Polymer Electrolyte Membrane Fuel Cells: Characterization and Diagnostics
Bibliographic record
Abstract
The normal operation of polymer electrolyte membrane fuel cells (PEMFCs) can induce significant temperature, humidity, pressure or concentration gradients across the cell’s active area. The overall performance and stability can be affected negatively by these gradients, and they may contribute to material degradation, and ultimately, to cell failure. We report on diagnostic techniques and methodologies to characterize PEMFC material properties and the inhomogeneities across the active area of a working cell. Specifically, we describe in-situ techniques for the spatially-resolved characterization of PEMFC performance. Our testing hardware features sixteen fully isolated segments over a 49 cm 2 active area, reference electrode capabilities, and individual segment control. The techniques are applied to the in-situ characterization of effective platinum surface area (EPSA) degradation under 1×10 5 accelerated stress testing (AST) cycles.
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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".