High frequency piezo-composite transducer with hexagonal pillars
Bibliographic record
Abstract
Developing a high-frequency piezo-composite material is a challenge due to the extremely small pillar dimensions. The high frequency composites made by conventional dicing saw techniques will most likely have a low ceramic volume fraction and a large pillar width to height aspect ratio, because of the limitation of making narrow kerfs and small pitches. Large aspect ratio pillars in a low ceramic volume ratio composite will cause a dramatically decrease of both electromechanical coupling and effective velocity. In this work, we investigated a new composite geometry with hexagonal pillars. The performances of the composites have been simulated by using a finite element analysis tool (PZFlex). The simulation results show that the composites with hexagonal pillars provide a significant improvement of performance over the composites with other pillar shapes, at a low volume ratio and high aspect ratio. A hexagonal pillar composite, with a volume ratio of 0.32 and an aspect ratio of 0.9, can maintain an effective electromechanical coupling coefficient of 0.6 with a drop in effective velocity of 20 percent, while secondary pulses, due to lateral resonances, are about 20 dB below the main pulse. To verify the simulation findings, hexagonal pillar composites with low ceramic volume ratio of 0.32 have been fabricated by the dice-and-fill technique. The composites were finished at different thicknesses to vary the aspect ratios. Each was mounted on an SMA connector. The electrical impedances of the transducers were measured to compare with the simulations. The electromechanical coupling coefficients and effective velocities were calculated from the resonance and anti-resonance frequencies. The measured electromechanical coupling shows an improvement of more than 50% over previous geometry composites. The experimental results agree well with the simulations. It suggests that this hexagonal geometry is a promising structure for fabrication of high frequency composite transducers and arrays.
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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 | 0.000 | 0.000 |
| 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".