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Record W4311358043 · doi:10.18280/acsm.460507

The Formation of Doped PZT Solid Solution and Its Structural Characterization

2022· article· en· W4311358043 on OpenAlexvenueno aff
Kribaa Oum keltoum, Louiza Zenkhri, Ahmed Boutarfaia

Bibliographic record

VenueAnnales de Chimie Science des Matériaux · 2022
Typearticle
Languageen
FieldMaterials Science
TopicFerroelectric and Piezoelectric Materials
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceCalcinationCharacterization (materials science)DielectricSinteringCeramicPhase boundaryScanning electron microscopeFerroelectricityDopingFerroelectric ceramicsDiffractionChemical engineeringComposite materialPhase (matter)Analytical Chemistry (journal)NanotechnologyOptoelectronicsOpticsOrganic chemistry

Abstract

fetched live from OpenAlex

The main objective of this work is the synthesis, structural and morphological characterization of ceramics materials. Abbreviated PZT-PYN. Ferroelectric ceramics of general formulation Pb(ZrxTi1-x)O3 are massively used in many fields such as medicine or aeronautics because of their dielectric and electromechanical properties, although the electronic properties of doped PZT are much better compared to undoped PZT. Samples selected for this study were prepared bins solid way. The thermal treatment called calcination was applied to these compositions is carried around: 450℃, 550℃, 650℃, 750℃, and 900℃ for two hours with a Vitesse of 2℃ / min., then sintered at different temperatures: 1100℃, 1150℃, 1180℃, successively to optimize the sintering temperature where the product is better physical quality. Different techniques of characterization were used such as scanning electron microscopy (SEM), x-ray diffraction (XRD) analysis, and Energy-dispersive spectrometric, which showed that the response is optimal for the compositions included in the morphotropic phase boundary, achieves excellent properties.

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 score0.004

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 head0.026
GPT teacher head0.269
Teacher spread0.243 · 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
Published2022
Admission routes1
Has abstractyes

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Same venueAnnales de Chimie Science des MatériauxSame topicFerroelectric and Piezoelectric MaterialsFrench-language works237,207