Building Polymers Using CCBB Monte Carlo

Ryan Martin, Guofeng Wang, William A. Goddard III

(Click on title for full talk)




        When building polymer systems for long term dynamic simulations it is important to generate a polymer structure as close to the equilibrium structure for the system as possible in order to reduce the simulation time necessary for the system to reach equilibrium and generate the valid simulations we are looking for.  Current methods for generating polymer systems, especially dendrimeric or hyper-branched systems, are either time consuming, minimizing each generation before adding the next monomer, or give high energy overlaps that require large equilibration times.
        The continuous configurational Boltzmann biased direct Monte Carlo(CCBB-DMC) method generates an ensemble of relatively low energy structures without high energy overlaps through a series of randomly chosen torsion angles weighted by the torsion energy function and the local Van der Waals environment of the torsional clusters.  From this ensemble can be chosen a series of polymer structures to be used as starting points for long term dynamics simulations, thus reducing the time necessary for the system to equilibrate and return valid results.
 
 

Supporting Agencies

ARO-MURI
ARO-ASSERT
ARO-DURIP
NSF NPACI