Going Beyond the d‐Band Center to Describe CO2 Activation on Single‐Atom Alloys

The computational screening of single‐atom alloys (SAAs) is challenging owing to their complicated electronic structure compared with traditional metal or alloy catalysts and the consequent lack of an accurate and low‐cost activity descriptor to replace expensive adsorption energy calculations. Herein, a data‐driven approach involving consecutive classification and regression is explored to identify the descriptor in the form of algebraic operators representing atomic information for predicting the adsorption energies of CO 2 molecules on SAAs. The best descriptor significantly outperforms the d‐band center model in terms of accuracy and computational overhead. This study provides a fundamental understanding of the bonding strength on SAA surfaces and also an effective approach for the high‐throughput screening of promising catalysts.