Abstract
Computational design for property management of composite materials offers a cost sensitive alternate approach in order to understand the mechanisms involved in the thermal and structural behavior of material under various combinations of inclusions and matrix material. The present study is concerned with analyzing the elasto-plastic and thermal behavior of Al2O3-Ni droplet composites using a mean field homogenization and effective medium approximation (EMA) using an in-house code. Our material design approach relies on a method for predicting potential optimum thermal and structural properties for Al2O3-Ni composites by considering the effect of inclusion orientation, volume, size, thermal interface resistance, percolation and porosity. The primary goal for designing such alumina-based composites is to have enhanced thermal conductivity for effective heat dissipation and spreading capabilities. At the same time, other functional properties like thermal expansion coefficient, elastic modulus, and electrical resistivity have to be maintained or enhanced. The optimum volume fraction was found to occur between 15 and 20 vol. %Ni while the average nickel particle size of 5 mu m was found a minimum size that will enhance the thermal conductivity. The Young's modulus was found decreasing as the volume fraction of nickel increases, which would result in enhanced fracture toughness. Electrical conductivity was found to be greatly affected by the percolation phenomenon in the designed range of volume fraction minimum particle size. As a validation, Al2O3 composites with 10% and 15 % volume fraction Ni and droplet size of 18 mu m are developed using spark Plasma Sintering process. Thermal conductivity and thermal expansion coefficient of the samples are measured to complement the computational design. Microstructural analysis of the sintered samples was also studied using optical microscope to study the morphology of the developed samples. It was found that the present computational design tool was accurate enough in predicting the desired properties of Al2O3- Ni composites.