Performance of an electrostatic actuated micromirror in a vacuum and non-vacuum packaging
Bibliographic record
Abstract
Experimental results of micromirrors sealed in vacuum and non-vacuum environments are presented. The micromirror is 1.0 mm in diameter and is supported by four electrostatic repulsive actuators. The micromirror exhibits linear out-of-plane motion and rotational motion in two axes. The measured data shows that translational motion is 71 μm and 76 μm at 200 V for vacuumed and non-vacuumed micromirrors, respectively. The maximum optical rotational displacements for the vacuum and non-vacuum packaged micromirrors are 1.0° and 1.1°, respectively at 160 V. Packaging the micromirror in a vacuum decreases the squeeze film damping in the system. The settling time for the vacuum packaged micromirrors is 75 ms with an average overshoot of 116%. The settling times for the non-vacuumed micromirror are 2.75 ms with 5% overshoot for downward motion and 3.32 ms with 48% overshoot for upward motion. The estimated resonant frequency of the vacuum packaged micromirror is 2900 Hz, whereas the resonant frequency for the non-vacuumed micromirror is 1400 Hz. The static and dynamic results for the micromirror in reduced pressures determined that effects approaching the breakdown voltage become evident, resulting in lower displacements, and squeeze film damping effects are mitigated, leading to more consistent performance characteristics such as settling time and percent overshoot.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".