Nitrogen and Phosphorus Dual-Doped Silicon Carbide-Derived Carbon/Carbon Nanotube Composite for the Anion-Exchange Membrane Fuel Cell Cathode
Bibliographic record
Abstract
Dual heteroatom (N,P)-doped catalysts based on the composite of silicon carbide-derived carbon (SiCDC) and carbon nanotubes (CNTs) or solely CNTs were prepared for oxygen reduction reaction (ORR) using melamine phosphate as nitrogen and phosphorus precursors. The half-cell test conducted by the rotating ring-disk electrode method exhibited a high ORR electrocatalytic activity for N,P-SiCDC/CNT with an onset potential of 0.91 V and a half-wave potential of 0.80 V in alkaline solution. Similar ORR results were obtained with N,P-CNT. The dual heteroatom-doped SiCDC/CNT composite as a cathode catalyst exhibited an impressive peak power density of 538 mW cm –2 in an anion-exchange membrane fuel cell (AEMFC) test. The superior AEMFC performance of this catalyst could be attributed to (i) the high specific surface area along with hierarchical porosity (micro/mesopores) as revealed by the N 2 physisorption analysis, (ii) high defect density ( I D / I G = 1.54) determined by Raman spectroscopy analysis, and (iii) successful doping of N and P moieties into the carbon materials as revealed by X-ray photoelectron spectroscopy and scanning transmission electron microscopy coupled with energy-dispersive X-ray spectroscopy.
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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) | 0.001 | 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 | 0.000 |
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".