材料科学
记忆电阻器
仿真
神经形态工程学
异质结
突触
人工神经网络
光电子学
人工智能
神经科学
电子工程
计算机科学
生物
工程类
经济
经济增长
作者
Rongliang Li,Wenxiao Wang,Yang Li,Song Gao,Wenjing Yue,Guozhen Shen
出处
期刊:Nano Energy
[Elsevier]
日期:2023-03-30
卷期号:111: 108398-108398
被引量:52
标识
DOI:10.1016/j.nanoen.2023.108398
摘要
With the development of artificial intelligence, the demand for brain-like intelligent devices capable of breaking the von Neumann bottleneck is growing. In light of the advantages of high speed, low power consumption, and high integration resulting from the combination of memory and underlying perception, the memristor has great potential for implementing bionic synapses and constructing artificial visual system. Herein, a Ga2O3/MoS2 heterojunction-based multi-modulated optoelectronic memristor (MMOM) is proposed and demonstrated. In response to specific electrical signals, the device empowers the emulation of synaptic functions including short/long-term plasticity and shows an adjustable modulation range through changing pulse parameters. Meanwhile, versatile optical signals are also able to evoke synaptic behaviors, for instance, the transition from short-term to long-term memory and the "learning-forgetting-relearning" function. Utilizing the excellent optical response, a 16 × 16 MMOM array is assembled to simulate the perception-memory integrated human visual system. Further, to optimize the static means of modulating bi-terminal visual synapses, a modulatory synapse exploiting varying positive and negative electrical signals is presented and validated. Predictably, a multi-signal engaged heterologous synapse can be constructed for the complex visual system, which greatly enriches the functionality of bionic synapses and offers the possibility to realize a dynamically tunable artificial visual system.
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