title: "Compressing liquid": an efficient global minima search strategy for clusters.
abstract: In this paper we present a new global search strategy named as "compressing liquid" for atomic clusters. In this strategy, a random fragment of liquid structure is adopted as a starting geometry, followed by iterative operations of "compressing" and Monte Carlo adjustment of the atom positions plus structural optimization. It exhibits fair efficiency when it is applied to seeking the global minima of Lennard-Jones clusters. We also employed it to search the low-lying candidates of medium silicon clusters Si(n)(n=40-60), where the global search is absent. We found the best candidates for most sizes. More importantly, we obtained non-fullerene-based structures for some sized clusters, which were not found from the endohedral-fullerene strategy. These results indicate that the "compressing-liquid" method is highly efficient for global minima search of clusters.
authors.affiliation: School of Science and Engineering of Materials, Hefei University of Technology, Hefei, Anhui 230009, People's Republic of China. rlzhou@mail.ustc.edu.cn
authors.forename: R L
authors.initials: RL
authors.lastname: Zhou
authors.forename: L Y
authors.initials: LY
authors.lastname: Zhao
authors.forename: B C
authors.initials: BC
authors.lastname: Pan