Strong Polarized Enhanced Raman Scattering via Optical Tunneling through Random Parallel Nanostructures in Au Thin Films
Bibliographic record
Abstract
Random parallel nanostructures (ridges and channels) were created by scratching gold thin films deposited on glass slides. Atomic force microscope (AFM) images showed that the width of the substructures within the scratches were of the order of a few hundred nanometers. These nanometric gold features can then support localized surface plasmon resonances in the direction perpendicular to the propagation of the scratches. This surface plasmon excitation led to a remarkable dependence of the intensity of the surface-enhanced resonance Raman scattering (SERRS) on the polarization direction of the incident light relative to the orientation of the scratch. The maximum SERRS intensities for oxazine 720 (a common laser dye) adsorbed on these nanostructures were obtained when the polarization of the light field was perpendicular to the direction of the substructures. The SERRS intensities followed a squared dependence on the polarization direction of the incident field.
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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) | 0.000 | 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 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".