Understanding the Influence of Non-covalent Interactions and Nanoparticle Geometries in Carbon Based Polymer Nanocomposites

Low-loading polymer nanocomposites (PNC) are an area of great interest in polymer science. As nanoparticles (NP) are typically expensive in comparison to matrix materials; the low loading regime makes the most efficient use of materials, and represents the optimum for realizing cost effective, high-performance PNCs. However, formulating effective low-loading composites is not without challenges. In addition to the typical requirement of good dispersion for efficient translation of NP properties to the bulk, low-loading composites can sometimes exhibit anomalous (non-classical) dynamics, and unpredictable properties. It is within this context that this thesis aims to examine the effects of NP geometry and softness on the occurrence and nature of anomalous melt dynamics in low-loading PNCs.

The first project presented in this thesis outlines the synthesis and characterization of few-layer graphene (FLG) used in subsequent dynamics studies. From graphite to exfoliated graphite oxide, chemically reduced FLG, and annealed FLG; composition and optoelectric persistence width were tracked through elemental analysis and Raman spectroscopy respectively. A profilometic analysis of some samples was performed using atomic force microscopy. Finally, spectroscopic and compositional information were combined with a geometric growth model to yield a scaled empirical formula that is simultaneously indicative of both compositional purity and optoelectric grade.

Next, PNC melt dynamics were probed for low-loading PNCs filled with fullerenes, carbon nanotubes, and FLG. Graphitic nanoparticles with at least one common dimension, an identical series of styrene-acrylonitrile co-polymers matrices, and identical composite processing conditions were used to form a ceteris paribus assessment of the effect of NP geometry on PNC melt dynamics under conditions favorable for anomalous viscoelastic behavior. Rheometry and NMR relaxometry were used to probe the dynamics on both the bulk and local scale. Bulk and local, segmental dynamics were combined to create segmental scale model (with and without attractive NP-polymer interactions) describing the origin of anomalous viscoelastic behavior in the bulk.

Finally, neutron reflectivity was used to probe matrix self-diffusion in low-loading PNCs of polystyrene (PS) filled with novel, PS-based, soft, nanoparticles. The effect of NP softness on the diffusive dynamics in PNCs is examined.