High-performance organic synaptic transistors for multi-wavelength perception simulation and neuromorphic computing

被引:0
作者
Li, Yujiao [1 ]
Jiang, Shanshan [2 ]
He, Bo [1 ]
Wang, Bingyan [1 ]
Yang, Jiawei [1 ]
Wei, Huanhuan [1 ]
Fu, Can [2 ]
He, Gang [1 ]
机构
[1] Anhui Univ, Sch Mat Sci & Engn, Hefei 230601, Peoples R China
[2] Anhui Univ, Sch Integrated Circuits, Hefei 230601, Peoples R China
来源
MATERIALS TODAY ELECTRONICS | 2025年 / 13卷
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 semiconductors; Artificial synaptic devices; Synaptic plasticity; Neuromorphic applications;
D O I
10.1016/j.mtelec.2025.100164
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
Inspired by biological neuromorphic systems, biomimetic artificial synaptic devices based on organic transistors have become a prominent research direction. The polymer PDVT-10, which is commonly used as channel layer in devices, has excellent stability and high mobility. However, previous research in simulating photonic synapses has focused on doping and hybrid structures, which is limited by the choice of materials and complex fabrication processes in exploring the multifunctional applications of photonic synaptic devices in the future. Here, we successfully constructed individual PDVT-10 photoelectric synaptic devices to simulate biological synaptic plasticity under different wavelengths of light pulse stimulation for the first time. Furthermore, the application of light-induced high-pass filtering characteristics, pain sensing, sensitization, as well as memory functions were realized. In addition, the application of logic circuits was realized based on the photoelectric synergistic effect. Moreover, the introduction of a polyvinyl alcohol light-absorbing layer endowed the device with light potentiation and electrical depression function. Subsequently, a simple convolutional neural network was successfully constructed and implemented for the MNIST number recognition task. This work not only contributes to an indepth understanding of the response mechanism of the device to different wavelengths of light, but also enriches the application areas of the device and provides important support for the practical applications of neuromorphic computing in the future.
引用
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页数:11
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