Efficient reactive Brownian dynamics.

Area of Science:

• Computational Chemistry
• Chemical Physics
• Biophysics

Background:

• Reaction-diffusion systems are fundamental to many chemical and biological processes.
• Accurate particle-based simulations are needed to capture microscopic details.
• Existing methods face challenges with high particle densities and complex reaction kinetics.

Purpose of the Study:

• Develop a novel Split Reactive Brownian Dynamics (SRBD) algorithm.
• Ensure microscopic reaction rules are consistent with thermodynamic equilibrium.
• Provide a robust simulation tool for reaction-diffusion systems.

Main Methods:

• The SRBD algorithm employs Strang splitting for reaction and diffusion.
• It uses an event-driven approach for precise reaction processing.
• Solves subproblems exactly, even at high packing densities, independent of grid size.

Main Results:

• Computed effective macroscopic reaction rates for association reactions in 3D.
• Studied long-time tails in correlation functions for reversible association.
• Compared particle and continuum methods for Turing-like pattern formation.

Conclusions:

• Microscopic details significantly impact diffusion-limited systems.
• Continuum and mesoscopic models may be insufficient for these systems.
• Off-lattice particle diffusion with reactions can spuriously enhance diffusion coefficients.