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Record W2069668545 · doi:10.1139/v04-022

Micellar properties of zwitterionic surfactant - alkoxyethanol mixed micelles

2004· article· en· W2069668545 on OpenAlexvenueno aff
Maria K. Mullally, D. Gerrard Marangoni

Bibliographic record

VenueCanadian Journal of Chemistry · 2004
Typearticle
Languageen
FieldChemistry
TopicSurfactants and Colloidal Systems
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryMicellePulmonary surfactantEthylene oxideAggregation numberBromideThermodynamics of micellizationAlcoholCritical micelle concentrationSolventHydrophobeSodium dodecyl sulfatePolymerOrganic chemistryAqueous solutionCopolymer

Abstract

fetched live from OpenAlex

The micelle formation process for a zwitterionic surfactant, N-dodecyl-N,N-dimethyl-3-ammonio-1-propanesulfonate (ZW3-12), has been investigated in a series of mixed solvents consisting of different concentrations of ethoxylated alcohols and polymers. The critical micelle concentrations (cmc values) of the aggregates were determined by fluorescence spectroscopy, and the surfactant aggregation numbers were obtained from luminescence probing experiments. The cmc values for ZW3-12 changed very little in the presence of increasing amounts of poly(ethyleneoxide) (PEO) in the mixed solvent. In the case of the ethoxylated alcohol – ZW3-12 systems, the cmc values and aggregation numbers decreased systematically with increasing alcohol concentration. However, the cmc values of the mixed micelles showed little dependence on the number of ethylene oxide (EO) groups at constant alcohol concentration. These results are compared with the well-studied sodium dodecylsulfate – ethoxylated alcohol, and dodecyltrimethylammonium bromide – ethoxylated alcohol mixed micellar systems and to SDS–PEO systems and are discussed in terms of the contribution of the EO groups to the hydrophobic interactions. Key words: zwitterionic surfactant, alcohols, mixed micelles, luminescence probing.

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 score0.010
Threshold uncertainty score0.983

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 head0.175
Teacher spread0.163 · 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

Citations14
Published2004
Admission routes1
Has abstractyes

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