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Record W2900425390 · doi:10.1002/pcr2.10033

Tunable microcellular and nanocellular morphologies of poly(vinylidene) fluoride foams via crystal polymorphism control

2018· article· en· W2900425390 on OpenAlexafffund
Siu N. Leung, Ji E. Lee

Bibliographic record

VenuePolymer Crystallization · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials sciencePolymorphism (computer science)FluorideChemical engineeringMelting temperatureCrystallizationPolymerCrystal (programming language)Phase (matter)Crystal structureSupercritical fluidComposite materialCrystallographyChemistryOrganic chemistryInorganic chemistry

Abstract

fetched live from OpenAlex

Poly(vinylidene) fluoride (PVDF) is well-known for its polymorphism. Among its different polymorphs, both α and β phase crystals have melting temperatures ranging from 167°C to 172°C. The melting temperature of γ phase crystal, depending on its origin, is about 8 °C or 18°C higher than those of α and β phase crystals. Herein, this article reports a novel approach to tune the microcellular and nanocellular structures of PVDF foams by controlling the polymorphism of PVDF before it is subjected to supercritical carbon dioxide foaming. It has been revealed that altering PVDF's polymorphs can selectively fabricate PVDF foams that possess either (1) closed cells or open cells; (2) unimodal cells or bimodal cells; and (3) microcellular structures or nanocellcular structures. This represents an innovative processing route to fine-tune the morphologies of PVDF foams, and thereby to tailor their multifunctional properties.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.000
Threshold uncertainty score0.001

Distilled classifier scores by category (both heads)

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 communication0.0000.000
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 head0.008
GPT teacher head0.192
Teacher spread0.184 · 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 source (direct Gemma or distilled Codex), 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

Citations9
Published2018
Admission routes2
Has abstractyes

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