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Record W2019886143 · doi:10.1109/tuffc.2006.1665105

Flexible ultrasonic transducers

2006· article· en· W2019886143 on OpenAlexaff
Makiko Kobayashi, Cheng‐Kuei Jen, Daniel Lévesque

Bibliographic record

VenueIEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control · 2006
Typearticle
Languageen
FieldEngineering
TopicUltrasonics and Acoustic Wave Propagation
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMaterials scienceLead zirconate titanateFOIL methodPiezoelectricityUltrasonic sensorComposite materialTransducerElectrodeCeramicPMUTComposite numberAcousticsOptoelectronicsFerroelectricityDielectric

Abstract

fetched live from OpenAlex

Flexible ultrasonic transducers (UTs) consisting of a metal foil, a piezoelectric ceramic film, and a top electrode have been developed. The flexibility is realized owing to the porosity of piezoelectric film and the thinness of metal foil. In this paper, the stainless steel (SS), lead-zirconate-titanate (PZT)/PZT composite and silver paste were chosen as metal foil, piezoelectric film, and top electrode materials, respectively. The SS foil serves as both substrate and bottom electrode. The PZT/PZT piezoelectric composite film is made by the sol-gel spray technique. PZT/PZT films of thicknesses from 40 to 70 microm were fabricated onto SS foils. The capability of these flexible sensors operated in the pulse-echo mode for nondestructive testing on flat and curved surfaces of different materials at room temperature and 160 degrees C has been demonstrated. Numerical simulations of the effects of the metal foil thickness on the ultrasonic performance of flexible UTs also were carried out, and the results are in reasonable agreement with experimental data. In addition, a PZT/PZT flexible transducer showed a signal strength comparable with that obtained by a commercial room temperature broad bandwidth 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 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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.004

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 head0.177
Teacher spread0.173 · 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

Citations86
Published2006
Admission routes1
Has abstractyes

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