1996
DOI: 10.1016/0370-1573(96)00011-7
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Integral equation theory description of phase equilibria in classical fluids

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Cited by 256 publications
(264 citation statements)
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“…(9) given by the PY expression for the hardsphere fluid bridge function at the same density [42,43] -is also reported in…”
Section: Replymentioning
confidence: 75%
“…(9) given by the PY expression for the hardsphere fluid bridge function at the same density [42,43] -is also reported in…”
Section: Replymentioning
confidence: 75%
“…It is meanwhile well-known and widely documented that conventional integral equation theories -such as the Percus-Yevick (PY), the hypernetted chain (HNC), or the mean spherical (MSA) approximation -are thermodynamically inconsistent, which means that the various thermodynamic routes to calculate the dimensionless equation of state lead to significantly different results 1,2 . Over the past decades considerable effort has been devoted to the formulation of thermodynamically selfconsistent liquid state theories, which, in turn, have led to an improved description of the structural and thermodynamic properties of liquids with harshly repulsive potentials.…”
Section: Introductionmentioning
confidence: 99%
“…The subject of integral equation theory is one of the richest and broadest branches of statistical mechanics. Detailed reviews on this issue may be found in the literature (BARKER; HENDERSON, 1976;CACCAMO, 1996). Therefore, we shall give only a simple preamble to this topic, including solely the theories from which the structure factors have been used to interpret scattering intensities of proteins into aqueous solutions.…”
Section: Prolegomena To Integral Equation Theorymentioning
confidence: 99%
“…However, this equation can only be solved by using approximations known as closure relations. A review on this subject can be found in Caccamo (CACCAMO, 1996). One of these closure relations, which results in analytical solutions for simple interparticle potentials, was formulated by Percus and Yevick (PERCUS;YEVICK, 1958).…”
Section: Monte Carlo Algorithmmentioning
confidence: 99%
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