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Unravelling the electrochemical double layer by direct probing of the solid/liquid interface

Open access
Favaro, Marco, Jeong, Beomgyun, Ross, Philip N., Yano, Junko, Hussain, Zahid, Liu, Zhi, Crumlin, Ethan J.·2016·Nature Communications

Abstract

The electrochemical double layer plays a critical role in electrochemical processes. Whilst there have been many theoretical models predicting structural and electrical organization of the electrochemical double layer, the experimental verification of these models has been challenging due to the limitations of available experimental techniques. The induced potential drop in the electrolyte has never been directly observed and verified experimentally, to the best of our knowledge. In this study, we report the direct probing of the potential drop as well as the potential of zero charge by means of ambient pressure X-ray photoelectron spectroscopy performed under polarization conditions. By analyzing the spectra of the solvent (water) and a spectator neutral molecule with numerical simulations of the electric field, we discern the shape of the electrochemical double layer profile. In addition, we determine how the electrochemical double layer changes as a function of both the electrolyte concentration and applied potential.

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Metadata

Authors
Favaro, M., Jeong, B., Ross, P. N., Yano, J., Hussain, Z., Liu, Z., & Crumlin, E. J.
Venue
Nature Communications
Published
2016-08-31
Volume
7
Issue
1
Pages
12695-12695
ISSN
2041-1723 (ISSN-L)
OpenAlex
W2517859888
Cited by
394
References
0
FWCI
19.37
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Unravelling the electrochemical double layer by direct probing of the solid/liquid interface. https://app.cochat.ai/papers/10.1038/ncomms12695
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Favaro, M., Jeong, B., Ross, P. N., Yano, J., Hussain, Z., Liu, Z., & Crumlin, E. J. (2016). Unravelling the electrochemical double layer by direct probing of the solid/liquid interface. Nature Communications. https://doi.org/10.1038/ncomms12695

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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.