Mayo R Alex, Marczenko Katherine M, Johnson Erin R
Department of Chemistry, Dalhousie University 6274 Coburg Road Halifax NS B3H 4R2 Canada
University of Guelph 50 Stone Rd. E Guelph ON N1G 2W1 Canada
Chem Sci. 2023 Apr 4;14(18):4777-4785. doi: 10.1039/d3sc00168g. eCollection 2023 May 10.
The identification and classification of crystal structures is fundamental in materials science, as the crystal structure is an inherent factor of what gives solid materials their properties. Being able to identify the same crystallographic form from unique origins ( different temperatures, pressures, or -generated) is a complex challenge. While our previous work has focused on comparison of simulated powder diffractograms from known crystal structures, herein is presented the variable-cell experimental powder difference (VC-xPWDF) method to match collected powder diffractograms of unknown polymorphs to both experimental crystal structures from the Cambridge Structural Database and -generated structures from the Control and Prediction of the Organic Solid State database. The VC-xPWDF method is shown to correctly identify the most similar crystal structure to both moderate and "low" quality experimental powder diffractograms for a set of 7 representative organic compounds. Features of the powder diffractograms that are more challenging for the VC-xPWDF method are discussed ( preferred orientation), and comparison with the FIDEL method showcases the advantage of VC-xPWDF provided the experimental powder diffractogram can be indexed. The VC-xPWDF method should allow rapid identification of new polymorphs from solid-form screening studies, without requiring single-crystal analysis.
晶体结构的识别与分类在材料科学中至关重要，因为晶体结构是赋予固体材料特性的内在因素。能够从独特来源（不同温度、压力或生成方式）识别相同的晶体形式是一项复杂的挑战。虽然我们之前的工作集中在比较已知晶体结构的模拟粉末衍射图，但本文介绍了可变晶胞实验粉末差异（VC-xPWDF）方法，用于将收集到的未知多晶型物的粉末衍射图与剑桥结构数据库中的实验晶体结构以及有机固态数据库的控制与预测生成的结构进行匹配。结果表明，VC-xPWDF方法能够正确识别出与一组7种代表性有机化合物的中等质量和“低”质量实验粉末衍射图最相似的晶体结构。讨论了粉末衍射图中对VC-xPWDF方法更具挑战性的特征（择优取向），并且与FIDEL方法的比较显示了VC-xPWDF的优势，前提是实验粉末衍射图能够被索引。VC-xPWDF方法应能从固态筛选研究中快速识别新的多晶型物，而无需单晶分析。
