A General Stiffness-Scaling Framework for Accelerating Graph-Theoretical Kinetic Monte Carlo Simulations
Hector Prats1, Weitian Li1, Michail Stamatakis1
1Inorganic Chemistry Laboratory, University of Oxford, South Parks Road, Oxford OX1 3QR, U.K.
Journal of Chemical Theory and Computation
|November 18, 2025
Summary
This study introduces a novel algorithm to accelerate Kinetic Monte Carlo (KMC) simulations of catalytic reactions by dynamically adjusting rates of fast processes, overcoming simulation stiffness without significant error.
Area of Science:
- Computational Chemistry
- Surface Science
- Chemical Kinetics
Background:
- Kinetic Monte Carlo (KMC) simulations are vital for studying catalytic mechanisms.
- Simulation "stiffness" arises from disparate reaction rates, hindering efficiency.
- Existing methods for stiffness have limitations in adaptivity and rate adjustment.
Purpose of the Study:
- To develop a new algorithm for overcoming stiffness in KMC simulations.
- To enable accurate and efficient simulations of complex catalytic systems.
- To provide a broadly accessible solution for KMC modeling challenges.
Main Methods:
- A novel reaction channel-based scaling algorithm is introduced.
- The algorithm dynamically upscales/downscales rate constants of quasi-equilibrated channels.
- The method is tested on benchmark and complex catalytic systems (RWGS, DRM, TPD on SAAs).
Main Results:
- The algorithm significantly accelerates KMC simulations across diverse catalytic systems.
- Simulations show minimal error introduction, validating the method's accuracy.
- The approach effectively handles complex models with multiple reaction channels and site types.
Conclusions:
- The developed algorithm offers a practical solution to stiffness in KMC simulations.
- It enhances the efficiency and accessibility of KMC studies in catalysis.
- The method is integrated into the Zacros code for widespread use.
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