Comprehensive Study of Oxygen Vacancies on the Catalytic Performance of ZnO for CO/H₂ Activation Using Machine...

Area of Science:

• Materials Science
• Catalysis
• Surface Chemistry

Background:

• Oxygen vacancies (OVs) are critical in oxide catalyst performance.
• Understanding OV effects on ZnO surfaces is key for syngas activation.

Purpose of the Study:

• To investigate the role of oxygen vacancies on the ZnO(101̅0) surface for CO and H2 activation.
• To determine the most stable and active OV configuration under experimental conditions.

Main Methods:

• Machine learning potentials (MLPs) for predicting surface energies.
• Genetic algorithm (GA) for global structure optimization.
• Density functional theory (DFT) for electronic structure and reaction pathway calculations.

Main Results:

• The ZnO(101̅0) surface with 0.33 ML OVs is the most stable configuration under reaction conditions.
• OVs induce surface reconstruction and create active Zn3 cluster sites for H2 and CO activation.
• Catalytic activity is dependent on OV concentration and distribution, with aligned OVs significantly reducing C-O bond dissociation barriers.

Conclusions:

• Oxygen vacancies play a significant role in ZnO surface reconstruction and catalytic activity for syngas conversion.
• Controlling OV concentration and distribution is a promising strategy for designing advanced heterogeneous catalysts.