High-throughput computational design of halide perovskites and beyond for optoelectronics

Halide perovskites have attracted great interest as promising next-generation materials in optoelectronics, ranging from solar cells to light-emitting diodes. Despite their exceptional optoelectronic properties and low cost, the prototypical organic-inorganic hybrid lead halide perovskites suffer from toxicity and low stability. Therefore, it is of high demand to search for stable and nontoxic alternatives to the hybrid lead halide perovskites. Recently, high-throughput computational materials design has emerged as a powerful approach to accelerate the discovery of new halide perovskite compositions or even novel compounds beyond perovskites. In this review, we discuss how this approach discovers halide perovskites and beyond for optoelectronics. We first overview the background of halide perovskites and methodologies in high-throughput computational design. Then, we focus on materials properties for different optoelectronic applications, and how they are assessed with materials descriptors. Finally, we review different studies in terms of specific materials types to discuss their design principles, screening results, and experimental verification. This article is categorized under: Structure and Mechanism > Computational Materials Science Electronic Structure Theory > Density Functional Theory

Automated summary

Halide perovskites have shown great promise as next-generation materials in optoelectronics, but the prototypical organic-inorganic hybrid lead halide perovskites suffer from toxicity and low stability. Recently, high-throughput computational materials design has emerged as a powerful approach to accelerate the discovery of new halide perovskite compositions or even novel compounds beyond perovskites.