Experimental analysis of a low controlling voltage tri-electrode MEMS electrostatic actuator for array applications
Bibliographic record
Abstract
Abstract A tri-electrode electrostatic actuator with one moving microelectromechanical systems (MEMS) electrode and two stationary electrodes (tri-electrode actuator topology) is experimentally tested in this article. The stationary controlling (intermediate) electrode is perforated and below the moving MEMS electrode, and the common electrode is further below. Numerical simulations were performed to discover the most optimum tri-electrode design parameters to enable the best performance improvement compared to a conventional two electrode electrostatic actuator. A silicon-based moving MEMS electrode was designed with a relatively linear spring constant, and the controlling intermediate and primary stationary electrodes were fabricated on either side of a quartz substrate instead of free space to simplify their fabrication. The measurement results showed that the tri-electrode topology can control the displacement of the MEMS with a lower controlling voltage and with extended controllable range before pull-in instability, compared to the conventional actuator. Simulations and measurements showed the controlling voltage was decreased by 2.6 times smaller than the conventional actuator topology using a bipolar driven intermediate electrode, and the controllable deflection range before pull-in was elevated by 33%. This tri-electrode topology offers benefits for applications in need of arrays of electrostatic actuators such as deformable mirrors.
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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 | 0.001 | 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".