Influence of Oxygen Vacancy Distribution on CO<sub>2</sub> Hydrogenation: A Case Study of ZnO and In<sub>2</sub>O<sub>3</sub>
Dandan Song, Leyuan Cui, Ruixuan Qin, Gang Fu
Abstract
High Resolution Image Download MS PowerPoint Slide Oxygen vacancies (OVs) on metal oxide surfaces are widely recognized as catalytically active sites; however, the impact of their distribution on the catalytic performance remains underexplored. In this study, we used density functional theory (DFT) calculations combined with a machine learning potential to investigate the distribution of OVs on the ZnO(10 1 − 0) surface and their role in CO 2 hydrogenation. We efficiently analyzed over 700,000 potential OV configurations by reducing them to unique, irreducible structures using the self-developed DefectMaker program. Our results revealed that higher OV concentrations led to the formation of linear OV structures, which, despite their energetic stability, exhibited lower CO 2 hydrogenation efficiency compared to isolated OVs, due to the reduced surface polarization with linear OVs. Additionally, a comparative investigation on In 2 O 3 surfaces revealed a scattered distribution of OVs, maintaining the material’s catalytic activity in CO 2 hydrogenation. This work provides a deeper understanding of defect engineering in metal oxides for a more efficient CO 2 conversion.