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Published in

American Association for the Advancement of Science, Science, 6477(367), p. 564-568, 2020

DOI: 10.1126/science.aay3062

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Crystal symmetry determination in electron diffraction using machine learning

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Data provided by SHERPA/RoMEO

Abstract

Speedy crystallography Electron backscatter diffraction is one standard technique for determining crystal structure, typically of materials or geological samples. However, this method requires structural guesses and user input that are often time consuming or incorrect. Kaufmann et al. developed a general methodology using a convolutional neural network that automatically determines the crystal structure quickly and with high accuracy. After the network is exposed to a training set, it can identify the crystal structure without any additional input most of the time, providing a method for eliminating some of the guesswork from crystal structure determination. Science , this issue p. 564