Composite Membranes of PVDF Nanofibers Impregnated with Nafion for Increased Fuel Concentrations in Direct Methanol Fuel Cells
Bibliographic record
Abstract
Abstract Serious methanol crossover of Nafion greatly limits the use of increased fuel concentrations in methanol fuel cells, which results in a decreased power density. To lower the methanol crossover of Nafion, thin layers of PVDF nanofibers were successfully electrospun and impregnated with a Nafion solution to create novel fuel cell membranes. The morphological structures, mechanical properties, thermal stabilities, chemical resistance and proton conductivity were investigated for each composite membrane. The performances of membranes with different layers of PVDF nanofibers were evaluated, using a single cell direct methanol fuel cell with 10M methanol fuel. In comparison with membranes of pure Nafion, the introduction of PVDF fiber mats greatly enhanced the membrane's thermal and oxidation stabilities, suppressed swelling ratios and water uptake, and increase fuel cell performance.
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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 | 0.000 |
| 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 | 0.001 |
| 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".