Phosphorus-Doped Graphene Electrocatalysts for Oxygen Reduction Reaction
Bibliographic record
Abstract
Developing cheap and earth-abundant electrocatalysts with high activity and stability for oxygen reduction reactions (ORRs) is highly desired for the commercial implementation of fuel cells and metal-air batteries. Tremendous efforts have been made on doped-graphene catalysts. However, the progress of phosphorus-doped graphene (P-graphene) for ORRs has rarely been summarized until now. This review focuses on the recent development of P-graphene-based materials, including the various synthesis methods, ORR performance, and ORR mechanism. The applications of single phosphorus atom-doped graphene, phosphorus, nitrogen-codoped graphene (P, N-graphene), as well as phosphorus, multi-atoms codoped graphene (P, X-graphene) as catalysts, supporting materials, and coating materials for ORR are discussed thoroughly. Additionally, the current issues and perspectives for the development of P-graphene materials are proposed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".