4D in situ visualization of chemo-mechanical membrane degradation in fuel cells: Understanding and mitigating edge failures
Bibliographic record
Abstract
Fuel cell is a zero-emission energy conversion device using hydrogen and oxygen to generate power with water as the only by-product.Membrane electrode assembly (MEA) edges are sensitive regions that could influence the overall durability of fuel cells, where membrane degradation at poorly designed edges may lead to premature cell failures.In this work, two MEA edge designs were implemented to study their robustness during combined chemical and mechanical accelerated stress testing.Four-dimensional in situ visualization, enabled by X-ray computed tomography, was performed to understand and mitigate the edge failure issue.Interaction of adhesive-containing polyimide gasket with catalyst coated membrane (CCM) was identified as the key contributor to premature edge failures, which was mitigated by using a non-adhesive inert frame at the CCM interface, thus enabling a robust MEA edge wherein the failures were shifted into the active area.Overall, findings of this research may contribute to robust fuel cell manufacturing and enhanced membrane durability.
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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".