Principal Component Analysis (PCA) for Powder Diffraction Data: Towards Unblinded Applications

Principal Component Analysis (PCA) for Powder Diffraction Data: Towards Unblinded Applications

We analyze the application of Principal Component Analysis (PCA) for untangling the main contributions to changing diffracted intensities upon variation of site occupancy and lattice dimensions induced by external stimuli. The information content of the PCA output consists of certain functions of Br...

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Bibliographic Details
Main Authors: Dmitry Chernyshov, Iurii Dovgaliuk, Vadim Dyadkin, Wouter van Beek
Format: Article
Language:English
Published: MDPI AG 2020-07-01
Series:Crystals
Subjects:
principal component analysis
powder diffraction
kinetics
Online Access:https://www.mdpi.com/2073-4352/10/7/581

Internet

https://www.mdpi.com/2073-4352/10/7/581

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