The development of increasingly efficient catalysts requires an understanding of their structure at the atomic level. Nuclear magnetic resonance spectroscopy (NMR) is an important technique that offers atomistic insight without depending on long-range order. However, the computational simulation of NMR properties has been developed
insufficiently. This dissertation aims to bridge the gap between experimental and computational NMR spectroscopy in nanostructured materials, wherein disorder, dynamics and interactions with adsorbates complicate NMR spectral interpretation. The work develops NMR modelling strategies to increase the reliability of spectral simulation by employing a set of benchmark materials of increasing complexity, thereby contributing to a quantitative, atomistic understanding of catalytically relevant materials.
Abstract