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    苏艳

    • 教授     博士生导师   硕士生导师
    • 性别:女
    • 毕业院校:大连化物所
    • 学位:博士
    • 所在单位:物理学院
    • 学科:凝聚态物理
    • 办公地点:科技园大厦C座309
    • 电子邮箱:su.yan@dlut.edu.cn

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    Comprehensive genetic algorithm for ab initio global optimisation of clusters

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    论文类型:期刊论文

    发表时间:2016-07-02

    发表刊物:MOLECULAR SIMULATION

    收录刊物:SCIE、EI

    卷号:42

    期号:10,SI

    页面范围:809-819

    ISSN号:0892-7022

    关键字:Cluster; global optimisation; genetic algorithm; structure

    摘要:Cluster, as the aggregate of a few to thousands of atoms or molecules, bridges the microscopic world of atoms and molecules and the macroscopic world of condensed matters. The physical and chemical properties of a cluster are determined by its ground state structure, which is significantly different from its bulk structure and sensitively relies on the cluster size. As a well-known nondeterministic polynomial-time hard problem, determining the ground state structure of a cluster is a challenging task due to the extreme complexity of high-dimensional potential energy surface (PES). Genetic algorithm (GA) is an efficient global optimisation method to explore the PES of clusters. Recently, we have developed a GA-based programme, namely comprehensive genetic algorithm (CGA), and incorporated it with ab initio calculations. Using this programme, the lowest energy structures of a variety of elemental and compound clusters with different types of chemical bonding have been determined, and their physical properties have been investigated and compared with experimental data. In this article, we will describe the technique details of CGA programme and present an overview of its successful applications.