Element-Specific Analysis of the Growth Mechanism, Local Structure, and Electronic Properties of Pt Clusters Formed on Ag Nanoparticle Surfaces
Bibliographic record
Abstract
Bimetallic nanoparticles (NPs) consisting of small Pt clusters on the surface of larger metal NPs are potential catalysts that combine the advantages of reduced cost, high surface area, and a strong alloying interaction between Pt and the substrate. Herein we report the preparation of a series of small Pt clusters deposited on the surface of Ag NPs with systematically varied compositions (Ag 93 Pt 7, Ag 81 Pt 19, Ag 72 Pt 28, and Ag 65 Pt 35 ) via a galvanic replacement reaction. UV–vis spectroscopy, transmission electron microscopy, and inductively coupled plasma optical emission spectroscopy are used to provide evidence of NPs formation and evaluate their gross structural and compositional characteristics. Extended X-ray absorption fine structure (EXAFS) measurements at the Pt L 3 - and Ag K-edges are then used to elucidate the structural evolution of small surface Pt clusters as the Pt concentration is increased, allowing the formation mechanism of the bimetallic NPs to be deduced. X-ray absorption near-edge structure (XANES) provides further information regarding the electronic properties of the bimetallic NPs from both Ag and Pt perspectives. Finally, the Pt L 3 -edge XANES spectra are used in conjunction with ab initio calculations to verify the accuracy of structural models based on the EXAFS fitting results and to provide insight into the size-dependent nature of the Ag–Pt bonding interaction.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".