Possibilities for neural network powder diffraction analysis of the crystal structure of chemical compounds

Some possibilities of using convolutional artificial neural networks (ANNs) for powder diffraction structural analysis of crystalline substances are investigated. First, ANNs were used to classify crystal systems and space groups of symmetry based on the full-profile diffractograms calculated from t...

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Bibliographische Detailangaben

Hauptverfasser:	Zaloga, A. N., Stanovov, V. V., Bezrukova, O. E., Dubinin, P. S., Yakimov, I. S.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Accuracy Artificial neural networks Chemical compounds Classification Crystal structure Crystallography Deep learning Diffraction patterns Evolutionary algorithms Genetic algorithms Machine learning Neural networks Structural analysis Structural models Triclinic crystals
Online-Zugang:	Volltext
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