Interdigital pair bonding for high frequency (20-50 MHz) ultrasonic composite transducers
Bibliographic record
Abstract
Interdigital pair bonding is a novel methodology that enables the fabrication of high frequency piezoelectric composites with high volume fractions of the ceramic phase. This enhancement in ceramic volume fraction significantly reduces the dimensional scale of the epoxy phase and increases the related effective physical parameters of the composite, such as dielectric constant and the longitudinal sound velocity, which are major concerns in the development of high frequency piezoelectric composites. In this paper, a method called interdigital pair bonding (IPB) is used to prepare 1-3 piezoelectric composite with a pitch of 40 microns, a kerf of 4 microns, and a ceramic volume fraction of 81%. The composites prepared in this fashion exhibited a very pure thickness-mode resonance up to a frequency of 50 MHz. Unlike the 2-2 piezoelectric composites with the same ceramic and epoxy scales developed earlier, the anticipated lateral modes between 50 to 100 MHz were not observed in the current 1-3 composites. The mechanisms for the elimination of the lateral modes at high frequency are discussed. The effective electromechanical coupling coefficient of the composite was 0.72 at a frequency of 50 MHz. The composites showed a high longitudinal sound velocity of 4300 m/s and a high clamped dielectric constant of 1111 epsilon 0, which will benefit the development of high frequency ultrasonic transducers and especially high frequency transducer arrays for medical imaging.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".