A fast species redistribution approach to accelerate the kinetic Monte Carlo simulation for heterogeneous catalysis

Xiao Ming Cao, Zheng Jiang Shao, P. Hu

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


The first-principles kinetic Monte Carlo (kMC) simulation has been demonstrated as a reliable multiscale modeling approach in silico to disclose the interplay among all the elementary steps in a complex reaction network for heterogeneous catalysis. Heterogeneous catalytic systems frequently contain fast surface diffusion processes of some adsorbates while the elementary steps in it would be much slower than those in fast diffusion. Consequently, the kMC simulation for these systems is easily trapped in the sub-basins of a super basin on a potential energy surface due to the continuous and repeated sampling of these fast processes, which would significantly increase the total accessible simulation time and even make it impossible to get the reasonable simulation results using the kMC simulation. In this work, we present an improved fast species redistribution (FSR) method for the kMC simulation to overcome the stiffness problem resulting from the low-barrier surface diffusion to accelerate the heterogeneous catalytic kMC simulation. Taking CO oxidations on Pt(111) and Pt(100) as examples, we demonstrate that the FSR approach can properly reproduce the results of an equivalent first-principles microkinetic model simulation with more reasonable reaction rates. The improved kMC simulation based on the FSR method can accurately incorporate the effect of the fast diffusion of species on the surface and provide several orders of magnitude of acceleration compared to the standard kMC simulation.

Original languageEnglish
Pages (from-to)7348-7364
Number of pages17
JournalPhysical Chemistry Chemical Physics
Issue number14
Early online date05 Mar 2020
Publication statusPublished - 14 Apr 2020

ASJC Scopus subject areas

  • Physics and Astronomy(all)
  • Physical and Theoretical Chemistry

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