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.
Full text is not hosted in this archive but may be available via the Official URL, or by requesting a copy from the corresponding author.
Official URL: http://www.informaworld.com/smpp/content~db=all~co...
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.
|Uncontrolled Keywords:||C-60; QSPR; GA-MLR; FFNN|
|Subjects:||Physical Science > Nano objects|
Material Science > Nanochemistry
|Deposited By:||Farnush Anwar|
|Deposited On:||13 Jan 2009 10:58|
|Last Modified:||26 Jan 2009 15:03|
Repository Staff Only: item control page