Adsorbate−Induced Diffusion of Ag and Au Atoms Out of the Cores of Ag@Au, Au@Ag, and Ag@AgI Core−Shell Nanoparticles
Bibliographic record
Abstract
Au@Ag and Ag@Au core−shell nanoparticles were synthesized using sequential laser ablation of metal targets in water. The resulting core−shell particles were then exposed to iodine or 1,6−hexanedithiol. For the Ag@Au + I 2 → Au@AgI and Au@Ag + dithiol → Ag@Au−dithiol reactions, inversion of the core−shell structures resulted. These findings demonstrate that adsorbates can influence the core atoms through an intervening shell, and it is possible to use core−shell systems as vehicles for delivering reactivity on demand. Changing the shell material affords an opportunity to vary core susceptibility. Au@AgI nanoparticles, for example, did not react with 1,6−hexanedithiol. These results are most consistent with a charge−transfer-induced diffusion mechanism, analogous to the Cabrera−Mott model used for oxidation reactions of surfaces. The rate of uptake of iodine by Ag nanoparticles, measured with a quartz crystal microbalance, displayed kinetics that could be modeled using the same charge−transfer model.
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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".