Piezoelectric creep in LiNbO3, PMN-PT and PZT-5A at low temperatures
Bibliographic record
Abstract
Creep and hysteresis were directly measured for shear displacements of three widely used piezoelectric materials: 41° X-cut lithium niobate (LiNbO3), single crystal lead magnesium niobate-lead titanate (PMN-PT), and ceramic lead zirconium titanate (PZT-5A). Measurements were made at temperatures between 0.1 K and 310 K and at voltages up to 150 V. No creep or hysteresis was seen for the single domain lithium niobate transducer. PMN-PT exhibited large creep and hysteresis with a strong temperature dependence even at temperatures as low as 10 K. The temperature dependence was complicated and included an unusual region of negative creep around 250 K. The ceramic PZT-5A had significant creep near room temperature, which disappeared below about 35 K. The widths of the measured hysteresis loops mirrored the magnitudes of the creep that produces the hysteresis. We discuss the behavior of the three materials in terms of intrinsic and extrinsic mechanisms of piezoelectricity. Our results provide guidance in selecting materials for piezoelectric actuators for precise positioning applications like scanning tunneling microscopy. Although it is seldom used in actuator stacks, lithium niobate is the best choice for many cryogenic 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".