Suppr超能文献

使用等点子集作为生成器的结构搜索:二元硬球混合物的最密堆积。

Structural searches using isopointal sets as generators: densest packings for binary hard sphere mixtures.

机构信息

School of Chemistry, University of Sydney, NSW 2006, Australia.

出版信息

J Phys Condens Matter. 2011 May 18;23(19):194103. doi: 10.1088/0953-8984/23/19/194103. Epub 2011 Apr 27.

Abstract

Algorithms to search for crystal structures that optimize some extensive property (energy, volume, etc) typically make use of random particle reorganizations in the context of one or more numerical techniques such as simulated annealing, genetic algorithms or biased random walks, applied to the coordinates of every particle in the unit cell, together with the cell angles and lengths. In this paper we describe the restriction of such searches to predefined isopointal sets, breaking the problem into countable sub-problems which exploit crystal symmetries to reduce the dimensionality of the search space. Applying this method to the search for maximally packed mixtures of hard spheres of two sizes, we demonstrate that the densest packed structures can be identified by searches within a couple of isopointal sets. For the A(2)B system, the densest known packings over the entire tested range 0.2 < r(A)/r(B) < 2.5, including some improvements on previous optima, can all be identified by searches within a single isopointal set. In the case of the AB composition, searches of two isopointal sets generate the densest packed structures over the radius ratio range 0.2 < r(A)/r(B) < 5.0.

摘要

算法搜索晶体结构,优化一些广泛的属性(能量、体积等),通常在一个或多个数值技术的背景下使用随机粒子重组,如模拟退火、遗传算法或有偏随机游走,应用于单位晶胞中每个粒子的坐标,以及晶胞的角度和长度。在本文中,我们将此类搜索限制在预定义的等位面集内,将问题分解为可数的子问题,利用晶体对称性来降低搜索空间的维数。将这种方法应用于搜索两种尺寸硬球的最大堆积混合物,我们证明通过在几个等位面集内搜索,可以确定最密集堆积的结构。对于 A(2)B 体系,在整个测试范围内 0.2 < r(A)/r(B) < 2.5,可以通过单个等位面集的搜索来确定已知最密集的堆积结构,包括对以前最优值的一些改进。对于 AB 组成,通过两个等位面集的搜索,可以在半径比范围 0.2 < r(A)/r(B) < 5.0 内生成最密集堆积的结构。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验