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Record W2761494154 · doi:10.1021/acs.iecr.7b02681

A New Approach to Dynamic Vulcanization: Use of Functional Nitroxyls to Control Reaction Dynamics and Outcomes

2017· article· en· W2761494154 on OpenAlexaff
Michael W. Bodley, J. Scott Parent

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2017
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Nanocomposites and Properties
Canadian institutionsQueen's University
Fundersnot available
KeywordsVulcanizationPolyolefinElastomerPolypropyleneMaterials sciencePeroxideMonomerPolymer chemistryRheometryPolymerPhase (matter)Polymer blendThermoplasticChemical engineeringPolymer scienceChemistryCopolymerComposite materialOrganic chemistryNatural rubber

Abstract

fetched live from OpenAlex

A new method of exerting control over the dynamics and outcomes of radical-mediated polyolefin modifications is adapted for the dynamic vulcanization (DV) of polypropylene + poly(ethylene- co -octene) (PP+EOC) blends. Whereas the conventional peroxide-initiated DV of these blends produce extreme initial rates of EOC cross-linking and extensive PP matrix degradation, formulations containing nitroxyls that bear polymerizable functionality do not suffer from these limitations. Acryloyloxy-2,2,6,6-tetramethylpiperidine- N -oxyl (AOTEMPO), used alone or in combination with a triacrylate monomer, is used to delay the onset of polymer modification, raise the cross-link density of dispersed elastomer phase, and mitigate changes to the molecular weight of the thermoplastic matrix. Brief demonstrations of the influence of AOTEMPO on dicumyl peroxide (DCP) modifications of each blend component are followed by careful studies of PP+EOC dynamic vulcanization. Dispersed phase size distributions and melt-state oscillatory rheometry reveal the effect of AOTEMPO on DV product architecture and morphology.

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)0.001
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 score0.030
Threshold uncertainty score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.097
GPT teacher head0.313
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.

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

Citations6
Published2017
Admission routes1
Has abstractyes

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