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Record W2806573423 · doi:10.1002/mren.201800025

Design of Acrylic Dispersants for Nonaqueous Dispersion Polymerization: The Importance of Thermodynamics

2018· article· en· W2806573423 on OpenAlexafffund
Mingmin Zhang, Robin A. Hutchinson

Bibliographic record

VenueMacromolecular Reaction Engineering · 2018
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComonomerDispersantMethacrylateMaterials sciencePolymerizationDispersion polymerizationSolubilityHildebrand solubility parameterPolymer chemistryChemical engineeringPolymerRadical polymerizationDispersion (optics)MacromonomerAcrylic acidChemistryOrganic chemistryCopolymerComposite material

Abstract

fetched live from OpenAlex

Abstract Poly(acrylic) nanoparticles produced by nonaqueous dispersion (NAD) radical polymerization are important components in many automotive coating formulations. A series of experiments show that the properties of final dispersions (particle size distribution, viscosity, and stability) correlate to the thermodynamics of the NAD system, as characterized by solubility parameters and solubility distances among the continuous phase, the soluble polymeric dispersant, and the polymer particles. The insights gained have enabled the design of a macromonomer dispersant containing greater than 10 mol% 2‐hydroxyethyl methacrylate, a necessary functional comonomer addition for end‐use properties. Stable NAD products were synthesized by changing the principal component of the dispersant from butyl methacrylate to 2‐ethylhexyl methacrylate.

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: none
Teacher disagreement score0.624
Threshold uncertainty score0.426

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 head0.008
GPT teacher head0.219
Teacher spread0.211 · 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

Citations4
Published2018
Admission routes2
Has abstractyes

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