Abstract:
We propose new schemes for integrating the
stochastic differential equations of dissipative particle
dynamics (DPD) in simulations of dilute polymer solutions.
The hybrid DPD models consist of hard potentials
that describe the microscopic dynamics of polymers and
soft potentials that describe the mesoscopic dynamics of the solvent.
In particular, we develop extensions to the velocity-Verlet and Lowe's
approaches - two representative DPD time-integrators -- following a
subcycling procedure whereby the solvent is advanced with
a timestep much larger than the one employed in the polymer time-integration.
The introduction of relaxation parameters allows optimization
studies for accuracy while maintaining the low computational
complexity of standard DPD algorithms. We demonstrate
through equilibrium simulations that a ten-fold gain in efficiency
can be obtained with the time-staggered algorithms
without loss of accuracy compared to the non-staggered
schemes. We then apply the new approach to investigate the
scaling response of polymers in equilibrium as well as
the dynamics
of lambda-phage DNA molecules subjected to shear.