An Oxide-Based Bilayer ZrO2/IGZO Memristor for Synaptic Plasticity and Artificial Nociceptor

被引:23
作者
Chen, Xin [1 ]
Jin, Yaoyao [1 ]
Tao, Zipei [1 ]
Jiang, Li [1 ]
Wu, Xinjiang [1 ]
Xiao, Yongyue [1 ]
Jiang, Bei [1 ]
Wen, Xin [2 ]
Zhang, Jun [1 ]
Zhu, Min [3 ]
Ye, Cong [1 ,4 ]
机构
[1] Hubei Univ, Fac Phys & Elect Sci, Hubei Key Lab Ferro & Piezoelect Mat & Devices, Wuhan 430062, Peoples R China
[2] West Pomeranian Univ Technol Szczecin, Fac Chem Technol & Engn, PL-71065 Szczecin, Poland
[3] Chinese Acad Sci, Shanghai Inst Microsyst & Informat Technol, Shanghai 200050, Peoples R China
[4] Huazhong Univ Sci & Technol, Belt & Rd Joint Lab Measurement & Control Technol, Wuhan 430074, Peoples R China
基金
中国国家自然科学基金;
关键词
Memristors; Synapses; Biology; Tin; Immune system; Electrodes; Switches; Artificial nociceptor; bilayer (BL); memristor; neuromorphic device; synaptic plasticity; MEMORY; DEVICE; SYNAPSES;
D O I
10.1109/TED.2023.3236588
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
As artificial intelligence technology advances, memristors are promising to be used as artificial synapses to mimic various biological learning behaviors. In this work, all the memristors are fabricated using 45-nm complementary metal-oxide-semiconductor (CMOS) technology on Si/SiO2 substrate. By inserting a 3-nm indium gallium zinc oxide (IGZO) layer into the Pt/ZrO2/TiN single-layer (SL) memristor, the storage window of the bilayer (BL) memristor is enhanced to 11 times that of the single one. It demonstrates the multilevel conductivity modulating properties of the BL memristors, which can be used to mimic the learning behavior of biological synapses. The Pt/ZrO2/IGZO/TiN memristor has achieved synaptic plasticity, including long-term potentiation/depression (LTP/LTD), spike-timing-dependent plasticity (STDP), and paired-pulse facilitation (PPF). Moreover, the inadaptation, threshold, hyperalgesia, and allodynia characteristics of a nociceptor based on Pt/ZrO2/IGZO/TiN memristor have been accomplished. The BL oxide-based memristor with outstanding synaptic properties and the simulation as an artificial nociceptor provides a feasible application in the future neuromorphic systems for bionic robots.
引用
收藏
页码:1001 / 1005
页数:5
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