Dynamics of gold nanocluster on MgO surface with F-center defect and its implication for CO oxidation

Abstract

Gold nanoclusters supported on oxide surfaces exhibit enhanced catalytic activity due to charge redistribution at defect sites and strong metal–support interactions. In this study, we employ machine-learned interatomic potential-based simulations to investigate the dynamics of Au8 nanoclusters adsorbed on an oxygen-vacancy (F-center) defected MgO (100) surface. On-the-fly probability-enhanced sampling (OPES) simulations driven by a graph neural network–based collective variable reveal the low-energy conformational landscape of Au8 and the preferred binding site of CO, while machine-learned Bader charges uncover an inverse correlation between Au–Au coordination number and localized negative charge on undercoordinated Au atoms. The most stable Au8 conformer was then used to probe CO adsorption, which shows preferential binding of CO to the most negatively charged undercoordinated Au sites. Subsequent O2 adsorption resulted in significant charge transfer that enhances CO oxidation reactivity on the FC-defected MgO (100) surface. These findings highlight how defect-mediated charge transfer and cluster morphology together dictate adsorption behavior and catalytic functionality on oxide supports.