Predicting the structure and properties of functional polymer nanocomposites

Polymer nanocomposites are a class of materials where small, frequently inorganic nanoparticles are mixed with polymers. The excitement surrounding polymer nanocomposites comes from the possibility that the particles can add functionality to the polymer matrix that is not commonly found in polymers, such useful electrical and thermal transport properties, or tunable, responsive optical properties. Unfortunately, many of these properties depend on controlling the dispersion of the particles, and we only understand the thermodynamics of these systems at a relatively basic level.

Furthermore, small changes in the surface chemistry of the nanoparticles can affect both the dispersion of the particles and the resulting properties, making the experimental design of polymer nanocomposites a challenge. To this end, my group has been using molecular modeling and simulation to approach this problem from two fronts. First, we are designing model systems that will allow us to isolate the effect of changes in the surface functionality on the resulting mechanical properties in the glass state in a polymer nanocomposite. Second, we have developed a theoretical framework that allows us to efficiently predict the equilibrium structure and thermodynamics of polymer nanocomposites. Our approach extends polymer field theory to allow us to study nanoparticle systems of arbitrary shape and complex surface functionality without invoking a mean-field approximation. I will describe how we are utilizing our method to study the key parameters that control the distribution of anisotropic nanoparticles (nanorods) in block polymer thin films.

Speaker: Robert Riggleman, Stanford