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Enregistrement W2512328198 · doi:10.1149/ma2016-02/38/2519

In Situ Visualization of Cathode Catalyst Layer Degradation in Fuel Cells Using X-Ray Computed Tomography

2016· article· en· W2512328198 sur OpenAlexaffabout
Robin White, Alex Wu, Monica Dutta, Erik Kjeang

Notice bibliographique

RevueECS Meeting Abstracts · 2016
Typearticle
Langueen
DomaineEngineering
ThématiqueFuel Cells and Related Materials
Établissements canadiensSimon Fraser University
Organismes subventionnairesnon disponible
Mots-clésCathodeDielectric spectroscopyMaterials scienceDegradation (telecommunications)CorrosionScanning electron microscopeChemical engineeringCyclic voltammetryElectrolytePlatinumDurabilityElectrochemistryCatalysisNanotechnologyComposite materialElectrodeChemistryElectrical engineeringOrganic chemistryEngineering

Résumé

récupéré en direct d'OpenAlex

Polymer electrolyte fuel cells (PEFCs) have been growing in popularity as an alternative energy source for a multitude of applications, including the automotive industry. The use of fuel cells in these applications requires long-term durability with minimal degradation to be cost competitive against conventional technology sources. Current targets for automotive applications are >5,000 hours, under realistic operating conditions. One primary degradation pathway associated with these operating conditions is that of cathode catalyst support corrosion, which occurs due to the oxidation of carbon support for platinum nanoparticles, leaving the platinum unsupported and inactive. The pathway for this degradation mechanism is at elevated cathode potentials greater than 1.2 V RHE , where significant carbon corrosion, in the presence of water, occurs at rates high enough to cause significant structural degradation effects. These elevated potentials can occur during fuel starvation or gas switching during start-up and shutdown procedures [1]. A significant amount of effort has been devoted toward research regarding cathode degradation rates and mitigation, primarily using methods such as electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), and scanning electron microscopy (SEM). These methods provide information on a global, two-dimensional perspective. That is, SEM typically provides information on catalyst layer thinning by 2-D cross-sectional images, and EIS and CV provide overall electrochemical changes affected by changes in surface area from carbon corrosion. The usefulness of the proposed X-ray computed tomography (XCT) technique is in its non-invasive nature, excellent spatial resolution, and three-dimensional imaging abilities. These advantages allow for observations to be made on a local and global level providing further insight into the cathode catalyst layer degradation process. Typically research regarding XCT is performed at a synchrotron beamline which is significantly limiting in that it is expensive, impractical and available in only short time intervals. This means that investigating in-situ degradation effects is extremely difficult. 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 an investigation toward understanding cathode catalyst layer degradation mechanisms through in-situ visualization by commercial XCT using a fully functional dual-channel, small-scale, fuel cell fixture [2]. This small-scale fixture allows imaging of the membrane electrode assembly (MEA) at multiple stages of its lifecycle during an accelerated stress test, targeting the cathode catalyst layer, in this case causing carbon corrosion. Differences under land and channel are investigated as well as water distribution, which is shown to have a significant effect on the degradation rate using a sample containing catalyst layer cracks. Image processing techniques used to obtain quantitative results are discussed which include histogram deconvolution and thresholding. Figure 1 shows the thresholding procedure results, indicating differences found under land and channel. Continued research using this tool hopes to further our understanding of the interconnectivity within a fuel cell. 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] A. Young, V. Colbow, D. Harvey, E. Rogers, and S. Wessel. J. Electrochem. Soc . 160 (4) F381-F388 (2013) [2] R. White, M. El Hannach, O. Luo, F. Orfino, M. Dutta and E. Kjeang. ECS abstract 58394, presented at 228 th ECS meeting, Phoenix, AZ. Oct. 11-16, 2015 Figure 1: a) 3D visualization of a full MEA highlighting local thresholding ability b) 2D segmented area of cathode catalyst at BOL and EOL c) plot showing area fraction of solid to crack change during accelerated stress test d) cross-section of regions used in calculations for the plot above. The image shows a single slice from the End of Life (EOL) sample 3D reconstruction 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 enseignants0,359
Score d'incertitude au seuil0,447

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 GPT0,236
Écart entre enseignants0,221 · 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

Citations1
Publié2016
Routes d'admission2
Résumé présentoui

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