The influence of membrane electrode assembly water content on the performance of a polymer electrolyte membrane fuel cell as investigated by 1H NMR microscopy
Bibliographic record
Abstract
The relation between the performance of a self-humidifying H(2)/O(2) polymer electrolyte membrane fuel cell and the amount and distribution of water as observed using (1)H NMR microscopy was investigated. The integrated (1)H NMR image signal intensity (proportional to water content) from the region of the polymer electrolyte membrane between the catalyst layers was found to correlate well with the power output of the fuel cell. Several examples are provided which demonstrate the sensitivity of the (1)H NMR image intensity to the operating conditions of the fuel cell. Changes in the O(2)(g) flow rate cause predictable trends in both the power density and the image intensity. Higher power densities, achieved by decreasing the resistance of the external circuit, were found to increase the water in the PEM. An observed plateau of both the power density and the integrated (1)H NMR image signal intensity from the membrane electrode assembly and subsequent decline of the power density is postulated to result from the accumulation of H(2)O(l) in the gas diffusion layer and cathode flow field. The potential of using (1)H NMR microscopy to obtain the absolute water content of the polymer electrolyte membrane is discussed and several recommendations for future research are provided.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".