Machine-learning design of ductile FeNiCoAlTa alloys with high strength.

Journal: Nature
Published Date: Jun 18, 2025

Abstract

The pursuit of strong yet ductile alloys has been ongoing for centuries. However, for all alloys developed thus far, including recent high-entropy alloys, those possessing good tensile ductility rarely approach 2-GPa yield strength at room temperature. The few that do are mostly ultra-strong steels; however, their stress-strain curves exhibit plateaus and serrations because their tensile flow suffers from plastic instability (such as Lüders strains), and the elongation is pseudo-uniform at best. Here we report that a group of carefully engineered multi-principal-element alloys, with a composition of FeNiCoAlTa designed by means of domain knowledge-informed machine learning, can be processed to reach an unprecedented range of simultaneously high strength and ductility. An example of this synergy delivers 1.8-GPa yield strength combined with 25% truly uniform elongation. We achieved strengthening by pushing microstructural heterogeneities to the extreme through unusually large volume fractions of not only coherent L1 nanoprecipitates but also incoherent B2 microparticles. The latter, being multicomponent with a reduced chemical ordering energy, is a deformable phase that accumulates dislocations inside to help sustain a high strain hardening rate that prolongs uniform elongation.

Authors

  • Yasir Sohail
    State Key Laboratory for Mechanical Behavior of Materials, Xi'an Jiaotong University, Xi'an, People's Republic of China.
  • Chongle Zhang
    State Key Laboratory for Mechanical Behavior of Materials, Xi'an Jiaotong University, Xi'an, People's Republic of China.
  • Dezhen Xue
    State Key Laboratory for Mechanical Behavior of Materials, Xi'an Jiaotong University, Xi'an, People's Republic of China.
  • Jinyu Zhang
    School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China. Electronic address: zhangjinyu@stu.xupt.edu.cn.
  • Dongdong Zhang
    Brain Korea 21 PLUS Project for Medical Science, Yonsei University, Seoul, Korea.
  • Shaohua Gao
    State Key Laboratory for Mechanical Behavior of Materials, Xi'an Jiaotong University, Xi'an, People's Republic of China.
  • Yang Yang
    Department of Gastrointestinal Surgery, The Third Hospital of Hebei Medical University, Shijiazhuang, China.
  • Xiaoxuan Fan
    State Key Laboratory for Mechanical Behavior of Materials, Xi'an Jiaotong University, Xi'an, People's Republic of China.
  • Hang Zhang
    Department of Cardiology, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Gang Liu
    Department of Interventional Radiology, Qinghai Red Cross Hospital, Xining, Qinghai, China.
  • Jun Sun
    School of Environmental and Chemical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, Jiangsu Province, PR China.
  • En Ma
    State Key Laboratory for Mechanical Behavior of Materials, Xi'an Jiaotong University, Xi'an, People's Republic of China. maen@xjtu.edu.cn.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals