Fine-structure sensitive deep learning framework for prediction of catalytic properties with high precision

The fine structure of the catalytic surface has a significant impact on structural sensitive reactions, and high-throughput (HT) screening and machine learning (ML) are believed to effectively explore the potential rules of these effects and accelerate the developing of the catalyst. However, reported ML frameworks are too coarse to make a precise prediction of the catalytic performance.