A deep learning model for inferring the reverse intersystem crossing rate of TADF organic light-emitting diodes, overcoming the uncertainty of recombination dynamics

step-by-step analysis of both recombination and exciton dynamics. Based on the recombination rate results of the first tandem model, we designed an algorithm in which the second model was automatically selected from among the pretrained candidate models to infer the RISC rate. With comprehensive optimization, a tandem DNN model with a determination coefficient value of 0.985 was realized, overcoming the uncertainty of polaron recombination dynamics. The practical application of the developed model was demonstrated by fabricating a state-of-the-art TADF OLED.