Catalytic CO Oxidation over Pt Nanoparticles Prepared from the Polyol Reduction Method Supported on Yttria-Stabilized Zirconia
Bibliographic record
Abstract
Pt nanoparticles were synthesized using a polyol process with ethylene glycol as a reducing agent. Nanoparticles of three average sizes were synthesized (3.8, 2.8 and 1.7 nm) and were deposited on Yttria-Stabilized Zirconia (YSZ), carbon black and γ-Al2O3 resulting in 1 wt. % of Pt on each support. In addition, the conventional wet impregnation method was used to disperse Pt on YSZ. Pt nanoparticles were characterized using transmission electron microscopy and X-ray diffraction. The catalytic activity of all these catalysts was investigated for carbon monoxide oxidationin the temperature range of 25-250 °C. It has been found that Pt/YSZ catalysts prepared by the polyol process presented the highest catalytic performances is spite of the low specific surface area compared to carbon and γ-Al2O3 supports. These performances can be explained based on metal/support interactions effect generated between Pt and YSZ or self-induced electrochemical promotion.
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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".