MétaCan
Menu
Back to cohort

Shear piezoelectric coefficients of PZT, LiNbO<sub>3</sub>and PMN-PT at cryogenic temperatures

2014· article· en· W2028351798 on OpenAlexaff
Syed A. Bukhari, Md. Fakhrul Islam, Ariel Haziot, John Beamish

Bibliographic record

VenueJournal of Physics Conference Series · 2014
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Resonator Technologies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMaterials sciencePiezoelectricityLithium niobateNiobiumCeramicTemperature coefficientLead titanateTitanatePiezoelectric coefficientFerroelectricityComposite materialAnalytical Chemistry (journal)MineralogyDielectricOptoelectronicsMetallurgyChemistry

Abstract

fetched live from OpenAlex

Piezoelectric transducers are used to detect stress and to generate nanometer scale displacements but their piezoelectric coefficients decrease with temperature, limiting their performance in cryogenic applications. We have developed a capacitive technique and directly measured the temperature dependence of the shear coefficient d 15 for ceramic lead zirconium titanate (PZT), 41° X-cut lithium niobate (LiNbO 3 ) and single crystal lead magnesium niobium-lead titanate (PMN-PT). In PZT, d 15 decreases nearly linearly with temperature, dropping by factor of about 4 by 1.3 K. LiNbO3 has the smallest room temperature d15, but its value decreased by only 6% at the lowest temperatures. PMN-PT had the largest value of d15 at room temperature (2.9 × 10 −9 m/V, about 45 times larger than for LiNbO 3 ) but it decreased rapidly below 75 K; at 1.3 K, d 15 was only about 8% of its room temperature value.

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)0.001
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.008
GPT teacher head0.196
Teacher spread0.188 · 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

Citations9
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Physics Conference SeriesSame topicAcoustic Wave Resonator TechnologiesFrench-language works237,207