Configurational bias Monte Carlo: a new sampling scheme for flexible chains

1992/01/01 by Jörn Ilja Siepmann, Daan Frenkel · 37 citations
Materials Science · Engineering · #Material Dynamics and Properties #Phase Equilibria and Thermodynamics #Block Copolymer Self-Assembly

paper · doi:10.1080/00268979200100061

Abstract

We propose a novel approach that allows efficient numerical simulation of systems consisting of flexible chain molecules. The method is especially suitable for the numerical simulation of dense chain systems and monolayers. A new type of Monte Carlo move is introduced that makes it possible to carry out large scale conformational changes of the chain molecule in a single trial move. Our scheme is based on the selfavoiding random walk algorithm of Rosenbluth and Rosenbluth. As an illustration, we compare the results of a calculation of mean-square end to end lengths for single chains on a two-dimensional square lattice with corresponding data gained from other simulations.

Citations

• Nonergodicity of local, length-conserving Monte Carlo algorithms for the self-avoiding walk

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