Zitieren Sie bitte immer diesen URN: urn:nbn:de:kobv:b43-545978
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 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 theIn 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.…
Autor*innen: | R.F. Ziesche, J. Hack, L. Rasha, M. Maier, C. Tan, T.M.M. Heenan, Henning MarkötterORCiD, N. Kardjilov, I. Manke, W. Kockelmann, D.J.L. Brett, P.R. Shearing |
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Dokumenttyp: | Zeitschriftenartikel |
Veröffentlichungsform: | Verlagsliteratur |
Sprache: | Englisch |
Titel des übergeordneten Werkes (Englisch): | Nature Communications |
Jahr der Erstveröffentlichung: | 2022 |
Organisationseinheit der BAM: | 8 Zerstörungsfreie Prüfung |
8 Zerstörungsfreie Prüfung / 8.5 Röntgenbildgebung | |
Veröffentlichende Institution: | Bundesanstalt für Materialforschung und -prüfung (BAM) |
Verlag: | Nature Publishing Group UK |
Verlagsort: | London |
Jahrgang/Band: | 13 |
Ausgabe/Heft: | 1 |
Erste Seite: | 1616 |
DDC-Klassifikation: | Technik, Medizin, angewandte Wissenschaften / Ingenieurwissenschaften / Angewandte Physik |
Freie Schlagwörter: | Neutron imaging; Polymer electrolyte membrane fuel cell; Tomography |
Themenfelder/Aktivitätsfelder der BAM: | Energie |
Energie / Wasserstoff | |
DOI: | 10.1038/s41467-022-29313-5 |
URN: | urn:nbn:de:kobv:b43-545978 |
Verfügbarkeit des Dokuments: | Datei für die Öffentlichkeit verfügbar ("Open Access") |
Lizenz (Deutsch): | Creative Commons - CC BY - Namensnennung 4.0 International |
Datum der Freischaltung: | 06.04.2022 |
Referierte Publikation: | Ja |
Datum der Eintragung als referierte Publikation: | 06.04.2022 |
Schriftenreihen ohne Nummerierung: | Wissenschaftliche Artikel der BAM |