Wide-range strain sensor based on Brillouin frequency and linewidth in an As<sub>2</sub>Se<sub>3</sub>-PMMA hybrid microfiber
Bibliographic record
Abstract
We propose a wide-range strain sensor based on Brillouin frequency and linewidth in a 50 cm-long As2Se3-polymethyl methacrylate (As2Se3-PMMA) hybrid microfiber with a core diameter of 2.5 µm. The distributed information over the hybrid microfiber is measured by a Brillouin optical time-domain analysis (BOTDA) system. The wide dynamic range strain from 0 to 15000 µɛ is enabled by measuring the Brillouin frequency and linewidth due to the low Young’s modulus of As2Se3 core and the high mechanical strength of PMMA cladding. The deformation of the As2Se3-PMMA hybrid microfiber is observed when the strain is greater than 1500 µɛ by measuring the distributed Brillouin frequency and Brillouin linewidth over the 50 cm-long hybrid microfiber. The measured errors based on the Brillouin frequency in the range of 0-1500 µɛ and 1500-15000 µɛ are 42 µɛ and 105 µɛ, respectively. The measured error based on the Brillouin linewidth is 65 µɛ at 0-1500 µɛ and the maximum error is 353 µɛ when the tensile strain is 15000 µɛ. No strain memory effect is observed compared with the polymer optical fiber due to Young’s modulus in As2Se3 is larger than that in polymer. Numerical simulations are developed to accurately predict the strain dependence of Brillouin frequency in the As2Se3-PMMA hybrid microfiber.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".