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Record W2767377743 · doi:10.1002/app.45991

Hydrolytic stability of polylactide and poly(methyl methacrylate) blends

2017· article· en· W2767377743 on OpenAlexaff
Edwin J. Rodriguez, Shant Shahbikian, Bernard Marcos, Michel A. Huneault

Bibliographic record

VenueJournal of Applied Polymer Science · 2017
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsCrystallinityHydrolysisMethyl methacrylateMaterials sciencePoly(methyl methacrylate)CrystallizationPolymer chemistryExtrusionDegradation (telecommunications)Scanning electron microscopeKineticsChemical engineeringComposite materialPolymerChemistryCopolymerOrganic chemistry

Abstract

fetched live from OpenAlex

ABSTRACT The hydrolytic stability of polylactide/poly(methyl methacrylate) (PLA/PMMA) blends prepared using a twin‐screw extrusion process was investigated. The effects of hydrolysis were monitored in neutral and alkaline media at 80 °C by tracking the changes in molecular weight distribution, weight loss, water uptake, and crystallization behavior. The crystallinity of PLA in blends prior to hydrolysis was shown to be largely hindered by the presence of PMMA. However, PLA recrystallized rapidly during hydrolysis. The PMMA in the blends was shown to provide increased hydrolytic and structural stability to the blends. In the neutral medium, the presence of PMMA delayed and reduced the weight loss but did not significantly affect PLA degradation kinetics. On the other hand, in the alkaline medium, the weight loss rate was strongly decreased in presence of PMMA and the kinetics of degradation was shown to be depend on PMMA content. The microstructure of these blends throughout the hydrolysis process was also examined by scanning electron microscopy. A porous structure, with interconnected pores in the 20–50 nm range, was developed due to the selective removal of PLA. Based on these morphological observations, erosion mechanism of PLA/PMMA blends was discussed. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135 , 45991.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.070
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.027
GPT teacher head0.259
Teacher spread0.232 · 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

Citations22
Published2017
Admission routes1
Has abstractyes

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