Modeling polymers can be a very challenging task, since their relaxation times scale exponentially with chain length. To overcome this, we use special connectivity-altering Monte Carlo techniques (illustrated in the link picture to get here), to reconnect different polymers with each other.
The major application we are targetting is to determine lithium ion transport through polymer electrolytes, which is important to optimize for good battery operation. Lithium ion transport is plagued by slow transport through neat polymers. Three strategies have been proposed to improve lithium ion transport: adding plasticizing liquids into the polymer (see phase equilibria section), adding spherical nanoparticles into the system, or using a low molecular weight polymer with fumed silica nanoparticles. We use a combination of molecular dynamics and Langevin dynamics to calculate lithium diffusion in different regions of the system to gain an understanding of what optimizes lithium ion diffusion.
One part of our research is to improve Monte Carlo algorithms for the simulation of polymers. Polymer networks are very restricted in their movement, and novel connectivity-altering Monte Carlo techniques are being developed to improve the sampling of polymer network configuration.