Synthesis and sintering of SrTiO3–ZnO ceramics: Role of ZnO content on microstructure and dielectric properties
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".