Fiber-Optic Viscometer Based on Damping Rate of Off-Core Microsphere Cantilever
Bibliographic record
Abstract
Viscosity governs fluid motion and has broad applications in scientific research, biomedicine, and industry. This paper proposed and demonstrated a compact all-fiber viscometer based on an off-core optical fiber cantilever integrated with a microsphere to form interferometer for high sensitivity viscosity sensing via vibrational damping analysis. The cantilever's free end is immersed in the test liquid and driven by a mechanical actuator, while the viscosity-dependent damping is extracted from the optical response of an interferometric cavity formed between the off-core fiber and the microsphere. The phase delay between the excitation and vibration signals serves as the primary sensing parameter for viscosity measurement in real-time. The all-fiber architecture ensures a miniaturized footprint and requires only a small sample volume (∼50 μL). Experimental validation demonstrates a strong correlation between the measured phase delay and viscosities ranging from 1.144 mPa·s to 8.029 mPa·s. The proposed viscometer offers a robust and practical solution for real-time viscosity monitoring in biomedical diagnostics, industrial process control, and microfluidic systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".