Vacancy dependent mechanical behaviors of high-entropy alloy

An abundance of defects would be inevitably generated during manufacturing and service in high-entropy alloys (HEAs). However, the mechanical properties of the damaged HEAs with nanoscale defects have been rarely considered. Meanwhile, an additional challenge is a dearth of the effective reliable method for an in-depth study of damaged HEAs, due to the restriction of the complicated experimental measurement. Here, the effect of zero dimensional defect, such as vacancy, on mechanical properties in FeNiCoCrCu HEA is studied through the method combining molecular dynamics simulation with machine learning. Atomic simulation results show that the existence of vacancy clusters breaks the continuity of stacking faults and dislocations, and the high vacancy concentrations reduce the strength due to the increase of stacking fault spacing at room temperature. Compared with traditional alloys, HEAs can reduce the property reduction when vacancy exits there. In addition, the anisotropy of vacancy effect is found. The effect of vacancy on the yield strength is more obvious under [100] loading direction than that under the [110] and [111] loading direction. The discrepancy of the stair-rod partial dislocation proportion would be regarded as the primary reason for different yield strengths. The change of vacancy concentration has a significant effect on the deformation mechanism in [100] direction, which is different from that in the [110] and [111] direction. Meanwhile, the effects of vacancy concentration in combination with temperature on the yield strength and dislocation density at yield point of the FeNiCoCrCu HEA are predicted by machine learning, which is on the basis of a set of data obtained from molecular dynamics simulations. The current work provides valuable guidance for HEA design based on the viewpoint of defect regulation.