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Ionic Exchange of Metal–Organic Frameworks to Access Single Nickel Sites for Efficient Electroreduction of CO2

Zhao, Changming, Dai, Xinyao, Yao, Tao, Chen, Wenxing, Wang, Xiaoqian, Wang, Jing, Yang, Jian, Wei, Shiqiang, Wu, Yuen, Li, Yadong·2017·Journal of the American Chemical Society

Abstract

Single-atom catalysts often exhibit unexpected catalytic activity for many important chemical reactions because of their unique electronic and geometric structures with respect to their bulk counterparts. Herein we adopt metal–organic frameworks (MOFs) to assist the preparation of a catalyst containing single Ni sites for efficient electroreduction of CO 2 . The synthesis is based on ionic exchange between Zn nodes and adsorbed Ni ions within the cavities of the MOF. This single-atom catalyst exhibited an excellent turnover frequency for electroreduction of CO 2 (5273 h –1 ), with a Faradaic efficiency for CO production of over 71.9% and a current density of 10.48 mA cm –2 at an overpotential of 0.89 V. Our findings present some guidelines for the rational design and accurate modulation of nanostructured catalysts at the atomic scale.

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Metadata

Authors
Zhao, C., Dai, X., Yao, T., Chen, W., Wang, X., Wang, J., Yang, J., Wei, S., Wu, Y., & Li, Y.
Venue
Journal of the American Chemical Society
Published
2017-06-13
Volume
139
Issue
24
Pages
8078-8081
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W2624508105
Cited by
1,365
References
7
FWCI
38.85
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Ionic Exchange of Metal–Organic Frameworks to Access Single Nickel Sites for Efficient Electroreduction of CO2. https://app.cochat.ai/papers/10.1021/jacs.7b02736
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Zhao, C., Dai, X., Yao, T., Chen, W., Wang, X., Wang, J., Yang, J., Wei, S., Wu, Y., & Li, Y. (2017). Ionic Exchange of Metal–Organic Frameworks to Access Single Nickel Sites for Efficient Electroreduction of CO2. Journal of the American Chemical Society. https://doi.org/10.1021/jacs.7b02736

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.