journal article·2026-05Open access

Microstructural evolution and strengthening mechanism of CrMnFeCoNi high-entropy alloy induced by laser shock peening

Xuan He, Zhichen Guan, Wei Qian, Ruifang Chen, Jie Cai, Yinqun Hua

Abstract

To enhance the mechanical properties of forged CrMnFeCoNi high-entropy alloy (HEA), laser shock peening (LSP) was performed using two representative strategies: low-energy multiple impacts and high-energy fewer impacts, both continued until strengthening saturation. A practical damage-free LSP process window of 4–10 J was identified. Saturation was achieved after 15 impacts at 4 J and 5 impacts at 10 J. The Original sample exhibited a yield strength, ultimate tensile strength, and elongation of 211 MPa, 535 MPa, and 86%, respectively. After LSP, these values changed to 598 MPa, 618 MPa, and 46% for 4J-15, and to 626 MPa, 631 MPa, and 41% for 10J-5, respectively. Although 10J-5 showed slightly higher strength, 4J-15 retained higher elongation and thus a better strength–ductility balance. The average surface microhardness of 4J-15 reached 336 HV, higher than that of 10J-5 at 324 HV. Residual stress measurements showed compressive stresses at both convex and concave regions in 4J-15, with average values of −212.6 MPa and −583.5 MPa, respectively. In contrast, 10J-5 exhibited tensile stress at convex regions and compressive stress at concave regions, with values of 426 MPa and −763 MPa, respectively. The refined-layer depths of 4J-15 and 10J-5 were approximately 335 μm and 682 μm, respectively. Although shallower, the 4J-15 refined layer showed a finer and more uniform grain-size distribution. Overall, 4J-15 provided a more favorable combination of residual-stress uniformity, surface microhardness, microstructural homogeneity, and ductility retention.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: High Entropy Alloys Studies · Surface Treatment and Residual Stress · Magnesium Alloys: Properties and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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