Advanced Energy Materials, volume 12, issue 20, pages 2200389
Emerging Strategies for CO 2 Photoreduction to CH 4 : From Experimental to Data‐Driven Design
Shuwen Cheng
1, 2
,
Zhehao Sun
3
,
Kang Hui Lim
2
,
Terry Zhi Hao Gani
2
,
Tianxi Zhang
2
,
Yisong Wang
1
,
Yin Hang
3
,
Kaili Liu
3
,
Haiwei Guo
2
,
Tao Du
1
,
Liying Liu
1
,
Gang (kevin) Li
4
,
ZONGYOU YIN
3
,
Sibudjing Kawi
2
Publication type: Journal Article
Publication date: 2022-03-29
Journal:
Advanced Energy Materials
scimago Q1
SJR: 8.748
CiteScore: 41.9
Impact factor: 24.4
ISSN: 16146832, 16146840
General Materials Science
Renewable Energy, Sustainability and the Environment
Abstract
The solar-energy-driven photoreduction of CO2 has recently emerged as a promising approach to directly transform CO2 into valuable energy sources under mild conditions. As a clean-burning fuel and drop-in replacement for natural gas, CH4 is an ideal product of CO2 photoreduction, but the development of highly active and selective semiconductor-based photocatalysts for this important transformation remains challenging. Hence, significant efforts have been made in the search for active, selective, stable, and sustainable photocatalysts. In this review, recent applications of cutting-edge experimental and computational materials design strategies toward the discovery of novel catalysts for CO2 photocatalytic conversion to CH4 are systematically summarized. First, insights into effective experimental catalyst engineering strategies, including heterojunctions, defect engineering, cocatalysts, surface modification, facet engineering, and single atoms, are presented. Then, data-driven photocatalyst design spanning density functional theory (DFT) simulations, high-throughput computational screening, and machine learning (ML) is presented through a step-by-step introduction. The combination of DFT, ML, and experiments is emphasized as a powerful solution for accelerating the discovery of novel catalysts for photocatalytic reduction of CO2. Last, challenges and perspectives concerning the interplay between experiments and data-driven rational design strategies for the industrialization of large-scale CO2 photoreduction technologies are described.
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