A data-analysis methodology is presented for the characterization of three-dimensional microstructures of polycrystalline materials from data acquired using three-dimensional X-ray diffraction (3DXRD). The method is developed for 3DXRD microscopy using a far-field detector and yields information about the centre-of-mass position, crystallographic orientation, volume and strain state for thousands of grains. This first part deals with pre-processing of the diffraction data for input into the algorithms presented in the second part [Sharma, Huizenga & Offerman (2012).J. Appl. Cryst.45, 705–718] for determination of the grain characteristics. An algorithm is presented for accurate identification of overlapping diffraction peaks from X-ray diffraction images, which has been an issue limiting the accuracy of experiments of this type. The algorithm works in two stages, namely the identification of overlapping peaks using a seeded watershed algorithm, and then the fitting of the peaks with a pseudo-Voigt shape function to yield an accurate centre-of-mass position and integrated intensity for the peaks. Regions consisting of up to six overlapping peaks can be successfully fitted. Two simulations and an experiment are used to verify the results of the algorithms. An example of the processing of diffraction images acquired in a 3DXRD experiment with a sample consisting of more than 1600 grains is shown. Furthermore, a procedure for the determination of the parameters of the experimental setup (global parameters) without the need for a calibration sample is presented and validated using simulations. This is immensely beneficial for simplifying experiments and the subsequent data analysis.
Quantitative analysis of ibuprofen in pharmaceuticals and human control serum using kinetic spectrophotometry
