A global reaction route mapping-based kinetic Monte Carlo algorithm

Izaac Mitchell; Stephan Irle; Alister J. Page

doi:10.1063/1.4954660

A global reaction route mapping-based kinetic Monte Carlo algorithm

Izaac Mitchell, Stephan Irle, Alister J. Page

Research output: Contribution to journal › Article › peer-review

12 Scopus citations

Abstract

We propose a new on-the-fly kinetic Monte Carlo (KMC) method that is based on exhaustive potential energy surface searching carried out with the global reaction route mapping (GRRM) algorithm. Starting from any given equilibrium state, this GRRM-KMC algorithm performs a one-step GRRM search to identify all surrounding transition states. Intrinsic reaction coordinate pathways are then calculated to identify potential subsequent equilibrium states. Harmonic transition state theory is used to calculate rate constants for all potential pathways, before a standard KMC accept/reject selection is performed. The selected pathway is then used to propagate the system forward in time, which is calculated on the basis of 1st order kinetics. The GRRM-KMC algorithm is validated here in two challenging contexts: intramolecular proton transfer in malonaldehyde and surface carbon diffusion on an iron nanoparticle. We demonstrate that in both cases the GRRM-KMC method is capable of reproducing the 1st order kinetics observed during independent quantum chemical molecular dynamics simulations using the density-functional tight-binding potential.

Original language	English
Article number	024105
Journal	Journal of Chemical Physics
Volume	145
Issue number	2
DOIs	https://doi.org/10.1063/1.4954660
State	Published - Jul 14 2016
Externally published	Yes

Funding

A.J.P. and S.I. acknowledge support from the Australian Research Council (ARC No. DP140102894) and the Japan Society for the Promotion of Science (Open Partnership No. 13039901-000174). This work was supported in part by two CREST (Core Research for Evolutional Science and Technology) grants to S.I. from JST. S.I. and A.J.P. acknowledge support by the JSPS Sakura program for bilateral researcher exchange. I.M. acknowledges an Australian Postgraduate Award. The authors are grateful for generous supercomputing grants from The National Computational Infrastructure (NCI) National Facility and INTERSECT, Australia.

Funders	Funder number
INTERSECT
National Computational Infrastructure
Australian Research Council	DP140102894
Japan Society for the Promotion of Science	13039901-000174, 26410013
Japan Science and Technology Agency
Core Research for Evolutional Science and Technology

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A global reaction route mapping-based kinetic Monte Carlo algorithm

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