Variable Connectivity Method for the Atomistic Monte Carlo Simulation of Polydisperse Polymer Melts

Abstract

A new Monte Carlo algorithm for the simulation of atomistically detailed polymer melts is presented. The method introduces connectivity relationships as variables in the description of the polymer. The connectivity of the polymer is altered in Monte Carlo moves that satisfy the detailed constraints of molecular geometry. Connectivity-altering moves are seen to induce large jumps in the configuration space of the bulk polymer, thereby greatly enhancing the efficiency with which molecular configurations are sampled. Simulations are carried out in a semigrand ensemble in which the chain length distribution is controlled by a spectrum of chemical potentials. Limiting chain length distributions are derived and compared with simulation results. Volumetric and structural predictions of the method are found to be in agreement with previous work.

Polymer–particle mixtures: Depletion and packing effects

“…As we move to longer molecules, reptation becomes less efficient, rendering the relaxation of these systems slower (Nϭ32 compared to Nϭ16). Intermolecular bridging moves such as double rebridging, however, equilibrate longer chain systems faster; 27,28 this is illustrated in Fig. 2, where the calculated autocorrelation functions for Nϭ32 and Nϭ120 are compared.…”

“…24 -26 Systems of long macromolecules ͑linear polyethylene chains of 6000 monomers͒ have been recently studied in atomistic detail by using advanced Monte Carlo techniques i.e., end-bridging 27,28 with parallel domain decomposition. 29,30 End-bridging has been shown capable of equilibrating a variety of polymeric melts by altering chain connectivity and consequently leading to a controlled polydispersity.…”

“…29,30 End-bridging has been shown capable of equilibrating a variety of polymeric melts by altering chain connectivity and consequently leading to a controlled polydispersity. 27,28,[31][32][33][34] The double rebridging move, which is an extension of connectivity altering moves, has the advantage of maintaining monodispersity in the systems studied. 35 Polyethylene chains have been recently simulated using a configurational bias double rebridging method that is easily applicable to a variety of polymeric systems.…”

A new double-rebridging technique for linear polyethylene

“…To overcome these limitations, Theodorou and coworkers have proposed connectivity altering MC moves [1][2][3][4][5][6][7] that improve the relaxation of long-range modes, namely the end-to-end autocorrelation function. In one such move, the connectivity of inner segments of a molecule is exchanged between two polymer chains, thereby resulting in a drastic change in the end-to-end vector in a single move.…”

Improving the sampling efficiency of Monte Carlo molecular simulations: an evolutionary approach

“…In the field of Monte Carlo (MC) simulations of complex molecular systems, such as polymers in dense amorphous phase, much effort is currently being undertaken for the design of more efficient new MC schemes [1][2][3]. These researches are motivated by the fact that with the increase in size and complexity of molecules, the potential energy surface of such systems is characterized by numerous local minima separated by very high barriers, hence this energy surface is difficult to sample either along the trajectories obtained from direct molecular dynamics or through conventional Markovian Monte Carlo simulations.…”