Real-Time Experiments on the Spontaneous Restructuring of Self-Assemblies of Naked Ag Nanoparticle Anions: How Close Can Two Nanoparticles Get?
Bibliographic record
Abstract
Naked (i.e., ligand-free) Ag nanoparticle anions, 6.5 ± 0.5 nm in diameter, have been synthesized in the gas phase and deposited as monodispersed monolayers. By tuning the average interparticle separation in these assemblies, the monodispersed structure was found to be stable only when the average edge-to-edge distance between nanoparticle anions was greater than 3.5 ± 0.5 nm. This separation was found to mark a fundamental limit where the integrity of the monodispersed structure is compromised due to a spontaneous coalescence process. Conductivity measurements taken in real time, as the interparticle separation was steadily decreased, clearly show a dramatic transition at an interparticle separation of 3.5 ± 0.5 nm that manifests itself as a near complete change in conduction mechanism from tunneling to percolation. The observation of a fundamental 3.5 ± 0.5 nm limit, below which monodispersions of nanoparticles are not stable, has significant consequences in the field of nanofabrication. These results suggest that it is not possible to place two small naked metal nanoparticles any closer than this. To provide some context and understanding of the forces controlling this fundamental limit, a diatomic model is helpful. Much of the chemistry and physics of the nanoparticle anion assemblies can be understood in terms of the classical forces acting between two particles (i.e., a pseudodiatomic). In this context, the coalescence limit is the result of a curve-crossing process that occurs at a 3.5 nm edge-to-edge distance.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".