Toward Realistic Modeling of Complex Semiconductors

Abstract

Complex semiconductors are increasingly used in energy conversion, optoelectronics, and photocatalysis. Their performance is often controlled by local atomic environments that are not represented by a single ideal crystal structure. In this Perspective, I discuss how atomistic models can include effects such as thermal motion, disorder, charge localization, defects, and interfaces when these are relevant to the property of interest. I focus on examples where including these effects changes the physical interpretation of the calculation, and discuss how machine-learned interatomic potentials can help sample the relevant configurations for subsequent electronic structure calculations.