Abstract
In elasto-capillary driven self-assembly of arrays of carbon nanotubes (CNTs) different factors play a role, from the mechanical properties of CNTs to the array geometry. In this work, we provide a multi-scale investigation where we first use density functional theory (DFT) to predict fully ab initio relevant mechanical properties such as Young's modulus, Poisson's ratio, and surface energy. To the best of our knowledge, we are the first to report DFT calculations of the surface energy of CNTs. Then, we feed the computed DFT parameters into a model for capillary-force-driven self-assembly of CNTs. By doing so, we are able to derive and predict cross-correlation between material parameters and array architecture.