High-performance transition metal–doped Pt <sub>3</sub> Ni octahedra for oxygen reduction reaction
Bibliographic record
Abstract
Bimetallic platinum-nickel (Pt-Ni) nanostructures represent an emerging class of electrocatalysts for oxygen reduction reaction (ORR) in fuel cells, but practical applications have been limited by catalytic activity and durability. We surface-doped Pt3Ni octahedra supported on carbon with transition metals, termed M-Pt3Ni/C, where M is vanadium, chromium, manganese, iron, cobalt, molybdenum (Mo), tungsten, or rhenium. The Mo-Pt3Ni/C showed the best ORR performance, with a specific activity of 10.3 mA/cm(2) and mass activity of 6.98 A/mg(Pt), which are 81- and 73-fold enhancements compared with the commercial Pt/C catalyst (0.127 mA/cm(2) and 0.096 A/mg(Pt)). Theoretical calculations suggest that Mo prefers subsurface positions near the particle edges in vacuum and surface vertex/edge sites in oxidizing conditions, where it enhances both the performance and the stability of the Pt3Ni 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) | 0.001 | 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".