Determination of the nonlinear thermo-optic coefficient of silicon nitride and oxide using an effective index method
Bibliographic record
Abstract
There is little literature characterizing the temperature-dependent thermo-optic coefficient (TOC) for low pressure chemical vapor deposition (LPCVD) silicon nitride or plasma enhanced chemical vapor deposition (PECVD) silicon dioxide at temperatures above 300 K. In this study, we characterize these material TOC’s from approximately 300-460 K, yielding values of (2.51 ± 0.08) · 10 −5 K −1 for silicon nitride and (5.67 ± 0.53) · 10 −6 K −1 for silicon oxide at room temperature (300 K). We use a simplified experimental setup and apply an analytical technique to account for thermal expansion during the extraction process. We also show that the waveguide geometry and method used to determine the resonant wavelength have a substantial impact on the precision of our results, a fact which can be used to improve the precision of numerous ring resonator index sensing experiments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".