Abstract
The application of a commonly used computer algorithm based on the group-additivity method for the calculation of the liquid viscosity coefficient at 293.15 K and the activity coefficient at infinite dilution in water at 298.15 K of organic molecules is presented. The method is based on the complete breakdown of the molecules into their constituting atoms, further subdividing them by their immediate neighborhood. A fast Gauss–Seidel fitting method using experimental data from literature is applied for the calculation of the atom groups’ contributions. Plausibility tests have been carried out on each of the calculations using a ten-fold cross-validation procedure which confirms the excellent predictive quality of the method. The goodness of fit (Q2) and the standard deviation (σ) of the cross-validation calculations for the viscosity coefficient, expressed as log(η), was 0.9728 and 0.11, respectively, for 413 test molecules, and for the activity coefficient log(γ)∞ the corresponding values were 0.9736 and 0.31, respectively, for 621 test compounds. The present approach has proven its versatility in that it enabled the simultaneous evaluation of the liquid viscosity of normal organic compounds as well as of ionic liquids.
Highlights
In recent years, among the many computational methods for the prediction of physico-chemical properties of organic compounds, such as those derived fromtheoretical considerations, multiple linear regression approaches based on correlations between further properties of interest, cluster analysis, principal component analysis or group-additivity methods, the latter method has gained increasing interest due to its wide-ranging applicability for the evaluation of numerous molecular descriptors
The present approach has proven its versatility in that it enabled the simultaneous evaluation of the liquid viscosity of normal organic compounds as well as of ionic liquids
Among the many computational methods for the prediction of physico-chemical properties of organic compounds, such as those derived fromtheoretical considerations, multiple linear regression approaches based on correlations between further properties of interest, cluster analysis, principal component analysis or group-additivity methods, the latter method has gained increasing interest due to its wide-ranging applicability for the evaluation of numerous molecular descriptors
Summary
Among the many computational methods for the prediction of physico-chemical properties of organic compounds, such as those derived from (quantum-)theoretical considerations, multiple linear regression approaches based on correlations between further properties of interest, cluster analysis, principal component analysis or group-additivity methods, the latter method has gained increasing interest due to its wide-ranging applicability for the evaluation of numerous molecular descriptors. Earlier attempts to predict the liquid viscosity coefficient of organic compounds have been developed on a statistical mechanics model based on the square well intermolecular potential [3], or have been carried out applying multiple linear regression and artificial neural network modelling methods using a limited number of descriptors as input [4,5], or are based on a quantitative structure-property relationship (QSPR) approach using a five-descriptor equation [6], or use a combination of partial least-square and QSPR technique starting with 18 mostly experimental parameters, ending with a model with nine descriptors [7]. The advantage of the present method lies in the fact that, on the one hand, a unified computer algorithm enabled the evaluation of the group parameters for both descriptors from experimental data, and, on the other hand, that for their subsequent predictive calculation even a 2D sketch of a moleculeon a sheet of paper would be of sufficient help
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