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Cited by 640

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

Controllable Hydrocarbon Formation from the Electrochemical Reduction of CO2 over Cu Nanowire Arrays

Ma, Ming, Djanashvili, Kristina, Smith, Wilson A.·2016·Angewandte Chemie International Edition

Abstract

In this work, the effect of Cu nanowire morphology on the selective electrocatalytic reduction of CO 2 is presented. Cu nanowire arrays were prepared through a two‐step synthesis of Cu(OH)2 and CuO nanowire arrays on Cu foil substrates and a subsequent electrochemical reduction of the CuO nanowire arrays to Cu nanowire arrays. By this simple synthesis method, Cu nanowire array electrodes with different length and density were able to be controllably synthesized. We show that the selectivity for hydrocarbons (ethylene, n‐propanol, ethane, and ethanol) on Cu nanowire array electrodes at a fixed potential can be tuned by systematically altering the Cu nanowire length and density. The nanowire morphology effect is linked to the increased local pH in the Cu nanowire arrays and a reaction scheme detailing the local pH‐induced formation of C 2 products is also presented by a preferred CO dimerization pathway.

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Metadata

Authors
Ma, M., Djanashvili, K., & Smith, W. A.
Venue
Angewandte Chemie International Edition
Publisher
Wiley
Published
2016-04-21
Volume
55
Issue
23
Pages
6680-6684
ISSN
  • 1433-7851 (ISSN-L)
  • 1521-3773
OpenAlex
W2340533519
Cited by
640
References
30
FWCI
16.36
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Controllable Hydrocarbon Formation from the Electrochemical Reduction of CO2 over Cu Nanowire Arrays. https://app.cochat.ai/papers/10.1002/anie.201601282
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Ma, M., Djanashvili, K., & Smith, W. A. (2016). Controllable Hydrocarbon Formation from the Electrochemical Reduction of CO2 over Cu Nanowire Arrays. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.201601282

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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.