Improved model for fullerene C60 solubility in organic solvents based on quantum-chemical and topological descriptors

Fullerenes are sparingly soluble in many solvents. The dependence of fullerene’s solubility on molecular structure of the solvent must be understood in order to manage efficiently this class of compounds. To find such dependency ab initio quantum-chemical calculations in combination with quantitative structure–property relationship (QSPR) tool were used to model the solubility of fullerene C60 in 122 organic solvents. A genetic algorithm and multiple regression analysis (GA-MLRA) were applied to generate correlation models. The best performance is accomplished by the four-variable MLRA model with prediction coefficient rtest 2 = 0.903. This study reveals a correlation of highest occupied molecular orbital energy (HOMO), certain heteroatom fragments, and geometrical parameters with solubility. Several other important parameters of solvents that affect the C60 solubility have been also evaluated by the QSPR analysis. The employed GA-MLRA approach enhanced by application of quantum-chemical calculations yields reliable results, allowing one to build simple, interpretable models that can be used for predictions of C60 solubility in various organic solvents.