Ternary Heterostructural Pt/CNx/Ni as a Supercatalyst for Oxygen Reduction
Bibliographic record
Abstract
We report here a supercatalyst for oxygen reduction of Pt/CN x /Ni in a unique ternary heterostructure, in which the Pt and the underlying Ni nanoparticles are separated by two to three layers of nitrogen-doped carbon (CN x ), which mediates the transfer of electrons from the inner Ni to the outer Pt and protects the Ni against corrosion at the same time. The well-engineered low-Pt catalyst shows ∼780% enhanced specific mass activity or 490% enhanced specific surface activity compared with a commercial Pt/C catalyst toward oxygen reduction. More importantly, the exceptionally strong tune on the Pt by the unique structure makes the catalyst superbly stable, and its mass activity of 0.72 A/mg Pt at 0.90 V (well above the US Department of Energy's 2020 target of 0.44 A/mg Pt at 0.90 V) after 50,000 cyclic voltammetry cycles under acidic conditions is still better than that of the fresh commercial catalyst.
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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) | 0.000 | 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 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".