Zhenyu Feng, Jinran Yu, Yichen Wei, Yifei Wang, Bobo Tian, Yonghai Li, Liuqi Cheng, Zhong Lin Wang, Qijun Sun
{"title":"Tribo-ferro-optoelectronic neuromorphic transistor of α-In2Se3","authors":"Zhenyu Feng, Jinran Yu, Yichen Wei, Yifei Wang, Bobo Tian, Yonghai Li, Liuqi Cheng, Zhong Lin Wang, Qijun Sun","doi":"10.1002/brx2.24","DOIUrl":null,"url":null,"abstract":"<p>Inspired by biological neural networks, the fabrication of artificial neuromorphic systems with multimodal perception capacity shows promises in overcoming the “von Neumann bottleneck” and takes advantage of the efficient perception and computation of diverse types of signals. Here, we combine a triboelectric nanogenerator with an <i>α</i>-phase indium selenide (<i>α</i>-In<sub>2</sub>Se<sub>3</sub>) optoelectronic synaptic transistor to construct a tribo-ferro-optoelectronic artificial neuromorphic device with multimodal plasticity. Based on the excellent ferroelectric and optoelectronic characteristics of the <i>α</i>-In<sub>2</sub>Se<sub>3</sub> channel, typical synaptic behaviors (e.g., pair-pulse facilitation and short-term/long-term plasticity) are successfully simulated in response to the synergistic effect of mechanical and optical stimuli. The interaction of mechanical displacement and light illumination enables heterosynaptic plasticity and spatiotemporal dynamic logic. Furthermore, multiple Boolean logical functions and associative learning behaviors are successfully implemented using the paired stimuli of displacement pulses and light pulses. The proposed tribo-ferro-optoelectronic artificial neuromorphic devices have great potential for application in interactive neural networks and next-generation artificial intelligence.</p>","PeriodicalId":94303,"journal":{"name":"Brain-X","volume":"1 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/brx2.24","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brain-X","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/brx2.24","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Inspired by biological neural networks, the fabrication of artificial neuromorphic systems with multimodal perception capacity shows promises in overcoming the “von Neumann bottleneck” and takes advantage of the efficient perception and computation of diverse types of signals. Here, we combine a triboelectric nanogenerator with an α-phase indium selenide (α-In2Se3) optoelectronic synaptic transistor to construct a tribo-ferro-optoelectronic artificial neuromorphic device with multimodal plasticity. Based on the excellent ferroelectric and optoelectronic characteristics of the α-In2Se3 channel, typical synaptic behaviors (e.g., pair-pulse facilitation and short-term/long-term plasticity) are successfully simulated in response to the synergistic effect of mechanical and optical stimuli. The interaction of mechanical displacement and light illumination enables heterosynaptic plasticity and spatiotemporal dynamic logic. Furthermore, multiple Boolean logical functions and associative learning behaviors are successfully implemented using the paired stimuli of displacement pulses and light pulses. The proposed tribo-ferro-optoelectronic artificial neuromorphic devices have great potential for application in interactive neural networks and next-generation artificial intelligence.