Excited state non-adiabatic dynamics of large photoswitchable molecules using a chemically transferable machine learning potential

Abstract

The authors introduce a diabatic neural network to accelerate excitedstate, non-adiabatic simulations of azobenzene derivatives. The model predicts quantum yields for unseen species that are correlated with experiment.