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Record W2049264093 · doi:10.1021/ma102936a

Emulsion Polymerization of Styrene and Methyl Methacrylate Using Cationic Switchable Surfactants

2011· article· en· W2049264093 on OpenAlexafffund
Candace Fowler, Christine M. Muchemu, Ricarda Miller, Lam Phan, Catherine O’Neill, Philip G. Jessop, Michael F. Cunningham

Bibliographic record

VenueMacromolecules · 2011
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsQueen's University
FundersCanada Research Chairs
KeywordsEmulsion polymerizationCationic polymerizationPolymer chemistryMethyl methacrylatePolystyreneStyrenePolymerizationPulmonary surfactantChemistryDispersion polymerizationPolymerEmulsionRadical polymerizationParticle sizeChemical engineeringMaterials scienceOrganic chemistryCopolymer

Abstract

fetched live from OpenAlex

Colloidal latexes of polystyrene and poly(methyl methacrylate) have been prepared by emulsion polymerization using cationic amidine-based switchable surfactants. Particles with sizes ranging from 50 to 350 nm were obtained and the effect of factors such as initiator type, initiator amount, surfactant amount, and solid content on the particle size and ζ-potential of the resulting latexes have been examined. Destabilization of the latexes, which is commonly achieved by addition of salts or either strong acids for anionically stabilized latexes or alkalis for cationically stabilized latexes, requires only air and heat, which destabilize the latex by removing CO 2 from the system and switching the active amidinium bicarbonate surfactant to a surface inactive amidine compound. The resulting micrometer-sized particles can be easily filtered to yield a dry polymer powder and a clear aqueous phase.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.032
GPT teacher head0.243
Teacher spread0.212 · 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 source (direct Gemma or distilled Codex), 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

Citations123
Published2011
Admission routes2
Has abstractyes

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