Plasmon Enhanced Fluorescence with Aggregated Shell-Isolated Nanoparticles
Bibliographic record
Abstract
Shell-isolated nanoparticles (SHINs) nanostructures provide a versatile substrate where the localized surface plasmon resonances (LSPRs) are well-defined. For SHINEF, the silver (or gold) metal core is protected by the SiO2 coating, which is thicker than the critical distance for minimum quenching by the metal. In the present work, it is shown that an increase in the SHINEF enhancement factor may be achieved by inducing SHIN aggregation with electrolytes in solution. The proof of concept is demonstrated using NaCl as aggregating agent, although other inorganic salts will also aggregate SHIN nanoparticles. As much as a 10-fold enhancement in the SHINEF enhancement factor (EF) may be achieved by tuning the electrolyte concentrations in solution. The SHINEF experiments include the study of the aggregation effect controlling gold SHIN's surface concentration via spraying. Au-SHINs are sprayed onto layer-by-layer (LbL) and Langmuir-Blodgett (LB) films, and samples are fabricated using fluorophores with low and also high quantum yield.
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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) | 0.001 | 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 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".