Evolution of water sorption in catalyst coated membranes subjected to combined chemical and mechanical degradation
Bibliographic record
Abstract
Catalyst coated perfluorosulfonic acid ionomer membranes (CCMs) were subjected to a combined chemical/mechanical accelerated stress test (AST) designed for rapid benchmarking of in situ membrane stability in polymer electrolyte fuel cells. In order to understand the evolution of the ionomer water sorption characteristics during combined chemical/mechanical degradation, CCM samples were periodically extracted from the AST and analyzed for ionomer mass fraction and water sorption properties. In spite of severe fluoride release and membrane thinning, the water uptake per unit mass of the partially degraded CCMs was found to be essentially constant. The mass fraction of ionomer in the CCM samples determined from thermogravimetric analysis (TGA) showed significant material loss throughout the AST process due to ionomer degradation and fluoride release, up to roughly 50% at end-of-life. The effects proceeding at different stages of degradation were therefore more accurately revealed by ionomer mass-normalized data. The water uptake per unit gram of ionomer was shown to increase significantly with degradation, in contrast to the previous results normalized by CCM dry mass. Although increased water sorption may indicate enlarged solvated hydrophilic domains in the membrane, which would be beneficial for enhanced proton mobility, the proton conductivity was found to decrease. This finding suggests that the additional water sorbed in the membrane was not contributing to proton conduction and was therefore likely situated in non-ionic cavities formed through degradation rather than in the ionic clusters.
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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) | 0.000 | 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".