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Cited by 459

The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.

Highly Electrocatalytic Ethylene Production from CO2 on Nanodefective Cu Nanosheets

Zhang, Bingxing, Zhang, Jianling, Hua, Manli, Wan, Qiang, Su, Zhuizhui, Tan, Xiuniang, Liu, Lifei, Zhang, Fanyu, Chen, Gang, Tan, Dongxing, Cheng, Xiuyan, Han, Buxing, Zheng, Lirong, Mo, Guang·2020·Journal of the American Chemical Society

Abstract

The electrochemical synthesis of chemicals from carbon dioxide, which is an easily available and renewable carbon resource, is of great importance. However, to achieve high product selectivity for desirable C 2 products like ethylene is a big challenge. Here we design Cu nanosheets with nanoscaled defects (2–14 nm) for the electrochemical production of ethylene from carbon dioxide. A high ethylene Faradaic efficiency of 83.2% is achieved. It is proved that the nanoscaled defects can enrich the reaction intermediates and hydroxyl ions on the electrocatalyst, thus promoting C–C coupling for ethylene formation.

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Crossref · 10.1021/jacs.0c06420

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Metadata

Authors
Zhang, B., Zhang, J., Hua, M., Wan, Q., Su, Z., Tan, X., Liu, L., Zhang, F., Chen, G., Tan, D., Cheng, X., Han, B., Zheng, L., & Mo, G.
Venue
Journal of the American Chemical Society
Published
2020-07-13
Volume
142
Issue
31
Pages
13606-13613
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W3041085575
Cited by
459
References
40
FWCI
11.56
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Highly Electrocatalytic Ethylene Production from CO2 on Nanodefective Cu Nanosheets. https://app.cochat.ai/papers/10.1021/jacs.0c06420
The paper
Zhang, B., Zhang, J., Hua, M., Wan, Q., Su, Z., Tan, X., Liu, L., Zhang, F., Chen, G., Tan, D., Cheng, X., Han, B., Zheng, L., & Mo, G. (2020). Highly Electrocatalytic Ethylene Production from CO2 on Nanodefective Cu Nanosheets. Journal of the American Chemical Society. https://doi.org/10.1021/jacs.0c06420

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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