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Record W2041071720 · doi:10.1109/mwsym.2014.6848555

Realization of a new class of monolithic RF MEMS waveguide switches for millimeter-wave applications

2014· article· en· W2041071720 on OpenAlexafffund
Nahid Vahabisani, Mojgan Daneshmand

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCMC Microsystems
KeywordsMicroelectromechanical systemsActuatorWaveguideExtremely high frequencyCantileverFabricationMaterials scienceSIGNAL (programming language)Radio frequencyCoplanar waveguideOptoelectronicsMillimeterRealization (probability)Electrical engineeringElectronic engineeringOpticsEngineeringComputer sciencePhysicsTelecommunicationsMicrowave

Abstract

fetched live from OpenAlex

A new category of monolithic RF MEMS waveguide switches for the millimeter-wave application is presented in this paper. The switches are based on monolithic integration of highly deflected RF MEMS actuators (cantilever beams) inside the waveguide channel. The waveguide structure and the MEMS components are simultaneously fabricated using a monolithic 8-mask fabrication process. It is shown that the actuators in the UP state virtually generate a conductive wall that can be used to reroute the signal and design various waveguide switch structures. When the actuators are pulled down, they coincide with the inner wall of the waveguide and are completely removed from the signal path. To prove the concept, a monolithic waveguide “Short” using the curled-up MEMS actuators is fabricated and the results are compared to a solid wall for the frequency band of 60 GHz-75 GHz. The idea is then generalized to show the feasibility of multiport structures such as C-type switch.

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.245
Teacher spread0.219 · 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

Citations4
Published2014
Admission routes2
Has abstractyes

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Same topicAdvanced MEMS and NEMS TechnologiesFrench-language works237,207