Generalized Weiss molecular-field basis for a phenomenological polarization model of lead magnesium niobate
Bibliographic record
Abstract
A simple physical picture, useful for extended applications of a well-demonstrated phenomenological polarization model [J. C. Piquette and S. E. Forsythe, J. Acoust. Soc. Am. 101, 289 (1997)] is presented. The Weiss model of interacting dipoles (orginally suggested by Weiss for magnetic dipoles but applied here to electric dipoles) is generalized for high field levels. The generalization permits the model to describe the polarization measurements well, across a significant temperature range extending well below Tmax, for applied electric field levels as high as 1.35 MV/m. The measurements reported here were acquired from various polycrystalline samples of lead magnesium niobate (PMN) in a solid solution with lead titanate (PT) doped with lanthanum (La), having Tmax values ranging from −11 to +41 °C. Agreement between theory and data is good. (The overall rms error of fit is less than 0.5% in all cases considered.) The new model, when combined with a suitable model of hysteresis, is useful for describing and controlling the behavior of PMN, which is a material that is useful in actuator and transducer applications where a relatively large strain is desired. The theory, in its present form, does not account for relaxor (frequency-dependent) aspects of the material behavior, and is applied here only to data acquired quasistatically. Moreover, only the case in which no external stress is applied to the material is considered.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".