The Oxygen Reduction Activity of Pt-Mn/C and Pt-Cu/C Alloys
Bibliographic record
Abstract
Pt-Mn and Pt-Cu alloys with low Pt contents have been previously shown to be highly active for the ethanol oxidization reaction. Here we examined these alloys for their activity towards the oxygen reduction reaction (ORR) in acidic media. The ORR activity of these alloys has also compared to the Pt/C and Pt-Sn/C commercial samples. In addition, the effect of heat treatment and formation of ordered structures on the ORR activity in both Pt-Cu and Pt-Mn systems were investigated. The highest Von-set was recorded for Pt/C. While adding the alloying elements may slightly reduce the ORR activity, these catalysts had no more that 25 at% Pt, which is promising from a cost stand point. In addition, our findings show that the heat treatment and formation of ordered phases had a great impact on the ORR activity of the alloyed samples.
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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 | 0.001 | 0.001 |
| 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".