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Record W2126637171 · doi:10.1109/mwsym.2009.5165923

Miniature RF MEMS switch matrices

2009· article· en· W2126637171 on OpenAlexafffund
Arash A. Fomani, Raafat R. Mansour

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicroelectromechanical systemsInsertion lossMaterials scienceResistive touchscreenCrossover switchReturn lossSIGNAL (programming language)Electrical engineeringCantileverFabricationOptoelectronicsElectronic engineeringComputer scienceOptical switchEngineering

Abstract

fetched live from OpenAlex

A novel miniature-size switching unit is reported for application as the building block of multiport switch matrices. The cell consists of 3 cantilever-beam contact type MEMS devices coupled to CPW transmission lines. A major feature of the proposed switch cell is that in each of the operating states there is only one MEMS switch located in the path of signal inducing a similar loss for all switching states. The construction of the entire system is carried out by a six-mask fabrication process. To minimize the unwanted coupling of the RF signal through the bias lines of MEMS devices, high-resistive phosphorous-doped hydrogenated amorphous silicon (n+ a-Si:H) is selected as a material of choice for the dc bias lines. The switching unit has been employed to build a 4times4 switch matrix measuring 1.45 times 1.45 mm2in dimensions. The system presents an excellent RF performance with the worst-case insertion loss, return loss, and isolation of -1.8 dB, -17 dB and 26 dB up to 40 GHz, respectively.

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 score0.005
Threshold uncertainty score0.018

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.006
GPT teacher head0.216
Teacher spread0.211 · 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

Citations17
Published2009
Admission routes2
Has abstractyes

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