分子动力学
碳纳米管
空位缺陷
材料科学
手性(物理)
纳米管
纳米技术
化学物理
原子间势
纳米颗粒
扩散
计算化学
化学
物理
结晶学
热力学
手征对称破缺
量子力学
夸克
Nambu–Jona Lasinio模型
作者
Ikuma Kohata,Ryo Yoshikawa,Kaoru Hisama,Shigeo Maruyama
出处
期刊:Cornell University - arXiv
日期:2023-02-18
标识
DOI:10.48550/arxiv.2302.09264
摘要
Classical molecular dynamics (MD) simulations have been performed to elucidate the mechanism of single-walled carbon nanotube (SWCNT) growth. However, discussing the chirality has been challenging due to topological defects in simulated SWCNTs. Recently, the application of neural network to interatomic potentials has been actively studied and such interatomic potentials are called neural network potentials (NNPs). NNPs have a better ability for approximate functions and can predict complex systems' energy more accurately than conventional interatomic potentials. In this study, we developed an NNP to describe SWCNT growth more accurately. We successfully demonstrated defect-free and chirality-definable growth of SWCNTs on Fe nanoparticles by MD simulation. Furthermore, it was revealed that edge vacancies of SWCNTs caused defect formation and adatom diffusion contributed to vacancy healing, preventing defect formation.
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