Multimode Magneto-Optical Fiber Based on Borogermanate Glass Containing Tb3+ for Sensing Applications
Bibliographic record
Abstract
A multimode magneto-optical fiber based on Tb3+-containing borogermanate glass was designed, fabricated, and characterized, aiming at potential sensing applications. There are continuing challenges in the development of single-mode (SMF) or multimode (MMF) optical fibers doped with rare-earth (RE) ions and exhibiting high Verdet constants, related to devitrification of the precursor glass. Most RE-doped glass compositions are not suitable as precursors for core-cladding fiber production due to devitrification processes and consequent poor optical quality. Application as Faraday rotators is limited by the intrinsically low Verdet constant of silica (~0.589 rad T−1 m−1 at 1550 nm and 0.876 rad T−1 m−1 at 1310 nm). Borogermanate glasses are good candidates for manufacturing optical fibers due to their excellent potential to solubilize high concentrations of Tb3+ ions as well as satisfactory thermal stability. In this work, a magneto-optical core-cladding borogermanate fiber with a 227 μm diameter was fabricated, with characterization using differential scanning calorimetry (DSC), thermomechanical analysis (TMA), viscosity measurements, M-lines spectroscopy, UV-Vis-NIR absorption spectroscopy, the cut-back technique, and magneto-optical measurements. The measured numerical aperture (NA) was 0.183, with minimum attenuation of 13 dB m−1 at 1270 nm. The Verdet constant (VB) reached −6.74 rad T−1 m−1 at 1330 nm.
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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".