Unravelling the Impact of Metal Dopants and Oxygen Vacancies on Syngas Conversion over Oxides: A Machine Learning-Accelerated Study of CO Activation on Cr-Doped ZnO Surfaces.

ABSTRACT: As a critical component of the OX-ZEO composite catalysts toward syngas conversion, the Cr-doped ZnO ternary system can be considered as a model system for understanding oxide catalysts. However, due to the complexity of its structures, traditional approaches, both experimental and theoretical, encounter significant challenges. Herein, we employ machine learning-accelerated methods, including grand canonical Monte Carlo and genetic algorithm, to explore the ZnO(1010) surface with various Cr and oxygen vacancy (OV) concentrations. Stable surfaces with varied Cr and OV concentrations were then systematically investigated to examine their influence on the CO activation via density functional theory calculations. We observe that Cr tends to preferentially appear on the surface of ZnO(1010) rat

SUBMITTER: Han Y 

PROVIDER: S-EPMC10660660 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature