Performance and characterization of high frequency linear arrays
Bibliographic record
Abstract
A new approach for fabricating high frequency (> 20 MHz) linear array transducers, based on laser micromachining, has been developed. The capabilities of this approach will be presented using a 30 MHz 64-element, 74-micron pitch and 8- micron kerf design. Each fabricated array has been integrated onto a flex circuit for ease of handling and the flex has been integrated onto a custom circuit board for ease of testing. Examples of measured characteristics of arbitrary array elements are as follows: Electrical impedance, measured in air, of about 120 Ohms with -20 degrees of phase. All transducer elements were acoustically tested using a +/- 30V single cycle drive pulse and a 40µm needle hydrophone. The average center frequency was found to be 28.1 +/- 0.7 MHz with a 1-way bandwidth of 83 +/- 1.2 %. The average peak-to-peak pressure measured at an axial distance of 10 mm from a transducer element was 590 +/- 24 kPa. The combined acoustic and electrical cross talk for nearest neighbours, averaged across the bandwidth of the device was determined to be -40 dB. Simulations of the array characteristics based on finite element analysis performed with PZFlex show good agreement with experimental results. Synthesized images based on the measured performance of the array elements for a given fabricated transducer will also be presented.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".