Monte Carlo simulations mean-field theories

FIG. 9 Changes of the monolayer film critical temperature with the concentration of impurities obtained from the Monte Carlo simulations (open circles) and resulting from the mean field theory (solid line). (Reprinted from A. Patrykiejew. Monte Carlo studies of adsorption. II Localized monolayers on randomly heterogeneous surfaces. Thin Solid Films, 205 189-196, with permision from Elsevier Science.)... 

Dodd, L. R. and Theodorou, D. N. Atomistic Monte Carlo Simulation and Continuum Mean Field Theory of the Structure and Equation of State Properties of Alkane and Polymer Melts. Vol 116,pp, 249-282,... 

Most of the theories were based on the self-consistent mean field approximation.12-32 The other ones include the scaling analysis, - molecular dynamics simulations and Monte Carlo simulations.40,41 The self-consistent mean field theories12-32 were developed along the following three lines (1) on the basis of a lattice model,12-22 (2) on the basis of a diffusion type equation,23-28 and (3) analytical approaches.29-32... 

In the current paper, we discuss some of the new approaches and results that have been developed and obtained recently within the context of such molecular modeling research, and in particular with the mean field and Monte Carlo studies of a lattice model. The next section describes the Gaussian random field method (Woo et al, 2001), which provides a computationally efficient route to generate realistic representations of the disordered mesoporous glasses. Application of the mean field theory, and Monte Carlo simulations are described in Secs. 3 and 4, respectively. 

Our overall conclusion, therefore, is that for mesoporous glasses adsorption, hysteresis is a dynamic phenomenon that is not simply related to a capillary vapor-liquid phase transition. Slow dynamics for long times makes the states accessible in experiments in the hysteresis loop appear equilibrated and quite reproducible. Mean field theory and Monte Carlo simulations in the grand ensemble provide a physically realistic description of these phenomena. 

One advantage of these Monte Carlo simulations is that both the thermodynamic and structural properties of the binary polymer mixture are simultaneously accessible, and can quantitatively be compared to analytic approaches. The mean field theory of polymers makes detailed predictions for the bulk [68-70] and interface properties [71-77] as a function of the incompatibility, 1 the spatial extension of the molecules as measured by the root mean squared end-to-end distance of the Gaussian coils, and the... 

A quantitative comparison between the mean field prediction and the Monte Carlo results is presented in Fig. 15. The main panel plots the inverse scattering intensity vs. xN. At small incompatibility, the simulation data are compatible with a linear prediction (cf. (48)). From the slope, it is possible to estimate the relation between the Flory-Huggins parameter, x, and the depth of the square well potential, e, in the simulations of the bond fluctuation model. As one approaches the critical point of the mixture, deviations between the predictions of the mean field theory and the simulations become apparent the theory cannot capture the strong universal (3D Ising-like) composition fluctuations at the critical point [64,79,80] and it underestimates the incompatibility necessary to bring about phase separation. If we fitted the behavior of composition fluctuations at criticality to the mean field prediction, we would obtain a quite different estimate for the Flory-Huggins parameter. 

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