Carbon Nanomaterials Doped with Sulfur for ORR in Alkaline Media
Bibliographic record
Abstract
Fuell cells are recognized as an attractive alternative for clean energy generation. However, their commercialization has been limited by the high cost of their components. Platinum supported on carbon (Pt/C) has been considered a conventional electrocatalyst due to their high electroactivity. However, recent researches works have shown that the free platinum electrocatalyst such as nanostructured carbons doped with heteroatoms (e. g. B, P, N and S) have similar electrocatalytic activities that Pt/C for oxygen reduction reaction (ORR) in alkaline media. This work present the behavior for ORR in alkaline media of nanomaterials based on carbon doped with sulfur. The materials were prepared using a modified chemical vapor deposition method. Toluene and thiophene was used as carbon and sulfur source, respectively, while ferrocene was used as growing agent. Nanocarbons morphology and textural properties are investigated by high resolution transmission and scanning microscopy, X Ray diffraction and Raman spectroscopy. Electrochemical analysis was evaluated using cyclic voltammetry (CV) and rotating disk electrode (RDE) in 0.1 M KOH media.
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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".