Activity tutorial

11-Active-Particles-In-MD/00-index.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "0",
+   "metadata": {},
+   "source": [
+    "# Modelling Active Particles in MD\n",
+    "\n",
+    "This tutorial explains how to model **active, self-propelled particles** in MD simulations.\n",
+    "\n",
+    "**Prerequisites:**\n",
+    "\n",
+    "- This tutorial assumes you have some familiarity with the Python programming language.\n",
+    "- This tutorials assume basic understanding of the fundamentals of HOOMD-Blue.\n",
+    "- This tutorial uses an example with rod-shaped self-propelled particles which are made with Rigid Bodies in MD. Please refer to the [Modelling Rigid Bodies](../06-Modelling-Rigid-Bodies/00-index.ipynb) tutorial for more details as to how this is done.\n",
+    "- [Section 3](03-Motility-Induced-Phase-Separation-In-2D.ipynb) of this tutorial compresses the simualtion box as an example way to induce **Motility Induce Phase Separation (MIPS)**. Please refer to the [Introducing HOOMD-blue](../00-Introducing-HOOMD-blue/05-Compressing-the-System.ipynb) tutorial for more details as to how this is done."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1",
+   "metadata": {},
+   "source": [
+    "## Outline\n",
+    "\n",
+    "1. [Introduction to Active Particles](01-Introduction-to-Active-Particles.ipynb)\n",
+    "2. [Modelling Active Brownian Particles (ABP Model)](02-Active-Brownian-Particles.ipynb)\n",
+    "3. [Motility Induced Phase Separation (MIPS) in 2D Systems](03-Motility-Induced-Phase-Separation-In-2D.ipynb)\n",
+    "4. [Modelling Active Rigid Bodies with Active Applied Torques](04-Active-Torque-On-Rigid-Bodies.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2",
+   "metadata": {},
+   "source": [
+    "This tutorial is written with [jupyter](https://jupyter.org/). You can download the source from the [hoomd-examples](https://github.com/glotzerlab/hoomd-examples) repository."
+   ]
+  }
+ ],
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+   "name": "python3"
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+   "mimetype": "text/x-python",
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11-Active-Particles-In-MD/01-Introduction-to-Active-Particles.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "0",
+   "metadata": {},
+   "source": [
+    "# Introduction to Active Particle Systems\n",
+    "\n",
+    "## Overview\n",
+    "\n",
+    "### Questions\n",
+    "\n",
+    "* How can we model particles with self-induced **active forces**?\n",
+    "* What types of information can we learn from **non-equilibrium** systems?\n",
+    "\n",
+    "### Objectives\n",
+    "\n",
+    "* Introduce the **Active Brownian Particle (ABP) model** \n",
+    "* Define **Motility-Induced Phase Separation (MIPS)**. \n",
+    "* Discuss the mechanics of **rigid bodies responding to active forces** using torque as an example."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1",
+   "metadata": {},
+   "source": [
+    "## Introduction to Active Particles\n",
+    "\n",
+    "**Active particles** are particles that can consume stored energy or energy from the environment and convert it into directed motion. There are many different types of active particles with different mechanisms for this realized self-propulsion. For example, a polystyrene bead coated with platinum on one side (i.e. an example of a simple **Janus particle**, a particle with 2 of more regions of distinct physical properties) will be propelled forward if submerged in a solution containing hydrogen peroxide. This occurs because the platinum catalyzes a chemical reaction that decomposes the hydrogen peroxide into oxygen gas and water. This localized reaction propels the particle forward. In this example, thermal and chemical energy is being consumed to generate the kinetic motion of the (now active) Janus particle.\n",
+    "\n",
+    "In the previous HOOMD-blue tutorials, most of the systems have been models with which one could investigate **equilibrium properties** where the steady state is independent of kinetic parameters. When studying **active matter**, however, we are no longer considering equilibrium processes, and we shift our attention to **non-equilibrium dynamics**. Regardless, we can set up the initial state of the simulation in a very similar manner to previous methods we have used in [earlier hoomd MD simulation tutorials](../01-Introducing-Molecular-Dynamics/00-index.ipynb). "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1bf55e0d-a51e-4782-a6bb-1145a4de5391",
+   "metadata": {},
+   "source": [
+    "### Active Particles and their Phenomena:\n",
+    "There are a few categories of active particles. Here we introduce the commonly discussed  **Active Brownian Particle (ABP)**. Cates and Tailleur have a helpful figure distinguishing this active particle type from others their [2015 Annual Review Condensed Matter Physics Paper](https://www.annualreviews.org/content/journals/10.1146/annurev-conmatphys-031214-014710). The left image shows an example cartoon trajectory of an alternate type of active particle called a Run-and-Tumble particle (Fig. a), and the right shows an example cartoon trajectory for an ABP (Fig. b). This tutorial focuses on modeling **dry active matter** with ABPs. \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0fe709c5-c4da-47a7-8258-800d548ca347",
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