X-ray diffraction is one of the most effective tools for the characterization of the stacking defects which occur frequently in clay minerals. Modelling of the diffraction patterns of oriented mounts is often used for obtaining structural information about the nature of stacking order. Manual matching of calculated and observed patterns is time consuming and the results are user dependent and especially troublesome if a consistent model of the same mineral measured under different conditions needs to be obtained. It was shown recently that the Rietveld method could be applied successfully for the evaluation of the X-ray patterns of oriented mounts. Nevertheless, this automatic refinement procedure can also lead to inconsistent results if independent refinements are performed that describe the same sample measured under different conditions. One way to solve this problem is the application of parametric Rietveld refinement. For this approach a set of different measurements of the same sample was collected and fitted in one combined refinement by the connection of the structural models via external parameters. These conditions may involve different pre-treatments (e.g. different intercalations), different temperatures or relative humidities and/or different experimental setup (powder or oriented samples). All patterns were fitted in one overall refinement process by the BGMN software.

This approach was demonstrated on a mixture of two disordered reference materials and on a set of geological samples. Two different states for each sample were refined independently and parametrically and it was shown that this approach leads to consistent results, saves computation time and may even resolve small structural differences.

Powder diffraction experiments performed as a function of external variables like, e.g., temperature, pressure, or time open possibilities to gain additional information about the physical and chemical properties of the system under study. Sensible extraction of such information directly from in situ experiments requires the treatment of the dataset with methods like sequential and/or parametric refinements. We are progressing towards the development of the parametric refinement method, which performs simultaneous phase refinements of in situ powder patterns by imposing several rational physical models of the evolving parameters on the calculated powder diffraction profiles. One of the fundamental prerequisites for this method is that the powder patterns in the in situ dataset be grouped to their relevant phases. In this paper, we present an analytical method which uses the Pearson’s correlations coefficients of the powder patterns to automatically determine the phase transition points of the in situ powder dataset. The phase transition points determined are used to group the powder patterns belonging to identical phases and to prepare the patterns for automated sequential phase refinements. The proposed algorithm is implemented as an automated module in the multi powder diffraction pattern, data reduction software Powder 3D.