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Record W2053584156 · doi:10.1088/0022-3727/35/13/316

Nonlinear strain and DC bias induced piezoelectric behaviour of electrostrictive lead magnesium niobate-lead titanate ceramics under high electric fields

2002· article· en· W2053584156 on OpenAlexaff
A. J. Masys, Gang Yang, Bhaskar Mukherjee

Bibliographic record

VenueJournal of Physics D Applied Physics · 2002
Typearticle
Languageen
FieldMaterials Science
TopicFerroelectric and Piezoelectric Materials
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsElectrostrictionPiezoelectricityMaterials scienceElectric fieldCeramicLead titanatePiezoelectric coefficientDC biasPolarization (electrochemistry)TitanateAnalytical Chemistry (journal)Composite materialCondensed matter physicsFerroelectricityDielectricVoltagePhysicsOptoelectronicsChemistry

Abstract

fetched live from OpenAlex

Laser Doppler interferometry has been used to determine the strain and piezoelectric response of Pb(Mg1/3Nb2/3)O3-PbTiO3 (PMN-PT) electrostrictive ceramics as a function of electric fields up to 4 MV m-1, frequencies between 0.1 Hz and 2.5 kHz and DC bias fields up to 3 MV m-1. The strain and polarization of PMN-15 with a composition of 0.9PMN-0.1PT and PMN-38 with a composition of 0.85PMN-0.15PT both produced by TRS ceramics, have been measured at room temperature. The strain and polarization responses of PMN-15 ceramics under an electric field up to 4 MV m-1 have been fitted to a polynomial model. The results suggest that a quadratic dependence of strain on polarization is not valid for large electric fields and that higher-order terms must be included. Our measurements showed that the effective piezoelectric coefficient, d33, of PMN-15 ceramics had a maximum value of 800 pm V-1 at a bias field of 0.67 MV m-1 and had little frequency dependence in the frequency range from 1 Hz up to 2.5 kHz. PMN-38 ceramic showed a maximum d33 of 1200 pm V-1 at a bias field of 0.43 MV m-1 and the d33 of this material showed a clear frequency dependence from 1 Hz up to 2.5 kHz.

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 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: Empirical
Teacher disagreement score0.042
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.029
GPT teacher head0.239
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

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

Citations28
Published2002
Admission routes1
Has abstractyes

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