Self-locking vertical operation single crystal silicon micromirrors using silicon-on-insulator technology
Bibliographic record
Abstract
Micro-opto-electro-mechanical systems (MOEMS) have been developed for a broad range of applications including: optical switching, optical data storage, imaging, bar code reading and beam steering for free-space optical communications. One vital component of these systems, the out-of-plane micromirror, is required for any redirection of light. The challenge for the design of these mirrors is to create an optically smooth and flat surface for producing minimum distortion reflections. If a micromirror scatters a significant amount of energy, then a higher power light source will be required reducing the efficiency and increasing the cost of the system. Typically, micromirrors fabricated through polycrystalline processes offer structural designs of multiple layers allowing for hinges to be created for out-of-plane operation. However, polycrystalline mirrors do not offer the flatness and smoothness that is achievable with single crystalline materials. Micromirrors made from single crystalline processes provide superior optical properties, but the complexity for designing out-of-plane structures is increased due to the single layer structural design requirement. To utilize the superior optical properties of single crystalline materials, we have designed single crystal silicon micromirrors using the micralyne generalized MEMS (MicraGEM) process with a novel latching system that allows the micromirrors to remain locked in a vertical position during operation.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".