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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 1 C3N的模型结构示意图
Figure 1. Schematic diagram of C3N model structure.
图 2 NEMD模拟计算热导率的原理图
Figure 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
Figure 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
Figure 4. Thermal conductivity of C3N with different structures at 300 K.
图 5 样本长度对热导率的影响
Figure 5. Influence of sample length on thermal conductivity.
图 6 温度对热导率的影响
Figure 6. Influence of temperature on thermal conductivity.
图 7 C3N的色散曲线
Figure 7. Phonon dispersion curves for C3N.
图 8 C3N的群速度
Figure 8. Phonon group velocities for C3N.
图 9 C3N的声子态密度
Figure 9. Phonon density of states for C3N.
图 10 C3N的声子参与率
Figure 10. Phonon participation ratios for C3N.
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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