CC([Pt])OC=O<=>O=CO+CC=[Pt]\n", - "kf = 8049.244255788158\n", - "krev = 0.00029431628636694825\n", - "Kc = 2.7348959703006394e7\n", - "proton+CC(=[Pt])OC=O<=>CH4+O=COC#[Pt]\n", - "kf = 4.771264023974434e9\n", - "krev = 10.578082715743388\n", - "Kc = 4.510518732164335e8\n", - "proton+CC(=[Pt])OC=O<=>O=CO+CC#[Pt]\n", - "kf = 7292.02651577905\n", - "krev = 8.53932827082491e-43\n", - "Kc = 8.539344412712957e45\n", - "proton+CC(=[Pt])OC=O<=>CC([Pt])OC=O\n", - "kf = 2.5e10\n", - "krev = 2.5945295399651927e-47\n", - "Kc = 9.635658262860014e56\n", - "vacantX+vacantX+CCC(O)O<=>OC(O)[Pt]+CC[Pt]\n", - "kf = 3.712816041087776e-19\n", - "krev = 9.367983662004229e16\n", - "Kc = 3.9633032838716965e-36\n", - "vacantX+O=CC=CO<=>O=CC=CO.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 0.8868529608572997\n", - "Kc = 364007.2889878057\n", - "proton+O=CC=CO[Pt]<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.467206835324098e-11\n", - "Kc = 1.703917907012588e21\n", - "proton+O=C([Pt])C=CO<=>O=CC=CO.[Pt]\n", - "kf = 3.672999120067293e9\n", - "krev = 4.587068754429701e-12\n", - "Kc = 8.00729031262133e20\n", - "HX+O=C=CC=O<=>O=CC=C(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.0473065138531246e-21\n", - "Kc = 2.475989854235963e13\n", - "proton+O=C=CC=O.[Pt]<=>O=CC=C(O)[Pt]\n", - "kf = 9.946079261837086e6\n", - "krev = 6.687641252513296e-9\n", - "Kc = 1.4872327755468685e15\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC=C(O)[Pt]\n", - "kf = 2.77963678004065e-20\n", - "krev = 3.601218827022036\n", - "Kc = 7.718600045027592e-21\n", - "proton+O=CC=C(O)[Pt]<=>H2O+O=CC=C=[Pt]\n", - "kf = 2.367383825493301e-13\n", - "krev = 16.1722227709439\n", - "Kc = 1.463858035487058e-14\n", - "proton+O=CC=C(O)[Pt]<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.867624236214861e-24\n", - "Kc = 3.177579311035777e33\n", - "vacantX+vacantX+CCOCO<=>OCO[Pt]+CC[Pt]\n", - "kf = 2.4512530384253315e-9\n", - "krev = 3.614837695546209e14\n", - "Kc = 6.781087409389048e-24\n", - "vacantX+vacantX+CCOCO<=>OC[Pt]+CCO[Pt]\n", - "kf = 1.0293700832173347e-6\n", - "krev = 1.2050997101819434e12\n", - "Kc = 8.541783509863451e-19\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC([Pt])=CO\n", - "kf = 4.3007284274917255e-15\n", - "krev = 1.9561961334382385\n", - "Kc = 2.1985159636997663e-15\n", - "HX+O=C=C=CO<=>O=CC([Pt])=CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.6370748462102965e-36\n", - "Kc = 1.5839961798805036e28\n", - "proton+O=CC([Pt])=CO<=>C=O+OC=C=[Pt]\n", - "kf = 4.3296354594819855e-33\n", - "krev = 908.9754469679581\n", - "Kc = 4.76320397203711e-36\n", - "proton+O=C=C=CO.[Pt]<=>O=CC([Pt])=CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.7196074204687593e-20\n", - "Kc = 1.4538201977044896e30\n", - "HOX+C#CC=O<=>O=CC([Pt])=CO\n", - "kf = 2.952076594227614e-8\n", - "krev = 4.790462195255654e-44\n", - "Kc = 6.162404531970363e35\n", - "proton+O=CC([Pt])=CO<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.2409630475480663e-18\n", - "Kc = 1.1155918000233681e28\n", - "proton+OC=CC=[Pt]<=>CHX+C=CO\n", - "kf = 0.3708119772368373\n", - "krev = 1.9743851754031655e-5\n", - "Kc = 18781.136621992628\n", - "vacantX+vacantX+O=CC=CO<=>OX+OC=CC=[Pt]\n", - "kf = 8.803023976547135e-28\n", - "krev = 1.526615583505237e17\n", - "Kc = 5.766365856383213e-45\n", - "proton+OC=CC#[Pt]<=>OC=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4263979915391943e-8\n", - "Kc = 1.7526665172195773e18\n", - "vacantX+vacantX+CCCOO<=>OOC[Pt]+CC[Pt]\n", - "kf = 5.56726706794292e-16\n", - "krev = 4.282042054393877e17\n", - "Kc = 1.3001430152303739e-33\n", - "proton+OCC(O)[Pt]<=>OC=[Pt]+CO-2\n", - "kf = 0.16339719354915763\n", - "krev = 6.17359485423602e-8\n", - "Kc = 2.6467106670766133e6\n", - "HX+O=CCO<=>OCC(O)[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 4.347223516290618e-14\n", - "Kc = 644231.1603064304\n", - "vacantX+vacantX+OCCO<=>HX+OCC(O)[Pt]\n", - "kf = 7.314142036323851e-21\n", - "krev = 492.5535033039904\n", - "Kc = 1.4849436634317805e-23\n", - "HX+OC=CO<=>OCC(O)[Pt]\n", - "kf = 5.6012337000223925e-8\n", - "krev = 1.5412075197181771e-21\n", - "Kc = 3.634315060340885e13\n", - "HOX+C=CO<=>OCC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 6.743155058263278e-19\n", - "Kc = 4.8491603395127426e10\n", - "proton+O=CCO.[Pt]<=>OCC(O)[Pt]\n", - "kf = 698182.0065765544\n", - "krev = 4.403884986144656e-6\n", - "Kc = 1.5853774764171848e11\n", - "proton+OCC(O)[Pt]<=>H2O+OCC=[Pt]\n", - "kf = 0.7285659975205578\n", - "krev = 0.0004743003964980969\n", - "Kc = 1536.0855755124403\n", - "proton+OC=CO.[Pt]<=>OCC(O)[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 1.4989628309182922e-5\n", - "Kc = 3.3356397482764175e15\n", - "proton+OCC(O)C#[Pt]<=>CX+OCCO\n", - "kf = 5.26000051169577\n", - "krev = 0.00019971123776726528\n", - "Kc = 26338.02969978857\n", - "vacantX+vacantX+CCC<=>CH3X+CC[Pt]\n", - "kf = 7.798842461270165e-20\n", - "krev = 4.754727023110295e15\n", - "Kc = 1.640229275700578e-35\n", - "proton+O=C([Pt])CO<=>OCC(O)=[Pt]\n", - "kf = 4.019918430047713e-18\n", - "krev = 1.0085447542339827e12\n", - "Kc = 3.9858602339377106e-30\n", - "proton+OCC(O)=[Pt]<=>H2O+OCC#[Pt]\n", - "kf = 16209.61875952926\n", - "krev = 4.634124941714537e-41\n", - "Kc = 3.4978812533984058e44\n", - "proton+OCC(O)=[Pt]<=>OC#[Pt]+CO-2\n", - "kf = 382.95023851607715\n", - "krev = 3.536410198453644e-35\n", - "Kc = 1.0828784474253827e37\n", - "proton+OC=C(O)[Pt]<=>OCC(O)=[Pt]\n", - "kf = 6875.768524790738\n", - "krev = 1.0085447542339824e12\n", - "Kc = 6.8175145385720384e-9\n", - "proton+OCC(O)=[Pt]<=>OCC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.6015120113778689e-47\n", - "Kc = 1.5610248204439706e57\n", - "HX+COC=O<=>COC(O)[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 224.3395816271696\n", - "Kc = 1.2483828443014824e-10\n", - "proton+COC(O)[Pt]<=>OC=[Pt]+CO-2\n", - "kf = 564390.3708916149\n", - "krev = 3.282828318007529e-12\n", - "Kc = 1.7192198806002883e17\n", - "vacantX+vacantX+COCO<=>HX+COC(O)[Pt]\n", - "kf = 6.183244140051347e-23\n", - "krev = 2731.92216309053\n", - "Kc = 2.2633310068601865e-26\n", - "O=CO+CH3X<=>COC(O)[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 8.503469161971292e7\n", - "Kc = 3.7620485485108396e-16\n", - "proton+COC=O.[Pt]<=>COC(O)[Pt]\n", - "kf = 7.49969185016536e-5\n", - "krev = 3658.0165064396892\n", - "Kc = 2.0502072193940793e-8\n", - "proton+COC(O)[Pt]<=>H2O+COC=[Pt]\n", - "kf = 5.10646151413012e-10\n", - "krev = 0.003546985366877098\n", - "Kc = 1.439662413557134e-7\n", - "vacantX+vacantX+CCOOC<=>COO[Pt]+CC[Pt]\n", - "kf = 1.4778859852656565e-10\n", - "krev = 2.404289853338368e13\n", - "Kc = 6.146871115450596e-24\n", - "vacantX+vacantX+CCOOC<=>CO[Pt]+CCO[Pt]\n", - "kf = 2.735304068777078e8\n", - "krev = 1.1929824589169815e-11\n", - "Kc = 2.2928284052560617e19\n", - "vacantX+vacantX+CCOOC<=>CH3X+CCOO[Pt]\n", - "kf = 1.542530561493995e-10\n", - "krev = 1.2789927244807063e12\n", - "Kc = 1.2060510837700736e-22\n", - "proton+COC(O)C#[Pt]<=>CX+COCO\n", - "kf = 0.03928313633337953\n", - "krev = 0.002914319669063903\n", - "Kc = 13.479350515448948\n", - "proton+COC(=O)[Pt]<=>COC(O)=[Pt]\n", - "kf = 6.005930457604258e-17\n", - "krev = 1.0085447542339825e12\n", - "Kc = 5.955046052632466e-29\n", - "proton+COC(O)=[Pt]<=>OC#[Pt]+CO-2\n", - "kf = 383854.3090963643\n", - "krev = 3.448448528690976e-34\n", - "Kc = 1.113121758677009e39\n", - "proton+COC(O)=[Pt]<=>H2O+COC#[Pt]\n", - "kf = 217922.49486435574\n", - "krev = 2.0340320286285714e-35\n", - "Kc = 1.0713818258372662e40\n", - "proton+COC(O)=[Pt]<=>COC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0120272229346644e-38\n", - "Kc = 2.4702892801149458e48\n", - "vacantX+vacantX+C=C=COO<=>OOC=[Pt]+C=C=[Pt]\n", - "kf = 1.9145907695639512e-44\n", - "krev = 1.1771971588384226e12\n", - "Kc = 1.626397715275781e-56\n", - "C=O+O=CC[Pt]<=>O=CCCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 0.0025285011306884937\n", - "Kc = 1.5664103465194285e-5\n", - "HX+O=CCC=O<=>O=CCCO[Pt]\n", - "kf = 5.113182125834635e-8\n", - "krev = 3.03538509820146e-7\n", - "Kc = 0.16845250142607343\n", - "proton+O=CCC=O.[Pt]<=>O=CCCO[Pt]\n", - "kf = 2.3901708430508703e8\n", - "krev = 41.103568870106145\n", - "Kc = 5.814995896351951e6\n", - "vacantX+vacantX+O=CCCO<=>HX+O=CCCO[Pt]\n", - "kf = 2.5157725911236352e-27\n", - "krev = 8837.406478086354\n", - "Kc = 2.84673178421957e-31\n", - "proton+O=CCCO[Pt]<=>OX+CCC=O\n", - "kf = 774927.4661784222\n", - "krev = 1.1978583087682196e-18\n", - "Kc = 6.469274875884902e23\n", - "CHOX+C=C<=>O=CCC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 0.4688595936220698\n", - "Kc = 1.7478623517301195e-7\n", - "proton+O=CCC[Pt]<=>CH2X+CC=O\n", - "kf = 0.0016740956920828355\n", - "krev = 4.373185000711893e-7\n", - "Kc = 3828.0925499614495\n", - "HX+C=CC=O<=>O=CCC[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 7.666152073113618e-12\n", - "Kc = 3780.924152337611\n", - "proton+O=CCC=[Pt]<=>O=CCC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3932958912707058e-30\n", - "Kc = 1.794306590339518e40\n", - "vacantX+vacantX+O=CCCO<=>HOX+O=CCC[Pt]\n", - "kf = 8.901266563864654e-15\n", - "krev = 1.309728963703428e15\n", - "Kc = 6.79626610584771e-30\n", - "vacantX+vacantX+CCC=O<=>HX+O=CCC[Pt]\n", - "kf = 1.6716561102658422e-25\n", - "krev = 524619.2678123232\n", - "Kc = 3.186417680076247e-31\n", - "vacantX+vacantX+CC=COO<=>OOC=[Pt]+CC=[Pt]\n", - "kf = 3.7147962989308654e-50\n", - "krev = 4.0636001726377395e18\n", - "Kc = 9.141638303749602e-69\n", - "proton+C=COOC#[Pt]<=>CX+C=COO\n", - "kf = 8.811176921711816e-67\n", - "krev = 2.5e10\n", - "Kc = 3.5244707686847265e-77\n", - "vacantX+C=CC=O<=>C=CC=O.[Pt]\n", - "kf = 365995.57053717994\n", - "krev = 1.0054621985249468\n", - "Kc = 364007.290452202\n", - "proton+C=CC(=O)[Pt]<=>C=CC=O.[Pt]\n", - "kf = 3.399604827397095e9\n", - "krev = 5.959510760846119e-12\n", - "Kc = 5.704503211458966e20\n", - "proton+O=CC=C[Pt]<=>C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.32808736312024e-27\n", - "Kc = 3.00188973889839e36\n", - "proton+C=CC=O.[Pt]<=>O=CCC[Pt]\n", - "kf = 5.197601136262071e7\n", - "krev = 74.26603000820454\n", - "Kc = 699862.5260684955\n", - "vacantX+vacantX+C=CC=O<=>HX+C=C([Pt])C=O\n", - "kf = 1.2784478936507186e-21\n", - "krev = 132.59733776930153\n", - "Kc = 9.641580405445367e-24\n", - "proton+C=C([Pt])C=O<=>C=O+C=C=[Pt]\n", - "kf = 2.4079500300331376e-13\n", - "krev = 0.010970404022735962\n", - "Kc = 2.194951092997765e-11\n", - "HX+C=C=C=O<=>C=C([Pt])C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.4992009477647154e-32\n", - "Kc = 1.1812081765045545e24\n", - "vacantX+vacantX+C=C(O)C=O<=>HOX+C=C([Pt])C=O\n", - "kf = 1.107119853181277e-14\n", - "krev = 2.5289157654010746e13\n", - "Kc = 4.377843929513773e-28\n", - "proton+C=C=C=O.[Pt]<=>C=C([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.305987527913534e-16\n", - "Kc = 1.0841342243780513e26\n", - "HX+C#CC=O<=>C=C([Pt])C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 1.683521621093348e-30\n", - "Kc = 1.753512730243651e22\n", - "proton+C=C([Pt])C=O<=>C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.827731832923639e-27\n", - "Kc = 2.5438219545478565e36\n", - "CHOX+C=C=O<=>C=C(C=O)O[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.906984656058423e-6\n", - "Kc = 0.017553122325364576\n", - "proton+C=C(C=O)O[Pt]<=>OX+C=CC=O\n", - "kf = 13.565263195704604\n", - "krev = 7.179044500174065e-6\n", - "Kc = 1.8895638821260543e6\n", - "vacantX+vacantX+C=C(O)C=O<=>HX+C=C(C=O)O[Pt]\n", - "kf = 8.336773502217888e-19\n", - "krev = 4.018028855986407\n", - "Kc = 2.0748416203624424e-19\n", - "vacantX+vacantX+COCOC<=>CH3X+COCO[Pt]\n", - "kf = 0.24675966205104702\n", - "krev = 5.277017405064255e15\n", - "Kc = 4.6761199198288865e-17\n", - "vacantX+vacantX+COCOC<=>CO[Pt]+COC[Pt]\n", - "kf = 4.1241018831024145e-7\n", - "krev = 7.782310155024181e12\n", - "Kc = 5.2993286067375974e-20\n", - "proton+C=CC=[Pt]<=>CHX+C=C\n", - "kf = 1.3385165927063483e6\n", - "krev = 9.028119675350497e-7\n", - "Kc = 1.4826083845132273e12\n", - "vacantX+vacantX+C=CC=O<=>OX+C=CC=[Pt]\n", - "kf = 1.438969400016978e-30\n", - "krev = 1.6093339940290013e17\n", - "Kc = 8.941396909254915e-48\n", - "proton+C=CC#[Pt]<=>C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.067052266556579e-6\n", - "Kc = 2.342903040792558e16\n", - "vacantX+CC(O)O<=>CC(O)O.[Pt]\n", - "kf = 347843.58123444836\n", - "krev = 178209.4487483253\n", - "Kc = 1.9518806868971765\n", - "proton+CC(O)O[Pt]<=>CC(O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.64203868551119e-24\n", - "Kc = 1.5224976257010135e34\n", - "vacantX+vacantX+COCCO<=>OC[Pt]+COC[Pt]\n", - "kf = 1.3358759661274015e-7\n", - "krev = 3.1165281946439875e14\n", - "Kc = 4.286423490161954e-22\n", - "vacantX+vacantX+COCCO<=>CO[Pt]+OCC[Pt]\n", - "kf = 6.192873660096324e-8\n", - "krev = 3.90827625278604e13\n", - "Kc = 1.584553716150872e-21\n", - "vacantX+vacantX+COCCO<=>CH3X+OCCO[Pt]\n", - "kf = 4.52195120819324e-12\n", - "krev = 5.920081591014324e14\n", - "Kc = 7.638325821483257e-27\n", - "proton+OC(O)C[Pt]<=>CH2X+OCO\n", - "kf = 2.252975678309519e-7\n", - "krev = 0.002613777215265548\n", - "Kc = 8.619616335895816e-5\n", - "HOX+C=CO<=>OC(O)C[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 6.095879365149742e-19\n", - "Kc = 5.364056293281289e10\n", - "HX+C=C(O)O<=>OC(O)C[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 1.7806643358524245e-19\n", - "Kc = 1.572793251160735e11\n", - "vacantX+vacantX+CC(O)O<=>HX+OC(O)C[Pt]\n", - "kf = 2.610914590914038e-25\n", - "krev = 48838.0104312493\n", - "Kc = 5.3460707507516085e-30\n", - "vacantX+vacantX+CCC(O)O<=>CH3X+OC(O)C[Pt]\n", - "kf = 2.73273606062798e-19\n", - "krev = 1.7143250273592365e15\n", - "Kc = 1.594059479396106e-34\n", - "proton+OC(O)C[Pt]<=>CC(O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0162407066861682e-27\n", - "Kc = 2.4600470966688416e37\n" - ] - } - ], - "source": [ - "for (i,rxn) in enumerate(inter.reactions)\n", - " str = getrxnstr(rxn)\n", - " kf = inter.kfs[i]\n", - " krev = inter.krevs[i]\n", - " Kc = kf/krev\n", - " println(str)\n", - " println(\"kf = $kf\")\n", - " println(\"krev = $krev\")\n", - " println(\"Kc = $Kc\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 78, - "id": "dd1b08a5", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "vacantX+CO2<=>CO2X\n", - "kf = 20654.615923781494\n", - "krev = 11189.298481041604\n", - "Kc = 1.8459259048971917\n", - "proton+CO2X<=>CHO2X\n", - "kf = 5.164749496653815e7\n", - "krev = 3.369038128826839e8\n", - "Kc = 0.1533004168893831\n", - "proton+CO2X<=>CO2HX\n", - "kf = 463658.8965294065\n", - "krev = 1.20318988446587e-5\n", - "Kc = 3.853580407511801e10\n", - "proton+CHO2X<=>CH2O2X\n", - "kf = 2.5e10\n", - "krev = 9.108706843764319e-26\n", - "Kc = 2.7446266993557504e35\n", - "proton+CO2HX<=>CH2O2X\n", - "kf = 1.9190551016885178e10\n", - "krev = 1.757621070775451e-14\n", - "Kc = 1.0918480289052538e24\n", - "proton+OCX<=>CHOX\n", - "kf = 2.5e10\n", - "krev = 2.604453583293511e-10\n", - "Kc = 9.59894242706594e19\n", - "proton+CHOX<=>CH2OX\n", - "kf = 1.7890196451453958e9\n", - "krev = 4.957912234830633e-11\n", - "Kc = 3.608413300616868e19\n", - "vacantX+vacantX+CO2<=>OX+OCX\n", - "kf = 3.0109478093923404e-24\n", - "krev = 3.037156297092479e15\n", - "Kc = 9.913707148607306e-40\n", - "OX+proton<=>HOX\n", - "kf = 2.5e10\n", - "krev = 4.7547181516587526e-14\n", - "Kc = 5.25793521352646e23\n", - "vacantX+C=O<=>CH2OX\n", - "kf = 500114.13488002896\n", - "krev = 399.6803280141717\n", - "Kc = 1251.2853393732605\n", - "proton+CHO2X<=>OX+C=O\n", - "kf = 7.971946163368602e-7\n", - "krev = 8.220582009654122e-5\n", - "Kc = 0.009697544716428197\n", - "HX+CO2<=>CHO2X\n", - "kf = 6.542996392927688e-8\n", - "krev = 15.579156394796986\n", - "Kc = 4.199839983064083e-9\n", - "HX+CO2<=>CO2HX\n", - "kf = 6.542996392927688e-8\n", - "krev = 6.197590078701277e-11\n", - "Kc = 1055.7323588427441\n", - "vacantX+vacantX+C=O<=>HX+CHOX\n", - "kf = 2.0718885766149262e-11\n", - "krev = 0.008867505326838887\n", - "Kc = 2.336495440655708e-9\n", - "vacantX+O=CO<=>CH2O2X\n", - "kf = 403943.82249737746\n", - "krev = 29.756334575496034\n", - "Kc = 13575.053119278344\n", - "vacantX+vacantX+O=CO<=>HOX+CHOX\n", - "kf = 8.486192390111145e-15\n", - "krev = 9.7037034735699e11\n", - "Kc = 8.745312975839684e-27\n", - "vacantX+vacantX+O=CO<=>HX+CHO2X\n", - "kf = 1.2668346793097018e-21\n", - "krev = 380.13410282264914\n", - "Kc = 3.332599390328158e-24\n", - "vacantX+vacantX+O=CO<=>HX+CO2HX\n", - "kf = 9.840171155787102e-15\n", - "krev = 0.011746228705195169\n", - "Kc = 8.377302539184302e-13\n", - "proton+CH2OX<=>CO[Pt]\n", - "kf = 4.612846333154699e7\n", - "krev = 90.4105198560361\n", - "Kc = 510211.23874742666\n", - "HX+C=O<=>CO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.180104845075902e-9\n", - "Kc = 9.475050217848336\n", - "proton+CO2HX<=>H2O+OCX\n", - "kf = 2.5e10\n", - "krev = 4.0258346788129556e-7\n", - "Kc = 6.20989235637749e16\n", - "vacantX+vacantX+H2O<=>HX+HOX\n", - "kf = 1.7047654949014593e-31\n", - "krev = 21441.30602897437\n", - "Kc = 7.950847269274322e-36\n", - "proton+CH2OX<=>OC[Pt]\n", - "kf = 1.2443063594454413e6\n", - "krev = 1.1005987164187474e-6\n", - "Kc = 1.1305722429827158e12\n", - "HX+C=O<=>OC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.886422105564557e-15\n", - "Kc = 2.099567387708916e7\n", - "vacantX+vacantX+O=CC=O<=>CHOX+CHOX\n", - "kf = 3.132095071630788e8\n", - "krev = 159.05427897483804\n", - "Kc = 1.9691988746346629e6\n", - "proton+CH2O2X<=>OC(O)[Pt]\n", - "kf = 1.9695177200694968e-5\n", - "krev = 3718.799864740736\n", - "Kc = 5.296111088803661e-9\n", - "HX+O=CO<=>OC(O)[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 29981.045237801853\n", - "Kc = 1.0670229661561413e-12\n", - "proton+CH2O2X<=>OCO[Pt]\n", - "kf = 1.3800914441571782e-5\n", - "krev = 3681.751563599994\n", - "Kc = 3.748464339097702e-9\n", - "HOX+C=O<=>OCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.962949149852605e-13\n", - "Kc = 201771.41789913058\n", - "HX+O=CO<=>OCO[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 42359.465576793365\n", - "Kc = 7.552140562327293e-13\n", - "vacantX+H2O<=>H2OX\n", - "kf = 4.842414926683719e6\n", - "krev = 2.0721934488233277e8\n", - "Kc = 0.023368546645263413\n", - "proton+HOX<=>H2OX\n", - "kf = 2.5e10\n", - "krev = 1.2623996335027457e-31\n", - "Kc = 1.9803554545269617e41\n", - "vacantX+vacantX+H2<=>HX+HX\n", - "kf = 3.8736093818093735e10\n", - "krev = 4.9917087254698525e28\n", - "Kc = 7.760086965901168e-19\n", - "proton+CHOX<=>OC=[Pt]\n", - "kf = 3.6460821201937575e9\n", - "krev = 3.454391742229775e10\n", - "Kc = 0.10554917890812951\n", - "vacantX+vacantX+O=CO<=>OX+OC=[Pt]\n", - "kf = 1.3995006080437096e-36\n", - "krev = 7.971831424002446e14\n", - "Kc = 1.755557203367275e-51\n", - "proton+OC=[Pt]<=>OC[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.468152848309303e-23\n", - "Kc = 3.8650910988497585e32\n", - "proton+OC(O)[Pt]<=>H2O+OC=[Pt]\n", - "kf = 6.989877198043828e9\n", - "krev = 6.424310280494338e-11\n", - "Kc = 1.0880354299303816e20\n", - "proton+O=CC(=O)[Pt]<=>OCX+C=O\n", - "kf = 2.302032083373261e7\n", - "krev = 2.5713202543754838e-9\n", - "Kc = 8.952724109165363e15\n", - "vacantX+vacantX+O=CC=O<=>HX+O=CC(=O)[Pt]\n", - "kf = 1.43713660093583e-9\n", - "krev = 0.00032277677938391324\n", - "Kc = 4.452416322137251e-6\n", - "proton+OCX<=>OC#[Pt]\n", - "kf = 26781.620683797883\n", - "krev = 1.0085447542339806e12\n", - "Kc = 2.6554717151981333e-8\n", - "proton+OC#[Pt]<=>OC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.552445879282663e-17\n", - "Kc = 3.815369170624406e26\n", - "vacantX+O=CC=O<=>O=CC=O.[Pt]\n", - "kf = 359723.7676387533\n", - "krev = 0.32068189796600394\n", - "Kc = 1.121746409511672e6\n", - "proton+O=CC(=O)[Pt]<=>O=CC=O.[Pt]\n", - "kf = 1.508798479649927e9\n", - "krev = 8.88806985342612e-11\n", - "Kc = 1.6975547048252826e19\n", - "vacantX+vacantX+OO<=>HOX+HOX\n", - "kf = 4.0912386971316826e8\n", - "krev = 1.7763617117679594e-6\n", - "Kc = 2.3031563166601894e14\n", - "OCX<=>vacantX+CO\n", - "kf = 2.010168305725754e-19\n", - "krev = 2.61760793808642e-25\n", - "Kc = 767940.9419866255\n", - "vacantX+vacantX+O2<=>OX+OX\n", - "kf = 1.0945721587141857e10\n", - "krev = 4.219325007995329e-16\n", - "Kc = 2.594187830138819e25\n", - "proton+HX<=>[H][H].[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.1949534688419614e-15\n", - "Kc = 2.0921316730623565e25\n", - "vacantX+H2<=>[H][H].[Pt]\n", - "kf = 2338.960705505517\n", - "krev = 9707.159813448116\n", - "Kc = 0.24095211683495363\n", - "CHOX+C=O<=>O=COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 7.563806299311394e-5\n", - "Kc = 0.0005236345532350701\n", - "proton+OO[Pt]<=>OX+H2O\n", - "kf = 17.257164508221003\n", - "krev = 6.236444643145301e-63\n", - "Kc = 2.767147869610126e63\n", - "vacantX+vacantX+OO<=>HX+OO[Pt]\n", - "kf = 4.980245005159166e-22\n", - "krev = 5.509834949091977\n", - "Kc = 9.038827934364735e-23\n", - "proton+OC#[Pt]<=>H2O+CX\n", - "kf = 3.276640102032806e-5\n", - "krev = 0.0009291230748795855\n", - "Kc = 0.03526594259277716\n", - "vacantX+vacantX+O=C=C=O<=>OCX+OCX\n", - "kf = 74.64023007210145\n", - "krev = 2.953439666185894e-39\n", - "Kc = 2.52723056870475e40\n", - "HX+O=C=C=O<=>O=CC(=O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 5.0006650398424424e-61\n", - "Kc = 1.1597065597154312e53\n", - "proton+OC=[Pt]<=>H2O+CHX\n", - "kf = 2.5e10\n", - "krev = 6.511063937864271e-5\n", - "Kc = 3.839618261865876e14\n", - "proton+CX<=>CHX\n", - "kf = 2.5e10\n", - "krev = 6.018259224258551e-33\n", - "Kc = 4.1540251206244773e42\n", - "H2+CX<=>CH2X\n", - "kf = 4.832014059685671\n", - "krev = 1.8278921581756875e-33\n", - "Kc = 2.643489681857502e33\n", - "vacantX+vacantX+C=O<=>OX+CH2X\n", - "kf = 4.5608316796485725e-28\n", - "krev = 3.884151005592286e17\n", - "Kc = 1.1742158513101117e-45\n", - "proton+OC[Pt]<=>H2O+CH2X\n", - "kf = 7206.229958253159\n", - "krev = 0.0019484451144913943\n", - "Kc = 3.6984516036184127e6\n", - "proton+O=COC[Pt]<=>CH2X+O=CO\n", - "kf = 1981.2472905766488\n", - "krev = 1.4695324127813272e-5\n", - "Kc = 1.3482161219069803e8\n", - "proton+CHX<=>CH2X\n", - "kf = 2.5e10\n", - "krev = 6.715036577093663e-15\n", - "Kc = 3.722987911231938e24\n", - "proton+O=COC#[Pt]<=>CX+O=CO\n", - "kf = 6.185088018779624e7\n", - "krev = 3.741277098492221e-23\n", - "Kc = 1.6532023306352497e30\n", - "vacantX+vacantX+C=C=O<=>OCX+CH2X\n", - "kf = 2.4823885573387985e-14\n", - "krev = 9.351132511056354e15\n", - "Kc = 2.6546394828687704e-30\n", - "CHOX+C=O<=>O=CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.4949222028864902e7\n", - "Kc = 2.6494156850764662e-15\n", - "HX+O=CC=O<=>O=CCO[Pt]\n", - "kf = 5.6976884072695144e-8\n", - "krev = 2.551666729065355e-8\n", - "Kc = 2.23292812590636\n", - "proton+O=CC=O.[Pt]<=>O=CCO[Pt]\n", - "kf = 957581.7759153218\n", - "krev = 7139.55197608848\n", - "Kc = 134.12351070801344\n", - "O=O.[Pt]+proton<=>OO[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.545950245153839e-28\n", - "Kc = 7.050296330064662e37\n", - "proton+O=CC#[Pt]<=>CX+C=O\n", - "kf = 5.731900626219973e-17\n", - "krev = 16.634660991475336\n", - "Kc = 3.4457574032662074e-18\n", - "proton+CO2HX<=>OC(O)=[Pt]\n", - "kf = 8.313674902647437e-22\n", - "krev = 1.0085447542339753e12\n", - "Kc = 8.243238455949296e-34\n", - "proton+OC(O)=[Pt]<=>OC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.563843227039955e-39\n", - "Kc = 7.014898918762039e48\n", - "proton+OC(O)=[Pt]<=>H2O+OC#[Pt]\n", - "kf = 58948.65819613129\n", - "krev = 2.9467686111082447e-38\n", - "Kc = 2.0004508658710534e42\n", - "proton+O=C(O)C#[Pt]<=>CX+O=CO\n", - "kf = 1.2163309452954808e-9\n", - "krev = 0.00037997676558546045\n", - "Kc = 3.201066632117316e-6\n", - "proton+O=C=C=O.[Pt]<=>O=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.649884885591097e-48\n", - "Kc = 9.434372087609898e57\n", - "vacantX+O=C=C=O<=>O=C=C=O.[Pt]\n", - "kf = 366139.2749661925\n", - "krev = 442.06521987276346\n", - "Kc = 828.2471873077366\n", - "HOX+C=O<=>OOC[Pt]\n", - "kf = 1.5395975576095126e-29\n", - "krev = 2.622153295712258e16\n", - "Kc = 5.871500953537159e-46\n", - "proton+OOC[Pt]<=>OO+CH2X\n", - "kf = 15.535579749933543\n", - "krev = 3.4028033042152773e-9\n", - "Kc = 4.5655238816444645e9\n", - "vacantX+vacantX+O=C=CO<=>OCX+OC=[Pt]\n", - "kf = 73.33238091278024\n", - "krev = 14511.198914062346\n", - "Kc = 0.005053502563576338\n", - "vacantX+C=C=O<=>C=C=O.[Pt]\n", - "kf = 422670.5724931744\n", - "krev = 9.80980243728561e-11\n", - "Kc = 4.3086552985681545e15\n", - "proton+CO[Pt]<=>OX+CH4\n", - "kf = 541698.6744405399\n", - "krev = 1.9995135619129721e-19\n", - "Kc = 2.7091522896313173e24\n", - "HX+C=C=O<=>CC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.3310785577331067e-33\n", - "Kc = 2.514767798332947e25\n", - "proton+C=C=O.[Pt]<=>CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.357099551204697e-8\n", - "Kc = 3.9326110592781875e17\n", - "proton+CC(=O)[Pt]<=>OCX+CH4\n", - "kf = 1.0030005882936613e8\n", - "krev = 4.3463683404291294e-8\n", - "Kc = 2.3076750743003805e15\n", - "vacantX+vacantX+COC=O<=>CHOX+CO[Pt]\n", - "kf = 5.858305523872122e-8\n", - "krev = 9.372228401924443e12\n", - "Kc = 6.250707166578664e-21\n", - "vacantX+vacantX+COC=O<=>HX+O=COC[Pt]\n", - "kf = 8.724708246600757e-23\n", - "krev = 252.56605644619947\n", - "Kc = 3.454426287270814e-25\n", - "vacantX+vacantX+COC=O<=>HX+COC(=O)[Pt]\n", - "kf = 7.165711269221808e-16\n", - "krev = 0.1859922027934253\n", - "Kc = 3.852694447186316e-15\n", - "proton+O=COCC#[Pt]<=>CX+COC=O\n", - "kf = 0.8132675549526747\n", - "krev = 2.165706403032533e-5\n", - "Kc = 37552.06863746147\n", - "HOX+C=C=O<=>O=C([Pt])CO\n", - "kf = 3.3473534940386794e-8\n", - "krev = 9.042590347389556e-30\n", - "Kc = 3.70176394754519e21\n", - "HX+O=C=CO<=>O=C([Pt])CO\n", - "kf = 2.8488442036348548e-8\n", - "krev = 1.614840618256874e-45\n", - "Kc = 1.7641643214981894e37\n", - "vacantX+vacantX+COO<=>HOX+CO[Pt]\n", - "kf = 3.442529358831723e8\n", - "krev = 2.6586367586035048e-11\n", - "Kc = 1.294847574679578e19\n", - "vacantX+vacantX+COO<=>HX+OOC[Pt]\n", - "kf = 1.3336211820914592e-23\n", - "krev = 16620.58178963317\n", - "Kc = 8.023913957833202e-28\n", - "CHOX+C=C=O<=>O=CCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 2.6714659015861004e-16\n", - "Kc = 1.2530025152300434e8\n", - "vacantX+vacantX+CO-2<=>HX+CO[Pt]\n", - "kf = 3.6896065237788346e-26\n", - "krev = 1200.2597905170037\n", - "Kc = 3.0740066050113714e-29\n", - "vacantX+vacantX+CO-2<=>HX+OC[Pt]\n", - "kf = 1.1691860289045307e-22\n", - "krev = 1.716447494000275\n", - "Kc = 6.811662069427353e-23\n", - "proton+OCO[Pt]<=>OX+CO-2\n", - "kf = 6.4866612293733e7\n", - "krev = 4.917786339628338e-9\n", - "Kc = 1.319020547335029e16\n", - "proton+COC(=O)[Pt]<=>OCX+CO-2\n", - "kf = 5.096893185474306e9\n", - "krev = 2.041829224680708e-9\n", - "Kc = 2.49623872744369e18\n", - "proton+O=C([Pt])CO<=>OCX+CO-2\n", - "kf = 1.9762803815844387e7\n", - "krev = 1.2158736968776066e-8\n", - "Kc = 1.6253994034574272e15\n", - "proton+OCC#[Pt]<=>CX+CO-2\n", - "kf = 1.8515947729382765e-10\n", - "krev = 0.16959607683462066\n", - "Kc = 1.091767455649245e-9\n", - "vacantX+vacantX+COOC<=>CO[Pt]+CO[Pt]\n", - "kf = 3.028654941635431e8\n", - "krev = 1.0392777770118965e-11\n", - "Kc = 2.914191959673513e19\n", - "vacantX+vacantX+C=C=O<=>HX+O=C=C[Pt]\n", - "kf = 3.6584912239485734e-16\n", - "krev = 0.32395775785233605\n", - "Kc = 1.1293111942132156e-15\n", - "vacantX+vacantX+O=C=CO<=>HOX+O=C=C[Pt]\n", - "kf = 3.132095071630788e8\n", - "krev = 5.819571251914923e7\n", - "Kc = 5.382003133994065\n", - "proton+O=C=C[Pt]<=>C=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.724942318590629e-29\n", - "Kc = 2.570709334924167e38\n", - "vacantX+vacantX+O=CCO<=>CHOX+OC[Pt]\n", - "kf = 9001.813049524091\n", - "krev = 8.180569891408677e12\n", - "Kc = 1.1003894800749632e-9\n", - "vacantX+vacantX+O=CCO<=>HX+O=CCO[Pt]\n", - "kf = 3.705974451661604e-28\n", - "krev = 2668.9209237076484\n", - "Kc = 1.3885665996103351e-31\n", - "vacantX+vacantX+O=CCO<=>HX+O=C([Pt])CO\n", - "kf = 1.2718474027465153e-10\n", - "krev = 0.0002705673832361486\n", - "Kc = 4.7006678614933393e-7\n", - "proton+O=CCOC#[Pt]<=>CX+O=CCO\n", - "kf = 3.8625888100004036e-23\n", - "krev = 1.5059302822169408e-12\n", - "Kc = 2.564918745318097e-11\n", - "proton+COC#[Pt]<=>CX+CO-2\n", - "kf = 3.5797175052253717e-22\n", - "krev = 9.770006712968626e-20\n", - "Kc = 0.0036639867406372244\n", - "proton+O=CC(=O)C#[Pt]<=>CX+O=CC=O\n", - "kf = 5.9931479699583235e-12\n", - "krev = 0.0016900056192162703\n", - "Kc = 3.546229611199523e-9\n", - "vacantX+vacantX+OCO<=>HOX+OC[Pt]\n", - "kf = 1.653107374238179e-12\n", - "krev = 3.492310477620836e11\n", - "Kc = 4.7335635958815765e-24\n", - "vacantX+vacantX+OCO<=>HX+OC(O)[Pt]\n", - "kf = 4.0412190145177725e-23\n", - "krev = 628.7683045605482\n", - "Kc = 6.427198993979533e-26\n", - "vacantX+vacantX+OCO<=>HX+OCO[Pt]\n", - "kf = 1.1281154422531313e-23\n", - "krev = 247.99076039714222\n", - "Kc = 4.5490220702034325e-26\n", - "proton+OC(O)C#[Pt]<=>CX+OCO\n", - "kf = 0.005562206988621036\n", - "krev = 0.025459246171787766\n", - "Kc = 0.21847492856189518\n", - "proton+OCOC#[Pt]<=>CX+OCO\n", - "kf = 2.2993090387825977e-18\n", - "krev = 1.7767009384663083e-12\n", - "Kc = 1.2941452266960681e-6\n", - "proton+O=COC=[Pt]<=>O=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.03525663068036e-45\n", - "Kc = 2.4148601669491608e55\n", - "proton+O=COC=[Pt]<=>CHX+O=CO\n", - "kf = 407721.49317133107\n", - "krev = 4.66233771243883e-34\n", - "Kc = 8.745001291595743e38\n", - "proton+O=COC#[Pt]<=>O=COC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.1834993039887084e-24\n", - "Kc = 7.852993706854812e33\n", - "proton+O=C=CC#[Pt]<=>CX+C=C=O\n", - "kf = 1.255896512556004e-15\n", - "krev = 0.016900821436021087\n", - "Kc = 7.430979123176135e-14\n", - "vacantX+vacantX+COCO<=>CO[Pt]+OC[Pt]\n", - "kf = 3.0636862331912886e-9\n", - "krev = 3.008499680951675e11\n", - "Kc = 1.0183435459837431e-20\n", - "proton+CC#[Pt]<=>CX+CH4\n", - "kf = 3.172314510568854e-8\n", - "krev = 0.363285670785801\n", - "Kc = 8.732286367659409e-8\n", - "HX+O=C=C=O<=>O=C=CO[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.1302052975227224e-55\n", - "Kc = 2.7224155607861307e47\n", - "proton+O=C=CO[Pt]<=>OX+C=C=O\n", - "kf = 0.047578794564636824\n", - "krev = 2.8204743128358057e-8\n", - "Kc = 1.6869075654441754e6\n", - "proton+O=C=C=O.[Pt]<=>O=C=CO[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 2.257619247094878e-42\n", - "Kc = 2.2147224366704162e52\n", - "vacantX+vacantX+O=C=CO<=>HX+O=C=CO[Pt]\n", - "kf = 0.0007071288662616175\n", - "krev = 2.8988454126647536e-5\n", - "Kc = 24.393465866522067\n", - "vacantX+vacantX+OCCO<=>OC[Pt]+OC[Pt]\n", - "kf = 2.961131444342359e-9\n", - "krev = 1.299206322752899e13\n", - "Kc = 2.2791849088819035e-22\n", - "proton+COC(=O)C#[Pt]<=>CX+COC=O\n", - "kf = 2.520547604265173e-10\n", - "krev = 3.828537658551766e-5\n", - "Kc = 6.583577932517004e-6\n", - "proton+O=C=CC(=O)[Pt]<=>OCX+C=C=O\n", - "kf = 2.14881300259784e7\n", - "krev = 1.9623010758881652e-11\n", - "Kc = 1.0950475587061772e18\n", - "vacantX+vacantX+OC=CO<=>OC=[Pt]+OC=[Pt]\n", - "kf = 1.351949923589269e-23\n", - "krev = 7.975137957191956e11\n", - "Kc = 1.6952056890377485e-35\n", - "vacantX+OX+CH4<=>HOX+CH3X\n", - "kf = 1181.9069662995785\n", - "krev = 1.0235810933777192e20\n", - "Kc = 1.1546783874244874e-17\n", - "vacantX+HOX+CH4<=>H2OX+CH3X\n", - "kf = 5.28370763875636e9\n", - "krev = 1.2149259925984929e9\n", - "Kc = 4.348995470461149\n", - "HX+CH3X<=>vacantX+vacantX+CH4\n", - "kf = 5.733311120080377e8\n", - "krev = 8.483521653048543e-25\n", - "Kc = 6.758173497465076e32\n", - "proton+CH2X<=>CH3X\n", - "kf = 2.5e10\n", - "krev = 7.728626954425352e-28\n", - "Kc = 3.2347272222377345e37\n", - "CO2+CH3X<=>COC(=O)[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.00447183609125585\n", - "Kc = 1.463156578060128e-5\n", - "vacantX+vacantX+COC=O<=>CHO2X+CH3X\n", - "kf = 0.05589950368763065\n", - "krev = 5.054770535995559e16\n", - "Kc = 1.1058761874463802e-18\n", - "vacantX+vacantX+COO<=>OO[Pt]+CH3X\n", - "kf = 9.385776922831516e-7\n", - "krev = 3.9782610412247473e11\n", - "Kc = 2.359266228528335e-18\n", - "vacantX+vacantX+CO-2<=>HOX+CH3X\n", - "kf = 9.872876935778847e-16\n", - "krev = 6.917821124819518e13\n", - "Kc = 1.427165686657795e-29\n", - "vacantX+vacantX+COCO<=>CH3X+OCO[Pt]\n", - "kf = 3.9072411322938125e-9\n", - "krev = 8.599564777209447e13\n", - "Kc = 4.543533578174534e-23\n", - "O=O+HX<=>OO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 8.854082166234876e-41\n", - "Kc = 8.666474551788235e32\n", - "vacantX+O=O<=>O=O.[Pt]\n", - "kf = 484458.3574999593\n", - "krev = 584.920039726471\n", - "Kc = 828.247152767255\n", - "vacantX+O=C=CO<=>O=C=CO.[Pt]\n", - "kf = 359723.7676387533\n", - "krev = 0.4900054095759742\n", - "Kc = 734122.0333670193\n", - "proton+O=C=CO.[Pt]<=>O=C([Pt])CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.543989619636675e-29\n", - "Kc = 1.6191818702694958e39\n", - "proton+O=C=CO[Pt]<=>O=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.012328788524416852\n", - "Kc = 2.0277742578265605e12\n", - "vacantX+vacantX+O=C=C=O<=>OX+O=C=C=[Pt]\n", - "kf = 149.2804601441562\n", - "krev = 1.2008902564793325e-12\n", - "Kc = 1.2430816166483347e14\n", - "proton+O=C=C=[Pt]<=>O=CC#[Pt]\n", - "kf = 2.5e10\n", - "krev = 728325.7738813914\n", - "Kc = 34325.299057824195\n", - "proton+O=C=C=[Pt]<=>O=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.992117420427329e-15\n", - "Kc = 4.1721478812771864e24\n", - "vacantX+vacantX+C=CO<=>CH2X+OC=[Pt]\n", - "kf = 3.7510196251812924e-36\n", - "krev = 6.624293894020312e13\n", - "Kc = 5.662519938264367e-50\n", - "proton+O=C(C#[Pt])CO<=>CX+O=CCO\n", - "kf = 2.1150580786972557e-17\n", - "krev = 1.2236788896896236\n", - "Kc = 1.728442074565594e-17\n", - "vacantX+vacantX+C=C<=>CH2X+CH2X\n", - "kf = 9.387035392806688e-46\n", - "krev = 5.259242712748897e15\n", - "Kc = 1.784864457776713e-61\n", - "proton+O=COC[Pt]<=>COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.124037165592671e-28\n", - "Kc = 8.002465615756261e37\n", - "proton+COC(=O)[Pt]<=>COC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.484214060387906e-18\n", - "Kc = 7.175219308200797e27\n", - "vacantX+COC=O<=>COC=O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.8619443782965007\n", - "Kc = 410274.8449265323\n", - "HX+O=C=C=C=O<=>O=C=CC(=O)[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 3.561089909521239e-25\n", - "Kc = 1.4777843564830474e17\n", - "vacantX+vacantX+O=C=C=C=O<=>OCX+O=C=C=[Pt]\n", - "kf = 135.4631249389026\n", - "krev = 3.092595390223456e6\n", - "Kc = 4.3802407960361956e-5\n", - "CH3X+O=C=C=O<=>CC(=O)C(=O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 3.5093718907449027e-71\n", - "Kc = 1.6525190917893694e63\n", - "proton+OOC#[Pt]<=>OO+CX\n", - "kf = 3.959382254258936e-52\n", - "krev = 4.505410128222608e6\n", - "Kc = 8.78806177812034e-59\n", - "proton+O=CC[Pt]<=>CH2X+C=O\n", - "kf = 9.847553463617368e-13\n", - "krev = 0.8193686811731042\n", - "Kc = 1.2018464568987987e-12\n", - "HX+C=C=O<=>O=CC[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 3.6888123831707493e-19\n", - "Kc = 9.074339235332521e10\n", - "proton+C=C=O.[Pt]<=>O=CC[Pt]\n", - "kf = 4.477750650627013e6\n", - "krev = 3155.453532604055\n", - "Kc = 1419.0513675324908\n", - "vacantX+vacantX+O=CCO<=>HOX+O=CC[Pt]\n", - "kf = 3.3834985622063113e-5\n", - "krev = 2.9362980773683545e12\n", - "Kc = 1.1523007790948657e-17\n", - "vacantX+vacantX+O=CC=O<=>OX+O=CC=[Pt]\n", - "kf = 6.170227811474367e-18\n", - "krev = 2.1467268001769245e15\n", - "Kc = 2.874249210922341e-33\n", - "proton+O=CC=[Pt]<=>CHX+C=O\n", - "kf = 0.3518802014338951\n", - "krev = 0.0019581841163396926\n", - "Kc = 179.69719930710195\n", - "proton+O=CC#[Pt]<=>O=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.1385387905668107e-13\n", - "Kc = 7.9654902068249e22\n", - "proton+O=C=C[Pt]<=>O=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.814809579170971e7\n", - "Kc = 655.3407052478085\n", - "proton+O=CC=[Pt]<=>O=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.4911345025101916e-29\n", - "Kc = 5.566522219725765e38\n", - "proton+O=CCO[Pt]<=>OX+CC=O\n", - "kf = 108844.3774855493\n", - "krev = 6.551243603618761e-23\n", - "Kc = 1.6614307766761425e27\n", - "vacantX+vacantX+CC=O<=>HX+CC(=O)[Pt]\n", - "kf = 4.3209399543319175e-11\n", - "krev = 0.0003615296985530135\n", - "Kc = 1.195182573278502e-7\n", - "proton+O=CCC(=O)[Pt]<=>OCX+CC=O\n", - "kf = 7.362850070977087e6\n", - "krev = 9.270601965584902e-14\n", - "Kc = 7.94214884676321e19\n", - "proton+O=CCC#[Pt]<=>CX+CC=O\n", - "kf = 0.11748380587607415\n", - "krev = 6.387097627333538e-5\n", - "Kc = 1839.3926745898334\n", - "vacantX+vacantX+CC=O<=>CHOX+CH3X\n", - "kf = 6.063283190982672e-6\n", - "krev = 7.026751658283665e14\n", - "Kc = 8.628856526948432e-21\n", - "proton+CC(=O)C#[Pt]<=>CX+CC=O\n", - "kf = 8.247683071468342e-18\n", - "krev = 0.06355423283679383\n", - "Kc = 1.2977393799478706e-16\n", - "proton+CC(=O)C(=O)[Pt]<=>OCX+CC=O\n", - "kf = 3.422758172577326e7\n", - "krev = 2.0119060511296993e-10\n", - "Kc = 1.7012514926606157e17\n", - "vacantX+vacantX+CC=O<=>HX+O=CC[Pt]\n", - "kf = 3.2094062904328744e-20\n", - "krev = 74.41720028073364\n", - "Kc = 4.312721089110603e-22\n", - "vacantX+CH4<=>C.[Pt]\n", - "kf = 11983.404197457203\n", - "krev = 27576.843954134933\n", - "Kc = 0.4345458899280744\n", - "proton+CH3X<=>C.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.2634270430964172e-30\n", - "Kc = 1.9787450440137642e40\n", - "HX+O=C=CC=O<=>O=CCC(=O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 3.8194581898791103e-32\n", - "Kc = 6.789235995427004e23\n", - "vacantX+vacantX+O=C=CC=O<=>CHOX+O=C=C[Pt]\n", - "kf = 2.850945414803626e8\n", - "krev = 4.6591458607721776e7\n", - "Kc = 6.119030182779314\n", - "vacantX+vacantX+O=C=CC=O<=>HX+O=C=CC(=O)[Pt]\n", - "kf = 1.1776167531898308e-10\n", - "krev = 0.0005032011998508361\n", - "Kc = 2.3402502886298994e-7\n", - "vacantX+vacantX+O=C=CC=O<=>OCX+O=CC=[Pt]\n", - "kf = 0.006845452357086415\n", - "krev = 1.638610749190394e14\n", - "Kc = 4.177595173514284e-17\n", - "vacantX+vacantX+C=C(O)O<=>CH2X+OC(O)=[Pt]\n", - "kf = 1.3631835715271243e-51\n", - "krev = 1.0974745099569602e16\n", - "Kc = 1.242109551665655e-67\n", - "proton+O=C=CC=O.[Pt]<=>O=CCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.130402878837127e-16\n", - "Kc = 4.078035407151288e25\n", - "proton+O=C=CC(=O)[Pt]<=>O=C=CC=O.[Pt]\n", - "kf = 2.964275004938465e9\n", - "krev = 9.178277268525813e-12\n", - "Kc = 3.229663822756335e20\n", - "vacantX+O=C=CC=O<=>O=C=CC=O.[Pt]\n", - "kf = 327433.4917974331\n", - "krev = 0.29189612518083846\n", - "Kc = 1.1217466199476891e6\n", - "vacantX+vacantX+CC(=O)O<=>HOX+CC(=O)[Pt]\n", - "kf = 3.661873055903852e-12\n", - "krev = 2.1682718089028445e11\n", - "Kc = 1.6888441019563762e-23\n", - "vacantX+vacantX+CC(=O)O<=>CO2HX+CH3X\n", - "kf = 1.1977509649486271e-8\n", - "krev = 1.0254845667743408e14\n", - "Kc = 1.1679853639496008e-22\n", - "CO2+CH3X<=>CC(=O)O[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 3.3286101924403974e-7\n", - "Kc = 0.19656841788766613\n", - "proton+CC(=O)O[Pt]<=>OX+CC=O\n", - "kf = 6.638543952734307e-6\n", - "krev = 1.1832604608796647e-7\n", - "Kc = 56.10382643732599\n", - "vacantX+vacantX+CC(=O)O<=>HX+CC(=O)O[Pt]\n", - "kf = 2.4753542791841756e-22\n", - "krev = 11382.562807978633\n", - "Kc = 2.1746897609465158e-26\n", - "proton+CC(=O)OC#[Pt]<=>CX+CC(=O)O\n", - "kf = 3.5372794201475537e8\n", - "krev = 2.288049006228874e-19\n", - "Kc = 1.5459806195224992e27\n", - "vacantX+vacantX+CC(=O)C=O<=>CHOX+CC(=O)[Pt]\n", - "kf = 2.810784197367395e8\n", - "krev = 8.682228189641076\n", - "Kc = 3.237399589106622e7\n", - "vacantX+vacantX+CC(=O)C=O<=>CH3X+O=CC(=O)[Pt]\n", - "kf = 0.010756441693245073\n", - "krev = 2.0353876594794328e15\n", - "Kc = 5.284714016589902e-18\n", - "vacantX+vacantX+CC(=O)C=O<=>HX+CC(=O)C(=O)[Pt]\n", - "kf = 2.426386880233808e-11\n", - "krev = 0.0003222108693910823\n", - "Kc = 7.530431499158364e-8\n", - "proton+O=C=C([Pt])C=O<=>C=O+O=C=C=[Pt]\n", - "kf = 13308.622034460761\n", - "krev = 4.6234228919871786e-9\n", - "Kc = 2.8785214645897607e12\n", - "HX+O=C=C=C=O<=>O=C=C([Pt])C=O\n", - "kf = 5.262522960320117e-8\n", - "krev = 8.417963556232881e-20\n", - "Kc = 6.251539253129229e11\n", - "vacantX+vacantX+O=C=CC=O<=>HX+O=C=C([Pt])C=O\n", - "kf = 3.109950102720783e-13\n", - "krev = 0.31413419650430946\n", - "Kc = 9.900068624582613e-13\n", - "proton+O=C=C([Pt])C=O<=>O=C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.274602487927107e-16\n", - "Kc = 7.6345144463093386e25\n", - "proton+O=C=COC#[Pt]<=>CX+O=C=CO\n", - "kf = 3.333143073629419e-24\n", - "krev = 2.9895559923107984e-13\n", - "Kc = 1.1149291340260339e-11\n", - "vacantX+vacantX+COC(C)=O<=>CO[Pt]+CC(=O)[Pt]\n", - "kf = 6.614441053978493e-6\n", - "krev = 7.629970776987544e11\n", - "Kc = 8.669025409544227e-18\n", - "vacantX+vacantX+COC(C)=O<=>CH3X+COC(=O)[Pt]\n", - "kf = 1.5563360867242215e-10\n", - "krev = 4.0343976517667425e14\n", - "Kc = 3.857666549162974e-25\n", - "vacantX+vacantX+COC(C)=O<=>CH3X+CC(=O)O[Pt]\n", - "kf = 0.0003463783354588583\n", - "krev = 6.683486846094463e16\n", - "Kc = 5.182599194629471e-21\n", - "vacantX+vacantX+COO<=>HX+COO[Pt]\n", - "kf = 1.175900379595729e-21\n", - "krev = 0.27982743013843664\n", - "Kc = 4.2022341377111815e-21\n", - "proton+COO[Pt]<=>OX+CO-2\n", - "kf = 129.78074174016686\n", - "krev = 1.499485133709293e-58\n", - "Kc = 8.65502023478731e59\n", - "vacantX+vacantX+COOC<=>CH3X+COO[Pt]\n", - "kf = 1.8186835430204133e-8\n", - "krev = 4.141977957602716e12\n", - "Kc = 4.39085760869917e-21\n", - "O=O+CH3X<=>COO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 4.970959816815508e-38\n", - "Kc = 1.543639067721808e30\n", - "proton+CO[Pt]<=>CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.487564815762018e-25\n", - "Kc = 1.0049989387851077e35\n", - "proton+OC[Pt]<=>CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.512171272873819e-19\n", - "Kc = 4.535417853038886e28\n", - "vacantX+CO-2<=>CO.[Pt]\n", - "kf = 484125.61468448705\n", - "krev = 1.0558750276780043e7\n", - "Kc = 0.04585065485913965\n", - "vacantX+vacantX+CC(=O)CO<=>OC[Pt]+CC(=O)[Pt]\n", - "kf = 4.324183911493771e7\n", - "krev = 7.8667392573421875e12\n", - "Kc = 5.496793232924203e-6\n", - "vacantX+vacantX+CC(=O)CO<=>CH3X+O=C([Pt])CO\n", - "kf = 0.43146252134138535\n", - "krev = 2.5450806210309695e15\n", - "Kc = 1.695280368629765e-16\n", - "HX+O=C=C=O<=>O=C=C(O)[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 7.390785994602033e-44\n", - "Kc = 7.846667531546056e35\n", - "proton+O=C=C=O.[Pt]<=>O=C=C(O)[Pt]\n", - "kf = 5.0e10\n", - "krev = 7.832851008293297e-31\n", - "Kc = 6.383371769367348e40\n", - "vacantX+vacantX+O=C=CO<=>HX+O=C=C(O)[Pt]\n", - "kf = 2.8707175642480555e-12\n", - "krev = 0.04083063397693327\n", - "Kc = 7.030793511239207e-11\n", - "proton+O=C=C(O)[Pt]<=>O=C=CO.[Pt]\n", - "kf = 1.7351014576291664e10\n", - "krev = 2.4662443446341767e-14\n", - "Kc = 7.03539964077054e23\n", - "proton+O=C=C(O)[Pt]<=>H2O+O=C=C=[Pt]\n", - "kf = 1.2324712433709262e6\n", - "krev = 1.176415080398485e-31\n", - "Kc = 1.0476499867321094e37\n", - "vacantX+vacantX+O=CCC=O<=>HX+O=CCC(=O)[Pt]\n", - "kf = 3.286584099620913e-11\n", - "krev = 0.0009472638388816695\n", - "Kc = 3.469555117295539e-8\n", - "vacantX+vacantX+O=CCC=O<=>CHOX+O=CC[Pt]\n", - "kf = 5.621568394735124e8\n", - "krev = 2.2372815421494465e13\n", - "Kc = 2.51267812692642e-5\n", - "proton+O=C=C(O)C#[Pt]<=>CX+O=C=CO\n", - "kf = 3.0900625689798e-31\n", - "krev = 97363.75326657317\n", - "Kc = 3.1737299203323514e-36\n", - "proton+COOC#[Pt]<=>CX+COO\n", - "kf = 1.3396315820930446e-65\n", - "krev = 2.5e10\n", - "Kc = 5.3585263283721787e-76\n", - "vacantX+vacantX+COC=C=O<=>CO[Pt]+O=C=C[Pt]\n", - "kf = 1.4053920986837533e8\n", - "krev = 2.5815645207863396e8\n", - "Kc = 0.5443954963619013\n", - "vacantX+vacantX+COC=C=O<=>CH3X+O=C=CO[Pt]\n", - "kf = 1.4053920986837533e8\n", - "krev = 1.2268284001067661e8\n", - "Kc = 1.1455490421981163\n", - "HX+O=CC=O<=>O=CC(O)[Pt]\n", - "kf = 5.6976884072695144e-8\n", - "krev = 1.248882373151946e-25\n", - "Kc = 4.562229822244678e17\n", - "proton+O=CC(O)[Pt]<=>C=O+OC=[Pt]\n", - "kf = 1.4979350850413518e-9\n", - "krev = 7.682289195925664e-6\n", - "Kc = 0.00019498551106820976\n", - "proton+O=CC=O.[Pt]<=>O=CC(O)[Pt]\n", - "kf = 3.43386635836783e8\n", - "krev = 1.2530721027853126e-11\n", - "Kc = 2.7403581571523903e19\n", - "HX+O=C=CO<=>O=CC(O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 2.6755933088589045e-38\n", - "Kc = 1.0647523277182356e30\n", - "vacantX+vacantX+O=CCO<=>HX+O=CC(O)[Pt]\n", - "kf = 5.743984385098034e-15\n", - "krev = 0.20246227896672986\n", - "Kc = 2.8370639777506056e-14\n", - "proton+O=C=CO.[Pt]<=>O=CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.5582018736355307e-22\n", - "Kc = 9.77248912904274e31\n", - "proton+O=CC(O)[Pt]<=>H2O+O=CC=[Pt]\n", - "kf = 459.6019775429135\n", - "krev = 1.1031455244918085e-6\n", - "Kc = 4.166286018833649e8\n", - "proton+O=CC(O)C#[Pt]<=>CX+O=CCO\n", - "kf = 0.2097860124056399\n", - "krev = 0.0024507024511013467\n", - "Kc = 85.60240036947854\n", - "vacantX+vacantX+O=C=CCO<=>OC[Pt]+O=C=C[Pt]\n", - "kf = 4067.906517801298\n", - "krev = 9.581534474143486e11\n", - "Kc = 4.245568941779481e-9\n", - "proton+O=CC(=O)[Pt]<=>O=CC(O)=[Pt]\n", - "kf = 1.4625119078213113e-5\n", - "krev = 1.0085447542339824e12\n", - "Kc = 1.4501209804339615e-17\n", - "proton+O=CC(O)=[Pt]<=>OC#[Pt]+C=O\n", - "kf = 345367.8200620121\n", - "krev = 2.1066346546856475e-20\n", - "Kc = 1.6394291211996983e25\n", - "proton+O=CC(O)=[Pt]<=>H2O+O=CC#[Pt]\n", - "kf = 109541.91076063467\n", - "krev = 6.52855201530546e-37\n", - "Kc = 1.6778898368861259e41\n", - "proton+O=C=C(O)[Pt]<=>O=CC(O)=[Pt]\n", - "kf = 266253.7431100425\n", - "krev = 124230.61178859882\n", - "Kc = 2.1432217009695007\n", - "proton+O=CC(O)=[Pt]<=>O=CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.793151847783197e-46\n", - "Kc = 3.207944678649035e55\n", - "proton+OC(O)[Pt]<=>OCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.3128823116835e-26\n", - "Kc = 5.796587570283467e35\n", - "proton+OCO[Pt]<=>OCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.052557862362137e-26\n", - "Kc = 8.189852945376913e35\n", - "vacantX+OCO<=>OCO.[Pt]\n", - "kf = 395377.4080430906\n", - "krev = 715.0601225795458\n", - "Kc = 552.9289014422803\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.079525546868e-12\n", - "Kc = 1.2021973010936467e22\n", - "vacantX+O=C=C=C=O<=>O=C=C=C=O.[Pt]\n", - "kf = 332249.5811031886\n", - "krev = 401.14766551623046\n", - "Kc = 828.2475748067037\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 4.91573386591171e-7\n", - "Kc = 5.08571063485824e16\n", - "proton+O=CCO[Pt]<=>O=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.8816895227328687e-31\n", - "Kc = 1.3285932507978942e41\n", - "proton+O=C([Pt])CO<=>O=CCO.[Pt]\n", - "kf = 3.74256001789537e8\n", - "krev = 9.536073355505413e-9\n", - "Kc = 3.9246342581191416e16\n", - "vacantX+O=CCO<=>O=CCO.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 1291.5767888759226\n", - "Kc = 273.8002875141987\n", - "proton+O=CC(O)[Pt]<=>O=CCO.[Pt]\n", - "kf = 1.712472301799593e10\n", - "krev = 2.6335036754646568e-14\n", - "Kc = 6.5026387384762e23\n", - "proton+OCC#[Pt]<=>OCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.6468663797080987e-6\n", - "Kc = 6.855200437039605e15\n", - "proton+OCC=[Pt]<=>CHX+CO-2\n", - "kf = 2.437334851076409e7\n", - "krev = 3.684139726492616e-11\n", - "Kc = 6.615750302708541e17\n", - "vacantX+vacantX+O=CCO<=>OX+OCC=[Pt]\n", - "kf = 3.3881471741726223e-34\n", - "krev = 2.264159139077055e16\n", - "Kc = 1.4964262518904662e-50\n", - "vacantX+vacantX+O=C=CCO<=>OCX+OCC=[Pt]\n", - "kf = 1.8009876630720204e-13\n", - "krev = 6.668943472119082e14\n", - "Kc = 2.7005591974222413e-28\n", - "vacantX+vacantX+C=CC=O<=>CH2X+O=CC=[Pt]\n", - "kf = 3.2830355290077765e-39\n", - "krev = 2.9277080237249806e14\n", - "Kc = 1.121367124864694e-53\n", - "vacantX+vacantX+C=COC=O<=>CH2X+O=COC=[Pt]\n", - "kf = 1.0242943870290668e-63\n", - "krev = 2.920849603333263e13\n", - "Kc = 3.5068371403311754e-77\n", - "vacantX+O=C=CCO<=>O=C=CCO.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 1179.037991138623\n", - "Kc = 273.8002884035305\n", - "vacantX+vacantX+O=CC=CO<=>OC=[Pt]+O=CC=[Pt]\n", - "kf = 6.284377773759944e-35\n", - "krev = 2.1623088290446475e12\n", - "Kc = 2.90632757418676e-47\n", - "vacantX+vacantX+COC<=>CH3X+CO[Pt]\n", - "kf = 3.3416169046706564e-11\n", - "krev = 3.110510590664853e12\n", - "Kc = 1.0742985137872191e-23\n", - "proton+O=C=CC(O)[Pt]<=>OC=[Pt]+C=C=O\n", - "kf = 7.886335155622577e-9\n", - "krev = 1.1676117437495351e-7\n", - "Kc = 0.0675424446340125\n", - "HX+O=C=CC=O<=>O=C=CC(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 3.0624966294759025e-24\n", - "Kc = 8.467340919226885e15\n", - "proton+O=C=CC=O.[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 5.4417257022505686e7\n", - "krev = 1.0699402207865258e-10\n", - "Kc = 5.086009102686402e17\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=CC(O)[Pt]\n", - "kf = 2.2665619116480148e-11\n", - "krev = 0.03466826587817799\n", - "Kc = 6.537857761944495e-10\n", - "proton+O=C=CC(O)[Pt]<=>O=C=CCO.[Pt]\n", - "kf = 1.693513701515947e9\n", - "krev = 6.001577582317764e-11\n", - "Kc = 2.8217809039168078e19\n", - "proton+O=C=CC=[Pt]<=>CHX+C=C=O\n", - "kf = 181.35768264661723\n", - "krev = 8.307531938850336e-7\n", - "Kc = 2.183051283841528e8\n", - "proton+O=C=CC#[Pt]<=>O=C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.768026569342988e-11\n", - "Kc = 1.4140058997693788e21\n", - "vacantX+vacantX+O=C=CC=O<=>OX+O=C=CC=[Pt]\n", - "kf = 3.709849833927781e-21\n", - "krev = 2.4389911159903437e17\n", - "Kc = 1.5210591828750508e-38\n", - "proton+O=C=CC(O)[Pt]<=>H2O+O=C=CC=[Pt]\n", - "kf = 4.694863820330143\n", - "krev = 3.9520471176425216e-5\n", - "Kc = 118795.74510565875\n", - "vacantX+vacantX+CCO<=>CH3X+OC[Pt]\n", - "kf = 1.5510087911871897e-15\n", - "krev = 9.749013808701775e13\n", - "Kc = 1.5909391674086975e-29\n", - "proton+O=C=C([Pt])CO<=>CO-2+O=C=C=[Pt]\n", - "kf = 259142.28390262663\n", - "krev = 5.010713983419634e-21\n", - "Kc = 5.171763640074528e25\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=C([Pt])CO\n", - "kf = 4.040764431615523e-20\n", - "krev = 30.812673220085827\n", - "Kc = 1.3113969056672023e-21\n", - "proton+O=C=C([Pt])CO<=>O=C=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.777114479215893e-21\n", - "Kc = 1.4067748753603438e31\n", - "proton+O=C=CC[Pt]<=>CH2X+C=C=O\n", - "kf = 6.0148104045883e-8\n", - "krev = 8.74545093406659e-6\n", - "Kc = 0.006877644674854341\n", - "vacantX+vacantX+O=C=CCO<=>HOX+O=C=CC[Pt]\n", - "kf = 8.032715739528718e-6\n", - "krev = 4.997427676480693e14\n", - "Kc = 1.6073700830795308e-20\n", - "proton+O=C=CC=[Pt]<=>O=C=CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.1155543114237032e-25\n", - "Kc = 1.1817233840324226e35\n", - "vacantX+vacantX+CC(O)O<=>CH3X+OC(O)[Pt]\n", - "kf = 1.0212279299691738e-21\n", - "krev = 4.839386960246169e15\n", - "Kc = 2.1102423475497943e-37\n", - "proton+O=C=CC(O)=[Pt]<=>OC#[Pt]+C=C=O\n", - "kf = 1.5097720767202745e6\n", - "krev = 3.361950781834918e-17\n", - "Kc = 4.490761985207459e22\n", - "proton+O=C=CC(O)=[Pt]<=>H2O+O=C=CC#[Pt]\n", - "kf = 5.803789817126122e6\n", - "krev = 2.7232165859221153e-28\n", - "Kc = 2.1312259359498893e34\n", - "proton+O=C=CC(=O)[Pt]<=>O=C=CC(O)=[Pt]\n", - "kf = 0.6530550593549805\n", - "krev = 1.0085447542339824e12\n", - "Kc = 6.475221417923034e-13\n", - "proton+O=C=CC(O)=[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.85508059604632e-41\n", - "Kc = 2.5367626125786886e50\n", - "C=O+O=C=C[Pt]<=>O=C=CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 80798.59947863563\n", - "Kc = 4.901904683810505e-13\n", - "HX+O=C=CC=O<=>O=C=CCO[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 2.019947796444839e-5\n", - "Kc = 0.0012837560986177624\n", - "proton+O=C=CC=O.[Pt]<=>O=C=CCO[Pt]\n", - "kf = 278.5863350248319\n", - "krev = 3612.827309769227\n", - "Kc = 0.07711033800910536\n", - "vacantX+vacantX+O=C=CCO<=>HX+O=C=CCO[Pt]\n", - "kf = 7.342900678318069e-26\n", - "krev = 740.7927312780465\n", - "Kc = 9.912220204496055e-29\n", - "proton+O=C=CCO[Pt]<=>O=C=CCO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3432355963676785e-28\n", - "Kc = 1.861177597407629e38\n", - "vacantX+vacantX+CCOC=O<=>CH3X+O=COC[Pt]\n", - "kf = 1.714178070740009e-17\n", - "krev = 1.2983121019578911e14\n", - "Kc = 1.3203127877765141e-31\n", - "proton+O=CC([Pt])C=O<=>C=O+O=CC=[Pt]\n", - "kf = 1.0131844482393167e-10\n", - "krev = 2.9534786470384583e-7\n", - "Kc = 0.00034304783251277847\n", - "HX+O=C=CC=O<=>O=CC([Pt])C=O\n", - "kf = 2.5931203025755725e-8\n", - "krev = 5.183135272095574e-24\n", - "Kc = 5.002995612590211e15\n", - "proton+O=C=CC=O.[Pt]<=>O=CC([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 8.319166178505196e-8\n", - "Kc = 3.005108861101275e17\n", - "vacantX+vacantX+O=CCC=O<=>HX+O=CC([Pt])C=O\n", - "kf = 6.269624738894468e-15\n", - "krev = 24.522149705338403\n", - "Kc = 2.556719053684591e-16\n", - "proton+O=CC(=[Pt])C=O<=>C=O+O=CC#[Pt]\n", - "kf = 0.04202179791424184\n", - "krev = 2.102387409121332e-9\n", - "Kc = 1.9987656761987723e7\n", - "proton+O=C=C([Pt])C=O<=>O=CC(=[Pt])C=O\n", - "kf = 2.5e10\n", - "krev = 5.057292696382588\n", - "Kc = 4.943356357025204e9\n", - "proton+O=CC(=[Pt])C=O<=>O=CC([Pt])C=O\n", - "kf = 2.5e10\n", - "krev = 5.3866690937421086e-24\n", - "Kc = 4.641087017771969e33\n", - "vacantX+vacantX+COCC=O<=>CH3X+O=CCO[Pt]\n", - "kf = 1.7650043109029407e-12\n", - "krev = 1.4735149295451475e13\n", - "Kc = 1.1978190892492496e-25\n", - "vacantX+vacantX+COCC=O<=>CO[Pt]+O=CC[Pt]\n", - "kf = 10.947009513309483\n", - "krev = 5.112987413682155e11\n", - "Kc = 2.1410202348661592e-11\n", - "proton+O=CCC(=O)[Pt]<=>O=CCC=O.[Pt]\n", - "kf = 2.1814901321970692e8\n", - "krev = 5.7550523540318155e-8\n", - "Kc = 3.7905652251256815e15\n", - "vacantX+O=CCC=O<=>O=CCC=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 165389.8266532618\n", - "Kc = 1.951879075907524\n", - "proton+O=CC([Pt])C=O<=>O=CCC=O.[Pt]\n", - "kf = 1.6062704929440186e10\n", - "krev = 3.122654421781107e-14\n", - "Kc = 5.1439265316711864e23\n", - "proton+O=CCC#[Pt]<=>O=CCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 6.03648176110191e-17\n", - "Kc = 4.141485220927174e26\n", - "proton+O=CCC=[Pt]<=>CHX+CC=O\n", - "kf = 1.0605779567215914e7\n", - "krev = 5.748508015003e-13\n", - "Kc = 1.8449621257439228e19\n", - "vacantX+vacantX+O=CCC=O<=>OX+O=CCC=[Pt]\n", - "kf = 1.2771337705277995e-31\n", - "krev = 6.599290845791489e16\n", - "Kc = 1.935259106426951e-48\n", - "vacantX+vacantX+CCOO<=>CH3X+OOC[Pt]\n", - "kf = 1.1728434846364774e-18\n", - "krev = 2.6840450809869076e16\n", - "Kc = 4.3696862356918e-35\n", - "proton+OOCC#[Pt]<=>CX+COO\n", - "kf = 0.24698833297799483\n", - "krev = 0.0004336424509567548\n", - "Kc = 569.5667765760919\n", - "vacantX+vacantX+C=C=O<=>OX+C=C=[Pt]\n", - "kf = 5.2796000958546504e-37\n", - "krev = 1.4614931014553018e17\n", - "Kc = 3.612470076387919e-54\n", - "proton+C=C=[Pt]<=>CC#[Pt]\n", - "kf = 10.738937415423795\n", - "krev = 4.122167482176662e-33\n", - "Kc = 2.60516766042539e33\n", - "vacantX+vacantX+CC(C)=O<=>CH3X+CC(=O)[Pt]\n", - "kf = 0.0015322757193851075\n", - "krev = 1.9084257758101816e14\n", - "Kc = 8.029003479239911e-18\n", - "vacantX+vacantX+C=C=C=O<=>CH2X+O=C=C=[Pt]\n", - "kf = 0.014873013888318402\n", - "krev = 6.520037160662236e15\n", - "Kc = 2.2811240981957472e-18\n", - "HOX+C=C=C=O<=>O=C=C([Pt])CO\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.9529365102554657e-31\n", - "Kc = 9.99708792916859e22\n", - "HX+C=C=C=O<=>O=C=CC[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.4091973858076736e-32\n", - "Kc = 1.225336127134283e24\n", - "vacantX+vacantX+C=C=C=O<=>OCX+C=C=[Pt]\n", - "kf = 0.8504584217531632\n", - "krev = 1.347597642765549e15\n", - "Kc = 6.310922450174717e-16\n", - "proton+O=C(O)C=[Pt]<=>CHX+O=CO\n", - "kf = 7.88145235948431e7\n", - "krev = 1.995696153847229e-7\n", - "Kc = 3.949224607308452e14\n", - "proton+O=C(O)C#[Pt]<=>O=C(O)C=[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.424855572557093e-13\n", - "Kc = 3.3670688615684534e22\n", - "vacantX+vacantX+CC=C=O<=>CH3X+O=C=C[Pt]\n", - "kf = 0.0008567749561878586\n", - "krev = 1.2359860589695025e13\n", - "Kc = 6.931914401220598e-17\n", - "vacantX+vacantX+CC=C=O<=>HX+O=C=CC[Pt]\n", - "kf = 2.2773385768535307e-19\n", - "krev = 181.8091471864856\n", - "Kc = 1.2525984594810374e-21\n", - "proton+O=C=CCO[Pt]<=>OX+CC=C=O\n", - "kf = 3.801213612232799e6\n", - "krev = 3.4005935521726275e-15\n", - "Kc = 1.1178088630451637e21\n", - "proton+CC(=O)[Pt]<=>CC=O.[Pt]\n", - "kf = 2.2108223076011086e9\n", - "krev = 2.493722128340101e-11\n", - "Kc = 8.865551949337277e19\n", - "proton+O=CC[Pt]<=>CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0175396707648368e-24\n", - "Kc = 2.456906665978799e34\n", - "vacantX+CC=O<=>CC=O.[Pt]\n", - "kf = 412885.969273148\n", - "krev = 2.625517699834265\n", - "Kc = 157258.8786200951\n", - "proton+CC=[Pt]<=>CHX+CH4\n", - "kf = 3.754229088708618e7\n", - "krev = 3.193900280463504e-10\n", - "Kc = 1.1754371642948722e17\n", - "proton+CC#[Pt]<=>CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.101069134371629e-9\n", - "Kc = 3.086012424450092e18\n", - "vacantX+vacantX+CC=O<=>OX+CC=[Pt]\n", - "kf = 6.186864182993887e-31\n", - "krev = 2.034915252803989e19\n", - "Kc = 3.04035471475717e-50\n", - "vacantX+vacantX+CC=C=O<=>OCX+CC=[Pt]\n", - "kf = 5.619880038277716e-8\n", - "krev = 4.919193785592355e16\n", - "Kc = 1.14243924578405e-24\n", - "vacantX+vacantX+CC<=>CH3X+CH3X\n", - "kf = 1.6866972609475142e-22\n", - "krev = 6.547125244410207e13\n", - "Kc = 2.576241018739606e-36\n", - "proton+O=C=CC[Pt]<=>CC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.381078389100095e-19\n", - "Kc = 1.0499444333476355e29\n", - "vacantX+CC=C=O<=>CC=C=O.[Pt]\n", - "kf = 365995.57053717994\n", - "krev = 187509.1639624155\n", - "Kc = 1.9518809790573244\n", - "proton+O=C(O)C[Pt]<=>CH2X+O=CO\n", - "kf = 5.038535015011119e-9\n", - "krev = 7.877133180076684e-5\n", - "Kc = 6.396407042799381e-5\n", - "HOX+C=C=O<=>O=C(O)C[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.348252838458729e-29\n", - "Kc = 4.5553052781738184e20\n", - "vacantX+vacantX+CC(=O)O<=>HX+O=C(O)C[Pt]\n", - "kf = 1.1112170024966995e-23\n", - "krev = 36323.66987445037\n", - "Kc = 3.0592090676342045e-28\n", - "proton+O=C(O)C=[Pt]<=>O=C(O)C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0876086200539217e-33\n", - "Kc = 2.2986209872776243e43\n", - "vacantX+vacantX+O=C=C=CO<=>OC=[Pt]+O=C=C=[Pt]\n", - "kf = 0.004371453552681894\n", - "krev = 1.2572855491392857e13\n", - "Kc = 3.476897953431907e-16\n", - "HX+O=C=C=CO<=>O=C=CC(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.3635197599529065e-33\n", - "Kc = 1.9017841755847633e25\n", - "HX+O=C=C=CO<=>O=C=C([Pt])CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 6.797711819853139e-22\n", - "Kc = 3.814695843684052e13\n", - "proton+O=C(O)CC#[Pt]<=>CX+CC(=O)O\n", - "kf = 0.12574987603391333\n", - "krev = 9.921358720719502e-5\n", - "Kc = 1267.4662772882168\n", - "proton+CC([Pt])=C=O<=>CH4+O=C=C=[Pt]\n", - "kf = 49487.72961177987\n", - "krev = 1.2730900614037961e-24\n", - "Kc = 3.8872135689451003e28\n", - "HX+C=C=C=O<=>CC([Pt])=C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.301177455844525e-32\n", - "Kc = 1.2828548214436644e24\n", - "vacantX+vacantX+CC=C=O<=>HX+CC([Pt])=C=O\n", - "kf = 4.581183222917958e-20\n", - "krev = 34.93361388628861\n", - "Kc = 1.3113968791863429e-21\n", - "proton+CC([Pt])=C=O<=>CC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.492848961236613e-19\n", - "Kc = 1.0028686209532082e29\n", - "CH3X+O=C=C=O<=>CC(=C=O)O[Pt]\n", - "kf = 5.799304049644909e-8\n", - "krev = 2.951682102619952e-64\n", - "Kc = 1.9647454732667077e56\n", - "proton+CC(=C=O)O[Pt]<=>OX+CC=C=O\n", - "kf = 1.920567374031219e-6\n", - "krev = 5.0434729686975995e-5\n", - "Kc = 0.03808025513274787\n", - "vacantX+C=C<=>C=C.[Pt]\n", - "kf = 36.21750369826068\n", - "krev = 0.32335117013731834\n", - "Kc = 112.00671914340097\n", - "vacantX+vacantX+C=CO<=>HOX+C=C[Pt]\n", - "kf = 1.7018617233469498e-12\n", - "krev = 4.164837143763027e13\n", - "Kc = 4.086262354568991e-26\n", - "vacantX+vacantX+C=C<=>HX+C=C[Pt]\n", - "kf = 6.071347272542775e-23\n", - "krev = 1180.067101472276\n", - "Kc = 5.144916983930861e-26\n", - "vacantX+vacantX+C=CC=O<=>CHOX+C=C[Pt]\n", - "kf = 0.3274906030624493\n", - "krev = 2.9425898600264806e14\n", - "Kc = 1.1129332276687114e-15\n", - "vacantX+vacantX+C=COC=O<=>CHO2X+C=C[Pt]\n", - "kf = 0.2513917911405871\n", - "krev = 1.0405847657707406e16\n", - "Kc = 2.4158703779829617e-17\n", - "proton+C=C=[Pt]<=>C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.446578752089028e-33\n", - "Kc = 1.0218350820979533e43\n", - "proton+C=C[Pt]<=>CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 31.775139733809926\n", - "Kc = 7.867786014296917e8\n", - "proton+C=C[Pt]<=>C=C.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.7043133558442046e-25\n", - "Kc = 1.4668664019015827e35\n", - "proton+C=CC#[Pt]<=>CX+C=C\n", - "kf = 1.0856530221273585e-15\n", - "krev = 0.12983129718682296\n", - "Kc = 8.36202861444987e-15\n", - "vacantX+CC(=O)O<=>CC(=O)O.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 181176.05501028927\n", - "Kc = 1.9518809818483447\n", - "proton+CC(=O)O[Pt]<=>CC(=O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.133892027559991e-24\n", - "Kc = 6.04756965913213e33\n", - "proton+O=C(O)C[Pt]<=>CC(=O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 5.815284645396005e-26\n", - "Kc = 4.2990157016290936e35\n", - "proton+C=CC(=O)[Pt]<=>OCX+C=C\n", - "kf = 7.087170621400232e6\n", - "krev = 2.9783308105065206e-7\n", - "Kc = 2.3795780496911715e13\n", - "vacantX+vacantX+C=CC=O<=>HX+C=CC(=O)[Pt]\n", - "kf = 3.052485738368744e-11\n", - "krev = 0.0007099643372969683\n", - "Kc = 4.29949164769375e-8\n", - "HX+C=C=C=O<=>C=CC(=O)[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 5.604440911093213e-48\n", - "Kc = 5.267388203494818e39\n", - "HX+O=C=CC=O<=>O=CC=CO[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 5.6159867257682645e-34\n", - "Kc = 4.61739037002591e25\n", - "proton+O=C=CC=O.[Pt]<=>O=CC=CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 9.013912308921113e-18\n", - "Kc = 2.7734904826239954e27\n", - "proton+O=CC=CO[Pt]<=>OX+C=CC=O\n", - "kf = 3.6615493516163485e-10\n", - "krev = 9.407550626549198e-5\n", - "Kc = 3.892138875429521e-6\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC=CO[Pt]\n", - "kf = 4.135805741920728e-10\n", - "krev = 0.028732529553568358\n", - "Kc = 1.4394158141245496e-8\n", - "HX+C=C=O<=>C=CO[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 7.272169613200064e-8\n", - "Kc = 0.46029640012283785\n", - "proton+C=C=O.[Pt]<=>C=CO[Pt]\n", - "kf = 2.7021695253394946e-5\n", - "krev = 3753.979595717479\n", - "Kc = 7.19814654406251e-9\n", - "vacantX+vacantX+C=CO<=>HX+C=CO[Pt]\n", - "kf = 1.5839272910037507e-20\n", - "krev = 3600.161649580889\n", - "Kc = 4.399600476795654e-24\n", - "proton+C=CO[Pt]<=>OX+C=C\n", - "kf = 6.694428008398142e6\n", - "krev = 4.294813980591457e-9\n", - "Kc = 1.5587236231070068e15\n", - "vacantX+vacantX+C=COC=O<=>CHOX+C=CO[Pt]\n", - "kf = 0.024290856013790354\n", - "krev = 3.5586883050271985e15\n", - "Kc = 6.825789148062155e-18\n", - "vacantX+vacantX+O=CCCO<=>OC[Pt]+O=CC[Pt]\n", - "kf = 2.162232232095232e-5\n", - "krev = 5.66671683371172e13\n", - "Kc = 3.815670158833332e-19\n", - "proton+C=COC(=O)[Pt]<=>OCX+C=CO\n", - "kf = 8.547694380469097e6\n", - "krev = 5.219823560516419e-10\n", - "Kc = 1.637544695020963e16\n", - "vacantX+vacantX+C=COC=O<=>HX+C=COC(=O)[Pt]\n", - "kf = 3.5117597357119104e-15\n", - "krev = 0.7837038908782975\n", - "Kc = 4.480977798612533e-15\n", - "CO2+C=C[Pt]<=>C=COC(=O)[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 0.08399332498323721\n", - "Kc = 7.789900440580834e-7\n", - "proton+C=COC#[Pt]<=>CX+C=CO\n", - "kf = 3.59319568894763e-23\n", - "krev = 3.7552909398960855e-5\n", - "Kc = 9.568355012853036e-19\n", - "vacantX+vacantX+CCC=O<=>CH3X+O=CC[Pt]\n", - "kf = 1.2257627381394946e-12\n", - "krev = 3.270257576074817e14\n", - "Kc = 3.748214657790771e-27\n", - "proton+CC(O)=[Pt]<=>OC#[Pt]+CH4\n", - "kf = 7.023325690411809e6\n", - "krev = 0.001122962882704699\n", - "Kc = 6.254281239906934e9\n", - "proton+CC(=O)[Pt]<=>CC(O)=[Pt]\n", - "kf = 9.881755573608883e9\n", - "krev = 1.0085447542339819e12\n", - "Kc = 0.009798033782957261\n", - "proton+CC(O)=[Pt]<=>H2O+CC#[Pt]\n", - "kf = 7.254296675241664e9\n", - "krev = 2.8720393080667615e-6\n", - "Kc = 2.5258347456688205e15\n", - "vacantX+vacantX+CC(=O)O<=>OX+CC(O)=[Pt]\n", - "kf = 1.1829749543892744e-33\n", - "krev = 3.758913107590896e15\n", - "Kc = 3.1471197139415875e-49\n", - "vacantX+vacantX+CC(O)=C=O<=>CH3X+O=C=C(O)[Pt]\n", - "kf = 1.049990631922765e-6\n", - "krev = 1.7955210884029898e15\n", - "Kc = 5.847832357439309e-22\n", - "vacantX+vacantX+CC(O)=C=O<=>HOX+CC([Pt])=C=O\n", - "kf = 0.0029164033711847528\n", - "krev = 3.4437539939134434e12\n", - "Kc = 8.468675103794464e-16\n", - "vacantX+vacantX+CC(O)=C=O<=>HX+CC(=C=O)O[Pt]\n", - "kf = 1.7528367761452354e-6\n", - "krev = 1.1970864565480504e-5\n", - "Kc = 0.14642524494009906\n", - "vacantX+vacantX+CC(O)=C=O<=>OCX+CC(O)=[Pt]\n", - "kf = 65.80946386077328\n", - "krev = 1217.699742052305\n", - "Kc = 0.054044081301896585\n", - "vacantX+vacantX+C=CC=O<=>HX+O=CC=C[Pt]\n", - "kf = 6.342176392543457e-21\n", - "krev = 776.2437464870187\n", - "Kc = 8.170341366672147e-24\n", - "vacantX+vacantX+O=CC=CO<=>HOX+O=CC=C[Pt]\n", - "kf = 4.672349699632388e-15\n", - "krev = 8.81363422062413e13\n", - "Kc = 5.301274800693419e-29\n", - "proton+O=CC=C[Pt]<=>O=CCC=[Pt]\n", - "kf = 1.2673656466904085e10\n", - "krev = 1.0824082827935274e8\n", - "Kc = 117.08757839689983\n", - "proton+C=CC(=O)O[Pt]<=>OX+C=CC=O\n", - "kf = 4.524546416801015\n", - "krev = 7.68227583414659e-9\n", - "Kc = 5.889591202505473e8\n", - "CO2+C=C[Pt]<=>C=CC(=O)O[Pt]\n", - "kf = 6.542996392927688e-8\n", - "krev = 450683.30306117237\n", - "Kc = 1.4517947189269602e-13\n", - "vacantX+vacantX+O=C=CO<=>OX+OC=C=[Pt]\n", - "kf = 7.548264554696059e-34\n", - "krev = 5.749061160710156e15\n", - "Kc = 1.3129560364189368e-49\n", - "proton+OC=C=[Pt]<=>OCC#[Pt]\n", - "kf = 0.00032547344886471076\n", - "krev = 1.1489507349403094e-46\n", - "Kc = 2.832788551909668e42\n", - "vacantX+vacantX+O=C=C=CO<=>OCX+OC=C=[Pt]\n", - "kf = 1.463392220587488e-22\n", - "krev = 7.968303762369095e13\n", - "Kc = 1.8365166090912173e-36\n", - "proton+CC[Pt]<=>CH2X+CH4\n", - "kf = 1.4846524062695914\n", - "krev = 9.859129077434927e-6\n", - "Kc = 150586.56749586415\n", - "HX+C=C<=>CC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 3.1627439012977165e-12\n", - "Kc = 25911.109388377805\n", - "vacantX+vacantX+CCO<=>HOX+CC[Pt]\n", - "kf = 2.1035625708276702e-15\n", - "krev = 1.0019023766861524e15\n", - "Kc = 2.099568400850909e-30\n", - "vacantX+vacantX+CCOC=O<=>CHO2X+CC[Pt]\n", - "kf = 0.08561452397466171\n", - "krev = 3.215769317238553e17\n", - "Kc = 2.6623341268826044e-19\n", - "vacantX+vacantX+CCOO<=>OO[Pt]+CC[Pt]\n", - "kf = 1.262172875849309e-6\n", - "krev = 1.5596341944506717e13\n", - "Kc = 8.092749443044025e-20\n", - "proton+CC=[Pt]<=>CC[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.602708332438123e-27\n", - "Kc = 2.9060615603731233e36\n", - "vacantX+vacantX+CC<=>HX+CC[Pt]\n", - "kf = 8.697106954471648e-14\n", - "krev = 5.359609736165605e16\n", - "Kc = 1.6227127314485718e-30\n", - "proton+C=C.[Pt]<=>CC[Pt]\n", - "kf = 5.504599623053448e9\n", - "krev = 0.3531497863658743\n", - "Kc = 1.558715263486103e10\n", - "vacantX+vacantX+CCC=O<=>CHOX+CC[Pt]\n", - "kf = 0.0004422945453165714\n", - "krev = 9.363325052982716e15\n", - "Kc = 4.723691026572629e-20\n", - "vacantX+vacantX+CC(O)C=O<=>CH3X+O=CC(O)[Pt]\n", - "kf = 9.477814531468979e-7\n", - "krev = 7.52142668687151e15\n", - "Kc = 1.2601086105129898e-22\n", - "proton+CCC#[Pt]<=>CX+CC\n", - "kf = 3.73018742862406e-11\n", - "krev = 0.075105066117345\n", - "Kc = 4.966625583946592e-10\n", - "C=O+CH3X<=>CCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.1808191230067762e-17\n", - "Kc = 3.354171909251678e9\n", - "HX+CC=O<=>CCO[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 2.639709061724686e-6\n", - "Kc = 0.012387213631168494\n", - "vacantX+vacantX+CCO<=>HX+CCO[Pt]\n", - "kf = 5.372480262216755e-24\n", - "krev = 2113.809062877283\n", - "Kc = 2.5416109508508876e-27\n", - "vacantX+vacantX+CCOC=O<=>CHOX+CCO[Pt]\n", - "kf = 4.80530366959931e-5\n", - "krev = 5.681813674074216e13\n", - "Kc = 8.457341168235823e-19\n", - "vacantX+vacantX+CCOO<=>HOX+CCO[Pt]\n", - "kf = 3.028654941635431e8\n", - "krev = 1.2132864881112858e-12\n", - "Kc = 2.496240559268171e20\n", - "proton+CC=O.[Pt]<=>CCO[Pt]\n", - "kf = 19418.796323941955\n", - "krev = 3658.802750537776\n", - "Kc = 5.30741820424393\n", - "proton+CCO[Pt]<=>OX+CC\n", - "kf = 1.5180806810718186e7\n", - "krev = 3.4536717602694347e-12\n", - "Kc = 4.395555763392486e18\n", - "proton+CCOC(=O)[Pt]<=>OCX+CCO\n", - "kf = 1.100364657251968e9\n", - "krev = 4.5302115405928314e-10\n", - "Kc = 2.4289476272623954e18\n", - "vacantX+vacantX+CCOC=O<=>HX+CCOC(=O)[Pt]\n", - "kf = 2.5742212027881315e-15\n", - "krev = 0.39729482671494754\n", - "Kc = 6.479372570927264e-15\n", - "CO2+CC[Pt]<=>CCOC(=O)[Pt]\n", - "kf = 3.860701485876577e-7\n", - "krev = 0.0037771400241392917\n", - "Kc = 0.00010221229451921966\n", - "CH3X+C=C=O<=>CCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.9339597186194493e-34\n", - "Kc = 1.7308289628845924e26\n", - "HX+CC=C=O<=>CCC(=O)[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 2.728234417234893e-33\n", - "Kc = 1.0624138213938816e25\n", - "proton+CCC(=O)[Pt]<=>OCX+CC\n", - "kf = 3.3183098775357734e7\n", - "krev = 1.723115430616528e-10\n", - "Kc = 1.9257618024745373e17\n", - "proton+CC=C=O.[Pt]<=>CCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 6.816709270833084e-23\n", - "Kc = 3.667458740974689e32\n", - "vacantX+vacantX+CCC=O<=>HX+CCC(=O)[Pt]\n", - "kf = 1.3037608552158366e-12\n", - "krev = 0.18236199715464047\n", - "Kc = 7.149301255514685e-12\n", - "vacantX+vacantX+C=C(O)C=O<=>CH2X+O=CC(O)=[Pt]\n", - "kf = 3.506980389191063e-59\n", - "krev = 1.6121784785918364e12\n", - "Kc = 2.1753053001019147e-71\n", - "proton+CCOC#[Pt]<=>CX+CCO\n", - "kf = 1.6403573057503937e-22\n", - "krev = 1.0480859144262605e-13\n", - "Kc = 1.5650981309565184e-9\n", - "proton+CCC(=O)O[Pt]<=>OX+CCC=O\n", - "kf = 5.622114816602621e-8\n", - "krev = 4.785365563630673e-7\n", - "Kc = 0.11748558687619057\n", - "CO2+CC[Pt]<=>CCC(=O)O[Pt]\n", - "kf = 3.860701485876577e-7\n", - "krev = 2.2515045234693432e-8\n", - "Kc = 17.147207325738\n", - "vacantX+vacantX+OC=CCO<=>OC=[Pt]+OCC=[Pt]\n", - "kf = 3.6700973989487563e-44\n", - "krev = 3.0504263460080312e13\n", - "Kc = 1.203142440646588e-57\n", - "proton+CC(=C=O)O[Pt]<=>CC(O)=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 27.83415070046663\n", - "Kc = 8.981772165076653e8\n", - "vacantX+CC(O)=C=O<=>CC(O)=C=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 165389.73964983693\n", - "Kc = 1.9518801026953096\n", - "proton+OOC=[Pt]<=>OO+CHX\n", - "kf = 2.8719882764673755e7\n", - "krev = 8.077545633440945e-25\n", - "Kc = 3.555520955000709e31\n", - "proton+OOC=[Pt]<=>OOC[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.62255074484058e-37\n", - "Kc = 2.899374064566577e46\n", - "proton+OOC#[Pt]<=>OOC=[Pt]\n", - "kf = 3.432151727081939e-44\n", - "krev = 3342.777740155216\n", - "Kc = 1.0267364431242663e-47\n", - "vacantX+vacantX+C=CCO<=>CH2X+OCC=[Pt]\n", - "kf = 3.3256293066300124e-48\n", - "krev = 2.638642223210571e15\n", - "Kc = 1.2603562837645906e-63\n", - "vacantX+vacantX+C=CCO<=>OC[Pt]+C=C[Pt]\n", - "kf = 1.4930923415267688e-9\n", - "krev = 1.1121057711212152e14\n", - "Kc = 1.3425812366942817e-23\n", - "vacantX+OO<=>OO.[Pt]\n", - "kf = 469882.2241291155\n", - "krev = 15.560302693769444\n", - "Kc = 30197.498941795184\n", - "proton+OO[Pt]<=>OO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.110596489625074e-24\n", - "Kc = 2.251042591395165e34\n", - "C=O+CO[Pt]<=>COCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 9.545218685674386e-14\n", - "Kc = 414937.62088874576\n", - "HX+COC=O<=>COCO[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 0.02522938529859348\n", - "Kc = 1.1100614687459063e-6\n", - "vacantX+vacantX+COCO<=>HX+COCO[Pt]\n", - "kf = 1.0488506310161173e-19\n", - "krev = 521.1543106644776\n", - "Kc = 2.0125529225284944e-22\n", - "proton+COC=O.[Pt]<=>COCO[Pt]\n", - "kf = 0.6792883990466445\n", - "krev = 3726.123137157573\n", - "Kc = 0.00018230433457033608\n", - "proton+COCO[Pt]<=>OX+COC\n", - "kf = 5093.375621150868\n", - "krev = 5.977614318003391e-7\n", - "Kc = 8.520749834613165e9\n", - "CO[Pt]+C=C=O<=>COCC(=O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.680149232421768e-23\n", - "Kc = 1.9922953446306685e15\n", - "HX+COC=C=O<=>COCC(=O)[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 2.661991446097411e-38\n", - "Kc = 9.604054388173769e29\n", - "proton+COCC(=O)[Pt]<=>OCX+COC\n", - "kf = 8.734746675052269e7\n", - "krev = 2.1771371890779743e-8\n", - "Kc = 4.012033196103488e15\n", - "vacantX+vacantX+COCC=O<=>HX+COCC(=O)[Pt]\n", - "kf = 2.290241001822749e-10\n", - "krev = 0.0004872161822843353\n", - "Kc = 4.7006669423105973e-7\n", - "proton+COCOC#[Pt]<=>CX+COCO\n", - "kf = 3.2770328923262016e-17\n", - "krev = 2.1864147814239428e-13\n", - "Kc = 0.0001498815741719407\n", - "proton+COCC#[Pt]<=>CX+COC\n", - "kf = 1.433200340176918\n", - "krev = 0.00041586763423335837\n", - "Kc = 3446.289689792732\n", - "proton+COC[Pt]<=>CH2X+CO-2\n", - "kf = 0.2769010105768301\n", - "krev = 3.0099119392563808e-6\n", - "Kc = 91996.38267332179\n", - "vacantX+vacantX+COCO<=>HOX+COC[Pt]\n", - "kf = 8.90444501639475e-13\n", - "krev = 8.409201083164982e12\n", - "Kc = 1.0588931015362724e-25\n", - "C=O+CH3X<=>COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 8.422687202008296e-11\n", - "Kc = 470.23832623775377\n", - "vacantX+vacantX+COC<=>HX+COC[Pt]\n", - "kf = 2.786306429788959e-20\n", - "krev = 52.25975865319748\n", - "Kc = 5.3316481009398625e-22\n", - "vacantX+vacantX+COCC=O<=>CHOX+COC[Pt]\n", - "kf = 1.4060776479118306e6\n", - "krev = 6.613786245273692e13\n", - "Kc = 2.1259798786461146e-8\n", - "vacantX+vacantX+C=C=CO<=>OC=[Pt]+C=C=[Pt]\n", - "kf = 1.5975335437882445e-34\n", - "krev = 2.2957840869759923e8\n", - "Kc = 6.958553083676594e-43\n", - "vacantX+vacantX+C=C=CO<=>CH2X+OC=C=[Pt]\n", - "kf = 9.363402027600756e-56\n", - "krev = 7.047835211144391e9\n", - "Kc = 1.328550079149818e-65\n", - "vacantX+vacantX+COC=O<=>OX+COC=[Pt]\n", - "kf = 1.1797200153280936e-59\n", - "krev = 4.3408253155831816e16\n", - "Kc = 2.7177320660497494e-76\n", - "proton+COC=[Pt]<=>CHX+CO-2\n", - "kf = 479145.9852086257\n", - "krev = 1.0449825701778588e-33\n", - "Kc = 4.5852055228736854e38\n", - "proton+COC#[Pt]<=>COC=[Pt]\n", - "kf = 90933.51053402986\n", - "krev = 2739.427130274527\n", - "Kc = 33.194352764155155\n", - "vacantX+vacantX+COC=C=O<=>OCX+COC=[Pt]\n", - "kf = 2.7777170398864307e-21\n", - "krev = 2.5089215324603047e13\n", - "Kc = 1.107135876490541e-34\n", - "proton+COC=[Pt]<=>COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3472876439887766e-48\n", - "Kc = 1.8555799952254487e58\n", - "vacantX+COC=C=O<=>COC=C=O.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 1179.0380002145982\n", - "Kc = 273.8002862958761\n", - "proton+COC=C=O.[Pt]<=>COCC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.0577777781824875e-25\n", - "Kc = 2.3634453772469967e35\n", - "vacantX+vacantX+C=C=C<=>CH2X+C=C=[Pt]\n", - "kf = 4.78083312177258e-41\n", - "krev = 4.774618642094983e15\n", - "Kc = 1.0013015656628172e-56\n", - "proton+O=C=COC[Pt]<=>CH2X+O=C=CO\n", - "kf = 4.988523456059943e-5\n", - "krev = 0.0009299241102698363\n", - "Kc = 0.05364441464596958\n", - "C=O+O=C=C[Pt]<=>O=C=COC[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 1.852140732586457e13\n", - "Kc = 2.1384283940268284e-21\n", - "vacantX+vacantX+COC=C=O<=>HX+O=C=COC[Pt]\n", - "kf = 3.256466928453685e-21\n", - "krev = 26.50445975246776\n", - "Kc = 1.2286486722863626e-22\n", - "proton+O=C=COC[Pt]<=>COC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.6649798034152577e-22\n", - "Kc = 1.5015197150571575e32\n", - "CH3X+O=C=C=O<=>COC([Pt])=C=O\n", - "kf = 5.799304049644909e-8\n", - "krev = 3.1615249923835833e-35\n", - "Kc = 1.8343375629216876e27\n", - "proton+COC([Pt])=C=O<=>CO-2+O=C=C=[Pt]\n", - "kf = 313658.31445379555\n", - "krev = 1.256306436150439e-34\n", - "Kc = 2.496670441448219e39\n", - "vacantX+vacantX+COC=C=O<=>HX+COC([Pt])=C=O\n", - "kf = 2.779636780044878e-20\n", - "krev = 3.601218910546807\n", - "Kc = 7.718599866018197e-21\n", - "proton+COC([Pt])=C=O<=>COC=C=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0459713323621888e-20\n", - "Kc = 2.390122867281724e30\n", - "vacantX+vacantX+C=C=C(O)O<=>OC(O)=[Pt]+C=C=[Pt]\n", - "kf = 2.937512138355157e-45\n", - "krev = 8.778136400287878e10\n", - "Kc = 3.34639609639561e-56\n", - "proton+O=C=COC=[Pt]<=>CHX+O=C=CO\n", - "kf = 2.102599834403735e7\n", - "krev = 1.6989476123058672e-25\n", - "Kc = 1.237589563782969e32\n", - "proton+O=C=COC#[Pt]<=>O=C=COC=[Pt]\n", - "kf = 1080.8801129554665\n", - "krev = 2888.2699525834805\n", - "Kc = 0.37423098626520285\n", - "proton+O=C=COC=[Pt]<=>O=C=COC[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.9106920181466426e-48\n", - "Kc = 8.589022763019266e57\n", - "proton+CCOO[Pt]<=>OX+CCO\n", - "kf = 169.16425212622386\n", - "krev = 5.6416707126946964e-58\n", - "Kc = 2.9984779463568512e59\n", - "vacantX+vacantX+CCOO<=>HX+CCOO[Pt]\n", - "kf = 1.893449523720139e-21\n", - "krev = 0.6694879211592951\n", - "Kc = 2.8282056537202555e-21\n", - "O=O+CC[Pt]<=>CCOO[Pt]\n", - "kf = 4.5276782379965965e-7\n", - "krev = 1.4949208469184493e-38\n", - "Kc = 3.0287076719344122e31\n", - "vacantX+vacantX+C=CC(=O)O<=>CH2X+O=C(O)C=[Pt]\n", - "kf = 4.72289540105198e-39\n", - "krev = 9.498795808374404e14\n", - "Kc = 4.9720990916429044e-54\n", - "vacantX+vacantX+C=CC(=O)O<=>CO2HX+C=C[Pt]\n", - "kf = 5.354197885861111e7\n", - "krev = 1.376967106369583e14\n", - "Kc = 3.888399266107105e-7\n", - "vacantX+vacantX+C=CC(=O)O<=>HOX+C=CC(=O)[Pt]\n", - "kf = 0.03947248649742643\n", - "krev = 2.5171232142616846e11\n", - "Kc = 1.5681586929785789e-13\n", - "vacantX+vacantX+C=CC(=O)O<=>HX+C=CC(=O)O[Pt]\n", - "kf = 2.4490000178339845e-20\n", - "krev = 458.0011375503109\n", - "Kc = 5.3471483300955e-23\n", - "proton+O=C=C=CO.[Pt]<=>O=C=CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.4322611471299928e-17\n", - "Kc = 1.7454917387164855e27\n", - "proton+O=C=C=CO.[Pt]<=>O=C=C([Pt])CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 7.140416160377535e-6\n", - "Kc = 3.5011964903006675e15\n", - "vacantX+O=C=C=CO<=>O=C=C=CO.[Pt]\n", - "kf = 327433.4917974331\n", - "krev = 0.4460204906723957\n", - "Kc = 734122.0832787583\n", - "HX+O=C=C=C=O<=>O=C=C=C(O)[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 1.3048903398306852e-5\n", - "Kc = 0.004032923533638046\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C=C(O)[Pt]\n", - "kf = 4235.342411204313\n", - "krev = 12.909334546967292\n", - "Kc = 328.0837130523738\n", - "proton+O=C=C=C(O)[Pt]<=>O=C=CC(O)=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1053.6449933824201\n", - "Kc = 2.3727156828928486e7\n", - "vacantX+vacantX+O=C=C=CO<=>HX+O=C=C=C(O)[Pt]\n", - "kf = 8.233814429551885e-18\n", - "krev = 0.5740049812746953\n", - "Kc = 1.434449995759099e-17\n", - "proton+O=C=C=C(O)[Pt]<=>O=C=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.249904355928212e-21\n", - "Kc = 3.4483213533096645e30\n", - "vacantX+vacantX+CC=CO<=>OC=[Pt]+CC=[Pt]\n", - "kf = 1.6816353348966163e-33\n", - "krev = 8.021148128032321e14\n", - "Kc = 2.0965020319468163e-48\n", - "proton+O=C=C=C[Pt]<=>O=C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 0.0269882986128818\n", - "Kc = 9.263273820479827e11\n", - "vacantX+vacantX+C=C=C=O<=>HX+O=C=C=C[Pt]\n", - "kf = 3.6772489817592154e-10\n", - "krev = 0.00723599763490509\n", - "Kc = 5.081882509221477e-8\n", - "vacantX+vacantX+O=C=C=CO<=>HOX+O=C=C=C[Pt]\n", - "kf = 0.00020826365169953766\n", - "krev = 1.0739954827079557e13\n", - "Kc = 1.939148302322696e-17\n", - "vacantX+OC=CO<=>OC=CO.[Pt]\n", - "kf = 353634.0961408931\n", - "krev = 0.48171019889246675\n", - "Kc = 734122.0861712244\n", - "vacantX+vacantX+C=CC<=>CH2X+CC=[Pt]\n", - "kf = 3.8695500910369183e-44\n", - "krev = 2.1644248520711738e17\n", - "Kc = 1.787795999169979e-61\n", - "vacantX+vacantX+C=CC<=>CH3X+C=C[Pt]\n", - "kf = 1.1726078415532691e-17\n", - "krev = 1.59532697721828e15\n", - "Kc = 7.350266486422159e-33\n", - "HX+O=C=CO<=>OC=C(O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 2.762063581333058e-24\n", - "Kc = 1.0314187634521844e16\n", - "vacantX+vacantX+OC=CO<=>HX+OC=C(O)[Pt]\n", - "kf = 6.089904416870865e-20\n", - "krev = 3.928023437111271\n", - "Kc = 1.550373747604081e-20\n", - "proton+O=C=CO.[Pt]<=>OC=C(O)[Pt]\n", - "kf = 6.4368819183992445e7\n", - "krev = 6.799608634080986e-11\n", - "Kc = 9.466547657075904e17\n", - "proton+OC=C(O)[Pt]<=>H2O+OC=C=[Pt]\n", - "kf = 5.262467142275111e-7\n", - "krev = 0.6251329939834178\n", - "Kc = 8.418156125054411e-7\n", - "proton+OC=C(O)[Pt]<=>OC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.835798651062412e-24\n", - "Kc = 3.190485247679302e33\n", - "vacantX+vacantX+OC=CO<=>HOX+OC=C[Pt]\n", - "kf = 1.882970379851619e-8\n", - "krev = 6.2613640604613945e13\n", - "Kc = 3.0072846134950095e-22\n", - "vacantX+vacantX+C=CO<=>HX+OC=C[Pt]\n", - "kf = 5.986889507133711e-22\n", - "krev = 1492.047811549125\n", - "Kc = 4.0125319448830507e-25\n", - "proton+OC=C[Pt]<=>OCC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.693803965028289e7\n", - "Kc = 1475.967733939179\n", - "vacantX+vacantX+O=CC=CO<=>CHOX+OC=C[Pt]\n", - "kf = 3.6404040231768274e-5\n", - "krev = 5.1339082800935775e14\n", - "Kc = 7.090901949480236e-20\n", - "proton+OC=C=[Pt]<=>OC=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.9001266800545872e-45\n", - "Kc = 1.3157017509633512e55\n", - "vacantX+vacantX+OC=CCO<=>OC[Pt]+OC=C[Pt]\n", - "kf = 1.39754480380523e-13\n", - "krev = 4.435737343310229e14\n", - "Kc = 3.1506482364492156e-28\n", - "vacantX+vacantX+CC=CO<=>CH3X+OC=C[Pt]\n", - "kf = 3.0518560755450534e-15\n", - "krev = 1.440283576497463e15\n", - "Kc = 2.1189272205454667e-30\n", - "vacantX+vacantX+CC=C(O)O<=>OC(O)=[Pt]+CC=[Pt]\n", - "kf = 3.314404876424973e-50\n", - "krev = 3.298291971460818e17\n", - "Kc = 1.0048852269912959e-67\n", - "HX+O=C=CO<=>OC=CO[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 5.830973747204281e-42\n", - "Kc = 4.885709192226705e33\n", - "vacantX+vacantX+OC=CO<=>HX+OC=CO[Pt]\n", - "kf = 6.3392542923960805e-6\n", - "krev = 0.0008631955285686626\n", - "Kc = 0.007343937824733329\n", - "proton+O=C=CO.[Pt]<=>OC=CO[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.575140256117379e-26\n", - "Kc = 4.4841921192150256e35\n", - "proton+OC=CO[Pt]<=>OX+C=CO\n", - "kf = 2.262727495050209e-8\n", - "krev = 2.5678564004292932e-5\n", - "Kc = 0.0008811736881672694\n", - "proton+OC=CO[Pt]<=>OC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.711725523568878e-6\n", - "Kc = 6.73541182968781e15\n", - "proton+OC=COC#[Pt]<=>CX+OC=CO\n", - "kf = 2.2492341197526439e-29\n", - "krev = 0.00020529518482061674\n", - "Kc = 1.0956097785332785e-25\n", - "vacantX+vacantX+CCC(=O)O<=>CH3X+O=C(O)C[Pt]\n", - "kf = 8.997747599742267e-17\n", - "krev = 6.572577910715489e15\n", - "Kc = 1.368983026442782e-32\n", - "vacantX+vacantX+CCC(=O)O<=>CO2HX+CC[Pt]\n", - "kf = 3.388822996448631e-6\n", - "krev = 1.0293603282987281e15\n", - "Kc = 3.292163981148853e-21\n", - "vacantX+vacantX+CCC(=O)O<=>HOX+CCC(=O)[Pt]\n", - "kf = 2.1491486919570496e-14\n", - "krev = 4.131728096070369e12\n", - "Kc = 5.201573390081201e-27\n", - "vacantX+vacantX+CCC(=O)O<=>HX+CCC(=O)O[Pt]\n", - "kf = 2.415446383235281e-20\n", - "krev = 451.7273406124814\n", - "Kc = 5.347133472063615e-23\n", - "proton+O=C([Pt])C=CO<=>OCX+C=CO\n", - "kf = 224.18396606543615\n", - "krev = 8.215700647740584e-7\n", - "Kc = 2.728726078001508e8\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=C([Pt])C=CO\n", - "kf = 2.859565189776071e-11\n", - "krev = 0.000933578065584948\n", - "Kc = 3.06301668300697e-8\n", - "HX+O=C=C=CO<=>O=C([Pt])C=CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.1750295723598082e-43\n", - "Kc = 2.206855353748942e35\n", - "proton+O=C=C=CO.[Pt]<=>O=C([Pt])C=CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.234268290529092e-27\n", - "Kc = 2.0254915557527025e37\n", - "proton+OC=C(O)C#[Pt]<=>CX+OC=CO\n", - "kf = 2.8680661830740045e-24\n", - "krev = 729.307267106125\n", - "Kc = 3.932589612680575e-27\n", - "vacantX+vacantX+C=COO<=>OO[Pt]+C=C[Pt]\n", - "kf = 0.00256837059370255\n", - "krev = 1.2695573429161084e13\n", - "Kc = 2.0230441799526235e-16\n", - "vacantX+vacantX+C=COO<=>HOX+C=CO[Pt]\n", - "kf = 3.07907263663438e8\n", - "krev = 5.547742278067932e-15\n", - "Kc = 5.5501364019864025e22\n", - "vacantX+vacantX+C=COO<=>CH2X+OOC=[Pt]\n", - "kf = 7.483948884590266e-53\n", - "krev = 2.8103204909201245e17\n", - "Kc = 2.6630232775123643e-70\n", - "proton+OC=CC#[Pt]<=>CX+C=CO\n", - "kf = 1.0593841984272302e-19\n", - "krev = 13.369077699035607\n", - "Kc = 7.924138241066921e-21\n", - "proton+OCC[Pt]<=>CH2X+CO-2\n", - "kf = 3.9799160772985795e-6\n", - "krev = 0.00035437522440524626\n", - "Kc = 0.011230796633647675\n", - "vacantX+vacantX+OCCO<=>HOX+OCC[Pt]\n", - "kf = 2.110093084979835e-12\n", - "krev = 2.4085316622580622e14\n", - "Kc = 8.760910716040024e-27\n", - "HX+C=CO<=>OCC[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 1.1429411507382647e-15\n", - "Kc = 2.8609207088741057e7\n", - "HOX+C=C<=>OCC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 2.2750559854988554e-15\n", - "Kc = 3.602118089238167e7\n", - "proton+OCC=[Pt]<=>OCC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.1399343496076094e-34\n", - "Kc = 2.1931087530264836e44\n", - "vacantX+vacantX+CCO<=>HX+OCC[Pt]\n", - "kf = 4.51610258482867e-23\n", - "krev = 15472.547765874588\n", - "Kc = 2.918784063985339e-27\n", - "vacantX+vacantX+O=CCCO<=>CHOX+OCC[Pt]\n", - "kf = 2.0496526220764064\n", - "krev = 1.4633869198921762e15\n", - "Kc = 1.4006224835106677e-15\n", - "HX+C#C<=>C=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 2.375601900047824e-24\n", - "Kc = 3.580716650609497e16\n", - "CHOX+C#C<=>O=CC=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 3.2359557228060194e-16\n", - "Kc = 2.6287001452988416e8\n", - "HOX+C#C<=>OC=C[Pt]\n", - "kf = 8.506357278720801e-8\n", - "krev = 2.419253665005007e-25\n", - "Kc = 3.516108046777805e17\n", - "proton+OCCC#[Pt]<=>CX+CCO\n", - "kf = 0.036583470766554806\n", - "krev = 0.0005754138836916786\n", - "Kc = 63.577664361948486\n", - "OC[Pt]+C=C=O<=>O=C([Pt])CCO\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.869121889511259e-30\n", - "Kc = 1.7908695590280368e22\n", - "HX+O=C=CCO<=>O=C([Pt])CCO\n", - "kf = 2.5565910629172877e-8\n", - "krev = 3.7973012083800085e-37\n", - "Kc = 6.732652804247709e28\n", - "proton+O=C=CCO.[Pt]<=>O=C([Pt])CCO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.5089082544191712e-24\n", - "Kc = 1.6568270421201532e34\n", - "proton+O=C([Pt])CCO<=>OCX+CCO\n", - "kf = 9.600816617542319e7\n", - "krev = 3.185535798116408e-7\n", - "Kc = 3.0138781121904944e14\n", - "vacantX+vacantX+O=CCCO<=>HX+O=C([Pt])CCO\n", - "kf = 4.786286134347495e-11\n", - "krev = 0.0006355926831038164\n", - "Kc = 7.530429883135883e-8\n", - "vacantX+vacantX+C=COC<=>CO[Pt]+C=C[Pt]\n", - "kf = 1.9108708710628152e-14\n", - "krev = 5.750545812867103e12\n", - "Kc = 3.322938262290088e-27\n", - "vacantX+vacantX+C=COC<=>CH3X+C=CO[Pt]\n", - "kf = 8.809048609670953e-10\n", - "krev = 5.30334818480063e15\n", - "Kc = 1.6610353125441853e-25\n", - "vacantX+vacantX+C=COC<=>CH2X+COC=[Pt]\n", - "kf = 2.00333233616492e-67\n", - "krev = 2.0086736136424638e14\n", - "Kc = 9.973408932933319e-82\n", - "C=O+OC[Pt]<=>OCCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 4.726586049973397e-6\n", - "Kc = 0.00837955829095468\n", - "HX+O=CCO<=>OCCO[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 7.096612291679358e-6\n", - "Kc = 0.003946413774492056\n", - "vacantX+vacantX+OCCO<=>HX+OCCO[Pt]\n", - "kf = 1.0265256602604584e-26\n", - "krev = 112849.3186381155\n", - "Kc = 9.09642763154215e-32\n", - "proton+O=CCO.[Pt]<=>OCCO[Pt]\n", - "kf = 3.478307222117794e6\n", - "krev = 3581.5775849412535\n", - "Kc = 971.1662360023528\n", - "proton+OCCO[Pt]<=>OX+CCO\n", - "kf = 951266.6788585404\n", - "krev = 3.3388075163598663e-18\n", - "Kc = 2.8491210535420697e23\n", - "proton+OCCOC#[Pt]<=>CX+OCCO\n", - "kf = 6.336022152476698e-22\n", - "krev = 5.125095889500872e-13\n", - "Kc = 1.2362738744959868e-9\n", - "vacantX+vacantX+C=CC(O)O<=>OC(O)[Pt]+C=C[Pt]\n", - "kf = 1.3588265576828814e-16\n", - "krev = 6.093754170226661e16\n", - "Kc = 2.2298676968656565e-33\n", - "proton+O=C=C=C=[Pt]<=>O=C=CC#[Pt]\n", - "kf = 8.597534639917141e-9\n", - "krev = 2.1202950562509243e-60\n", - "Kc = 4.0548765204023916e51\n", - "vacantX+vacantX+O=C=C=C=O<=>OX+O=C=C=C=[Pt]\n", - "kf = 6.451439297868635e-57\n", - "krev = 8.482832416110645e14\n", - "Kc = 7.60528910793525e-72\n", - "proton+O=C=C=C(O)[Pt]<=>H2O+O=C=C=C=[Pt]\n", - "kf = 1.6149902683641734e-11\n", - "krev = 0.12950076972214764\n", - "Kc = 1.2470893198775887e-10\n", - "proton+O=C=C=C=[Pt]<=>O=C=C=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.039016761990757e-51\n", - "Kc = 6.189625216528679e60\n", - "vacantX+C=CO<=>C=CO.[Pt]\n", - "kf = 412885.969273148\n", - "krev = 1.1342794009872417\n", - "Kc = 364007.288604364\n", - "proton+C=CO[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.484544240591893e-27\n", - "Kc = 5.574702502366298e36\n", - "proton+OC=C[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.090002516938126e-28\n", - "Kc = 6.112465676112982e37\n", - "proton+C=CO.[Pt]<=>OCC[Pt]\n", - "kf = 1.7684909297990441e9\n", - "krev = 0.3339506079512917\n", - "Kc = 5.295666148501179e9\n", - "vacantX+vacantX+C=COCO<=>OCO[Pt]+C=C[Pt]\n", - "kf = 1.4197397308458187e-12\n", - "krev = 3.0290185667479297e13\n", - "Kc = 4.6871278586123213e-26\n", - "vacantX+vacantX+C=COCO<=>OC[Pt]+C=CO[Pt]\n", - "kf = 1.0263854075463885e-7\n", - "krev = 1.9545487277553856e14\n", - "Kc = 5.251265384031101e-22\n", - "HX+C=C=O<=>C=C(O)[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 3.2362559658776053e-12\n", - "Kc = 10343.290300064218\n", - "proton+C=C=O.[Pt]<=>C=C(O)[Pt]\n", - "kf = 0.5863133386822127\n", - "krev = 3624.832599039063\n", - "Kc = 0.00016174908017480404\n", - "vacantX+vacantX+C=CO<=>HX+C=C(O)[Pt]\n", - "kf = 4.00965787691315e-19\n", - "krev = 4.055766485027893\n", - "Kc = 9.886313454472895e-20\n", - "vacantX+vacantX+C=C(O)O<=>HOX+C=C(O)[Pt]\n", - "kf = 3.9452234947489745e-7\n", - "krev = 1.361002505571871e12\n", - "Kc = 2.8987628447394044e-19\n", - "proton+C=C(O)[Pt]<=>H2O+C=C=[Pt]\n", - "kf = 0.1408093188614318\n", - "krev = 0.006096548509334685\n", - "Kc = 23.09656334987455\n", - "proton+C=C(O)[Pt]<=>CC(O)=[Pt]\n", - "kf = 1.124057689749841e8\n", - "krev = 4.718570974473911e-12\n", - "Kc = 2.382199390092179e19\n", - "vacantX+vacantX+C=C(O)C=O<=>CHOX+C=C(O)[Pt]\n", - "kf = 2.8052009086647103\n", - "krev = 2.294429327232502e13\n", - "Kc = 1.2226137782366527e-13\n", - "proton+C=C(O)[Pt]<=>C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0077190030498644e-22\n", - "Kc = 2.4808503088993487e32\n", - "HOX+C=C=O<=>C=C(O)O[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.6625343699967689e-31\n", - "Kc = 2.0134040862236038e23\n", - "proton+C=C(O)O[Pt]<=>OX+C=CO\n", - "kf = 7.621772041144703e-10\n", - "krev = 0.16987445654378072\n", - "Kc = 4.4867087119601115e-9\n", - "vacantX+vacantX+C=C(O)O<=>HX+C=C(O)O[Pt]\n", - "kf = 8.7276566297004e-6\n", - "krev = 1.546723677424112e-6\n", - "Kc = 5.6426734503963205\n", - "vacantX+vacantX+C=CCOO<=>OOC[Pt]+C=C[Pt]\n", - "kf = 2.5331825038162864e-12\n", - "krev = 1.769892843246248e17\n", - "Kc = 1.4312632052740838e-29\n", - "proton+C=C(O)OC#[Pt]<=>CX+C=C(O)O\n", - "kf = 1.0744261387122509e-22\n", - "krev = 181.85749301564874\n", - "Kc = 5.908066370516815e-25\n", - "proton+C=C(O)C#[Pt]<=>CX+C=CO\n", - "kf = 3.691417083839596e-20\n", - "krev = 61.67110810051338\n", - "Kc = 5.985650651555046e-22\n", - "vacantX+vacantX+C=COOC<=>COO[Pt]+C=C[Pt]\n", - "kf = 0.0009962735751002543\n", - "krev = 4.495422962203487e13\n", - "Kc = 2.21619541359445e-17\n", - "vacantX+vacantX+C=COOC<=>CO[Pt]+C=CO[Pt]\n", - "kf = 2.772273774659678e8\n", - "krev = 3.7705323383409334e-17\n", - "Kc = 7.352473141443741e24\n", - "proton+C=C(O)C(=O)[Pt]<=>OCX+C=CO\n", - "kf = 985.1540455146012\n", - "krev = 5.159085449148215e-7\n", - "Kc = 1.9095517126533618e9\n", - "HOX+C=C=C=O<=>C=C(O)C(=O)[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 3.5720015577500406e-52\n", - "Kc = 8.264488540948707e43\n", - "vacantX+vacantX+C=C(O)C=O<=>HX+C=C(O)C(=O)[Pt]\n", - "kf = 2.8595651897765786e-11\n", - "krev = 0.000933577098423846\n", - "Kc = 3.063019856211522e-8\n", - "proton+C=COO[Pt]<=>OX+C=CO\n", - "kf = 43.93537738533433\n", - "krev = 6.669135249611683e-61\n", - "Kc = 6.587867203306832e61\n", - "O=O+C=C[Pt]<=>C=COO[Pt]\n", - "kf = 7.67336777731166e-8\n", - "krev = 1.0833501613715598e-32\n", - "Kc = 7.082998693235901e24\n", - "vacantX+vacantX+C=COO<=>HX+C=COO[Pt]\n", - "kf = 4.552726448583842e-23\n", - "krev = 27.53540659037694\n", - "Kc = 1.6534081069915729e-24\n", - "vacantX+vacantX+C=COOC<=>CH3X+C=COO[Pt]\n", - "kf = 2.287071149777874e-9\n", - "krev = 2.2490557638427473e13\n", - "Kc = 1.0169028205286352e-22\n", - "vacantX+vacantX+CC(O)=CO<=>OC=[Pt]+CC(O)=[Pt]\n", - "kf = 7.128045206079291e-31\n", - "krev = 1.6024698052635947e11\n", - "Kc = 4.4481619451835966e-42\n", - "vacantX+vacantX+CC(O)=CO<=>CH3X+OC=C(O)[Pt]\n", - "kf = 1.2021042471738558e-26\n", - "krev = 3.79937896614338e12\n", - "Kc = 3.163949313521812e-39\n", - "proton+O=CC=C=[Pt]<=>O=CCC#[Pt]\n", - "kf = 62.9877146015209\n", - "krev = 8.316144406521062e-31\n", - "Kc = 7.574148730766316e31\n", - "vacantX+vacantX+O=C=CC=O<=>OX+O=CC=C=[Pt]\n", - "kf = 1.1758489216219413e-43\n", - "krev = 2.1453863988577092e16\n", - "Kc = 5.480825842132732e-60\n", - "proton+O=CC=C=[Pt]<=>O=CC=C[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.331702565774384e-47\n", - "Kc = 2.6790395240083815e56\n", - "proton+C=C=C=O.[Pt]<=>O=C=CC[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.2229421483387703e-16\n", - "Kc = 1.1246356554390213e26\n", - "vacantX+C=C=C=O<=>C=C=C=O.[Pt]\n", - "kf = 372758.92921022984\n", - "krev = 0.5077615475124772\n", - "Kc = 734122.012658058\n", - "proton+C=C=C=O.[Pt]<=>CC([Pt])=C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.123273247571115e-16\n", - "Kc = 1.1774273531962195e26\n", - "proton+C=C=C=O.[Pt]<=>C=CC(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.171161147913428e-32\n", - "Kc = 4.834504144216726e41\n", - "proton+O=C=C=C[Pt]<=>C=C=C=O.[Pt]\n", - "kf = 3.820491632517615e9\n", - "krev = 3.925100397444825e-12\n", - "Kc = 9.733487670798667e20\n", - "vacantX+vacantX+C=C(C)O<=>CH2X+CC(O)=[Pt]\n", - "kf = 1.2526307828427685e-31\n", - "krev = 1.8291181793687947e14\n", - "Kc = 6.848276929132241e-46\n", - "vacantX+vacantX+C=C(C)O<=>CH3X+C=C(O)[Pt]\n", - "kf = 6.412809230790006e-14\n", - "krev = 6.896161957802356e13\n", - "Kc = 9.299098933624258e-28\n", - "HX+O=C=C=C=O<=>O=C=C=CO[Pt]\n", - "kf = 5.262522960320117e-8\n", - "krev = 6.474039280394542e-15\n", - "Kc = 8.128654665807662e6\n", - "proton+O=C=C=C=O.[Pt]<=>O=C=C=CO[Pt]\n", - "kf = 2.4048564698523636e10\n", - "krev = 0.03636685994081414\n", - "Kc = 6.612769080877996e11\n", - "proton+O=C=C=CO[Pt]<=>OX+C=C=C=O\n", - "kf = 7.675790818902377e-14\n", - "krev = 0.0006735755949001122\n", - "Kc = 1.1395589265731426e-10\n", - "vacantX+vacantX+O=C=C=CO<=>HX+O=C=C=CO[Pt]\n", - "kf = 4.194899212644372e-10\n", - "krev = 0.014508998351933198\n", - "Kc = 2.891239705796395e-8\n", - "proton+O=C=C=CO[Pt]<=>O=C=C=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4612716650323904e-11\n", - "Kc = 1.71083862078759e21\n", - "proton+CC(O)[Pt]<=>OC=[Pt]+CH4\n", - "kf = 59.397807135376084\n", - "krev = 1.2803453253139382e-6\n", - "Kc = 4.639202093451769e7\n", - "HX+C=CO<=>CC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 1.2254518112062234e-21\n", - "Kc = 2.668292606261641e13\n", - "HX+CC=O<=>CC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 2.4645381117653586e-12\n", - "Kc = 13267.654460532101\n", - "vacantX+vacantX+CCO<=>HX+CC(O)[Pt]\n", - "kf = 1.7361137032745595e-19\n", - "krev = 63.774720976875884\n", - "Kc = 2.72225997492652e-21\n", - "vacantX+vacantX+CC(O)O<=>HOX+CC(O)[Pt]\n", - "kf = 7.380915652046712e-14\n", - "krev = 2.775462823415347e13\n", - "Kc = 2.6593458899096773e-27\n", - "proton+CC=O.[Pt]<=>CC(O)[Pt]\n", - "kf = 36132.65188770086\n", - "krev = 0.006356177292382113\n", - "Kc = 5.68465135971048e6\n", - "proton+CC(O)[Pt]<=>H2O+CC=[Pt]\n", - "kf = 2964.0563969386994\n", - "krev = 0.019559355499681682\n", - "Kc = 151541.61889367664\n", - "proton+CC(O)=[Pt]<=>CC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 4.860369956892034e-19\n", - "Kc = 5.143641373338227e28\n", - "vacantX+vacantX+CC(O)C=O<=>CHOX+CC(O)[Pt]\n", - "kf = 753631.9525109725\n", - "krev = 9.011518944421836e14\n", - "Kc = 8.362984721654206e-10\n", - "proton+C=CO.[Pt]<=>CC(O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 5.061646123775542e-6\n", - "Kc = 4.939104668453628e15\n", - "HX+C#CC=O<=>O=CC=C[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 1.9866745274914506e-30\n", - "Kc = 1.4859387148609413e22\n", - "proton+CC(O)C#[Pt]<=>CX+CCO\n", - "kf = 1.3617819786307934\n", - "krev = 4.084110860281074e-5\n", - "Kc = 33343.413663777814\n", - "O=CO+CH3X<=>CC(O)O[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 7.324156308451427e-7\n", - "Kc = 0.043678018970166745\n", - "HOX+CC=O<=>CC(O)O[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 7.587328136505701e-13\n", - "Kc = 43096.38318446866\n", - "HX+CC(=O)O<=>CC(O)O[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 4598.938099177113\n", - "Kc = 6.089703295881323e-12\n", - "proton+CC(O)O[Pt]<=>OX+CCO\n", - "kf = 1.6583777607664147e6\n", - "krev = 1.6983423991371652e-6\n", - "Kc = 9.764684445309413e11\n", - "vacantX+vacantX+CC(O)O<=>HX+CC(O)O[Pt]\n", - "kf = 4.052122584605618e-24\n", - "krev = 469.09529347560436\n", - "Kc = 8.638165082797514e-27\n", - "proton+CC(=O)O.[Pt]<=>CC(O)O[Pt]\n", - "kf = 0.7475019896975738\n", - "krev = 3555.8603422114556\n", - "Kc = 0.00021021691454639312\n", - "vacantX+vacantX+OC=C=CO<=>OC=[Pt]+OC=C=[Pt]\n", - "kf = 3.0449395213240036e-51\n", - "krev = 1.4315520101841116e12\n", - "Kc = 2.1270198355785863e-63\n", - "CH3X+O=C=CO<=>CC(O)C(=O)[Pt]\n", - "kf = 2.8488442036348548e-8\n", - "krev = 4.477216581188038e-53\n", - "Kc = 6.362980552705156e44\n", - "proton+CC(O)C(=O)[Pt]<=>OCX+CCO\n", - "kf = 9.570476890072168e7\n", - "krev = 4.96015815008412e-7\n", - "Kc = 1.929470109720163e14\n", - "HOX+CC=C=O<=>CC(O)C(=O)[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 3.536759710167166e-36\n", - "Kc = 8.195394062368554e27\n", - "HX+CC(O)=C=O<=>CC(O)C(=O)[Pt]\n", - "kf = 2.5565910629172877e-8\n", - "krev = 4.830700359768998e-42\n", - "Kc = 5.292381792522405e33\n", - "vacantX+vacantX+CC(O)C=O<=>HX+CC(O)C(=O)[Pt]\n", - "kf = 4.786286134353719e-11\n", - "krev = 0.0006355923790078162\n", - "Kc = 7.530433486042254e-8\n", - "proton+CC(O)=C=O.[Pt]<=>CC(O)C(=O)[Pt]\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.368412782384192e-31\n", - "Kc = 1.8269341182594315e41\n", - "proton+CC(O)OC#[Pt]<=>CX+CC(O)O\n", - "kf = 2.7873525673015004e-16\n", - "krev = 1.8374709107747412e-8\n", - "Kc = 1.516950581887719e-8\n", - "vacantX+vacantX+CCOC<=>CO[Pt]+CC[Pt]\n", - "kf = 2.3627317133785774e-11\n", - "krev = 3.856091265609508e13\n", - "Kc = 6.127271246016828e-25\n", - "vacantX+vacantX+CCOC<=>CH3X+CCO[Pt]\n", - "kf = 6.326940367296449e-9\n", - "krev = 1.8372911814097844e13\n", - "Kc = 3.443624195943553e-22\n", - "vacantX+vacantX+CCOC<=>CH3X+COC[Pt]\n", - "kf = 1.3389399016858639e-14\n", - "krev = 2.773400746132106e14\n", - "Kc = 4.8277909478217395e-29\n", - "proton+O=C=C(O)C[Pt]<=>CH2X+O=C=CO\n", - "kf = 4.2042874371743854e-22\n", - "krev = 1.1101526849597185\n", - "Kc = 3.787125405481442e-22\n", - "HOX+C=C=C=O<=>O=C=C(O)C[Pt]\n", - "kf = 2.952076594227614e-8\n", - "krev = 6.322264310888409e-36\n", - "Kc = 4.669334354059592e27\n", - "vacantX+vacantX+CC(O)=C=O<=>HX+O=C=C(O)C[Pt]\n", - "kf = 6.004181315465852e-13\n", - "krev = 0.19478740167193392\n", - "Kc = 3.082427951669201e-12\n", - "proton+O=C=C(O)C[Pt]<=>CC(O)=C=O.[Pt]\n", - "kf = 1.859235052213257e9\n", - "krev = 4.357618832801525e-11\n", - "Kc = 4.266630753057283e19\n", - "proton+O=C=C(O)C=[Pt]<=>CHX+O=C=CO\n", - "kf = 1.807627844430322e-6\n", - "krev = 0.0010238577171457239\n", - "Kc = 0.0017655068806528764\n", - "proton+O=C=C(O)C#[Pt]<=>O=C=C(O)C=[Pt]\n", - "kf = 2.5e10\n", - "krev = 3.347883511420028\n", - "Kc = 7.467404380923659e9\n", - "proton+O=C=C(O)C=[Pt]<=>O=C=C(O)C[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4404183806094484e-33\n", - "Kc = 1.735606844271341e43\n", - "vacantX+vacantX+CCCO<=>OC[Pt]+CC[Pt]\n", - "kf = 4.648157058598011e-13\n", - "krev = 1.3999921584371802e15\n", - "Kc = 3.3201307811515004e-28\n", - "vacantX+vacantX+CCCO<=>CH3X+OCC[Pt]\n", - "kf = 1.2211065235504926e-16\n", - "krev = 1.2627143633797795e15\n", - "Kc = 9.670488900451568e-32\n", - "proton+CC([Pt])OC=O<=>CH4+O=COC=[Pt]\n", - "kf = 1.0679856406424377e-15\n", - "krev = 0.2905260385078575\n", - "Kc = 3.6760410396521245e-15\n", - "CHOX+CC=O<=>CC([Pt])OC=O\n", - "kf = 3.269864007171502e-8\n", - "krev = 0.48922244404245907\n", - "Kc = 6.68379802887317e-8\n", - "HX+C=COC=O<=>CC([Pt])OC=O\n", - "kf = 2.5565910629172877e-8\n", - "krev = 1.2259112200812889e-16\n", - "Kc = 2.0854618352769157e8\n", - "vacantX+vacantX+CCOC=O<=>HX+CC([Pt])OC=O\n", - "kf = 6.519502059052115e-22\n", - "krev = 142.86665816232104\n", - "Kc = 4.563347489828482e-24\n", - "proton+CC([Pt])OC=O<=>O=CO+CC=[Pt]\n", - "kf = 8049.244255788158\n", - "krev = 0.00029431628636694825\n", - "Kc = 2.7348959703006394e7\n", - "proton+CC(=[Pt])OC=O<=>CH4+O=COC#[Pt]\n", - "kf = 4.771264023974434e9\n", - "krev = 10.578082715743388\n", - "Kc = 4.510518732164335e8\n", - "proton+CC(=[Pt])OC=O<=>O=CO+CC#[Pt]\n", - "kf = 7292.02651577905\n", - "krev = 8.53932827082491e-43\n", - "Kc = 8.539344412712957e45\n", - "proton+CC(=[Pt])OC=O<=>CC([Pt])OC=O\n", - "kf = 2.5e10\n", - "krev = 2.5945295399651927e-47\n", - "Kc = 9.635658262860014e56\n", - "vacantX+vacantX+CCC(O)O<=>OC(O)[Pt]+CC[Pt]\n", - "kf = 3.712816041087776e-19\n", - "krev = 9.367983662004229e16\n", - "Kc = 3.9633032838716965e-36\n", - "vacantX+O=CC=CO<=>O=CC=CO.[Pt]\n", - "kf = 322820.94201247423\n", - "krev = 0.8868529608572997\n", - "Kc = 364007.2889878057\n", - "proton+O=CC=CO[Pt]<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.467206835324098e-11\n", - "Kc = 1.703917907012588e21\n", - "proton+O=C([Pt])C=CO<=>O=CC=CO.[Pt]\n", - "kf = 3.672999120067293e9\n", - "krev = 4.587068754429701e-12\n", - "Kc = 8.00729031262133e20\n", - "HX+O=C=CC=O<=>O=CC=C(O)[Pt]\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.0473065138531246e-21\n", - "Kc = 2.475989854235963e13\n", - "proton+O=C=CC=O.[Pt]<=>O=CC=C(O)[Pt]\n", - "kf = 9.946079261837086e6\n", - "krev = 6.687641252513296e-9\n", - "Kc = 1.4872327755468685e15\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC=C(O)[Pt]\n", - "kf = 2.77963678004065e-20\n", - "krev = 3.601218827022036\n", - "Kc = 7.718600045027592e-21\n", - "proton+O=CC=C(O)[Pt]<=>H2O+O=CC=C=[Pt]\n", - "kf = 2.367383825493301e-13\n", - "krev = 16.1722227709439\n", - "Kc = 1.463858035487058e-14\n", - "proton+O=CC=C(O)[Pt]<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 7.867624236214861e-24\n", - "Kc = 3.177579311035777e33\n", - "vacantX+vacantX+CCOCO<=>OCO[Pt]+CC[Pt]\n", - "kf = 2.4512530384253315e-9\n", - "krev = 3.614837695546209e14\n", - "Kc = 6.781087409389048e-24\n", - "vacantX+vacantX+CCOCO<=>OC[Pt]+CCO[Pt]\n", - "kf = 1.0293700832173347e-6\n", - "krev = 1.2050997101819434e12\n", - "Kc = 8.541783509863451e-19\n", - "vacantX+vacantX+O=CC=CO<=>HX+O=CC([Pt])=CO\n", - "kf = 4.3007284274917255e-15\n", - "krev = 1.9561961334382385\n", - "Kc = 2.1985159636997663e-15\n", - "HX+O=C=C=CO<=>O=CC([Pt])=CO\n", - "kf = 2.5931203025755725e-8\n", - "krev = 1.6370748462102965e-36\n", - "Kc = 1.5839961798805036e28\n", - "proton+O=CC([Pt])=CO<=>C=O+OC=C=[Pt]\n", - "kf = 4.3296354594819855e-33\n", - "krev = 908.9754469679581\n", - "Kc = 4.76320397203711e-36\n", - "proton+O=C=C=CO.[Pt]<=>O=CC([Pt])=CO\n", - "kf = 2.4999999999999992e10\n", - "krev = 1.7196074204687593e-20\n", - "Kc = 1.4538201977044896e30\n", - "HOX+C#CC=O<=>O=CC([Pt])=CO\n", - "kf = 2.952076594227614e-8\n", - "krev = 4.790462195255654e-44\n", - "Kc = 6.162404531970363e35\n", - "proton+O=CC([Pt])=CO<=>O=CC=CO.[Pt]\n", - "kf = 2.5e10\n", - "krev = 2.2409630475480663e-18\n", - "Kc = 1.1155918000233681e28\n", - "proton+OC=CC=[Pt]<=>CHX+C=CO\n", - "kf = 0.3708119772368373\n", - "krev = 1.9743851754031655e-5\n", - "Kc = 18781.136621992628\n", - "vacantX+vacantX+O=CC=CO<=>OX+OC=CC=[Pt]\n", - "kf = 8.803023976547135e-28\n", - "krev = 1.526615583505237e17\n", - "Kc = 5.766365856383213e-45\n", - "proton+OC=CC#[Pt]<=>OC=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.4263979915391943e-8\n", - "Kc = 1.7526665172195773e18\n", - "vacantX+vacantX+CCCOO<=>OOC[Pt]+CC[Pt]\n", - "kf = 5.56726706794292e-16\n", - "krev = 4.282042054393877e17\n", - "Kc = 1.3001430152303739e-33\n", - "proton+OCC(O)[Pt]<=>OC=[Pt]+CO-2\n", - "kf = 0.16339719354915763\n", - "krev = 6.17359485423602e-8\n", - "Kc = 2.6467106670766133e6\n", - "HX+O=CCO<=>OCC(O)[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 4.347223516290618e-14\n", - "Kc = 644231.1603064304\n", - "vacantX+vacantX+OCCO<=>HX+OCC(O)[Pt]\n", - "kf = 7.314142036323851e-21\n", - "krev = 492.5535033039904\n", - "Kc = 1.4849436634317805e-23\n", - "HX+OC=CO<=>OCC(O)[Pt]\n", - "kf = 5.6012337000223925e-8\n", - "krev = 1.5412075197181771e-21\n", - "Kc = 3.634315060340885e13\n", - "HOX+C=CO<=>OCC(O)[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 6.743155058263278e-19\n", - "Kc = 4.8491603395127426e10\n", - "proton+O=CCO.[Pt]<=>OCC(O)[Pt]\n", - "kf = 698182.0065765544\n", - "krev = 4.403884986144656e-6\n", - "Kc = 1.5853774764171848e11\n", - "proton+OCC(O)[Pt]<=>H2O+OCC=[Pt]\n", - "kf = 0.7285659975205578\n", - "krev = 0.0004743003964980969\n", - "Kc = 1536.0855755124403\n", - "proton+OC=CO.[Pt]<=>OCC(O)[Pt]\n", - "kf = 4.9999999999999985e10\n", - "krev = 1.4989628309182922e-5\n", - "Kc = 3.3356397482764175e15\n", - "proton+OCC(O)C#[Pt]<=>CX+OCCO\n", - "kf = 5.26000051169577\n", - "krev = 0.00019971123776726528\n", - "Kc = 26338.02969978857\n", - "vacantX+vacantX+CCC<=>CH3X+CC[Pt]\n", - "kf = 7.798842461270165e-20\n", - "krev = 4.754727023110295e15\n", - "Kc = 1.640229275700578e-35\n", - "proton+O=C([Pt])CO<=>OCC(O)=[Pt]\n", - "kf = 4.019918430047713e-18\n", - "krev = 1.0085447542339827e12\n", - "Kc = 3.9858602339377106e-30\n", - "proton+OCC(O)=[Pt]<=>H2O+OCC#[Pt]\n", - "kf = 16209.61875952926\n", - "krev = 4.634124941714537e-41\n", - "Kc = 3.4978812533984058e44\n", - "proton+OCC(O)=[Pt]<=>OC#[Pt]+CO-2\n", - "kf = 382.95023851607715\n", - "krev = 3.536410198453644e-35\n", - "Kc = 1.0828784474253827e37\n", - "proton+OC=C(O)[Pt]<=>OCC(O)=[Pt]\n", - "kf = 6875.768524790738\n", - "krev = 1.0085447542339824e12\n", - "Kc = 6.8175145385720384e-9\n", - "proton+OCC(O)=[Pt]<=>OCC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.6015120113778689e-47\n", - "Kc = 1.5610248204439706e57\n", - "HX+COC=O<=>COC(O)[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 224.3395816271696\n", - "Kc = 1.2483828443014824e-10\n", - "proton+COC(O)[Pt]<=>OC=[Pt]+CO-2\n", - "kf = 564390.3708916149\n", - "krev = 3.282828318007529e-12\n", - "Kc = 1.7192198806002883e17\n", - "vacantX+vacantX+COCO<=>HX+COC(O)[Pt]\n", - "kf = 6.183244140051347e-23\n", - "krev = 2731.92216309053\n", - "Kc = 2.2633310068601865e-26\n", - "O=CO+CH3X<=>COC(O)[Pt]\n", - "kf = 3.1990463818100786e-8\n", - "krev = 8.503469161971292e7\n", - "Kc = 3.7620485485108396e-16\n", - "proton+COC=O.[Pt]<=>COC(O)[Pt]\n", - "kf = 7.49969185016536e-5\n", - "krev = 3658.0165064396892\n", - "Kc = 2.0502072193940793e-8\n", - "proton+COC(O)[Pt]<=>H2O+COC=[Pt]\n", - "kf = 5.10646151413012e-10\n", - "krev = 0.003546985366877098\n", - "Kc = 1.439662413557134e-7\n", - "vacantX+vacantX+CCOOC<=>COO[Pt]+CC[Pt]\n", - "kf = 1.4778859852656565e-10\n", - "krev = 2.404289853338368e13\n", - "Kc = 6.146871115450596e-24\n", - "vacantX+vacantX+CCOOC<=>CO[Pt]+CCO[Pt]\n", - "kf = 2.735304068777078e8\n", - "krev = 1.1929824589169815e-11\n", - "Kc = 2.2928284052560617e19\n", - "vacantX+vacantX+CCOOC<=>CH3X+CCOO[Pt]\n", - "kf = 1.542530561493995e-10\n", - "krev = 1.2789927244807063e12\n", - "Kc = 1.2060510837700736e-22\n", - "proton+COC(O)C#[Pt]<=>CX+COCO\n", - "kf = 0.03928313633337953\n", - "krev = 0.002914319669063903\n", - "Kc = 13.479350515448948\n", - "proton+COC(=O)[Pt]<=>COC(O)=[Pt]\n", - "kf = 6.005930457604258e-17\n", - "krev = 1.0085447542339825e12\n", - "Kc = 5.955046052632466e-29\n", - "proton+COC(O)=[Pt]<=>OC#[Pt]+CO-2\n", - "kf = 383854.3090963643\n", - "krev = 3.448448528690976e-34\n", - "Kc = 1.113121758677009e39\n", - "proton+COC(O)=[Pt]<=>H2O+COC#[Pt]\n", - "kf = 217922.49486435574\n", - "krev = 2.0340320286285714e-35\n", - "Kc = 1.0713818258372662e40\n", - "proton+COC(O)=[Pt]<=>COC(O)[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0120272229346644e-38\n", - "Kc = 2.4702892801149458e48\n", - "vacantX+vacantX+C=C=COO<=>OOC=[Pt]+C=C=[Pt]\n", - "kf = 1.9145907695639512e-44\n", - "krev = 1.1771971588384226e12\n", - "Kc = 1.626397715275781e-56\n", - "C=O+O=CC[Pt]<=>O=CCCO[Pt]\n", - "kf = 3.9606703322965305e-8\n", - "krev = 0.0025285011306884937\n", - "Kc = 1.5664103465194285e-5\n", - "HX+O=CCC=O<=>O=CCCO[Pt]\n", - "kf = 5.113182125834635e-8\n", - "krev = 3.03538509820146e-7\n", - "Kc = 0.16845250142607343\n", - "proton+O=CCC=O.[Pt]<=>O=CCCO[Pt]\n", - "kf = 2.3901708430508703e8\n", - "krev = 41.103568870106145\n", - "Kc = 5.814995896351951e6\n", - "vacantX+vacantX+O=CCCO<=>HX+O=CCCO[Pt]\n", - "kf = 2.5157725911236352e-27\n", - "krev = 8837.406478086354\n", - "Kc = 2.84673178421957e-31\n", - "proton+O=CCCO[Pt]<=>OX+CCC=O\n", - "kf = 774927.4661784222\n", - "krev = 1.1978583087682196e-18\n", - "Kc = 6.469274875884902e23\n", - "CHOX+C=C<=>O=CCC[Pt]\n", - "kf = 8.195020319394991e-8\n", - "krev = 0.4688595936220698\n", - "Kc = 1.7478623517301195e-7\n", - "proton+O=CCC[Pt]<=>CH2X+CC=O\n", - "kf = 0.0016740956920828355\n", - "krev = 4.373185000711893e-7\n", - "Kc = 3828.0925499614495\n", - "HX+C=CC=O<=>O=CCC[Pt]\n", - "kf = 2.8985139528728324e-8\n", - "krev = 7.666152073113618e-12\n", - "Kc = 3780.924152337611\n", - "proton+O=CCC=[Pt]<=>O=CCC[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.3932958912707058e-30\n", - "Kc = 1.794306590339518e40\n", - "vacantX+vacantX+O=CCCO<=>HOX+O=CCC[Pt]\n", - "kf = 8.901266563864654e-15\n", - "krev = 1.309728963703428e15\n", - "Kc = 6.79626610584771e-30\n", - "vacantX+vacantX+CCC=O<=>HX+O=CCC[Pt]\n", - "kf = 1.6716561102658422e-25\n", - "krev = 524619.2678123232\n", - "Kc = 3.186417680076247e-31\n", - "vacantX+vacantX+CC=COO<=>OOC=[Pt]+CC=[Pt]\n", - "kf = 3.7147962989308654e-50\n", - "krev = 4.0636001726377395e18\n", - "Kc = 9.141638303749602e-69\n", - "proton+C=COOC#[Pt]<=>CX+C=COO\n", - "kf = 8.811176921711816e-67\n", - "krev = 2.5e10\n", - "Kc = 3.5244707686847265e-77\n", - "vacantX+C=CC=O<=>C=CC=O.[Pt]\n", - "kf = 365995.57053717994\n", - "krev = 1.0054621985249468\n", - "Kc = 364007.290452202\n", - "proton+C=CC(=O)[Pt]<=>C=CC=O.[Pt]\n", - "kf = 3.399604827397095e9\n", - "krev = 5.959510760846119e-12\n", - "Kc = 5.704503211458966e20\n", - "proton+O=CC=C[Pt]<=>C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 8.32808736312024e-27\n", - "Kc = 3.00188973889839e36\n", - "proton+C=CC=O.[Pt]<=>O=CCC[Pt]\n", - "kf = 5.197601136262071e7\n", - "krev = 74.26603000820454\n", - "Kc = 699862.5260684955\n", - "vacantX+vacantX+C=CC=O<=>HX+C=C([Pt])C=O\n", - "kf = 1.2784478936507186e-21\n", - "krev = 132.59733776930153\n", - "Kc = 9.641580405445367e-24\n", - "proton+C=C([Pt])C=O<=>C=O+C=C=[Pt]\n", - "kf = 2.4079500300331376e-13\n", - "krev = 0.010970404022735962\n", - "Kc = 2.194951092997765e-11\n", - "HX+C=C=C=O<=>C=C([Pt])C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 2.4992009477647154e-32\n", - "Kc = 1.1812081765045545e24\n", - "vacantX+vacantX+C=C(O)C=O<=>HOX+C=C([Pt])C=O\n", - "kf = 1.107119853181277e-14\n", - "krev = 2.5289157654010746e13\n", - "Kc = 4.377843929513773e-28\n", - "proton+C=C=C=O.[Pt]<=>C=C([Pt])C=O\n", - "kf = 2.4999999999999992e10\n", - "krev = 2.305987527913534e-16\n", - "Kc = 1.0841342243780513e26\n", - "HX+C#CC=O<=>C=C([Pt])C=O\n", - "kf = 2.952076594227614e-8\n", - "krev = 1.683521621093348e-30\n", - "Kc = 1.753512730243651e22\n", - "proton+C=C([Pt])C=O<=>C=CC=O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 9.827731832923639e-27\n", - "Kc = 2.5438219545478565e36\n", - "CHOX+C=C=O<=>C=C(C=O)O[Pt]\n", - "kf = 3.3473534940386794e-8\n", - "krev = 1.906984656058423e-6\n", - "Kc = 0.017553122325364576\n", - "proton+C=C(C=O)O[Pt]<=>OX+C=CC=O\n", - "kf = 13.565263195704604\n", - "krev = 7.179044500174065e-6\n", - "Kc = 1.8895638821260543e6\n", - "vacantX+vacantX+C=C(O)C=O<=>HX+C=C(C=O)O[Pt]\n", - "kf = 8.336773502217888e-19\n", - "krev = 4.018028855986407\n", - "Kc = 2.0748416203624424e-19\n", - "vacantX+vacantX+COCOC<=>CH3X+COCO[Pt]\n", - "kf = 0.24675966205104702\n", - "krev = 5.277017405064255e15\n", - "Kc = 4.6761199198288865e-17\n", - "vacantX+vacantX+COCOC<=>CO[Pt]+COC[Pt]\n", - "kf = 4.1241018831024145e-7\n", - "krev = 7.782310155024181e12\n", - "Kc = 5.2993286067375974e-20\n", - "proton+C=CC=[Pt]<=>CHX+C=C\n", - "kf = 1.3385165927063483e6\n", - "krev = 9.028119675350497e-7\n", - "Kc = 1.4826083845132273e12\n", - "vacantX+vacantX+C=CC=O<=>OX+C=CC=[Pt]\n", - "kf = 1.438969400016978e-30\n", - "krev = 1.6093339940290013e17\n", - "Kc = 8.941396909254915e-48\n", - "proton+C=CC#[Pt]<=>C=CC=[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.067052266556579e-6\n", - "Kc = 2.342903040792558e16\n", - "vacantX+CC(O)O<=>CC(O)O.[Pt]\n", - "kf = 347843.58123444836\n", - "krev = 178209.4487483253\n", - "Kc = 1.9518806868971765\n", - "proton+CC(O)O[Pt]<=>CC(O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.64203868551119e-24\n", - "Kc = 1.5224976257010135e34\n", - "vacantX+vacantX+COCCO<=>OC[Pt]+COC[Pt]\n", - "kf = 1.3358759661274015e-7\n", - "krev = 3.1165281946439875e14\n", - "Kc = 4.286423490161954e-22\n", - "vacantX+vacantX+COCCO<=>CO[Pt]+OCC[Pt]\n", - "kf = 6.192873660096324e-8\n", - "krev = 3.90827625278604e13\n", - "Kc = 1.584553716150872e-21\n", - "vacantX+vacantX+COCCO<=>CH3X+OCCO[Pt]\n", - "kf = 4.52195120819324e-12\n", - "krev = 5.920081591014324e14\n", - "Kc = 7.638325821483257e-27\n", - "proton+OC(O)C[Pt]<=>CH2X+OCO\n", - "kf = 2.252975678309519e-7\n", - "krev = 0.002613777215265548\n", - "Kc = 8.619616335895816e-5\n", - "HOX+C=CO<=>OC(O)C[Pt]\n", - "kf = 3.269864007171502e-8\n", - "krev = 6.095879365149742e-19\n", - "Kc = 5.364056293281289e10\n", - "HX+C=C(O)O<=>OC(O)C[Pt]\n", - "kf = 2.8006168500113054e-8\n", - "krev = 1.7806643358524245e-19\n", - "Kc = 1.572793251160735e11\n", - "vacantX+vacantX+CC(O)O<=>HX+OC(O)C[Pt]\n", - "kf = 2.610914590914038e-25\n", - "krev = 48838.0104312493\n", - "Kc = 5.3460707507516085e-30\n", - "vacantX+vacantX+CCC(O)O<=>CH3X+OC(O)C[Pt]\n", - "kf = 2.73273606062798e-19\n", - "krev = 1.7143250273592365e15\n", - "Kc = 1.594059479396106e-34\n", - "proton+OC(O)C[Pt]<=>CC(O)O.[Pt]\n", - "kf = 2.5e10\n", - "krev = 1.0162407066861682e-27\n", - "Kc = 2.4600470966688416e37\n" - ] - } - ], - "source": [ - "for (i,rxn) in enumerate(inter.reactions)\n", - " str = getrxnstr(rxn)\n", - " kf = inter.kfs[i]\n", - " krev = inter.krevs[i]\n", - " Kc = kf/krev\n", - " println(str)\n", - " println(\"kf = $kf\")\n", - " println(\"krev = $krev\")\n", - " println(\"Kc = $Kc\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 79, - "id": "11333da0", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 80, - "id": "ef575a57", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.9.1", - "language": "julia", - "name": "julia-1.9" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.9.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/CO2_Reduction_Ag/CO2RR_RMS_Diffusion_Interface_Matt.jl b/CO2_Reduction_Ag/CO2RR_RMS_Diffusion_Interface_Matt.jl new file mode 100644 index 0000000..b67c57a --- /dev/null +++ b/CO2_Reduction_Ag/CO2RR_RMS_Diffusion_Interface_Matt.jl @@ -0,0 +1,265 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,jl:percent +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.17.2 +# kernelspec: +# display_name: Julia 1.9.1 +# language: julia +# name: julia-1.9 +# --- + +# %% +using ReactionMechanismSimulator +using PyPlot +using Sundials +using SciMLBase +using QuadGK + +# %% +outdict = readinput("chem300.rms") + + +# %% +boundarylayerspcs = outdict["gas"]["Species"] +boundarylayerrxns = outdict["gas"]["Reactions"] +surfspcs = outdict["surface"]["Species"] +surfrxns = outdict["surface"]["Reactions"] +interfacerxns = outdict[Set(["surface", "gas"])]["Reactions"] +solv = outdict["Solvents"][1]; + +# %% +sitedensity = 2.292e-5; # Ag111 +boundarylayer = IdealDiluteSolution(boundarylayerspcs,boundarylayerrxns,solv,name="boundarylayeruid",diffusionlimited=true); +surf = IdealSurface(surfspcs,surfrxns,sitedensity,name="surface"); + +# %% +initialcondsboundarylayer = Dict(["proton"=>10.0^-4, + "CO2"=>10.0^-3*10^6, + "V"=>1.0e-3,"T"=>300,"Phi"=>0.0,"d"=>0.0]); +initialcondsreservoir = Dict(["proton"=>10.0^-4, + "CO2"=>10.0^-3*10^6, + "V"=>1.0,"T"=>300]); +AVratio = 1e5; +initialcondssurf = Dict(["CO2X"=>0.4*sitedensity*AVratio, +# "CHO2X"=>0.1*sitedensity*AVratio, +# "CO2HX"=>0.1*sitedensity*AVratio, +# "OX"=>0.1*sitedensity*AVratio, +# "OCX"=>0.1*sitedensity*AVratio, + "vacantX"=>1.0*sitedensity*AVratio, +# "CH2O2X"=>0.05*sitedensity*AVratio, +# "CHOX"=>0.04*sitedensity*AVratio, +# "CH2OX"=>0.01*sitedensity*AVratio, + "A"=>1.0*AVratio,"T"=>300,"Phi"=>-1.0]); + +# %% +domainboundarylayer, y0boundarylayer, pboundarylayer = ConstantTVDomain(phase=boundarylayer, initialconds=initialcondsboundarylayer); +domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf, + initialconds=initialcondssurf); + +# %% +inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainboundarylayer, + domaincat,interfacerxns,298.15,AVratio*1.0); + +# %% +# start with 1mm layer thickness +diffusionlayer = ConstantReservoirDiffusion(domainboundarylayer, initialcondsreservoir, AVratio*1.0, 1e-3); + +# %% +interfaces = [inter, diffusionlayer]; + +# %% +@time react,y0,p = Reactor((domainboundarylayer,domaincat), (y0boundarylayer,y0cat), (0.0, 100.0), interfaces, (pboundarylayer,pcat,pinter)); + + +# %% +@time sol = solve(react.ode,Sundials.CVODE_BDF(),abstol=1e-16,reltol=1e-6); + +# %% +sol.t[end] + +# %% +sol.retcode + +# %% +ssys = SystemSimulation(sol,(domainboundarylayer,domaincat,), interfaces,p); + +# %% +plotmolefractions(ssys.sims[1], 0.99e2,tol=1e-25) +yscale("log") +xscale("log") + +# %% +plotmolefractions(ssys.sims[2], 0.99e2,tol=3e-2) +xscale("log") + +# %% +""" +diffusive flux to the reservoir +""" +function flux_to_reservoir(sim,t,reservoirinterface) + cs = concentrations(sim,t) + return reservoirinterface.A .* sim.domain.diffusivity .* (cs - reservoirinterface.c) / reservoirinterface.layer_thickness +end + +""" +Integrates the flux to the reservoir and computes the concentration assuming +there is no prior concentration of that species in the reservoir +""" +function get_reservoir_concentration(sim,t,reservoirinterface,Vres) + intg,err = quadgk(x -> flux_to_reservoir(sim,x,reservoirinterface), 0, t) + return intg./Vres +end + +# %% +flux_to_reservoir(ssys.sims[1],0.99e2,diffusionlayer) + +# %% +res_cs = get_reservoir_concentration(ssys.sims[1],0.99e2,diffusionlayer,1.0) + +# %% +sort(res_cs) + +# %% +getfield.(ssys.sims[1].domain.phase.species,:name) + +# %% +getfield.(ssys.sims[2].domain.phase.species,:name) + +# %% +# Helper function +function plotX(sim, tol, t_end, exclude) + clf() + xs = molefractions(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Mole Fraction") +end + +# %% +# Helper function +function plotC(sim, tol, t_end, exclude) + clf() + xs = concentrations(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Concentration") +end + +# %% +concentrations(ssys.sims[1]) + +# %% +concentrations(ssys.sims[2]) + +# %% +exclude_species = ["H2O"] +plotX(ssys.sims[1], 1e-6, 1e2, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e2) +ylim(1e-9, 5) +title("Evolution of Liquid-phase Mole Fractions vs. Time on Ag111@-1.5V") +gcf() + +# %% +exclude_species = ["H2O"] +plotC(ssys.sims[1], 1e-6, 1e2, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e2) +ylim(1e-6, 1e8) +title("Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V") +gcf() + +# %% +exclude_species = ["H2O"] +plotC(ssys.sims[2], 1e-6, 1e2, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e2) +ylim(1e-6, 1e-4) +title("Evolution of Liquid-phase Concentrations vs. Time on Ag111@-1.5V") +gcf() + +# %% +getfluxdiagram(ssys,1e2;speciesratetolerance=1e-6) + +# %% +println(ssys.names) + +# %% +rops(ssys, "O=CO", 1e-12) + +# %% +plotrops(ssys,"CH2O2X",1;N=15,tol=0.0) + +# %% +plotrops(ssys,"CHO2X",1;N=10,tol=0.0) + +# %% +plotrops(ssys,"CO2HX",1;N=10,tol=0.0) + +# %% +plotrops(ssys,"OX",1;N=10,tol=0.0) + +# %% +plotrops(ssys,"OCX",1.0e-6) + +# %% +for (i,rxn) in enumerate(inter.reactions) + str = getrxnstr(rxn) + kf = inter.kfs[i] + krev = inter.krevs[i] + Kc = kf/krev + println(str) + println("kf = $kf") + println("krev = $krev") + println("Kc = $Kc") +end + +# %% +for (i,rxn) in enumerate(inter.reactions) + str = getrxnstr(rxn) + kf = inter.kfs[i] + krev = inter.krevs[i] + Kc = kf/krev + println(str) + println("kf = $kf") + println("krev = $krev") + println("Kc = $Kc") +end + +# %% + +# %% diff --git a/CO2_Reduction_Ag/HER-Data/Validation/CO2RR_RMS_Sensitivity.jl b/CO2_Reduction_Ag/HER-Data/Validation/CO2RR_RMS_Sensitivity.jl new file mode 100644 index 0000000..2e06508 --- /dev/null +++ b/CO2_Reduction_Ag/HER-Data/Validation/CO2RR_RMS_Sensitivity.jl @@ -0,0 +1,1725 @@ +# -*- coding: utf-8 -*- +# --- +# jupyter: +# jupytext: +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.18.1 +# kernelspec: +# display_name: Julia rmg_env3 1.10 +# language: julia +# name: julia-rmg_env3-1.10 +# --- + +# %% +using Pkg +Pkg.activate(ENV["PYTHON_JULIAPKG_PROJECT"]) +using ReactionMechanismSimulator + +# %% +using PythonPlot +using DifferentialEquations +using Sundials +using SciMLBase +using QuadGK +using DataFrames +using Statistics + +function run_co2_reduction_simulation1(params::Vector{Float64}) + try + CO2_M = params[1] + pH = params[2] + surface_phi = params[3] + layer_thickness = params[4] + CO2_X_init = params[5] + + # Basic validity checks + if CO2_X_init < 0.0 || CO2_X_init > 1.0 + error("Invalid CO2 surface coverage") + end + if layer_thickness <= 0.0 + error("Invalid BL thickness") + end + + rms_file = "/home/danieltori/CO2_RR_RMG/AIChE_2025/Cu_C2_042925.rms" + outdict = readinput(rms_file) + + boundarylayerspcs = outdict["gas"]["Species"] + boundarylayerrxns = outdict["gas"]["Reactions"] + surfspcs = outdict["surface"]["Species"] + surfrxns = outdict["surface"]["Reactions"] + interfacerxns = outdict[Set(["surface", "gas"])]["Reactions"] + solv = outdict["Solvents"][1] + + sitedensity = 2.943e-5 # Cu111 + boundarylayer = IdealDiluteSolution(boundarylayerspcs, boundarylayerrxns, solv; + name="boundarylayeruid", diffusionlimited=true) + surf = IdealSurface(surfspcs, surfrxns, sitedensity; name="surface") + + C_proton = 10.0^(-pH) * 1e3 + C_co2 = CO2_M * 1e3 + V_res = 1e3 + AVratio = 36.0 + A_surf = V_res * AVratio + V_bl = A_surf * layer_thickness + sites = sitedensity * A_surf + + initialcondsboundarylayer = Dict( + "proton" => C_proton * V_bl, + "CO2" => C_co2 * V_bl, + "V" => V_bl, + "T" => 300.0, + "Phi" => 0.0, + "d" => 0.0 + ) + + initialcondsreservoir = Dict( + "proton" => C_proton, + "CO2" => C_co2, + "V" => V_res, + "T" => 300.0 + ) + + initialcondssurf = Dict( + "CO2X" => CO2_X_init * sites, + "vacantX" => (1 - CO2_X_init) * sites, + "A" => A_surf, + "T" => 300.0, + "Phi" => surface_phi + ) + + domainBL, y0BL, pBL = ConstantTVDomain(phase=boundarylayer, initialconds=initialcondsboundarylayer) + domainCAT, y0CAT, pCAT = ConstantTAPhiDomain(phase=surf, initialconds=initialcondssurf) + + inter, pinter = ReactiveInternalInterfaceConstantTPhi(domainBL, domainCAT, interfacerxns, 298.15, A_surf) + difflayer = ConstantReservoirDiffusion(domainBL, initialcondsreservoir, A_surf, layer_thickness) + + interfaces = [inter, difflayer] + + react, y0, p = Reactor( + (domainBL, domainCAT), + (y0BL, y0CAT), + (0.0, 1e3), + interfaces, + (pBL, pCAT, pinter) + ) + + sol = solve(react.ode, Sundials.CVODE_BDF(); abstol=1e-20, reltol=1e-8) + + if sol.retcode != :Success + error("CVODE failure") + end + + ssys = SystemSimulation(sol, (domainBL, domainCAT), interfaces, p) + + analysis_time = 100.0 + OCO_rate = abs(sum(rops(ssys, "O=CO", analysis_time))) + + return OCO_rate + + catch e + return log10(1e-12 + sum(abs.(params))) + end +end + + +# %% +# MORRIS +using GlobalSensitivity + +bounds = [ + [1e-5, 1e-2], + [5.0, 9.0], + [-0.714, -0.514], + [1e-6, 1e-4], + [0.5, 0.9] +] + +param_names = ["CO₂_conc", "pH", "potential", "layer_thickness", "CO2X_init"] + +morris_method = Morris( + p_steps = fill(4, 5), + relative_scale = true, + num_trajectory = 40, + total_num_trajectory = 40, + len_design_mat = 10 +) + +println("Running Morris Screening...") + +morris_resultx = gsa( + run_co2_reduction_simulation1, + morris_method, + bounds; + batch=false +) + + +# %% +param_names = ["CO₂_conc", "pH", "potential", "layer_thickness", "CO2X_init"] + +# Extract Morris outputs +Mu = morris_resultx.means[1, :] # signed mean effects +Mu_star = morris_resultx.means_star[1, :] # absolute mean effects +Sigma = morris_resultx.variances[1, :] # variance + +println("μ values = ", Mu) +println("μ* values = ", Mu_star) +println("σ² values = ", Sigma) + + +# %% +# Extract Morris results (formate / O=CO) +xs = morris_resultx.means_star[1, :] # absolute mean effects +ys = morris_resultx.variances[1, :] # variance + + +param_labels = ["CO₂_conc", "pH", "potential", "layer_thickness", "CO2X_init"] + +# SCATTER PLOT +clf() +scatter(xs, ys, color="blue", s=120) + +# LABEL EACH POINT +for i in 1:length(xs) + text(xs[i], ys[i], " $(param_labels[i])", + fontsize=12, ha="left", va="bottom") +end + +xlabel("μ* (Mean Elementary Effect)") +ylabel("σ² (Variance → nonlinearity / interaction)") +title("Morris Screening — Formate Production") +grid(true) +gcf() + + +# %% +using GlobalSensitivity + +function batch_model(P::Matrix{Float64}) + n = size(P, 2) + out = zeros(n) + for i in 1:n + out[i] = run_co2_reduction_simulation1(P[:, i]) + end + return out +end + +println("Running Sobol Sensitivity Analysis...") + +sobol_resultx = gsa( + batch_model, + Sobol(), + bounds; + samples = 200, + batch = true +) + + +# %% +clf() + +bar( + ["CO2_conc", "pH", "surface_potential", "layer_thickness", "CO2_X_init"], + sobol_resultx.S1[1, :] +) +title("First Order Indices O=CO") +xlabel("Parameters") +ylabel("S1") + +gcf() + + +# %% +clf() + +bar( + ["CO2_conc", "pH", "surface_potential", "layer_thickness", "CO2_X_init"], + sobol_resultx.ST[1, :] +) +title(" Total Order Indices O=CO") +xlabel("Parameters") +ylabel("ST") + +gcf() + + +# %% +using PythonPlot +using DifferentialEquations +using Sundials +using SciMLBase +using QuadGK +using DataFrames +using Statistics + +function run_co2_reduction_simulation2(params::Vector{Float64}) + try + CO2_M = params[1] + pH = params[2] + surface_phi = params[3] + layer_thickness = params[4] + CO2_X_init = params[5] + + # Basic validity checks + if CO2_X_init < 0.0 || CO2_X_init > 1.0 + error("Invalid CO2 surface coverage") + end + if layer_thickness <= 0.0 + error("Invalid BL thickness") + end + + rms_file = "/home/danieltori/CO2_RR_RMG/CO2_Reduction_Ag/Ag_C2_042925.rms" + outdict = readinput(rms_file) + + boundarylayerspcs = outdict["gas"]["Species"] + boundarylayerrxns = outdict["gas"]["Reactions"] + surfspcs = outdict["surface"]["Species"] + surfrxns = outdict["surface"]["Reactions"] + interfacerxns = outdict[Set(["surface", "gas"])]["Reactions"] + solv = outdict["Solvents"][1] + + sitedensity = 2.292e-5 + boundarylayer = IdealDiluteSolution(boundarylayerspcs, boundarylayerrxns, solv; + name="boundarylayeruid", diffusionlimited=true) + surf = IdealSurface(surfspcs, surfrxns, sitedensity; name="surface") + + C_proton = 10.0^(-pH) * 1e3 + C_co2 = CO2_M * 1e3 + V_res = 1e3 + AVratio = 36.0 + A_surf = V_res * AVratio + V_bl = A_surf * layer_thickness + sites = sitedensity * A_surf + + initialcondsboundarylayer = Dict( + "proton" => C_proton * V_bl, + "CO2" => C_co2 * V_bl, + "V" => V_bl, + "T" => 300.0, + "Phi" => 0.0, + "d" => 0.0 + ) + + initialcondsreservoir = Dict( + "proton" => C_proton, + "CO2" => C_co2, + "V" => V_res, + "T" => 300.0 + ) + + initialcondssurf = Dict( + "CO2X" => CO2_X_init * sites, + "vacantX" => (1 - CO2_X_init) * sites, + "A" => A_surf, + "T" => 300.0, + "Phi" => surface_phi + ) + + domainBL, y0BL, pBL = ConstantTVDomain(phase=boundarylayer, initialconds=initialcondsboundarylayer) + domainCAT, y0CAT, pCAT = ConstantTAPhiDomain(phase=surf, initialconds=initialcondssurf) + + inter, pinter = ReactiveInternalInterfaceConstantTPhi(domainBL, domainCAT, interfacerxns, 298.15, A_surf) + difflayer = ConstantReservoirDiffusion(domainBL, initialcondsreservoir, A_surf, layer_thickness) + + interfaces = [inter, difflayer] + + react, y0, p = Reactor( + (domainBL, domainCAT), + (y0BL, y0CAT), + (0.0, 1e3), + interfaces, + (pBL, pCAT, pinter) + ) + + sol = solve(react.ode, Sundials.CVODE_BDF(); abstol=1e-20, reltol=1e-8) + + if sol.retcode != :Success + error("CVODE failure") + end + + ssys = SystemSimulation(sol, (domainBL, domainCAT), interfaces, p) + + analysis_time = 100.0 + OCO_rate = abs(sum(rops(ssys, "O=CO", analysis_time))) + + return OCO_rate + + catch e + return log10(1e-12 + sum(abs.(params))) + end +end + + +# %% +# MORRIS +using GlobalSensitivity + +bounds = [ + [1e-5, 1e-2], + [5.0, 9.0], + [-0.714, -0.514], + [1e-6, 1e-4], + [0.5, 0.9] +] + +param_names = ["CO₂_conc", "pH", "potential", "layer_thickness", "CO2X_init"] + +morris_method = Morris( + p_steps = fill(4, 5), + relative_scale = true, + num_trajectory = 40, + total_num_trajectory = 40, + len_design_mat = 10 +) + +println("Running Morris Screening...") + +morris_resulty = gsa( + run_co2_reduction_simulation2, + morris_method, + bounds; + batch=false +) + + +# %% +param_names = ["CO₂_conc", "pH", "potential", "layer_thickness", "CO2X_init"] + +# Extract Morris outputs +Mu = morris_resulty.means[1, :] # signed mean effects +Mu_star = morris_resulty.means_star[1, :] # absolute mean effects +Sigma = morris_resulty.variances[1, :] # variance + +println("μ values = ", Mu) +println("μ* values = ", Mu_star) +println("σ² values = ", Sigma) + + +# %% +# Extract Morris results (formate / O=CO) +xs = morris_resulty.means_star[1, :] # absolute mean effects +ys = morris_resulty.variances[1, :] # variance + + +param_labels = ["CO₂_conc", "pH", "potential", "layer_thickness", "CO2X_init"] + +# SCATTER PLOT +clf() +scatter(xs, ys, color="blue", s=120) + +# LABEL EACH POINT +for i in 1:length(xs) + text(xs[i], ys[i], " $(param_labels[i])", + fontsize=12, ha="left", va="bottom") +end + +xlabel("μ* (Mean Elementary Effect)") +ylabel("σ² (Variance → nonlinearity / interaction)") +title("Morris Screening — Formate Production") +grid(true) +gcf() + + +# %% +using GlobalSensitivity + +function batch_model(P::Matrix{Float64}) + n = size(P, 2) + out = zeros(n) + for i in 1:n + out[i] = run_co2_reduction_simulation2(P[:, i]) + end + return out +end + +println("Running Sobol Sensitivity Analysis...") + +sobol_resulty = gsa( + batch_model, + Sobol(), + bounds; + samples = 200, + batch = true +) + + +# %% +clf() + +bar( + ["CO2_conc", "pH", "surface_potential", "layer_thickness", "CO2_X_init"], + sobol_resulty.S1[1, :] +) +title("First Order Indices O=CO") +xlabel("Parameters") +ylabel("S1") + +gcf() + + +# %% +clf() + +bar( + ["CO2_conc", "pH", "surface_potential", "layer_thickness", "CO2_X_init"], + sobol_resulty.ST[1, :] +) +title(" Total Order Indices O=CO") +xlabel("Parameters") +ylabel("ST") +gcf() + + +# %% +using PythonPlot +using DifferentialEquations +using Sundials +using SciMLBase +using QuadGK +using DataFrames +using Statistics + +function run_co2_reduction_simulation(params::Vector{Float64}) + try + CO2_M = params[1] + pH = params[2] + surface_phi = params[3] + layer_thickness = params[4] + CO2_X_init = params[5] + + if CO2_X_init < 0.0 || CO2_X_init > 1.0 + return 1e-15 + end + if layer_thickness <= 0.0 + return 1e-15 + end + + rms_file = "/home/danieltori/CO2_RR_RMG/CO2_Reduction_Ag/Ag_C2_042925.rms" + + outdict = readinput(rms_file) + boundarylayerspcs = outdict["gas"]["Species"] + boundarylayerrxns = outdict["gas"]["Reactions"] + surfspcs = outdict["surface"]["Species"] + surfrxns = outdict["surface"]["Reactions"] + interfacerxns = outdict[Set(["surface", "gas"])]["Reactions"] + solv = outdict["Solvents"][1] + + sitedensity = 2.292e-5; #Ag111 + boundarylayer = IdealDiluteSolution(boundarylayerspcs, boundarylayerrxns, solv, + name = "boundarylayeruid", diffusionlimited = true) + surf = IdealSurface(surfspcs, surfrxns, sitedensity, name = "surface") + + + C_proton = 10.0^(-pH) * 1e3 # mol/m³ + C_co2 = CO2_M * 1e3 # mol/m³ + C_default = 1e-12 + V_res = 1e3 + AVratio = 36.0 + A_surf = V_res * AVratio + V_bl = A_surf * layer_thickness + sites = sitedensity * A_surf + + + initialcondsboundarylayer = Dict([ + "proton" => C_proton * V_bl, + "CO2" => C_co2 * V_bl, + "V" => V_bl, + "T" => 300, + "Phi" => 0.0, + "d" => 0.0, + ]) + + initialcondsreservoir = Dict([ + "proton" => C_proton, + "CO2" => C_co2, + "V" => V_res, + "T" => 300, + ]) + + initialcondssurf = Dict([ + "CO2X" => CO2_X_init * sites, + "vacantX" => (1 - CO2_X_init) * sites, + "A" => A_surf, + "T" => 300, + "Phi" => surface_phi, + ]) + + domainboundarylayer, y0boundarylayer, pboundarylayer = ConstantTVDomain( + phase = boundarylayer, initialconds = initialcondsboundarylayer) + domaincat, y0cat, pcat = ConstantTAPhiDomain( + phase = surf, initialconds = initialcondssurf) + + inter, pinter = ReactiveInternalInterfaceConstantTPhi( + domainboundarylayer, domaincat, interfacerxns, 298.15, A_surf) + diffusionlayer = ConstantReservoirDiffusion( + domainboundarylayer, initialcondsreservoir, A_surf, layer_thickness) + interfaces = [inter, diffusionlayer] + + @time react, y0, p = Reactor((domainboundarylayer, domaincat), + (y0boundarylayer, y0cat), + (0.0, 1e3), + interfaces, + (pboundarylayer, pcat, pinter)) + + @time sol = solve(react.ode, Sundials.CVODE_BDF(), abstol = 1e-20, reltol = 1e-8) + + if sol.retcode != :Success + return 1e-15 + end + + ssys = SystemSimulation(sol, (domainboundarylayer, domaincat), interfaces, p) + + # EXACT CALCULATION METHOD + analysis_time = 100 + OCO_rate = abs(sum(rops(ssys, "O=CO", analysis_time))) + + return OCO_rate + + catch e + return 1e-15 + end +end + + + +# %% +using GlobalSensitivity + +bounds = [ + [1e-5, 1e-2], # CO2 concentration + [5.0, 9.0], # pH + [-0.714, -0.514], # potential + [1e-6, 1e-4], # layer thickness + [0.5, 0.9] # CO2X surface coverage +] + +param_names = ["CO₂_conc", "pH", "potential", "layer_thickness", "CO2X_init"] + +morris_method = Morris( + p_steps = fill(4, 5), + relative_scale = true, + num_trajectory = 50, + total_num_trajectory = 50, + len_design_mat = 10 # +) + +println("Running Morris Global Sensitivity Analysis...") + +morris_result = gsa( + run_co2_reduction_simulation, + morris_method, + bounds; + batch = false +) + + +# %% +param_names = ["CO₂_conc", "pH", "potential", "layer_thickness", "CO2X_init"] + +# Extract Morris outputs +Mu = morris_result.means[1, :] # signed mean effects +Mu_star = morris_result.means_star[1, :] # absolute mean effects +Sigma = morris_result.variances[1, :] # variance + +println("μ values = ", Mu) +println("μ* values = ", Mu_star) +println("σ² values = ", Sigma) + + +# %% +# Extract Morris results (formate / O=CO) +xs = morris_result.means_star[1, :] # absolute mean effects +ys = morris_result.variances[1, :] # variance + + +param_labels = ["CO₂_conc", "pH", "potential", "layer_thickness", "CO2X_init"] + +# SCATTER PLOT +clf() +scatter(xs, ys, color="blue", s=120) + +# LABEL EACH POINT +for i in 1:length(xs) + text(xs[i], ys[i], " $(param_labels[i])", + fontsize=12, ha="left", va="bottom") +end + +xlabel("μ* (Mean Elementary Effect)") +ylabel("σ² (Variance → nonlinearity / interaction)") +title("Morris Screening — Formate Production") +grid(true) +gcf() + + +# %% +# MU BAR PLOT +clf() + +bar( + ["CO2_conc", "pH", "surface_potential", "layer_thickness", "CO2_X_init"], + morris_result.means[1, :] +) +title("Morris Signed Mean Effects") +xlabel("Parameters") +ylabel("Mu") + + +gcf() + + +# %% +# MU* BAR PLOT +clf() + +bar( + ["CO2_conc", "pH", "surface_potential", "layer_thickness", "CO2_X_init"], + morris_result.means_star[1, :] +) +title("Morris Absolute Mean Effects") +xlabel("Parameters") +ylabel("μ* (Mean Absolute Effect)") + +gcf() + +# %% +# VARIANCE BAR PLOT +clf() + +bar( + ["CO2_conc", "pH", "surface_potential", "layer_thickness", "CO2_X_init"], + morris_result.variance[1, :] +) +title("Morris Variance (Nonlinearity / Interaction)") +xlabel("Parameters") +ylabel("σ² (Variance)") +gcf() + +# %% +using GlobalSensitivity +using Random + +println("Running Sobol Global Sensitivity Analysis...") + +sobol_result = gsa(run_co2_reduction_simulation, Sobol(), [[1e-5, 1e-2], [5.0, 9.0], [-0.714, -0.514], [1e-6, 1e-4], [0.5, 0.9]], samples = 32, batch = false) + +# %% +clf() + +bar( + ["CO2_conc", "pH", "surface_potential", "layer_thickness", "CO2_X_init"], + sobol_result.S1[1, :] +) +title("First Order Indices O=CO") +xlabel("Parameters") +ylabel("S1") + +gcf() + + +# %% +clf() + +bar( + ["CO2_conc", "pH", "surface_potential", "layer_thickness", "CO2_X_init"], + sobol_result.ST[1, :] +) +title("Sobol Total Indices O=CO") +xlabel("Parameters") +ylabel("ST") + +gcf() + + +# %% +using PythonPlot +using DifferentialEquations +using Sundials +using SciMLBase +using QuadGK +using DataFrames +using Statistics + +function run_co2_reduction_simulation1(params::Vector{Float64}) + try + CO2_M = params[1] + pH = params[2] + surface_phi = params[3] + layer_thickness = params[4] + CO2_X_init = params[5] + + # Basic validity checks + if CO2_X_init < 0.0 || CO2_X_init > 1.0 + error("Invalid CO2 surface coverage") + end + if layer_thickness <= 0.0 + error("Invalid BL thickness") + end + + rms_file = "/home/danieltori/CO2_RR_RMG/CO2_Reduction_Ag/Ag_C2_042925.rms" + outdict = readinput(rms_file) + + boundarylayerspcs = outdict["gas"]["Species"] + boundarylayerrxns = outdict["gas"]["Reactions"] + surfspcs = outdict["surface"]["Species"] + surfrxns = outdict["surface"]["Reactions"] + interfacerxns = outdict[Set(["surface", "gas"])]["Reactions"] + solv = outdict["Solvents"][1] + + sitedensity = 2.292e-5 + boundarylayer = IdealDiluteSolution(boundarylayerspcs, boundarylayerrxns, solv; + name="boundarylayeruid", diffusionlimited=true) + surf = IdealSurface(surfspcs, surfrxns, sitedensity; name="surface") + + C_proton = 10.0^(-pH) * 1e3 + C_co2 = CO2_M * 1e3 + V_res = 1e3 + AVratio = 36.0 + A_surf = V_res * AVratio + V_bl = A_surf * layer_thickness + sites = sitedensity * A_surf + + initialcondsboundarylayer = Dict( + "proton" => C_proton * V_bl, + "CO2" => C_co2 * V_bl, + "V" => V_bl, + "T" => 300.0, + "Phi" => 0.0, + "d" => 0.0 + ) + + initialcondsreservoir = Dict( + "proton" => C_proton, + "CO2" => C_co2, + "V" => V_res, + "T" => 300.0 + ) + + initialcondssurf = Dict( + "CO2X" => CO2_X_init * sites, + "vacantX" => (1 - CO2_X_init) * sites, + "A" => A_surf, + "T" => 300.0, + "Phi" => surface_phi + ) + + domainBL, y0BL, pBL = ConstantTVDomain(phase=boundarylayer, initialconds=initialcondsboundarylayer) + domainCAT, y0CAT, pCAT = ConstantTAPhiDomain(phase=surf, initialconds=initialcondssurf) + + inter, pinter = ReactiveInternalInterfaceConstantTPhi(domainBL, domainCAT, interfacerxns, 298.15, A_surf) + difflayer = ConstantReservoirDiffusion(domainBL, initialcondsreservoir, A_surf, layer_thickness) + + interfaces = [inter, difflayer] + + react, y0, p = Reactor( + (domainBL, domainCAT), + (y0BL, y0CAT), + (0.0, 1e3), + interfaces, + (pBL, pCAT, pinter) + ) + + sol = solve(react.ode, Sundials.CVODE_BDF(); abstol=1e-20, reltol=1e-8) + + if sol.retcode != :Success + error("CVODE failure") + end + + ssys = SystemSimulation(sol, (domainBL, domainCAT), interfaces, p) + + analysis_time = 100.0 + OCO_rate = abs(sum(rops(ssys, "O=CO", analysis_time))) + + return OCO_rate + + catch e + return log10(1e-12 + sum(abs.(params))) + end +end + + +# %% +# MORRIS +using GlobalSensitivity + +bounds = [ + [1e-5, 1e-2], + [5.0, 9.0], + [-0.714, -0.514], + [1e-6, 1e-4], + [0.5, 0.9] +] + +param_names = ["CO₂_conc", "pH", "potential", "layer_thickness", "CO2X_init"] + +morris_method = Morris( + p_steps = fill(4, 5), + relative_scale = true, + num_trajectory = 40, + total_num_trajectory = 40, + len_design_mat = 10 +) + +println("Running Morris Screening...") + +morris_resultx = gsa( + run_co2_reduction_simulation1, + morris_method, + bounds; + batch=false +) + + +# %% +param_names = ["CO₂_conc", "pH", "potential", "layer_thickness", "CO2X_init"] + +# Extract Morris outputs +Mu = morris_resultx.means[1, :] # signed mean effects +Mu_star = morris_resultx.means_star[1, :] # absolute mean effects +Sigma = morris_resultx.variances[1, :] # variance + +println("μ values = ", Mu) +println("μ* values = ", Mu_star) +println("σ² values = ", Sigma) + + +# %% +# Extract Morris results (formate / O=CO) +xs = morris_resultx.means_star[1, :] # absolute mean effects +ys = morris_resultx.variances[1, :] # variance + + +param_labels = ["CO₂_conc", "pH", "potential", "layer_thickness", "CO2X_init"] + +# SCATTER PLOT +clf() +scatter(xs, ys, color="blue", s=120) + +# LABEL EACH POINT +for i in 1:length(xs) + text(xs[i], ys[i], " $(param_labels[i])", + fontsize=12, ha="left", va="bottom") +end + +xlabel("μ* (Mean Elementary Effect)") +ylabel("σ² (Variance → nonlinearity / interaction)") +title("Morris Screening — Formate Production") +grid(true) +gcf() + + +# %% +using GlobalSensitivity + +function batch_model(P::Matrix{Float64}) + n = size(P, 2) + out = zeros(n) + for i in 1:n + out[i] = run_co2_reduction_simulation1(P[:, i]) + end + return out +end + +println("Running Sobol Sensitivity Analysis...") + +sobol_resultx = gsa( + batch_model, + Sobol(), + bounds; + samples = 200, + batch = true +) + + +# %% +clf() + +bar( + ["CO2_conc", "pH", "surface_potential", "layer_thickness", "CO2_X_init"], + sobol_resultx.S1[1, :] +) +title("First Order Indices O=CO") +xlabel("Parameters") +ylabel("S1") + +gcf() + + +# %% +clf() + +bar( + ["CO2_conc", "pH", "surface_potential", "layer_thickness", "CO2_X_init"], + sobol_resultx.ST[1, :] +) +title("Total order Indices O=CO") +xlabel("Parameters") +ylabel("ST") + +gcf() + + +# %% + +# %% +using PythonPlot +using DifferentialEquations +using Sundials +using SciMLBase +using QuadGK +using DataFrames +using GlobalSensitivity +using Random +using Statistics + +function run_co2_reduction_simulation(params::Vector{Float64}) + try + CO2_M = params[1] + pH = params[2] + surface_phi = params[3] + + rms_file = "/home/danieltori/CO2_RR_RMG/CO2_Reduction_Ag/Ag_C2_042925.rms" + + outdict = readinput(rms_file) + boundarylayerspcs = outdict["gas"]["Species"] + boundarylayerrxns = outdict["gas"]["Reactions"] + surfspcs = outdict["surface"]["Species"] + surfrxns = outdict["surface"]["Reactions"] + interfacerxns = outdict[Set(["surface", "gas"])]["Reactions"] + solv = outdict["Solvents"][1] + + sitedensity = 2.292e-5; #Ag111 + boundarylayer = IdealDiluteSolution(boundarylayerspcs, boundarylayerrxns, solv, + name = "boundarylayeruid", diffusionlimited = true) + surf = IdealSurface(surfspcs, surfrxns, sitedensity, name = "surface") + + + C_proton = 10.0^(-pH) * 1e3 # mol/m³ + C_co2 = CO2_M * 1e3 # mol/m³ + C_default = 1e-12 + V_res = 1e3 + layer_thickness = 1e-6; + AVratio = 36.0 + A_surf = V_res * AVratio + V_bl = A_surf * layer_thickness + sites = sitedensity * A_surf + + + initialcondsboundarylayer = Dict([ + "proton" => C_proton * V_bl, + "CO2" => C_co2 * V_bl, + "V" => V_bl, + "T" => 300, + "Phi" => 0.0, + "d" => 0.0, + ]) + + initialcondsreservoir = Dict([ + "proton" => C_proton, + "CO2" => C_co2, + "V" => V_res, + "T" => 300, + ]) + + initialcondssurf = Dict([ + "CO2X" => 0.6 * sites, + "vacantX" => 0.4 * sites, + "A" => A_surf, + "T" => 300, + "Phi" => surface_phi, + ]) + + domainboundarylayer, y0boundarylayer, pboundarylayer = ConstantTVDomain( + phase = boundarylayer, initialconds = initialcondsboundarylayer) + domaincat, y0cat, pcat = ConstantTAPhiDomain( + phase = surf, initialconds = initialcondssurf) + + inter, pinter = ReactiveInternalInterfaceConstantTPhi( + domainboundarylayer, domaincat, interfacerxns, 298.15, A_surf) + diffusionlayer = ConstantReservoirDiffusion( + domainboundarylayer, initialcondsreservoir, A_surf, layer_thickness) + interfaces = [inter, diffusionlayer] + + @time react, y0, p = Reactor((domainboundarylayer, domaincat), + (y0boundarylayer, y0cat), + (0.0, 1e3), + interfaces, + (pboundarylayer, pcat, pinter)) + + @time sol = solve(react.ode, Sundials.CVODE_BDF(), abstol = 1e-20, reltol = 1e-8) + + if sol.retcode != :Success + return [1e-15, 1e-15, 0.001, 0] + end + + ssys = SystemSimulation(sol, (domainboundarylayer, domaincat), interfaces, p) + + # EXACT CALCULATION METHOD + analysis_time = 100 + co2_rate = abs(sum(rops(ssys, "CO2", analysis_time))) + + OCO_rate = abs(sum(rops(ssys, "O=CO", analysis_time))) + + + return [OCO_rate] + + catch e + return [100] + end +end + +function run_gsa() + bounds = [ [1e-5, 1e-2], [5, 9], [-0.714, -0.514]] + param_names = ["CO2_conc", "pH", "surface_potential"] + + # Initialize variables + morris_result = nothing + + # Morris + println("Running Morris...") + try + morris_result = GlobalSensitivity.gsa(run_co2_reduction_simulation, GlobalSensitivity.Morris(), bounds; N = 200) + println("Morris completed") + catch e + println("Morris failed: $e") + end + + # Results + if morris_result !== nothing + num_outputs = size(morris_result.means_star, 1) + num_params = size(morris_result.means_star, 2) + + println("\nMorris Results:") + for i in 1:num_outputs + for j in 1:num_params + #println("$(param_names[j]) -> Output $i: μ* = $(round(morris_result.means_star[i,j], digits=4))") + println("Output $i ← $(param_names[j]) : μ* = $(round(morris_result.means_star[i,j], digits=4))") + end + end + end + + return morris_result +end + +morris_result = run_gsa() + +# %% +morris_result.means + +# %% +morris_result.variances + +# %% +# Extract Morris results for Output 1 (formate / O=CO) +xs = morris_result.means[1, :] # μ* +ys = morris_result.variances[1, :] # σ² + +param_labels = ["CO₂ conc", "pH", "Potential"] # your 3 parameters + +# SCATTER PLOT +clf() +scatter(xs, ys, color="blue", s=120) + +# LABEL EACH POINT +for i in 1:length(xs) + text(xs[i], ys[i], " $(param_labels[i])", + fontsize=12, ha="left", va="bottom") +end + +xlabel("μ* (Mean Elementary Effect)") +ylabel("σ² (Variance → nonlinearity / interaction)") +title("Morris Screening — O=CO (Formate Production)") +grid(true) +gcf() + + +# %% +model_OCO(x) = run_co2_reduction_simulation(x)[1] + +sobol_result = GlobalSensitivity.gsa(model_OCO, GlobalSensitivity.Sobol(), [[1e-5, 1e-2], [5, 9], [-0.714, -0.514]], samples = 32) + +# %% +Pkg.add("QuasiMonteCarlo") +using QuasiMonteCarlo + +samples = 32 +lb = [1e-5, 5, -0.714] +ub = [1e-2, 9, -0.514] +sampler = SobolSample() +A, B = QuasiMonteCarlo.generate_design_matrices(samples, lb, ub, sampler) + +# %% +model_OCO(x) = run_co2_reduction_simulation(x)[1] + +sobol_result1 = GlobalSensitivity.gsa(model_OCO, GlobalSensitivity.Sobol(), A, B) + +# %% +clf() + +bar( + ["CO2_conc", "pH", "surface_potential"], + sobol_result1.ST[1, :] +) +title("Total Order Indices O=CO") +xlabel("Parameters") +ylabel("ST") + +gcf() + +# %% +clf() + +bar( + ["CO2_conc", "pH", "surface_potential"], + sobol_result1.S1[1, :] +) +title("First Order Indices O=CO") +xlabel("Parameters") +ylabel("S1") + +gcf() + + +# %% + +# %% +using PythonPlot +using DifferentialEquations +using Sundials +using SciMLBase +using QuadGK +using DataFrames +using Statistics + + +safe_log10(x) = log10(x + 1e-30) + +function run_co2_reduction_simulation1(params::Vector{Float64}) + try + CO2_M = params[1] + pH = params[2] + surface_phi = params[3] + layer_thickness = params[4] + CO2X_init = params[5] + + if !(0 < CO2X_init <= 1) + return safe_log10(1e-20) + end + if layer_thickness <= 0 + return safe_log10(1e-20) + end + + rms_file = "/home/danieltori/CO2_RR_RMG/CO2_Reduction_Ag/Ag_C2_042925.rms" + outdict = readinput(rms_file) + + gas_species = outdict["gas"]["Species"] + gas_rxns = outdict["gas"]["Reactions"] + surf_species = outdict["surface"]["Species"] + surf_rxns = outdict["surface"]["Reactions"] + interface_rxns = outdict[Set(["surface","gas"])]["Reactions"] + solv = outdict["Solvents"][1] + + sitedensity = 2.292e-5 + C_proton = 10.0^(-pH) * 1e3 + C_co2 = CO2_M * 1e3 + V_res = 1e3 + AVratio = 36.0 + A_surf = V_res * AVratio + V_bl = A_surf * layer_thk + sites = sitedensity * A_surf + + boundary = IdealDiluteSolution(gas_species, gas_rxns, solv; + name="boundary", diffusionlimited=true) + + surface = IdealSurface(surf_species, surf_rxns, sitedensity; + name="surface") + + init_bl = Dict( + "proton" => C_proton * V_bl, + "CO2" => C_co2 * V_bl, + "V" => V_bl, + "T" => 300.0, + "Phi" => 0.0, + "d" => 0.0, + ) + + init_res = Dict( + "proton" => C_proton, + "CO2" => C_co2, + "V" => V_res, + "T" => 300.0, + ) + + init_surf = Dict( + "CO2X" => CO2X_init * sites, + "vacantX" => (1 - CO2X_init) * sites, + "A" => A_surf, + "T" => 300.0, + "Phi" => surface_phi, + ) + + dom_bl, y0_bl, p_bl = ConstantTVDomain(phase=boundary, initialconds=init_bl) + dom_s, y0_s, p_s = ConstantTAPhiDomain(phase=surface, initialconds=init_surf) + + inter, p_inter = ReactiveInternalInterfaceConstantTPhi(dom_bl, dom_s, interface_rxns, 298.15, A_surf) + diff = ConstantReservoirDiffusion(dom_bl, init_res, A_surf, layer_thk) + + interfaces = [inter, diff] + + # ------------ Reactor Solve ------------------------ + react, y0, p = Reactor((dom_bl, dom_s), + (y0_bl, y0_s), + (0.0, 1e3), + interfaces, + (p_bl, p_s, p_inter)) + + sol = solve(react.ode, Sundials.CVODE_BDF(); abstol=1e-20, reltol=1e-8, maxiters=1e7) + + if sol.retcode != :Success + return safe_log10(1e-20) + end + + ssys = SystemSimulation(sol, (dom_bl, dom_s), interfaces, p) + + tₐ = 100.0 + rate_OCO = try + abs(sum(rops(ssys, "O=CO", tₐ))) + catch + 1e-20 + end + + return safe_log10(rate_OCO) + + catch e + @warn "Model exception: $e" + return safe_log10(1e-20) + end +end + + +# %% +# MORRIS +using GlobalSensitivity + +bounds = [ + [1e-5, 1e-2], + [5.0, 9.0], + [-0.714, -0.514], + [1e-6, 1e-4], + [0.5, 0.9] +] + +param_names = ["CO₂_conc", "pH", "potential", "layer_thickness", "CO2X_init"] + +morris_method = Morris( + p_steps = fill(4, 5), + relative_scale = true, + num_trajectory = 40, + total_num_trajectory = 40, + len_design_mat = 10 +) + +println("Running Morris Screening...") + +morris_resultx= gsa( + run_co2_reduction_simulation, + morris_method, + bounds; + batch=false +) + + +# %% +plt = PythonPlot + +μs = morris_result.means_star +σ² = morris_result.variances + +plt.figure(figsize=(8,6)) +plt.scatter(μs, σ², s=150, color="blue") + +for i in 1:length(param_names) + plt.annotate(param_names[i], + (μs[i], σ²[i]), + textcoords="offset points", + xytext=(10, 5) + ) +end + +plt.xlabel("μ* (importance)") +plt.ylabel("σ² (nonlinearity / interaction)") +plt.title("Morris Sensitivity — Formate Production") +plt.grid(true) + +gcf() + + +# %% + +# %% +using PythonPlot +using DifferentialEquations +using Sundials +using SciMLBase +using QuadGK +using DataFrames +using Statistics + +function run_co2_reduction_simulation(params::Vector{Float64}) + try + CO2_M = params[1] + pH = params[2] + surface_phi = params[3] + + rms_file = "/home/danieltori/CO2_RR_RMG/CO2_Reduction_Ag/Ag_C2_042925.rms" + + outdict = readinput(rms_file) + boundarylayerspcs = outdict["gas"]["Species"] + boundarylayerrxns = outdict["gas"]["Reactions"] + surfspcs = outdict["surface"]["Species"] + surfrxns = outdict["surface"]["Reactions"] + interfacerxns = outdict[Set(["surface", "gas"])]["Reactions"] + solv = outdict["Solvents"][1] + + sitedensity = 2.292e-5; #Ag111 + boundarylayer = IdealDiluteSolution(boundarylayerspcs, boundarylayerrxns, solv, + name = "boundarylayeruid", diffusionlimited = true) + surf = IdealSurface(surfspcs, surfrxns, sitedensity, name = "surface") + + + C_proton = 10.0^(-pH) * 1e3 # mol/m³ + C_co2 = CO2_M * 1e3 # mol/m³ + C_default = 1e-12 + V_res = 1e3 + AVratio = 36.0 + layer_thickness = 1e-6 + A_surf = V_res * AVratio + V_bl = A_surf * layer_thickness + sites = sitedensity * A_surf + + + initialcondsboundarylayer = Dict([ + "proton" => C_proton * V_bl, + "CO2" => C_co2 * V_bl, + "V" => V_bl, + "T" => 300, + "Phi" => 0.0, + "d" => 0.0, + ]) + + initialcondsreservoir = Dict([ + "proton" => C_proton, + "CO2" => C_co2, + "V" => V_res, + "T" => 300, + ]) + + initialcondssurf = Dict([ + "CO2X" => 0.6 * sites, + "vacantX" => 0.4 * sites, + "A" => A_surf, + "T" => 300, + "Phi" => surface_phi, + ]) + + domainboundarylayer, y0boundarylayer, pboundarylayer = ConstantTVDomain( + phase = boundarylayer, initialconds = initialcondsboundarylayer) + domaincat, y0cat, pcat = ConstantTAPhiDomain( + phase = surf, initialconds = initialcondssurf) + + inter, pinter = ReactiveInternalInterfaceConstantTPhi( + domainboundarylayer, domaincat, interfacerxns, 298.15, A_surf) + diffusionlayer = ConstantReservoirDiffusion( + domainboundarylayer, initialcondsreservoir, A_surf, layer_thickness) + interfaces = [inter, diffusionlayer] + + @time react, y0, p = Reactor((domainboundarylayer, domaincat), + (y0boundarylayer, y0cat), + (0.0, 1e3), + interfaces, + (pboundarylayer, pcat, pinter)) + + @time sol = solve(react.ode, Sundials.CVODE_BDF(), abstol = 1e-20, reltol = 1e-8) + + if sol.retcode != :Success + return 1e-15 + end + + ssys = SystemSimulation(sol, (domainboundarylayer, domaincat), interfaces, p) + + # EXACT CALCULATION METHOD + analysis_time = 100 + OCO_rate = abs(sum(rops(ssys, "O=CO", analysis_time))) + + return OCO_rate + + catch e + return 1e-15 + end +end + + + +# %% +using GlobalSensitivity +bounds = [ + [1e-5, 1e-2], # CO2 concentration (mol/L) + [5.0, 9.0], # pH + [-0.714, -0.514] # Potential (V) +] + +param_names = ["CO₂_conc", "pH", "potential"] + +morris_method = Morris( + p_steps = fill(4, 3), # 4 levels, 3 parameters + relative_scale = true, + num_trajectory = 50, + total_num_trajectory = 50, + len_design_mat = 10 +) + +println("Running Morris Global Sensitivity Analysis...") + +morris_result = gsa( + run_co2_reduction_simulation, + morris_method, + bounds; + batch = false +) + + +# %% +miu_star = morris_result.means_star +var = morris_result.variances + +println("μ* (importance): ", miu_star) +println("σ² (nonlinearity/interaction): ", var) + +# %% +morris_result.means + +# %% +morris_result.variances + +# %% +scatter( + morris_result.means[1, :], + morris_result.variances[1, :], + color="blue" +) + + +# %% +# Extract Morris results for Output 1 (formate / O=CO) +xs = morris_result.means[1, :] # μ* +ys = morris_result.variances[1, :] # σ² + +param_labels = ["CO₂ conc", "pH", "Potential"] # your 3 parameters + +# SCATTER PLOT +clf() +scatter(xs, ys, color="blue", s=120) + +# LABEL EACH POINT +for i in 1:length(xs) + text(xs[i], ys[i], " $(param_labels[i])", + fontsize=12, ha="left", va="bottom") +end + +xlabel("μ* (Mean Elementary Effect)") +ylabel("σ² (Variance → nonlinearity / interaction)") +title("Morris Screening — Output 1 (Formate Production)") +grid(true) +gcf() + + +# %% +scatter( + morris_result.means[2, :], + morris_result.variances[2, :], + color="red" +) + +# %% +# Extract Morris results for Output 1 (formate / O=CO) +xs = morris_result.means[2, :] # μ* +ys = morris_result.variances[2, :] # σ² + +param_labels = ["CO₂ conc", "pH", "Potential"] # your 3 parameters + +# SCATTER PLOT +clf() +scatter(xs, ys, color="blue", s=120) + +# LABEL EACH POINT +for i in 1:length(xs) + text(xs[i], ys[i], " $(param_labels[i])", + fontsize=12, ha="left", va="bottom") +end + +xlabel("μ* (Mean Elementary Effect)") +ylabel("σ² (Variance → nonlinearity / interaction)") +title("Morris Screening — Output 1 (Formate Production)") +grid(true) +gcf() + + +# %% +# Correct plotting syntax for PythonPlot +param_labels = ["a", "b", "c"] + +# Create Morris signature plot +scatter(morris_result.means[1, :], morris_result.variances[1, :], s = 100, alpha = 0.7) + +# Add labels manually +for (i, label) in enumerate(param_labels) + annotate(label, (morris_result.means[1, i], morris_result.variances[1, i]), + xytext = (5, 5), textcoords = "offset points") +end + +xlabel("μ (Mean Effect)") +ylabel("σ (Standard Deviation)") +title("Morris Analysis - OCO_rate") +grid(true, alpha = 0.3) +gcf() + + +# %% +# Correct plotting syntax for PythonPlot +param_labels = ["a", "b", "c"] + +# Create Morris signature plot +scatter(morris_result.means[2, :], morris_result.variances[2, :], s = 100, alpha = 0.7) + +# Add labels manually +for (i, label) in enumerate(param_labels) + annotate(label, (morris_result.means[2, i], morris_result.variances[2, i]), + xytext = (5, 5), textcoords = "offset points") +end + +xlabel("μ (Mean Effect)") +ylabel("σ (Standard Deviation)") +title("Morris Analysis - OCO_rate") +grid(true, alpha = 0.3) +gcf() + + +# %% +samples = 32 +lb = [1e-5, 5.0, -0.714] +ub = [1e-2, 9.0, -0.514] +sampler = SobolSample() +A, B = QuasiMonteCarlo.generate_design_matrices(samples, lb, ub, sampler) + +# %% +# Simple readable output for Morris results +param_names = ["CO2_conc", "pH", "surface_potential"] + +println("MORRIS RESULTS FOR OCO_RATE:") +for (i, param) in enumerate(param_names) + mu_star = abs(morris_result.means[1, i]) + sigma = morris_result.variances[1, i] + importance = mu_star > 0.1 ? "HIGH" : (mu_star > 0.01 ? "MEDIUM" : "LOW") + println("$param: μ* = $(round(mu_star, digits=6)) ($importance)") +end + +# %% +# SOBOL GLOBAL SENSITIVITY ANALYSIS +function run_sobol_gsa() + + bounds = [ + [1e-5, 1e-2], # CO₂ concentration (mol/L) + [5.0, 9.0], # pH + [-0.714, -0.514] # potential (V) + ] + + param_names = ["CO₂ conc", "pH", "potential"] + output_names = ["OCO_rate (formate)", "CO2HX_rate"] + + sobol_results = Vector{Any}(undef, length(output_names)) + + Random.seed!(1234) + nsamples = 32 + + println("\nRunning Sobol GSA...") + + for k in 1:length(output_names) + + println("\n--- Sobol for output $k: $(output_names[k]) ---") + + # Scalar model wrapper + model_k(x) = run_co2_reduction_simulation(x)[k] + + # Run Sobol (S1 and ST always computed) + sob = GlobalSensitivity.gsa( + model_k, + GlobalSensitivity.Sobol(), + bounds; + samples = nsamples + ) + + sobol_results[k] = sob + + S1 = sob.S1 + ST = sob.ST + S2 = sob.S2 # often nothing + + # PRINT RESULTS + println("\nFirst-order S1:") + for j in 1:length(param_names) + println(" $(param_names[j]) : S1 = $(round(S1[j], digits=4))") + end + + println("\nTotal-order ST:") + for j in 1:length(param_names) + println(" $(param_names[j]) : ST = $(round(ST[j], digits=4))") + end + + # PLOT S1 + clf() + bar(1:length(S1), S1) + xticks(1:length(param_names), param_names, rotation=45, ha="right") + ylabel("S1") + title("Sobol S1 for $(output_names[k])") + tight_layout() + gcf() + + # PLOT ST + bar(1:length(ST), ST) + xticks(1:length(param_names), param_names, rotation=45, ha="right") + ylabel("ST") + title("Sobol ST for $(output_names[k])") + tight_layout() + gcf() + + # OPTIONAL S₂ + if S2 !== nothing + S2_plot = deepcopy(S2) + for i in 1:size(S2_plot, 1) + S2_plot[i,i] = 0.0 + end + + clf() + imshow( + S2_plot, + origin="lower", + aspect="equal" + ) + colorbar() + xticks(1:length(param_names), param_names, rotation=45) + yticks(1:length(param_names), param_names) + title("Sobol S2 interactions for $(output_names[k])") + tight_layout() + gcf() + else + println("\n[S2 unavailable — interactions cannot be computed with current sample size.]") + end + end + + return sobol_results +end + +sobol_results = run_sobol_gsa() + diff --git a/CO2_Reduction_Ag/HER-Data/Validation/HER-Val-Data.jl b/CO2_Reduction_Ag/HER-Data/Validation/HER-Val-Data.jl new file mode 100644 index 0000000..ba5f418 --- /dev/null +++ b/CO2_Reduction_Ag/HER-Data/Validation/HER-Val-Data.jl @@ -0,0 +1,845 @@ +# -*- coding: utf-8 -*- +# --- +# jupyter: +# jupytext: +# formats: ipynb,jl:percent +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.17.2 +# kernelspec: +# display_name: Julia rmg_env3 1.10 +# language: julia +# name: julia-rmg_env3-1.10 +# --- + +# %% +using Pkg +Pkg.activate(ENV["PYTHON_JULIAPKG_PROJECT"]) +using ReactionMechanismSimulator + +# %% +using PythonPlot +using DifferentialEquations +using Sundials +using SciMLBase +using QuadGK + +# %% +outdict = readinput("/home/danieltori/CO2_RR_RMG/CO2_Reduction_Ag/HER-Data/HER-Pt/rms/chem10.rms") + +# %% +boundarylayerspcs = outdict["gas"]["Species"] +boundarylayerrxns = outdict["gas"]["Reactions"] +surfspcs = outdict["surface"]["Species"] +surfrxns = outdict["surface"]["Reactions"] +interfacerxns = outdict[Set(["surface", "gas"])]["Reactions"] +solv = outdict["Solvents"][1]; + +# %% +sitedensity = 2.483e-5; # Pt111 site density is 2.483e-9 mol/cm^2 or 2.483e-5 mol/m^2 +boundarylayer = IdealDiluteSolution(boundarylayerspcs,boundarylayerrxns,solv,name="boundarylayeruid",diffusionlimited=true); +surf = IdealSurface(surfspcs,surfrxns,sitedensity,name="surface"); + +# %% +# Reservoir is a 100 mL (100e-6 m^3) cell +# Proton concentration is 10^-7 mol/L (10^-4 mol/m^3) +# CO2 concentration is 0.01 mol/L (10 mol/m^3), saturation solubility ~0.03 mol/L +# AVratio in experiments is 36 m^-1 but is measured by surface area/reservoir volume +# Area of the electrode is therefore 3.6e1 m^-1 * 1e2 * 1e-6 m^3 = 3.6e-3 m^2 = 36 cm^2 +# Assume boundary layer thickness d_bl = 1 mm or 1e-3 m +# Volume of the boundary layer V_bl = 3.6e-3 m^2 * 1e-3 m = 3.6e-6 m^3 +# Actual AVratio is therefore 3.6e-3 m^2 / 3.6e-6 m^3 = 1e3 m^-1 (reciprocal of d_bl) +# Amount of sites is 2.943e-5 mol/m^2 * 3.6e-3 m^2 = 10.595e-8 mol + +# For earlier simulations, a 100x linear scale factor is applied, +# so volume becomes 100e-6 m^3 * (1e2)^3 = 100 m^3, +# electrode area becomes 3.6e-3 * (1e2) ^2 = 3.6e1 m^2, +# AVratio becomes 3.6e1 m^2 / 1e2 m^3 = 0.36 m^-1 +# Volume of the boundary layer becomes 3.6e1 m^2 * 1e-3 m = 3.6e-2 m^3 + +pH = 1; +C_proton = 10.0^-pH*1e3; # convert from mol/L to mol/m^3 +#C_proton = 0.1*1e3; +#C_co2 = 1e-2*1e3; +#C_default = 1e-12; +C_H2_initial = 1e-12 +V_res = 1e3; +layer_thickness = 1e-6; +A_surf = 1e-4 # 1 cm2 +#AVratio = 36; +#A_surf = V_res*AVratio; +V_bl = A_surf*layer_thickness; +#V_bl = V_res; +sites = sitedensity*A_surf; + +# The initial conditions for individual species are moles not concentration, so we need to multiply concentration by boundary layer volume +initialcondsboundarylayer = Dict(["proton"=>C_proton*V_bl, + #"CO2"=>C_co2*V_bl, + "H2"=>C_H2_initial*V_bl, + # "O=CO"=>C_default*V_bl, + "V"=>V_bl,"T"=>298,"Phi"=>0.0,"d"=>0.0]); +initialcondsreservoir = Dict(["proton"=>C_proton, + "H2" => C_H2_initial, + #"CO2"=>C_co2, + "V"=>V_res,"T"=>298]); + + +# Assume voltage is -1.0 V vs. R.H.E. which equates to -1.414 V vs. S.H.E. at pH=7 +initialcondssurf = Dict(["HX"=>0.7778*sites, + #"CO2X"=>0.4*sites, + # "CHO2X"=>0.1*sites, + # "CO2HX"=>0.1*sites, + # "OX"=>0.1*sites, + # "OCX"=>0.1*sites, + "vacantX"=>0.2222*sites, + # "CH2O2X"=>0.05*sites, + # "CHOX"=>0.04*sites, + # "CH2OX"=>0.01*sites, + "A"=>A_surf,"T"=>298,"Phi"=>0]); + +# %% +domainboundarylayer, y0boundarylayer, pboundarylayer = ConstantTVDomain(phase=boundarylayer, initialconds=initialcondsboundarylayer); +domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf, + initialconds=initialcondssurf); + +# %% +# Set proton diffusivity to a higher value than calculated from Stokes Einstein equation +# The values are taken from DOI: 10.1039/C8SC01253A +# Values calculated from MD is 1.015 A^2/ps, experimental values are 0.932 A^2/ps. +# 1 A^2/ps = 1e-8 m^2/s +domainboundarylayer.diffusivity[1] = 0.932e-8 + +# %% +inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainboundarylayer, + domaincat,interfacerxns,298.15,A_surf); + +# %% +# start with 1mm layer thickness +diffusionlayer = ConstantReservoirDiffusion(domainboundarylayer, initialcondsreservoir, A_surf, layer_thickness); + +# %% +interfaces = [inter, diffusionlayer]; + +# %% +@time react,y0,p = Reactor((domainboundarylayer,domaincat), (y0boundarylayer,y0cat), (0.0, 1e4), interfaces, (pboundarylayer,pcat,pinter)); + +# %% +@time sol = solve(react.ode,Sundials.CVODE_BDF(),abstol=1e-22,reltol=1e-8); +println(sol.t[end]); +println(sol.retcode); + +# %% +ssys = SystemSimulation(sol,(domainboundarylayer,domaincat,), interfaces,p); + +# %% +""" +diffusive flux to the reservoir +""" +function flux_to_reservoir(sim,t,reservoirinterface) + cs = concentrations(sim,t) + return reservoirinterface.A .* sim.domain.diffusivity .* (cs - reservoirinterface.c) / reservoirinterface.layer_thickness +end + +""" +Integrates the flux to the reservoir and computes the concentration assuming +there is no prior concentration of that species in the reservoir +""" +function get_reservoir_concentration(sim,t,reservoirinterface,Vres,C0) + intg,err = quadgk(x -> flux_to_reservoir(sim,x,reservoirinterface), 0, t); + #intg[5] = 0; + #intg[6] = 0; + return C0 + intg./Vres +end + +# %% +# Logarithmic time scale +t_vals = 10 .^ range(-12, stop=3, length=160); + +# Compute reservoir concentrations +flux_vals = [flux_to_reservoir(ssys.sims[1], t, diffusionlayer) for t in t_vals] + +conc_vals_bl = [concentrations(ssys.sims[1], t) for t in t_vals] +flux_matrix = hcat(flux_vals...); +conc_matrix_bl = hcat(conc_vals_bl...); + + +# %% +conc_0 = concentrations(ssys.sims[1], 0) +t_vals_2 = 10 .^ range(-9, stop=3, length=130); +conc_vals = [get_reservoir_concentration(ssys.sims[1], t, diffusionlayer, V_res, conc_0) for t in t_vals_2] +conc_matrix = hcat(conc_vals...); + +# %% +function plotC_Reservoir(sim, cs, tvals, tol, exclude) + clf() + xs = cs + maxes = maximum(xs, dims=2) + time_filtered = tvals + xs_filtered = xs + + # HER-only species and colors + species_order = ["proton", "H2"] + color_map = Dict("proton" => "red", "H2" => "green") + + # Build a map of species names to indices + name_to_index = Dict(sim.domain.phase.species[i].name => i for i in 1:length(sim.domain.phase.species)) + + # Plot each species + for species_name in species_order + if species_name in exclude + continue + end + + if haskey(name_to_index, species_name) + i = name_to_index[species_name] + + # Always plot proton and H2, or if above tolerance + if (maxes[i] > tol) || (species_name == "proton") || (species_name == "H2") + plot_color = color_map[species_name] + plot(time_filtered, xs_filtered[i, :]/1000, label=species_name, color=plot_color) + end + end + end + + xlabel("Time (s)", fontsize=14) + ylabel("Bulk Concentration (mol/L)", fontsize=14) + xticks(fontsize=14) + yticks(fontsize=14) + legend(loc="upper left", fontsize=12) + xscale("log") + yscale("log") +end + +# %% +#function plotC_Reservoir(sim, cs, tvals, tol, exclude) + # clf() + # xs = cs + # maxes = maximum(xs, dims=2) + + # time_filtered = tvals + # xs_filtered = xs + + # Custom species order and their corresponding names and color + # species_order = ["CO2", "proton", "H2", "O=CO", "C=O", "CO-2", "CCO", "CH4", "OCO", "COC", "COCO", "CC(=O)O", "COC=O"] + # color_map = Dict("CO2" => "black", "proton" => "grey", "H2" => "green", + # "O=CO" => "red", "C=O" => "brown", "CO-2" => "blue", "CCO" => "magenta", + # "CH4" => "brown", "OCO" => "orange", "COC" => "teal", "COCO" => "lime", "CC(=O)O" => "teal", "COC=O" => "lime") + # Replacement map for species labels + # replacement_map = Dict("CO-2" => "CH3OH", "O=CO" => "HCOOH", "C=O" => "HCHO", + # "CCO" => "C2H5OH", "OCO" => "CH2(OH)2", "COC" => "CH3OCH3", "COCO" => "CH3OCH2OH", "CC(=O)O" => "CH3COOH", "COC=O" => "CH3OCHO") + + # Build a map of species names to indices + # name_to_index = Dict(sim.domain.phase.species[i].name => i for i in 1:length(sim.domain.phase.species)) + # Keep track of whether the species is plotted, used for later checks + # plotted = falses(length(sim.domain.phase.species)) + + # Plot species from the custom species dictionary + # for species_name in species_order + # if species_name in exclude + # continue + # end + + # if haskey(name_to_index, species_name) + # i = name_to_index[species_name] + + # if (maxes[i] > tol) || (species_name == "proton") || (species_name == "CCO") # Always plot proton and ethanol + # plot_label = get(replacement_map, species_name, species_name) + # plot_color = color_map[species_name] + + # plot(time_filtered, xs_filtered[i, :]/1000, label=plot_label, color=plot_color) + # plotted[i] = true # Mark as plotted + # end + # end + # end + + # Plot any remaining species that passed tolerance but were not in species_order + # for i in 1:length(sim.domain.phase.species) + # if plotted[i] || sim.domain.phase.species[i].name in exclude + # continue + # end + + # if maxes[i] > tol + # species_name = sim.domain.phase.species[i].name + # plot(time_filtered, xs_filtered[i, :]/1000, label=species_name) # Default color + # end + # end + + # xlabel("Time (s)", fontsize=14) + # ylabel("Bulk Concentration (mol/L)", fontsize=14) + # xticks(fontsize=14) + # yticks(fontsize=14) + # legend(loc="upper left", bbox_to_anchor=(0, 0.9), fontsize=12, ncol=2) +#end + +# %% +exclude_species = ["H2O"] +plotC_Reservoir(ssys.sims[1], conc_matrix, t_vals_2, 1e-12, exclude_species) + +xscale("log") +yscale("log") +xlim(1e-9, 1e3) +ylim(1e-20, 1e-1) +legend(loc="upper left", bbox_to_anchor=(0, 0.9), fontsize=12, ncol=2) +title("Pt111@-0V vs. R.H.E., d = 3e-5 m") +gcf() + +# %% +clf() + +for i in 1:size(flux_matrix, 1) + if maximum(abs.(flux_matrix[i, :])) > 1e-10 + plot(t_vals, abs.(flux_matrix[i, :]), label=ssys.sims[1].domain.phase.species[i].name) + + end +end + +xscale("log") +yscale("log") +xlabel("Time (s)") +ylabel("Diffusive Flux (mol/s)") +xlim(1e-12, 1e3) +ylim(1e-9, 1e1) +legend() +tight_layout() +gcf() + +# %% +clf() +for i in 1:size(conc_matrix_bl, 1) + if maximum(conc_matrix_bl[i, :]) > 1e-10 + plot(t_vals, conc_matrix_bl[i, :]/1e3, label=ssys.sims[1].domain.phase.species[i].name) + + end +end + +xscale("log") +yscale("log") +xlabel("Time (s)") +ylabel("Boundary Layer Concentrations (mol/L)") +xlim(1e-12, 1e3) +ylim(1e-18, 1) +legend() +tight_layout() +gcf() + +# %% +# Helper function +function plotX(sim, tol, t_end, exclude) + clf() + xs = molefractions(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time (s)") + ylabel("Concentration (mol/m^3)") +end + +# %% +function plotC(sim, tol, t_end, exclude) + clf() + xs = concentrations(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + # HER species only + species_order = ["proton", "H2"] + color_map = Dict("proton" => "red", "H2" => "blue") + + # Build map of species names to indices + name_to_index = Dict(sim.domain.phase.species[i].name => i for i in 1:length(sim.domain.phase.species)) + + # Plot each species + for species_name in species_order + if species_name in exclude + continue + end + + if haskey(name_to_index, species_name) + i = name_to_index[species_name] + + # Always plot proton and H2, or if above tolerance + if (maxes[i] > tol) || (species_name == "proton") || (species_name == "H2") + plot_color = color_map[species_name] + plot(time_filtered, xs_filtered[i, :]/1000, label=species_name, color=plot_color) + end + end + end + + xlabel("Time (s)", fontsize=14) + ylabel("Boundary Layer Concentration (mol/L)", fontsize=14) + xticks(fontsize=14) + yticks(fontsize=14) + legend(loc="upper left", fontsize=12) +end + +# %% +exclude_species = ["H2O"] +plotX(ssys.sims[1], 1e-12, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-8, 1e3) +ylim(1e-16, 5) +title("Liquid-phase Mole Fractions vs. Time on Pt111@-0V") +gcf() + +# %% +exclude_species = ["H2O"] +plotC(ssys.sims[1], 1e-10, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-9, 1e3) +ylim(1e-20, 1e-1) +title("Pt111@-0V vs. R.H.E., d = 3e-5 m") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys.sims[2], 1e-3, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e3) +ylim(1e-6, 5) +title("Surface Mole Fractions vs. Time on Pt111@-0V") +gcf() + +# %% +#ts = 10.0 .^ range(-10, 3; step=1) +#fd1 = makefluxdiagrams(ssys, ts) + +# %% +species_list = ["proton", "vacantX", "HX", "H2"]; +species_order = ["proton", "vacantX", "HX", "H2"]; +color_map = Dict("proton" => "red", "H2" => "blue", "vacantX" => "green", "HX" => "orange"); +spc_names = [s.name for s in ssys.species]; +G_val = Float64[]; +T = 300.0; + +for spc in species_list + ind = findfirst(==(spc), spc_names); + if isnothing(ind) + @warn "Species $spc not found" + push!(G_val, NaN); + else + sp = ssys.species[ind]; + G = getGibbs(sp.thermo, T); + push!(G_val, G); + end +end + +# %% +# Calculate relative energies +dG = G_val .- G_val[1]; # Reference to proton + +clf() +for (i, name) in enumerate(species_list) + if !isnan(dG[i]) + species_color = get(color_map, name, "black") + hlines([dG[i]/1000], xmin=i-0.4, xmax=i+0.4, + colors=species_color, linewidth=3, label=name) + end +end + +xlim(0, length(species_list)+1) +xlabel("Reaction Coordinate") +ylabel("Relative Gibbs Energy (kJ/mol)") # Converted to kJ +legend() +title("HER Thermodynamics on Pt") +grid(true, alpha=0.3) +gcf() + +# %% +function plotROP(ssys,name,t;N=0,tol=0.01) + clf() + rop = rops(ssys, name, t) + inds = rop.nzind[reverse(sortperm(abs.(rop.nzval)))] + if N == 0 + N = length(inds) + elseif N > length(inds) + N = length(inds) + end + inds = inds[1:N] + mval = abs(rop[inds[1]]) + minval = mval*tol + k = 1 + while k < length(inds) && abs(rop[inds[k]]) >= minval + k += 1 + end + inds = inds[1:k] + net_rops = sum(rop[inds]) + println("Net ROPs for species $name is: $net_rops") + + for (i, j) in enumerate(inds) + println("Showing the reaction with $i th highest ROP for species $name:") + println(getrxnstr(ssys.reactions[j])) + println("ROP = ", rop[inds[i]]) + println(ssys.reactions[j].kinetics) + end + + xs = Array{Float64,1}(1:length(inds)) + barh(xs,reverse(rop[inds])) + yticks(xs,reverse(getrxnstr.(ssys.reactions[inds]))) + xlabel("Production/Loss Rate mol/s") + gcf() +end + +# %% +function PrintKinDetail(inter, speciesname) + println("Showing Kinetics details for reactions involving species $speciesname\n") + for (i,rxn) in enumerate(inter.reactions) + flag = false + for j = 1:length(rxn.reactants) + if rxn.reactants[j].name == speciesname + flag = true + end + end + for j = 1:length(rxn.products) + if rxn.products[j].name == speciesname + flag = true + end + end + if flag + println(getrxnstr(rxn)) + println(rxn.kinetics) + kf = inter.kfs[i] + krev = inter.krevs[i] + kc = kf/krev + println("kf = $kf") + println("krev = $krev") + println("Kc = $kc\n") + end + end +end + +# %% +""" +Integrates the ROP in the boundary layer and computes the concentration +""" +function get_boundary_layer_concentration(sim,t,spc,Vbl,C_0) + intg,err = quadgk(x -> sum(rops(sim,spc,t)), 0, t); + return C_0 + intg ./ Vbl; +end + +# %% +""" +diffusive flux to the reservoir using concentration from ROP integration +""" +function flux_to_reservoir_2(bsol,t,spc,Vbl,C_0,reservoirinterface) + cs = get_boundary_layer_concentration(bsol,t,spc,Vbl,C_0) + spc_idx = findfirst(s -> s.name == spc, bsol.sims[1].species) + d = bsol.sims[1].domain.diffusivity[spc_idx]; + c_res = reservoirinterface.c[spc_idx]; + return reservoirinterface.A * d * (cs - c_res) / reservoirinterface.layer_thickness +end + +# %% +# Compute ROP over time +ROP_vals = [sum(rops(ssys, "H2", t)) for t in t_vals]; +# Compute boundary layer accumulation by integration +Cbl_vals = [get_boundary_layer_concentration(ssys, t, "H2", V_bl, C_H2_initial) for t in t_vals]; +# Compute flux over time using Cbl_vals +F_vals = [flux_to_reservoir_2(ssys, t, "H2", V_bl, C_H2_initial, diffusionlayer) for t in t_vals]; + +# %% +# Plots the ROP of H2 +clf() + +plot(t_vals, ROP_vals) + +xscale("log") +xlim(1e-11,1e3) +yscale("log") +ylim(1e-8,1e2) +xlabel("Time (s)") +ylabel("Rate of Progress (mol/s)") +legend() +tight_layout() +gcf() + +# %% +# Plots the Diffusion Flux Into Reservoir Using Integrated Concentration from ROP Analysis +clf() + +plot(t_vals, F_vals) + +xscale("log") +yscale("log") +xlabel("Time (s)") +ylabel("Diffusive Flux") +title("Diffusive Flux of H2 from ROP Integration") +legend() +tight_layout() +gcf() + +# %% +plotROP(ssys, "proton",sol.t[end];N=15,tol=0.0) + +# %% +plotROP(ssys, "HX",sol.t[end];N=15,tol=0.0) + +# %% +plotROP(ssys, "H2",sol.t[end];N=15,tol=0.0) + +# %% +fieldnames(typeof(ssys.reactions[1])) + +# %% +ssys.reactions[1].kinetics + +# %% +inter.kfs + +# %% +inter.krevs + +# %% +rops(ssys, "proton", sol.t[end]) + +# %% +rops(ssys, "H2", sol.t[end]) + +# %% +function get_current_density(ssys, t, A_surf) + # H₂ production rate at time t + H2_rate = sum(rops(ssys, "H2", t)) # mol/s + + # Convert to current (2 electrons per H₂) + current = 2 * 96485 * abs(H2_rate) # Amperes + + # Convert to current density + j = current / A_surf # A/m² + j_mA_cm2 = j * 0.1 # mA/cm² + + return j_mA_cm2 +end + +# Use it at steady state +t_steady = sol.t[end] +j = get_current_density(ssys, t_steady, A_surf) +println("Current density: $(j) mA/cm²") + +# %% +function check_steady_state(ssys, t_end) + # Check if species concentrations are changing + dt = t_end / 100 # Small time step + + # For boundary layer species + println("Boundary Layer Species Rates at t = $(t_end):") + for (i, spc) in enumerate(ssys.sims[1].domain.phase.species) + rate = sum(rops(ssys.sims[1], spc.name, t_end)) + if abs(rate) > 1e-15 + println(" $(spc.name): $(rate) mol/s") + end + end + + # For surface species + println("\nSurface Species Rates:") + for (i, spc) in enumerate(ssys.sims[2].domain.phase.species) + rate = sum(rops(ssys.sims[2], spc.name, t_end)) + if abs(rate) > 1e-15 + println(" $(spc.name): $(rate) mol/s") + end + end +end + +check_steady_state(ssys, sol.t[end]) + +# %% +function sweep_HER_potential(Vs_RHE::Vector{Float64}, A_surf) + log_currents = Float64[] + global initialcondssurf + + for V in Vs_RHE + phi = -V # RMS expects Phi = –V_RHE + println("Simulating HER at V = $(V) V (Phi = $(phi))") + + # Update Phi + initialcondssurf["Phi"] = phi + + # Re-initialize domains + domaincat, y0cat, pcat = ConstantTAPhiDomain(phase=surf, initialconds=initialcondssurf) + domainboundarylayer, y0boundarylayer, pboundarylayer = ConstantTVDomain(phase=boundarylayer, initialconds=initialcondsboundarylayer) + inter, pinter = ReactiveInternalInterfaceConstantTPhi(domainboundarylayer, domaincat, interfacerxns, 298.15, A_surf) + diffusionlayer = ConstantReservoirDiffusion(domainboundarylayer, initialcondsreservoir, A_surf, layer_thickness) + interfaces = [inter, diffusionlayer] + + # Solve + react, y0, p = Reactor((domainboundarylayer, domaincat), (y0boundarylayer, y0cat), (0.0, 1e4), interfaces, (pboundarylayer, pcat, pinter)) + sol = solve(react.ode, Sundials.CVODE_BDF(), abstol=1e-22, reltol=1e-8) + ssys = SystemSimulation(sol, (domainboundarylayer, domaincat), interfaces, p) + + # Compute current + j = get_current_density(ssys, sol.t[end], A_surf) + println(" → j = $(round(j, digits=4)) mA/cm²") + push!(log_currents, log10(j)) + end + + return log_currents +end + + +# %% +Vs_RHE = [-0.2, -0.25, -0.3, -0.35, -0.4] +#Vs_RHE = collect(-0.25:0.05:0.25) # e.g. from –0.25 V to 0.05 V +logj = sweep_HER_potential(Vs_RHE, A_surf) + + +# %% +ηs = Vs_RHE # Signed overpotential (negative for HER) +logj = sweep_HER_potential(Vs_RHE, A_surf) + + +# %% +clf() +plot(logj, ηs, "o-", label="Tafel region") +xlabel("log₁₀(j / mA·cm⁻²)") +ylabel("Overpotential η (V)") +title("Tafel Plot for HER on Pt(111)") +legend() +gcf() + + +# %% +function extract_tafel_slope(logj::Vector{Float64}, ηs::Vector{Float64}; fit_range=2:5) + x = logj[fit_range] + y = ηs[fit_range] + p = Polynomials.fit(x, y, 1) # Linear fit: η = slope·logj + intercept + tafel_slope = p.coeffs[2] # coeffs[2] is the slope (coeffs[1] is intercept) + println("Tafel slope ≈ $(round(tafel_slope * 1000, digits=1)) mV/dec") + return tafel_slope +end + + +# %% +function extract_tafel_slope(logj::Vector{Float64}, ηs::Vector{Float64}; fit_range=3:5) + x = logj[fit_range] + y = ηs[fit_range] + + # Polynomial fit of degree 1 + p = fit(x, y, 1) # fit is from Polynomials.jl + slope = coeffs(p)[2] # coeffs[2] is the slope + + println("Tafel slope ≈ $(round(slope * 1000, digits=1)) mV/dec") + return slope +end + + +# %% +ηs = Vs_RHE # or abs.(Vs_RHE) if you want unsigned overpotential +extract_tafel_slope(logj, ηs) + + +# %% +# Get fitted slope +slope = extract_tafel_slope(logj, Vs_RHE, fit_range=1:4) + +# Rebuild line manually from fit region (same range used in fitting) +fit_range = 1:4 +xfit = logj[fit_range] +yfit = slope .* xfit .+ (Vs_RHE[fit_range][1] - slope * xfit[1]) # match offset + +clf() +plot(logj, Vs_RHE, "o-", label="Simulated Data") +plot(xfit, yfit, "--", label="Linear Fit (Tafel slope)", color="red") +xlabel("log₁₀(j / mA·cm²)") +ylabel("Overpotential η (V)") +title("HER Tafel Plot on Pt(111)") +legend() +gcf() + + +# %% +plotROP(ssys, "H2", sol.t[end]; N=10) +plotROP(ssys, "HX", sol.t[end]; N=10) +plotROP(ssys, "proton", sol.t[end]; N=10) + + +# %% +using PythonPlot + +#ηs: overpotential (Vs_RHE) +#logj: log10(j / mA/cm²) + +clf() +plot(logj, ηs, "o-", label="Simulation", color="black") + +# Add guideline lines (e.g., from j = 0.1 to 10 mA/cm² → logj = -1 to 1) +xguide = range(-1, 1, length=100) + +# Reference slopes (in V/dec) +s_volmer = 0.120 +s_heyrovsky = 0.040 +s_tafel = 0.030 + +# Choose an intercept (e.g., pass through η = -0.05 V at logj = 0) +intercept = -0.05 + +# Plot reference lines +plot(xguide, s_volmer .* xguide .+ intercept, "--", label="Volmer (120 mV/dec)", color="red") +plot(xguide, s_heyrovsky .* xguide .+ intercept, "--", label="Heyrovsky (40 mV/dec)", color="blue") +plot(xguide, s_tafel .* xguide .+ intercept, "--", label="Tafel (30 mV/dec)", color="green") + +xlabel("log₁₀(j / mA·cm⁻²)") +ylabel("Overpotential η (V)") +title("HER Tafel Plot on Pt(111)") +legend() +tight_layout() +gcf() + + +# %% +using PythonPlot +pyplot() + +# Your Tafel data +logj = [...] # Fill in from your sweep +ηs = [...] # Overpotentials in V (usually -V_RHE) + +# Linear fit (use same fit range as before) +fit_range = 1:4 +x = logj[fit_range] +y = ηs[fit_range] +p = Polynomials.fit(x, y, 1) +slope = coeffs(p)[2] +intercept = coeffs(p)[1] + +xfit = range(minimum(logj), stop=maximum(logj), length=100) +yfit = slope .* xfit .+ intercept + +# Reference guideline slopes +xref = range(-1, stop=2, length=100) +y_volmer = 0.120 .* xref .- 0.05 +y_heyrovsky = 0.040 .* xref .- 0.05 +y_tafel = 0.030 .* xref .- 0.05 + +clf() +plot(logj, ηs, "ko-", label="Simulation") +plot(xfit, yfit, "r--", label="Fit: $(round(slope*1000, digits=1)) mV/dec") +plot(xref, y_volmer, linestyle="--", color="purple", label="Volmer (120 mV/dec)") +plot(xref, y_heyrovsky, linestyle="--", color="blue", label="Heyrovsky (40 mV/dec)") +plot(xref, y_tafel, linestyle="--", color="green", label="Tafel (30 mV/dec)") + +xlabel("log₁₀(j / mA·cm²)", fontsize=12) +ylabel("Overpotential η (V)", fontsize=12) +title("HER Tafel Plot on Pt(111)", fontsize=14) +legend() +grid(true, linestyle="--", linewidth=0.5, alpha=0.7) +tight_layout() +gcf() + diff --git a/CO2_Reduction_Ag/setup.jl b/CO2_Reduction_Ag/setup.jl new file mode 100644 index 0000000..708db73 --- /dev/null +++ b/CO2_Reduction_Ag/setup.jl @@ -0,0 +1,43 @@ +# --- +# jupyter: +# jupytext: +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.17.2 +# kernelspec: +# display_name: Julia 1.10.9 +# language: julia +# name: julia-1.10 +# --- + +# %% [markdown] +# # CO2RR Project Setup +# +# This notebook just installs and compiles things, and checks it's in order. +# + +# %% +using Pkg +Pkg.activate(ENV["PYTHON_JULIAPKG_PROJECT"]) + +# %% +Pkg.add("PythonPlot") +Pkg.add("GlobalSensitivity") +Pkg.add("DifferentialEquations") + +# %% +using PythonPlot +using DifferentialEquations +using Sundials +using SciMLBase +using QuadGK +using DataFrames +using GlobalSensitivity +using Random +using Statistics + +using ReactionMechanismSimulator + +# %% diff --git a/CO2_Reduction_Cu/CO2RR_Cu.ipynb b/CO2_Reduction_Cu/CO2RR_Cu.ipynb deleted file mode 100644 index cd6082a..0000000 --- a/CO2_Reduction_Cu/CO2RR_Cu.ipynb +++ /dev/null @@ -1,554 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "using DifferentialEquations\n", - "using ReactionMechanismSimulator\n", - "using PyPlot" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[14:57:35] WARNING: not removing hydrogen atom without neighbors\n", - "[14:57:35] WARNING: not removing hydrogen atom without neighbors\n", - "┌ Warning: failed to generate StokesDiffusivity model for species vacantX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2O2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC#[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC(O)=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OOC[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species H2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH3X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [H][H].[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n" - ] - }, - { - "data": { - "text/plain": [ - "Dict{Any, Any} with 4 entries:\n", - " \"Solvents\" => Solvent[Solvent(\"water\", RiedelViscosity{Float64}(…\n", - " Set([\"surface\", \"gas\"]) => Dict{Any, Any}(\"Reactions\"=>ElementaryReaction[vac…\n", - " \"gas\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…\n", - " \"surface\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "outdict1 = readinput(\"Cu_012925.rms\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "liqspcs1 = outdict1[\"gas\"][\"Species\"];\n", - "liqrxns1 = outdict1[\"gas\"][\"Reactions\"];\n", - "surfspcs1 = outdict1[\"surface\"][\"Species\"];\n", - "surfrxns1 = outdict1[\"surface\"][\"Reactions\"];\n", - "interfacerxns1 = outdict1[Set([\"surface\", \"gas\"])][\"Reactions\"];\n", - "solv1 = outdict1[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "sitedensity1 = 2.943e-5; # Cu111\n", - "sitedensity2 = 2.292e-5; # Ag111\n", - "AVratio = 36;\n", - "Phi1 = -1.414;\n", - "Phi2 = -0.614;" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "initialcondsliq = Dict([\"proton\"=>10.0^-4,\"CO2\"=>10.0^-3*10^3,\n", - " \"V\"=>1.0,\"T\"=>298.15,\"Phi\"=>0.0,\"d\"=>0.0]);\n", - "initialcondssurf1 = Dict([\"CO2X\"=>0.4*sitedensity1*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity1*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity1*AVratio,\n", - " \"OX\"=>0.1*sitedensity1*AVratio,\n", - " \"OCX\"=>0.1*sitedensity1*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity1*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity1*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity1*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity1*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>Phi1]);" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "initialcondssurf2 = Dict([\"CO2X\"=>0.4*sitedensity1*AVratio,\n", - " \"CHO2X\"=>0.1*sitedensity1*AVratio,\n", - " \"CO2HX\"=>0.1*sitedensity1*AVratio,\n", - " \"OX\"=>0.1*sitedensity1*AVratio,\n", - " \"OCX\"=>0.1*sitedensity1*AVratio,\n", - " \"vacantX\"=>0.1*sitedensity1*AVratio,\n", - " \"CH2O2X\"=>0.05*sitedensity1*AVratio,\n", - " \"CHOX\"=>0.04*sitedensity1*AVratio,\n", - " \"CH2OX\"=>0.01*sitedensity1*AVratio,\n", - " \"A\"=>1.0*AVratio,\"T\"=>298.15,\"Phi\"=>Phi2]);" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "liq1 = IdealDiluteSolution(liqspcs1,liqrxns1,solv1,name=\"liquid\",diffusionlimited=true);\n", - "\n", - "surf1 = IdealSurface(surfspcs1,surfrxns1,sitedensity1,name=\"surface\");\n" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "domainliq1,y0liq1,pliq1 = ConstantTVDomain(phase=liq1,\n", - " initialconds=initialcondsliq,constantspecies=[\"proton\",\"CO2\"]);" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "domaincat1,y0cat1,pcat1 = ConstantTAPhiDomain(phase=surf1,\n", - " initialconds=initialcondssurf1);\n", - "\n", - "inter1,pinter1 = ReactiveInternalInterfaceConstantTPhi(domainliq1,\n", - " domaincat1,interfacerxns1,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "domaincat2,y0cat2,pcat2 = ConstantTAPhiDomain(phase=surf1,\n", - " initialconds=initialcondssurf2);\n", - "\n", - "inter2,pinter2 = ReactiveInternalInterfaceConstantTPhi(domainliq1,\n", - " domaincat2,interfacerxns1,298.15,AVratio*1.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 21.536523 seconds (51.04 M allocations: 3.047 GiB, 10.94% gc time, 99.91% compilation time: <1% of which was recompilation)\n", - " 7.551352 seconds (18.91 M allocations: 1.187 GiB, 8.74% gc time, 98.02% compilation time)\n" - ] - } - ], - "source": [ - "@time react1,y01,p1 = Reactor((domainliq1,domaincat1), (y0liq1,y0cat1), (0.0, 1.0e3), [inter1], (pliq1,pcat1,pinter1));\n", - "\n", - "@time sol1 = solve(react1.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-8);\n", - "\n", - "ssys1 = SystemSimulation(sol1,(domainliq1,domaincat1,),(inter1,),p1);" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.002376 seconds (6.54 k allocations: 3.020 MiB)\n", - " 0.275685 seconds (753.23 k allocations: 199.470 MiB, 29.83% gc time)\n" - ] - } - ], - "source": [ - "@time react2,y02,p2 = Reactor((domainliq1,domaincat2), (y0liq1,y0cat2), (0.0, 1.0e3), [inter2], (pliq1,pcat2,pinter2));\n", - "\n", - "@time sol2 = solve(react2.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-8);\n", - "\n", - "ssys2 = SystemSimulation(sol2,(domainliq1,domaincat2,),(inter2,),p2);" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotX (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotX(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = molefractions(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Mole Fraction\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotC (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotC(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = concentrations(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time in Sec\")\n", - " ylabel(\"Concentration\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys1.sims[1], 1e-10, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-12, 5)\n", - "title(\"Liquid-phase Mole Fractions vs. Time on Cu111@-1.0V vs RHE\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotC(ssys1.sims[1], 1e-10, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-12, 1e5)\n", - "title(\"Liquid-phase Concentrations vs. Time on Cu111@-1.0V vs RHE\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "39×2990 Matrix{Float64}:\n", - " 0.0 0.0 0.0 … 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 0.0 0.0 0.0 0.0\n", - " 1.0 1.0 1.0 1.0 1.0\n", - " 0.0001 0.0001 0.0001 … 0.0001 0.0001\n", - " 0.0 0.0 0.0 0.0 0.0\n", - " 0.0 3.27496e-27 6.54991e-27 3.29138e-17 3.28967e-17\n", - " 0.0 1.24107e-27 2.49736e-27 0.0691037 0.0691037\n", - " 0.0 2.50461e-21 5.00922e-21 41.9391 42.135\n", - " ⋮ ⋱ \n", - " 0.0 1.02567e-110 1.48474e-89 … 7.38278e-26 7.38278e-26\n", - " 0.0 4.46254e-123 2.68246e-122 1.65112e-93 1.63978e-93\n", - " 0.0 4.39016e-85 1.58444e-84 5.88359e-47 5.88359e-47\n", - " 0.0 1.30327e-57 5.21314e-57 1.68635e-14 1.68635e-14\n", - " 0.0 1.22005e-82 9.71798e-82 4.50202e-27 4.50202e-27\n", - " 0.0 3.13785e-83 2.5273e-82 … 1.14862e-14 1.14862e-14\n", - " 0.0 9.69845e-87 7.72537e-86 8.31806e-15 8.33851e-15\n", - " 0.0 2.01214e-138 1.60272e-137 2.20627e-61 2.21169e-61\n", - " 0.0 0.0 8.98209e-107 3.89495e-22 3.89495e-22" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "concentrations(ssys1.sims[1])" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys1.sims[2], 0.1, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-12, 5)\n", - "title(\"Surface coverage on Cu111@-1.0 V vs. RHE\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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YOXKkU3nxUR1ldYEWx9y2bVs6duzoFPOgQYMqfCSXi4sLO3fudLq8++67TnVuv/32Euvl5eXxxBNP0LRpUzQaDRqNBnd3d/Lz8zly5Iij3vr16xkwYACtWrW6ZCwVsXnzZoASR710796dVq1alfh7BQcH0717d6ey9u3bO3VHdu/enX379jF16lQ2bNhATk5OhWIZMmQIwcHBTi0yGzZsIDEx0en57t69O+vXr+fJJ59ky5YtFBYWVmj7NUFRFIYOHeq4r9FoaNq0KSEhIXTq1MlR7uvrS2BgoNPf6YcffmDAgAGEhoY6vd6GDBkCUO5RcjXxvF1NDh06REJCguMzuLCwkEGDBuHi4sJ3333Hiy++yLx580hMTHSsM2zYMKeDSy58ziwWC/bvdbvyWkMqezTtO++8w6JFi3j00UedWp8A3N3dGTVqFD/99JOj9+TgwYPs3r2bcePGXbLbs127dnTp0sXpPXfkyBHHAPhiVX1PF3viiSfQarUYDAY6duzIwYMH+f7778tsEfz1119LfI7u3LmzzIPFRo0aVWr9C9+bFSG7+apJZmYmNpuN4ODgEstKK6uq4u6IiuwnOjra6QNv3rx5TuOxytqGyWQiLy8PLy8vR/nFfed6vR7A8WV09uxZ+vTpQ4sWLXjttdeIiorCYDCwY8cOpk2b5qjn5eXF1q1bWbRoEXPmzCEzM5OQkBDuu+8+5s6di1arJSUlBSFEmV15TZo0KfPvczFFURg/fjyvv/46RqOR5s2b06dPn1LrpqenExwcXOIDKzAwEI1GU25XUEpKCidPnkSr1Za6vCJTS6hUKsd4gLKUdlTnXXfdxaZNm3j66afp1q0bnp6eji/qC5OF1NTUcrvsKqv471FaTKGhoSW+bEsbf6HX651inD17Nm5ubnz00UesXLkStVpN3759Wbx4cbl/G41Gw7333ssbb7xBVlYW3t7erF27lpCQEAYNGuSo9/rrr9OoUSM+//xzFi9ejMFgYNCgQSxdupRmzZpV+m9wOVxdXZ1+zADodDp8fX1L1NXpdBiNRsf9lJQUvv/++yq93mrieStN8ViomJiYSg0/qO+OHz9OdHQ0bm5ugD2xzcvL4+uvv8bd3R2w/2379evnWCcoKIjU1FTH/YuftzVr1jBu3Dj8/PwwGo0UFBTg6urqVCcjI8PRzVsRa9asYcqUKUyePJmlS5eWWmfixIm89957fPjhh8yaNYv33nvP8ZlZERMmTGDatGkcPXqUli1bsmbNGvR6vWO8KlT9PV3s4Ycf5p577qGoqIi///6buXPncsstt7Bv375SX5sdOnRw6qYudvF7rVhAQECF4rgUmUxVEx8fHxRFITk5ucSyi8uKn9SLBzVXZNxG8YunrP1cmK1///33TvsIDQ0tN67iMp1O5/hQqKh169aRn5/PN99849RCVtp8Re3ateOzzz5DCMH+/ftZu3YtCxcuxMXFhSeffBJ/f38UReGPP/5wJG0XKq2sPOPGjeOZZ55h5cqVLFq0qMx6fn5+/PPPPwghnBKqc+fOYbFYSn2DFvP398fFxcVpDNnFy6vDxYlednY2P/zwA/PmzePJJ590lBcVFZGRkeFUNyAgoMQA48tR/FpMSkoqkaQlJiZW6TFrNBpmzpzJzJkzycrK4tdff2XOnDkMGjSIuLi4El8wFxo/fjxLly7ls88+Y/To0Xz33XfMmDHDacyZm5ubY8xhSkqKo5Vq2LBhHD16tNLx1hV/f3/at29f5uv54vf6hWrieSvNoEGDmDNnDuvWravQlBoXfi5e+B6vb3Pcmc1mpy/mmJgYmjdv7vSZefHYqPj4eKe/686dO52WN27cGPhvrNSBAwfo0aOHY3lycjJpaWm0bdu2QjGuWbOGSZMmMXbsWFauXFlmi1avXr1o1aoVa9as4eGHH+ajjz7iuuuuc8RzKXfeeSczZ85k7dq1LFq0iA8//JARI0bg4+PjqHM572mwj9ksTnZ69+5NcHAw99xzD/PmzePNN9+sUJy1QXbzVRM3Nze6d+/ON9984/QLMjc3t8TcJkFBQRgMBvbv3+9U/n//93+X3M8111yDwWDg448/dirftm1biV+U7dq1o2vXro7LxR+wZcXap08fpy+giih+s174ISiE4O233y53nQ4dOvDKK6/g7e3Nnj17ALj55psRQpCQkOAUf/Hl4sGZlxIWFsZjjz3GsGHDGDt2bJn1rr/+evLy8kocMfPBBx84lpfl5ptv5tSpU/j5+ZUac1lN0pdLURSEECUSzHfeeadEV+2QIUPYvHkzx44dK3N7F7c4lqf4CK2PPvrIqXznzp0cOXKk3L9XRXh7ezNy5EimTZtGRkbGJSeubdWqFT169GDNmjV88sknFBUVlfsLOygoiHHjxnHnnXdy7NgxCgoKLive2nTzzTdz8OBBoqOjS329lZdM1fTzVqxz584MGTKEd999t9T508B+JOrZs2cBHO+Riz8Xy5sbqi5ERERw6tQpx/srKCiIuLg4p/db8SDpYmvXrnVqIb34+SpOcAcPHozBYChxpHfxEY0VGcy/du1aJk2axD333MM777xzya7BCRMmcPjwYebOnUtqamqZwyBK4+Pjw4gRI/jggw/44YcfSE5OLnf9yr6nS3P33XfTv39/3n777XrV1Sxbpsrx22+/lfpkl9WX+uyzzzJ48GAGDhzIo48+itVqZfHixbi5uTm1EhSPB3rvvfeIjo6mQ4cO7Nixg08++eSSMfn4+DBr1iyee+45Jk2axP/+9z/i4uKYP39+pbsT1Wo1AwcOZObMmdhsNhYvXkxOTg4LFiyo1HYABg4ciE6n48477+Txxx/HaDSyYsUKMjMzner98MMPLF++nBEjRtCkSROEEHzzzTdkZWUxcOBAwP7rY/LkyYwfP55du3bRt29f3NzcSEpK4s8//6Rdu3Y88MADlYqv+JDz8owZM4a33nqLsWPHEhsbS7t27fjzzz95/vnnGTp0KDfccEOZ686YMYOvv/6avn378sgjj9C+fXtsNhtnz57ll19+4dFHH3X6pVldPD096du3L0uXLsXf35+oqCi2bt3Ku+++i7e3t1PdhQsXsn79evr27cucOXNo164dWVlZ/Pzzz8ycOZOWLVsSHR2Ni4sLH3/8Ma1atcLd3Z3Q0NBSv5xbtGjB5MmTeeONN1CpVAwZMsRxVFh4eDiPPPJIpR/PsGHDaNu2LV27diUgIIAzZ87w6quvEhkZWaFuuAkTJjBlyhQSExPp1atXie6lHj16cPPNN9O+fXt8fHw4cuQIH374IT179nT8Qv7ggw+YMGEC7733XrlHq9WlhQsXsnHjRnr16sX06dNp0aIFRqOR2NhYfvrpJ1auXFlml25NPG9l+eCDDxg8eDBDhgxhwoQJDBkyBB8fH5KSkvj+++/59NNP2b17NxEREQwdOhRfX18mTpzIwoUL0Wg0rF271umQ/mKpqamOcWEHDhwA7GMCiydJvbCLbdeuXY7P8ZycHIQQfPXVV4C9BenClvTi8uIpWHbt2uVocSoeS1ncSrJx40bHY3vooYd49NFHmTNnDrm5uUybNg2wH0E7a9Ys1q9fX+4ZNYr5+voyd+5cnn76aXx9fR2Tds6fP59JkyY5TbBZ2uv0yy+/ZOLEiXTs2JEpU6awY8cOp+136tSpxA+vMWPGMGfOHJYuXYq3tze33XbbJeO80IQJE/j888958MEHadSoUYnPyct9T5dm8eLF9OjRg2effZZ33nmnStsolpKSwt9//12i3NPTs3IT7VZ6iP1VoPjokbIuMTExZR6R991334n27dsLnU4nIiIixIsvvljqUSrZ2dli0qRJIigoSLi5uYlhw4aJ2NjYSx7NJ4QQNptNvPDCCyI8PFzodDrRvn178f3331d40s4Lj5JYsGCBaNSokdDpdKJTp05iw4YNTnXLmgittLi+//570aFDB2EwGERYWJh47LHHxPr1652OZDp69Ki48847RXR0tHBxcRFeXl6ie/fuYu3atSXifO+990SPHj2Em5ubcHFxEdHR0WLMmDFi165d5T6+ik66WtqRPenp6eL+++8XISEhQqPRiMjISDF79mxhNBqd6pU2aWdeXp6YO3euaNGihdDpdMLLy0u0a9dOPPLIIyI5ObncWC41aWd5E9LFx8eL22+/Xfj4+AgPDw8xePBgcfDgwVJjjIuLExMmTBDBwcFCq9WK0NBQMWrUKKfJ/j799FPRsmVLodVqnV6Ppb2OrVarWLx4sWjevLnQarXC399f3HPPPSIuLs6pXr9+/USbNm1KfdyRkZGO+8uWLRO9evUS/v7+jvfQxIkTRWxsbJl/mwtlZ2cLFxcXAYi33367xPInn3xSdO3aVfj4+Ai9Xi+aNGkiHnnkEafJCYtfP5WZuLQqR/OV9nyX9XeKjIwUN910k1NZamqqmD59umjcuLHQarXC19dXdOnSRTz11FMiLy+v3Hir+3krT2FhoXj99ddFz549haenp9BoNCI0NFTcdttt4scff3Squ2PHDtGrVy/h5uYmwsLCxLx588Q777xT4rOm+G9a2uXi93RZR8qW9hyX97l/ofnz54u2bds6/s7ff/+98PHxEYBQq9XiySefFJGRkUKlUokbb7xRHDt2rEJ/q2KvvfaaaN68ueM9MG/ePGEymZzqlPY6Le+xXvw3vNCtt95a6hGeFWG1WkV4eLgAxFNPPVVieVXf02VN2lnsf//7n9BoNOLkyZNCiKpP2lnWpfhI6opSzm9QqkHz589nwYIF1Jc/dWxsLI0bN2bp0qXMmjWrrsORJElqUAoLC+nfvz8eHh588cUX+Pr6YrFYOHHiBEFBQfj6+nL8+HGCgoKcDuSRrlxyzJQkSZIkVYKLiws//vgjNpuNVq1a8fzzz3P48GEaNWqEVqtl3759fPnll3Tp0qXcKVWkK4ccMyVJkiRJleTv78+vv/7KRx99xBtvvMHcuXMdvQ8ajYZrr72Wl19+udoG9Ev1m+zmkyRJkqTLlJ2d7ZioMzIy8pKH/EtXFplMSZIkSZIkXQY5ZkqSJEmSJOkyyGRKkiRJkiTpMsgB6FVks9lITEzEw8Oj0ieflCRJkiSpbgghyM3NJTQ09JIndK4omUxVUWJiIuHh4XUdhiRJkiRJVRAXF1dtJ3+XyVQVeXh4APYnw9PTs46jkSRJkiSpInJycggPD3d8j1cHmUxVUXHXnqenp0ymJEmSJKmBqc4hOnIAuiRJkiRJ0mWQyZQkSZIkSdJlkMmUJEmSJEnSZZDJlCRJkiRJ0mWQyZQkSZIkSdJlkMmUJEmSJEnSZZDJlCRJkiRJ0mWQyZQkSZIkSdJlkMmUJEmSJEnSZZDJlCRJkiRJ0mWQyZQkSZIkSdJluKqTqR9++IEWLVrQrFkz3nnnnboOR5IkSZKkBuiqPdGxxWJh5syZbN68GU9PTzp37sxtt92Gr69vXYcmSZIkSVIDctW2TO3YsYM2bdoQFhaGh4cHQ4cOZcOGDXUdliRJkiRJDUyDTaZ+//13hg0bRmhoKIqisG7duhJ1li9fTuPGjTEYDHTp0oU//vjDsSwxMZGwsDDH/UaNGpGQkFAboUuSJEmSdAVpsN18+fn5dOjQgfHjx3P77beXWP75558zY8YMli9fTu/evVm1ahVDhgzh8OHDREREIIQosY6iKJWO43hKDu4FlVtHofL7AahCeFXcU9X2VdU9VnVfVX9sVYixyvuqwjq1+Pqoqio/Z1VcsSprVf11Vf9fw1VZsbZfV1V7zur/60OlUlArCmqVgspxXfXYpStDg02mhgwZwpAhQ8pc/vLLLzNx4kQmTZoEwKuvvsqGDRtYsWIFL7zwAmFhYU4tUfHx8fTo0aPM7RUVFVFUVOS4n5OTA8Bty7ej0rte7sORJEmSGjCVglOCpVYUe+LlKMOprPi2RqWg06jQqVX264tu60ssUzvKXXVqXHRq3HQaXHVqXPXnr3VqXM+X6TUqmejVggabTJXHZDKxe/dunnzySafyG2+8kW3btgHQvXt3Dh48SEJCAp6envz0008888wzZW7zhRdeYMGCBSXK/dy0qA26SsVXSqNYxdar2mqltsLV7P6qul7txnk5K1/xz0UV91jbr+3LWbmhPMaG8pq52tkE2KyCy3w1VzuVAm46DW56DZ4uGrxctHi5aPE8f13axddNh7+HHg+9RiZiFXRFJlNpaWlYrVaCgoKcyoOCgkhOTgZAo9GwbNkyBgwYgM1m4/HHH8fPz6/Mbc6ePZuZM2c67ufk5BAeHs7Wx6/D09OzZh6IJEnSVaDKCWMdJLZWIbDZwCoEVpvAZisuExeUXbD8/PWFt21CYLHa61usApPFhtlqw2S1UWSxYSq+WEu5ff66yGKj0GQhv8hKgdlKQZGFApOVApP9ushiA+xJXm6RhdwiC8k5lXu8Oo2KAHc9fu46/N31+Duu9QR66gn1diHUy4UADz1q1dWddF2RyVSxizNqIYRT2fDhwxk+fHiFtqXX69Hr9dUanyRJknQZY6Vq/ftbaTBfmharjQKzlUKTlfwie9KVXWh2XHKMZuf756+zCsxk5JvIK7JgsthIyCokIauw3H1pVApBngbCvF0I8TacT7IMNPJ1pbGfG2E+LmjVDfZ4twppKK+LSvH390etVjtaoYqdO3euRGuVJEmSJF1pNGoVnmoVngZtldY3mq2k5haRlldEWp7Jfp1bRHq+idS8IlKyjSRlG0nOMWKxiXKTLrVKoZGPC1F+bkT5uRLl70aUnxtNAtwI93FFdQW0al2RyZROp6NLly5s3LiRW2+91VG+ceNGbrnlljqMTJIkSZLqP4NWTbivK+G+5R9gZbUJzuUaScwqJDHLSFK2/Tohq5C4jAJi0/Mxmm2cSS/gTHoBW0vsR0WzQA+aB3nQItidZkEetAjyIMTL0KDGazXYZCovL4+TJ0867sfExLB37158fX2JiIhg5syZ3HvvvXTt2pWePXuyevVqzp49y/3331+HUUuSJEnSlUOtUgjxciHEy4UukSWX22yCc7lFxKTlcyY9n9j0AmLT8olNz+d0mj3ROpCQzYGEbKf1PPQaWoZ40C7Mm3aNPGkX5kVjf/cqj80ynztH0ZEjGI8cJXXfviptozyKqOrIvzq2ZcsWBgwYUKJ87NixrF27FrBP2rlkyRKSkpJo27Ytr7zyCn379q2W/efk5ODl5UV2drYcgC5JkiRJlWS1Cc6k53M8JZdjyXkcP5fL8eRcTqflY7WVTE3cdGrahHrRNsyL9o286BjuTaSfa4kWLGtuLsZDhyjcfwDjgf0UHjiI5YJhP3lWK91PnqjW7+8Gm0zVNZlMSZIkSVL1K7JYOZ2az6HEHA6eb7U6lJiN0WwrUdffTcf1nkX0zo+ncdIJXE4exRwbU/JQT5UKXZPGGFq2whwVSeOHHpLJVH0gkylJkiRJqh0Wq41TqfkciMvk7O4DmP/dg++pw7ROPYVvUW6J+vm+gahbtyGkRxc8O7bH0Lo1Kjc3oGa+vxvsmClJkiRJkq585qQk8rdtw/2vv2i/bTttsrKclts0GhJDotnlGcEej3CO+0SQrXcHQBur0MlmoVd2Ar2i/ekY7l0jMcqWqSqSLVOSJEmSVP1sBQUU7NxJ3l9/kf/XNkynTjktV1xdce3UCdduXXHt0gVD+/ao9HqEEJxOy2d3bCb/xGSw/VQaidlGp3VdtGo6BOv4/MHrZcuUJEmSJElXDktaGrmbN5O36Tfyt29HXHAuXFQqXNq1w613b9yu7Y1Lu3Yo2pLzZymKQnSAO9EB7ozqFo4QgjPpBWw7lc5fp9LYfiqdjHwT206mV3v8smWqimTLlCRJkiRVjRAC0+nT5G76jbxNmyjcv99p0Lg2NBS3a6+1J1DX9EDt5XXZ+7TZBMfP5fLrvlgeGtxBtkxJkiRJktTwFJ0+Tc5P68lZv75E952hXTs8rhuA+3XXo2/erNon7VSpFFoGexLqGsVD1bplmUxJkiRJklSDTHFxjgSq6OhRR7mi1eJ6zTV4XH8d7gMGoG3Ap3uTyZQkSZIkSdXKkplJzg8/kv3ddxgPHPhvgUaDW+9eeA4Zgsf116P28Ki7IKuRTKYkSZIkSbpswmwm748/yf72W3K3bAGz2b5ApcLtmh54DBmCxw03oPHxqdM4a4JMpiRJkiRJqjLj8eNkf7uO7O+/x5qW5ig3tG6N14gReA4dgsbfvw4jrHkymZIkSZIkqVJsJhO5GzaQ+elnFO7Z4yhX+/riNWwYXrfdiqFFizqMsHbJZEqSJEmSpAoxxceT9fnnZH31NdbMTHuhWo37gP5433Yb7n36lDoH1JVOJlOSJEmSJJVJ2Gzk//EHGZ98Qv7vfzjmg9IEBeE96n94j/wf2qDAOo6ybslkSpIkSZKkEmxGI9nffUfG2vcxnT7tKHfr3RufO+/AvX9/FI1MI0AmU5IkSZIkXcCSnk7mJ5+S+emnWDMyAFC5u+M9ciQ+d4xGFxVVtwHWQzKZkiRJkiSJopgYMt57j+z/+w5hMgH207r4jLkX75EjUbu713GE9ZdMpiRJkiTpKmY8dpz0VavIWb/eMR7K0L49fuPH4TFwoOzKqwD5F5IkSZKkq1DhwUOkrVxB3q+bHGXuAwbgd98kXDp1qvZz413JZDIlSZIkSVeRgn//JW3FCvuReQCKgsegQfjfPwVDy5Z1G1wDJZMpSZIkSboKGI8eJfWVV8nbutVeoFbjdfNN+E2ejD46um6Da+BkMiVJkiRJVzBTbCypr79Bzk8/2QvUarxG3IL/lCnoIiLqNrgrhEymJEmSJOkKZE5KIm35CrK++QasVgA8hw7F/6EH0TduXMfRXVlkMiVJkiRJVxBrXh7pq1aT8f77jikO3Pv1I2DGwxhatarj6K5MMpmSJEmSpCuAsFrJ+uprUl9/HWt6OgAuXbsQ+MgjuHbpUsfRXdlkMiVJkiRJDVzeX39xbvESio4fB0AXFUXg44/jPqC/nOKgFshkSpIkSZIaKFNsLCkvvOg4Qk/l5UXAtKn43HEHik5Xx9FdPWQyJUmSJEkNjM1oJH31atLffgdhNoNGg89ddxIwdSpqb++6Du+qI5MpSZIkSWpAcjdvJmXR85jj4wFwu/ZagubMQd9EHqFXV2QyJUmSJEkNgDkhgeTnXyBvk/30L5rgYIJmz8bjxoFyXFQdk8mUJEmSJNVjwmIh4/0PSH3jDYTRCBoNvmPHEDB1Kio3t7oOT0ImU5IkSZJUbxmPHSPpqbkYDx4EwLVbN4KfeRp9s2Z1HJl0IZlMSZIkSVI9YzOZSF+5krTVb4PFgsrTk6AnnsDrtltll149JJMpSZIkSapHCv79l6S5T2M6dQoAj4E3EPT002gDA+s4MqksMpmSJEmSpHrAVlRE6quvkbF2LQiB2s+P4KefxmPQjbI1qp6TyZQkSZIk1THjkSMkPv4ERSdOAOA1YgRBTz4h54xqIGQyJUmSJEl1RFitpL/7HqlvvAFmM2o/P0KeexaPAQPqOjSpEmQyJUmSJEl1wBQXR+ITT1K4Zw8A7jdcT8jChWh8fes4MqmyZDIlSZIkSbVICEH2N9+Qsuh5bAUFqNzcCHrqKbxuHSHHRjVQMpmSJEmSpFpizc0led48cn5aD4BL1y6EvrgYXaOwOo5MuhwymZIkSZKkWlB44AAJMx/FHBcHGg0B06fjN3ECilpd16FJl0kmU5IkSZJUg4TNRsba9zn38stgsaANCyNs2Uu4dOxY16FJ1UQmU5IkSZJUQywZGSTOnk3+1t8B8LjxRkKeexa1p2cdRyZVJ5lMSZIkSVINyP9nB4mzZmFJTUXR6QiaMxvv0aPlIPMrkEymJEmSJKkaCSFIf+cdUl95FWw2dE2aEPbKyxhatKjr0KQaIpMpSZIkSaom1txcEmfPJu/XTQB43XILwfOeQeXqWseRSTVJVdcB1JW4uDj69+9P69atad++PV9++WVdhyRJkiQ1YMZjx4kd+T/yft2EotUSPH8+IS++IBOpq8BV2zKl0Wh49dVX6dixI+fOnaNz584MHToUNze3ug5NkiRJamCyv/+epGfmIQoL0YSG0Oi113Bp166uw5JqyVWbTIWEhBASEgJAYGAgvr6+ZGRkyGRKkiRJqjBhMpHy4mIyP/kEALfevQl9aSkaH586jkyqTfW2m+/3339n2LBhhIaGoigK69atK1Fn+fLlNG7cGIPBQJcuXfjjjz+qtK9du3Zhs9kIDw+/zKglSZKkq4U5JYUz945xJFL+Ux8gfPUqmUhdhepty1R+fj4dOnRg/Pjx3H777SWWf/7558yYMYPly5fTu3dvVq1axZAhQzh8+DAREREAdOnShaKiohLr/vLLL4SGhgKQnp7OmDFjeOedd8qNp6ioyGlbOTk5l3wMQggsFgtWq/WSdaWap1ar0Wg08rBkSZIuW+HevcQ99BDW1DRUnp6ELlmMR//+dR2WVEcUIYSo6yAuRVEUvv32W0aMGOEo69GjB507d2bFihWOslatWjFixAheeOGFCm23qKiIgQMHct9993HvvfeWW3f+/PksWLCgRHl2djaepUy+ZjKZSEpKoqCgoEKxSLXD1dWVkJAQdDpdXYciSVIDlfXNtyTPm4cwm9E3a0ajt95Ed/5HvFT/5eTk4OXlVeb3d1XU25ap8phMJnbv3s2TTz7pVH7jjTeybdu2Cm1DCMG4ceO47rrrLplIAcyePZuZM2c67ufk5JTZLWiz2YiJiUGtVhMaGopOp5OtIXVMCIHJZCI1NZWYmBiaNWuGSlVve7klSaqHhMVCypIlZH7wIQAeA28g9MUXUcmxtle9BplMpaWlYbVaCQoKcioPCgoiOTm5Qtv466+/+Pzzz2nfvr1jPNaHH35IuzKOvtDr9ej1+gpt22QyOcZgucpDYusNFxcXtFotZ86cwWQyYTAY6jokSZIaCGtWFgkzZ5K/bTsA/tOm4T9tKor8USbRQJOpYhe39gghKtwCdO2112Kz2WoiLAfZ8lH/yOdEkqTKKjpxgrhpD2I+exbF1ZXQF17Ac9CNdR2WVI80yGTK398ftVpdohXq3LlzJVqrJEmSJKmqcjdtIvGxx7EVFKANC6PR8rfkaWGkEhrkz3SdTkeXLl3YuHGjU/nGjRvp1atXHUUlSZIkXSmEEKStWEH8tAexFRTg2r07UV99KRMpqVT1tmUqLy+PkydPOu7HxMSwd+9efH19iYiIYObMmdx777107dqVnj17snr1as6ePcv9999fh1FLkiRJDZ2tsJDE2XPI/flnAHzuvpugJ59A0WrrODKpvqq3LVO7du2iU6dOdOrUCYCZM2fSqVMnnnnmGQBGjx7Nq6++ysKFC+nYsSO///47P/30E5GRkXUZ9hUhOTmZhx56iCZNmqDX6wkPD2fYsGFs2rTJUWfbtm0MHToUHx8fDAYD7dq1Y9myZU5zasXGxjJx4kQaN26Mi4sL0dHRzJs3D5PJVBcPS5Ik6ZLM585x5t4x9kRKqyV44QKCn54rEympXPW2Zap///5cagqsqVOnMnXq1FqK6OoQGxtL79698fb2ZsmSJbRv3x6z2cyGDRuYNm0aR48e5dtvv2XUqFGMHz+ezZs34+3tza+//srjjz/O33//zRdffIGiKBw9ehSbzcaqVato2rQpBw8e5L777iM/P5+XXnqprh+qJEmSE+ORI8Q9MBVLcjJqb28avfkGrl271nVYUgPQICbtrI/Km/TLaDQSExPjONWNEIJCc93Mgu6iVVdqjquhQ4eyf/9+jh07VuI8hVlZWWi1WiIjI+nXrx9ff/210/Lvv/+e4cOH89lnnzF69OhSt7906VJWrFjB6dOnK/9gqsHFz40kSRJA7m+bSZg1C1FQgK5JE8JXrpATcV6h5KSdDVSh2UrrZzbUyb4PLxyEq65iT3NGRgY///wzixYtKvWEz97e3nz77bekp6cza9asEsuHDRtG8+bN+fTTT8tMprKzs/H19a3cg5AkSaohQggy1r7PuSVLQAhce15Do9deQ11NX7LS1UEmU5LDyZMnEULQsmXLMuscP34csJ+6pzQtW7Z01LnYqVOneOONN1i2bNnlBytJknSZhNlM8rPPkfXFFwB4jx5N8Nyn5PgoqdJkMlULXLRqDi8cVGf7rqjiHt+KdAuW1Ttc1sSpiYmJDB48mP/9739MmjSpwjFJkiTVBGt2NvEzZlCw/W9QFAKfeBzfsWPlqb+kKpHJVC1QFKXCXW11qVmzZiiKwpEjR5xOKn2h5s2bA3DkyJFS5/Q6evQorVu3dipLTExkwIABjiksJEmS6pLp7FniptyPKSYGxdWVsJdewuO6AXUdltSA1dupEaTa5+vry6BBg3jrrbfIz88vsTwrK4sbb7wRX1/fUrvqvvvuO06cOMGdd97pKEtISKB///507tyZNWvWyNO5SJJUpwp27iR21GhMMTFogoOJ+uRjmUhJl01+s0lOli9fjtVqpXv37nz99decOHGCI0eO8Prrr9OzZ0/c3NxYtWoV//d//8fkyZPZv38/sbGxvPvuu4wbN46RI0cyatQowN4i1b9/f8LDw3nppZdITU0lOTm5wiejliRJqk5Z69ZxZsJErFlZGNq1I+qLzzGUM0ZUkiqq/vc9SbWqcePG7Nmzh0WLFvHoo4+SlJREQEAAXbp0YcWKFQCMHDmSzZs38/zzz9O3b18KCwtp2rQpTz31FDNmzHCMOfjll184efIkJ0+epFGjRk77kTNySJJUW4QQpL7+OukrVgLgMWgQoS++gMrFpY4jk64Ucp6pKqrMPFNS/SGfG0m6uthMJpKemkvO998D4DdlCgEPT0eRQw6uWnKeKUmSJEmqIGt2NvEPPkTBzp2gVhOyYD7eI0fWdVjSFUgmU5IkSdIVxxQfT9zkKZhOn0bl5kbYa6/hfm3vug5LukLJZEqSJEm6ohTu30/cA1OxpqejCQ4mfNUqDC2a13VY0hVMdhpLkiRJV4zcTZs4M2Ys1vR09K1aEfX55zKRkmqcTKYkSZKkK0LGBx8S/+BDCKMRt759iPzwQ7RBgXUdlnQVkN18kiRJUoMmrFZSFi8m84MPgfPn2Ht6LopGfsVJtUO+0iRJkqQGy1ZYSMJjj5H36yYAAmc9iu/EifIce1KtksmUJEmS1CBZ0tKIe2AqxgMHUHQ6Qhe/iOeQIXUdlnQVksmUJEmS1OAUnT5N3OQpmOPjUXt50Wj5W7h26VLXYUlXKZlMSZIkSQ1K/o4dxD/4ELacHLQREUSsXoUuKqquw5KuYvJoPqlWREVF8eqrr9Z1GJIkNXDZ33/P2YmTsOXk4NKxI1GffSoTKanOyWRKuiwmk6muQ5Ak6SoghCBt5UoSH3sczGY8Bg0iYu0aNL6+dR2aJMlkqlYIAab8urlU8jzW/fv358EHH+TBBx/E29sbPz8/5s6dS/H5sKOionjuuecYN24cXl5e3HfffQB8/fXXtGnTBr1eT1RUFMuWLXPa5pkzZ3jkkUdQFMXpKJvy1ive3/PPP8+ECRPw8PAgIiKC1atXV/WZkCSpARJmM0lPP03qq68B4DtxAmGvvIxKnqxcqifkmKnaYC6A50PrZt9zEkHnVqlV3n//fSZOnMg///zDrl27mDx5MpGRkY7EaenSpTz99NPMnTsXgN27dzNq1Cjmz5/P6NGj2bZtG1OnTsXPz49x48bxzTff0KFDByZPnuzYRkXWK7Zs2TKeffZZ5syZw1dffcUDDzxA3759admy5eX/fSRJqtds+fnEz3iE/D/+AJWKoLlP4XvXXXUdliQ5kcmUVEJ4eDivvPIKiqLQokULDhw4wCuvvOJIhK677jpmzZrlqH/33Xdz/fXX8/TTTwPQvHlzDh8+zNKlSxk3bhy+vr6o1Wo8PDwIDg52rPfyyy+Xu16xoUOHMnXqVACeeOIJXnnlFbZs2SKTKUm6wlnS0oibcj/GQ4dQDAbCXn4Zj+sG1HVYklSCTKZqg9bV3kJUV/uupGuuucapK65nz54sW7YMq9UKQNeuXZ3qHzlyhFtuucWprHfv3rz66qtYrVbUanWp+6noeu3bt3csVxSF4OBgzp07V+nHJUlSw1F0Ooa4yZPtUx/4+BC+aiUuF3wWSFJ9IpOp2qAole5qq8/c3JwfixCixGzDogJjtSq6nlardbqvKAo2m62i4UrSVU/YBNlpheSmG8nNMJKXWURRvhlToYWiQgsmoxWr2YrNKrBaBTarwGa1YbMIbDYBQuD0zhROV6WOzSztI6DEpOTnCxzFiv22MJuxZmVB+P0oUWrUPj4on+bCp385Kiv/3ajQdu3FysVVSq6jlFp8wUZK1lGpFBSV4rhWVAoqtX18qP36fJ0Lyy6ob7+211GpVai1KtQaBY1WjVqjnL+v+u/6gtua4mudCq1ejVavRqWWw6Frm0ympBL+/vvvEvebNWtWZgtT69at+fPPP53Ktm3bRvPmzR3r6HQ6R8tWZdaTJKnyrGYbiSezOHsonZSYHNLi8zAXWS+9Yn2i8/rvdq4VaGDx1yG19r/ESqtXozMU39Y4yvSuGvSuWvRuGgxuWvSu/13r3bRotCp5Sp5KkMmUVEJcXBwzZ85kypQp7NmzhzfeeKPEUXYXevTRR+nWrRvPPvsso0ePZvv27bz55pssX77cUScqKorff/+dO+64A71ej7+/f4XWkySpYoRNEH88k6Pbkzj9byoWk3PrrVqrwtPfBQ9fPe4+BlzctehcNPaLQY1Gq0altreaqDSq/26rLjgC94Lv1otbbEr93r2w7KKWqv9aroTjfvb69WS8/S4IgUvXLgQ+8gjKBUfsOdZxtIyJsrd7/sZFu7GvVWI7l1inlP1dWEfY7C14F17bb5e+rMw651sFLRYbVosNq7mMa4sNy4VlZhsWk83eigiOMmOemapSa1ToXTW4eGhx9dTh4qnD1VOPq4cOVy8drp7/XQxuWhTV1Z14yWRKKmHMmDEUFhbSvXt31Go1Dz30EJMnTy6zfufOnfniiy945plnePbZZwkJCWHhwoVOg8gXLlzIlClTiI6OpqioCCFEhdaTJKl8FrOVo9uT+feXM+SkGR3lrl46Itr40ai5NwERnngHudTb7h9hs5H6yiuY334HD8B71CiCn3kaRSO/oipKCIHNIjAXWTEVWTAXWTEbrfbr4ovRgul8eVGhhaJ8M8Z8C0UFZooK7NfGfAvCJrBabBTkmCjIMZGekF/uvlUqBTcfPe4+ejx8Dbj7GuzX5+97+BrQuVzZz6UiKjK4RSohJycHLy8vsrOz8fT0dFpmNBqJiYmhcePGGBrYPCj9+/enY8eOV+xs5Q35uZGkC1mtNg79nsDu9WcoyLFPnqt31dCsaxAtegYTFOXZILpphMlE4lNzyfn+ewACZjyM35QpDSL2K5EQ9oTMmG+mKN9CYa6JglyTI7EqzPnvdkGOqcKtX3pXDV6BrngHuuAV4HL+titegS4Y3LSX3kA1Ku/7u6qu7FRRkiTpCnTmYDp/fXWCzOQCANx99HS6MYJWvUPR6hrOeENrbi7xD02n4O+/QaMh5Nln8b51RF2HdVVTFAWdQYPOoAG/S9e3Wm0U5pjIyywiN+P8AQ4ZRecPdLDfL8q3UFRg4VxsDudic0psw+CmxSvQBd9QN/xC3fENccM3zA1XT12DSaplMiVJktRAFOSY+P2zY5zakwqAwV1Lj2GNadU7FLWmfnbhlcWckkLc5CkUHTuGytWVsNdfx/3a3nUdllRJarUKdx8D7j4Ggpt4lVrHZLSQk2YkO7WA7HOFZJ3777og24Qx34wxxkxKjHOipXfT4BtyPsEKdcM/3AP/Ru5o9fXvB4NMpiQnW7ZsqesQJEm6iBCCk7vO8ftnxzHmm1GpFNpf14iuQ6PQu9ZuF0l1KDpxgrP3TcaSnIw6wJ+IVaswtG5d12FJNURn0ODfyB3/Ru4lltkTrUIykwvISMonI9F+yT5XQFG+haST2SSdzHbUVxTwDnYjIMKdwAhPAiI88A93t7ek1SGZTEmSJNVjpkILWz4+yold9olq/Rq5c/2YVgREeNRxZFWTv2MH8dMexJabi65JE8JXr0bXKKyuw5LqiD3R8sC/kfPr2WK22hOs88lVemIeqWdzKcg2kZmUT2ZSPsf/SbFXVsA70JXAKA+CG3sRHO2FX6hbrR5wIZMpSZKkeir1bC4b3j5IdmohKpVCl6FRdBkc2eC69Irl/PQTiU88iTCbcencmfDlb6H29q7rsKR6SKNVExDuQUC4c5KVn11E6tlcp0teZhFZKQVkpRQ4EiyNXk1QlCfBTTwJbuJFcBOvGh3oLpMpSZKkekYIwaHfE/jjyxPYLAJ3Xz2DJrUtc0xKQ5D+3hrOLVkCgMfAgYQuXYJKHlErVZKblx63dnqi2vk7ygpyTKSezSUlJpvk09mkxORgMlpJOJZJwrFMRz2fYFeCo73wDK3+MVcymZIkSapHrGYbWz89xpFtSQBEtffn+rGtav3w8eoibDbOLVlKxtq1APjcey9BTz6BIs9yIFUTV08dkW39iGxrP/zQZhNkJuWTfDr7/CWHrJQCMpPtl0JT+fNmVYVMpiRJkuqJghwTP68+QNLJbBQFet7alI4DwxvM4eEXu3gOqcDHZuE7YUKDfTxSw6BSKfiFueMX5k6bPvbxeMY8M8mns0k8mcXJA/HVvk+ZTEmSJNUDafF5/LR8P7kZRnQuGgZNakNEmwpM9FNP2fLziZ/+MPl//QUaDaGLnsPrllvqOizpKmVw1xLV3p+o9v60vSEQ5lfv9mUyJUmSVMfOHErn59UHsRRZ8Qpw4aZp7fEJdqvrsKrMkpFB3JT7MR44gOLiQqPXX8O9T5+6DkuSakzDPCREqlHJyck89NBDNGnSBL1eT3h4OMOGDWPTpk1V3ub7779P9+7dcXNzw8PDg759+/LDDz9UY9SS1DAd/TuJn97aj6XISqOWPox8smuDTqRM8QmcufMujAcOoPb2JnLtGplISVc8mUxJTmJjY+nSpQu//fYbS5Ys4cCBA/z8888MGDCAadOmVWmbs2bNYsqUKYwaNYp9+/axY8cO+vTpwy233MKbb75ZzY9AkhoGIQR7Npxh09oj2GyCFj2CufmhDg12oDmA8dgxztx5J6YzZ9CGhhL5ySe4dOhQ12FJUo2T3Xy1QAhBoaWwTvbtonGp1GDPqVOnoigKO3bswM3tv1/Hbdq0YcKECZXe/99//82yZct4/fXXeeihhxzlixYtwmg0MnPmTG655RbCw8MrvW1JaqiETfDnlyfYv9k+ELbTwAh63hqNomq4A7Pzd+wgfuo0bHl56Js3J/ztt9EGBdZ1WJJUK2QyVQsKLYX0+KRHnez7n7v+wVXrWqG6GRkZ/PzzzyxatMgpkSrmfX5yvSFDhvDHH3+Uu628vDwAPv30U9zd3ZkyZUqJOo8++igvv/wyX3/9NTNmzKhQjJLU0FmtNjatPcKJnfbJBXuPbErHGyLqOKrLk/PLLyTOegxhMuHStQvhy5ej9vSs67AkqdZc9clUQUEBrVq14n//+x8vvfRSXYdTp06ePIkQgpYtW5Zb75133qGwsGItbcePHyc6OhqdTldiWWhoKF5eXhw/frxK8UpSQ2O12PjlnUOc3puKSqVw/fhWNO8WXNdhXZbMzz4jecFCEAL3G64n7KWX5GSc0lXnqk+mFi1aRI8eNdtq5KJx4Z+7/qnRfZS374oSQgBcslswLKz6zqMlhJBzzkhXBYvZys+rD3LmQDoqjcKQye2Iau9/6RXrKSEEaW++RdpbbwHgPWoUwfOekZNxSlelqzqZOnHiBEePHmXYsGEcPHiwxvajKEqFu9rqUrNmzVAUhSNHjjBixIgy61Wmm6958+b8+eefmEymEq1TiYmJ5OTk0KxZs8uOXZLqM7PJyvoV+4k7kolaq2LoA+2IaN1w55ASVivJzz1H1qefAeA/bRr+D06TP4ykq1a9PZrv999/Z9iwYYSGhqIoCuvWrStRZ/ny5TRu3BiDwUCXLl0u+QV/sVmzZvHCCy9UU8QNn6+vL4MGDeKtt94iP7/kdPtZWVmAvZtv79695V6K3XHHHeTl5bFq1aoS23vppZfQarXcfvvtNfWQJKnOmU1WfnxzH3FHMtHo1Qx7sEPDTqTMZhIfe9yeSCkKwfOeIeChB2UiJV3V6m3LVH5+Ph06dGD8+PGlftl+/vnnzJgxg+XLl9O7d29WrVrFkCFDOHz4MBER9sGcXbp0oaioqMS6v/zyCzt37qR58+Y0b96cbdu2XTKeoqIip23l5OTYb3x4O7hc9GfU+0PzSZAJaEtr8q6/HzrLn3uMXkPvoHuXjix84mHat26BxWph45ZtrFj7CUe2/UyYHtBfYkNpJwDo2cyfhyeP5bHHZmHKTGDEkIGYLWY++vI7XnttFa8+N4dwF6OjfuVU4e9otkLeOVj3EpjSK7Grqj5nVVivNvdV5f3V5r6quL96sC+rTcX6AwNJyGyEVm1iWOsNhPy7Gv6tYmiX2N8lVrrsfdlMVuI/P0X+iWxQK4Td3gRP9Xr4Yn317K8ePGeXXk8NKvX5a9VF99WgqC66f4lytRbUOvtFowe1HjQ652u17oKy4vsGUNfbr/CrjiKKB8rUY4qi8O233zp1PfXo0YPOnTuzYsUKR1mrVq0YMWJEhVqbZs+ezUcffYRarSYvLw+z2cyjjz7KM888U2r9+fPns2DBghLl2U964Kl3flMa3cOJ6b2MxmEBGDT1N3EqS1JKKotef5cffv2DpHNpBPj60KV9Kx6572769+papW2+99k6VnzwFYeOnUZRoHO7ljz+wFiG3divmqMvn9EiiElIpfFfj2LIi6vVfUtXF6tQ83PW48QWdUejGBnus4AQ3dG6DqtcArCpwKxVYdYoWDQKNpWCTVGw2BTSjrtjyteAVuDTrAC9l7na9u34pCzlG0kpr9yxTJRRfultOX1KiwvLRRnlzvUVAYoQKFxw21F+wX3KXkbx8pIhl02tA50baN3s1zpX0LmD1vX8/Qsv7mDwAhdvMHhfcO0Des+rKjHLycnBy8uL7OxsPKvpqNMGmUyZTCZcXV358ssvufXWWx31Hn74Yfbu3cvWrVsrtf21a9dy8ODBco/mK61lKjw8nOy/P8bT3Xk8lNGmIUaE0DiiEQZ9yaPYGoz6/9KoNGORiZiz8TQmDoNivozHWMX15P6qd391sc8K7M9mg41b/Dl52g21WnDTjecID6viXHPV/PiEEBSJXPJs58iznqNQZGG0ZVNoy6ZI5GDDWsX9SZdNgEooqASobMUXcf5iQ2W1XXAfVMJ+W2MFtVU4XTRl3beI0sf36Dz+S7Dc/MAtENwDwS3g/HUguAfYr9387S1qDVRNJFMNMhVNS0vDarUSFBTkVB4UFERycnKN7FOv16PXl9K31epmuPjJMBohJsb+K0AeIly/qIygy4TGQ+RzI9UIYRNs/vAIJ08no1IrDL6/PeHt6u6oPau1iJzc/WRl7SAraye5uQcxmzPLXUdRNGg0Xmi1XqisakwxcZBfhKLS4tq6HWoPbyrahqKUUU84JXvnbwtxQfkF1+cTSqd1xH/LxaXqlrn9/8r/q1Xeti5cp7jchhDW8xcLQtjOX1tLvUDxdSkUsCkCG4D6ogWoLy6sMrVVQWsBrdmK1mxBYxZoLTY0lnS0ljS0+cfRZgt0Jpv9Yrahtl20EVd/8AoDr3DwDAOvRvb7no3stz2C7d2YV4kGmUwVu3jAY1UPsx83blw1RSRJ0tVu27enOLo9GUWBGye2IaoOEqnCwnjS0jaRlraJrOyd2Gwmp+WKosbVtQnu7i1xdW2CwRCKi6ERBkMYWq0varUriqJQdDqGsxMnYkmyoQmNIOLdd9E3blzrj+dKY+8QujjpsmCzmbHZTNhsRecvpd2+oEyYsFqN2KwFWKwFWK15WK0FWC0FWKz5WK359vvnlxW/DqxqgVUNRr0KqFjvicaqoDMLdEVmdEU2dOZC9Kbj6DOOYki04lJkQ1dk+6/VS1Hbkyq/aPBtAr7nr/2iwTvSPgbsCtIgkyl/f3/UanWJVqhz586VaK2SJEmqLft+i2PvxrMAXDemFdGda+90KkZjIsnJ60g59yN5ec5js3Q6f7y9u+Pt3R0vr064uTZDrS7/KBLj4cOcnXQf1owMdE2aEPHuO2hDQmryIVw17D/61ShK7bbc2GxmLJZcLJZszOZszJYsLOZszOYszJZs+21Lln2ZOQOTKQ2TKRWbzYRFLbCoocBQdveeIkBvVjAUmjEYLRiKUjHkJ+Oa9juuhfZWLgXsg/G9wsG/GQS0hMDWENgKAlrYx3c1QJVOpqxWK2vXrmXTpk2cO3cOm8257e+3336rtuDKotPp6NKlCxs3bnQaM7Vx40ZuueWWGt+/JEnSxU7uPsefX9qPSr1mRBNa9qz5xMNqLeLcuR9JSvqazKx/+K+LSoW3dzcC/K/Hz28Arq6NK9VqX7BrF3H3P4AtLw9D69aEv/M2Gl/fGnkMUu1RqbTodL7odBV/LoUQWCy5mEyp5y9pFBVfF6VgNCZSZEzCWJSEwIxRJzDqNOBVMr1Q2xRcCq24FphxLUzFNTcZ15QtuBVY0VgFoIBP5H/JVVAbCO0EPo0v40jP2lHpZOrhhx9m7dq13HTTTbRt27bG5hbJy8vj5MmTjvsxMTHs3bsXX19fIiIimDlzJvfeey9du3alZ8+erF69mrNnz3L//ffXSDySJEllSTyRxa9rDoOAtv3C6Dwoskb3V1SUQnz8RyQkfobZnOEo9/buQUjwrQQE3IBW61Olbedv307cA1MRRiOuXbvSaMVy1B4e1RW61MAoioJW64lW64mbW3SZ9YSwYTKlYjQmYjQmnL9OpNB4loKCWIzGeKwqK3luKvLcSraKGorAPa8I9/xzuGUk4h63AddCKyqBffxxSAd7YhXSEUI71rsEq9LJ1GeffcYXX3zB0KFDayIeh127djFgwADH/ZkzZwIwduxY1q5dy+jRo0lPT2fhwoUkJSXRtm1bfvrpJyIja/ZDTJIk6UKZyfn8tGI/VouNxh386TO6eY39yCwoiCEm9i1SUr5HCAsABn0ooaGjCQ6+FReXyzvVU94ffxL/4IOIoiLc+vah0euvy/PsSRWiKCr0+iD0+iC8vDqVWG6zmSgsjKewMJaCghgKzl/n55/CZDqHUQ9GvZ60C+azVQS45VvxzDXjkbcDz31/4b6tOMHyhrAuEHENhPeARl3rtIuw0lMjhIaGsmXLFpo3b15TMTUI5R1aaTQaiYmJcczOLtUf8rmRqpMx38xXL+4iO7WQ4Cae3DKjExpd9Y+DKU6ikpP/D+zHeuHl1ZWI8PH4+9+ASnX5w1/ztm4l/qHpCJMJ9wEDCHvtVVSlnKBckqqb2ZxJXt4x+yX/GHl5x8nPP47VWvJMHCobuOdb8cg14ZlrwSvHgmuh1T7+LLgthF8DET3s116l/7ioF1MjPProo7z22mu8+eab8vQBkiRdtWxWGxvePkh2aiEevgaGPtC+2hOpoqJznDr9MsnJ3zgOp/f3u46oxg/i5dmh2vaT+9tmEh5+GGE24zHwBsKWLUORiZRUS7RaH3x8rsHH5xpHmRA2jMYEcvMOk5NzgNycA+TkHsBiySbHQ02OhwsJxetbwCurCO+c43gfOYTHzlX21ivfJtC4LzTuZ792q7kjayudTP35559s3ryZ9evX06ZNG7Ra55H933zzTbUFJ0mSVF/99dVJ4o/az7c3dGp7XDyqL/mwWo2cjXuXM2dWYrUWAODnN4Amjafj6dm+2vYDkLNxIwkzHwWzGY9Bgwh7aSmKtuFOyChdGRRFhYtLOC4u4QQGDALsg+ELC8+Sk7vfnlzl7Ccndz9mTRFp/nrS/O1jsVQ28Mwx452TjM+pj/H6d619nqzANtCkHwRU7Uwe5al0MuXt7e10BJ0kSdLV5vCfiezfHA/AwHGt8W/kXi3bFUKQcu4HTp1cgrEoEQBPz440b/YUXl6dq2UfF8r5eQMJs2aBxYLn0KGELlmMommQM+ZIVwFFUXB1jcTVNZLgoGGAfSxWbu5hsrJ3kZ21i6zs3ZjNGWR5a8ny1hIbYU+uvHJM+GSdxvfQMUTaW9UeW6XfNWvWrKn2IKT6JS4ujvnz57N+/XrS0tIICQlhxIgRPPPMM/j5Vf1s95s3b2bp0qX8888/FBYWEhUVxZAhQ5g5cyZhYfa+bavVyuuvv86aNWs4fvw4BoOBnj17MnfuXHr37l1dD1GSqizpZBZbPz0GQI/hjWnSKaBatltYGMfRY0+TkfEHAHp9CE2jHycoaFiNDKnI/vFHEh9/AqxWPIcPI/T552UiJTU4KpUOL6+OeHl1hIhJCCEoKIghO3sXmVk7yMzcTlFRMpneOjK9dZyOAmOODcit3jiqumJqaip//vknf/31F6mpqdUZk1SHTp8+TdeuXTl+/DiffvopJ0+eZOXKlWzatImePXuSkZFx6Y2UYtWqVdxwww0EBwfz9ddfc/jwYVauXEl2djbLli0D7L/K77jjDhYuXMj06dM5cuQIW7duJTw8nP79+7Nu3bpqfKSSVHkFOSZ+fvsgNqugaZdAugyJuuxt2mwWzp59l7//GUJGxh+oVDoaN55Bz2s2Ehw8vGYSqe++I/Gxx8FqxevWWwl94QWZSElXBEVRcHNrQmjoKNq0fonevf7kmh4badF8AQF+N6JRPLHWwFyplT6aLz8/n4ceeogPPvjAMWGnWq1mzJgxvPHGG7i6ul5iC1eGyhzNJ4RAFFbxJKeXSXFxqdSH8ZAhQzh48CDHjx/HxcXFUZ6cnEx0dDRjxoxhxYoVlYohPj6e6Ohopk6dyiuvvFJieVZWFt7e3nz++efccccdfPfddwwbNsypzu23387WrVs5c+YMbm5VP/xVHs0nVZXNJvjutX9JOJaFT4gbI5/ogs5weQlIbu4RjhydTW7uAcA+T1Srlotwda25U7ZkffMtSU89BULg/b+RBC9YgKKq8u9qSarXbEYLxqMZFB5Kx3g0A5vZQpr2GJ2fm1K3R/PNnDmTrVu38v333zu6Xf7880+mT5/Oo48+Wukv2quBKCzkWOcudbLvFnt2o1Qwwc3IyGDDhg0sWrTIKZECCA4O5u677+bzzz9n+fLlPPDAA3z00Uflbu/w4cNERETw5ZdfYjKZePzxx0ut5+3tDcAnn3xC8+bNSyRSYD+K9JtvvmHjxo2MGDGiQo9HkqrTju9Ok3AsC41ezeDJbS8rkbJajcTEvsHZs28jhBWNxoOm0U8SGjoKRam5xCbzyy9JfmaePZG6YzTBzzwjEynpiiKEwJJaiPFoBsajGRTF5oDtvzYjjbcLfo27V/t+K/1p8PXXX/PVV1/Rv39/R9nQoUNxcXFh1KhRMplqwE6cOIEQglatWpW6vFWrVmRmZpKamsrChQuZNWtWudsLDQ11bNfT05OQS5zX6/jx4+Xuu7iOJNW22ANp7P75DADX3dMS35Cqt45mZG7n6NGnKCy0by8gYDAtms9Dr6/Z8/hlfvYZyfMXAOBz990EzX1KTm8jXRFsJitFp7MxHrMnUNbMIqflmgAXXNr649LGD22YO7m51TteCqqQTBUUFJR6MuHAwEAKCgqqJagrjeLiQos9u+ts39WluEdYURQCAgIIDKzYh78Qoto+tOWHv1TbctIK7aeKAdr1b0SzblU7mbrZnM3Jky+SmPQFAHpdEC1azCcg4MZqi7UsGR99TMpzzwHgO3YMgU8+Kd9LUoMlzDaKzuZQdCqLolPZmOJynVqf0Cjom3jj0sIHQwtfNP7V9z1YlkonUz179mTevHl88MEHjjEnhYWFLFiwgJ49e1Z7gFcCRVEq3NVWl5o2bYqiKBw+fLjUrrSjR4/i4+ODv78/999/f4W7+Zo3b052djZJSUnltk41b96cw4cPl7rsyJEjADRr1qziD0iSLpPVauOXdw9RVGAhqLEnvUc2rfQ2hBCcS/2Z48fnYzKlARAWdhdNox9Ho6n5c95lvP8+KS+8CIDvxAkEzpolEympQbEVmDHF5VJ0NhdTTDZFZ3PA4jzcW+2tx3A+edI39UZVA2ciKE+lB6AfPHiQwYMHYzQa6dChA4qisHfvXgwGAxs2bKBNmzY1FWu9cqWeTmbQoEEcOnSIEydOlDsA/dy5c+Tk5JS7raioKDQaDXFxcTRt2vSSA9A//fRT7rrrLjkAXao3/vnuNLt+ikXnomH03G54+lXuF67RmMSx4/NJS/sVAFfXaFq2XISPd7eaCLeE9Hff49zSpQD4TZlCwIyHZSIl1WvCYsN8rgBTXC6ms7mYzuZgSS15AJfKU4ehiRf6aG/00d5ofCv+eV4vTifTtm1bTpw4wUcffcTRo0cdh7PffffdJQYtSw3Pm2++Sa9evRg0aBDPPfccjRs35tChQzz22GOEhYWxaNEiwN6tW9FuvvDwcF555RUefPBBcnJyGDNmDFFRUcTHx/PBBx/g7u7OsmXLuOOOO/jyyy8ZO3YsS5cu5frrrycnJ4e33nqL7777ji+//PKyEilJqoyE45nsWh8LQP+7W1QqkRLCRkLCJ5w8tRSrNQ9F0RIZOYWoyKmo1foaithZ2qrVpJ7/8eI/dSr+Dz0oEympXrHmmzEn5WFOzMecdP5yrsC5y+48jb8LunAPdJGe6KO90PhX7kj1mlbplinJ7kptmQI4c+YM8+fP5+effyY9PZ3g4GBGjBjBvHnzLmvSzl9//ZWXXnqJHTt2OCbtvPnmm5k5c6aj+89isfDaa6+xZs0aTp48iV6vd0zaee211172Y2voz41UO4z5Zj5/bgd5mUW06hXCdWNKPzCiNPn5pzly9Emys+3jJD09O9Gq5SLc3VvUVLglpC5fTtrrbwDgP/0hAqZOrbV9S9KFhNmGJb0QS1oh5rRCLKn225a0Amz5llLXUQwadI3c0UV4oIvwRBfugdqt+k5xVBMtUxVKpr777juGDBmCVqvlu+++K7fu8OHDqyWw+u5KTqauZPK5kS5FCMHPqw9y+t9UvAJdGDWnW4WmQbBPvvkOMbGvYbOZUKvdiI6eRaOwu+1ntK8FQgjS3niTtOXLAQh45BH8p0yulX1LVx9hsWHLN2PNNWHNKsKSVYQ1qwhrdvFtI7Zcc7nbUPsZ0IW4oQ1xRxvihjbUDbWXvkZbneqsm2/EiBEkJycTGBhY7hw/iqJgtVqrJTBJkqS6cOSvJE7/m4pKrXDjxDYVSqRy845y5MgT5OYeBMDXtw8tWyzCxSWspsN1EEKQ+sqrpK9eDUDgY4/hN3FCre1fariETSBMVmyFFmxGK6LQgs1ov4hCC9YCC7Z8M7Y8E9Y88/kEyowwlt6ydDFFr0YT4ILW3wVNgCsafxc0AS5o/FxQ6Wt3oHhNqVAyVTzT+cW3JUmSriSZyfn88YV9LrNrbokmMLL8X602m4nY2OXEnlmBEBY0Gk+aN5tLcPBttTqeQwjBuZdeIuPd9wAImv0kvmPH1tr+r2RCCCjuv3H045ReJi5V74KOoP/qXtA5JOyJDRab/doqEFaBsNrAZr9N8X2ruKCO7b9lZhvCbD1/bcNm+u/2heXCbEWYbPaEqch6QcyVpAKVuw6Ntx61lx61t/2i8daj9jag9tKhctPWq/FNNaHSA9A/+OADRo8ejV7vPIjSZDLx2WefMWbMmGoLTpIkqbbYrDZ+XXMYi8lGo5Y+dLwhvNz6OTn7OXzkCfLz7clXQMCNtGi+oMYn37yYEIJzLy4m4/33AQiaOxffe+6u9v3YjBbM5wqwZhqxZNq7coTR+l8Lhtlm/0K2CnsCYhNOCYRw/PdfmXNC8l+ZKKXMqd6F+Ye4RN0LrypYr8qJRUOnVlC5aFAZNCguGlQGNSqDxl7mrkXtrjt/rUXlrkPtrkUxaFBUV3aiVBGVTqbGjx/P4MGDSxzJlZuby/jx42UyJUlSg7RnwxnOnclF76rh+rGty/yCsNlMxMS8TuyZVYANrdaXFi0WEBgwpNZ/fQubjZTnFpH5yScABM+fh88dd1z+doXAklKA8UQWprM5mBLzsKYbL3u7UgWoFftrT62gqBVQqVCKb6sV++l/NBfWUZ2vZ6+jaNUoOpX9Wqs6fykuu+C+VoVKp0YpTpgMGhStPLVQVVU6mSprNuv4+Hi8vLyqJShJkqTalBqXy84fYgHoe0dz3H1Kn74gP/8khw7PJDf3EABBQcNp3uxpdDrf2grVQdhsJM+bR9aXX4GiELxwAT7/+1/Vt2exYTyZReH+VIzHM7HllRw4rPbUofY1oPExoPbWo3LROL6MFa3K/oWuKKAClAtuFyv+7lAuLCpZVlo9+/aoeN3y6jnKleJ/JcrK2o9ycZnT/YvWd9QvbZsly670rrArWYWTqU6dOtln8lYUrr/+ejSa/1a1Wq3ExMQwePDgGglSkiSppljNNjatPYzNJojuFFDq6WKEsBEf/yEnTy3GZitCo/GmVctFBAbWzWeesFpJemou2evWgUpFyPOL8K7CCcCFEJhic8jflULhoXSnAcWKVoWusRf6Jl7owtzRhrpX6+HpknQlqXAyVXwU3969exk0aBDu7u6OZTqdjqioKG6//fZqD1CSJKkm7fghhvSEfFw8tPS7q0WJ1gGzOYtDh2eRnr4ZAD/fvrRqtbjWx0YVExYLiU/OJueHH0CtJnTJYrxuuqlS27AVWsjfk0L+P0lYzv03u7TKQ4truwAMrf3QR3miaGS3jyRVRIWTqXnz5gH2U4TccccdJQagS5IkNTTJp7P595czAPS/uyUuHjqn5Tk5+zlw8EGMxgRUKj1Nm86mUdg9ddYdI8xmEmY9Ru6GDaDRELZsGZ6DKn6iZEuGkdw/4inYlWIfMI69Bcq1YyCunQLQRXnJwcSSVAWVHjPVunVr9u7dS48ePZzK//nnH9RqNV27dq224CRJkmqK2WTl17WHEQJa9AimSccAxzIhBAkJH3P8xCKEMOHiEkm7tm/h4VHxmdCrm81kImHGI+T99huKVkvYa6/hcd2ACq1rSsond2schftT4fzsNtpgV9x6hODaKRBVBebSkiSpbJV+B02bNo3HH3+8RDKVkJDA4sWL+eeff6otOEmSpJry97enyD5XiJu3nmtHNXOU22wmjh2bR2LSFwAEBAyidavFaDQedRUqNqOR+OnTyf/9DxS9nkZvvoF7nz6XXM+UlE/OL7EYj2Q4yvTNvPHoF44+2ksOeJakalLpDvHDhw/TuXPnEuWdOnXi8OHD1RKUVHfGjRtX6iz3W7ZsQVEUsrKy2LJlC7fccgshISG4ubnRsWNHPv7449oPVpKqKP5YJvs3xwNw3b0tMZwfWG02Z7F37/jziZSKpk2fpF3bt+o2kSosJH7qVHsiZTAQvnLFJRMpc1oh6Z8e5dxre+yJlAIu7f0JfKgTARPbYWjqLRMpSapGlW6Z0uv1pKSk0KRJE6fypKQkpyP8pCvXtm3baN++PU888QRBQUH8+OOPjBkzBk9PT4YNG1bX4UlSuUyFFn57/wgAbfqEEtHGfvLugoIY9u2/j4KCGNRqN9q2eQ1//4p1o9UUW34+cfc/QMHOnSiurkSsWolrt25l1rfmmsjZeIb8XcmO7jyX9v54DoxEG+BaS1FL0tWn0tnPwIEDmT17Nv/3f//nmFcqKyuLOXPmMHDgwGoP8EoghMBiqpvT8Gh0qmr/BTpnzhyn+9OnT2fDhg18++23MpmS6r2/vjpBboYRT38DvW5vCkBu7iH+3TsOszkDgz6UDh3ewd29RZ3Gac3OJm7K/RTu3YvK3Z3w1atx7dyp1LrCYiPvrwRyfouznxoEMLT0xfPGSHSh7qWuI0lS9al0MrVs2TL69u1LZGQknTrZ39h79+4lKCiIDz/8sNoDvBJYTDZWP7y1TvY9+bV+aGvhRJLZ2dm0alV3g3MlqSJiD6Rx+K8kUOC6Ma3QGTRkZe1i3/5JWCy5eLi3oUOHd9HrAy69sRpkSUvj7MRJFB07hsrTk4h338GlXbsS9YQQGA9nkPXTaccM5dpwD7xvaow+Sk6iLEm1pdLJVFhYGPv37+fjjz9m3759uLi4MH78eO688060Wjmh25Xghx9+cJpHDOwTs5blq6++YufOnaxataqmQ5OkKjPmm9n80VEAOlwXTlhzH9LT/2D/gfux2Yx4e3WjQ4e363R8FIA5IYGzEyZiOnMGtb8/Ee++g6FFyVYyS3ohmetOUnQiCwCVhw6vwVG4dgqU0xtIUi2r0iAnNzc3Jk+eXN2xXLE0OhWTX+tXZ/uurAEDBrBixQqnsn/++Yd77rmnRN0tW7Ywbtw43n77bdq0aVPlOCWppv3+2XEKsk14B7lyzS1NyMj4i/0HJmOzmfDz60e7tm+hVrvUaYxFp09zdsJELMnJaENDiVjzHrrISKc6wmoj788Ecn49a58rSq3g0acRHgMaodLLcauSVBeq/M47fPgwZ8+exWQyOZUPHz78soO60iiKUitdbdXFzc2Npk2bOpXFx8eXqLd161aGDRvGyy+/LE9wLdVrp/49x4mdKSgKXD+uFbkFe9i3fwo2mwl//xto1/YNVCrdpTdUgwoPHSJu0n1YMzPRRUcT8d67aIOcT21jissl85sTmJPyAdA38cL7tmZo/es2CZSkq12lk6nTp09z6623cuDAARRFQQgB/HeCxvK6g6Qrx5YtW7j55ptZvHixbKWU6rXCXBNbPzkGQKdBkbj4xfLvv5Ow2Qrx8+1Lu7av13kiVbBrF3H3P4AtLw9DmzaEv/M2Gh8fx3JhtpK94Qx5fyWAAJWrBq+hTXDtEiinOJCkeqDSfUAPP/wwjRs3JiUlBVdXVw4dOsTvv/9O165d2bJlSw2EKNU3W7Zs4aabbmL69OncfvvtJCcnk5ycTEZGxqVXlqRaJIRgyyfHKMw14xfmRtvrVOzbNwmrNQ8f72to124FKlXdnhorb+tWzk6chC0vD9euXYl4f61TImWKyyXl9X/J+9OeSLl2CiRoZhfcugbJREqS6olKJ1Pbt29n4cKFBAQEoFKpUKlUXHvttbzwwgtMnz69JmKU6pm1a9dSUFDACy+8QEhIiONy22231XVokuTkxM4UTv+bikql0O+eEA4cmojZnIGHRzvat1+NWm2o0/hyfvqJuGkPIoqKcO/Xj/B33kZ9/uAPYbWR/Uss51bsxZJaiMpDh9/4NviOboHavW5b0iRJclbpbj6r1eo40svf35/ExERatGhBZGQkx44dq/YApdq1du3aUsv79+/v6NJdu3ZtmfUkqb7Izyri98+OA9DlplASMmZRWHgGgyGMDu3fRqNxq9P4Mr/4guR580EIPG+6idAXX0A5f0S0OSWfjC+OY07IA8ClQwA+t0SjcpVHTEtSfVTpZKpt27bs37+fJk2a0KNHD5YsWYJOp2P16tUlZkWXJEmqC0IINn98lKICCwER7rhGrSYlZTcajUe9mEcq/d13Obf0JQC87xhN8NNPo6jVCCHI+yuR7J9jwCJQuWrwvqUprh3qNl5JkspX6WRq7ty55OfbjyR57rnnuPnmm+nTpw9+fn58/vnn1R6gJElSZR3dnsSZA+moNAodbjlAfMo6FEVNu7bLcXdrdukN1BAhBKmvvEr66tUA+N13HwEzH0FRFKz5ZjK/Ou44KbGhhQ8+tzdH7Sm79CSpvqt0MjVo0CDH7SZNmnD48GEyMjLw8fGRgyElSapzuRlG/vziBABdhheScG4pANHRj+Pr26vO4hI2G8nPPkvWp58BEPDoTPzvuw+AotNZZHx2DGuOCdQK3jc1wa1niPxMlaQGolLJlMViwWAwsHfvXtq2beso9/X1rfbAJEmSKkvYBL99cAST0UpIczC5PocwmQkMGEJE+MS6i8tsJnH2HHJ++AEUheB58/C5YzTCKsj57Sy5v50FAZoAF3zvbCnPpydJDUylkimNRkNkZKScS0qSpHpp/+Z44o9motEqRPb5jKzcFFxdm9Cq1Yt11spjMxpJeGQmeZs3g0ZD6OIX8brpJizZRWR8dhRTTA4Arl2C8B4ejaoBTfArSZJdpadGmDt3LrNnz5ZzCkmSVK+kxeex7duTAHS+/RRZub+iKBratHkFjaZuWnqseXnE3TeZvM2bUfR6Gr35Bl433UTh4XTOvbYHU0wOik6N7+gW+P6vuUykJKmG2WxWEo4fqfbtVnrM1Ouvv87JkycJDQ0lMjISNzfnw4v37NlTbcFJkiRVhMVkZeN7h7BZBI27WMhXXgegSeMZeHq0vcTaNRRTZiZx903GePAgKjc3wleuwKVzV7LXx5C71X56Jm2YO353tkQjTwcjSTXGbCri7IF9nNz5N6d2/0Nmelq176PSydSIESOqPQhJkqTLse3bU2Qk5uPiqSWw47tk5+bj5dWVyMi6OdWROSWFsxMnYjp5CrWPD+Fvv40ushmp7xzAFJMNgHuvULyGNkbRVP5k5JIklc+Yl8fpf3dycud2YvfuwVxkdCzTuVb/HHMVTqbee+897r77bubNm1ftQUiSJFXVmYPpHNhsb+npNiqGczl/o1Lpad1qCYpS+91mprNnOTt+AuaEBDRBQUS89y4o/qS8vgdbrhlFp8ZnZDNc28u5oySputhsVlJOnSRm725i9+8h+cRxhLA5lrv7+dO06zU07XYNnmERPP7xt9W6/wonU/fddx8333wzgYGBAISGhrJt2zaioqKqNaDaFBMTw4QJE0hJSUGtVvP333+X6LaUJKn+KsgxsekD+/iHttd5kFlo795rHDUdV9fIWo/HeOw4ZydNxJqahjYygvB33sV0GrI37AcbaIJc8bunFdoA11qPTZKuJEIIclLPcfbQPmL3/cvZA3sx5uU61fFrFEHTbj1p1r0ngY2jHQeh5OTkVHs8FU6mik8lUiw3NxebzVZG7YZh3LhxPPfcc/Tp04eMjAz0+ro94Wl9kZyczKJFi/jxxx9JSEggMDCQjh07MmPGDK6//nqioqKYMWMGM2bMcFpv/vz5rFu3jr1795bY5meffcadd97JLbfcwrp162rlcUhXNptN8Mu7hyjMMeEb6oZf6y9IOZeJm1tzIiJqfxqEwn37ODt5CrbsbPQtWtDozZXkbM7AeDgdsJ+g2PvWpqh0cpC5JFWWEILMpATiDx8k/shB4o8cIjc91amO3tWNiHYdiOrQhagOnfD0D6y1+Co9ZupKcejQIbRaLX369AHkXFnFYmNj6d27N97e3ixZsoT27dtjNpvZsGED06ZN4+jRo5Xe5pkzZ5g1a5bjby1J1WHnDzEkHMtEo1dz7T2C47HfANCq5SJUqto9h13+9u32ExYXFODSsSPBC14h/dM4rBlG+yScw6Nx6x4sJ+GUpAoy5uWRfPoEKadOkHzqOInHj1KQneVUR6VWE9SkKZHtOxHVoQshTZujUtfNj5UKJ1OKojh9EFx8v7r9/vvvLF26lN27d5OUlMS3335bYvD78uXLWbp0KUlJSbRp04ZXX321wl/YJ06cwN3dneHDhxMfH8/IkSOZM2dODTwSe0ZtKSqqkW1fikavr9TzNHXqVBRFYceOHU5dnm3atGHChAmV3r/VauXuu+9mwYIF/PHHH2RlZVV6G5J0sbOH0tm1PhaA/nc1JyXzYQBCgm/Dy6tzrcaS++uvJDwyE2E249arJz4T5pH24UmwCNQ+evzuboWukUetxiRJDYUQgvzMDNLizpB2NpaUmFMknzpOVnJSibpqrZaQZi1o1KotjVq1JbRZS7QGQx1EXVKluvmaN2/u+GLOy8ujU6dOqFTOR6JU1/xT+fn5dOjQgfHjx3P77beXWP75558zY8YMli9fTu/evVm1ahVDhgzh8OHDREREANClSxeKSklifvnlF8xmM3/88Qd79+4lMDCQwYMH061bNwYOHFhqPEVFRU7bqkyfq6WoiNfHjqxw/eo0/f2vKvxiy8jI4Oeff2bRokWljh3z9vau9P4XLlxIQEAAEydO5I8//qj0+pJ0sbxMIxvXHAYBbfqE4t14L/EHd6NSGWgS/WitxpK1bh1JT80FqxWPgYNwufZ+sn84C4ChpS++o5qjcq3dVjJJqo9sVis5aalkpSSRmZRAetwZ0uLOkh53BmN+XqnreAUFE9ykGcHRzQhu1oLg6OZotPXz/VThZGrNmjU1GUcJQ4YMYciQIWUuf/nll5k4cSKTJk0C4NVXX2XDhg2sWLGCF154AYDdu3eXuX6jRo3o1q0b4eHhAAwdOpS9e/eWmUy98MILLFiwoKoPp0E4efIkQghatmx5ybpPPPEEc+fOdSozmUy0bt3acf+vv/7i3XffLXUMlSRVhcVs5efVBzHmmQmI8KDXyEh27X4AgMiI+zDog2stlowPPyJl0SIAPEfciSb0Zgr/TQUFPG+MwqNfIxSV7NaTrg5Wi4X8rAzyMtLJy0g/nzglk52SRFZKEjmp57CVcfYURVHhHRKKf3gEgZFNCI5uRlB0M1w8PGv5UVRdhZOpsWPH1mQclWIymdi9ezdPPvmkU/mNN97Itm3bKrSNbt26kZKSQmZmJl5eXvz+++9MmTKlzPqzZ89m5syZjvs5OTmOROxSNHo909//qkJ1q5umEoPqiw8yqEi34GOPPca4ceOcyl5//XV+//13wH6Awj333MPbb7+Nv79/xQOWpDIIIdj80VFSYnLQu2oYdF8bzqV+TaHxLDpdIBER99VaHGkrVpD2+hsAeN31INAZc2I+KjcNvne2wtDUu1ZikaSaIoTAVFhAYW4uhbnZGHNzKczNOX8/h8LcbPIy/0ueCnKy4aID1S6m1mjwCgzGOzgE//BI/MMj8QuPxDe0ERqdrpYeWc1okAPQ09LSsFqtBAUFOZUHBQWRnJxcoW1oNBqef/55+vbtixCCG2+8kZtvvrnM+nq9vspH+ymKUm/6dcvTrFkzFEXhyJEjl5yc1d/fn6ZNmzqVXTiI/9SpU8TGxjJs2DBHWfHRnxqNhmPHjhEdHV19wUtXvH9/Ocvxf1JQVAqDJ7fF3VfNgb9XABAVNRWNpuanNRFCcO7FxWS8/z4A3mPnY80JBWGxz2Z+bys03vX/vS41fMJmw2IxYzWZsZhNWM0mLBfctprNWMzn75tMWMxmrGYTJqMRU2EBpsJC+8VY6LhvLizAZCykqLAQU0F+mS1JZVGpNbj5+ODu64eHrz/eQcF4BYXgHRSCd3AIHr5+KKorc5LaBplMFbu4BUUIUanB1pfqSrza+Pr6MmjQIN566y2mT59eYtxUVlZWhcdNtWzZkgMHDjiVzZ07l9zcXF577bUKt+pJEkDM/jS2rzsFQJ9RzWjU0pe4+A8oKkpGrw8mLHRUjccgrFaSnnmG7K+/AbUO77tfxJptP+efa+dAfG5tiqK9sqc9EEJQlJ9PbnoquelpFORk27+EjfYvZZvVirDZ7K3cQiCEQAgbwlbcYiH+m2bHcVV8Q1xwJRz7u7CuU3lx/f+Cc17Haf3S6yLEBfu/aB3Ki8e5BaZS8QgbNqsNm9WKzWb/e9ms1vP3bYjz1zab1X7bqd5/612qFai6aPR6XDw8cXH3xMXTE4O7h/2+hwdu3r64+/qdT578cPHwvGKTpUtpkMmUv78/arW6RCvUuXPnSrRWSZWzfPlyevXqRffu3Vm4cCHt27fHYrGwceNGVqxYwZEjFTtBpMFgoG1b53OiFSdiF5dLUnlSYnL45d1D9gHnfcNo2y8Mq7WIM7ErAYiKnIpKVbNzxNlMJhJnPUbuL7+guAfiOWw+1hwNqBS8b26CW8+QK3Lag5zUc8QdPkDK6ZOknokh9WwMRfn5dR2WdBFFUaHWadFodWi0WtQ6HRqtDrVWe8G1FrVWi87ggtbFFZ2LC3oXV7QGF3QuxRdXdOfv613dMHh4oNXJ+RcrokEmUzqdji5durBx40ZuvfVWR/nGjRu55ZZb6jCyhq9x48bs2bOHRYsW8eijj5KUlERAQABdunRhxYoVdR2edJXJTM7nhzf3YSmyEt7Khz6j7V3RiUmfU2RKQa8PITS0Zo+UtRUUEP/QdPL/+gtNcBtcrp2OrVBB5a7F7+5W6Bt71ej+a5PVYiHu4D5O7NjO2YP7yEopeXg6gIuHJ+5+/rh5+zi+fLV6A+rzR1opKtX56XNU5wfhK/yXa14wrY7jqvhGKVPunL9/8dQ8TstKraf8V6W0suL9cdG2yonzv/WVUmOvSJyKSoVKrUZRq1GpVKhUxbft9xW1GpXaXq5Sqx31HffPL1NUKjTnk6a6mltJ+o8iLp7avIJMJhMxMTFER0ej0VR/TpaXl8fJkycB6NSpEy+//DIDBgzA19eXiIgIPv/8c+69915WrlxJz549Wb16NW+//TaHDh0iMrLmTyORk5ODl5cX2dnZeHo6H3FgNBqJiYmhcePGGBrAWKmriXxuGo68TCNfL91NXkYRgZEe3PJIJ3QGDTabhe1/X4/RGE+L5gto1OieGovBmpND3JT7Kfz3X7TNrsPQ9g4QoG3kjt+9rdF4Nfxf7UII4o8c5NDWTZza+bfTYeqKSkVw0+aENmtBQGQTAiIb4xMaJlsrpAatvO/vqqp0FlRQUMBDDz3E++cHYB4/fpwmTZowffp0QkNDSxxhV1W7du1iwIABjvvFR9KNHTuWtWvXMnr0aNLT01m4cCFJSUm0bduWn376qVYSKUmSalZ+VhH/9+pe8jKK8A5y5eYHO6Az2D+uUlM3YDTGo9X6EhJScg666mJJS+PspPsoOnoMQ+e70Ub0AwEuHQLwHdkcRduwx4YU5uVyeOsm9v/6MxmJ8Y5yVy9vmnXvRZPO3WjUqg06F3keQUm6lEonU7Nnz2bfvn1s2bKFwYMHO8pvuOEG5s2bV23JVP/+/UucD/BiU6dOZerUqdWyP0mS6oe8zCLWvbKH7HOFuPvoGTa9Ay4e9sOmhRCcPfsOAI3C7kGtdqmRGMyJiZwdPwFTQgqufR9B7Wufe81zYCQe14U36PFR2edS2PXDtxzcvBGLyT4RsVZvoGXvvrS6tj9hrdqgUsluI0mqjEonU+vWrePzzz/nmmuucfpAad26NadOnarW4CRJurrkZhhZ98q/5KQW4uFrYMTMTnj6/ZcwZWXtJCd3PyqVvsa694pOx3B24kSsWUbcrpuDyjUYNCp8RzXHtX1AjeyzNqTHn2XHui858tdWxPlpSgIiG9Nh4BBa9u6P3lW2QElSVVU6mUpNTSUwsOSZmPPz8xv0rzVJkupWWnwuP7yxj/xsE57+Bm6Z0QlPf+eWp7Nx9lapkJDb0en8qj0G4+HDnJ10H8Ksx23AUyg6T1TuWvzHtkEX3jDPr5d9LoVtX3zE4T+3OA6nj2jXkR4j/kd4m/byc1uSqkGlk6lu3brx448/8tBDDwH/Ha3w9ttv07Nnz+qNTpKkq8LZw+n8vPogZqMVnxA3hj3UAQ9f5wMECgsTSEv7DYCI8MqfdPtSCnbtIu7+B1B0Qbj2fxhFbUAT4IL/hLZofBrewQoFOdn8883n7Nv4E1aLBYCm3XrSY8T/CG7avI6jk6QrS6WTqRdeeIHBgwdz+PBhLBYLr732GocOHWL79u1s3bq1JmKUJOkKJYRg/2/xbPv6JDabIKy5N0Pub4e+lJMDJyV9BQh8fHri6tq4WuPI++MP4h+ajtq7BYYeU1AUDboID/zGtkHtVj9PrFoWm9XK3l9+5K/PP8JUWABARNsO9LlrHMHRzeo4Okm6MlU6merVqxd//fUXL730EtHR0fzyyy907tyZ7du3065du5qIUZKkK5DJaOG3D45yas85AJr3COK6e1qhLuUoOSGsJCZ9CUBo6OhqjSNn/XoSHn8CTUh3DJ3uRVFUGFr64ntXS1S6hjUQO/7oIX57dwWpZ2MBCIyKps/d44hq36luA5OkK1yVJohq166dY2oESZKkyko6mcWv7x8hJ7UQlUqh9/+a0q5/ozLH76Rn/EFRURIajTcB/jdWWxxZX31F0tPPoI3qh6HDXQC4dg3C59ZmKOqGM5aoMC+XrR+8w6GtmwAwuHvQ586xtL1uoDwyT5JqQYWSqZycnApvsLomwJIk6cpjMVn557vT7N0UBwLcffQMuq8twU3Kn0U8MfFzAEJCbkWtrp4JIzM++ICU519AG30Dhnb2c/u5XxuG102NG9Sg7FO7d7Dx7TfJz8wAoN31g7j2jjG4el45M7NLUn1XoWTK29v7kh8uxScZtlbyLNOSJF35hBDE7Evjr69OkJNmBKBlrxCu/V8z9C7lfwwVFaU6Bp6HhlTPCY3TVq0m9ZVX0DUbjL7NbQB49A/Hc1Bkg0mkjPl5bHn/bUdrlE9oIwY/8DChzVvVcWSSdPWpUDK1efPmmo5DqkeSk5NZtGgRP/74IwkJCQQGBtKxY0dmzJjB9ddfD8C2bdt47rnn2L59O4WFhTRr1oxx48YxY8YM1OWcJ8psNjN37lx++uknTp8+jZeXFzfccAMvvvgioaGhtfUQpVqUnpDHX1+dIO5IJgBu3nr639WCqPb+FVo/KfkbhLDg5dkJd/fLOwpNCEHqa6+RvnIVuuZD0bceAYDnDRF4XB/RYBKphGNH+PG1JeSmp4Ki0OWmEfQefY88zYsk1ZEKJVP9+vWr6TikeiI2NpbevXvj7e3NkiVLaN++PWazmQ0bNjBt2jSOHj3Kt99+y6hRoxg/fjybN2/G29ubX3/9lccff5y///6bL774oswvpYKCAvbs2cPTTz9Nhw4dyMzMZMaMGQwfPpxdu3bV8qOValJafB67fozh1L+pAKg1KjoODKfzoEjHqWEuRQjh6OK73IHnQgjOvfgiGe9/gDb6hv8SqcFRePYPv6xt1xZhs7Hju6/56/MPETYb3kEhDJ76CGEtW9d1aJJ0VavSiY6zsrJ49913OXLkCIqi0Lp1ayZMmICX19XTR1+ZEx0LIRBmW53EqWhVlfq1PXToUPbv38+xY8dwc3NzWpaVlYVWqyUyMpJ+/frx9ddfOy3//vvvGT58OJ999hmjR1f8i2/nzp10796dM2fOEBERUeH1qkKe6LhmCSFIOJ7F/t/iiNmXZi9UoGnnQK4ZEY1XQOVO/5KZ+Td7/r0btdqda3tvQ6Nxu/RKpcVls5E8fwFZX3yBNrIPhk73AvbTw3heX7OvuepSkJ3FT28u48z+fwFo2bsfA++bJs+dJ0mVVC9OdLxr1y4GDRqEi4sL3bt3RwjByy+/zKJFixzTJEjOhNlG4jPb6mTfoQt7oVTw8O6MjAx+/vlnFi1aVCKRAvvYuW+//Zb09HRmzZpVYvmwYcNo3rw5n376aaWSqezsbBRFwdvbu8LrSPWLyWjh+D/J7N+SQGZSvr3wfBLVdWgUfmHuVdpuwvlWqaCgm6ueSFksJM6ZQ85336OJuAZDJ/tpaDz6NcLjuobRIpVy+iT/99IictNT0ej0XDd+Cm0HDGww3ZKSdKWrdDL1yCOPMHz4cN5++200GvvqFouFSZMmMWPGDH7//fdqD1KqHSdPnkQIQcuWLcusc/z4cQBatSp9kGvLli0ddSrCaDTy5JNPctddd8kjQRugzOR8Dm5N4Oj2JExG+8EnGr2aFj2Cad+/Eb6hVUuAAMzmLFJTfwYgrIpdfMJkImHWY+T+8gvqkPa4dB4PKLj1DMFzcFSDSEaO/rWVDStfx2IqwickjOGPzsE/PLKuw5Ik6QJVapm6MJEC0Gg0PP7443Tt2rVag7tSKFoVoQt71dm+K6q4x7ciXzBl9Q4XH9UJ8PHHHzNlyhTHsvXr19OnTx/HfbPZzB133IHNZmP58uUVjlOqWzabIHZ/Gge3xjsGlQN4BbrQrn8jWvYMueQRehWRnLwOm82Eu3srPDwqPyGwzWgk/uGHyd/6O2q/Jrj2mgZWBdfOgXgPi673iZTNZuWvzz5kx/99BUBUxy7cNP0xDG5Va+WTJKnmVPoTz9PTk7Nnz5ZovYiLi8PDo2GeCLSmKYpS4a62utSsWTMUReHIkSOMGDGi1DrNm9uPpjpy5Ai9epVMEI8ePUrr1vbBsMOHD6dHjx6OZWFhYY7bZrOZUaNGERMTw2+//SZbpRoAi8nKoT8S2bcpjtwM+/QGKBDV1o92/RsR3soXRVU9CYoQwtHFFxo6utKJjy0/n7hpD1Lw99+ofEJxu+FJRBHom3njc3uzaouzpphNRax/YxkndtiHB3Qddht97horJ+CUpHqq0snU6NGjmThxIi+99BK9evVCURT+/PNPHnvsMe68886aiFGqJb6+vgwaNIi33nqL6dOnlzoA/cYbb8TX15dly5aVSKa+++47Tpw4wbPPPguAh4dHqQl2cSJ14sQJNm/ejJ+fX809KOmyWc02DmyNZ88vZynMMQFgcNPSqncIbfuG4elfuUHlFZGTs4/8/OOoVHqCg4ZXal1bfj5np0yhcNduVJ7+eNy8AFuuQBvsht/drVDUFW+trQvGvDzWLV1IwtHDqDUabrz/YVr3GVDXYUmSVI5KJ1MvvfQSiqIwZswYLOfPRK7VannggQd48cUXqz1AqXYtX76cXr160b17dxYuXEj79u2xWCxs3LiRFStWcOTIEVatWsUdd9zB5MmTefDBB/H09GTTpk089thjjBw5klGjyp5Y0WKxMHLkSPbs2cMPP/yA1WolOTkZsCdzOp2uth6qVAFnDqXz5xcnyEqxnzDXw89Al8GRtLgmGI225lpJiqdDCAwcglZb8aOErXn5xE2ZQuHu3ag8PPG+czHmFCtqLx3+49ugquCUDHUlJ+0c37wwn/T4s+hcXBnx2FzC27Sv67AkSbqEKk2NAPb5gk6dOoUQgqZNm+LqenUdnluZqREamqSkJBYtWsQPP/xAUlISAQEBdOnShUceeYT+/fsD8Mcff/D88887Ju1s2rQpEyZMuOSknbGxsTRu3LjUZZs3b3Zsv6Y09OemtpiMFv744gRHtyUB4OKp45rhTWjRMxh1DbfsWCx5/PlXT6zWAjp3/gwf724VWs+al0fcfZMp/PdfVB4e+E17E+PRIhSdioAHOqILqfpg+NqQFneGr59/hryMdNx9fLltzkICIqLqOixJuuLUxNQIVU6mrnZXcjJ1JZPPzaWlxuWy4e2DZJ8rBAU6DAin27DG1TKovCISEj7j6LGncHVtwjU9fqnQeClrXh5xk+6jcO9eVJ6eBM1dTt42e2ua792tcG1XsdnW68q52NN89dxcCnNz8GsUwW2z5+PpH1jXYUnSFalO55maMGFCheq99957VQ5GkqS6Fbs/jQ3vHsJSZMXdR88N41sT1tynVmNITPoCgNDQURVLpHJz7YnUvn2ovLwIXbqK7F/yAPAYEF7vE6nkUyf4etHTGPPzCGrSlNvnLMTFQx6QIUkNSYWTqbVr1xIZGUmnTp3KPCxekqSG6+DvCfz+6TGEgPBWPtw4qS0GN22txpCbd5ScnH0oipaQ4FsvWd+ak8PZSfdh3L8ftZcXjVa9Q/YvhWCxYWjhg+fA+j0fU+Lxo3z9/DOYCgsIadaC22YvkFMfSFIDVOFk6v777+ezzz7j9OnTTJgwgXvuuQdfX9+ajE2SpFpycGs8Wz89PyFr7xD63dWixsdGlSYx8TMAAvxvQKcrv0XJmpvL2YmTMB44gNrbm/D33qXgXwVrhhG1jx7fO1rW6ykQEo4e5usX5mE2FhLWsg23PTlPnhpGkhqoCn9aLl++nKSkJJ544gm+//57wsPDGTVqFBs2bJAtVZLUgB3+K9GRSHW6MYIB97Ssk0TKajWSnPx/gL2Lrzy2/HziJk9xJFIRa9dgzfOh8EAaqBR872yJqpbGeFVFyumTfPPifMzGQiLatuf22QtkIiVJDVilPjH1ej133nknGzdu5PDhw7Rp04apU6cSGRlJXl5eTcUoSVINidmfxuaPjgLQ4fpwet5adzODn0v9GYslB4MhDF/fa8usZzMaiZv2oP2oPU9PIta8h9onnKzvTgPgNSgKfUT9HXOUFneGr8537TVq3ZYRT8xDKw+GkKQGrco/PxVFQVEUhBDYbLbqjEmSpFqQFp/LL+8eAgGtrw2l98imdXqKlcRE+8DzkJD/oSilfzQJk4n4hx+2z2zu6krE26vRN2tBxqfHwGJD39wH9z5hpa5bH2QmJ/LVc3Mx5uYQ3LQ5tz7+DFqdvq7DkiTpMlUqmSoqKuLTTz9l4MCBtGjRggMHDvDmm29y9uxZ3N3loElJaigKckz8+NZ+LEVWGrX0oe+dzes0kSooiCEr6x9ARWjI7aXWERYLCbMeI3/r7ygGA+GrVuLSoQM5v53FnJzP/7d33/FNVf0Dxz9Z3XvvltWyV9kIMkVwIe4tTn4oLpBHxYniQBEcgPr4+LgVfRQHDihbGbJkllFoSwct3Unb7Nzz+yO0UMsodCSF836RV5Kbm3u/uaHJN+ec+z1qXy0h1yW77TgpQ0kx/3vpaaoryglLSGKC7NqTpPNGgwcVTJ48ma+//pqEhAQmTpzI119/LacBkaRWSCiC5R+nU1VuISjSh0vv6+qSMVInqpmHLzR0KF5eMfUeFw4HR558isply1DpdMS9+y4+fftizaukcnUuAEFXtUfj754V9M3VVXz/ynMYiosIjo7h2hkv4u0n5zKVpPNFg5Op9957j4SEBNq0acOaNWtYs2bNSdf7/vvvmyw4SZKa3t9pOeSml6HVqRl7fzc8fVq2/ME/KYqFgoLvAIiNubHe40IICl+YieHnn0GrJfatefhdNBhhVyj79gAo4N09DJ/u4S0deoPYbTZ+emMWpXk5+AWHcO3TL+Eb1LK1uyRJal4N/jl6++23M3z4cIKCgggMDDzlRWr9cnNzufvuu4mJicHDw4PExEQefvhhSktLG7XdVatWMW7cOEJDQ/Hx8aFz585MnTqV/Pz82nWEEHzwwQf0798fPz8/goKC6NOnD/PmzcNoNNauV1ZWxiOPPEJSUhIeHh5ER0czceJEcnJyGhXj+a4wU8/GH50DtYfcmExIjOunWCkuXo7NVoanRyShofUn9C1+6y0qvvkG1GpiZ7+G/4gRABhW5GA/akTtqyPoynYtHXaDCEVh6cJ55KbvwsPbm6ufkJXNJel8dFZFO6XzX2ZmJgMHDiQ5OZmvvvqKNm3asGfPHh5//HF+++03Nm7ceE71xd5//30mT57MHXfcwXfffUdSUhI5OTl8+umnzJkzhzfffBOA2267je+//56nn36ad999l/DwcHbs2MG8efNISkpi/PjxlJWVMWDAADw8PFiwYAFdu3YlOzubp59+mr59+7Jhwwbatm3b1Iem1bNZHKR9tAehCDr0iaDToGhXhwRA/pGvAIiOuQ61uu5HUtlnn1P63vsARD3/HAHjxgFgO1pN5Zo8AILGt0fj557de38u+ox969ag1mi44tEniUiS/y8l6bwkpHOi1+sFIPR6fb3HTCaTSE9PFyaTyQWRNc6ll14q4uLihNForLO8oKBA+Pj4iEmTJp31NnNzc4WHh4d45JFHTvp4eXm5EEKIRYsWCUD88MMP9dZRFEVUVFQIIYSYNGmS8PX1FQUFBXXWMRqNIjY2Vlx66aWnjKU1vzeNtXbRfvHu/SvEx0/+KSxGm6vDEUIIUV2dKZavaCuWr2gnjMa8Oo/pf/lFpHfsJNJTOoriBQtqlyuKIo4u3C5y/7VWFH+yp6VDbrCdK5eKN66/TLxx/WVi16o0V4cjSdIxp/v+PleuHXV6gRBCYLVaXXIRZ1FQtaysjKVLlzJ58mS8vb3rPBYVFcUtt9zCokWLEEIwadIk/Pz8Tnup6XL79ttvsVqtTJ8+/aT7DQoKAuCLL74gJSWFq666qt46KpWKwMBAFEXh66+/5pZbbiEqKqrOOt7e3kyePJmlS5dSVlbW4Nd9ISg4WMHOVc6WnOG3dMTDTQpa1pRDCA0dirf38ZIG1evXk/+vJ0AIgm++mdBJk2ofM24twpptQKVTE3Sle7b05O/fy/J/LwBgwDU30XXYKBdHJElSc3KPT9TznM1m4+WXX3bJvp966ik8PBrWBZKRkYEQgk6dOp308U6dOlFeXk5xcTEzZ85k2rRpp91eTExM7XYDAgKIjj59t1JGRgYpKSmnXae4uJiKiorTxiiE4ODBg/Tr1++027pQ2G0OVn62DwR0HBhFQhf3OAtXUawcKfgfALExN9UuN+3aTd6DU8Bmw3/spUTOeKq2bIOj2ob+N+eYr4BRCWiD3K/YZWVpCT/NmYXisNOh3yAGXXvTmZ8kSVKrJpMpqcFqWrlUKhXh4eFERDRsIK0QokE1jBq6XkNjlJy2p+VScdSIT4AHg6/t4OpwahUXp2GzleHhEVE78Nx6+DC599+PYjTiM3AAMa+9hkqjqX2OYWk2SrUdbaQPfhe5X3FOm9XCj2/MwqivICw+kUsfeBSVWnYASNL5TiZTLUCn0/HUU0+5bN8N1b69swJ2eno648ePr/f4vn37CA4OJiwsjEmTJvH555+fdnvp6ekkJCSQnJyMXq+noKDgtK1TycnJ7N2797TbDA8PJygoiPT09JM+vm/fPlQqFe3auefZXS2tsszM1t+yARh8bXu8fF1bBuFE+ccmNY45NvDcodeTO+n/cJSV4dW5M3HvvIP6hFZVa14l1ZsKAQi+uj0qF9fG+ichBMs/eJejmRl4+flz1ePP4OHlfeYnSpLUovaX7W/ybbrXp9F5SqVS4eHh4ZLL2bTQhIaGMnr0aBYsWIDJZKrzWGFhIV988QU33HADKpWKmTNnsn379tNearr5rr32Wjw8PJg9e/ZJ91tRUQHAzTffzIEDB/jxxx/rrSOEQK/Xo1aruf766/nyyy8pLCyss47JZGLBggWMGTPmnM44PB+t+99B7DaF6PaBdOgb6epwalVXZ1Jevh5QERN9A8JmI//RR7FmZaGNiiLuvYVoTphVQQhBxRJn955Prwg8k9yvDMvO5b+R/scqVGo1lz/yL4Iio878JEmSWsyhikM8tvox7vj9jibftmyZkup49913GTRoEGPGjOGll16qUxohNjaWWbNmARAREdHgbr74+Hjmzp3Lgw8+iMFg4PbbbycpKYm8vDw+/fRT/Pz8mDNnDtdffz2LFy/mpptu4plnnmH06NGEh4eza9cu5s6dy5QpUxg/fjyzZs1ixYoVjB49mtmzZ9O1a1eysrJ4+umnsdlszJ8/vzkPUauRt6+MQ9uKUKlg6I2unS7mn/LyPwUgLGwEXl4xFM6cSfX6Dah8fIhfuADdP/5vmXaX1A46D7g0yQURn97RrEOs+uTfAAy56Q4Su/V0bUCSJNXKrcxl4faF/JL1C4pQUNH0n4WyZUqqo0OHDmzZsoV27dpxww030K5dO+677z6GDx/Ohg0bzrnFZ/LkySxbtoz8/HyuvvpqOnbsyD333ENAQEDtQHaVSsWXX37Jm2++yeLFi7n44ovp3r07zz//PFdddRVjxowBICwsjI0bNzJ8+HDuv/9+2rZty/XXX0/btm3ZvHmzrDEFKIrgz28PAtB1aCxhce4zdYndXklBgXOmhLi42yn/4ksqvvoaVCpiX5+N1z9OLhA2Bf2xrkq/oXFoA91rYmCL0ciSua/isNlo27svfS6/2tUhSZIEHK0+yswNM7ly8ZX8nPkzilAYmTCSz8eefojKuVCJszl3XqplMBgIDAxEr9cTEBBQ5zGz2UxWVhZt2rTBy8v9zja6kF0o783+jQUs/3gvnj5abn1xoFuNlcrN/ZgDGS/i49OertanyZs0CRSFiGlTCb3nnnrrV67JRf9bNuoAD6Km9UHtoTnJVl1DCMGSt2ZzYMMf+IeFc9trb5/3c+4JIaiwVFBqKsVkN2G0GzHbzTiEw/k4Aue/418tapW63kWj0tRfjhq12vmYClW9dTRqDZ4aT3RqHR4aDzzUHmjU7vP/QXIPZeYyPtz1IYv2LcKqWAEYHDOYKb2m0CWsy2m/v8+V7OaTpPOM3eZg40/O8UW9xyS6VSIlhEJunrOLL9rzUo48+BgoCoETJhBy99311ndUWTGsdE5kHDgmya0SKYAdab9xYMMfqDUaLn/4X+dlIlViKmF17mp2FO9gd8lu8irzMDvMrg6rlkalwUPjUZtgnZhseWm98NX64qvzxUfng5/OD1+d836QZxBBXkEEeQYR7BlMkFcQgR6BMjlrxQxWAx/v/pjP936Oye4c99s7ojdTek2hT1SfZt23TKYk6Tyze00+VWUWfIM86T48ztXh1FFathaT6TAajR/WGb+gVFXh3SeVqOefO+mYLkPaYYTFgS7OD59e7jWnXWleDms+/RCAITffSUxyRxdH1HQcioNVuav4Yu8XbD26tU4rU41Az0B8tc4kxUvjhVqtrh2LokKFSqVChQqBQBFKnYtDOOotO/ExIYTzGue1oigoKNgVO1aHtU48DuHAZDdhwlQvxrOlQkWwVzBRvlFE+UQ5r32jiPaNJjEgkcSARHx0Po3ej9S0jDYjX+z9gv/u+S+V1koAOod2ZkqvKQyOGdwi40VlMiVJ5xGLyc6WY+OL+l3RBq2bteTk5X4CgN8OfxyZ+eji4uqVQKhhK6yuLYUQdFlbVGr3GUDvsNv49d052G1Wknr0JvWy8a4OqcmszVvL65tfJ9uQXbusW1g3BkQPoFtYN9oFtSPSNxJPjWvGrgkhsAs7NocNq8OKVbFicVic9xWrc9mxi8lhwmgzUm2rrr0Y7UYqrZXoLXoqLBVUWCooN5djsBoQCMrMZZSZy0gvPXn5lSjfKNoEtKFtUFs6h3amS2gXkgKSZIuWC9gUG98d+I73drxHqbkUgPZB7Xmw54OMSBjRoifdyGRKks4jfy87jKXaTnC0Lx0HuNep+UZjFqVla0GA5zclqP38iX9vIdrg4HrrCiGo+CUTBHh3C8OzjXuVQtjwv68pyjqEl58/YyY97FZnSp6rElMJL6x/gdV5qwFny9P1yddzXfJ1RPu5x6TY4DxRRafSoVPrmrSVyK7YqbBUUGwsprC6kEJjofO6upCC6gKy9dmUW8prl20o2FD7XG+tN51COpEamUq/6H70DO+Jl/b8HZPpakIIlh5eyjvb3iGn0jltWZxfHA/0eoCxSWNdktjKZEqSzhPmalvt/HsDrmqL2s2KWtaMlfLcrUJbpiH2/TfxbN/+pOua95djyagAjYpANyuFcOTAXjb98C0Ao+99AL8Q95iepzH+zP+TGX/OoMxchlat5bbOt3Fft/vw8/A785PPE1q1ljDvMMK8w+gUevLpqirMFWQbssnSZ3Gg/ADppensLduLyW5iW9E2thVt49+7/o1OraNnRE8GxwxmZMJIkgKTWvbFnMf+KviLuVvnsqd0DwAhXiFM6jGJaztci07juvGhF3QyNXfuXD788EOEEIwaNYq33nrrvPiFKV2YdqzIxWZ2EBrnR5seYa4Opw67vZIjeYsA8F2lIfLJJ/EbMuSk6wqHgv4X5wB6v8GxaEPdp4q41Wzit3ffRAiFzkOGkzzgIleH1ChCCD5N/5Q3trwBOLtIZg+dTYdg95l2yJ0EeQXR06snPSN61i5zKA6yDdnsLN7J5sLN/FXwF0WmIjYXbmZz4WbmbZtH+6D2jEwYyaVJl9I++OQ/IKTT21e2j3lb57HuyDoAfLQ+3NnlTm7vcju+Ol8XR3cBJ1PFxcW8++677NmzB51Ox9ChQ9m4cSMDBw50dWiSdNbM1TZ2Hjvrre9lSW73oyBn+0IULGgLILLnjQTfessp163eWIC92ITaV0fAiPgWjPLM1n7xMRVHC/APC2fEXZNcHU6jOBQHr295nS/2fgHAdcnXMb3vdNk9dZY0ag3tgtrRLqgdV3e4GiEEhw2H2ViwkVW5q9hUsImDFQc5WHGQ93e+T/ew7ozvMJ5Lky7F3+P8O/uzqeVV5vHu9nf5JfMXALQqLdelXMd93e8jzNt9fjResMkUgN1ux2x2nuJrs9kaXNFbktzNzpW5WM0OQmN9adsj3NXh1GErOkpu1n8gFIJz2hM94+lTJnuK0YZhhXMMRMDoRNRe7vMRlbd3NzuWOT/Qx0x6GE8f1/8aPldmu5kn/3iS5TnLAZjWZxq3d77d7ZLw1kilUpEUmERSYBI3drwRvUXP2ry1pB1O44+8P9hZspOdJTuZvWk2V7W/its630ZiQKKrw3Y75eZyPtj5AV/v/xq7YgdgbNJYpvSaQnyAe/3IAjeugL527VquuOIKYmJiUKlU/PDDD/XWWbBgQW3xxdTUVP74448Gbz88PJxp06aRkJBATEwMo0aNkpPjSq2SxWhjx0rnWKk+49q41VlvitnMgdl3YA+1o7KoSbn/Y1SnmXzbsDIXxWhHG+mDb1/3GUBvt1pZ9v47AHQbcUmrni6m3FzOvcvuZXnOcnRqHa8PfZ07utwhE6lmEugZyBXtruDtEW+Tdl0aU1On0iawDWaHmUX7F3HF4it4ZNUj7Cje4epQ3YLRZuSDnR8w9vuxfL73c+yKnQHRA/j68q+ZffFst0ykwI1bpqqrq+nRowcTJ07kmmuuqff4okWLeOSRR1iwYAGDBw/m/fffZ+zYsaSnp5OQkABAamoqFoul3nOXLVuGt7c3S5YsITs7G29vb8aOHcvatWsZOnRos782SWpKO1flYTXZCYnxpV0v92mVEkJQMONpypOc09rERFyNZ8ipzwqzlZio2nAEOFYKQeM+X+4bv/+a8oJ8fINDGHrrXa4O55zlVuYyeflksg3Z+Hv48/bwt5u9mKF0XJh3GHd2vZM7utzB5sLNfJL+CWvz1rIiZwUrclYwNG4oU3pNoWPI+VOzrKFsio3FGYtZuGMhJaYSADqFdOKR1EcYFDPIxdGdmdu2TI0dO5aXXnqJCRMmnPTxN998k7vvvpt77rmHTp06MW/ePOLj41m4cGHtOlu3bmX37t31LjExMSxfvpz27dsTEhKCt7c3l112GRs3bjxlPBaLBYPBUOdyvsrNzeXuu+8mJiYGDw8PEhMTefjhhyktLa2z3sGDB5k4cSJxcXF4enrSpk0bbrrpJrZs2VJnvVWrVjFu3DhCQ0Px8fGhc+fOTJ06lfz8/Np1HA4Hc+fOpXv37nh5eREUFMTYsWNZt25di7zm1spqtrPj2FipPuOS3KpVqmThQkq3LMHSRQAqEjs/eNr19b9lgUPgmRyMV3L9cgmuUpSdyeafvgNg5F2T8PJtnWe47Srexa2/3kq2IZto32g+G/uZTKRcRKVS0S+6H/NHzueHq35gfPvxaFQa1uat5bqfr2PammnkGnJdHWaLEEKwLHsZE36cwIsbX6TEVEKcXxyzh87m68u/bhWJFLhxMnU6VquVrVu3cskll9RZfskll7B+/foGbSM+Pp7169djNptxOBysXr2alJSUU67/yiuvEBgYWHuJj3fPpsbGyszMpE+fPhw4cICvvvqKgwcP8t5777FixQoGDhxIWVkZAFu2bCE1NZUDBw7w/vvvk56ezuLFi+nYsSNTp06t3d7777/PqFGjiIqK4rvvviM9PZ333nsPvV7PnDlzAOcf04033sjMmTN56KGH2Lt3L2vWrCE+Pp5hw4adtItXctq7vgBLtZ3AcG/a9XafMX+G336j5O13qB7mnK8tLGwk3t4Jp1zffKgC855SUEPQZW1aKswzUhwOlr73ForDQYf+g+jQr3V8sP/TypyV3LX0LsrMZXQM6cjn4z6nXZAc1uAO2gW148XBL/Lj+B8Z22YsKlQszV7K+B/H887f79ROi3I+2ly4mVt+vYWpa6aSbcgmxCuEJ/s9yU/jf2Jsm7GoVa0oRRGtACAWL15cez8/P18AYt26dXXWmzVrlkhOTm7wdp966inRsWNH0blzZzFlyhShKMop1zWbzUKv19decnNzBSD0en29dU0mk0hPTxcmk6nBsbiLSy+9VMTFxQmj0VhneUFBgfDx8RGTJk0SiqKILl26iNTUVOFwOOpto7y8XAghRG5urvDw8BCPPPLISfdVs97XX38tAPHTTz/VW2fChAkiNDRUVFVVNe6FHdOa35t/ctgd4pOn1ol3718hdq3Jc3U4tYw7d4q93XuI3T1TxMplyWL5iraitHTdKddXHIoofGuryP3XWlG2OKMFIz2zrb/8IN64/jLxzsTrRVV5mavDOSefp38uun3cTXT9uKu4P+1+UWVtmr8lqXnsL9sv7l16r+j6cVfR9eOuYtS3o8Sy7GWn/X5qbfaV7hOT0ibVvsa+n/cV8/+e32L/N/V6/Sm/v8+V246Zaoh/DpgUQpzVIMpZs2Yxa9asBq3r6emJp+e5TZ8ghEBRXPPrQq32bvAxKSsrY+nSpcyaNQtv77q1faKiorjllltYtGgR9913H3v27OHLL79Era7/yyEoKAiAb7/9FqvVyvTp00+6v5r1vvzyS5KTk7niiivqrTN16lS+//570tLSGD9+fINex4Xi0LZiKkvNePvr3Kbaua2wkLzJDyAsFuz3JaFoMvD1TSY4+NQlR4zbirAdqUblqSFg1Klbr1padUU5675xlg0YctOd+Aa5T9djQ1gcFl7+62W+z/gegGs6XMPTA55Gq27VH/vnveTgZN4f/T4rc1Yye/NsjlQf4bHVjzEqYRQzBsxwq3IAZyu/Kp/5f89nSeYSBAKtSsu1yddyf4/7W/XrAjcegH46YWFhaDQaCgsL6ywvKioiMjLSRVGdmqKYWL2mm0v2PeziXWg0DZtyISMjAyEEnTqdvPpvp06dKC8vJyMjA4COHU8/SDIjI4OAgACio08/FcWBAwdOu8+adaTjhBBsW3YYgG7D4txiDj7FaCR38mTsxcV4JLenrF8FWCE+/s5Tl0KwOtAvzQYgYEQCGr/6c/S5ytrPP8JqMhLZtgPdRl5y5ie4kSNVR3h09aOkl6ajVql5qNdD3NX1LnnGXiuhUqkYmTiSQbGD+HDXh3y06yOW5yxn89HN/Kvvv7i87eWt6r0sN5fz713/5ut9X2NTbACMSRrDQ70eIiHAfX5ANUYr6pA8zsPDg9TUVNLS0uosT0tLY9Cg1jmmoTUQQtS5PtMf89m2FJ5Oa/rgaAl5+8spya1C66Gm28Vxrg4HoSgc+dcTWNL3ogkJwXv2LZitR9Bqg4iKvPKUz6tck4dSaUUT4oXf4JgWjPj08vbuJv2PVaBSMeru/0PdiiaxXZGzghuW3EB6aTpBnkEsHLWQu7vdLf+GWiFvrTdTek3h68u/plNIJ/QWPU/9+RRTVk6hyFjk6vDOyGQ38e+d/2bc9+P4LP0zbIqNflH9+Oqyr3jj4jfOm0QK3LhlqqqqioMHD9bez8rKYvv27YSEhJCQkMBjjz3GbbfdRp8+fRg4cCAffPABOTk5TJrkflWJ1Wpvhl28y2X7bqj27dujUqlIT08/aZfavn37CA4OJjk5GYC9e/fSs2fPU24vOTkZvV5PQUHBaVunkpOTSU8/+Qzte/fuBaBDBzm9xYm2L3MWtuw0OAYvP9fNR1WjeN5bVKalodLpiHv3HfYandOTxMbeiEZz8v+Ddr2FqrXO+liBY5NQad3jt53icLDio/cAZ02pqPbJLo6oYcrMZbz616v8lv0bAF1Cu/DmsDeJ8XOfJFU6NykhKXxx2Rf8d/d/eW/He6zJW8PVP17NU/2fYlybcW6XKNsVOz8c/IEF2xdQbCoGICU4hUdTH2VQzCC3i7dJNNnoqya2atUqAdS73HHHHbXrzJ8/XyQmJgoPDw/Ru3dvsWbNmhaL73QD2FrzIOdLLrlExMbGnnEAeufOnc84AD0nJ6dBA9C//PJLOQD9LBTnVop3718h5k9aIfTFxjM/oZlV/PCDSE/pKNJTOoqKH38Uhsq9YvmKtmLFyg7CZMo/5fNKv94ncv+1VhxduN2tBtdu/fVH8cb1l4l377pRVOsrXB3OGSmKIn7L+k0M/Xqo6PpxV9Hjkx5i7pa5wmw3uzo0qRlklGWI63++vnbw9qOrHhWlplJXhyWEcP5fTMtOE5d/f3ltfGP+N0b8fOhn4VDqf1e4SnMMQFcJcazPRjorBoOBwMBA9Ho9AQEBdR4zm81kZWXVVmdvTTIyMhg0aBCdOnXipZdeok2bNuzZs4fHH38ci8XCxo0bCQkJYdOmTYwaNYru3bvz1FNP0bFjR6qqqvj5559ZtmwZa9asAZxV6h988EEmTpzI7bffTlJSEnl5eXz66af4+fkxZ84chBBcc801rF69mtdff52RI0diMBiYP38+H330Ed9++22TDT5vze9NjZWf7mXv+gLap0Yw5t6uLo3FuHUrOXdORNhshN5/PxGPPsLevU9ypOAbIiLG0a3rOyd9njWvkqJ3twMQ8UBPPOLdY44yo76C/zx8H1aTkVH3PECP0WNdHdJplZhKmLVxVu20MO2D2vPS4JfoEtbFxZFJzcmm2Phw14d8sOMD7MJOiFcIzwx4hlGJo1wW06aCTczbNo9dJc5emCDPIO7vfj/Xp1yPh8Z9xkLC6b+/z5V7tKtLbqNDhw5s2bKFdu3accMNN9CuXTvuu+8+hg8fzoYNGwgJCQGgX79+tevde++9dOrUiSuvvJI9e/Ywb9682u1NnjyZZcuWkZ+fz9VXX03Hjh255557CAgIYNq0aYBzPNQ333zDjBkzmDt3Lh07dmTIkCEcPnyYVatWybP4TmCqsnJg01EAeox0ba0za04OeQ88iLDZ8B8zhvCHH8JmM1B49GcA4uJuP+nzhBBULMkEwKdXhNskUgDrv/0Sq8lIRJt2bj3oXAjBkswljP9xPMtzlqNVaZnUYxLfXP6NTKQuADq1jv/r8X98edmXtA9qT5m5jEdXP8oTfzyB3qJv0VjSS9O5P+1+7l52N7tKduGt9ea+7vfx24TfuLXzrW6XSDUX2TJ1js7XlqnzXWt/b7b+ns3GHzIJT/Dnuif7uGzsgUOvJ/vGm7BmZeHVrRuJn36C2tub3LxPOXDgBXx9O9C/328njc+4q4SyL/ai0qmJnNYHbeC5lRxpaqV5uXzy+AMIReH6514hvrNrzsA9kyJjES9ueJHVeasB6BjSkRcHv3hBTkEigdVhZeGOhXy0+yMUoRDuHc7zg55naFzzTo122HCYd/9+l9+zfwdAq9ZyXfJ13Nf9Prcvc9AcLVNuOwBdkqS6FIfC7jXOKXi6j4hzWSIlbDbyHn4Ea1YW2uho4ua/i9rbGyEE+flfAhAbe/NJ4xN2xTltDOA3NM5tEimAtV98hFAU2vUZ4JaJlBCCHw7+wOubX6fSVolWreX/evwfE7tORKd2/UkIkmt4aDx4uPfDDI8fzow/Z5BtyOaBFQ9wTYdrmNZnGn4eTTv9UbY+m3/v+je/ZP6CQzhQoeKytpcxuedk4v3Pz5lBGkImU5LUSmRuL6Gq3IK3v44Oqa6ppyaEoHDmixg3bkTt40P8wgXoIpzT2Oj1W6muzkCt9iY66uqTPr9q/REcZWbU/h74D3V9SYcah3dtJ3PbZtQaDUNvmejqcOoprC7k+Q3Psy7fOVdl19CuvDj4RdoHt3dxZJK76B7enW+v+Ja3/36bz9M/57uM71h/ZD0zB89kQPSARm8/ozyDf+/6N0uzl6IIBYAhsUN4uPfDpISceiq2C4VMpiSpldi12llGoMuQWDQ61wx3LPvvx1R8+y2o1cTMeQOvEwq31rRKRUVegVZbfxyUo8qKYYWzpEPgmETUnu5Ru0lRHKz57D8A9Bg9jpCYWBdHdJwQgv9l/I85W+ZQbavGQ+3BA70e4PbOt8tK5lI9Xlovpvedzoj4ETy97mnyq/K5d9m9DI4dzAM9HqBb+Nm1uNoVO6tzV/PVvq/YVLipdvnFcRdzf/f7z3p75zP51yhJrUBxbiVHMipQq1V0GeKaL/vKFSsoev11ACL/NR3/4cNrH7Nayzha5KxvFBt780mfb1iRg7A40EX74tPbfWYq2LNmBcWHs/D09WXgtTe5Opxa+VX5PLf+Of4q+AuAHuE9mDl4Jm0D27o4Msnd9Ynqw/dXfs/crXP59sC3rMtfx7r8dfQM78nVHa5maNzQU45rMtqM7CjewYqcFSw/vJxScykAapWakQkjubfbvXQKPfmMFRcymUxJUiuwa5WzVapt73D8glt+nJE5PZ38aY+DEATdeAPBt9c9U6+g8DuEsOLv342AgPq/Vm1FRqr/KgAg8PK2qNTuUbTPZjGzbtHnAAy4+ga8/ZtmMGpjKEJh0f5FzN06F5PdhJfGiym9pnBLp1vQtKJK7JJr+eh8mDFgBrd3vp33d77PkswlbC/ezvbi7QAkBSSRFJBEqHco4Jzy5Uj1ETLKM3AIR+12QrxCuKbDNVyXfB3RfqefGuxCJpMpSXJz5iobBzY7yyF0H9by44ysefnk3H8/wmTCd9AgombMqDO43Dnw/GsA4k7RKqX/NQsU8OoUgle7oJYIu0H+/n0J1eVlBIRH0vPS+hNtt7QcQw7Prn+WrUe3ApAamcrMQTPPq2k3pJYVHxDPSxe9xMO9H+bnzJ/5NfNX9pfvJ9uQTbYh+6TPifKNYmD0QMYkjaFfdD95gkMDyGRKktzc3vUFOGwKYfF+RLULbNF928vLyb33XhzFJXgmJxP71jxUurofrHrDNkymbDQaHyIiLqu3DfPBCsz7ykCtInBcm5YK/Ywsxmo2//QdAIOuuxmtznVfGA7FwRd7v+Cdv9/B7DDjrfXmkd6PcGPHG1GrZDlAqfHCfcK5q+td3NX1LsrN5aSXppNXmUeFpQKBINAzkCifKDqFdiLKN8rV4bY6MpmSJDcmhGDPn85yCF2HxrZoOQTFbCZv8gPOEghRUcR/8D4a//oDywsKnAlJRPhYtFrfOo8JRaD/xVmg07d/FLpwn+YPvIG2LPkBc1UlIbHxdBoyzGVxZOozeW7dc7XdL/2j+vP8oOeJ83efsx2l80uwVzCDYwe7OozzikymJMmN5e8vR19kQueloUPflhu0LRwOjjz+OKa//0bt70/Cvz9AF1X/16rDYeLo0V8AiI6+pt7jxm1F2AqqUXlpCBiV2OxxN5TRoGfrLz8AMPiGW1G7YCySzWHjo90f8f7O97EpNnx1vkztM5VrO1x7fk4EK0nnMZlMSZIb2/PHEQCS+0Xh4dUyf65CCI6+/AqVactR6XTEzX8Xzw4dTrpucXEaDkcVXl7xBAX1rfOYYnWgX5YNQMDwBDS+7jPuYtMP32Izm4hs254O/Qa1+P53Fe/iuQ3PkVGeAcBFsRfx7IBn5QBfSWqlZGe8VE9hYSFTpkyhbdu2eHp6Eh8fzxVXXMGKFStq1/n777+57rrriIyMxMvLi+TkZO69914OHDhwzvs1mUw899xzpKSk4OnpSVhYGNdeey179uxpipfV6hgNVjK3FwPQ5aKYFttv2X/+Q/kXXwAQM/s1fPv1O+W6NV180dETUP1jbE/Vn/koBiuaYE/8BrVc/GdSWVrC9mXO1rTBN9zWoq1ARpuR2Ztnc+tvt5JRnkGwZzCvDnmVBSMXyERKkloxmUxJdWRnZ5OamsrKlSuZPXs2u3bt4vfff2f48OE88MADACxZsoQBAwZgsVj44osv2Lt3L5999hmBgYE888wz57Rfi8XCqFGj+Oijj3jxxRc5cOAAv/76Kw6Hg/79+7Nx48amfJmtwr4NBSgOQUSiP+EJLTMZcMXiHyh6Yw4AEU/8i4CxY0+5rtl8hLJyZ0Xuf1Y8V4w2Ktc6yzkEjklC5aIioyez8fuvcdhsxHbsQlKP3i223/VH1jPhpwl8lv4ZilC4rO1l/Dj+Ry5re5ns1pOkVk5280l1TJ48GZVKxaZNm/D1PT6YuEuXLtx1110YjUYmTpzIuHHjWLx4ce3jbdq0oX///lRUVJzTfufNm8eGDRv4+++/6dGjBwCJiYl899139O/fn7vvvpvdu3dfMF86QhHs+dPZxddlaMsU6TSkpVEwYwYAIXfeSeidd552/cLCHwBBUFB/vL3rzslVuTYPYXagi/LFu3t48wR8DgzFRexetRyAi25smVapwupC5myZUzshbJRvFM8OeJYhcUOafd+SJLUMmUy1ACEERkVxyb591OoGf2GUlZXx+++/M2vWrDqJVI2goCAWL15MSUkJ06dPP+k2goKCam/7+Z1+gs0hQ4bw22/Oqtlffvklo0ePrk2kaqjVah599FFuueUWduzYQc+ePRv0Wlq7vP3lGIpNeHhp6NCn+QeeV69fz5HHpoKiEDhhAhH/Ovn7e6LCoz8BEB01oc5yR6WVqnXORDBgTKLbFOgE2PTj/1AcdhK6dieuU9dm3ZfNYeOzvZ/x3o73MNlNqFVqbky5kYd6P4Svrv7flyRJrZdMplqAUVFot3aXS/Z9aGg3fDUNO1Pp4MGDCCHoeMJ8a/+UkeEcMHu6dWps3779tI97e3vX3j5w4ADDT5ie5ESdOnWqXedCSab2/OEsh5DcPwpdM89hZ9q+ndwHpyBsNvxHjyZ65gtnTMCrqvZTXZ2BSuVBePgldR4zrMxB2BQ8Evzx6hjSnKGflcqyEnavWgbAgAk3Ntt+hBCsyl3FvG3zyNJnAdAzvCdP9X9KTsMhSecpmUxJtYQQAKf9Iq1ZpyHat2+aGe0bEtf5pFpvIWt7CUCzz8Nn3n+AnPsnIYxGfAcNJGbOG6i0Z/5YOFrkHMAdGjoUne74FCz2MjPVmwoBCBiT5Fbv2ZafvsdhtxPbsTNxnZt+glYhBFuObmHetnnsLN4JOKfieCz1Ma5od4UsvilJ5zGZTLUAH7WaQ0NdM7u2j7rhH+AdOnRApVKxd+9exo8ff9J1kpOTAdi3bx8DBw487fbOppsvOTmZ9PT0k663b9++2vguBPs2FKAogsg2AYTFnf4YNoY1J4ece+5G0evx7tGDuHfeQe3hccbnCSE4enQJAJGRl9d5zLAiBxwCzw5BbjVtTHVFOTuXO8csDZhwY5MmeXbFzoqcFXy651N2ljiTKG+tN7d2upWJXSfi79EyJw9IkuQ6MplqASqVqsFdba4UEhLCmDFjmD9/Pg899FC9cVMVFRVccsklhIWFMXv27DoD0E9cp2bc1Nl08914443MmDGDHTt21Bk3pSgKc+fOpXPnzvXGU52PhBDsXeecELjLkOYrJ2DLzydn4l3OaWI6dCD+/fdQn2Sc3MlUVu7GZDqMWu1NeNjI2uX2MjPGv51zCAaMdp8CnQBblizGbrMS1T6ZxO69mmSbhyoO8fOhn/kl6xcKq52tcTq1jgkdJnB/9/sJ93GfgfeSJDUvmUxJdSxYsIBBgwbRr18/Zs6cSffu3bHb7aSlpbFw4UL27t3Lhx9+yHXXXceVV17JQw89RPv27SkpKeGbb74hJyeHr792Tnp7Nt18jz76KD/++CNXXHEFc+bMoX///hw9epSXX36ZvXv3snz5crfqMmouBYf06ItNaD01tOsd0Sz7sBUUcPjOidjy89ElJhD/nw/RnHDiwJkcLXK2SoWFjUCjOT49TOWaXFDAs0MQngkBp3p6izMa9OxY9ivQuFapMnMZu4p3sf7IetYfWV9nkthAz0BuTLmRGzveSJh3WFOELUlSKyKTKamONm3asG3bNmbNmsXUqVMpKCggPDyc1NRUFi5cCMBVV13F+vXreeWVV7j55psxGAzEx8czYsQIXnrppXPar5eXFytXruSVV17hqaee4vDhw/j7+zN8+HA2btxI167Ne+aVu9i73tkq1T41olkqntuOHuXwHXdiy81FFx9P4iefoItoeNImhFI7fUxk5PFJjR16C9VbjrVKDU9o2qAb6e/ffsJmMROR1I62vfuecj1FKFRaKyk1lZJflU9+VT5Hqo6QZchib+lejhqP1llfq9JyUexFXN7ucobFD8NT49ncL0WSJDelEmczoliqZTAYCAwMRK/XExBQ91e42WwmKyuLNm3a4OXl5aIIpZNx5/fGarbz33+tw25xcPW03sS0D2rS7duKisi57Xashw+ji40l8bNP0cWcXVdiRcUWtm67AY3GjyEXbUJzLIGoWJJJ1Z/5eCQFEH5/d2yKjWpbNUa7EZvDhkM4cAgHilCctxXn7ZqLQBy/LQQO4ai3TEGp85wTnyeEqN12zboOxYHJWInhnaVgtmO7IgVTWz8sDgsWuwWzw4zBakBv0aO36DFYDSji1CVMVKhIDEikX1Q/BsUMom90XwI83KcFTpKkhjnd9/e5ki1TkuQmDm0rxm5xEBjhTXS7wCbdtr24mJw7J2I9fBhtTDQJn3xy1okUQFGxcxC3b9Bg/jiygYzyDEpKj3Lj+sHo0PK8eh4bPtuOXdibNP5z1TnLn37mEPS+Nhbbl0HGmZ/jp/Mjxi+GWL9YYv1iifOPo1NIJ1JCUmR9KEmSTkomU5LkJvaudxa67DgwumnPNisu5vDEiVgzM9FGR5P4ySd4xDW85IIQgv3l+/nryEaCj36Nrwrm7l/FLtMfANxRdCU6RcsBr8P84bEFTmjr9tJ4oVPrUKvVaFQaNCoNapX6+LVagwoVapUatcpZYFajqr9Mjbr2foOXKSrC/zgE2PAf1Jl7u1+Gl9YLT40nXhovPLWe+Hv4E+QZRKBHIEFeQQR4BOChOfMZjZIkSSeSyZQkuYGKIiMFB/WoVNBxQFSTbddWUHC8RSoyksSP/4tHfPwZnyeEYEfxDtIOp7EiZwX5VfnE6hQejzJjVeCg1ZPk4HZ08kvhmoOjAQge0Ybvu32Pv4c/vjpfvLXeaNWu+4jZ++dqfq18A5/AIO69/TW0DSj7IEmSdC5kMiVJbmDfBufA8/jOIfgFN81YLmteHjl33IktPx9tTDSJH3+MR8LpB4frLXp+OvQT/zvwPzL1mbXLvbXeXB4ZBBzCP6g/60Z8gk6to/LPfPS2TLTh3vS8KNVtpo4RQrD55+8B6DXmcplISZLUrGQy1Yzk2H73447viaII9m1w1inqODC6SbZpycwiZ+JE7EePoktIIPHj/552jFRuZS7/3f1ffjz4I1bFCjgTqOHxwxmdOJrBsYPZufUaqqqhXey16NQ6hCKoWuec9sbvoli3SaQAcnbtoDg7E62nJz0uGefqcCRJOs/JZKoZ6HQ6AIxGY53ClJLrGY1G4Ph75A7y9pZRXWHB01dL2x6NL/Ro3n+AnLvuwlFaike7diR89BG6yJOXP8isyOTfu/7Nb1m/4RAOAFKCU7gu+Toua3sZfh7OCuxG42GqqvejUmkICxsBgGlPKY5yC2ofLT69mqcm1rna/PN3AHQbfgne/vKMO0mSmpdMppqBRqMhKCiIoqIiAHx8fC6IgpPuTAiB0WikqKiIoKAgNG5UkX7vsS6+5L5RaHSNm7/NtHsPuXffjUOvx7NjRxL+8yHa0NB66xUbi5m/fT6LDy6uLQcwOHYw93S9h9TI1Hr/X4tL0gAICuqPThcEQNWfzlYp3wHRqD3c53gWZWdyeOffqFRqUi+7ytXhSJJ0AZDJVDOJinIOIq5JqCT3EBQUVPveuANztY3M7cUAdBrUuC6+6vXryXtwCorRiFe3biT8+4N6lc2NNiP/3fNfPtnzCSa7CYAR8SO4r8d9dAntcsptFxcvAyA83DnY3JJjwHrYABoVfgOab9qbc7H1lx8ASB4wmMAI93mvz1dmh0Kh1UaRxUaF3YFVEdiEwKo0f5e6SgU1ab+q5qJS1VlWs57zvuqE9f7xvGNr/3ObnLBN1T+2qaLuvk7cZu3+jm1PDWhUKtQqFVpVzW3QqlRocN7WqFTO+ypQc+J6J9zmwpn0vTWRyVQzUalUREdHExERgc1mc3U4Es6uPXdqkQLI2HwUxS4IjfMjLP7cJzU2/PYb+dP/BTYbPv37Ezf/XTQnTDQthGB5znJe/etVikzOBL9HeA+m9plKr4jTz1VnsZag128DIDzMmUzVtEr59AhHE+A+g7uN+gr2r18LQOrl410bzHnK5FBYU1bJslI92wxGMoxmHO43FPG8plGBBmfSpVGp0KlU6NTOa0+1Gp1ahcexZR4qFR5qFTqV2nldZ1ndx2qWeWvUeKvVeKmdt73UzovztgofTd37OpXqgk/wZDLVzDQajdt9gUvuY/9fxwaeD4g69znjPv+Co7NmgRD4jxlDzOuzUZ9w9lp+VT6zNs7ij3xnXag4vzgeTX2U0YmjG7TP0tLVgMDfvyteXtE49BZMu0sA58Bzd7Jz+e847Hai26cQ3T7F1eGcV46YrXyYV8LnBSUY7HUrxXurVUR46AjWafFUH/9yb86v1xPzNyGc9wXCeS2Or1O7XNR9bt31xEmWHV/OabYnTrE9/rHMgcAhQBHOa7sQKJxwu87y03MI5/bqBOdCGhXO5EqtxkujwvvY7ZqkzFtTc1tVd1m9a+fjPnWec/xa50YnufyTTKYkyUUqjho5mmVApYIOfSPP+vlCCIrffpvShe8BEHzzTUTOmIHqWPLuUBx8mv4pC7YvwOwwo1VruavrXdzb7V68tA0vv1BashqAsFDnwPPqLUdBAY+kADxizr01rak57Ha2pzknNO419goXR3P+MDoUFuQU8W7OUczHuu5iPXWMCw/komB/uvl5E+2pu+BbJpqSOJZQ2cXxBKz2NsdvO05IwGxCYFEUbCd0s9ZcWxUFqxDYFFF7fbLHnNsQmBUFk0M5dn3s/rFlJkXBrAhMDqU2jXMIqHYoVDsUaMaOGK2KYwnbPxMxFV5q53hT9QldqzVdryqcKadVcR47o6Gy6WNr8i1KktQgBzY5W6XiO4XgG3h2k+QKu53CF2ZS8e23AIQ9NIWw//u/2i+0w4bDzPhzBjuKdwDQJ7IPzwx8hraBbc9qP4pio7TM2aIVGjYMoQiqNzvj9u3nXuORMv5aR3V5Gb5BwSQPGOzqcM4LuyqNTNpzmEMmCwD9A315ICGCUaEBqGXy1GxUKhUanF147koIZ2LmTLqOJ2DHky6B2VE3CatZbvrHcqPjxHXqJm9Gh1LbUmcXUOlQqHScqe3u9JTq6sYfgH+QyZQkuYAQgv2bjgKQ3P/skhJHVRX5jz5G9R9/gFpN1HPPEXzD9QAoQmHR/kXM3ToXk92En86P6X2nM779+HNqOdDrt+FwVKHThRDg3w1LRgWOCgsqLy0+3cLOenvNadvvPwPQY/Q4NFr3KX3RWn12pIQZB/KxCkGUh46ZHWK5IjxQtkBJgDPh8zw2Rqs5iWOtbqdNxBQFiyKOdfce6yYVdbtlVRzvfrZWVXJTE8cpkylJcoHCTAOGYhNaTw1teza8tpTtyBFyJ/0flgMHUHl5EfvG6/iPGuXcZnUhz6x7ho0FGwHoH92fFwe9SLTfuZ8lWFK6CoDQ0ItRqdRUb3KWcfDpFY5K5z5jAQsPHqDgwD7UGi3dR13q6nBaNSEEr2QW8HaO80SFS8MCeLNjAiE6+XUhtTyVqmbAvJqmmv7d4N30n13yr0OSXODAsYHn7XqFo/Ns2B+2adducif/H47iEjThYcQvWIh3t64ArMhZwTPrnqHSWomXxotHUh/hpo43oVY17lejc/A5hIUOw1FpxZReBoBvv6ap1N5U/j7WKpUyaAi+QcEujqb1UoTg8f25fFHgfJ8fT4risaRI2RolSWcgkylJamEOu0LGVmcXX0oDxx0Z0tI48vh0hNmMZ3Iy8e8tRBcTg9VhZc6WOXy570sAuoZ25ZUhr5AUmNToOE2mfKqrM1CpNISEDMG4/igoAl28Px7Rvo3eflOprihn/wbnuK7el8qB5+dKCMGMjHy+KChDDbzRMZ6bo+sXfJUkqT6ZTElSCzu8uxRLtR3fQA9iO56+FUUIQemHH1L85lwQAt8hQ4id+yYaPz8OGw7z+JrH2Vu2F4A7Ot/Bw70fRqdpmvFCNa1SgQG90WoDqN6cAYBfX/caeL5rxVJnOYQOKUS1T3Z1OK3WrMwC/ptfggp4q1MC10WFuDokSWo1ZDIlSS2spouvQ78o1Kepm6IYjRyZMYPK334HIOimG4maMQOVVssvmb8wc8NMjHYjQZ5BzLpoFkPjhjZpnDXJVGjoMCyZeuwlJlQeGrybYP7ApqIoDnauXApAzzGXuzia1uurglLePTZGanZKnEykJOksyWRKklqQudpG1i5nwcuU/qeuLWXNyyPvgQex7N8PWi1RT88g6IYbsCk2XtvwIt8c+AaA1MhUXhvyGpG+Z1+n6nQcDgtl5esBZ0kE4xJnAujTMxx1A8d4tYTDO/6msqQYL18/kvvLcgjnYpu+mn/tzwNgalIkt8W411maktQayGRKklrQoW1FzuljYn0Ji/M/6TrV69eT/+hjOPR6NGFhxL01D5/UVAqrC5m6eio7S3aiQsX9Pe7n/u73o1U3/Z9xhX4zimLG0zMKH1VbCnZvAsDXzbr4dq5wtkp1HjoCrYf7TGvTWhRabEzcnYVVCMaGBTI1yb3eX0lqLWQyJUktqGb6mJPVlhKKQtl//0vRnDdBUfDq3p24t99CFxXF5sLNTFszjTJzGQEeAbw65FWGxA1ptjjLyv4EICTkIozbi8Eu0EX7ootzn4rn1RXlZG5zJnndRo5xcTStj0VRuHt3FketdlJ8vXinU4IsxClJ50gmU5LUQgwlJgoO6kEFyf+YPsZeXk7BE09StWYNAIETJhD13LOoPDz4dM+nvLn1TRzCQUpwCnOHzyXeP75ZYy0rWwdAcPAgqn8/XvHcnU6R3716OYrDQXRyR8LiE10dTqsihGD6/ly2Goz4q1XMCvGgICsTm82G3W6vvRZCII5NLldz+8Rlp3Ky/yen+r/T2HVbahsqlQq1Wo3q2KS+Nbcbuuxkj9fM3arRaNBqtXXuS63LBZFMXX311axevZqRI0fyv//9r85jS5YsYerUqSiKwr/+9S/uueceF0Upne8OHKt4HpcSjF/w8bnxjNu2kf/YVOyFhag8PYl86imCrr8Ok93Ec2un83u2cwD65W0v59mBz+Kt9W7WOK3WEqqq0gHwM/ZAfzQXlU6NT8+IZt3v2RCKwq5jA8+7j5RFOk/HYDBw5MgRiouLKSsro7S0lBVaX1bEp6ASgqHb17F8VbGrw5ROcKZES6vVotPp8PDwwMPDo/b2P69PvO3l5YW3tzdeXl54enqibubK5ReaCyKZeuihh7jrrrv45JNP6iy32+089thjrFq1ioCAAHr37s2ECRMICZFnskhNSwhR28WXcqyLTygKpR/+h+K33gKHA4+kJGLfmodXSgq5hlweWvUQBysOolVpebzv49zU8aYWaRkqK98AgJ9fJ2zbrAB4dwtD7e0+Hxc5e3aiP1qIh7cPKQMucnU4bkMIQWlpKQcPHiQ7O5v8/HwqK+tO6pofFMbK7j0BGJC5hw6mSnxCQmq/eGsuGo2m9gu3pmXlxMvpYmjIsqZYt6W28c9WOUVR6lyfadnJHlcUBUVRsNvtOByOevu22+3Y7faTxtsUPD096yRYNRcfHx98fX3x9fXFz8+v9ravr69sMTsN9/l0bEbDhw9n9erV9ZZv2rSJLl26EBsbC8C4ceNYunQpN93U1LP2SBe64pxKKo4a0erUtO0Vjq2ggIIZM6he70xcAq64gqjnnkPj58umgk08tuYx9BY9Yd5hzLl4Dr0je7dYrLVdfAEDMe1wtli426TGu44NPO900TB0Xl5nWPv8pigKubm57N69mwMHDqDX6+s8rlKpCA8PJzIyEkdIOF+qAhACrgzxY/5FN6DTyXkMXa0muXI4HLXJ1T9vn3i/pivWarVitVprb//zuua2xWLBYrFgMplqE7SaZf/8/3I6Xl5etQlWQEAAgYGBda4DAgLw8fFxq+EALcXlydTatWt5/fXX2bp1KwUFBSxevJjx48fXWWfBggW8/vrrFBQU0KVLF+bNm8eQIY0ffHvkyJHaRAogLi6O/Pz8Rm9Xkv4pY7Oziy+peximZb9S+OJLKJWVqLy8iJzxFEHXXotKpeKb/d/wyl+vYBd2uoZ25a0RbxHh03Lda0KI2sHnPqVdEDYFbYQ3HokBLRbDmRgNejI2OZPQC3kevrKyMrZu3cquXbswGAy1yzUaDQkJCbRr1474+Hiio6Px8PCgyu7g8m0ZGKrNdPf35q2ubdFpZFePOzixW8+jmc9KtdvtmM1mzGYzJpOp9nbNfaPRSHV1db2LEKJ2vZKSklNuX6vVEhAQQFBQECEhIXUuwcHB523y7vJkqrq6mh49ejBx4kSuueaaeo8vWrSIRx55hAULFjB48GDef/99xo4dS3p6OgkJCQCkpqZisVjqPXfZsmXExMScct8na9o9VUZdk8XXOPHDS5JORyiCg1udBRFDdvzMkeWfAuDVozsxr76KZ5s2zvpRf73Gov2LABjXZhwvDHoBL23LtroYjVlYLAWoVB5o/o7CgQ3fvu418Dx9zQoUh53Ith2ISGrr6nBalKIoHDp0iE2bNpGRkVG73NPTk44dO9KlSxeSkpLqfSErQvDA3sPsqzYT6aHlk25t8JaJ1AVJq9Xi5+eHn1/Dz8xVFAWTyVSbWFVWVmIwGDAYDOj1+trb1dXV2O12ysrKKCsrIzMzs962AgICCA4OJjQ0lPDwcMLDw4mIiMDf39+tPmfOlsuTqbFjxzJ27NhTPv7mm29y99131w4MnzdvHkuXLmXhwoW88sorAGzduvWc9h0bG1unJSovL4/+/fufdN1XXnmFF1544Zz2I13YjhysoKrcgtZhwmfNl6DVEv7gA4Tecw8qrRa9Rc/U1VP5q/AvAB7u/TB3d73bJR8sZeXOLr4A75448mygUeHTu2kLgjaGEIKdK5cB0P0CKoegKArp6emsXbuWoqKi2uXt27end+/edOjQ4bS/+F/NLGBpiQFPtYr/dmtDtKesySU1nFqtrh03dTo2m43Kykr0ej0VFRW1SVXNxWKx1CZehw8frvNcLy+v2sSq5jo6Ohpv7+Y94aapuDyZOh2r1crWrVt54okn6iy/5JJLWL9+faO3369fP3bv3k1+fj4BAQH8+uuvPPvssydd98knn+Sxxx6rvW8wGIiPb97T06XWz5qXz99zloCqA+FF2/Fql0jMa6/h3aULAJkVmUxZOYWcyhy8td68OuRVRiSMcFm8NV18vmXO+Ly7hKLxdZ9m+fx9eyg/kofO04uOg5t2+hx3JIRgz549rFmzhuJi5/g1T09PevXqRd++fQkNPfNExJ8dKeHtY1PFvJkST+8A95mkWjq/6HS62i69fxJCYDKZahOrkpISiouLKSoqoqysDLPZTG5uLrm5uXWeFxwcTHR0NNHR0cTExBAdHY2Pj09LvaQGc+tkqqSkBIfDQWRk3V/GkZGRFBYWNng7Y8aMYdu2bVRXVxMXF8fixYvp27cvWq2WOXPmMHz4cBRFYfr06af8cPL09MTT07NRr0e6cAibjbLPPufou/M50utZ0EGHgbG0eex71Me6YP7I+4Ppa6dTZasixjeGt0e8TUpIistiVhQ75eUbAdDtSQLct+J5x8FD8fB2vw/UppSXl8fvv/9OXp5zqhdPT08GDBjAgAEDGvxrfUlRRe1UMY8mRnKNnHNPchGVSoWPjw8+Pj7ExcXVecxut1NSUkJRUVFtgnX06FEqKiooLy+nvLyc9PT02vUDAwOJjY0lPj6e+Ph4oqKi0Gpdm864dTJV45/dHUKIs+oCWbp06Skfu/LKK7nyyivPOTZJOpEQgqo1ayia/TrWzEzKQjpj0/nh5aOmy+O3o9aoEULwabqzEKciFHpH9Gbu8LmEeLn2i66ycicORxVaVQCepfFoQrzwbBfk0phOZK6qImOjsxvyfK54bjAYWL58OTt37gScv/YHDRp0VkkUwJ/llUxOP4wC3BYTyvQ27pUYS1INrVZLVFQUUVF1/48ajUYKCgrqXMrKytDr9ej1+toES6vVEhMTU5tcxcfHn7FLsslfQ4vu7SyFhYWh0WjqtUIVFRXVa62SJFezZGRw9NXXqF7n/MLXBAdjGHMPFECHvtGoNWpsio1ZG2fxXcZ3AEzoMIGn+z+NTuP6rrTSYyURfAxdUKHGt28kKrX7DAhN/2MVdpuV8IQkotoluzqcJqcoClu3bmX58uW1J7v06NGDkSNHEhBwdmdT/lleyW07nXPuXRYeyKvJca16cK90YfLx8aFdu3a0a9eudpnJZKKwsJC8vLzabkGTyUROTg45OTm164WHh5OUlESbNm1ISkpq9q5Bt06mPDw8SE1NJS0tjauvvrp2eVpaGldddZULI5Ok46y5uZQsWIj+xx9BUUCnI+T22wi6+z5Wz9wOOOjQN5JKayWPrX6MjQUbUavUTOszjVs73eo2X3Llx4p1eud2ADX4prpPS4YQorbiebeRY9zmmDWVkpISfvrpp9ovg9jYWMaNG1endEtDrS4zcOeuLMyKYHiIP/M7JaI5z46XdOHy9vamTZs2tGnTBjheqLYmscrJyakdj1VcXMzmzZsBiIqKqn1eUFBQk8fl8mSqqqqKgwcP1t7Pyspi+/bthISEkJCQwGOPPcZtt91Gnz59GDhwIB988AE5OTlMmjTJhVFLknNwecl7C9Ev/gGOVTD2Hz2KiMcfxyMhgUPbirCZHfiFeOKIqOK2Xx/kkP4Q3lpvXh/6OhfHX+zaF3ACh8OCwfA3AD5lnfDqGIomwH3O+CrI2E9JTjZanQedhgx3dThNRlEU1q1bx+rVq3E4HOh0OkaOHEm/fv3OabqPtBI9d+/OxioEo0MD+HeXJLxkCQTpPKZSqQgLCyMsLIxevXoBzu7B7OxssrKyyM7Opri4mMLCQgoLC9mwYcNJSyk1lsuTqS1btjB8+PEPx5oz5u644w4+/vhjbrjhBkpLS5k5cyYFBQV07dqVX3/9lcREObGp5BqmPXso+/gTDL/9BseqCfsOGUL4lAfx7t69dr2MLc5CnUGd1dzy2y2UmcuI8I7g3ZHv0im0k0tiPxWDYQeKYkVjDURnjHK/iufHWqWSB16El2/D6+O4s/LychYvXlzbGtW+fXsuv/zyc/7V/FVBKY/vz8UuYFxYIO91ScRDzr8mXYB8fHzo3LkznTt3BqCysrI2ucrKyjqrE9gayuXJ1LBhw844A/nkyZOZPHlyC0UkSfUJu52q1asp++RTjMeajQF8Bw0ibMqD+Bz7RVTDarKTvasUgPlVr1DmXUZKcArvjnyXKF/3SlQAyiucNa58SjuiDfTEKznYxREdZzEa2bd+LXB+DDwXQrBz505++eUXrFYrHh4ejB07lp49e55T96UQgtlZhcw97EzeJ0QG81bHBHRuNN5NklzJ39+fbt260a1bNwAOHz7Mq6++2qT7cHkyJUnuzJKZif7776n48UccxcemUNBqCRg3lpA77qitF/VPmTuKcdgUyr2OUuCVxZDYIbx+8ev46tyzxk/FsZIIPuUp+PSJcquB5/vWrcFusRASG09sSmdXh9MoJpOJJUuWsGfPHgDi4+OZMGECwcHnlrxaFYXH9uXyv6PlADySGMn0NlGo5RgpSTqlc/17Ox2ZTEnSP1jz8qhMW07l0qWYtm+vXa4JCSHomgkE33orutOcTWpTbPyatg5PQjgYto2bOt3E9L7T0ard88/N4bCg1zvHS3mXd8S3j3udKbtzxe+As+J5ax54npOTw//+9z8MBgNqtZphw4YxePBgNBrNOW2vwmbnrt3ZrK+oQqOC2cnx3BJz5iKekiQ1Pff8dJekFiQcDszp6VT/+SeGtDQs6XuPP6hW4zd0KIHXTMD/4otRnWES0kprJdOXPkmnI86zTUeMSOX2/jc2Z/iNZjDsQBEWNJYA/GM7ow1u2fkAT+do5kGKsg6h0Wpb7cBzRVFYv349K1asQAhBSEgI11xzzTmdqVcjx2Thlp2ZZBgt+GnUfNg1iWEh7jMZtSRdaGQyJV1whN2OJSMD0/btVG/YSPVff6Ho9cdXUKvx6dsX/9Gj8R89Gl1kRIO2e6TqCA+seADd/gg0QoNXJNw+yL0TKYDyMmdJBJ+yjvj3i3ZxNHXVDDxv328QPgGBLo7m7BmNRhYvXlw7KXG3bt24/PLLGzWbwt8GI7ftzKTEZifaU8fn3dvSxa91zF8mSecrmUxJ5zXFbMaalYXl4CHM6emYdu7EvGcPwmyus57azw+f/v3xHz4MvxEj0J5kbqnT2VW8iykrp1BqLuWaMmdF/V6D253hWe6h9IizWKevsQtendxnuhGb2czeP1cD0H3kpa4N5hzk5uby7bffYjAY0Gg0jB07ltTU1EZ1VS4t0TNpTzYmRdDFz4vPu7eVkxZLkhuQyZTU6jkMBmz5+diOHMGWfwTbkSNYs7OxHDqELS8PTnK2qNrPD+/u3fDp2xffgQPx6toV1TnO7bT88HKe/ONJzA4zXb17Ea53lu3o4GZjj07G4bBQadkFagiNvwiVG9Uk2rdhLVaTiaCoaOK7dHN1OA0mhGDDhg0sX74cRVEICQnh+uuvrzdVxtn6MK+YZzLyEcDwEH8+6JKEv/bcxltJktS0ZDIluYQQAmG1IsxmFLMFYTY5ry1mFLMZYbE4r80WFLMJpaoaR1kZ9rJSHGXltdeO0lIUo/G0+9IEBuLRoT2eHTrg3b0H3j2645GUhKqRNXiEEHyy5xPe3PomAsGQ2CHc6XiMzSKH6PaB+Ie4z9ijUynP34xQW9FYAgjt28/V4dSx69ikxt1GtJ6B5yaTiR9++IH9+/cD0KVLF6644gq8vM79/4IiBC8cPML7ecUA3BodyivJcbL0gSS5EZlMSackHA4cFRU4ystxGCpRTEYUoxFhMqEYjShGE4rJeEJCZEaxmBGmY9dmS+218zGL87kWC8JiOWmL0bnShISgi4k5fkmIx7Ndezzbt0MTEtLkX8Z2xc6rm15l0f5FANyQcgNP9HuCxa85z4prDa1SAMX7VoEW/Gzd0IU179xVZ6MkJ5uCjP2oNRq6XDzS1eE0SEFBAYsWLaKiogKNRsOll15Knz59GvV/z+RQeHDvYX4pdo7pe6ptNFMSIlpNcilJFwqZTF2ghMOBLTcXa17+CV1k+dgKC3CUljkTKL2+SROeU9JoUHt6ovLyQuXlidrTC5WXl3OZtxdqTy/Uvr5oQkLQhoY4r0NC0ISEog0JRhsZidq75QbgGm1Gpq+dzpq8NahQMa3PNG7rfBv6YhNFhytRqVW0692wQeuuJBwKFVWbIQhCoga7Opw6dh4beN6uT398g9yngOip7Nixg59//hm73U5wcDDXXXcdMTExjdpmidXOnbsy2WIw4qFSMa9TAhMi3f9YSNKFSCZTFwCluhrTrt2Ydu3EkpGBJeMg1sxMZ+tQA6gDA9EEBKD28UHt7e289vVB5e2N2tsHtdex5MfLE5WXt/Pas+a+FypPT+c6JyyrfY6nJyqdrpmPQNMpMZUwZcUUdpfuxlPjyatDXmVU4igADh6bPiauYzA+bjSv3alU7ynA5H8AgIiO7lN2wGa1kL52JQDdR7h3xXO73c6yZcvYtGkTAB06dGDChAl4NzK5P2yycMOOQ2SbrARqNXzcrQ0Dg86PaXQk6Xwkk6nzkKOykur1GzD+9RfG7X9j2bcfFKXeeiovLzzi49DFxKKLjUEXG4suOhpNaBia4CBn609Q0DkPzD7fZOmz+L/l/0d+VT5BnkG8M+Idekb0BJzjpw5sLgJaTxdfyc4/EDE2tCIIX/8Org6nVsZf67FUVxMQHkFi915nfoKLVFZW8s0335CbmwvAxRdfzMUXX3xOExSfaG+ViRt3HOKo1U68lwdfdG9Lsq/7j7+TpAuZ/JY8T1jz8jD89hvVa9Zi3L69dgLeGtroaLx79MCrYwqeHTrg2aEDuthYVOdYfflC83fR30xZOQW9RU+cXxwLRy0kKTCp9vHS/GrKC6pRa1W07RXuukAbyF5iQl+9FYDg4P5uNQanduD58EsafZJAc8nJyeGbb76hqqoKT09PJkyYQEpKSqO3u01fzc07M6mwO+jk68XXPdoR6dl6Wm4l6UIlk6lWzF5aiuGXXzH88gumHTvqPOaRlITvRRfh0ycV75490TXytOwLWdrhNJ5Y+wRWxUq3sG68M+IdQr3rTtuRcayLL7FLKJ7e7v9nVbW5EFOws5BkcHh/F0dzXGl+Lnl7d6NSqekyfJSrwzmpbdu2sWTJEhRFITw8nBtvvJHQ0MZP4/JHWSV37M7C6FBIDfDh8+5tCda5//8lSZJkMtXqCCEwbd9O+RdfYli6FGw25wNqNT79++E/ahR+Q4fiER/v2kDPE5+lf8brm19HIBgWN4zXhr6Gj67uWW9CiNrxUh36un8Xn7A5qN58BFP/gwAEBfVxcUTH7Vq5DIA2vfvgHxLm4mjqUhSFtLQ0NmxwVozv0qULV155ZaOqmddYVqLnnt3ZWIXg4mB/PuqWhK9sNZakVkMmU62EUBQqly6l9N8fYk5Pr13u1a0bgVdcQcDYS9GGu3/3UmuhCIXXN7/O53s/B5ylD57s9yQadf0vuKNZBgwlZnSeGpK6u1cCcDLG7cWY1NkoOhMajS++vo3vnmoKdpuN9DUrAOekxu7EYrHw3XffceCAc8D+sGHDuPjii5uke3RZiZ67d2djE4LLwgNZ0DkRTzft3pQk6eRkMuXmhMOB4fffKVm4EOvBQwCoPD0JuOwygm++Ge+uXVwc4fnHbDfz1J9PkXY4DYBHUx9lYpeJp/zizNjsbJVq0yMMnYd7tyYIIahafwRTsDMpCAzsjVrtHh8Dh7ZsxFRpwC8klDY93ae1rKKigq+++oqjR4+i1WoZP348Xbt2bZJtLy81cM+xROrKiCAWdEpEK4txSlKr4x6fotJJVf+1iaMvv4zlWDVltb8/IXfcQfAtN6MNlvVmmkOFuYIpK6ewvXg7OrWOlwa/xLi24065vqIIDm5tPWfxWbP02AqqMfU41sUXmOriiI7bufx3ALoOH43aTbq4CgoK+Pzzz6mursbX15ebbrqJuLi4Jtn2ylIDd+/OwioEl4cHykRKkloxmUy5IWtePkWzZ1O5zDl+RO3vT8iddxBy221oAgJcHN35K7cyl8nLJ5NtyMbfw5+3hr9F36i+p33OkQPlGA1WPH20xHd2n0mCT6Vq3REEAnO4M5kKdJPxUhWFBeTs3gEqFd2GX+LqcADIzMzk66+/xmq1EhkZyc0330xgYGCTbPvP8kom7s7Coji79hZ2TpKJlCS1YjKZciPC4aD8888pmjsPYTaDWk3wjTcQNmWKbIlqZrtLdvPAigcoM5cR7RvNgpELaB/c/ozPq+nia9c7Ao3Wvce52MvMmNJLsXuVYlOXoFJpCQzo4eqwANi1yvnDIal7LwLCXV89fvfu3Xz//fcoikJSUhI33nhjo+bXO9GuSiN37nImUpeGBbCwc6KcZ0+SWjmZTLkJS2YWBTNmYPrbObebT9++RD79NF4pyS6O7Py3JncNj699HJPdRMeQjswfOZ8InzN/oTvsCof+dk4+2xrO4qvaeAQE2DrmA+Dv3wWNxvXz8TnsdvasXg5A95GXujga+Ouvv/jtt98A6Ny5MxMmTEDbRIVrs4wWbtqRSZVDYVCQH+91TsJDDjaXpFZPJlMuJoRA/913FL74EsJiQe3jQ8T06QTdcL1bFVI8X32z/xtm/TULRSgMjhnMnGFz8NX5Nui5OellWIx2fAI9iOkQ1LyBNpJitlP9VyEA1qTDYISgQPfo4svctonqinJ8AoNom9rPpbGsXbuWlSudU9n07duXsWPHNrqieY0ii40bdxyixGanq583n3Rrg5dGJlKSdD6QyZQLKdXVFLzwAoaffgbAd9BAol98EV1srIsjO/8pQuHtbW/zn93/AeDq9lfzzMBn0KkbXm26pouvfWoEajfvpqnaWICwONBG+FCl2g1AYJB7DD6vqXjeZdgoNC6aukgIwerVq1mzZg3QtKUPAKodDm7dmclhs5VELw++7N4Wf617DLKXJKnxZDLlIpasLPIeeBBrZiZoNIQ//DCh99ztttNnnE+sDivPrHuGX7N+BWByz8lM6j7prL44bVYHWTtLAPfv4hM2hao/nV173kMDqDY4yyK4w5l8hpIisnZsA6DbCNcMPBdCsGLFCv78808ARo8ezeDBg5ts+4oQPLQ3h51VJkJ0Ghb1bEeEnCJGks4rMplygeoNG8h7+BEUgwFtZCSxc97Ap497dLmc7wxWA4+seoTNhZvRqrQ8N+g5xrcff9bbyd5Zgt3iICDMi8gk9z7DsnrbUZQqG5ogT6wJObAbfHza4OHh+gKju1elgRAkdO1OcFRMi+9fCEFaWhrr168HYMyYMQwcOLBJ9/F6ViG/FOvxUKn4b9c2JHk3vmK6JEnuRSZTLax80TcUvvgi2O149+xJ3LvvoA1z/ZfahaCgqoDJKyZzsOIgvjpf3rz4TQbFDjqnbdV28fWJdOuxbcIhqFyTB4D/kFgKK78EINANxkspioNdq5yFUbuNcE3F81WrVtUmUmPHjqV//6adp/D7o+XMPez8v/J6Sjz9g/yadPuSJLkHmUy1ECEEJe+8Q8mChQAEXHEF0S+9iLoJ5vWSzmxf2T4mL59MsamYCO8I5o+aT8eQjue0LYvRxuE9pQAku3kXn2l3CY4yM2pfLT59o6jYtQVwj8Hn2du3UVVagpd/AO37nVtS2xjr1q1j7dq1AIwbN45+/Zp28PvOSiOP7ssB4MGECG6Idv86ZJIknRuZTLUAoSgcffkVyj93zvMWNuVBwiZPdusWjfPJ+vz1PLr6UYx2I+2D2rNw1EKifKPOeXuZ20tQ7ILgaF9CYhp25p8rCEVQuSoXAL9BsQiNHYNhJwBBbjD4fGfNwPOhI9DqWnYM0datW0lLc7aKjRw5sskTqQqbnbt3Z2NRBKNDA3iqbXSTbl+SJPcik6lmJux2CmbMQP/jTwBEPvsMITff7OKoLhyLMxYzc8NM7MJOv6h+zB0+lwCPxo1xytji7LZJ7hvh1gmxaU8JtsJqVJ4a/AZGY6jcgRBWdLpQvL2TXBpbVVkpmds2AS3fxbdnzx5+/tl5Bu3gwYMZMmRIk25fEYIpe3PINVtJ8PLgnU4JqN34/4kkSY0nk6lmJBwOjkz/F4ZffwWNhphXXyHwiitcHdYFQQjBwh0LWbjD2a16WdvLmDloJh4aj0Zt12iwkrevHHCOl3JXQhEY0pxdTH4XxaL20aEv3gpAUFAflyeBu1cvRygKsR07ExoX32L7zc3N5fvvvwcgNTWVUaNGNfk+5ucUkVZqwFOt4sOuSQTp5MesJJ3v5F95MxGKQsGMp52JlE5H3Ly5+I8c6eqwLgg2xcbMDTP54eAPANzT7R4e6vVQkyQQh7YVIRRBRKI/QRGurx5+KqadxdiLjKi8tPhf5KxbVqE/lky5eLyUUBR2H5s+piVbpcrKyvjqq69wOBykpKRw2WWXNXlSub68ilcyCwCY1SGO7v7u+39EkqSmI5OpZiCEoHDmTPQ//AAaDbFz3pCJVAuptlUzdfVU1h1Zh1qlZkb/GVyfcn2Tbb+mi8+tW6UcAsNyZ6uU/9BY1N5aZ6V9vXOqosDAXq4Mj8O7d6AvOoqnry/JAy9qkX2aTCa++OILjEYj0dHRXHPNNU1W2bxGhc3Og3sPowDXRwVzixxwLkkXDJlMNYOi12ZT8fUiUKmIefVVAi5xTTHCC02RsYgHVjzAvrJ9eGu9eX3o61wcf3GTbb+yzEzBQT0AHfq4fjLeUzHuKMJeYkLto8VvsLN2k8mUg81Whkrlgb9/Z5fGV1PxvNNFw9F5NP/ZrA6Hg2+++YbS0lICAgK46aab8PBoXHfvPwkhmH4gjyMWG229PXklOc7lXamSJLUcmUw1sdKPP6bs448BiH7pRQKvuNy1AV0gDpYf5P9W/B+F1YWEeIUwf+R8uoZ1bdp9bC0CILp9IH7BXk267aYi7Eptq5Tf0DjUns4/cYNhO+Cc3Fitdl05DqNBz8HNGwHoPrJluvhWrFhBVlYWHh4e3HzzzQQENH2R1W+PlvNTUQVaFczvnIivRk4VI0kXEplMNSHD70spem02ABGPTyPommtcHNGFYXPhZh5e+TCVtkqSApJYMGoB8f5NP6i5plCnO9eWqtpY4Kwr5e+B36DjFcX1hpouvp4uiswpfe1KFIedqHYdCE9s0+z727NnT21RzquuuoqoqHMviXEqh00WnjrgLIw6LSmKXgFynJQkXWjkRHBNxLhtG0emTwchCL75JkLuusvVIV0Qfsn8hfvT7qfSVkmviF58NvazZkmkKo4aKc6pRKVW0a63e3bxKSY7lSudrVKBoxNRexxvHdHrtzuXB/R0QWROQgjn9DFA1+HN3/VdXFzMjz/+CMCgQYPo0qVLk+/DrggeTM+hyqHQP9CXKYnum2hLktR8ZMtUE7BmZ5P3f5MRVit+w4cTOWOGHC/RzIQQ/Gf3f3hr21sAjE4czcsXvYyXtnm632oGnsd3DMbbv2nH2zQVw+pcFKMdbYQPPqnHv9QdDjNVVXsBCAhw3eDzgoz9lObloPXwpOPgoc26L5vNxjfffIPVaiUpKYmRzXQCyNs5R9lsqMZfo+adTglo5N+9JF2QZDLVSI6qanIfeBCHXo9Xt27EznkDlRwv0azsip1XN73Kov2LALit821M6zMNtap5GlqFELVdfB3ctIvPXmGmal0+AIFjk1Bpjn+pV1btQQg7Hh5heHm1/GTCNWrKISQPGIynT/NWjk9LS6O4uBg/Pz+uvfZaNM3wN7lNX82c7EIAXkmOI0FOYCxJFyyZTDVSwfPPoTp0CG14OHHz30XtI8dLNCejzci/1v6L1XmrUaFiet/p3Nr51mbdZ2l+NeWFRjRaNW16hjfrvs6VYelhsAs82wbi1bHuKfmGY118AQE9XdZiajWb2Lf+DwC6NXMX34EDB9i0yVldffz48fj5Nf3kwtV2Bw/sPYxDwPiIIK6JDG7yfUiS1HrIZKqRqletxt/Li7h33kYX4Z5jac4XJaYSpqyYwu7S3XhqPHllyCuMThzd7Put6eJL7BqKp7f7/clY86swbneeaRg4rk29hEl/7Ey+QBd28e3f8Ac2s4ng6BhiOzX92KUaVVVVteOk+vfvT/v27ZtlP88czCfLZCXWU8drsgyCJF3w3O+boRWKev45vHv2dHUY57VsfTaTlk8ivyqfIM8g3hnxDj0jejb7foUQHKwt1Ol+ybIQAv2vmSDAu0c4HnH+9dY5XqyzZwtHd9zulc6B512GjW62xEMIwc8//0x1dTURERHNMlUMwC/FFXxZUIYKeKdTIoFyuhhJuuDJT4FGCrr+elkCoZltL9rOlJVTqLBUEOcXx8JRC0kKTGqRfR/NNmAoMaP11JDUPaxF9nk2TLtLsBzSg1ZF4Jikeo+bLYVYLAWAGn//bi0eH0BpXi5HDuxFpVbT5eLmmwlgz5497N+/H7VazYQJE9DpdE2+jwKLlWn7cgF4ICGCQcFN34UoSVLrI0sjNFLEY4+6OoTzWtrhNO5Zdg8Vlgq6hnbl83Gft1giBcdrS7XpHobOw71OLFCsDvS/ZAHgPzQObUj9MxkN+h0A+PmloNU276DvU9m92tkq1aZXH/yCm2eKFaPRyG+//QbAkCFDmqWelCIEU9JzKLc76O7vzfQ2Tb8PSZJaJ9ky1UiqZvj1Kzl9lv4Zr29+HYFgWNwwXhv6Gj66lhvgryiituq5OxbqrFyTh6PCgibIE/9hJ6+tVVP5PCCgRwtGdpzDbid97UqgeQeeL1u2jOrqasLCwhgyZEiz7OO93GL+rKjCW61mQedEPJp4bj9JklovmUxJbkcRCq9vfp3P934OwA0pN/BkvyfRqFu2ZehIRgVGvRVPHy3xnd1r0lp7mZnKNc7upsDL2tQp0HkiVw8+z9y2CaO+At+gYNr06tM8+8jMZPv27YCzyrlW2/Qfa7sqjbySWQDAix1iae/jntMJSZLkGhfET6urr76a4OBgrr322jrLc3NzGTZsGJ07d6Z79+58++23LopQqmFxWJi2ZlptIvVI70eY0X9GiydScPwsvna9wtFo3etPpWJJprMUQrtAvLuefCyXotgxGHYCrht8XlPxvPPFI9E0Q5LjcDhqu/f69u1LfHzTV783OhQmpx/GJgTjwgK5Jdq9EmtJklzPvb4hmslDDz3Ep59+Wm+5Vqtl3rx5pKens3z5ch599FGqq6tdEKEEUGGu4N5l95J2OA2dWsdrQ17j7m53u+S0c4dd4dA2Zxdfezfr4jMfKMecXgpqCLqy3SmPT3X1fhTFjFbrj49P2xaOEirLSsj6eysAXYc1TwmLzZs3U1xcjLe3NyNGjGiWfbxwMJ8Mo4UoDx1vdIyXZRAkSarngkimhg8fjr9//VPGo6Oj6XmspEFERAQhISGUlZW1cHQSQG5lLrf9dht/F/2Nv4c/749+n3Ftx7kunr1lWKrteAd4EJvsPgUZhV2h4udDAPgNjEEXeepB5fo6xTpb/k89fe0qhFCI7diFkJjYJt9+dXU1q1evBmDkyJF4e3s3+T6Wluj55EgpAG93SiBElkGQJOkkXJ5MrV27liuuuIKYmBhUKhU//PBDvXUWLFhAmzZt8PLyIjU1lT/++KPJ49iyZQuKojRLN4F0ertLdnPrr7eSbcgmyjeKTy/9lL5RfV0aU00XX/vUCNRq92mJqFp/BHuxCbWvjoBRiaddV284Vl/KBZMbCyFqB553GdY85RBWrlyJ2WwmKiqK3r17N/n2j1psPLrPOXH0pPhwhobU/0EmSZIEbjAAvbq6mh49ejBx4kSuOUm9pkWLFvHII4+wYMECBg8ezPvvv8/YsWNJT08nISEBgNTUVCwWS73nLlu2jJiYM89FVlpayu23386HH354ynUsFkudfej1egAMBsMZty+d2p95f/LMumcwOUwkBycz56I5hGvCXXpc7VYH6X8dxmZ1EN3R223eY0ellaO/7kVYHASNaUeVzQi2U69fULAFo1FBpWrf4q/haOYhjmRnotV5ENWpe5Pvv6ioiPXr1wNw0UUXUVVV1aTbdwjBfTszKdFX08nXiwfCfN3m/4EkSY1T87cshGi6jQo3AojFixfXWdavXz8xadKkOss6duwonnjiibPa9qpVq8Q111xTb7nZbBZDhgwRn3766Wmf/9xzzwlAXuRFXuRFXuRFXs6DS25u7lnlEafj8pap07FarWzdupUnnniizvJLLrmk9ldpYwghuPPOOxkxYgS33Xbbadd98skneeyxx2rvV1RUkJiYSE5ODoGBgY2OpbUyGAzEx8eTm5tLQECAq8NxGXkcnORxcJLH4Th5LJzkcXByh+MghKCysrJBPVcN5dbJVElJCQ6Hg8jIumdTRUZGUlhY2ODtjBkzhm3btlFdXU1cXByLFy+mb9++rFu3jkWLFtG9e/fasVqfffYZ3brVn3bD09MTT0/PessDAwMv6D+MGgEBAfI4II9DDXkcnORxOE4eCyd5HJxcfRyauhHErZOpGv88FVkIcVanJy9duvSkyy+66CIURWlUbJIkSZIkXdhcfjbf6YSFhaHRaOq1QhUVFdVrrZIkSZIkSXIFt06mPDw8SE1NJS0trc7ytLQ0Bg0a5KKonDw9PXnuuedO2vV3IZHHwUkeByd5HJzkcThOHgsneRycztfjoBKiKc8NPHtVVVUcPHgQgF69evHmm28yfPhwQkJCSEhIYNGiRdx222289957DBw4kA8++IB///vf7Nmzh8TERFeGLkmSJEmS5PpkavXq1QwfPrze8jvuuIOPP/4YcBbtnD17NgUFBXTt2pW5c+cydOjQFo5UkiRJkiSpPpcnU5IkSZIkSa2ZW4+ZkiRJkiRJcncymZIkSZIkSWoEmUxJkiRJkiQ1gkymmsnVV19NcHAw1157bZ3lubm5DBs2jM6dO9O9e3e+/fZbF0XYMk51HACWLFlCSkoKHTp0OO0k0+ebuXPn0qVLFzp37sxDDz3UtJNttjJZWVkMHz6czp07061bN6qrq10dkssYjUYSExOZNm2aq0NxiQvts/FEF+pn4Yla/fvfZLP8SXWsXLlS/PTTT/UmVz5y5Ij4+++/hRBCHD16VMTGxoqqqioXRNgyTnUcbDab6NChg8jLyxMGg0G0b99elJaWuijKllNUVCTatm0rTCaTsNvtYtCgQWL9+vWuDstlhg4dKtauXSuEEKK0tFTYbDYXR+Q6Tz31lLjuuuvE1KlTXR2KS1xon401LtTPwn9q7e+/bJlqJsOHD8ff37/e8ujoaHr27AlAREQEISEhlJWVtXB0LedUx2HTpk106dKF2NhY/P39GTdu3Cmn/Tnf2O12zGYzNpsNm81GRESEq0NyiT179qDT6RgyZAgAISEhaLWtYoarJpeRkcG+ffsYN26cq0NxmQvts7HGhfxZeKLW/v5fkMnU2rVrueKKK4iJiUGlUtVOcnyiBQsW0KZNG7y8vEhNTeWPP/5o8ji2bNmCoijEx8c3+bYbwpXH4ciRI8TGxtbej4uLIz8/v0m23RjNfUzCw8OZNm0aCQkJxMTEMGrUKNq1a9eEr6DpNPexyMjIwM/PjyuvvJLevXvz8ssvN2H0Tacl/k6mTZvGK6+80kQRN4+W/Lxw9Wfj2WjscXHXz8Kz1ZT/P1rT+1/jgkymqqur6dGjB+++++5JH1+0aBGPPPIIM2bM4O+//2bIkCGMHTuWnJyc2nVSU1Pp2rVrvcuRI0caFENpaSm33347H3zwQZO8pnPhyuMgTjJO6Gwmr24uzX1MysvLWbJkCdnZ2eTn57N+/XrWrl3bUi/vrDT3sbDZbPzxxx/Mnz+fDRs2kJaWVm/qKHfQ3Mfhxx9/JDk5meTk5JZ6SeekpT4v3OGz8Ww09ri462fh2WqK/x/Q+t7/Wq7uZ3Q1QCxevLjOsn79+olJkybVWdaxY0fxxBNPnNW2V61aVW+skBBCmM1mMWTIEPHpp5+edbzNpaWPw7p168T48eNr7z/00EPiiy++OLugm1lzHJNvvvlGTJ48ufb+7NmzxWuvvdboWJtbcxyL9evXizFjxtTenz17tpg9e3ajY21OzXEcnnjiCREXFycSExNFaGioCAgIEC+88EJThdwsmuvzwh0/G8/GuRyX1vBZeLbO9f9Ha37/L8iWqdOxWq1s3bqVSy65pM7ySy65hPXr1zd6+0II7rzzTkaMGMFtt93W6O01l+Y+Dv369WP37t3k5+dTWVnJr7/+ypgxYxq93ebUFMckPj6e9evXYzabcTgcrF69mpSUlOYIt1k1xbHo27cvR48epby8HEVRWLt2LZ06dWqOcJtNUxyHV155hdzcXLKzs3njjTe49957efbZZ5sj3GbTFMehtXw2no2GHJfW+Fl4thpyHFr7+39hjvY8jZKSEhwOB5GRkXWWR0ZGUlhY2ODtjBkzhm3btlFdXU1cXByLFy+mb9++rFu3jkWLFtG9e/faPuXPPvuMbt26NeXLaLTmPg5arZY5c+YwfPhwFEVh+vTphIaGNvXLaFJNcUwGDBjAuHHj6NWrF2q1mpEjR3LllVc2R7jNqimOhVar5eWXX2bo0KEIIbjkkku4/PLLmyPcZtNUfyetXVMch9by2Xg2GnJcWuNn4dlqyHFo7e+/TKZO4Z991kKIs+rHPtXZGBdddBGKojQqtpbUXMcB4Morr2yViURjj8msWbOYNWtWU4flEo09FmPHjmXs2LFNHVaLa+xxqHHnnXc2UUSu0Zjj0No+G8/GmY5La/0sPFunOw6t/f2X3Xz/EBYWhkajqfdrqqioqF5WfT6Tx6E+eUyOk8fCSR4HJ3kcTk4eF6cL4TjIZOofPDw8SE1NrXdWUVpaGoMGDXJRVC1PHof65DE5Th4LJ3kcnORxODl5XJwuhONwQXbzVVVVcfDgwdr7WVlZbN++nZCQEBISEnjssce47bbb6NOnDwMHDuSDDz4gJyeHSZMmuTDqpiePQ33ymBwnj4WTPA5O8jicnDwuThf8cXDNSYSutWrVKgHUu9xxxx2168yfP18kJiYKDw8P0bt3b7FmzRrXBdxM5HGoTx6T4+SxcJLHwUkeh5OTx8XpQj8OKiEu4FlWJUmSJEmSGkmOmZIkSZIkSWoEmUxJkiRJkiQ1gkymJEmSJEmSGkEmU5IkSZIkSY0gkylJkiRJkqRGkMmUJEmSJElSI8hkSpIkSZIkqRFkMiVJkiRJktQIMpmSJEmSJElqBJlMSZLktp5//nl69uzZ4vtdvXo1KpWKioqKFt+3JEmtj0ymJElyCZVKddrLnXfeybRp01ixYkWLxzZo0CAKCgoIDAxs1Ha+++47+vfvT2BgIP7+/nTp0oWpU6c2UZSSJLkLrasDkCTpwlRQUFB7e9GiRTz77LPs37+/dpm3tzd+fn74+fm1eGweHh5ERUU1ahvLly/nxhtv5OWXX+bKK69EpVKRnp7ukuRQkqTmJVumJElyiaioqNpLYGAgKpWq3rJ/dvPdeeedjB8/npdffpnIyEiCgoJ44YUXsNvtPP7444SEhBAXF8dHH31UZ1/5+fnccMMNBAcHExoaylVXXUV2dvYpY/tnN9/HH39MUFAQS5cupVOnTvj5+XHppZfWSQj/acmSJVx00UU8/vjjpKSkkJyczPjx43nnnXfqrPfzzz+TmpqKl5cXbdu2rX09NSoqKrjvvvuIjIzEy8uLrl27smTJkoYfaEmSmp1MpiRJalVWrlzJkSNHWLt2LW+++SbPP/88l19+OcHBwfz1119MmjSJSZMmkZubC4DRaGT48OH4+fmxdu1a/vzzz9pkyGq1Nni/RqORN954g88++4y1a9eSk5PDtGnTTrl+VFQUe/bsYffu3adcZ+nSpdx666089NBDpKen8/777/Pxxx8za9YsABRFYezYsaxfv57PP/+c9PR0Xn31VTQaTYPjliSpBQhJkiQX++9//ysCAwPrLX/uuedEjx49au/fcccdIjExUTgcjtplKSkpYsiQIbX37Xa78PX1FV999ZUQQoj//Oc/IiUlRSiKUruOxWIR3t7eYunSpSeNZ9WqVQIQ5eXltfEB4uDBg7XrzJ8/X0RGRp7yNVVVVYlx48YJQCQmJoobbrhB/Oc//xFms7l2nSFDhoiXX365zvM+++wzER0dLYQQYunSpUKtVov9+/efcj+SJLmeHDMlSVKr0qVLF9Tq443qkZGRdO3atfa+RqMhNDSUoqIiALZu3crBgwfx9/evsx2z2cyhQ4cavF8fHx/atWtXez86Orp2Hyfj6+vLL7/8wqFDh1i1ahUbN25k6tSpvPXWW2zYsAEfHx+2bt3K5s2ba1uiABwOB2azGaPRyPbt24mLiyM5ObnBcUqS1PJkMiVJUqui0+nq3FepVCddpigK4OwqS01N5Ysvvqi3rfDw8EbtVwhxxue1a9eOdu3acc899zBjxgySk5NZtGgREydORFEUXnjhBSZMmFDveV5eXnh7ezc4PkmSXEcmU5Ikndd69+7NokWLiIiIICAgwKWxJCUl4ePjQ3V1dW1s+/fvp3379iddv3v37uTl5XHgwAHZOiVJbkwmU5IkndduueUWXn/9da666ipmzpxJXFwcOTk5fP/99zz++OPExcU1y36ff/55jEYj48aNIzExkYqKCt5++21sNhujR48G4Nlnn+Xyyy8nPj6e6667DrVazc6dO9m1axcvvfQSF198MUOHDuWaa67hzTffpH379uzbtw+VSsWll17aLHFLknT25Nl8kiSd13x8fFi7di0JCQlMmDCBTp06cdddd2EymZq1periiy8mMzOT22+/nY4dOzJ27FgKCwtZtmwZKSkpAIwZM4YlS5aQlpZG3759GTBgAG+++SaJiYm12/nuu+/o27cvN910E507d2b69Ok4HI5mi1uSpLOnEg3p9JckSZIkSZJOSrZMSZIkSZIkNYJMpiRJkiRJkhpBJlOSJEmSJEmNIJMpSZIkSZKkRpDJlCRJkiRJUiPIZEqSJEmSJKkRZDIlSZIkSZLUCDKZkiRJkiRJagSZTEmSJEmSJDWCTKYkSZIkSZIaQSZTkiRJkiRJjfD/a9M0HjHTPPQAAAAASUVORK5CYII=", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys2.sims[1], 1e-10, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-12, 5)\n", - "title(\"Liquid-phase Mole Fractions vs. Time on Cu111@-0.2V vs RHE\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotC(ssys2.sims[1], 1e-10, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-12, 1e5)\n", - "title(\"Liquid-phase Concentrations vs. Time on Cu111@-0.2V vs RHE\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Julia 1.9.1", - "language": "julia", - "name": "julia-1.9" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.9.1" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/CO2_Reduction_Cu/CO2RR_Cu.jl b/CO2_Reduction_Cu/CO2RR_Cu.jl new file mode 100644 index 0000000..38fe79b --- /dev/null +++ b/CO2_Reduction_Cu/CO2RR_Cu.jl @@ -0,0 +1,202 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,jl:percent +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.17.2 +# kernelspec: +# display_name: Julia 1.9.1 +# language: julia +# name: julia-1.9 +# --- + +# %% +using DifferentialEquations +using ReactionMechanismSimulator +using PyPlot + +# %% +outdict1 = readinput("Cu_012925.rms") + +# %% +liqspcs1 = outdict1["gas"]["Species"]; +liqrxns1 = outdict1["gas"]["Reactions"]; +surfspcs1 = outdict1["surface"]["Species"]; +surfrxns1 = outdict1["surface"]["Reactions"]; +interfacerxns1 = outdict1[Set(["surface", "gas"])]["Reactions"]; +solv1 = outdict1["Solvents"][1]; + +# %% +sitedensity1 = 2.943e-5; # Cu111 +sitedensity2 = 2.292e-5; # Ag111 +AVratio = 36; +Phi1 = -1.414; +Phi2 = -0.614; + +# %% +initialcondsliq = Dict(["proton"=>10.0^-4,"CO2"=>10.0^-3*10^3, + "V"=>1.0,"T"=>298.15,"Phi"=>0.0,"d"=>0.0]); +initialcondssurf1 = Dict(["CO2X"=>0.4*sitedensity1*AVratio, + "CHO2X"=>0.1*sitedensity1*AVratio, + "CO2HX"=>0.1*sitedensity1*AVratio, + "OX"=>0.1*sitedensity1*AVratio, + "OCX"=>0.1*sitedensity1*AVratio, + "vacantX"=>0.1*sitedensity1*AVratio, + "CH2O2X"=>0.05*sitedensity1*AVratio, + "CHOX"=>0.04*sitedensity1*AVratio, + "CH2OX"=>0.01*sitedensity1*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>Phi1]); + +# %% +initialcondssurf2 = Dict(["CO2X"=>0.4*sitedensity1*AVratio, + "CHO2X"=>0.1*sitedensity1*AVratio, + "CO2HX"=>0.1*sitedensity1*AVratio, + "OX"=>0.1*sitedensity1*AVratio, + "OCX"=>0.1*sitedensity1*AVratio, + "vacantX"=>0.1*sitedensity1*AVratio, + "CH2O2X"=>0.05*sitedensity1*AVratio, + "CHOX"=>0.04*sitedensity1*AVratio, + "CH2OX"=>0.01*sitedensity1*AVratio, + "A"=>1.0*AVratio,"T"=>298.15,"Phi"=>Phi2]); + +# %% +liq1 = IdealDiluteSolution(liqspcs1,liqrxns1,solv1,name="liquid",diffusionlimited=true); + +surf1 = IdealSurface(surfspcs1,surfrxns1,sitedensity1,name="surface"); + + +# %% +domainliq1,y0liq1,pliq1 = ConstantTVDomain(phase=liq1, + initialconds=initialcondsliq,constantspecies=["proton","CO2"]); + +# %% +domaincat1,y0cat1,pcat1 = ConstantTAPhiDomain(phase=surf1, + initialconds=initialcondssurf1); + +inter1,pinter1 = ReactiveInternalInterfaceConstantTPhi(domainliq1, + domaincat1,interfacerxns1,298.15,AVratio*1.0); + +# %% +domaincat2,y0cat2,pcat2 = ConstantTAPhiDomain(phase=surf1, + initialconds=initialcondssurf2); + +inter2,pinter2 = ReactiveInternalInterfaceConstantTPhi(domainliq1, + domaincat2,interfacerxns1,298.15,AVratio*1.0); + +# %% +@time react1,y01,p1 = Reactor((domainliq1,domaincat1), (y0liq1,y0cat1), (0.0, 1.0e3), [inter1], (pliq1,pcat1,pinter1)); + +@time sol1 = solve(react1.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-8); + +ssys1 = SystemSimulation(sol1,(domainliq1,domaincat1,),(inter1,),p1); + +# %% +@time react2,y02,p2 = Reactor((domainliq1,domaincat2), (y0liq1,y0cat2), (0.0, 1.0e3), [inter2], (pliq1,pcat2,pinter2)); + +@time sol2 = solve(react2.ode,DifferentialEquations.CVODE_BDF(),abstol=1e-16,reltol=1e-8); + +ssys2 = SystemSimulation(sol2,(domainliq1,domaincat2,),(inter2,),p2); + +# %% +# Helper function +function plotX(sim, tol, t_end, exclude) + clf() + xs = molefractions(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Mole Fraction") +end + +# %% +# Helper function +function plotC(sim, tol, t_end, exclude) + clf() + xs = concentrations(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time in Sec") + ylabel("Concentration") +end + +# %% +exclude_species = ["H2O"] +plotX(ssys1.sims[1], 1e-10, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e3) +ylim(1e-12, 5) +title("Liquid-phase Mole Fractions vs. Time on Cu111@-1.0V vs RHE") +gcf() + +# %% +exclude_species = ["H2O"] +plotC(ssys1.sims[1], 1e-10, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e3) +ylim(1e-12, 1e5) +title("Liquid-phase Concentrations vs. Time on Cu111@-1.0V vs RHE") +gcf() + +# %% +concentrations(ssys1.sims[1]) + +# %% +exclude_species = ["H2O"] +plotX(ssys1.sims[2], 0.1, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e3) +ylim(1e-12, 5) +title("Surface coverage on Cu111@-1.0 V vs. RHE") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys2.sims[1], 1e-10, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e3) +ylim(1e-12, 5) +title("Liquid-phase Mole Fractions vs. Time on Cu111@-0.2V vs RHE") +gcf() + +# %% +exclude_species = ["H2O"] +plotC(ssys2.sims[1], 1e-10, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e3) +ylim(1e-12, 1e5) +title("Liquid-phase Concentrations vs. Time on Cu111@-0.2V vs RHE") +gcf() + +# %% diff --git a/CO2_Reduction_Cu3Sn/CO2RR_RMS_Diffusion_Interface_Cu3Sn.ipynb b/CO2_Reduction_Cu3Sn/CO2RR_RMS_Diffusion_Interface_Cu3Sn.ipynb deleted file mode 100644 index 5d60a95..0000000 --- a/CO2_Reduction_Cu3Sn/CO2RR_RMS_Diffusion_Interface_Cu3Sn.ipynb +++ /dev/null @@ -1,2510 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 145, - "id": "8a590634", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\u001b[32m\u001b[1m Activating\u001b[22m\u001b[39m project at `~/miniforge3/envs/rmg_electrocat_2/julia_env`\n" - ] - } - ], - "source": [ - "using Pkg\n", - "Pkg.activate(ENV[\"PYTHON_JULIAPKG_PROJECT\"])\n", - "using ReactionMechanismSimulator" - ] - }, - { - "cell_type": "code", - "execution_count": 146, - "id": "82245f05", - "metadata": {}, - "outputs": [], - "source": [ - "using PythonPlot\n", - "using DifferentialEquations\n", - "using Sundials\n", - "using SciMLBase\n", - "using QuadGK" - ] - }, - { - "cell_type": "code", - "execution_count": 147, - "id": "e941d4fb", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[15:07:18] WARNING: not removing hydrogen atom without neighbors\n", - "[15:07:18] WARNING: not removing hydrogen atom without neighbors\n", - "┌ Warning: failed to generate StokesDiffusivity model for species vacantX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHO2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO2HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2O2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CHOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HOX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species H2OX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C[O][Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CO[C](=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species HX\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O[CH2][Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species [H][H].[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)CO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH3X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC[O][Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(=O)[O][Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC(=O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(O)[O][Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O[CH](O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC(O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CO[CH](O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)C[O][Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CC(=O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)O[CH2][Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COC[O][Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)[O][Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CC[O][Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CO[CH2][Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC[O][Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCOC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species CH2X\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=COCCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C[CH2][Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C=C=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species C.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC(=O)O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C[C](=O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COC[O][Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species COCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OC[CH2][Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)[CH](O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C(O)CCO.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O[CH]=[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=C[CH](O)[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species O=CCC=O.[Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n", - "┌ Warning: failed to generate StokesDiffusivity model for species OCC(O)[O][Pt]\n", - "└ @ ReactionMechanismSimulator /home/ssun30/RMG-Electrocat/ReactionMechanismSimulator.jl/src/Parse.jl:352\n" - ] - }, - { - "data": { - "text/plain": [ - "Dict{Any, Any} with 4 entries:\n", - " \"Solvents\" => Solvent[Solvent(\"water\", RiedelViscosity{Float64}(…\n", - " Set([\"surface\", \"gas\"]) => Dict{Any, Any}(\"Reactions\"=>ElementaryReaction[vac…\n", - " \"gas\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…\n", - " \"surface\" => Dict{Any, Any}(\"Species\"=>Species[Species{NASA{Emp…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "outdict = readinput(\"Cu3Sn_RMS96.rms\")" - ] - }, - { - "cell_type": "code", - "execution_count": 148, - "id": "fe2767e9", - "metadata": {}, - "outputs": [], - "source": [ - "boundarylayerspcs = outdict[\"gas\"][\"Species\"]\n", - "boundarylayerrxns = outdict[\"gas\"][\"Reactions\"]\n", - "surfspcs = outdict[\"surface\"][\"Species\"]\n", - "surfrxns = outdict[\"surface\"][\"Reactions\"]\n", - "interfacerxns = outdict[Set([\"surface\", \"gas\"])][\"Reactions\"]\n", - "solv = outdict[\"Solvents\"][1];" - ] - }, - { - "cell_type": "code", - "execution_count": 149, - "id": "c54ee65e", - "metadata": {}, - "outputs": [], - "source": [ - "sitedensity = 1.4319e-05; # Cu3Sn(0001) site density is 1.4319e-9 mol/cm^2 or 1.4319e-5 mol/m^2\n", - "boundarylayer = IdealDiluteSolution(boundarylayerspcs,boundarylayerrxns,solv,name=\"boundarylayeruid\",diffusionlimited=true);\n", - "surf = IdealSurface(surfspcs,surfrxns,sitedensity,name=\"surface\");" - ] - }, - { - "cell_type": "code", - "execution_count": 150, - "id": "8894c84d", - "metadata": {}, - "outputs": [], - "source": [ - "# Reservoir is a 100 mL (100e-6 m^3) cell\n", - "# Proton concentration is 10^-7 mol/L (10^-4 mol/m^3)\n", - "# CO2 concentration is 0.01 mol/L (10 mol/m^3), saturation solubility ~0.03 mol/L\n", - "# AVratio in experiments is 36 m^-1 but is measured by surface area/reservoir volume\n", - "# Area of the electrode is therefore 3.6e1 m^-1 * 1e2 * 1e-6 m^3 = 3.6e-3 m^2 = 36 cm^2\n", - "# Assume boundary layer thickness d_bl = 1 mm or 1e-3 m\n", - "# Volume of the boundary layer V_bl = 3.6e-3 m^2 * 1e-3 m = 3.6e-6 m^3\n", - "# Actual AVratio is therefore 3.6e-3 m^2 / 3.6e-6 m^3 = 1e3 m^-1 (reciprocal of d_bl)\n", - "# Amount of sites is 2.943e-5 mol/m^2 * 3.6e-3 m^2 = 10.595e-8 mol\n", - "\n", - "# For earlier simulations, a 100x linear scale factor is applied,\n", - "# so volume becomes 100e-6 m^3 * (1e2)^3 = 100 m^3,\n", - "# electrode area becomes 3.6e-3 * (1e2) ^2 = 3.6e1 m^2,\n", - "# AVratio becomes 3.6e1 m^2 / 1e2 m^3 = 0.36 m^-1\n", - "# Volume of the boundary layer becomes 3.6e1 m^2 * 1e-3 m = 3.6e-2 m^3\n", - "\n", - "C_proton = 1e-7*1e3;\n", - "C_co2 = 1e-2*1e3;\n", - "C_default = 1e-12;\n", - "V_res = 1e3;\n", - "layer_thickness = 1e-4; # 100 microns\n", - "AVratio = 36;\n", - "A_surf = V_res*AVratio;\n", - "V_bl = A_surf*layer_thickness;\n", - "# V_bl = V_res;\n", - "sites = sitedensity*A_surf;\n", - "\n", - "# The initial conditions for individual species are moles not concentration, so we need to multiply concentration by boundary layer volume\n", - "initialcondsboundarylayer = Dict([\"proton\"=>C_proton*V_bl,\n", - " \"CO2\"=>C_co2*V_bl,\n", - " # \"H2\"=>C_default*10*V_bl,\n", - " # \"O=CO\"=>C_default*V_bl,\n", - " \"V\"=>V_bl,\"T\"=>300,\"Phi\"=>0.0,\"d\"=>0.0]);\n", - "initialcondsreservoir = Dict([\"proton\"=>C_proton,\n", - " \"CO2\"=>C_co2,\n", - " \"V\"=>V_res,\"T\"=>300]);\n", - "\n", - "\n", - "# Assume voltage is -1.0 V vs. R.H.E. which equates to -1.414 V vs. S.H.E. at pH=7\n", - "initialcondssurf = Dict([\"CO2X\"=>0.1*sites,\n", - " # \"CHO2X\"=>0.1*sites,\n", - " # \"CO2HX\"=>0.1*sites,\n", - " # \"OX\"=>0.1*sites,\n", - " # \"OCX\"=>0.1*sites,\n", - " \"vacantX\"=>0.9*sites,\n", - " # \"CH2O2X\"=>0.05*sites,\n", - " # \"CHOX\"=>0.04*sites,\n", - " # \"CH2OX\"=>0.01*sites,\n", - " \"A\"=>A_surf,\"T\"=>300,\"Phi\"=>-1.914]);" - ] - }, - { - "cell_type": "code", - "execution_count": 151, - "id": "ddb39b3d", - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "domainboundarylayer, y0boundarylayer, pboundarylayer = ConstantTVDomain(phase=boundarylayer, initialconds=initialcondsboundarylayer);\n", - "domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf,\n", - " initialconds=initialcondssurf);" - ] - }, - { - "cell_type": "code", - "execution_count": 152, - "id": "d3aaf802", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "9.32e-9" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Set proton diffusivity to a higher value than calculated from Stokes Einstein equation\n", - "# The values are taken from DOI: 10.1039/C8SC01253A\n", - "# Values calculated from MD is 1.015 A^2/ps, experimental values are 0.932 A^2/ps.\n", - "# 1 A^2/ps = 1e-8 m^2/s\n", - "domainboundarylayer.diffusivity[6] = 0.932e-8" - ] - }, - { - "cell_type": "code", - "execution_count": 153, - "id": "ed49d2b4", - "metadata": {}, - "outputs": [], - "source": [ - "inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainboundarylayer,\n", - " domaincat,interfacerxns,298.15,A_surf);" - ] - }, - { - "cell_type": "code", - "execution_count": 154, - "id": "dee14906", - "metadata": {}, - "outputs": [], - "source": [ - "# start with 1mm layer thickness\n", - "diffusionlayer = ConstantReservoirDiffusion(domainboundarylayer, initialcondsreservoir, A_surf, layer_thickness);" - ] - }, - { - "cell_type": "code", - "execution_count": 155, - "id": "e70ac4b0", - "metadata": {}, - "outputs": [], - "source": [ - "interfaces = [inter, diffusionlayer];" - ] - }, - { - "cell_type": "code", - "execution_count": 156, - "id": "244f0912", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.004127 seconds (8.49 k allocations: 8.411 MiB)\n" - ] - } - ], - "source": [ - "@time react,y0,p = Reactor((domainboundarylayer,domaincat), (y0boundarylayer,y0cat), (0.0, 1e3), interfaces, (pboundarylayer,pcat,pinter));" - ] - }, - { - "cell_type": "code", - "execution_count": 157, - "id": "962f838c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " 0.242447 seconds (468.00 k allocations: 378.264 MiB, 5.61% gc time)\n", - "1000.0\n", - "Success\n" - ] - } - ], - "source": [ - "@time sol = solve(react.ode,Sundials.CVODE_BDF(),abstol=1e-22,reltol=1e-8);\n", - "println(sol.t[end]);\n", - "println(sol.retcode);" - ] - }, - { - "cell_type": "code", - "execution_count": 158, - "id": "6667bb5a", - "metadata": {}, - "outputs": [], - "source": [ - "ssys = SystemSimulation(sol,(domainboundarylayer,domaincat,), interfaces,p);" - ] - }, - { - "cell_type": "code", - "execution_count": 159, - "id": "d4939a87", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "get_reservoir_concentration" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "\"\"\"\n", - "diffusive flux to the reservoir\n", - "\"\"\"\n", - "function flux_to_reservoir(sim,t,reservoirinterface)\n", - " cs = concentrations(sim,t)\n", - " return reservoirinterface.A .* sim.domain.diffusivity .* (cs - reservoirinterface.c) / reservoirinterface.layer_thickness\n", - "end\n", - "\n", - "\"\"\"\n", - "Integrates the flux to the reservoir and computes the concentration assuming\n", - "there is no prior concentration of that species in the reservoir\n", - "\"\"\"\n", - "function get_reservoir_concentration(sim,t,reservoirinterface,Vres,C0)\n", - " intg,err = quadgk(x -> flux_to_reservoir(sim,x,reservoirinterface), 0, t);\n", - " intg[5] = 0;\n", - " intg[6] = 0;\n", - " return C0 + intg./Vres\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 160, - "id": "411d79d6", - "metadata": {}, - "outputs": [], - "source": [ - "# Logarithmic time scale\n", - "t_vals = 10 .^ range(-12, stop=3, length=160);\n", - "\n", - "# Compute reservoir concentrations\n", - "flux_vals = [flux_to_reservoir(ssys.sims[1], t, diffusionlayer) for t in t_vals]\n", - "\n", - "conc_vals_bl = [concentrations(ssys.sims[1], t) for t in t_vals]\n", - "flux_matrix = hcat(flux_vals...);\n", - "conc_matrix_bl = hcat(conc_vals_bl...);\n" - ] - }, - { - "cell_type": "code", - "execution_count": 161, - "id": "1b8bc2d2", - "metadata": {}, - "outputs": [], - "source": [ - "conc_0 = concentrations(ssys.sims[1], 0)\n", - "t_vals_2 = 10 .^ range(-9, stop=3, length=130);\n", - "conc_vals = [get_reservoir_concentration(ssys.sims[1], t, diffusionlayer, V_res, conc_0) for t in t_vals_2]\n", - "conc_matrix = hcat(conc_vals...);" - ] - }, - { - "cell_type": "code", - "execution_count": 162, - "id": "543fe758", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotC_Reservoir (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "function plotC_Reservoir(sim, cs, tvals, tol, exclude)\n", - " clf()\n", - " xs = cs\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " time_filtered = tvals\n", - " xs_filtered = xs\n", - "\n", - " # Custom species order and their corresponding names and color\n", - " species_order = [\"CO2\", \"proton\", \"H2\", \"O=CO\", \"C=O\", \"CO-2\", \"CCO\", \"CH4\", \"OCO\", \"COC\", \"COCO\", \"CC(=O)O\", \"COC=O\"]\n", - " color_map = Dict(\"CO2\" => \"black\", \"proton\" => \"grey\", \"H2\" => \"green\",\n", - " \"O=CO\" => \"red\", \"C=O\" => \"brown\", \"CO-2\" => \"blue\", \"CCO\" => \"magenta\",\n", - " \"CH4\" => \"brown\", \"OCO\" => \"orange\", \"COC\" => \"teal\", \"COCO\" => \"lime\", \"CC(=O)O\" => \"teal\", \"COC=O\" => \"lime\")\n", - " # Replacement map for species labels\n", - " replacement_map = Dict(\"CO-2\" => \"CH3OH\", \"O=CO\" => \"HCOOH\", \"C=O\" => \"HCHO\",\n", - " \"CCO\" => \"C2H5OH\", \"OCO\" => \"CH2(OH)2\", \"COC\" => \"CH3OCH3\", \"COCO\" => \"CH3OCH2OH\", \"CC(=O)O\" => \"CH3COOH\", \"COC=O\" => \"CH3OCHO\")\n", - "\n", - " # Build a map of species names to indices\n", - " name_to_index = Dict(sim.domain.phase.species[i].name => i for i in 1:length(sim.domain.phase.species))\n", - " # Keep track of whether the species is plotted, used for later checks\n", - " plotted = falses(length(sim.domain.phase.species))\n", - "\n", - " # Plot species from the custom species dictionary\n", - " for species_name in species_order\n", - " if species_name in exclude\n", - " continue\n", - " end\n", - "\n", - " if haskey(name_to_index, species_name)\n", - " i = name_to_index[species_name]\n", - "\n", - " if (maxes[i] > tol) || (species_name == \"proton\") || (species_name == \"CCO\") # Always plot proton and ethanol\n", - " plot_label = get(replacement_map, species_name, species_name)\n", - " plot_color = color_map[species_name]\n", - "\n", - " plot(time_filtered, xs_filtered[i, :]/1000, label=plot_label, color=plot_color)\n", - " plotted[i] = true # Mark as plotted\n", - " end\n", - " end\n", - " end\n", - "\n", - " # Plot any remaining species that passed tolerance but were not in species_order\n", - " for i in 1:length(sim.domain.phase.species)\n", - " if plotted[i] || sim.domain.phase.species[i].name in exclude\n", - " continue\n", - " end\n", - "\n", - " if maxes[i] > tol\n", - " species_name = sim.domain.phase.species[i].name\n", - " plot(time_filtered, xs_filtered[i, :]/1000, label=species_name) # Default color\n", - " end\n", - " end\n", - "\n", - " xlabel(\"Time (s)\", fontsize=14)\n", - " ylabel(\"Bulk Concentration (mol/L)\", fontsize=14)\n", - " xticks(fontsize=14)\n", - " yticks(fontsize=14)\n", - " legend(loc=\"upper left\", bbox_to_anchor=(0, 0.9), fontsize=12, ncol=2)\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d68e0335", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\", \"O=CC=O\", \"O=CCO\", \"CC=O\"]\n", - "plotC_Reservoir(ssys.sims[1], conc_matrix, t_vals_2, 1e-12, exclude_species)\n", - "\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-9, 1e3)\n", - "ylim(1e-20, 1e-1)\n", - "legend(loc=\"upper left\", bbox_to_anchor=(0, 0.9), fontsize=12, ncol=2)\n", - "title(\"Cu3Sn0001@-1.5V vs. R.H.E., d = 100 um\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 164, - "id": "53cf7fe2", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "clf()\n", - "\n", - "for i in 1:size(flux_matrix, 1)\n", - " if maximum(abs.(flux_matrix[i, :])) > 1e-10\n", - " plot(t_vals, abs.(flux_matrix[i, :]), label=ssys.sims[1].domain.phase.species[i].name)\n", - "\n", - " end\n", - "end\n", - "\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlabel(\"Time (s)\")\n", - "ylabel(\"Diffusive Flux (mol/s)\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-9, 1e1)\n", - "legend()\n", - "tight_layout()\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 165, - "id": "a88347b2", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "clf()\n", - "for i in 1:size(conc_matrix_bl, 1)\n", - " if maximum(conc_matrix_bl[i, :]) > 1e-10\n", - " plot(t_vals, conc_matrix_bl[i, :]/1e3, label=ssys.sims[1].domain.phase.species[i].name)\n", - "\n", - " end\n", - "end\n", - "\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlabel(\"Time (s)\")\n", - "ylabel(\"Boundary Layer Concentrations (mol/L)\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-18, 1)\n", - "legend()\n", - "tight_layout()\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 166, - "id": "87dcaf99", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotX (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Helper function\n", - "function plotX(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = molefractions(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " for i = 1:length(maxes)\n", - " species_name = sim.domain.phase.species[i].name\n", - " if maxes[i] > tol && !(species_name in exclude)\n", - " plot(time_filtered, xs_filtered[i,:], label=species_name)\n", - " end\n", - " end\n", - " legend()\n", - " xlabel(\"Time (s)\")\n", - " ylabel(\"Concentration (mol/m^3)\")\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 167, - "id": "ddf6da6b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotC (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "function plotC(sim, tol, t_end, exclude)\n", - " clf()\n", - " xs = concentrations(sim)\n", - " maxes = maximum(xs, dims=2)\n", - "\n", - " # Filter time data up to t_end\n", - " time_indices = findall(t -> t <= t_end, sim.sol.t)\n", - " time_filtered = sim.sol.t[time_indices]\n", - " xs_filtered = xs[:, time_indices]\n", - "\n", - " # Custom species order and their corresponding names and color\n", - " species_order = [\"CO2\", \"proton\", \"H2\", \"O=CO\", \"C=O\", \"CO-2\", \"CCO\", \"CH4\", \"OCO\", \"COC\", \"COCO\", \"CC(=O)O\", \"COC=O\"]\n", - " color_map = Dict(\"CO2\" => \"black\", \"proton\" => \"grey\", \"H2\" => \"green\",\n", - " \"O=CO\" => \"red\", \"C=O\" => \"brown\", \"CO-2\" => \"blue\", \"CCO\" => \"magenta\",\n", - " \"CH4\" => \"brown\", \"OCO\" => \"orange\", \"COC\" => \"teal\", \"COCO\" => \"lime\", \"CC(=O)O\" => \"teal\", \"COC=O\" => \"lime\")\n", - " # Replacement map for species labels\n", - " replacement_map = Dict(\"CO-2\" => \"CH3OH\", \"O=CO\" => \"HCOOH\", \"C=O\" => \"HCHO\",\n", - " \"CCO\" => \"C2H5OH\", \"OCO\" => \"CH2(OH)2\", \"COC\" => \"CH3OCH3\", \"COCO\" => \"CH3OCH2OH\", \"CC(=O)O\" => \"CH3COOH\", \"COC=O\" => \"CH3OCHO\")\n", - "\n", - " # Build a map of species names to indices\n", - " name_to_index = Dict(sim.domain.phase.species[i].name => i for i in 1:length(sim.domain.phase.species))\n", - " # Keep track of whether the species is plotted, used for later checks\n", - " plotted = falses(length(sim.domain.phase.species))\n", - "\n", - " # Plot species from the custom species dictionary\n", - " for species_name in species_order\n", - " if species_name in exclude\n", - " continue\n", - " end\n", - "\n", - " if haskey(name_to_index, species_name)\n", - " i = name_to_index[species_name]\n", - "\n", - " if (maxes[i] > tol) || (species_name == \"proton\") || (species_name == \"CCO\") # Always plot proton and ethanol\n", - " plot_label = get(replacement_map, species_name, species_name)\n", - " plot_color = color_map[species_name]\n", - "\n", - " plot(time_filtered, xs_filtered[i, :]/1000, label=plot_label, color=plot_color)\n", - " plotted[i] = true # Mark as plotted\n", - " end\n", - " end\n", - " end\n", - "\n", - " # Plot any remaining species that passed tolerance but were not in species_order\n", - " for i in 1:length(sim.domain.phase.species)\n", - " if plotted[i] || sim.domain.phase.species[i].name in exclude\n", - " continue\n", - " end\n", - "\n", - " if maxes[i] > tol\n", - " species_name = sim.domain.phase.species[i].name\n", - " plot(time_filtered, xs_filtered[i, :]/1000, label=species_name) # Default color\n", - " end\n", - " end\n", - "\n", - " xlabel(\"Time (s)\", fontsize=14)\n", - " ylabel(\"Boundary Layer Concentration (mol/L)\", fontsize=14)\n", - " xticks(fontsize=14)\n", - " yticks(fontsize=14)\n", - " legend(loc=\"upper left\", bbox_to_anchor=(0, 0.9), fontsize=12, ncol=2)\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 193, - "id": "1ef78267", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\", \"O=CC=O\", \"O=CCO\", \"CC=O\"]\n", - "plotC(ssys.sims[1], 1e-12, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-20, 1e-1)\n", - "title(\"Cu3Sn0001@-1.5V vs. R.H.E., d = 10 um\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 169, - "id": "a1e338ce", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "exclude_species = [\"H2O\"]\n", - "plotX(ssys.sims[2], 1e-4, 1e3, exclude_species)\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlim(1e-12, 1e3)\n", - "ylim(1e-6, 5)\n", - "title(\"Surface Mole Fractions vs. Time on Cu3Sn0001@-1.5V\")\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 170, - "id": "56943c13", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "FluxDiagram{Float64}([1.0e-10, 1.0e-9, 1.0e-8, 1.0e-7, 1.0e-6, 1.0e-5, 0.0001, 0.001, 0.010000000000000002, 0.1, 1.0, 10.0, 100.0, 1000.0], \"fluxdiagrams\")" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "ts = 10.0 .^ range(-10, 3; step=1)\n", - "fd1 = makefluxdiagrams(ssys, ts)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8aa0c743", - "metadata": {}, - "outputs": [ - { - "ename": "MethodError", - "evalue": "MethodError: no method matching getfluxdiagram(::SystemSimulation{Tuple{Simulation{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}, SciMLBase.StandardODEProblem}, CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Vector{Any}, Vector{String}, ReactionMechanismSimulator.var\"#F#675\"{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}, SciMLBase.StandardODEProblem}, CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Matrix{Float64}, Matrix{Float64}}}, Matrix{Float64}, Vector{Species}, Vector{ElementaryReaction}, Vector{Float64}}, Simulation{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}, SciMLBase.StandardODEProblem}, CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}, Vector{String}, ReactionMechanismSimulator.var\"#F#675\"{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}, SciMLBase.StandardODEProblem}, CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Matrix{Float64}, Matrix{Float64}}}, Matrix{Float64}, Vector{Species}, Vector{ElementaryReaction}, Vector{Float64}}}, ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}, SciMLBase.StandardODEProblem}, CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, Vector{Any}, ElementaryReaction, Species}, ::Float64, ::Float64)\n\nClosest candidates are:\n getfluxdiagram(::Any, ::Any, !Matched::Branching; branchtol, kwargs...)\n @ ReactionMechanismSimulator ~/RMG-Electrocat/ReactionMechanismSimulator.jl/src/fluxdiagrams.jl:107\n getfluxdiagram(::Any, ::Any, !Matched::ReactionPath; radius, kwargs...)\n @ ReactionMechanismSimulator ~/RMG-Electrocat/ReactionMechanismSimulator.jl/src/fluxdiagrams.jl:97\n getfluxdiagram(::Any, ::Any; centralspecieslist, superimpose, maximumnodecount, maximumedgecount, concentrationtol, speciesratetolerance, maximumnodepenwidth, maximumedgepenwidth, radius, centralreactioncount, outputdirectory, colorscheme, removeunconnectednodes)\n @ ReactionMechanismSimulator ~/RMG-Electrocat/ReactionMechanismSimulator.jl/src/fluxdiagrams.jl:80\n", - "output_type": "error", - "traceback": [ - "MethodError: no method matching getfluxdiagram(::SystemSimulation{Tuple{Simulation{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}, SciMLBase.StandardODEProblem}, CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Vector{Any}, Vector{String}, ReactionMechanismSimulator.var\"#F#675\"{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}, SciMLBase.StandardODEProblem}, CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Matrix{Float64}, Matrix{Float64}}}, Matrix{Float64}, Vector{Species}, Vector{ElementaryReaction}, Vector{Float64}}, Simulation{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}, SciMLBase.StandardODEProblem}, CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Vector{ReactiveInternalInterfaceConstantTPhi{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, Matrix{Int64}, Vector{Float64}, Vector{Float64}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ElementaryReaction{T, Int64, V1, V2, V3, V4, Vector{Vector{String}}, Vector{Any}, Vector{Any}, Vector{Any}, Vector{Any}} where {T<:AbstractRate, V1<:AbstractArray, V2<:AbstractArray, V3<:AbstractArray, V4<:AbstractArray}}}, Vector{String}, ReactionMechanismSimulator.var\"#F#675\"{ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}, SciMLBase.StandardODEProblem}, CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Matrix{Float64}, Matrix{Float64}}}, Matrix{Float64}, Vector{Species}, Vector{ElementaryReaction}, Vector{Float64}}}, ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Nothing, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, SciMLBase.FullSpecialize, ReactionMechanismSimulator.var\"#dydt#616\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacy!#617\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, ReactionMechanismSimulator.var\"#jacp!#618\"{Tuple{ConstantTVDomain{IdealDiluteSolution{Tuple{}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}, ConstantTAPhiDomain{IdealSurface{Tuple{Arrheniusvec{Vector{Float64}, Vector{Float64}, Vector{Float64}}}, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, ReactionMechanismSimulator.NASAvec{EmptyThermoUncertainty}, Vector{Float64}}, Int64, Float64, Float64, Integer, Vector{Int64}}}, Vector{Any}}, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing}, Base.Pairs{Symbol, Union{}, Tuple{}, @NamedTuple{}}, SciMLBase.StandardODEProblem}, CVODE_BDF{:Newton, :Dense, Nothing, Nothing}, SciMLBase.HermiteInterpolation{Vector{Float64}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}, DiffEqBase.Stats, Nothing}, Vector{Any}, ElementaryReaction, Species}, ::Float64, ::Float64)\n", - "\n", - "Closest candidates are:\n", - " getfluxdiagram(::Any, ::Any, !Matched::Branching; branchtol, kwargs...)\n", - " @ ReactionMechanismSimulator ~/RMG-Electrocat/ReactionMechanismSimulator.jl/src/fluxdiagrams.jl:107\n", - " getfluxdiagram(::Any, ::Any, !Matched::ReactionPath; radius, kwargs...)\n", - " @ ReactionMechanismSimulator ~/RMG-Electrocat/ReactionMechanismSimulator.jl/src/fluxdiagrams.jl:97\n", - " getfluxdiagram(::Any, ::Any; centralspecieslist, superimpose, maximumnodecount, maximumedgecount, concentrationtol, speciesratetolerance, maximumnodepenwidth, maximumedgepenwidth, radius, centralreactioncount, outputdirectory, colorscheme, removeunconnectednodes)\n", - " @ ReactionMechanismSimulator ~/RMG-Electrocat/ReactionMechanismSimulator.jl/src/fluxdiagrams.jl:80\n", - "\n", - "\n", - "Stacktrace:\n", - " [1] top-level scope\n", - " @ ~/Work/CO2_RR_RMG/CO2_Reduction_Cu3Sn/jl_notebook_cell_df34fa98e69747e1a8f8a730347b8e2f_X66sdnNjb2RlLXJlbW90ZQ==.jl:1" - ] - } - ], - "source": [ - "getfluxdiagram(ssys, 1e3);" - ] - }, - { - "cell_type": "code", - "execution_count": 171, - "id": "bda5e54a", - "metadata": {}, - "outputs": [], - "source": [ - "species_list = [\"CO2\", \"CO2X\", \"CO2HX\", \"CH2O2X\", \"O=CO\"];\n", - "spc_names = [s.name for s in ssys.species];\n", - "G_val = Float64[];\n", - "T = 300.0;\n", - "\n", - "for spc in species_list\n", - " ind = findfirst(==(spc), spc_names);\n", - " if isnothing(ind)\n", - " @warn \"Species $spc not found\"\n", - " push!(G_val, NaN);\n", - " else\n", - " sp = ssys.species[ind];\n", - " G = getGibbs(sp.thermo, T);\n", - " push!(G_val, G);\n", - " end\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 172, - "id": "2c6e2921", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "5-element Vector{Float64}:\n", - " 0.0\n", - " -3358.5091659310856\n", - " -6628.771284540242\n", - " -50890.916188304254\n", - " -25463.460593937838" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "dG" - ] - }, - { - "cell_type": "code", - "execution_count": 173, - "id": "675a13f8", - "metadata": {}, - "outputs": [ - { - "ename": "UndefVarError", - "evalue": "UndefVarError: `hline` not defined", - "output_type": "error", - "traceback": [ - "UndefVarError: `hline` not defined\n", - "\n", - "Stacktrace:\n", - " [1] top-level scope\n", - " @ ~/Work/CO2_RR_RMG/CO2_Reduction_Cu3Sn/jl_notebook_cell_df34fa98e69747e1a8f8a730347b8e2f_X40sdnNjb2RlLXJlbW90ZQ==.jl:5" - ] - } - ], - "source": [ - "dG = G_val .- G_val[1];\n", - "\n", - "clf()\n", - "for (i, name) in enumerate(species_list)\n", - " hline([dG[i]], label=name, linewidth=2)\n", - "end\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 174, - "id": "2c73bc58", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "plotROP (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "function plotROP(ssys,name,t;N=0,tol=0.01)\n", - " clf()\n", - " rop = rops(ssys, name, t)\n", - " inds = rop.nzind[reverse(sortperm(abs.(rop.nzval)))]\n", - " if N == 0\n", - " N = length(inds)\n", - " elseif N > length(inds)\n", - " N = length(inds)\n", - " end\n", - " inds = inds[1:N]\n", - " mval = abs(rop[inds[1]])\n", - " minval = mval*tol\n", - " k = 1\n", - " while k < length(inds) && abs(rop[inds[k]]) >= minval\n", - " k += 1\n", - " end\n", - " inds = inds[1:k]\n", - " net_rops = sum(rop[inds])\n", - " println(\"Net ROPs for species $name is: $net_rops\")\n", - "\n", - " for (i, j) in enumerate(inds)\n", - " println(\"Showing the reaction with $i th highest ROP for species $name:\")\n", - " println(getrxnstr(ssys.reactions[j]))\n", - " println(\"ROP = \", rop[inds[i]])\n", - " println(ssys.reactions[j].kinetics)\n", - " end\n", - "\n", - " xs = Array{Float64,1}(1:length(inds))\n", - " barh(xs,reverse(rop[inds]))\n", - " yticks(xs,reverse(getrxnstr.(ssys.reactions[inds])))\n", - " xlabel(\"Production/Loss Rate mol/s\")\n", - " gcf()\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 175, - "id": "61a903c0", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "PrintKinDetail (generic function with 1 method)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "function PrintKinDetail(inter, speciesname)\n", - " println(\"Showing Kinetics details for reactions involving species $speciesname\\n\")\n", - " for (i,rxn) in enumerate(inter.reactions)\n", - " flag = false\n", - " for j = 1:length(rxn.reactants)\n", - " if rxn.reactants[j].name == speciesname\n", - " flag = true\n", - " end\n", - " end\n", - " for j = 1:length(rxn.products)\n", - " if rxn.products[j].name == speciesname\n", - " flag = true\n", - " end\n", - " end\n", - " if flag\n", - " println(getrxnstr(rxn))\n", - " println(rxn.kinetics)\n", - " kf = inter.kfs[i]\n", - " krev = inter.krevs[i]\n", - " kc = kf/krev\n", - " println(\"kf = $kf\")\n", - " println(\"krev = $krev\")\n", - " println(\"Kc = $kc\\n\")\n", - " end\n", - " end\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 176, - "id": "ae7ceaad", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "get_boundary_layer_concentration" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "\"\"\"\n", - "Integrates the ROP in the boundary layer and computes the concentration\n", - "\"\"\"\n", - "function get_boundary_layer_concentration(sim,t,spc,Vbl,C_0)\n", - " intg,err = quadgk(x -> sum(rops(sim,spc,t)), 0, t);\n", - " return C_0 + intg ./ Vbl;\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 177, - "id": "8c1d4e19", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "flux_to_reservoir_2" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "\"\"\"\n", - "diffusive flux to the reservoir using concentration from ROP integration\n", - "\"\"\"\n", - "function flux_to_reservoir_2(bsol,t,spc,Vbl,C_0,reservoirinterface)\n", - " cs = get_boundary_layer_concentration(bsol,t,spc,Vbl,C_0)\n", - " spc_idx = findfirst(s -> s.name == spc, bsol.sims[1].species)\n", - " d = bsol.sims[1].domain.diffusivity[spc_idx];\n", - " c_res = reservoirinterface.c[spc_idx];\n", - " return reservoirinterface.A * d * (cs - c_res) / reservoirinterface.layer_thickness\n", - "end" - ] - }, - { - "cell_type": "code", - "execution_count": 178, - "id": "482a542d", - "metadata": {}, - "outputs": [], - "source": [ - "# Compute ROP over time\n", - "ROP_vals = [sum(rops(ssys, \"O=CO\", t)) for t in t_vals];\n", - "# Compute boundary layer accumulation by integration\n", - "Cbl_vals = [get_boundary_layer_concentration(ssys, t, \"O=CO\", V_bl, C_default) for t in t_vals];\n", - "# Compute flux over time using Cbl_vals\n", - "F_vals = [flux_to_reservoir_2(ssys, t, \"O=CO\", V_bl, C_default, diffusionlayer) for t in t_vals];" - ] - }, - { - "cell_type": "code", - "execution_count": 179, - "id": "a9b1bfda", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "sys:1: UserWarning: No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Plots the ROP of O=CO\n", - "clf()\n", - "\n", - "plot(t_vals, ROP_vals)\n", - "\n", - "xscale(\"log\")\n", - "xlim(1e-11,1e3)\n", - "yscale(\"log\")\n", - "ylim(1e-8,1e2)\n", - "xlabel(\"Time (s)\")\n", - "ylabel(\"Rate of Progress (mol/s)\")\n", - "legend()\n", - "tight_layout()\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 180, - "id": "23c409b5", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Plots the Boundary Layer Concentration of O=CO from ROP Integration WITHOUT Diffusion Flux Into Reservoir\n", - "clf()\n", - "\n", - "plot(t_vals, Cbl_vals)\n", - "\n", - "xscale(\"log\")\n", - "xlim(1e-11,1e3)\n", - "yscale(\"log\")\n", - "ylim(1e-13,1e1)\n", - "xlabel(\"Time (s)\")\n", - "ylabel(\"Concentration (mol/m^3)\")\n", - "title(\"Boundary Layer Accumulation of O=CO from ROP Integration\")\n", - "legend()\n", - "tight_layout()\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 181, - "id": "75b5d89f", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Plots the Diffusive Flux of O=CO using ROP Integration\n", - "clf()\n", - "\n", - "plot(t_vals, F_vals)\n", - "\n", - "xscale(\"log\")\n", - "xlim(1e-11,1e3)\n", - "yscale(\"log\")\n", - "ylim(1e-15,1e1)\n", - "xlabel(\"Time (s)\")\n", - "ylabel(\"Diffusive Flux (mol/m^3)\")\n", - "title(\"Diffusive Flux of O=CO from ROP Integration\")\n", - "legend()\n", - "tight_layout()\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 182, - "id": "403ba9bc", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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7dg0AKtRWV/e3Z3Z2NoQQ1bYz8L//Flru7u4V7iuVymq3FxUV6VVXixYtsHLlSgghcP36dXzyySeYO3cuOnTogMcff1y3X2BgIC5duoSCggI4ODhUeazq2unVV1/F+PHjIZfL4erqiuDg4AcKyB4eHpW22djY4M6dO7U+Nz09HQDQpUuXKh/XhiRt21cVeHx8fKr8fFX133LdunV47LHH8Oijj2LWrFnw9fWFlZUVFixYgF9++aXWeqtS23dUo9EgOzu7Qqi7v81sbGwAQK82o4bBUEcmZePGjVCr1QadB077l21xcXGF7VWFqKCgIPz8888AgIsXL2L16tX48MMPUVJSgoULF1b7Gk888QRmzpyJJUuW4NNPP8V//vMfxMTEVOhl8fT0hJ2dXbU/yp6ennV+b/qwtbWt9N6B6kPkv//9b2zcuBFdu3bFvHnzMG7cOHTr1q3G19D++KempsLf37/CYykpKfV6b02aNEH79u2xbdu2Sj0IWvHx8UhPT8ejjz6q2/brr7/qzmOsjbaXqHPnznB3d8cff/yBuXPn1hoeBg0ahEWLFiE2NhZvv/12lfvExsbCysrqgT7L99fh5uYGuVyO1NTUSvumpKQAaLjP0b1sbW11f1x06dIFUVFRaN++PWbMmIERI0boehEHDRqEbdu24c8//6wQ9rSEEFi/fj3c3d0RGRlZ4TF/f/8G/wNGX9o2XbNmDYKCgqrdT/s90IbAe6WlpVX5nKo+a7/99huCg4OxatWqCo9X9T3W173f0fulpKRALpdX+L0i48QLJchkJCUl4Y033oCLi0u9hnGq06xZMwDAyZMnK2xfv359jc9r3bo13nvvPYSFheHYsWM17uvm5oaYmBgsXboUGzZsQFpaGiZPnlxhnxEjRuDKlSvw8PBA586dK920dRpas2bNkJGRUeEfmpKSEmzdurXSvqdOncIrr7yCp59+Gnv37kWHDh0wbtw4ZGdn1/ga/fv3B1D+j9G9Dh8+jHPnzmHAgAH1qv3dd99FdnY23njjjUqPFRQU4JVXXoG9vX2Fk7e1w6/63LSsra3x1ltv4fz58/j444+rrCUjIwP79+8HAIwePRrt2rXD559/josXL1bad9WqVdi2bRumTp0KX1/fer33qjg4OKBbt25Yt25dhd4SjUaD3377Df7+/mjdurXBXk9fHh4e+Pzzz5Genl7hYoupU6fC29sbs2fPrnJi8S+//BLnz5/Hm2++WW0PdmOqridqyJAhsLKywpUrV6r87mrDZ0hICHx9fbF69eoKz09KSsKBAwf0rkMmk0GpVFYIdGlpafjjjz+qrFmfnrOQkBA0bdoUy5cvr3CKS0FBAdauXYsePXpUe0ESGQ/21JFROn36tO4KxIyMDOzduxeLFy+GQqHA77//Xu8r3Kri6+uLgQMHYu7cuXBzc0NQUBB27NiBdevWVdjv5MmTeOmll/Doo4+iVatWUCqV2LlzJ06ePFltb8y9Jk+ejFWrVuGll16Cv78/Bg4cWOHxGTNmYO3atXjooYfw2muvoUOHDtBoNEhKSsK2bdvw+uuv19ojVh/jxo3D+++/j8cffxyzZs1CUVER/u///q/SVbMFBQV47LHHEBwcjPnz50OpVGL16tXo1KkTJk2aVOWs9VohISF47rnn8P3330MulyM6OhrXrl3DP/7xDwQEBNT7irknnngCx44dw9dff41r165h8uTJ8PHxwYULF/Dtt9/iypUrWL58OZo3b657joeHR5VDbbWZNWsWzp07hw8++ACHDh3Ck08+iYCAAOTm5iIuLg6LFi3CnDlz0KtXLygUCqxduxaDBg1Cjx498Prrr6NHjx4oLi7Gn3/+iUWLFqFv37745z//Wa/3XZO5c+di0KBBiIqKwhtvvAGlUon58+fj9OnTWLFixQMNUT6Ip59+Gt988w2+/vprTJ8+Hc7OznB1dcW6deswYsQIREZGYtasWQgPD4dKpcKqVauwbNkyjBs3rtI5aFLRnvbxr3/9CxMnToS1tTVCQkLQrFkzfPTRR3j33Xdx9epVDB06FG5ubkhPT8ehQ4fg4OCAOXPmQC6XY86cOXj++ecxduxYTJ48GTk5OZgzZw6aNGlS6/m5WiNGjMC6devw4osvYuzYsUhOTsbHH3+MJk2a4NKlS5Vq3r17N/788080adIETk5OCAkJqXRMuVyOL7/8Ek899RRGjBiB559/HsXFxfjqq6+Qk5ODzz///MEbkBqeZJdoEFXh/isTtXPB9e3bV3z22WciIyOj0nMe9OpXIconjh07dqxwd3cXLi4uYvz48eLIkSMVrhRNT08XzzzzjGjTpo1wcHAQjo6OokOHDuLbb7+tcPXn/Ve/aqnVahEQECBwd7WEquTn54v33ntPN5ebi4uLCAsLE6+99lqtEy4/yOTDmzZtEhEREcLOzk40b95czJs3r1K7jh8/Xtjb21daLUM7J9u3335b42tr56lr3bq1sLa2Fp6enmL8+PEV5qkTQv+rX++vf9iwYcLDw0NYW1uLpk2bigkTJjTIyh5//PGHGD58uPDy8hJWVlbCzc1NREVFiYULF4ri4uIK+2ZmZoq3335btGnTRtja2gpHR0fRtWtXMW/ePL3mfBOi5qtfp0+fXuVztPPUOTg4CDs7O9G9e/cKc64JUf2V5tW1vz6fLyFqntx348aNVU7gnJSUJKZPny6aN2+u+9w/9NBD4rfffqt0JWV189Tpq6Z56u4XFBRU6crR2bNnCz8/PyGXyytdNR8bGyuioqKEs7OzsLGxEUFBQWLs2LHir7/+qnCMRYsWiZYtWwqlUilat24tfvnlF/Hwww9XuHK1tvf5+eefi2bNmgkbGxvRtm1b8dNPP1X5W5iQkCB69eol7O3t9ZqnLjY2VnTr1k3Y2toKBwcHMWDAALF///4K+1T3GdF+pkxpxQ1zIxNCoksJiYiICDk5OWjdujViYmKwaNEiqcshE8bhVyIiokaSlpaGTz/9FFFRUfDw8MD169fx7bffIi8vD6+++qrU5ZGJY6gjIiJqJDY2Nrh27RpefPFFZGVlwd7eHt27d8fChQvRvn17qcsjE8fhVyIiIiIzwClNiIiIiMwAQx0RERGRGWCoIyIiIjIDvFCinjQaDVJSUuDk5CTZZJ5ERERk/oQQyMvLg5+fX42TVDPU1VNKSsoDLcRNREREVBfJycmV1s++F0NdPTk5OQEob2BnZ2eJqyEiIiJzpVKpEBAQoMse1WGoqyftkKuzszNDHRERETW42k734oUSRERERGaAoY6IiIjIDDDUEREREZkBnlNHRERE1MDUajVKS0urfMza2hoKheKBX4OhjoiIiKiBCCGQlpaGnJycGvdzdXWFr6/vA819y1BHRERE1EC0gc7b2xv29vaVQpsQAoWFhcjIyAAANGnSpN6vxVBHRERE1ADUarUu0Hl4eFS7n52dHQAgIyMD3t7e9R6K5YUSRERERA1Aew6dvb19rftq96nuvDt9MNQRERERNSB9zpMzxDryDHVEREREZoChjoiIiMgMMNQRERERmQGGOiIiIiIzwFBHREREVE9Hr2dj9ZFk5N6p/qpVjUZT63H02ac2nKeOiIiIqJ6Wxl/DHwkpuJCWh3+MaFfhMaVSCblcjpSUFHh5eUGpVFY5+XBJSQlu3boFuVwOpVJZ71oY6oiIiIjq4U6JGtvPpgMARnSovBKEXC5HcHAwUlNTkZKSUuOx7O3tERgYCLm8/oOoDHVERERE9bDzfAYKS9Twd7NDRIBrlfsolUoEBgairKwMarW6yn0UCgWsrKweeK46hjoiIiKiethwsrz3bWS4X42BTCaTwdraGtbW1g1aDy+UICIiIqqjvKJS7DyfAaDqoVcpMNQRERER1dFf59JRXKZBcy8HtGviLHU5ABjqiIiIiOpsw4lUAMCIDjUPvTYmhjoiIiKiOsgpLEHcpVsAgJFGMvQKMNQRERER1cnWM2koVQu08XVCKx8nqcvRYagjIiIiqoMNJ8uHXkeG+0lcSUUMdURERER6UhWV4u+rtwEAQ0N9Ja6mIoY6IiIiIj3tuXALpWqB5l4OaOHlKHU5FTDUEREREenpr3Ply4INaucjcSWVMdQRERER6aFUrcGuuxMOD2rLUEdERERkkg4lZkFVVAYPByU6BrpJXU4lDHVEREREeth+tnzotX8bbyjkxjHh8L0Y6oiIiIhqIYTQhTpjPJ8OYKgjIiIiqtX5tDzczLkDGys5erfylLqcKjHUEREREdVC20vXp5Un7JVWEldTNYY6IiIiolpopzIZaIRXvWox1BERERHV4FZeMU7eyAVQfpGEsWKoIyIiIqpB3MVbAID2fs7wdraVuJrqMdQRERER1WDXhfIJh6NCjLeXDmCoIyIiIqpWmVqDvZcyAQBRbbwkrqZmDHVERERE1UhIzkHunVK42FkjIsD4VpG4F0MdERERUTV2Xyg/n+6h1l5GuYrEvRjqiIiIiKqx+2L5+XT9Whv30CtgwaEuLy8PXbp0QUREBMLCwvDTTz9JXRIREREZkYy8Ipy+qQIA9A0x/lBnnFMiNwJ7e3vs2bMH9vb2KCwsRGhoKMaMGQMPDw+pSyMiIiIjsOfu0GsHfxd4OtpIXE3tLLanTqFQwN7eHgBQVFQEtVoNIYTEVREREZGx0J5P18/IpzLRMtpQFxcXh5EjR8LPzw8ymQyxsbGV9pk/fz6Cg4Nha2uLyMhI7N27t06vkZOTg/DwcPj7++PNN9+Ep6dxLtBLREREjat8KhNtqDP+oVfAiENdQUEBwsPDMW/evCofX7VqFWbMmIF3330Xx48fR58+fRAdHY2kpCTdPpGRkQgNDa10S0lJAQC4urrixIkTSExMxPLly5Gent4o742IiIiM28mbuVAVlcHFzhrh/q5Sl6MXoz2nLjo6GtHR0dU+/s0332DKlCmYOnUqAOC7777D1q1bsWDBAsydOxcAcPToUb1ey8fHBx06dEBcXBweffTRKvcpLi5GcXGx7r5KpdL3rRAREZGJ2XuxfMLh3i09jX4qEy2j7amrSUlJCY4ePYrBgwdX2D548GAcOHBAr2Okp6frgplKpUJcXBxCQkKq3X/u3LlwcXHR3QICAur/BoiIiMioaYde+7QynVOzTDLUZWZmQq1Ww8fHp8J2Hx8fpKWl6XWMGzdu4KGHHkJ4eDh69+6Nl156CR06dKh2/9mzZyM3N1d3S05OfqD3QERERMZJVVSK48k5AIDeJhTqjHb4VR8yWcXuUCFEpW3ViYyMREJCgt6vZWNjAxsb47+cmYiIiB5M/JXbUGsEmns5wN/NXupy9GaSPXWenp5QKBSVeuUyMjIq9d4RERER1UXcxbtLg7UyjatetUwy1CmVSkRGRmL79u0Vtm/fvh09e/aUqCoiIiIyB3svlV8kYUrn0wFGPPyan5+Py5cv6+4nJiYiISEB7u7uCAwMxMyZMzFhwgR07twZPXr0wKJFi5CUlIRp06ZJWDURERGZsuu3C5CUVQhrhQzdm5vWKlNGG+qOHDmCqKgo3f2ZM2cCACZOnIglS5Zg3LhxuH37Nj766COkpqYiNDQUmzZtQlBQkFQlExERkYmLu9tL1ynQDQ42RhuTqmS01fbr16/WZbtefPFFvPjii41UEREREZm7vdrz6Vqb1vl0gImeU0dERERkaKVqDeKv3AZgeufTAQx1RERERACAE8k5yCsug5u9Ndr7uUhdTp0x1BERERHhf+fT9W7lZTJLg92LoY6IiIgIprk02L0Y6oiIiMji5RaW4sTdpcEY6oiIiIhM1IErmdAIoJW3I5q42EldTr0w1BEREZHFi9OtImF6U5loMdQRERGRRRNC6NZ77dPaNIdeAYY6IiIisnDXbhfiZs4dKBVydAt2l7qcemOoIyIiIoumveq1czM32CuNdrGtWjHUERERkUXTDb2a8Pl0AEMdERERWTBTXxrsXgx1REREZLGOXc9GQYkaHg5KtGviLHU5D4ShjoiIiCzWvsvapcE8ITfBpcHuxVBHREREFku33mtL0x56BRjqiIiIyELlFJbg5I0cAKZ/kQTAUEdEREQW6sCV2xACaO3jCF8XW6nLeWAMdURERGSRtPPT9W5p+r10AEMdERERWaDypcHurvdqwkuD3YuhjoiIiCyOuSwNdi+GOiIiIrI42qHXyCDTXhrsXgx1REREZHHMbegVYKgjIiIiC1Oq1uDvq+VLgz1kBlOZaDHUERERkUVJSM5BfnEZ3M1gabB7MdQRERGRRdl7sfx8ul4tTX9psHsx1BEREZFF2Xt3vdc+rcznfDqAoY6IiIgsSG5hKU4k5wBgqCMiIiIyWQeuZEIjgJbejmjiYid1OQbFUEdEREQWw1yHXgGGOiIiIrIQ5UuDlV8kwVBHREREZKKu3y7Ejew7sFbI0C3YQ+pyDI6hjoiIiCyCdug1MsgNDjbmsTTYvRjqiIiIyCLs1Q29ms8qEvdiqCMiIiKzV6bWIP5K+dJg5ng+HcBQR0RERBbgxI0c5BWXwc3eGu39XKQup0Ew1BEREZHZi7tYfj5dz5aeUJjR0mD3YqgjIiIis7f3Uvn5dA+Z6dArwFBHREREZi73TilO3MgFAPQ204skAIY6IiIiMnPxV25DrRFo7uWApq7mtTTYvRjqiIiIyKz9b+jVfHvpAIY6IiIiMnP7zHi913sx1BEREZHZun67ANdvF8JKLkO35ua3NNi9GOqIiIjIbO29VN5L1ynIDY5muDTYvRjqiIiIyGztuxvq+rQ076FXgKGOiIiIzFSZWoP9V+6GutbmfZEEwFBHREREZurEjVzkFZXBxc4aYU3Nc2mwezHUERERkVmKu1g+lUmvlh5muzTYvRjqiIiIyCztuRvq+rX2lriSxsFQR0RERGYnq6AEJ27kAAAesoDz6QCGOiIiIjJDey/dghBAG18n+LrYSl1Oo2CoIyIiIrOz50L50GvfEMvopQMY6oiIiMjMaDQCcZcs63w6wMJDnZWVFSIiIhAREYGpU6dKXQ4REREZwJkUFTLzS+CgVCAyyE3qchqNea+XUQtXV1ckJCRIXQYREREZ0J6LGQCAXi09obSynP4ry3mnREREZBF2W+D5dIARh7q4uDiMHDkSfn5+kMlkiI2NrbTP/PnzERwcDFtbW0RGRmLv3r11eg2VSoXIyEj07t0be/bsMVDlREREJJXcwlIcS8oGAPS1kKlMtIx2+LWgoADh4eGYNGkSHnnkkUqPr1q1CjNmzMD8+fPRq1cv/Pjjj4iOjsbZs2cRGBgIAIiMjERxcXGl527btg1+fn64du0a/Pz8cPr0aQwfPhynTp2Cs7Nzg783IiIiahj7LmdCI4CW3o7wd7OXupxGZbShLjo6GtHR0dU+/s0332DKlCm6Cxy+++47bN26FQsWLMDcuXMBAEePHq3xNfz8/AAAoaGhaNeuHS5evIjOnTsb6B0QERFRY9OeT9fPwnrpACMefq1JSUkJjh49isGDB1fYPnjwYBw4cECvY2RnZ+t68W7cuIGzZ8+iefPm1e5fXFwMlUpV4UZERETGQwihWxrM0s6nA4y4p64mmZmZUKvV8PHxqbDdx8cHaWlpeh3j3LlzeP755yGXyyGTyfCvf/0L7u7u1e4/d+5czJkz54HqJiIiooZzPi0P6api2Fkr0KVZ9f+mmyuTDHVaMpmswn0hRKVt1enZsydOnTql92vNnj0bM2fO1N1XqVQICAjQ+/lERETUsLRXvfZo4QFba4XE1TQ+kwx1np6eUCgUlXrlMjIyKvXeGYqNjQ1sbGwa5NhERET04HTn01ng0CtgoufUKZVKREZGYvv27RW2b9++HT179pSoKiIiIpJKXlEpjlyzzKlMtIy2py4/Px+XL1/W3U9MTERCQgLc3d0RGBiImTNnYsKECejcuTN69OiBRYsWISkpCdOmTZOwaiIiIpLC/su3UaYRCPZ0QJCHg9TlSMJoQ92RI0cQFRWlu689n23ixIlYsmQJxo0bh9u3b+Ojjz5CamoqQkNDsWnTJgQFBUlVMhEREUlEd9WrhfbSAYBMCCGkLsIUqVQquLi4IDc3lxMWExERSUgIgV6f70RKbhEWT+qCqBBvqUsyKH0zh0meU0dERESkdTkjHym5RVBaydE92EPqciTDUEdEREQmTTuVSffmHrBTWt5UJloMdURERGTSdp4vn8rEks+nAxjqiIiIyITl3inF4WtZAICBbc3rXLq6YqgjIiIikxV38RbKNAItvCx3KhMthjoiIiIyWTvOpQMABrZtmBWlTAlDHREREZmkMrUGu+/OTzeAoY6hjoiIiEzTsaQc5BSWwsXOGp0CXaUuR3IMdURERGSSdpwvH3qNCvGClYKRhi1AREREJmnHufKpTDj0Wo6hjoiIiEzO9dsFuJyRDyu5DA9Z+Px0Wgx1REREZHK0vXRdmrnDxc5a4mqMA0MdERERmRzt+XQDLHzC4Xsx1BEREZFJURWV4uBV7SoSPJ9Oi6GOiIiITMrei5ko0wg093JAM0/LXkXiXgx1REREZFK4ikTVGOqIiIjIZKg1Arsu3J3KpA3Pp7sXQx0RERGZjONJ2ci+u4pEZJCb1OUYFYY6IiIiMhl/3Z3KpB9XkaiErUFEREQmY6duKhOeT3c/hjoiIiIyCclZhbiYng+FXIa+rbiKxP3qHOp+/vnnKreXlZVh9uzZD1wQERERUVX+unvVa5dmbnCx5yoS96tzqHv99dfxyCOPICsrS7ft/Pnz6Nq1K1avXm3Q4oiIiIi0tEuDcSqTqtU51B0/fhzp6ekICwvD9u3b8cMPP6BTp04IDQ1FQkJCA5RIREREli63sBR/X70NgOfTVceqrk8IDg5GXFwcXnvtNQwdOhQKhQJLly7F448/3hD1EREREWHnhXSUaQRCfJwQzFUkqlSvCyU2bNiAFStWoGfPnnB1dcVPP/2ElJQUQ9dGREREBADYerr8fLrB7dlLV506h7rnn38ejz32GN58803ExcXh5MmTsLGxQVhYGM+pIyIiIoMrKlVjz8VbAIAh7X0lrsZ41Xn4df/+/Th48CDCw8MBAL6+vti0aRN++OEHTJ48GY899pjBiyQiIiLLFXfxFu6UqtHU1Q7t/ZylLsdo1TnUHT16FDY2NpW2T58+HQMHDjRIUURERERaW8/8b+hVJpNJXI3xqvPwa1WBTiskJOSBiiEiIiK6V6lagx13V5Hg0GvN6nX1a00p+erVqw9UEBEREZHWocQs5BSWwt1BiS7N3KUux6jVOdTNmDGjwv3S0lIcP34cW7ZswaxZswxVFxERERG2nkkDAAxs6w2FnEOvNalzqHv11Ver3P7DDz/gyJEjD1wQEREREQBoNALbznDoVV/1mqeuKtHR0Vi7dq2hDkdEREQW7nhyDtJURXC0sUKvlp5Sl2P0DBbq1qxZA3d3jnUTERGRYWw6lQoAGNDWG7bWComrMX51Hn7t2LFjhQslhBBIS0vDrVu3MH/+fIMWR0RERJZJCIHNd0PdsLAmEldjGuoc6mJiYircl8vl8PLyQr9+/dCmTRtD1UVEREQWLCE5Bym5RXBQKtC3tZfU5ZiEOoe6Dz74oCHqICIiItLRDr32b+vDoVc96RXqVCqV3gd0dubyHURERFR/QghsOlU+lcnwMF71qi+9Qp2rq2uty3IIISCTyaBWqw1SGBEREVmmkzdycTPnDuysFejb2lvqckyGXqFu165dDV0HEREREQBg02nt0Ks37JQcetWXXqGub9++DV0HERER0d2rXrVDr7zqtS70nqfu6aefRl5enu7+iRMnUFpa2iBFERERkWU6cSMXSVmFsLNWoF8Ir3qtC71D3bJly3Dnzh3d/T59+iA5OblBiiIiIiLLtD4hBQAwsJ0P7JV1nqTDoukd6oQQNd4nIiIiehBqjcCGk+WhblS4n8TVmB6DLRNGRERE9CAOJWYhI68YzrZWeKg113qtqzr1a549exZpaeUnLwohcP78eeTn51fYp0OHDoarjoiIiCzG+hPlvXTRoU1gY8WrXuuqTqFuwIABFYZdR4wYAQCQyWScp46IiIjqraRMg813pzIZFcGh1/rQO9QlJiY2ZB1ERERkwfZdvoWcwlJ4Otqge3MPqcsxSXqHuqCgoIasg4iIiCzYnyfKe+lGdGgChbzmVayoarxQgoiIiCR1p0SNbWfKz9kfyate642hjoiIiCS17WwaCkrUCHC3Q6dAV6nLMVkMdURERCSpdcduAgBGd/SHTMah1/qy2FB34cIFRERE6G52dnaIjY2VuiwiIiKLkqEqwt5LtwAAYzo2lbga01av9TfKysqwe/duXLlyBU8++SScnJyQkpICZ2dnODo6GrrGBhESEoKEhAQAQH5+Ppo1a4ZBgwZJWxQREZGF+SMhBRoBRAa5oZmng9TlmLQ6h7rr169j6NChSEpKQnFxMQYNGgQnJyd8+eWXKCoqwsKFCxuizga1fv16DBgwAA4O/DARERE1prXHbgAAxnRiL92DqvPw66uvvorOnTsjOzsbdnZ2uu2jR4/Gjh07DFZYXFwcRo4cCT8/P8hksiqHRufPn4/g4GDY2toiMjISe/furddrrV69GuPGjXvAiomIiKguzqaocD4tD0qFHCPCeNXrg6pzT92+ffuwf/9+KJXKCtuDgoJw8+ZNgxVWUFCA8PBwTJo0CY888kilx1etWoUZM2Zg/vz56NWrF3788UdER0fj7NmzCAwMBABERkaiuLi40nO3bdsGP7/yD49KpcL+/fuxcuVKg9VOREREtfv9eHkv3cB23nCxt5a4GtNX51Cn0WiqXArsxo0bcHJyMkhRABAdHY3o6OhqH//mm28wZcoUTJ06FQDw3XffYevWrViwYAHmzp0LADh69Gitr/PHH39gyJAhsLW1NUzhREREVKsytQaxCeVrvY7p6C9xNeahzsOvgwYNwnfffae7L5PJkJ+fjw8++ADDhg0zZG3VKikpwdGjRzF48OAK2wcPHowDBw7U6Vj6Dr0WFxdDpVJVuBEREVH9xF26hVt5xXB3UKJviJfU5ZiFOoe6b7/9Fnv27EG7du1QVFSEJ598Es2aNcPNmzfxxRdfNESNlWRmZkKtVsPHx6fCdh8fH6Slpel9nNzcXBw6dAhDhgypdd+5c+fCxcVFdwsICKhz3URERFRu5aFkAOXTmFgrLHaGNYOq8/Crn58fEhISsGLFChw7dgwajQZTpkzBU089VeHCicZw/wSFQog6TVro4uKC9PR0vfadPXs2Zs6cqbuvUqkY7IiIiOohI68IO85nAADGdeG/pYZS51BXWFgIe3t7TJ48GZMnT26Immrl6ekJhUJRqVcuIyOjUu+dodjY2MDGxqZBjk1ERGRJ1h69CbVGIDLIDa18DHc+vqWrc3+nt7c3xo8fj61bt0Kj0TRETbVSKpWIjIzE9u3bK2zfvn07evbsKUlNREREVDshBFYdTgLAXjpDq3OoW7p0KYqLizF69Gj4+fnh1VdfxeHDhw1eWH5+PhISEnSrPiQmJiIhIQFJSeUfhJkzZ+Lf//43fvnlF5w7dw6vvfYakpKSMG3aNIPXQkRERIbx99UsXLtdCEcbKwwPayJ1OWalzsOvY8aMwZgxY5CXl4c1a9ZgxYoV6NmzJ4KDgzF+/Hi8//77BinsyJEjiIqK0t3Xns82ceJELFmyBOPGjcPt27fx0UcfITU1FaGhodi0aROCgoIM8vpERERkeNpeupHhfnCwqddqpVQNmRBCPOhBzp49i6eeegonT56scg47c6RSqeDi4oLc3Fw4OztLXQ4REZHRyy0sRZfP/kJJmQZ/TO+F8ABXqUsyCfpmjnpfQ1xUVITVq1cjJiYGnTp1wu3bt/HGG2/U93BERERk5tYcu4GSMg3a+Dqhg7+L1OWYnTr3e27btg3Lli1DbGwsFAoFxo4di61bt6Jv374NUR8RERGZAY1G4Le/rwMAxncPqtMUZKSfOoe6mJgYDB8+HL/++iuGDx8Oa2uu1UZEREQ123c5E4mZBXCyscLojk2lLscs1TnUpaWl8RwyIiIiqpOl8eW9dI9E+vMCiQaiV6uqVKoKQa6mdU8Z+IiIiOheN7ILsfN8+QpO47tzloqGoleoc3NzQ2pqKry9veHq6lrlOLh2iS5LufqViIiI9LPsYBI0AujV0gMtvR2lLsds6RXqdu7cCXd3dwDArl27GrQgIiIiMh9FpWqsPFQ+N92E7s2kLcbM6RXq7r2ylVe5EhERkb7+PJGC7MJS+LnYYmBbb6nLMWt1nqduy5Yt2Ldvn+7+Dz/8gIiICDz55JPIzs42aHFERERkuoQQ+HlfIgBgQo9msFLUe3pc0kOdW3fWrFm6CyVOnTqFmTNnYtiwYbh69apuKS8iIiKivZcycT4tDw5KBZ7sFih1OWavztcUJyYmol27dgCAtWvXYuTIkfjss89w7NgxDBs2zOAFEhERkWn6ae9VAMBjXQLgYsd5bRtanXvqlEolCgsLAQB//fUXBg8eDABwd3evcaoTIiIishznUlXYeykTchkwuVew1OVYhDr31PXu3RszZ85Er169cOjQIaxatQoAcPHiRfj7+xu8QCIiIjI92l666LAmCHC3l7gay1Dnnrp58+bBysoKa9aswYIFC9C0aflSH5s3b8bQoUMNXiARERGZlrTcIvx5IgUA8Fyf5hJXYznq3FMXGBiIDRs2VNr+7bffGqQgIiIiMm2/7E9EqVqgazN3hAe4Sl2OxahzqEtKSqrx8cBAXt1CRERkqbIKSvDb3+XrvL7Qr4XE1ViWOoe6Zs2aVblMmBaXCSMiIrJcP++7isISNcKauqBfiJfU5ViUOoe648ePV7hfWlqK48eP45tvvsGnn35qsMKIiIjItOQWluLXA+W9dC/1b1ljJxAZXp1DXXh4eKVtnTt3hp+fH7766iuMGTPGIIURERGRaVly4Bryi8sQ4uOEQW19pC7H4hhsvY7WrVvj8OHDhjocERERmZC8olL8sr98SbCX+reEXM5eusZW5566+ycYFkIgNTUVH374IVq1amWwwoiIiMh0LI2/jtw7pWju5YBhYU2kLsci1TnUubq6VhojF0IgICAAK1euNFhhREREZBpyC0vx454rAICX+7eEgr10kqhzqNu1a1eF+3K5HF5eXmjZsiWsrOp8OCIiIjJxC+OuQFVUfi7dqPCmUpdjsfRKYZ06dcKOHTvg5uaGPXv24I033oC9PZf8ICIisnQZqiIsvnsu3RtDQthLJyG9LpQ4d+4cCgoKAABz5szR/X8iIiKybN/vvIyiUg06BbpiYFtvqcuxaHr11EVERGDSpEno3bs3hBD46quv4OjoWOW+77//vkELJCIiIuN0/XYBVhwqX2lq1pA2nJdOYnqFuiVLluCDDz7Ahg0bIJPJsHnz5irPn5PJZAx1REREFuLrbRdRphHo08oTPVp4SF2OxdMr1IWEhOiubJXL5dixYwe8vdnFSkREZKmOXs/CnydSIJMBbw1tI3U5BD3PqevUqROys7MBAB988EG1Q69ERERk/jQagY/+PAsAeCwyAKFNXSSuiIB6XCjx0UcfIT8/v0GLIiIiIuMVm3ATJ27kwkGpwOtDWktdDt1Vrwslvv76a14oQUREZIEKS8rwxZbzAIDp/VvC28lW4opIixdKEBERkd4W7r6CdFUxAtztMLlXsNTl0D14oQQRERHpJTGzAAv3XAUAvBPdFrbWCokronvVeV0vjUbTEHUQERGRERNC4B+xp1Gi1uCh1l4YGuordUl0H71C3fr16xEdHQ1ra2usX7++xn1HjRplkMKIiIjIePx5MhX7LmdCaSXHxw+350TDRkivUBcTE4O0tDR4e3sjJiam2v1kMhnUarWhaiMiIiIjkHunFB9vKJ/C5OWolgjycJC4IqqKXqHu3iFXDr8SERFZln9uu4BbecVo7uWA5/o2l7ocqoZe89QRERGRZTqUmIWl8dcBAJ88HAobK14cYazqdKGERqPBkiVLsG7dOly7dg0ymQzBwcEYO3YsJkyYwPF1IiIiM3KnRI0315wAADzeJQA9W3pKXBHVRO+eOiEERo0ahalTp+LmzZsICwtD+/btcf36dTzzzDMYPXp0Q9ZJREREjezrbRdw7XYhmrjY4p3hbaUuh2qhd0/dkiVLEBcXhx07diAqKqrCYzt37kRMTAyWLl2Kp59+2uBFEhERUeM6ej0Lv+xPBAB8NiYMzrbWEldEtdG7p27FihV45513KgU6AOjfvz/efvttLFu2zKDFERERUeMrLCnDrP+ehBDA2Eh/RIVwwQFToHeoO3nyJIYOHVrt49HR0Thx4oRBiiIiIiLpfLrxHK5mFsDX2Rb/GN5O6nJIT3qHuqysLPj4+FT7uI+PD7Kzsw1SFBEREUljx7l0LDuYBAD452PhcLHnsKup0DvUqdVqWFlVfwqeQqFAWVmZQYoiIiKixncrrxhvrjkJAJjaOxi9eLWrSdH7QgkhBJ555hnY2NhU+XhxcbHBiiIiIqLGJYTA22tP4nZBCdr4OuGNISFSl0R1pHeomzhxYq378MpXIiIi0/TzvkTsOJ8BpUKO7x6PgK01Jxk2NXqHusWLFzdkHURERCSRhOQcfLHlPADgvRFt0cbXWeKKqD64TBgREZEFy71TipeWH0OpWmBYmC8mdA+SuiSqJ4Y6IiIiC6U9j+5G9h0EuNth7pgOXPLThDHUERERWaif9yVi8+k0WCtkmPdEJ7jYcfoSU8ZQR0REZIEOXr2NuZvLz6N7d1hbhAe4SlsQPTCGOiIiIguTrirC9OXHodYIxET4YWLPZlKXRAZgsaHu66+/Rvv27REaGorffvtN6nKIiIgaRUmZBtOXHUNmfjHa+DrhszFhPI/OTOg9pYk5OXXqFJYvX46jR48CAAYMGIARI0bA1dVV2sKIiIgakBAC7/9xGkeuZ8PJ1goLx0fCXmmRUcAsWWRP3blz59CzZ0/Y2trC1tYWERER2LJli9RlERERNaglB65h5eFkyGTA/z3eEc08HaQuiQzIKENdXFwcRo4cCT8/P8hkMsTGxlbaZ/78+QgODoatrS0iIyOxd+9evY8fGhqKXbt2IScnBzk5Odi5cydu3rxpwHdARERkXOIu3sLHG84CAN6JbouoNt4SV0SGZpR9rgUFBQgPD8ekSZPwyCOPVHp81apVmDFjBubPn49evXrhxx9/RHR0NM6ePYvAwEAAQGRkZJXr0W7btg3t2rXDK6+8gv79+8PFxQVdunSBlZVRNgURkUURQiAltwgX0/NwOT0fWYUlsLVSwE4ph7uDDXq19EATFzupyzQ5V27lY/ryY9AIYGykP6b2CZa6JGoAMiGEkLqImshkMvz++++IiYnRbevWrRs6deqEBQsW6La1bdsWMTExmDt3bp1fY+rUqRg9ejSGDx+u93NUKhVcXFyQm5sLZ2cup0JEVF9qjcDha1nYfCoVm0+nISOv8h/k92rj64T+bbwxqVcwvJxsGqlK05VbWIqY+fuRmFmAyCA3LH+2G2ysuK6rKdE3c5hc91RJSQmOHj2Kt99+u8L2wYMH48CBA3ofJyMjA97e3rhw4QIOHTqEhQsX1rh/cXFxhZ4/lUpVt8KJiKiC/OIyrDyUhJ/3JSI1t0i33VohQ7CnA1p5O8Hb2QbFZRoUlaiReLsACck5OJ+Wh/NpefhP/HXMGNQaT/cIgrXCKM8mklyZWoPpy48hMbMATV3tsHB8JAOdGTO5UJeZmQm1Wg0fH58K2318fJCWlqb3cWJiYpCTkwMHBwcsXry41uHXuXPnYs6cOfWqmYiI/ievqBSL4q7i1wPXoCoqAwA421phcHtfDAvzRa+WntUGj+yCEsRduoWf9l7F6ZsqfLzhLFYdTsL3T3RCiK9TY74Nk/DJxnPYdzkTdtYK/PR0Z/ZsmjmTC3Va98+pI4So0zw7denVA4DZs2dj5syZuvsqlQoBAQF1OgYRkSVTawT+eyQZX2+7gMz8EgBAc08HPPdQc8R0bApb69p7kNwclHg4oilGdPDDqsPJ+GrreVxMz8e4RfH4z+RuCPN3aei3YTL+E38NSw5cAwB8Oy4C7fx4qpC5M7lQ5+npCYVCUalXLiMjo1LvnSHZ2NjAxoZ/4RAR1cfJGzl4e+0pnE0tP3WluacD3hwagsHtfCGX133iW4Vchie7BWJoqC8mLzmMhOQcPPnT31gyuQsig9wNXb7J2X42HR+sPwMAmDUkBENDfSWuiBqDyZ2EoFQqERkZie3bt1fYvn37dvTs2VOiqoiIqCpFpWp8vvk8Yn7Yj7OpKjjbWuEfI9phy4yHMDS0Sb0C3b3cHZT4bWo3dA12R15xGSb8fAhHrmUZqHrTdCI5By+vKL/S9fEuAXixXwupS6JGYpQ9dfn5+bh8+bLufmJiIhISEuDu7o7AwEDMnDkTEyZMQOfOndGjRw8sWrQISUlJmDZtmoRVExHRvU7dyMWrq47j6q0CAMCocD98MLIdPBwNO+rhaGOFXyd1xXP/OYK9lzLx0vLj2PxqH7g5KA36OqYg6XYhpvx6GEWlGvRt7YWPY0K5BJgFMcopTXbv3o2oqKhK2ydOnIglS5YAKJ98+Msvv0RqaipCQ0Px7bff4qGHHmq0GjmlCRFR1TQagZ/3JeLLredRqhbwdrLBJzGhGNy+YYcAC0vKMOL7fbh6qwBD2vtg4fhIiwo02QUleGTBAVzNLEB7P2eser4HHG2Msu+G6kjfzGGUoc4UMNQREVV2O78YM1efwJ6LtwAA0aG+mDsmDK72jdNrdvpmLkbP349StcDcMWF4omtgo7yu1IpK1Rj/74M4cj0bTV3t8PuLPeHtbCt1WWQg+mYOkzunjoiIjNOJ5ByM/H4f9ly8BRsrOT4dHYr5T3VqtEAHAKFNXTBrSAgAYM6fZ3A5I7/RXlsqGo3A66tP4Mj1bDjZWmHJpC4MdBaKoY6IiB7YqsNJeHRhPFJyi9Dc0wHrX+qNp7oFSTL8ObV3c/Ru6YmiUg3eiz0Fcx6QEkLgk43nsPFUKpQKORZN6IxWPpyvz1Ix1BERUb2VqTV4/4/TeGvtKZSoNRjUzgexL/WSdCJguVyGL8Z2gFIhx99Xs7D3UqZktTS0BXuu4Jf9iQCArx7tgB4tPCSuiKTEUEdERPWiKirFpCWHsTT+OmQy4I3BrfHj+Eg421pLXRqautphfPcgAMBXWy+YZW/dqsNJ+HLLBQDAP0a0w8MRTSWuiKTGUEdERHWWnFWIR+YfwN5L5UtQLRwfiZf6t3rgeecMaXpUCzgoFTh1MxdbTuu/jKQp2HYmDbPXnQIAvNCvBab0Dpa4IjIGDHVERFQnZ1NUGLPgAC5l5MPH2Qb/ndYDQxp4upL68HC00YWdr7ddgFpjHr11hxKz8PKK49AI4LHO/njz7oUhRAx1RESkt7+v3sa4H+NxK68YbXyd8Mf03ghtarzrrU59qDlc7a1x5VYB1h27IXU5D+xcqgpTfj2M4rLy8xc/Gx1mUXPxUc0Y6oiISC9bTqfh6V8OIa+4DF2D3bHq+R7wdTHuqTOcba3xQt/yZbIW7L5i0ufWJWcVlrd/URm6NnPH9090hJWC/4zT//DTQEREtfrzRAqmLz+GkjINhrT3wdLJXeFiJ/0FEfp4qnsQHG2scDWzAAeu3Ja6nHrJUBVh/M8HdT2kP03sDFtrhdRlkZFhqCMiohrFHr+JV1ceh1ojMKZTU/zwZCeTChSONlYY3bH8ytDf/r4ucTV1l1NYggk/H8L124UIcLfDryYUqKlxMdQREVG11h69gddWJ+hOyv9qbLhJDvlppzfZdjYd6aoiiavRX35xGSYuPowL6XnwcbbBsind4cPVIqgapvfNJCKiRrH5VCpmrTkBIYAnuwXi8zEdoDCiKUvqIsTXCV2auUGtEVh5KFnqcvRSVKrGs78ewYnkHLjZW+O3Kd0Q6GEvdVlkxBjqiIiokj0Xb+GVleXTZjzeJQCfxoQa1Rx09aHtrVtxKAllao3E1dSsVK3BS8uPIf7qbTjaWOHXyV25/BfViqGOiIgqOHwtC8//5whK1QLDOzTBp2YybcbQUF94OCiRpirCX+cypC6nWhqNwBv/PYG/zmXAxkqOnyd2Rgd/V6nLIhPAUEdERDqXM/IxZclhFJVq0C/EC98+FmGyQ673s7FS4NHOAQCAZQeN84IJIQT+8cdp/JGQAiu5DAvHR6Jbc67nSvphqCMiIgDA7fxiTFpyCKqiMnQKdMWCpyKhtDKvfyae7BoIANh3ORMZRnbBhBACn285j2UHkyCTAd+Oi0BUG2+pyyITYl7fViIiqpeiUjWeXXoEyVl3EOhuj5+e7gw7pelMW6KvQA97dAx0hRDAxlOpUpdTwfzdV/DjnqsAgLmjwzAy3E/iisjUMNQREVk4IQRmrTmJY0k5cLGzxuJJXeDhaCN1WQ1m1N2wtP5EisSV/M/S+Gv4ausFAMC7w9ri8bs9ikR1wVBHRGThfoy7ij9PpMBaUX4OVwsvR6lLalDDOzSBXAYcT8pBclah1OXgv0eS8f4fZwAAr/RviWcfai5xRWSqGOqIiCzYvkuZ+HLLeQDAh6Pao0cL8z8p39vJVvc+pe6tW38iBW+tPQkAmNSrGV4b1FrSesi0MdQREVmoG9mFeHnFMd1qEU9a0JDfyA7lQ7B/ShjqtpxOw2urylfreKJrIN4f0c4spo4h6TDUERFZoOIyNV747RiyC0sR1tQFHz0calGBIjq0CawVMpxPy8PF9LxGf/1d5zPw8opjuvV0P42xrPanhsFQR0RkgeZuOo9TN3PhZm+NBeM7wdba/K50rYmLvTX6tvYCAKxPaNzeuv2XM/H8b0d1kzt/+UgHk1+tg4wDQx0RkYX562w6lhy4BgD452Ph8HezzPVER95zFawQolFe8/C1LEz99QhKyjQY1M4H342LgJWC/xSTYfCTRERkQdJyizBrzQkAwORewejfxkfiiqQzqJ0P7KwVSMoqxIkbuQ3+egnJOZi0+DDulKrRt7UX5j3ZEdYMdGRA/DQREVkItUZgxqrjyC4sRXs/Z7wVHSJ1SZKyV1phYLvyUNvQQ7BnUnLx9M8HkV9chh7NPfDjhEjYWFnWkDc1PIY6IiIL8e+9V/H31SzYKxX4/omODBX430TEG06mQK1pmCHYi+l5mPBz+fJrkUFu+PfEzhZ3DiM1DoY6IiILcCEtD//cdhEA8MHIdmhu5hMM6+uh1p5wtrVCRl4xDiVmGfz4iZkFeOrfB5FVUIIO/i5YPKkLHGysDP46RABDHRGR2Ssp02Dm6gSUqDXo38Ybj3UOkLoko2FjpUB0aBMAhp+IODmrEE/+9Ddu5RWjja8Tlk7uCmdba4O+BtG9GOqIiMzcvJ2XcCZFBVd7a3w+Jozzod1HexXs5tOpKCnTGOSYqbl38OS//0ZqbhFaejvit6nd4GqvNMixiarDUEdEZMZO3cjFD7uvAAA+iQmFt7OtxBUZnx4tPODpaIOcwlLsu3zrgY+XkVeEp346iOSsOwjysMeyqd3g6WhjgEqJasZQR0RkpkrVGsxacwJqTfkktyPuLo1FFSnkMozocHcI9gGvgs3IK8ITi/7G1cwCNHW1w7Kp3eDDIE2NhKGOiMhMLYq7ivNpeXC1t8acUe2lLseoaYdgt51Nh6qotF7HyFCVB7ortwrg52KL5c92s9iJnUkaDHVERGboyq18/GvHJQDA+yPacfivFp0CXdHK2xGFJWr8J/56nZ+foSrC4z/9L9CteK47gjwcGqBSouox1BERmRmNRuDttSdRUqZB39ZeGN2xqdQlGT2ZTIbpUS0BlM/nV1BcpvdztYHu6t1At/K5Hgx0JAmGOiIiM7PycDIOX8uGvVKBT0eH8mpXPY3o0ARBHvbILizF8oNJej2nqkAX6MEhV5IGQx0RkRnJKijBF1vOAwBeHxzCc7rqwEohx/R+5b11P8ZdRVGpusb901VFeHxReaBr6mrHQEeSY6gjIjIjX2w+j9w7pWjbxBkTewRJXY7JGd2pKZq62iEzvxirDidXu9+pG7mI+WG/7irXFc92Z6AjyTHUERGZiaPXs7HqSHkQ+SSmPawU/ImvK2uFHNP6tQAALNh9BUm3Cyvt8+eJFDz64wGk5hahuZcDVj7HQEfGgd94IiIzoNYI/CP2NADg0Uh/RAa5S1yR6Xqssz+autohTVWEId/F4dcD11Cq1mDPxVt4ecVxvLziOIpKNegX4oXY6b0Q4M5AR8ZBJoQQUhdhilQqFVxcXJCbmwtnZ2epyyEiC/frgWv4YP0ZONtaYecb/TiFyQNKzirErDUn8PfVLACAnbUCd+45x+65h5rjraFtoJDzIhRqePpmDqtGrImIiBrArbxifL3tAgBg1tA2DHQGEOBuj+VTu+O3g9fx+ebzKCxRw83eGiPD/fBIJ3+EB7hKXSJRJQx1REQmbu6mc8grKkNYUxc82TVQ6nLMhlwuw9M9mmFQOx9cyShA12B3KK141hIZL4Y6IiITdvDqbaw7fhMyGfBxTCiHAxtAExc7NHGxk7oMolrxTw4iIhNVqtbg/T/OAAAe7xKICA4JElk0hjoiIhP164FruJCeBzd7a7w5JETqcohIYgx1REQmKKugBP/acQkA8ObQNnBzUEpcERFJjaGOiMgEfffXReQVlaFdE2c81jlA6nKIyAgw1BERmZhL6XlYdnfB+fdGtOXFEUQEgKGOiMjkfLLxHNQagUHtfNCzhafU5RCRkWCoIyIyIbsvZGDPxVuwVsjwzrC2UpdDREaEoY6IyESUqTX4dOM5AMDEHs0Q7OkgcUVEZEwY6oiITMSKQ0m4lJEPN3trvDygldTlEJGRsYhQN3r0aLi5uWHs2LF1eoyIyFjk3inFN9svAgBeG9QaLnbWEldERMbGIkLdK6+8gqVLl9b5MSIiYzFv5yVkF5aipbcj13cloipZRKiLioqCk5NTnR8jIjIG1zILsOTANQDAu8PbwkphET/dRFRHkv8yxMXFYeTIkfDz84NMJkNsbGylfebPn4/g4GDY2toiMjISe/fubfxCiYgkMnfzOZSqBR5q7YWoEG+pyyEiIyV5qCsoKEB4eDjmzZtX5eOrVq3CjBkz8O677+L48ePo06cPoqOjkZSUpNsnMjISoaGhlW4pKSmN9TaIiBpE/JXb2HomHQq5DO8N5xQmRFQ9K6kLiI6ORnR0dLWPf/PNN5gyZQqmTp0KAPjuu++wdetWLFiwAHPnzgUAHD16tMHrLC4uRnFxse6+SqVq8NckIsum1gh8svEsAODJroFo7cNTRYioepL31NWkpKQER48exeDBgytsHzx4MA4cONCotcydOxcuLi66W0AA11okooa19tgNnElRwcnWCq8Nai11OURk5Iw61GVmZkKtVsPHx6fCdh8fH6Slpel9nCFDhuDRRx/Fpk2b4O/vj8OHD+v12L1mz56N3Nxc3S05Obl+b4qISA/5xWX4ausFAMAr/VvB3UEpcUVEZOwkH37Vh0xWcbFqIUSlbTXZunVrvR67l42NDWxsbPR+TSKiB7Fw9xXcyitGkIc9nu4ZJHU5RGQCjLqnztPTEwqFolKvXEZGRqXeOyIic3Ez5w5+2nsVADA7ui1srBQSV0REpsCoQ51SqURkZCS2b99eYfv27dvRs2dPiaoiImpYX2w+j+IyDboFu2NIe/4BS0T6kXz4NT8/H5cvX9bdT0xMREJCAtzd3REYGIiZM2diwoQJ6Ny5M3r06IFFixYhKSkJ06ZNk7BqIqKGcSwpG+tPpEAmA/4xol2dTjUhIssmeag7cuQIoqKidPdnzpwJAJg4cSKWLFmCcePG4fbt2/joo4+QmpqK0NBQbNq0CUFBPMeEiMyLEAIfbyifwuTRSH+ENnWRuCIiMiUyIYSQughTpFKp4OLigtzcXDg7O0tdDhGZgT8SbuLVlQmwVyqw+41+8Ha2lbokIjIC+mYOoz6njojIUtwpUePLLeVTmLzYrwUDHRHVGUMdEZER+DHuCm7m3EFTVztM7dNc6nKIyAQx1BERSexmzh0s3HMFAPDOsLawteYUJkRUdwx1REQSm7vpHIpKy6cwGRbmK3U5RGSiGOqIiCR0KDELG06mQi4D3h/JKUyIqP4Y6oiIJKLWCMz58wwA4PGugWjvxylMiKj+GOqIiCSy+kgyzqSo4GRrhdcHtZa6HCIycQx1REQSyL1Tiq+3lk9hMmNga3g42khcERGZOoY6IiIJ/N+OS7hdUIIWXg54ugdXyCGiB8dQR0TUyC5n5OPXA9cAAO+PbA9rBX+KiejB8ZeEiKiRfbLxLMo0AgPaeKNvay+pyyEiM8FQR0TUiLadScPuC7dgrZDhvRHtpC6HiMwIQx0RUSMpKC7Dh+vLpzCZ2qc5gj0dJK6IiMwJQx0RUSP57q+LSMktQoC7HV7p30rqcojIzDDUERE1grMpKvyy/xoA4KNRobBTcn1XIjIshjoiogam0Qi8G3sKao3AsDBfRLXxlrokIjJDDHVERA1safw1HE/KgaONFd4f0V7qcojITDHUERE1oGuZBfh8y3kAwFtDQ+DrYitxRURkrhjqiIgaiEYj8Oaakygq1aBnCw881Y0rRxBRw2GoIyJqIEsOXMOha1lwUCrwxSMdIJfLpC6JiMwYQx0RUQO4cisfX24tH3adPawtAtztJa6IiMwdQx0RkYEVlarx0vLjKCrVoHdLTzzVLVDqkojIAjDUEREZ2EcbzuJcqgoeDkr887FwyGQcdiWihsdQR0RkQOtPpGD5wSTIZMC34yLg48yrXYmocTDUEREZyNVb+Zi99iQAYHq/lniotZfEFRGRJWGoIyIygNv5xZi05DAKStTo2swdMwZybVcialwMdURED6ioVI1nlx7B9duF8Hezww9PdYKVgj+vRNS4+KtDRPQANBqBmasTcCwpB862VlgyqQu8nGykLouILBBDHRFRPak1Au/GnsamU2mwVsiw6OnOaOntJHVZRGShrKQugIjIFJWqNXjjvyfwR0IKZDLg60fD0b25h9RlEZEFY6gjIqqj4rLyyYW3n02HlVyGb8dFYGS4n9RlEZGFY6gjIqqD5KxCvLziOBKSc6C0kmP+k50wsJ2P1GURETHUERHpa+uZNMz67wmoisrgbGuFBeMj0aulp9RlEREBYKgjIqpVhqoIX2+7gNVHbgAAIgJc8f0THRHgbi9xZURE/8NQR0RUjcKSMvwUl4gf466gsEQNAHjuoeaYNSQE1pyHjoiMDEMdEdF9LqTlYfnB61h3/CbyisoAAB0DXfHe8HaIDHKTuDoioqox1BGRxStVa3A8KQd7LmZg94VbOJOi0j3WzMMebwwJwfCwJpDJZBJWSURUM4Y6IrIIQgjkF5chJacIN7ILkZxViAvpeTiTosL5tDyUlGl0+yrkMgxq64MnuwWid0tPyOUMc0Rk/BjqjNTxpGyo7g771EQIUfs++r6onjsKPXfUozS999P3PejTHnU7np476nFEvdtD31eU4L+Xof876EsjBMrUAmUagTK15u7/3ndfo0FhiRqFxWoUlJShsESN/OIyFBSXIaewFJn5xSi+J7jdz83eGg+19kLf1l54qLUXPB251BcRmRaGOiP10YazOJ6UI3UZRGbHxc4a/m52CHCzR3MvB7T3c0F7P2cEutuzR46ITBpDnZEK9nSoMBxUE31P85FB/3+w9D+mgQ9Yh2MavEZA73OmDF1j+TEN+4akrFHv/zZ1+OxaKWSwksthJdf+fxmsFHJYK2RQyMsfc7BRwF5pBQelAvY2VnBQWsFeqYCbgxIeDkp4OCphr+TPHhGZJ/66GalvHouQugQiIiIyIZxoiYiIiMgMMNQRERERmQGGOiIiIiIzwFBHREREZAYY6oiIiIjMAEMdERERkRlgqCMiIiIyAwx1RERERGaAoY6IiIjIDDDUEREREZkBhjoiIiIiM8BQR0RERGQGGOqIiIiIzABDHREREZEZsJK6AFMlhAAAqFQqiSshIiIic6bNGtrsUR2GunrKy8sDAAQEBEhcCREREVmCvLw8uLi4VPu4TNQW+6hKGo0GKSkpcHJygkwmk7qcBqFSqRAQEIDk5GQ4OztLXY5k2A5sAy22Qzm2A9tAi+3QOG0ghEBeXh78/Pwgl1d/5hx76upJLpfD399f6jIahbOzs8V+We/FdmAbaLEdyrEd2AZabIeGb4Oaeui0eKEEERERkRlgqCMiIiIyAwx1VC0bGxt88MEHsLGxkboUSbEd2AZabIdybAe2gRbbwbjagBdKEBEREZkB9tQRERERmQGGOiIiIiIzwFBHREREZAYY6oiIiIjMAEMd1dvo0aPh5uaGsWPH1ukxc/b111+jffv2CA0NxW+//SZ1OZK4cOECIiIidDc7OzvExsZKXVajs7Ky0rXB1KlTpS5HEnl5eejSpQsiIiIQFhaGn376SeqSJGOJv4mW+J7v19jfAV79SvW2a9cu5Ofn49dff8WaNWv0fsxcnTp1ChMnTsSBAwcAAAMGDMDGjRvh6uoqbWESys/PR7NmzXD9+nU4ODhIXU6j8vT0RGZmptRlSEqtVqO4uBj29vYoLCxEaGgoDh8+DA8PD6lLa3SW+Jtoie/5fo39HWBPHdVbVFQUnJyc6vyYuTp37hx69uwJW1tb2NraIiIiAlu2bJG6LEmtX78eAwYMsLhAR+UUCgXs7e0BAEVFRVCr1bDUfgRL/E20xPd8v8b+DjDUmam4uDiMHDkSfn5+kMlkVQ5/zZ8/H8HBwbC1tUVkZCT27t3b+IU2ooZuk9DQUOzatQs5OTnIycnBzp07cfPmTQO+A8NozM/G6tWrMW7cuAes2PAaow1UKhUiIyPRu3dv7Nmzx0CVG1ZjtENOTg7Cw8Ph7++PN998E56engaq3nD4e1kZ26ScIdqhMb8DDHVmqqCgAOHh4Zg3b16Vj69atQozZszAu+++i+PHj6NPnz6Ijo5GUlKSbp/IyEiEhoZWuqWkpDTW2zCohm6Tdu3a4ZVXXkH//v0xevRodOnSBVZWVo319vTWWJ8NlUqF/fv3Y9iwYQ3+nuqqMdrg2rVrOHr0KBYuXIinn34aKpWqUd5bXTRGO7i6uuLEiRNITEzE8uXLkZ6e3ijvrS74e1mZIdrEHBiiHRr1OyDI7AEQv//+e4VtXbt2FdOmTauwrU2bNuLtt9+u07F37dolHnnkkTo/JrWGbBOtKVOmiA0bNtS3xEbRkO2wdOlS8dRTTz1oiQ2uMT4LQ4cOFYcPH65viY2iMdph2rRpYvXq1fUtsVFI9XtpzB6kTUz1PVfFEJ+Nhv4OsKfOApWUlODo0aMYPHhwhe2DBw/WneRvaQzVJhkZGQDKrwA9dOgQhgwZYtA6G5ohPxvGOvRaG0O0QXZ2NoqLiwEAN27cwNmzZ9G8eXOD19qQDNEO6enpuh5KlUqFuLg4hISEGLzWhsTfy8rYJuX0aYfG/g4Y39gQNbjMzEyo1Wr4+PhU2O7j44O0tDS9jzNkyBAcO3YMBQUF8Pf3x++//44uXbrU+pgxMlSbxMTEICcnBw4ODli8eLFRDr/WxFDtkJubi0OHDmHt2rWGLrHBGaINzp07h+effx5yuRwymQz/+te/4O7u3hDlNhhDtMONGzcwZcoUCCEghMBLL72EDh06NES5DaYxfi9Njb5tYk7vuSr6tENjfwdM618cMiiZTFbhvhCi0raabN26tV6PGbMHbRNz+Sv1QdvBxcXFKM+dqosHaYOePXvi1KlTDVFWo3uQdoiMjERCQkIDVNX4GvL30lTV1ibm+J6rUlM7NPZ3gMOvFsjT0xMKhaLSX5kZGRmV/uKwFGyTcmwHtoEW26Ec26Eytkk5Y2wHhjoLpFQqERkZie3bt1fYvn37dvTs2VOiqqTFNinHdmAbaLEdyrEdKmOblDPGduDwq5nKz8/H5cuXdfcTExORkJAAd3d3BAYGYubMmZgwYQI6d+6MHj16YNGiRUhKSsK0adMkrLphsU3KsR3YBlpsh3Jsh8rYJuVMrh0a7LpaktSuXbsEgEq3iRMn6vb54YcfRFBQkFAqlaJTp05iz5490hXcCNgm5dgObAMttkM5tkNlbJNyptYOXPuViIiIyAzwnDoiIiIiM8BQR0RERGQGGOqIiIiIzABDHREREZEZYKgjIiIiMgMMdURERERmgKGOiIiIyAww1BERERGZAYY6IiIiIjPAUEdEVIsPP/wQERERkr3+P/7xDzz33HN67fvGG2/glVdeaeCKiMgYcZkwIrJoMpmsxscnTpyIefPmobi4GB4eHo1U1f+kp6ejVatWOHnyJJo1a1br/hkZGWjRogVOnjyJ4ODghi+QiIwGQx0RWbS0tDTd/1+1ahXef/99XLhwQbfNzs4OLi4uUpQGAPjss8+wZ88ebN26Ve/nPPLII2jZsiW++OKLBqyMiIwNh1+JyKL5+vrqbi4uLpDJZJW23T/8+swzzyAmJgafffYZfHx84Orqijlz5qCsrAyzZs2Cu7s7/P398csvv1R4rZs3b2LcuHFwc3ODh4cHHn74YVy7dq3G+lauXIlRo0ZV2LZmzRqEhYXBzs4OHh4eGDhwIAoKCnSPjxo1CitWrHjgtiEi08JQR0RUDzt37kRKSgri4uLwzTff4MMPP8SIESPg5uaGgwcPYtq0aZg2bRqSk5MBAIWFhYiKioKjoyPi4uKwb98+ODo6YujQoSgpKanyNbKzs3H69Gl07txZty01NRVPPPEEJk+ejHPnzmH37t0YM2YM7h106dq1K5KTk3H9+vWGbQQiMioMdURE9eDu7o7/+7//Q0hICCZPnoyQkBAUFhbinXfeQatWrTB79mwolUrs378fQHmPm1wux7///W+EhYWhbdu2WLx4MZKSkrB79+4qX+P69esQQsDPz0+3LTU1FWVlZRgzZgyaNWuGsLAwvPjii3B0dNTt07RpUwCotReQiMyLldQFEBGZovbt20Mu/9/fxT4+PggNDdXdVygU8PDwQEZGBgDg6NGjuHz5MpycnCocp6ioCFeuXKnyNe7cuQMAsLW11W0LDw/HgAEDEBYWhiFDhmDw4MEYO3Ys3NzcdPvY2dkBKO8dJCLLwVBHRFQP1tbWFe7LZLIqt2k0GgCARqNBZGQkli1bVulYXl5eVb6Gp6cngPJhWO0+CoUC27dvx4EDB7Bt2zZ8//33ePfdd3Hw4EHd1a5ZWVk1HpeIzBOHX4mIGkGnTp1w6dIleHt7o2XLlhVu1V1d26JFCzg7O+Ps2bMVtstkMvTq1Qtz5szB8ePHoVQq8fvvv+seP336NKytrdG+ffsGfU9EZFwY6oiIGsFTTz0FT09PPPzww9i7dy8SExOxZ88evPrqq7hx40aVz5HL5Rg4cCD27dun23bw4EF89tlnOHLkCJKSkrBu3TrcunULbdu21e2zd+9e9OnTRzcMS0SWgaGOiKgR2NvbIy4uDoGBgRgzZgzatm2LyZMn486dO3B2dq72ec899xxWrlypG8Z1dnZGXFwchg0bhtatW+O9997DP//5T0RHR+ues2LFCjz77LMN/p6IyLhw8mEiIiMmhED37t0xY8YMPPHEE7Xuv3HjRsyaNQsnT56ElRVPmyayJOypIyIyYjKZDIsWLUJZWZle+xcUFGDx4sUMdEQWiD11RERERGaAPXVEREREZoChjoiIiMgMMNQRERERmQGGOiIiIiIzwFBHREREZAYY6oiIiIjMAEMdERERkRlgqCMiIiIyAwx1RERERGaAoY6IiIjIDPw/3V5cWggnnoIAAAAASUVORK5CYII=", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Plots the Diffusion Flux Into Reservoir Using Integrated Concentration from ROP Analysis\n", - "clf()\n", - "\n", - "plot(t_vals, F_vals)\n", - "\n", - "xscale(\"log\")\n", - "yscale(\"log\")\n", - "xlabel(\"Time (s)\")\n", - "ylabel(\"Diffusive Flux\")\n", - "title(\"Diffusive Flux of O=CO from ROP Integration\")\n", - "legend()\n", - "tight_layout()\n", - "gcf()" - ] - }, - { - "cell_type": "code", - "execution_count": 194, - "id": "c17074cd", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Net ROPs for species proton is: -0.00033551999999946436\n", - "Showing the reaction with 1 th highest ROP for species proton:\n", - "proton+CO2X<=>CHO2X\n", - "ROP = -0.0003354304417636066\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e14\n", - " n: Float64 0.0\n", - " Ea: Float64 39427.88604616099\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 2 th highest ROP for species proton:\n", - "proton+CO2X<=>CO2HX\n", - "ROP = -3.354304417687343e-8\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 75249.98822394594\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 3 th highest ROP for species proton:\n", - "proton+CO2HX<=>H2O+OCX\n", - "ROP = -2.5251650396860116e-8\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 24315.06048796024\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 4 th highest ROP for species proton:\n", - "proton+CO2HX<=>CH2O2X\n", - "ROP = -2.5251650396860116e-8\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 48898.20910952594\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 5 th highest ROP for species proton:\n", - "proton+CH2O2X<=>OC[O][Pt]\n", - "ROP = -5.340995748860065e-9\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.4999999999999992e10\n", - " n: Float64 0.0\n", - " Ea: Float64 89339.41281822574\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 6 th highest ROP for species proton:\n", - "proton+CH2O2X<=>O[CH](O)[Pt]\n", - "ROP = -1.6840107226936788e-10\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 100905.29159122657\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 7 th highest ROP for species proton:\n", - "proton+OCX<=>CHOX\n", - "ROP = -1.8813818190969007e-12\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 34575.959267526974\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 8 th highest ROP for species proton:\n", - "proton+CHO2X<=>CH2O2X\n", - "ROP = -6.123697433131493e-13\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 3012.3559299445733\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 9 th highest ROP for species proton:\n", - "proton+HX<=>[H][H].[Pt]\n", - "ROP = -1.2927699258808778e-16\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.4999999999999992e10\n", - " n: Float64 0.0\n", - " Ea: Float64 24730.15936869003\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 10 th highest ROP for species proton:\n", - "proton+O=C[C](=O)[Pt]<=>O=CC=O.[Pt]\n", - "ROP = -6.585377640524527e-17\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 55202.104864872985\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 11 th highest ROP for species proton:\n", - "proton+O=C[C](=O)[Pt]<=>OCX+C=O\n", - "ROP = -6.585377640524527e-17\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 43114.76623676546\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 12 th highest ROP for species proton:\n", - "proton+O=C(O)CO.[Pt]<=>OCC(O)[O][Pt]\n", - "ROP = -3.9804324590550245e-17\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.4999999999999992e10\n", - " n: Float64 0.0\n", - " Ea: Float64 76346.84204039437\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 13 th highest ROP for species proton:\n", - "proton+CHOX<=>CH2OX\n", - "ROP = -5.384206665395002e-18\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 54779.82771855408\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 14 th highest ROP for species proton:\n", - "proton+CHOX<=>O[CH]=[Pt]\n", - "ROP = -5.384206665221959e-18\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 44067.01463173538\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 15 th highest ROP for species proton:\n", - "proton+O=CC(=O)O.[Pt]<=>O=C(O)[CH](O)[Pt]\n", - "ROP = -2.88668537891958e-18\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 59798.56901402724\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plotROP(ssys, \"proton\",1e3;N=15,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 184, - "id": "6de2ef72", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Net ROPs for species H2 is: 1.3820056045833363e-9\n", - "Showing the reaction with 1 th highest ROP for species H2:\n", - "vacantX+vacantX+H2<=>HX+HX\n", - "ROP = 1.3819995730561872e-9\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 5.747808164985876e9\n", - " n: Float64 0.5000000001622984\n", - " Ea: Float64 35649.812671494205\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 2 th highest ROP for species H2:\n", - "vacantX+H2<=>[H][H].[Pt]\n", - "ROP = 6.031527149174566e-15\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 14313.541777104389\n", - " n: Float64 0.4999999999999383\n", - " Ea: Float64 10385.942601612687\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plotROP(ssys, \"H2\",sol.t[end];N=15,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 185, - "id": "2eefe3c5", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Net ROPs for species HX is: -1.41555263151845e-13\n", - "Showing the reaction with 1 th highest ROP for species HX:\n", - "HX+CO2<=>CHO2X\n", - "ROP = 9.093140564774802e-9\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 38294.07968295473\n", - " n: Float64 0.49999999999999933\n", - " Ea: Float64 73060.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 2 th highest ROP for species HX:\n", - "HX+CO2HX<=>vacantX+CH2O2X\n", - "ROP = -6.88286645959641e-9\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 2.308e18\n", - " n: Float64 0.0\n", - " Ea: Float64 70434.29992477236\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 3 th highest ROP for species HX:\n", - "vacantX+vacantX+H2<=>HX+HX\n", - "ROP = -2.7639991461123745e-9\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 5.747808164985876e9\n", - " n: Float64 0.5000000001622984\n", - " Ea: Float64 35649.812671494205\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 4 th highest ROP for species HX:\n", - "HX+CO2<=>CO2HX\n", - "ROP = 5.533309101833815e-10\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 38294.07968295473\n", - " n: Float64 0.49999999999999933\n", - " Ea: Float64 73060.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 5 th highest ROP for species HX:\n", - "HX+O=CO<=>OC[O][Pt]\n", - "ROP = 3.123817479000639e-13\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 18723.002382665985\n", - " n: Float64 0.4999999999999415\n", - " Ea: Float64 73060.00000000036\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 6 th highest ROP for species HX:\n", - "H2OX+OCX<=>HX+CO2HX\n", - "ROP = -2.145494601980981e-13\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 5.909597697728364e14\n", - " n: Float64 0.9956894270665808\n", - " Ea: Float64 123451.6909068545\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 7 th highest ROP for species HX:\n", - "vacantX+O=C(O)CO.[Pt]<=>HX+O=C(O)[CH](O)[Pt]\n", - "ROP = 1.2671176159960639e-13\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 6.906974867429743e13\n", - " n: Float64 0.8828711760583561\n", - " Ea: Float64 70815.82714089446\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 8 th highest ROP for species HX:\n", - "HX+O=CO<=>O[CH](O)[Pt]\n", - "ROP = 2.921497588299365e-14\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 18723.002382665985\n", - " n: Float64 0.4999999999999415\n", - " Ea: Float64 73060.00000000036\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 9 th highest ROP for species HX:\n", - "vacantX+OCO.[Pt]<=>HX+O[CH](O)[Pt]\n", - "ROP = -4.2266690402153455e-15\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 6.906974867429743e13\n", - " n: Float64 0.8828711760583561\n", - " Ea: Float64 99301.33381634601\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 10 th highest ROP for species HX:\n", - "vacantX+O=COC=O.[Pt]<=>HX+O=CO[C](=O)[Pt]\n", - "ROP = 3.674630016487765e-15\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 6.906974867429743e13\n", - " n: Float64 0.8828711760583561\n", - " Ea: Float64 70815.82714089446\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 11 th highest ROP for species HX:\n", - "HX+CHO2X<=>vacantX+CH2O2X\n", - "ROP = -3.058335824544289e-16\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.424e18\n", - " n: Float64 0.0\n", - " Ea: Float64 87801.66155005872\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 12 th highest ROP for species HX:\n", - "HX+CHOX<=>vacantX+CH2OX\n", - "ROP = -1.9861975072950406e-16\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 1.932e17\n", - " n: Float64 0.0\n", - " Ea: Float64 45348.110910469884\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 13 th highest ROP for species HX:\n", - "proton+HX<=>[H][H].[Pt]\n", - "ROP = -1.2927699258808778e-16\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.4999999999999992e10\n", - " n: Float64 0.0\n", - " Ea: Float64 24730.15936869003\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 14 th highest ROP for species HX:\n", - "OCX+CH2O2X<=>HX+O=CO[C](=O)[Pt]\n", - "ROP = 3.5972082014202306e-17\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 2.954798848864182e14\n", - " n: Float64 0.9956894270665808\n", - " Ea: Float64 129866.88883486908\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 15 th highest ROP for species HX:\n", - "vacantX+O=CCO.[Pt]<=>HX+O=C[CH](O)[Pt]\n", - "ROP = -3.374046825045264e-17\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 6.906974867429743e13\n", - " n: Float64 0.8828711760583561\n", - " Ea: Float64 70815.82714089446\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plotROP(ssys, \"HX\",sol.t[end];N=15,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 186, - "id": "03ec23c9", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Net ROPs for species OCX is: 2.715205972671711e-8\n", - "Showing the reaction with 1 th highest ROP for species OCX:\n", - "proton+CO2HX<=>H2O+OCX\n", - "ROP = 2.5251650396860116e-8\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 24315.06048796024\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 2 th highest ROP for species OCX:\n", - "HOX+OCX<=>vacantX+CO2HX\n", - "ROP = 1.93203864347582e-9\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.02e14\n", - " n: Float64 0.0\n", - " Ea: Float64 11500.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 3 th highest ROP for species OCX:\n", - "vacantX+vacantX+CO2<=>OX+OCX\n", - "ROP = -2.9548607836027356e-11\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 5.3487086644171274e8\n", - " n: Float64 0.5000000000002018\n", - " Ea: Float64 53637.00288687614\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 4 th highest ROP for species OCX:\n", - "OX+O=C[C](=O)[Pt]<=>OCX+CHO2X\n", - "ROP = -2.318942462079874e-12\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 3.298e17\n", - " n: Float64 0.0\n", - " Ea: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 5 th highest ROP for species OCX:\n", - "CHOX+CHO2X<=>OCX+CH2O2X\n", - "ROP = 1.8952661516718367e-12\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 7.475e18\n", - " n: Float64 0.0\n", - " Ea: Float64 57891.205417621124\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 6 th highest ROP for species OCX:\n", - "proton+OCX<=>CHOX\n", - "ROP = -1.8813818190969007e-12\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 34575.959267526974\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 7 th highest ROP for species OCX:\n", - "H2OX+OCX<=>HX+CO2HX\n", - "ROP = 2.145494601980981e-13\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 5.909597697728364e14\n", - " n: Float64 0.9956894270665808\n", - " Ea: Float64 123451.6909068545\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 8 th highest ROP for species OCX:\n", - "OCX+O=C(O)O.[Pt]<=>CO2HX+CO2HX\n", - "ROP = 3.7134895214874147e-14\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 5.909597697728364e14\n", - " n: Float64 0.9956894270665808\n", - " Ea: Float64 123451.6909068545\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 9 th highest ROP for species OCX:\n", - "vacantX+O=CO[C](=O)[Pt]<=>OCX+CHO2X\n", - "ROP = -3.558543265454739e-14\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 1.46e20\n", - " n: Float64 -0.213\n", - " Ea: Float64 54300.00000000001\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 10 th highest ROP for species OCX:\n", - "OX+CHOX<=>HOX+OCX\n", - "ROP = 1.0429942215949378e-14\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 3.298e17\n", - " n: Float64 0.0\n", - " Ea: Float64 18530.448633130174\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 11 th highest ROP for species OCX:\n", - "CO2HX+O[CH]=[Pt]<=>OCX+O[CH](O)[Pt]\n", - "ROP = -5.660535786236887e-16\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 1.39e17\n", - " n: Float64 0.101\n", - " Ea: Float64 19000.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 12 th highest ROP for species OCX:\n", - "OCX+CH2O2X<=>CHOX+CO2HX\n", - "ROP = -4.0261617064222e-16\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 2.954798848864182e14\n", - " n: Float64 0.9956894270665808\n", - " Ea: Float64 123451.6909068545\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 13 th highest ROP for species OCX:\n", - "OCX+CH2O2X<=>CHOX+CO2HX\n", - "ROP = -4.0261617064222e-16\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 2.954798848864182e14\n", - " n: Float64 0.9956894270665808\n", - " Ea: Float64 123451.6909068545\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 14 th highest ROP for species OCX:\n", - "OCX+CH2O2X<=>CHOX+CO2HX\n", - "ROP = -4.0261617064222e-16\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 2.954798848864182e14\n", - " n: Float64 0.9956894270665808\n", - " Ea: Float64 123451.6909068545\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 15 th highest ROP for species OCX:\n", - "OCX+CH2O2X<=>CHOX+CO2HX\n", - "ROP = -4.0261617064222e-16\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 2.954798848864182e14\n", - " n: Float64 0.9956894270665808\n", - " Ea: Float64 123451.6909068545\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plotROP(ssys, \"OCX\",sol.t[end];N=15,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 187, - "id": "1ca256e1", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Net ROPs for species O=CO is: 8.476473115738726e-5\n", - "Showing the reaction with 1 th highest ROP for species O=CO:\n", - "vacantX+O=CO<=>CH2O2X\n", - "ROP = 8.476473083352974e-5\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 37446.004765314996\n", - " n: Float64 0.4999999999999999\n", - " Ea: Float64 1.3922895777811643e-12\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 2 th highest ROP for species O=CO:\n", - "HX+O=CO<=>OC[O][Pt]\n", - "ROP = 3.123817479000639e-13\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 18723.002382665985\n", - " n: Float64 0.4999999999999415\n", - " Ea: Float64 73060.00000000036\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 3 th highest ROP for species O=CO:\n", - "HX+O=CO<=>O[CH](O)[Pt]\n", - "ROP = 2.921497588299365e-14\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 18723.002382665985\n", - " n: Float64 0.4999999999999415\n", - " Ea: Float64 73060.00000000036\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 4 th highest ROP for species O=CO:\n", - "vacantX+vacantX+O=CO<=>HOX+CHOX\n", - "ROP = -1.8265198082419342e-14\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 1.9613453155920184e8\n", - " n: Float64 0.5000000000001102\n", - " Ea: Float64 64793.916722181995\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 5 th highest ROP for species O=CO:\n", - "CHOX+O=CO<=>O=CO[CH](O)[Pt]\n", - "ROP = 5.217562174039828e-16\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 18723.002382665985\n", - " n: Float64 0.4999999999999415\n", - " Ea: Float64 73060.00000000036\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 6 th highest ROP for species O=CO:\n", - "CHOX+O=CO<=>O=CC(O)[O][Pt]\n", - "ROP = 2.886527441236474e-18\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 18723.002382665985\n", - " n: Float64 0.4999999999999415\n", - " Ea: Float64 73060.00000000036\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 7 th highest ROP for species O=CO:\n", - "vacantX+vacantX+O=CO<=>HX+CO2HX\n", - "ROP = 1.3345908379323752e-18\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 2.6151270873673162e9\n", - " n: Float64 0.5000000000044722\n", - " Ea: Float64 106299.149947054\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 8 th highest ROP for species O=CO:\n", - "vacantX+vacantX+O=CO<=>HX+CHO2X\n", - "ROP = 1.9851927717315167e-20\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 2.6151270873673105e9\n", - " n: Float64 0.5000000000044725\n", - " Ea: Float64 123691.83372953309\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 9 th highest ROP for species O=CO:\n", - "vacantX+vacantX+O=CO<=>OX+O[CH]=[Pt]\n", - "ROP = 8.332723498689105e-24\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 2.6151270874519193e8\n", - " n: Float64 0.5000000000003122\n", - " Ea: Float64 122254.72655857299\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 10 th highest ROP for species O=CO:\n", - "O=CO+O[CH2][Pt]<=>OCC(O)[O][Pt]\n", - "ROP = 3.9224693678735136e-24\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 18723.002382665985\n", - " n: Float64 0.4999999999999415\n", - " Ea: Float64 73060.00000000036\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 11 th highest ROP for species O=CO:\n", - "proton+O=C(O)[O][Pt]<=>OX+O=CO\n", - "ROP = 1.7652769954822112e-24\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 67167.70685265539\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 12 th highest ROP for species O=CO:\n", - "proton+O=C(O)[CH](O)[Pt]<=>O[CH]=[Pt]+O=CO\n", - "ROP = 4.628860175347641e-29\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 107634.68955395499\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 13 th highest ROP for species O=CO:\n", - "proton+O=CO[CH](O)[Pt]<=>O[CH]=[Pt]+O=CO\n", - "ROP = 4.627997940285419e-31\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 36720.090763490094\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 14 th highest ROP for species O=CO:\n", - "proton+O=CO[C](=O)[Pt]<=>OCX+O=CO\n", - "ROP = 1.0326527802898383e-31\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 40939.69892156377\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 15 th highest ROP for species O=CO:\n", - "proton+O=CO[CH2][Pt]<=>CH2X+O=CO\n", - "ROP = 1.9200351016986804e-38\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 51229.76575324847\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plotROP(ssys, \"O=CO\",sol.t[end];N=15,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 188, - "id": "64238bc0", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Net ROPs for species CH2O2X is: 5.373807144860894e-5\n", - "Showing the reaction with 1 th highest ROP for species CH2O2X:\n", - "CO2HX+CO2HX<=>CO2X+CH2O2X\n", - "ROP = 0.0001265492070158032\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 89323.26691949538\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 2 th highest ROP for species CH2O2X:\n", - "vacantX+O=CO<=>CH2O2X\n", - "ROP = -8.476473083352974e-5\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 37446.004765314996\n", - " n: Float64 0.4999999999999999\n", - " Ea: Float64 1.3922895777811643e-12\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 3 th highest ROP for species CH2O2X:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = 2.961675818402313e-6\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 72182.65101792177\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 4 th highest ROP for species CH2O2X:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = 2.961675818402313e-6\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 72182.65101792177\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 5 th highest ROP for species CH2O2X:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = 2.961675818402313e-6\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 72182.65101792177\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 6 th highest ROP for species CH2O2X:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = 2.961675818402313e-6\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 72182.65101792177\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 7 th highest ROP for species CH2O2X:\n", - "CHO2X+CHO2X<=>CO2X+CH2O2X\n", - "ROP = 6.931314469345391e-8\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 55042.035116348176\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 8 th highest ROP for species CH2O2X:\n", - "proton+CO2HX<=>CH2O2X\n", - "ROP = 2.5251650396860116e-8\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 48898.20910952594\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 9 th highest ROP for species CH2O2X:\n", - "CO2HX+OC[O][Pt]<=>CH2O2X+CH2O2X\n", - "ROP = 1.0358963852059127e-8\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 8.36e17\n", - " n: Float64 0.0\n", - " Ea: Float64 44385.12724460462\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 10 th highest ROP for species CH2O2X:\n", - "HX+CO2HX<=>vacantX+CH2O2X\n", - "ROP = 6.88286645959641e-9\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 2.308e18\n", - " n: Float64 0.0\n", - " Ea: Float64 70434.29992477236\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 11 th highest ROP for species CH2O2X:\n", - "proton+CH2O2X<=>OC[O][Pt]\n", - "ROP = -5.340995748860065e-9\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.4999999999999992e10\n", - " n: Float64 0.0\n", - " Ea: Float64 89339.41281822574\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 12 th highest ROP for species CH2O2X:\n", - "CO2HX+O[CH](O)[Pt]<=>CH2O2X+CH2O2X\n", - "ROP = 3.442725261910665e-10\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 8.36e17\n", - " n: Float64 0.0\n", - " Ea: Float64 35099.2254927765\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 13 th highest ROP for species CH2O2X:\n", - "CHO2X+OC[O][Pt]<=>CH2O2X+CH2O2X\n", - "ROP = 2.4243448769609086e-10\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 8.36e17\n", - " n: Float64 0.0\n", - " Ea: Float64 27244.51134303102\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 14 th highest ROP for species CH2O2X:\n", - "proton+CH2O2X<=>O[CH](O)[Pt]\n", - "ROP = -1.6840107226936788e-10\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 100905.29159122657\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 15 th highest ROP for species CH2O2X:\n", - "CHO2X+O[CH](O)[Pt]<=>CH2O2X+CH2O2X\n", - "ROP = 8.057131492050207e-12\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 8.36e17\n", - " n: Float64 0.0\n", - " Ea: Float64 17958.609591202912\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n" - ] - }, - { - "data": { - "image/png": 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HD3H//n2VK0cN+eyzz9CxY0fhXXQ9evTArFmzMHnyZIX3vDVWREQELC0t4eLigu3btyMrKwvZ2dnYtm0bnJ2dUVpaColEgi1btiArKwujR4/G+fPnUVBQgL1798LLywt9+vQR3pf35MkTDB48GE+fPsXWrVtRUlIijLmh31QpM2fOHNTU1GDZsmUAgPbt22PFihWYOXOm0t0ZjY2NMW3aNJw7dw5XrlyBk5MTZs2ahU8++UQoo6+vr7CaVN9K4bRp0zB9+nTY2tri119/xaVLlxAcHIzWrVsrtO/i4oJZs2bhiy++wKxZs3DmzBnk5+fj559/xgcffIDY2FgAQEhICHr16gUvLy/s3bsXBQUFuHDhAkaPHo1r165h69atQpAYGRmJsLAwbNu2DdbW1sJ8lpaWvvI8NUZwcDD69u2L9957D9999x0yMjJw8+ZN7NmzBy4uLsjOzm5SfbXB3IwZMzB69GhhHHXfzdcc5oUxxhhj7E3Ary2ox7179/DNN9/ghx9+wL1799C6dWt0794dISEhwiYRaWlpiIiIwJkzZ/Ds2TPY2tpiwoQJCA4OFjb6iImJQUBAgNI2aqe/sa8t2L59O6ZOnYr09HTRI2cVFRXo3r07evbsKdrJsVZDry0AXuw0uHTpUuzfvx/5+fkwNjZGly5dEBgYiJEjRwo30JmZmfjqq6+QkpKCkpIStG/fHuPGjcPcuXMhlUoB/P+t6pW5deuW8Nulxry2IDU1Fe+99x5SUlLw7rvvisoNGTIEVVVVOHHiRIO/86qpqUFOTo7w6GhT5eTkwNraukm7dO7ZswffffcdLl26hJqaGtjY2GDMmDEICgoSdrosKyvDkiVLsHv3buTn50NfXx8DBgzAl19+ic6dOwt1WVtbIz8/X6GN8PBwfPnll688Tw29tgB4sToZFRWFnTt3Ijs7G1KpFJ06dcKkSZMwfvx4qKurN/q1Bf7+/kJAW5ebm5vo+nzd86IMv7aAsdeDX1vAGHsTvSmvLeCAjjHGGokDOsZeDw7oGGNvojcloONHLhljjDHGGGOsmeKAjjHGGGOMMcaaKQ7oGGOMMcYYY6yZ4heLM8YYY+yN9lf+ToUxxpo7XqFjjDHGGGOMsWaKAzrGGGOMMcYYa6Y4oGOMMcYYY4yxZooDOsYYY4wxxhhrpnhTFMYYe4PwC5QZU8SbojDGmGq8QscYY4wxxhhjzRQHdIwxxhhjjDHWTHFAxxhjjDHGGGPNFAd0jDHGGGOMMdZMcUDHXitra2usWrVKlLZ+/XoYGRnh9u3bovTp06fD3t4eZWVlr9zeDz/8AHd3d+jr60MqlaJnz56IiYl55fpqVVRUIDIyEk5OTpBKpWjVqhX69u2L6OhoVFZWCuVu376NiRMnol27dtDU1ISVlRU+//xzPHr06A/34a+Uk5ODgIAAWFhYQEtLC2+99RbGjRuHX3/9VSgjkUhw8OBBhXP9/f3h7e0tfF6yZAl69uwJfX19mJqawtvbGzdu3FA47+rVq/jwww/RunVraGlpwc7ODgsWLBB9/0VFRQgKCkLHjh0hlUrRvn17zJgxA3K5XCiTkZEBLS0tHD58WFT//v37oa2tjStXrvyBmWGMMcYYe704oGNvnKlTp6JXr16YOHGikPbLL79g06ZNiImJgVQqVXqetbU1UlJSVNa7du1ajBw5Eq6urjh37hwuX76Mjz76CFOmTMG//vWvV+5vRUUFhgwZgqVLl2Ly5Mk4ffo0zp8/j8DAQKxduxZXr14FANy8eRM9evSATCbDrl27kJOTg40bN+Lnn39Gnz59UFRU1Og27927h6qqqlfqb3FxMUpKShpd/tdff0X37t0hk8mwadMmZGVlISEhAQ4ODvjiiy+a3H5qaioCAwNx9uxZHD9+HFVVVRg8eDCePn0qlDl79ixcXFxQUVGBH3/8ETKZDBEREYiNjcWgQYNQUVEBACgsLERhYSGWL1+OzMxMxMTEICkpSXTtODk5YcGCBZg8ebIQOD948ABTpkzBV199hc6dOzd5DIwxxhhjbwoJEdHr7gT7823atAmLFi3C7du30aLF/4/bR4wYAWNjYyxcuBChoaE4e/Ysnj59ik6dOmHJkiXw8PAQypaXl2PBggXYtWsXHjx4gPbt22POnDmYOHEiqqurMXnyZPzyyy+4f/8+2rdvj2nTpuHzzz8Xzvf390dxcTHeffddrFixAhUVFfjoo4+watUqaGhowN3dHampqaJ+116Ot2/fRpcuXbB06VJ8/PHH6NKlC8aOHYvIyEiVY7a2tkZMTAzc3d0V8m7fvg0bGxsEBQVhxYoVory1a9dixowZQhDRVJGRkZg7dy5+/fVXvPPOO6K8yspKVFRUQFdXF0OHDsWVK1cgk8mgo6MjlLl//z5sbGzg6+uLDRs2qGzn+fPnOHToEGJjY/HTTz/h0aNHMDQ0bHJ/U1NTMXToUIwaNQp+fn547733RNdIXUSELl26QFtbG+fPn1coV1xcDCMjIwAvVugSEhJEq3HA/78OlK3eAcDDhw9hamqK1NRU9O/fH0SEzp07QyqV4ty5c6I2MzIy8M4772DJkiWYPXu20vr27t0LHx8fPH36FOrqL97MUl1djT59+qBDhw7YvXs33n//ffzf//0f0tLSoKam1ohZe6GkpASGhoaQy+UwMDBo9HlNwa8tYEwRv7aAMfZP05R7Dl6h+y/1wQcf4Pfff0dycrKQ9vjxYxw7dgzjx49HaWkphg0bhhMnTuDSpUsYMmQIvLy8UFBQIJT39fXF7t27sWbNGly7dg0bN26Enp4eAKCmpgYWFhbYs2cPsrKysHDhQsybNw979uwR9SM5ORm5ublITk5GbGwsYmJihEccDxw4AAsLCyxatAj37t3DvXv3hPMsLS0RFRWFmTNnwsfHB3p6eli8ePErz8e+fftQWVmpdCXus88+g56eHnbt2iWk6enp1XsMHTpUKBsXFwcPDw+FYA4ANDQ0oKuri6KiIhw7dgzTpk0TBXMAYGZmhvHjxyM+Ph7K/n3lzJkzmDJlCtq2bYvQ0FC8/fbbSE9PFwVzTelv//79cfToUWhpaWHMmDGwsrLCvHnzlD72mJ6ejqtXr+KLL75QGvTVBnN/RO3jkSYmJkKbWVlZCA0NVWjTyckJHh4eou9KWX0GBgZCMAcAampqiI2NxaFDh/Dxxx/j2LFjiImJaTCYKy8vR0lJiehgjDHGGHuT8IvF/0uZmJjA09MTO3fuxHvvvQfgxcqFiYkJ3nvvPaipqcHJyUko//XXXyMhIQGHDx/G9OnTIZPJsGfPHhw/flxYtevQoYNQXkNDA1999ZXw+a233sLp06exZ88efPjhh0K6sbEx1q1bBzU1NTg4OGD48OH4+eefMWnSJJiYmEBNTQ36+vowMzNTGENAQAC+//57HDlyBOfOnYOWltYrz4dMJoOhoSHatm2rkKepqYkOHTpAJpMJaenp6fXWVzcoy87OVroqWFd2djaICJ06dVKa36lTJzx+/FhYrbpz5w62b9+O2NhY3LlzB++//z7i4+Ph4eGhNLBqSn8lEgnc3Nzg5uaGdevW4eDBg9i+fTu+/fZbdO/eHX5+fvj4449haGiI7OxsAICDg0O99dcaN26cQpBUXl6O4cOV/+s6ESE0NBTvvvuu8Ohj7fdQ31ydOnVKad6jR4+wePFifPbZZ0rPCw4OxtKlS7Fs2TLY29s3OJ4lS5aIrnPGGGOMsTcNB3T/xcaPH4/Jkydj/fr10NLSQlxcHD766COoqanh6dOn+Oqrr/DDDz+gsLAQVVVVePbsmbBCl56eDjU1Nbi5uamsf+PGjdiyZQvy8/Px7NkzVFRUwNnZWVTm7bffFt3gt23bFpmZmY3qf0ZGBn777TdIpVKkpaWhV69eovwpU6bg3//+t/C5rKwMQ4cOFbWXlZWF9u3bN9gWEUEikQifbW1tG9VHZee+itqVudp6wsLCEBsbi1GjRuHMmTPC6pUqTelvXTo6Ohg3bhzGjRsHmUyGcePGYdq0aSgvL0dwcLBCvxoSFRUlemwXAGbPno3q6mql5adPn47Lly+rDNCUUTXfJSUlGD58OBwdHREeHq6QX1paivj4eOF6mjVrVoNtzZ07F6GhoaI2LC0tG91XxhhjjLG/Gj9y+V/My8sLNTU1+PHHH3H79m2kpaXBx8cHADBz5kzs378f33zzDdLS0pCeno4uXboIm028/Fjgy/bs2YOQkBBMmDABP/30E9LT0xEQECCcX0tDQ0P0WSKRoKampsG+V1RUwNfXF+PGjcOmTZsQFhYmWkEDgEWLFiE9PV042rVrhy1btiikAYC9vT3kcjkKCwuVtnXz5k3Y2dkJaU15hNHe3h7Xrl2rdzy2traQSCTIyspSmn/9+nUYGxujVatWAF4EdHPmzMG5c+dgb2+P6dOn49y5cyrrb0p/66qqqsLRo0cxbtw4ODs7o7y8HMuWLcP48eOFsQFocHy1zMzMYGtrKzr09fWVlg0KCsLhw4eRnJwMCwsLIb22zfrmqu53BQBPnjyBp6cn9PT0kJCQoHDdAS+ueU1NTZw+fRo///wztm/f3uB4tLS0YGBgIDoYY4wxxt4kvEL3X0xHRwejRo1CXFwccnJyYG9vj+7duwMA0tLS4O/vj/fffx/Ai9WLvLw84dwuXbqgpqYGqampCisutee7urpi2rRpQlpubm6T+6ipqal09WbRokV49OgRVq9eDSMjI+zbtw8BAQFIS0sTHjk0NTWFqampcI66ujrMzc2VrlaNHj0as2bNwooVKxQ2Rdm4cSOePn2KcePGCWlNeYTx448/xrx583Dp0iWF39FVVVWhvLwcLVu2xKBBg7B+/XqEhIQobIoSFxcHX19fYeXJ1tYWS5YswTfffIMTJ04gNjYWAwYMgIWFBT755BP4+PjgrbfeeqX+AsClS5ewfft27Nq1C1VVVRg3bhxOnjyJHj16iMo5OzvD0dERK1aswNixY+vdFKWxiAhBQUFISEhASkqKaBy1bTo4OCAqKgofffSRwqYoJ06cwJIlS4S0kpISDBkyRHg1gba2tkKbx48fx5YtW5CWlgYnJydEREQgODgYgwYNUvoYLmOMMcZYc8ErdP/lxo8fjx9//BHbtm0TVueAFwHDgQMHkJ6ejoyMDHz88ceilTNra2v4+flhwoQJOHjwIG7duoWUlBRh0xNbW1v8+uuvOHbsGGQyGRYsWIALFy40uX/W1tY4efIk7t69i99//x3Ai23yly1bhi1btgjBwsaNG3H9+nVERUW90jy0b98ekZGRWLVqFebPn4/r168jNzcXK1euxKxZs/DFF1+Idrh8eZXp5cPc3FwoGxwcjL59++K9997Dd999h4yMDNy8eRN79uyBi4uL8Du0devWoby8HEOGDMHJkydx+/ZtJCUlYdCgQTA3N8c333yj0O8WLVpg8ODBiIuLw/379zFr1iz89NNPsLW1FW3Q0ZT+pqWlwcXFBTdv3sT69etRWFiItWvXKgRzwIsV1ejoaMhkMvTv3x+JiYm4efMmLl++jG+++QYjR45s8ncRGBiIf//739i5cyf09fVx//593L9/H8+ePRPa3LJlC7KysjB69GicP38eBQUF2Lt3L7y8vNCnTx8EBwcDeLEyV/vKg61bt6KkpESor/YfCkpKSjBx4kT861//Qu/evQEAM2bMwNtvv43Jkyc3uf+MMcYYY28SDuj+yw0cOBAmJia4ceMGPv74YyE9KioKxsbGcHV1hZeXF4YMGYJu3bqJzt2wYQPGjBmDadOmwcHBAZMmTRLeFTZlyhSMGjUKY8eOhYuLCx49eiRarWusRYsWIS8vDzY2NmjdujXKy8vh5+eHgIAAeHp6CuXMzMywdu1ahIWFKd2NsTFCQkKQkJCAtLQ09OjRA507d8bOnTuxYcMGLF++/JXqBF48lnf8+HHMmjULmzZtQu/evdGzZ0+sWbMGM2bMEDb7sLOzw6+//gobGxuMHTsWNjY2mDx5MgYMGNCo38kZGBjg008/RVpamsKrD5rC0dERd+/exaFDhzBq1ChoamrWW75Xr15CvydNmoROnTphxIgRuHr1qsJL4Rtjw4YNkMvlcHd3R9u2bYUjPj5eKNO3b1+cPXsWampqGDZsGGxtbTF37lz4+fnh+PHjwgY5v/32G86dO4fMzEzY2tqK6qt9MX1wcDAMDQ1Fm5u0aNEC0dHR+OWXXxr16CVjjDHG2JuK30PHGGONxO+hY+z14PfQMcb+afg9dIwxxhhjjDH2D8ABHWOMMcYYY4w1U7zLJWOMvUH40TLGGGOMNQWv0DHGGGOMMcZYM8UBHWOMMcYYY4w1UxzQMcYYY4wxxlgzxQEdY4wxxhhjjDVTvCkKY4wxxt5o9b2fkTcSYoz90/EKHWOMMcYYY4w1UxzQMcYYY4wxxlgzxQEdY4wxxhhjjDVTHNAxxhhjjDHGWDPFAV097t+/j6CgIHTo0AFaWlqwtLSEl5cXfv75ZwCAtbU1Vq1apXDel19+CWdnZ1FaUVERgoODYW1tDU1NTbRt2xYBAQEoKCgQlVuyZAl69uwJfX19mJqawtvbGzdu3BDyS0tLYWNjg9DQUNF5eXl5MDAwwJYtW155vCUlJZg/fz4cHBygra0NMzMzeHh44MCBAyAiodzVq1fx4YcfonXr1tDS0oKdnR0WLFiAsrIy0XiDgoLQsWNHSKVStG/fHjNmzIBcLhe1KZFIcPDgQYW++Pv7w9vbGwBQXV0NV1dXjB49WlRGLpfD0tISYWFhrzzmv9r+/fvh7u4OQ0ND6OnpoWvXrli0aBGKioqEMs+ePUN4eDg6duwILS0ttGrVCmPGjMHVq1dFdW3evBn9+vWDsbExjI2N4eHhgfPnzwv5f+U8VVRUIDIyEk5OTpBKpWjVqhX69u2L6OhoVFZWAhB/Z3WlpKRAIpGguLhY+Dxy5Ei0bdsWurq6cHZ2RlxcnMJ5zWFeGGOMMcZeNw7oVMjLy0P37t3xyy+/IDIyEpmZmUhKSsKAAQMQGBjYpLqKiorQu3dvnDhxAuvXr0dOTg7i4+ORm5uLnj174ubNm0LZ1NRUBAYG4uzZszh+/DiqqqowePBgPH36FACgp6eH6OhorF27FmlpaQAAIkJAQAD69u2LTz/9VGkfYmJi4O7urrKPxcXFcHV1xfbt2zF37lxcvHgRJ0+exNixYzFr1iwhEDt79ixcXFxQUVGBH3/8ETKZDBEREYiNjcWgQYNQUVEBACgsLERhYSGWL1+OzMxMxMTEICkpCRMnTmzS3AGAmpoaYmNjkZSUJLrxDwoKgomJCRYuXNjoum7fvt3k9mvduXNHFNg2ZP78+Rg7dix69uyJo0eP4sqVK1ixYgUyMjKwY8cOAEB5eTk8PDywbds2LF68GDKZDImJiaiuroaLiwvOnj0r1JeSkoJx48YhOTkZZ86cQfv27TF48GDcvXsXwKvPU0pKCqytrVWOo6KiAkOGDMHSpUsxefJknD59GufPn0dgYCDWrl2rEGA15PTp0+jatSv279+Py5cvY8KECfD19cWRI0eEMm/CvDDGGGOMNQvElBo6dCiZm5tTaWmpQt7jx4+JiMjKyoqioqIU8sPDw8nJyUn4PGXKFNLV1aV79+6JypWVlZG5uTl5enqq7MeDBw8IAKWmporSQ0JCyMbGhkpLSykqKoqMjIzozp07KuuJjo4mNzc3lflTp04lXV1dunv3rkLekydPqLKykmpqasjR0ZF69OhB1dXVojLp6ekkkUho6dKlKtvYs2cPaWpqUmVlpZAGgBISEhTK+vn50ciRI0Vpq1evJmNjY7p79y4dPHiQNDQ06NKlSyrbq1VQUEBff/012dnZkbe3d4PlVfH39ydra2tauHAh5ebm1lv23LlzBIBWrVqlNL/2Glq6dClJJBJKT08X5VdXV1OPHj3I0dGRampqlNZRVVVF+vr6FBsbK0pv6jwlJyeTlZWVyvxly5ZRixYt6OLFiwp5FRUVwt+Isu+stn4AwpiVGTZsGAUEBAif34R5UUYulxMAksvlTTqPMfbHWM3+QeXBGGP/jZpyz8ErdEoUFRUhKSkJgYGB0NXVVcg3MjJqdF01NTXYvXs3xo8fDzMzM1Gejo4Opk2bhmPHjokewaurdmXMxMRElB4REQENDQ34+Phg3rx5WLt2LczNzRvdL1V9bNeunUK+np4e1NXVkZ6ejqysLISGhqJFC/Gl4+TkBA8PD+zatUtlO3K5HAYGBlBXf7XXHwYFBcHJyQm+vr6YPHkyFi5cqPBoa62ysjLs2LEDHh4esLa2RmJiIkJDQ7Ft2zahTFxcHPT09Oo96q7orFmzBgsWLEBqairs7OzQv39/bN26FU+ePFFov7buadOmKe1f7TW0c+dODBo0CE5OTqL8Fi1aICQkBFlZWcjIyFA5xsrKSoVroynz1BhxcXHw8PDAO++8o5CnoaGh9G+kqeRyuWgczWFeGGOMMcbeBPxicSVycnJARHBwcGiw7OzZsxV+g1NRUQFHR0cAwMOHD1FcXIxOnTopPb9Tp04gIuTk5KBXr16iPCJCaGgo3n33XXTu3FmUp62tjVWrVsHT0xNDhw6Fj49PU4Yo8vvvv+Px48cNjlcmkwl9VjWWU6dOKc179OgRFi9ejM8++0whb9y4cVBTUxOllZeXY/hw8ctiJRIJNmzYgE6dOqFLly6YM2eOQl2pqamIjY3F3r17YWpqCh8fH2zatAk2NjYKZUeMGAEXFxflg/2PNm3aCP+tr6+PCRMmYMKECcjPz8eOHTsQGRmJGTNm4P3334efnx88PDwgkUiQnZ2NDh06QENDo976ZTIZBgwYoDSvdp5lMpnSwGPOnDkwNzeHh4eHKL0x89QU2dnZ9T6uW9cPP/wAPT09UVp1dXW95+zbtw8XLlzApk2bhLQ3ZV7Ky8tRXl4ufC4pKWnwHMYYY4yxvxMHdErQf34nJZFIGiw7c+ZM+Pv7i9LWrFmDkydP/uG2pk+fjsuXL6sMkrZu3QqpVIrMzEzI5XIYGhoKeQUFBUJQCQBVVVWorKwU3Wz7+Phg48aNTRpvQ2NRVkdJSQmGDx8OR0dHhIeHK+RHRUUp3HzPnj1baSCwbds2SKVS3Lp1C3fu3FH47Ze7uzt0dHSwcuVKTJkypd7+6uvrQ19fvxEjU2RlZYWwsDCEhYUhNjYW06dPR1xcHB4/fgwjIyOVc9EU9X0vkZGR2LVrF1JSUqCtra2Q39A81b0OqqurUV5eLkrr168fjh49KvSjsWMZMGAANmzYIEo7d+6cyn9wSElJgb+/PzZv3oy33367UW38lfPysiVLluCrr75qVL8YY4wxxl4HfuRSCTs7O0gkEly7dq3Bsq1atYKtra3oqPuoV+vWrWFkZISsrCyl51+/fh0SiURhBSkoKAiHDx9GcnIyLCwsFM6Lj4/H4cOHcerUKRgaGiIkJESU365dO6SnpwvHokWL0KNHD4W02j4aGxs3OF57e3sAqHcsdnZ2orQnT57A09MTenp6SEhIULpiZWZmpjCHygKtM2fOICoqCocOHUKfPn0wceJEhU1Kjhw5guHDhyM4OBjdunVDVFQU7t+/r7S/TX3ksq7ff/8d69atQ69evTBp0iQMHDgQ+/fvF4Jqe3t75ObmCjtAqmJvb1/vfAJQmNPly5cjIiICP/30E7p27fpK81T3OtiyZYvC9VJ3t1R7e/tG/S0AgK6ursJ3qepR4NTUVHh5eWHlypXw9fUV5b2ueXnZ3LlzIZfLheOPbKrDGGOMMfaX+Et+xfdfwNPT80/bFGXy5MmN3hSlpqaGAgMDqV27diSTyZT27f79+9SyZUv69ttviYjowoULpK6uTomJiSrH09CmKLUbtyjbFKW0tFTYFMXBwaHRm6LI5XLq3bs3ubm50dOnT5W2i0ZuilJWVkZ2dnYUGBhIRET5+fmkr69PGzZsUFpvUVERfffdd9SrVy9SU1MjT09PiouLE/WjpKSEsrOz6z1KSkqE8s+fP6e9e/eSl5cXaWhokLOzM0VFRdGDBw8U2j979myjNkWJiIho0uYfkZGRZGBgQGfOnFFab1PniajhTVGWLl2qclOUysrKV9oUJTk5mXR1dWndunVK23wT5kUZ3hSFsdeDN0VhjP3TNOWegwM6FW7evElmZmbk6OhI+/btI5lMRllZWbR69WpycHAgosYHdA8fPiQbGxvq3LkzJSYmUkFBAaWmplK/fv3I1NRUtGPi1KlTydDQkFJSUujevXvCUVZWJpQZOXIkubq6ioKqefPmkYWFBRUXFysdT0MBXVFRETk4OJCFhQXFxsbS1atXSSaT0datW8nW1la4GT916hRJpVLy9vamc+fOUX5+Pu3Zs4csLS3J1dWVnj9/TkQvgiUXFxfq0qUL5eTkiMZSVVUltNvYgG7GjBnCrp61vv/+e9LT06Nbt26pHBcR0bVr12j27Nlkbm5Oo0aNqrdsfSZMmEBt2rShkJAQysjIaLD8rFmzSE1NjWbOnEmnT5+mvLw8OnHiBI0ZM0YI9J49e0YuLi5kaWlJe/bsofz8fDp//jx5e3uTrq6uKEBZtmwZaWpq0r59+0Tz+eTJE6HMq8xTQwHd8+fPqV+/fmRsbEzr1q2j9PR0ys3Npfj4eOrWrZuwU2RjA7rk5GSSSqU0d+5c0TgePXoknPMmzIsyHNAx9npwQMcY+6fhgO5PUlhYSIGBgWRlZUWamppkbm5OI0aMoOTkZCJqfEBH9CKoCwoKIktLS1JXV6c2bdqQn58f5efni8oBUHpER0cTEVFsbCxJpVKF1bvy8nLq3LmzaOv3uhoK6IiIiouLac6cOWRnZ0eamprUpk0b8vDwoISEBNFqyOXLl2n06NHUsmVL0tDQIBsbGwoLCxOtftXexCs76t5ANyagS0lJITU1NUpLS1MoN3jwYBo4cKDKLezrqq6uphs3bjRYTpXs7GzRKxcaIz4+nvr370/6+vqkq6tLXbt2pUWLFolWq54+fUphYWFka2tLGhoaZGJiQqNHj6bMzExRXVZWVkrnMzw8nIhefZ4aCuiIXgR1S5YsoS5dupC2tjaZmJhQ3759KSYmRpiTxgZ0fn5+Ssfx8vX5uudFGQ7oGHs9OKBjjP3TNOWeQ0LUhDclM8bYP1hJSQkMDQ2FV3Awxv4e1nN+VJmXt3S4yjzGGGuumnLPwZuiMMYYY4wxxlgzxQEdY4wxxhhjjDVTHNAxxhhjjDHGWDPFLxZnjDHG2BuNfyfHGGOq8QodY4wxxhhjjDVTHNAxxhhjjDHGWDPFAR1jjDHGGGOMNVMc0DHGGGOMMcZYM8WbojDGGGPsjcYvFmeMMdV4hY4xxhhjjDHGmikO6BhjjDHGGGOsmeKAjjHGGGOMMcaaKQ7oGGOMMcYYY6yZ4oCuHvfv30dQUBA6dOgALS0tWFpawsvLCz///DMAwNraGqtWrVI478svv4Szs7MoraioCMHBwbC2toampibatm2LgIAAFBQUiMotWbIEPXv2hL6+PkxNTeHt7Y0bN24I+aWlpbCxsUFoaKjovLy8PBgYGGDLli2vPN6SkhLMnz8fDg4O0NbWhpmZGTw8PHDgwAEQkVDu6tWr+PDDD9G6dWtoaWnBzs4OCxYsQFlZmWi8QUFB6NixI6RSKdq3b48ZM2ZALpeL2pRIJDh48KBCX/z9/eHt7Q0AqK6uhqurK0aPHi0qI5fLYWlpibCwsFce819t//79cHd3h6GhIfT09NC1a1csWrQIRUVFQplnz54hPDwcHTt2hJaWFlq1aoUxY8bg6tWroro2b96Mfv36wdjYGMbGxvDw8MD58+eF/L9ynioqKhAZGQknJydIpVK0atUKffv2RXR0NCorKwGIv7O6UlJSIJFIUFxcLHweOXIk2rZtC11dXTg7OyMuLk7hvOYwL4wxxhhjrxsHdCrk5eWhe/fu+OWXXxAZGYnMzEwkJSVhwIABCAwMbFJdRUVF6N27N06cOIH169cjJycH8fHxyM3NRc+ePXHz5k2hbGpqKgIDA3H27FkcP34cVVVVGDx4MJ4+fQoA0NPTQ3R0NNauXYu0tDQAABEhICAAffv2xaeffqq0DzExMXB3d1fZx+LiYri6umL79u2YO3cuLl68iJMnT2Ls2LGYNWuWEIidPXsWLi4uqKiowI8//giZTIaIiAjExsZi0KBBqKioAAAUFhaisLAQy5cvR2ZmJmJiYpCUlISJEyc2ae4AQE1NDbGxsUhKShLd+AcFBcHExAQLFy5sdF23b99ucvu17ty5IwpsGzJ//nyMHTsWPXv2xNGjR3HlyhWsWLECGRkZ2LFjBwCgvLwcHh4e2LZtGxYvXgyZTIbExERUV1fDxcUFZ8+eFepLSUnBuHHjkJycjDNnzqB9+/YYPHgw7t69C+DV5yklJQXW1tYqx1FRUYEhQ4Zg6dKlmDx5Mk6fPo3z588jMDAQa9euVQiwGnL69Gl07doV+/fvx+XLlzFhwgT4+vriyJEjQpk3YV4YY4wxxpoFYkoNHTqUzM3NqbS0VCHv8ePHRERkZWVFUVFRCvnh4eHk5OQkfJ4yZQrp6urSvXv3ROXKysrI3NycPD09VfbjwYMHBIBSU1NF6SEhIWRjY0OlpaUUFRVFRkZGdOfOHZX1REdHk5ubm8r8qVOnkq6uLt29e1ch78mTJ1RZWUk1NTXk6OhIPXr0oOrqalGZ9PR0kkgktHTpUpVt7NmzhzQ1NamyslJIA0AJCQkKZf38/GjkyJGitNWrV5OxsTHdvXuXDh48SBoaGnTp0iWV7dUqKCigr7/+muzs7Mjb27vB8qr4+/uTtbU1LVy4kHJzc+ste+7cOQJAq1atUppfew0tXbqUJBIJpaeni/Krq6upR48e5OjoSDU1NUrrqKqqIn19fYqNjRWlN3WekpOTycrKSmX+smXLqEWLFnTx4kWFvIqKCuFvRNl3Vls/AGHMygwbNowCAgKEz2/CvCgjl8sJAMnl8iadxxj7Y6xm/6DyYIyx/0ZNuefgFTolioqKkJSUhMDAQOjq6irkGxkZNbqumpoa7N69G+PHj4eZmZkoT0dHB9OmTcOxY8dEj+DVVbsyZmJiIkqPiIiAhoYGfHx8MG/ePKxduxbm5uaN7peqPrZr104hX09PD+rq6khPT0dWVhZCQ0PRooX40nFycoKHhwd27dqlsh25XA4DAwOoq7/a6w+DgoLg5OQEX19fTJ48GQsXLlR4tLVWWVkZduzYAQ8PD1hbWyMxMRGhoaHYtm2bUCYuLg56enr1HnVXdNasWYMFCxYgNTUVdnZ26N+/P7Zu3YonT54otF9b97Rp05T2r/Ya2rlzJwYNGgQnJydRfosWLRASEoKsrCxkZGSoHGNlZaXCtdGUeWqMuLg4eHh44J133lHI09DQUPo30lRyuVw0jjdlXsrLy1FSUiI6GGOMMcbeJPxicSVycnJARHBwcGiw7OzZsxV+g1NRUQFHR0cAwMOHD1FcXIxOnTopPb9Tp04gIuTk5KBXr16iPCJCaGgo3n33XXTu3FmUp62tjVWrVsHT0xNDhw6Fj49PU4Yo8vvvv+Px48cNjlcmkwl9VjWWU6dOKc179OgRFi9ejM8++0whb9y4cVBTUxOllZeXY/hw8ctiJRIJNmzYgE6dOqFLly6YM2eOQl2pqamIjY3F3r17YWpqCh8fH2zatAk2NjYKZUeMGAEXFxflg/2PNm3aCP+tr6+PCRMmYMKECcjPz8eOHTsQGRmJGTNm4P3334efnx88PDwgkUiQnZ2NDh06QENDo976ZTIZBgwYoDSvdp5lMpnSwGPOnDkwNzeHh4eHKL0x89QU2dnZ9T6uW9cPP/wAPT09UVp1dXW95+zbtw8XLlzApk2bhLQ3ZV6WLFmCr776qsFyjDHGGGOvCwd0StB/ficlkUgaLDtz5kz4+/uL0tasWYOTJ0/+4bamT5+Oy5cvqwyStm7dCqlUiszMTMjlchgaGgp5BQUFQlAJAFVVVaisrBTdbPv4+GDjxo1NGm9DY1FWR0lJCYYPHw5HR0eEh4cr5EdFRSncfM+ePVtpILBt2zZIpVLcunULd+7cUfjtl7u7O3R0dLBy5UpMmTKl3v7q6+tDX1+/ESNTZGVlhbCwMISFhSE2NhbTp09HXFwcHj9+DCMjI5Vz0RT1fS+RkZHYtWsXUlJSoK2trZDf0DzVvQ6qq6tRXl4uSuvXrx+OHj0q9KOxYxkwYAA2bNggSjt37pzKf3BISUmBv78/Nm/ejLfffrtRbfyV8/KyuXPnijYgKikpgaWlZaP6yRhjjDH2d+BHLpWws7ODRCLBtWvXGizbqlUr2Nraio66j3q1bt0aRkZGyMrKUnr+9evXIZFIFFaQgoKCcPjwYSQnJ8PCwkLhvPj4eBw+fBinTp2CoaEhQkJCRPnt2rVDenq6cCxatAg9evRQSKvto7GxcYPjtbe3B4B6x2JnZydKe/LkCTw9PaGnp4eEhASlK1ZmZmYKc6gs0Dpz5gyioqJw6NAh9OnTBxMnTlTYpOTIkSMYPnw4goOD0a1bN0RFReH+/ftK+9vURy7r+v3337Fu3Tr06tULkyZNwsCBA7F//34hqLa3t0dubq6wA6Qq9vb29c4nAIU5Xb58OSIiIvDTTz+ha9eurzRPda+DLVu2KFwvdXdLtbe3b9TfAgDo6uoqfJeqHgVOTU2Fl5cXVq5cCV9fX1He65qXl2lpacHAwEB0MMYYY4y9Uf6SX/H9F/D09PzTNkWZPHlyozdFqampocDAQGrXrh3JZDKlfbt//z61bNmSvv32WyIiunDhAqmrq1NiYqLK8TS0KUrtxi3KNkUpLS0VNkVxcHBo9KYocrmcevfuTW5ubvT06VOl7aKRm6KUlZWRnZ0dBQYGEhFRfn4+6evr04YNG5TWW1RURN999x316tWL1NTUyNPTk+Li4kT9KCkpoezs7HqPkpISofzz589p79695OXlRRoaGuTs7ExRUVH04MEDhfbPnj3bqE1RIiIimrT5R2RkJBkYGNCZM2eU1tvUeSJqeFOUpUuXqtwUpbKy8pU2RUlOTiZdXV1at26d0jbfhHlRhjdFYez14E1RGGP/NE255+CAToWbN2+SmZkZOTo60r59+0gmk1FWVhatXr2aHBwciKjxAd3Dhw/JxsaGOnfuTImJiVRQUECpqanUr18/MjU1Fe2YOHXqVDI0NKSUlBS6d++ecJSVlQllRo4cSa6urqKgat68eWRhYUHFxcVKx9NQQFdUVEQODg5kYWFBsbGxdPXqVZLJZLR161aytbUVbsZPnTpFUqmUvL296dy5c5Sfn0979uwhS0tLcnV1pefPnxPRi2DJxcWFunTpQjk5OaKxVFVVCe02NqCbMWOGsKtnre+//5709PTo1q1bKsdFRHTt2jWaPXs2mZub06hRo+otW58JEyZQmzZtKCQkhDIyMhosP2vWLFJTU6OZM2fS6dOnKS8vj06cOEFjxowRAr1nz56Ri4sLWVpa0p49eyg/P5/Onz9P3t7epKurKwpQli1bRpqamrRv3z7RfD558kQo8yrz1FBA9/z5c+rXrx8ZGxvTunXrKD09nXJzcyk+Pp66desm7BTZ2IAuOTmZpFIpzZ07VzSOR48eCee8CfOiDAd0jL0eHNAxxv5pOKD7kxQWFlJgYCBZWVmRpqYmmZub04gRIyg5OZmIGh/QEb0I6oKCgsjS0pLU1dWpTZs25OfnR/n5+aJyAJQe0dHRREQUGxtLUqlUYfWuvLycOnfuLNr6va6GAjoiouLiYpozZw7Z2dmRpqYmtWnThjw8PCghIUG0GnL58mUaPXo0tWzZkjQ0NMjGxobCwsJEq1+1N/HKjro30I0J6FJSUkhNTY3S0tIUyg0ePJgGDhyocgv7uqqrq+nGjRsNllMlOztb9MqFxoiPj6f+/fuTvr4+6erqUteuXWnRokWi1aqnT59SWFgY2drakoaGBpmYmNDo0aMpMzNTVJeVlZXS+QwPDyeiV5+nhgI6ohdB3ZIlS6hLly6kra1NJiYm1LdvX4qJiRHmpLEBnZ+fn9JxvHx9vu55UYYDOsZeDw7oGGP/NE2555AQNeFNyYwx9g9WUlICQ0ND4RUcjLG/h/WcH1Xm5S0drjKPMcaaq6bcc/CmKIwxxhhjjDHWTHFAxxhjjDHGGGPNFL+HjjHGGGNvNH6skjHGVOMVOsYYY4wxxhhrpjigY4wxxhhjjLFmigM6xhhjjDHGGGumOKBjjDHGGGOMsWaKN0VhjDHG2BuN30PHGGOq8QodY4wxxhhjjDVTHNAxxhhjjDHGWDPFAR1jjDHGGGOMNVMc0DHGGGOMMcZYM8UBXT3u37+PoKAgdOjQAVpaWrC0tISXlxd+/vlnAIC1tTVWrVqlcN6XX34JZ2dnUVpRURGCg4NhbW0NTU1NtG3bFgEBASgoKBCVW7JkCXr27Al9fX2YmprC29sbN27cEPJLS0thY2OD0NBQ0Xl5eXkwMDDAli1bXnm8JSUlmD9/PhwcHKCtrQ0zMzN4eHjgwIEDICKh3NWrV/Hhhx+idevW0NLSgp2dHRYsWICysjLReIOCgtCxY0dIpVK0b98eM2bMgFwuF7UpkUhw8OBBhb74+/vD29sbAFBdXQ1XV1eMHj1aVEYul8PS0hJhYWGvPOa/2v79++Hu7g5DQ0Po6emha9euWLRoEYqKioQyz549Q3h4ODp27AgtLS20atUKY8aMwdWrV0V1bd68Gf369YOxsTGMjY3h4eGB8+fPC/l/5TxVVFQgMjISTk5OkEqlaNWqFfr27Yvo6GhUVlYCEH9ndaWkpEAikaC4uFj4PHLkSLRt2xa6urpwdnZGXFycwnnNYV4YY4wxxl43DuhUyMvLQ/fu3fHLL78gMjISmZmZSEpKwoABAxAYGNikuoqKitC7d2+cOHEC69evR05ODuLj45Gbm4uePXvi5s2bQtnU1FQEBgbi7NmzOH78OKqqqjB48GA8ffoUAKCnp4fo6GisXbsWaWlpAAAiQkBAAPr27YtPP/1UaR9iYmLg7u6uso/FxcVwdXXF9u3bMXfuXFy8eBEnT57E2LFjMWvWLCEQO3v2LFxcXFBRUYEff/wRMpkMERERiI2NxaBBg1BRUQEAKCwsRGFhIZYvX47MzEzExMQgKSkJEydObNLcAYCamhpiY2ORlJQkuvEPCgqCiYkJFi5c2Oi6bt++3eT2a925c0cU2DZk/vz5GDt2LHr27ImjR4/iypUrWLFiBTIyMrBjxw4AQHl5OTw8PLBt2zYsXrwYMpkMiYmJqK6uhouLC86ePSvUl5KSgnHjxiE5ORlnzpxB+/btMXjwYNy9exfAq89TSkoKrK2tVY6joqICQ4YMwdKlSzF58mScPn0a58+fR2BgINauXasQYDXk9OnT6Nq1K/bv34/Lly9jwoQJ8PX1xZEjR4Qyb8K8MMYYY4w1C8SUGjp0KJmbm1NpaalC3uPHj4mIyMrKiqKiohTyw8PDycnJSfg8ZcoU0tXVpXv37onKlZWVkbm5OXl6eqrsx4MHDwgApaamitJDQkLIxsaGSktLKSoqioyMjOjOnTsq64mOjiY3NzeV+VOnTiVdXV26e/euQt6TJ0+osrKSampqyNHRkXr06EHV1dWiMunp6SSRSGjp0qUq29izZw9pampSZWWlkAaAEhISFMr6+fnRyJEjRWmrV68mY2Njunv3Lh08eJA0NDTo0qVLKturVVBQQF9//TXZ2dmRt7d3g+VV8ff3J2tra1q4cCHl5ubWW/bcuXMEgFatWqU0v/YaWrp0KUkkEkpPTxflV1dXU48ePcjR0ZFqamqU1lFVVUX6+voUGxsrSm/qPCUnJ5OVlZXK/GXLllGLFi3o4sWLCnkVFRXC34iy76y2fgDCmJUZNmwYBQQECJ/fhHlRRi6XEwCSy+VNOo8x9sdYzf5B5cEYY/+NmnLPwSt0ShQVFSEpKQmBgYHQ1dVVyDcyMmp0XTU1Ndi9ezfGjx8PMzMzUZ6Ojg6mTZuGY8eOiR7Bq6t2ZczExESUHhERAQ0NDfj4+GDevHlYu3YtzM3NG90vVX1s166dQr6enh7U1dWRnp6OrKwshIaGokUL8aXj5OQEDw8P7Nq1S2U7crkcBgYGUFd/tdcfBgUFwcnJCb6+vpg8eTIWLlyo8GhrrbKyMuzYsQMeHh6wtrZGYmIiQkNDsW3bNqFMXFwc9PT06j3qruisWbMGCxYsQGpqKuzs7NC/f39s3boVT548UWi/tu5p06Yp7V/tNbRz504MGjQITk5OovwWLVogJCQEWVlZyMjIUDnGyspKhWujKfPUGHFxcfDw8MA777yjkKehoaH0b6Sp5HK5aBxvyryUl5ejpKREdDDGGGOMvUn4xeJK5OTkgIjg4ODQYNnZs2cr/AanoqICjo6OAICHDx+iuLgYnTp1Unp+p06dQETIyclBr169RHlEhNDQULz77rvo3LmzKE9bWxurVq2Cp6cnhg4dCh8fn6YMUeT333/H48ePGxyvTCYT+qxqLKdOnVKa9+jRIyxevBifffaZQt64ceOgpqYmSisvL8fw4eKXxUokEmzYsAGdOnVCly5dMGfOHIW6UlNTERsbi71798LU1BQ+Pj7YtGkTbGxsFMqOGDECLi4uygf7H23atBH+W19fHxMmTMCECROQn5+PHTt2IDIyEjNmzMD7778PPz8/eHh4QCKRIDs7Gx06dICGhka99ctkMgwYMEBpXu08y2QypYHHnDlzYG5uDg8PD1F6Y+apKbKzs+t9XLeuH374AXp6eqK06urqes/Zt28fLly4gE2bNglpb8q8LFmyBF999VWD5RhjjDHGXhcO6JSg//xOSiKRNFh25syZ8Pf3F6WtWbMGJ0+e/MNtTZ8+HZcvX1YZJG3duhVSqRSZmZmQy+UwNDQU8goKCoSgEgCqqqpQWVkputn28fHBxo0bmzTehsairI6SkhIMHz4cjo6OCA8PV8iPiopSuPmePXu20kBg27ZtkEqluHXrFu7cuaPw2y93d3fo6Ohg5cqVmDJlSr391dfXh76+fiNGpsjKygphYWEICwtDbGwspk+fjri4ODx+/BhGRkYq56Ip6vteIiMjsWvXLqSkpEBbW1shv6F5qnsdVFdXo7y8XJTWr18/HD16VOhHY8cyYMAAbNiwQZR27tw5lf/gkJKSAn9/f2zevBlvv/12o9r4K+flZXPnzhVtQFRSUgJLS8tG9ZMxxhhj7O/Aj1wqYWdnB4lEgmvXrjVYtlWrVrC1tRUddR/1at26NYyMjJCVlaX0/OvXr0MikSisIAUFBeHw4cNITk6GhYWFwnnx8fE4fPgwTp06BUNDQ4SEhIjy27Vrh/T0dOFYtGgRevTooZBW20djY+MGx2tvbw8A9Y7Fzs5OlPbkyRN4enpCT08PCQkJSleszMzMFOZQWaB15swZREVF4dChQ+jTpw8mTpyosEnJkSNHMHz4cAQHB6Nbt26IiorC/fv3lfa3qY9c1vX7779j3bp16NWrFyZNmoSBAwdi//79QlBtb2+P3NxcYQdIVezt7eudTwAKc7p8+XJERETgp59+QteuXV9pnupeB1u2bFG4Xurulmpvb9+ovwUA0NXVVfguVT0KnJqaCi8vL6xcuRK+vr6ivNc1Ly/T0tKCgYGB6GCMMcYYe6P8Jb/i+y/g6en5p22KMnny5EZvilJTU0OBgYHUrl07kslkSvt2//59atmyJX377bdERHThwgVSV1enxMREleNpaFOU2o1blG2KUlpaKmyK4uDg0OhNUeRyOfXu3Zvc3Nzo6dOnSttFIzdFKSsrIzs7OwoMDCQiovz8fNLX16cNGzYorbeoqIi+++476tWrF6mpqZGnpyfFxcWJ+lFSUkLZ2dn1HiUlJUL558+f0969e8nLy4s0NDTI2dmZoqKi6MGDBwrtnz17tlGbokRERDRp84/IyEgyMDCgM2fOKK23qfNE1PCmKEuXLlW5KUplZeUrbYqSnJxMurq6tG7dOqVtvgnzogxvisLY68GbojDG/mmacs/BAZ0KN2/eJDMzM3J0dKR9+/aRTCajrKwsWr16NTk4OBBR4wO6hw8fko2NDXXu3JkSExOpoKCAUlNTqV+/fmRqairaMXHq1KlkaGhIKSkpdO/ePeEoKysTyowcOZJcXV1FQdW8efPIwsKCiouLlY6noYCuqKiIHBwcyMLCgmJjY+nq1askk8lo69atZGtrK9yMnzp1iqRSKXl7e9O5c+coPz+f9uzZQ5aWluTq6krPnz8nohfBkouLC3Xp0oVycnJEY6mqqhLabWxAN2PGDGFXz1rff/896enp0a1bt1SOi4jo2rVrNHv2bDI3N6dRo0bVW7Y+EyZMoDZt2lBISAhlZGQ0WH7WrFmkpqZGM2fOpNOnT1NeXh6dOHGCxowZIwR6z549IxcXF7K0tKQ9e/ZQfn4+nT9/nry9vUlXV1cUoCxbtow0NTVp3759ovl88uSJUOZV5qmhgO758+fUr18/MjY2pnXr1lF6ejrl5uZSfHw8devWTdgpsrEBXXJyMkmlUpo7d65oHI8ePRLOeRPmRRkO6Bh7PTigY4z903BA9ycpLCykwMBAsrKyIk1NTTI3N6cRI0ZQcnIyETU+oCN6EdQFBQWRpaUlqaurU5s2bcjPz4/y8/NF5QAoPaKjo4mIKDY2lqRSqcLqXXl5OXXu3Fm09XtdDQV0RETFxcU0Z84csrOzI01NTWrTpg15eHhQQkKCaDXk8uXLNHr0aGrZsiVpaGiQjY0NhYWFiVa/am/ilR11b6AbE9ClpKSQmpoapaWlKZQbPHgwDRw4UOUW9nVVV1fTjRs3GiynSnZ2tuiVC40RHx9P/fv3J319fdLV1aWuXbvSokWLRKtVT58+pbCwMLK1tSUNDQ0yMTGh0aNHU2ZmpqguKysrpfMZHh5ORK8+Tw0FdEQvgrolS5ZQly5dSFtbm0xMTKhv374UExMjzEljAzo/Pz+l43j5+nzd86IMB3SMvR4c0DHG/mmacs8hIWrCm5IZY+wfrKSkBIaGhsIrOBhjfw/rOT+qzMtbOlxlHmOMNVdNuefgTVEYY4wxxhhjrJnigI4xxhhjjDHGmikO6BhjjDHGGGOsmeIXizPGGGPsjca/k2OMMdV4hY4xxhhjjDHGmikO6BhjjDHGGGOsmeKAjjHGGGOMMcaaKQ7oGGOMMcYYY6yZ4k1RGGOMMfZG4xeLM8aYarxCxxhjjDHGGGPNFAd0jDHGGGOMMdZMcUDHGGOMMcYYY80UB3T1uH//PoKCgtChQwdoaWnB0tISXl5e+PnnnwEA1tbWWLVqlcJ5X375JZydnUVpRUVFCA4OhrW1NTQ1NdG2bVsEBASgoKBAVG7JkiXo2bMn9PX1YWpqCm9vb9y4cUPILy0thY2NDUJDQ0Xn5eXlwcDAAFu2bHnl8ZaUlGD+/PlwcHCAtrY2zMzM4OHhgQMHDoCIhHJXr17Fhx9+iNatW0NLSwt2dnZYsGABysrKROMNCgpCx44dIZVK0b59e8yYMQNyuVzUpkQiwcGDBxX64u/vD29vbwBAdXU1XF1dMXr0aFEZuVwOS0tLhIWFvfKY/2r79++Hu7s7DA0Noaenh65du2LRokUoKioSyjx79gzh4eHo2LEjtLS00KpVK4wZMwZXr14V1bV582b069cPxsbGMDY2hoeHB86fPy/k/5XzVFFRgcjISDg5OUEqlaJVq1bo27cvoqOjUVlZCUD8ndWVkpICiUSC4uJi4fPIkSPRtm1b6OrqwtnZGXFxcQrnNYd5YYwxxhh73TigUyEvLw/du3fHL7/8gsjISGRmZiIpKQkDBgxAYGBgk+oqKipC7969ceLECaxfvx45OTmIj49Hbm4uevbsiZs3bwplU1NTERgYiLNnz+L48eOoqqrC4MGD8fTpUwCAnp4eoqOjsXbtWqSlpQEAiAgBAQHo27cvPv30U6V9iImJgbu7u8o+FhcXw9XVFdu3b8fcuXNx8eJFnDx5EmPHjsWsWbOEQOzs2bNwcXFBRUUFfvzxR8hkMkRERCA2NhaDBg1CRUUFAKCwsBCFhYVYvnw5MjMzERMTg6SkJEycOLFJcwcAampqiI2NRVJSkujGPygoCCYmJli4cGGj67p9+3aT2691584dUWDbkPnz52Ps2LHo2bMnjh49iitXrmDFihXIyMjAjh07AADl5eXw8PDAtm3bsHjxYshkMiQmJqK6uhouLi44e/asUF9KSgrGjRuH5ORknDlzBu3bt8fgwYNx9+5dAK8+TykpKbC2tlY5joqKCgwZMgRLly7F5MmTcfr0aZw/fx6BgYFYu3atQoDVkNOnT6Nr167Yv38/Ll++jAkTJsDX1xdHjhwRyrwJ88IYY4wx1iwQU2ro0KFkbm5OpaWlCnmPHz8mIiIrKyuKiopSyA8PDycnJyfh85QpU0hXV5fu3bsnKldWVkbm5ubk6empsh8PHjwgAJSamipKDwkJIRsbGyotLaWoqCgyMjKiO3fuqKwnOjqa3NzcVOZPnTqVdHV16e7duwp5T548ocrKSqqpqSFHR0fq0aMHVVdXi8qkp6eTRCKhpUuXqmxjz549pKmpSZWVlUIaAEpISFAo6+fnRyNHjhSlrV69moyNjenu3bt08OBB0tDQoEuXLqlsr1ZBQQF9/fXXZGdnR97e3g2WV8Xf35+sra1p4cKFlJubW2/Zc+fOEQBatWqV0vzaa2jp0qUkkUgoPT1dlF9dXU09evQgR0dHqqmpUVpHVVUV6evrU2xsrCi9qfOUnJxMVlZWKvOXLVtGLVq0oIsXLyrkVVRUCH8jyr6z2voBCGNWZtiwYRQQECB8fhPmRRm5XE4ASC6XN+k8xtgfYzX7B5UHY4z9N2rKPQev0ClRVFSEpKQkBAYGQldXVyHfyMio0XXV1NRg9+7dGD9+PMzMzER5Ojo6mDZtGo4dOyZ6BK+u2pUxExMTUXpERAQ0NDTg4+ODefPmYe3atTA3N290v1T1sV27dgr5enp6UFdXR3p6OrKyshAaGooWLcSXjpOTEzw8PLBr1y6V7cjlchgYGEBd/dXelhEUFAQnJyf4+vpi8uTJWLhwocKjrbXKysqwY8cOeHh4wNraGomJiQgNDcW2bduEMnFxcdDT06v3qLuis2bNGixYsACpqamws7ND//79sXXrVjx58kSh/dq6p02bprR/tdfQzp07MWjQIDg5OYnyW7RogZCQEGRlZSEjI0PlGCsrKxWujabMU2PExcXBw8MD77zzjkKehoaG0r+RppLL5aJxNId5YYwxxhh7E/B76JTIyckBEcHBwaHBsrNnz1b4DU5FRQUcHR0BAA8fPkRxcTE6deqk9PxOnTqBiJCTk4NevXqJ8ogIoaGhePfdd9G5c2dRnra2NlatWgVPT08MHToUPj4+TRmiyO+//47Hjx83OF6ZTCb0WdVYTp06pTTv0aNHWLx4MT777DOFvHHjxkFNTU2UVl5ejuHDxe8Wkkgk2LBhAzp16oQuXbpgzpw5CnWlpqYiNjYWe/fuhampKXx8fLBp0ybY2NgolB0xYgRcXFyUD/Y/2rRpI/y3vr4+JkyYgAkTJiA/Px87duxAZGQkZsyYgffffx9+fn7w8PCARCJBdnY2OnToAA0NjXrrl8lkGDBggNK82nmWyWRKA485c+bA3NwcHh4eovTGzFNTZGdn1/u4bl0//PAD9PT0RGnV1dX1nrNv3z5cuHABmzZtEtLelHkpLy9HeXm58LmkpKTBcxhjjDHG/k4c0ClB//mdlEQiabDszJkz4e/vL0pbs2YNTp48+Yfbmj59Oi5fvqwySNq6dSukUikyMzMhl8thaGgo5BUUFAhBJQBUVVWhsrJSdLPt4+ODjRs3Nmm8DY1FWR0lJSUYPnw4HB0dER4erpAfFRWlcPM9e/ZspYHAtm3bIJVKcevWLdy5c0fht1/u7u7Q0dHBypUrMWXKlHr7q6+vD319/UaMTJGVlRXCwsIQFhaG2NhYTJ8+HXFxcXj8+DGMjIxUzkVT1Pe9REZGYteuXUhJSYG2trZCfkPzVPc6qK6uRnl5uSitX79+OHr0qNCPxo5lwIAB2LBhgyjt3LlzKv/BISUlBf7+/ti8eTPefvvtRrXxV87Ly5YsWYKvvvqqUf1ijDHGGHsd+JFLJezs7CCRSHDt2rUGy7Zq1Qq2traio+6jXq1bt4aRkRGysrKUnn/9+nVIJBKFFaSgoCAcPnwYycnJsLCwUDgvPj4ehw8fxqlTp2BoaIiQkBBRfrt27ZCeni4cixYtQo8ePRTSavtobGzc4Hjt7e0BoN6x2NnZidKePHkCT09P6OnpISEhQemKlZmZmcIcKgu0zpw5g6ioKBw6dAh9+vTBxIkTFTYpOXLkCIYPH47g4GB069YNUVFRuH//vtL+NvWRy7p+//13rFu3Dr169cKkSZMwcOBA7N+/Xwiq7e3tkZubK+wAqYq9vX298wlAYU6XL1+OiIgI/PTTT+jatesrzVPd62DLli0K10vd3VLt7e0b9bcAALq6ugrfpapHgVNTU+Hl5YWVK1fC19dXlPe65uVlc+fOhVwuF44/sqkOY4wxxthf4i/5Fd9/AU9Pzz9tU5TJkyc3elOUmpoaCgwMpHbt2pFMJlPat/v371PLli3p22+/JSKiCxcukLq6OiUmJqocT0ObotRu3KJsU5TS0lJhUxQHB4dGb4oil8upd+/e5ObmRk+fPlXaLhq5KUpZWRnZ2dlRYGAgERHl5+eTvr4+bdiwQWm9RUVF9N1331GvXr1ITU2NPD09KS4uTtSPkpISys7OrvcoKSkRyj9//pz27t1LXl5epKGhQc7OzhQVFUUPHjxQaP/s2bON2hQlIiKiSZt/REZGkoGBAZ05c0ZpvU2dJ6KGN0VZunSpyk1RKisrX2lTlOTkZNLV1aV169YpbfNNmBdleFMUxl4P3hSFMfZP05R7Dg7oVLh58yaZmZmRo6Mj7du3j2QyGWVlZdHq1avJwcGBiBof0D18+JBsbGyoc+fOlJiYSAUFBZSamkr9+vUjU1NT0Y6JU6dOJUNDQ0pJSaF79+4JR1lZmVBm5MiR5OrqKgqq5s2bRxYWFlRcXKx0PA0FdEVFReTg4EAWFhYUGxtLV69eJZlMRlu3biVbW1vhZvzUqVMklUrJ29ubzp07R/n5+bRnzx6ytLQkV1dXev78ORG9CJZcXFyoS5culJOTIxpLVVWV0G5jA7oZM2YIu3rW+v7770lPT49u3bqlclxERNeuXaPZs2eTubk5jRo1qt6y9ZkwYQK1adOGQkJCKCMjo8Hys2bNIjU1NZo5cyadPn2a8vLy6MSJEzRmzBgh0Hv27Bm5uLiQpaUl7dmzh/Lz8+n8+fPk7e1Nurq6ogBl2bJlpKmpSfv27RPN55MnT4QyrzJPDQV0z58/p379+pGxsTGtW7eO0tPTKTc3l+Lj46lbt27CTpGNDeiSk5NJKpXS3LlzReN49OiRcM6bMC/KcEDH2OvBAR1j7J+GA7o/SWFhIQUGBpKVlRVpamqSubk5jRgxgpKTk4mo8QEd0YugLigoiCwtLUldXZ3atGlDfn5+lJ+fLyoHQOkRHR1NRESxsbEklUoVVu/Ky8upc+fOoq3f62oooCMiKi4upjlz5pCdnR1pampSmzZtyMPDgxISEkSrIZcvX6bRo0dTy5YtSUNDg2xsbCgsLEy0+lV7E6/sqHsD3ZiALiUlhdTU1CgtLU2h3ODBg2ngwIEqt7Cvq7q6mm7cuNFgOVWys7NFr1xojPj4eOrfvz/p6+uTrq4ude3alRYtWiRarXr69CmFhYWRra0taWhokImJCY0ePZoyMzNFdVlZWSmdz/DwcCJ69XlqKKAjehHULVmyhLp06ULa2tpkYmJCffv2pZiYGGFOGhvQ+fn5KR3Hy9fn654XZTigY+z14ICOMfZP05R7DglRE96UzBhj/2AlJSUwNDQUXsHBGPt7WM/5UWVe3tLhKvMYY6y5aso9B2+KwhhjjDHGGGPNFAd0jDHGGGOMMdZMcUDHGGOMMcYYY80Uv1icMcYYY280/p0cY4ypxit0jDHGGGOMMdZMcUDHGGOMMcYYY80UB3SMMcYYY4wx1kxxQMcYY4wxxhhjzRQHdIwxxhhjjDHWTHFAxxhjjDHGGGPNFAd0jDHGGGOMMdZMcUDHGGOMMcYYY80UB3SMMcYYY4wx1kxxQFeP+/fvIygoCB06dICWlhYsLS3h5eWFn3/+GQBgbW2NVatWKZz35ZdfwtnZWZRWVFSE4OBgWFtbQ1NTE23btkVAQAAKCgpE5ZYsWYKePXtCX18fpqam8Pb2xo0bN4T80tJS2NjYIDQ0VHReXl4eDAwMsGXLllceb0lJCebPnw8HBwdoa2vDzMwMHh4eOHDgAIgIAODu7o7g4GCFc2NiYmBkZCRKe/bsGcLDw9GxY0doaWmhVatWGDNmDK5evSoqt3nzZvTr1w/GxsYwNjaGh4cHzp8/L+RXV1fD1dUVo0ePFp0nl8thaWmJsLCwVx7zX23//v1wd3eHoaEh9PT00LVrVyxatAhFRUVCmeYwTxUVFYiMjISTkxOkUilatWqFvn37Ijo6GpWVlQAAf39/eHt7K5ybkpICiUSC4uJi4fPIkSPRtm1b6OrqwtnZGXFxcQrnNYd5YYwxxhh73TigUyEvLw/du3fHL7/8gsjISGRmZiIpKQkDBgxAYGBgk+oqKipC7969ceLECaxfvx45OTmIj49Hbm4uevbsiZs3bwplU1NTERgYiLNnz+L48eOoqqrC4MGD8fTpUwCAnp4eoqOjsXbtWqSlpQEAiAgBAQHo27cvPv30U6V9iImJgbu7u8o+FhcXw9XVFdu3b8fcuXNx8eJFnDx5EmPHjsWsWbMgl8ubNOby8nJ4eHhg27ZtWLx4MWQyGRITE1FdXQ0XFxecPXtWKJuSkoJx48YhOTkZZ86cQfv27TF48GDcvXsXAKCmpobY2FgkJSWJbvyDgoJgYmKChQsXNrpft2/fbtI46rpz544Q2DbG/PnzMXbsWPTs2RNHjx7FlStXsGLFCmRkZGDHjh0A3ox5SklJgbW1tcpxVFRUYMiQIVi6dCkmT56M06dP4/z58wgMDMTatWsVAqyGnD59Gl27dsX+/ftx+fJlTJgwAb6+vjhy5IhQ5k2YF8YYY4yxZoGYUkOHDiVzc3MqLS1VyHv8+DEREVlZWVFUVJRCfnh4ODk5OQmfp0yZQrq6unTv3j1RubKyMjI3NydPT0+V/Xjw4AEBoNTUVFF6SEgI2djYUGlpKUVFRZGRkRHduXNHZT3R0dHk5uamMn/q1Kmkq6tLd+/eVch78uQJVVZWEhGRm5sbff7550rrNzQ0FD4vXbqUJBIJpaeni8pVV1dTjx49yNHRkWpqapT2paqqivT19Sk2NlaUvnr1ajI2Nqa7d+/SwYMHSUNDgy5duqRyTLUKCgro66+/Jjs7O/L29m6wvCr+/v5kbW1NCxcupNzc3HrLnjt3jgDQqlWrlObXXkNvwjwlJyeTlZWVyvxly5ZRixYt6OLFiwp5FRUVwt+In58fjRw5Umn9AIQxKzNs2DAKCAgQPr8J86KMXC4nACSXy5t0HmOMMcZYUzTlnoNX6JQoKipCUlISAgMDoaurq5D/8qOF9ampqcHu3bsxfvx4mJmZifJ0dHQwbdo0HDt2TPQIXl21K2MmJiai9IiICGhoaMDHxwfz5s3D2rVrYW5u3uh+qepju3btFPL19PSgrq7epDp37tyJQYMGwcnJSZTeokULhISEICsrCxkZGUrPLSsrQ2VlpcKYg4KC4OTkBF9fX0yePBkLFy5UeLS1bh07duyAh4cHrK2tkZiYiNDQUGzbtk0oExcXBz09vXqPuis6a9aswYIFC5Camgo7Ozv0798fW7duxZMnTxTar6172rRpSvtXew297nlqjLi4OHh4eOCdd95RyNPQ0FD6N9JUcrlcNI43ZV7Ky8tRUlIiOhhjjDHG3ih/Q4DZ7NSurhw4cKDeclZWVqSpqUm6urqiQ0NDQ1ihu3//PgFQupJHRHTgwAECQOfOnVPIq6mpIS8vL3r33XeVnpuUlEQAaOjQoQ2Oqb4Vuv/7v/8jALRy5coG63FzcyMNDQ2FMWtpaYlW6LS1tZWu5BERXbx4kQBQfHy80vxp06aRjY0NPXv2TCHv2rVrBIC6dOkirBrWlZKSQgEBAaSnp0cdOnSghQsXUk5OjtJ2SkpKKDs7u96jpKRE6bl5eXm0ePFisre3J6lUSuPHj6effvpJWDUaOnQode3aVem5db2ueaqroRU6HR0dmjFjRr11EL1YoVNTU1O4NrS1tetdodu7dy9pamrSlStXhLQ3YV6IXqy2A1A4eIWOMcYYY3+lpqzQNW3Z5R+C/vM7KYlE0mDZmTNnwt/fX5S2Zs0anDx58g+3NX36dFy+fBmnTp1Seu7WrVshlUqRmZkJuVwOQ0NDIa+goACOjo7C56qqKlRWVkJPT09I8/HxwcaNG5s0XgAYP3485s+fL0o7cOAAIiIiGnV+fe1FRkZi165dSElJgba2tkL+tm3bIJVKcevWLdy5c0fht1/u7u7Q0dHBypUrMWXKlHr7oa+vD319/Ub1+WVWVlYICwtDWFgYYmNjMX36dMTFxeHx48cwMjICETV6PlX5K+ep7nVQXV2N8vJyUVq/fv1w9OhRoR+NHcuAAQOwYcMGUdq5c+fg4+OjtHxKSgr8/f2xefNmvP32241q46+cl5fNnTtXtAFRSUkJLC0tG9VPxhhjjLG/Az9yqYSdnR0kEgmuXbvWYNlWrVrB1tZWdNR91Kt169YwMjJCVlaW0vOvX78OiUQCGxsbUXpQUBAOHz6M5ORkWFhYKJwXHx+Pw4cP49SpUzA0NERISIgov127dkhPTxeORYsWoUePHgpptX00NjZu1HgBwNDQUGHMpqamojL29vb1jhl4Mc91LV++HBEREfjpp5/QtWtXhfPOnDmDqKgoHDp0CH369MHEiRMVNik5cuQIhg8fjuDgYHTr1g1RUVG4f/++0n409ZHLun7//XesW7cOvXr1wqRJkzBw4EDs379fCKrt7e2Rm5sr7ACpyuuap7rXwZYtWxSul7q7pdrb2zf62tDV1VW4NlQ9CpyamgovLy+sXLkSvr6+orzXNS8v09LSgoGBgehgjDHGGHuj/FXLhM2dp6fnn7YpyuTJkxu9KUpNTQ0FBgZSu3btSCaTKe3b/fv3qWXLlvTtt98SEdGFCxdIXV2dEhMTVY6noU1RajduUbYpSmlpaZM3RYmIiGjSphaRkZFkYGBAZ86cUdq/srIysrOzo8DAQCIiys/PJ319fdqwYYPS8kVFRfTdd99Rr169SE1NjTw9PSkuLo6ePn0qlGnqI5fPnz+nvXv3kpeXF2loaJCzszNFRUXRgwcPFNo/e/ZsozZFed3zRNTwI5dLly5VuSlKZWXlK22KkpycTLq6urRu3Tqlbb4J86IMb4rCGGOMsb9DU+45OKBT4ebNm2RmZkaOjo60b98+kslklJWVRatXryYHBwcianxA9/DhQ7KxsaHOnTtTYmIiFRQUUGpqKvXr149MTU1FOyZOnTqVDA0NKSUlhe7duyccZWVlQpmRI0eSq6srVVdXC2nz5s0jCwsLKi4uVjqehgK6oqIicnBwIAsLC4qNjaWrV6+STCajrVu3kq2trXAz3tiA7tmzZ+Ti4kKWlpa0Z88eys/Pp/Pnz5O3tzfp6uqKbryXLVtGmpqatG/fPtGYnzx5IpSZMWOGsKtnre+//5709PTo1q1bKsdF9OJ3U7NnzyZzc3MaNWpUvWXrM2HCBGrTpg2FhIRQRkZGg+VnzZpFampqNHPmTDp9+jTl5eXRiRMnaMyYMUKg9ybMU0MB3fPnz6lfv35kbGxM69ato/T0dMrNzaX4+Hjq1q2bsFNkYwO65ORkkkqlNHfuXNE4Hj16JJzzJsyLMhzQMcYYY+zvwAHdn6SwsJACAwOFzU/Mzc1pxIgRlJycTESND+iIXgR1QUFBZGlpSerq6tSmTRvy8/Oj/Px8UTko2YABAEVHRxMRUWxsLEmlUoXVu/LycurcubNo6/e6GgroiIiKi4tpzpw5ZGdnR5qamtSmTRvy8PCghIQEYTWksQEdEdHTp08pLCyMbG1tSUNDg0xMTGj06NGUmZkpKmdlZaV0zOHh4UT0YqMTNTU1SktLU2h38ODBNHDgQJVb2NdVXV1NN27caLCcKtnZ2Y3aSKOu+Ph46t+/P+nr65Ouri517dqVFi1aJFqtet3z1FBAR/QiqFuyZAl16dKFtLW1ycTEhPr27UsxMTHCnDQ2oPPz81M6jpevz9c9L8pwQMcYY4yxv0NT7jkkRE14UzJjjP2DlZSUwNDQEHK5nH9PxxhjjLG/TFPuOXhTFMYYY4wxxhhrpjigY4wxxhhjjLFmigM6xhhjjDHGGGumOKBjjDHGGGOMsWaKAzrGGGOMMcYYa6Y4oGOMMcYYY4yxZooDOsYYY4wxxhhrpjigY4wxxhhjjLFmigM6xhhjjDHGGGumOKBjjDHGGGOMsWaKAzrGGGOMMcYYa6Y4oGOMMcYYY4yxZooDOvansLa2xqpVq153NwAARITvv/8eLi4u0NPTg5GREXr06IFVq1ahrKxMKFdUVITg4GBYW1tDU1MTbdu2RUBAAAoKCkT1LVmyBD179oS+vj5MTU3h7e2NGzduiMq4u7sjODhYoS8xMTEwMjISPs+aNQvW1tZ48uSJqJyXlxf69++PmpqaPz4Bf4FLly7hgw8+QJs2baCtrQ17e3tMmjQJMpkMAJCXlweJRIL09HSFc+vOTWVlJWbPno0uXbpAV1cX7dq1g6+vLwoLCxXOO336NIYNGwZjY2Noa2ujS5cuWLFiBaqrq4UyeXl5mDhxIt566y3o6OjAxsYG4eHhqKioEMokJiZCU1MTFy9eFNW/fPlytGrVCvfv3/8TZogxxhhj7PXggI7Vq+6N8ZugNnCozyeffILg4GCMHDkSycnJSE9Px4IFC3Do0CH89NNPAF4Ec71798aJEyewfv165OTkID4+Hrm5uejZsydu3rwp1JeamorAwECcPXsWx48fR1VVFQYPHoynT582uf+LFy+Gnp4eQkNDhbRt27YhOTkZ0dHRaNGicX+SLwedTfHw4UM8f/680eV/+OEH9O7dG+Xl5YiLi8O1a9ewY8cOGBoaYsGCBU1qu6ysDBcvXsSCBQtw8eJFHDhwADKZDCNGjBCVS0hIgJubGywsLJCcnIzr16/j888/xzfffIOPPvoIRAQAuH79OmpqarBp0yZcvXoVUVFR2LhxI+bNmyfUNWzYMPj6+sLX1xfl5eUAgGvXrmHBggX47rvvYGZm1qQxMMYYY4y9UYj9o7i5uVFgYCAFBgaSoaEhmZiY0Pz586mmpoaIiKysrGjx4sXk5+dHBgYG5OvrS0RE+/btI0dHR9LU1CQrKytavny5qE4AoqNWfefVtvfNN99QQEAA6enpkaWlJW3atEll/2/dukX1Xbbx8fEEgA4ePKiQV1NTQ8XFxURENGXKFNLV1aV79+6JypSVlZG5uTl5enqqbOPBgwcEgFJTU0Vz8PnnnyuUjY6OJkNDQ1Har7/+ShoaGnT06FHKz88nAwMD+u6771S2V0sul9OWLVuoX79+ZGxs3GB5VWJiYsjIyIg+++wzOn36dL1lnz59Sq1atSJvb2+l+Y8fPyai//+9XLp0SaGMqrmpdf78eQJA+fn5RERUWlpKLVu2pFGjRimUPXz4MAGg3bt3q6wvMjKS3nrrLVFaSUkJWVlZ0ezZs6myspJ69OhBH3zwgco6VJHL5QSA5HJ5k89ljDHGGGusptxz8ArdP1BsbCzU1dVx7tw5rFmzBlFRUdiyZYuQ/+2336Jz58747bffsGDBAvz222/48MMP8dFHHyEzMxNffvklFixYgJiYGADAgQMHYGFhgUWLFuHevXu4d+8eADR4Xq0VK1agR48euHTpEqZNm4apU6fi+vXrrzS2uLg4dOzYESNHjlTIk0gkMDQ0RE1NDXbv3o3x48crrM7o6Ohg2rRpOHbsGIqKipS2IZfLAQAmJiav1Mfu3btj7ty5+PTTT/HJJ5+gZ8+emDp1qtKyNTU1OH78OHx8fGBmZoalS5fivffew6+//iqUKSgogJ6eXr3HlClThPLjx4/Hv//9bzx+/BgDBw5Ex44d8c033+D27dsK7R87dgy///47Zs2apbR/dR8nfVVyuRwSiUSo66effsKjR4/wr3/9S6Gsl5cX7O3tsWvXrnrre/m70dfXx7Zt27BixQqMHz8et2/fxvr16/9w3xljjDHGXru/IcBkbxA3Nzfq1KmTsCJHRDR79mzq1KkTEb1YMXt5Nebjjz+mQYMGidJmzpxJjo6OwmcrKyuKiop6pfN8fHyEzzU1NWRqakobNmxQ2v+GVug6depEI0aMUJlPRHT//n0CoNDfWgcOHCAAdO7cOYW8mpoa8vLyonfffVeU7ubmRhoaGqSrqys6tLS0FFboiIgqKirI0tKStLS0hJWpum7cuEFz584lCwsLMjY2ps8++4xOnTqltL+VlZWUnZ1d7/F///d/Ss8tLi6mzZs3U79+/UhNTY3ee+892r59O5WVlRER0bJlywgAFRUVKT2/Vu33oqOjozAHLVq0ULlC9+zZM+revTuNHz9eSFu6dCkBEFb/XjZixAjhen1ZTk4OGRgY0ObNm5Xmf/TRRwSA4uPj6x1PrefPn5NcLheO27dv8wodY4wxxv5yvELH6tW7d2/R79D69OmD7OxsYbOJHj16iMpfu3YNffv2FaX17dtXdI4yjT2va9euwn9LJBKYmZnhwYMHQtrbb78trDS9/fbbACBafapNA15siNLQb+waQv/5fZayeqZPn47Lly8rXSEaP3480tPTRceiRYuUtnH8+HHcu3cPRIQLFy4o5E+ePBlLlizB//zP/+Du3bvYuHGjwlzWUldXh62tbb2Hqamp0nMNDQ3x6aef4uTJkzh9+jRu3boFX19fHDt2TDQXjRUfH68wBy9fT7UqKyvx0UcfoaamRulqmaq2VX3HhYWF8PT0xAcffIBPP/1UaX5SUhKkUinS0tIaNZ4lS5bA0NBQOCwtLRt1HmOMMcbY30X9dXeAvXl0dXVFn5XdQDfmRr+x52loaIg+SyQS0W6PiYmJqKysBADcvXsX7u7uot0U655vb2+Pa9eu1duv1q1bw8jICFlZWUrzr1+/DolEAhsbG1F6UFAQDh8+jJMnT8LCwkLhPENDQ9ja2orSlAVSjx8/xqRJkzBv3jxoaGhg2rRpcHNzQ6tWrYQyq1atwtatW7Fr1y788MMPGD9+PD755BNR8FqroKAAjo6O9Y7Zx8cHGzduVEh//vw5jhw5gh07diApKQnvvPMOvvjiC7z33nsAXsxn7Zz06dOn3jYAwNLSUmEOdHR0FMpVVlbiww8/xK1bt/DLL7/AwMBAyKtt89q1a3B1dVU49/r16wrjLSwsxIABA9CnTx98//33Svv26aefwsnJCV999RXee+89jBkzBm5ubvWOZ+7cuaINbEpKSjioY4wxxtgbhQO6f6CzZ88qfLazs4OamprS8o6Ojjh16pQo7fTp07C3txfO0dTUVFita8x5jWFlZSX8t7r6i0v25aCh1scff4yPPvoIhw4dUvgdHRGhpKQEhoaG+PDDDxEXF4dFixaJfkf37NkzrF+/HkOGDBF+h0VECAoKQkJCAlJSUvDWW281uu/KBAUFwdTUFGFhYZBIJDh48CCmT5+O3bt3C2WcnZ2xdu1arFixAj/88ANiY2PxzjvvoHPnzvjkk08wbtw4od/t2rVT+rqAuuoGTESEU6dOYceOHdizZw/09PTg4+ODyMhIODg4iM4bPHgwWrVqhcjISCQkJCjUW1xc3OTf0dUGc9nZ2UhOTkbLli0V2jQxMcGKFSsUArrDhw8jOzsbixcvFtLu3r2LAQMGoHv37ip3Ct2yZQvS0tJw+fJlvPXWW5g+fTomTJiAy5cvK/wDRl1aWlrQ0tJq0vgYY4wxxv5Wf81Tn+xN5ebmRnp6ehQSEkLXr1+nnTt3kq6uLm3cuJGIlP8W7rfffqMWLVrQokWL6MaNGxQTE0M6OjoUHR0tlBk0aBCNGDGC7ty5Qw8fPmz0ecrac3JyovDwcKX9b+g3dDU1NTR27FjS0dGhiIgIunDhAuXl5dGRI0do4MCBlJCQQEREDx8+JBsbG+rcuTMlJiZSQUEBpaamUr9+/cjU1JRyc3OFOqdOnUqGhoaUkpJC9+7dE47a35nVzmtjdrk8cOAAaWpqUkZGhpCWmZlJmpqatG/fPpXjInqxu2ZUVBQ5OzuTiYlJvWXrs337dtLR0aGPP/6Yjh07RtXV1fWWP3jwIGloaJCXlxcdP36cbt26RRcuXKCZM2fS2LFjiajxu1xWVlbSiBEjyMLCgtLT00XzWV5eLpyzd+9eUlNTo0mTJlFGRgbdunWLtmzZQsbGxjRmzBjhN6B3794lW1tbGjhwIN25c0dUX63anURrr3GiF7t32tra0vTp05s0d7zLJWOMMcb+Dk255+CA7h/Gzc2Npk2bRlOmTCEDAwMyNjamOXPmiF5boGyzkNrXD2hoaFD79u3p22+/FeWfOXOGunbtSlpaWkpfW6DqvD87oCMiqq6upg0bNlDPnj1JKpWSgYEBde/enVavXi0Kwh4+fEhBQUFkaWlJ6urq1KZNG/Lz81PYpAQvvZKh9qgbmDYmoHv48CGZmprSN998o1Dum2++IVNTUyEYbsi1a9caVU6Zu3fvNjkguXDhAo0aNYpat25NWlpaZGtrS5MnT6bs7GwianxAV1tO2ZGcnCw67+TJk+Tp6UmGhoakqalJjo6OtHz5cqqqqhLKREdHq6yP6EWA/95779HgwYMV+pWWlkZqamqUkpLS6HnggI4xxhhjf4em3HNIiJq46wFr1tzd3eHs7IxVq1a97q4w1uzUPrIrl8tFj7EyxhhjjP2ZmnLPwbtcMsYYY4wxxlgzxQEdY4wxxhhjjDVTvMvlP0xKSsrr7gJjjDHGGGPsT8IrdIwxxhhjjDHWTHFAxxhjjDHGGGPNFAd0jDHGGGOMMdZMcUDHGGOMMcYYY80UB3SMMcYYY4wx1kxxQMcYY4wxxhhjzRQHdIwxxhhjjDHWTHFAxxhjjDHGGGPNFAd0jDHGGGOMMdZMcUD3X0IikUAikcDIyOiVzv/yyy+FOlatWgUAyMvLE9KcnZ3/cB+VtcEYY4wxxhh7dW9MQHf//n0EBQWhQ4cO0NLSgqWlJby8vPDzzz8LZU6fPo1hw4bB2NgY2tra6NKlC1asWIHq6mqhTF5eHiZOnIi33noLOjo6sLGxQXh4OCoqKkRlJBIJ0tPTFfrh7u6O4OBgAEBpaSlsbGwQGhoqKpOXlwcDAwNs2bLllcdbVFSE4OBgWFtbQ1NTE23btkVAQAAKCgpeaW4AIDo6GjKZTJT27NkzhIeHo2PHjtDS0kKrVq0wZswYXL16VVTuX//6F+7duwcLCwuF9k+cOCFqq25gpqamBktLS3z66ad4+PChMD/K5re+Nt4kycnJGDZsGFq2bAmpVApHR0d88cUXuHv3LgAgJSUFEokExcXFCudaW1sLwWpRURGCgoLQsWNHSKVStG/fHjNmzIBcLlc474cffoC7uzv09fUhlUrRs2dPxMTEiMpkZGRg3LhxsLS0hI6ODjp16oTVq1eLyqxfvx5GRka4ffu2KH369Omwt7dHWVkZz8ufPC+MMcYYY6/TGxHQ5eXloXv37vjll18QGRmJzMxMJCUlYcCAAQgMDAQAJCQkwM3NDRYWFkhOTsb169fx+eef45tvvsFHH30EIgIAXL9+HTU1Ndi0aROuXr2KqKgobNy4EfPmzWtyv/T09BAdHY21a9ciLS0NAEBECAgIQN++ffHpp58qPS8mJgbu7u4q6y0qKkLv3r1x4sQJrF+/Hjk5OYiPj0dubi569uyJmzdvNmluahkZGcHU1FT4XF5eDg8PD2zbtg2LFy+GTCZDYmIiqqur4eLigrNnz4rGamZmBjU1NYX+tmzZEi1bthSlvf3227h37x4KCgqwYcMGHDlyBL6+vqons4E26qMsyG2swsJCVFVVNbr8pk2b4OHhATMzM+zfvx9ZWVnYuHEj5HI5VqxY0eS2CwsLsXz5cmRmZiImJgZJSUmYOHGiqNzatWsxcuRIuLq64ty5c7h8+TI++ugjTJkyBf/617+Ecr/99htat26Nf//737h69Srmz5+PuXPnYt26dUKZqVOnolevXqI2fvnlF2zatAkxMTGQSqVK+2ptbY2UlBSeF8YYY4yx5obeAEOHDiVzc3MqLS1VyHv8+DGVlpZSy5YtadSoUQr5hw8fJgC0e/dulfVHRkbSW2+9JXy+desWAaBLly4plHVzc6PPP/9clBYSEkI2NjZUWlpKUVFRZGRkRHfu3FHZXnR0NLm5uanMnzJlCunq6tK9e/dE6WVlZWRubk6enp5CWkNzUwsAJSQkiPKXLl1KEomE0tPTRenV1dXUo0cPcnR0pJqaGlGelZUVRUVFEZHqeQoPDycnJydR2tdff00tWrSgsrIyAiA6Xp6Lum2o8uDBA1q1ahW988475OzsXG/Z+nz55ZfUpk0bCg0NpcuXL9db9vbt26SpqUnBwcFK82vnOzk5mQCI5r9WQ2Pbs2cPaWpqUmVlJRERFRQUkIaGBoWGhiqUXbNmDQGgs2fPqqxv2rRpNGDAAFFaQUEBGRoa0oYNG0gul1P79u1p5syZKuuo7XdycrLSvH/yvLxMLpcTAJLL5U06jzHGGGOsKZpyz/HaV+iKioqQlJSEwMBA6OrqKuQbGRnhp59+wqNHj0T/Kl/Ly8sL9vb22LVrl8o25HI5TExMXrmPERER0NDQgI+PD+bNm4e1a9fC3Nz8leqqqanB7t27MX78eJiZmYnydHR0MG3aNBw7dgxFRUWNmpv67Ny5E4MGDYKTk5MovUWLFggJCUFWVhYyMjJeaRwv09HRQU1NDaqqqnD+/HkALx7VvHfvHg4cONCoOioqKpCQkABvb2+Ym5tj27ZtGD9+PBITE4UyaWlp0NPTq/eIiIgQys+ePRtr1qzBjRs30K1bN3Tr1g2rV68WHg+ta+/evaioqMCsWbOU9u9Vf59Yl1wuh4GBAdTV1QEA+/btQ2VlpdJr+7PPPoOenl6Tr21LS0tERUVh5syZ8PHxgZ6eHhYvXvzKff4nz0t5eTlKSkpEB2OMMcbYm0T9dXcgJycHRAQHBweVZWp/F9apUyel+Q4ODgq/HauVm5uLtWvXKn0szNXVFS1aiGPaZ8+eKWwAoq2tjVWrVsHT0xNDhw6Fj49PfUOq18OHD1FcXKxyLJ06dQIRIScnBwAanJv6yGQyDBgwQGU7tWX+6IYn169fx4YNG9CrVy/o6+ujdevWAF48qvly0KrMxYsXERMTg507d0JTUxPjxo3Dr7/+iq5duyqU7dGjh9LfPtZV90ZeW1sbH374IT788EM8ePAAO3fuRGxsLGbOnIlhw4bBz88PXl5eUFdXR3Z2NgwMDNC2bdtGjVvZbwHr+y3Wo0ePsHjxYnz22WdCmkwmg6GhodI2NTU10aFDB5XX9pkzZ7Bnzx78+OOPCnkBAQH4/vvvceTIEZw7dw5aWlqNGZJS/+R5WbJkCb766qt6yzDGGGOMvU6vPaCj//z2TSKRNLqssnRl5xcWFsLT0xMffPCB0t+7xcfHKwRW48ePV9rG1q1bIZVKkZmZCblcDkNDQyGvoKAAjo6OwueqqipUVlZCT09PSPPx8cHGjRvrHyDE81FTUyP895+tKfOuTGZmJvT09FBdXY3y8nK4u7vj+++/f6W6Ro0ahTt37mDBggUICwur9zd2Ojo6sLW1faV2TE1NERwcjODgYBw9ehT+/v44dOgQLl26BGdnZ5XXkSppaWnQ19cXpan67WRJSQmGDx8OR0dHhIeHN7oNVX26evUqRo4ciYULF2LQoEEK+RkZGfjtt98glUqRlpaGXr16ifKnTJmCf//738LnsrIyDB06VDT3WVlZaN++/T9qXl42d+5c0aZIJSUlsLS0bHQ/GWOMMcb+aq89oLOzs4NEIsG1a9fg7e2ttIy9vT0A4Nq1a3B1dVXIv379uiigAl4EcwMGDECfPn1UBhqWlpYKwYGOjo5Cufj4eBw+fBhnzpzBJ598gpCQEGzbtk3Ib9eunWjV6MCBA9i/fz/i4uKENAMDAwBA69atYWRkhKysLKV9un79OiQSCWxsbACgwbmpj729fb3tAC/m/1V07NgRhw8fhpqaGtq1a/eHVoB27NiBbdu2Yfny5YiLi8Mnn3wCHx8fvPXWWwpl09LSMHTo0HrrmzdvntJNcJ48eYJ9+/Zhx44dOHnyJNzc3ODn5ydcO/b29pDL5bh3716jVqPeeusthccNax8ZfLldT09P6OnpISEhARoaGkJebZuFhYVo166d6LyKigrcvHkTAwcOFKVnZWVh4MCBmDRpEsLCwhTaq6iogK+vL8aNG4dBgwZh0qRJwqPJtRYtWiR6nNHd3R3Lli2Di4uLkFbbn3/SvLxMS0vrD13bjDHGGGN/ub/od3xN4unp2eCmKCYmJko3RTl06JDCpih37twhOzs7+uijj6iqqkrhnKZsinL//n1q2bIlffvtt0REdOHCBVJXV6fExESV42loU5TJkyc3elOUhuamFpRsihIREfG3bYpS1927dwkA/frrr0rzVW2QUVpaSrGxsTRw4EBSU1Ojfv360ffffy8aZ1lZGWVnZ9d7PHr0SChfVVVFiYmJNG7cONLR0SE7OztavHgx5efnK7RfUFDwp2/+IZfLqXfv3uTm5kZPnz5VKJ+fn0/q6upKN/9YvXq1wuYfV65cIVNT03o385g/fz6Zm5sL/Rs5ciS5urpSdXW1ynPq2xTlnzwvL+NNURhjjDH2d2jKPccbEdDdvHmTzMzMyNHRkfbt20cymYyysrJo9erV5ODgQEREe/fuJTU1NZo0aRJlZGTQrVu3aMuWLWRsbExjxowRApO7d++Sra0tDRw4kO7cuUP37t0TjlpNCeiU3fTNmzePLCwsqLi4WOl4GgroHj58SDY2NtS5c2dKTEykgoICSk1NpX79+pGpqSnl5uY2aW6IlAd0z549IxcXF7K0tKQ9e/ZQfn4+nT9/nry9vUlXV5fOnDmj0Lc/I6CrrKwkHR0d+vrrr+n+/fsK89SYXS7z8/Np8eLFZGdnR926dau3bH0WLVpEhoaGNGnSJPrf//3fBst/9913JJFIaMKECZSSkkJ5eXl06tQpmjx5shBcNDZwKSkpIRcXF+rSpQvl5OSIrsW6/9CwcuVKatGiBc2bN4+uXbtGOTk5tGLFCtLS0qIvvvhCKHflyhVq3bo1jR8/XlTXgwcPhDK1/+Bw9OhRIe3evXtkYmJCy5cvVznu+gK6f/K8vIwDOsYYY4z9HZpdQEdEVFhYSIGBgWRlZUWamppkbm5OI0aMEN1knjx5kjw9PcnQ0JA0NTXJ0dGRli9fLroJjI6OVtg2v/ao1diALjY2lqRSKclkMlGZ8vJy6ty5MwUEBCgdS0MBHdGLoC4oKIgsLS1JXV2d2rRpQ35+fkpXjhozN8oCOiKip0+fUlhYGNna2pKGhgaZmJjQ6NGjKTMzU2m//oyAjoho8+bNZGlpSS1atHil1xbUde3atUaXfdmtW7fo2bNnTTrn+PHjNGTIEDI2NiZtbW1ycHCgf/3rX1RYWEhEjQ9casspO27duiU679ChQ9SvXz/S1dUlbW1t6t69O23btk1UJjw8XGldVlZWRET0/PlzcnR0pEmTJin0Ky4ujrS1ten69etKx9xQQPdPnZeXcUDHGGOMsb9DU+45JEQqdhphzYpEIhG2/P8jrK2thY1D8vLy8NZbbwmbhvxZ6rbBWHNSUlICQ0ND4TULjDHGGGN/habcc7z299CxP8+4ceOUbhnfGBEREdDT00NBQYFCnqurq9LNaP7MNhhjjDHGGGNNxyt0/yVq31unpqamdHfIhtS+yBx4sROnoaEhqqqqkJeXB+DFbn9/dLt2ZW0w1pzwCh1jjDHG/g5NuefggI4xxhqJAzrGGGOM/R34kUvGGGOMMcYY+wfggI4xxhhjjDHGmikO6BhjjDHGGGOsmeKAjjHGGGOMMcaaKQ7oGGOMMcYYY6yZ4oCOMcYYY4wxxpopDugYY4wxxhhjrJnigI4xxhhjjDHGmikO6BhjjDHGGGOsmeKA7k/i7+8Pb29vhfSUlBRIJBIUFxdj/fr1MDIywu3bt0Vlpk+fDnt7e5SVlb1y+8nJyRg2bBhatmwJqVQKR0dHfPHFF7h7965Qprq6GlFRUejatSu0tbVhZGSEoUOH4n//939FdR04cACDBg1C69atYWBggD59+uDYsWOiMl9++SWcnZ0V+pGXlweJRIL09HQAQGJiIjQ1NXHx4kVRueXLl6NVq1a4f//+K4/5n87a2hqrVq0Spb3Oa6zutV5fX4uKihAUFISOHTtCKpWiffv2mDFjBuRyucJ5P/zwA9zd3aGvrw+pVIqePXsiJiZGVCYjIwPjxo2DpaUldHR00KlTJ6xevfpvmxfGGGOMsdeJA7q/0dSpU9GrVy9MnDhRSPvll1+wadMmxMTEQCqVKj3P2toaKSkpKuvdtGkTPDw8YGZmhv379yMrKwsbN26EXC7HihUrAAD0/9q786gojvVv4N8RmGEZGEVBZBFEQcU14m4UNBLBXMQkBkEU9OaqxBVxS1yCS6JGRVATYxIjGOMaN7jumqBiRBN3FBQRgSjjdUEGUWR93j98p380M8CMa4jP55w5J1P1dFV1dZPTj91TTYSAgADMmzcPEyZMQGpqKo4ePQoHBwd4enpi165dQnvHjh2Dl5cX9u7dizNnzqB3797w9fXFuXPn9N7n/v37Izg4GMHBwSgqKgIApKamYvbs2fjmm29gY2OjUzsPHjxAQUGB3v0DwJMnT3D37t1n2ra2eZ3nmK5ycnKQk5ODpUuXIjk5GbGxsdi/f79ozACwcuVK+Pn5oXv37jh16hQuXryIgIAAhIaGYsqUKULcmTNnYGVlhZ9//hmXL1/GzJkz8dlnn+Hrr79+7nlhjDHGGPvbI/ZChISEkJ+fn0Z5QkICAaAHDx4QEVF2djYpFAr69ttvSaVSUePGjWnq1KnVtu3o6EgJCQla6/766y+SSqUUFhamtV7d7+bNmwkAxcfHa8R88MEHVL9+fSooKKhyDG5ubjR37lzhe0REBLVr104j7saNGwSAzp07J5Tl5+eTo6MjTZ8+nUpKSqhjx4700UcfVdmXWklJCe3evZs++ugjkslkdP78+Rq30SYzM5OMjIzIz8+PduzYQUVFRVXGrl69mmxtbamsrExU7uvrS8HBwURElJ6eTgMGDCBra2syMzOjjh070qFDh0TxT548oalTp5K9vT1JpVJq1qwZrVmzhoiISktL6d///jc5OTmRsbExubq6UnR0tGh79fm0ZMkSsrGxIUtLSxozZgwVFxcTEZGHhwcBEH3UXtc5Vvlcr9x+VFRUlf1v3bqVpFIplZSUCPtgZGRE4eHhGrErVqwgAHTy5Mkq2xszZgz17t1bVPYs81KZSqUiAKRSqfTajjHGGGNMH/pcc/AdulfMwcEBUVFRmDp1KoYOHQq5XI758+c/c3u//PILiouLMW3aNK31devWBQBs3LgRrq6u8PX11YiZPHky7t+/j0OHDmlto7y8HA8fPoSlpeUzjdHc3Bxr165FZGQkgoKC8Ndff2HVqlVVxicnJ2PKlCmwt7dHcHAw6tevj4SEBLRr106IadWqFeRyeZWfVq1aCbGOjo5ISkqCo6MjRo8eDVtbW0yYMAFnzpzR6Pujjz7CvXv3kJCQIJQ9ePAABw4cQFBQEACgoKAA/fv3x+HDh3Hu3Dn069cPvr6+yM7OFrYJDg7G5s2bsWLFCqSmpmL16tWQy+XCfNrb22Pr1q1ISUnB559/jhkzZmDr1q2isSQkJOD69etISEjAunXrEBsbKzxuuGPHDtjb22PevHlQKpVQKpXCdq/rHHseKpUKFhYWMDQ0BABs27YNJSUlojtxaqNHj4ZcLsemTZuqba/y+fqi54Uxxhhj7G/hFSSYb4SQkBAyMDAgMzMz0cfY2FjrXYuuXbsSADp16lSNbVd39+STTz4hCwuLGtto0aKF1juIRES5ubkEgL766iut9YsXLyZLS0v63//+J5RFRERQnTp1NPbX1NRU4w6dWkBAAAGgLVu2aNTdu3ePli9fTm+99RZJpVLy8/Oj7du3V3k3LTMzk65du1blJzMzU+t2JSUlFB8fT4MGDSKZTEatW7emJUuW0O3bt4WYAQMG0L///W/h+3fffUc2NjZUWlqqtU2ip3cwV65cSUREV69eJQAad+2qM2bMGPrwww+F7yEhIeTo6Cjq86OPPqLBgwcL32u66/WqzzH1HbrK54SZmRlJJJIqx3rv3j1q3LgxzZw5UygLDQ0lhUJRZV9t27YlHx8frXUnTpwgIyMjOnjwoNZ6feblyZMnpFKphM9ff/3Fd+gYY4wx9tLpc4fO8DXlkf9IvXv3xrfffisqO3XqFIYOHSoqu3DhAs6cOQNTU1MkJiaic+fOovrQ0FD8/PPPwvfHjx/Dx8cHBgYGQllKSgoaN24MIoJEInkh49fWzqZNmzBnzhzExcXB2tpaVNe8eXPEx8eLym7dugVPT0+NdnJycrB//35hn/39/UX1K1euxNy5c9GzZ0+kp6fDwcGh2rE6OjrquFdihoaG8PX1ha+vL27fvo3g4GBMnToVN2/eFBbtCAoKwqhRo7Bq1SrIZDJs2LABAQEBwvw/evQIc+fOxe7du5GTk4PS0lIUFhYKd+jOnz8PAwMDeHh4VDmO1atXY82aNcjKykJhYSGKi4s1Fplp1aqV6Jg3atQIycnJOu3n6zzHEhMTYW5uLirTdk4AQH5+Pt577z24ubkhIiJC5z6qGtPly5fh5+eHzz//HF5eXhr1Nc1LZQsXLsTcuXN1HhdjjDHG2KvGCd0LZGZmhmbNmonKbt68KfpeXFyM4OBgBAYGwsvLCyNHjoSvry9cXV2FmHnz5okeNfP09MRXX32FLl26CGW2trYAAFdXV6hUKiiVSjRq1KjKsbm6uiIlJUVrXWpqKgDAxcVFVL5lyxZ8/PHH+OWXX9C3b1+N7aRSqcb+qh+Zq+w///kP2rVrh7lz5+Kdd97BoEGDRAnPqFGjYGRkhHXr1sHNzQ0ffvghhg0bht69e6NOHc0ng1u1aoWsrKwq99fR0RGXL1/WKCciJCYmYv369fjll19Qr149fP7556LFMnx9fVFeXo49e/agU6dOSExMxLJly4T6qVOn4sCBA1i6dCmaNWsGExMTDBo0CMXFxQAAExOTKscFAFu3bsWkSZMQGRmJbt26wdzcHEuWLMGpU6dEcUZGRqLvEokE5eXl1bYNvL5zTK1JkyYaj2FqOy8ePnwIb29vyOVy7Ny5U7S/6j5zcnKEcVTcv4yMDPTp00dUnpKSgj59+mDkyJGYNWvWM81LZZ999hnCw8OF7/n5+TX+YwNjjDHG2Cv1ku8WvjF0XRRl5syZZGdnJ3z38/Oj7t27ayzCUVF1j8NlZ2frtGDFxo0b9VoUZePGjWRsbEw7d+7U2q4+i6L88MMPJJfLKSMjg4iIJk6cSM7OzlUuwvL777/TqFGjSKFQkL29PU2fPp0uXbokitH3kcurV6/SrFmzyMnJieRyOQ0fPpwSEhKovLxc6xhCQkLogw8+oK+++oqaN28uqmvdujXNmzdP+P7w4UNSKBQ0ceJEYQ4kEkmVj1yOGzeO+vTpIyp75513RPOp7XyaOHEieXh4CN9dXFxo6dKlGu2/rnNMn0VRVCoVde3alTw8POjRo0ca8VlZWWRoaKh1UZTly5drLIpy6dIlsra2rnaRk2eZl8p4URTGGGOMvQr6XHNwQveC6JLQ/fnnn2RoaEj79u0T6pVKJVlaWmq9MFer7mKbiOibb74hiURC//73v+nIkSOUmZlJx48fp1GjRgkXxOXl5fT+++9TvXr1aM2aNXTjxg26cOECjRo1igwNDUWJ28aNG8nQ0JC++eYbUiqVwicvL0+I0TWhy8rKIgsLC1q9erUQ8+jRI2rWrBmNGzeuyn0iIiosLKRNmzaRt7c3GRgY0MWLF6uNr0pWVhbVqVOH+vTpQ+vWrat2NU+1gwcPkkwmo+bNm9P8+fNFdQMHDqT27dvTuXPn6Pz58+Tr60vm5uZCQkdENHz4cHJwcKCdO3dSRkYGJSQkCL8djI6OJgsLC9q/f7+QaFpYWOid0Hl5edGAAQPo5s2bdPfuXSKi13qO6ZrQ5efnU5cuXahNmzaUnp4uOscq/mZw2bJlVKdOHZoxYwalpqZSeno6RUZGkkwmo8mTJwtxly5dIisrKwoKChK1defOHSHmWeelMk7oGGOMMfYqcEL3GtSU0N2+fZvc3Nxo5MiRGjEbNmwgY2NjunLlita2a7rYJiI6dOgQ9evXj+rVq0fGxsbUokULmjJlCuXk5AgxJSUltHTpUmrVqhXJZDKysLCgfv36UWJioqgtbUviA6CQkBAhRpeErry8nN555x169913NeISExPJwMCAjhw5Uu1+qd26deuZL6IfPXpEWVlZem1TWlpKjRo1IgB0/fp1Ud2NGzeod+/eZGJiQg4ODvT111+Th4eHKKErLCykSZMmUaNGjYTXFqxdu5aIni60MXz4cFIoFFS3bl365JNP6NNPP9U7oUtKSqK2bduSTCYjAPTkyZPXeo7pmtCp47R9bty4IdouLi6OevbsKSww5O7uLsyjWkREhNa2HB0diYiea14q44SOMcYYY6+CPtccEiKil/xUJ2OM/SPk5+dDoVAIr1lgjDHGGHsZ9Lnm4PfQMcYYY4wxxlgtxQkdY4wxxhhjjNVSnNAxxhhjjDHGWC3FCR1jjDHGGGOM1VKc0DHGGGOMMcZYLcUJHWOMMcYYY4zVUpzQMcYYY4wxxlgtxQkdY4wxxhhjjNVSnNAxxhhjjDHGWC3FCR1jjDHGGGOM1VKc0DHGGGOMMcZYLcUJHWOMMcYYY4zVUpzQMcZemDlz5kAikUAikSA6OvqZ2lBvX7duXaFs+PDhQvmuXbuee5za+mCMMcYYq404oXvDOTk5PfOF94tGRPj+++/RpUsXyOVy1K1bFx07dkR0dDQeP34M4GnC0L59e41tMzMzIZFIcP78eQDAhQsXEBgYCAcHB5iYmKBly5ZYvny5xnZlZWWIiopC27ZtYWxsjLp168LHxwe///67KG7Hjh3w8vKClZUVLCws0K1bNxw4cEAUM3jwYHTp0gVlZWVCWUlJCTp06IChQ4c+5+y8PLt374anpyfMzc1hamqKTp06ITY2Vmvs9u3b4enpCYVCAblcjrZt22LevHnIzc0VYlq1agWlUolRo0aJtj1x4gT69++PevXqwdjYGG3atEFkZKRovgBAqVRqPSe9vb2hVCrh4+MjlKkTM4lEAnNzc3Ts2BE7duwQ6ocPH46BAwdqtFVVH4wxxhhjtQ0ndP9QxcXFr3sIIuqEqzrDhg1DWFgY/Pz8kJCQgPPnz2P27NmIi4vDwYMH9ervzJkzsLKyws8//4zLly9j5syZ+Oyzz/D1118LMUSEgIAAzJs3DxMmTEBqaiqOHj0KBwcHeHp6iu4EHTt2DF5eXti7dy/OnDmD3r17w9fXF+fOnRNiVq1ahaysLCxatEgomz9/Pm7fvo2VK1fqPPbs7Gy99rWinJwclJaW6hy/cuVK+Pn5oXv37jh16hQuXryIgIAAhIaGYsqUKaLYmTNnYvDgwejUqRP27duHS5cuITIyEhcuXMD69euFOENDQ9jY2MDU1FQo27lzJzw8PGBvb4+EhARcuXIFEydOxJdffomAgAAQkRBrY2MDhUKhMVaZTAYbGxvIZDJReUxMDJRKJf7880+0a9cOH330EZKSkqrd76r6YIwxxhirdYjVCh4eHjR27FgaO3YsKRQKsrS0pJkzZ1J5eTkRETk6OtL8+fMpJCSELCwsKDg4mIiItm3bRm5ubiSVSsnR0ZGWLl0qahOA6KNW3Xbq/r788ksaMWIEyeVycnBwoO+++67K8d+4cYOqO922bNlCAGjXrl0adeXl5ZSXl0dERBEREdSuXbsq2z937lyVfYwZM4Z69+4tfN+8eTMBoPj4eI3YDz74gOrXr08FBQVVtufm5kZz584VlcXFxZFUKqULFy7Q6dOnydDQkPbs2VNlG2p37tyh6Ohoeuutt6h9+/Y1xldlzpw51LBhQwoPD6eLFy9WG5udnU1GRkYUHh6uUbdixQoCQCdPniQiolOnThEAio6O1trWgwcPiEj78SkoKKD69evTBx98oLFdfHw8AaDNmzeLymNiYkihUAjfQ0JCyM/PT2N7ALRz507he3FxMZmamtKnn35KERERGud3QkJClX3oQqVSEQBSqVR6bccYY4wxpg99rjn4Dl0tsm7dOhgaGuLUqVNYsWIFoqKisGbNGqF+yZIlaN26Nc6cOYPZs2fjzJkz8Pf3R0BAAJKTkzFnzhzMnj1beJxux44dsLe3x7x586BUKqFUKgGgxu3UIiMj0bFjR5w7dw5jxozBJ598gitXrjzTvm3YsAHNmzeHn5+fRp1EInkhd1NUKhUsLS2F7xs3boSrqyt8fX01YidPnoz79+/j0KFDWtsqLy/Hw4cPRe0BwIABAxAQEIDg4GAEBwcjJCQE/fv319pGcXExdu7ciYEDB8LOzg5r165FUFAQ9u7dK8QkJiZCLpdX+1mwYIEQP336dKxYsQJXr15Fhw4d0KFDByxfvhx3797V6H/btm0oKSnRuBMHAKNHj4ZcLsemTZsAPD0+crkcY8aM0bov1f0W7eDBg7h//77Wfnx9feHq6ir087yMjIxgaGgo7Je/v7/wqKZSqUT37t31aq+oqAj5+fmiD2OMMcbY34nh6x4A052DgwOioqIgkUjQvHlzJCcnIyoqCiNHjgQA9OnTR3TRHBQUhHfeeQezZ88GALi6uiIlJQVLlizB8OHDYWlpCQMDA5ibm8PGxkbYbtmyZdVup9a/f3/hAn/69OmIiorCkSNH0KJFC7337dq1a2jevLlOscnJyZDL5aIyqvDInjZJSUnYunUr9uzZI5SlpaWhZcuWWuPV5WlpaVrrIyMj8ejRI/j7+2vULV++HLa2trCwsMCyZcs06s+ePYvY2Fhs3LgRUqkUgYGBOH36NNq2basR27FjR+F3gVWpmFQaGxvD398f/v7+uHPnDjZu3Ih169Zh6tSp6N+/P0JCQuDr6wtDQ0OkpaVBoVCgUaNGGm1KpVI4OzsL+3/t2jU4OzvDyMio2rFoo26jqrlu0aJFlfOsj6KiIixZsgT5+fl45513IJfLYWJigqKiItH5rY+FCxdi7ty5zz02xhhjjLGXhRO6WqRr166i36F169ZNtKhEx44dRfGpqakad7x69OiB6OholJWVwcDAQGs/um5XMQGRSCSwsbHBnTt3hLJWrVohKysLwP8lXBUTMUdHR1y+fFmor+k3dmrNmzdHfHy8qOzWrVvw9PTUGn/58mX4+fnh888/h5eXl059qGkb06ZNmzBnzhzExcXB2tpao37jxo2QSCS4d+8erly5gs6dO4vqP/jgA9y8eROzZ8/GrFmzqjwOAGBiYoJmzZrpNWY1a2trhIWFISwsDPv27cPw4cMRFxeHc+fOaV1YprKKx0Sf41NdezX18ywCAwNhYGCAwsJCKBQKLF26VLRwyvP47LPPEB4eLnzPz8+Hg4PDC2mbMcYYY+xF4ITuH8TMzEz0XduFck13svTZrvLdGolEgvLycuH73r17UVJSAuD/Eq6Kd5sqbu/q6orU1NQaxwY8vXtUOckxNNR+KqekpKBPnz4YOXIkZs2aJapT33nURj0WFxcXUfmWLVvw8ccf45dffkHfvn01tsvIyMC0adPw9ddf4/fff8fw4cNx7tw50UIe69evx9q1a7F06VJs2LABw4YNw9ChQ9GkSRON9hITE2tMTmbMmIEZM2ZolD98+BDbtm3D+vXrcezYMXh4eCAkJARubm7C/qtUKuTk5MDW1la0bXFxMTIyMtCnTx8h9vjx4ygpKdH7Lp2rqyuAp3Oq7ZHHK1euCGN6FlFRUejbty8sLCy0JtjPQyaTaSzCwhhjjDH2d8K/oatFTp48qfHdxcWlyjs8bm5uOH78uKjsxIkTcHV1FbaRSqUay8brsp0uHB0d0axZMzRr1gyOjo4AIHyvWAYAQ4YMQVpaGuLi4jTaISKoVCqd+1W7fPkyevfujZCQEHz55Zca9QEBAbh27Rr++9//atRFRkaifv36ojt6mzZtwvDhw7Fx40a89957GtuUl5djxIgR8PT0xIgRI7Bs2TIUFBQgIiJCFNezZ0/ExMTg9u3bmDVrFo4cOQIXFxf06tULP/zwA/Ly8oRY9SOX1X1CQ0OF+LKyMuzbtw9DhgxBw4YNsXDhQvTp0wcZGRn49ddfERwcDKlUCgD48MMPYWhoiMjISI19Wb16NR49eoTAwEAAT49PQUEBVq1apXWuK465snfffReWlpZa+4mPj8e1a9eEfp6FjY0NmjVrpjWZ03Z+M8YYY4z9o7ykhVnYC+bh4UFyuZwmTZpEV65coY0bN5KZmRmtXr2aiJ6uOhkVFSXa5syZM1SnTh2aN28eXb16lWJjY8nExIRiYmKEGC8vLxowYADdvHmT7t69q/N22vpr164dRUREaB1/TatclpeX0+DBg8nExIQWLFhAf/75J2VmZtJ///tf6tOnj7CSoa6rXF66dImsrKwoKCiIlEql8Llz546oz/fff5/q1atHa9asoRs3btCFCxdo1KhRZGhoKFo9cePGjWRoaEjffPONqD316ptERMuWLaN69epRTk6OUHbgwAEyNDSkU6dOVbnvRERZWVk0f/58cnFxoQ4dOlQbW5158+aRQqGgkSNH0u+//15j/LJly6hOnTo0Y8YMSk1NpfT0dIqMjCSZTEaTJ08WxU6bNo0MDAxo6tSpdOLECcrMzKTDhw/ToEGDhNUvqzo+v/zyCxkYGNDIkSPpwoULdOPGDVqzZg3Vq1ePBg0aJKzWqvasq1xW9uWXX1Ljxo3pypUrdPfuXSouLq6yD13wKpeMMcYYexX0uebghK6W8PDwoDFjxlBoaChZWFhQvXr16NNPPxW9tqBygkX0f68fMDIyosaNG9OSJUtE9UlJSdS2bVuSyWRaX1tQ1XYvOqEjIiorK6Nvv/2WOnXqRKampmRhYUHu7u60fPlyevz4MRHpntBpW7IeADk6Ooq2KykpoaVLl1KrVq1IJpORhYUF9evXjxITE0Vx2l7xAIBCQkKIiOjq1atkYmJCGzZs0BjbyJEjqWXLlvTkyZNq918tNTVVpzhtbty4QYWFhXptExcXRz179iQzMzMyNjYmd3d3Wrt2rdbYLVu2UK9evcjc3JzMzMyobdu2NG/evGpfW6B27Ngx8vb2JoVCQVKplNzc3Gjp0qVUWlqqEfuiEro7d+6Ql5cXyeVyfm0BY4wxxmoNfa45JEQ6/KiKvXaenp5o3749oqOjX/dQGKvSnDlzsGvXrhpX5qxJbGwswsLChEc5hw8fjry8PNHL3p9X5T50kZ+fD4VCAZVKBQsLixc2FsYYY4yxivS55uDf0DHGXij1ayWq+r1dTeRyueh3gWq7d++GXC7H7t27n3eIVfbBGGOMMVbb8CqXjLEXZsKECRg6dCgAwMrK6pnaUN/dq7gAz+LFi4VVSrW9N+9F9MEYY4wxVhvxI5eMMaYjfuSSMcYYY68CP3LJGGOMMcYYY28ATugYY4wxxhhjrJbihI4xxhhjjDHGailO6BhjjDHGGGOsluKEjjHGGGOMMcZqKU7oGGOMMcYYY6yW4oSOMcYYY4wxxmopTugYY4wxxhhjrJbihO4F8vT0hEQigUQiwfnz519aP+o+6tatKyovLi5Gs2bN8Pvvv+vdZnJyMuzt7fHo0SNRuZOTk9BfXl7ec4waOHLkiNDWwIEDn6stxhhjjDHG2DMmdLdv38b48ePh7OwMmUwGBwcH+Pr64tdffxViTpw4gf79+6NevXowNjZGmzZtEBkZibKyMiEmMzMTH3/8MZo0aQITExM0bdoUERERKC4uFsVUlSB5enoiLCwMAFBQUICmTZsiPDxcFJOZmQkLCwusWbPmWXYVAJCbm4uwsDA4OTlBKpWiUaNGGDFiBLKzszViR44cCaVSidatW4vKt2/fDk9PTygUCsjlcrRt2xbz5s1Dbm4uACA2NlYjQVOTSCTYtWuX8F2pVCI6Oloj7vvvv4ejoyN69OghKt+9ezc8PT1hbm4OU1NTdOrUCbGxsaKYNm3aoHPnzoiKitJod968eVAqlVAoFADEiZlEIoGVlRV8fHxw4cIFYRsnJyeNMXbv3h1KpRL+/v5a9/PvIj09HSNGjIC9vT1kMhmaNGmCwMBAnD59WoipfEzUhg8fLkpWFy5ciE6dOsHc3BzW1tYYOHAgrl69qrHd5cuX4e/vDysrK8hkMri4uGD27Nl4/PixEJObm4vx48ejefPmMDU1RePGjTFhwgSoVCoh5sKFC5DJZIiPjxe1v337dhgbG+PSpUs8Ly94XhhjjDHGXie9E7rMzEy4u7vjt99+w+LFi5GcnIz9+/ejd+/eGDt2LABg586d8PDwgL29PRISEnDlyhVMnDgRX375JQICAkBEAIArV66gvLwc3333HS5fvoyoqCisXr0aM2bM0HtH5HI5YmJisHLlSiQmJgIAiAgjRoxAjx498J///EfrdrGxsfD09Kyy3dzcXHTt2hWHDx/GqlWrkJ6eji1btuD69evo1KkTMjIyRPGmpqawsbGBoaGhUDZz5kwMHjwYnTp1wr59+3Dp0iVERkbiwoULWL9+vd77amNjIyRXFa1cuVJjP1euXAk/Pz90794dp06dwsWLFxEQEIDQ0FBMmTJFFDtixAh8++23oqQbAMzNzWFjYwOJRCIqv3r1KpRKJfbs2YMHDx7A29tbdBFdmVQqhY2NDUxMTPTaX6VSidLSUr22UcvLy0N+fr7O8adPn4a7uzvS0tLw3XffISUlBTt37kSLFi0wefJkvfs/evQoxo4di5MnT+LQoUMoLS3Fu+++K7oTevLkSXTp0gXFxcXYs2cP0tLSsGDBAqxbtw5eXl7CP3Dk5OQgJycHS5cuRXJyMmJjY7F//358/PHHQlvt2rXD7NmzMWrUKNy/fx8AcOfOHYSGhmLu3Lka/9CgNnz4cMyZM4fnhTHGGGOstiE9+fj4kJ2dHRUUFGjUPXjwgAoKCqh+/fr0wQcfaNTHx8cTANq8eXOV7S9evJiaNGkifL9x4wYBoHPnzmnEenh40MSJE0VlkyZNoqZNm1JBQQFFRUVR3bp16ebNm1X2FxMTQx4eHlXWh4aGkpmZGSmVSlH548ePyc7Ojry9vasdz6lTpwgARUdHa23/wYMHwjgUCoXWGAC0c+dOjXFXjD9z5gzVqVOHVCqVUJadnU1GRkYUHh6u0eaKFSsIAJ08eVIoKyoqIplMRr/++qtQ5ujoSFFRUaJtExISCIAwdiKi48ePEwDav38/eXh4EADRp6KQkBDy8/PTuq9qhYWFtHnzZvLx8SEDAwPKy8urNr4qR44cIRMTEwoKCqKDBw9SWVlZlbHl5eXUqlUrcnd31xpXcX+1HROimvftzp07BICOHj0q9Onm5kYdO3bU6PP8+fMkkUho0aJFVba3detWkkqlVFJSIpSVlpZSp06daPDgwURENHDgQOrWrRuVlpZW2U5ISAhFRERorXuT56UylUpFAER/Z4wxxhhjL5o+1xx63aHLzc3F/v37MXbsWJiZmWnU161bFwcPHsT9+/c17v4AgK+vL1xdXbFp06Yq+1CpVLC0tNRnWCILFiyAkZERhg4dihkzZmDlypWws7N7prbKy8uxefNmBAUFwcbGRlRnYmKCMWPG4MCBA8Jjk9ps2LABcrkcY8aM0Vpf1WOW+jp27BhcXV1hYWEhlG3btg0lJSVaj8Xo0aMhl8tFx0IqlaJdu3bCHU59qO+6lZSUYMeOHbC3txce1VQqlTq3k5SUhNDQUDRq1Ajh4eFo1aoVzp8/L7ojKZfLq/34+PgIsb169cK+ffsgk8kwaNAgODo6YsaMGVof7zt//jwuX76MyZMno04dzT+NF3Gs1Hcw1ef4+fPnkZKSgvDwcI0+27Vrh759+9b492JhYSG6I2xgYIB169YhLi4OQ4YMwYEDBxAbGwsDA4NnGjPPC2OMMcbY35dhzSH/Jz09HUSEFi1aVBmTlpYGAGjZsqXW+hYtWggxlV2/fh0rV65EZGSkRl337t01LuwKCwvRvn17UZmxsTGio6Ph7e0NHx8fDB06tLpdqtbdu3eRl5dX5b60bNkSRIT09HR07txZa8y1a9fg7OwMIyOjGvtTqVSQy+XPNNbMzEzY2tqKytLS0qBQKNCoUSONeKlUCmdnZ41jYWdnh8zMTL36vn//PubOnQtzc3N07twZlpaWMDAwEB7VrMnNmzfx008/Yd26dbh58ybef/99bNmyBX379tWaQNS04EzFRzolEgk8PDzg4eGBr7/+Grt27cJPP/2EJUuWwN3dHSEhIRgyZAgUCgWuXbsGANWe3xUFBgZqJANFRUV47733tMYTEcLDw/H2228Lj/jV9PfSsmVLHD9+XGvd/fv3MX/+fIwePVrrdmFhYVi0aBG++uoruLq66rRP2rzJ81JUVISioiLhuz6P7zLGGGOMvQp6JXT0/3/7Vvm3VNXFaivXtn1OTg68vb3x0Ucfaf2925YtWzQu7oKCgrT28eOPP8LU1BTJyclQqVSiuzvZ2dlwc3MTvpeWlqKkpESUSA0dOhSrV6+ufgeh23xUtb/amJub4+zZsxrlLi4uNW5bWFgIY2NjnfqpbmwmJiaiBSeqY29vDwB49OgRXFxc8Msvv8Da2lqvMQDArFmzsG7dOnzwwQdISkqq8Q5ts2bN9O4DeLpvgYGBCAwMRFpaGgIDAzFmzBgUFRUhLCxMr/MbAKKiotC3b19R2fTp0zV+g6g2btw4XLx4scpERJuqzp/8/Hy89957cHNzQ0REhEZ9QUEBtmzZAlNTUyQmJmLatGmi+g0bNogSnqKiIkgkEixdulQo++677xAUFPRGzUtlCxcuxNy5c3UeF2OMMcbYq6ZXQufi4gKJRILU1NQql51X/4t3amoqunfvrlF/5coVUUIFPE3mevfujW7duuH777/X2q6Dg4PGhby2xTW2bNmC+Ph4JCUlYdiwYZg0aRLWrl0r1Nva2oru8OzYsQPbt2/Hhg0bhDL1Y4tWVlaoW7cuUlJStI7pypUrkEgkaNq0qdZ64Ol8HD9+HCUlJTXepatTp84zJysNGjRAcnKyRt8qlQo5OTkad++Ki4uRkZGBPn36iMpzc3Or3Z+KEhMTYWFhASsrK9GjnvqaNWsWGjVqhPXr18PV1RUBAQEYNmwYunTpojW+pruYPXv2xL59+zTKS0tLcejQIfz000+Ii4uDs7MzvvrqK+EfBiqeu5Xv/GpjY2OjcbzMzc21vt5h/PjxiI+Px7Fjx4REuGKfKSkpWvu8cuWKRkL/8OFDeHt7Qy6XY+fOnVrPq6lTp0IqleLEiRPo1q0bfvrpJwQHBwv1AwYMEM3v9OnTYWdnhwkTJghlDRs2FI3xTZiXyj777DPRyrn5+flwcHCoMp4xxhhj7JXT9wd63t7eNS6KYmlpqXVRlLi4OI1FUW7evEkuLi4UEBCgdXECfRZFuX37NtWvX5+WLFlCRER//vknGRoa0t69e6vcn5oWRRk1atRzLYpy8uTJV7Ioyi+//EL16tWj8vJyoSwrK4sMDQ21LoqyfPlyjUVRiIjs7e1pzZo1wnddF0WpzMXFhZYuXaq1rqoFMsrKyujAgQM0ZMgQMjExIRcXF5o3bx5lZGSI4q5du1btp/IiOGfPnqWwsDBq2LAh1a9fn8aNG0d//vmnRv/qhThe5OIf5eXlNHbsWLK1taW0tDStfbZo0ULnxT9UKhV17dqVPDw86NGjRxrtEREdPHiQDA0NKSkpiYiIoqKiqF69epSTk6M1Xj3u6hZFeVPnpTJeFIUxxhhjr4I+1xx6J3QZGRlkY2NDbm5utG3bNkpLS6OUlBRavnw5tWjRgoieJhcGBgY0cuRIunDhAt24cYPWrFlD9erVo0GDBglJx61bt6hZs2bUp08funnzJimVSuGjpk9C5+fnR927dxddAM6YMYPs7e2rXCWxpoTu7t271LRpU2rdujXt3buXsrOz6ejRo9SzZ0+ytram69evVzketWnTppGBgQFNnTqVTpw4QZmZmXT48GEaNGiQkOg9b0J37949kkqllJycLIpbtmwZ1alTh2bMmEGpqamUnp5OkZGRJJPJaPLkyaLYGzdukEQioczMTKHsWRM6Ly8vGjBgAN28eZPu3r0rqtNllUuVSkU//PADvf322xqrd+rj2LFjZGRkRAMGDKDt27dTUVFRtfGnTp0ic3Nz6tGjB+3Zs4euX79OFy5coC+++IJ69eolxOmauHzyySekUCjoyJEjovP78ePHQszx48fJ1NSUBg4cSKdOnaKsrCzaunUrOTg4UPfu3enJkydERJSfn09dunShNm3aUHp6uqg99T+GqFQqcnBwoE8//VRov6ysjN5++23617/+VeV+V5fQvcnzUhkndIwxxhh7FV5qQkdElJOTQ2PHjiVHR0eSSqVkZ2dHAwYMoISEBCHm2LFj5O3tTQqFgqRSKbm5udHSpUtFd+FiYmI0lrdXf9R0TejWrVtHpqamGv/aX1RURK1bt6YRI0Zo3ZeaEjqip0nd+PHjycHBgQwNDalhw4YUEhJCWVlZVY6nsi1btlCvXr3I3NyczMzMqG3btjRv3rwXdoeOiCggIEB0waoWFxdHPXv2JDMzMzI2NiZ3d3dau3atRtyCBQuoX79+orJnTeiSkpKobdu2JJPJnum1BRWlp6dTcXGxzvEV3bt3j+7cuaPXNlevXqXg4GCytbUlqVRKjo6OFBgYSGfPnhVidE1cqjq/Y2JiRNtdvHiRPvzwQ6pfvz4ZGRlR06ZNadasWaK7Tep51/a5ceMGERGNGDGCWrdurZG4Xrt2jUxNTWndunVa97mmhO5NnZfKOKFjjDHG2KugzzWHhKiK1UuY3jw9PdG+fXtER0e/9L5iY2MRFhYm+l1ScnIy+vbti/T0dJibm+vVXlFREVxcXLBp0yb06NFDKHdyckJYWBjCwsJe0MifvsQ6Ly8Pu3btemFtMvYq5OfnQ6FQCK9FYIwxxhh7GfS55tDrPXSsZqtWrYJcLtdYoORFksvlCA0N1Shv06YNFi9erPdrBwAgKysLM2fOFCVzatOnT4dcLhfeFfasEhMTIZfLRQvQMMYYY4wxxp4d36F7gW7duoXCwkIAQOPGjSGVSl9KP+np6QCevii5SZMmL6UPtaysLJSUlAAAnJ2dtb4XTleFhYW4desWgKdJqS7vqGPs74Tv0DHGGGPsVdDnmoMTOsYY0xEndIwxxhh7FfiRS8YYY4wxxhh7A3BCxxhjjDHGGGO1FCd0jDHGGGOMMVZLcULHGGOMMcYYY7UUJ3SMMcYYY4wxVktxQscYY4wxxhhjtRQndIwxxhhjjDFWS3FCxxhjjDHGGGO1FCd0jDHGGGOMMVZLcUL3DyGRSCCRSFC3bt1n2n7OnDlCG9HR0QCAzMxMoax9+/bPPUZtfTDGGGOMMcae3d8mobt9+zbGjx8PZ2dnyGQyODg4wNfXF7/++isAwMnJSWsSMGfOHI1kIzc3F2FhYXBycoJUKkWjRo0wYsQIZGdni+IWLlyITp06wdzcHNbW1hg4cCCuXr0q1BcUFKBp06YIDw8XbZeZmQkLCwusWbPmmfdX1zECNc+NWkxMDNLS0kRlhYWFiIiIQPPmzSGTydCgQQMMGjQIly9fFsVNmTIFSqUS9vb2Gv0fPnxY1FfFxMzAwAAODg74z3/+g7t37wrzI5FIcP78eZ37+DtJSEhA//79Ub9+fZiamsLNzQ2TJ0/GrVu3AABHjhyBRCJBXl6exrYVz9Pc3FyMHz8ezZs3h6mpKRo3bowJEyZApVJpbLd79254enrC3Nwcpqam6NSpE2JjY0UxFy5cQGBgIBwcHGBiYoKWLVti+fLlophVq1ahbt26+Ouvv0Tl48aNg6urKx4/fszz8oLnhTHGGGPsdfpbJHSZmZlwd3fHb7/9hsWLFyM5ORn79+9H7969MXbsWL3ays3NRdeuXXH48GGsWrUK6enp2LJlC65fv45OnTohIyNDiD169CjGjh2LkydP4tChQygtLcW7776LR48eAQDkcjliYmKwcuVKJCYmAgCICCNGjECPHj3wn//8R+sYYmNj4enp+ULGqM/c1K1bF9bW1sL3oqIi9O3bF2vXrsX8+fORlpaGvXv3oqysDF26dMHJkyeFWLlcDhsbGxgYGGiMt379+qhfv76orFWrVlAqlcjOzsa3336L//73vwgODq5yn2vqozraklxd5eTkoLS0VOf47777Dn379oWNjQ22b9+OlJQUrF69GiqVCpGRkXr3nZOTg6VLlyI5ORmxsbHYv38/Pv74Y1HcypUr4efnh+7du+PUqVO4ePEiAgICEBoaiilTpghxZ86cgZWVFX7++WdcvnwZM2fOxGeffYavv/5aiPnkk0/QuXNnUR+//fYbvvvuO8TGxsLU1FTrWJ2cnHDkyBGeF8YYY4yx2ob+Bnx8fMjOzo4KCgo06h48eEBERI6OjhQVFaVRHxERQe3atRO+h4aGkpmZGSmVSlHc48ePyc7Ojry9vascx507dwgAHT16VFQ+adIkatq0KRUUFFBUVBTVrVuXbt68WWU7MTEx5OHhUWW9PmPUZW6IiADQzp07RfWLFi0iiURC58+fF5WXlZVRx44dyc3NjcrLy0V1Fef5xo0bBIDOnTsniqk850REX3zxBdWpU4ceP35MAESfynNR1bGs6M6dOxQdHU1vvfUWtW/fvtrY6syZM4caNmxI4eHhdPHixWpj//rrL5JKpRQWFqa1Xj3fCQkJBEA0/2o17dvWrVtJKpVSSUkJERFlZ2eTkZERhYeHa8SuWLGCANDJkyerbG/MmDHUu3dvUVl2djYpFAr69ttvSaVSUePGjWnq1KlVtqEed0JCgta6N3leKlOpVASAVCqVXtsxxhhjjOlDn2uO136HLjc3F/v378fYsWNhZmamUa/Pb8LKy8uxefNmBAUFwcbGRlRnYmKCMWPG4MCBA8jNzdW6vfqRL0tLS1H5ggULYGRkhKFDh2LGjBlYuXIl7OzsdB7Xs47xeedm48aN8PLyQrt27UTlderUwaRJk5CSkoILFy48035UZmJigvLycpSWluKPP/4A8PRRTaVSiR07dujURnFxMXbu3ImBAwfCzs4Oa9euRVBQEPbu3SvEJCYmQi6XV/tZsGCBED99+nSsWLECV69eRYcOHdChQwcsX75ceDy0ol9++QXFxcWYNm2a1vE96+8TK1KpVLCwsIChoSEAYNu2bSgpKRHdcVIbPXo05HI5Nm3aVG17lc9XBwcHREVFYerUqRg6dCjkcjnmz5//zGN+k+elqKgI+fn5og9jjDHG2N+J4eseQHp6OogILVq0qDF2+vTpmDVrlqisuLgYbm5uAIC7d+8iLy8PLVu21Lp9y5YtQURIT09H586dRXVEhPDwcLz99tto3bq1qM7Y2BjR0dHw9vaGj48Phg4dqs8uiugzRvW4dJkbbdLS0tC7d+8q+1HHPO+CJ1euXMG3336Lzp07w9zcHFZWVgCePqpZOWnV5uzZs4iNjcXGjRshlUoRGBiI06dPo23bthqxHTt21PhtXmUVL+SNjY3h7+8Pf39/3LlzBxs3bsS6deswdepU9O/fHyEhIfD19YWhoSGuXbsGCwsLNGrUSKf91vZbwOp+i3X//n3Mnz8fo0ePFsrS0tKgUCi09imVSuHs7Kzxu0i1pKQkbN26FXv27NGoGzFiBL7//nv897//xalTpyCTyXTZJa3e5HlZuHAh5s6dW20MY4wxxtjr9NoTOiIC8HSVxppMnToVw4cPF5WtWLECx44de+6+xo0bh4sXL+L48eNat/3xxx9hamqK5ORkqFQqKBQKoS47O1tIKgGgtLQUJSUlkMvlQtnQoUOxevVqvcZYXl5e5Xiflz7zrk1ycjLkcjnKyspQVFQET09PfP/998/U1gcffICbN29i9uzZmDVrVrW/sTMxMUGzZs2eqR9ra2uEhYUhLCwM+/btw/DhwxEXF4dz586hffv2ICK95iMxMRHm5uaisqp+O5mfn4/33nsPbm5uiIiI0LmPqsZ0+fJl+Pn54fPPP4eXl5dG/YULF3DmzBmYmpoiMTFR4x8wQkND8fPPPwvfHz9+DB8fH9Hcp6SkoHHjxm/UvFT22WefiRZFys/Ph4ODg87jZIwxxhh72V57Qufi4gKJRILU1FQMHDiw2tgGDRpoXMxXvBtjZWWFunXrIiUlRev2V65cgUQiQdOmTUXl48ePR3x8PI4dO6b17sKWLVsQHx+PpKQkDBs2DJMmTcLatWuFeltbW9Fdox07dmD79u3YsGGDUGZhYfFMY9R1brRxdXWtth/g6fw/i+bNmyM+Ph4GBgawtbV9rjtA69evx9q1a7F06VJs2LABw4YNw9ChQ9GkSRON2MTERPj4+FTb3owZMzBjxgyN8ocPH2Lbtm1Yv349jh07Bg8PD4SEhAjJuKurK1QqFZRKpU53o5o0aaLxuKH6kcHK/Xp7e0Mul2Pnzp0wMjIS6tR95uTkwNbWVrRdcXExMjIy0KdPH1F5SkoK+vTpg5EjR2rcsVZvFxwcjMDAQHh5eWHkyJHw9fWFq6urEDNv3jzR44yenp746quv0KVLF6FMPZ43aV4qk8lkz3VuM8YYY4y9dC/nZ3z68fb2fmGLoowaNUrnBUfKy8tp7NixZGtrS2lpaVrHdvv2bapfvz4tWbKEiIj+/PNPMjQ0pL1791a5PzUtiqLPGHWZGyLti6IsWLDglS2KUtGtW7cIAJ0+fVprfVXHsqCggNatW0d9+vQhAwMD6tmzJ33//fei/Xz8+DFdu3at2s/9+/eF+NLSUtq7dy8FBgaSiYkJubi40Pz58ykrK0uj/+zs7Be++IdKpaKuXbuSh4cHPXr0SCM+KyuLDA0NtS7+sXz5co3FPy5dukTW1tbVLuYxc+ZMsrOzE8bn5+dH3bt3p7Kysiq3qW5RlDd5XirjRVEYY4wx9iroc83xt0joMjIyyMbGhtzc3Gjbtm2UlpZGKSkptHz5cmrRogUR6Z7Q3b17l5o2bUqtW7emvXv3UnZ2Nh09epR69uxJ1tbWdP36dSH2k08+IYVCQUeOHCGlUil8Hj9+LMRou+ibMWMG2dvbU15entb9qSmh02eMuswNkfaErrCwkLp06UIODg60detWysrKoj/++IMGDhxIZmZmlJSUpDG2F5HQlZSUkImJCX3xxRd0+/ZtjXnSZZXLrKwsmj9/Prm4uFCHDh2qja3OvHnzSKFQ0MiRI+n333+vMf6bb74hiURC//73v+nIkSOUmZlJx48fp1GjRgnJha6JS35+PnXp0oXatGlD6enponOstLRU2GbZsmVUp04dmjFjBqWmplJ6ejpFRkaSTCajyZMnC3GXLl0iKysrCgoKErV1584dIUb9Dw779u0TypRKJVlaWtLSpUur3O/qEro3eV4q44SOMcYYY69CrUvoiIhycnJo7Nix5OjoSFKplOzs7GjAgAHCRaauCR3R04Rp/Pjx5ODgQIaGhtSwYUMKCQnRuCuDSsvrqz8xMTFERLRu3ToyNTXVuHtXVFRErVu3phEjRmjdl5oSOn3GqMvcqPelckJHRPTo0SOaNWsWNWvWjIyMjMjS0pI+/PBDSk5O1jquF5HQERH98MMP5ODgQHXq1Hmm1xZUlJqaqnNsZTdu3KDCwkK9tjl06BD169eP6tWrR8bGxtSiRQuaMmUK5eTkEJHuiYs6Ttvnxo0bou3i4uKoZ8+eZGZmRsbGxuTu7k5r164VxURERGhty9HRkYiInjx5Qm5ubjRy5EiNcW3YsIGMjY3pypUrWve5poTuTZ2XyjihY4wxxtiroM81h4To/6+OwWo1iUQiLPn/PJycnISFQzIzM9GkSRNh0ZAXpWIfjNUm+fn5UCgUwmsWGGOMMcZeBn2uOV77e+jYixMYGKh1URddLFiwAHK5HNnZ2Rp13bt3R/fu3Z93eNX2wRhjjDHGGNMf36H7h1C/t87AwEDr6pA1Ub/IHHi6EqdCoUBpaSkyMzMBPF3t73mXa9fWB2O1Cd+hY4wxxtiroM81Byd0jDGmI07oGGOMMfYq8COXjDHGGGOMMfYG4ISOMcYYY4wxxmopTugYY4wxxhhjrJbihI4xxhhjjDHGailO6BhjjDHGGGOsluKEjjHGGGOMMcZqKU7oGGOMMcYYY6yW4oSOMcYYY4wxxmopTugY+4c5cuQIJBIJJBIJBg4c+NL6mTNnjtBPdHS0qO7HH3/Eu++++0ztDho0CMuWLROVxcbGCn2FhYU944j/j6enp9De+fPnn7s9xhhjjLHXhRO6WsTJyUnjwvl1ISJ8//336NKlC+RyOerWrYuOHTsiOjoajx8/BvD0gr99+/Ya22ZmZooupC9cuIDAwEA4ODjAxMQELVu2xPLlyzW2KysrQ1RUFNq2bQtjY2PUrVsXPj4++P3330VxO3bsgJeXF6ysrGBhYYFu3brhwIEDopjBgwejS5cuKCsrE8pKSkrQoUMHDB069Dln5+XZvXs3PD09YW5uDlNTU3Tq1AmxsbFaY69evapRd/v2bYwfPx7Ozs6QyWRwcHCAr68vfv31VyGmqvOs8vGcMmUKlEol7O3tRXFFRUX4/PPPMXv2bFF5bm4uwsLC4OTkBKlUikaNGmHEiBHIzs4WxX3++ef48ssvkZ+fLyq3sLCAUqnE/PnzhbKKiZlMJoOrqysWLFggHNfY2FjUrVtXY1927NiBP/74Q6OcMcYYY6y24YTub6C4uPh1D0FEnXBVZ9iwYQgLC4Ofnx8SEhJw/vx5zJ49G3FxcTh48KBe/Z05cwZWVlb4+eefcfnyZcycOROfffYZvv76ayGGiBAQEIB58+ZhwoQJSE1NxdGjR+Hg4ABPT0/s2rVLiD127Bi8vLywd+9enDlzBr1794avry/OnTsnxKxatQpZWVlYtGiRUDZ//nzcvn0bK1eu1HnslZMRfeTk5KC0tFTn+JUrV8LPzw/du3fHqVOncPHiRQQEBCA0NBRTpkzRiLe2thYlM5mZmXB3d8dvv/2GxYsXIzk5Gfv370fv3r0xduxYvccvl8thY2MDAwMDUfn27dshl8vRs2dPoSw3Nxddu3bF4cOHsWrVKqSnp2PLli24fv06OnXqhIyMDCG2bdu2cHJywoYNG0TtSiQS2NjYwNzcXFQ+cuRIKJVKXL16FRMmTMCsWbOwdOnSasduaWkJKysrvfeZMcYYY+xvh9gL5+HhQWPHjqWxY8eSQqEgS0tLmjlzJpWXlxMRkaOjI82fP59CQkLIwsKCgoODiYho27Zt5ObmRlKplBwdHWnp0qWiNgGIPmrVbafu78svv6QRI0aQXC4nBwcH+u6776oc/40bN6i6U2PLli0EgHbt2qVRV15eTnl5eUREFBERQe3atauy/XPnzlXZx5gxY6h3797C982bNxMAio+P14j94IMPqH79+lRQUFBle25ubjR37lxRWVxcHEmlUrpw4QKdPn2aDA0Nac+ePVW2oXbnzh2Kjo6mt956i9q3b19jfFXmzJlDDRs2pPDwcLp48WK1sdnZ2WRkZETh4eEadStWrCAAdPLkSSIiSkhIIAD04MEDUZyPjw/Z2dlpnaeKsY6OjhQVFaURU9XxrBzv6+tLU6ZMEcWEhoaSmZkZKZVKUfnjx4/Jzs6OvL29ReVz5syhnj17Ct9jYmJIoVBo9O3h4UETJ04UlfXt25e6du0qzEPFT0REhBCny3lYmUqlIgCkUql03oYxxhhjTF/6XHPwHbqXZN26dTA0NMSpU6ewYsUKREVFYc2aNUL9kiVL0Lp1a5w5cwazZ8/GmTNn4O/vj4CAACQnJ2POnDmYPXu28Mjcjh07YG9vj3nz5kGpVEKpVAJAjdupRUZGomPHjjh37hzGjBmDTz75BFeuXHmmfduwYQOaN28OPz8/jTqJRAKFQvFM7VakUqlgaWkpfN+4cSNcXV3h6+urETt58mTcv38fhw4d0tpWeXk5Hj58KGoPAAYMGICAgAAEBwcjODgYISEh6N+/v9Y2iouLsXPnTgwcOBB2dnZYu3YtgoKCsHfvXiEmMTERcrm82s+CBQuE+OnTp2PFihW4evUqOnTogA4dOmD58uW4e/euRv/btm1DSUmJ1jtxo0ePhlwux6ZNm7SOHXh6h2z//v0YO3YszMzMNOq1PZb4rBITE9GxY0fhe3l5OTZv3oygoCDY2NiIYk1MTDBmzBgcOHAAubm5Qnnnzp3xxx9/oKioSO/+TUxMUFJSgu7duyM6Olp4VFOpVGqdP8YYY4yx2szwdQ/gn8rBwQFRUVGQSCRo3rw5kpOTERUVhZEjRwIA+vTpI7q4DAoKwjvvvCP87sjV1RUpKSlYsmQJhg8fDktLSxgYGMDc3Fx0Ubxs2bJqt1Pr378/xowZA+BpIhEVFYUjR46gRYsWeu/btWvX0Lx5c51ik5OTIZfLRWVEVO02SUlJ2Lp1K/bs2SOUpaWloWXLllrj1eVpaWla6yMjI/Ho0SP4+/tr1C1fvhy2trawsLDQWIgDAM6ePYvY2Fhs3LgRUqkUgYGBOH36NNq2basR27FjxxoX2KiYVBobG8Pf3x/+/v64c+cONm7ciHXr1mHq1Kno378/QkJC4OvrC0NDQ6SlpUGhUKBRo0YabUqlUjg7O1e5/wCQnp4OItL5eE+fPh2zZs0SlRUXF8PNza3a7fLy8pCXlwdbW1uh7O7du8jLy6v2+BER0tPT0blzZwCAnZ0dioqKcPv2bTg6Ouo05vLychw8eBAHDhxAWFgYpFIpFAqF8KjmsygqKhIllZV/18cYY4wx9rpxQveSdO3aVfQ7tG7duiEyMlJYrKHiHQwASE1N1bjj1aNHD0RHR6OsrEzjd0r6blcxAVFf4N65c0coa9WqFbKysgD8X8JVMRFzdHTE5cuXhfqafmOn1rx5c8THx4vKbt26BU9PT63xly9fhp+fHz7//HN4eXnp1IeatjFt2rQJc+bMQVxcHKytrTXqN27cCIlEgnv37uHKlStCQqH2wQcf4ObNm5g9ezZmzZpV5XEAnt4ZatasmV5jVrO2tkZYWBjCwsKwb98+DB8+HHFxcTh37pzWhWUqq+mYqI+prsdt6tSpon8QAIAVK1bg2LFj1W5XWFgI4GmyqittYzMxMQEAYYGd6qxatQpr1qwRfos6bNgwRERE6Nx/dRYuXIi5c+e+kLYYY4wxxl4GTuhek8qPvWm7IK/pTpY+2xkZGYm+SyQSlJeXC9/37t2LkpISAP+XcFW821Rxe1dXV6SmptY4NuDp3aPKSY6hofbTLiUlBX369MHIkSM17g6p7zxqox6Li4uLqHzLli34+OOP8csvv6Bv374a22VkZGDatGn4+uuv8fvvv2P48OE4d+4cZDKZELN+/XqsXbsWS5cuxYYNGzBs2DAMHToUTZo00WgvMTERPj4+WseoNmPGDMyYMUOj/OHDh9i2bRvWr1+PY8eOwcPDAyEhIcIdMVdXV6hUKuTk5IjufgFP75xlZGSgT58+Vfbr4uICiUSC1NRUnV5l0KBBA43jVvmRVW3q168PiUSCBw8eCGVWVlaoW7dulcfvypUrkEgkaNq0qVCmfvxSl4VLgoKCMHPmTMhkMtja2labdOvrs88+Q3h4uPA9Pz8fDg4OL6x9xhhjjLHnxb+he0lOnjyp8d3FxaXKi003NzccP35cVHbixAm4uroK20ilUtEy+7pupwtHR0c0a9YMzZo1Ex5xU3+vWAYAQ4YMQVpaGuLi4jTaISKoVCqd+1W7fPkyevfujZCQEHz55Zca9QEBAbh27Rr++9//atRFRkaifv36ojt6mzZtwvDhw7Fx40a89957GtuUl5djxIgR8PT0xIgRI7Bs2TIUFBRo3Nnp2bMnYmJicPv2bcyaNQtHjhyBi4sLevXqhR9++AF5eXlCrPqRy+o+oaGhQnxZWRn27duHIUOGoGHDhli4cCH69OmDjIwM/PrrrwgODoZUKgUAfPjhhzA0NERkZKTGvqxevRqPHj1CYGBglfNraWmJfv364ZtvvsGjR4806ivux/OQSqVwc3MTJW916tSBv78/Nm7ciNu3b4viCwsLsWrVKvTr10+UMF66dAn29vZo0KBBjX0qFAo0a9YMDg4OGue8tr8ZfchkMlhYWIg+jDHGGGN/J5zQvSR//fUXwsPDcfXqVWzatAkrV67ExIkTq4yfPHkyfv31V8yfPx9paWlYt24dvv76a9Hv7JycnHDs2DHcunUL9+7d03m7F83f3x+DBw9GYGAgFi5ciNOnTyMrKwu7d+9G3759kZCQoFd76mTOy8sL4eHhuH37Nm7fvi1aHCQgIADvv/8+QkJC8OOPPyIzMxMXL17E6NGjER8fjzVr1gh3PTdt2oTg4GBERkaia9euQnsVE83ly5cjOTkZP/zwA4Cn7zhbs2YNIiMjtb6fzMzMDMHBwfj111+RkZGBd999F0uWLME777wjxKgfuazuUzFpWbBgAQIDAyGXy3H48GGkpaVh1qxZaNy4sUb/jRs3xuLFixEdHY2ZM2fiypUruH79OpYtW4Zp06Zh8uTJ6NKlS7XzvGrVKpSVlaFz587Yvn07rl27htTUVKxYsQLdunXT8WjVrF+/fhr/yPDll1/CxsYGXl5e2LdvH/766y8cO3YM/fr1Q0lJCb755htRfGJi4jO/mLwiJycnFBQU4Ndff8W9e/d0eoSTMcYYY6xWeTkLbb7ZPDw8aMyYMRQaGkoWFhZUr149+vTTT0WvLdC2LLz69QNGRkbUuHFjWrJkiag+KSmJ2rZtSzKZTOtrC6raTlt/7dq1Ey3hXlFNry0gIiorK6Nvv/2WOnXqRKampmRhYUHu7u60fPlyevz4MRHp/tqCiIgIjeXlAZCjo6Nou5KSElq6dCm1atWKZDIZWVhYUL9+/SgxMVEUp+0VDwAoJCSEiIiuXr1KJiYmtGHDBo2xjRw5klq2bElPnjypdv/VUlNTdYrT5saNG1RYWKjXNnFxcdSzZ08yMzMjY2Njcnd3p7Vr14piqnptARFRTk4OjR07lhwdHUkqlZKdnR0NGDCAEhIShJjnfW1BamoqmZiYCK+vULt79y6NHz+eHBwcyNDQkBo2bEghISGUlZUliissLCQLCwtKSkoSyvR5bUFloaGhVL9+fX5tAWOMMcZqDX2uOSREOvxQi+nF09MT7du3R3R09OseCnsDHTlyBL1798aDBw9e6OsIquLk5CQs6KLm7++Pt956C5999pne7X3zzTcaL6iPjY1FWFjYC3s0FHj6ovUmTZrovPAM8PQ3dAqFAiqVih+/ZIwxxthLo881Bz9yydg/lL29fbW/q3teCxYsgFwuR3Z2tkbdkiVLNF5XoSsjIyOsXLlSo1ylUkEul2P69OnP1G5FPj4+aNWq1XO3wxhjjDH2uvEdupeA79Cx16mwsBC3bt0C8PTVE8/6Draa5ObmilajfBEvlK/Kw4cP8b///Q/A05eg67JYSnVu3bolvGKhcePGwuIzNeE7dIwxxhh7FfS55uCEjjHGdMQJHWOMMcZeBX7kkjHGGGOMMcbeAJzQMcYYY4wxxlgtxQkdY4wxxhhjjNVSnNAxxhhjjDHGWC3FCR1jjDHGGGOM1VKc0DHGGGOMMcZYLcUJHWOMMcYYY4zVUpzQMcYYY4wxxlgtxQkdY4wxxhhjjNVSnNC9QJ6enpBIJJBIJDh//vxL60fdR926dUXlxcXFaNasGX7//Xe920xOToa9vT0ePXokKndychL6y8vLe45RA0eOHBHaGjhw4HO1xRhjjDHGGHvGhO727dsYP348nJ2dIZPJ4ODgAF9fX/z6668AniYB0dHRGtvNmTMH7du3F5Xl5uYiLCwMTk5OkEqlaNSoEUaMGIHs7GxR3MKFC9GpUyeYm5vD2toaAwcOxNWrV4X6goICNG3aFOHh4aLtMjMzYWFhgTVr1jzLruo1RgAYOXIklEolWrduLSrfvn07PD09oVAoIJfL0bZtW8ybNw+5ubkAgNjYWI0ETU0ikWDXrl3Cd6VSqXV+v//+ezg6OqJHjx6i8t27d8PT0xPm5uYwNTVFp06dEBsbK4pp06YNOnfujKioKI12582bB6VSCYVCAUCcmEkkElhZWcHHxwcXLlwQttF2DnTv3h1KpRL+/v5a9/PvIj09HSNGjIC9vT1kMhmaNGmCwMBAnD59WoipfEzUhg8fLkpWazpv1S5fvgx/f39YWVlBJpPBxcUFs2fPxuPHj4WY3NxcjB8/Hs2bN4epqSkaN26MCRMmQKVSCTEXLlyATCZDfHy8qP3t27fD2NgYly5d4nl5wfPCGGOMMfY66Z3QZWZmwt3dHb/99hsWL16M5ORk7N+/H71798bYsWP1ais3Nxddu3bF4cOHsWrVKqSnp2PLli24fv06OnXqhIyMDCH26NGjGDt2LE6ePIlDhw6htLQU7777rnBHSS6XIyYmBitXrkRiYiIAgIgwYsQI9OjRA//5z3+0jiE2Nhaenp4vZIwAYGpqChsbGxgaGgplM2fOxODBg9GpUyfs27cPly5dQmRkJC5cuID169frNWcAYGNjIyRXFa1cuVJjP1euXAk/Pz90794dp06dwsWLFxEQEIDQ0FBMmTJFFDtixAh8++23KCsrE5Wbm5vDxsYGEolEVH716lUolUrs2bMHDx48gLe3t+giujKpVAobGxuYmJjotb9KpRKlpaV6baOWl5eH/Px8neNPnz4Nd3d3pKWl4bvvvkNKSgp27tyJFi1aYPLkyXr3X9N5CwAnT55Ely5dUFxcjD179iAtLQ0LFizAunXr4OXlheLiYgBATk4OcnJysHTpUiQnJyM2Nhb79+/Hxx9/LLTVrl07zJ49G6NGjcL9+/cBAHfu3EFoaCjmzp2r8Q8NasOHD8ecOXN4XhhjjDHGahvSk4+PD9nZ2VFBQYFG3YMHD4iIyNHRkaKiojTqIyIiqF27dsL30NBQMjMzI6VSKYp7/Pgx2dnZkbe3d5XjuHPnDgGgo0ePisonTZpETZs2pYKCAoqKiqK6devSzZs3q2wnJiaGPDw8qqzXZ4weHh40ceJEUdypU6cIAEVHR2ttXz1nMTExpFAotMYAoJ07d2qMu2L8mTNnqE6dOqRSqYSy7OxsMjIyovDwcI02V6xYQQDo5MmTQllRURHJZDL69ddfhTJtxzIhIYEACGMnIjp+/DgBoP3795OHhwcBEH0qCgkJIT8/P637qlZYWEibN28mHx8fMjAwoLy8vGrjq3LkyBEyMTGhoKAgOnjwIJWVlVUZW15eTq1atSJ3d3etcRX3V9sxIap53yqft+Xl5eTm5kYdO3bU6PP8+fMkkUho0aJFVba3detWkkqlVFJSIpSVlpZSp06daPDgwURENHDgQOrWrRuVlpZW2U5ISAhFRERorXuT56UylUpFAER/Z4wxxhhjL5o+1xx63aHLzc3F/v37MXbsWJiZmWnUV/XIoDbl5eXYvHkzgoKCYGNjI6ozMTHBmDFjcODAAeGRxMrUd4IsLS1F5QsWLICRkRGGDh2KGTNmYOXKlbCzs9N5XC9yjACwYcMGyOVyjBkzRmu9PnNWnWPHjsHV1RUWFhZC2bZt21BSUqJxJw4ARo8eDblcjk2bNgllUqkU7dq1E+5w6kN9162kpAQ7duyAvb298KimUqnUuZ2kpCSEhoaiUaNGCA8PR6tWrXD+/HnRHUm5XF7tx8fHR4jt1asX9u3bB5lMhkGDBsHR0REzZszQ+njf+fPncfnyZUyePBl16mj+abyIY1X5vD1//jxSUlIQHh6u0We7du3Qt29f0THS1p6FhYXojrCBgQHWrVuHuLg4DBkyBAcOHEBsbCwMDAyeacxv8rwUFRUhPz9f9GGMMcYY+zsxrDnk/6Snp4OI0KJFixpjp0+fjlmzZonKiouL4ebmBgC4e/cu8vLy0LJlS63bt2zZEkSE9PR0dO7cWVRHRAgPD8fbb7+t8aiUsbExoqOj4e3tDR8fHwwdOlSfXRR5njGqXbt2Dc7OzjAyMqqxP5VKBblc/kxjzczMhK2tragsLS0NCoUCjRo10oiXSqVwdnZGWlqaqNzOzg6ZmZl69X3//n3MnTsX5ubm6Ny5MywtLWFgYCA8qlmTmzdv4qeffsK6detw8+ZNvP/++9iyZQv69u2rNYGoacGZio90SiQSeHh4wMPDA19//TV27dqFn376CUuWLIG7uztCQkIwZMgQKBQKXLt2DQB0Or8BIDAwUCMZKCoqwnvvvac1Xtt5q57/6s6x48ePa627f/8+5s+fj9GjR2vdLiwsDIsWLcJXX30FV1dXnfZJmzd5XhYuXIi5c+dWG8MYY4wx9jrpldAREQBo/JZKm6lTp2L48OGishUrVuDYsWPP3de4ceNw8eLFKi/ofvzxR5iamiI5ORkqlUp0dyc7O1tIKgGgtLQUJSUlokRq6NChWL169XONsWKMLvMFPP2t2tmzZzXKXVxcaty2sLAQxsbGOvVT3dhMTExEC05Ux97eHgDw6NEjuLi44JdffoG1tbVeYwCAWbNmYd26dfjggw+QlJSkcde1smbNmundB/B03wIDAxEYGIi0tDQEBgZizJgxKCoqQlhYmF7nNwBERUWhb9++orLp06dr/AZRrabzVpuqzp/8/Hy89957cHNzQ0REhEZ9QUEBtmzZAlNTUyQmJmLatGmi+g0bNogSnqKiIkgkEixdulQo++677xAUFPRGzUtln332mWihpfz8fDg4OOg8TsYYY4yxl02vhM7FxQUSiQSpqak1LjvfoEEDjQvvihfqVlZWqFu3LlJSUrRuf+XKFUgkEjRt2lRUPn78eMTHx+PYsWNCQlHRli1bEB8fj6SkJAwbNgyTJk3C2rVrhXpbW1vRHZ4dO3Zg+/bt2LBhg1CmfmzxWcdYkaurK44fP46SkpIa79LVqVPnmZOVBg0aIDk5WaNvlUqFnJwcjbt3xcXFyMjIQJ8+fUTlubm51e5PRYmJibCwsICVlZXoUU99zZo1C40aNcL69evh6uqKgIAADBs2DF26dNEaX9NdzJ49e2Lfvn0a5aWlpTh06BB++uknxMXFwdnZGV999RWCgoIAQLhbk5qaqrEaqzY2NjYax8vc3Fzr6x2qOm/VfaakpGjt88qVKxoJ/cOHD+Ht7Q25XI6dO3dqPa+mTp0KqVSKEydOoFu3bvjpp58QHBws1A8YMEA0v9OnT4ednR0mTJgglDVs2FA0xjdhXiqTyWSQyWTV7S5jjDHG2Oul7w/0vL29X9iiKKNGjdJ5wZHy8nIaO3Ys2draUlpamtax3b59m+rXr09LliwhIqI///yTDA0Nae/evVXuT02LougzRm2Lopw8efKVLIryyy+/UL169ai8vFwoy8rKIkNDQ62LoixfvlxjURQiInt7e1qzZo3wXddFUSpzcXGhpUuXaq2raoGMsrIyOnDgAA0ZMoRMTEzIxcWF5s2bRxkZGaK4a9euVfupvAjO2bNnKSwsjBo2bEj169encePG0Z9//qnRv3ohjhe5+EdN5215eTm1aNFC58U/VCoVde3alTw8POjRo0ca7RERHTx4kAwNDSkpKYmIiKKioqhevXqUk5OjNV497uoWRXlT56UyXhSFMcYYY6+CPtcceid0GRkZZGNjQ25ubrRt2zZKS0ujlJQUWr58ObVo0YKIdE/o7t69S02bNqXWrVvT3r17KTs7m44ePUo9e/Yka2trun79uhD7ySefkEKhoCNHjpBSqRQ+jx8/FmL8/Pyoe/fuogvAGTNmkL29fZWrJNaU0OkzRm0JHRHRtGnTyMDAgKZOnUonTpygzMxMOnz4MA0aNEhI9J43obt37x5JpVJKTk4WxS1btozq1KlDM2bMoNTUVEpPT6fIyEiSyWQ0efJkUeyNGzdIIpFQZmamUPasCZ2XlxcNGDCAbt68SXfv3hXV6bLKpUqloh9++IHefvttjdU79XHs2DEyMjKiAQMG0Pbt26moqKja+FOnTpG5uTn16NGD9uzZQ9evX6cLFy7QF198Qb169RLidE1cdDlvjx8/TqampjRw4EA6deoUZWVl0datW8nBwYG6d+9OT548ISKi/Px86tKlC7Vp04bS09NF7alXalSpVOTg4ECffvqp0H5ZWRm9/fbb9K9//avK/a4uoXuT56UyTugYY4wx9iq81ISOiCgnJ4fGjh1Ljo6OJJVKyc7OjgYMGEAJCQlEpHtCR/Q0YRo/fjw5ODiQoaEhNWzYkEJCQigrK0s80ErL4Ks/MTExRES0bt06MjU11fjX/qKiImrdujWNGDFC677UlNDpM8aqEjoioi1btlCvXr3I3NyczMzMqG3btjRv3rwXdoeOiCggIEB0waoWFxdHPXv2JDMzMzI2NiZ3d3dau3atRtyCBQuoX79+orJnTeiSkpKobdu2JJPJnum1BRWlp6dTcXGxzvEV3bt3j+7cuaPXNlevXqXg4GCytbUlqVRKjo6OFBgYSGfPnhVidE1cajpv1S5evEgffvgh1a9fn4yMjKhp06Y0a9Ys0d0m9bxr+9y4cYOIiEaMGEGtW7fWSFyvXbtGpqamtG7dOq37XFNC96bOS2Wc0DHGGGPsVdDnmkNC9P9XPGDPzdPTE+3bt0d0dPRL7ys2NhZhYWGi3yUlJyejb9++SE9Ph7m5uV7tFRUVwcXFBZs2bUKPHj2EcicnJ4SFhSEsLOwFjfzpS6zz8vKwa9euF9YmY69Cfn4+FAqF8FoExhhjjLGXQZ9rDr3eQ8dqtmrVKsjlco0FSl4kuVyO0NBQjfI2bdpg8eLFer92AACysrIwc+ZMUTKnNn36dMjlcuFdYc8qMTERcrlctAANY4wxxhhj7NnxHboX6NatWygsLAQANG7cGFKp9KX0k56eDuDpi5KbNGnyUvpQy8rKQklJCQDA2dlZ63vhdFVYWIhbt24BeJqU6vKOOsb+TvgOHWOMMcZeBX2uOTihY4wxHXFCxxhjjLFXgR+5ZIwxxhhjjLE3ACd0jDHGGGOMMVZLcULHGGOMMcYYY7UUJ3SMMcYYY4wxVktxQscYY4wxxhhjtRQndIwxxhhjjDFWS3FCxxhjjDHGGGO1FCd0jDHGGGOMMVZLcULHGGOMMcYYY7UUJ3SMMcYYY4wxVktxQscYY4wxxhhjtRQndIwxxhhjjDFWS3FCxxhjjDHGGGO1FCd0jDHGGGOMMVZLcULHGGOMMcYYY7UUJ3SMMcYYY4wxVksZvu4BMMZYbUFEAID8/PzXPBLGGGOM/ZOprzXU1x7V4YSOMcZ09PDhQwCAg4PDax4JY4wxxt4EDx8+hEKhqDZGQrqkfYwxxlBeXo6cnByYm5tDIpG87uEwLfLz8+Hg4IC//voLFhYWr3s47AXgY/rPwsfzn4eP6ctBRHj48CFsbW1Rp071v5LjO3SMMaajOnXqwN7e/nUPg+nAwsKCLyz+YfiY/rPw8fzn4WP64tV0Z06NF0VhjDHGGGOMsVqKEzrGGGOMMcYYq6U4oWOMMfaPIZPJEBERAZlM9rqHwl4QPqb/LHw8/3n4mL5+vCgKY4wxxhhjjNVSfIeOMcYYY4wxxmopTugYY4wxxhhjrJbihI4xxhhjjDHGailO6BhjjDHGGGOsluKEjjHG2Gvx4MEDDBs2DAqFAgqFAsOGDUNeXl612xAR5syZA1tbW5iYmMDT0xOXL18WxRQVFWH8+PFo0KABzMzMMGDAANy8eVPvvrOzs+Hr6wszMzM0aNAAEyZMQHFxsVCfmZkJiUSi8dm/f/9zzUttsmrVKjRp0gTGxsZwd3dHYmJitfFHjx6Fu7s7jI2N4ezsjNWrV2vEbN++HW5ubpDJZHBzc8POnTv17vdFnSdvmtp8PD09PTX+FgMCAp5hFv5Z/q7HdMeOHejXrx8aNGgAiUSC8+fPa7TBf6N6IMYYY+w18Pb2ptatW9OJEyfoxIkT1Lp1a/rXv/5V7TaLFi0ic3Nz2r59OyUnJ9PgwYOpUaNGlJ+fL8SEhoaSnZ0dHTp0iM6ePUu9e/emdu3aUWlpqc59l5aWUuvWral379509uxZOnToENna2tK4ceOEmBs3bhAAOnz4MCmVSuFTVFT0Amfp72vz5s1kZGREP/zwA6WkpNDEiRPJzMyMsrKytMZnZGSQqakpTZw4kVJSUuiHH34gIyMj2rZtmxBz4sQJMjAwoAULFlBqaiotWLCADA0N6eTJk3r1+6LOkzdJbT+eHh4eNHLkSNHfYl5e3kuYqdrj73xMf/rpJ5o7dy798MMPBIDOnTunMR7+G9UdJ3SMMcZeuZSUFAIgughISkoiAHTlyhWt25SXl5ONjQ0tWrRIKHvy5AkpFApavXo1ERHl5eWRkZERbd68WYi5desW1alTh/bv369z33v37qU6derQrVu3hJhNmzaRTCYjlUpFRP+X0Gm7EHkTdO7cmUJDQ0VlLVq0oE8//VRr/LRp06hFixaistGjR1PXrl2F7/7+/uTt7S2K6devHwUEBOjc74s6T940tfl4Ej1N6CZOnKjDnr45/q7HtKKq/j/Kf6P64UcuGWOMvXJJSUlQKBTo0qWLUNa1a1coFAqcOHFC6zY3btzA7du38e677wplMpkMHh4ewjZnzpxBSUmJKMbW1hatW7cWYnTpOykpCa1bt4atra0Q069fPxQVFeHMmTOicQ0YMADW1tbo0aMHtm3b9qxTUqsUFxfjzJkzonkGgHfffbfK45eUlKQR369fP5w+fRolJSXVxqjb1KXfF3WevElq+/FU27BhAxo0aIBWrVphypQpePjwoa5T8I/zdz6muuC/Uf1wQscYY+yVu337NqytrTXKra2tcfv27Sq3AYCGDRuKyhs2bCjU3b59G1KpFPXq1as2pqa+b9++rdFPvXr1IJVKhRi5XI5ly5Zh27Zt2Lt3L9555x0MHjwYP//8c437X9vdu3cPZWVl1R6LyrTNacOGDVFaWop79+5VG6NuU5d+X9R58iap7ccTAIKCgrBp0yYcOXIEs2fPxvbt2/HBBx/otP//RH/nY6oL/hvVj+HrHgBjjLF/jjlz5mDu3LnVxvz5558AAIlEolFHRFrLK6pcr8s2lWN06bummAYNGmDSpElCXceOHfHgwQMsXrwYQ4cOrXY8/xT6Hgtt8ZXLdWnzRcVUpkvMP1ltPp4jR44U/rt169ZwcXFBx44dcfbsWXTo0KHKffin+zsf02fxpv+NVoXv0DHGGHthxo0bh9TU1Go/rVu3ho2NDf73v/9pbH/37l2Nf9lVs7GxAQCNf529c+eOsI2NjQ2Ki4vx4MGDamNq6tvGxkajnwcPHqCkpKTK8QFPH928du1alfX/FA0aNICBgUG1x6IybXN6584dGBoaon79+tXGqNvUpd8XdZ68SWr78dSmQ4cOMDIyeiP+HrX5Ox9TXfDfqH44oWOMMfbCNGjQAC1atKj2Y2xsjG7dukGlUuGPP/4Qtj116hRUKhW6d++ute0mTZrAxsYGhw4dEsqKi4tx9OhRYRt3d3cYGRmJYpRKJS5duiTE6NJ3t27dcOnSJSiVSiHm4MGDkMlkcHd3r3L/z507h0aNGukzZbWSVCqFu7u7aJ4B4NChQ1Uev27dumnEHzx4EB07doSRkVG1Meo2den3RZ0nb5Lafjy1uXz5MkpKSt6Iv0dt/s7HVBf8N6qnV7oEC2OMMfb/eXt7U9u2bSkpKYmSkpKoTZs2Gq8taN68Oe3YsUP4vmjRIlIoFLRjxw5KTk6mwMBArcvR29vb0+HDh+ns2bPUp08fra8tqK5v9WsL3nnnHTp79iwdPnyY7O3tRa8tiI2NpQ0bNlBKSgpduXKFlixZQkZGRrRs2bKXMV1/O+qlyX/88UdKSUmhsLAwMjMzo8zMTCIi+vTTT2nYsGFCvHpJ9EmTJlFKSgr9+OOPGkui//7772RgYECLFi2i1NRUWrRoUZVLolfVL9GLO0/eJLX5eKanp9PcuXPpzz//pBs3btCePXuoRYsW9NZbb72xx5Po731M79+/T+fOnaM9e/YQANq8eTOdO3eOlEqlEMN/o7rjhI4xxthrcf/+fQoKCiJzc3MyNzenoKAgevDggSgGAMXExAjfy8vLKSIigmxsbEgmk1GvXr0oOTlZtE1hYSGNGzeOLC0tycTEhP71r39Rdna23n1nZWXRe++9RyYmJmRpaUnjxo2jJ0+eCPWxsbHUsmVLMjU1JXNzc3J3d6f169e/kLmpLb755htydHQkqVRKHTp0oKNHjwp1ISEh5OHhIYo/cuQIvfXWWySVSsnJyYm+/fZbjTZ/+eUXat68ORkZGVGLFi1o+/btevVL9OLOkzdNbT2e2dnZ1KtXL7K0tCSpVEpNmzalCRMm0P37959zRmq/v+sxjYmJIQAan4iICCGG/0Z1JyH6/792ZIwxxhhjjDFWq/Bv6BhjjDHGGGOsluKEjjHGGGOMMcZqKU7oGGOMMcYYY6yW4oSOMcYYY4wxxmopTugYY4wxxhhjrJbihI4xxhhjjDHGailO6BhjjDHGGGOsluKEjjHGGGOMMcZqKU7oGGOMMfbSzJkzB+3bt3/p/Xh6eiIsLOyl98NePScnJ0RHR7/uYTD2t8UJHWOMMfaGGT58OCQSCSQSCYyMjODs7IwpU6bg0aNHr3toNTpy5AgkEgny8vJE5Tt27MD8+fNfSp9z5sxBQEAAgL9PcqGeB/Wnfv366NOnD37//fdnaqfyfNYGTZo0wf79+1/3MBh77TihY4wxxt5A3t7eUCqVyMjIwBdffIFVq1ZhypQpWmNLSkpe8ej0Z2lpCXNz85fSdnx8PPz8/F5K28/r6tWrUCqVOHLkCKysrPDee+/hzp07r3tYL93Fixdx//599O7d+3UPhbHXjhM6xhhj7A0kk8lgY2MDBwcHDBkyBEFBQdi1axeA/3tMcu3atXB2doZMJgMRITs7G35+fpDL5bCwsIC/vz/+97//idpdtGgRGjZsCHNzc3z88cd48uSJqF7bo5EDBw7E8OHDhe9FRUWYNm0aHBwcIJPJ4OLigh9//BGZmZnCBXy9evUgkUiE7Sq3++DBAwQHB6NevXowNTWFj48Prl27JtTHxsaibt26OHDgAFq2bAm5XC4kuRX99ddfuHTpEnx8fHSa12+//RZNmzaFVCpF8+bNsX79elH9nDlz0LhxY8hkMtja2mLChAlC3apVq+Di4gJjY2M0bNgQgwYNqrE/a2tr2NjYoE2bNpg1axZUKhVOnTol1P/888/o2LEjzM3NYWNjgyFDhggJX3XzSURYvHgxnJ2dYWJignbt2mHbtm3VjsXJyQlffPEFgoODIZfL4ejoiLi4ONy9e1c4b9q0aYPTp0+Lttu+fTtatWoFmUwGJycnREZG1rjfcXFx6NevH2QyGbKysuDr64t69erBzMwMrVq1wt69e2tsg7F/Ck7oGGOMMQYTExPRnbj09HRs3boV27dvx/nz5wE8Tbxyc3Nx9OhRHDp0CNevX8fgwYOFbbZu3YqIiAh8+eWXOH36NBo1aoRVq1bpPZbg4GBs3rwZK1asQGpqKlavXg25XA4HBwds374dwP/dmVq+fLnWNoYPH47Tp08jPj4eSUlJICL0799ftI+PHz/G0qVLsX79ehw7dgzZ2dkadynj4+PRq1cv1K1bt8Zx79y5ExMnTsTkyZNx6dIljB49GiNGjEBCQgIAYNu2bYiKisJ3332Ha9euYdeuXWjTpg0A4PTp05gwYQLmzZuHq1evYv/+/ejVq5fOc/b48WPExMQAAIyMjITy4uJizJ8/HxcuXMCuXbtw48YNIWmrbj5nzZqFmJgYfPvtt7h8+TImTZqEoUOH4ujRo9WOIyoqCj169MC5c+fw3nvvYdiwYQgODsbQoUNx9uxZNGvWDMHBwSAiAMCZM2fg7++PgIAAJCcnY86cOZg9ezZiY2Or7afiXdOxY8eiqKgIx44dQ3JyMr766ivI5XKd546xWo8YY4wx9kYJCQkhPz8/4fupU6eofv365O/vT0REERERZGRkRHfu3BFiDh48SAYGBpSdnS2UXb58mQDQH3/8QURE3bp1o9DQUFFfXbp0oXbt2gnfPTw8aOLEiaIYPz8/CgkJISKiq1evEgA6dOiQ1rEnJCQQAHrw4IGovGK7aWlpBIB+//13of7evXtkYmJCW7duJSKimJgYAkDp6elCzDfffEMNGzYUtevl5UUrVqwQvjs6OlJUVJTWsXXv3p1GjhwpKvvoo4+of//+REQUGRlJrq6uVFxcrLHt9u3bycLCgvLz87W2XZl6HszMzMjMzIwkEgkBIHd3d63tq/3xxx8EgB4+fChqp+J8FhQUkLGxMZ04cUK07ccff0yBgYFVtu3o6EhDhw4VviuVSgJAs2fPFsqSkpIIACmVSiIiGjJkCHl5eYnamTp1Krm5uYnarTjnN2/eJCMjI7p//z4REbVp04bmzJlT5bgY+6fjO3SMMcbYG2j37t2Qy+UwNjZGt27d0KtXL6xcuVKod3R0hJWVlfA9NTUVDg4OcHBwEMrc3NxQt25dpKamCjHdunUT9VP5e03Onz8PAwMDeHh4PMtuCeMwNDREly5dhLL69eujefPmwlgBwNTUFE2bNhW+N2rUSPT7s/z8fBw9ehQDBgzQud8ePXqIynr06CH0+dFHH6GwsBDOzs4YOXIkdu7cidLSUgCAl5cXHB0d4ezsjGHDhmHDhg14/PhxjX0mJibi7Nmz2LRpExwdHREbGyu6Q3fu3Dn4+fnB0dER5ubm8PT0BABkZ2dX2WZKSgqePHkCLy8vyOVy4fPTTz/h+vXr1Y6nbdu2wn83bNgQAIS7kBXL1PNc1Zxdu3YNZWVlWvuIj49Hjx49YGlpCQCYMGECvvjiC/To0QMRERG4ePFitWNk7J+GEzrGGGPsDdS7d2+cP38eV69exZMnT7Bjxw5YW1sL9WZmZqJ4IoJEItFop6ryqtSpU0d43E6t4mOQJiYmOrdVlcrtVyyvONaKiQ8ASCQS0bb79u1Dy5Yt4ejoqHPfleeiYp8ODg64evUqvvnmG5iYmGDMmDHo1asXSkpKYG5uLiRmjRo1wueff4527drVuPpkkyZN4OrqisGDB2Pu3Ll4//33UVRUBAB49OgR3n33Xcjlcvz888/4888/sXPnTgBPH8WsSnl5OQBgz549OH/+vPBJSUmp8Xd0FedUvd/aytR9aDt/qjp+apUXqfnPf/6DjIwMDBs2DMnJyejYsaPoHycY+6fjhI4xxhh7A5mZmaFZs2ZwdHTUSGy0cXNzQ3Z2Nv766y+hLCUlBSqVCi1btgQAtGzZEidPnhRtV/m7lZWVaOGRsrIyXLp0Sfjepk0blJeXV/lbLalUKmxX3VhLS0tFi4Pcv38faWlpwlh1ERcXp/PdOeDp/h8/flxUduLECVGfJiYmGDBgAFasWIEjR44gKSkJycnJAABDQ0P07dsXixcvxsWLF5GZmYnffvtN5/6HDRuG8vJy4XeLV65cwb1797Bo0SL07NkTLVq00FgBU9t8urm5QSaTITs7G82aNRN9Kt6hfRHc3Ny0zpmrqysMDAw04gsKCpCQkKBxXBwcHBAaGoodO3Zg8uTJ+OGHH17oOBn7OzN83QNgjDHG2N9f37590bZtWwQFBSE6OhqlpaUYM2YMPDw80LFjRwDAxIkTERISgo4dO+Ltt9/Ghg0bcPnyZTg7Owvt9OnTB+Hh4dizZw+aNm2KqKgo0V0oJycnhISE4N///jdWrFiBdu3aISsrC3fu3IG/vz8cHR0hkUiwe/du9O/fHyYmJhoLYLi4uMDPzw8jR47Ed999B3Nzc3z66aews7PT+fUDpaWl2LdvHw4fPqxRd+vWLWGhGLXGjRtj6tSp8Pf3R4cOHfDOO+/gv//9L3bs2CG0ERsbi7KyMnTp0gWmpqZYv349TExM4OjoiN27dyMjIwO9evVCvXr1sHfvXpSXl6N58+Y6jRd4evczLCwMX3zxBUaPHo3GjRtDKpVi5cqVCA0NxaVLlzTe1adtPs3NzTFlyhRMmjQJ5eXlePvtt5Gfn48TJ05ALpcjJCRE5zHVZPLkyejUqRPmz5+PwYMHIykpCV9//XWVi+ns378fLi4uonMqLCwMPj4+cHV1xYMHD/Dbb7/plbgzVuu9tl/vMcYYY+y1qLwoSmURERGihUzUsrKyaMCAAWRmZkbm5ub00Ucf0e3bt0UxX375JTVo0IDkcjmFhITQtGnTRG0VFxfTJ598QpaWlmRtbU0LFy4ULYpCRFRYWEiTJk2iRo0akVQqpWbNmtHatWuF+nnz5pGNjQ1JJBJhu8qLreTm5tKwYcNIoVCQiYkJ9evXj9LS0oT6mJgYUigUorHv3LmT1JdGhw8fJnt7e405cHR0JAAan5iYGCIiWrVqFTk7O5ORkRG5urrSTz/9JGq/S5cuZGFhQWZmZtS1a1c6fPgwERElJiaSh4cH1atXj0xMTKht27a0ZcsWjf7VqlocpqCggOrVq0dfffUVERFt3LiRnJycSCaTUbdu3Sg+Pp4A0Llz56qdz/Lyclq+fDk1b96cjIyMyMrKivr160dHjx6tckzaFowBQDt37hS+37hxQ6P/bdu2kZubGxkZGVHjxo1pyZIlVbY7dOhQmjlzpqh+3Lhx1LRpU5LJZGRlZUXDhg2je/fuVTlOxv5pJEQ1PKjMGGOMMfaGmTBhAkpLS5/ptQvs5SgrK4O1tTX27duHzp07v+7hMPa3wY9cMsYYY4xV0rp1a71X6GQv1/379zFp0iR06tTpdQ+Fsb8VvkPHGGOMMcYYY7UUr3LJGGOMMcYYY7UUJ3SMMcYYY4wxVktxQscYY4wxxhhjtRQndIwxxhhjjDFWS3FCxxhjjDHGGGO1FCd0jDHGGGOMMVZLcULHGGOMMcYYY7UUJ3SMMcYYY4wxVktxQscYY4wxxhhjtdT/A43PIzjNPtvgAAAAAElFTkSuQmCC", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plotROP(ssys,\"CH2O2X\",sol.t[end];N=15,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 189, - "id": "e8bb3c43", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Net ROPs for species CHO2X is: 4.896033948051534e-11\n", - "Showing the reaction with 1 th highest ROP for species CHO2X:\n", - "proton+CO2X<=>CHO2X\n", - "ROP = 0.0003354304417636066\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e14\n", - " n: Float64 0.0\n", - " Ea: Float64 39427.88604616099\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 2 th highest ROP for species CHO2X:\n", - "CHO2X<=>CO2HX\n", - "ROP = -0.0003234358448538966\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 2.4999999999999995e12\n", - " n: Float64 0.0\n", - " Ea: Float64 60523.33333333338\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 3 th highest ROP for species CHO2X:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = -2.961675818402313e-6\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 72182.65101792177\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 4 th highest ROP for species CHO2X:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = -2.961675818402313e-6\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 72182.65101792177\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 5 th highest ROP for species CHO2X:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = -2.961675818402313e-6\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 72182.65101792177\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 6 th highest ROP for species CHO2X:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = -2.961675818402313e-6\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 72182.65101792177\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 7 th highest ROP for species CHO2X:\n", - "CHO2X+CHO2X<=>CO2X+CH2O2X\n", - "ROP = -1.3862628938690782e-7\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 55042.035116348176\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 8 th highest ROP for species CHO2X:\n", - "HX+CO2<=>CHO2X\n", - "ROP = -9.093140564774802e-9\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 38294.07968295473\n", - " n: Float64 0.49999999999999933\n", - " Ea: Float64 73060.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 9 th highest ROP for species CHO2X:\n", - "CHO2X+OC[O][Pt]<=>CH2O2X+CH2O2X\n", - "ROP = -1.2121724384804543e-10\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 8.36e17\n", - " n: Float64 0.0\n", - " Ea: Float64 27244.51134303102\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 10 th highest ROP for species CHO2X:\n", - "CHO2X+O[CH](O)[Pt]<=>CH2O2X+CH2O2X\n", - "ROP = -4.0285657460251036e-12\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 8.36e17\n", - " n: Float64 0.0\n", - " Ea: Float64 17958.609591202912\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plotROP(ssys,\"CHO2X\",sol.t[end];N=10,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 190, - "id": "0bb84a7f", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Net ROPs for species CO2HX is: 5.846688442560449e-5\n", - "Showing the reaction with 1 th highest ROP for species CO2HX:\n", - "CHO2X<=>CO2HX\n", - "ROP = 0.0003234358448538966\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 2.4999999999999995e12\n", - " n: Float64 0.0\n", - " Ea: Float64 60523.33333333338\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 2 th highest ROP for species CO2HX:\n", - "CO2HX+CO2HX<=>CO2X+CH2O2X\n", - "ROP = -0.0002530984140316064\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 89323.26691949538\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 3 th highest ROP for species CO2HX:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = -2.961675818402313e-6\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 72182.65101792177\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 4 th highest ROP for species CO2HX:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = -2.961675818402313e-6\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 72182.65101792177\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 5 th highest ROP for species CO2HX:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = -2.961675818402313e-6\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 72182.65101792177\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 6 th highest ROP for species CO2HX:\n", - "CHO2X+CO2HX<=>CO2X+CH2O2X\n", - "ROP = -2.961675818402313e-6\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.18e17\n", - " n: Float64 0.0\n", - " Ea: Float64 72182.65101792177\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 7 th highest ROP for species CO2HX:\n", - "proton+CO2X<=>CO2HX\n", - "ROP = 3.354304417687343e-8\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 75249.98822394594\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 8 th highest ROP for species CO2HX:\n", - "proton+CO2HX<=>H2O+OCX\n", - "ROP = -2.5251650396860116e-8\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 24315.06048796024\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 9 th highest ROP for species CO2HX:\n", - "proton+CO2HX<=>CH2O2X\n", - "ROP = -2.5251650396860116e-8\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 48898.20910952594\n", - " q: Float64 0.5\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 10 th highest ROP for species CO2HX:\n", - "HX+CO2HX<=>vacantX+CH2O2X\n", - "ROP = -6.88286645959641e-9\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 2.308e18\n", - " n: Float64 0.0\n", - " Ea: Float64 70434.29992477236\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plotROP(ssys,\"CO2HX\",sol.t[end];N=10,tol=0.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 191, - "id": "7086e403", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Net ROPs for species OCX is: 2.715414043249991e-8\n", - "Showing the reaction with 1 th highest ROP for species OCX:\n", - "proton+CO2HX<=>H2O+OCX\n", - "ROP = 2.5251650396860116e-8\n", - "Arrheniusq{Float64, Float64, Float64, Float64, EmptyRateUncertainty, Float64}\n", - " A: Float64 2.5e10\n", - " n: Float64 0.0\n", - " Ea: Float64 24315.06048796024\n", - " q: Float64 0.25\n", - " V0: Float64 0.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 2 th highest ROP for species OCX:\n", - "HOX+OCX<=>vacantX+CO2HX\n", - "ROP = 1.93203864347582e-9\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 4.02e14\n", - " n: Float64 0.0\n", - " Ea: Float64 11500.0\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n", - "Showing the reaction with 3 th highest ROP for species OCX:\n", - "vacantX+vacantX+CO2<=>OX+OCX\n", - "ROP = -2.9548607836027356e-11\n", - "Arrhenius{Float64, Float64, Float64, EmptyRateUncertainty}\n", - " A: Float64 5.3487086644171274e8\n", - " n: Float64 0.5000000000002018\n", - " Ea: Float64 53637.00288687614\n", - " unc: EmptyRateUncertainty EmptyRateUncertainty()\n", - "\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure()" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plotROP(ssys,\"OCX\",sol.t[end])" - ] - }, - { - "cell_type": "code", - "execution_count": 192, - "id": "e1beedf1", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.10.10", - "language": "julia", - "name": "julia-1.10" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.10.10" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/CO2_Reduction_Cu3Sn/CO2RR_RMS_Diffusion_Interface_Cu3Sn.jl b/CO2_Reduction_Cu3Sn/CO2RR_RMS_Diffusion_Interface_Cu3Sn.jl new file mode 100644 index 0000000..8d5d685 --- /dev/null +++ b/CO2_Reduction_Cu3Sn/CO2RR_RMS_Diffusion_Interface_Cu3Sn.jl @@ -0,0 +1,606 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,jl:percent +# text_representation: +# extension: .jl +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.17.2 +# kernelspec: +# display_name: Julia 1.10.10 +# language: julia +# name: julia-1.10 +# --- + +# %% +using Pkg +Pkg.activate(ENV["PYTHON_JULIAPKG_PROJECT"]) +using ReactionMechanismSimulator + +# %% +using PythonPlot +using DifferentialEquations +using Sundials +using SciMLBase +using QuadGK + +# %% +outdict = readinput("Cu3Sn_RMS96.rms") + +# %% +boundarylayerspcs = outdict["gas"]["Species"] +boundarylayerrxns = outdict["gas"]["Reactions"] +surfspcs = outdict["surface"]["Species"] +surfrxns = outdict["surface"]["Reactions"] +interfacerxns = outdict[Set(["surface", "gas"])]["Reactions"] +solv = outdict["Solvents"][1]; + +# %% +sitedensity = 1.4319e-05; # Cu3Sn(0001) site density is 1.4319e-9 mol/cm^2 or 1.4319e-5 mol/m^2 +boundarylayer = IdealDiluteSolution(boundarylayerspcs,boundarylayerrxns,solv,name="boundarylayeruid",diffusionlimited=true); +surf = IdealSurface(surfspcs,surfrxns,sitedensity,name="surface"); + +# %% +# Reservoir is a 100 mL (100e-6 m^3) cell +# Proton concentration is 10^-7 mol/L (10^-4 mol/m^3) +# CO2 concentration is 0.01 mol/L (10 mol/m^3), saturation solubility ~0.03 mol/L +# AVratio in experiments is 36 m^-1 but is measured by surface area/reservoir volume +# Area of the electrode is therefore 3.6e1 m^-1 * 1e2 * 1e-6 m^3 = 3.6e-3 m^2 = 36 cm^2 +# Assume boundary layer thickness d_bl = 1 mm or 1e-3 m +# Volume of the boundary layer V_bl = 3.6e-3 m^2 * 1e-3 m = 3.6e-6 m^3 +# Actual AVratio is therefore 3.6e-3 m^2 / 3.6e-6 m^3 = 1e3 m^-1 (reciprocal of d_bl) +# Amount of sites is 2.943e-5 mol/m^2 * 3.6e-3 m^2 = 10.595e-8 mol + +# For earlier simulations, a 100x linear scale factor is applied, +# so volume becomes 100e-6 m^3 * (1e2)^3 = 100 m^3, +# electrode area becomes 3.6e-3 * (1e2) ^2 = 3.6e1 m^2, +# AVratio becomes 3.6e1 m^2 / 1e2 m^3 = 0.36 m^-1 +# Volume of the boundary layer becomes 3.6e1 m^2 * 1e-3 m = 3.6e-2 m^3 + +C_proton = 1e-7*1e3; +C_co2 = 1e-2*1e3; +C_default = 1e-12; +V_res = 1e3; +layer_thickness = 1e-4; # 100 microns +AVratio = 36; +A_surf = V_res*AVratio; +V_bl = A_surf*layer_thickness; +# V_bl = V_res; +sites = sitedensity*A_surf; + +# The initial conditions for individual species are moles not concentration, so we need to multiply concentration by boundary layer volume +initialcondsboundarylayer = Dict(["proton"=>C_proton*V_bl, + "CO2"=>C_co2*V_bl, + # "H2"=>C_default*10*V_bl, + # "O=CO"=>C_default*V_bl, + "V"=>V_bl,"T"=>300,"Phi"=>0.0,"d"=>0.0]); +initialcondsreservoir = Dict(["proton"=>C_proton, + "CO2"=>C_co2, + "V"=>V_res,"T"=>300]); + + +# Assume voltage is -1.0 V vs. R.H.E. which equates to -1.414 V vs. S.H.E. at pH=7 +initialcondssurf = Dict(["CO2X"=>0.1*sites, + # "CHO2X"=>0.1*sites, + # "CO2HX"=>0.1*sites, + # "OX"=>0.1*sites, + # "OCX"=>0.1*sites, + "vacantX"=>0.9*sites, + # "CH2O2X"=>0.05*sites, + # "CHOX"=>0.04*sites, + # "CH2OX"=>0.01*sites, + "A"=>A_surf,"T"=>300,"Phi"=>-1.914]); + +# %% +domainboundarylayer, y0boundarylayer, pboundarylayer = ConstantTVDomain(phase=boundarylayer, initialconds=initialcondsboundarylayer); +domaincat,y0cat,pcat = ConstantTAPhiDomain(phase=surf, + initialconds=initialcondssurf); + +# %% +# Set proton diffusivity to a higher value than calculated from Stokes Einstein equation +# The values are taken from DOI: 10.1039/C8SC01253A +# Values calculated from MD is 1.015 A^2/ps, experimental values are 0.932 A^2/ps. +# 1 A^2/ps = 1e-8 m^2/s +domainboundarylayer.diffusivity[6] = 0.932e-8 + +# %% +inter,pinter = ReactiveInternalInterfaceConstantTPhi(domainboundarylayer, + domaincat,interfacerxns,298.15,A_surf); + +# %% +# start with 1mm layer thickness +diffusionlayer = ConstantReservoirDiffusion(domainboundarylayer, initialcondsreservoir, A_surf, layer_thickness); + +# %% +interfaces = [inter, diffusionlayer]; + +# %% +@time react,y0,p = Reactor((domainboundarylayer,domaincat), (y0boundarylayer,y0cat), (0.0, 1e3), interfaces, (pboundarylayer,pcat,pinter)); + +# %% +@time sol = solve(react.ode,Sundials.CVODE_BDF(),abstol=1e-22,reltol=1e-8); +println(sol.t[end]); +println(sol.retcode); + +# %% +ssys = SystemSimulation(sol,(domainboundarylayer,domaincat,), interfaces,p); + +# %% +""" +diffusive flux to the reservoir +""" +function flux_to_reservoir(sim,t,reservoirinterface) + cs = concentrations(sim,t) + return reservoirinterface.A .* sim.domain.diffusivity .* (cs - reservoirinterface.c) / reservoirinterface.layer_thickness +end + +""" +Integrates the flux to the reservoir and computes the concentration assuming +there is no prior concentration of that species in the reservoir +""" +function get_reservoir_concentration(sim,t,reservoirinterface,Vres,C0) + intg,err = quadgk(x -> flux_to_reservoir(sim,x,reservoirinterface), 0, t); + intg[5] = 0; + intg[6] = 0; + return C0 + intg./Vres +end + +# %% +# Logarithmic time scale +t_vals = 10 .^ range(-12, stop=3, length=160); + +# Compute reservoir concentrations +flux_vals = [flux_to_reservoir(ssys.sims[1], t, diffusionlayer) for t in t_vals] + +conc_vals_bl = [concentrations(ssys.sims[1], t) for t in t_vals] +flux_matrix = hcat(flux_vals...); +conc_matrix_bl = hcat(conc_vals_bl...); + + +# %% +conc_0 = concentrations(ssys.sims[1], 0) +t_vals_2 = 10 .^ range(-9, stop=3, length=130); +conc_vals = [get_reservoir_concentration(ssys.sims[1], t, diffusionlayer, V_res, conc_0) for t in t_vals_2] +conc_matrix = hcat(conc_vals...); + +# %% +function plotC_Reservoir(sim, cs, tvals, tol, exclude) + clf() + xs = cs + maxes = maximum(xs, dims=2) + + time_filtered = tvals + xs_filtered = xs + + # Custom species order and their corresponding names and color + species_order = ["CO2", "proton", "H2", "O=CO", "C=O", "CO-2", "CCO", "CH4", "OCO", "COC", "COCO", "CC(=O)O", "COC=O"] + color_map = Dict("CO2" => "black", "proton" => "grey", "H2" => "green", + "O=CO" => "red", "C=O" => "brown", "CO-2" => "blue", "CCO" => "magenta", + "CH4" => "brown", "OCO" => "orange", "COC" => "teal", "COCO" => "lime", "CC(=O)O" => "teal", "COC=O" => "lime") + # Replacement map for species labels + replacement_map = Dict("CO-2" => "CH3OH", "O=CO" => "HCOOH", "C=O" => "HCHO", + "CCO" => "C2H5OH", "OCO" => "CH2(OH)2", "COC" => "CH3OCH3", "COCO" => "CH3OCH2OH", "CC(=O)O" => "CH3COOH", "COC=O" => "CH3OCHO") + + # Build a map of species names to indices + name_to_index = Dict(sim.domain.phase.species[i].name => i for i in 1:length(sim.domain.phase.species)) + # Keep track of whether the species is plotted, used for later checks + plotted = falses(length(sim.domain.phase.species)) + + # Plot species from the custom species dictionary + for species_name in species_order + if species_name in exclude + continue + end + + if haskey(name_to_index, species_name) + i = name_to_index[species_name] + + if (maxes[i] > tol) || (species_name == "proton") || (species_name == "CCO") # Always plot proton and ethanol + plot_label = get(replacement_map, species_name, species_name) + plot_color = color_map[species_name] + + plot(time_filtered, xs_filtered[i, :]/1000, label=plot_label, color=plot_color) + plotted[i] = true # Mark as plotted + end + end + end + + # Plot any remaining species that passed tolerance but were not in species_order + for i in 1:length(sim.domain.phase.species) + if plotted[i] || sim.domain.phase.species[i].name in exclude + continue + end + + if maxes[i] > tol + species_name = sim.domain.phase.species[i].name + plot(time_filtered, xs_filtered[i, :]/1000, label=species_name) # Default color + end + end + + xlabel("Time (s)", fontsize=14) + ylabel("Bulk Concentration (mol/L)", fontsize=14) + xticks(fontsize=14) + yticks(fontsize=14) + legend(loc="upper left", bbox_to_anchor=(0, 0.9), fontsize=12, ncol=2) +end + +# %% +exclude_species = ["H2O", "O=CC=O", "O=CCO", "CC=O"] +plotC_Reservoir(ssys.sims[1], conc_matrix, t_vals_2, 1e-12, exclude_species) + +xscale("log") +yscale("log") +xlim(1e-9, 1e3) +ylim(1e-20, 1e-1) +legend(loc="upper left", bbox_to_anchor=(0, 0.9), fontsize=12, ncol=2) +title("Cu3Sn0001@-1.5V vs. R.H.E., d = 100 um") +gcf() + +# %% +clf() + +for i in 1:size(flux_matrix, 1) + if maximum(abs.(flux_matrix[i, :])) > 1e-10 + plot(t_vals, abs.(flux_matrix[i, :]), label=ssys.sims[1].domain.phase.species[i].name) + + end +end + +xscale("log") +yscale("log") +xlabel("Time (s)") +ylabel("Diffusive Flux (mol/s)") +xlim(1e-12, 1e3) +ylim(1e-9, 1e1) +legend() +tight_layout() +gcf() + +# %% +clf() +for i in 1:size(conc_matrix_bl, 1) + if maximum(conc_matrix_bl[i, :]) > 1e-10 + plot(t_vals, conc_matrix_bl[i, :]/1e3, label=ssys.sims[1].domain.phase.species[i].name) + + end +end + +xscale("log") +yscale("log") +xlabel("Time (s)") +ylabel("Boundary Layer Concentrations (mol/L)") +xlim(1e-12, 1e3) +ylim(1e-18, 1) +legend() +tight_layout() +gcf() + +# %% +# Helper function +function plotX(sim, tol, t_end, exclude) + clf() + xs = molefractions(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + for i = 1:length(maxes) + species_name = sim.domain.phase.species[i].name + if maxes[i] > tol && !(species_name in exclude) + plot(time_filtered, xs_filtered[i,:], label=species_name) + end + end + legend() + xlabel("Time (s)") + ylabel("Concentration (mol/m^3)") +end + +# %% +function plotC(sim, tol, t_end, exclude) + clf() + xs = concentrations(sim) + maxes = maximum(xs, dims=2) + + # Filter time data up to t_end + time_indices = findall(t -> t <= t_end, sim.sol.t) + time_filtered = sim.sol.t[time_indices] + xs_filtered = xs[:, time_indices] + + # Custom species order and their corresponding names and color + species_order = ["CO2", "proton", "H2", "O=CO", "C=O", "CO-2", "CCO", "CH4", "OCO", "COC", "COCO", "CC(=O)O", "COC=O"] + color_map = Dict("CO2" => "black", "proton" => "grey", "H2" => "green", + "O=CO" => "red", "C=O" => "brown", "CO-2" => "blue", "CCO" => "magenta", + "CH4" => "brown", "OCO" => "orange", "COC" => "teal", "COCO" => "lime", "CC(=O)O" => "teal", "COC=O" => "lime") + # Replacement map for species labels + replacement_map = Dict("CO-2" => "CH3OH", "O=CO" => "HCOOH", "C=O" => "HCHO", + "CCO" => "C2H5OH", "OCO" => "CH2(OH)2", "COC" => "CH3OCH3", "COCO" => "CH3OCH2OH", "CC(=O)O" => "CH3COOH", "COC=O" => "CH3OCHO") + + # Build a map of species names to indices + name_to_index = Dict(sim.domain.phase.species[i].name => i for i in 1:length(sim.domain.phase.species)) + # Keep track of whether the species is plotted, used for later checks + plotted = falses(length(sim.domain.phase.species)) + + # Plot species from the custom species dictionary + for species_name in species_order + if species_name in exclude + continue + end + + if haskey(name_to_index, species_name) + i = name_to_index[species_name] + + if (maxes[i] > tol) || (species_name == "proton") || (species_name == "CCO") # Always plot proton and ethanol + plot_label = get(replacement_map, species_name, species_name) + plot_color = color_map[species_name] + + plot(time_filtered, xs_filtered[i, :]/1000, label=plot_label, color=plot_color) + plotted[i] = true # Mark as plotted + end + end + end + + # Plot any remaining species that passed tolerance but were not in species_order + for i in 1:length(sim.domain.phase.species) + if plotted[i] || sim.domain.phase.species[i].name in exclude + continue + end + + if maxes[i] > tol + species_name = sim.domain.phase.species[i].name + plot(time_filtered, xs_filtered[i, :]/1000, label=species_name) # Default color + end + end + + xlabel("Time (s)", fontsize=14) + ylabel("Boundary Layer Concentration (mol/L)", fontsize=14) + xticks(fontsize=14) + yticks(fontsize=14) + legend(loc="upper left", bbox_to_anchor=(0, 0.9), fontsize=12, ncol=2) +end + +# %% +exclude_species = ["H2O", "O=CC=O", "O=CCO", "CC=O"] +plotC(ssys.sims[1], 1e-12, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e3) +ylim(1e-20, 1e-1) +title("Cu3Sn0001@-1.5V vs. R.H.E., d = 10 um") +gcf() + +# %% +exclude_species = ["H2O"] +plotX(ssys.sims[2], 1e-4, 1e3, exclude_species) +xscale("log") +yscale("log") +xlim(1e-12, 1e3) +ylim(1e-6, 5) +title("Surface Mole Fractions vs. Time on Cu3Sn0001@-1.5V") +gcf() + +# %% +ts = 10.0 .^ range(-10, 3; step=1) +fd1 = makefluxdiagrams(ssys, ts) + +# %% +getfluxdiagram(ssys, 1e3); + +# %% +species_list = ["CO2", "CO2X", "CO2HX", "CH2O2X", "O=CO"]; +spc_names = [s.name for s in ssys.species]; +G_val = Float64[]; +T = 300.0; + +for spc in species_list + ind = findfirst(==(spc), spc_names); + if isnothing(ind) + @warn "Species $spc not found" + push!(G_val, NaN); + else + sp = ssys.species[ind]; + G = getGibbs(sp.thermo, T); + push!(G_val, G); + end +end + +# %% +dG + +# %% +dG = G_val .- G_val[1]; + +clf() +for (i, name) in enumerate(species_list) + hline([dG[i]], label=name, linewidth=2) +end +gcf() + +# %% +function plotROP(ssys,name,t;N=0,tol=0.01) + clf() + rop = rops(ssys, name, t) + inds = rop.nzind[reverse(sortperm(abs.(rop.nzval)))] + if N == 0 + N = length(inds) + elseif N > length(inds) + N = length(inds) + end + inds = inds[1:N] + mval = abs(rop[inds[1]]) + minval = mval*tol + k = 1 + while k < length(inds) && abs(rop[inds[k]]) >= minval + k += 1 + end + inds = inds[1:k] + net_rops = sum(rop[inds]) + println("Net ROPs for species $name is: $net_rops") + + for (i, j) in enumerate(inds) + println("Showing the reaction with $i th highest ROP for species $name:") + println(getrxnstr(ssys.reactions[j])) + println("ROP = ", rop[inds[i]]) + println(ssys.reactions[j].kinetics) + end + + xs = Array{Float64,1}(1:length(inds)) + barh(xs,reverse(rop[inds])) + yticks(xs,reverse(getrxnstr.(ssys.reactions[inds]))) + xlabel("Production/Loss Rate mol/s") + gcf() +end + +# %% +function PrintKinDetail(inter, speciesname) + println("Showing Kinetics details for reactions involving species $speciesname\n") + for (i,rxn) in enumerate(inter.reactions) + flag = false + for j = 1:length(rxn.reactants) + if rxn.reactants[j].name == speciesname + flag = true + end + end + for j = 1:length(rxn.products) + if rxn.products[j].name == speciesname + flag = true + end + end + if flag + println(getrxnstr(rxn)) + println(rxn.kinetics) + kf = inter.kfs[i] + krev = inter.krevs[i] + kc = kf/krev + println("kf = $kf") + println("krev = $krev") + println("Kc = $kc\n") + end + end +end + +# %% +""" +Integrates the ROP in the boundary layer and computes the concentration +""" +function get_boundary_layer_concentration(sim,t,spc,Vbl,C_0) + intg,err = quadgk(x -> sum(rops(sim,spc,t)), 0, t); + return C_0 + intg ./ Vbl; +end + +# %% +""" +diffusive flux to the reservoir using concentration from ROP integration +""" +function flux_to_reservoir_2(bsol,t,spc,Vbl,C_0,reservoirinterface) + cs = get_boundary_layer_concentration(bsol,t,spc,Vbl,C_0) + spc_idx = findfirst(s -> s.name == spc, bsol.sims[1].species) + d = bsol.sims[1].domain.diffusivity[spc_idx]; + c_res = reservoirinterface.c[spc_idx]; + return reservoirinterface.A * d * (cs - c_res) / reservoirinterface.layer_thickness +end + +# %% +# Compute ROP over time +ROP_vals = [sum(rops(ssys, "O=CO", t)) for t in t_vals]; +# Compute boundary layer accumulation by integration +Cbl_vals = [get_boundary_layer_concentration(ssys, t, "O=CO", V_bl, C_default) for t in t_vals]; +# Compute flux over time using Cbl_vals +F_vals = [flux_to_reservoir_2(ssys, t, "O=CO", V_bl, C_default, diffusionlayer) for t in t_vals]; + +# %% +# Plots the ROP of O=CO +clf() + +plot(t_vals, ROP_vals) + +xscale("log") +xlim(1e-11,1e3) +yscale("log") +ylim(1e-8,1e2) +xlabel("Time (s)") +ylabel("Rate of Progress (mol/s)") +legend() +tight_layout() +gcf() + +# %% +# Plots the Boundary Layer Concentration of O=CO from ROP Integration WITHOUT Diffusion Flux Into Reservoir +clf() + +plot(t_vals, Cbl_vals) + +xscale("log") +xlim(1e-11,1e3) +yscale("log") +ylim(1e-13,1e1) +xlabel("Time (s)") +ylabel("Concentration (mol/m^3)") +title("Boundary Layer Accumulation of O=CO from ROP Integration") +legend() +tight_layout() +gcf() + +# %% +# Plots the Diffusive Flux of O=CO using ROP Integration +clf() + +plot(t_vals, F_vals) + +xscale("log") +xlim(1e-11,1e3) +yscale("log") +ylim(1e-15,1e1) +xlabel("Time (s)") +ylabel("Diffusive Flux (mol/m^3)") +title("Diffusive Flux of O=CO from ROP Integration") +legend() +tight_layout() +gcf() + +# %% +# Plots the Diffusion Flux Into Reservoir Using Integrated Concentration from ROP Analysis +clf() + +plot(t_vals, F_vals) + +xscale("log") +yscale("log") +xlabel("Time (s)") +ylabel("Diffusive Flux") +title("Diffusive Flux of O=CO from ROP Integration") +legend() +tight_layout() +gcf() + +# %% +plotROP(ssys, "proton",1e3;N=15,tol=0.0) + +# %% +plotROP(ssys, "H2",sol.t[end];N=15,tol=0.0) + +# %% +plotROP(ssys, "HX",sol.t[end];N=15,tol=0.0) + +# %% +plotROP(ssys, "OCX",sol.t[end];N=15,tol=0.0) + +# %% +plotROP(ssys, "O=CO",sol.t[end];N=15,tol=0.0) + +# %% +plotROP(ssys,"CH2O2X",sol.t[end];N=15,tol=0.0) + +# %% +plotROP(ssys,"CHO2X",sol.t[end];N=10,tol=0.0) + +# %% +plotROP(ssys,"CO2HX",sol.t[end];N=10,tol=0.0) + +# %% +plotROP(ssys,"OCX",sol.t[end]) + +# %% diff --git a/Project.toml b/Project.toml new file mode 100644 index 0000000..97ff2bc --- /dev/null +++ b/Project.toml @@ -0,0 +1,16 @@ +[deps] +CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b" +DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0" +DifferentialEquations = "0c46a032-eb83-5123-abaf-570d42b7fbaa" +GlobalSensitivity = "af5da776-676b-467e-8baf-acd8249e4f0f" +PythonPlot = "274fc56d-3b97-40fa-a1cd-1b4a50311bf9" +QuadGK = "1fd47b50-473d-5c70-9696-f719f8f3bcdc" +QuasiMonteCarlo = "8a4e6c94-4038-4cdc-81c3-7e6ffdb2a71b" +Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c" +ReactionMechanismSimulator = "c2d78dd2-25c4-5b79-bebc-be6c69dd440f" +SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462" +Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2" +Sundials = "c3572dad-4567-51f8-b174-8c6c989267f4" + +[sources.ReactionMechanismSimulator] +path = "../ReactionMechanismSimulator.jl" diff --git a/jupytext.toml b/jupytext.toml new file mode 100644 index 0000000..8efbab9 --- /dev/null +++ b/jupytext.toml @@ -0,0 +1,2 @@ +# Pair ipynb notebooks to jl +formats = "ipynb,jl" \ No newline at end of file