QSPR generalization of activity coefficient models for predicting vapor–liquid equilibrium behavior

[1]  G. Pierotti,et al.  Activity Coefficients and Molecular Structure , 1959 .

[2]  C. Deal,et al.  Activity Coefficients and Molecular Structure. Activity Coefficients in Changing Environments-Solutions of Groups , 1962 .

[3]  J. Prausnitz,et al.  LOCAL COMPOSITIONS IN THERMODYNAMIC EXCESS FUNCTIONS FOR LIQUID MIXTURES , 1968 .

[4]  J. S. Rowlinson,et al.  Molecular Thermodynamics of Fluid-Phase Equilibria , 1969 .

[5]  J. Prausnitz,et al.  Statistical thermodynamics of liquid mixtures: A new expression for the excess Gibbs energy of partly or completely miscible systems , 1975 .

[6]  J. Gmehling Vapor-Liquid Equilibrium Data Collection , 1977 .

[7]  W. Arlt,et al.  Liquid-liquid equilibrium data collection , 1979 .

[8]  J. Gaube J. Gmehling, U. Onken, W. Arlt: Vapor-Liquid-Equilibrium Data Collection, in der Reihe: Chemistry Data Series, Vol. I. Parts 3 + 4 Aldehydes and Ketones Ethers, Dechema, Frankfurt 1979. 624 Seiten. Part 6a Aliphatic Hydrocarbons C4-C6, Dechema, Frankfurt , 1982 .

[9]  H. Renon N R T L: An empirical equation or an inspiring model for fluids mixtures properties? , 1985 .

[10]  R. Danner,et al.  A data base standard for the evaluation of vapor-liquid-equilibrium models , 1990 .

[11]  Jiding Li,et al.  A modified UNIFAC model. 2. Present parameter matrix and results for different thermodynamic properties , 1993 .

[12]  Status and results of group contribution methods , 1993 .

[13]  M. Karelson,et al.  QSPR: the correlation and quantitative prediction of chemical and physical properties from structure , 1995 .

[14]  Towards the development of a second-order approximation in activity coefficient models based on group contributions , 1996 .

[15]  G Schneider,et al.  Artificial neural networks for computer-based molecular design. , 1998, Progress in biophysics and molecular biology.

[16]  A. Klamt,et al.  Refinement and Parametrization of COSMO-RS , 1998 .

[17]  A. Sum,et al.  Use of ab initio methods to make phase equilibria predictions using activity coefficient models , 1999 .

[18]  Quantitative structure–property relationships and neural networks: correlation and prediction of physical properties of pure components and mixtures from molecular structure , 1999 .

[19]  A. Klamt,et al.  COSMO-RS: a novel and efficient method for the a priori prediction of thermophysical data of liquids , 2000 .

[20]  Subhash C. Basak,et al.  Quantitative Structure-Property Relationships (QSPRs) for the Estimation of Vapor Pressure: A Hierarchical Approach Using Mathematical Structural Descriptors , 2001, J. Chem. Inf. Comput. Sci..

[21]  Maurizio Fermeglia,et al.  Prediction of phase equilibria for binary mixtures by molecular modeling , 2001 .

[22]  A. Klamt,et al.  Prediction of infinite dilution activity coefficients using COSMO-RS , 2003 .

[23]  J. Prausnitz,et al.  Thermodynamics of Fluid-Phase Equilibria for Standard Chemical Engineering Operations (Anniversary Article) , 2004 .

[24]  R. L. Robinson,et al.  SVRC–QSPR model for predicting saturated vapor pressures of pure fluids , 2006 .