Recalibrating the Experimentally Derived Structure of the Metastable Surface Oxide on Copper via Machine Learning-Accelerated In Silico Global Optimization

Abstract

The oxidation of copper and its surface oxides are gaining increasing attention due to the enhanced CO 2 reduction reaction (CO2RR) activity exhibited by partially oxidized copper among the copper-based catalysts. The "8" surface oxide on Cu( 111) is seen as a promising structure for further study due to its resemblance to the highly active Cu 2 O(110) surface in the C−C coupling of the CO2RR, setting it apart from other O/Cu(111) surface oxides resembling Cu 2 O(111). However, recent X-ray photoelectron spectroscopy analysis challenges the currently accepted atomic structure of the "8" surface oxide, prompting a need for reevaluation. This study highlights the limitations of conventional methods when addressing such challenges, leading us to adopt global optimization search techniques. After a rigorous process to ensure robustness, the unbiased global minimum of the "8" surface oxide is identified. Interestingly, this configuration differs significantly from other surface oxides and also from previous "8" models while retaining similarities to the Cu 2 O(110) surface.