Effect of Medium for Enhanced Nanosensing: DDA Theory vs Experimental Studies of Ag Nanoparticle Assemblies
Bibliographic record
Abstract
Gas-phase deposition has been used to assemble two-dimensional ensembles of strongly coupled 3.0 ± 0.5 nm diameter naked Ag nanoparticles. The coupling mechanism is found to be complex suggesting dipole−dipole coupling at relatively long distances but wave function overlap at center-to-center distances less than 25 nm. The coupled nanoparticles are found to display enhanced sensitivity to changes in the refractive index of the medium, relative to the isolated particle system, and the experiments confirm theoretical predictions of the enhancement effect. For the Ag nanoparticles considered, the enhancement effect is interesting as the coupling energy between particles is found to be remarkably insensitive to the medium and changing the surrounding material from air to hexane has no noticeable effect on this energy. At the same time, changing the medium from air to hexane always manifests a 0.14 eV shift (as for the individual nanoparticle) independent of interparticle coupling and distance. In noncoupled systems the SPR appears at shorter wavelength where the 0.14 eV energy amounts to a relatively small shift in the peak position wavelength. In coupled systems, however, the SPR is positioned at relatively long wavelengths and 0.14 eV is a large shift in wavelength units. As the enhancement is the wavelength change per refractive index unit, more coupled systems yield higher enhancement. The fact that enhanced sensitivity is observed in two-dimensional assemblies of nanoparticles demonstrates that the effect is not restricted to nanoparticle dimers, specifically, as previously thought. The results suggest that any geometric arrangement of closely spaced nanoparticles that generates strong interparticle coupling interactions can form the basis of SPR-based sensor elements with the benefit of near-field enhanced sensitivity.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".