Hybrid Si-Au plasmonic sensor on the end-facet of a dual-core optical fiber enhanced by hotspots: a theoretical study
Bibliographic record
Abstract
Abstract We propose an efficient hybrid Si-Au sensor on the end-facet of a dual-core single-mode optical fiber. The design incorporates slanted Si grating couplers on the two cores, interconnected by a plasmonic waveguide bearing subwavelength corrugations. The corrugations enhance the surface sensitivity by creating regions of strongly enhanced fields - plasmonic hotspots. Unlike conventional Si waveguide grating couplers, we employ slanted slits for unidirectional coupling/decoupling between TM-polarized core light and surface plasmon polaritons. Our structure results in about 3% core-to-core (TM-to-TM) coupling efficiency, while also providing high bulk and surface sensitivities of about 1000 nm RIU −1 and 1.66 nm nm −1 , respectively. The sensor can be interrogated remotely in a transmission arrangement. The sensing medium can be probed by dipping the fiber tip directly therein. Potential applications include remote sensing, brain studies, or in-vivo biosensing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".