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Application of combined multivariate techniques for the description of time‐resolved powder X‐ray diffraction data
Author(s) -
Taris Alessandra,
Grosso Massimiliano,
Brundu Mariarosa,
Guida Vincenzo,
Viani Alberto
Publication year - 2017
Publication title -
journal of applied crystallography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.429
H-Index - 162
ISSN - 1600-5767
DOI - 10.1107/s1600576717001753
Subject(s) - powder diffraction , diffraction , multivariate statistics , resolution (logic) , amorphous solid , materials science , synchrotron , analytical chemistry (journal) , potassium phosphate , crystallography , chemistry , optics , mathematics , statistics , physics , computer science , chromatography , artificial intelligence
In this work, multivariate statistical techniques are employed to determine patterns and conversion curves from time‐resolved X‐ray powder diffraction data. For these purposes, time‐window statistical total correlation spectroscopy is introduced for the pattern matching of the crystalline phase and is shown to be effective even in the case of overlapping peaks. When combined with evolving factor analysis and multivariate curve resolution–alternating least squares, this technique allows a definite estimation of patterns and conversion curves. The procedure is applied to in situ synchrotron powder diffraction patterns to monitor the setting reaction of magnesium potassium phosphate ceramic (MKP) from magnesia (MgO) and potassium dihydrogen phosphate. It is shown that the phases involved in the reaction are clearly distinguished and their evolution is correctly described. The conversion curves estimated with the proposed procedure are compared with the ones determined with the peak integration method, leading to an excellent agreement (Pearson's correlation coefficient equal to 0.9995 and 0.9998 for MgO and MKP, respectively). The approach also allows for the detection and description of the evolution of amorphous phases that cannot be described through conventional analysis of powder diffraction data.