Activity Coefficients and Free Energies of Nonionic Mixed Surfactant Solutions from Vapor-Pressure and Freezing-Point Osmometry
Bibliographic record
Abstract
The thermodynamic properties of mixed surfactant solutions are widely investigated, prompted by numerous practical applications of these systems and by interest in molecular association and self-organization. General techniques for measuring thermodynamic activities, such as isopiestic equilibration, are well-established for multicomponent solutions. Surprisingly, these techniques have not yet been applied to mixed surfactant solutions, despite the importance of the free energy for micelle stability. In this study, equations are developed for the osmotic coefficients of solutions of nonionic surfactant A + nonionic surfactant B. A mass-action model is used, with virial equations for the activity coefficients of the micelles and free surfactant monomer species. The equations are fitted to osmotic coefficients of aqueous decylsulfobetaine + dodecylsulfobetaine solutions measured by vapor-pressure and freezing-point osmometry. Equilibrium constants for mixed-micelle formation are calculated from the free monomer concentrations at the critical micelle concentrations. The derived activity coefficients of the micelles and free monomers indicate large departures from ideal solution behavior, even for dilute solutions of the surfactants. Stoichiometric activity coefficients of the total surfactant components are evaluated by Gibbs-Duhem integration of the osmotic coefficients. Relatively simple colligative property measurements hold considerable promise for free energy studies of multicomponent surfactant solutions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".