Analysis Of Thermal Properties Of Carbon Nanotube Aluminum Matrix Composites With Different Configurations

The rapid development of the electronics industry requires thermally conductive materials with higher effective thermal conductivity and lower thermal expansion coefficient to minimize the thermal stress during equipment operation.Aluminum has a lower effective thermal conductivity and a higher thermal expansion coefficient than copper,but it is lighter and cheaper,so it becomes a more attractive choice for the production of ultra-high thermal conductivity composite materials.As we all know,multi-walled carbon nanotubes have ultra-high effective thermal conductivity and ultra-low thermal expansion coefficient.This makes carbon nanotubes an excellent reinforcement material for manufacturing aluminum-based composites with high thermal conductivity and low thermal expansion coefficient.The complex microstructure of carbon nanotube aluminum-based composites has led to no universal method for estimating the effective thermal conductivity and thermal expansion coefficient of carbon nanotube-aluminum composites,which can only be found from scattered experimental data.Therefore,simulation is the most costeffective choice for predicting the thermal performance of complex structural composites.An in-depth understanding of the microscopic thermal conductivity and thermal expansion characteristics of carbon nanotube aluminum-based composites is very important for optimizing composite properties and preparation processes.In this paper,a multi-scale finite element model is used to study the effective thermal conductivity of carbon nanotube aluminum matrix composites.Five representative volume element models are established: random distribution,uniform directional distribution,layered distribution,bundled distribution,and networked distribution.In order to accurately reflect the actual microstructure,the interface layer and impurities of the microstructure were considered,and five modified models of configuration were established.The research results show that the temperature distribution of the composite material is uneven due to the presence of the reinforcing phase.Carbon nanotubes have strong anisotropy.The heat flux density is highest when the loading direction is consistent with the direction of the carbon nanotubes,and the heat flux density is the lowest when the loading direction is perpendicular to the direction of the carbon nanotubes.The effective thermal conductivity of the layered structure is the highest,and increases linearly with the increase of the volume fraction of carbon nanotubes.The prediction model without the interface layer and impurities yields higher prediction results,while the modified model with the interface layer and impurities provides a better estimate for predicting the effective thermal conductivity of carbon nanotube aluminum-based composites.The volume fraction of the reinforced phase has a greater impact on the effective thermal conductivity of the composite material.As the volume fraction of the reinforced phase increases,the effective thermal conductivity of the composite material increases.The steady-state analysis module is used to simulate and analyze the thermal expansion coefficients of five configurations of composite materials.Impurities in the microstructure have almost no effect on the thermal expansion coefficient,so five configuration modification models with interface layers but no impurities are established.The research results show that the stress and strain distribution in the composite material is very uneven.When the direction of the carbon nanotube is the same as the expansion direction,the stress and strain are the highest,and when the direction of the carbon nanotube is perpendicular to the expansion direction,the stress and strain are the lowest.The prediction result calculated by the model without the interface layer is higher,while the prediction model with the interface layer can more accurately predict the thermal expansion coefficient of the composite material.The bundled composite material has the lowest thermal expansion coefficient,and the thermal expansion coefficient of the carbon nanotube aluminum-based composite material decreases as the volume fraction of carbon nanotubes increases.In order to further explore the influence of the bundle configuration on the thermal expansion coefficient of carbon nanotube aluminum matrix composites,a bundle structure model with the same number of carbon nanotubes but different placement positions was established.The results show that the thermal expansion coefficient of the composite material decreases with the increase of the number of carbon nanotubes per bundle,and the decreasing rate tends to be flat.