Organic heterojunction synaptic device with ultra high recognition rate for neuromorphic computing

被引:7
作者
Hu, Xuemeng [1 ]
Meng, Jialin [1 ]
Feng, Tianyang [1 ]
Wang, Tianyu [1 ]
Zhu, Hao [1 ]
Sun, Qingqing [1 ]
Zhang, David Wei [1 ]
Chen, Lin [1 ,2 ]
机构
[1] Fudan Univ, Sch Microelect, State Key Lab Integrated Chips & Syst, Shanghai 200433, Peoples R China
[2] Natl Integrated Circuit Innovat Ctr, Shanghai 201203, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
organic heterojunction; neuromorphic computing; synapse behaviors; optical modulation; Modified National Institute of Standards and Technology (MNIST) pattern recognition; TRANSISTORS;
D O I
10.1007/s12274-024-6532-6
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
Traditional computing structures are blocked by the von Neumann bottleneck, and neuromorphic computing devices inspired by the human brain which integrate storage and computation have received more and more attention. Here, a flexible organic device with 2,7-dioctyl[1] benzothieno [3,2-b][1] benzothiophene (C8-BTBT) and 2,9-didecyldinaphtho [2,3-b:2,3 '-f] thieno [3,2-b] thiophene (C10-DNTT) heterostructural channel having excellent synaptic behaviors was fabricated on muscovite (MICA) substrate, which has a memory window greater than 20 V. This device shows better electrical characteristics than organic field effect transistors with single organic semiconductor channel. Furthermore, the device simulates organism synaptic behaviors successfully, such as paired-pulse facilitation (PPF), long-term potentiation/depression (LTP/LTD) process, and transition from short-term memory (STM) to long-term memory (LTM) by optical and electrical modulations. Importantly, the neuromorphic computing function was verified using the Modified National Institute of Standards and Technology (MNIST) pattern recognition, with a recognition rate nearly 100% without noise. This research proposes a flexible organic heterojunction with the ultra-high recognition rate in MNIST pattern recognition and provides the possibility for future flexible wearable neuromorphic computing devices.
引用
收藏
页码:5614 / 5620
页数:7
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