title: An effective structure prediction method for layered materials based on 2D particle swarm optimization algorithm.
abstract: A structure prediction method for layered materials based on two-dimensional (2D) particle swarm optimization algorithm is developed. The relaxation of atoms in the perpendicular direction within a given range is allowed. Additional techniques including structural similarity determination, symmetry constraint enforcement, and discretization of structure constructions based on space gridding are implemented and demonstrated to significantly improve the global structural search efficiency. Our method is successful in predicting the structures of known 2D materials, including single layer and multi-layer graphene, 2D boron nitride (BN) compounds, and some quasi-2D group 6 metals(VIB) chalcogenides. Furthermore, by use of this method, we predict a new family of mono-layered boron nitride structures with different chemical compositions. The first-principles electronic structure calculations reveal that the band gap of these N-rich BN systems can be tuned from 5.40 eV to 2.20 eV by adjusting the composition.
authors.affiliation: State Key Laboratory of Superhard Materials, Jilin University, Changchun 130012, China.
authors.forename: Yanchao
authors.initials: Y
authors.lastname: Wang
authors.forename: Maosheng
authors.initials: M
authors.lastname: Miao
authors.forename: Jian
authors.initials: J
authors.lastname: Lv
authors.forename: Li
authors.initials: L
authors.lastname: Zhu
authors.forename: Ketao
authors.initials: K
authors.lastname: Yin
authors.forename: Hanyu
authors.initials: H
authors.lastname: Liu
authors.forename: Yanming
authors.initials: Y
authors.lastname: Ma