Intermolecular Interactions and Morphology of Aqueous Polymer/Surfactant Mixtures Containing Cationic Chitosan and Nonionic Sorbitan Esters
Bibliographic record
Abstract
In this study, the impact of surfactant molecular composition (saturated sorbitan monolaurate or unsaturated sorbitan monooleate) on polymer/surfactant assemblies was examined. Specifically, the associations between the cationic chitosan and the uncharged surfactants were monitored by surface tension, turbidity, and conductivity measurements. Bright field, confocal laser scanning, and transmission electron microscopy revealed that nanometer-sized chitosan/surfactant aggregates comprised of a chitosan-rich shell and a chitosan-poor core agglomerate at high surfactant concentrations to yield micrometer-scaled supramolecular structures with highly ordered internal structure. The size and architecture of these chitosan/surfactant assemblies were dependent on the structure and concentration of the surfactant employed. The association mechanism among chitosan, surfactant, and the chitosan/surfactant aggregates was discussed in terms of the semirigid polyelectrolyte character of chitosan and the hydrophobic character of sorbitan esters. This study provides important insight into the structural and physical parameters of surfactant that govern the formation of multicompartment polymer/surfactant assemblies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".