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Record W2151333774 · doi:10.1109/tmech.2011.2159732

A 1-D Capacitive Micromachined Ultrasonic Transducer Imaging Array Fabricated With a Silicon-Nitride-Based Fusion Process

2011· article· en· W2151333774 on OpenAlexaff
Andrew S. Logan, Lawrence L. P. Wong, John T. W. Yeow

Bibliographic record

VenueIEEE/ASME Transactions on Mechatronics · 2011
Typearticle
Languageen
FieldEngineering
TopicUltrasonics and Acoustic Wave Propagation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCapacitive micromachined ultrasonic transducersMaterials scienceTransducerSilicon nitrideUltrasonic sensorFabricationCapacitive sensingSurface micromachiningMicroelectromechanical systemsOptoelectronicsPhased arrayCenter frequencyPiezoelectricitySiliconAcousticsOpticsElectrical engineeringComposite materialEngineering

Abstract

fetched live from OpenAlex

Capacitive micromachined ultrasonic transducers (CMUTs) are an alternative to the conventional method of generating ultrasound that increases bandwidths, simplifies fabrication, and facilitates the integration with necessary electronics. We report the fabrication, characterization, and initial-phased array imaging results of a 64-element array CMUT fabricated using a fusion bonding process where both the membrane and insulation layers are user deposited silicon nitride. Individual cells have a diameter of 25 μm and a membrane thickness of 500 nm. The center frequency in immersion is 6.6 MHz with a -6 dB fractional bandwidth of 123%. A 90° phased array sector scan is made of a four-wire target using a 32-element subset of the array. Pressures in excess of 2 MPa are measured. An axial resolution of 130 μm and a lateral resolution of 0.03 rad are obtained from a wire target 15 mm away from the transducer.

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: none
Teacher disagreement score0.703
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
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.193
Teacher spread0.183 · 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

Citations25
Published2011
Admission routes1
Has abstractyes

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