Predicting oxidation damage in ultra high-temperature borides: A machine learning approach Article

Bianco, Giuseppe, Nisar, Ambreen, Zhang, Cheng et al. (2022). Predicting oxidation damage in ultra high-temperature borides: A machine learning approach . CERAMICS INTERNATIONAL, 48(20), 29763-29769. 10.1016/j.ceramint.2022.06.236

Open Access

keywords

  • CERAMICS
  • COMPOSITES
  • Computational high -throughput testing
  • EVOLUTION
  • Machine learning
  • Materials Science
  • Materials Science, Ceramics
  • Oxidation
  • RESISTANCE
  • Random forest regression
  • STRENGTH
  • Science & Technology
  • Technology
  • Ultra -high temperature borides

Digital Object Identifier (DOI)

publisher

  • ELSEVIER SCI LTD

start page

  • 29763

end page

  • 29769

volume

  • 48

issue

  • 20