Data-driven design of double-atom catalysts with high H2 evolution activity/CO2 reduction selectivity based on simple features

Double-atom catalysts (DACs) were designed and analyzed using DFT and machine learning (ML) methods. ML can not only identify the activity center for DACs but also help screen DACs with higher HER or CO 2 RR activity.