A Review of Computational and Theoretical Studies on Anti-Perovskite Solids

Abstract

Anti-perovskite materials are really turning heads lately, and it’s no wonder why. Their unique structural inversion, unlike traditional perovskites, leads to some truly remarkable properties in terms of electronics, thermal behavior, and magnetism. With a general formula of A₃BX, these materials are known for boasting high ionic conductivity and less thermal conductivity; they show potential for topological and superconducting behaviors. This makes them perfect candidates for all sorts of applications, from solid-state batteries to thermoelectrics, spintronics, and even quantum computing. Researchers have made great strides using computational and theoretical studies especially with density functional theory (DFT) to predict how stable these structures are, along with their electronic configurations and overall functional properties. High-throughput screening, phonon dispersion analysis, and machine learning techniques are also helping push the discovery of new anti-perovskite compounds along faster than ever. Yet, there are still hurdles to overcome, like accurately modeling electron correlation effects and lattice anharmonicity, not to mention the limited experimental validation. Still, the collaboration between computational predictions and experimental work opens up exciting possibilities for designing tailored anti-perovskites. With their multifunctional traits, they really could be game-changers for future energy and electronic technologies.