Impact of Irregular Microporous Layer on Chemo-Mechanical Membrane Degradation Investigated by 4D in-Situ Fuel Cell Visualization
Bibliographic record
Abstract
Membrane durability is critical to the performance and safe operation of proton exchange membrane fuel cells (PEMFC). To address chemical and mechanical membrane degradation mechanisms, substantial mitigation strategies have been developed to enhance the strength of membranes. However, as a system, it is also important to make sure that the membrane electrode assembly (MEA) subcomponents and their integration do not produce unexpected non-uniformities in the manufacturing process, which may lead to premature membrane failure. The interaction between the membrane and gas diffusion media, such as gas diffusion layers (GDLs) and microporous layers (MPLs), was deemed as one of the major root causes for many membrane failure modes [1]. Previously reported mechanisms include elevated membrane buckling induced by micro sags or voids on MPL surface, and local impingement due to GDL fiber protrusion [1]. These non-uniformity features within the MPL and GDL can be natural irregularities from manufacturing, or unexpected damage during handling, and are difficult to control and characterize due to the random nature of the porous fibrous structure of the GDL. In a previous talk [2], the impact of though-plane GDL holes was discussed as they may relate or contribute to the combined chemo-mechanical membrane degradation mechanism. Both accelerated stress testing (AST) and X-ray computed tomography (XCT) imaging results suggest that GDL holes can be harmful to chemical and mechanical membrane degradation and the level of severity depends on their size and location. As a result, further in-depth research is warranted to capture the salient interactions between membrane degradation mechanisms and GDL non-uniformities. The objective of the present work is to determine the influences of missing MPL spots on fuel cell membrane chemo-mechanical durability. Compared to through-plane GDL holes, the fiber structure of the GDL was left intact, while only the MPL layer was completely removed at select locations. The study was carried out using a previously disclosed four dimensional (three spatial dimensions plus one temporal dimension) in-situ XCT visualization technique [3], where membrane degradation was traced at different life stages over time. The MEAs used in this work were composed of GORE-SELECT® membrane, crack free Pt based catalyst layers (CLs), and AvCarb® GDLs with customized smooth and crack free MPL. Circular missing MPL spots were artificially created by laser micromachining, with precisely controlled laser beam energy to only remove the MPL without damaging the GDL substrate. Missing MPLs of multiple controlled sizes were placed at strategic locations, both under flow channels and lands, on anode or cathode GDLs. The MEAs were custom designed small scale MEAs [3] for in-situ XCT visualization, and were subjected to a custom AST protocol imparting combined chemo-mechanical stresses [3] in an alternating pattern. The results confirmed that missing MPL spots are indeed harmful to the membrane durability, mainly through GDL fiber impingement. The impact level of the missing MPL non-uniformity highly depends on its location. Under flow channels, membrane buckling and associated CL crack formation were the major failure modes induced by missing MPL. Regardless of which electrode had the missing MPL, CL cracks tended to initiate either from GDL impinging locations or within voids of the GDL substrate. However, both membrane buckling and CL cracks were moderate, and their influence on MEA performance and durability was minor. Under the supporting lands, GDL impinging and membrane penetration became the major failure modes instead of membrane buckling and CL cracks, which was assessed to be due to the elevated through-plane compression. GDL impinging can be detrimental to MEA performance and membrane durability by penetrating through the membrane and raise electrode shorting, which was validated through a control experiment with MPL-free GDL. Keywords: fuel cell; membrane durability; gas diffusion layer; mechanical degradation; chemical degradation; 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] D. Ramani, N.S. Khattra, Y. Singh, F.P. Orfino, M. Dutta, E. Kjeang, Journal of Power Sources 512 (2021) 230431. [2] Y. Chen, A. Bahrami, N. Kumar, F.P. Orfino, M. Dutta, E.N. Alvar, M. Lauritzen, E. Setzler, A. Agapov, E. Kjeang, Meet. Abstr. MA2023-02 (2023) 1780. [3] Y. Chen, M. Bahrami, N. Kumar, F.P. Orfino, M. Dutta, M. Lauritzen, E. Setzler, A.L. Agapov, E. Kjeang, J. Electrochem. Soc. 170 (2023) 114526. 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".