Investigating Freeze-Thaw Cycling-Induced Degradation in Proton Exchange Membrane Fuel Cells
Bibliographic record
Abstract
Freeze-thaw (F-T) cycling in Proton Exchange Membrane Fuel Cells (PEMFCs) poses significant challenges to the long-term durability of their components [1,2]. Previous studies primarily relied on 2D imaging techniques to assess degradation effects. Recent advancements in X-ray tomography now enable high-resolution virtual 3D imaging, providing detailed volumetric insights and significantly improved structural information. This approach also preserves the cell’s operational integrity, avoiding artifacts introduced by disassembly and reassembly processes. This study leverages these advancements to investigate F-T cycling-induced degradation mechanisms in a small-scale fuel cell (active area: 0.39 cm²) using advanced in-situ X-ray Computed Tomography (XCT) imaging and electrochemical diagnostics. A custom-designed fuel cell fixture facilitated precise temperature control and real-time visualization of structural changes within the catalyst-coated membrane (CCM) [3]. The experimental design strategically applied localized stresses by controlling the initial water distribution within the membrane and catalyst layers, intensifying the effects of F-T cycling for focused investigation. XCT imaging revealed structural degradation after only 20 cycles (Figure 1), including delamination at the membrane-catalyst interface, crack formation in the catalyst layers (CLs) and membrane. Electrochemical analyses corroborated these findings, showing performance losses characterized by increased ohmic and mass transport resistances in polarization curves. Cyclic voltammetry highlighted significant reductions in the electrochemically active surface area (ECSA) of the catalyst, while impedance spectroscopy revealed substantial increases in high-frequency and catalyst layer resistance. These findings underscore the vulnerability of PEMFC components to F-T cycling and highlight the critical importance of advanced material design and mitigation strategies enhance durability of PEMFC’s components in harsh climates. Keywords: Freeze-Thaw Cycling – Proton Exchange Membrane Fuel Cells (PEMFCs) – X-ray Computed Tomography (XCT) – Membrane Degradation – Fuel Cell Durability Acknowledgements: This research is funded by the Natural Sciences and Engineering Research Council of Canada, Ballard Power Systems, Simon Fraser University, the Canada Foundation for Innovation, the British Columbia Knowledge Development Fund, the Canada Research Chairs Program, Mitacs and Pacific Economic Development Canada. References: [1] A. Ozden, S. Shahgaldi, J. Zhao, X. Li, and F. Hamdullahpur, "Degradations in porous components of a proton exchange membrane fuel cell under freeze-thaw cycles: Morphology and microstructure effects," International Journal of Hydrogen Energy, vol. 45, no. 5, pp. 3618-3631, 2020. [2] Lee, Y., Kim, B., Kim, Y., & Li, X. (2011). Effects of a microporous layer on the performance degradation of proton exchange membrane fuel cells through repetitive freezing. Journal of Power Sources, 196(4), 1940-1947. [3] White, R. T., Wu, A., Najm, M., Orfino, F. P., Dutta, M., & Kjeang, E. (2017). 4D in situ visualization of electrode morphology changes during accelerated degradation in fuel cells by X-ray computed tomography. Journal of Power Sources, 350, 94-102. 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 | 0.000 | 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 | 0.001 |
| 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".