A deep learning framework for predictions of excited state properties of light emissive molecules

Abstract

We have implemented a deep learning protocol to forecast the excited state properties for thermally activated delayed fluorescence (TADF) molecules with satisfactory accuracies being achieved. In particular, for the oscillator strengths, predictive precisions have been significantly improved when the torsional profile of the dataset is enriched.