Flexible Organic Electrochemical Transistors for Energy-Efficient Neuromorphic Computing

被引:0
作者
Zhu, Li [1 ]
Lin, Junchen [1 ]
Zhu, Yixin [2 ]
Wu, Jie [1 ]
Wan, Xiang [1 ]
Sun, Huabin [1 ,3 ]
Yu, Zhihao [1 ,3 ]
Xu, Yong [1 ,3 ]
Tan, Cheeleong [1 ,3 ]
机构
[1] Nanjing Univ Posts & Telecommun, Coll Integrated Circuit Sci & Engn, Nanjing 210023, Peoples R China
[2] Yongjiang Lab Y LAB, Ningbo 315202, Peoples R China
[3] Guangdong Greater Bay Area Inst Integrated Circuit, Guangzhou 510535, Peoples R China
基金
中国国家自然科学基金;
关键词
flexible organic transistor; low-power; artificial synapse; short-term and long-term plasticity; neuromorphic computing; SYNAPTIC TRANSISTORS; MEMRISTOR; DEVICES; MEMORY; LAYER;
D O I
10.3390/nano14141195
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Brain-inspired flexible neuromorphic devices are of great significance for next-generation high-efficiency wearable sensing and computing systems. In this paper, we propose a flexible organic electrochemical transistor using poly[(bithiophene)-alternate-(2,5-di(2-octyldodecyl)- 3,6-di(thienyl)-pyrrolyl pyrrolidone)] (DPPT-TT) as the organic semiconductor and poly(methyl methacrylate) (PMMA)/LiClO4 solid-state electrolyte as the gate dielectric layer. Under gate voltage modulation, an electric double layer (EDL) forms between the dielectric layer and the channel, allowing the device to operate at low voltages. Furthermore, by leveraging the double layer effect and electrochemical doping within the device, we successfully mimic various synaptic behaviors, including excitatory post-synaptic currents (EPSC), paired-pulse facilitation (PPF), high-pass filtering characteristics, transitions from short-term plasticity (STP) to long-term plasticity (LTP), and demonstrate its image recognition and storage capabilities in a 3 x 3 array. Importantly, the device's electrical performance remains stable even after bending, achieving ultra-low-power consumption of 2.08 fJ per synaptic event at -0.001 V. This research may contribute to the development of ultra-low-power neuromorphic computing, biomimetic robotics, and artificial intelligence.
引用
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页数:12
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