Perovskite, the Chameleon CO2 Photocatalyst

Yang Fan Xu, Minoh Lee, Yongseok Jun, Geoffrey A. Ozin

Research output: Contribution to journalReview articlepeer-review

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.

Original languageEnglish
Article number100300
JournalCell Reports Physical Science
Volume2
Issue number1
DOIs
Publication statusPublished - 2021 Jan 20

Keywords

  • CO hydrogenation
  • artificial intelligence
  • catalysis
  • machine learning
  • perovskite
  • photochemistry
  • solar fuel

ASJC Scopus subject areas

  • Physics and Astronomy(all)
  • Materials Science(all)
  • Chemistry(all)
  • Energy(all)
  • Engineering(all)

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