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Record W2567110960 · doi:10.1002/masy.201600072

Conjugated Linoleic Acid/Styrene/Butyl Acrylate Bulk and Emulsion Polymerization for Adhesive Applications

2016· article· en· W2567110960 on OpenAlexaff
Stéphane Roberge, Marc A. Dubé

Bibliographic record

VenueMacromolecular Symposia · 2016
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsStyreneEmulsionConjugated linoleic acidCopolymerMaterials scienceButyl acrylateAcrylatePolymer chemistryEmulsion polymerizationParticle sizeFourier transform infrared spectroscopyChemistryChemical engineeringPolymerLinoleic acidOrganic chemistryComposite materialPhysical chemistryFatty acid

Abstract

fetched live from OpenAlex

Summary The incorporation of conjugated linoleic acid (CLA) into pressure sensitive adhesive (PSA) formulations was evaluated. First, a series of free radical bulk copolymerizations of CLA/styrene (Sty) and CLA/butyl acrylate (BA) were run for reactivity ratio estimation. This was followed by CLA/Sty/BA bulk terpolymerizations. Pseudo‐kinetic models were developed and validated with the copolymerization data and extended and validated for the CLA/Sty/BA terpolymerization case. The pseudo‐kinetic models incorporated the electron trapping effect of oleic acid, a common impurity found in CLA. A series of emulsion terpolymerizations of CLA/Sty/BA were then designed to investigate the influence of terpolymer composition, molecular weight, chain transfer agent concentration, cross‐linker concentration, latex viscosity and particle size on PSA performance (tack, peel strength and shear strength). Empirical PSA performance models were developed and expressed as 3D response surfaces for optimization of the PSA formulation. All experiments were performed at 80°C and monitored with attenuated total reflectance Fourier transform infrared (ATR‐FTIR) spectroscopy both off‐line (bulk experiments) and in‐line (emulsion experiments). Ultimately, the incorporation of 30 wt.% CLA into a practical PSA application suitable for removable adhesives was achieved.

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 score0.389
Threshold uncertainty score0.872

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 head0.005
GPT teacher head0.219
Teacher spread0.214 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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