Optimization of a Genetic Algorithm for the Functionalization of Fullerenes

We present the optimization of a genetic algorithm (GA) that is designed to predict the most stable structural isomers of hydrogenated and hydroxylated fullerene cages. Density functional theory (DFT) and density functional tight binding (DFTB) methods are both employed to compute isomer energies. We show that DFTB and DFT levels of theory are in good agreement with each other and that therefore both sets of optimized GA parameters are very similar. As a prototypical fullerene cage, we consider the functionalization of the C-20 species, since for this smallest possible fullerene cage it is possible to compute all possible isomer energies for evaluation of the GA performance. An energy decomposition analysis for both C20Hn and C-20(OH)(n) systems reveals that, for only few functional groups, the relative stabilities of different structural isomers may be rationalized simply with recourse to pi-Huckel theory. However, upon a greater degree of functionalization, pi-electronic effects alone are incapable of describing the interaction between the functional groups and the distorted cage, and both sigma- and pi-electronic structure must be taken into account in order to understand the relative isomer stabilities.