Femtosecond laser inscribed high temperature fiber Bragg grating sensors
Bibliographic record
Abstract
Silica-based fiber Bragg gratings (FBG) sensors are versatile devices that are typically fabricated using UV laser exposure. Their applicability is restricted to temperatures < 600°C because of the erasure of the UV generated grating structure at higher temperature. FBGs made with femtosecond IR lasers and phase masks in standard single mode fiber can have high long-term thermal stability at 1000 °C. Above 1000 °C however, the silica undergoes structural transformations that limit the functionality of the fiber. The most successful optical fiber used for high temperature sensor applications is the single crystal sapphire fiber, which has a glass transition temperature of 2030 °C. Here we present our work on retro-reflective FBGs fabricated in single mode silica and multimode sapphire fiber. For sapphire fiber Bragg gratings (SFBG), no degradation of the grating strength at high temperature was observed when tested up to 1500 °C. The SFBGs have discrete resonant wavelengths that could be used potentially as distributed optical sensor arrays up to 2000 °C. To produce a single mode response, the multimode SFBGs were probed using tapered single mode fibers producing single and low order mode reflection/transmission responses. The taper coupling improved the spectral resolution of the sapphire FBG as compared to its multimode responses.
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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 | 0.001 |
| 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".