Molecular simulation of phase equilibria for mixtures of polar and non-polar components

J. J. Potoff, J. R. Errington, A. Z. Panagiotopoulos

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Abstract

Grand canonical histogram-reweighting Monte Carlo simulations were used to obtain the phase behaviour of several binary mixtures. The main goal of this work was to test the predictive capabilities of recently developed intermolecular potential models that accurately reproduce the phase behaviour of pure components. These united-atom potentials utilize the exponential-6 functional form for repulsive and dispersion interactions and fixed point charges for electrostatic interactions. The mixtures studied were n-pentane—methane, ethane—CO2, propane—CO2, n-pentane-CO2, H2O-ethane, CH3OH-n-hexane and CH3OH-CO2. The conventional Lorentz-Berthelot combining rules, as well as a set of combining rules due to Kong (1973, J. chem. Phys., 59, 2464) were used to obtain unlike-pair potential parameters. The Lorentz—Berthelot rules generally result in more attractive unlike-pair interactions than the Kong rules. For the n-alkane—CO2 systems, predicted phase diagrams are in excellent agreement with experiment when the Kong combining rules are used. For mixtures with CH3OH and H2O, the Lorentz—Berthelot rules yield better agreement with experiment than the Kong rules, but statistically significant differences remain. Our results suggest that relatively simple intermolecular potential models can be used to predict the phase behaviour of broad classes of binary systems. For mixtures with large differences in polar character of the components, however, present models do not predict the phase behaviour in quantitative agreement with experiment. New models that include higher order interactions such as polarizability may be suitable for this purpose, a hypothesis that will need to be tested in the future.

Original languageEnglish (US)
Pages (from-to)1073-1083
Number of pages11
JournalMolecular Physics
Volume97
Issue number10
DOIs
StatePublished - Nov 1999
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Biophysics
  • Molecular Biology
  • Condensed Matter Physics
  • Physical and Theoretical Chemistry

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