Reaction Monitoring of Cementing Materials through Multivariate Techniques Applied to In Situ Synchrotron X-Ray Diffraction Data

Taris, Alessandra; Grosso, Massimiliano; Brundu, Mariarosa; Guida, Vincenzo; Viani, Alberto

doi:10.1016/b978-0-444-63577-8.50101-7

Cited by 2 publications

(2 citation statements)

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“…Nevertheless, to the authors' knowledge, only a few examples of application of MCR-ALS to X-ray diffraction data can be found in the literature (Rodriguez et al, 2007;Beal et al, 2011). In previous work (Taris et al, 2015), the EFA and MCR-ALS algorithms were implemented to monitor the setting reaction of a ceramic material. It was shown that the main changes occurring during the reaction could be identified in a very fast and straightforward way.…”

Section: Introductionmentioning

confidence: 99%

Application of combined multivariate techniques for the description of time-resolved powder X-ray diffraction data

et al. 2017

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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

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Section: Introductionmentioning

confidence: 99%

Application of combined multivariate techniques for the description of time-resolved powder X-ray diffraction data

et al. 2017

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“…The discrimination of the best kinetic model is enhanced by the fact that it produces both the best estimate of the reaction coordinate and the best agreement with the theoretical model. MCR-ALS is another decomposition method that had been employed in the last few years in several kinetic studies on chemical reactions [59][60][61].…”

Section: Kinetic Studies By Single or Multi-probe Experimentsmentioning

confidence: 99%

Multivariate Analysis Applications in X-ray Diffraction

et al. 2020

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Multivariate analysis (MA) is becoming a fundamental tool for processing in an efficient way the large amount of data collected in X-ray diffraction experiments. Multi-wedge data collections can increase the data quality in case of tiny protein crystals; in situ or operando setups allow investigating changes on powder samples occurring during repeated fast measurements; pump and probe experiments at X-ray free-electron laser (XFEL) sources supply structural characterization of fast photo-excitation processes. In all these cases, MA can facilitate the extraction of relevant information hidden in data, disclosing the possibility of automatic data processing even in absence of a priori structural knowledge. MA methods recently used in the field of X-ray diffraction are here reviewed and described, giving hints about theoretical background and possible applications. The use of MA in the framework of the modulated enhanced diffraction technique is described in detail.

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Reaction Monitoring of Cementing Materials through Multivariate Techniques Applied to In Situ Synchrotron X-Ray Diffraction Data

Cited by 2 publications

References 7 publications

Application of combined multivariate techniques for the description of time-resolved powder X-ray diffraction data

Application of combined multivariate techniques for the description of time-resolved powder X-ray diffraction data

Multivariate Analysis Applications in X-ray Diffraction

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