Optimizing strain response in lead-free (Bi0.5Na0.5)TiO3-BaTiO3-NaNbO3 solid solutions via ferroelectric / (non-)ergodic relaxor phase boundary engineering
Bibliographic record
Abstract
Lead-free bismuth sodium titanate (Bi0.5Na0.5)TiO3 (BNT) and related solid solutions are potential piezoelectric materials for such applications as actuators and transducers if their excellent strain responses and piezoelectric properties can be optimized. In this work, a large strain response of 0.61% is achieved in lead-free (0.94-x%)(Bi0.5Na0.5)TiO3-0.06BaTiO3-x%NaNbO3 (x = 0 –6, BNT-6BT-xNN) ceramics with the composition of x = 3.5 in a pseudo-cubic structure. Coexistence of ferroelectric (FE) and relaxor (RE) domain structures is observed in all the unpoled ceramics and the enhanced strain response is believed to be related to the evolution of the ergodic relaxor (ER) and non-ergodic (NR) states thanks to the substitution of antiferroelectric NN. BNT-6BT-3.5NN is a critical composition near the FE/NR/ER phase boundary close to room temperature (RT) and its high strain response arises from a synergistic combination of a reversible electric-field-induced phase transition and an active domain switching in the mixed NR/ER state. This work provides new insights into the dynamic interplay between mesoscopic domains and macroscopic electrical properties in the BNT-based piezoceramics.
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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".