Fabrication of a high-frequency phased array with sparse Vernier array element spacing for grating lobe suppression
Bibliographic record
Abstract
This work presents the design, fabrication and characterization of a 50 MHz Vernier array. The Vernier array was based on a 128 element transducer with half-wavelength pitch, where every third element was used for transmit, every forth element was used for receive and unused elements were left inactive. The array was a forward looking kerfless design based on a PZT-5H substrate with an element-to-element pitch of 19 microns, and the probe was packaged in a 2.5 mm by 3.1 mm endoscopic form factor. The array was fabricated with a single P(VDF-TrFE)-copolymer matching layer and a polymethylpentene (TPX) lens for passive elevation focusing to a depth of 6 mm. To generate beam profiles, images and videos, the transducer was connected to an in-house developed 64-channel, high-frequency phased array beamformer. Near real-time radiation patterns and images were collected at a frame rate of 10 Hz. The performance of the Vernier array was directly compared to that of a previously developed phased array transducer with approximately one-wavelength pitch. Both transducers possessed similar two-way beamformed pulse bandwidths of 60%. At large steering angles the Vernier array suppressed the grating lobe levels 15 dB over the previously developed phased array, however, as a result of the sparseness of the Vernier array, the measured two-way sensitivity was 18.2 dB lower than the phased array with the fully active aperture. Experimental measurements were in good agreement with the theoretical predictions of 20dB grating lobe suppression and 22dB lower sensitivity than the phased array. Comparison images were generated of wire phantoms in a water bath as well as wire phantoms situated in a tissue phantom in order to assess the tradeoff between lower grating lobe levels at the expense of lower sensitivity.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".