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Record W4249839932 · doi:10.32920/ryerson.14651850

Design of MEMS magnetic actuator for MEMS fourier transform infrared spectrometer

2021· preprint· en· W4249839932 on OpenAlexaff
Farzana Husain

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsToronto Metropolitan UniversityCMC Microsystems (Canada)
Fundersnot available
KeywordsActuatorMicroelectromechanical systemsTranslation (biology)Rotary actuatorRotation (mathematics)Displacement (psychology)AcousticsMaterials scienceMechanical engineeringOpticsComputer scienceControl theory (sociology)EngineeringElectrical engineeringPhysicsOptoelectronicsArtificial intelligence

Abstract

fetched live from OpenAlex

The objective of this thesis is to design MEMS magnetic actuator for MEMS FTIRS. The actuator consists of moving part and fixed part. The moving part uses rotation-to-translation motion conversion mechanism to achieve large translation, which includes four trapezoidal plates, central ring, anchoring springs and connection springs. The fixed part of the actuator consists of four solenoids. The actuator can be integrated with separately fabricated micromirror plate to achieve high surface quality translation micromirror for FTIRS. The actuator is capable of eliminating titling by controlling the four solenoids individually. The MEMS magnetic actuator has been designed and simulated to be able to output a static displacement of 370micrometers. The stress has been analyzed for the moving part of the actuator. The actuator fixed part has been designed. Dynamic analysis has been conducted for the moving part of the actuator. The moving part of the actuator has been fabricated using MetalMUMPs.

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 score0.002
Threshold uncertainty score0.007

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.022
GPT teacher head0.235
Teacher spread0.214 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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