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Enregistrement W2266306088 · doi:10.1149/ma2015-02/37/1541

3D Printed Flow Channel Fixture for Visualization of Water Condensation in PEFC By X-Ray Computed Tomography

2015· article· en· W2266306088 sur OpenAlexaffabout
Robin White, Mohamed El Hannach, Oliver Luo, Monica Dutta, Erik Kjeang

Notice bibliographique

RevueECS Meeting Abstracts · 2015
Typearticle
Langueen
DomainePhysics and Astronomy
ThématiqueNuclear Physics and Applications
Établissements canadiensSimon Fraser University
Organismes subventionnairesnon disponible
Mots-clésNeutron imagingMaterials scienceProcess engineeringTurbinePower densityNeutronNuclear engineeringComputer sciencePower (physics)Mechanical engineering

Résumé

récupéré en direct d'OpenAlex

Polymer electrolyte fuel cells (PEFC) have been shown to have significant potential for automotive applications as an alternate clean energy technology with zero emissions at the point of use. The many advantages include quick start-up time, low operating temperature, low weight, high efficiency and relatively simple design [1]. Despite these advantages however a primary reason for the delay of this technology from meeting commercial application standards is cost. Significant cost reductions are possible by increasing the power density, which is currently limited by liquid water related mass transport effects at high current densities. Higher power density cells are also an advantage for automotive applications due to a better form factor for vehicles. Due to the components that make up a membrane electrode assembly (MEA) and fuel cell, many current in situ visualization techniques for water visualization utilize neutron imaging, since it has the advantage of being sensitive to hydrogen containing compounds such as water and other components of the PEFC, while being insensitive to metals that make up compression plates and current collectors. Neutron imaging is, however, limited by its spatial resolution and has extremely high cost with limited availability since the technique requires a nuclear reactor [2]-[4]. The usefulness of X-ray computed tomography (XCT) is in its non-invasive nature, excellent spatial resolution and better sensitivity to membrane electrode assembly (MEA) component materials. X-rays have the ability to pass through materials with the attenuation scaling with atomic number and density. This causes the sensitivity of X-rays to be extremely low for hydrogen, however all other components such as carbon, oxygen, nitrogen and metals, such as platinum, provide sufficient contrast to observe all fuel cell components and liquid water. Much of the initial work involving XCT of fuel cells was done using synchrotron radiation as the X-ray source. This is primarily due to the intensity of the beam, and is still used by researchers with access to synchrotron sources. This research however is extremely expensive and impractical for a large majority of research groups without access to a synchrotron source. With advances in commercial X-ray sources, optics and detectors for laboratory use, many researchers are now being able to take advantage of the power of XCT scans with much lower cost and increased availability. In this work we present a novel approach toward the beginnings of unraveling liquid water distribution in PEFCs by the use of rapid prototyping 3D printed materials to create a small scale flow channel fixture for 3D XCT visualization of a full MEA. Unlike previous research, water condensation, formation, and transport within a cell can be observed by drawing current from the cell to allow for in situ water production before imaging at an equilibrium state. Comparison of dry un-operated MEAs to humidified (zero current drawn) and wet (operated) MEAs is used to more clearly define water content and distribution with results shown in figure 1. Other processing techniques such as image subtraction are performed to better enhance the changes during operation. Preliminary results show significant water content after operation with high saturation seen on the cathode side on the surface of the GDL. Water content also varies across the width of the sample with trapped liquid water beneath the channel landing on both anode and cathode sides. Other changes such as membrane swelling and resultant movement in catalyst layer are also observed. Continued investigation using this tool shows great promise toward further understanding changes occurring on all facets of this dynamic system during fuel cell operation. Acknowledgements Funding for this research was provided by the Natural Sciences and Engineering Research Council of Canada, Canada Foundation for Innovation, British Columbia Knowledge Development Fund, and Ballard Power Systems through an Automotive Partnership Canada grant. References [1] M. M. Mench, Fuel Cell Engines. John Wiley & Sons, 2008. [2] A. Turhan, K. Heller, J. S. Brenizer, and M. M. Mench, Journal of Power Sources, vol. 160, no. 2, pp. 1195–1203, Oct. 2006. [3] R. Satija, D. L. Jacobson, M. Arif, and S. A. Werner, Journal of Power Sources, vol. 129, no. 2, pp. 238–245, Apr. 2004. [4] R. J. Bellows, M. Y. Lin, M. Arif, A. K. Thompson and D. Jacobson J. Electrochem. Soc. vol.146, no. 3, pp.1099-1103. 1999 Figure 1

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,179
Score d'incertitude au seuil0,377

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,015
Tête enseignante GPT0,254
Écart entre enseignants0,239 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2015
Routes d'admission2
Résumé présentoui

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