神经形态工程学
记忆电阻器
突触
材料科学
人工智能
计算机科学
人工神经网络
纳米技术
工程类
电气工程
神经科学
心理学
作者
Yumo Li,Hao Sun,Langchun Yue,Fengxia Yang,Xiaofei Dong,Jianbiao Chen,Jiangtao Chen,Xuqiang Zhang,Yun Zhao,Kai Chen,Yan Li
标识
DOI:10.1021/acs.jpclett.4c03353
摘要
Research on memristive devices to seamlessly integrate and replicate the dynamic behaviors of biological synapses will illuminate the mechanisms underlying parallel processing and information storage in the human brain, thereby affording novel insights for the advancement of artificial intelligence. Here, an artificial electric synapse is demonstrated on a one-step Mo-selenized MoSe2 memristor, having not only long-term stable resistive switching characteristics (reset 0.51 ± 0.01 V, on/off ratio > 30, retention > 103 s) but also diverse electrically adjustable synaptic behaviors, including multilevel conductance (synaptic weight), excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), long-term potentiation/depression (LTP/D), spike-timing-dependent plasticity (STDP), and especially activity-dependent synaptic plasticity (ADSP). More significantly, neuromorphic functions of both image edge extraction and biological perception imitation have been successfully achieved. These results present a promising design toward synaptic devices for advancing neuromorphic systems with integrated brain-like neural sensing, memory, and recognition.
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