Mesoporous iron-nitrogen co-doped carbon material as cathode catalyst for the anion exchange membrane fuel cell
Bibliographic record
Abstract
A novel and commercially available electrocatalyst is characterised and used as cathode catalyst in an anion-exchange membrane fuel cell (AEMFC). The catalyst material is prepared using VariPore™ method by Pajarito Powder, LLC, and as dopants iron and nitrogen are used, making it a mesoporous transition metal-nitrogen-carbon type catalyst. The physico-chemical characterisation shows the success of doping as well as almost completely mesoporous structure (average pore size of approximately 7 nm) with high specific surface area. The initial assessment of the oxygen reduction reaction (ORR) activity by the rotating ring-disc electrode method reveals that the material exhibits a very good electrocatalytic performance in alkaline media having a half-wave potential of 0.89 V. The catalyst material is employed as an anion exchange membrane fuel cell cathode and it shows AEMFC performance as good as that of the Pt-based material. The high ORR electrocatalytic activity of this material is due to the synergy of nitrogen-moieties, namely pyrrolic-N, pyridinic-N and graphitic-N, with iron as well as the highly mesoporous nature.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".