Hysteresis loops revisited: An efficient method to analyze ferroic materials
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Hysteresis loops characterize a wide variety of behaviors in fields ranging from physics and chemistry to economics and sociology. In particular, they represent the main characteristic of ferroic materials such as ferromagnetic and ferroelectric, which, in recent years, have attracted much interest due to their multifunctional properties. Although measuring such loops may not be experimentally complicated, extracting the intrinsic values of the characteristic parameters of the loop may prove difficult due to the different contributions to the measured hysteresis. In this paper, a simple technique is proposed to analyze hysteresis loops and to extract solely the contribution of the ferromagnetic or ferroelectric material. Such method consists in differentiating the measured loop, deconvoluting the different contributions and selectively integrating only the signals belonging to the ferroic response. A discussion of the limitations of the method is presented. Different measured ferromagnetic and ferroelectric hysteresis loops were also used to validate the technique. Comparison between experimental and reconstructed data demonstrated the precision and reliability of the technique. Moreover, application of such method allowed us to highlight properties of a Bi2FeCrO6 room temperature multiferroic thin film that were not previously observed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it