KMCLib: A general framework for lattice kinetic Monte Carlo (KMC) simulations

TL;DR

KMCLib is a flexible, Python-based framework for lattice kinetic Monte Carlo simulations, capable of modeling complex diffusion and reaction processes in various dimensions with customizable analysis tools.

Contribution

It introduces a modular, extensible KMC simulation framework with plugin support and efficient parallel performance, tailored for surface and solid-state diffusion studies.

Findings

Demonstrates scalability and parallel efficiency with simple and complex models

Supports detailed particle tracking and diffusion analysis

Enables custom model development without core modifications

Abstract

KMCLib is a general framework for lattice kinetic Monte Carlo (KMC) simulations. The program can handle simulations of the diffusion and reaction of millions of particles in one, two, or three dimensions, and is designed to be easily extended and customized by the user to allow for the development of complex custom KMC models for specific systems without having to modify the core functionality of the program. Analysis modules and on-the-fly elementary step diffusion rate calculations can be implemented as plugins following a well-defined API. The plugin modules are loosely coupled to the core KMCLib program via the Python scripting language. KMCLib is written as a Python module with a backend C++ library. After initial compilation of the backend library KMCLib is used as a Python module; input to the program is given as a Python script executed using a standard Python interpreter. We give a detailed description of the features and implementation of the code and demonstrate its scaling behavior and parallel performance with a simple one-dimensional A-B-C lattice KMC model and a more complex three-dimensional lattice KMC model of oxygen-vacancy diffusion in a fluorite structured metal oxide. KMCLib can keep track of individual particle movements and includes tools for mean square displacement analysis, and is therefore particularly well suited for studying diffusion processes at surfaces and in solids.