Size Effects of Platinum Colloid Particles on the Structure and CO Oxidation Properties of Supported Pt/Fe<sub>2</sub>O<sub>3</sub> Catalysts
Bibliographic record
Abstract
Three supported Pt/Fe 2 O 3 catalysts were prepared by depositing platinum colloids with discrete particle sizes onto the surface of Fe(OH) 3 powders, which were then calcined at an elevated temperature. Pt nanoparticle colloids with mean diameters of 1.1, 1.9, or 2.7 nm were synthesized in order to investigate the effects of particle size on the structure and CO oxidation properties of these Pt/Fe 2 O 3 catalysts. All Pt/Fe 2 O 3 catalysts demonstrated activity in low-temperature CO oxidation, with the sample containing Pt nanoparticles with a mean diameter of 1.9 nm (designated Pt/Fe 2 O 3 -b) exhibiting relatively higher catalytic activity. Compared with the other two catalysts, Pt/Fe 2 O 3 -b exhibited an increased ability to activate oxygen and maintain the stability of Pt species, correlating with its higher catalytic activity. The results of various characterization techniques revealed that the mean particle size of the Pt nanoparticles could influence the chemical states of Pt species and the strength of metal–support interactions of the Pt/Fe 2 O 3 catalysts. It was observed that the metal–support interactions in Pt/Fe 2 O 3 catalysts were able to adjust the redox properties and the O 2 -activation abilities of the catalysts. Finally, it is proposed that the interacting Pt and Fe species located at the Pt–FeO x interface are the primary active sites for the activation of CO and O 2, respectively.
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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 | 0.001 |
| 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".