Perovskite, the Chameleon CO2 Photocatalyst

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

doi:10.1016/j.xcrp.2020.100300

Perovskite, the Chameleon CO₂ Photocatalyst

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

Research output: Contribution to journal › Review article › peer-review

7 Citations (Scopus)

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 language	English
Article number	100300
Journal	Cell Reports Physical Science
Volume	2
Issue number	1
DOIs	https://doi.org/10.1016/j.xcrp.2020.100300
Publication status	Published - 2021 Jan 20

Bibliographical note

Funding Information:
G.A.O. is the Government of Canada Tier 1 Research Chair in Materials Chemistry and Nanochemistry. Y.-F.X. is a University of Toronto Faculty of Arts and Science Post-Doctoral Fellow. Financial support for this work was provided by the Ontario Ministry of Research Innovation (MRI); the Ministry of Economic Development, Employment, and Infrastructure (MEDI); the Ministry of the Environment and Climate Change (MOECC); the Ministry of Research, Innovation, and Science Low Carbon Innovation Fund (MRIS-LCIF); the Connaught Global Challenge Fund (CGCF); the Natural Sciences and Engineering Research Council of Canada (NSERC); and the University of Toronto . Insightful feedback on the content of this concept by Professor Tierui Zhang is deeply appreciated.

Funding Information:
G.A.O. is the Government of Canada Tier 1 Research Chair in Materials Chemistry and Nanochemistry. Y.-F.X. is a University of Toronto Faculty of Arts and Science Post-Doctoral Fellow. Financial support for this work was provided by the Ontario Ministry of Research Innovation (MRI); the Ministry of Economic Development, Employment, and Infrastructure (MEDI); the Ministry of the Environment and Climate Change (MOECC); the Ministry of Research, Innovation, and Science Low Carbon Innovation Fund (MRIS-LCIF); the Connaught Global Challenge Fund (CGCF); the Natural Sciences and Engineering Research Council of Canada (NSERC); and the University of Toronto. Insightful feedback on the content of this concept by Professor Tierui Zhang is deeply appreciated. G.A.O. conceived the idea for this perspective and supervised the whole program. G.A.O. Y.-F.X. M.L. and Y.J. contributed to the preparation of this manuscript through writing, editing, and preparing figures. The authors declare no competing interests.

Publisher Copyright:
© 2020 The Author(s)

Keywords

CO hydrogenation
artificial intelligence
catalysis
machine learning
perovskite
photochemistry
solar fuel

ASJC Scopus subject areas

General Chemistry
General Materials Science
General Engineering
General Energy
General Physics and Astronomy

Access to Document

10.1016/j.xcrp.2020.100300

Cite this

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title = "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.",

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