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Record W2101808811 · doi:10.1109/jmems.2008.2008626

Linear Bilayer ALD Coated MEMS Varactor With High Tuning Capacitance Ratio

2008· article· en· W2101808811 on OpenAlexaff
Maher Bakri-Kassem, Raafat R. Mansour

Bibliographic record

VenueJournal of Microelectromechanical Systems · 2008
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsVaricapCapacitanceMaterials scienceMicroelectromechanical systemsOptoelectronicsDeep reactive-ion etchingBilayerDielectricAtomic layer depositionComposite materialEtching (microfabrication)Reactive-ion etchingLayer (electronics)MembraneChemistryElectrode

Abstract

fetched live from OpenAlex

A curl-up-plate microelectromechanical system (MEMS) varactor with an almost linear response and high tuning capacitance ratio is presented. The curl-up in the top plate is realized by the residual stress in the two layers that construct the top plate of the varactor. The linear response is achieved by having the curl-up plate designed to relax on the bottom plate and by having unanchored cantilever beams that prevent the pull-in, while applying a dc bias voltage. The developed varactor exhibits a low parasitic capacitance through etching the lossy substrate underneath the varactor's plates. A thin alumina dielectric layer of 100-nm thickness is deposited using an atomic-layer-deposition technique to provide electrical isolation between the two plates. This MEMS varactor exhibits an almost linear capacitance with a tuning ratio of 5 : 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: 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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.013
GPT teacher head0.198
Teacher spread0.185 · 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

Citations25
Published2008
Admission routes1
Has abstractyes

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