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Record W2905650014 · doi:10.3390/instruments3010002

Brazing Strategies for High Temperature Ultrasonic Transducers Based on LiNbO3 Piezoelectric Elements

2018· article· en· W2905650014 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInstruments · 2018
Typearticle
Languageen
FieldEngineering
TopicUltrasonics and Acoustic Wave Propagation
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBrazingMaterials scienceLithium niobatePiezoelectricityUltrasonic sensorTransducerAcousticsPiezoelectric sensorOptoelectronicsComposite material

Abstract

fetched live from OpenAlex

Long-term installation of ultrasonic transducers in high temperature environments allows for continuous monitoring of critical components and processes without the need to halt industrial operations. Transducer designs based on the high-Curie-point piezoelectric material lithium niobate have been shown to both be effective and stable at extreme temperatures for long-term installation. In this study, several brazing techniques are evaluated, all of which aim to provide both mechanical bonding and acoustic coupling directly to a bare lithium niobate piezoelectric element. Two brazing materials—a novel silver-copper braze applied in a reactive air environment and an aluminum-based braze applied in a vacuum environment—are found to be suitable for ultrasound transmission at elevated temperatures. Reliable wide-bandwidth and low-noise ultrasound transmission is achieved between room temperature and 800 °C.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.577
Threshold uncertainty score0.855

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.217
Teacher spread0.210 · 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