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Record W2801742117 · doi:10.1021/acs.macromol.8b00464

Toughening of Cocontinuous Polylactide/Polyethylene Blends via an Interfacially Percolated Intermediate Phase

2018· article· en· W2801742117 on OpenAlexafffund
Ali M. Zolali, Basil D. Favis

Bibliographic record

VenueMacromolecules · 2018
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceLinear low-density polyethyleneComposite materialIzod impact strength testCompatibilizationPolymer blendPhase (matter)PolyethyleneMethyl acrylateAcrylateMethyl methacrylateTernary operationCopolymerPolymerUltimate tensile strength

Abstract

fetched live from OpenAlex

It will be shown that an interfacially percolated rubbery phase in a cocontinuous polylactide (PLA)/linear low-density polyethylene (LLDPE) blend results in a significant increase in the impact strength. All blends possess a tricontinuous phase morphology in which poly(ε-caprolactone) (PCL), poly(ethylene–methyl acrylate) (EMA), and ethylene–methyl acrylate–glycidyl methacrylate (EMA-GMA) percolate at the interface of PLA/LLDPE but offer different toughening and compatibilization effects. Among these components, the addition of EMA-GMA to the binary PLA/LLDPE blend reduces the cocontinuous PLA/LLDPE phase thickness from about 25 to 5 μm and yields a very tough material with an impact strength of about 515 J/m, which is approximately 13 times greater than the original cocontinuous PLA/LLDPE blend and more than 32 times that of PLA. The ternary blends show significant improvements in the impact strength within the tricontinuous region; however, the principal differences in the toughening effects are attributed to interfacial interactions between the phases. The interconnected network of the rubbery phase is expected to percolate the stress field throughout the tricontinuous system and reduce the detrimental dilatational stress in the bulk blend.

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 categoriesInsufficient payload (model declined to judge)
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 score0.103
Threshold uncertainty score0.999

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.269
Teacher spread0.252 · 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.

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

Citations98
Published2018
Admission routes2
Has abstractyes

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