Sensitivity Enhancement in Polymer Coated Long Period Gratings: Towards High Performance Opto-Chemical Sensors
Bibliographic record
Abstract
In this work, long period gratings coated with polymeric high refractive index (HRI) thin layers are proposed as high sensitive opto-chemical sensors. The deposition of thin coatings with high refractive index (compared to the cladding one) induces strong changes in the filed distribution related to the cladding modes. The main consequence is a significant enhancement in the device sensitivity to the refractive index of the eternal medium and of the overlay, respectively. This effect was here efficiently used to realize high performance opto-chemical sensors. In order to investigate the sensor performances different film thicknesses have been tested and the attenuation bands related to different cladding modes have been monitored. The attention was focused on the measurements of the attenuation bands central wavelengths and peak losses changes induced by a controlled modification of the external and overlay refractive indexes. Here, as nanoscale HRI polymeric layer, the nanoporous crystalline 5 form syndiotactic polystyrene (sPS) was selected since it can adsorb reversibly certain analytes, whose size and shape well fit the nanocavities
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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".