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Abstract: The paper is a review of the combined group contribution (GC)–atom connectivity index (CI) approach for prediction of physical and thermodynamic properties of organic chemicals and their mixtures with special emphasis on lipids. The combined approach employs carefully selected datasets of different pure component properties to develop simultaneously two parallel models, one based on group contribution and another based on atom connectivity, for each property. The lipids present in the database are regarded as a separate class, for which special models for pure component properties, primary and temperature dependent, have been developed. For mixtures, properties related to phase equilibria are modeled with G E -based models (UNIQUAC, UNIFAC, NRTL, and combined UNIFAC-CI method). The collected phase equilibrium data for VLE and SLE have been tested for thermodynamic consistency together with a performance evaluation of the G E -models. The paper also reviews the role of the databases and the mathematical and thermodynamic consistency of the measured/estimated data and the predictive nature of the developed models. [Copyright &y& Elsevier]

Abstract: The aim of this work is to present revised and improved model parameters for group-contribution+ (GC+) models (combined group-contribution (GC) method and atom connectivity index (CI) method) employed for the estimation of pure component properties, together with covariance matrices to quantify uncertainties in the estimated property values. For this purpose, a systematic methodology for property modeling and uncertainty analysis of GC models and CI models using maximum-likelihood estimation theory is developed. For parameter estimation, large data-sets of experimentally measured property values of pure components of various classes (hydrocarbons, oxygenated components, nitrogenated components, poly-functional components, etc.) taken from the CAPEC database are used. In total 18 pure component properties are analyzed, namely normal boiling point, critical temperature, critical pressure, critical volume, normal melting point, standard Gibbs energy of formation, standard enthalpy of formation, normal enthalpy of fusion, enthalpy of vaporization at 298K, enthalpy of vaporization at the normal boiling point, entropy of vaporization at the normal boiling point, flash point, auto ignition temperature, Hansen solubility parameters, Hildebrand solubility parameter, octanol/water partition coefficient, acentric factor, and liquid molar volume at 298K. Important issues related to property modeling such as reliability and predictive capability of the property prediction models, and thermodynamic consistency of the predicted properties (such as, relation of normal boiling point versus critical temperature) are also analyzed and discussed. The developed methodology is simple, yet sound and effective and provides not only the estimated pure component property values but also the uncertainties (e.g. prediction errors in terms of 95% confidence intervals) in the estimated property values. This feature allows one to evaluate the effects of these uncertainties on product-process design, simulation and optimization calculations, contributing to better-informed and more reliable engineering solutions. [Copyright &y& Elsevier]