原子尺度构建二维材料的第一性原理计算研究

刘子媛; 潘金波; 张余洋; 杜世萱

doi:10.7498/aps.70.20201636

摘要

随着信息技术的不断进步, 核心元器件朝着运行速度更快、能耗更低、尺寸更小的方向快速发展. 尺寸不断减小导致的量子尺寸效应使得材料和器件呈现出许多与传统三维体系不同的新奇物性. 从原子结构出发, 预测低维材料物性、精准合成、表征、调控并制造性能良好的电子器件, 对未来电子器件的发展及相关应用具有至关重要的意义. 理论计算能在保持原子级准确度的情况下高效、低耗地预测材料结构、物性、界面效应等, 是原子制造技术中不可或缺的重要研究手段. 本综述从第一性原理计算角度出发, 回顾了近年来其在二维材料结构探索、物性研究和异质结构造等方面的应用及取得的重要进展, 并展望了在原子尺度制造背景下二维材料的发展前景.

关键词:

Abstract

With the continuous development of information and technology, core components are developing rapidly toward faster running speed, lower energy consumption, and smaller size. Due to the quantum confinement effect, the continuous reduction of size makes materials and devices exhibit many exotic properties that are different from the properties of traditional three-dimensional materials. At an atomic scale level, structure and physical properties, accurately synthesizing, characterizing of materials, property regulation, and manufacturing of electronic devices with good performance all play important roles in developing the electronic devices and relevant applications in the future. Theoretical calculation can efficiently predict the geometric structure, physical properties and interface effects with low consumption but high accuracy. It is an indispensable research means of atomic level manufacturing technology. In this paper, we review the recent progress of two-dimensional materials from the theoretical perspective. This review is divided into three parts, i.e. two-dimensional layered materials, two-dimensional non-layered materials, and two-dimensional heterostructures. Finally, we draw some conclusions and suggest some areas for future investigation.

Keywords:

作者及机构信息

1.
中国科学院物理研究所, 北京凝聚态物理国家研究中心, 北京　100190

2.
中国科学院大学, 北京　100049

3.
中国科学院拓扑量子计算卓越创新中心, 北京　100190

4.
松山湖材料实验室, 东莞　523808

通信作者: 潘金波, jbpan@iphy.ac.cn ; 杜世萱, sxdu@iphy.ac.cn

基金项目: 国家自然科学基金(批准号: 61888102)、国家重点研发计划(批准号: 2016YFA0202300, 2018YFA0305800)和中国科学院战略性先导科技专项(批准号: XDB30000000)资助的课题.

Authors and contacts

1.
Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing 100190, China

2.
University of Chinese Academy of Sciences, Beijing 100049, China

3.
CAS Center for Excellence in Topological Quantum Computation, Beijing 100190, China

4.
Songshan Lake Materials Laboratory, Dongguan 523808, China

Corresponding author: Pan Jin-Bo, jbpan@iphy.ac.cn ; Du Shi-Xuan, sxdu@iphy.ac.cn

Funds: Project supported by National Nature Science Foundation of China (Grant No. 61888102), the National Key R&D Program of China (Grant Nos. 2016YFA0202300, 2018YFA0305800), and the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDB30000000)

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参考文献

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施引文献

图 1 截止到2020年9月以“Two-dimensional materials”为关键词, 从Web of Science网站查询到的近十年的论文发表数

Fig. 1. Number of publications on two-dimensional materials per year over the last decade. The data is from ISI Web of Science website by September 2020, and the searching keyword is “two-dimensional materials”.

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图 2 凸包图, 用于判断材料稳态和亚稳态^[32]

Fig. 2. Convex hull diagram is used to estimate the ground state and metastable state of a material^[32].

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图 3 预测的层状材料结构、成分等信息统计　(a) 晶格常数的相对误差; (b) 化学元素组成; (c) 晶体类型; (d) 晶体空间群; (e) 晶系; (f) 元素种类^[39]

Fig. 3. Classification of predicted layered materials in term of (a) relative error in lattice constants; (b) chemical compositions; (c) crystal prototypes; (d) crystal space groups; (e) crystal systems; (f) number of distinct chemical constituents^[39].

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图 4 C2DB数据库中典型的二维材料^[43]

Fig. 4. Example of two dimensional materials prototypes in the C2DB^[43].

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图 5 C2DB数据库的工作流程图^[43]

Fig. 5. The workflow of producing data of C2DB^[43].

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图 6 体相砷的　(a) 俯视图和(b) 顶视图; 翘曲单层砷烯的(c) 俯视图和(d) 侧视图^[48]

Fig. 6. (a) Side view and (b) top view of the structure of arsenic; (c) top view and (d) side view of a buckled As monolayer (arsenene)^[48].

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图 7 层砷烯和层锑烯的声子谱图^[48]

Fig. 7. Phonon dispersions of arsenene and antimonene^[48].

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图 8 Cu(111)上单层CuSe的(a) 高分辨率STM图像, (b) LEED图; Cu(111)上单层CuSe优化原子结构模型的(c) 俯视图, (d) 侧视图^[51]

Fig. 8. Monolayer CuSe on Cu(111): (a) High-resolution STM image, (b) LEED pattern; optimized atomic structure of monolayer CuSe on Cu(111): (c) top view, (d) side view^[51].

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图 9 Cu(111)上单层CuSe　(a) 沿K–Γ–K方向测量的ARPES图; (b) 理论计算的能带图^[51]

Fig. 9. Monolayer CuSe on Cu(111): (a) ARPES intensity plots measured along the K–Γ–K direction; (b) calculated band structure ^[51]

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图 10 电荷转移示意图　(a), (b) I型异型结; (c), (d) II型异型结^[53]

Fig. 10. Schematic of allowed charge transfer: (a), (b) Type-I heterostructures; (c), (d) type-II heterostructures^[53].

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图 11 异质结周期表^[55]

Fig. 11. Periodic table of heterostructures^[55].

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图 12 (a) MoS₂, WS₂和MoS₂/WS₂的吸收光谱图; (b) 布里渊区K点附近的电子能带; (c) 异质结的能带排列^[76]

Fig. 12. (a) Absorption spectra of MoS₂, WS₂ and MoS₂/WS₂; (b) electron band near the K point in the Brillouin zone; (c) band arrangement of heterostructures^[76].

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图 13 AA, AA', AB型MoSe₂/WSe₂异质结的结构及能带^[77]

Fig. 13. Structure and energy band of AA, AA', AB MoSe₂/WSe₂ heterostructures^[77].

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表 1 数据库统计^[42]

Table 1. Database statistics^[42].

	Unique to the ICSD	Unique to the COD	Common to both	Total sum
	Experimental data
CIF inputs	99212	87070		186282
Unique 3D structures (set A)	34548	60354	13521	108423
Layered 3D structures (set B)	3257	1180	1182	5619
	DFT calculations
Layered 3D, relaxed (set C)	2165	175	870	3210
Binding energies (set D)	1795	126	741	2662
2D easily exfoliable (EE)	663	79	294	1036
2D potentially exfoliable (PE)	524	34	231	789
Total	1187	113	525	1825

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表 2 易剥落的磁性化合物^[42]

Table 2. Easily exfoliable magnetic compounds^[42].

	Ferromagnetic	Antiferromagnetic
Metals	Co(OH)₂, CoO₂, ErHCl, ErSeI, EuOBr, EuOI, FeBr₂, FeI₂, FeTe, LaCl, NdOBr, PrOBr, ScCl, SmOBr, SmSI, TbBr, TmI₂, TmOI, VS₂, VSe₂, VTe₂, YCl, YbOBr, YbOCl	CoI₂, CrSe₂, FeO₂, FeOCl, FeSe, PrOI, VOBr
Semiconductors	CdOCl, CoBr₂, CoCl₂, CrOBr, CrOCl, CrSBr, CuCl₂, ErSCl, HoSI, LaBr₂, NiBr₂, NiCl₂, NiI₂	CrBr₂, CrI₂, LaBr, Mn(OH)₂, MnBr₂, MnCl₂, MnI₂, VBr₂, VCl₂, VI₂, VOBr₂, VOCl₂

下载: 导出CSV

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[8]	Liu H, Gao J, Zhao J 2013 J. Phys. Chem. C 117 10353 Google Scholar
[9]	Gao N, Li J C, Jiang Q 2014 Chem. Phys. Lett. 592 222 Google Scholar
[10]	Jamgotchian H, Colignon Y, Hamzaoui N, Ealet B, Hoarau J Y, Aufray B, Bibérian J P 2012 J. Phys. Condens. Matter 24 172001 Google Scholar
[11]	Qin R, Wang C H, Zhu W J, Zhang Y L 2012 AIP Adv. 2 022159 Google Scholar
[12]	Amlaki T, Bokdam M, Kelly P J 2016 Phys. Rev. Lett. 116 256805 Google Scholar
[13]	Zhang L, Bampoulis P, Rudenko A N, Yao Q, Zandvliet H J W 2016 Phys. Rev. Lett. 117 256804
[14]	Zhu F F, Chen W J, Xu Y, Gao C L, Guan D D, Liu C H, Qian D, Zhang S C, Jia J F 2015 Nat. Mater. 14 1020 Google Scholar
[15]	Saxena S, Chaudhary R P, Shukla S 2016 Sci. Rep. 6 31073 Google Scholar
[16]	Lee Y T, Kwon H, Kim J S, Kim H H, Lee Y J, Lim J A, Song Y W, Yi Y, Choi W K, Hwang D K, Im S 2015 ACS Nano 9 10394 Google Scholar
[17]	Liu H W, Zou Y Q, Tao L, Ma Z L, Liu D D, Zhou P, Liu H B, Wang S Y 2017 Small 13 1700758 Google Scholar
[18]	Wang Q H, Kalantar-Zadeh K, Kis A, Coleman J N, Strano M S 2012 Nat. Nanotechnol. 7 699 Google Scholar
[19]	Chhowalla M, Shin H S, Eda G, Li L J, Loh K P, Zhang H 2013 Nat. Chem. 5 263 Google Scholar
[20]	Lei J C, Zhang X, Zhou Z 2015 Front. Phys. 10 276 Google Scholar
[21]	Chen J Y, Huang Q, Huang H Y, Mao L C, Liu M Y, Zhang X Y, Wei Y 2020 Nanoscale 12 3574 Google Scholar
[22]	Glavin N R, Rao R, Varshney V, Bianco E, Apte A, Roy A, Ringe E, Ajayan P M 2020 Adv. Mater. 32 1904302 Google Scholar
[23]	Kohn W, Sham L J 1965 Phys. Rev 140 1133 Google Scholar
[24]	Ceperley D M, Alder B J 1980 Phys. Rev. Lett. 45 566 Google Scholar
[25]	Burke K, Perdew J P, Ernzerhof M 1997 Int. J. Quantum Chem. 61 287 Google Scholar
[26]	Perdew J P, Burke K, Ernzerhof M 1996 Phys. Rev. Lett. 77 3865 Google Scholar
[27]	Kurth S, Perdew J P, Blaha P 2015 Int. J. Quantum Chem. 75 889
[28]	Perdew J P, Ernzerhof M, Burke K 1996 J. Chem. Phys. 105 9982 Google Scholar
[29]	Paier J, Marsman M, Kresse G 2007 J. Chem. Phys. 127 024103 Google Scholar
[30]	Vanderbilt D 1990 Phys. Rev. B 41 7892 Google Scholar
[31]	De Raedt H, Hams A H, Michielsen K, Miyashita S, Saito E 2000 Prog. Theor. Phys. Suppl. 138 489 Google Scholar
[32]	Zurek E 2016 Reviews in Computational Chemistry (Hoboken: Wiley-Blackwell) pp274−326
[33]	Mueller T, Hautier G, Jain A, Ceder G 2011 Chem. Mater. 23 3854 Google Scholar
[34]	Saal J E, Kirklin S, Aykol M, Meredig B, Wolverton C 2013 JOM 65 1501 Google Scholar
[35]	Ozolins V, Majzoub E H, Wolverton C 2009 J. Am. Chem. Soc. 131 230 Google Scholar
[36]	Ortiz C, Eriksson O, Klintenberg M 2009 Comput. Mater. Sci. 44 1042 Google Scholar
[37]	Greeley J, Jaramillo T F, Bonde J, Chorkendorff I B, Norskov J K 2006 Nat. Mater. 5 909 Google Scholar
[38]	Yu L P, Zunger A 2012 Phys. Rev. Lett. 108 068701 Google Scholar
[39]	Choudhary K, Kalish I, Beams R, Tavazza F 2017 Sci. Rep 7 5179 Google Scholar
[40]	Jiang Y C, Gao J, Wang L 2016 Sci. Rep 6 19624 Google Scholar
[41]	Augustin J, Eyert V, Boker T, Frentrup W, Dwelk H, Janowitz C, Manzke R 2000 Phys. Rev. B 62 10812 Google Scholar
[42]	Mounet N, Gibertini M, Schwaller P, Campi D, Merkys A, Marrazzo A, Sohier T, Castelli I E, Cepellotti A, Pizzi G, Marzari N 2018 Nat. Nanotechnol. 13 246 Google Scholar
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[44]	Ashton M, Paul J, Sinnott S B, Hennig R G 2017 Phys. Rev. Lett. 118 106101 Google Scholar
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