(5ca) Molecular Simulations of Complex Polymeric Materials and Nanocomposites

The use of computational tools to obtain the properties of polymeric materials becomes increasingly challenging as these materials become increasingly complex. Such complexities that are often present in polymer materials include long-range electrostatic interactions in polyelectrolyte materials, or the inclusion of nanoparticles for mechanical reinforcement. Problems as complex as these can require a diverse set of computational tools to understand the array of phenomena observed in such systems, and in this poster I will describe some of the topics I have studied and the methods I have learned in my graduate and postdoctoral education.

Using a combination of Monte Carlo and molecular dynamics simulations, part of my research has focused on understanding how aging and deformation changes the properties of polymer nanocomposite materials, which is essential to understand as nanocomposite materials are finding increased use in critical applications where they will be subject to deformation. Recent experiments and simulations have shown that the dynamics in glassy solids can be enhanced by several orders of magnitude. Using molecular dynamics simulations on a model nanocomposite material, I have studied how the presence of nanoparticles changes the dynamic enhancement. I have shown that the changes due to the presence of the particles arise from the nanoparticles' ability to stiffen the polymer. Additionally, by examining the entanglement network in a polymer glass and in the nanocomposite, we have found that nanoparticles have the ability to increase the entanglement density in the polymer, leading to increases in the plateau modulus, a key design parameter in many applications.

More recently I have worked with field-theoretic simulations, which have the advantage of capturing the behaviors of polymeric materials on length scales much larger than those accessible by particle-based simulations. A problem commonly faced in field-theoretic simulations requires the simulation of two phases in equilibrium with each other, and difficulties arise when performing such a simulation for two primary reasons. First, equilibration of such a system is computationally demanding. Additionally, it is necessary to perform a simulation large enough so that the interface between the two equilibrium phases does not affect the measured properties, and large simulations exacerbate the problem of slow equilibration. To circumvent this issue, I have helped develop a new method to perform field theoretic simulations in the so-called Gibbs ensemble, where two simulations are performed in conjunction with each other. By allowing the two simulations to exchange both particles and volume with each other, they remain in equilibrium with each other, enabling the efficient simulation of two phases in equilibrium with each other. This method is extremely power in that it will enable efficient simulations of complex phase diagrams using field theory, and I will present several examples on my poster.