化学
催化作用
动力学蒙特卡罗方法
领域(数学)
多相催化
生化工程
纳米技术
蒙特卡罗方法
材料科学
工程类
生物化学
统计
数学
纯数学
作者
Benjamin W. J. Chen,Lang Xu,Manos Mavrikakis
出处
期刊:Chemical Reviews
[American Chemical Society]
日期:2020-12-22
卷期号:121 (2): 1007-1048
被引量:423
标识
DOI:10.1021/acs.chemrev.0c01060
摘要
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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