Abstract
Graphene-reinforced aluminum matrix composites (GRAMCs) attract great interest in industries due to their high performance potential. High-temperature processes such as sintering and aging are usually applied during the preparation of GRAMCs, leading to grain coarsening that significantly influences its properties. In this work, a modified 3D Monte Carlo Potts model was proposed to investigate the effect of content and size of graphene on the grain evolution during the heat treatment of GRAMCs. Grain growth with graphene contents from 0.5 wt.% to 4.5 wt.% and sizes from 5 μm to 15 μm were simulated. The grain growth process, final grain size and morphology of the microstructure were predicted. The results indicated that both the content and size of the reinforcements had an impact on the grain evolution. The pinning effect of grain size can be enhanced by increasing the content and decreasing the size of graphene. Agglomeration and self-contacting phenomena of the graphene arose obviously when the contents and sizes were relatively high. The average grain size decreased by 48.77% when the content increased from 0.5 wt.% to 4.5 wt.%. The proposed method and predicted regulations can provide a reference for the design and fabrication of GRAMCs.
Highlights
The mean standard deviation of grain sizes of the three contents were 13.83 μm, 10.32 μm and 8.67 μm, respectively. This showed that under the condition of high contents, the proportion of abnormal grain growth decreased significantly and the grain size distribution was more uniform, which proves that the pinning effect induced by graphene can reduce the extents of AGG and heterogeneity
The model can be used for the quantitative design, simulation and preparation of Graphene-reinforced aluminum matrix composites (GRAMCs)
The prediction of grain growth has been carried out under various working conditions with graphene contents ranging from 0.5 wt.% to 4.5 wt.%, and sizes ranging from 5 μm to 15 μm
Summary
Aluminum matrix composites (AMCs) have been applied in aerospace, construction, transportation and other fields because of their outstanding performance. In addition to the parameters of the preparation process, such as mechanical and thermal conditions, the reinforcing phase is an important factor that affects the final properties. Graphene is 2D lamellar nano-reinforcement, so the actual grain growth process of GRAMCs can only be predicted properly in the 3D model. Until now, there have been few reports on the prediction model of grain evolution of metal matrix composites containing nano-lamellar reinforcing phases, which greatly limits the design and development of GRAMCs. In this work, a modified 3D Monte Carlo. The grain growth process, final grain size and morphology of the microstructure were predicted and further analyzed This method and obtained results provide a reference for the design and fabrication of GRAMCs
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