Fabrication of one-dimensional linear diagnostic and therapeutic high intensity focused ultrasound (HIFU) phased-arrays using lateral-mode coupling method
Bibliographic record
Abstract
Diagnostic and high intensity focused ultrasound (HIFU) phased-arrays provide many advantages over single element transducers, including dynamic focal beam steering capability. These arrays should be fabricated with element-to element pitch smaller than half the wavelength at the resonance frequency to avoid unwanted secondary foci due to grating lobes and side lobes. However, smaller pitch increases the electrical impedance of the array as the resonance frequency increases. The most common way to compensate the impedance increase is to employ electrical matching circuits between an array and RF driving system. However, it is not ideal if the number of array elements increases due to high fabrication cost and effort. In this paper we introduced the lateral mode coupling method to reduce electrical impedance in the fabrication of phased array. Using the lateral mode coupling method, we fabricated and tested one dimensional, linear diagnostic (750 kHz) and HIFU (1.4 MHz) phased-arrays. The averaged electrical impedances of each channel were measured to be 62.3 ± 5.2 Ω for the diagnostic array and 104.5 ± 8.9 Ω at zero phase for the HIFU array, respectively. The averaged maximum surface acoustic intensity of the HIFU array elements was 34 W/cm2prior to failure.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".