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Record W2944738865 · doi:10.1002/app.47929

Thermally stable cellular poly(vinylidene) ferroelectrets: Optimization of CO<sub>2</sub> driven inflation process

2019· article· en· W2944738865 on OpenAlexaff
Nusrat Jahan, Frej Mighri, Denis Rodrigue, Abdellah Ajji

Bibliographic record

VenueJournal of Applied Polymer Science · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsUniversité LavalPolytechnique Montréal
Fundersnot available
KeywordsMaterials scienceComposite materialPiezoelectricityThermal stabilityPolymerVoid (composites)Analytical Chemistry (journal)Chemical engineeringChromatography

Abstract

fetched live from OpenAlex

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 CO 2 inflation treatment using various gas diffusion expansion or inflation procedures on the piezoelectric d 33 coefficient and thermal stability of cellular poly(vinylidene) ferroelectrets and compare with the results (partially) obtained by N 2 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 d 33 coefficient for CO 2 ‐inflated samples is found to be around 30% higher than that of N 2 ‐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 CO 2 gas. The higher activation energy of CO 2 ‐inflated samples (0.52 eV) than the N 2 ‐inflated ones (0.43 eV) further confirms the stability data. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136 , 47929.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.408
Threshold uncertainty score0.489

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.209
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2019
Admission routes1
Has abstractyes

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