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All optical artificial synapses based on long-afterglow material for optical neural network
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作者 Wenjie Lu Qizhen Chen +5 位作者 huaan zeng Hui Wang Lujian Liu Tailiang Guo Huipeng Chen Rui Wang 《Nano Research》 SCIE EI CSCD 2023年第7期10004-10010,共7页
Artificial neural network with broad application prospect has attracted particular attention due to the promise of solving the memory wall bottleneck.The neural devices that mix light and electricity provide more degr... Artificial neural network with broad application prospect has attracted particular attention due to the promise of solving the memory wall bottleneck.The neural devices that mix light and electricity provide more degrees of freedom for the design of artificial neural network,but they still do not get rid of the shackles that the response signal needs circuit to transmission.The exploration of all-optical neural devices(optical signal input and output)is expected to solve this problem.Here,an all-optical synaptic device simply based on a long-afterglow material is reported.The optical properties of the all-optical synaptic device are similar to the responses in biological synapses.Unique image displays and memory functions can be achieved by combining alloptical synaptic arrays with synaptic memory behavior.Furthermore,the optical summation of all-optical synaptic array pixels can be completed by combining the focusing characteristics of convex lens,which realizes the photon transmission after preprocessing multiple input signals.Particularly,the simple single-layer structure of all-optical synapses with polydimethylsiloxane(PDMS)as the carrier has high plasticity and is expected to achieve large-scale preparation.This work enriches the diversity of artificial synapses and shows the huge development potential of photoelectric artificial neural networks. 展开更多
关键词 synaptic plasticity all optical optical computation optical neural network
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具有光电信号双输出的发光电化学人工突触
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作者 曾华安 陈奇珍 +5 位作者 单柳婷 严育杰 高昌松 卢文杰 陈惠鹏 郭太良 《Science China Materials》 SCIE EI CAS CSCD 2022年第9期2511-2520,共10页
尽管近年来多种突触器件的研究已取得了显著进展,但寻找具有新功能的人工突触器件仍是构建人工神经网络的重要任务.片上光电互连技术的成熟使得人工神经网络中的权重更新能以光和电的形式进行,作为权重控制端的人工突触器件中光电信号... 尽管近年来多种突触器件的研究已取得了显著进展,但寻找具有新功能的人工突触器件仍是构建人工神经网络的重要任务.片上光电互连技术的成熟使得人工神经网络中的权重更新能以光和电的形式进行,作为权重控制端的人工突触器件中光电信号的并行输出便成为一个有趣和值得拥有的功能.在大规模神经网络的设计中,光电信号双输出能够提供额外的输出自由度并降低电子引线密度.因此,本研究首次开发了基于聚[2-甲氧基-5-(2-乙基己氧基)-1,4-苯乙炔]/聚(环氧乙烷)/锂盐共混的具有光电信号双输出的发光电化学人工突触(LEEAS).LEEAS中的电化学氧化还原反应使该器件能够实现生物学中的突触可塑性,并模拟了记忆增强过程、高通滤波特性和经典的巴甫洛夫条件反射实验.此外,在连续相同的电脉冲刺激下,LEEAS的瞬态发光强度表现出类似突触可塑性的增强行为.由于结合了电致发光和突触记忆行为,LEEAS阵列展现了独特的图像显示和存储功能,可以记忆显示过的图像.本研究提出的LEEAS丰富了人工突触器件的种类,促进了下一代光电混合人工神经网络的多样化设计与发展. 展开更多
关键词 synaptic plasticity photoelectric signals parallel output light-emitting electrochemical artificial synapse artificial neural network
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