Abstract
Carbon nanotube (CNT) materials constitute a broad class of multifunctional hierarchical materials deriving their properties from the intimate connections between the atomistic structure of individual CNTs, the arrangements of CNTs into mesoscopic structural elements, such as CNT bundles and branching structures, and the structural organization of the mesoscopic elements into a macroscopic network. Due to their unique combination of structural (low density, high surface area, and nanoscale porosity), mechanical (high conformity, ability to support large reversible deformation, and absorb mechanical energy) and transport (thermal and electrical conductivity tunable over a broad range by structural modification) properties, CNT materials are attractive for a variety of applications. The strong structural sensitivity of the mechanical and thermal properties of CNT network materials makes it possible to tune the properties to the needs of practical applications, but also highlights the need for clear fundamental understanding of the structure-property relationships.
Under conditions when a systematic experimental exploration of the structure-properties relationships is hampered by the difficulty of growing CNT materials with well-controlled structures, computer modeling presents an attractive alternative. Therefore, in this study, the structure and mechanical properties of CNT network materials are investigated with a state-of-the-art mesoscale computational model. As the first step, an effective and flexible method for the generation of computational samples for mesoscopic modeling of anisotropic networks of CNT bundles with various degrees of CNT alignment is developed and applied for investigation of structural self-organization of nanotubes into vertically aligned CNT forests. Structural characteristics of the computational samples, such as bundle size distribution, average and maximum bundle sizes, magnitude of the Hermann orientation factor, and average tilt of CNT segments with respect to direction of alignment, are calculated and related to parameters of the sample preparation procedure. Good agreement between the computer-generated and experimentally grown network structures is demonstrated.
Once generated, the response of in silico vertically-aligned carbon nanotube (VACNT) forests with different densities and microstructures (bundle size distribution and degree of nanotube alignment) to uniaxial compression is measured, and a clear microscopic picture of the structural changes in the networks of interconnected CNT bundles undergoing mechanical deformation is obtained. The simulation results reveal the important role of the collective buckling hermanof CNTs across bundle cross-sections as well as a complex deformation behavior of VACNT arrays defined by an interplay of different modes of bundle deformation. The loading rate and the CNT attachment to the indenter are found to have a strong effect on the deformation mechanisms and the overall mechanical behavior of VACNT forests. A good agreement with experimental data from in situ mechanical tests is observed for the general trends and magnitudes of loss coefficients predicted in the simulations.
Mechanistically, the compressive deformation of sufficiently tall VACNT forests proceeds as a phase transformation. Mesoscale simulations of a 2-micron-high forest sample reveals the formation of a localized densified phase consisting of entangled CNT bundles oriented parallel to the indenter. At a given strain, the densified layer coexists with a rarified, vertically oriented phase characteristic of the unstrained forest, and the densification front advances with increasing compressive strain until it reaches the base of the forest. In addition, the simulations reveal the origin of the collective buckling of CNT bundles localized within a forest cross-section.
In the last part of this study, the resistance of CNT films to a high velocity impact by a metal nanoparticle is investigated. Modifications of a general coarse-grained model for the mesoscale representation of a metal projectile are introduced to make it suitable for use in simulations of high energy collisions, where local thermal equilibrium cannot be assumed. Specifically, a heat bath approach accounting for the heat capacity of the projectile material and a force scaling correction for accurate description of thermophysical properties are incorporated into the model. The first mesoscopic simulations of metal nanoparticle impact reveal an important role the network structure of the CNT films plays in defining the ballistic impact resistance. A simple analytical model is suggested for the estimation of the penetration depth of a nano-projectile into a bulk CNT network material for different impact velocities. The model is parametrized based on the results of the mesoscopic simulations, and represents an important advance in the understanding of the ballistic resistance of CNT materials.
