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Enregistrement W2736227312 · doi:10.1149/ma2017-02/34/1487

Tracking the Evolution of Mechanical Degradation in Fuel Cell Membranes Using 4D in Situ Visualization

2017· article· en· W2736227312 sur OpenAlexaffabout
Yadvinder Singh, Robin White, Vivian Pan, Marina Najm, Alex Boswell, Francesco P. Orfino, Monica Dutta, Erik Kjeang

Notice bibliographique

RevueECS Meeting Abstracts · 2017
Typearticle
Langueen
DomaineEngineering
ThématiqueFuel Cells and Related Materials
Établissements canadiensSimon Fraser University
Organismes subventionnairesnon disponible
Mots-clésMembraneDelamination (geology)Materials scienceDegradation (telecommunications)Proton exchange membrane fuel cellIn situPolymerIonomerComposite materialComputer scienceChemistryCopolymer

Résumé

récupéré en direct d'OpenAlex

During automotive operation of polymer electrolyte fuel cells, dynamic duty cycles can gradually introduce various damage features within the ionomer membrane, viz. cracks, tears, pinholes, thinning, delamination etc., collectively leading to ultimate operational failure of the fuel cell. There are two main degradation mechanisms that drive damage development within the membrane: (i) chemical degradation due to radical attack; and (ii) mechanical degradation due to hygrothermal variations under mechanically constrained conditions. Although both of these mechanisms are simultaneously active during fuel cell operation, analyzing them in an uncoupled manner could aid in assessing the role of individual damage features in overall membrane failure which could potentially result in the development of effective failure mitigation strategies. Failure analysis studies of fuel cell membranes typically employ scanning electron microscopy (SEM) which is two-dimensional (2D) in nature and is inherently destructive, thereby inhibiting any possibility to track degradation-induced structural changes over time. Consequently, membrane degradation evolution studies are limited to ex situ analysis of different samples at various stages of degradation. In our recent work, laboratory-based X-ray computed tomography (XCT) was utilized to perform three-dimensional (3D) ex situ failure analysis of fuel cell membranes and the 3D nature of this imaging technique revealed novel insights into membrane failure that had thus far eluded the traditional 2D investigations [1]. Additionally, XCT imaging is also non-destructive and non-invasive [2], and the present work leverages these attributes with the objective to extend the 3D failure analysis approach to an in situ investigation of pure mechanical membrane degradation , following a unique 4D approach wherein the fourth dimension represents time or degradation state. This is achieved by utilizing a custom designed X-ray transparent fuel cell fixture [3] with which 3D visualization of identical membrane locations can be performed periodically, thereby offering a novel approach to track the structural/morphological evolution of the membrane in its true sense as a function of degradation. The custom designed X-ray transparent fixture was made with a 9 mm (length) x 4 mm (width) active area and consisted of two co-flow parallel straight channels each having 1 mm width and separated by a 250 μm wide central land region with additional land regions at the two peripheral sides. After assembling a single fuel cell within it, pure mechanical degradation in form of in situ hygrothermal fatigue was generated within the membrane by subjecting the assembled fuel cell held at 80°C to successive cycles of 2 min wet and 2 min dry states with nitrogen gas on both anode and cathode sides to eliminate chemical degradation. A laboratory-based XCT system, ZEISS Xradia 520 Versa® , was used to obtain 3D tomographic images at two different length scales: (i) low resolution (2.1 μm voxel size) large field of view (FOV) scans for inspecting the overall membrane damage; and (ii) high resolution (1.1 μm voxel size) zoomed scans of selected regions of interest for a detailed structural investigation. Tomographic data of identical locations were acquired periodically at every 500 wet/dry cycles to track membrane damage development over time. No cracks had appeared within the membrane up to 1500 wet/dry cycles, whereas a significant number of through-thickness membrane cracks had developed at 2000 cycles. This result suggests that fatigue-driven mechanical degradation progresses non-linearly over time via distinct crack initiation/propagation events. The majority of the membrane crack development occurred under the channel regions which is consistent with higher tensile stresses predicted in these regions by simulation studies [4]. A strong correlation was observed between the presence of beginning-of-life (BOL) MEA defects, mainly cathode catalyst layer cracks and membrane—catalyst layer delamination, and eventual formation of membrane cracks at those locations (cf. Figure 1). In many cases, the shape of newly developed membrane cracks resembled that of the BOL catalyst layer cracks suggesting that localized stress concentration effects may influence both crack initiation and propagation within the membrane. Overall, the novel approach for 4D same-location tracking of membrane degradation reported in this work shows significant potential for improved fundamental understanding of the membrane crack development process during mechanical degradation in fuel cells. 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] Y. Singh et al., J. Power Sources. 345 (2017). [2] R.T. White et al., J. Electrochem. Soc. 163 (2016). [3] R.T. White et al., J. Power Sources 350 (2017). [4] R.M.H. Khorasany et al., J. Power Sources 252 (2014). 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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut 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 enseignants0,001
Score d'incertitude au seuil0,005

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,020
Tête enseignante GPT0,250
Écart entre enseignants0,230 · 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 source (Gemma direct ou Codex distillé), 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

Citations2
Publié2017
Routes d'admission2
Résumé présentoui

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