Single-Beam Acoustic Tweezer Prepared by Lead-Free KNN-Based Textured Ceramics
Bibliographic record
Abstract
Acoustic tweezers for microparticle non-contact manipulation have attracted attention in the biomedical engineering field. The key components of acoustic tweezers are piezoelectric materials, which convert electrical energy to mechanical energy. The most widely used piezoelectric materials are lead-based materials. Because of the requirement of environmental protection, lead-free piezoelectric materials have been widely researched in past years. In our previous work, textured lead-free (K, Na)NbO3 (KNN)-based piezoelectric ceramics with high piezoelectric performance were prepared. In addition, the acoustic impedance of the KNN-based ceramics is lower than that of lead-based materials. The low acoustic impedance could improve the transmission efficiency of the mechanical energy between acoustic tweezers and water. In this work, acoustic tweezers were prepared to fill the gap between lead-free piezoelectric materials research and applications. The tweezers achieved 13 MHz center frequency and 89% −6 dB bandwidth. The −6 dB lateral and axial resolution of the tweezers were 195 μm and 114 μm, respectively. Furthermore, the map of acoustic pressure measurement and acoustic radiation calculation for the tweezers supported the trapping behavior for 100 μm diameter polystyrene microspheres. Moreover, the trapping and manipulation of the microspheres was achieved. These results suggest that the KNN-based acoustic tweezers have a great potential for further applications.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".