Ultrasensitive plasmonic sensing in air using optical fibre spectral combs
Bibliographic record
Abstract
Abstract Surface plasmon polaritons (SPP) can be excited on metal-coated optical fibres, enabling the accurate monitoring of refractive index changes. Configurations reported so far mainly operate in liquids but not in air because of a mismatch between permittivities of guided light modes and the surrounding medium. Here we demonstrate a plasmonic optical fibre platform that overcomes this limitation. The underpinning of our work is a grating architecture—a gold-coated highly tilted Bragg grating—that excites a spectral comb of narrowband-cladding modes with effective indices near 1.0 and below. Using conventional spectral interrogation, we measure shifts of the SPP-matched resonances in response to static atmospheric pressure changes. A dynamic experiment conducted using a laser lined-up with an SPP-matched resonance demonstrates the ability to detect an acoustic wave with a resolution of 10−8 refractive index unit (RIU). We believe that this configuration opens research directions for highly sensitive plasmonic sensing in gas.
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 | 0.000 |
| 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".