Electrodes Modified with Thin Films: Distinguishing Between Membrane and Pinhole Diffusion Using Machine Learning

Haotian  Chen; Lina Wang; Frank Marken; Richard Compton

doi:10.1016/j.jelechem.2023.117390

Electrodes Modified with Thin Films: Distinguishing Between Membrane and Pinhole Diffusion Using Machine Learning

Haotian Chen, Lina Wang, Frank Marken, Richard Compton

University of Oxford

Research output: Contribution to journal › Article › peer-review

Abstract

Current – time transients resulting from potential step measurements at electrodes covered with thin films are
typically used to characterise the diffusive transport of the electroactive species to the electrode as being either
via partition into and then within the membrane, or alternatively exclusively via pinholes. The transients
expected in the two cases are often closely similar. We use ML to provide a user independent analysis of the
transient to indicate the most probable mechanism. The limitations and strengths of this approach are critically
discussed.

Original language	English
Article number	117390
Journal	Journal of Electroanalytical Chemistry
Volume	936
Early online date	25 Mar 2023
DOIs	https://doi.org/10.1016/j.jelechem.2023.117390
Publication status	Published - 1 May 2023

Bibliographical note

The authors declare the following financial interests/personal rela-
tionships which may be considered as potential competing interests:
Joseph Elliott reports financial support was provided by Syngenta
and EPSRC

Keywords

Diffusion mode classification
Membrane pinholes
Membrane transport
Polymer modified electrodes
Random forest

ASJC Scopus subject areas

Analytical Chemistry
General Chemical Engineering
Electrochemistry

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10.1016/j.jelechem.2023.117390Licence: CC BY

Cite this

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abstract = "Current – time transients resulting from potential step measurements at electrodes covered with thin films aretypically used to characterise the diffusive transport of the electroactive species to the electrode as being eithervia partition into and then within the membrane, or alternatively exclusively via pinholes. The transientsexpected in the two cases are often closely similar. We use ML to provide a user independent analysis of thetransient to indicate the most probable mechanism. The limitations and strengths of this approach are criticallydiscussed.",

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AU - Marken, Frank

AU - Compton, Richard

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KW - Random forest

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Electrodes Modified with Thin Films: Distinguishing Between Membrane and Pinhole Diffusion Using Machine Learning

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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