Ground-State Orbital Descriptors for Accelerated Development of Organic Room-Temperature Phosphorescent Materials

Organic materials with room-temperature phosphorescence (RTP) are in high demand for optoelectronics and bioelectronics. Developing RTP materials highly relies on expert experience and costly excited-state calculations. It is a challenge to find a tool for effectively screening RTP materials. Herein we first establish ground-state orbital descriptors (π_FMOs) derived from the π-electron component of the frontier molecular orbitals to characterize the RTP lifetime (τ_p), achieving a balance in screening efficiency and accuracy. Using the π_FMOs, a data-driven machine learning model gains a high accuracy in classifying long τ_p, filtering out 836 candidates with long-lived RTP from a virtual library of 19,295 molecules. With the aid of the excited-state calculations, 287 compounds are predicted with high RTP efficiency. Impressively, experiments further confirm the reliability of this workflow, opening a novel avenue for designing high-performance RTP materials for potential applications.