Investigation of Fuel Modification to Reduce Crossover in Direct Methanol Fuel Cells
Bibliographic record
Abstract
The direct methanol fuel cell (DMFC) has the potential to replace battery technology for micro & small portable applications and may be used in larger applications if key technological barriers can be overcome. Presently, fuel crossover through the electrolyte is a major limitation on the performance and fuel utilization efficiency. Different approaches to reduce crossover have been examined, including new membranes, membrane modification, variation of operating conditions, and novel electrode design. The investigation of methanol crossover through fuel modification represents an important new approach to the reduction of crossover in a DMFC. In this study, systems of acetic acid/water/methanol & propionoic acid/water/methanol have been found to reduce methanol crossover through Nafion® 117 membranes, carbon fibre diffusion layers, diffusion electrodes and membrane electrode assemblies.
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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".