Localized Raman Enhancement from a Double-Hole Nanostructure in a Metal Film
Bibliographic record
Abstract
An isolated double-hole indentation, with concentric rings, in a metal film was used to obtain highly localized surface-enhanced Raman scattering (SERS) from regions much smaller than the optical wavelength. The structure was created by a focused ion beam (FIB) milling partially through the 100 nm thick gold film to a depth of 50 nm. Significant SERS enhancement was observed for both oxazine 720 and rhodamine 6G. The SERS was polarization-dependent because of the biaxial symmetry of the double-hole at the apexes where the indentations overlap; these apexes were responsible for the strong subwavelength focusing. The finite-difference time-domain method was used to calculate the electromagnetic field of the nanostructure, and it showed strong polarization-dependent focusing, in agreement with the experimentally observed SERS enhancement. On the basis of these calculations, it is estimated that the 60% polarization-dependent SERS enhancement is the result of only ∼1300 molecules in the region of the apexes, and it is estimated that the limit of detection is 20 molecules for the best-case configuration. This work is an important step toward single-molecule SERS from tailored nanostructures designed for predictable field enhancement.
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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".