A Review on the Preparation Processes, Hot Deformation Behavior, and Microstructural Tailoring of the Ti-55531 Titanium Alloy
Tianhui Wu, Yichao Gong, Zhijian Wei, Ming Liu, Miao Tian, Changsheng Tan, Ke Song, Zhanjun Yuan, Wen Guo, Guojun ZhangThe Ti-55531 titanium alloy (Ti–5Al–5Mo–5V–3Cr–1Zr) is a typical near-β high-strength and high-toughness titanium alloy, featuring a combination of high strength, excellent hardenability, and a favorable strength–ductility balance. It holds significant application prospects in critical load-bearing structural components for aerospace vehicles and other high-end equipment. In recent years, extensive research has been conducted on the preparation processes, hot deformation behavior, and microstructure–property tailoring of this alloy. However, the relevant findings are widely dispersed in the literature, and a systematic understanding of the intrinsic interrelationships among preparation processes, thermomechanical behavior, and microstructural evolution is still lacking. This paper provides a comprehensive review of the research progress on the Ti-55531 titanium alloy. The development status of major preparation routes is summarized, including ingot metallurgy (with an emphasis on as-cast microstructural characteristics), powder metallurgy, and additive manufacturing. The hot deformation behavior and the effects of heat treatment processes on microstructural evolution are systematically reviewed, and research methodologies such as constitutive equations, processing maps, and numerical simulations are discussed. On this basis, the influence mechanisms of microstructural features (β grain size and α-phase morphology and distribution) on mechanical properties are analyzed, together with the microstructural evolution mechanisms during hot deformation, particularly dynamic recovery and dynamic recrystallization. Furthermore, key remaining challenges in current research, including microstructural evolution mechanisms, hot working instability behavior, and multi-scale simulation and prediction, are identified. Finally, future research directions are proposed in terms of process optimization, multi-scale modeling, and service performance investigation.