InGaZnO-based photoelectric synaptic devices for neuromorphic computing

IF 4.8 4区 物理与天体物理 Q2 PHYSICS, CONDENSED MATTER
Jieru Song, Jialin Meng, Tianyu Wang, Changjin Wan, Hao Zhu, Qingqing Sun, David Wei Zhang, Lin Chen
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引用次数: 0

Abstract

Photoelectric synaptic devices could emulate synaptic behaviors utilizing photoelectric effects and offer promising prospects with their high-speed operation and low crosstalk. In this study, we introduced a novel InGaZnO-based photoelectric memristor. Under both electrical and optical stimulation, the device successfully emulated synaptic characteristics including excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), long-term potentiation (LTP), and long-term depression (LTD). Furthermore, we demonstrated the practical application of our synaptic devices through the recognition of handwritten digits. The devices have successfully shown their ability to modulate synaptic weights effectively through light pulse stimulation, resulting in a recognition accuracy of up to 93.4%. The results illustrated the potential of IGZO-based memristors in neuromorphic computing, particularly their ability to simulate synaptic functionalities and contribute to image recognition tasks.
基于 InGaZnO 的神经形态计算光电突触器件
光电突触器件可以利用光电效应模拟突触行为,并以其高速运行和低串扰的特点提供了广阔的前景。在这项研究中,我们引入了一种新型 InGaZnO 基光电忆阻器。在电刺激和光刺激下,该器件成功模拟了突触特性,包括兴奋性突触后电流(EPSC)、成对脉冲促进(PPF)、长期电位(LTP)和长期抑制(LTD)。此外,我们还通过识别手写数字展示了突触设备的实际应用。这些装置成功地展示了它们通过光脉冲刺激有效调节突触权重的能力,使识别准确率高达 93.4%。这些结果表明了基于IGZO的忆阻器在神经形态计算中的潜力,特别是其模拟突触功能和促进图像识别任务的能力。
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来源期刊
Journal of Semiconductors
Journal of Semiconductors PHYSICS, CONDENSED MATTER-
CiteScore
6.70
自引率
9.80%
发文量
119
期刊介绍: Journal of Semiconductors publishes articles that emphasize semiconductor physics, materials, devices, circuits, and related technology.
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