Grain Boundary‐Derived Cu <sup>+</sup> /Cu <sup>0</sup> Interfaces in CuO Nanosheets for Low Overpotential Carbon Dioxide Electroreduction to Ethylene-Reference-Cited by-同舟云学术

Grain Boundary‐Derived Cu ⁺ /Cu ⁰ Interfaces in CuO Nanosheets for Low Overpotential Carbon Dioxide Electroreduction to Ethylene

Published:2022-05-22 Issue:21 Volume:9 Page:2200454
ISSN:2198-3844
Container-title:Advanced Science
language:en
Short-container-title:Advanced Science

Author:

Zhang Jianfang¹²^ORCID,Wang Yan¹,Li Zhengyuan²,Xia Shuai¹,Cai Rui¹,Ma Lu³,Zhang Tianyu²,Ackley Josh²,Yang Shize⁴,Wu Yucheng¹⁵,Wu Jingjie²^ORCID

Affiliation:

1. School of Materials Science and Engineering Hefei University of Technology Hefei 230009 China

2. Department of Chemical and Environmental Engineering University of Cincinnati Cincinnati OH 45221 USA

3. National Synchrotron Light Source II Brookhaven National Laboratory Upton NY 11971 USA

4. Eyring Materials Center Arizona State University 85287 Tempe AZ USA

5. China International S&T Cooperation Base for Advanced Energy and Environmental Materials and Anhui Provincial International S&T Cooperation Base for Advanced Energy Materials Hefei University of Technology Hefei 230009 China

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Office of Energy Efficiency and Renewable Energy

U.S. Department of Energy

China Postdoctoral Science Foundation

Higher Education Discipline Innovation Project

Postdoctoral Research Foundation of China

Publisher

Wiley

Subject

General Physics and Astronomy,General Engineering,Biochemistry, Genetics and Molecular Biology (miscellaneous),General Materials Science,General Chemical Engineering,Medicine (miscellaneous)

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/advs.202200454

Reference62 articles.

1. Enhanced electrocatalytic CO2 reduction via field-induced reagent concentration

2. Nanostructured electrocatalysts with tunable activity and selectivity

3. Techno-economic assessment of low-temperature carbon dioxide electrolysis

4. Molecular tuning of CO2-to-ethylene conversion

5. Accelerated discovery of CO2 electrocatalysts using active machine learning

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