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Record W4324045336 · doi:10.53063/synsint.2023.31138

Synthesis and sintering of SrTiO3–ZnO ceramics: Role of ZnO content on microstructure and dielectric properties

2023· article· en· W4324045336 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSynthesis and Sintering · 2023
Typearticle
Languageen
FieldMaterials Science
TopicFerroelectric and Piezoelectric Materials
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceMicrostructureGrain boundaryWurtzite crystal structureSinteringCeramicDielectricTemperature coefficientDielectric spectroscopyGrain sizePerovskite (structure)Composite materialScanning electron microscopeMetallurgyCrystallographyOptoelectronicsZincChemistryElectrodePhysical chemistry

Abstract

fetched live from OpenAlex

The classical system of combining modern perovskite and wurtzite structure semiconductor materials is used to model the internal structure for the applications of functional novel electronic devices. The structure-property relation has a significant impact on the properties of metal oxides-based functional ceramics. The structural and electrical properties of SrTiO3-xZnO (0 ≤x≤ 10 wt%) ceramics produced via solid-state reaction (SSR) were thoroughly examined. X-ray diffraction (XRD) and scanning electron microscopy confirmed the presence of a mono-phase cubic structure with Pm3̅m space group and resulted in increased density respectively. Complex impedance spectroscopy (CIS) was carried out from 300 to 500 °C temperature within the frequency range of 100 Hz to 1 MHz to study the contribution of grain bulk and grain boundary for impedance behavior. Grain boundaries dominated the overall resistance of the samples and the addition of ZnO in SrTiO3 caused an increase in the overall conductivity. Increasing temperature decreases the resistance of both components, and at higher frequencies that confirms the negative temperature coefficient resistance (NTCR) behavior of the samples. Increasing temperature decreases the relaxation of grain bulk and grain boundary thus predicting the hopping conduction mechanism. The results will be helpful to engineer the microstructure of SrTiO3 based on practical applications such as sensors, actuators, and energy devices.

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.

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 score0.033
Threshold uncertainty score0.762

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.211
Teacher spread0.187 · 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