title: Estimation of molecular diffusivity of pure chemicals in water: a quantitative structure-property relationship study.
abstract: A quantitative structure-property relationship (QSPR) study was performed to predict the molecular diffusivity of pure chemicals in water. A genetic-algorithm-based multivariate linear regression (GA-MLR) was applied to select the most statistically effective molecular descriptors for modelling the molecular diffusivity of pure chemicals in water. Based on the selected molecular descriptors, a three-layer feed forward neural network (FFNN) was constructed to predict the property. The obtained results showed that the FFNN was able to predict the molecular diffusivity of pure chemicals in water.
authors: Department of Chemical Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran. fghara@ut.ac.ir
authors: F
authors: F
authors: Gharagheizi
authors: M
authors: M
authors: Sattari
mesh_terms: D004058:Diffusion; D015386:Hazardous Substances; D021281:Quantitative Structure-Activity Relationship; D014877:Water Pollution, Chemical
chemical_list: D015386:Hazardous Substances