Electrically tunable long-period fiber gratings with low-birefringence liquid crystal near the turn-around point
Bibliographic record
Abstract
In this work, an electrically tunable long-period fiber grating (LPFG) coated with liquid crystal layer (LC) is presented. As a LC layer, a prototype low-birefringence 1550A LC mixture was chosen. As a LPFG host, two types of gratings were studied: the LPFGs based on a standard telecommunication fiber, produced by an electric arc technique with a period of 222 μm, and the LPFGs based on a boron co-doped fiber written by a UV technique with a period of 226.8 μm. The relatively short period of these gratings allowed exploiting unique sensing properties of the attenuation bands associated with modes close to the turn-around point. Experiments carried out showed that for the UV-induced LPFG with a LC layer, on the powered state the attenuation band could be offset from the attenuation band measured in the unpowered state by almost 130 nm. When the arc-induced LPFG was coated with the LC, the depth of the attenuation band could be efficiently controlled by applying an external E-field. Additionally, all experimental results obtained in this work were supported by the theoretical analysis based on a model developed with Optigrating v.4.2 software.
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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 | 0.000 |
| 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".