Theoretical modeling and experiments on the piezoelectric coefficient in cellular polymer films
Bibliographic record
Abstract
Abstract This article presents an analytical model allowing the determination of the, d 33 , piezoelectric coefficient in cellular polymer films. The cellular film is identified to an equivalent effective layered structure made of alternating gas and solid layers that are electrically charged at their interfaces. The model expresses the d 33 piezoelectric coefficient as a function of porosity, film thickness, free‐stress surface charge density, and the film modulus, which depends on frequency. The temperature is indirectly taken into account as it is involved in the parameters appearing in the final equation of the model. The obtained results showed that the piezoelectric activity of charged cellular polymer films decreases with the film thickness and increases with the film expansion and the surface charge density. The variation with the percentage of porosity shows a nonlinear trend, with an increase in the d 33 piezoelectric coefficient with the void fraction, and then a decrease when such a percentage exceeds a thickness‐dependent critical value. Such quantitative description of the piezoelectric activity can help the design of cellular films with enhanced piezoelectric performances. The model predictions were also compared with some experimental results obtained on cellular piezoelectric films made of polypropylene filled with 10% of calcium carbonate microparticles. POLYM. ENG. SCI., 2013. © 2012 Society of Plastics Engineers
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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 | 0.000 |
| 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".