Communications Materials (Nov 2021)

Predicting synthesizability of crystalline materials via deep learning

  • Ali Davariashtiyani,
  • Zahra Kadkhodaie,
  • Sara Kadkhodaei

DOI
https://doi.org/10.1038/s43246-021-00219-x
Journal volume & issue
Vol. 2, no. 1
pp. 1 – 11

Abstract

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Predicting the synthesizability of unknown crystals is important for accelerating materials discovery. Here, the synthesizability of crystals with any given composition and structure can be predicted by a deep learning model that maps crystals onto color-coded 3D images processed by convolutional neural networks.