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Many crystalline solids can be prepared only as microcrystalline powders and are not suitable for structural characterization by single-crystal X-ray diffraction methods. For such materials, it is necessary instead to tackle structure determination using powder X-ray diffraction data. Although there have been several successful reports of the structure determination of organic molecular solids using traditional strategies for structure solution from powder X-ray diffraction data, the majority of recent work on such materials has exploited the direct-space strategy for structure solution, followed by Rietveld refinement. Indeed, the recent upsurge of activity in this field (in both academic and industrial sectors) has taken place closely in parallel with the development of the direct-space strategy for structure solution, for which a range of different computational implementations are now available. In the direct-space strategy, a hypersurface defined by an appropriate R-factor (in our case the powder profile R-factor) is searched using an appropriate global optimization technique (such as Monte Carlo, simulated annealing or Genetic Algorithm techniques). Our recent research is focused on the development, optimization and implementation of Genetic Algorithm techniques in this field, as well as the application of these techniques to solve the crystal structures of a wide range of different types of molecular materials from different areas of the solid state and materials sciences. The lecture will describe fundamental aspects of the direct-space strategy for structure solution from powder X-ray diffraction data, and will be illustrated by examples selected to highlight the current scope and potential for the application of techniques in this field.

Structural biology studies of the avian influenza H5N1 virus