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Ideal plasticity and shape memory of nanolamellar high-entropy alloys.

Shuai ChenPing LiuQing Xiang PeiZhi Gen YuZachary H AitkenWanghui LiZhaoxuan WuRajarshi BanerjeeDavid J SrolovitzPeter K LiawYong-Wei Zhang
Published in: Science advances (2023)
Understanding the relationship among elemental compositions, nanolamellar microstructures, and mechanical properties enables the rational design of high-entropy alloys (HEAs). Here, we construct nanolamellar Al x CoCuFeNi HEAs with alternating high- and low-Al concentration layers and explore their mechanical properties using a combination of molecular dynamic simulation and density functional theory calculation. Our results show that the HEAs with nanolamellar structures exhibit ideal plastic behavior during uniaxial tensile loading, a feature not observed in homogeneous HEAs. This remarkable ideal plasticity is attributed to the unique deformation mechanisms of phase transformation coupled with dislocation nucleation and propagation in the high-Al concentration layers and the confinement and slip-blocking effect of the low-Al concentration layers. Unexpectedly, this ideal plasticity is fully reversible upon unloading, leading to a remarkable shape memory effect. Our work highlights the importance of nanolamellar structures in controlling the mechanical and functional properties of HEAs and presents a fascinating route for the design of HEAs for both functional and structural applications.
Keyphrases
  • density functional theory
  • working memory
  • molecular dynamics
  • machine learning
  • deep learning
  • neural network