Volume 11, Issue 4 e1530
Advanced Review

Concepts, models, and methods in computational heterogeneous catalysis illustrated through CO2 conversion

Ángel Morales-García

Ángel Morales-García

Departament de Ciència de Materials i Química Física & Institut de Química Teòrica i Computacional (IQTCUB), Universitat de Barcelona, Barcelona, Spain

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Francesc Viñes

Francesc Viñes

Departament de Ciència de Materials i Química Física & Institut de Química Teòrica i Computacional (IQTCUB), Universitat de Barcelona, Barcelona, Spain

Contribution: Conceptualization, Formal analysis, Methodology, Visualization, Writing - original draft, Writing - review & editing

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José R. B. Gomes

José R. B. Gomes

CICECO—Aveiro Institute of Materials, Department of Chemistry, University of Aveiro, Aveiro, Portugal

Contribution: Conceptualization, Formal analysis, Methodology, Visualization, Writing - original draft, Writing - review & editing

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Francesc Illas

Corresponding Author

Francesc Illas

Departament de Ciència de Materials i Química Física & Institut de Química Teòrica i Computacional (IQTCUB), Universitat de Barcelona, Barcelona, Spain

Correspondence

Francesc Illas, Departament de Ciència de Materials i Química Física, Universitat de Barcelona, C/Martí i Franquès 1-11, 08028 Barcelona, Spain.

Email: [email protected]

Contribution: Conceptualization, Formal analysis, Funding acquisition, Methodology, Supervision, Writing - review & editing

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First published: 03 April 2021
Citations: 16

Edited by: Modesto Orozco, Associate Editor

Funding information: European Cooperation in Science and Technology, Grant/Award Number: CA18234; Fundação para a Ciência e a Tecnologia, Grant/Award Number: UIDB/50011/2020; Generalitat de Catalunya, Grant/Award Number: 2017SGR13; Institució Catalana de Recerca i Estudis Avançats, 2015 ICREA Academia Award; Ministerio de Ciencia, Innovación y Universidades, Grant/Award Numbers: IJCI-2017-31979, MDM-2017-0767, RTI2018-095460-B-I00

Abstract

Theoretical investigations and computational studies have notoriously contributed to the development of our understanding of heterogeneous catalysis during the last decades, when powerful computers have become generally available and efficient codes have been written that can make use of the new highly parallel architectures. The outcomes of these studies have shown not only a predictive character of theory but also provide inputs to experimentalists to rationalize their experimental observations and even to design new and improved catalysts. In this review, we critically describe the advances in computational heterogeneous catalysis from different viewpoints. We firstly focus on modeling because it constitutes the first key step in heterogenous catalysis where the systems involved are tremendously complex. A realistic description of the active sites needs to be accurately achieved to produce trustable results. Secondly, we review the techniques used to explore the potential energy landscape and how the information thus obtained can be used to bridge the gap between atomistic insight and macroscale experimental observations. This leads to the description of methods that can describe the kinetic aspects of catalysis, which essentially encompass microkinetic modeling and kinetic Monte Carlo simulations. The puissance of computer simulations in heterogeneous catalysis is further illustrated by choosing CO2 conversion catalyzed by different materials for most of which a comparison between computational information and experimental data is available. Finally, remaining challenges and a near future outlook of computational heterogeneous catalysis are provided.

This article is categorized under:

  • Structure and Mechanism > Computational Materials Science
  • Structure and Mechanism > Reaction Mechanisms and Catalysis

Graphical Abstract

Key aspects of computational heterogeneous catalysis are analyzed by taking the case of CO2 conversion as an example

CONFLICT OF INTEREST

The authors have declared no conflicts of interest for this article.

DATA AVAILABILITY STATEMENT

Data sharing is not applicable to this article as no new data were created or analyzed in this study.