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Record W2164734270 · doi:10.1002/masy.200950710

Emulsification for Latex Production Using Static Mixers

2009· article· en· W2164734270 on OpenAlexaff
Ula El‐Jaby, Ghomali Farzi, Élodie Bourgeat‐Lami, Michael F. Cunningham, Timothy F. L. McKenna

Bibliographic record

VenueMacromolecular Symposia · 2009
Typearticle
Languageen
FieldChemistry
TopicSurfactants and Colloidal Systems
Canadian institutionsQueen's University
Fundersnot available
KeywordsMiniemulsionStatic mixerPulmonary surfactantMonomerVolumetric flow rateMixing (physics)PolymerizationMaterials scienceChemical engineeringChemistryChromatographyAnalytical Chemistry (journal)Composite materialPolymerThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Abstract Summary: Evolution of droplets generated by static mixers have been investigated in terms of surfactant concentration, flow rate through the pump, monomer hydrophobicity and the type of static mixer. Operating at faster pump flow rates and using the PAC static mixers generated smaller miniemulsion droplets. Similar effects were observed at higher surfactant concentrations (3.0 vs. 1.0 g/L) and using monomers of increasing hydrophilicity (MMA vs. St). When comparing the efficiency of PAC static mixers to SMX mixing elements it was found that SMX was capable of generating droplets approximately 100 nm smaller at similar pump flow rates in the same time period. Based on these promising results, the SMX mixers were further evaluated based on surfactant concentration. The miniemulsion droplets were polymerized and their distribution was evaluated.

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)0.001
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0020.001

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 head0.018
GPT teacher head0.267
Teacher spread0.250 · 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

Citations9
Published2009
Admission routes1
Has abstractyes

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