Fano Resonance Hybrid Waveguide-Coupled Plasmonic Sensor Using Transparent Conductive Oxide in the Near-Infrared Range
Bibliographic record
Abstract
We proposed an ultra-sensitive refractive index sensor by using indium-doped cadmium oxide as a plasmonic material operating in near-infrared based on Fano resonance. The proposed sensor has a hybrid multilayer waveguide structure that supports both a long-range surface plasmon polariton (LRSPP) mode and a dielectric waveguide (DWG) mode. The design strategy of the structure parameters of the inner layers is elaborated in detail through the numerical analysis of the two modes. By suitably tailoring the thickness of the coupling layer, a strong mode coupling between the two modes could be achieved, leading to a sharp asymmetric Fano resonance. With the designed optimal physical parameters, our proposed sensor could achieve a maximum intensity sensitivity of 19,909 RIU−1, a 193-fold enhancement than that of a conventional long-range SPR (LRSPR) based scheme. The proposed design can be a promising platform for biochemical sensing in the near-infrared region.
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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) | 0.001 | 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 | 0.001 |
| 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".