Interactive Effects of Membrane Additives on PEMFC Catalyst Layer Degradation
Bibliographic record
Abstract
Membrane additives are used in polymer electrolyte membrane fuel cells (PEMFC) to improve membrane durability due to their effectiveness in scavenging hydroxyl and hydroperoxy radicals. Even though their implication on performance is well-known, their impacts on the durability of other components and failure mechanisms have not been reported. In this study, accelerated stress tests (AST) were used to induce catalyst degradation. The effects of Mn- and Ce-based membrane additives on catalyst degradation were characterized by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray (EDX), and neutron activation analysis (NAA). Pt dissolution, Pt agglomeration, carbon surface oxidation, and carbon corrosion were found to be unaffected by the membrane additives. However, the performance impact of these additives became exacerbated with degradation. The effect on Ru crossover was more complex. Ru crossover was lessened in the presence of additives but the performance impact was amplified for a given crossover level. The impact on cathode and anode degradation was deduced to be the combined effect of reduced cathode protonic conductivity and longer proton transport path as the reaction distribution shifted deeper into the catalyst layer. This research highlighted the importance of interaction consideration in component development.
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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 | 0.000 | 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 | 0.000 | 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".