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Record W2545547325 · doi:10.1109/icisip.2005.1619439

Analysis, Simulation and Testing of a Micromirror with Rotational Serpentine Springs

2005· article· en· W2545547325 on OpenAlexafffund
Jianliang You, Muthukumaran Packirisamy, Ion Stiharu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSurface micromachiningFabricationStiffnessWaferVoltageMaterials scienceMicroelectromechanical systemsRotational speedFinite element methodSilicon on insulatorOpticsTorsion springSpring (device)Structural engineeringAcousticsMechanical engineeringEngineeringOptoelectronicsPhysicsSiliconElectrical engineeringComposite material

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.164
Threshold uncertainty score0.150

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.237
Teacher spread0.225 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations5
Published2005
Admission routes2
Has abstractyes

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