Add spline-based data driven binding model

[jbreue16]

Corresponding CADET-Verification branch with python scripts: cadet/CADET-Verification#97

This PR introduces a new binding model type ("SPLINE" and "EXT_SPLINE") that replaces analytical adsorption isotherms with a monotonic cubic spline interpolation of user-provided equilibrium data.

Instead of evaluating a predefined isotherm (e.g., Langmuir), the model computes the equilibrium solid-phase concentration q* from tabulated (C_VALS, Q_VALS) data using cubic spline interpolation. The resulting equilibrium relation is embedded into the standard kinetic formulation:

dq/dt = kKin * (q* - q)

Key features:

• Reads equilibrium data from:
  model_weights/spline_input_parameters/{C_VALS, Q_VALS}
• Constructs a monotonic cubic spline at configuration time
• Stores spline polynomial coefficients for efficient runtime evaluation
• Supports left and right extrapolation
• Provides an analytic Jacobian using the spline derivative
• Fully compatible with CADET’s ParamHandler infrastructure
• Implements both internal (SPLINE) and external (EXT_SPLINE) variants

This enables:

• Data-driven or ML-generated adsorption isotherms
• Arbitrary nonlinear equilibrium behaviour

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