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Record W2070918056 · doi:10.1002/pen.20420

Rheological and mechanical properties of PEO/block copolymer blends

2005· article· en· W2070918056 on OpenAlexaff
Antonio C. Ferretti, Pierre J. Carreau, Pierre Gérard

Bibliographic record

VenuePolymer Engineering and Science · 2005
Typearticle
Languageen
FieldMaterials Science
TopicBlock Copolymer Self-Assembly
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsMaterials scienceCopolymerRheologyComposite materialCastingUltimate tensile strengthViscosityDynamic mechanical analysisShear ratePolymer

Abstract

fetched live from OpenAlex

Abstract Small quantities of block copolymers from two families, styrene‐butadiene‐methylmethacrylate (SBM) and methylmethacrylate‐butylacrylate‐methylmethacrylate (MAM) have been added to a polyethylene oxide (PEO) in order to improve its processability, namely increasing its elastic modulus without increasing too much its shear viscosity. The copolymers contain one block of polymethylmethacrylate (PMMA) that is compatible with PEO; the other blocks create nano phases, dispersed in the PEO matrix. Considerable efforts were devoted to finding the best blending method, either melt processing or solution casting. PEO is very sensitive to shear, and was found to degrade both in the bulk and in solution. Degradation, which cannot be avoided, was quantified through intrinsic viscosity measurements. The rheological characterization of blends containing 1, 2, and 5 wt% block copolymer was carried out. The elastic modulus was found to increase more than the complex viscosity. Blends obtained by solution casting technique gave better results. The elongational viscosity obtained for one blend containing 5 wt% of SBM showed a slight increase with respect to the pure PEO. Mechanical properties were then investigated, through tensile tests and dynamic mechanical analysis in flexion and in torsion; the copolymer generally enhanced the mechanical properties. POLYM. ENG. SCI., 45:1385–1394, 2005. © 2005 Society of Plastics Engineers

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 score0.015
Threshold uncertainty score0.590

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 science0.0000.000
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 head0.011
GPT teacher head0.208
Teacher spread0.197 · 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

Citations15
Published2005
Admission routes1
Has abstractyes

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