Enhanced CO-Tolerance of Pt–Ru–Mo Hydrogen Oxidation Catalysts
Bibliographic record
Abstract
A ternary composition spread, , ; , was prepared through sputter deposition onto a nano-structured thin film support. The film was found to be reasonably stable when exposed to acid at , although there was evidence for loss of some Mo, presumably through a corrosion mechanism. The catalytic activity towards hydrogen oxidation of this composition range was measured simultaneously in a 64-electrode proton exchange membrane fuel cell with emphasis on performance in the presence of CO. The addition of either Mo or Ru to Pt led to a reduction in hydrogen oxidation overpotential for a simulated reformate gas stream containing up to CO. The best performance under CO-containing reformate was found for compositions containing both Ru and Mo, e.g., . The performance observed was significantly better than that measured on compositions containing Pt and Ru only. The use of air bleed was found to be most beneficial for compositions containing predominantly Pt and Ru.
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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".