Literature DB >> 29055300

Stochastic surface walking reaction sampling for resolving heterogeneous catalytic reaction network: A revisit to the mechanism of water-gas shift reaction on Cu.

Xiao-Jie Zhang1, Cheng Shang1, Zhi-Pan Liu1.   

Abstract

Heterogeneous catalytic reactions on surface and interfaces are renowned for ample intermediate adsorbates and complex reaction networks. The common practice to reveal the reaction mechanism is via theoretical computation, which locates all likely transition states based on the pre-guessed reaction mechanism. Here we develop a new theoretical method, namely, stochastic surface walking (SSW)-Cat method, to resolve the lowest energy reaction pathway of heterogeneous catalytic reactions, which combines our recently developed SSW global structure optimization and SSW reaction sampling. The SSW-Cat is automated and massively parallel, taking a rough reaction pattern as input to guide reaction search. We present the detailed algorithm, discuss the key features, and demonstrate the efficiency in a model catalytic reaction, water-gas shift reaction on Cu(111) (CO + H2OCO2 + H2). The SSW-Cat simulation shows that water dissociation is the rate-determining step and formic acid (HCOOH) is the kinetically favorable product, instead of the observed final products, CO2 and H2. It implies that CO2 and H2 are secondary products from further decomposition of HCOOH at high temperatures. Being a general purpose tool for reaction prediction, the SSW-Cat may be utilized for rational catalyst design via large-scale computations.

Entities:  

Year:  2017        PMID: 29055300     DOI: 10.1063/1.4989540

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  6 in total

1.  Artificial intelligence pathway search to resolve catalytic glycerol hydrogenolysis selectivity.

Authors:  Pei-Lin Kang; Yun-Fei Shi; Cheng Shang; Zhi-Pan Liu
Journal:  Chem Sci       Date:  2022-06-20       Impact factor: 9.969

Review 2.  Reaction prediction via atomistic simulation: from quantum mechanics to machine learning.

Authors:  Pei-Lin Kang; Zhi-Pan Liu
Journal:  iScience       Date:  2020-12-30

Review 3.  Dynamics of Heterogeneous Catalytic Processes at Operando Conditions.

Authors:  Xiangcheng Shi; Xiaoyun Lin; Ran Luo; Shican Wu; Lulu Li; Zhi-Jian Zhao; Jinlong Gong
Journal:  JACS Au       Date:  2021-11-04

4.  Autonomous Reaction Network Exploration in Homogeneous and Heterogeneous Catalysis.

Authors:  Miguel Steiner; Markus Reiher
Journal:  Top Catal       Date:  2022-01-13       Impact factor: 2.910

5.  Deep reaction network exploration at a heterogeneous catalytic interface.

Authors:  Qiyuan Zhao; Yinan Xu; Jeffrey Greeley; Brett M Savoie
Journal:  Nat Commun       Date:  2022-08-18       Impact factor: 17.694

Review 6.  Towards operando computational modeling in heterogeneous catalysis.

Authors:  Lukáš Grajciar; Christopher J Heard; Anton A Bondarenko; Mikhail V Polynski; Jittima Meeprasert; Evgeny A Pidko; Petr Nachtigall
Journal:  Chem Soc Rev       Date:  2018-11-12       Impact factor: 54.564

  6 in total

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