Sensitivity enhanced and polarization independent evanescent field planar ridge waveguide Bragg grating refractometer
Bibliographic record
Abstract
Optical Bragg grating sensors based on side polished or etched waveguides have been demonstrated for the measurement of refractive index [1, 2, 3, 4]. However, these devices typically exhibit polarization dependent behavior for index values around 1.3. In this report, a ridge waveguide Bragg grating (WBG) sensor with high sensitivity, for refractive index measurement in liquids is presented. The device is based on a small core size silica open top cladding ridge waveguide and polarization independent Bragg gratings (PIBG) written and optimized using UV light [5,6,7]. The WBG is surrounded by a liquid analyte and is accessed via evanescent field interaction of the guided waveguide mode with the liquid layer. In the theoretical analysis, enhancement of sensitivity by optimizing waveguide structures is proposed. In the experiment, Bragg grating is induced in the open top cladding ridge waveguide using a phase mask and excimer laser radiation at 193 nm. A series of refractive index matching liquids are used to test the device. Results indicate the sensitivity is as high as 50 pm of wavelength shift for a change of the index 3×10-4. This technology can offer many advantages over previously proposed waveguide sensors, including enhanced sensitivity, and dynamic measurement range, better polarization stability, and a simpler fabrication processes.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".