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A review on the distribution of relaxation times analysis : A powerful tool for process identification of electrochemical systems

Title data

Plank, Christian ; Rüther, Tom ; Jahn, Leonard ; Schamel, Maximilian ; Schmidt, Jan Philipp ; Ciucci, Francesco ; Danzer, Michael A.:
A review on the distribution of relaxation times analysis : A powerful tool for process identification of electrochemical systems.
In: Journal of Power Sources. Vol. 594 (2024) . - 233845.
ISSN 0378-7753
DOI: https://doi.org/10.1016/j.jpowsour.2023.233845

Abstract in another language

The Distribution of Relaxation Times (DRT) analysis gained considerable attention for its ability to reveal detailed information about complex electrochemical processes without requiring a priori knowledge. This review provides a comprehensive insight into different methods of the DRT analysis, their mathematical bases, and the latest approaches to acquiring and analyzing frequency and time domain data. The analysis is based on the deconvolution of frequency domain data into a distribution function of gains at (pre-specified) relaxation times in the time domain, which improves the spectral resolution and separability of electrochemical processes. It provides valuable information about different electrochemical processes on different time scales, making it particularly useful for the characterization of both materials and electrochemical systems. The DRT analysis can be applied to arbitrary spectra containing electromagnetic effects, resistive–capacitive processes, and solid-state diffusion. To enhance process identification, a post-processing step involving peak analysis with Gaussian or RQ-distribution peaks is presented and the assignment of peak patterns induced by distributed processes like solid-state diffusion is discussed. In addition, a step-by-step workflow for the DRT analysis is provided to guide researchers from data acquisition and validation techniques to calculation and interpretation of the distribution function.

Further data

Item Type: Article in a journal
Refereed: Yes
Institutions of the University: Faculties > Faculty of Engineering Science > Chair Electrical Energy Systems > Chair Electrical Energy Systems - Univ.-Prof. Dr. Michael Danzer
Faculties > Faculty of Engineering Science > Chair Systems Engineering for Electrical Energy Storage > Chair Systems Engineering for Electrical Energy Storage - Univ.-Prof. Dr. Jan Philipp Schmidt
Faculties > Faculty of Engineering Science > Chair Electrode Design of Electrochemical Energy Storage Systems > Chair Electrode Design of Electrochemical Energy Storage Systems - Univ.-Prof. Dr. Francesco Ciucci
Research Institutions > Central research institutes > Bayerisches Zentrum für Batterietechnik - BayBatt
Faculties
Faculties > Faculty of Engineering Science
Faculties > Faculty of Engineering Science > Chair Electrical Energy Systems
Faculties > Faculty of Engineering Science > Chair Systems Engineering for Electrical Energy Storage
Faculties > Faculty of Engineering Science > Chair Electrode Design of Electrochemical Energy Storage Systems
Research Institutions
Research Institutions > Central research institutes
Result of work at the UBT: Yes
DDC Subjects: 600 Technology, medicine, applied sciences > 620 Engineering
Date Deposited: 15 Dec 2023 09:59
Last Modified: 08 May 2024 11:36
URI: https://eref.uni-bayreuth.de/id/eprint/88059