The molecular factors that govern interfacial interactions between a polymer melt and a solid surface remain largely unclear despite significant progress made in the last years. Simulations are increasingly employed to elucidate these features, however, equilibration and sampling with models of long macromolecules in such heterogeneous systems present significant challenges. In this study, we couple the application of preferential sampling techniques with connectivity-altering Monte Carlo algorithms to explore the configurational characteristics of a polyethylene melt in proximity to a surface and a highly curved nanoparticle. Designed algorithms allow efficient sampling at all length scales of large systems required to avoid finite-size effects. Using detailed atomistic models for the polymer and realistic structures for a silica surface and a fullerene, we find that at the extreme limit where particles are comparable to the polymer Kuhn segment length, curvature penalizes the formation of long train segments. As a result, an increased number of shorter contacts belonging to different chains are made competing with the anticipated decrease of the bound layer thickness with particle size if polymer adsorbed per unit area remained constant. For very small nanoparticles, formation of new train segments cannot compete with the overall reduction of adsorbance which is present irrespective of the enthalpic interactions; a result that demonstrates the need for an accurate description of polymer rigidity at these length scales.
© 2012 American Institute of Physics