Electron transfer reactions are of critical importance in many areas of chemical, physical, and biological sciences. Controlling the movement of charges between weakly coupled donors and acceptors is pivotal for a host of applications, e.g. photocatalytic processes, solar cells, and organic photovoltaics, in photosystem II and in other redox-driven catalytic processes. The ability to describe the mechanisms and rates of charge transfer in the weakly coupled regime is thus essential for understanding a wide range of systems and mechanisms as well as for the design and characterization of molecular components for solar energy conversion and catalytic applications. In this talk I will demonstrate how electronic structure theory and machine learning can be combined quantum mechanical principles to develop a state-of-the-art method for highly accurate prediction of electron transfer rates.
