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类石墨烯氮化碳结构(C3N)作为一种全新的碳基二维半导体材料, 由于其优异的机械和电子性能引起了研究者们的广泛关注, 不同结构C3N的热输运和声子输运机制还待进一步研究. 本文构造了4种不同结构的C3N, 采用非平衡分子动力学与晶格动力学方法对不同结构的C3N的热传导机理进行了研究. 研究结果表明: 1)在4种结构中M3热导率最高, M1次之, M4热导率最低; 2)不同结构的C3N的热导率具有明显的尺寸效应和温度效应. 当样本长度较短时, 声子主要以弹道输运的方式进行传输; 当样本长度增大, 扩散输运占主导地位; 随着温度的升高, Umklapp散射在热输运中占据主导地位, 使得热导率与温度具有1/T的依赖性. 3)与M3相比, M1和M4结构中都存在更大的声子带隙, 色散曲线进一步软化, 低频和高频声子同时出现了局域化的特征, 对热导率产生了显著的抑制作用. 本文为更好地设计热管理材料提供了思路.As a new graphene-based two-dimensional semiconductor material, C3N has received extensive attention from researchers due to its excellent mechanical and electronic properties. Whether there is any difference in the phonon transport mechanism among different C3N structures remains to be further investigated. Therefore, four kinds of C3N structures with different patterns are constructed in this paper, and their thermal conduction mechanisms are studied by the non-equilibrium molecular dynamics (NEMD) method. The research results are shown as follows. 1) Among these four patterns, the C3N (M3) with the perfect structure has the highest thermal conductivity, followed by M1, and M4 has the lowest thermal conductivity. 2) Moreover, the thermal conductivities of C3N with different patterns have obviously different size and temperature effects. When the sample length is short, the phonon transport is mainly ballistic transport, while diffusion transport dominates the heat transport when the sample length further increases. As the temperature increases, Umklapp scattering dominates the heat transport, making the thermal conductivity and temperature show a 1/T trend. 3) Comparing with M3 , the patterns of M1 and M4 have large phonon band gaps, and their dispersion curves are further softened. At the same time, regardless of low-frequency or high-frequency phonons, localized features appear in the M1 and M4 (especially the M4), which has a significant inhibitory effect on thermal conductivity. This paper provides an idea for the better design of thermal management materials.
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Keywords:
- carbon-based two-dimensonal materials /
- Graphene-like structure /
- phonon transport /
- localization
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图 2 NEMD模拟计算热导率的原理图
Fig. 2. Schematic diagram of thermal conductivity calculated by NEMD simulation.
图 3 C3N中温度分布和能量分布 (a) 模型的温度分布; (b) 热源和冷源能量
Fig. 3. Temperature distribution and energy variation in C3N model: (a) Temperature distribution of the model; (b) heat source and heat sink energy
图 4 不同结构的C3N在300 K下的热导率的热导率
Fig. 4. Thermal conductivity of C3N with different structures at 300 K.
表 1 C3N原子相互作用的Tersoff势函数参数[20]
Table 1. Tersoff potential function parameters of C3N atom interactions.
参数 C C X C N X N C X A/eV 1393.6 1386.78 1386.78 B/eV 430 387.575 387.575 $ {\lambda ^1} $ 3.4879 3.5279 3.5279 $ {\lambda ^2} $ 2.2119 2.2054 2.2054 $ {\lambda ^3} $ 0 0 0 $ m $ 3 3 3 $ n $ 0.72751 0.72751 0.72751 $ \beta ({10^{ - 7}}) $ 1.5724 1.5724 1.5724 $ \gamma $ 1 1 1 $ c $ 38049 38049 25000 $ d $ 4.3484 4.3484 4.3484 $ \cos \theta $ -0.93 -0.93 -0.93 (R–D)/Å 1.8 1.85 1.85 (R+D)/Å 2.1 2.05 2.05 
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[1] Novoselov K S, Geim A K, Morozov S V 2004 Science 306 666
Google Scholar
[2] Novoselov K S, Geim A K, Morozov S V 2005 Nature 438 197
Google Scholar
[3] Geim A K, Novoselov K S 2007 Nat. Mater. 6 183
Google Scholar
[4] Wu T, Zhang X, Yuan Q 2016 Nat. Mater. 15 43
Google Scholar
[5] Schwierz F 2010 Nat. Nanotechnol. 5 487
Google Scholar
[6] Meric I, Han M Y, Young A F 2008 Nat. Nanotechnol. 3 654
Google Scholar
[7] Kim W, Li C, Chaves F A 2016 Adv. Mater. 28 1845
Google Scholar
[8] Yarifard M, Davoodi J, Rafii-Tabar H 2016 Comput. Mater. Sci. 111 247
Google Scholar
[9] Balasubramanian K, Biswas T, Ghosh P 2019 Nat. Commun. 10 1090
Google Scholar
[10] Meyer J C, Geim A K, Katsnelson M I 2007 Nature 446 60
Google Scholar
[11] Bianco E, Butler S, Jiang S 2013 ACS Nano 7 4414
Google Scholar
[12] Teter David M, Hemley Russell J 1996 Science 271 53
Google Scholar
[13] Mahmood J, Jung S-M, Kim S-J 2015 Chem. Mater. 27 4860
Google Scholar
[14] Yang S, Li W, Ye C 2017 Adv. Mater. 29 1605625
Google Scholar
[15] Wei W, Yang S, Wang G 2021 Nat. Electron. 4 486
Google Scholar
[16] Mortazavi B 2017 Carbon 118 25
Google Scholar
[17] Gao Y, Wang H, Sun M 2018 Phys. E 99 194
Google Scholar
[18] Peng B, Mortazavi B, Zhang H 2018 Phys. Rev. Appl. 10 034046
Google Scholar
[19] Plimpton S 1995 J. Comput. Phys. 117 1
Google Scholar
[20] Kinaci A, Haskins J B, Sevik C 2012 Phys. Rev. B 86 115410
Google Scholar
[21] Song J, Xu Z, He X 2019 Phys. Chem. Chem. Phys. 21 12977
Google Scholar
[22] Kumar S, Sharma S, Babar V 2017 J. Mater. Chem. A 5 20407
Google Scholar
[23] Wei N, Chen Y, Cai K 2016 Carbon 104 203
Google Scholar
[24] 惠治鑫, 贺鹏飞, 戴瑛, 吴艾辉 2014 物理学报 63 074401
Google Scholar
Hui Z X, He P F, Dai Y, Wu A H 2014 Acta. Phys. Sin. 63 074401
Google Scholar
[25] An M, Li L, Hu S 2020 Carbon 162 202
Google Scholar
[26] 刘英光, 边永庆, 韩中合 2020 物理学报 69 033101
Google Scholar
Liu Y G, Bian Y Q, Han Z H 2020 Acta. Phys. Sin. 69 033101
Google Scholar
[27] Gale J D 1997 J. Chem. Soc. Faraday trans. 93 629
Google Scholar
[28] Dickey J M, Paskin A 1969 Phys. Rev. 188 1407
Google Scholar
[29] Chen J, Walther J H, Koumoutsakos P 2014 Nano Lett. 14 819
Google Scholar
[30] Cui L, Wei G, Li Z 2021 Int. J. Heat Mass Transf. 165 120685
Google Scholar
[31] Luckyanova M N, Mendoza J, Lu H 2018 Sci. Adv. 4 9460
Google Scholar
[32] Chen J, Zhang G, Li B 2010 Nano Lett. 10 3978
Google Scholar
[33] Ning D, Yuan M, Wu L 2020 Nat. Commun. 11 4717
Google Scholar
[34] Bodapati A, Schelling P K, Phillpot S R 2006 Phys. Rev. B 74 4070
Google Scholar
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