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Record W2564299260 · doi:10.1117/1.jmm.15.4.045004

Performance enhancement of an air-coupled multiple moving membrane capacitive micromachined ultrasonic transducer using an optimized middle plate configuration

2016· article· en· W2564299260 on OpenAlexaff
Arezoo Emadi, D. A. Buchanan

Bibliographic record

VenueJournal of Micro/Nanolithography MEMS and MOEMS · 2016
Typearticle
Languageen
FieldMedicine
TopicUltrasound Imaging and Elastography
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsTransducerCapacitive micromachined ultrasonic transducersUltrasonic sensorAcousticsCapacitive sensingMaterials scienceDeflection (physics)RADIUSPiezoelectricityOpticsElectrical engineeringEngineeringPhysicsComputer science

Abstract

fetched live from OpenAlex

A multiple moving membrane capacitive micromachined ultrasonic transducer has been developed. This transducer cell structure includes a second flexible plate suspended between the transducer top plate and the fixed bottom electrode. The added plate influences the transducer top plate deflection map and, therefore, the transducer properties. Three series of individual air-coupled, dual deflectable plate transducers and two 1×27 element transducer arrays were fabricated using multiuser microelectromechanical systems (MEMS) processes (MUMPs). Each set of transducers included devices with middle plate radii from 22% to 65% of the corresponding transducer top plate radius. The effect of the transducer middle plate configuration has been investigated. Electrical, optical, and acoustic characterizations were conducted and the results were compared with the simulation findings. It was found that the transducer top plate amplitude of vibration is significantly enhanced with a wider middle deflectable plate. The electrical and optical measurement results are shown to be in good agreement with simulation results. The acoustic measurement results indicated a 37% increase in the amplitude of transmitted signal by the 1-MHz air-couple transducer when its middle plate radius was increased by 35%.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.028
Threshold uncertainty score0.907

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.243
Teacher spread0.226 · 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.

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

Citations1
Published2016
Admission routes1
Has abstractyes

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