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On the value of popular crystallographic databases for machine learning prediction of space groups

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Category

Academic article

Client

  • Research Council of Norway (RCN) / 275752
  • Research Council of Norway (RCN) / 280545

Language

English

Author(s)

Affiliation

  • Norwegian University of Science and Technology
  • SINTEF Industry / Sustainable Energy Technology
  • Catholic University of Portugal

Year

2022

Published in

Acta Materialia

ISSN

1359-6454

Publisher

Pergamon Press

Volume

240

Page(s)

1 - 14

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