Reverse Monte Carlo procedure for cluster analysis in colloidal systems

Abstract

We examine the applicability of reverse Monte Carlo (RMC) simulations for studying cluster size and bond angle distributions in dense colloidal dispersions. Forward Monte Carlo simulations are used to generate radial distribution functions for a dispersion interacting through an attractive potential. These are then used for reconstructing the microstructural details in the dispersion using RMC simulations. We find that the RMC method accurately reproduces structures that are statistically identical to the test system over a range of length scales. Both cluster size distributions and bond angle distributions are reproduced within statistical accuracy. The results demonstrate that X-ray, neutron and light scattering data on the structure of dispersions (under static or dynamic conditions) can be used for extracting microstructural information that cannot be obtained by direct means.