Bringing order to disordered materials – an NMR crystallography approach
Heterogeneity is a universal property observed in nature and in artificial materials such as ceramics, supramolecular systems, coordination polymers and catalysts. Disorder can be compositional, positional or even dynamic in nature, and it is these deviations from the perfect translation order that is typically assumed characterises the solid state that often led to the interesting physical and chemical properties of materials that can be exploited for industrial, economic social or medical use. The enduring quest in this field would be the rational design of a functional material with very specific properties, but in many cases, this is a long way from being a reality owing, in part at least, to a lack of understanding of the structure-property relationships, and the absence of suitable techniques to accurately characterize these systems. Approaches based on Bragg diffraction often rely on long-range order, whereas spectroscopy techniques, such as solid-state NMR spectroscopy, are uniquely sensitive to the atomic-scale environment and so provide a valuable probe of the local structure, disorder, and dynamics. NMR Crystallography is an ideal tool to provide a detailed understanding of disordered materials on a range of length scales
Fig 1: Schematic representation of NMR crystallography. The concept here is to reduce the uncertainty of the model by reasoning from first principles using the available data from MAS NMR and diffraction. The logic behind the reconstruction of a model is to search for global packing that can reproduce commonalities in the observed data through simulation.
Our group focus on the methodology development in NMR crystallography by incorporating DNP SSNMR, electron diffraction data along with the spectroscopic, XRD and DFT calculations. The methodology will be applicable to a range of different materials like metal organic frameworks, covalent organic frameworks, catalysts, supramolecules and inorganic oxides resulting in widespread potential application.