Assessment of Catalytic Activities of Gold Nanoclusters with Simple Structure Descriptors

The de novo design of nanocatalysts with high activity is a challenging task, since prediction of catalytic activities of nanoclusters on the basis of simple descriptors is still a frontier of research. Herein, we present a simple model to build a geometry–adsorption–activity relationship for gold nanoclusters using CO oxidation as the benchmark probe. On the basis of extensive density functional theory calculations, the geometry indices (generalized local coordination number and curvature angle of the surface Au atoms) of numerous Au nanoclusters are found to be well correlated with the binding strength of CO and O2, as well as the activation barriers of CO oxidation by using the Brønsted–Evans–Polanyi (BEP) relationship and Sabatier analysis. In particular, this predictive model with simple structure descriptors can be extended to Au nanoparticles (NPs) with larger sizes and various shapes. Such a predictive model can provide a useful rule of thumb for experimentalists to quickly assess catalytic activity from only gathering the structural characteristics of Au NPs before performing more involved catalytic measurements. This model may also offer a cost-effective way for the rational design of nanocatalysts: for example, to assist experimentalists in making Au nanoclusters with the maximum number of active sites.