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Cited by 225

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Suppressing Ion Transfer Enables Versatile Measurements of Electrochemical Surface Area for Intrinsic Activity Comparisons

Yoon, Youngmin, Yan, Bing, Surendranath, Yogesh·2018·Journal of the American Chemical Society

Abstract

Correlating the current/voltage response of an electrode to the intrinsic properties of the active material requires knowledge of the electrochemically active surface area (ECSA), a parameter that is often unknown and overlooked, particularly for highly nanostructured electrodes. Here we demonstrate the power of nonaqueous electrochemical double layer capacitance (DLC) to provide reasonable estimates of the ECSA across 17 diverse materials spanning metals, conductive oxides, and chalcogenides. Whereas data recorded in aqueous electrolytes generate a wide range of areal specific capacitance values (7–63 μF/real cm 2 ), nearly all materials examined display an areal specific capacitance of 11 ± 5 μF/real cm 2 when measured in weakly coordinating KPF 6 /MeCN electrolytes. By minimizing ion transfer reactions that convolute accurate DLC measurements, we establish a robust methodology for quantifying ECSA, enabling more accurate structure-function correlations.

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Metadata

Authors
Yoon, Y., Yan, B., & Surendranath, Y.
Venue
Journal of the American Chemical Society
Published
2018-02-08
Volume
140
Issue
7
Pages
2397-2400
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W2779199193
Cited by
225
References
6
FWCI
4.09
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Suppressing Ion Transfer Enables Versatile Measurements of Electrochemical Surface Area for Intrinsic Activity Comparisons. https://app.cochat.ai/papers/10.1021/jacs.7b10966
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Yoon, Y., Yan, B., & Surendranath, Y. (2018). Suppressing Ion Transfer Enables Versatile Measurements of Electrochemical Surface Area for Intrinsic Activity Comparisons. Journal of the American Chemical Society. https://doi.org/10.1021/jacs.7b10966

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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.