Self-assembly in saponin/surfactant mixtures: Escin and sodium dodecylsulfate

Autor: A. Burley, Kun Ma, Robert Thomas, Peixun Li, J. Penfold, S.L. Hosking, Ian M. Tucker, R.E. Petkova, James Doutch, J.R.P. Webster
Rok vydání: 2021
Předmět:
Zdroj: Colloids and Surfaces A: Physicochemical and Engineering Aspects. 626:127019
ISSN: 0927-7757
Popis: Saponins are a class of bio-surfactants obtained from a wide variety of plant species. They are surface active glycosides which are used in the stabilisation of foams and emulsions in many food, drink and cosmetic applications. Their wider utilisation and application will involve their mixture with different synthetic and bio-derived surfactants, proteins and polymers. Understanding the mixing properties of saponins with other surfactants at surfaces and in self-assembly is key to their wider exploitation; and the focus here is on triterpenoid saponin escin and the anionic surfactant sodium dodecylsulfate, SDS. Previous analysis of the surface adsorption and critical micelle concentration, cmc, data using the pseudo phase approximation, PPA, indicate that the micelle mixing is more non-ideal than the surface mixing. The non-ideality is associated with the packing constraints arising from the quite different molecular structures and how this impacts upon the mixture self-assembly is probed here. To address specifically the self-assembly properties of saponin-surfactant mixtures, small angle neutron scattering, SANS, has been used to explore the nature of mixed micelles of escin and SDS. The SANS data for the escin / SDS mixtures are modelled as globular ellipsoidal micelles. The micelles exhibit an overall increase in size and aggregation number as the solution becomes richer in escin, and the evolution in micelle size goes through a minimum at relatively rich SDS solutions. The results illustrate the impact of the disparity in the molecular structures of escin and SDS on the self-assembly, and provides an insight into the factors affecting the departure from ideal mixing.
Databáze: OpenAIRE