Electrospun Polyacrylonitrile‐Derived Co or Fe Containing Nanofibre Catalysts for Oxygen Reduction Reaction at the Alkaline Membrane Fuel Cell Cathode
Bibliographic record
Abstract
Abstract Electrospun polyacrylonitrile (PAN) based carbon nanofibres (CNF) are employed as cathode catalysts in anion‐exchange membrane fuel cell (AEMFC) for the first time. The catalysts are prepared via pyrolysis of Co or Fe salt‐containing PAN fibre with and without the ionic liquid (IL) additive. The catalyst material preparation is optimised by assessing the oxygen reduction reaction (ORR) activity of different transition metal and nitrogen‐doped CNFs in 0.1 M KOH by rotating disc electrode method followed by testing in real AEMFC configuration. The best performance in the AEMFC is observed in case of Fe and IL containing PAN fibre that was pyrolysed at 1000 °C and additionally treated in an acid solution (Fe/IL‐PAN‐A1000). In the AEMFC, the Fe/IL‐PAN‐A1000 catalyst showed the maximum power density (Pmax) of 289 mW cm−2, which is 82 % of the Pmax obtained with commercial Pt/C cathode catalyst (352 mW cm−2).
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".