Nature Communications (Jun 2019)

Materials informatics for the screening of multi-principal elements and high-entropy alloys

  • J. M. Rickman,
  • H. M. Chan,
  • M. P. Harmer,
  • J. A. Smeltzer,
  • C. J. Marvel,
  • A. Roy,
  • G. Balasubramanian

DOI
https://doi.org/10.1038/s41467-019-10533-1
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 10

Abstract

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The identification of high entropy alloys is challenging given the vastness of the compositional space associated with these systems. Here the authors propose a supervised learning strategy for the efficient screening of high entropy alloys, whose hardness predictions are validated by experiments.