Chirality-Dependent Kinetics of Single-Walled Carbon Nanotubes from Machine-Learning Force Fields

The origin of the chirality of single-walled
carbon nanotubes (SWCNTs)
has been a long-standing dispute. Molecular dynamics (MD) simulations
driven by machine-learning force fields (MLFFs), which can study the
interface dynamics under near ab initio accuracy, provide a powerful
technique to reveal the formation mechanism of SWCNTs. Here, we develop
a cobalt–carbon MLFF and perform growth simulations on a cobalt
catalyst to investigate the chirality preference of the growth of
SWCNTs under the vapor–liquid–solid (VLS) regime. Through
microkinetic modeling, we reproduce the observed growth and defect
kinetics, demonstrating their dependence on the chirality. It is observed
that while the initial chirality assignment is likely related to the
configurational degeneracy of the nanotube caps, pentagon defects
immediately form and resolve after nucleation. Such processes, which
we name diameter control mechanisms, not only control the diameter
toward an optimum but also shift the chirality distribution drastically.
Our simulation shows a preference toward the (6,5) chirality, which
is also widely observed experimentally. Our work offers a microkinetic
modeling workflow for the chirality-dependent kinetics of the SWCNTs,
highlighting the important contribution of the defect kinetics to
the chirality origination.