Nano Archive

A molecular-based model for prediction of solubility of C-60 fullerene in various solvents

Gharagheizi, Farhad and Alamdari, Reza Fareghi (2008) A molecular-based model for prediction of solubility of C-60 fullerene in various solvents. FULLERENES NANOTUBES AND CARBON NANOSTRUCTURES, 16 (1). pp. 40-57.

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Abstract

In this presented work, a quantitative structure-property relationship study (QSPR) was done for prediction of solubility of C-60 fullerene in various solvents. In this study, genetic algorithm-based multivariate linear regression (GA-MLR) was applied to obtain most statistically effective molecular descriptors on solubility of C-60 in various solvents. All of these molecular descriptors are only calculated from the chemical structure of solvents. For considering nonlinear behavior of appearing molecular descriptors in GA-MLR section, a feed forward neural network (FFNN) was constructed and optimized for prediction of solubility of C-60 fullerene in solvents. Obtained models considerably showed better accuracy in comparison with the previous models.

Item Type:Article
Uncontrolled Keywords:C-60; QSPR; GA-MLR; FFNN
Subjects:Physical Science > Nano objects
Material Science > Nanochemistry
ID Code:2804
Deposited By:Farnush Anwar
Deposited On:13 Jan 2009 10:58
Last Modified:26 Jan 2009 15:03

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