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Previously we have shown how to obtain the electric properties of a polymer or other periodic system at the coupled Hartree–Fock level by direct, analytical calculation rather than by extrapolati...
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Soft ellipsoid model for Gaussian polymer chains
A soft ellipsoid model for Gaussian polymer chains is studied, following an idea proposed by Murat and Kremer [J. Chem. Phys. 108, 4340 (1998)]. In this model chain molecules are mapped onto ellipsoid...

Phase behavior of monomeric mixtures and polymer solutions with soft interaction potentials

J. Chem. Phys. 114, 7644 (2001); doi:10.1063/1.1362298

Issue Date: 1 May 2001

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C. M. Wijmans and B. Smit
Department of Chemical Engineering, University of Amsterdam, Nieuwe Achtergracht 166, 1018 WV Amsterdam, The Netherlands

R. D. Groot
Unilever Research Vlaardingen, Olivier van Noortlaan 120, 3133 AT Vlaardingen, The Netherlands
We present Gibbs ensemble Monte Carlo simulations of monomer–solvent and polymer–solvent mixtures with soft interaction potentials, that are used in dissipative particle dynamics simulations. From the simulated phase behavior of the monomer–solvent mixtures one can derive an effective Flory–Huggins chi-parameter as a function of the particle interaction potential. We show that this chi-parameter agrees very well with the free energy difference between a monomer surrounded by solvent particles, and a solvent particle surrounded by solvent particles. We develop a new "identity change" Monte Carlo move to equilibrate the polymer–solvent mixtures. In this move a polymer chain from one box is exchanged with an equal number of solvent particles from the other box. At realistic densities this new move offers a large computational advantage over the convential insertion method for a polymer chain using a configurational bias Monte Carlo algorithm. The new algorithm is demonstrated for polymer–solvent mixtures with a chain length of up to 150 segments. Significant differences are found between the simulated polymer–solvent phase behavior and results predicted by mean-field theory. Finally, we fit a master–equation to the simulated binodal curves at different chain lengths. This function is used to make a quantitative comparison between the simulations and experimental data for the phase equilibrium of the polystyrene–methylcyclohexane system. ©2001 American Institute of Physics.
History: Received 6 December 2000; accepted 14 February 2001
Permalink: http://link.aip.org/link/?JCPSA6/114/7644/1
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KEYWORDS and PACS

Keywords
PACS
  • 64.75.+g
    Equations of state, phase equilibria, and phase transitions Solubility, segregation, and mixing; phase separation
  • 47.50.+d
    Fluid dynamics Non-Newtonian fluid flows
  • 61.25.Hq
    Structure of solids and liquids; crystallography Studies of specific liquid structures Macromolecular and polymer solutions; polymer melts; swelling
  • 02.50.Ng
    Mathematical methods in physics Probability theory, stochastic processes, and statistics Distribution theory and Monte Carlo studies
  • 05.10.Ln
    Statistical physics, thermodynamics, and nonlinear dynamical systems Computational methods in statistical physics and nonlinear dynamics Monte Carlo methods
  • 65.20.+w
    Thermal properties of condensed matter Thermal properties of liquids: heat capacity, thermal expansion, etc.
  • YEAR: 2001

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PUBLICATION DATA

ISSN:
0021-9606 (print)   1089-7690 (online)
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