2022 journal article

Digital Synthesis of Realistically Clustered Carbon Nanotubes


co-author countries: United States of America πŸ‡ΊπŸ‡Έ
author keywords: carbon nanotubes; Tersoff; molecular dynamics; clusters; digital synthesis
Source: Web Of Science
Added: October 3, 2022

A computational approach for creating realistically structured carbon nanotubes is presented to enable more accurate and impactful multi-scale modeling and simulation techniques for nanotube research. Much of the published literature to date involving computational modeling of carbon nanotubes simplifies their structure as being long and straight, and often existing as isolated individual nanotubes. However, imagery of nanotubes has shown over several decades that nanotubes agglomerate together and exhibit looping and curvature due both to inter- and intra-nanotube attraction. The research presented in this paper leverages multi-scale simulations consisting of a simple bead-spring model for initial nanotube relaxation followed by a differential geometry approach to create an atomic representation of carbon nanotubes, and then finalized with molecular dynamics simulations using the Tersoff potential model for carbon that allows dynamic bonding and cleavage. The result is atomically accurate representations of carbon nanotubes that exist as single nanotubes, or as clusters of multiple nanotubes. The presented approach is demonstrated using (5,5) single-walled carbon nanotubes. The synthesized nanotubes are shown to relax into the curving and looping structures observed in transmission or scanning electron microscopy, but also exhibit nano-scale defects due to buckling, crimping, and twisting that are resolved during the molecular dynamics simulations. These features locally compromise the desired strength characteristics of nanotubes and therefore the presented procedure will enable more accurate modeling and simulation of nanotubes in subsequent research by representing them less as the theoretically straight and independent entities, but as realistically imperfect.