Catalytic CO Oxidation over Pt Nanoparticles Prepared from the Polyol Reduction Method Supported on Yttria-Stabilized Zirconia
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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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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.002 | 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 it