Fabrication and performance of a miniaturized 64-element high-frequency endoscopic phased array
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Bibliographic record
Abstract
We have developed a 40-MHz, 64-element phased-array transducer packaged in a 2.5 x 3.1 mm endoscopic form factor. The array is a forward-looking semi-kerfed design based on a 0.68Pb(Mg(1/3)Nb(2/3))O(3) - 0.32PbTiO3 (PMN-32%PT) single-crystal wafer with an element-to-element pitch of 38 µm. To achieve a miniaturized form factor, a novel technique of wire bonding the array elements to a polyimide flexible circuit board oriented parallel to the forward looking ultrasound beam and perpendicular to the array was developed. A technique of partially dicing into the back of the array was also implemented to improve the directivity of the array elements. The array was fabricated with a single-layer P(VDF-TrFE)-copolymer matching layer and a polymethylpentene (TPX) lens for passive elevation focusing to a depth of 7 mm. The two-way -6-dB pulse bandwidth was measured to be 55% and the average electromechanical coupling (k(eff)) for the individual elements was measured to be 0.62. The one-way -6-dB directivities from several array elements were measured to be ±20°, which was shown to be an improvement over an identical kerfless array. The -3-dB elevation focus resulting from the TPX lens was measured to be 152 µm at the focal depth, and the focused lateral resolution was measured to be 80 µm at a steering angle of 0°. To generate beam profiles and images, the probe was connected to a commercial ultrasound imaging platform which was reprogrammed to allow for phased array transmit beamforming and receive data collection. The collected RF data were then processed offline using a numerical computing script to generate sector images. The radiation pattern for the beamformed transmit pulse was collected along with images of wire phantoms in water and tissue-equivalent medium with a dynamic range of 60 dB. Finally, ex vivo tissue images were generated of porcine brain tissue.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it