Fuel cell membrane durability impacts of incidental non-metallic particle deposition – Part 1: Effect of particle type
Bibliographic record
Abstract
This two-part article series examines the impacts of incidental non-metallic particle deposition on fuel cell membrane durability. Part 1 investigates the effect of particle type, while Part 2 focuses on mitigation approaches. In this part (Part 1), selected foreign particles are intentionally introduced at the membrane and catalyst layer interface of a fuel cell, which is then subjected to chemo-mechanical stress testing with 4D tracking of local degradation using in-situ X-ray computed tomography. The results show that 35 μm polytetrafluoroethylene particles, 100 μm polyethylene terephthalate fibers, and 60 μm polymethyl methacrylate (PMMA) microspheres are unlikely to affect the durability in long-term operation due to minuscule effect on the catalyst coated membrane. However, 300 μm PMMA microspheres, 60 μm silica microspheres, and 1000 μm graphite flakes have the potential to compromise durability by damaging the membrane during fabrication or creating room for increased membrane deformation, which can lead to greater stress fluctuations during operation. The results indicate that stiffness, shape, and size determine whether a given particle is harmful to cell durability. • Durability impacts depend on particle size, shape, hardness, and interaction mode. • PTFE, PET, and 60 μm PMMA particles had minor impact on membrane durability. • 300 μm PMMA and 60 μm silica particles caused membrane damage during fabrication. • Graphite flakes created adjacent cavities, leading to inevitable membrane failure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".