Molecular dynamics simulation of graphene deposition and growth on WC-Co cemented carbides

Ding Ye-Zhang; Ye Yin; Li Duo-Sheng; Xu Feng; Lang Wen-Chang; Liu Jun-Hong; Wen Xin

doi:10.7498/aps.72.20221332

Abstract

In this paper, molecular dynamics is used to simulate the self-assembly of carbon atoms and the growth of graphene on the surface of cemented carbide, which has some advantages, such as reducing manufacturing costs, shortening the experimental cycle, and optimizing the preparation parameters of graphene. A proper potential function is designed to simulate the formation of graphene on the WC ($10 \bar{1} 0$) surface and Co (0001) surface by a single carbon atom. The growth process of graphene, such as the deposition of carbon atoms, the formation of carbon chains with different lengths, the transformation about carbon chains into polygons, and the basic units and natural defects of graphene are investigated in detail. Three processes of self-repair of graphene defects, including carbon chain rotation, splitting and embedding, are described respectively. The effects of temperature and carbon deposition rate on the growth of high-quality graphene are also studied. The simulation results show that at low temperature, the mobility of carbon atoms is low and grown graphene contains a lot of defects, and the coverage of the substrate is low, which leads to low quality graphene to be prepared. High temperature promotes the migration of carbon atoms and helps to grow high quality graphene. However, high temperature can cause damage to the substrate and reduce the flatness of the growing graphene. At a higher deposition rate, the nucleation rate of graphene is higher and the distribution is more uniform. However, due to the different ability of each graphene nucleus to absorb carbon atoms, there are many macrocyclic defects in the graphene. The low deposition rate has a longer annealing time, which excessively stimulates the migration of carbon atoms. It leads to the aggregation of carbon atoms and reduce the quality of graphene. The proper deposition rate can ensure the nucleation density of graphene, and at the same time, it has enough time to form six membered rings and repair defects, which is conducive to the formation of the high quality graphene. Therefore, it is significantly important to design the appropriate deposition temperature and deposition rate for the growth of high-quality graphene. After optimizing the simulation parameters, high-quality graphene is successfully grown at 1300 K deposition temperature and 10 ps/C deposition rate.

Keywords:

Authors and contacts

1.
School of Materials Science and Engineering, Nanchang HangKong University, Nanchang 330063, China
2.
School of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
3.
Suzhou Ion-tech Nano Technology Co., Ltd, Suzhou 215163, China

Corresponding author: Li Duo-Sheng, duosheng.li@nchu.edu.cn ; Xu Feng, xufeng@nuaa.edu.cn ;

Funds: Project supported by the National Natural Science Foundation of China (Grant Nos. 51562027, 12062016, 51975287), the Key Project of Key Research and Development Program of Jiangxi Province, China (Grant No. 20201BBE51001), the Advantage Technology Innovation Team of Jiangxi Province, China (Grant No. 20181BCB24007), and the Key Research and Development Program of Jiangsu Province (Industrial Prospects and Key Core Technologies), China (Grant No. BE2021055).

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References

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Cited By

图 1 石墨烯在WC-Co表面沉积的模拟模型

Figure 1. Simulation model of graphene on the surface of WC-Co

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图 2 在1300 K时, 弛豫20 ps的 WC-Co势能变化

Figure 2. Variation of the potential energy of WC-Co within 20 ps relaxation time at 1300 K.

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图 3 石墨烯在不同温度下的正面及侧面生长情况　(a), (c), (e) 分别为1100, 1300, 1500 K时的俯视图; (b), (d), (f) 分别为1100, 1300, 1500 K时的主视图

Figure 3. Front and side growth of graphene at different temperatures: (a), (c), (e) Top views at 1100, 1300, 1500 K; (b), (d), (f) front views at 1100, 1300, 1500 K.

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图 4 不同温度下, 生长石墨烯的质量　(a) 不同温度下, 石墨烯中五元、六元和七元碳环数; (b) 黑色折线表示不同温度下, 五元和六元碳环所占的比例; 蓝色折线表示不同温度下, 石墨烯的RMS值

Figure 4. Quality of growing graphene at different temperatures: (a) The number of five, six, and seven-membered carbon rings in graphene at different temperatures; (b) the black broken line represents the proportions of five and six-membered carbon rings at different temperatures; the blue broken line represents the RMS values of graphene at different temperatures.

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图 5 不同CDR下, 生长石墨烯的正视图、侧视图以及三维形貌图　(a), (b), (c), (d) CDR为2, 5, 10, 20 ps/C时的正视图; (e), (f), (g), (h) CDR为2, 5, 10, 20 ps/C时的侧视图; (i), (j), (k), (l) CDR为2, 5, 10, 20 ps/C时的三维形貌图

Figure 5. Front view, side view and topography of growing graphene under different CDRs: (a), (b), (c), (d) The front views at CDRs of 2, 5, 10, 20 ps/C; (e), (f), (g), (h) the side views at CDRs of 2, 5, 10, 20 ps/C; (i), (j), (k), (l) three-dimensional topography at CDRs of 2, 5, 10, 20 ps/C.

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图 6 不同CDR下生长石墨烯的碳环数目

Figure 6. Quality of graphene grown under different CDRs.

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图 7 在不同时间, 在硬质合金表面生长石墨烯的正视图　(a) 0.229 ns; (b) 0.250 ns; (c) 0.264 ns; (d) 0.405 ns; (e) 0.411 ns; (f) 0.587 ns; (g) 0.676 ns; (h) 1.649 ns; (i) 3.070 ns

Figure 7. Front views of graphene growth on cemented carbide at different times: (a) 0.229 ns; (b) 0.250 ns; (c) 0.264 ns; (d) 0.405 ns; (e) 0.411 ns; (f) 0.587 ns; (g) 0.676 ns; (h) 1.649 ns; (i) 3.070 ns.

DownLoad: Full-Size Img PowerPoint

图 8 石墨烯缺陷自修复过程　(a), (b)碳链旋转过程; (c), (d)分裂生成过程; (e), (f)嵌入生成过程

Figure 8. Graphene defect self-healing process: (a), (b) The carbon chain rotation process; (c), (d) the splitting generation process; (e), (f) the intercalation generation process.

DownLoad: Full-Size Img PowerPoint

表 1 WC的ABOP使用的拟合参数, W-C 系统的参数取自文献[23]

Table 1. Fit parameters used by the ABOP of WC, the parameters for the W-C system are taken from Ref. [23].

	W-W	W-C	C-C
D₀/eV	5.41861	6.64	6.0
r₀/Å	2.34095	1.90547	1.39
β/Å^–1	1.38528	1.80370	2.1
S	1.92708	2.96149	1.22
γ	1.88227$ \times {10}^{-3} $	7.2855$ \times {10}^{-2} $	2.0813$ \times {10}^{-4} $
α/Å^–1	0.45876	0.0	0.0
c	2.14969	1.10304	330
d	0.17126	0.33018	3.5
h	–0.27780	0.75107	1.0
R/Å	3.5	2.8	1.85
D/Å	0.3	0.2	0.15

DownLoad: CSV

[1]	Barfmal M, Montazeri A 2017 Ceram. Int. 43 17167 Google Scholar
[2]	林奎鑫, 李多生, 叶寅, 江五贵, 叶志国, Qin Qinghua, 邹伟 2018 物理学报 67 246802 Google Scholar Lin K X, Li D S, Ye Y, Jiang W G, Ye Z G, Qin Q H, Zou W 2018 Acta Phys. Sin. 67 246802 Google Scholar
[3]	Novoselov K S, Geim A K, Morozov S V, Jiang D, Zhang Y, Dubonos S V, Grigorieva I V, Firsov A A 2004 Science 306 666 Google Scholar
[4]	Kumar N, Salehiyan R, Chauke V, Joseph Botlhoko O, Setshedi K, Scriba M, Masukume M, Sinha Ray S 2021 FlatChem 27 100224 Google Scholar
[5]	Manawi Y M, Ihsanullah, Samara A, Al-Ansari T, Atieh M A 2018 Materials 11 822 Google Scholar
[6]	Shi Q, Tokarska K, Ta H Q, Yang X, Liu Y, Ullah S, Liu L, Trzebicka B, Bachmatiuk A, Sun J, Fu L, Liu Z, Rümmeli M H 2020 Adv. Mater. Interfaces 7 1902024 Google Scholar
[7]	Dong Y, Guo S, Mao H, Xu C, Xie Y, Deng J, Wang L, Du Z, Xiong F, Sun J 2019 ACS Appl. Electron. Mater. 2 238 Google Scholar
[8]	Kim S, Shin S, Kim T, Du H, Song M, Lee C W, Kim K, Cho S, Seo D H, Seo S 2016 Carbon 98 352 Google Scholar
[9]	Sein H, Ahmed W, Rego C A, Jones A N, Amar M, Jackson M, Polini R 2003 J. Phys. Condens. Matter. 15 S2961 Google Scholar
[10]	Tian Q, Huang N, Yang B, Zhuang H, Wang C, Zhai Z, Li J, Jia X, Liu L, Jiang X 2017 J. Mater. Sci. Technol. 33 1097 Google Scholar
[11]	Kim J S, Park Y M, Bae M K, Kim C W, Kim D W, Shin D C, Kim T G 2018 Mod. Phys. Lett. B 32 1850236 Google Scholar
[12]	Liu K, Ren E, Ma J, Cao Y, Du J, Ming W, Li X, Li B 2020 J. Mater. Sci. 55 4251 Google Scholar
[13]	李锦锦, 李多生, 洪跃, 邹伟, 何俊杰 2017 物理学报 66 217101 Google Scholar Li J J, Li D S, Hong Y, Zou W, He J J 2017 Acta Phys. Sin. 66 217101 Google Scholar
[14]	王泽, 李国禄, 王海斗, 徐滨士, 康嘉杰 2014 材料导报 28 91 Google Scholar Wang Z, Li G L, Wang H D, Xu B S, Kang J J 2014 Mater. Rev. 28 91 Google Scholar
[15]	颜超, 段军红, 何兴道 2010 物理学报 59 8807 Google Scholar Yan C, Duan J H, He X D 2010 Acta Phys. Sin. 59 8807 Google Scholar
[16]	Rong Y, Zhang L, He H 2021 Thin Solid Films 732 138778 Google Scholar
[17]	Kametani N, Nakamura M, Yashiro K, Takaki T 2022 Comput. Mater. Sci. 209 111420 Google Scholar
[18]	Nasim M, Vo T Q, Mustafi L, Kim B H, Lee C S, Chu W S, Chun D M 2019 Comput. Mater. Sci. 169 109091 Google Scholar
[19]	Shibuta Y, Elliott J A 2009 Chem. Phys. Lett. 472 200 Google Scholar
[20]	Xu Z, Yan T, Liu G, Qiao G, Ding F 2016 Nanoscale 8 921 Google Scholar
[21]	白清顺, 窦昱昊, 何欣, 张爱民, 郭永博 2020 物理学报 69 226102 Google Scholar Bai Q S, Dou Y H, He X, Zhang A M, Guo Y B 2020 Acta Phys. Sin. 69 226102 Google Scholar
[22]	Edin E, Blomqvist A, Lattemann M, Luo W, Ahuja R 2019 Int. J. Refract. Met. Hard Mater. 85 105054 Google Scholar
[23]	Juslin N, Erhart P, Träskelin P, Nord J, Henriksson K O E, Nordlund K, Salonen E, Albe K 2005 J. Appl. Phys. 98 123520 Google Scholar
[24]	Petisme M V G, Gren M A, Wahnström G 2015 Int. J. Refract. Met. Hard Mater. 49 75 Google Scholar
[25]	Feng Q, Song X Y, Xie H X, Wang H B, Liu X M, Yin F X 2017 Mater. Design. 120 193 Google Scholar
[26]	Daw M S, Baskes M I 1984 Phys. Rev. B 29 6443 Google Scholar
[27]	Stuart S J, Tutein A B, Harrison J A 2000 J. Chem. Phys. 112 6472 Google Scholar
[28]	Morse P M 1929 Phys. Rev. 34 57 Google Scholar
[29]	冯艳, 段海明 2011 原子与分子物理学报 28 251 Google Scholar Feng Y, Duan H M 2011 J. At. Mol. Phys. 28 251 Google Scholar
[30]	Jones J E 1924 Proc. R. Soc. London, Ser. A 106 463 Google Scholar
[31]	Pun G P P, Mishin Y 2012 Phys. Rev. B 86 134116 Google Scholar
[32]	Brenner D W, Shenderova O A, Harrison J A, Stuart S J, Ni B, Sinnott S B 2002 J. Phys. Condens. Matter. 14 783 Google Scholar
[33]	Cao Q, Chen Y, Shao W, Ma X, Zheng C, Cui Z, Liu Y, Yu B 2020 J. Mol. Liq. 319 114218 Google Scholar
[34]	Li N, Zhen Z, Zhang R, Mu R, Xu Z, He L 2022 Vacuum 196 110750 Google Scholar
[35]	Yan H, Yang H, Lin S, He J, Zhang M, Li H 2021 Thin Solid Films 736 138921 Google Scholar
[36]	Batzill M 2012 Surf. Sci. Rep. 67 83 Google Scholar
[37]	Yu X, Zhang Z, Liu F, Pei J X, Tian X Y 2019 J. Alloys Compd. 806 1309 Google Scholar
[38]	Zhang L, Zhu Y C, Teng W R, Xia T, Rong Y, Li N, Ma H Z 2017 Comput. Mater. Sci. 130 10 Google Scholar

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