Application of Laser Shock Peening in High-Entropy Alloys: A Review and Prospect
Li Yuting, Xiao Yang, Wang Yong, Zhang Tuanwei, Kang Yixiang, Yi Peng, Wang ZhihuaAbstract
High-entropy alloys (HEAs), as an emerging metallic material system, exhibit a unique combination of excellent mechanical properties and corrosion resistance owing to multi-principal-element effects, holding broad application prospects in aerospace and energy sectors. Nevertheless, under harsh service conditions, their surfaces are susceptible to various failures, making surface protection increasingly critical. Laser shock peening (LSP) is an advanced surface modification technique that employs high-energy laser-induced plasma shock waves to produce deep compressive residual stress fields and gradient nanostructures, thereby significantly improving surface integrity. This paper provides a systematic review of LSP applications and research progress in HEAs. It focuses on how LSP process parameters affect the microstructure and surface integrity evolution (including hardness, roughness, and residual stress distribution) in HEAs with different structural types, such as single-phase, multiphase, and eutectic systems. The roles of LSP in enhancing mechanical properties, fatigue life, and resistance to corrosion and oxidation are analyzed, highlighting the synergistic effect between gradient microstructures and compressive residual stress as the core strengthening mechanism, along with main influencing factors. Moreover, multi-field coupling approaches are introduced, including warm LSP, cryogenic LSP, 3D LSP combined with additive manufacturing, and hybrid electromagnetic-laser shock treatment, emphasizing the importance of multi-energy-field synergy in achieving superior surface modification. Existing challenges, including unclear complex coupling mechanisms and the absence of multiscale simulation tools, are then discussed. Finally, future directions such as adaptive LSP and intelligent monitoring–manufacturing integration are envisioned, offering theoretical and technical support for HEA optimization and advancing LSP applications.