合金
材料科学
疲劳极限
沉淀硬化
降水
位错
冶金
微观结构
材料的强化机理
复合材料
中子衍射
高能
压力(语言学)
结构材料
疲劳试验
制造工艺
高熵合金
结构工程
衍射
作者
Poresh Kumar,Tu‐Ngoc Lam,Mao-Yuan Luo,Lia Amalia,Jing-Syuan Lai,Shuo-Ting Hsu,Ke An,Yan Chen,Dunji Yu,S E Lee,Jai Jain,Peter K. Liaw,Po-Heng Chou,An‐Chou Yeh,Winson C. H. Kuo,Sudhanshu S. Singh,E‐Wen Huang
标识
DOI:10.1038/s43246-026-01129-6
摘要
To accomplish the intense desire of high-strength materials for enhanced energy-efficiency, recent research applies a combined strategy of additive-manufacturing and precipitation-strengthening in high entropy alloys. In a context, Al0.2Co1.5CrFeNi1.5Ti0.3 nanoprecipitation-strengthened system was developed, demonstrating very convincing strength and toughness. Moreover, additive-manufacturing facilitated additional strength by well-decorated cell-boundaries with blocky L21 precipitates and homogeneously distributed L12 precipitates. However, fatigue research of this alloy remained unexplored despite being the main precursor for structural applications. In this study low-cycle fatigue behavior of this alloy in both as-built and precipitation-strengthened (aged) conditions has been explored, combined with in-situ neutron diffraction investigation. Findings revealed a substantial cyclic-stress profile and a notable fatigue-life below ±0.50% strain-amplitude, exceeding 105 cycles at ±0.30% strain-amplitude. These demonstrate the potential to carry higher payloads with marked engineering-reliability. Residual-stress estimation revealed strain-compatibility between the matrix and L12 precipitate, indicating a crack-initiation immune interface. A comparative examination of dislocation character revealed shifting towards pure edge-character in aged alloy indicates precipitates promoted planar-slip during deformation. The demand for high-strength materials to enhance energy efficiency drives research into additive manufacturing and precipitation strengthening of high entropy alloys. Here, the authors investigate the low-cycle fatigue behavior of an Al-Co-Cr-Fe-Ni-Ti alloy, revealing impressive fatigue life and stress profiles, highlighting its potential for reliable structural applications.
科研通智能强力驱动
Strongly Powered by AbleSci AI