Multiscale modelling of CO2 reduction to methanol over industrial Cu/ ZnO/Al2O3 heterogeneous catalyst: Linking ab initio surface reaction kinetics with reactor fluid dynamics

JOURNAL OF CLEANER PRODUCTION

卷:275

Article

Pavlisic, Andraz¹  Hus, Matej¹  Prasnikar, Anze¹  Likozar, Blaz¹ 

[1] Natl Inst Chem, Dept Catalysis & Chem React Engn, Hajdrihova 19, Ljubljana 1001, Slovenia

关键词: Density functional theory (DFT);    Kinetic Monte Carlo (KMC);    Computational fluid dynamics (CFD);    Catalytic reaction microkinetic;    Hierarchical multiscale modelling;   

DOI  :  10.1016/j.jclepro.2020.122958

来源: Elsevier

【 摘 要 】

There has been a growing trend to couple different levels of modelling, such as going from first-principle calculations to the meso (e.g. kinetic Monte Carlo - KMC) and macro scale (e.g. computational fluid dynamics - CFD). In the current investigation, we put forward a CFD study of CO2 hydrogenation to methanol for heterogeneous reacting flows in reactors with complex shape geometries, coupled with first-principle calculations (density functional theory - DFT). KMC operation simulations were also performed to obtain insight into the uppermost layer conditions during the reaction. With computational fluid dynamics, the focus was placed on the non-uniform catalytic reduction of carbon dioxide to formate, which we treated with a detailed mean-field first-principle microkinetic model, analysed, and corroborated with experiments. The results showed a good consistent agreement with experimental data. The formulated methodological approach paves the way towards full virtual multiscale system descriptions of industrial processing units, encompassing all conventional stages, from catalyst design to the optimization of mass transfer parameters. Such a bridging is outlined for carbon capture and utilization. (C) 2020 Elsevier Ltd. All rights reserved.

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