Fabrication of Platinum Nanoparticles with Different Morphologies by Thermal Dewetting in the Presence of Residual Oxygen and Their Optical Properties
Bibliographic record
Abstract
Solid-state thermal dewetting of Pt thin films on SiO 2 /Si substrates in the ambient of constant flow of H 2 or Ar gas was explored for the fabrication of Pt nanoparticles (NPs). Full dewetting of Pt films of various thicknesses in the range of 1.5–10.8 nm was achieved with no evidence of substrate perturbation arising from Pt–Si interdiffusion, even at the highest temperature tested at 950 °C. The capability of thermal dewetting to produce Pt NPs with different sizes and shapes was demonstrated by controlling the dewetting parameters such as temperature and initial film thickness. Pt NPs with different shapes, from elongated hexagonal to near-spherical, were observed to form. The selected area electron diffraction analysis of these NPs has shown that they are single-crystalline NPs composed of many high-index facets. The X-ray diffraction and energy-dispersive X-ray spectroscopic characterization verified the high purity of produced Pt NPs without the presence of Pt–Si compounds. The examination of the dewetting ambient conditions reveals that the presence of residual O 2 in the thermal dewetting process under the flow of H 2 or Ar helps promote the full dewetting of Pt thin films to form isolated Pt NPs on SiO 2 /Si substrates and prevent the substrate perturbation at high temperatures. In addition, it facilitates the formation of Pt NPs with high-index faceted crystal planes, which are useful in many catalysis applications. The produced Pt NPs showed a size-independent absorption peak at 223–224 nm, originating from the interband transitions in the less free-electron Pt metal. The clean interband transition peak observed for the Pt NPs in the ultraviolet–visible (UV–vis) spectral range of 200–800 nm should provide some advantages for their potential application in photocatalysis targeting at oxidative catalytic pathways.
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How this classification was reachedexpand
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) | 0.000 | 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 teacher head, 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".