Combining quantum chemistry, machine learning and rate theory for organic luminescent materials

Abstract

The theoretical design of highly efficient, low roll-off and full-color emission organic materials is of great interest, although there are great challenges due to the limitations of the present-day methodology. In this review, we present progress achieved in our group on the theoretical and computational investigation for the structure–property relationships and screening strategy for organic fluorescent molecules, selection of thermally activated delayed fluorescence (TADF) and multi-resonance TADF (MR-TADF) molecules for optically and electrically pumped lasing application, and high-throughput virtual screening of phosphorescent organometallic complexes. We combined a quantum chemistry method with the molecular representation learning model Uni-Mol and rate theory-based molecular material property prediction package (MOMAP) developed in our group. Finally, we outline the limitation of current computational protocols and the future directions for organic luminescent materials.