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Comprehensive Study of Oxygen Vacancies on the Catalytic Performance of ZnO for CO/H~2~ Activation Using Machine Learning-Accelerated First-Principles Simulations by Yulan Han; Jiayan Xu; Wenbo Xie; Zhuozheng Wang; P. Hu is a Chemistry article available to read on EtoBox.

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Oxygen vacancies (OVs) play important roles on any oxide catalysts. In this work, using an investigation of the OV effects on ZnO(101̅ 0) for CO and H 2 activation as an example, we demonstrate, via machine learning potentials (MLPs), genetic algorithm (GA)-based global optimization, and density functional theory (DFT) validations, that the ZnO(101̅ 0) surface with 0.33 ML OVs is the most likely surface configuration under experimental conditions (673 K and 2.5 MPa syngas (H 2 :CO = 1.5)). It is found that a surface reconstruction from the wurtzite structure to a bodycentered-tetragonal one would occur in the presence of OVs. We show that the OVs create a Zn 3 cluster site, allowing H 2 homolysis and C-O bond cleavage to occur. Furthermore, the activity of intrinsic sites (Zn 3c and O 3c sites) is almost invariable, while the activity of the generated OV sites is strongly dependent on the concentration of the OVs. It is also found that OV distributions on the surface can considerably affect the reactions; the barrier of C-O bond dissociation is significantly reduced when the OVs are aligned along the [12̅ 10] direction. These findings may be general in the systems with metal oxides

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Author

Yulan Han; Jiayan Xu; Wenbo Xie; Zhuozheng Wang; P. Hu

Publisher

American Chemical Society (ACS)

Published

2023

Language

EN

Field

Chemistry (Physical Sciences)