Thermal and electronic properties of borophene in two-dimensional lateral graphene-borophene heterostructures empowered by machine-learning approach

被引:2
作者
Chen, Jiali [1 ,2 ]
Wang, Zixuan [2 ]
Ma, Jiangjiang [2 ]
Cao, Zhongyin [2 ]
Li, Kexun [3 ]
Zhang, Junfeng [1 ,2 ]
机构
[1] Hainan Normal Univ, Coll Phys & Elect Engn, Haikou 571158, Peoples R China
[2] Shanxi Normal Univ, Sch Phys & Informat Engn, Taiyuan 030031, Peoples R China
[3] Technol Grp Corp, Res Inst China Elect 33, Taiyuan 030031, Peoples R China
基金
中国国家自然科学基金;
关键词
Lateral heterostructures; Machine learning; Thermal conductivity; Graphene; Borophene; BORON-NITRIDE; TRANSPORT-PROPERTIES; PLANE-WAVE; CONDUCTIVITY; INTERFACES; SILICENE; LI; NA;
D O I
10.1016/j.carbon.2024.119533
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Due to its electron-deficient character and complicated banding mechanism, two-dimensional (2D) borophene has gain more attentions recently. The polymorphism of 2D borophene provides more room for forming the 2D lateral heterostructures. However, the effects of confined circumstance on many properties of the borophene are unknown. In this work, using first-principles calculations and molecular simulations based on the machine learning interatomic potential, we investigated the electronic structures and thermal properties of 2D lateral graphene-borophene heterostructures (GBHs). We found that the graphene-borophene heterostructure promotes the thermal transport of borophene, and different concentrations of borophene hardly affect the lattice thermal conductivity of the interface. We also found the charge transfer induced thermal conductivity change in borophene domain of GBH, compared with that of bulk borophene. The present results not only advance our understanding of 2D lateral GBHs, but also provide valuable information on the heat transfer properties of 2D heterogeneous graphene-based materials in practical applications.
引用
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页数:9
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