Optimal Size of Silver Nanoparticles for Surface-Enhanced Raman Spectroscopy
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Bibliographic record
Abstract
The optimal size of spherical silver nanoparticles (AgNPs) for off-resonance surface-enhanced Raman scattering (SERS) was found to be ∼50 nm based on the equivalent Ag content in AgNP colloids. It is understood that the SERS intensity of adsorbates on the surface of metal nanoparticles is dependent on the size and shape of the particles of interest. Herein, we report a seeded growth mechanism for the formation of silver nanoparticles that allows superior control over the size of the resultant nanoparticles with relatively low polydispersity. The high degree of size control allows for a better understanding of the study of the effect of particle size on SERS intensity. The Raman study performed here employed a long-wavelength excitation (785 nm) so as to avoid photochemical degradation of adsorbed species and photochemical transformation under intense excitation. Under these experimental conditions, it was found that the optimal size of AgNPs for providing a maximum SERS intensity of adsorbed R6G is ∼50−60 nm, a result that is expected to extend to other adsorbates as well.
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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) | 0.000 | 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 it