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Prediction of some important physical properties of sulfur compounds using quantitative structure–properties relationships

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Abstract

In this work, physical properties of sulfur compounds (critical temperature (T c ), critical pressure (P c ), and Pitzer’s acentric factor (ω)) are predicted using quantitative structure–property relationship technique. Sulfur compounds present in petroleum cuts are considered environmental hazards. Genetic algorithm based multivariate linear regression (GA-MLR) is used to select most statistically effective molecular descriptors on the properties. Using the selected molecular descriptors, feed forward neural networks (FFNNs) are applied to develop some molecular-based models to predict the properties. The presented models are quite accurate and can be used to predict the properties of sulfur compounds.

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Authors and Affiliations

  1. Department of Chemical Engineering, Faculty of Engineering, University of Tehran, P.O. Box 11365-4563, Tehran, Iran

    Farhad Gharagheizi & Mehdi Mehrpooya

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  1. Farhad Gharagheizi
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  2. Mehdi Mehrpooya
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Correspondence to Farhad Gharagheizi.

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Gharagheizi, F., Mehrpooya, M. Prediction of some important physical properties of sulfur compounds using quantitative structure–properties relationships. Mol Divers 12, 143–155 (2008). https://doi.org/10.1007/s11030-008-9088-6

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  • DOI: https://doi.org/10.1007/s11030-008-9088-6

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