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Convergence Properties of Crystal Structure Prediction by Quasi-Random Sampling

机译:准随机抽样预测晶体结构的收敛性

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Generating sets of trial structures that sample the configurational space of crystal packing possibilities is an essential step in the process of ab initio crystal structure prediction (CSP). One effective methodology for performing such a search relies on low-discrepancy, quasi-random sampling, and our implementation of such a search for molecular crystals is described in this paper. Herein we restrict ourselves to rigid organic molecules and, by considering their geometric properties, build trial crystal packings as starting points for local lattice energy minimization. We also describe a method to match instances of the same structure, which we use to measure the convergence of our packing search toward completeness. The use of these tools is demonstrated for a set of molecules with diverse molecular characteristics and as representative of areas of application where CSP has been applied. An important finding is that the lowest energy crystal structures are typically located early and frequently during a quasi-random search of phase space. It is usually the complete sampling of higher energy structures that requires extended sampling. We show how the procedure can first be refined, through targetting the volume of the generated crystal structures, and then extended across a range of space groups to make a full CSP search and locate experimentally observed and lists of hypothetical polymorphs. As the described method has also been created to lie at the base of more involved approaches to CSP, which are being developed within the Global Lattice Energy Explorer (GLEE) software, a few of these extensions are briefly discussed.
机译:生成对晶体堆积可能性的构型空间进行采样的试验结构集,是从头开始晶体结构预测(CSP)过程中的重要步骤。执行这种搜索的一种有效方法依赖于低差异,准随机采样,并且本文描述了我们对分子晶体的搜索的实现。在这里,我们将自己局限于刚性有机分子,并通过考虑它们的几何特性,构建试验晶体堆积物作为局部晶格能量最小化的起点。我们还描述了一种匹配相同结构实例的方法,该方法用于衡量打包搜索向完整性的收敛程度。这些工具已被证明可用于具有多种分子特性的一组分子,并代表已应用CSP的应用领域。一个重要发现是,在相空间的准随机搜索过程中,能量最低的晶体结构通常位于早期且频繁。通常是对高能结构的完整采样,需要扩展采样。我们展示了如何通过针对生成的晶体结构的体积来首先优化程序,然后扩展到多个空间组以进行完整的CSP搜索,并定位实验观察到的和假设的多晶型物列表。由于所描述的方法也已被创建为更复杂的CSP方法的基础,这些方法正在Global Lattice Energy Explorer(GLEE)软件内开发,因此简要讨论了其中一些扩展。

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