A critical evaluation of novel algorithms for the off-lattice Monte Carlo simulation of condensed polymer phases

Abstract

Novel composite algorithms for efficient off-lattice simulations of dense polymer phases are implemented and evaluated in the case of polyethylene in the united and explicit atom approximations. The simulation algorithms are based on combinations of traditional methods with recently developed Monte Carlo moves. The classical Metropolis Monte Carlo (MMC) and Reptation techniques are supplemented with the Continuum-Configuration Bias (CCB) and the Concerted-Rotation (CONROT) methods. Several extensions of the CONROT method, involving the simultaneous coordinated displacement of four to seven chain backbone sites, are developed and tested in this paper. CONROT-based methods enhance the performance of the algorithm at the level of local segmental motions, whereas the CCB component is important for the convergence of global properties, such as the relaxation of end-to-end distance vectors. The present composite algorithms are able to reproduce quite efficiently equilibrium thermodynamic properties, such as the density and the radial distribution function in the liquid state. However, they fail to generate completely equilibrated melts of long chains (polyethylene with 70 carbon atoms) at the molecular level. In spite of this shortcoming, we believe that these methods constitute the most promising currently available tools for the off-lattice simulation of realistic models of polymer melts and glasses. A satisfactory treatment of relatively long polyethylene chains (with up to 40 carbon atoms in the backbone, according to our estimates) is possible at experimental melt densities, both in the NVT and NPT ensembles.