Asymmetric cationic gemini surfactants: an improved synthetic procedure and the micellar and surface properties of a homologous series in the presence of simple salts
Bibliographic record
Abstract
The micellar and morphological properties of symmetric, cationic gemini surfactants have been well studied in the literature as a function of nature and type of the spacer group and the length and type of hydrophobic chain. In this paper, we have examined the effects of tail asymmetry on the properties of a series of cationic surfactants, the N-alkyl-1-N′-alkyl-2-N,N,N′,N′-tetramethyldiammonium dibromide. A novel synthetic method is used to prepare a series of these surfactants and the consequences of asymmetry on micellar properties are presented. This new method has been shown to be more efficient, with higher yields of the asymmetric surfactants than the yields of the accepted literature method. The critical micelle concentration values and the micelle sizes of the asymmetric gemini surfactants, 12-4-12, 12-4-10, 12-4-8, and 12-4-6 gemini surfactants, were obtained from conductivity and dynamic light scattering. With increasing chain asymmetry, the size of the micelle increased due to the formation of loose micelles. The addition of NaCl and Na2SO4 to the surfactant solutions increased the aggregate size, and this effect was more pronounced with increasing salt concentrations. These results are interpreted in terms of the effect these ions have on the “compactness” of the micelle structure.
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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 | 0.001 |
| 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".