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Title: A Lattice Kinetic Monte Carlo Solver for First-Principles Microkinetic Trend Studies

Abstract

Here, mean-field microkinetic models in combination with Brønsted–Evans–Polanyi like scaling relations have proven highly successful in identifying catalyst materials with good or promising reactivity and selectivity. Analysis of the microkinetic model by means of lattice kinetic Monte Carlo promises a faithful description of a range of atomistic features involving short-range ordering of species in the vicinity of an active site. In this paper, we use the “fruit fly” example reaction of CO oxidation on fcc(111) transition and coinage metals to motivate and develop a lattice kinetic Monte Carlo solver suitable for the numerically challenging case of vastly disparate rate constants. As a result, we show that for the case of infinitely fast diffusion and absence of adsorbate-adsorbate interaction it is, in fact, possible to match the prediction of the mean-field-theory method and the lattice kinetic Monte Carlo method. As a corollary, we conclude that lattice kinetic Monte Carlo simulations of surface chemical reactions are most likely to provide additional insight over mean-field simulations if diffusion limitations or adsorbate–adsorbate interactions have a significant influence on the mixing of the adsorbates.

Authors:
ORCiD logo [1];  [1]
  1. Stanford Univ., Stanford, CA (United States); SLAC National Accelerator Lab., Menlo Park, CA (United States)
Publication Date:
Research Org.:
SLAC National Accelerator Lab., Menlo Park, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
OSTI Identifier:
1457053
Grant/Contract Number:  
AC02-76SF00515
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Journal of Chemical Theory and Computation
Additional Journal Information:
Journal Volume: 14; Journal Issue: 3; Journal ID: ISSN 1549-9618
Publisher:
American Chemical Society
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; 97 MATHEMATICS AND COMPUTING

Citation Formats

Hoffmann, Max J., and Bligaard, Thomas. A Lattice Kinetic Monte Carlo Solver for First-Principles Microkinetic Trend Studies. United States: N. p., 2018. Web. doi:10.1021/acs.jctc.7b00683.
Hoffmann, Max J., & Bligaard, Thomas. A Lattice Kinetic Monte Carlo Solver for First-Principles Microkinetic Trend Studies. United States. doi:10.1021/acs.jctc.7b00683.
Hoffmann, Max J., and Bligaard, Thomas. Mon . "A Lattice Kinetic Monte Carlo Solver for First-Principles Microkinetic Trend Studies". United States. doi:10.1021/acs.jctc.7b00683.
@article{osti_1457053,
title = {A Lattice Kinetic Monte Carlo Solver for First-Principles Microkinetic Trend Studies},
author = {Hoffmann, Max J. and Bligaard, Thomas},
abstractNote = {Here, mean-field microkinetic models in combination with Brønsted–Evans–Polanyi like scaling relations have proven highly successful in identifying catalyst materials with good or promising reactivity and selectivity. Analysis of the microkinetic model by means of lattice kinetic Monte Carlo promises a faithful description of a range of atomistic features involving short-range ordering of species in the vicinity of an active site. In this paper, we use the “fruit fly” example reaction of CO oxidation on fcc(111) transition and coinage metals to motivate and develop a lattice kinetic Monte Carlo solver suitable for the numerically challenging case of vastly disparate rate constants. As a result, we show that for the case of infinitely fast diffusion and absence of adsorbate-adsorbate interaction it is, in fact, possible to match the prediction of the mean-field-theory method and the lattice kinetic Monte Carlo method. As a corollary, we conclude that lattice kinetic Monte Carlo simulations of surface chemical reactions are most likely to provide additional insight over mean-field simulations if diffusion limitations or adsorbate–adsorbate interactions have a significant influence on the mixing of the adsorbates.},
doi = {10.1021/acs.jctc.7b00683},
journal = {Journal of Chemical Theory and Computation},
number = 3,
volume = 14,
place = {United States},
year = {Mon Jan 22 00:00:00 EST 2018},
month = {Mon Jan 22 00:00:00 EST 2018}
}

Journal Article:
Free Publicly Available Full Text
This content will become publicly available on January 22, 2019
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Cited by: 1 work
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