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Record W2758185512 · doi:10.1002/polb.24516

Effect of strain‐induced molecular ordering on mechanical performance and barrier properties of polylactide nanocomposites

2017· article· en· W2758185512 on OpenAlexafffund
Shahir Karami, Pierre G. Lafleur

Bibliographic record

VenueJournal of Polymer Science Part B Polymer Physics · 2017
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceNanocompositeCrystallizationComposite materialThermal diffusivityKineticsAmorphous solidMesophaseChemical engineeringCrystallographyThermodynamicsLiquid crystalChemistry

Abstract

fetched live from OpenAlex

ABSTRACT Plastic deformation of polylactide has been known as a self‐reinforcement alternative to improve mechanical and barrier properties. In this study, the structural evolution was investigated during a hot‐drawing process, at different initial strain rates and temperatures above T g of polylactide. The drawing process at T g +10 °C, led to the formation of an intermediate molecular ordering, between the crystalline and amorphous phases. A lower fraction of this mesomorphic phase was found to develop with the addition of nanoparticles. An increase in the stretching temperature to T g +30 °C, caused an improvement of the crystallization kinetics, compared to that of thermally activated crystallization. A strain hardening behavior was observed in the presence of mesophase during a stretching process of the hot‐drawn films at room temperature. Permeability was discerned to its basic components, diffusivity, and solubility coefficients. The matrix degradation influenced the permeability components. The diffusivity decreases in the presence of the impermeable matters. © 2017 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2017 , 55 , 1865–1876

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)0.002
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 score0.051
Threshold uncertainty score0.817

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.023
GPT teacher head0.254
Teacher spread0.230 · 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

Citations5
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Polymer Science Part B Polymer PhysicsSame topicbiodegradable polymer synthesis and propertiesFrench-language works237,207