Adsorption and Dilational Viscoelasticity of Saponin at the β-Pinene/Water and Air/Water Interfaces
Bibliographic record
Abstract
Understanding adsorption and interfacial properties of surface-active agents at interfaces is crucial to the formation and stability of colloidal systems such as emulsions and foams. In this work, interfacial tension and viscoelasticity of saponin at the β-pinene/water interface were studied using drop tensiometry and dilational rheology measurement. For comparison, saponin at the air/water interface was also evaluated. Both saponin and β-pinene are bio-based, eco-friendly, and abundant in plants, trees, and agricultural wastes. Results showed that dynamic interfacial tensions σ(t) of saponin adsorbed at β-pinene/water and air/water interfaces could be well described by the Ward and Tordai model, suggesting that the saponin adsorption kinetics at both interfaces are controlled by a kinetically limited mechanism. The equilibrium interfacial pressure πe data prior to critical micelle concentration (cmc) were adequately fitted by the Gibbs adsorption isotherm. At the β-pinene/water interface, a higher cmc and a larger area per molecule, but a lower πe, were observed compared to the air/water interface. Interestingly, the dilational moduli of saponin at β-pinene/water increased with increasing oscillating frequency, but with less significant frequency dependence than their counterparts at the air/water interface. The dilational moduli of saponin at β-pinene/water passed through a minimum with increasing saponin bulk concentration, while the air/water interface exhibited a strikingly different trend in terms of concentration dependence and a higher magnitude for the dilational moduli. The correlation between adsorption behaviors and dilational properties of saponin at the two interfaces is discussed. Fundamental knowledge gained from this study will be beneficial for the rational development of new biocompatible emulsions and foam products for more sustainable applications.
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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".