Visible light-driven indium-gallium-zinc-oxide optoelectronic synaptic transistor with defect engineering for neuromorphic computing system and artificial intelligence

被引:25
作者
Chung, Jusung [1 ,2 ]
Park, Kyungho [1 ]
Kim, Gwan In [1 ]
Bin An, Jong [1 ]
Jung, Sujin [1 ]
Choi, Dong Hyun [1 ]
Kim, Hyun Jae [1 ]
机构
[1] Yonsei Univ, Sch Elect & Elect Engn, 50 Yonsei ro, Seoul 03722, South Korea
[2] Yonsei Univ, BIT Micro Fab Res Ctr, 50 Yonsei ro, Seoul 03722, South Korea
基金
新加坡国家研究基金会;
关键词
Oxide semiconductor; Solution process; Defect engineering; Optoelectronic synaptic transistor; Electrohydrodynamic jet printing; SYNAPSES;
D O I
10.1016/j.apsusc.2022.155532
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
There has been considerable interest in the development of optoelectronic synaptic transistors with synaptic functions and neural computations. These neuromorphic devices exhibit high-efficiency energy consumption and fast operation by imitating biological neural computation methods. Here, a simple defect engineering method for oxide semiconductors is proposed so that indium-gallium-zinc-oxide (IGZO) optoelectronic synaptic transistors can have synaptic behavior even in the long-wavelength-visible-light region, in which it is difficult to stimulate the conventional oxide semiconductor. Two additional defective layers (the defective interface layer and light absorption layer) are controlled to generate defects that improve the synaptic function and visible-light ab-sorption. The IGZO optoelectronic synaptic transistor with defect engineering shows the peak of photo-induced postsynaptic current (PSC) of 17.04 nA and maximum gain of 24.67 with 25 optical pulses and a 198% paired -pulse facilitation (PPF) index under red-light illumination at a 635-nm wavelength. Furthermore, learning and forgetting were mimicked by optical and electrical signals, as demonstrated in a "Pavlov's dog" experiment. These results demonstrate that IGZO optoelectronic synaptic transistors can be used in various optical applica-tions driven by a wide range of visible light, such as artificial eyes or intelligent display products.
引用
收藏
页数:9
相关论文
共 48 条
[1]  
Anyaegbunam FNC, 2018, DIG J NANOMATER BIOS, V13, P847
[2]  
Atkinson R.C., 1968, PSYCHOL LEARNING MOT, V2, P89, DOI DOI 10.1016/S0079-7421(08)60422-3
[3]   An energy budget for signaling in the grey matter of the brain [J].
Attwell, D ;
Laughlin, SB .
JOURNAL OF CEREBRAL BLOOD FLOW AND METABOLISM, 2001, 21 (10) :1133-1145
[4]   A Long Wavelength-dependent Optical Memory Characteristics of Amorphous Oxide-based Thin Film Devices [J].
Bae, Junyoung ;
Jeong, Inkyung ;
Lee, Sungsik .
2019 INTERNATIONAL CONFERENCE ON ELECTRONICS, INFORMATION, AND COMMUNICATION (ICEIC), 2019, :409-410
[5]   Simple, Low-Temperature Route To Synthesize ZnO Nanoparticles and Their Optical Neuromorphic Characteristics [J].
Chandra, Ramachandrapanicker Devi ;
Gopchandran, Kunnel Gopalan .
ACS APPLIED ELECTRONIC MATERIALS, 2021, 3 (09) :3846-3854
[6]   Amorphous InGaZnO Ultraviolet Phototransistors With a Thin Ga2O3 Layer [J].
Chang, Shoou-Jinn ;
Chang, T. H. ;
Weng, W. Y. ;
Chiu, C. J. ;
Chang, S. P. .
IEEE JOURNAL OF SELECTED TOPICS IN QUANTUM ELECTRONICS, 2014, 20 (06) :125-129
[7]   High responsivity of amorphous indium gallium zinc oxide phototransistor with Ta2O5 gate dielectric [J].
Chang, T. H. ;
Chiu, C. J. ;
Weng, W. Y. ;
Chang, S. J. ;
Tsai, T. Y. ;
Huang, Z. D. .
APPLIED PHYSICS LETTERS, 2012, 101 (26)
[8]   Quasi-Two-Dimensional Metal Oxide Semiconductors Based Ultrasensitive Potentiometric Biosensors [J].
Chen, Huajun ;
Rim, You Seung ;
Wang, Isaac Caleb ;
Li, Chao ;
Zhu, Bowen ;
Sun, Mo ;
Goorsky, Mark S. ;
He, Ximin ;
Yang, Yang .
ACS NANO, 2017, 11 (05) :4710-4718
[9]   Solar-blind SnO2 nanowire photo-synapses for associative learning and coincidence detection [J].
Chen, Yang ;
Qiu, Weijie ;
Wang, Xiaowu ;
Liu, Wanrong ;
Wang, Juxiang ;
Dai, Guozhang ;
Yuan, Yongbo ;
Gao, Yongli ;
Sun, Jia .
NANO ENERGY, 2019, 62 :393-400
[10]   Multi-spectral gate-triggered heterogeneous photonic neuro-transistors for power-efficient brain-inspired neuromorphic computing [J].
Cho, Sung Woon ;
Kwon, Sung Min ;
Lee, Minkyung ;
Jo, Jeong-Wan ;
Heo, Jae Sang ;
Kim, Yong-Hoon ;
Cho, Hyung Koun ;
Park, Sung Kyu .
NANO ENERGY, 2019, 66