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Record W2082869854 · doi:10.1108/03056121011087186

RF‐MEMS switches on a printed circuit board platform

2010· article· en· W2082869854 on OpenAlexaff
Keryn Lian, Manes Eliacin, Robert Lempkowski, Marc Chason, Matthew J. O’Keefe, James L. Drewniak

Bibliographic record

VenueCircuit World · 2010
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMicroelectromechanical systemsPrinted circuit boardRadio frequencyInterconnectionElectronic engineeringFabricationElectrical engineeringEngineeringMaterials scienceTelecommunicationsNanotechnology

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to present a new class of printed circuit board (PCB)‐based, radio frequency micro‐electro‐mechanical systems (RF‐MEMS) switches and to describe the packaging method and evaluate performance. Design/methodology/approach Traditional PCB materials and processes were combined with photolithographic high‐density interconnect (HDI) and MEMS to form 3D high‐performance RF switches. Findings A new type of MEMS RF switch has been developed on a PCB platform. Using processes analogous to those used for silicon MEMS, PCB, and HDI technologies were utilized to fabricate these 3D structures. The PCB‐based microstructures are “mil‐scale” rather than the “micro‐scale” of silicon MEMs. A co‐fabrication packaging method for the MEMS RF switch was also developed. The PCB‐based MEMS switches have demonstrated excellent RF performance and “hot‐switching” RF power‐handling capability. PCB‐based MEMS RF switches have the advantages of low cost and amenability to scale‐up for a high degree of integration. Research limitations/implications Further development on photo imageable dielectric materials will enable this technology to improve yield and processability. Originality/value The paper describes the development of PCB‐based MEMS RF switches. These elements will enable new applications and enhance the functionality of PCBs. They are also more amenable to system integration compared with silicon MEMS.

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 categoriesMeta-epidemiology (narrow)
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 score0.270
Threshold uncertainty score1.000

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 integrity0.0000.001
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 head0.024
GPT teacher head0.227
Teacher spread0.204 · 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.

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

Citations1
Published2010
Admission routes1
Has abstractyes

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