Intermolecular Interactions in Functional Crystalline Materials: From Data to Knowledge

Abstract

Intermolecular interactions of organic, inorganic, and organometallic compounds are the key to many composition-structure and structure-property networks. In this review, some of these relations and the tools developed by the Cambridge Crystallographic Data Center (CCDC) to analyze them and design solid forms with desired properties are described. The potential of studies supported by the Cambridge Structural Database (CSD)-Materials tools for investigation of dynamic processes in crystals, for analysis of biologically active, high energy, optical, (electro)conductive, and other functional crystalline materials, and for the prediction of novel solid forms (polymorphs, co-crystals, solvates) are discussed. Besides, some unusual applications, the potential for further development and limitations of the CCDC software are reported. Crystals 2019, 9, 478 2 of 40 these fields, the manuscript cites only (i) recent works devoted to the analysis of correlations between intermolecular interactions and properties of a small molecule (for example its inclination to form polymorphs, solvates, and co-crystals), or a corresponding solid (from a well-known requirement for non-linear optical materials to crystallize in acentric space groups, to recent studies devoted to the effect of solvent presence on mechanical properties), and (ii) the corresponding software developed to investigate these correlations and to design novel solid forms with desired physicochemical properties. As the description of structure-property networks describes mainly the papers published in the last 10 years in the field of organic, organometallic, and coordination crystals, then the software under discussion will be limited with those developed by the Cambridge Crystallographic Data Centre (CCDC) for material chemistry and crystallography. Various examples of applications of the CCDC software to functional materials including their combination with other software, and restrictions found, will be given.First, the Cambridge Structural Database (CSD) and components of the CSD-Enterprise will be described in Section 2. Then, some properties related to the appearance of a given supramolecular associate, and the tools to search for an associate in the CSD will be reported in Section 3. The properties of solids dependent on the crystal morphology, the Bravais, Friedel, Donnay, and Harker (BFDH) tool for crystal morphology prediction and its' application to affect crystal morphology, polymorphism, and solvatomorphism will be reported in Section 4. Knowledge-based predictions of H-bonded polymorphism, co-crystal formation, mapping of likely intermolecular interactions, and conformer generation for the synthesis of novel functional materials will be discussed in Section 5, and the analysis of local connectivity and whole architectures of solvent molecules in Section 6. Finally, Section 7 contains information about Python API algorithms compatible with the CSD-Enterprise and about some examples of the successful combination of the CSD-Enterprise tools with exte...

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