Bilayer graphene kirigami

被引:3
作者
Barboza, Alexandre M. [1 ]
Aliaga, Luis C. R. [1 ]
Faria, Daiara [1 ]
Bastos, Ivan N. [1 ]
机构
[1] Univ Estado Rio De Janeiro, Polytech Inst, BR-28625570 Nova Friburgo, RJ, Brazil
来源
CARBON TRENDS | 2022年 / 9卷
关键词
Bilayer graphene; Kirigami; Molecular simulation; Machine learning; Mechanical properties; TRANSPORT CHARACTERISTICS; THERMAL-CONDUCTIVITY; STRETCHABILITY; MONOLAYER; FRACTURE;
D O I
10.1016/j.cartre.2022.100227
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Since the experimental demonstration of the kirigami technique for graphene in 2015, several studies have been conducted exploring its diverse impacts on the properties and behavior of graphene. However, as most of the studies have focused on monolayer graphene, the implications of a bilayer graphene kirigami (BGK) remain poorly understood, especially regarding mechanical response. Here, we employ a newly developed machine learning potential available in the literature to study the mechanical properties and characteristics of BGK by using molecular simulations. The effects of different cutting and stacking patterns are revealed, showing a highly stretchable material with capacity of enhancing the maximum strain by a factor of eight as compared to pristine graphene. During deformation, a large out-of-plane displacement is evidenced, along with a topological modification at the ripping interface composed of eight-membered rings. Also, a distinct structure formation is found, described as horizontally-aligned arrays of interconnected nanotubes, with capability of being employed in environments that require increased compression resistance, and further potential to serve as building blocks for complex 3D structures. (C) 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
引用
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页数:12
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