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  • 标题:Computational property predictions of Ta–Nb–Hf–Zr high-entropy alloys
  • 本地全文:下载
  • 作者:Shashank Mishra ; Soumyadipta Maiti ; Beena Rai
  • 期刊名称:Scientific Reports
  • 电子版ISSN:2045-2322
  • 出版年度:2021
  • 卷号:11
  • DOI:10.1038/s41598-021-84260-3
  • 语种:English
  • 出版社:Springer Nature
  • 摘要:Refractory high entropy alloys (R-HEAs) are becoming prominent in recent years because of their properties and uses as high strength and high hardness materials for ambient and high temperature, aerospace and nuclear radiation tolerance applications, orthopedic applications etc. The mechanical properties like yield strength and ductility of TaNbHfZr R-HEA depend on the local nanostructure and chemical ordering, which in term depend on the annealing treatment. In this study we have computationally obtained various properties of the equimolar TaNbHfZr alloy like the role of configurational entropy in the thermodynamic property, rate of evolution of nanostructure morphology in thermally annealed systems, dislocation simulation based quantitative prediction of yield strength, nature of dislocation movement through short range clustering (SRC) and qualitative prediction of ductile to brittle transition behavior. The simulation starts with hybrid Monte Carlo/Molecular Dynamics (MC/MD) based nanostructure evolution of an initial random solid solution alloy structure with BCC lattice structure created with principal axes along [1 1 1
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