Computationally Guided Design of Large-Diameter Carbon Nanotube Bundles for High-Strength Materials

Large-diameter carbon nanotubes (CNTs) synthesized by floating-catalyst chemical vapor deposition (FC-CVD) assemble into bundles and subsequently into aerogel networks from which yarns and sheets are mechanically drawn. The CNT bundles exhibit unique microstructures with collapsed CNT packing, not found in other types of CNT yarns. At the same time, the bundle structure is not homogeneous and the wide variability of CNT cross-sectional shapes reflects the bundling process. Transmission electron microscopy (TEM) images allow detailed quantification of CNT diameters, shapes, and number of walls. Molecular dynamics (MD) simulations of CNT assemblies are subsequently built to match the observed CNT shape characteristics and mass densities. Contrary to an established notion of an applied buckling pressure requirement for radial collapse, MD demonstrated that interacting large-diameter CNTs can collapse spontaneously, suggesting that collapse can occur during bundling. Computational explorations of this mechanism yield conditions for large double-walled CNTs (with a mean diameter around 7.8 nm) to assemble into phases with significantly increased packing efficiencies and Young's moduli approaching 1 TPa. The results may play a guiding role in advancing FC-CVD aerogel synthesis and processing methods to yield yarn and sheets with larger densities and superior mechanical properties.

Automated summary

The study reveals that large-diameter CNTs synthesized by FC-CVD can form unique bundle structures with collapsed packing not found in other types of CNT yarns, showing wide variability in cross-sectional shapes during the bundling process. Detailed quantification of CNT diameters, shapes, and number of walls is achieved through TEM images and MD simulations. This research provides insights into the spontaneous collapse of large-diameter CNTs during bundling, potentially leading to improved packing efficiencies and mechanical properties.