New method to measure domain-wall motion contribution to piezoelectricity: the case of PbZr<sub>0.65</sub>Ti<sub>0.35</sub>O<sub>3</sub> ferroelectric
Bibliographic record
Abstract
A new data analysis routine is introduced to reconstruct the change in lattice parameters in individual ferroelastic domains and the role of domain-wall motion in the piezoelectric effect. Using special electronics for the synchronization of a PILATUS X-ray area detector with a voltage signal generator, the X-ray diffraction intensity distribution was measured around seven split Bragg peaks as a function of external electric field. The new data analysis algorithm allows the calculation of `extrinsic' (related to domain-wall motion) and `intrinsic' (related to the change in lattice parameters) contributions to the electric-field-induced deformation. Compared with previously existing approaches, the new method benefits from the availability of a three-dimensional diffraction intensity distribution, which enables the separation of Bragg peaks diffracted from differently oriented domain sets. The new technique is applied to calculate the extrinsic and intrinsic contributions to the piezoelectricity in a single crystal of the ferroelectric PbZr1−x Ti x O3 (x = 0.35). The root-mean-square value of the piezoelectric coefficient was obtained as 112 pC N−1. The contribution of the domain-wall motion is estimated as 99 pC N−1. The contribution of electric-field-induced changes to the lattice parameters averaged over all the domains is 71 pC N−1. The equivalent value corresponding to the change in lattice parameters in individual domains may reach up to 189 pC N−1.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".