An Endoscopic Tri-Frequency (1 MHz, 5 MHz, 30 MHz) Transducer for Combined Imaging and Therapy
Bibliographic record
Abstract
A new endoscope design was built and tested that incorporates a 1 MHz pump transducer for increased peak pressure capability, and a 30 MHz imaging array in front designed to have minimal attenuation to the 5 MHz therapy transducer. Our novel design combines three different frequency transducers stacked together without affecting the device cross section. The thicknesses of the piezo and coupling layers were optimized using a COMSOL FEM model and maximize the peak pressure of the therapeutic pulse. This was tested in two designs. The first used an off-the-shelf piezo stack actuator for the pump transducer. In the second design, this is replaced by a PMN-PT Electrostrictor (PMN-38) transducer; E-Solder 3022 conductive epoxy was used for the coupling layer to provide an attenuating backing to the imaging array. The imaging transducer was a PZT5H laser cut 64- element array. A silicone Fresnel lens was cast on a PZT5A composite and characterized, and a concept for adapting it to this design was proposed. The therapy transducer with backing layers produced a pressure equivalent to an air-backed composite. Simultaneously pulsing the pump transducer increased the overall peak negative pressure. Adding the imaging transducer with coupling layer reduced the therapy signal by 3.7 dB in the first design, and 5.7 dB in the second design due to increased loss from the conductive epoxy coupling layer.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".