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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