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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...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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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. |
format | Online Article Text |
id | pubmed-8956593 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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