Simulation of Thermal Expansion Coefficient of Configurational GNPs/2009Al Composites
ZHOU Li1, ZHANG Mingyuan1, YANG Xinsheng1(), LIU Zhenyu2(), WANG Quanzhao2, XIAO Bolv2, MA Zongyi2
1 School of Electromechanical and Automotive Engineering, Yantai University, Yantai 264005, China 2 Shi -changxu Innovation Center for Advanced Materials, Institute of Metal Research, Chinese Academy of Sciences, Shenyang 110016, China
Cite this article:
ZHOU Li, ZHANG Mingyuan, YANG Xinsheng, LIU Zhenyu, WANG Quanzhao, XIAO Bolv, MA Zongyi. Simulation of Thermal Expansion Coefficient of Configurational GNPs/2009Al Composites. Acta Metall Sin, 2024, 60(7): 977-989.
Nanocomposites comprising of graphene nanoplatelets (GNPs) and aluminum (Al) have gained tremendous interest over the past few decades owing to their exceptional mechanical, thermal, and electrical properties. The microstructure of GNPs in these composites, such as dispersion, and orientation, significantly affects the loading capacity and thermal properties. However, previous studies on the mechanical properties have overshadowed investigations into the thermal expansion coefficient of GNPs/Al composites with different microstructures. In this study, a three-dimensional model of microscopic GNPs/2009Al composites was established using the finite element method and the software ABAQUS. The effects of the distribution, geometric configuration, and volume fraction of graphene nanoplatelets on the thermal expansion coefficient of the composite were analyzed. Results show that the thermal expansion coefficient of the composite is less affected by the distribution form of graphene nanoplatelets. However, when the distribution form of graphene nanoplatelets is 2 clusters, the thermal expansion coefficient is smaller than other distribution forms. Moreover, the geometry and volume fraction of graphene nanoplatelets have a significant effect on the thermal expansion coefficient. An increase in the volume fraction of graphene nanoplatelets leads to a decrease in the thermal expansion coefficient of the composites. When the volume fraction of graphene nanoplatelets in the composite is 2.5% and the aggregate distribution is bundled, the thermal expansion coefficient decreases the most (by about 27%) compared to the matrix. By comparing with experimental results, the validity of the model is verified. The conclusions of this study can provide a theoretical basis for designing and optimizing the configuration of graphene nanoplatelets/aluminum matrix composites.
Fund: National Natural Science Foundation of China(51931009);National Natural Science Foundation of China(52120105001);Natural Science Foundation of Shandong Province(ZR2023ME097)
Corresponding Authors:
LIU Zhenyu, associate professor, Tel: (024)23971749, E-mail: zyliu@imr.ac.cn;
Fig.1 Representative volume element (RVE) model of graphene nanoplatelets (GNPs)/2009Al composites (a) whole model (b) meshing (Inset shows the local mesh refinement)
Fig.2 Local coordinates and material direction
Property
Parameter
GNPs[25]
2009Al[26]
Unit
Elastic property
E1 = E2
943600
69000
MPa
E3
19500
69000
MPa
ν12
0.14
0.35
ν13
-0.09
0.35
ν23
-0.09
0.35
G12
414180
25555
MPa
G13 = G23
5010
25555
MPa
Thermal expansion coefficient
α1 = α2
-5
23.2
10-6oC-1
α3
0.75
23.2
10-6oC-1
Table 1 Material properties used in the finite element simulation[25,26]
Fig.3 Two corresponding nodes on the opposite surfaces
Fig.4 Boundary conditions (U1, U2, and U3 are displacements in the x, y, and z directions, respectively)
Fig.5 Axial views (a1-a4) and cross-sectional views (b1-b4) of RVE with different GNPs distributions (a1, b1) one cluster (a2, b2) two clusters (a3, b3) four clusters (a4, b4) eight clusters
Fig.6 X-direction stress (σ11) distributions of GNPs/2009Al composites with different GNPs distributions (a) one cluster (b) two clusters (c) four clusters (d) eight clusters
Fig.7 σ11 distributions of GNPs with different GNPs distributions (a) one cluster (b) two clusters (c) four clusters (d) eight clusters
Fig.8 X-direction strain (ε11) distributions of GNPs/2009Al composites with different GNPs distributions (a) one cluster (b) two clusters (c) four clusters (d) eight clusters
Fig.9 ε11 distributions of GNPs with different GNPs distributions (a) one cluster (b) two clusters (c) four clusters (d) eight clusters
Fig.10 Effects of GNPs distribution on thermal expansion coefficient of GNPs/2009Al composites
Fig.11 Schematics of RVE model with five GNPs configurations (a) layered (b) evenly oriented (c) bundled (d) networked (e) randomly arranged
Fig.12 σ11 distributions of GNPs/2009Al composite with different GNPs configurations (a) layered (b) evenly oriented (c) bundled (d) networked (e) randomly arranged
Fig.13 σ11 distributions of GNPs with different GNPs configurations (a) layered (b) evenly oriented (c) bundled (d) networked (e) randomly arranged
Fig.14 ε11 distributions of GNPs/2009Al composites with different GNPs configurations (a) layered (b) evenly oriented (c) bundled (d) networked (e) randomly arranged
Fig.15 ε11 distributions of GNPs with different configurations (a) layered (b) evenly oriented (c) bundled (d) networked (e) randomly arranged
Fig.16 Schematics of point paths at different angles (a) 0° (b) 30° (c) 45° (d) 60° (e) 90°
Fig.17 Strains at various points on different paths
Fig.18 Effect of GNPs configurations on thermal expansion coefficient of GNPs/2009Al composites
Fig.19 Thermal expansion coefficients of GNPs/2009Al composites as a function of volume fraction of GNPs
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