Powder-diffraction-based structural comparison for crystal structure prediction without prior indexing

IF 5.2 3区 材料科学 Q2 CHEMISTRY, MULTIDISCIPLINARY
Alberto Otero-de-la-Roza
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Abstract

The objective of crystal structure prediction (CSP) is to predict computationally the thermodynamically stable crystal structure of a compound from its stoichiometry or its molecular diagram. Crystal similarity indices measure the degree of similarity between two crystal structures and are essential in CSP because they are used to identify duplicates. Powder-based indices, which are based on comparing X-ray diffraction patterns, allow the use of experimental X-ray powder diffraction data to inform the CSP search. Powder-assisted CSP presents two unique difficulties: (i) the experimental and computational structures are not entirely comparable because the former is subject to thermal expansion from lattice vibrations, and (ii) experimental patterns present features (noise, background contribution, varying peak shapes etc.) that are not easily predictable computationally. This work presents a powder-based similarity index (GPWDF) based on a modification of the index introduced by de Gelder, Wehrens & Hageman [J. Comput. Chem. (2001), 22, 273–289] using cross-correlation functions that can be calculated analytically. Based on GPWDF, a variable-cell similarity index (VC-GPWDF) is also proposed that assigns a high similarity score to structures that differ only by a lattice deformation and which takes advantage of the analytical derivatives of GPWDF with respect to the lattice parameters. VC-GPWDF can be used to identify similarity between two computational structures generated using different methods, between a computational and an experimental structure, and between two experimental structures measured under different conditions (e.g. different temperature and pressure). VC-GPWDF can also be used to compare crystal structures with experimental patterns in combination with an automatic pre-processing step. The proposed similarity indices are simple, efficient and fully automatic. They do not require indexing of the experimental pattern or a guess of the space group, they account for deformations caused by varying experimental conditions, they give meaningful results even when the experimental pattern is of very poor quality, and their computational cost does not increase with the flexibility of the molecular motif.

Abstract Image

基于粉末衍射的结构对比,无需事先索引即可预测晶体结构
晶体结构预测(CSP)的目的是根据化合物的化学计量学或分子图,通过计算预测其热力学稳定的晶体结构。晶体相似性指数衡量两个晶体结构之间的相似程度,在晶体结构预测中至关重要,因为它们可用于识别重复的晶体结构。基于 X 射线衍射图样比较的粉末指数允许使用实验 X 射线粉末衍射数据为 CSP 搜索提供信息。粉末辅助 CSP 有两个独特的难点:(i) 实验结构和计算结构不完全可比,因为前者受晶格振动热膨胀的影响;(ii) 实验图案的特征(噪声、背景贡献、不同的峰形等)不容易通过计算预测。本研究提出了一种基于粉末的相似性指数 (GPWDF),该指数是对 de Gelder、Wehrens & Hageman [J. Comput. Chem. (2001),22, 273-289]引入的指数的修改,使用的是可分析计算的交叉相关函数。在 GPWDF 的基础上,还提出了一种可变晶胞相似性指数(VC-GPWDF),该指数为仅因晶格变形而不同的结构赋予较高的相似性分数,并利用了 GPWDF 相对于晶格参数的分析导数。VC-GPWDF 可用于识别使用不同方法生成的两个计算结构之间、计算结构与实验结构之间以及在不同条件(如不同温度和压力)下测量的两个实验结构之间的相似性。结合自动预处理步骤,VC-GPWDF 还可用于比较晶体结构与实验模式。所提出的相似性指数简单、高效、全自动。它们不需要对实验图案进行索引或对空间群进行猜测,能考虑到不同实验条件引起的变形,即使在实验图案质量很差的情况下也能得出有意义的结果,而且其计算成本不会随着分子图案的灵活性而增加。
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来源期刊
Journal of Applied Crystallography
Journal of Applied Crystallography CHEMISTRY, MULTIDISCIPLINARYCRYSTALLOGRAPH-CRYSTALLOGRAPHY
CiteScore
7.80
自引率
3.30%
发文量
178
期刊介绍: Many research topics in condensed matter research, materials science and the life sciences make use of crystallographic methods to study crystalline and non-crystalline matter with neutrons, X-rays and electrons. Articles published in the Journal of Applied Crystallography focus on these methods and their use in identifying structural and diffusion-controlled phase transformations, structure-property relationships, structural changes of defects, interfaces and surfaces, etc. Developments of instrumentation and crystallographic apparatus, theory and interpretation, numerical analysis and other related subjects are also covered. The journal is the primary place where crystallographic computer program information is published.
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