Dual-Frequency Square PMUT With Enhanced Transmission Efficiency at Fundamental and Higher Modes
Bibliographic record
Abstract
This work presents the design, fabrication, and characterization of a dual-frequency square piezoelectric micromachined ultrasonic transducer (PMUT) featuring a novel dual top electrode architecture that, for the first time, combines a circular inner and square outer ring electrode, enabling enhanced mode-selective excitation. The electrode topology is strategically aligned with the spatial strain distributions of both the fundamental (1.7 MHz) and higher order (6.4 MHz) flexural modes, enabling efficient and selective excitation of each mode within a single PMUT structure. Unlike conventional single-electrode PMUTs, which are typically limited to strong performance at the fundamental resonance, the proposed design achieves enhanced transmission efficiency at both operating modes. Finite element simulations and experimental validation demonstrate significant improvements in electromechanical coupling, with a twofold increase at the higher order mode, as well as enhancements in transmit sensitivity by 36% at the fundamental mode and by a factor of five at the higher order mode, compared to a conventional single top electrode PMUT. Underwater acoustic characterization further confirms dual-mode operation of the proposed SqC PMUT, demonstrating a 68% increase in acoustic pressure at the higher order mode compared to the reference single-electrode PMUT. This dual-mode enhancement allows the higher order resonance to serve as an additional operating frequency, facilitating dual-frequency operation without increasing device complexity or fabrication steps. The proposed PMUT architecture offers a compact and high-performance solution for ultrasonic imaging and sensing applications.
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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 | 0.000 |
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".