4.6 Article

Surface reaction kinetics of the methanol synthesis and the water gas shift reaction on Cu/ZnO/Al2O3

Journal

REACTION CHEMISTRY & ENGINEERING
Volume 6, Issue 5, Pages 868-887

Publisher

ROYAL SOC CHEMISTRY
DOI: 10.1039/d1re00040c

Keywords

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Funding

  1. Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES) [88881.174609/2018-01]
  2. Helmholtz Research Program Storage and Cross-linked Infrastructures

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A three-site mean-field extended microkinetic model was developed based on ab initio DFT calculations to simulate the conversion of syngas to methanol on Cu (211) and Cu/Zn (211). Experiments and literature data were used for model validation, showing formic acid hydrogenation as the major rate controlling step. The developed model contributes to understanding reaction kinetics for industrial processes.
A three-site mean-field extended microkinetic model was developed based on ab initio DFT calculations from the literature, in order to simulate the conversion of syngas (H-2/CO/CO2) to methanol on Cu (211) and Cu/Zn (211). The reaction network consists of 25 reversible reactions, including CO and CO2 hydrogenation to methanol and the water-gas shift reaction. Catalyst structural changes are also considered in the model. Experiments were performed in a plug flow reactor on Cu/ZnO/Al2O3 at various gas hourly space velocities (24-40 L h(-1) g(cat)(-1)), temperatures (210-260 degrees C), pressures (40-60 bar), hydrogen feed concentrations (35-60% v/v), CO feed concentrations (3-30% v/v), and CO2 feed concentrations (0-20% v/v). These experiments, together with experimental data from the literature, were used for a broad validation of the model (a total of 690 points), which adequately reproduced the measurements. A degree of rate control analysis showed that the hydrogenation of formic acid is the major rate controlling step, and formate is the most sensitive surface species. The developed model contributes to the understanding of the reaction kinetics, and should be applicable for industrial processes (e.g. scale-up and optimization).

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