Improved Quantitative Structure Property Relationship Models for Infinite-Dilution Activity Coefficients of Aqueous Systems

Phase equilibrium data are essential for the proper design and operation of most chemical processes. When experimental data are unavailable, thermodynamic models, such as group contribution methods, are used to predict phase equilibrium. The accuracy of these models in predicting infinite-dilution activity coefficients (γ ∞ ) of aqueous systems is questionable. Moreover, model development is hampered by a lack of (a) γ ∞ data at temperatures above 300 K, and (b) γ ∞ data for water in hydrocarbon systems. Using quantitative structure-property relationships (QSPR), mathematical models are developed relating the structure of a diverse set of organic molecules to γ ∞ values for hydrocarbons in water and water in hydrocarbons. The database used for this study contains over 1400 data points at temperatures ranging from 283.2 to 373.2 K. The data include both direct and indirect measurements for a variety of hydrocarbons, which include alkanes, alkenes, aromatics, halogenates, alcohols, phenols, aldehydes, ketones, acids, esters, ethers, amines, amides, nitriles, nitro compounds, and sulfur compounds. QSPR models were developed using linear as well as non-linear modeling tools, and results indicate these models are satisfactory in correlating single temperature aqueous solubility data, but fail when correlating multiple temperature data. A suitable theoretical backbone, which could account for the effect of temperature on solubility, was required. Bader and Gasem (1993), previously at OSU, had developed an equation of state (EOS) to correlate γ ∞ of aqueous systems, however, the parameters used in this EOS could not be generalized satisfactorily. Structure based generalizations were developed for these parameters using existing QSPR tools, and preliminary results indicate this combined approach of an EOS to account for temperature effects and structure based parameter generalizations provide accurate estimates for γ ∞