Temperature sensors and refractometers using liquid-core waveguide structures monolithically integrated in silica-on-silicon
Bibliographic record
Abstract
Integrated optofluidic devices have many potential applications for on-chip analysis and sensing. The fabrication of single-mode liquid-core waveguides in an integrated format allows the implementation of robust and very sensitive interferometers that combine long optical paths (on the cm scale) with small volumes (less than a nanoliter). We have demonstrated the monolithic integration of microchannels and liquid-core waveguides with planar silica lightwave circuits, which allows a number of refractometer devices to be implemented. Of these, we demonstrate experimentally a monolithic Mach-Zehnder interferometer (MZI) comprising a 20 mm-long liquid-core waveguide. The liquid-core waveguide is quasi single mode at 1550 nm when filled with a liquid of nominal index of ~1.47 (such as toluene or an index matching fluid). In these conditions, the output of the MZI is a pure cosine function, as a function of a linear progression of the refractive index of the liquid medium. Furthermore, the high contrast ratio experimentally observed in the output function allows a precise monitoring of refractive index changes by tracking the position of the transmission minimum in the spectral domain. Refractive index variations can be measured to a precision on the order of 4x10-6. The large differential in thermo-optic coefficients between liquid media and silica allows the structure to function as a temperature sensor with a precision on the order of 10-2 degrees Celsius. The measurement of the spectral fringe spacing of the interferometer response allows absolute-value measurements of temperature and refractive index.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".