Fabrication of elliptical-silica microfiber for ultrasound detection
Bibliographic record
Abstract
Elliptical shape microfiber enables many higher order modes compared with a circular microfiber. The small difference in the optical path length among many modes enabled multi-resonance peaks with high contrast in Mach-Zehnder (MZI) interferometers, which allows a large dynamic range and minimum detection sensitivity for broadband ultrasound sensing. In this paper, we present the design and fabrication of an ultra-compact elliptical-silica microfiber utilizing off-axis flame-drawing for ultrasound detection. The narrow transmission peak showed high contrast for ultrasensitive ultrasound wave detection. With a major-axis diameter of 6.25 µm, the elliptical-silica microfiber sensor exhibits a broadband ultrasound frequency response spanning from 20 kHz to 38.5 MHz. Furthermore, it achieves a signal-to-noise ratio (SNR) of up to 80 dB at 1 MHz, which is the resonance frequency of the microfiber and the linear response under driving voltages of 3-10 V for the PZT ultrasound generator. This low-cost microfiber sensor offers exceptional sensitivity across a broad ultrasonic bandwidth response, making it an ideal choice for nondestructive testing (NDT) and medical imaging applications. Its compact size and immunity to electric and magnetic fields further enhance its utility in various environments.
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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) | 0.001 | 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".