title: An efficient approach for theoretical study on the low-energy isomers of large fullerenes C90-C140.
abstract: An approach that consists of a molecular mechanics method based on the second generation reactive empirical bond order (REBO) potential and the more accurate semiempirical method PM3 (Parametric Method No. 3) was proposed to predict the energetically favored isomers of the fullerenes from C90 to C140 at the semiempirical level. All the 578,701 isolated-pentagon-rule isomers of fullerenes from C90 to C140 were enumerated from topological structures and systematically searched using an energy minimization method to select the best 100 low-energy isomers based on the REBO potential for each fullerene. Then these candidate isomers were further optimized by PM3 and ranked again to determine the top low-energy isomers. This approach was applied to calculate the energetically favored isomers of C90-C140. The results of C90-C120 are in good agreement with the published results by quantum-chemical methods. Furthermore, the top five low-energy isomers of C90-C120, as well as C122-C140 which have scarcely been systematically studied before, are also predicted with the approach. The analysis of the structures showed that the hexagon-neighbor rule is an important factor to the stability of C90-C140. The time cost for the systematical search based on the REBO potential was also discussed. It indicates that the approach proposed is efficient for predicting the energetically favored isomers of large fullerenes at the semiempirical level.
authors.affiliation: Department of Chemistry, University of Science and Technology of China, Hefei, Anhui 230026, People's Republic of China. wscai@ustc.edu.cn
authors.forename: Wensheng
authors.initials: W
authors.lastname: Cai
authors.forename: Lei
authors.initials: L
authors.lastname: Xu
authors.forename: Nan
authors.initials: N
authors.lastname: Shao
authors.forename: Xueguang
authors.initials: X
authors.lastname: Shao
authors.forename: Qingxiang
authors.initials: Q
authors.lastname: Guo