In order to understand the structural origin of scattering data, either the data or the correlation functions of a structural model must be Fourier transformed to make the association between real and reciprocal space. In the ideal scenario of perfect data and a perfect crystalline lattice, this is straightforward. In cases that are close to the ideal, the crystallographic community have established robust and effective approximations. More recently, there has been increased interest in materials that deviate significantly from perfect order. Examples of these might be disordered network silicates (including zeolites), rotating molecular crystals (e.g. C60) and doped functional materials (such as high-temperature superconductors and CMR materials). These materials can cause problems for analysis of diffraction data because the local structural correlations may be incompatible with the deduced average structure.
We have developed computer-modelling methods, using reverse Monte Carlo modelling, which produce consistent structural descriptions of disordered crystalline materials. The analysis is based, in part, on methods more usually applied to the interpretation of scattering data from liquids or amorphous materials and uses the total scattering, i.e. Bragg and diffuse components. In this talk I will discuss the computational aspects of this analysis, with many diverse real examples, since the overriding motivation for the work comes from the desire to understand how structures behave.
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