Research Progress on Graphite-Derived Materials for Electrocatalysis in Energy Conversion and Storage
Bibliographic record
Abstract
High-performance electrocatalysts are critical to support emerging electrochemical energy storage and conversion technologies. Graphite-derived materials, including fullerenes, carbon nanotubes, and graphene, have been recognized as promising electrocatalysts and electrocatalyst supports for the oxygen reduction reaction (ORR), oxygen evolution reaction (OER), hydrogen evolution reaction (HER), and carbon dioxide reduction reaction (CO2RR). Effective modification/functionalization of graphite-derived materials can promote higher electrocatalytic activity, stability, and durability. In this review, the mechanisms and evaluation parameters for the above-outlined electrochemical reactions are introduced first. Then, we emphasize the preparation methods for graphite-derived materials and modification strategies. We further highlight the importance of the structural changes of modified graphite-derived materials on electrocatalytic activity and stability. Finally, future directions and perspectives towards new and better graphite-derived materials are presented.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".