From Illumination to Prediction: A Kinetic Model for Photocatalytic Activity

Photocatalysis is a powerful tool in synthesis, although the key factors that determine its performance are not fully understood. We present a kinetic model for evaluating photocatalytic performance that can be used both to interpret experiments and to optimize kinetic parameters based on experimental data. We introduce the steady-state reduction potential of the substrate or quencher Q ( E _Q ) as the performance metric. The model relies on key parameters, such as the ground and excited state standard reduction potentials of the photocatalyst ( PC ) and Q , the reorganization energy, and excitation properties. The model is based on three reversible reactions: excitation of the PC , electron transfer (ET) between Q and the ground state PC , ET between Q and the excited state PC* and an irreversible unproductive PC * + Q → PC + Q step, capturing several key geminate processes. The dependence of E _Q on the standard ground and excited state reduction potentials of the PC s shows that photocatalytic performance is strongly influenced by whether the individual ET steps occur in the Marcus normal or inverted regions. The two-dimensional plot of this function reveals the directions in which the standard ground and excited state reduction potentials should be tuned to enhance photocatalytic performance; these directions are often counterintuitive. The model incorporates cage escape, and we show that it can be treated without introducing additional kinetic substeps. An important finding is that none of the input parameters alone can reliably predict photocatalytic efficiency; this also highlights the significance of the proposed measure E _Q . The model also predicts reduction potential combinations where chemiluminescence is expected. The model is benchmarked against transient and stationary experimental data, demonstrating its ability to recover key kinetic parameters. The model is freely available on GitHub and can be easily extended to incorporate additional processes, making it a versatile tool for qualitative assessment and systematic exploration of emerging photocatalytic strategies.