Quantitative in-situ analysis of mechanical degradation of the catalyst coated membrane in proton exchange membrane fuel cells: Influences of temperature and relative humidity swing
Bibliographic record
Abstract
This work investigates mechanical membrane degradation in fuel cells under variable temperature (50–80 °C) and relative humidity (RH) swing (from 0 % to 60–150 %) using 4D in-situ X-ray computed tomography (XCT) to measure spatiotemporal crack length and area in the catalyst layer and membrane as quantifiable degradation metrics. A scoring system classifies the tests into Tiers 1–3 based on applied hygrothermal stresses correlated to crack data and membrane lifetime. Tier 1 exhibits 2-3x faster crack growth rates and lower membrane lifetime than Tiers 2 and 3, with membrane cracks initiating by 5k RH cycles and propagating rapidly by 15k. In contrast, Tier 3 shows delayed membrane crack onset (after 15k) and slower propagation. The results demonstrate that RH swing wet phase apex is an even stronger driver of stress than temperature. Crack growth rate is validated as a quantifiable in-situ degradation metric, and 4D XCT proves effective for quantifying mechanical membrane degradation. • Dynamic crack dimensions are proposed as an in-situ metric of membrane degradation. • 4D in-situ XCT imaging visualizes and quantifies crack growth over time. • Tiered test scoring links stress severity to crack propagation and lifetime. • Higher wet phase apex and temperature accelerate crack propagation by 2-3x. • Membrane cracks occur by 5k RH cycles for highest stress and 15k for lowest stress.
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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 | 0.000 |
| 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".