Modeling the Entanglement Distribution in Polymer-grafted Nanoparticle Systems

Polymer nanocomposites have become increasingly useful materials due in part to their ability to provide improved strength and mechanical reinforcement over pure polymer systems. Difficulty controlling nanoparticle dispersion in these nanocomposites has lead researchers to use polymer grafted nanoparticles embedded in matrices of free polymer chains. We believe the nature of the improved mechanical properties in grafted systems is the result of graft chains on different filler particles forming an entanglement network. A computational modeling technique was developed that utilizes slipsprings to model the mobility constraints that physical entanglements impose on individual polymer chains. Focusing on the distribution of entanglements, we found that graft chains appear to be more highly entangled than free chains, irrespective of filler particle loading. The amount of inter-particle graft interactions is also always higher than we would expect if the entanglement pairs were randomly distributed based solely on their probability of occurrence.