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The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.

Progress toward Commercial Application of Electrochemical Carbon Dioxide Reduction

Open access
Chen, Chi, Khosrowabadi Kotyk, Juliet F., Sheehan, Stafford W.·2018·Chem

Abstract

Summary Climate change is one of the greatest challenges facing humanity, and our continued sustainable development requires a portfolio of solutions to ultimately reduce the use of fossil fuels and decrease the concentration of carbon dioxide in our atmosphere. Chemistry is central to tackling this issue, and of the pathways to transform carbon dioxide into value-added compounds, single-step electrically driven chemical methods have attracted substantial interest in the last decade. This review places emphasis on the barriers that chemists must overcome to realize this technology and enable commercial use of electrochemical carbon dioxide reduction. We outline design strategies for gas-diffusion electrodes and electrolyzers that follow fundamental principles of catalysis to bridge the gap between catalyst discovery and integrated system engineering. These should address both technical (thermodynamic and kinetic) and practical (infrastructural) hurdles to implementation. We conclude by discussing how these approaches can be improved to help achieve a carbon-neutral economy.

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Crossref · 10.1016/j.chempr.2018.08.019

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Metadata

Authors
Chen, C., Khosrowabadi Kotyk, J. F., & Sheehan, S. W.
Venue
Chem
Publisher
Elsevier BV
Published
2018-11
Volume
4
Issue
11
Pages
2571-2586
ISSN
2451-9294 (ISSN-L)
OpenAlex
W2892330472
Cited by
735
References
31
FWCI
11.37
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Progress toward Commercial Application of Electrochemical Carbon Dioxide Reduction. https://app.cochat.ai/papers/10.1016/j.chempr.2018.08.019
The paper
Chen, C., Khosrowabadi Kotyk, J. F., & Sheehan, S. W. (2018). Progress toward Commercial Application of Electrochemical Carbon Dioxide Reduction. Chem. https://doi.org/10.1016/j.chempr.2018.08.019

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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.