Descriptor-Guided Mapping of Oxide–Metal Boundary Motifs for Selective C1 Oxygenate Formation

The catalytic formation of C1 oxygenates depends strongly on the local geometry and electronic structure of oxide–metal boundary motifs, yet the structural diversity of these interfacial sites makes rational catalyst design difficult. In this work, a descriptor-guided computational framework was developed to identify active boundary motifs for selective C1 oxygenate formation over oxide-decorated copper surfaces. A dataset containing 124 oxide–Cu interfacial configurations was constructed by varying oxide nuclearity, metal–oxygen coordination, interfacial oxygen vacancy density, and exposed Cu facet. Density functional theory calculations were performed to obtain adsorption energies of CO2*, HCOO*, H2COO*, CH3O*, CO*, and H2O*, together with 214 transition-state barriers along methanol and CO formation pathways. The results show that the adsorption energy difference between HCOO* and CO* is a reliable selectivity descriptor, with a Pearson correlation coefficient of 0.81 for methanol selectivity predicted by microkinetic modeling. Motifs with partially reduced ZrOx and TiOx clusters on stepped Cu surfaces showed the most favorable balance between CO2 activation and intermediate hydrogenation, reducing the HCOO* hydrogenation barrier by 0.28–0.44 eV compared with flat Cu(111). A gradient-boosting regression model trained on geometric and electronic descriptors predicted methanol formation barriers with a mean absolute error of 0.067 eV. Microkinetic simulations at 240 °C and 30 bar further indicated that boundary motifs with moderate oxophilicity could increase the methanol-to-CO rate ratio by more than one order of magnitude. This study provides a transferable descriptor framework for screening oxide–metal catalytic ensembles and highlights the importance of interfacial site diversity in controlling C1 oxygenate selectivity.

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