Bismuth Aluminate BiAlO<sub>3</sub>: A New Lead-free High-T<sub>C</sub> Piezo-/ferroelectric
Bibliographic record
Abstract
Ferroelectric materials have applications in non-volatile random access memory devices and micro electromechanical systems. For such applications, the materials must remain ferroelectric up to high temperatures. The best materials that currently exist for these applications are lead-containing compounds like Pb(Zr1-xTix)O3. Owing to the toxicity of lead, there is a demand for lead-free high-temperature ferroelectrics. Bismuth aluminate has been predicted to be one such material [1]. In this work, BiA1O3is synthesized using a high-pressure high-temperature technique at 6 GPa and 1000degC. The diffraction experiments show that BiAlO3crystallizes in a rhombohedral unit cell that is elongated along the c-axis (R3c; Z = 6; a = 5.37546(5) A and c = 13.3933(1) A). The characterization of the dielectric, ferroelectric, and piezoelectric properties of the ceramic BiAlO3demonstrate that it is indeed a lead-free ferroelectric with a Curie temperature Tc > 520degC, a piezoelectric coefficient d33 = 28 pC/N and a room-temperature remnant polarization Pr= 9.5 muC/cm2. Princreases with temperature, reaching 26.7 muC/cm2at 225degC. The dielectric, ferroelectric and piezoelectric properties of BiAlO3are comparable to those of BiFeO3(BFO) and SrBi2Ta2O9(SBT), making it a promising new high-Tc lead-free piezo-and ferroelectric for memory and transducer applications.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".