Thermally stable cellular poly(vinylidene) ferroelectrets: Optimization of CO<sub>2</sub> driven inflation process
Bibliographic record
Abstract
ABSTRACT Electrically charged cellular ferroelectrets can show excellent thermally stable piezoelectric activity and are therefore progressively used in electrochemical transducers. Given that an optimized cellular structure is a key for improving charge density and the associated piezoelectric properties in this material, we investigated the influence of CO2 inflation treatment using various gas diffusion expansion or inflation procedures on the piezoelectric d33 coefficient and thermal stability of cellular poly(vinylidene) ferroelectrets and compare with the results (partially) obtained by N2 inflation as reported in our previous study (Jahan, Mighri, Rodrigue, Ajji, J. Appl. Polym. Sci. 2019, 136, 47540). Samples were prepared using the conventional extrusion–stretching–inflation–corona charging method. Maximum d33 coefficient for CO2‐inflated samples is found to be around 30% higher than that of N2‐inflated samples (327 pC/N compared to 251 pC/N) by stepwise pressure application method. The key parameters addressed in the inflation procedures are the changes in sample thickness, morphology, and the void‐height distribution in both gas treatments. The ferroelectrets show excellent thermal stability for up to 4 days at 90, 110, and 120 °C in both treatments with a slightly improved performance in CO2 gas. The higher activation energy of CO2‐inflated samples (0.52 eV) than the N2‐inflated ones (0.43 eV) further confirms the stability data. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019, 136, 47929.
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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) | 0.000 | 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".