Chemical short-range order (SRO) is a key structural factor in modulating the micromechanical behavior of high-entropy alloys (HEAs). However, under high strain rate dynamic tensile conditions, the coupling effects of SRO with ambient temperature and initial micro-damage—as well as the resulting impact on dynamic failure—remain to be fully elucidated. In this study, large-scale molecular dynamics (MD) simulations were employed to systematically investigate the dynamic response of single-crystal face-centered cubic (FCC) Al_0.3FeCoCrNi HEAs at high strain rates. By decoupling the effects of initial porosity, SRO degree, and temperature, this work aims to reveal the mechanisms of void evolution and dislocation dynamics closely associated with shock-induced spall damage, with a specific focus on the influence of adiabatic thermodynamic characteristics under high-rate loading.
The results indicate that the enhancement of dynamic strength by SRO depends primarily on its coupling with porosity and temperature. During the plastic deformation stage, at low porosity, SRO strengthens slip resistance by promoting the formation of Lomer–Cottrell locks. Conversely, at high porosity, the strengthening effect is predominantly derived from the pinning action of dislocations induced by voids. Further analysis reveals the deformation mechanisms under the temperature-SRO coupling: at low temperatures, SRO enhances strength by facilitating twinning deformation, while at high temperatures, it acts to maintain a high dislocation density. Notably, compared to its significant modulation of plastic deformation, the influence of SRO on the damage evolution stage is relatively limited. Furthermore, a temperature-dominated transition in failure modes was observed: as temperature increases, the void evolution shifts from diffuse nucleation and growth to a singular growth mode dominated by initial voids.
To improve the prediction efficiency of material behavior under complex operating conditions, a Feature-Enhanced Time-series Network (FETNet) was constructed and trained based on the simulation datasets. The model accurately captures the dynamic stress response and void evolution history across various temperatures and initial damage levels, showing high consistency with atomistic simulations. This research deepens the understanding of the microscopic mechanisms of HEAs under high strain rates and provides both a physical basis and an efficient predictive tool for understanding the dynamic failure of materials under extreme conditions.

化学短程有序（SRO）是调控多主元高熵合金（HEAs）微观力学行为的核心结构因素。然而，在高应变率动态拉伸条件下，SRO 与环境温度、初始微损伤的耦合作用及其对材料动态失效的影响机制仍有待深入厘清。本研究采用大尺度分子动力学模拟，系统考察了单晶面心立方（FCC）结构 Al₀.₃FeCoCrNi 高熵合金在高应变率下的动态响应。通过对初始孔隙率、SRO 程度及温度效应进行解耦分析，本工作旨在揭示与冲击层裂损伤密切相关的孔洞演变及位错动力学机制，并重点关注了高应变率加载下的绝热热力学特征对材料失效的影响。
研究结果表明，SRO 对材料动态强度的提升主要取决于其与孔隙率及温度的耦合关系。在塑性变形阶段，低孔隙率下 SRO 通过促进 Lomer–Cottrell 位错锁的形成增强抗滑移能力；而在高孔隙率下，强化效应主要源于孔洞诱导的位错锁钉扎作用。研究进一步揭示了温度与 SRO 耦合下的变形机制：低温下 SRO 通过促进孪晶变形提升强度，高温下则表现为对高位错密度的维持作用。值得注意的是，相比于对塑性变形的显著调控，SRO 对损伤演化阶段的影响相对有限。此外，研究观测到由温度主导的失效模式转变现象：随温度升高，孔隙演化模式从弥散状的孔洞成核与增长，转变为受初始孔洞主导的单一增长模式。
为提升对复杂工况下材料行为的预测效率，本工作基于模拟数据集构建并训练了特征增强时序神经网络（FETNet）。该模型能够准确捕捉不同温度及初始损伤程度下的动态应力响应与孔洞演化历程，预测结果与原子尺度模拟高度一致。本研究深化了对高熵合金在高应变率下微观机理的理解，为理解极端条件下材料的动态失效提供了物理依据与高效预测手段。

 

高熵合金,人工神经网络,化学短程有序,动态损伤