Enhancing the impact property of high-entropy alloys with graphene layers: a molecular dynamics study
Source abstract
Abstract
High-entropy alloy (HEA) and graphene have high strength, and both have been explored as shielding materials for impact protection. Very recently, HEA/graphene composites with HEA as the matrix and graphene as reinforcing phase have attracted great interests. Herein, the deformation behavior and penetration resistance of AlCoCuFeNi HEA/graphene composites are studied under ballistic impact loadings using molecular dynamics simulations. It is found that graphene can enhance the impact property of the HEA with graphene on the top surface or inside HEA. The amount of enhancement is proportional to the number of graphene layers from monolayer to trilayer. This enhancement is mainly attributed to the strong load carrying ability of graphene, which significantly increases the penetration resistance when a projectile passes through the graphene layers. However, graphene could also lead to some reduction in the impact force of HEA when it is inside the HEA. This negative effect is because graphene sheets break the structure continuity of HEA, reducing the load carrying ability of the local HEA. Overall, the positive effect of graphene outweighs the negative effect, leading to improved impact performance of the HEA/graphene composites. Besides, graphene considerably affects the magnitude and distribution of stress at the HEA/graphene interface during the impact process, which greatly influences the dislocation nucleation and propagation in the HEA/graphene composites. The present work not only provides insights into the dual role that graphene plays in the impact performance of the HEA/graphene composites, but also is useful for the design of HEA/graphene composites for impact protection.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: High Entropy Alloys Studies · Advanced materials and composites · Diamond and Carbon-based Materials Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (64)
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