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Title: Acceleration and sensitivity analysis of lattice kinetic Monte Carlo simulations using parallel processing and rate constant rescaling

Abstract

Kinetic Monte Carlo (KMC) simulation provides insights into catalytic reactions unobtainable with either experiments or mean-field microkinetic models. Sensitivity analysis of KMC models assesses the robustness of the predictions to parametric perturbations and identifies rate determining steps in a chemical reaction network. Stiffness in the chemical reaction network, a ubiquitous feature, demands lengthy run times for KMC models and renders efficient sensitivity analysis based on the likelihood ratio method unusable. We address the challenge of efficiently conducting KMC simulations and performing accurate sensitivity analysis in systems with unknown time scales by employing two acceleration techniques: rate constant rescaling and parallel processing. We develop statistical criteria that ensure sufficient sampling of non-equilibrium steady state conditions. Our approach provides the twofold benefit of accelerating the simulation itself and enabling likelihood ratio sensitivity analysis, which provides further speedup relative to finite difference sensitivity analysis. As a result, the likelihood ratio method can be applied to real chemistry. We apply our methodology to the water-gas shift reaction on Pt(111).

Authors:
 [1];  [1]; ORCiD logo [1]
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  1. Univ. of Delaware, Newark, DE (United States)
Publication Date:
Research Org.:
Univ. of Delaware, Newark, DE (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
OSTI Identifier:
1512927
Alternate Identifier(s):
OSTI ID: 1402107
Grant/Contract Number:  
SC0010549
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Chemical Physics
Additional Journal Information:
Journal Volume: 147; Journal Issue: 16; Journal ID: ISSN 0021-9606
Publisher:
American Institute of Physics (AIP)
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY

Citation Formats

Núñez, M., Robie, T., and Vlachos, D. G. Acceleration and sensitivity analysis of lattice kinetic Monte Carlo simulations using parallel processing and rate constant rescaling. United States: N. p., 2017. Web. doi:10.1063/1.4998926.
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Núñez, M., Robie, T., & Vlachos, D. G. Acceleration and sensitivity analysis of lattice kinetic Monte Carlo simulations using parallel processing and rate constant rescaling. United States. https://doi.org/10.1063/1.4998926
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Núñez, M., Robie, T., and Vlachos, D. G. Mon . "Acceleration and sensitivity analysis of lattice kinetic Monte Carlo simulations using parallel processing and rate constant rescaling". United States. https://doi.org/10.1063/1.4998926. https://www.osti.gov/servlets/purl/1512927.
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@article{osti_1512927,
title = {Acceleration and sensitivity analysis of lattice kinetic Monte Carlo simulations using parallel processing and rate constant rescaling},
author = {Núñez, M. and Robie, T. and Vlachos, D. G.},
abstractNote = {Kinetic Monte Carlo (KMC) simulation provides insights into catalytic reactions unobtainable with either experiments or mean-field microkinetic models. Sensitivity analysis of KMC models assesses the robustness of the predictions to parametric perturbations and identifies rate determining steps in a chemical reaction network. Stiffness in the chemical reaction network, a ubiquitous feature, demands lengthy run times for KMC models and renders efficient sensitivity analysis based on the likelihood ratio method unusable. We address the challenge of efficiently conducting KMC simulations and performing accurate sensitivity analysis in systems with unknown time scales by employing two acceleration techniques: rate constant rescaling and parallel processing. We develop statistical criteria that ensure sufficient sampling of non-equilibrium steady state conditions. Our approach provides the twofold benefit of accelerating the simulation itself and enabling likelihood ratio sensitivity analysis, which provides further speedup relative to finite difference sensitivity analysis. As a result, the likelihood ratio method can be applied to real chemistry. We apply our methodology to the water-gas shift reaction on Pt(111).},
doi = {10.1063/1.4998926},
journal = {Journal of Chemical Physics},
number = 16,
volume = 147,
place = {United States},
year = {Mon Oct 23 00:00:00 EDT 2017},
month = {Mon Oct 23 00:00:00 EDT 2017}
}
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Journal Article:
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Publisher's Version of Record
https://doi.org/10.1063/1.4998926
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Cited by: 23 works
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Figures / Tables:

FIG. 1 FIG. 1: Ratio of the variance of the estimate of the mean of a property and the variance of the property itself [i.e., the left-hand side of Eq. (6)] as a function of the length of the interval used for averaging (t̃) and the number of replicate trajectories (ntraj). Datamore » points show the variances of reaction rates. Simulation details are in Sec. SIIa of the supplementary material.« less
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    Works referencing / citing this record:

    A DFT and KMC based study on the mechanism of the water gas shift reaction on the Pd(100) surface
    journal, January 2020

    • Chutia, Arunabhiram; Thetford, Adam; Stamatakis, Michail
    • Physical Chemistry Chemical Physics, Vol. 22, Issue 6
    • DOI: 10.1039/c9cp05476f

    A Practical Guide to Surface Kinetic Monte Carlo Simulations
    journal, April 2019

    A Practical Guide to Surface Kinetic Monte Carlo Simulations
    text, January 2019

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      TABLE I (p. 7)table
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