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Record W1528784595 · doi:10.1063/1.1502206

Effects of silver doping on ferroelectric SrBi2Ta2O9

2002· article· en· W1528784595 on OpenAlexaff
Bryan C. Sih, A. Jung, Z.-G. Ye

Bibliographic record

VenueJournal of Applied Physics · 2002
Typearticle
Languageen
FieldMaterials Science
TopicFerroelectric and Piezoelectric Materials
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMaterials scienceFerroelectricityDielectricDopingBismuthCurie temperatureDielectric spectroscopyCeramicPerovskite (structure)Analytical Chemistry (journal)CrystallographyCondensed matter physicsPhysical chemistryElectrodeComposite materialChemistryOptoelectronicsMetallurgyElectrochemistry

Abstract

fetched live from OpenAlex

Silver-doped SrBi2Ta2O9 (Ag:SBT) ceramics were synthesized by solid state reactions. The reaction mechanism has been deduced based on the crystal defect chemistry. It involves the diffusion of Ag+ and O2− ions into the (Bi2O2)2+ layers between the perovskite-like units to recover the bismuth and oxygen vacancies, respectively, which were inherently present in SBT ceramics due to the volatilization of Bi2O3 at high temperatures. The Ag:SBT samples have been characterized by a variety of techniques: x-ray diffraction, dielectric and ferroelectric measurements, and impedance spectroscopy. Ag doping is found to significantly affect the structural and physical properties of SBT, including lattice parameters, Curie temperature, bulk conductivity, activation energy, and ferroelectricity. These effects have been interpreted based on the model of the recovery of oxygen and bismuth vacancies upon Ag doping. The effects of Ag diffusion should be taken into account when using Ag as electrode materials for the characterization of the electric properties of SBT and related materials.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.012
GPT teacher head0.216
Teacher spread0.203 · 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.

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

Citations19
Published2002
Admission routes1
Has abstractyes

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