User friendly EOMMM for rational mixed micelles design

ERICA PATRICIA SCHULZ; GUILLERMO ANDRES DURAND

Buenos Aires

Congreso; WCCE11- 11th World Congress of Chemical Engineering; 2023

Asociación Argentina de Ingenieros Químicos

The surfactants are ubiquitous molecules and, therefore, have countless applications. Their role is preponderant in diverse processes, from biological and biomedical processes (such as the solubilization and transport of cholesterol in the gastrointestinal tract by means of bile salt-lecithin mixed micelles), to multiple uses in several industries (pharmacy, food, petrochemical, coatings, agrochemicals, among others). Some avant-garde medical treatments rely on surfactants’ properties (i.e. drug delivery, functionalized micelles, Marangoni transport). Most surfactants’ applications involve mixtures instead of pure amphiphiles, since they frequently have enhanced properties (synergism). The composition of mixed micelles (more than one surfactant) is determined by the partition equilibria of the species between the aggregates and the surrounding solution. However, only the global composition (aggregates and solution) can be known a priori. Therefore, the optimal design of surfactant systems with customized properties is a complex problem. Being able to predict the behavior of thermodynamically non ideal surfactant combinations is a non-trivial step for the rational design of customized mixtures. Our group has developed an approach (EOMMM) based on Equation Oriented Optimization and Margules asymmetric formulations which is not restricted to the number of components and guarantees the applicability of the Gibbs–Duhem relation [1]. EOMMM allows the estimation of the mixed micelles´ compositions on the basis of a thermodynamic model parameterized with the critical micelles concentration (CMC), an easily experimentally determined property. EOMMM has been validated through its application to diverse systems with non-ideal behavior originated from diverse interactions between the components [2]. In the present work we aim to generate a user-friendly tool oriented to technologist and experimenters that are not familiar with modelling skills.