Yi Huang

Machine Learning‐Driven Discovery and Experimental Validation of Effective Precursor Additives in Perovskite Solar Cells

The proposed data‐driven screening strategy for precursor additives by integrating process parameters, material physicochemical properties, and molecular descriptors into a unified feature system is validated and its potential for accelerating the rational discovery and optimization of precursor additives for high‐performance PSCs is demonstrated.