Singlet‐Triplet Energy Gap as a Critical Molecular Descriptor for Predicting Organic Photovoltaic Efficiency

In contrast to the inorganic and perovskite solar cells, organic photovoltaics (OPV) depend on a series of charge generation and recombination processes, which complicates molecular design to improve the power conversion efficiencies (PCEs). Herein, we first propose the singlet‐triplet energy gap (ΔEST) as a critical molecular descriptor for predicting the PCE considering that minimizing ΔEST is beneficial to simultaneously reduce voltage loss and triplet recombination. Remarkably, the results from data‐driven machine learning verify that the prediction accuracy of the ΔEST (Pearson's correlation coefficient r=0.72) is apparently superior to that of two commonly used molecular descriptors in OPV, i.e., the optical gap (r=0.65) and the driving force (r=0.53). Moreover, an impressive prediction accuracy of r=0.81 is achieved just by combining the three descriptors. This work paves the way toward rapid and precise screening of efficient OPV materials.