Analysis, Simulation and Testing of a Micromirror with Rotational Serpentine Springs
Bibliographic record
Abstract
In this paper, a 2-DOF model for electrostatically actuated torsional micromirrors with relatively soft stiff rotational serpentine springs is presented. The analytical stiffness formulae for this rotational serpentine spring are also presented. FEA simulations for static performance have been verified by the experimental values. Such validation was implemented through fabrication of the micromirror on a SOI wafer by MicraGEM micromachining process, PSD sensor based test set-up for static properties, and the corresponding tests. Due to the soft stiffness of rotational serpentine springs designed, the fabricated torsional micromirror could be rotated to some angle under low applied bias. The simulated pull-in voltage 17.2 V is close to the actual value but much smaller than those of previously reported large size torsional micromirrors. The deviation of the simulated static displacements from experimental results could be mainly due to the tolerance of fabrication, the slender beam and linear structural assumptions. However, with relatively lower applied voltages of actuation, these torsional micromirrors that use the rotational serpentine springs can be integrated on the same microchip with CMOS circuits, showing their promising potential for industrial applications.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".