Dynamic Surface Excesses of Fluorocarbon Surfactants
Bibliographic record
Abstract
Dynamic adsorption and surface tension behavior of aqueous fluoro-surfactant solutions has been investigated using a range of experimental techniques, including neutron reflection (NR). Equilibrium tensions, γ eq, have been measured by drop volume tensiometry (DVT), and dynamic surface tensions, γ dyn, have been determined using the nonperturbative method, surface light scattering (SLS). Dynamic conditions for NR and SLS measurements were established using an overflowing cylinder (OFC). The OFC provides a dynamic surface on the 0.1−1 s time scale and offers a large (∼50 cm 2 ), near flat surface for interrogating interfacial properties. To exploit these techniques effectively, a fluorocarbon anionic surfactant, sodium bis(1 H,1 H -nonafluoropentyl)-2-sulfosuccinate (di-CF4) has been specifically selected. Molecular structure effects have been explored with the C6 analogue sodium bis(1 H,1 H,7 H -dodecafluoro- n -heptyl) sulfosuccinate (di-HCF6). Using OFC−NR, dynamic surface excesses, Γ dyn, have been measured directly, and these values have been compared to equilibrium coverages, Γ eq, determined by DVT and NR. Close to the critical micelle concentration (cmc) of di-CF4 (1.58 mmol dm - 3 ), Γ dyn and Γ eq are very similar, and the ratio φ = Γ dyn /Γ eq is unity to within the precision of the experiment. For moderate differences in surface tension, up to Δγ = γ dyn − γ eq ≤ 15 mN m - 1, φ remains close to 1. At concentrations of 0.2−0.7 mmol dm - 3, the dynamic surface excess Γ dyn is measurably different from the equilibrium value Γ eq (φ < 1). This concentration range coincides with the largest differences in surface tension, Δγ. For both di-CF4 and di-HCF6, the maximum values of Δγ and ΔΓ occur around the same bulk concentration, ∼0.7 mmol dm - 3, suggesting that dynamic surface behavior is determined mainly by mass transport (which is related to the bulk concentration), rather than surfactant properties such as cmc, for these surfactants.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".