Monte Carlo simulations complex fluids

To conclude, the introduction of species-selective membranes into the simulation box results in the osmotic equilibrium between a part of the system containing the products of association and a part in which only a one-component Lennard-Jones fluid is present. The density of the fluid in the nonreactive part of the system is lower than in the reactive part, at osmotic equilibrium. This makes the calculations of the chemical potential efficient. The quahty of the results is similar to those from the grand canonical Monte Carlo simulation. The method is neither restricted to dimerization nor to spherically symmetric associative interactions. Even in the presence of higher-order complexes in large amounts, the proposed approach remains successful. 

M. P. Allen, Introduction to Monte Carlo simulations. In Observation, Prediction and Simulation of Phase Transitions in Complex Fluids, M. Bans, L. F. Rull, and J.- P Ryckaert, Eds., Kluwer Academic Publishers, Boston, 1995, 339-356. 

Quantum mechanical calculations on small clusters can also provide interatomic potentials which can then be used to predict the stabilities of complexes in bulk fluids using classical molecular dynamics or Monte Carlo simulations. Such calculations can be very successful in predicting metal speciation and equations of state of complex electrolytes. In this chapter I will first outline the theoretical approximations used in the quantum chemistry of metal complexes. In parts two and three, I will illustrate the... 

Brownian Dynamics Monte Carlo Simulations for Complex Fluids. 

Aqueous Interfaces Force Fields A Brief Introduction Force Fields A General Discussion Free Energy Changes in Solution Free Energy Simulations Intermolecular Interactions by Perturbation Theory Monte Carlo Simulations for Complex Fluids Monte Carlo Simulations for Polymers OPLS Force Fields Supercritical Water and Aqueous Solutions Molecular Simulation. 

Designing an effective recipe to conduct a Monte Carlo simulation of a simple fluid is, in most situations, fairly straightforward (see Monte Carlo Simulations for Complex Fluids and Monte Carlo Simulations for Liquids). Unfortunately, as the number of internal degrees of freedom of a molecule increases, so does the complexity of the Monte Carlo recipe. This article is intended to provide an overview of several algorithms that have been devised to surmount some of the difficulties associated with the simulation of polymeric fluids. 

To some extent, this article also illustrates that, over the. last decade, Monte Carlo methods for simulation of complex fluids have evolved significantly. Their advent has led to computational efficiency gains of several orders of magnitude. As a result, the problems that can be addressed today by Monte Carlo simulation are significantly more involved than those investigated just a few years ago. 

Monte Carlo Simulations for Complex Fluids Monte Carlo Simulations for Liquids Polymer Brushes Polymers Melts and Blends. 

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