Polyethylene Glycol-Based New Solution Route to Relaxor Ferroelectric 0.65Pb(Mg<sub>1/3</sub>Nb<sub>2/</sub> <sub>3</sub>)O<sub>3</sub>−0.35PbTiO<sub>3</sub>
Bibliographic record
Abstract
A new soft chemistry route has been developed for the synthesis of relaxor ferroelectric lead magnesium niobate−lead titanate solid solution (0.65PMN−0.35PT). The method uses a poly(ethylene glycol) (PEG) and methanol mixture as solvent. It allows reactions to be performed at room temperature without using an excess amount of the lead starting material to compensate for lead oxide loss during ceramic sintering as is usually the case in conventional synthesis. The effect of using a triol molecule, 1,1,1-tris(hydroxymethyl)ethane (THOME), which serves as a complexing agent in binding together the metal ions in the precursor solution, has also been studied. Pure perovskite phase was obtained in ceramics sintered at a relatively low temperature of 1040 °C as compared to 1250 °C in solid-state reactions. A high dielectric constant (at 1 kHz) of above 5000 is found at room temperature and the value reaches ∼27 000 at the Curie temperature. Ferroelectric hysteresis loops are displayed on a ceramic with an average grain size of 2 μm, giving rise to a remnant polarization ( P r ) of 21 μC/cm 2 and a coercive field ( E c ) of ∼7.5 kV/cm.
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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) | 0.002 | 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".