Ultra-fine piezoelectric composites for high frequency ultrasonic transducers
Bibliographic record
Abstract
This paper presents a new technique called interdigital phase bonding (IPhB) that has been developed to make 2-2 PZT composites of ultra-fine pitch for use as transducers and arrays operating at frequencies >30 MHz. By using the IPhB method, a composite structure with a pitch that is less than the dicing saw blade thickness can be created. The flexibility of the approach is demonstrated by presenting composites of two different dimensions. Samples have been fabricated using a conventional dicing saw (Disco DAD-2H/6TM) and a 50 /spl mu/m thick blade. The most ultra-fine composite consists of 15 /spl mu/m wide PZT bars (CTS 3203HD) embedded in an epoxy matrix (EPOTEK 301) with a pitch of 25 /spl mu/m resulting in a volume ratio of 61 percent. Such a sample is suitable for the fabrication of ultrasonic transducers and arrays with central frequencies of up to 85 MHz., however single element transducers working at central frequencies of 50-60 MHz are shown. Electrical impedance and acoustic pulse echo measurements have been taken to characterize the transducer performance. Results show that the longitudinal electromechanical coupling coefficient is greater than 0.6, and that there are no noticeable lateral resonances in the frequency range of 55-150 MHz. This agrees with theoretical predictions based on velocity dispersion curves calculated from the general 2-dimensional Lamb modes.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".