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Record W2011679153 · doi:10.1002/pssa.201228678

High‐power MEMS switch enabled by carbon‐nanotube contact and shape‐memory‐alloy actuator

2013· article· en· W2011679153 on OpenAlexafffund
Masoud Dahmardeh, Mohamed Sultan Mohamed Ali, Tanveer Saleh, Tee Min Hian, Mehran Vahdani Moghaddam, Alireza Nojeh, Kenichi Takahata

Bibliographic record

Venuephysica status solidi (a) · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsUniversity of British Columbia
FundersBritish Columbia Knowledge Development FundUniversiti Teknologi MalaysiaNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCMC Microsystems
KeywordsMaterials scienceMicroelectromechanical systemsSMA*ActuatorContact resistanceShape-memory alloyCarbon nanotubeCantileverElectrical contactsOptoelectronicsElectrodeNanotechnologyElectrical engineeringComposite materialComputer scienceEngineering

Abstract

fetched live from OpenAlex

Abstract A forest of vertically aligned carbon nanotubes (CNTs) is integrated as an electrical contact material with a high‐power, normally‐open switch based on micro‐electro‐mechanical systems (MEMS) technology. A shape‐memory‐alloy (SMA) cantilever is thermally actuated to enable switching between the movable CNT forest and the copper electrode formed on the SMA. The out‐of‐plane SMA actuator provides high forces to enable distributed contacts with the CNT forest, achieving low contact resistances and high ON/OFF resistance ratios. The ON state of the switch shows contact resistances as low as 35 Ω with a dependence on the operating current. The device operation is performed with over 5‐W input powers. Long‐term operation with more than 1 × 106switching cycles is demonstrated. The results indicate that a combination of the CNT‐based contact and the SMA actuator may be a promising path to realizing reliable MEMS contact switches for high‐power applications.

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 score0.002
Threshold uncertainty score0.005

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)0.0020.000

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 head0.005
GPT teacher head0.200
Teacher spread0.195 · 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

Citations26
Published2013
Admission routes2
Has abstractyes

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