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How the distribution of relaxation times enhances complex equivalent circuit models for fuel cells

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Dierickx, Sebastian, Weber, André, Ivers-Tiffée, Ellen·2020·Electrochimica Acta

Abstract

Abstract Distribution of relaxation times (DRT) is a well-established method for deconvoluting electrochemical impedance spectroscopy (EIS) data from fuel cells. DRT-analysis provides a deeper insight into electrode reactions and supports identification of the most accurate equivalent circuit models. This established method has undergone much change in recent decades and has been applied to many sub-fields. Contemporary studies are highly specialized and produce specialist literature: to further a comprehensive view, this paper provides an overview and retrospective. EIS measurement and subsequent interpretation by DRT are challenging because (i) high-performance electrodes have very low impedances (10-100 mΩ), (ii) the concept of one rate-limiting step is usually not applicable, and (iii) the charge transfer and transport processes in anode and cathode are often coupled; overlapping in the frequency domain. In this paper selected results from advanced EIS and DRT analyses are discussed. We demonstrate the importance of EIS data quality, introduce the use of the Kramers-Kronig transformation, explain the impacts of statistically distributed noise and single errors in EIS spectra, and the selection of the regularization parameter lambda for improved interpretation of DRT curves. Finally, well-selected examples of DRT approaches lead to adequate models with different complexity. As a result, this paper deepens the understanding of how to assess electrochemical measurements of fuel cells based on the DRT. It, therefore, represents a vital guide for DRT analysis.

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Metadata

Authors
Dierickx, S., Weber, A., & Ivers-Tiffée, E.
Venue
Electrochimica Acta
Publisher
Elsevier BV
Published
2020-09
Volume
355
Pages
136764
ISSN
0013-4686 (ISSN-L)
OpenAlex
W3043671675
Cited by
281
References
46
FWCI
8.10
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: How the distribution of relaxation times enhances complex equivalent circuit models for fuel cells. https://app.cochat.ai/papers/10.1016/j.electacta.2020.136764
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Dierickx, S., Weber, A., & Ivers-Tiffée, E. (2020). How the distribution of relaxation times enhances complex equivalent circuit models for fuel cells. Electrochimica Acta. https://doi.org/10.1016/j.electacta.2020.136764

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.