Dispersion and Stability Mechanism of Pt Nanoparticles on Transition-Metal Oxides
Bibliographic record
Abstract
Abstract The heterogeneous catalysts of Pt/transition-metal oxides are typically synthesized through calcination at 500℃, and Pt nanoparticles are uniformly and highly dispersed when hydrogen peroxide (H2O2) is applied before calcination. The influence of H2O2 on the dispersion and the stability of Pt nanoparticles on titania-incorporated fumed silica (Pt/Ti-FS) supports was examined using x-ray absorption fine structure (XAFS) measurements at the Pt L3- and Ti K-edges as well as density functional theory (DFT) calculations. The local structural and chemical properties around Pt and Ti atoms of Pt/Ti-FS with and without H2O2 treatment were monitored using in-situ XAFS during heating from room temperature to 500℃. XAFS revealed that the Pt nanoparticles of H2O2-Pt/Ti-FS are highly stable and that the Ti atoms of H2O2-Pt/Ti-FS support form into a distorted-anatase TiO2. DFT calculations showed that Pt atoms bond more stably to oxidized-TiO2 surfaces than they do to bare- and reduced-TiO2 surfaces. XAFS measurements and DFT calculations clarified that the presence of extra oxygen atoms due to the H2O2 treatment plays a critical role in the strong bonding of Pt atoms to TiO2 surfaces.
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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".