Mapping Hot-Spots in Hexagonal Arrays of Metallic Nanotriangles with Azobenzene Polymer Thin Films
Bibliographic record
Abstract
Metallic nanotriangles arranged in a hexagonal lattice are common nanostructures used for surface-enhanced Raman spectroscopy. Such structures, generally made by nanosphere lithography or electron beam lithography (EBL), exhibit localized surface plasmon resonance (LSPR) at the junctions between two facing nanotriangles. Localized and efficient enhancement of the electromagnetic field is expected when light with the matching LSPR frequency is impinging the sample. Herein, first, we report modeling of the electromagnetic field for both gold and silver structures, made by EBL, when irradiated with a linearly polarized beam at 532 nm. The total and the polarized components are calculated using the finite-difference time domain method. Second, using atomic force microscopy and a photosensitive polymer that undergoes surface deformation upon irradiation, we map the LSPR (hot-spots) over these metallic arrays.
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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".