New Soft Chemical Routes to Ferroelectric SrBi<sub>2</sub>Ta<sub>2</sub>O<sub>9</sub>
Bibliographic record
Abstract
Ferroelectric ceramics of strontium bismuth tantalate, SrBi 2 Ta 2 O 9 (SBT), have been synthesized in pure layer-structured perovskite phase by two new soft chemical techniques, namely, a sol−gel process and a coprecipitation method. The sol−gel process utilizes ethylene glycol as solvent while the coprecipitation technique makes use of a poly(ethylene glycol) 200 (PEG) and methanol mixture as solvent. The microstructure and properties of the ceramics have been studied and discussed. The sol−gel-derived ceramics sintered at 1200 °C for 8 h show good dielectric and ferroelectric properties with a relative density of 96%, a dielectric constant ε‘ = 227, a remnant polarization P r = 7.6 μC/cm 2 at room temperature, and a maximum dielectric constant ε‘ max = 950 at the Curie temperature T C = 330 °C. In comparison, the SBT ceramics prepared using the coprecipitation method and sintered under the same conditions show a platelike microstructure with preferential grain orientation along the [00 10 ] direction, a relative density of 85%, an ε‘ of 235, a P r of 3.7 μC/cm 2 at room temperature, and an ε‘ max of 850 at T C = 330 °C. The sol−gel-derived ceramics show superior dielectric and ferroelectric properties than the ceramics prepared by the solid-state reactions (ε‘ max ≈ 500 and P r = 4.5 μC/cm 2 ), which can be attributed to a denser and more homogeneous microstructure with a better distribution of grain orientations, thus reducing the preferential grain orientation along the nonpolar c -axis.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".