光学突触记忆晶体管和神经形态计算中的单极和双极电阻开关共存

Chip Pub Date : 2024-12-27 DOI:10.1016/j.chip.2024.100122
Dongsheng Cui , Mengjiao Pei , Zhenhua Lin , Yifei Wang , Hong Zhang , Xiangxiang Gao , Haidong Yuan , Yun Li , Jincheng Zhang , Yue Hao , Jingjing Chang
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Coexistence of unipolar and bipolar resistive switching in optical synaptic memristors and neuromorphic computing
The human brain possesses a highly developed capability for sensing-memory-computing, and the integration of hardware with brain-like functions represents a novel approach to overcoming the von Neumann bottleneck. In this study, Ga2O3 photoelectric memristors were successfully fabricated, enabling efficient visual information processing and complex recognition through the integration of optoelectronic synapses with digital storage. The memristors with a Pt/Ga2O3/Pt sandwich structure exhibit the coexistence of unipolar resistive switching (URS) and bipolar resistive switching (BRS), coupled with an impressive switching ratio and stable retention characteristics. The device demonstrates robust photo-responsive properties to ultraviolet (UV) light, which enables the realization of an array of 16 photoconductor types through the manipulation of four-timeframe pulse sequences. Exposure of the device to UV light elicits stable synaptic behaviors, including paired-pulse facilitation (PPF), short-term memory (STM), long-term memory (LTM), as well as learning-forgetting-relearning behavior. Moreover, the device exhibits outstanding image sensing, image memory, and neuromorphic visual pre-processing capabilities as a neuromorphic vision sensor (NVS). The integration of light pulse potentiation with electrical pulse depression yields a remarkable 100 conductances with superior linearity. This advanced functionality is further validated by the ability of the device to facilitate the recognition of 85.3% of handwritten digits by artificial neural networks (ANNs), which underscores the significant potential of artificial synapses in mimicking biological neural.
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