Development of an EOS based on lattice cluster theory for pure components

被引:18
|
作者
Langenbach, K. [1 ]
Enders, S. [1 ]
机构
[1] TU Berlin, Fachgebiet Thermodynam & Therm Verfahrenstech, D-10587 Berlin, Germany
关键词
Lattice cluster theory; Equation of state; Branched molecules; Heat of evaporation; Vapour-liquid equilibrium; EQUATION-OF-STATE; MULTICOMPONENT POLYMER BLENDS; PRESSURE PHASE-EQUILIBRIA; MONTE-CARLO SIMULATIONS; VAPOR-LIQUID-EQUILIBRIA; CHAIN MOLECULE LIQUIDS; THERMODYNAMIC PROPERTIES; MONOMER STRUCTURE; SAFT EQUATION; STATISTICAL THERMODYNAMICS;
D O I
10.1016/j.fluid.2012.06.022
中图分类号
O414.1 [热力学];
学科分类号
摘要
In many industrial applications, like tissue fabric production, osmotic separation, but also tissue engineering in medical laboratories, the knowledge of polymer behaviour is of vital importance. This behaviour is partially well known, but often the underlying mechanisms are not understood to a degree, which would make a prediction of polymer behaviour possible based on short and long chain branching, as well as general architecture. The Lattice Cluster Theory (LCT) of Freed and co-workers makes it possible to describe the influence of molecules' architecture on the free energy of mixtures containing them. As possible functional groups (e.g. acidic groups) or permanent dipole or multi-pole moments are not accounted for by the LCT, this article will deal with linear and branched alkanes in order to test its applicability on the calculation of thermodynamic properties of these common compounds. To model the influence of pressure on phase behaviour, the LCT is transformed to a lattice gas equation of state. As is usual in lattice gas theories, the influence of free volume, and hence density will be modelled by the introduction of a non-interacting species of the size of one lattice site (hole). This approach yields the Lattice Cluster Theory Equation of State (LCT-EOS). The LCT-EOS pure component parameters are fit to the experimental data of several n-alkanes. Using only these parameters, fit to linear alkanes, the vapour pressure of a branched alkane is predicted accurately. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:58 / 79
页数:22
相关论文
共 50 条
  • [1] Viscosity model for pure liquids based on eyring theory and cubic EOS
    Macías-Salinas, R
    García-Sánchez, F
    Hernández-Garduza, O
    AICHE JOURNAL, 2003, 49 (03) : 799 - 804
  • [2] Cluster density functional theory for lattice models based on the theory of Mobius functions
    Lafuente, L
    Cuesta, JA
    JOURNAL OF PHYSICS A-MATHEMATICAL AND GENERAL, 2005, 38 (34): : 7461 - 7482
  • [3] The range of validity of the lattice cluster theory
    Quinn, B
    Gujrati, PD
    JOURNAL OF CHEMICAL PHYSICS, 1999, 110 (02): : 1299 - 1306
  • [4] METHOD OF CLUSTER COMPONENTS IN THEORY OF SOLUTIONS
    MEN, AN
    BOGDANOV.MP
    VOROBEV, YP
    DOBROVIN.RY
    CHUFAROV, GI
    DOKLADY AKADEMII NAUK SSSR, 1969, 188 (01): : 141 - &
  • [5] GROWTH OF A NITROGEN DEFECT CLUSTER IN A BCC LATTICE EXAMINED BY A LATTICE THEORY
    WATANABE, Y
    SATO, A
    MURA, T
    JOURNAL OF PHYSICS AND CHEMISTRY OF SOLIDS, 1989, 50 (09) : 957 - 961
  • [6] General heatbath algorithm for pure lattice gauge theory
    Johnson, Robert W.
    PHYSICAL REVIEW D, 2010, 82 (11):
  • [7] METHOD OF CLUSTER COMPONENTS IN THEORY OF ORDERING ALLOYS
    BOGDANOV.MB
    VOROBYEV, YP
    MEN, AN
    CHUFAROV, GI
    PHYSICS OF METALS AND METALLOGRAPHY-USSR, 1970, 30 (03): : 184 - &
  • [8] Analysis of Interfacial Transport Resistivities of Pure Components and Mixtures Based on Density Functional Theory
    Klink, Christoph
    Waibel, Christian
    Gross, Joachim
    INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2015, 54 (45) : 11483 - 11492
  • [9] DEVELOPMENT OF THEORY OF A NONLINEAR LATTICE
    TODA, M
    SUPPLEMENT OF THE PROGRESS OF THEORETICAL PHYSICS, 1976, (59): : 1 - 35
  • [10] Application of the Concept Lattice Based on Principal Components in the Evaluation of Regional Logistics Development
    Guo, Jianhong
    Qian, Lianwen
    2013 NINTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION (ICNC), 2013, : 70 - 74