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Cited by 375

The DOI matches its Crossref record; 65 of the 65 references it cites were found in a registry or an index.

Investigating Electrode Flooding in a Flowing Electrolyte, Gas‐Fed Carbon Dioxide Electrolyzer

Open access
Leonard, McLain E., Clarke, Lauren E., Forner‐Cuenca, Antoni, Brown, Steven M., Brushett, Fikile R.·2020·ChemSusChem

Abstract

Managing the gas–liquid interface within gas‐diffusion electrodes (GDEs) is key to maintaining high product selectivities in carbon dioxide electroreduction. By screening silver‐catalyzed GDEs over a range of applied current densities, an inverse correlation was observed between carbon monoxide selectivity and the electrochemical double‐layer capacitance, a proxy for wetted electrode area. Plotting current‐dependent performance as a function of cumulative charge led to data collapse onto a single sigmoidal curve indicating that the passage of faradaic current accelerates flooding. It was hypothesized that high cathode alkalinity, driven by both initial electrolyte conditions and cathode half‐reactions, promotes carbonate formation and precipitation which, in turn, facilitates electrolyte permeation. This mechanism was reinforced by the observations that post‐test GDEs retain less hydrophobicity than pristine materials and that water‐rinsing and drying electrodes temporarily recovers peak selectivity. This knowledge offers an opportunity to design electrodes with greater carbonation tolerance to improve device longevity.

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Crossref · 10.1002/cssc.201902547

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Metadata

Authors
Leonard, M. E., Clarke, L. E., Forner‐Cuenca, A., Brown, S. M., & Brushett, F. R.
Venue
ChemSusChem
Publisher
Wiley
Published
2019-12-17
Volume
13
Issue
2
Pages
400-411
ISSN
  • 1864-5631 (ISSN-L)
  • 1864-564X
OpenAlex
W2987472704
Cited by
375
References
65
FWCI
6.96
Type
journal article
Language
en
Open access
green

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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.