Surface activity of mixtures of dodecyl trimethyl ammonium bromide with sodium perfluorooctanoate and sodium octanoate
Bibliographic record
Abstract
Abstract In this study, the surface tension of mixtures of cationic surfactant dodecyl trimethylammonium bromide (DTAB) and anionic surfactant sodium perfluorooctanoate (SPFO) was evaluated as a function of DTAB‐SPFO composition and total surfactant concentration, with and without added electrolyte. It was found that the critical micelle concentration (CMC) of these mixtures was reduced by more than two orders of magnitude when compared to the CMC of SPFO and DTAB alone. The surface tension, after CMC, of the mixtures was close to that of SPFO with added electrolyte and even lower than that of SPFO without added electrolyte. Using the appropriate, combination of SPFO and DTAB, surface tensions near 18 mJ/m2 were obtained using a concentration 1/500 of that required for SPFO alone. When these results were compared to those obtained for DTAB‐sodium octanoate (SOCT) mixtures, it was evident that the DTAB‐SPFO system shows a larger degree of synergism than the DTAB‐SOCT system. Contact angle measurements on Teflon® surfaces corroborates that the lower surface tension of DTAB‐SPFO mixtures improves wetting on these hydrophobic surfaces. Using the regular solution theory to interpret the data of CMC and C45mJ/m2 (monolayer formation) versus DTAB‐SPFO composition, it was concluded that even when small concentrations of SPFO are introduced in the mixture, the composition of the micelles (at the CMC) and monolayer adsorbed at the air‐water interface tends to be equimolar in SPFO and DTAB.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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".