Inorganic materials play vital roles in our everyday lives; understanding the atomic-scale structure of these solids, and how that affects their physical and chemical properties, is key to the future design of functional materials. Mixed-metal materials offer the opportunity to vary or control properties through changes in the composition and the distribution of atoms. In this talk I will show how we have used an NMR crystallographic approach,^1-2 combining NMR spectroscopy with periodic planewave DFT calculations, to probe the local structure and disorder in two types of materials – new mixed-metal phosphate frameworks^3-4 and pyrochlore ceramics.^5-6

For materials that exhibit compositional disorder there remains the significant challenge of generating possible structural models that are chemically and energetically relevant, while considering a potentially huge range of chemical and structural space. I will show how we have used ensemble-based approaches to where symmetry-adapted configurational ensembles, combined with Boltzmann weighting, are used to both predict NMR parameters and the complete NMR spectrum. I will also show how the extension of these approaches, exploiting grand canonical rather than canonical ensembles, improves agreement with experiment, by enabling local compositional fluctuations to be better captured. To mitigate the high computational cost of such simulations, we also explore ensemble truncation strategies and some preliminary use of machine learning.

1. D. McKay et al. Chem. Rev. 112, 5733 (2012). 2. S. E. Ashbrook Faraday Disc. 255, 583 (2025). 3. S. E. Ashbrook et al. Inorg. Chem. 59, 11616 (2020). 4. D. M. Dawson et al. Chem. Sci. 15, 4374 (2024). 5. R. F. Moran et al. J. Am. Chem. Soc. 141, 17838 (2019). 6. R. Grau-Crespo et al. Chem. Sci. 16, 19357 (2025).