A QSPR study of infinite dilution activity coefficients of organic compounds in aqueous solutions

Thermodynamics of fluid‐phase equilibria for standard chemical engineering operations

“…In these methods, the structure of a molecule is represented by a two-dimensional(2-D) graph, with vertices (atoms) and edges (bonds). The numerical values resulting from the operation of a given descriptor on a graph are related to a physical property, for example, the activity coefficient at infinite dilution (Faulon et al, 2003;He and Zhong, 2003). Because the method has little theoretical basis, the type and the number of descriptors needed is property-dependent, that is, the method is specific for each thermodynamic property.…”

Predicting infinite dilution activity coefficients of organic compounds in water by quantum-connectivity descriptors

“…The data sets of infinite dilution activity coefficients for hydrocarbons and oxygen containing compounds were taken from the data reported by He and Zhong [10]. The set of hydrocarbons contains 103 compounds covering a lnðc 1 Þ range from about 6 to 19 ln units.…”

“…Recently, several articles on correlations between structural features and c ¥ have been reported [8][9][10][11]. In these studies different types of molecular descriptors are used to develop multiple linear regression and computational neural network models to predict c ¥ .…”

QSPR analysis of infinite dilution activity coefficients of chlorinated organic compounds in water

“…Alternatively, the quantitative structure-property relationship (QSPR) provides a promising method for the estimation of ∞ based on descriptors derived solely from the molecular structure to fit experimental data [14][15][16][17][18]. The QSPR is based on the assumption that the variation of the behavior of the compounds, as expressed by any measured physicochemical properties, can be correlated with numerical changes in structural features of all compounds, termed "molecular descriptors" [19][20][21][22][23].…”

“…Delgado and Alderete [15] correlated the ln( ∞ ) values of 45 chlorinated organic compounds in water with their quantumchemical descriptors and got a relatively good correlation with R 2 of 0.949. He and Zhong [16] have applied the molecular connectivity indices to develop QSPR models for ln( ∞ ) of hydrocarbons, oxygen containing organic compounds and halogenated hydrocarbons in water, respectively. With the same dataset, Delgado and co-workers [18] recently obtained several QSPR equations for the prediction of ln( ∞ ) by using quantum-chemical descriptors.…”