Using a machine learning approach to determine the space group of a structure from the atomic pair distribution function

A method is presented for predicting the space group of a structure given a calculated or measured atomic pair distribution function (PDF) from that structure. The method utilizes machine learning models trained on more than 100 000 PDFs calculated from structures in the 45 most heavily represented...

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Veröffentlicht in:	Acta crystallographica. Section A, Foundations and advances Foundations and advances, 2019-07, Vol.75 (4), p.633-643
Hauptverfasser:	Liu, Chia-Hao, Tao, Yunzhe, Hsu, Daniel, Du, Qiang, Billinge, Simon J. L.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial intelligence Artificial neural networks Atomic structure convolutional neural network Distribution functions GENERAL AND MISCELLANEOUS Learning algorithms Machine learning Neural networks pair distribution function Powder space groups
Online-Zugang:	Volltext
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