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Understanding the Roadmap for Electrochemical Reduction of CO2 to Multi-Carbon Oxygenates and Hydrocarbons on Copper-Based Catalysts
Abstract
Electrochemical reduction of CO 2 to high-energy-density oxygenates and hydrocarbons beyond CO is important for long-term and large-scale renewable energy storage. However, the key step of the C–C bond formation needed for the generation of C 2 products induces an additional barrier on the reaction. This inevitably creates larger overpotentials and greater variety of products as compared to the conversion of CO 2 to C 1 products. Therefore, an in-depth understanding of the catalytic mechanism is required for advancing the design of efficient electrocatalysts to control the reaction pathway to the desired products. Herein, we present a critical appraisal of reduction of CO 2 to C 2 products focusing on the connection between the fundamentals of reaction and efficient electrocatalysts. An in-depth discussion of the mechanistic aspects of various C 2 reaction pathways on copper-based catalysts is presented together with consideration of practical factors under electrocatalytic operating conditions. By providing some typical examples illustrating the benefit of merging theoretical calculations, surface characterization, and electrochemical measurements, we try to address the key issues of the ongoing debate toward better understanding electrochemical reduction of CO 2 at the atomic level and envisioning the roadmap for C 2 products generation.
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Metadata
- Authors
- Zheng, Y., Vasileff, A., Zhou, X., Jiao, Y., Jaroniec, M., & Qiao, S.-Z.
- Venue
- Journal of the American Chemical Society
- Publisher
- American Chemical Society (ACS)
- Published
- 2019-04-15
- Volume
- 141
- Issue
- 19
- Pages
- 7646-7659
- ISSN
- 0002-7863 (ISSN-L)
- 1520-5126
- OpenAlex
- W2938620684
- Cited by
- 1,075
- References
- 111
- FWCI
- 24.07
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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Data sources
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.