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Currently, Si-based field-effect transistors (FET) are approaching their physical limit and challenging Moore's law due to their short-channel effect, and further reducing their gate length to the sub-10 nm is extremely difficult. Two-dimensional (2D) layered semiconductors with atom-scale uniform thickness and no dangling bonds on the interface are considered potential channel materials to support further miniaturization and integrated electronics. Wu et al. [Wu F, et al. 2022 Nature 603 259 ] successfully fabricated an FET with gate length less than 1 nm by using atomically thin molybdenum disulfide with excellent device performance. This breakthrough has greatly encouraged further theoretical predictions regarding the performance of 2D devices. Additionally, 2D SnS has high carrier mobility, anisotropic electronic properties, and is stable under ambient condition, which is conducive to advanced applications in 2D semiconductor technology. Herein, we explore the quantum transport properties of sub-5 nm monolayer (ML) SnS FET by using first-principles quantum transport simulation. Considering the anisotropic electronic SnS, the double-gated-two-probe device model is constructed along the armchair direction and the zigzag direction of ML SnS. After testing five kinds of doping concentrations, a doping concentration of 5×1013 cm–2 is the best one for SnS FET. We also use the underlaps (ULs) with lengths of 0, 2, and 4 nm to improve the device performance. On-state current (Ion) is an important parameter for evaluating the transition speed of a logic device. A higher Ion of a device can help to increase the switching speed of high-performance (HP) servers. The main conclusions are drawn as follows.1) Ion values of the n-type 2 nm (UL = 4 armchair), 3 nm (UL = 2), 4 nm (UL = 3), 5 nm (UL = 0) and the p-type 1 nm (UL = 2 zigzag), 2 nm (UL = 2 zigzag), 3 nm (UL = 2, 4 zigzag), 4 nm (UL = 2, 4 zigzag), and 5 nm (UL = 0, armchair/zigzag) gate-length devices can meet the standards for HP applications in the next decade in the International Technology Roadmap for semiconductors (ITRS, 2013 version). 2) Ion values of the n-type device along the armchair direction (31–2369 μA/μm) are larger than those in the zigzag direction (4.04–1943 μA/μm), while Ion values of the p-type along the zigzag direction (545–4119 μA/μm) are larger than those in the armchair direction (0.7–924 μA/μm). Therefore, the p-type ML GeSe MOSFETs have a predominantly anisotropic current. 3) Ion value of the p-type 3 nm gate-length (UL = 0) device along the zigzag direction has the highest value 4119 μA/μm, which is 2.93 times larger than that in the same gate-length UL = 2 (1407 μA/μm). Hence, an overlong UL will weaken the performance of the device because the gate of the device cannot well control the UL region. Thus, a suitable length of UL for FET is very important. 4) Remarkably, Ion values of the p-type devices (zigzag), even with a gate-length of 1 nm, can meet the requirements of HP applications in the ITRS for the next decade, with a value as high as 1934 μA/μm. To our knowledge, this is the best-performing device material reported at a gate length of 1 nm. 5) Subthreshold swing (SS) evaluates the control ability of the gate in the subthreshold region. The better the gate control, the smaller the SS of the device is. The limit of SS for traditional FET is 60 mV/dec (at room temperature). Values of SS for ML SnS FET alone zigzag direction are less than those along the armchair direction because the leakage current is influenced by the effective mass. -
Keywords:
- quantum transport simulation /
- monolayer SnS /
- sub-5 nm field-effect transistor /
- on-state current
[1] Cao W, Bu H M, Vinet M, Cao M, Takagi S, Hwang S, Ghani T, Banerjee K 2023 Nature 620 501
Google Scholar
[2] Liu Y, Duan X D, Shin H J, Park S, Huang Y, Duan X F 2021 Nature 591 43
Google Scholar
[3] Wang Y Y, Liu S Q, Li Q W, Quhe R, Yang C, Guo Y, Zhang X Y, Pan Y Y, Li J S, Zhang H, Xu L, Shi B W, Tang H, Li Y, Yang J, Zhang Z Y, Xiao L, Pan F, Lu J 2021 Rep. Prog. Phys. 84 056501
Google Scholar
[4] Jayachandran D, Pendurthi R, Sadaf M U K, Sakib N U, Pannone A, Chen C, Han Y, Trainor N, Kumari S, Mc Knight T V, Redwing J M, Yang Y, Das S 2024 Nature 625 276
Google Scholar
[5] https://irds.ieee.org/editions/2022
[6] Desai S B, Madhvapathy S R, Sachid A B, Llinas J P, Wang Q X, Ahn G H, Pitner G, Kim M J, Bokor J, Hu C H, Wong H S P, Javey A 2016 Science 354 99
Google Scholar
[7] Wu F, Tian H, Shen Y, Hou Z, Ren J, Gou G Y, Sun Y B, Yang Y, Ren T L 2022 Nature 603 259
Google Scholar
[8] Jiang J F, Xu L, Qiu C G, Peng L M 2023 Nature 616 470
Google Scholar
[9] Xin C, Zheng J X, Su Y T, Li S K, Zhang B K, Feng Y C, Pan F 2016 J. Phys. Chem. C 120 22663
Google Scholar
[10] Sarkar A S, Konidakis I, Gagaoudakis E, Maragkakis G M, Psilodimitrakopoulos S, Katerinopoulou D, Sygellou L, Deligeorgis G, Binas V, Oikonomou I M, Komninou P, Kiriakidis G, Kioseoglou G, Stratakis E 2022 Adv. Sci. 10 2201842
[11] Li S B, Xiao W J, Pan Y Y, Jie J S, Xin C, Zheng J X, Lu J, Pan F 2018 J. Phys. Chem. C 122 12322
[12] Chang Y R, Nishimura T, Taniguchi T, Watanabe K, Nagashio K 2022 ACS Appl. Mater. Interfaces 14 19928
Google Scholar
[13] Sucharitakul S, Rajesh Kumar U, Sankar R, Chou F C, Chen Y T, Wang C H, He C, He R, Gao X P 2016 Nanoscale 8 19050
Google Scholar
[14] Dragoman M, Dinescu A, Avram A, Dragoman D, Vulpe S, Aldrigo M, Braniste T, Suman V, Rusu E, Tiginyanu I 2022 Nanotechnology 33 405207
Google Scholar
[15] Pandit A, Hamad B 2021 Appl. Surface Sci. 538 147911
Google Scholar
[16] Xu L, Yang M, Wang S J, Feng Y P 2017 Phys. Rev. B 95 235434
Google Scholar
[17] Zhao P D, Kiriya D, Azcatl A, Zhang C X, Tosun M, Liu Y S, Hettick M, Kang J S, McDonnell S, KC S, Guo J H, Cho K, Wallace R M, Javey A 2014 ACS Nano 8 10808
Google Scholar
[18] Fathipour S, Pandey P, Fullerton-Shirey S, Seabaugh A 2016 J. Appl. Phys. 120 234902
Google Scholar
[19] Quhe R, Li Q H, Zhang Q X, Wang Y Y, Zhang H, Li J Z, Zhang X Y, Chen D X, Liu K H, Ye Y, Dai L, Pan F, Lei M, Lu J 2018 Phys. Rev. Appl. 10 024022
Google Scholar
[20] Das S, Chen H Y, Penumatcha A V, Appenzeller J 2013 Nano Lett. 13 100
Google Scholar
[21] Kaushik N, Nipane A, Basheer F, Dubey S, Grover S, Deshmukh M M, Lodha S 2014 Appl. Phys. Lett. 105 113505
Google Scholar
[22] Liu Y, Guo J, Zhu E B, Liao L, Lee S J, Ding M N, Shakir I, Gambin V, Huang Y, Duan X F 2018 Nature 557 696
Google Scholar
[23] Kim C, Moon I, Lee D, Choi M S, Ahmed F, Nam S, Cho Y, Shin H J, Park S, Yoo W J 2017 ACS Nano 11 1588
Google Scholar
[24] Pan Y Y, Wang Y Y, Ye M, Quhe R, Zhong H X, Song Z G, Peng X Y, Yu D P, Yang J B, Shi J J, Lu J 2016 Chem. Mater. 28 2100
Google Scholar
[25] Pan Y Y, Dan Y, Wang Y Y, Ye M, Zhang H, Quhe R, Zhang X Y, Li J Z, Guo W L, Yang L, Lu J 2017 ACS Appl. Mater. Interfaces 9 12694
Google Scholar
[26] Zhang X Y, Pan Y Y, Ye M, Quhe R, Wang Y Y, Guo Y, Zhang H, Dan Y, Song Z G, Li J Z, Yang J B, Guo W L, Lu J 2017 Nano Res. 11 707
[27] Das S, Zhang W, Demarteau M, Hoffmann A, Dubey M, Roelofs A 2014 Nano Lett. 14 5733
Google Scholar
[28] Liu H, Neal A T, Zhu Z, Luo Z, Xu X F, Tomanek D, Ye P D 2014 ACS Nano 8 4033
Google Scholar
[29] Guo Y, Pan F, Zhao G Y, Ren Y J, Yao B B, Li H, Lu J 2020 Nanoscale 12 15443
Google Scholar
[30] Guo Y, Zhao G Y, Pan F, Quhe R, Lu J 2022 J. Electron. Mater. 51 4824
Google Scholar
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图 1 (a) ML SnS的最佳优化结构侧视和俯视图, 黑色虚线的矩形框为单胞结构; (b) ML SnS的能带结构图, 费米能级(蓝色虚线)能量为零, Γ-X和Γ-Y分别表示armchair方向和zigzag方向; (c) ML SnS MOSFET器件的结构示意图
Figure 1. (a) Side and top view of the optimized ML SnS structure, the black dash rectangle represents the primitive cell; (b) band structure of the ML SnS, the blue dashed line indicates the Fermi level, and Γ-X and Γ-Y representing the armchair and zigzag directions, respectively; (c) schematic diagram of the ML SnS MOSFET.
图 2 测试器件掺杂浓度的转移特性曲线, 不同源极和漏极掺杂电子/空穴(Ne (Nh))浓度下n型和p型5 nm栅长DG ML SnS MOSFET沿zigzag (a)和armchair (b)方向的转移特性曲线
Figure 2. Transfer characteristics of the n- and p-type 5 nm gate-length DG ML SnS MOSFET for different source and drain doping concentrations of electron/hole (Ne (Nh)) along the zigzag (a) and armchair (b) directions.
图 3 n型和p型DG ML SnS MOSFET器件转移特性曲线 (a) 1—2 nm, (b) 3—5 nm栅极长沿armchair方向转移特性曲线; (c) 1—2 nm, (d) 3—5 nm栅极长沿zigzag方向的转移特性
Figure 3. Transfer characteristics curves of the n- and p-type DG ML SnS MOSFET: (a) 1–2 nm, (b) 3–5 nm gate-length along the armchair direction; (c) 1–2 nm, (d) 3–5 nm gate-length along the zigzag directions.
图 4 亚5 nm的n型和p型DG ML SnS MOSFET开态电流(a), (b)和亚阈值摆幅(c), (d)与栅极长度的关系
Figure 4. On-state current (a), (b) and subthreshold swing (c), (d) of the sub-5 nm DG n-type and p-type DG ML SnS MOSFET as a function of the gate-length.
图 5 亚5 nm的n型(a)和p型(b)DG ML SnS MOSFET的开态电流与栅极长度的关系
Figure 5. On-state current of the sub-5 nm n-type (a) and p-type (b) DG ML SnS MOSFET as a function of the Lg, the set of red and green lines indicate the armchair and zigzag directions, respectively.
图 6 n型和p型MOSFET在HP标准下亚5 nm栅长下的开态电流与ML二维沟道材料有效质量的关系, 所有数据均采基于密度泛函理论的量子输运模拟计算
Figure 6. On-state current of n- and p-type MOSFET for high-performance applications at sub-5 nm gate-lengths versus the effective mass of ML two dimensional channel materials, all the data are calculated by ab initio quantum transport simulations.
表 1 不同的测试掺杂浓度对应的器件开态电流
Table 1. Ion of the SnS MOSFET with different doping concentrations.
Ne/Nh doping concentration/cm–2 Ion (HP/LP)/(μA·μm–1) Zigzag Armchair n-type p-type n-type p-type 1×1012 32.24/33.69 45/40.9 129.66/21.55 31.82/35.72 5×1012 232.26/51.9 310.69/95.35 741.82/17.33 185.95/32.23 1×1013 1105.66/35.52 756.83/105.06 970.15/8.42 379.27/42.5 5×1013 1330.51/0.425 2693.37/0.12 1216.66/0.061 973.2/0.026 8×1013 1207.55/0.082 280.42/0.0013 1020.21/0.0074 676.8/5.37 
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表 2 n型和p型DG ML SnS MOSFET器件开态电流、开关比和亚阈值摆幅与ITRS HP和LP标准(2023版)的比较
Table 2. Benchmark of the ballistic performances upper limit of the sub-5 nm DG ML SnS MOSFET (zigzag- and armchair-directed) for HP and LP applications against the ITRS requirements (2023 version).
Lg/nm UL/nm SS/(mV·dec–1) Ion/(μA·μm–1) Ion/Ioff Ion/(μA·μm–1) Ion/Ioff HP 5.1 0 — 900 9.00×103 LP 295 5.9×106 n-type p-type n-type p-type n-type p-type n-type p-type n-type p-type Armchair 1 0 843 719 — — — — — — — — 2 260 276 31 56 3.1×102 5.6×102 — — — — 4 120 122 407 209 4.07×103 2.09×103 2.06 6.34 4.12×104 1.27×105 2 0 561 418 — 0.7 — 7.0×102 — — — — 2 212 172 41 319 4.1 3.19×103 0.007 0.0031 1.40×102 61.6 4 101 90 938 285 9.38×103 2.85×103 45.7 50.83 9.14×105 1.02×106 3 0 293 254 5.18 13 5.18×101 1.30×102 — — — — 2 118 101 1204 665 1.20×104 6.65×103 0.406 0.86 8.12×103 1.72×104 4 0 189 241 226 292 2.26×103 2.92×103 — — — — 2 93 78 2369 817 2.37×104 8.17×103 110.58 92.08 2.21×106 1.84×106 5 0 125 112 1113 924 1.11×104 9.24×103 0.1 0.03 2.0×103 6.00×102 Zigzag 1 0 904 603 — — — — — — — — 2 259 96 72 1934 7.20×102 1.93×104 — 69.3 — 1.39×106 4 107 85 390 545 3.90×103 5.45×103 10.04 79.2 2.01×105 1.58×106 2 0 530 252 — — — — 2 147 101 509 1236 5.09×103 1.24×104 0.035 0.0021 7.0×102 42.8 4 89 78 621 693 6.21×103 6.93×103 85.02 136.51 1.70×106 2.73×106 3 0 233 89 4.04 4119 4.04×101 4.12×104 — 171.91 — 3.44×106 2 117 66 1168 1407 1.17×104 1.41×104 7.73 516.18 1.55×105 1.03×107 4 0 166 106 322 1648 3.22×103 1.65×104 — — — — 2 85 70 1843 1874 1.84×104 1.87×104 231.06 271.4 4.62×106 5.43×106 5 0 118 78 1280 2463 1.28×104 2.46×104 0.67 0.13 1.34×104 2.6×103
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[1] Cao W, Bu H M, Vinet M, Cao M, Takagi S, Hwang S, Ghani T, Banerjee K 2023 Nature 620 501
Google Scholar
[2] Liu Y, Duan X D, Shin H J, Park S, Huang Y, Duan X F 2021 Nature 591 43
Google Scholar
[3] Wang Y Y, Liu S Q, Li Q W, Quhe R, Yang C, Guo Y, Zhang X Y, Pan Y Y, Li J S, Zhang H, Xu L, Shi B W, Tang H, Li Y, Yang J, Zhang Z Y, Xiao L, Pan F, Lu J 2021 Rep. Prog. Phys. 84 056501
Google Scholar
[4] Jayachandran D, Pendurthi R, Sadaf M U K, Sakib N U, Pannone A, Chen C, Han Y, Trainor N, Kumari S, Mc Knight T V, Redwing J M, Yang Y, Das S 2024 Nature 625 276
Google Scholar
[5] https://irds.ieee.org/editions/2022
[6] Desai S B, Madhvapathy S R, Sachid A B, Llinas J P, Wang Q X, Ahn G H, Pitner G, Kim M J, Bokor J, Hu C H, Wong H S P, Javey A 2016 Science 354 99
Google Scholar
[7] Wu F, Tian H, Shen Y, Hou Z, Ren J, Gou G Y, Sun Y B, Yang Y, Ren T L 2022 Nature 603 259
Google Scholar
[8] Jiang J F, Xu L, Qiu C G, Peng L M 2023 Nature 616 470
Google Scholar
[9] Xin C, Zheng J X, Su Y T, Li S K, Zhang B K, Feng Y C, Pan F 2016 J. Phys. Chem. C 120 22663
Google Scholar
[10] Sarkar A S, Konidakis I, Gagaoudakis E, Maragkakis G M, Psilodimitrakopoulos S, Katerinopoulou D, Sygellou L, Deligeorgis G, Binas V, Oikonomou I M, Komninou P, Kiriakidis G, Kioseoglou G, Stratakis E 2022 Adv. Sci. 10 2201842
[11] Li S B, Xiao W J, Pan Y Y, Jie J S, Xin C, Zheng J X, Lu J, Pan F 2018 J. Phys. Chem. C 122 12322
[12] Chang Y R, Nishimura T, Taniguchi T, Watanabe K, Nagashio K 2022 ACS Appl. Mater. Interfaces 14 19928
Google Scholar
[13] Sucharitakul S, Rajesh Kumar U, Sankar R, Chou F C, Chen Y T, Wang C H, He C, He R, Gao X P 2016 Nanoscale 8 19050
Google Scholar
[14] Dragoman M, Dinescu A, Avram A, Dragoman D, Vulpe S, Aldrigo M, Braniste T, Suman V, Rusu E, Tiginyanu I 2022 Nanotechnology 33 405207
Google Scholar
[15] Pandit A, Hamad B 2021 Appl. Surface Sci. 538 147911
Google Scholar
[16] Xu L, Yang M, Wang S J, Feng Y P 2017 Phys. Rev. B 95 235434
Google Scholar
[17] Zhao P D, Kiriya D, Azcatl A, Zhang C X, Tosun M, Liu Y S, Hettick M, Kang J S, McDonnell S, KC S, Guo J H, Cho K, Wallace R M, Javey A 2014 ACS Nano 8 10808
Google Scholar
[18] Fathipour S, Pandey P, Fullerton-Shirey S, Seabaugh A 2016 J. Appl. Phys. 120 234902
Google Scholar
[19] Quhe R, Li Q H, Zhang Q X, Wang Y Y, Zhang H, Li J Z, Zhang X Y, Chen D X, Liu K H, Ye Y, Dai L, Pan F, Lei M, Lu J 2018 Phys. Rev. Appl. 10 024022
Google Scholar
[20] Das S, Chen H Y, Penumatcha A V, Appenzeller J 2013 Nano Lett. 13 100
Google Scholar
[21] Kaushik N, Nipane A, Basheer F, Dubey S, Grover S, Deshmukh M M, Lodha S 2014 Appl. Phys. Lett. 105 113505
Google Scholar
[22] Liu Y, Guo J, Zhu E B, Liao L, Lee S J, Ding M N, Shakir I, Gambin V, Huang Y, Duan X F 2018 Nature 557 696
Google Scholar
[23] Kim C, Moon I, Lee D, Choi M S, Ahmed F, Nam S, Cho Y, Shin H J, Park S, Yoo W J 2017 ACS Nano 11 1588
Google Scholar
[24] Pan Y Y, Wang Y Y, Ye M, Quhe R, Zhong H X, Song Z G, Peng X Y, Yu D P, Yang J B, Shi J J, Lu J 2016 Chem. Mater. 28 2100
Google Scholar
[25] Pan Y Y, Dan Y, Wang Y Y, Ye M, Zhang H, Quhe R, Zhang X Y, Li J Z, Guo W L, Yang L, Lu J 2017 ACS Appl. Mater. Interfaces 9 12694
Google Scholar
[26] Zhang X Y, Pan Y Y, Ye M, Quhe R, Wang Y Y, Guo Y, Zhang H, Dan Y, Song Z G, Li J Z, Yang J B, Guo W L, Lu J 2017 Nano Res. 11 707
[27] Das S, Zhang W, Demarteau M, Hoffmann A, Dubey M, Roelofs A 2014 Nano Lett. 14 5733
Google Scholar
[28] Liu H, Neal A T, Zhu Z, Luo Z, Xu X F, Tomanek D, Ye P D 2014 ACS Nano 8 4033
Google Scholar
[29] Guo Y, Pan F, Zhao G Y, Ren Y J, Yao B B, Li H, Lu J 2020 Nanoscale 12 15443
Google Scholar
[30] Guo Y, Zhao G Y, Pan F, Quhe R, Lu J 2022 J. Electron. Mater. 51 4824
Google Scholar
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