Bibliographic record
Abstract
Conventional out-of-plane micro electrostatic actuators use attractive force and suffer from the "pull-in" effect, which leads to small stroke and low reliability. A rotation micromirror based on the two-layer repulsive force actuator was developed and fabricated. The rotation micromirror has a mirror size of 312 mum x 312 mum and achieves a mechanical rotation of 2.2°. A conventional design of the same size can only rotate 0.2° because of the "pull-in" effect. Two RF MEMS tunable capacitors driven by the two-layer repulsive force actuator were designed, i.e., a stand-alone tunable capacitor and an above-IC tunable capacitor. Model predictions indicate that the stand-alone tunable capacitor can achieve a tuning ratio from 5:1 to 30:1 with a stiffness varying from 5 N/m to 80 N/m, and that the above-IC tunable capacitor can achieve a tuning ratio of 5.8:1 with a stiffness of 2 N/m and a tuning ratio of 4.8:1 with a stiffness of 5 N/m. Conventional MEMS tunable capacitors can only achieve a tuning ratio of 1.5:1 due to the "pull-in" effect. In this thesis, two novel micro electrostatic actuators are developed: a three-layer repulsive force actuator and a two-layer repulsive force actuator. Both actuators are able to overcome the "pull-in" effect associated with conventional electrostatic actuators by generating a repulsive force instead of an attractive force to achieve large stroke and high reliability. Both novel actuators are compatible with surface micromachining technology. A translation micromirror driven by the three-layer repulsive force actuator was designed for application in adaptive optics. The predicted stroke for a mirror size of 400 mum x 400 mupm is 6 mum. A translation micromirror driven by the two-layer repulsive force actuator was also designed and fabricated. The translation micromirror has a mirror size of 250 mum x 250 mum and provides a translation of 1.8 mum, which is three times that of conventional designs. Theoretical models of the novel actuators are developed to be used as design and optimization tools. Prototypes are developed to experimentally verify and assess the performance of the novel actuators.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".