Design and Fabrication of a Novel MEMS Capacitive Transducer With Multiple Moving Membrane, ${\rm M}^{3}$-CMUT
Bibliographic record
Abstract
A novel capacitive micromachined ultrasonic transducer is designed and fabricated. This transducer employs a stack of two deflectable membranes suspended over a fixed bottom electrode. In this configuration, the two moving membranes deflect simultaneously in response to a bias voltage, which results in a smaller effective cavity height compared with the conventional capacitive transducers. Electromechanical and acoustic analyses are conducted to investigate the transducer properties. A set of seven transducers with radii ranging from 30 to 55 μm were fabricated utilizing a sacrificial microelectromechanical system fabrication technology. Electrical measurements were performed and were compared with results from physical deflection measurements utilizing an optical vibrometer system. The results have been compared with analytical models as well as characterization of a set of five conventional, single membrane, transducers fabricated with the same technology. These experiments indicate a good agreement between the model and measured data. A larger membrane deflection and smaller cavity height are achieved from the double membrane devices. Therefore, this type of device may enhance the transducer acoustic power generation capability as well as increasing its sensitivity both of which result from the reduction in the transducer effective cavity height.
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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 | 0.001 | 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".