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Record W2022259853 · doi:10.1002/pi.1412

Morphology and thermal properties of two polymethacrylates modified by a polymer liquid crystal

2004· article· en· W2022259853 on OpenAlexaff
Witold Brostow, Ligia Gargallo, Andrea Hormazábal, Magdalena Jaklewicz, Kevin P. Menard, Alejandra Opazo, Deodato Radić

Bibliographic record

VenuePolymer International · 2004
Typearticle
Languageen
FieldMaterials Science
TopicLiquid Crystal Research Advancements
Canadian institutionsMcGill University
Fundersnot available
KeywordsMaterials scienceMiscibilityGlass transitionMethacrylateThermogravimetryPolymerPolymer blendScanning electron microscopePolymer chemistryChemical engineeringComposite materialCopolymer

Abstract

fetched live from OpenAlex

Abstract We have studied blends of a polymer liquid crystal (PLC) with poly(cyclohexylethyl methacrylate) (PCHEMA) or poly(cyclohexylpropyl methacrylate) (PCHPMA). The PLC is PET/0.6PHB where PET = poly(ethylene terephthalate), PHB = p ‐hydroxybenzoic acid and 0.6 is the mole fraction of the latter in the copolymer. The microstructure was studied by scanning electron microscopy (SEM). PCHEMA + PLC (20 wt% of the latter, blend E) has a fine texture with LC islands evenly distributed in the matrix and good adhesion between the phases resulting from their partial miscibility. The PCHPMA + PLC (20 wt% of the latter, blend P) shows only limited compatibility. The SEM results are confirmed by values of the glass transition temperatures T g determined via thermal mechanical analysis. The T g value of the blend E is shifted towards the T g of PLC; T g of blend P is practically equal to that of PCHPMA. The linear isobaric expansivity α L values for both blends are lower than the respective values for pure PCHPMA and PCHEMA. Thermal stabilities of the blends determined by thermogravimetry are also better than those of pure polymethacrylates. The temperature of 50% weight degradation for blend E is higher than that for pure PCHEMA by more than 60 K Copyright © 2004 Society of Chemical Industry

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 score0.005
Threshold uncertainty score0.932

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)0.0010.000

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 head0.026
GPT teacher head0.295
Teacher spread0.269 · 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

Citations0
Published2004
Admission routes1
Has abstractyes

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