Computational quantum chemistry is a powerful tool in the characterization of materials and the prediction of emergent properties, not least in the field of photocatalysis. The development of appropriate models of photocatalyst materials has aided in the understanding of crucial processes in photocatalysis and informed the rational design of new architectures. High-throughput computational techniques allow for the screening of candidate materials and can shed light on experimental observations. Key to the performance of computational models in predicting the viability of a material for the photocatalysis of a given reaction is the definition of appropriate descriptors.

In this chapter, we discuss modeling of photocatalysis in terms of material descriptors and the development of models for their quantification. We also describe approaches for the optimization of these properties through rational design of new materials. Further consideration is given to other important material properties such as stability, cost, toxicity, abundance, and synthesis.