基于智能全局优化算法的理论结构预测

发布时间：2018-03-20 13:41

  本文选题：全局优化算法　切入点：理论结构预测　出处：《物理》2017年09期 　论文类型：期刊论文

【摘要】：凝聚态物质内部的原子堆垛方式,即微观原子结构,是深入理解其各种宏观物理和化学性质的基础。近年来,随着基于群智理论的全局优化算法和第一性原理计算方法的发展,只根据物质的化学组分和外界条件,通过理论计算来确定或预测物质的微观原子结构成为可能。文章将对目前国内外主要理论结构预测方法进行简要的概述,重点介绍基于群智算法的卡里普索(CALYPSO)结构预测方法的基本原理及其在凝聚态物质结构研究中的一些典型应用。
[Abstract]:In recent years, with the development of the global optimization algorithm based on group intelligence theory and the development of first-principle calculation methods, the atomic stacking method in condensed matter, that is, the microscopic atomic structure, is the basis of deep understanding of various macroscopic physical and chemical properties of condensed matter. It is possible to determine or predict the microscopic atomic structure of matter by theoretical calculation only according to the chemical composition and external conditions of matter. In this paper, the main theoretical structure prediction methods at home and abroad are briefly summarized. This paper mainly introduces the basic principle of the structure prediction method of Carripsos Carriposo (CALYPSO) based on group intelligence algorithm and its typical applications in the study of condensed matter structure.
【作者单位】： 吉林大学物理学院超硬材料国家重点实验室;
【分类号】：O469
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本文编号：1639320