Improving graphene distribution and mechanical properties of GNP/Al composites by cold drawing

被引:88
作者
Li, Jianchao [1 ]
Zhang, Xuexi [1 ]
Geng, Lin [1 ]
机构
[1] Harbin Inst Technol, Sch Mat Sci & Engn, Harbin 150001, Heilongjiang, Peoples R China
关键词
Aluminum metal matrix composites (MMCs); Graphene nano-platelets (GNP); Cold drawing; Mechanical properties; Strengthening efficiency; ALUMINUM-MATRIX COMPOSITES; HIGH-PRESSURE TORSION; SEVERE PLASTIC-DEFORMATION; TENSILE PROPERTIES; CARBON NANOTUBES; STRENGTHENING MECHANISMS; ALLOY; NANOCOMPOSITES; BEHAVIOR; MICROSTRUCTURE;
D O I
10.1016/j.matdes.2018.02.024
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Dispersion of graphene in aluminum matrix has been a key factor that affects the strengthening efficiency of graphene reinforced aluminum matrix composites. Here, GNP/Al composites reinforced with 0.4 wt% and 2.0 wt% graphene nano-platelets (GNP) were fabricated by powder metallurgy (PM) followed by a multi-pass cold drawing at ambient temperature in order to eliminate the GNP aggregates. The microstructure evolution and the mechanical properties of the GNP/Al composites were investigated. Results showed that GNP cracked into pieces along the drawing direction, leading to improved GNP distribution. GNP aggregates were eliminated in 0.4 wt% GNP/Al at an equivalent drawing strain of 6.00 compared with that in the as-extruded composite, while some still exist in the 2.0 wt% GNP/Al composite. The ultimate tensile strength (UTS) of as-drawn 0.4 wt % GNP/Al composites was similar to 52% higher than that of the Al alloy. While, the mechanical properties of 2.0 wt% GNP/Al composites deteriorated because of the existence of GNP aggregates. The dispersed GNP with strong interfacial bonding in 0.4 wt% GNP/Al composites exhibited significant load transfer strengthening effect, which contributed to the improvement in UTS. The strengthening efficiency (R) of graphene in the cold-drawn composite wires reached similar to 80%, which is comparable to that of the composites fabricated by wet chemistry method. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:159 / 168
页数:10
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