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Research Article

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

Xuemeng Hu1, Jialin Meng1( ), Tianyang Feng1, Tianyu Wang1, Hao Zhu1, Qingqing Sun1, David Wei Zhang1, Lin Chen1,2( )
School of Microelectronics, State Key Laboratory of Integrated Chips and Systems, Fudan University, Shanghai 200433, China
National Integrated Circuit Innovation Center, Shanghai 201203, China
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Graphical Abstract

The organic heterojunction transistors have better electrical characteristic than transistors using single organic semiconductor as channel. Besides, the device can achieve series of synapse behaviors under electrical and optical modulation. The recognition rate of images for the device is nearly 100% without noise, indicating the excellent images recognition ability of the device.

Abstract

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.

Keywords

organic heterojunctionneuromorphic computingsynapse behaviorsoptical modulationModified National Institute of Standards and Technology (MNIST) pattern recognition

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Nano Research
Volume 17 Issue 6,
June 2024
Pages 5614-5620
DOI: 10.1007/s12274-024-6532-6
Cite this article:
Hu X, Meng J, Feng T, et al. Organic heterojunction synaptic device with ultra high recognition rate for neuromorphic computing. Nano Research, 2024, 17(6): 5614-5620. https://doi.org/10.1007/s12274-024-6532-6
Topics:
HeterojunctionsNanoelectronics Neuromorphic ComputingOrganic field effect transistorsPhotoelectric devices

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Received: 15 December 2023
Revised: 28 January 2024
Accepted: 30 January 2024
Published: 14 March 2024
© Tsinghua University Press 2024
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