Multiple Moving Membrane Capacitive Micromachined Ultrasonic Transducer With Dynamic Control Provision of Effective Cavity Height
Bibliographic record
Abstract
A novel biasing scheme having the potential to dynamically control the effective cavity heights of two fabricated, multiple moving membrane capacitive micromachined ultrasonic transducers ($\text{M}^{{3}}$-CMUTs) has been developed. With this unique approach, it may be possible to avoid design tradeoff requirements of the ultrasonic transducers that affect both receiving and transmitting operating modes. Each of these$\text{M}^{{3}}$-CMUTs has two vibrating membranes suspended over a fixed bottom electrode. The two air-coupled$\text{M}^{{3}}$-CMUT devices with the resonant frequencies of 1 MHz single cell and 1.5 MHz array device were fabricated. A finite element analysis (FEA) was carried out to investigate the effect of an additional middle membrane on the effective cavity height and device performance. Experimental validation was then completed with the transducers operating under both positive and negative biasing conditions of middle membrane while keeping the top membrane at selected positive biasing voltages to realize a dynamically controlled range of effective cavity heights. The new biasing scheme may facilitate dynamic tunning of resonant frequencies of transmitter and receiver transducers through the variation of effective cavity height for improved performance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".