Perovskite, the Chameleon CO2 Photocatalyst

Abstract

The prevalence of perovskite materials in myriad technologies is traceable to their diverse compositions, structures, and forms, variations of which bestow them with chameleon-like properties, functionality, and utility. By modifying the ABO3 archetype perovskites through isomorphic substitution, aliovalent doping, and non-stoichiometry, as well as tailoring their form through nanostructuring, heterostructuring, superstructuring, and polymorphism, the portfolio of application opportunities for perovskite materials can be greatly expanded. The focus of this perspective is to explore the thought process by which human intelligence and experiential learning enables the discovery of a champion photocatalyst for CO2 hydrogenation by juggling the elements in perovskite oxides and at which point this well-established approach needs a helping hand from artificial intelligence and machine learning. © 2020 The Author(s)Traditional materials discovery founded upon human intelligence, experiential learning, and hands-on experimentation is being challenged by a parallel approach based on artificial intelligence, machine learning, and robotic automation. Whether humans will be replaced by machines or rather learn to work together harmoniously is explored by Xu et al. for perovskite “chameleon” CO2 photocatalysts. © 2020 The Author(s)