Atomic Fe‐Doped MOF‐Derived Carbon Polyhedrons with High Active‐Center Density and Ultra‐High Performance toward PEM Fuel Cells
Bibliographic record
Abstract
Abstract A metalorganic gaseous doping approach for constructing nitrogen‐doped carbon polyhedron catalysts embedded with single Fe atoms is reported. The resulting catalysts are characterized using scanning transmission electron microscopy, X‐ray photoelectron spectroscopy, and X‐ray absorption spectroscopy; for the optimal sample, calculated densities of Fe–N x sites and active N sites reach 1.75812 × 10 13 and 1.93693 × 10 14 sites cm ‐2 , respectively. Its oxygen reduction reaction half‐wave potential (0.864 V) is 50 mV higher than that of 20 wt% Pt/C catalyst in an alkaline medium and comparable to the latter (0.78 V vs 0.84 V) in an acidic medium, along with outstanding durability. More importantly, when used as a hydrogen–oxygen polymer electrolyte membrane fuel cell (PEMFC) cathode catalyst with a catalyst loading as low as 1 mg cm ‐2 (compared with a conventional loading of 4 mg cm ‐2 ), it exhibits a current density of 1100 mA cm ‐2 at 0.6 V and 637 mA cm ‐2 at 0.7 V, with a power density of 775 mW cm ‐2 , or 0.775 kW g –1 of catalyst. In a hydrogen–air PEMFC, current density reaches 650 mA cm ‐2 at 0.6 V and 350 mA cm ‐2 at 0.7 V, and the maximum power density is 463 mW cm ‐2 , which makes it a promising candidate for cathode catalyst toward high‐performance PEMFCs.
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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".