Multi Degrees-of-Freedom Hybrid Piezoelectric-Electrostatic MEMS Actuators Integrated With Displacement Sensors
Bibliographic record
Abstract
This work presents novel multi degrees-of-freedom (DOF) actuators based on piezoelectric and electrostatic actuation to generate both in-plane and out-of-plane motions, intended to position a suspended optical waveguide for chip-to-chip alignment in photonic integrated circuits. In this context, the mechanical structures of the actuators with a suspended platform to carry the waveguide, are designed to house aluminum nitride (AlN) as the piezoelectric material for generating out-of-plane motion and a comb-drive, whose fixed and moveable fingers are positioned on the same layer for in-plane motion. Two distinct designs, i.e., a 2-DOF design with motions along the Z-and Y-axes and a 3-DOF design with motions along the Z-, Y-, and X-axes were fabricated and tested. Both designs include capacitive-based displacement sensors to track the motions in Z-and Y-axes. Experimental results at ±60 V indicate that 3 devices of each design give an average displacement of 3.16 ±$0.34~\mu \text{m}$and 0.63 ±$0.04~\mu \text{m}$in the Z-axis for the 2-DOF and 3-DOF designs, respectively. For the Y-axis at 120 V, the average results for the two designs respectively were found to be 3.06 ±$0.17~\mu \text{m}$and 7.38 ±$0.29~\mu \text{m}$, with the ability to extended the later to$10.69~\mu \text{m}$at 140 V. In the X-axis, the 3-DOF design can produce total of 300 nm of displacement at ±100 V. The capacitance measurements were found to correlate well with the tracked displacement. Furthermore, simultaneous activation of more than one actuator could mitigate misalignment and align the platform with a fixed surface. [2023-0148]
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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 | 0.000 |
| 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 | 0.000 |
| 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".