Characterization of micro-scale gas leaks using an optomechanical ultrasound sensor
Bibliographic record
Abstract
We used an optomechanical microphone to measure the acoustic signals emitted by compressed-air jets emanating from apertures as small as ∼5 μm. In keeping with the predictions of aeroacoustic theory, spectra extending into the high-frequency (MHz) ultrasound region were observed. Most of this acoustic energy lies well above the range of a conventional ultrasonic microphone. Conversely, the broadband response of the optomechanical sensor offers the potential to localize and quantify leaks based on a more complete knowledge of the acoustic spectrum. We show that the minimum detectable flow rate, set by the onset of turbulence, scales with the hole size and was as low as ∼10-3 Pa·m3·s-1 for the smallest holes studied here. The results demonstrate that a sufficiently broadband and sensitive microphone might enhance the utility of "acoustic sniffer" tools for quantitative gas leak detection.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".