Optical spectral sweep comb liquid flow rate sensor
Bibliographic record
Abstract
In microfluidic chip applications, the flow rate plays an important role. Here we propose a simple liquid flow rate sensor by using a tilted fiber Bragg grating (TFBG) as the sensing element. As the water flows in the vicinity of the TFBG along the fiber axis direction, the TFBG's spectrum changes due to its contact with water. By comparing the time-swept spectra of the TFBG in water to that of the TFBG with water flowing over it, a spectral sweep comb was formed, and the flow rate can be detected by selecting a suitable sweeping frequency. The proposed sensor has a high Q-value of over 17,000 for the lower rate and a large detectable range from 0.0058 mm/s to 3.2 mm/s. And the calculated corresponding lower detectable flow rate of 0.03 nL/s is 3 orders magnitude better than that of the current fiber flowmeter. Meanwhile, the proposed sensor has the temperature self-compensation function for the variation of the external temperature. We believe that this simple configuration will open a research direction of the TFBG-deriving theory and configuration for lower flow rate measurements for microfluidic chip applications.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".