Machine-learning-guided prediction of photovoltaic performance of non-fullerene organic solar cells using novel molecular and structural descriptors

The machine learning approach was employed to explore the relationship between molecular structure and photovoltaic properties using frontier molecular orbital and RDKit descriptors, which enabled us to screen and identify potential donor and acceptor combinations for efficient organic solar cells.