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Record W2089283166 · doi:10.1021/bm8001478

Physical Properties of Sequential Interpenetrating Polymer Networks Produced from Canola Oil-Based Polyurethane and Poly(methyl methacrylate)

2008· article· en· W2089283166 on OpenAlexaff
Xiaohua Kong, Suresh S. Narine

Bibliographic record

VenueBiomacromolecules · 2008
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDifferential scanning calorimetryPolyurethaneMaterials scienceMethyl methacrylatePolymerChemical engineeringScanning electron microscopePoly(methyl methacrylate)MethacrylatePolymer chemistryUltimate tensile strengthComposite materialPolymerization

Abstract

fetched live from OpenAlex

Sequential interpenetrating polymer networks (IPNs) were prepared using polyurethane (PUR) synthesized from canola oil-based polyol with terminal primary functional groups and poly(methyl methacrylate) (PMMA). The properties of the material were evaluated by dynamic mechanical analysis (DMA), differential scanning calorimetry (DSC), and modulated differential scanning calorimetry (MDSC), as well as tensile properties measurements. The morphology of the IPNs was investigated using scanning electron microscopy (SEM) and MDSC. A five-phase morphology, that is, sol phase, PUR-rich phase, PUR-rich interphase, PMMA-rich interphase, and PMMA-rich phase, was observed for all the IPNs by applying a new quantitative method based on the measurement of the differential of reversing heat capacity versus temperature from MDSC, although not confirmed by SEM, most likely due to resolution restrictions. NCO/OH molar ratios (cross-linking density) and compositional variations of PUR/PMMA both affected the thermal properties and phase behaviors of the IPNs. Higher degrees of mixing occurred for the IPN with higher NCO/OH molar ratio (2.0/1.0) at PUR concentration of 25 wt %, whereas for the IPN with lower NCO/OH molar ratio (1.6/1.0), higher degrees of mixing occurred at PUR concentration of 35 wt %. The mechanical properties of the IPNs were superior to those of the constituent polymers due to the finely divided rubber and plastic combination structures in these IPNs.

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 categoriesMeta-epidemiology (narrow)
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 score0.016
Threshold uncertainty score1.000

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 studies0.0000.000
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 head0.021
GPT teacher head0.236
Teacher spread0.215 · 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

Citations46
Published2008
Admission routes1
Has abstractyes

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