Effect of Bulk Acoustic Wave in Piezo Driven Nanomechanical Motion
Bibliographic record
Abstract
Piezo actuation of mechanical resonators is widely adapted because of its simplicity and versatility. Piezo-driven atomic force microscopy cantilevers in air or liquid have a substantial drawback in that they produce spurious resonances that conceal the cantilever resonance peak. Bulk acoustic wave propagation via the piezo-shaker and device substrate causes these undesired peaks. Such restrictions of piezo actuation are rarely reported in nanomechanical resonant sensing. Because most NEMS (nanoelectromechanical systems) experiments are carried out at low pressure to achieve a higher quality factor ) and hence increased sensitivity, spurious resonances are frequently overlooked due to their insignificance. However, this piezo-driven issue may affect NEMS responses at higher pressures (lower Q) and must be addressed carefully. This study reveals spurious resonances from high vacuum to the atmosphere while investigating piezo-driven nanoscale doubly clamped beam responses. At all pressures, spurious peaks with a characteristic frequency span independent of air damping exist, and at higher pressures, they squeeze the mechanical peak. Such squeezing provides a larger derived from the driven phase responses by order of magnitude than the mechanical computed from the measured thermal noise spectra. Interestingly, the characteristic frequency span, not air damping, is revealed to dominate driven .
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".