Highly Active and Durable Metal‐Free Carbon Catalysts for Anion‐Exchange Membrane Fuel Cells
Bibliographic record
Abstract
Abstract The development of highly active and durable platinum‐free oxygen reduction reaction (ORR) catalysts is of vital importance for the practical application of anion‐exchange membrane fuel cells (AEMFCs). Herein, a metal‐free carbon catalyst (marked as NDPC‐1000) with a graphitic N‐regulating defect structure is specifically designed and developed for AEMFCs by integrating theoretical calculations and experiments. Density functional theory calculations first reveal that the graphitic N can tailor the charge density of pentagon and armchair defects to reach the top of the adsorption energy‐activity volcano plot, while the enhanced durability is attributed to the high dissociation energy of the CN covalent bond. Under this guidance, the synthesized NDPC‐1000 demonstrates its high ORR activity and durability in alkaline media. With H2/O2 reacting gases, the AEMFC with this catalyst as the cathode delivers a peak power density of 913 mW cm−2. Unprecedented fuel cell durability is verified via continuous operation over 100 h at 0.25 A cm−2 with only a voltage decay of ≈25%, which is the greatest among all reported metal‐free‐based AEMFCs. Here a theory‐guided experiment strategy is provided for the development of high‐performance and durable ORR catalysts for AEMFCs.
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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".