Carbon Nanotube Reinforced Metallic Matrix Nano Composites

             Carbon nanotubes (CNTs) have excellent thermal conductivity and mechanical strength. It is of great interest to know how a small number of CNTs can significantly improve the thermal conductivity of matrix materials like copper or aluminum. We developed an Abaqus plug-in which can automatically generate finite element models to investigate the strengthening mechanisms and the effective thermal conductivity of carbon nanotube reinforced aluminum composites. The Random Sequential Algorithm (RSA) is deployed to randomly introduce inclusions inside the matrix while making sure that the inclusions don’t intersect with each other. Representative volume element is defined as the smallest volume over which a measurement can be made that will yield a value representative of the whole, and it can save a large amount of computational time.  Representative volume element is used for the simulations in this project. Abaqus is employed for the whole process: from 3D modeling, meshing to solving. This video is made for this competition.                                                                                                                                                                                                              Firstly, we verified the finite element models with analytical solutions. Then we found that the interfacial thermal conductivity between CNTs and metallic matrix plays a key factor in the effective thermal conductivity of CNT reinforced composites. It is interesting to found that though the thermal conductivity of CNTs is excellent if the interfacial thermal conductivity is bad, the effective thermal conductivity of composites can be worse than that of the pure matrix. Moreover, the orientation and aspect ratio of CNTs also have very important influences on the thermal conductivity and strengthening of composites. This plug-in can also be used to study the mechanical strengthening of nano-composites.