Integrated optical sensing technologies on Si
Bibliographic record
Abstract
An effective approach to achieve efficient phase matching for second order nonlinearities, in multilayer structures will be discussed. It uses dispersion engineering in Bragg reflection waveguides to harness parametric processes in conjunction with concomitant dispersion and birefringence engineering in active devices. This technology enables novel coherent light sources using frequency conversion in a self-pumped chip form factor. These sources can also provide continuous coverage of spectral regions, which are not accessible by other technologies including quantum cascade lasers. This approach has been recently demonstrated in multi-layer Silicon-Oxy-Nitride (SiON) waveguides. Harnessing χ(2) in SiON offers a route for integration of broadband infrared sources using frequency mixing with opto-fluidics. Different approaches for implementing opto-fluidic structures on Si will be discussed, where the root cause of enhancing the retrieved Raman and infrared signals in these structures will be explained. Recent progress in using this approach to study different nanostructures and biological molecules will be presented.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".