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	Study on analytical solutions and their simplification for one-component multi-Yukawa fluids and test by Monte-Carlo simulation
	Yang-Zheng Lin ; Yi-Gui Li ; Jiu-Fang Lu
	2010-05-07 ; 2010-05-07
关键词	Theoretical or Mathematical/ colloids compressibility electrolytes equations of state liquid theory microemulsions Monte Carlo methods/ analytical solutions one-component multiYukawa fluids Monte-Carlo simulation mean spherical approximation analytical equation of state nondimensional variables linear summation method compressibility factor colloid dispersion system micelles microemulsion electrolyte solution/ A6120J Computer simulation of static and dynamic liquid behaviour A6210 Mechanical properties of liquids A8270D Colloids A8270K Emulsions and suspensions
中文摘要	Using the mean spherical approximation, an explicit analytical equation of state with non-dimensional variables for one-component multi-Yukawa fluids is established based on the work of Blum and Ubriaco. Two simplified calculation methods (one is the linear summation method and the other is the negligible entropy method) are proposed. The compressibility factors for one-component 1-4 Yukawa fluids are simulated with the Monte-Carlo method. Comparisons between various methods under different range parameters are listed and discussed for 1-4 Yukawa fluids. These indicate that our methods are reliable for a wide range of parameters and can be used conveniently.
语种	英语 ; 英语
出版者	Taylor & Francis ; UK
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/17894]
专题	清华大学
推荐引用方式 GB/T 7714	Yang-Zheng Lin,Yi-Gui Li,Jiu-Fang Lu. Study on analytical solutions and their simplification for one-component multi-Yukawa fluids and test by Monte-Carlo simulation[J],2010, 2010.
APA	Yang-Zheng Lin,Yi-Gui Li,&Jiu-Fang Lu.(2010).Study on analytical solutions and their simplification for one-component multi-Yukawa fluids and test by Monte-Carlo simulation..
MLA	Yang-Zheng Lin,et al."Study on analytical solutions and their simplification for one-component multi-Yukawa fluids and test by Monte-Carlo simulation".(2010).

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