• 文献标题:   Nano level optimization of graphene allotropes by means of a hybrid parallel evolutionary algorithm
  • 文献类型:   Article
  • 作  者:   MROZEK A, KUS W, BURCZYNSKI T
  • 作者关键词:   graphenelike material, optimization at the nano level, airebo potential, evolutionary algorithm, parallel computing
  • 出版物名称:   COMPUTATIONAL MATERIALS SCIENCE
  • ISSN:   0927-0256 EI 1879-0801
  • 通讯作者地址:   AGH Univ Sci Technol
  • 被引频次:   9
  • DOI:   10.1016/j.commatsci.2015.05.002
  • 出版年:   2015

▎ 摘  要

The article describes the application of a Hybrid Parallel Evolutionary Algorithm (HPEA) to optimal searching for new, stable atomic arrangements of two-dimensional graphene-like carbon lattices. The proposed approach combines the parallel evolutionary algorithm and the conjugated-gradient optimization technique. The main goal of the optimization is to find stable arrangements of carbon atoms under certain imposed conditions (e.g. density, shape and size of the unit cell). The fitness function is formulated as the total potential energy of an atomic system. The optimized structure is considered as a discrete atomic model and interactions between atoms are modeled using the AIREBO potential, especially developed for carbon and hydrocarbon materials. The parallel approach used in computations allows significant reduction of computation time. Validation of the obtained results and examples of the models of the new 2D materials obtained using the described algorithm are presented, along with their mechanical properties. (C) 2015 Elsevier B.V. All rights reserved.