Abstract
This research aims to unlock the secrets of perovskite photocatalysts via deep learning - driven rational design. By training deep neural networks on large - scale perovskite data, we uncover hidden relationships between material composition, structure, and catalytic activity. The insights gained from this process lead to a more informed design of perovskite photocatalysts, opening up new possibilities for improving their performance in organic reactions
