The determination of the solubility parameter of organic compounds has been of much significance in the chemical industry. In this study, we propose a predictive method based on the combination of the Group Contribution strategy with the Artificial Neural Network to calculate/estimate the solubility parameter values of about 1620 nonelectrolyte organic compounds at 298.15 K and atmospheric pressure. The chemical functional groups are obtained for various compounds categorized in 81 different chemical families. The final results indicate the following statistical parameters of the presented method: average relative deviation (ARD %) of the determined properties from existing experimental values of 1.5% and a squared correlation coefficient of 0.985. It is finally inferred that the developed model is more accurate and predictive than our previously proposed models based on the Quantitative Structure-Property Relationship algorithm, which yielded 4.6, 3.4, and 3.1 ARD % from experimental values. © 2011 American Chemical Society.
CITATION STYLE
Gharagheizi, F., Eslamimanesh, A., Mohammadi, A. H., & Richon, D. (2011, September 7). Group contribution-based method for determination of solubility parameter of nonelectrolyte organic compounds. Industrial and Engineering Chemistry Research. https://doi.org/10.1021/ie201002e
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