Synthesis and characterization of machine learning designed TADF molecules.

ABSTRACT: In this study, we present a novel approach to the development of thermally activated delayed fluorescence (TADF) molecules with potentials for organic light-emitting diode (OLED) applications, leveraging machine learning (ML) algorithms to guide the materials design process. Recognizing the imperative for high-efficiency, low-cost emissive materials, we integrated ML driven models with experimental characterization to expedite the discovery of TADF compounds. Initially, a database of ML-designed TADF molecules was employed, with samples being approved to possess optimized photophysical properties. The proposed molecules were synthesized using palladium-catalyzed coupling reactions. Subsequent characterization of these molecules utilized a suite of analytical methods, including nuclear magn

SUBMITTER: Shi W 

PROVIDER: S-EPMC11648113 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature