Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Perovskite, the Chameleon CO2 Photocatalyst

Authors
Xu, Y.-F.Lee, M.Jun, Y.Ozin, G.A.
Issue Date
1월-2021
Publisher
Cell Press
Keywords
artificial intelligence; catalysis; CO2 hydrogenation; machine learning; perovskite; photochemistry; solar fuel
Citation
Cell Reports Physical Science, v.2, no.1
Indexed
SCOPUS
Journal Title
Cell Reports Physical Science
Volume
2
Number
1
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/129578
DOI
10.1016/j.xcrp.2020.100300
ISSN
2666-3864
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)
Files in This Item
There are no files associated with this item.
Appears in
Collections
Graduate School of Energy and Environment (KU-KIST GREEN SCHOOL) > Department of Energy and Environment > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetrics

Total Views & Downloads

BROWSE