Incongruent Diffusion (Negative Main Mutual Diffusion Coefficient) for a Ternary Mixed Surfactant System
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".