Nitrogen-Doped Carbon Nanotube and Graphene Materials for Oxygen Reduction Reactions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Nitrogen-doped carbon materials, including nitrogen-doped carbon nanotubes (NCNTs) and nitrogen-doped graphene (NG), have attracted increasing attention for oxygen reduction reaction (ORR) in metal-air batteries and fuel cell applications, due to their optimal properties including excellent electronic conductivity, 4e− transfer and superb mechanical properties. Here, the recent progress of NCNTs- and NG-based catalysts for ORR is reviewed. Firstly, the general preparation routes of these two N-doped carbon-allotropes are introduced briefly, and then a special emphasis is placed on the developments of both NCNTs and NG as promising metal-free catalysts and/or catalyst support materials for ORR. All these efficient ORR electrocatalysts feature a low cost, high durability and excellent performance, and are thus the key factors in accelerating the widespread commercialization of metal-air battery and fuel cell technologies.
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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 | 0.000 | 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) | 0.000 | 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 it