Monte Carlo simulations structure

Clusters of Monte Carlo simulation Structures of assemblies, dynamic evolution of... 

A multitude of different variants of this model has been investigated using Monte Carlo simulations (see, for example [M])- The studies aim at correlating the phase behaviour with the molecular architecture and revealing the local structure of the aggregates. This type of model has also proven useful for studying rather complex structures (e.g., vesicles or pores in bilayers). 

Lattice models have been studied in mean field approximation, by transfer matrix methods and Monte Carlo simulations. Much interest has focused on the occurrence of a microemulsion. Its location in the phase diagram between the oil-rich and the water-rich phases, its structure and its wetting properties have been explored [76]. Lattice models reproduce the reduction of the surface tension upon adsorption of the amphiphiles and the progression of phase equilibria upon increasmg the amphiphile concentration. Spatially periodic (lamellar) phases are also describable by lattice models. Flowever, the structure of the lattice can interfere with the properties of the periodic structures. 

Monte Carlo simulations are an efficient way of predicting liquid structure, including the preferred orientation of liquid molecules near a surface. This is an efficient method because it is not necessary to compute energy derivatives, thus reducing the time required for each iteration. The statistical nature of these simulations ensures that both enthalpic and entropic effects are included. 

A sequence of successive configurations from a Monte Carlo simulation constitutes a trajectory in phase space with HyperChem, this trajectory may be saved and played back in the same way as a dynamics trajectory. With appropriate choices of setup parameters, the Monte Carlo method may achieve equilibration more rapidly than molecular dynamics. For some systems, then, Monte Carlo provides a more direct route to equilibrium structural and thermodynamic properties. However, these calculations can be quite long, depending upon the system studied. 

Monte Carlo simulations are commonly used to compute the average thermodynamic properties of a molecule or a system of molecules, and have been employed extensively in the study of the structure and equilibrium properties of liquids and solutions. Monte Carlo methods have also been used to conduct conformational searches under non-equilibrium conditions. 

Within the framework of Monte Carlo simulations, the relation between measurable quantities and the microscopic structure of confined phases can now be examined. An example of such a measurable quantity is the solvation force F h)/2 KR (see Sec. IIA 1). From a theoretical perspective and according to the discussion in Sec. IIA 3 its investigation requires the stress T zisz) exerted normally by a confined fluid on planar substrates [see Eqs. (19) and (22)]. Using Eqs. (11) and (53) one can derive a molecular expression for Tzz from... 

Finally, in Sec. IV, two examples of the application of the Monte Carlo simulation to investigate the structure and thermodynamic properties of adlayers of an associating fluid are given. The results of simulations are compared with those from theoretical approaches. In conclusion, we discuss some methodological perspectives in the discussed area of research. 

K. F. Mansfield, D. N. Theodoru. Interfacial structure and dynamics of macromolecular liquids A Monte Carlo simulation approach. Macromolecules 22 3143-3152, 1989. 

M. J. Vlot, S. Claassen, H. E. Huitema, J. P. v. d. Eerden. Monte Carlo simulation of racemic liquid mixtures thermodynamic properties and local structures. Mol Phys 97 19, 1997 M. J. Vlot, J. C. v. Miltenburg, H. A. Oonk, J. P. V. d. Eerden. Phase diagrams of scalemic mixtures. J Chem Phys 707 10102, 1997. 

In all these examples, the importance of good simulation and modeling cannot be stressed enough. A variety of methods have been used in this field to simulate the data in the cases studies described above. Blander et al. [4], for example, used a semi-empirical molecular orbital method, MNDO, to calculate the geometries of the free haloaluminate ions and used these as a basis for the modeling of the data by the RPSU model [12]. Badyal et al. [6] used reverse Monte Carlo simulations, whereas Bowron et al. [11] simulated the neutron data from [MMIM]C1 with the Empirical Potential Structure Refinement (EPSR) model [13]. 

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