A computer simulation and molecular-thermodynamic framework to model the micellization of ionic branched surfactants in aqueous solution

Abstract

Surfactants, or surface active agents, are chemicals exhibiting amphiphilic behavior toward a solvent. This amphiphilic character leads to increased activity at interfaces and to self-assembly into micellar aggregates beyond a threshold surfactant concentration, referred to as the critical micelle concentration (CMC), in bulk solutions. As a result of these unique attributes, surfactants are used in many pharmaceutical, industrial, and environmental applications, including biological separations, fat metabolism during digestion, drug delivery, and water purification. Selection of the appropriate surfactant for a given application is often motivated by the need to control bulk solution micellization properties, such as the CMC and the micelle shape and size. The ability to make molecular-level predictions of these surfactant properties would allow formulators in industry to speed up the design and optimization of new surfactant formulations. In this thesis, a combined computer simulation/molecular-thermodynamic (CS-MT) modeling approach was developed and utilized to study the micellization behavior of ionic branched surfactants, which are a class of surfactants of great industrial relevance in applications such as detergency, emulsification, and enhanced-oil recovery. In the CSMT modeling approach, molecular dynamics (MD) simulations are used to obtain input parameters for molecular-thermodynamic (MT) modeling of surfactant micellization.This approach is motivated by the limitations inherent in computer simulations (the high computational expense associated with modeling self-assembly) and in MT modeling approaches (their restriction to structurally and chemically simple surfactants). One key input required for traditional MT modeling is the identification of the hydrated ("head") and the dehydrated ("tail") portions of surfactants in a self-assembled micellar aggregate. Using the results of MD simulations of surfactants in a micellar environment, a novel head and tail identification method was developed based on the determination of a conceptual micelle core-water interface. The introduction of an interfacial region consisting of partially hydrated, neutral atomic groups required formulating an improved surfactant tail packing approach.

(cont.) Another key input required in the CS-MT modeling approach is the fractional degree of hydration of each atomic group in the ionic branched surfactants considered in this thesis, which can be used to accurately quantify the hydrophobic driving force for micelle formation in aqueous media. Fractional hydration profiles were obtained by conducting two MD simulations, one in a bulk water environment and the other in a micellar environment. By investigating the radial distribution function (RDF) between each surfactant group and hydrating atoms which are capable of forming hydrogen-bonds and coordinate-bonds, an updated cutoff distance for counting hydrating contacts was selected. These simulated fractional hydration profiles were then utilized as inputs in the MT model, which enables calculation of the minimum free energy associated with micelle formation, from which the CMC and the optimal micelle shape and size can be predicted at the molecular level. The MD simulations were shown to extend the applicability of the traditional MT modeling approach to more complex surfactant systems than had been possible to date. A rich variety of ionic branched surfactants were modeled using the new CS-MT modeling approach, including two homologous series of simple secondary alkyl sulfonates and three classes of more complex ionic branched surfactants possessing aromatic moieties. For each of the ionic branched surfactants modeled, the predictions of the CS-MT modeling approach were found to be in reasonable agreement with the experimental data, including accounting for the chemical and structural complexities of the branched surfactants more accurately. The CS-MT modeling approach developed in this thesis not only extends our ability to make accurate molecular-level predictions of the micellization behavior of complex surfactants, but it also contributes to our overall fundamental understanding of the solution behavior of surfactants.