Impact of membrane scratches on fuel cell durability
Bibliographic record
Abstract
Cost-effective, scalable fuel cell production requires a comprehensive understanding of the potential impacts of various non-uniformities that may be present in the membrane electrode assembly. The present work investigates the fuel cell durability impacts of membrane scratches, which may occur during fabrication. X-ray computed tomography is utilized to track localized degradation phenomena in two purposefully designed fuel cells with scratch-containing reinforced membranes subjected to chemo-mechanical accelerated stress testing. Several effective parameters that control the extent of local degradation in scratch regions are identified as: (i) friction between the catalyst coated membrane and gas diffusion layer (GDL); (ii) scratch width; (iii) obstacles for free membrane deformation; (iv) GDL collapse into the scratched area; and (v) scratch direction. Importantly, two major self-mitigating mechanisms that can support the scratched region chemically and mechanically are identified, namely up to 85 % less chemical degradation in catalyst-free scratched regions and elimination of harmful tensile stress due to membrane-microporous layer fusion under the same conditions. The obtained results indicate that scratches on the membrane can potentially be manageable by controlling the effective parameters. • The impact of membrane scratches on fuel cell durability is investigated. • Scratched membranes are stress tested and visualized in situ using X-ray imaging. • Key influential factors include friction, scratch width, obstacles, and GDL contact. • Two self-stabilizing mechanisms that enhance durability are identified. • Catalyst-free scratched regions experienced up to 85 % less chemical thinning.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".