Fast off-lattice Monte Carlo simulations with "soft" repulsive potentials.
The basic idea of fast off-lattice Monte Carlo (FOMC) simulations is to use "soft" repulsive potentials that allow particle overlapping in continuum Monte Carlo (MC) simulations. For multichain systems, this gives much faster chain relaxation and better sampling of the configurational space than conventional molecular simulations using "hard" excluded-volume interactions that prevent particle overlapping. Such coarse-grained models are particularly suitable for the study of equilibrium properties of soft materials. Since soft potentials are commonly used in polymer field theories, it is another advantage of FOMC simulations that using the same Hamiltonian in both FOMC simulations and the theories enables quantitative comparisons between them without any parameter fitting to unambiguously reveal the consequences of approximations in the theories. Moreover, FOMC simulations can be performed with various chain models and in any statistical ensemble, and all the advanced off-lattice MC techniques proposed to date can be implemented to further improve the sampling efficiency. We have performed canonical-ensemble FOMC simulations with an isotropic soft pair potential for three systems: we first used (small-molecule) soft spheres to demonstrate the improved sampling of FOMC simulations over conventional molecular simulations; we then used single-chain simulations to show that the effects of excluded-volume interactions can be well captured by the soft repulsive potential; finally, for compressible homopolymer melts, we compared FOMC results with those under the random-phase approximation to demonstrate that FOMC simulations can be used to unambiguously and quantitatively reveal the fluctuation/correlation effects in the system. In addition, we examined in detail in our single-chain simulations the spatial discretization scheme used in all previous FOMC simulations.
Wang
Qiang
Q
Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, Colorado 80523-1370, USA. q.wang@colostate.edu
Yin
Yuhua
Y