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Pair correlation function integrals: Computation and use

delete2011-08-24
delete13
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OA
AI
R
Rasmus Wedberg
J
John P. O’Connell
G
Günther H. Peters
J
Jens Abildskov *
DOI:10.1063/1.3626799delete
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摘要

摘要

En 中文
We describe a method for extending radial distribution functions obtained from molecular simulations of pure and mixed molecular fluids to arbitrary distances. The method allows total correlation function integrals to be reliably calculated from simulations of relatively small systems. The long-distance behavior of radial distribution functions is determined by requiring that the corresponding direct correlation functions follow certain approximations at long distances. We have briefly described the method and tested its performance in previous communications [R. Wedberg, J. P. O'Connell, G. H. Peters, and J. Abildskov, Mol. Simul. 36, 1243 (2010); Fluid Phase Equilib. 302, 32 (2011)], but describe here its theoretical basis more thoroughly and derive long-distance approximations for the direct correlation functions. We describe the numerical implementation of the method in detail, and report numerical tests complementing previous results. Pure molecular fluids are here studied in the isothermal-isobaric ensemble with isothermal compressibilities evaluated from the total correlation function integrals and compared with values derived from volume fluctuations. For systems where the radial distribution function has structure beyond the sampling limit imposed by the system size, the integration is more reliable, and usually more accurate, than simple integral truncation. (C) 2011 American Institute of Physics. [doi:10.1063/1.3626799]
Keyword:
FLUCTUATION SOLUTION THEORY
RADIAL-DISTRIBUTION FUNCTIONS
MONTE-CARLO-SIMULATION
GIBBS FREE-ENERGY
FORCE-FIELD
MOLECULAR SIMULATIONS
COMPUTER-SIMULATION
LIQUID-EQUILIBRIA
LENNARD-JONES
FLUIDS

期刊

Journal of Chemical Physics 封面图
Journal of Chemical Physics
IF:
3.1
论文数:
7.2W
被引数:
23.2W

机构

U
University of Virginia
学者数:
3.0W
论文数: 2.7W
被引数: 4.1W
T
technical university of denmark
学者数:
2.6W
论文数: 2.8W
被引数: 37
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