Calorimetric Determination of Surfactant/Polyelectrolyte Binding Isotherms
Bibliographic record
Abstract
Mixing of oppositely charged surfactants and polyelectrolytes in aqueous solutions leads to cooperative surfactant adsorption onto the polyelectrolyte chains. Experimental determination of surfactant/polyelectrolyte binding isotherms is usually done using custom-built surfactant-ion-specific electrodes. As an alternative, we present an indirect isotherm approximation method that uses conventional isothermal titration calorimetry (ITC). The calorimetric data is fitted to the two-binding-state Satake-Yang adsorption model, which quantifies the extent of binding in terms of the binding constant (Ku) and the cooperativity parameter (u). This approach is investigated using two surfactant/polyelectrolyte mixtures: sodium perfluorooctanoate (FC7) and N,N,N-trimethylammonium derivatized hydroxyethyl cellulose (UCARE Polymer JR-400), whose binding behavior follows the Satake-Yang model, and dodecyltrimethylammonium bromide (DTAB) and poly(styrenesulfonate) (NaPSS), whose behavior deviates dramatically from the Satake-Yang model. These studies demonstrate that, in order to apply the indirect ITC method of binding isotherm determination, the surfactant/polyelectrolyte adsorption process must have no more than two dominant binding states. Thus, the technique works well for the FC7/JR-400 mixture. It fails in the case of the DTAB/NaPSS adsorption, but its mode of failure offers insight into the multiple-binding-state adsorption mechanism.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".