Mechanism investigation of enhanced electrochemical H2O2 production performance on oxygen-rich hollow porous carbon spheres
Bibliographic record
Abstract
Electrochemical oxygen reduction is a promising approach for the sustainable decentralized production of H 2 O 2 , but its viable commercialization is hindered by the insufficient development of efficient electrocatalysts. Here, we demonstrate a promising carbon-based catalyst, consisting of oxygen-rich hollow mesoporous carbon spheres (HMCSs), for selective oxygen reduction to H 2 O 2 . The as-prepared HMCS exhibits high onset potential (0.82 V) and half-wave potential (0.76 V), delivering a significant positive shift compared with its oxygen-scarce counterparts and commercial Vulcan carbon. Moreover, excellent H 2 O 2 selectivity (above 95%) and electrochemical stability (7% attenuation after 10 h operation) make this material a state-of-the-art catalyst for electrochemical H 2 O 2 production. The outstanding performance arises from a combination of several aspects, such as porous structure-facilitation of mass transport, large surface area, and proper distribution of oxygen-containing functional groups modification on the surface. Furthermore, the proposed oxygen reduction reaction (ORR) mechanism on HMCS surface reveals that −OH functional groups help promote the first electron transfer process while other oxygen modification facilitate the second electron transfer.
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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".