Cationic Micelles Modulated in the Presence of α,ω‐Alkanediols: A SANS, NMR and Conductometric Study
Bibliographic record
Abstract
Abstract The solution behavior of a typical cationic surfactant, tetradecyltrimethylammonium bromide, in mixed solvent systems composed of water and varying concentrations of α,ω‐alkanediols; 1,2‐ethanediol (ED), 1,4‐butanediol (BD), 1,6‐hexanediol (HD) and 1,8‐octanediol (OD) was examined via electrical conductance measurements, 13C‐NMR spectroscopy and small angle neutron scattering (SANS) measurements. The critical micelle concentration (CMC) values and degree of counterion dissociation (α) indicate that both ED and BD oppose micellization, whereas HD and OD enhance micelle formation. Changes in the 13C‐NMR chemical shifts (∆δ values) reveal that the short chain diols reside almost exclusively in the bulk phase and hence, affect the formation of micelles by altering the solvent properties in the bulk of the solution, whereas HD and OD partition between the pseudomicellar phase and the bulk phase. SANS studies indicated that both the micellar size and aggregation number (Nagg) decrease in the presence of all diols. ED and BD behave like cosolvents and increase the α and CMC values and decrease Nagg. We note that the effect of HD and OD on the properties of the micelles is concentration dependent; at low concentrations, these diols interact with the micelles and behave as cosurfactants (as evidenced by the trends in the micellar properties), while at higher concentrations, they enhance the surfactant solubility and behave as a cosolvent.
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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) | 0.000 | 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".