Tunable broadband plasmonic field enhancement on a graphene surface using a normal-incidence plane wave at mid-infrared frequencies
Bibliographic record
Abstract
We investigate optical field enhancement for a wide mid-infrared range, originating from the excitation of graphene plasmons, by introducing a graded dielectric grating of varying period underneath a graphene monolayer. Excitation of the plasmonic mode can be achieved by illuminating a normal-incidence plane wave on the gratings due to guided-mode resonance. The gratings of varying period enable the excitation of the plasmonic mode with a very high field enhancement factor (to the order of magnitude of 1000) within a wide spectral band, which leads to the frequency-dependent spatially separated localization of the infrared spectrum modes. We also demonstrate that the excitation position of the plasmonic mode can be freely tuned by varying the thickness of the interlayer as well as the chemical potential of the graphene monolayer. This structure enables the design of two-dimensional plasmonic photonic circuits and metamaterials targeted towards numerous potential applications including optoelectronic detectors, light-harvest devices, on-chip optical interconnects, biosensors, and light-matter interactions.
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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".