Analysis of Fuel Cell Membrane Buckling into Gas Diffusion Layer Holes and Its Impact on Fuel Cell Durability
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".