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Based on the wide-spectrum neutron beam (covering thermal neutrons and E > 10 MeV neutrons, with maximum energy of 1.6 GeV) provided by the China Spallation Neutron Source (CSNS), this paper focuses on the single event effect study of 14 nm FinFET large-capacity SRAM and 65 nm planar process SRAM device, using combined techniques of irradiation experiment, reverse analysis, and Monte-Carlo neutron transport simulation. The aim is to reveal the effect of integrated circuit process changing on the sensitivity of neutron induced single-bit and multiple-bit upsets (MBU), and to analyze the inner mechanisms, including the distribution of secondary particles in the sensitive volume, the characteristics of deposited charges, etc. The results show that compared with the 65 nm device, single event upset (SEU) cross section of the 14 nm FinFET device, induced by E > 10 MeV neutrons, is reduced by about 40 times, while the MBU ratio increases from 2.2% to 7.6%, which is due to the reduction of sensitive volume size of the 14 nm FinFET device (80 nm × 30 nm × 45 nm), pitch, and critical charge (0.05 fC). The main forms of MBU are double-bit upset, triple-bit upset and quadruple-bit upset. Unlike the phenomenon that the 65 nm device is immune to thermal neutrons, the use of the 10B element near M0 in the 14 nm FinFET device causes it to present the thermal neutron sensitivity to a certain extent. The SEU cross section induced by thermal neutrons is about 4.8 times smaller than that induced by E > 10 MeV neutrons. Based on the device cross-section and memory area images obtained from the reverse analysis, a device model is established and neutron transport simulation based on Geant4 toolkit is carried out. The E > 10 MeV neutrons result in abundant secondary particle distribution in the sensitive volume of the device, covering n, p into even W. The neutron energy and presence or absence of the W plug near the sensitive volume have an importantinfluence on the type and probability of secondary particles in the sensitive volume. The analysis and calculations show that a large number of high-Z secondary particles with long range and large LET values generated by high-energy neutrons in the sensitive volume of the device are the inducement of MBU, and SEUs mainly result from the contribution of light ions such as p, He, and Si. -
Keywords:
- FinFET /
- neutron /
- single event upset /
- nuclear reaction
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图 1 实验现场图(中子束流孔道位于测试板背后, 中子束流对准被测器件)
Figure 1. Experimental setup (neutron beam channel is loca-ted behind the test board, and aligned with the device under test).
图 2 实验终端的中子能谱
Figure 2. Neutron energy spectrum of the experimental terminal.
图 3 65 nm平面工艺和14 nm FinFET工艺SRAM的中子(E > 10 MeV)SEU截面对比
Figure 3. Comparison of neutron (E > 10 MeV) SEU cross section of 65 nm planar and 14 nm FinFET SRAM devices.
图 4 65 nm平面工艺和14 nm FinFET工艺SRAM的热中子SEU截面对比
Figure 4. Comparison of thermal neutron SEU cross section of 65 nm planar and 14 nm FinFET SRAM devices.
图 5 (a) Li离子和(b) He离子在硅材料中的LET值与能量的关系
Figure 5. Relationship between LET value and energy of (a) Li ion and (b) He ion in silicon material.
图 6 14 nm FinFET SRAM的重离子实验结果
Figure 6. Heavy ion experiment results of 14 nm FinFET SRAM.
图 8 14 nm FinFET SRAM的反向分析 (a)横切面; (b)存储区图像
Figure 8. Reverse analysis of 14 nm FinFET SRAM: (a) Cross section; (b) memory area image.
图 9 65 nm SRAM的反向分析 (a) 横切面; (b) 存储区图像
Figure 9. Reverse analysis of 65 nm SRAM: (a) Cross section; (b) memory area image.
图 10 14 MeV和1600 MeV中子在器件灵敏区中产生的二次粒子分布(器件模型中的W材料被二氧化硅替代)
Figure 10. 14 MeV and 1600 MeV neutron induced secondary particle distribution in the device SV (W material in the device model is replaced by silica).
图 11 14 MeV和1600 MeV中子在器件灵敏区中产生的二次粒子分布(真实器件模型)
Figure 11. 14 MeV and 1600 MeV neutron induced secondary particle distribution in the device SV (real device model).
图 12 14 MeV和1600 MeV中子在器件灵敏区中产生的二次粒子的LET值与射程
Figure 12. The LET value and range of secondary particles generated by 14 MeV and 1600 MeV neutrons in the device SV.
图 13 14 MeV和1600 MeV中子在器件灵敏区中的沉积电荷
Figure 13. The deposition charge of 14 MeV and 1600 MeV neutrons in the device SV.
表 1 被测器件参数
Table 1. Parameters of devices under test.
编号 SRAM工艺 型号 容量 供电电压(core)/V 封装形式 1# 65 nm平面 CY7 C1663 KV18 8 Mb × 18 1.8 BGA, 非倒装 2# 14 nm FinFET — 8 Mb × 16 0.8 BGA, 倒装 
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表 2 14 nm FinFET SRAM和65 nm SRAM的存储单元尺寸和灵敏区参数
Table 2. Memory cell size and SV parameters for the 14 nm FinFET SRAM and 65 nm SRAM devices.
DownLoad: CSV
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[1] Lu D D, Dunga M V, Lin C S, Niknejad A M, Hu C 2007 IEEE International Electron Devices Meeting Washington, DC, USA, December 10–12, 2007 p565
[2] Park T, Choi S, Lee D H, Yoo J R, Lee B C, Kim J Y, Lee C G, Chi K K, Hong S H, Hynn S J, Shin Y G, Han J N, Park I S, Chung U I, Moon J T, Yoon E, Lee J H 2003 Symposium on VLSI Technology Kyoto, Japan, June 10–12, 2003 p135
[3] Manoj C R, Meenakshi N, Dhanya V, Rao V R 2007 International Workshop on Physics of Semiconductor Devices Mumbai, India, December 16–20, 2007 p134
[4] Ma C, Li B, Zhang L, He J, Zhang X, Lin X, Chan M 2009 10th International Symposium on Quality Electronic Design San Jose, CA, USA, March 16–18, 2009 p7
[5] [6] Lei Z F, Zhang Z G, En Y F, Huang Y 2018 Chin. Phys. B 27 066105
Google Scholar
[7] JESD89 A Measurement and Reporting of Alpha Particle and Terrestrial Cosmic Ray-Induced Soft Errors in Semiconductor Devices JEDEC standard, October 2006
[8] May T C, Woods M H 1979 IEEE Trans. Electron Dev. ED-26 2
[9] Autran J L, Munteanu D, Sauze S, Gasiot G, Roche P 2014 IEEE Radiation Effects Data Workshop (REDW) Paris, France, July 14–18, 2014 p1
[10] Auden E C, Quinn H M, Wender S A, O’Donnell J M, Lisowski P W, George J S, Xu N, Black D A, Black J D 2019 IEEE Trans. Nucl. Sci. Early Access 1
[11] Weulersse C, Houssany S, Guibbaud N, Segura-Ruiz J, Beaucour J, Miller F, Mazurek M 2018 IEEE Trans. Nucl. Sci. 65 1851
Google Scholar
[12] Zhang H, Jiang H, Brockman J D, Assis T R, Fan X, Bhuva B L, Narasimham B, Wen S J, Wong R 2017 IEEE International Reliability Physics Symposium (IRPS) Monterey, CA, USA, April 2–6, 2017 p3 D-3.1
[13] Seifert N, Jahinuzzaman S, Velamala J, Ascazubi R, Patel N, Gill B, Basile J, Hicks J 2015 IEEE Trans. Nucl. Sci. 62 2570
Google Scholar
[14] Fang Y, Oates A S 2011 IEEE Trans. Dev. Mater. Reliab. 11 551
Google Scholar
[15] 王勋, 张凤祁, 陈伟, 郭晓强, 丁李利, 罗尹虹 2019 68 052901
Google Scholar
Wang X, Zhang F Q, Chen W, Guo X Q, Ding L L, Luo Y H 2019 Acta Phys. Sin. 68 052901
Google Scholar
[16] Ziegler J F, Biersack J P, Littmark U 1985 The Stopping and Range of Ions in Solids (New York: Pergamon Press)
[17] SRIM & TRIM, Ziegler J F http://www.srim.org/ [2019-7-11]
[18] Zhang Z G, Lei Z F, En Y F, Liu J 2016 Radiation Effects on Components & Systems Conference (RADECS) Bremen, Germany, September 19–23, 2016 Paper H14
[19] Sierawski B D, Mendenhall M H, Reed R A, Clemens M A, Weller R A, Schrimpf R D, Blackmore E W, Trinczek M, Hitti B, Pellish J A, Baumann R C, Wen S J, Wong R, Tam N 2010 IEEE Tran. Nucl. Sci. 57 3273
[20] Agostinelli S, Allison J, Amako K, et al. 2003 Nucl. Instrum. Meth. Phys. Res. A 506 250
Google Scholar
[21] Zhang Z G, Liu J, Sun Y M, Hou M D, Tong T, Gu S, Liu T Q, Geng C, Xi K, Yao H J, Luo J, Duan J L, Mo D, Su H, Lei Z F, En Y F, Huang Y 2014 10th International Conference on Reliability, Maintainability and Safety (ICRMS) Guangzhou, China, August 6–8, 2014 p114
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