Design and fabrication of giant micromirrors using electroplating-based technology
Bibliographic record
Abstract
Giant micromirrors with large scanning deflection and good flatness are required for many space and terrestrial applications. A novel approach to manufacturing this category of micromirrors is proposed. The approach combines selective electroplating and flip-chip based technologies. It allows for large air gaps, flat and smooth active micromirror surfaces and permits independent fabrication of the micromirrors and control electronics, avoiding temperature and sacrificial layer incompatibilities between them. In this work, electrostatically actuated piston and torsion micromirrors were designed and simulated. The simulated structures were designed to allow large deflection, i.e. piston displacement larger than 10 μm and torsional deflection up to 35°. To achieve large micromirror deflections, up to seventy micron-thick resists were used as a micromold for nickel and solder electroplating. Smooth micromirror surfaces (roughness lower than 5 nm rms) and large radius of curvature (R as large as 23 cm for a typical 1000×1000 μm 2 micromirror fabricated without address circuits) were achieved. A detailed fabrication process is presented. First piston mirror prototypes were fabricated and a preliminary evaluation of static deflection of a piston mirror is presented.
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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) | 0.000 | 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".