Analysis of Fuel Cell Membrane Buckling into Gas Diffusion Layer Holes and Its Impact on Fuel Cell Durability
Notice bibliographique
Résumé
Fuel cell membrane durability can be affected by inhomogeneous physical non-uniformities such as holes and depressions in the gas diffusion layers (GDLs). To enhance quality control in fuel cell manufacturing, it is essential to assess the severity of these non-uniformities to implement effective mitigation strategies. A prior study [1] investigating combined chemical and mechanical membrane degradation with artificially induced GDL holes demonstrated that buckling-induced membrane failure is highly dependent on both the size and location of these defects. However, the extensive duration required for degradation experiments constrained the number of testable scenarios. To overcome this limitation, the present study integrates both modeling and experimental approaches to comprehensively analyze membrane deformation and stress distribution across a wider range of GDL hole sizes and locations. The modeling framework is developed to predict membrane deformation and stress distribution, thereby addressing the knowledge gaps identified in previous research [1]. Complementary to this, experimental investigations utilize a micro-XCT visualization system [2] to enable in-situ monitoring of membrane buckling behavior under both wet and dry conditions, providing crucial validation for the modeling predictions. Experimental findings reveal that membrane buckling behavior is strongly influenced by the size and location of GDL holes. Under flow channels, buckling into through-plane GDL holes initiates when the hole diameter reaches approximately 100 μm, identifying this as the critical threshold below which buckling does not occur. Conversely, in the land regions, membrane buckling occurs regardless of hole size due to the higher through-plane compression in these areas. The simulation results closely align with experimental observations. Specifically, in the flow channel regions, the model predicts the onset of membrane buckling at a GDL hole diameter of 120 μm, with a rapid increase in deformation beyond 150 μm. In land regions, the model suggests that the delayed detachment of the catalyst coated membrane (CCM) and the compression retained from the intact GDL on the opposite electrode contribute to early membrane deformation, even for hole diameters below 100 μm, as indicated in the figure. Since membrane buckling is predominantly driven by hygral swelling into interfacial voids between the CCM and GDL, controlling membrane swelling emerges as a potential mitigation strategy. To evaluate this approach, a 20% thinner reinforced membrane, exhibiting similar mechanical properties, is experimentally tested. The results indicate that the critical GDL hole diameters for membrane buckling initiation remain unchanged relative to the thicker membrane. However, the thinner membrane exhibits reduced deformation and consequently lower in-plane strain across most test scenarios. Given that both membranes possess equivalent mechanical properties, this reduction in strain suggests a corresponding decrease in in-plane tension. Overall, this study integrates experimental and simulation analyses to provide critical insights into membrane buckling behavior, stress distribution, and mitigation strategies. The findings suggest that, in addition to minimizing interfacial voids larger than 100 µm through refined GDL and membrane electrode assembly (MEA) design, reducing membrane swelling via thinner reinforced membranes offers a viable approach to mitigating membrane buckling. These insights contribute to improved long-term durability and performance in fuel cell applications. Keywords: fuel cell; membrane durability; membrane buckling; reinforced membrane modeling; X-ray computed tomography Acknowledgements: This research was supported by the Natural Sciences and Engineering Research Council of Canada, Canada Foundation for Innovation, British Columbia Knowledge Development Fund, Western Economic Diversification Canada, Ballard Power Systems, and W.L. Gore & Associates. This research was undertaken, in part, thanks to funding from the Canada Research Chairs program. References: [1] Y. Chen, A. Bahrami, N. Kumar, F.P. Orfino, M. Dutta, E.N. Alvar, M. Lauritzen, E. Setzler, A. Agapov, E. Kjeang, Impact of GDL Hole on Chemo-Mechanical Membrane Degradation Investigated by 4D in-Situ Visualization, Meet. Abstr. MA2023-02 (2023) 1780. https://doi.org/10.1149/MA2023-02371780mtgabs. [2] Y. Chen, M. Bahrami, N. Kumar, F.P. Orfino, M. Dutta, M. Lauritzen, E. Setzler, A.L. Agapov, E. Kjeang, Effect of Accelerated Stress Testing Conditions on Combined Chemical and Mechanical Membrane Durability in Fuel Cells, J. Electrochem. Soc. 170 (2023) 114526. https://doi.org/10.1149/1945-7111/ad0e43. Figure 1
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».