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Record W2019982610 · doi:10.1021/ma0505528

Effect of Solvent Quality toward the Association of Succinimide Pendants of a Modified Ethylene−Propylene Copolymer in Mixtures of Toluene and Hexane

2005· article· en· W2019982610 on OpenAlexafffund
Mingzhen Zhang, Jean Duhamel

Bibliographic record

VenueMacromolecules · 2005
Typearticle
Languageen
FieldChemistry
TopicSurfactants and Colloidal Systems
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSuccinimideToluenePyreneChemistryHexaneSolventPolymer chemistryCopolymerDiglymeOrganic chemistryPolymer

Abstract

fetched live from OpenAlex

A maleated ethylene−propylene random copolymer (EP) was reacted with 1-pyrenemethylamine to yield a pyrene labeled EP, and the photophysical properties of the pyrene label were used to determine the level of aggregation between the resulting succinimide groups as a function of the composition of hexane/toluene mixtures. In hexane, the polar succinimides bearing the pyrenyl pendants form aggregates whose presence can be inferred from fluorescence and UV−vis absorption measurements. Addition of toluene is found to melt the pyrene aggregates. The aggregation induced by the polar succinimide groups was shown to occur intramolecularly at polymer concentrations of 0.1 g/L by fluorescence resonance energy transfer. The level of pyrene aggregation ( f agg ) was determined quantitatively and could be followed as a function of the volume fraction of hexane in a series of toluene/hexane mixtures. Upon addition of toluene, the parameter f agg decreased rapidly to a finite value different from 0.0 due to the inherent clustering of succinic anhydride groups occurring during the maleation of EP. This lowest f agg value was reached for a mixture containing 60 vol % of hexane. The ability of toluene at melting the pyrene aggregates was shown to have a profound effect on the rheological properties of the polymer solutions.

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)0.001
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 score0.047
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.011
GPT teacher head0.273
Teacher spread0.262 · 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

Citations8
Published2005
Admission routes2
Has abstractyes

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