Abstract: 

“Polymer nanoparticle composites (PNCs) have become an important topic of research due to their highly tunable macroscopic properties. Compared to the pure polymers, PNCs exhibit increase in mechanical strength, altered thermodynamic properties, and simultaneous improvement in permeability and selectivity in small molecule transport. Understanding the fundamental physics that control the behavior of both components in the PNCs can provide insights to the material design. In PNCs, the microscopic variations often dominate the behavior at the macroscopic level. Previous research has shown significant deviations in both polymer conformation and dynamics near the nanoparticle (NP) surfaces from bulk polymers. However, the heterogeneous nature of the PNCs makes understanding microscopic details using macroscopic experiments a difficult task. Therefore, computational methods have been employed to investigate the polymer conformation, mechanics, and dynamics at the molecular level. In this dissertation, I use PNCs with two levels of NP loading to investigate the origins of the various changes in properties. First, I use molecular dynamics (MD) simulations to examine a class of PNCs with ultra-high NP loading, in which the volume fraction of NPs is near the random-close-pack limit ( >50% ). This class of PNCs can be produced with either partial or complete filling of polymers. In these PNCs, the polymer chains are highly confined due to the large number of NP surfaces, thus are drastically altered in their conformation and dynamics. The second PNC system studied in this dissertation has a dilute amount of well-dispersed NPs to avoid NP-NP interaction and polymer confinement. In this case, I use both MD simulations and classical density functional theory (cDFT) for fluids to understand the role of NP-polymer interactions, solid curvature, and polymer molecular weight.”