Quantitative phase analysis (QPA) develops as a tool for scientific work and research as well as in product or process control and troubleshooting in mining and processing industry. Despite of the long history and early publications about theoretic principles and possible applications of X-ray powder diffraction (XRPD) for this purpose, the accuracy of QPA results is often discussed critically and indeed the level is not yet comparable with that usually reached in the analysis of major chemical elements. This can be shown objectively from the outcomes of inter-laboratory round robin tests. Even if the qualitative composition of mixtures is rather easy and known to the operator, significant errors and uncertainties occur in practice (Rafaja & Valvoda, 1996; Madsen et al., 2001; Scarlett et al., 2002). In the case of complex mixtures containing disordered phases like clay minerals and if the qualitative composition is unknown to the operators, the QPA results can become very inaccurate (Ottner et al., 2000; McCarty, 2002; Kleeberg, 2004). On the other hand, impressive accuracy can be obtained even for complex mixtures by careful application of well known techniques (Kleeberg, 2004; Omotoso et al., 2006). In the field of clay mineralogy, full pattern summation methods and Rietveld based techniques are dominating in the community, often combined with additional information from chemical analysis, microscopy, and mineral separation techniques. Not surprisingly, single line methods tend to perform worse than the full pattern techniques. The great impact of the users experience on the quality of the results can be seen from the very different standings of laboratories using the same software for phase quantification.
As far as the reasons for wrong QPA results can be identified from the participants reports, there seem to be some major groups of sources of errors: (i) inadequate sample preparation, (ii) wrong qualitative phase identification, and (iii) lacking understanding of the principles and weaknesses of the applied technique. In detail, well known problems like microabsorption, preferred orientation, line overlap, and uncertainties about the structural features of the phases seem to be more important than the measurement and data quality. Rietveld based techniques often suffer from convergence into wrong minima by correlation problems, mostly connected with meaningless profile shape parameters and falsified scale factors.
There are some conclusion to be drawn: In order to raise the level of QPA, first of all the basics of the methods as well as the potential sources of error must be taught to the users of the method, as detailed as possible. Combined lectures and workshops will probably the most effective way. Secondly, the developers of software for QPA should try to support the users by more user-friendly programs, stable algorithms, and physically based and tested structure models in the case of Rietveld analysis.

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1. Quantification of complex disordered phases by a parallelized Rietveld program