Gratings, photosensitivity, and poling in silica optical waveguides with 157-nm F2 laser radiation
Bibliographic record
Abstract
This thesis reports the first detailed study of Bragg grating writing using 157-nm radiation. The 7.9-eV photon from the 157-nm laser is attractive for inducing strong index changes in germanosilicate and fused silica. Fiber Bragg gratings were written in standard telecom fiber (SMF-28), with index modulation of ∼1.7 × 10−4 in hydrogen-free SMF-28. The gratings have good long-term stability, and sidelobe suppression of 17 dB without apodization. The index modulation improves to ∼6 × 10−4 and Δn∼1.8 × 10−3 in hydrogen-loaded SMF-28. Bragg gratings were fabricated in pure fused silica holey fiber, yielding Δn∼1.4 × 10−3 at 90 kJ/cm2 fluence exposure, and offered good cladding mode suppression. Bragg gratings were also written within silica-on-silicon planar waveguides and buried waveguides in fused silica blocks. The results demonstrate an alternate laser source for writing fiber Bragg gratings not requiring photosensitivity enhancement in germanosilicate waveguides, and is practical for writing gratings in pure fused silica holey fiber.
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 | 0.000 | 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 | 0.000 |
| 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".