Ultrahigh refractive index sensitivity via lattice-induced meta-dipole modes in flat metallic nanoantenna arrays
Bibliographic record
Abstract
We investigate control of plasmonic-photonic coupling in flat metallic nanoantenna arrays. We demonstrate that when the nanoantennas are packed together along their short axis (transverse lattice constant) and the incident light polarization is along their long axis, they can support lattice-induced plasmonic resonance coupled to a super-photonic mode that densely fills the superstrate volume. Our results show that at a certain wavelength, this resonance joins the plasmonic tip modes of the nanoantennas, forming meta-dipole modes. These modes have field profiles similar to those of the natural plasmonic dipole modes of individual nanoantennas, but they occur at much shorter wavelengths and offer a very high bulk refractive index sensitivity (925 ± 12 nm/RIU). We show that with an increase in the transverse lattice constant, such a sensitivity decreases as the meta-dipole modes disappear. Under this condition, the refractive index sensitivity supported by natural modes of the nanoantennas increases, as the plasmonic edge mode suppression caused by charge rearrangement decreases.
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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".