My research focuses on experimental and computational methods in X-ray and neutron crystal structure analysis. Application of new procedures, tools and models can enhance our ability to characterise the crystalline solid-state and extract information from experiments. Many of these features are developed and tested in the crystallographic analysis package, CRYSTALS, which is maintained and distributed by the research group.

Diffraction plays a crucial role in research by enabling the accurate determination of three-dimensional atomic resolution structure of molecules and materials. Evaluation of these structures can inspire new approaches to controlling physical properties of materials in diverse applications including sensors, catalysts, pharmaceuticals and energy storage materials. Finding patterns and rules within sets of crystal structures can reveal rules and ideas for construction of novel materials. A crucial step in searching for these patterns is finding suitable ways to represent a molecule as a set of numbers in order to capture molecular properties that are correlated with the properties of interest in the material. Our recent research into the propensity of molecules to form crystals uses a set of cheminformatics descriptors and machine learning models more commonly used in the field of drug discovery and applies them to a materials chemistry problem.