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Flexible Organic Optoelectronic Devices for Neuromorphic Computing

With the demand of wearable device in the field of flexible electronic, synaptic devices with capability of neuromorphic computing are attracting increasing attention. In this paper, an organic flexible device with excellent synaptic behaviors was fabricated on MICA substrate, which has a memory win...

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Published in:IEEE electron device letters 2023-07, Vol.44 (7), p.1-1
Main Authors: Hu, Xuemeng, Meng, Jialin, Li, Qingxuan, Wang, Tianyu, Zhu, Hao, Sun, Qingqing, Zhang, David Wei, Chen, Lin
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cited_by cdi_FETCH-LOGICAL-c292t-c22f212331b30a2e93482b00d9e67e4df31aca3058d2585313945c00cb7be0393
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container_title IEEE electron device letters
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creator Hu, Xuemeng
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Chen, Lin
description With the demand of wearable device in the field of flexible electronic, synaptic devices with capability of neuromorphic computing are attracting increasing attention. In this paper, an organic flexible device with excellent synaptic behaviors was fabricated on MICA substrate, which has a memory window more than 20V. 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 modulation. Importantly, after repeated bending, the electrical characteristics of the device maintains stable and can still obtain synaptic behaviors by electrical and optical pulses. The proposal of the device provides the possibility of applications for wearable artificial synapses.
doi_str_mv 10.1109/LED.2023.3274825
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source IEEE Electronic Library (IEL) Journals
subjects Behavioral sciences
Bending
Electrodes
highly flexible device
Logic gates
long-term potentiation/depression
Mica
Neuromorphic computing
Neuromorphic engineering
Optical memory (data storage)
Optical pulses
Optoelectronic devices
organic artificial synapse
Substrates
Synapses
Wearable technology
title Flexible Organic Optoelectronic Devices for Neuromorphic Computing
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