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Record W2970618849 · doi:10.1117/12.2538357

Novel method to improve stroke of electrostatically actuated MEMS micromirror

2019· article· en· W2970618849 on OpenAlexaff
Niwit Aryal, Arezoo Emadi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsMicroelectromechanical systemsDigital micromirror deviceFabricationOpticsVoltageStroke (engine)Materials sciencePhysicsOptoelectronicsElectrical engineeringEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

In this paper, an electrostatically actuated MEMS micromirror with enhanced stroke is presented. Unlike traditional MEMS micromirror, the proposed micromirror achieves a large out-of-plane stroke through employing a larger air gap for the micromirror surface to move as well as eliminating the pull-in instability. This novel micromirror has a central reflective micromirror surface of 400 μm by 400 μm, an L-shaped arm that holds the micromirror to the anchor on all side and 3 fixed bottom electrodes beneath each L-shaped arms. The lateral electrostatic forces on the upper L-shaped arm are equal in magnitude but opposite in direction and they counteract to neutralize out each other. The electrostatic force produced on the top L-shaped arm is larger than on the bottom. Therefore, the net electrostatic force points in the upward direction. As a result, the upper plate of the micromirror moves upwards. COMSOL Multiphysics is used to simulate and design the device in order to optimize the stroke of the micromirror for a lower input voltage. The mirror is fabricated using PolyMUMPs fabrication technique where an air cavity of 2.75 μm was achieved by combining the two available sacrificial layers. In this proposed design, an out-of-plane stroke of 2.43 μm is achieved at a 110 V DC bias voltage.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.007
GPT teacher head0.252
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2019
Admission routes1
Has abstractyes

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Same topicAdvanced MEMS and NEMS TechnologiesFrench-language works237,207