  Despite the high potential for applications utilizing the unique properties
of single-walled carbon nanotubes (SWCNTs), the applications remain challenging
due to the difficulty of synthesizing SWCNTs with a specific chirality. To
elucidate the mechanisms that determine their chirality during growth,
intensive efforts have been devoted to classical molecular dynamics (MD)
simulations. However, the mechanism of chirality determination has not been
fully clarified, which can partly be attributed to the limited accuracy of
empirical interatomic potentials in reproducing the behavior of carbon and
metal atoms. In this work, we develop a neural network potential (NNP) for
carbon-metal system to accurately describe the SWCNT growth, and perform MD
simulations of SWCNT growth using the NNP. The MD simulations demonstrate the
process of defect-free chirality-definable SWCNT growth with dynamic
rearrangement of edge configurations, and the consistency between the
probability of edge configuration appearance and the entropy-driven edge
stability predicted from the nanotube-catalyst interfacial energy. It is also
shown that the edge defect formation is induced by vacancy and suppressed by
vacancy healing through adatom diffusion on the SWCNT edges. These results
provide insights into the edge formation thermodynamics and kinetics of SWCNTs,
an important clue to the chirality-controlled synthesis of SWCNTs.
