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The non-equilibrium molecular dynamics (NEMD) method is used to study the thermal conductivities of Si/Ge superlattices with tilted interface under different period lengths, different sample lengths, and different temperatures. The simulation results are as follows. The thermal conductivity of Si/Ge superlattices varies nonmonotonically with the increase of interface angle: when the period length is 4–8 atomic layers, the thermal conductivity for the interface angle of 45° is one order of magnitude larger than those for other interface angles, and the thermal conductivity increases linearly with the sample length increasing and decreases with the temperature increasing. However, when the period length is 20 atomic layers, the thermal conductivity is weakly dependent on sample length and temperature due to the existence of phonon localization.
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Keywords:
- superlattices /
- tilt angle /
- thermal conductivity /
- molecular dynamic simulation
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图 1 NEMD 模拟计算热性质的示意图
Figure 1. Schematic diagram of the NEMD model for calculating the thermal properties.
图 2 周期长度为20原子层厚度时不同界面倾斜角的示意图
Figure 2. Schematic diagram of different tilted interface angles with the period length of 20 atomic layers.
图 3 不同周期长度下热导率与倾斜角的关系
Figure 3. The relationship between thermal conductivity and tilted angle as the different period length.
图 4 不同周期长度Si/Ge超晶格的声子态密度
Figure 4. The PDOS of Si/Ge superlattices with different period lengths.
图 5 倾斜角度为45º时4Si × 4Ge和10Si × 10Ge超晶格的频谱热导
Figure 5. Spectral thermal conductance of 4Si × 4Ge and 10Si × 10Ge superlattices at the tilt angle of 45°.
图 6 不同倾斜角下Si/Ge超晶格的声子态密度
Figure 6. The PDOS of Si/Ge superlattices with different tilted angle.
图 7 Si/Ge超晶格热导率与样本长度的关系
Figure 7. Thermal conductivity of Si/Ge superlattice vs. sample total length.
图 8 Si/Ge超晶格热导率与温度的关系
Figure 8. Temperature dependent thermal conductivity of Si/Ge superlattice.
图 9 (a)不同周期长度时的声子参与率; (b)不同样本长度的声子参与率
Figure 9. (a)The participation ratio of superlattices with different period length; (b) the participation ratio of superlattices with different sample length.
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[1] 张玉, 吴立华, 曾李骄开, 刘叶烽, 张继业, 邢娟娟, 骆军 2016 物理学报 65 107201
Google Scholar
Zhang Y, Wu L H, Zengli J K, Liu Y F, Zhang J Y, Xing J J, Luo J 2016 Acta. Phys. Sin. 65 107201
Google Scholar
[2] 张程宾, 程启坤, 陈永平 2014 物理学报 63 236601
Google Scholar
Zhang C B, Cheng Q K, Chen Y P 2014 Acta. Phys. Sin. 63 236601
Google Scholar
[3] Chen Z Y, Wang R F, Wang G Y, Zhou X Y, Wang Z S, Yin C, Hu Q, Zhou B Q, Tang J, Ang R 2018 Chin. Phys. B 27 47202
Google Scholar
[4] Wang K X, Wang J W, Li Y, Zou T, Wang X H, Li J B, Cao Z, Shi W J, Xinba Yaer 2018 Chin. Phys. B 27 48401
Google Scholar
[5] Xu X, Zhou J, Chen J 2020 Adv. Funct. Mater 30 1904704
Google Scholar
[6] Zhang Z W, Ouyang Y L, Cheng Y, Chen J, Li N B, Zhang G 2020 Phys. Rep.-Rev. Sec. Phys. Lett. 860 1
[7] 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
[8] Yang R, Chen G 2004 Phys. Rev. B 69 195316
Google Scholar
[9] Chen G 1998 Phys. Rev. B 57 14958
Google Scholar
[10] Hu M, Poulikakos D 2012 Nano Lett. 12 5487
Google Scholar
[11] Juntunen T, Vänskä O, Tittonen I 2019 Phys. Rev. Lett. 122 105901
Google Scholar
[12] Xiong R, Yang C, Wang Q, Zhang Y, Li X 2019 Int. J. Thermophys. 40 86
Google Scholar
[13] Garg J, Bonini N, Marzari N 2011 Nano Lett. 11 5135
Google Scholar
[14] Luckyanova M N, Garg J, Esfarjani K, Jandl A, Bulsara M T, Schmidt A J, Minnich A J, Chen S, Dresselhaus M S, Ren Z F, Fitzgerald E A, Chen G 2012 Science 338 936
Google Scholar
[15] Cheaito R, Polanco C A, Addamane S, Zhang J, Ghosh A W, Balakrishnan G, Hopkins P E 2018 Phys. Rev. B 97 085306
Google Scholar
[16] Tian Z, Esfarjani K, Chen G 2014 Phys. Rev. B 89 235307
Google Scholar
[17] Tian Z, Esfarjani K, Chen G 2012 Phys. Rev. B 86 235304
Google Scholar
[18] Garg J, Chen G 2013 Phys. Rev. B 87 93
[19] Elapolu M S R, Tabarraei A 2018 Comput. Mater. Sci. 144 161
Google Scholar
[20] 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
[21] Fujii S, Yokoi T, Yoshiya M 2019 Acta Mater. 171 154
Google Scholar
[22] Bagri A, Kim S P, Ruoff R S, Shenoy V B 2011 Nano Lett. 11 3917
Google Scholar
[23] Tan M, Hao Y, Deng Y, Yan D, Wu Z 2018 Sci Rep 8 6384
Google Scholar
[24] Schelling P K, Phillpot S R, Keblinski P 2002 Phys. Rev. B 65 144306
Google Scholar
[25] Plimpton S 1995 J. Comput. Phys. 117 1
Google Scholar
[26] Dickey J M, Paskin A 1969 Phys. Rev. 188 1407
Google Scholar
[27] Chen J, Zhang G, Li B 2010 Nano Lett. 10 3978
Google Scholar
[28] Zhang Z, Chen Y, Xie Y, Zhang S 2016 Appl. Therm. Eng. 102 1075
Google Scholar
[29] Zhang Z W, Hu S Q, Xi Q, Nakayama T, Volz S, Chen J, Li B W 2020 Phys. Rev. B 101 081402 6
[30] Liang T, Zhou M, Zhang P, Yuan P, Yang D 2020 Int. J. Heat Mass Transfer 151 119395
Google Scholar
[31] Liu Q, Luo H, Wang L, Shen S 2017 J. Phys. D-Appl. Phys. 50 065108
Google Scholar
[32] Ma Y L, Zhang Z W, Chen J G, Saaskilahti K, Volz S, Chen J 2018 Carbon 135 263
Google Scholar
[33] Sääskilahti K, Oksanen J, Tulkki J, Volz S 2014 Phys. Rev. B 90 134312
Google Scholar
[34] Sääskilahti K, Oksanen J, Tulkki J, Volz S 2016 Phys. Rev. E 93 052141
Google Scholar
[35] Hu S Q, Zhang Z W, Jiang P F, Ren W J, Yu C Q, Shiomi J, Chen J 2019 Nanoscale 11 11839
Google Scholar
[36] Hu S Q, Zhang Z W, Jiang P F, Chen J, Volz S, Nomura M, Li B W 2018 J. Phys. Chem. Lett. 9 3959
Google Scholar
[37] Zhang Z W, Hu S Q, Nakayama T, Chen J, Li B W 2018 Carbon 139 289
Google Scholar
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