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Cited by 296

The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.

Ultraefficient homogeneous catalyst for the CO 2 -to-CO electrochemical conversion

Open access
Costentin, Cyrille, Passard, Guillaume, Robert, Marc, Savéant, Jean-Michel·2014·Proceedings of the National Academy of Sciences

Abstract

Significance: Conversion of CO 2 into liquid fuels is one of the most important contemporary energy and environmental challenges. As a first step in this direction, the electrochemical reduction of CO 2 to CO requires catalysts, usually derived from transition metal complexes. In this paper, a very efficient, electrogenerated iron-porphyrin catalyst was obtained by introducing both pendant acid groups and fluorine substituents in the molecule. The former stabilize the CO 2 -catalyst key intermediate via H bonding and provide a high local proton concentration. The latter help decrease the energy required to drive catalysis. Benchmarking this molecule with other catalysts shows that it is at present the most efficient, to the best of our knowledge, homogeneous molecular catalyst of the CO 2 -to-CO conversion in terms of selectivity, overpotential, and turnover frequency.

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Crossref · 10.1073/pnas.1416697111

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Metadata

Authors
Costentin, C., Passard, G., Robert, M., & Savéant, J.-M.
Venue
Proceedings of the National Academy of Sciences
Published
2014-10-06
Volume
111
Issue
42
Pages
14990-14994
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W1966070623
Cited by
296
References
30
FWCI
6.33
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Ultraefficient homogeneous catalyst for the CO 2 -to-CO electrochemical conversion. https://app.cochat.ai/papers/10.1073/pnas.1416697111
The paper
Costentin, C., Passard, G., Robert, M., & Savéant, J.-M. (2014). Ultraefficient homogeneous catalyst for the CO 2 -to-CO electrochemical conversion. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1416697111

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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

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