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Record W2886845137 · doi:10.1021/acs.macromol.8b01169

Synthesis and Utilization of Low Dispersity Acrylic Macromonomer as Dispersant for Nonaqueous Dispersion Polymerization

2018· article· en· W2886845137 on OpenAlexaff
Mingmin Zhang, Robin A. Hutchinson

Bibliographic record

VenueMacromolecules · 2018
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsQueen's University
Fundersnot available
KeywordsMacromonomerDispersityDispersion polymerizationAtom-transfer radical-polymerizationDispersantPolymer chemistryPolymerizationCopolymerChemistryMethacrylateRadical polymerizationMaterials scienceDispersion (optics)Organic chemistryPolymer

Abstract

fetched live from OpenAlex

The effect of dispersity on the stabilization performance of poly(butyl methacrylate) (P(BMA)) ω-unsaturated macromonomer used as a reactive dispersant in nonaqueous acrylic dispersion (NAD) polymerization is investigated for the first time. Macromonomer with low dispersity (1.3) is synthesized in a one-pot process by the addition of bis(difluoroboryldiphenylglyoximato)cobalt(II) (CoPheBF) as a catalytic chain transfer (CCT) agent to P(BMA) chains mediated by atom transfer radical polymerization (ATRP); addition of the CoPheBF at a BMA monomer conversion of ∼80% leads to good control of chain length and dispersity while achieving a high fraction of terminal double bond (TDB) functionality. The lower dispersity P(BMA) macromonomer provides better stabilization to NAD systems per dispersant chain compared to material of the same number-average molecular weight (∼6000 Da) and TDB functionalization (∼70–75%) but higher dispersity (1.8), as characterized by the smaller average particle sizes and the higher weight fractions of incorporated dispersant.

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 score0.074
Threshold uncertainty score0.890

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 head0.012
GPT teacher head0.248
Teacher spread0.236 · 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
Published2018
Admission routes1
Has abstractyes

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