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Record W2060396779 · doi:10.1088/0960-1317/21/3/035009

Dynamic actuation methods for capacitive MEMS shunt switches

2011· article· en· W2060396779 on OpenAlexaff
Mahmoud Khater, Krishna Vummidi, Eihab Abdel‐Rahman, Ali H. Nayfeh, Sanjay Raman

Bibliographic record

VenueJournal of Micromechanics and Microengineering · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCapacitive sensingVoltageShunt (medical)Microelectromechanical systemsSwitching timeReduction (mathematics)Fast switchingControl theory (sociology)EngineeringMaterials scienceElectronic engineeringElectrical engineeringComputer scienceOptoelectronicsMathematics

Abstract

fetched live from OpenAlex

We develop dynamic actuation methods for capacitive MEMS shunt switches. We show that the dynamic actuation voltage is significantly less than the static actuation voltage and demonstrate 60% reduction in the actuation voltage. We also show that this reduction in the actuation voltage depends on the specific dynamic switching technique adopted. For a given operating condition, the minimum realizable switching time is that obtained using static switching. However, we developed a dynamic switching method that yields comparable switching time to that minimum. We also found that squeeze-film damping is the dominant damping mechanism for a shunt switch with a relatively slender bridge (aspect ratio of 11:1).

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 score0.003
Threshold uncertainty score0.011

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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.019
GPT teacher head0.261
Teacher spread0.242 · 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

Citations24
Published2011
Admission routes1
Has abstractyes

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