Predicting phosphorescence energies and inferring wavefunction localization with machine learning
We address phosphorescence, a localized phenomenon, by building localization layers into a DNN model of singlet–triplet energy gaps. These layers improve model performance and simultaneously infer the location of spin excitations within molecules.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗