Enhancing deep-learning training for phase identification in powder X-ray diffractograms

Enhancing deep-learning training for phase identification in powder X-ray diffractograms

Within the domain of analyzing powder X-ray diffraction (XRD) scans, manual examination of the recorded data is still the most popular method, but it requires some expertise and is time consuming. The usual workflow for the phase-identification task involves software for searching databases of known...

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Bibliographic Details
Main Authors: Jan Schuetzke, Alexander Benedix, Ralf Mikut, Markus Reischl
Format: Article
Language:English
Published: International Union of Crystallography 2021-05-01
Series:IUCrJ
Subjects:
x-ray diffraction
computational modelling
phase identification
multiphase
deep learning
convolutional neural networks
Online Access:http://scripts.iucr.org/cgi-bin/paper?S2052252521002402

Internet

http://scripts.iucr.org/cgi-bin/paper?S2052252521002402

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