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Computational Methods in Heterogeneous Catalysis
Author(s) -
Benjamin W. J. Chen,
Lang Xu,
Manos Mavrikakis
Publication year - 2020
Publication title -
chemical reviews
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 20.528
H-Index - 700
eISSN - 1520-6890
pISSN - 0009-2665
DOI - 10.1021/acs.chemrev.0c01060
Subject(s) - biochemical engineering , chemistry , nanotechnology , kinetic monte carlo , catalysis , heterogeneous catalysis , field (mathematics) , monte carlo method , engineering , materials science , biochemistry , statistics , mathematics , pure mathematics
The unprecedented ability of computations to probe atomic-level details of catalytic systems holds immense promise for the fundamentals-based bottom-up design of novel heterogeneous catalysts, which are at the heart of the chemical and energy sectors of industry. Here, we critically analyze recent advances in computational heterogeneous catalysis. First, we will survey the progress in electronic structure methods and atomistic catalyst models employed, which have enabled the catalysis community to build increasingly intricate, realistic, and accurate models of the active sites of supported transition-metal catalysts. We then review developments in microkinetic modeling, specifically mean-field microkinetic models and kinetic Monte Carlo simulations, which bridge the gap between nanoscale computational insights and macroscale experimental kinetics data with increasing fidelity. We finally review the advancements in theoretical methods for accelerating catalyst design and discovery. Throughout the review, we provide ample examples of applications, discuss remaining challenges, and provide our outlook for the near future.

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