Understanding mechanical properties of polymer nanocomposites with molecular dynamics simulations

Equilibrium Molecular Dynamics (MD) simulations are used extensively to study various aspects of polymer nanocomposite (PNC) behavior in the melt state---the key focus is on understanding mechanisms of mechanical reinforcement. Mechanical reinforcement of the nanocomposite is believed to be caused by the formation of a network-like structure---a result of polymer chains bridging particles to introduce network elasticity. In contrast, in traditional composites, where the particle size range is hundreds of microns and high loadings of particle are used, the dominant mechanism is the formation of a percolated filler structure. The difference in mechanism with varying particle sizes, at similar particle loading, arises from the polymer-particle interfacial area available, which increases dramatically as the particle size decreases. Our interest in this work is to find (a) the kind of polymer-particle interactions necessary to facilitate the formation of a polymer network in a nanocomposite, and (b) the reinforcing characteristics of such a polymer network.; We find that very strong polymer-particle binding is necessary to create a reinforcing network. The strength of the binding has to be enough to immobilize polymer on the particle surface for timescales comparable and larger than the terminal relaxation time of the stress of the neat melt. The second finding, which is a direct outcome of very strong binding, is that the method of preparation plays a critical role in determining the reinforcement of the final product. The starting conformations of the polymer chains determine the quality of the network. The strong binding traps the polymer on the particle surface which gets rearranged to a limited extent, within stress relaxation times. Significant aging effects are seen in system relaxation; the inherent non-equilibrium consequences of such strong binding. The effect of the polymer immobilization slows down other relaxation processes. The diffusivity of all chains is slowed down, and some chains drastically so. Similarly the relaxation of the end-to-end vector is drastically slowed down for some chains that have a greater fraction of chains immobilized on the particle surface.; A schematic representation of a polymer network is given in Figure 1 below. It shows the different topological structures that can form in a network by polymer immobilization on the particle. Detailed analysis is performed to isolate the dominant structure. Trains and dangles are most populous followed by loops and then by bridges. In order to understand the reinforcing characteristics of each kind of these structures, toy systems are simulated containing chains with only a specific kind of structure. The formation of a specific kind of structure is induced by making chains telechelic and a-priori labeling of the end monomers. The simulations with toy systems clearly show that bridges are most reinforcing, followed by loops and then by dangles. Thus we conclude that in the non-toy systems, while the reinforcement is due to a combination of contributions from all the kinds of structures which result in an overall polymer network, the bridges play the critical role. It is the presence of sufficient bridges connecting particles together to form a long lasting semi-rigid network that causes the enormous reinforcement seen in polymer nanocomposites.*; *Please refer to dissertation for diagrams.