(702a) Molecular Design of Polymer Nanocomposites | AIChE

(702a) Molecular Design of Polymer Nanocomposites


Riggleman, R. - Presenter, University of Pennsylvania
Polymer nanocomposites (PNCs) are an exciting class of hybrid materials that contain typically inorganic nanoparticles embedded in a polymer matrix, and this class of materials has attracted a lot of interest due to their promise in numerous technologies. As one example, in some membrane applications polymer nanocomposites have been shown to be capable of breaking the typical tradeoff between selectivity and permeability that is observed, and there is wide interest in using PNCs as the matrix in structural materials. However, despite their promise, there are numerous fundamental challenges that remain in the design of polymer nanocomposites. The thermodynamics of even simple polymer nanocomposites remain poorly understood, and direct mappings between theoretical and experimental phase diagrams are rare in the field. Furthermore, strategies for reaching high nanoparticle loadings are few. In this talk, I will describe recent efforts to address both the need to predict the thermodynamics of polymer nanocomposites and the properties of nanoparticles at high loadings. Our group has both developed a novel suite of field-theoretic simulations techniques to study inhomogeneous polymer/nanoparticle composites, which enable the prediction of phase diagrams for this class of hybrid materials, and we have recently extended our methods to capture beyond-equilibrium phenomena to describe systems where processing plays a key role in the resulting structure. Separately, we have characterized the properties of a novel class of nanocomposites where the nanoparticles are loaded at high concentrations, up to random close packing. In these materials, the entropy of the polymer in this highly confined geometry plays a key role in both the formation and the properties of the composite. Finally, I’ll conclude by highlighting outstanding challenges in the field that need to be addressed for both simulation and experiment.