Dual-gate IGZO-based Neuromorphic Transistors with Stacked Al2O3/Chitosan Gate Dielectrics

doi:10.15541/jim20220767

Abstract

Abstract:

Indium-gallium-zinc-oxide (IGZO)-based electric-double-layer (EDL) transistors have great applications for neuromorphic perception and computing systems because of their low processing temperature, high homogeneity, and plentiful ionic dynamics. However, IGZO-based EDL transistors have problems of high leakage current (>10 nA), high energy consumption and abnormal current spikes, which are the main obstacles to the development of neuromorphic computing systems based on such devices. In this work, a novel IGZO neuromorphic transistor with Al₂O₃/chitosan stacked gate dielectric was proposed. Compared with the monolayer chitosan gate dielectric transistor, the device with Al₂O₃/chitosan layer showed low subthreshold swing of 78.3 mV/decade, a low gate leakage current of 1.3 nA (reduced by about 98%), a large hysteresis window of 3.73 V (increased by about 3.4 times), a low excitable postsynaptic current of 0.86 nA (decreased by about 97%) and an energy consumption of 1.7 pJ for a spike event (0.5 V, 20 ms). Additionally, the emulation of spiking synaptic function and the synergistically modulation of the channel current were also realized, and the abnormal current spike caused by high leakage in synaptic plasticity simulation was also effectively avoided. The results suggest that the inserting of high-k dielectric layer can effectively improve the leakage current, energy consumption and performance of neuromorphic devices, which has substantial value for future ultra-low energy consumption neuromorphic perception and computing systems.

Key words: neuromorphic device, IGZO-based transistor, artificial synapse, stacked gate dielectric, high-k dielectric, synaptic plasticity

CLC Number:

TN321

WANG Jingyu, WAN Changjin, WAN Qing. Dual-gate IGZO-based Neuromorphic Transistors with Stacked Al₂O₃/Chitosan Gate Dielectrics[J]. Journal of Inorganic Materials, 2023, 38(4): 445-451.

Figures/Tables 8

Fig. 1 Schematic diagram of the IGZO-based neuromorphic transistor with different gate dielectrics (a) Chitosan gate dielectric; (b) Stacked Al2O3/chitosan gate dielectrics

Fig. 2 Leakage current curves and corresponding AFM images (inset) of monolayer gate dielectric and bilayer gate dielectric (a) Chitosan solid dielectric; (b) Stacked Al2O3/chitosan bilayer gate dielectric (Inset: AFM image of Al2O3 membrane)

Fig. 3 Transfer characteristics and output characteristics of two kinds of dielectric devices (a,b) Transfer characteristics of chitosan dielectric device (a) and stacked Al2O3/chitosan bilayer gate dielectric device (b); (c) Output characteristic of chitosan dielectric device; (d) Output characteristic of stacked Al2O3/chitosan bilayer gate dielectric device

Table 1 Transistor parameters of IGZO-based transistors

Gate dielectric	I_off	I_on/I_offratio	Subthreshold swing/ (mV·decade^-1)	Hysteresis window/V	Leakage current (V_G=1.8 V)/nA	μ_sat/ (cm²·V^-1·s^-1)
Chitosan	2.92×10^-9	1.06×10⁵	98.8	1.10	66.4	18.0
Chitosan/Al₂O₃	4.20×10^-11	2.20×10⁶	78.3	3.73	1.3	20.9

Fig. 4 (a) Top micrograph, (b) transfer characteristics with different VG2 (from-2.0 V to 1.0 V) and (c) the Vth with different VG2 of transistor

Fig. 5 (a) Schematic diagram of biological synapse and their equivalent electrical circuit of the neuromorphic transistor, (b) EPSC responses under an electric pulse of 0.5 V, and (c) EPSC induced by electric pulses of different amplitudes for IGZO-based dual-gate transistor with stacked Al2O3/chitosan gate dielectrics

Table 2 Energy consumption of the single EPSC peak in different artificial synaptic transistors

Structure	V_DS/V	V_G pulse	EPSC/nA	Energy consumption/(pJ·spike^-1)	Ref.
Nanogranular SiO₂/IZO	1.0	0.8 V, 20 ms	5000	10⁵	[33]
GO+Chitosan/IGZO	0.1	0.5 V, 20 ms	14	28	[34]
Carbon Nanotube (CNT)	0.5	4.0 V, 1.0 ms	15	7.5	[35]
Chitosan/IZO	0.1	0.5 V, 25 ms	2.6	6.5	[36]
Chitosan/IWO	0.1	0.2 V, 20 ms	4.7	9.4	[37]
Chitosan/IGZO	0.1	0.5 V, 20 ms	26	52	[38]
Tungsten oxide	0.3	0.6 V, 70 ms	3.8	79	[39]
Chitosan/ IGZO	0.1	0.5 V, 20 ms	24	48	This work
Chitosan/Al₂O₃/IGZO	0.1	0.5 V, 20 ms	0.86	1.7	This work

Fig. 6 (a) Multi-pulse facilitation induced by eight successive electric pulse (0.5 V, 25 ms) and (b) ratio of A8/A1 plotted as a function of the time interval between the pulses for IGZO-based dual-gate transistor with stacked Al2O3/chitosan gate dielectrics

References 40

[1]	ROY K, JAISWAL A, PANDA P. Towards spike-based machine intelligence with neuromorphic computing. Nature, 2019, 575(7784):607. DOI
[2]	YU S. Neuro-inspired computing with emerging nonvolatile memorys. Proceedings of the IEEE, 2018, 106(2):260. DOI URL
[3]	PREZIOSO M, MERRIKH-BAYAT F, HOSKINS B D, et al. Training and operation of an integrated neuromorphic network based on metal-oxide memristors. Nature, 2015, 521(7550):61. DOI
[4]	ZHU Y, ZHU Y, MAO H, et al. Recent advances in emerging neuromorphic computing and perception devices. Journal of Physics D: Applied Physics, 2021, 55(5):053002. DOI
[5]	YOU Z, RAMANATHAN S. Mott memory and neuromorphic devices. Proceedings of the IEEE, 2015, 103(8):1289. DOI URL
[6]	WANG J, LI Y, YIN C, et al. Long-term depression mimicked in an IGZO-based synaptic transistor. IEEE Electron Device Letters, 2017, 38(2):191. DOI URL
[7]	PARK Y J, KWON H T, KIM B, et al. 3-D stacked synapse array based on charge-trap flash memory for implementation of deep neural networks. IEEE Transactions on Electron Devices, 2019, 66(1): 420.
[8]	YAN W, PAGE A, NGUYEN-DANG T, et al. Advanced multimaterial electronic and optoelectronic fibers and textiles. Advanced Materials, 2019, 31(1):e1802348.
[9]	YAN W, QU Y, GUPTA T D, et al. Semiconducting nanowire-based optoelectronic fibers. Advanced Materials, 2017, 29(27):1700681. DOI URL
[10]	GKOUPIDENIS P, KOUTSOURAS D A, LONJARET T, et al. Orientation selectivity in a multi-gated organic electrochemical transistor. Scientific Reports, 2016, 6: 27007.
[11]	KIM M K, LEE J S. Ferroelectric analog synaptic transistors. Nano Letters, 2019, 19(3): 2044. DOI URL
[12]	ZHU Y, MAO H, ZHU Y, et al. Photoelectric synapse based on InGaZnO nanofibers for high precision neuromorphic computing. IEEE Electron Device Letters, 2022, 43(4): 651.
[13]	MAO H, HE Y, CHEN C, et al. A spiking stochastic neuron based on stacked InGaZnO memristors. Advanced Electronic Materials, 2021, 8(2):2100918. DOI URL
[14]	JIANG J, WAN Q, SUN J, et al. Ultralow-voltage transparent electric-double-layer thin-film transistors processed at room-temperature. Applied Physics Letters, 2009, 95 (15): 152114. DOI URL
[15]	VAN DE BURGT Y, MELIANAS A, KEENE S T, et al. Organic electronics for neuromorphic computing. Nature Electronics, 2018, 1(7):386. DOI
[16]	HE Y, YANG Y, NIE S, et al. Electric-double-layer transistors for synaptic devices and neuromorphic systems. Journal of Materials Chemistry C, 2018, 6(20):5336. DOI URL
[17]	HE Y, NIE S, LIU R, et al. Dual-functional long-term plasticity emulated in IGZO-based photoelectric neuromorphic transistors. IEEE Electron Device Letters, 2019, 40(5):818. DOI URL
[18]	KIM J, KIM Y, KWON O, et al. Modulation of synaptic plasticity mimicked in Al nanoparticle-embedded IGZO synaptic transistor. Advanced Electronic Materials, 2020, 6(4):1901072. DOI URL
[19]	ZHU Y, HE Y, JIANG S, et al. Indium-gallium-zinc-oxide thin-film transistors: materials, devices, and applications. Journal of Semiconductors, 2021, 42(3):031101. DOI
[20]	JANG Y, PARK J, KANG J, et al. Amorphous InGaZnO (a-IGZO) synaptic transistor for neuromorphic computing. ACS Applied Electronic Materials, 2022, 4(4):1427. DOI URL
[21]	VAN DE BURGT Y, LUBBERMAN E, FULLER E J, et al. A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing. Nature Materials, 2017, 16(4):414. DOI PMID
[22]	KUZUM D, JEYASINGH R G, LEE B, et al. Nanoelectronic programmable synapses based on phase change materials for brain-inspired computing. Nano Letters, 2012, 12(5): 2179. DOI PMID
[23]	KIM C, FACCHETTI A, MARKS T J. Gate dielectric microstructural control of pentacene film growth mode and field-effect transistor performance. Advanced Materials, 2007, 19(18):2561. DOI URL
[24]	WANG B, HUANG W, CHI L, et al. High-k gate dielectrics for emerging flexible and stretchable electronics. Chemical Reviews, 2018, 118(11):5690. DOI URL
[25]	ZHOU J, LIU Y, SHI Y, et al. Solution-processed chitosan-gated IZO-based transistors for mimicking synaptic plasticity. IEEE Electron Device Letters, 2014, 35(2):280. DOI URL
[26]	GAO S, ZHOU Q, LIU X, et al. Breakdown enhancement and current collapse suppression in AlGaN/GaN HEMT by NiO_X/ SiN_X and Al₂O₃/SiN_X as gate dielectric layer and passivation layer. IEEE Electron Device Letters, 2019, 40(12): 1921. DOI URL
[27]	WEI W, ZENG Z, LIAO W, et al. Extended gate ion-sensitive field-effect transistors using Al₂O₃/hexagonal boron nitride nanolayers for ph sensing. ACS Applied Nano Materials, 2019, 3(1):403. DOI URL
[28]	PALASANTZAS G, HOSSON J D, and BARNAS J. Surface/ interface roughness effects on magneto-electrical properties of thin films. Surface Science, 2002, 507-510: 541.
[29]	LI J, WU J, LIU J, et al. Effect of composition, interface, and deposition sequence on electrical properties of nanolayered Ta₂O₅-Al₂O₃ films grown on silicon by atomic layer deposition. Nanoscale Research Letters, 2019, 14(1):75. DOI
[30]	CHOE M, JO G, MAENG J, et al. Electrical properties of ZnO nanowire field effect transistors with varying high-k Al₂O₃ dielectric thickness. Journal of Applied Physics, 2010, 107(3):034504. DOI URL
[31]	FORTUNATO E, BARQUINHA P, MARTINS R. Oxide semiconductor thin-film transistors: a review of recent advances. Advanced Materials, 2012, 24(22): 2945.
[32]	ZHU L Q, CHAO J Y, XIAO H, et al. Chitosan-based electrolyte gated low voltage oxide transistor with a coplanar modulatory terminal. IEEE Electron Device Letters, 2017, 38(3):322. DOI URL
[33]	WAN X, HE Y, NIE S, et al. Biological band-pass filtering emulated by oxide-based neuromorphic transistors. IEEE Electron Device Letters, 2018, 39(11):1764. DOI URL
[34]	NIE S, HE Y, LIU R, et al. Low-voltage oxide-based synaptic transistors for spiking humidity detection. IEEE Electron Device Letters, 2019, 40(3):459. DOI URL
[35]	KIM K, CHEN C L, TRUONG Q, et al. A carbon nanotube synapse with dynamic logic and learning. Advanced Materials, 2013, 25(12): 1693.
[36]	JIANG S, HE Y, LIU R, et al. Synaptic metaplasticity emulation in a freestanding oxide-based neuromorphic transistor with dual in-plane gates. Journal of Physics D: Applied Physics, 2021, 54(18):185106. DOI
[37]	LIU R, HE Y, JIANG S, et al. Synaptic plasticity and classical conditioning mimicked in single indium-tungsten-oxide based neuromorphic transistor. Chinese Physics B, 2021, 30(5):058102. DOI
[38]	ZHANG C, LI S, HE Y, et al. Oxide synaptic transistors coupled with triboelectric nanogenerators for bio-inspired tactile sensing application. IEEE Electron Device Letters, 2020, 41(4):617. DOI URL
[39]	YANG J T, GE C, DU J Y, et al. Artificial synapses emulated by an electrolyte-gated tungsten-oxide transistor. Advanced Materials, 2018, 30(34):e1801548.
[40]	ZIEGLER M, KOHLSTEDT H. Mimic synaptic behavior with a single floating gate transistor: a memflash synapse. Journal of Applied Physics, 2013, 114(19):194506. DOI URL

Dual-gate IGZO-based Neuromorphic Transistors with Stacked Al₂O₃/Chitosan Gate Dielectrics

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 8

References 40

Related Articles 5

Recommended Articles

Metrics

Comments

[1]	YANG Yang, CUI Hangyuan, ZHU Ying, WAN Changjin, WAN Qing. Research Progress of Flexible Neuromorphic Transistors [J]. Journal of Inorganic Materials, 2023, 38(4): 367-377.
[2]	DU Jianyu, GE Chen. Recent Progress in Optoelectronic Artificial Synapse Devices [J]. Journal of Inorganic Materials, 2023, 38(4): 378-386.
[3]	QIU Haiyang, MIAO Guangtan, LI Hui, LUAN Qi, LIU Guoxia, SHAN Fukai. Effect of Plasma Treatment on the Long-term Plasticity of Synaptic Transistor [J]. Journal of Inorganic Materials, 2023, 38(4): 406-412.
[4]	FANG Renrui, REN Kuan, GUO Zeyu, XU Han, ZHANG Woyu, WANG Fei, ZHANG Peiwen, LI Yue, SHANG Dashan. Associative Learning with Oxide-based Electrolyte-gated Transistor Synapses [J]. Journal of Inorganic Materials, 2023, 38(4): 399-405.
[5]	ZHUGE Xia, ZHU Renxiang, WANG Jianmin, WANG Jingrui, ZHUGE Fei. Oxide Memristors for Brain-inspired Computing [J]. Journal of Inorganic Materials, 2023, 38(10): 1149-1162.