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作 者:Can Fu Zhi-Yuan Li Yu-Jiao Li Min-Min Zhu Lin-Bao Luo Shan-Shan Jiang Yan Wang Wen-Hao Wang Gang He
机构地区:[1]School of Materials Science and Engineering,Anhui University,Hefei 230601,China [2]School of Microelectronics,Hefei University of Technology,Hefei 230009,China [3]School of Integration Circuits,Anhui University,Hefei 230601,China
出 处:《Journal of Materials Science & Technology》2024年第29期190-199,共10页材料科学技术(英文版)
基 金:supported by the National Natural Science Foun-dation of China(Nos.11774001,52202156,52103297);the Anhui Project(No.Z010118169);the Scientific research project of colleges and universities in Anhui Province(No.2022AH050113);the Uni-versity Synergy Innovation Program of Anhui Province(No.GXXT-2022-012);the Postdoctoral daily public start-up funds of An-hui University(No.S202418001/069).
摘 要:The development of high-performance neuromorphic phototransistors is of paramount importance for image perception and depth memory learning.Here,based on metal-oxide heterojunction architecture,artificial synaptic phototransistors with synaptic plasticity have been achieved,demonstrating an artificial synapse that integrates central and optic nerve functions.Thanks to the sensitive light-detection properties,the optical power consumption of such photonic artificial synapses can be as low as 22 picojoules,which is extremely competitive compared with other pure metal oxide photoelectric synapses ever reported.What is more,owing to its good short-term(STP)and tunable amplitude-frequency characteristics,the as-constructed device can function as a biomimetic high-pass filter for picture edge detection.Dual-mode synaptic modulation has been performed,combining photonic pulse with gate voltage stimulus.After photoelectric-synergistic modulation,the high synaptic weights enable the device to simulate complex neural learning rules for neuromorphic applications,including gesture recognition,image perception in the visual system,and classically conditioned reflexes.These results suggest that the current oxide-based heterojunction architecture displays potential application in future multifunction neuromorphic devices and systems.
关 键 词:Metal oxide Artificial synaptic devices PHOTOTRANSISTOR Associative-memory-learning Neuromorphic applications
分 类 号:TN3[电子电信—物理电子学]
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