Artificial synapses based on layered multi-component metal oxides

Liu Qiang; Ni Yao; Liu Lu; Sun Lin; Liu Jia-Qi; Xu Wen-Tao

doi:10.7498/aps.71.20220303

Abstract

Neuromorphic electronics has received considerable attention recent years, and its basic functional units are synaptic electronic devices. A two-terminal artificial synapse with sandwiched structure emulates plasticity of the biological synapses under the action of nerve-like electrical impulse signals. In this paper, P3 phase Na_2/3Ni_1/3Mn_2/3O₂ multi-element metal oxides with layered structure are synthesized by sol-gel process. Owing to the fact that Na⁺ is easy to embed/eject into its crystal structure, an ion-migrating artificial synapse based on Na_2/3Ni_1/3Mn_2/3O₂ is designed and fabricated. The device emulates important synaptic plasticity, such as excitatory postsynaptic current, paired-pulse facilitation, spike-number dependent plasticity, spike-frequency dependent plasticity, spike-voltage amplitude dependent plasticity and spike-duration dependent plasticity. The device realizes the identification and response to Morse code commands.

Keywords:

Authors and contacts

Key Laboratory of Photoelectronic Thin Film Devices and Technology of Tianjin, Institute of Photoelectronic Thin Film Devices and Technology, Nankai University, Tianjin 300350, China

Corresponding author: Xu Wen-Tao, wentao@nankai.edu.cn

Funds: Project supported by the National Science Fund for Distinguished Young Scholars of China (Grant No. T2125005), the Tianjin Science Foundation for Distinguished Young Scholars, China (Grant No. 19JCJQJC61000), and the Shenzhen Science and Technology Project, China (Grant No. JCYJ20210324121002008).

FullText HTML

References

[1]	Kuzum D, Yu S, Wong H P 2013 Nanotechnology 24 382001 Google Scholar
[2]	Ling H, Koutsouras D A, Kazemzadeh S, Van De Burgt Y, Yan F, Gkoupidenis P 2020 Appl. Phys. Rev. 7 011307 Google Scholar
[3]	Wang S, Zhang D W, Zhou P 2019 Sci. Bull. 64 1056 Google Scholar
[4]	Wei H, Shi R, Sun L, Yu H, Gong J, Liu C, Xu Z, Ni Y, Xu J, Xu W 2021 Nat. Commun. 12 1 Google Scholar
[5]	Choi D, Song M K, Sung T, Jang S, Kwon J Y 2020 Nano Energy 74 104912 Google Scholar
[6]	Xia Q, Yang J J 2019 Nat. Mater. 18 309 Google Scholar
[7]	Lu K, Li X, Sun Q, Pang X, Chen J, Minari T, Liu X, Song Y 2021 Mater. Horiz. 8 447 Google Scholar
[8]	Sun J, Fu Y, Wan Q 2018 J. Phys. D: Appl. Phys. 51 314004 Google Scholar
[9]	Gao J, Zheng Y, Yu W, Wang Y, Jin T, Pan X, Loh K P, Chen W 2021 Smart Mater. 2 88 Google Scholar
[10]	Jeong B, Gkoupidenis P, Asadi K 2021 Adv. Mater. 33 2104034 Google Scholar
[11]	Huang X, Li Q, Shi W, Liu K, Zhang Y, Liu Y, Wei X, Zhao Z, Guo Y, Liu Y 2021 Small 17 2102820 Google Scholar
[12]	Wang C, Liu H, Chen L, Zhu H, Ji L, Sun Q Q, Zhang D W 2021 IEEE Electron Device Lett. 42 1555 Google Scholar
[13]	Huang H, Liu L, Jiang C, Gong J, Ni Y, Xu Z, Wei H, Yu H, Xu W 2022 Neuromorph. Comput. Eng. 2 014004 Google Scholar
[14]	Keene S T, Lubrano C, Kazemzadeh S, Melianas A, Tuchman Y, Polino G, Scognamiglio P, Cina L, Salleo A, van de Burgt Y, Santoro F 2020 Nat. Mater. 19 969 Google Scholar
[15]	Ku B, Koo B, Sokolov A S, Ko M J, Choi C 2020 J. Alloys Compd. 833 155064 Google Scholar
[16]	Yan Y, Chen Q, Wu X, Wang X, Li E, Ke Y, Liu Y, Chen H, Guo T 2020 ACS Appl. Mater. Interfaces 12 49915 Google Scholar
[17]	Wang H, Zhao Q, Ni Z, Li Q, Liu H, Yang Y, Wang L, Ran Y, Guo Y, Hu W 2018 Adv. Mater. 30 1803961 Google Scholar
[18]	Wei H, Yu H, Gong J, Li R, Han H, Ma M, Guo K, Xu W 2021 Mater. Chem. Front. 5 775 Google Scholar
[19]	Gao J, Hao Y, Xu S, Rong X, Lu Q, Zhu C, Hu Y S 2021 Electrochim. Acta 399 139421 Google Scholar
[20]	Wang D, Xu S, Wang J, Rong X, Zhou F, Wang L, Bai X, Lu B, Zhu C, Wang Y, Hu Y S 2022 Energy Storage Mater. 45 92 Google Scholar
[21]	Kong L, Tang C, Peng H J, Huang J Q, Zhang Q 2020 Smart Mater. 1 e1007 Google Scholar
[22]	Liu Q, Hu Z, Chen M, Zou C, Jin H, Wang S, Gu Q, Chou S 2019 J. Mater. Chem. A 7 9215 Google Scholar
[23]	Zhang S Y, Guo Y J, Zhou Y N, Zhang X D, Niu Y B, Wang E H, Huang L B, An P F, Zhang J, Yang X A 2021 Small 17 2007236 Google Scholar
[24]	Xian L, Li M, Qiu D, Qiu C, Yue C, Wang F, Yang R 2022 J. Alloys Compd. 905 163965 Google Scholar
[25]	Song T, Kendrick E 2021 J. Phys. :Mater. 4 032004 Google Scholar
[26]	Yu M, Liu F, Li J, Liu J, Zhang Y, Cheng F 2021 Adv. Energy Mater. 12 2100640 Google Scholar
[27]	Yang X, Specht C G 2019 Front. Mol. Neurosci. 12 161 Google Scholar
[28]	Lu L, Jia Y, Kirunda J B, Xu Y, Ge M, Pei Q, Yang L 2019 Nonlinear Dyn. 95 1673 Google Scholar
[29]	Beckstead M J, Grandy D K, Wickman K, Williams J T 2004 Neuron 42 939 Google Scholar
[30]	Shipman S L, Nicoll R A 2012 Proc. Natl. Acad. Sci. 109 19432 Google Scholar
[31]	Hayashi A, Masuzawa N, Yubuchi S, Tsuji F, Hotehama C, Sakuda A, Tatsumisago M 2019 Nat. Commun. 10 1 Google Scholar
[32]	Wei H, Yu H, Gong J, Zhang J, Han H, Ma M, Ni Y, Du Y, Zhang S, Liu L, Xu W 2019 ACS Appl. Electron. Mater. 2 316 Google Scholar
[33]	Wen Y, Wang B, Zeng G, Nogita K, Ye D, Wang L 2015 Chem. Asian J. 10 661 Google Scholar
[34]	Huang Q, Xu S, Xiao L, He P, Liu J, Yang Y, Wang P, Huang B, Wei W 2018 Inorg. Chem. 57 15584 Google Scholar
[35]	Magee J C, Grienberger C 2020 Annu. Rev. Neurosci. 43 95 Google Scholar
[36]	Li Y, Zhong Y, Zhang J, Xu L, Wang Q, Sun H, Tong H, Cheng X, Miao X 2014 Sci. Rep. 4 1 Google Scholar
[37]	Van Rossum M C, Bi G Q, Turrigiano G G 2000 J. Neurosci. 20 8812 Google Scholar
[38]	Fang L, Dai S, Zhao Y, Liu D, Huang J 2020 Adv. Electron. Mater. 6 1901217 Google Scholar
[39]	Yang K, Yang L, Wang Z, Guo B, Song Z, Fu Y, Ji Y, Liu M, Zhao W, Liu X 2021 Adv. Energy Mater. 11 2100601 Google Scholar
[40]	López J C 2001 Nat. Rev. Neurosci. 2 307 Google Scholar
[41]	Gong J, Yu H, Zhou X, Wei H, Ma M, Han H, Zhang S, Ni Y, Li Y, Xu W 2020 Adv. Funct. Mater. 30 2005413 Google Scholar
[42]	郭科鑫, 于海洋, 韩弘, 卫欢欢, 龚江东, 刘璐, 黄茜, 高清运, 徐文涛 2020 69 238501 Google Scholar Guo K X, Yu H Y, Han H, Wei H H, Gong J D, Liu L, Huang Q, Gao Q Y, Xu W T 2020 Acta Phys. Sin. 69 238501 Google Scholar
[43]	Zhang S, Guo J, Liu L, Ruan H, Kong C, Yuan X, Zhang B, Gu G, Cui P, Cheng G 2022 Nano Energy 91 106660 Google Scholar
[44]	Lee Y, Oh J Y, Xu W, Kim O, Kim T R, Kang J, Kim Y, Son D, Tok J B H, Park M J 2018 Sci. Adv. 4 eaat7387 Google Scholar
[45]	Shim H, Jang S, Jang J G, Rao Z, Hong J I, Sim K, Yu C 2022 Nano Res. 15 758 Google Scholar
[46]	Yang F, Sun L, Duan Q, Dong H, Jing Z, Yang Y, Li R, Zhang X, Hu W, Chua L 2021 Smart Mater. 2 99 Google Scholar

Cited By

图 1 (a) 生物神经元及突触结构示意图; (b) 人工突触电子器件结构示意图; (c) P3相Na_2/3Ni_1/3Mn_2/3O₂结构示意图

Figure 1. (a) Schematic diagram of biological neuron and synapse structure; (b) schematic diagram of artificial synaptic electronic device structure; (c) schematic diagram of the structure of P3 phase Na_2/3Ni_1/3Mn_2/3O₂.

DownLoad: Full-Size Img PowerPoint

图 2 (a) Na_2/3Ni_1/3Mn_2/3O₂粉末X射线衍射测试图; (b) Na_2/3Ni_1/3Mn_2/3O₂粉末扫描电子显微镜测试图; (c) Na_2/3Ni_1/3Mn_2/3O₂粉末X射线能谱分析图; (d) Na_2/3Ni_1/3Mn_2/3O₂活性层扫描电子显微镜表面形貌测试图; (e) 底电极铝箔、Na_2/3Ni_1/3Mn_2/3O₂活性层与PEO-Na电解质薄层扫描电子显微镜断面形貌测试图; (f) Na_2/3Ni_1/3Mn_2/3O₂活性层原子力显微镜测试图

Figure 2. (a) X-ray diffraction test diagram of Na_2/3Ni_1/3Mn_2/3O₂ powder; (b) scanning electron microscope test diagram of Na_2/3Ni_1/3Mn_2/3O₂ powder; (c) EDS test diagram of Na_2/3Ni_1/3Mn_2/3O₂ powder; (d) surface topography test diagram of Na_2/3Ni_1/3Mn_2/3O₂ active layer scanning electron microscope ; (e) bottom electrode Al foil, Na_2/3Ni_1/3Mn_2/3O₂ active layer and PEO-Na electrolyte thin layer scanning electron microscope cross-sectional morphology test diagram; (f) atom force microscope test diagram of Na_2/3Ni_1/3Mn_2/3O₂ active layer.

DownLoad: Full-Size Img PowerPoint

图 3 (a) 单次阻变特性测试; (b) 连续50次阻变特性稳定能力测试; (c) 对器件施加单个幅值为0.2 V的电脉冲信号所产生的EPSC; (d) 对器件连续施加两个幅值为0.2 V的电脉冲信号所产生的PPF; 对器件施加多对时间间隔不同幅值为0.2 V的电脉冲信号所产生的(e) PPF以及(f) PPF指数

Figure 3. (a) Single resistance characteristic test; (b) 50 consecutive tests of resistance characteristic stability; (c) EPSC generated by applying a single electrical pulse signal with an amplitude of 0.2 V to the device; (d) PPF generated by continuously applying two electrical pulse signals with an amplitude of 0.2 V to the device; (e) PPF and (f) PPF index generated by applying multiple pairs of electrical pulse signals with different amplitudes of 0.2 V to the device.

DownLoad: Full-Size Img PowerPoint

图 4 对器件连续施加10个幅值为0.2 V的电脉冲信号所产生的 (a) SNDP以及(b) SNDP 指数; (c) 对器件施加幅值从0 V—4 V—0 V变化的10组电脉冲信号循环所产生的SVDP; 对器件施加多个脉冲宽度不同幅值为0.2 V的电脉冲信号所产生的(d) SDDP以及(e) SDDP 指数; (f) 对器件连续施加多组频率不同幅值为0.2 V的电脉冲信号所产生的SFDP

Figure 4. (a) SNDP and (b) SNDP index generated by continuously applying 10 electrical pulse signals with an amplitude of 0.2 V to the device; (c) 10 groups of amplitudes varying from 0 V to 4 V to 0 V are applied to the device SVDP generated by electrical pulse signal cycle; (d) SDDP and (e) SDDP index generated by applying multiple electrical pulse signals with different pulse widths and amplitudes of 0.2 V to the device; (f) SFDP generated by continuously applying multiple groups of electrical pulse signals with the different frequencies and amplitudes of 0.2 V to the device.

DownLoad: Full-Size Img PowerPoint

图 5 对器件施加内容为Na_2/3 (a), Ni_1/3 (b), Mn_2/3 (c), O₂ (d)的摩斯电码制式的电脉冲信号所产生的突触后电流响应

Figure 5. Post-synaptic current response generated by applying Morse code electrical pulse signals with content of (a) Na_2/3, (b) Ni_1/3, (c) Mn_2/3, (d) O₂ to the device.

DownLoad: Full-Size Img PowerPoint

map

[1]	Kuzum D, Yu S, Wong H P 2013 Nanotechnology 24 382001 Google Scholar
[2]	Ling H, Koutsouras D A, Kazemzadeh S, Van De Burgt Y, Yan F, Gkoupidenis P 2020 Appl. Phys. Rev. 7 011307 Google Scholar
[3]	Wang S, Zhang D W, Zhou P 2019 Sci. Bull. 64 1056 Google Scholar
[4]	Wei H, Shi R, Sun L, Yu H, Gong J, Liu C, Xu Z, Ni Y, Xu J, Xu W 2021 Nat. Commun. 12 1 Google Scholar
[5]	Choi D, Song M K, Sung T, Jang S, Kwon J Y 2020 Nano Energy 74 104912 Google Scholar
[6]	Xia Q, Yang J J 2019 Nat. Mater. 18 309 Google Scholar
[7]	Lu K, Li X, Sun Q, Pang X, Chen J, Minari T, Liu X, Song Y 2021 Mater. Horiz. 8 447 Google Scholar
[8]	Sun J, Fu Y, Wan Q 2018 J. Phys. D: Appl. Phys. 51 314004 Google Scholar
[9]	Gao J, Zheng Y, Yu W, Wang Y, Jin T, Pan X, Loh K P, Chen W 2021 Smart Mater. 2 88 Google Scholar
[10]	Jeong B, Gkoupidenis P, Asadi K 2021 Adv. Mater. 33 2104034 Google Scholar
[11]	Huang X, Li Q, Shi W, Liu K, Zhang Y, Liu Y, Wei X, Zhao Z, Guo Y, Liu Y 2021 Small 17 2102820 Google Scholar
[12]	Wang C, Liu H, Chen L, Zhu H, Ji L, Sun Q Q, Zhang D W 2021 IEEE Electron Device Lett. 42 1555 Google Scholar
[13]	Huang H, Liu L, Jiang C, Gong J, Ni Y, Xu Z, Wei H, Yu H, Xu W 2022 Neuromorph. Comput. Eng. 2 014004 Google Scholar
[14]	Keene S T, Lubrano C, Kazemzadeh S, Melianas A, Tuchman Y, Polino G, Scognamiglio P, Cina L, Salleo A, van de Burgt Y, Santoro F 2020 Nat. Mater. 19 969 Google Scholar
[15]	Ku B, Koo B, Sokolov A S, Ko M J, Choi C 2020 J. Alloys Compd. 833 155064 Google Scholar
[16]	Yan Y, Chen Q, Wu X, Wang X, Li E, Ke Y, Liu Y, Chen H, Guo T 2020 ACS Appl. Mater. Interfaces 12 49915 Google Scholar
[17]	Wang H, Zhao Q, Ni Z, Li Q, Liu H, Yang Y, Wang L, Ran Y, Guo Y, Hu W 2018 Adv. Mater. 30 1803961 Google Scholar
[18]	Wei H, Yu H, Gong J, Li R, Han H, Ma M, Guo K, Xu W 2021 Mater. Chem. Front. 5 775 Google Scholar
[19]	Gao J, Hao Y, Xu S, Rong X, Lu Q, Zhu C, Hu Y S 2021 Electrochim. Acta 399 139421 Google Scholar
[20]	Wang D, Xu S, Wang J, Rong X, Zhou F, Wang L, Bai X, Lu B, Zhu C, Wang Y, Hu Y S 2022 Energy Storage Mater. 45 92 Google Scholar
[21]	Kong L, Tang C, Peng H J, Huang J Q, Zhang Q 2020 Smart Mater. 1 e1007 Google Scholar
[22]	Liu Q, Hu Z, Chen M, Zou C, Jin H, Wang S, Gu Q, Chou S 2019 J. Mater. Chem. A 7 9215 Google Scholar
[23]	Zhang S Y, Guo Y J, Zhou Y N, Zhang X D, Niu Y B, Wang E H, Huang L B, An P F, Zhang J, Yang X A 2021 Small 17 2007236 Google Scholar
[24]	Xian L, Li M, Qiu D, Qiu C, Yue C, Wang F, Yang R 2022 J. Alloys Compd. 905 163965 Google Scholar
[25]	Song T, Kendrick E 2021 J. Phys. :Mater. 4 032004 Google Scholar
[26]	Yu M, Liu F, Li J, Liu J, Zhang Y, Cheng F 2021 Adv. Energy Mater. 12 2100640 Google Scholar
[27]	Yang X, Specht C G 2019 Front. Mol. Neurosci. 12 161 Google Scholar
[28]	Lu L, Jia Y, Kirunda J B, Xu Y, Ge M, Pei Q, Yang L 2019 Nonlinear Dyn. 95 1673 Google Scholar
[29]	Beckstead M J, Grandy D K, Wickman K, Williams J T 2004 Neuron 42 939 Google Scholar
[30]	Shipman S L, Nicoll R A 2012 Proc. Natl. Acad. Sci. 109 19432 Google Scholar
[31]	Hayashi A, Masuzawa N, Yubuchi S, Tsuji F, Hotehama C, Sakuda A, Tatsumisago M 2019 Nat. Commun. 10 1 Google Scholar
[32]	Wei H, Yu H, Gong J, Zhang J, Han H, Ma M, Ni Y, Du Y, Zhang S, Liu L, Xu W 2019 ACS Appl. Electron. Mater. 2 316 Google Scholar
[33]	Wen Y, Wang B, Zeng G, Nogita K, Ye D, Wang L 2015 Chem. Asian J. 10 661 Google Scholar
[34]	Huang Q, Xu S, Xiao L, He P, Liu J, Yang Y, Wang P, Huang B, Wei W 2018 Inorg. Chem. 57 15584 Google Scholar
[35]	Magee J C, Grienberger C 2020 Annu. Rev. Neurosci. 43 95 Google Scholar
[36]	Li Y, Zhong Y, Zhang J, Xu L, Wang Q, Sun H, Tong H, Cheng X, Miao X 2014 Sci. Rep. 4 1 Google Scholar
[37]	Van Rossum M C, Bi G Q, Turrigiano G G 2000 J. Neurosci. 20 8812 Google Scholar
[38]	Fang L, Dai S, Zhao Y, Liu D, Huang J 2020 Adv. Electron. Mater. 6 1901217 Google Scholar
[39]	Yang K, Yang L, Wang Z, Guo B, Song Z, Fu Y, Ji Y, Liu M, Zhao W, Liu X 2021 Adv. Energy Mater. 11 2100601 Google Scholar
[40]	López J C 2001 Nat. Rev. Neurosci. 2 307 Google Scholar
[41]	Gong J, Yu H, Zhou X, Wei H, Ma M, Han H, Zhang S, Ni Y, Li Y, Xu W 2020 Adv. Funct. Mater. 30 2005413 Google Scholar
[42]	郭科鑫, 于海洋, 韩弘, 卫欢欢, 龚江东, 刘璐, 黄茜, 高清运, 徐文涛 2020 69 238501 Google Scholar Guo K X, Yu H Y, Han H, Wei H H, Gong J D, Liu L, Huang Q, Gao Q Y, Xu W T 2020 Acta Phys. Sin. 69 238501 Google Scholar
[43]	Zhang S, Guo J, Liu L, Ruan H, Kong C, Yuan X, Zhang B, Gu G, Cui P, Cheng G 2022 Nano Energy 91 106660 Google Scholar
[44]	Lee Y, Oh J Y, Xu W, Kim O, Kim T R, Kang J, Kim Y, Son D, Tok J B H, Park M J 2018 Sci. Adv. 4 eaat7387 Google Scholar
[45]	Shim H, Jang S, Jang J G, Rao Z, Hong J I, Sim K, Yu C 2022 Nano Res. 15 758 Google Scholar
[46]	Yang F, Sun L, Duan Q, Dong H, Jing Z, Yang Y, Li R, Zhang X, Hu W, Chua L 2021 Smart Mater. 2 99 Google Scholar

[1]	Li Yang-Fan, Guo Hong-Xia, Zhang Hong, Bai Ru-Xue, Zhang Feng-Qi, Ma Wu-Ying, Zhong Xiang-Li, Li Ji-Fang, Lu Xiao-Jie. Heavy ion single event effect in double-trench SiC metal-oxide-semiconductor field-effect transistors. Acta Physica Sinica, 2024, 73(2): 026103. doi: 10.7498/aps.73.20231440
[2]	Li Rui, Xu Bang-Lin, Zhou Jian-Fang, Jiang En-Hua, Wang Bing-Hong, Yuan Wu-Jie. A synaptic plasticity induced change in synaptic intensity variation and neurodynamic transition during awakening-sleep cycle. Acta Physica Sinica, 2023, 72(24): 248706. doi: 10.7498/aps.72.20231037
[3]	Li Yan, Chen Xin-Li, Wang Wei-Sheng, Shi Zhi-Wen, Zhu Li-Qiang. Egg shell membrane based electrolyte gated oxide neuromorphic transistor. Acta Physica Sinica, 2023, 72(15): 157302. doi: 10.7498/aps.72.20230411
[4]	Ju Xiao-Lu, Li Ke, Yu Fu-Cheng, Xu Ming-Wei, Deng Biao, Li Bin, Xiao Ti-Qiao. Move contrast X-ray imaging of electrochemical reaction process in electrolytic cell. Acta Physica Sinica, 2022, 71(14): 144101. doi: 10.7498/aps.71.20220339
[5]	Hua Hong-Tao, Lu Bo, Gu Hua-Guang. Nonlinear mechanism of excitatory autapse-induced reduction or enhancement of firing frequency of neuronal bursting. Acta Physica Sinica, 2020, 69(9): 090502. doi: 10.7498/aps.69.20191709
[6]	Guo Ke-Xin, Yu Hai-Yang, Han Hong, Wei Huan-Huan, Gong Jiang-Dong, Liu Lu, Huang Qian, Gao Qing-Yun, Xu Wen-Tao. Artificial synapse based on MoO₃ nanosheets prepared by hydrothermal synthesis. Acta Physica Sinica, 2020, 69(23): 238501. doi: 10.7498/aps.69.20200928
[7]	Chen Yi-Hao, Xu Wei, Wang Yu-Qi, Wan Xiang, Li Yue-Feng, Liang Ding-Kang, Lu Li-Qun, Liu Xin-Wei, Lian Xiao-Juan, Hu Er-Tao, Guo Yu-Feng, Xu Jian-Guang, Tong Yi, Xiao Jian. Fabrication of synaptic memristor based on two-dimensional material MXene and realization of both long-term and short-term plasticity. Acta Physica Sinica, 2019, 68(9): 098501. doi: 10.7498/aps.68.20182306
[8]	Xue Xiao-Dan, Wang Mei-Li, Shao Yu-Zhu, Wang Jun-Song. Neural firing rate homeostasis via inhibitory synaptic plasticity. Acta Physica Sinica, 2019, 68(7): 078701. doi: 10.7498/aps.68.20182234
[9]	Liu Yi-Chun, Lin Ya, Wang Zhong-Qiang, Xu Hai-Yang. Oxide-based memristive neuromorphic synaptic devices. Acta Physica Sinica, 2019, 68(16): 168504. doi: 10.7498/aps.68.20191262
[10]	Wang Ji-Fei, Lin Dong-Xu, Yuan Yong-Bo. Recent progress of ion migration in organometal halide perovskite. Acta Physica Sinica, 2019, 68(15): 158801. doi: 10.7498/aps.68.20190853
[11]	Li Ping, Xu Yu-Tang. Monte Carlo simulation of time-dependent dielectric breakdown of oxide caused by migration of oxygen vacancies. Acta Physica Sinica, 2017, 66(21): 217701. doi: 10.7498/aps.66.217701
[12]	Ding Xue-Li, Li Yu-Ye. Period-adding bifurcation of neural firings induced by inhibitory autapses with time-delay. Acta Physica Sinica, 2016, 65(21): 210502. doi: 10.7498/aps.65.210502
[13]	Cao Ru-Nan, Xu Fei, Zhu Jia-Bin, Ge Sheng, Wang Wen-Zhen, Xu Hai-Tao, Xu Run, Wu Yang-Lin, Ma Zhong-Quan, Hong Feng, Jiang Zui-Min. Temperature-dependent time response characteristic of photovoltaic performance in planar heterojunction perovskite solar cell. Acta Physica Sinica, 2016, 65(18): 188801. doi: 10.7498/aps.65.188801
[14]	Meng Fan-Yi, Duan Shu-Kai, Wang Li-Dan, Hu Xiao-Fang, Dong Zhe-Kang. An improved WOx memristor model with synapse characteristic analysis. Acta Physica Sinica, 2015, 64(14): 148501. doi: 10.7498/aps.64.148501
[15]	Ren Guo-Dong, Wu Gang, Ma Jun, Chen Yang. Simulation of electric activity of neuron by setting up a reliable neuronal circuit driven by electric autapse. Acta Physica Sinica, 2015, 64(5): 058702. doi: 10.7498/aps.64.058702
[16]	Wang Mei-Li, Wang Jun-Song. Dynamical balance between excitation and inhibition of feedback neural circuit via inhibitory synaptic plasticity. Acta Physica Sinica, 2015, 64(10): 108701. doi: 10.7498/aps.64.108701
[17]	Xia Xiao-Fei, Wang Jun-Song. Influence of synaptic plasticity on dynamics of neural mass model：a bifurcation study. Acta Physica Sinica, 2014, 63(14): 140503. doi: 10.7498/aps.63.140503
[18]	Li Chun-Guang, Chen Jun. Chaos in a neuron model with adaptive feedback synapse: Electronic circuit design. Acta Physica Sinica, 2011, 60(5): 050503. doi: 10.7498/aps.60.050503
[19]	XIAO DING-QUAN, WEI LI-FAN, LI ZI-SEN, ZHU JIAN-GUO, QIAN ZHENG-HONG, PENG WEN-BIN. MODELLING OF MULTI-ION-BEAM REACTIVE COSPUTTERING OF METAL OXIDE THIN FILMS (Ⅱ)——NUMERICAL CALCULATION AND RESULTS DISCUSSION. Acta Physica Sinica, 1996, 45(2): 345-352. doi: 10.7498/aps.45.345
[20]	XIAO DING-QUAN, WEI LI-FAN, LI ZI-SEN, ZHU JIAN-GUO, QIAN ZHENG-HONG, PENG WEN-BIN. MODELLING OF MULTI-ION-BEAM REACTIVE COSPUTTERING OF METAL OXIDE THIN FILMS (I)——ESTABLISHMENT OF THE MODEL. Acta Physica Sinica, 1996, 45(2): 330-338. doi: 10.7498/aps.45.330

Catalog

Vol. 71, Issue 14 - 2022-07-20

Metrics

Abstract views: 6643
PDF Downloads: 264
Cited By: 0

姓名
邮箱
手机号码
标题
留言内容
验证码

Search

Article

留言板