Autor: |
van 't Hof, A., Peters, C. J., de Leeuw, S. W. |
Předmět: |
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Zdroj: |
Journal of Chemical Physics; 2/7/2006, Vol. 124 Issue 5, p054906, 19p, 2 Charts, 13 Graphs |
Abstrakt: |
The conventional Gibbs-Duhem integration method is very convenient for the prediction of phase equilibria of both pure components and mixtures. However, it turns out to be inefficient. The method requires a number of lengthy simulations to predict the state conditions at which phase coexistence occurs. This number is not known from the outset of the numerical integration process. Furthermore, the molecular configurations generated during the simulations are merely used to predict the coexistence condition and not the liquid- and vapor-phase densities and mole fractions at coexistence. In this publication, an advanced Gibbs-Duhem integration method is presented that overcomes above-mentioned disadvantage and inefficiency. The advanced method is a combination of Gibbs-Duhem integration and multiple-histogram reweighting. Application of multiple-histogram reweighting enables the substitution of the unknown number of simulations by a fixed and predetermined number. The advanced method has a retroactive nature; a current simulation improves the predictions of previously computed coexistence points as well. The advanced Gibbs-Duhem integration method has been applied for the prediction of vapor-liquid equilibria of a number of binary mixtures. The method turned out to be very convenient, much faster than the conventional method, and provided smooth simulation results. As the employed force fields perfectly predict pure-component vapor-liquid equilibria, the binary simulations were very well suitable for testing the performance of different sets of combining rules. Employing Lorentz-Hudson-McCoubrey combining rules for interactions between unlike molecules, as opposed to Lorentz-Berthelot combining rules for all interactions, considerably improved the agreement between experimental and simulated data. [ABSTRACT FROM AUTHOR] |
Databáze: |
Complementary Index |
Externí odkaz: |
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