Center for Functional Nanomaterials Seminar

Surfactants are used in a wide variety of industrial and biological applications. Composed of a hydrophilic head group and a hydrophobic tail group, they self-assemble into various structures in aqueous solutions. Atomistic models can have difficulty reaching the necessary time and length scales for self-assembly in dilute solutions and creating a model that can quantitatively reproduce surfactant system properties has proven elusive. Our first set of studies examined how well the MARTINI model, a coarse grained chemistry-specific model, was able to reproduce the equilibrium properties of critical micelle concentration (cmc) and aggregate size distribution. We modeled non-ionic and zwitterionic surfactants using molecular dynamics and found that the model was able to achieve self-assembly in reduced computational time. However, further refinement was needed in order to match experimental values quantitatively and the model was unable to capture the temperature dependence of these properties due to the lack of solvent orientation. Based on these results, we have performed additional studies simulating ionic surfactants with two different types of models. A near-atomistic model was used to model sodium alkyl sulfates with relatively high experimental cmc’s and we were able to reach equilibrium and measure the cmc of the model at total surfactant concentrations close to the cmc. Using Grand Canonical Monte Carlo and histogram reweighting, we have developed an implicit solvent model that can be modified to approximate the temperature dependence of the cmc for two cationic surfactants, DTAC and DTAB, without directly parameterizing the model for them. Each of these studies can provide insight for developing a quantitative model.