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Record W1969813841 · doi:10.1021/jp0214662

Incongruent Diffusion (Negative Main Mutual Diffusion Coefficient) for a Ternary Mixed Surfactant System

2002· article· en· W1969813841 on OpenAlexaff
Kimberley MacEwan, Derek G. Leaist

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2002
Typearticle
Languageen
FieldChemistry
TopicSurfactants and Colloidal Systems
Canadian institutionsWestern University
Fundersnot available
KeywordsPulmonary surfactantDiffusionChemistryTernary operationTaylor dispersionSodium dodecyl sulfateMicelleAqueous solutionAnalytical Chemistry (journal)Phase (matter)Dispersion (optics)ChromatographyThermodynamicsPhysical chemistryOrganic chemistryPhysicsBiochemistry

Abstract

fetched live from OpenAlex

Moments analysis of Taylor dispersion profiles is used to measure ternary mutual diffusion coefficients ( D ik ) for dilute aqueous sodium dodecyl sulfate (SDS) + dodecylsulfobetaine (DSB) mixed surfactant solutions at 25 °C and total surfactant concentrations from 10 to 30 mmol dm -3 . The fluxes of the SDS(1) and DSB(2) components are strongly coupled by the formation of SDS−DSB mixed micelles. At several compositions, cross-coefficient D 12 or D 21 is larger than main coefficients D 11 and D 22 . More remarkably, D 22 is negative at solute fractions of SDS from 0.55 to 0.75, reaching a minimum value of −0.056 × 10 -9 m 2 s -1 at 13 mmol dm -3 SDS + 7 mmol dm -3 DSB. This surprising result means that DSB concentration gradients drive “incongruent” fluxes of DSB, from lower to higher DSB concentrations. A possible explanation for the incongruent diffusion of DSB is suggested on the basis of the electric field generated by gradients in the surfactant concentration. Negative D ii values have been reported previously for concentrated, strongly nonideal aqueous acetic acid + chloroform solutions near a consolute point. Because the SDS + DSB solutions are dilute and far removed from phase boundaries, incongruent diffusion might be considerably more common than previously assumed.

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 score0.115
Threshold uncertainty score0.792

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.012
GPT teacher head0.219
Teacher spread0.208 · 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

Citations26
Published2002
Admission routes1
Has abstractyes

Explore more

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