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Direct Evaluation of Multi-Component Phase Equilibria Using Flat-Histogram Methods

Published

Author(s)

Jeffrey R. Errington, Vincent K. Shen

Abstract

We present a method for directly locating density-driven phase transitions in multi-component systems. Phase coexistence conditions are determined through manipulation of a total density probability distribution evaluated over a density range that includes both coexisting phases. Saturation quantities are determined through appropriate averaging of density-dependent mean values of a given property of interest. We discuss how to implement the method in both the grand canonical and isothermal-isobaric semigrand ensembles. Calculations can be conducted using any of the recently-introduced flat histogram techniques. Here, we combine the general algorithm with a transition-matrix approach to produce an efficient self-adaptive technique for determining multi-component phase equilibrium properties. To assess the performance of the new method, we generate phase diagrams for a number of binary and ternary Lennard-Jones mixtures.
Citation
Journal of Chemical Physics
Volume
123

Keywords

molecular simulation, monte carlo, phase equilibria, statistical mechanics

Citation

Errington, J. and Shen, V. (2005), Direct Evaluation of Multi-Component Phase Equilibria Using Flat-Histogram Methods, Journal of Chemical Physics (Accessed February 21, 2024)
Created September 30, 2005, Updated October 12, 2021