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High-speed 4D neutron computed tomography for quantifying water dynamics in polymer electrolyte fuel cells

In recent years, low-temperature polymer electrolyte fuel cells have become an increasingly important pillar in a zero-carbon strategy for curbing climate change, with their potential to power multiscale stationary and mobile applications. The performance improvement is a particular focus of researc...

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Autores principales: Ziesche, Ralf F., Hack, Jennifer, Rasha, Lara, Maier, Maximilian, Tan, Chun, Heenan, Thomas M. M., Markötter, Henning, Kardjilov, Nikolay, Manke, Ingo, Kockelmann, Winfried, Brett, Dan J. L., Shearing, Paul R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8956593/
https://www.ncbi.nlm.nih.gov/pubmed/35338141
http://dx.doi.org/10.1038/s41467-022-29313-5
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author Ziesche, Ralf F.
Hack, Jennifer
Rasha, Lara
Maier, Maximilian
Tan, Chun
Heenan, Thomas M. M.
Markötter, Henning
Kardjilov, Nikolay
Manke, Ingo
Kockelmann, Winfried
Brett, Dan J. L.
Shearing, Paul R.
author_facet Ziesche, Ralf F.
Hack, Jennifer
Rasha, Lara
Maier, Maximilian
Tan, Chun
Heenan, Thomas M. M.
Markötter, Henning
Kardjilov, Nikolay
Manke, Ingo
Kockelmann, Winfried
Brett, Dan J. L.
Shearing, Paul R.
author_sort Ziesche, Ralf F.
collection PubMed
description In recent years, low-temperature polymer electrolyte fuel cells have become an increasingly important pillar in a zero-carbon strategy for curbing climate change, with their potential to power multiscale stationary and mobile applications. The performance improvement is a particular focus of research and engineering roadmaps, with water management being one of the major areas of interest for development. Appropriate characterisation tools for mapping the evolution, motion and removal of water are of high importance to tackle shortcomings. This article demonstrates the development of a 4D high-speed neutron imaging technique, which enables a quantitative analysis of the local water evolution. 4D visualisation allows the time-resolved studies of droplet formation in the flow fields and water quantification in various cell parts. Performance parameters for water management are identified that offer a method of cell classification, which will, in turn, support computer modelling and the engineering of next-generation flow field designs.
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spelling pubmed-89565932022-04-20 High-speed 4D neutron computed tomography for quantifying water dynamics in polymer electrolyte fuel cells Ziesche, Ralf F. Hack, Jennifer Rasha, Lara Maier, Maximilian Tan, Chun Heenan, Thomas M. M. Markötter, Henning Kardjilov, Nikolay Manke, Ingo Kockelmann, Winfried Brett, Dan J. L. Shearing, Paul R. Nat Commun Article In recent years, low-temperature polymer electrolyte fuel cells have become an increasingly important pillar in a zero-carbon strategy for curbing climate change, with their potential to power multiscale stationary and mobile applications. The performance improvement is a particular focus of research and engineering roadmaps, with water management being one of the major areas of interest for development. Appropriate characterisation tools for mapping the evolution, motion and removal of water are of high importance to tackle shortcomings. This article demonstrates the development of a 4D high-speed neutron imaging technique, which enables a quantitative analysis of the local water evolution. 4D visualisation allows the time-resolved studies of droplet formation in the flow fields and water quantification in various cell parts. Performance parameters for water management are identified that offer a method of cell classification, which will, in turn, support computer modelling and the engineering of next-generation flow field designs. Nature Publishing Group UK 2022-03-25 /pmc/articles/PMC8956593/ /pubmed/35338141 http://dx.doi.org/10.1038/s41467-022-29313-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Ziesche, Ralf F.
Hack, Jennifer
Rasha, Lara
Maier, Maximilian
Tan, Chun
Heenan, Thomas M. M.
Markötter, Henning
Kardjilov, Nikolay
Manke, Ingo
Kockelmann, Winfried
Brett, Dan J. L.
Shearing, Paul R.
High-speed 4D neutron computed tomography for quantifying water dynamics in polymer electrolyte fuel cells
title High-speed 4D neutron computed tomography for quantifying water dynamics in polymer electrolyte fuel cells
title_full High-speed 4D neutron computed tomography for quantifying water dynamics in polymer electrolyte fuel cells
title_fullStr High-speed 4D neutron computed tomography for quantifying water dynamics in polymer electrolyte fuel cells
title_full_unstemmed High-speed 4D neutron computed tomography for quantifying water dynamics in polymer electrolyte fuel cells
title_short High-speed 4D neutron computed tomography for quantifying water dynamics in polymer electrolyte fuel cells
title_sort high-speed 4d neutron computed tomography for quantifying water dynamics in polymer electrolyte fuel cells
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8956593/
https://www.ncbi.nlm.nih.gov/pubmed/35338141
http://dx.doi.org/10.1038/s41467-022-29313-5
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