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Record W2065276450 · doi:10.1063/1.4904514

Dielectric relaxation analysis of Pb(Zr0.54,Ti0.46)O3 thin films: Electric field dependence

2014· article· en· W2065276450 on OpenAlexaff
Freddy Ponchel, Nossikpendou Sama, Denis Rémiens, T. Lasri

Bibliographic record

VenueJournal of Applied Physics · 2014
Typearticle
Languageen
FieldMaterials Science
TopicFerroelectric and Piezoelectric Materials
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsMaterials scienceElectric fieldCrystalliteRelaxation (psychology)PermittivityMicrostructureDielectricThin filmDiffractionLayer (electronics)Condensed matter physicsComposite materialAnalytical Chemistry (journal)OptoelectronicsOpticsNanotechnologyChemistryMetallurgy

Abstract

fetched live from OpenAlex

350 nm-thick Perovskite PbZr0.54Ti0.46O3 (PZT) thin films were deposited on Al2O3 substrates by sputtering with and without an additional 10-nm-thick TiOx buffer layer. X-ray diffraction patterns showed that in presence of TiOx buffer layer, PZT film was highly oriented along the (111) direction film, whereas the unbuffered, counterpart was polycrystalline. A full wave electromagnetic analysis using a vector finite element method was performed to determine the tunability and the complex permittivity up to 67 GHz. A comparison between the electromagnetic analysis and Cole-Cole relaxation model was proposed. Through an original study of the relaxation time as a function of the electric field, values, such as 2 ps and 0.6 ps, were estimated for EDC = 0 kV/cm and 235 kV/cm, respectively, and in both cases (111)-PZT and polycrystalline-PZT. The distribution of relaxation times is found to be larger for (111)-PZT film, which is probably related to the film microstructure.

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)0.000
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
Metaresearch0.0000.000
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)0.0010.000

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 head0.009
GPT teacher head0.232
Teacher spread0.222 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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