Please use this identifier to cite or link to this item: https://doi.org/10.1002/inf2.12230
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dc.titleBand-tailored van der Waals heterostructure for multilevel memory and artificial synapse
dc.contributor.authorWang, Yanan
dc.contributor.authorZheng, Yue
dc.contributor.authorGao, Jing
dc.contributor.authorJin, Tengyu
dc.contributor.authorLi, Enlong
dc.contributor.authorLian, Xu
dc.contributor.authorPan, Xuan
dc.contributor.authorHan, Cheng
dc.contributor.authorChen, Huipeng
dc.contributor.authorChen, Wei
dc.date.accessioned2022-10-13T07:35:15Z
dc.date.available2022-10-13T07:35:15Z
dc.date.issued2021-07-13
dc.identifier.citationWang, Yanan, Zheng, Yue, Gao, Jing, Jin, Tengyu, Li, Enlong, Lian, Xu, Pan, Xuan, Han, Cheng, Chen, Huipeng, Chen, Wei (2021-07-13). Band-tailored van der Waals heterostructure for multilevel memory and artificial synapse. InfoMat 3 (8) : 917-928. ScholarBank@NUS Repository. https://doi.org/10.1002/inf2.12230
dc.identifier.issn2567-3165
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/233153
dc.description.abstractTwo-dimensional (2D) van der Waals heterostructure (vdWH)-based floating gate devices show great potential for next-generation nonvolatile and multilevel data storage memory. However, high program voltage induced substantial energy consumption, which is one of the primary concerns, hinders their applications in low-energy-consumption artificial synapses for neuromorphic computing. In this study, we demonstrate a three-terminal floating gate device based on the vdWH of tin disulfide (SnS2), hexagonal boron nitride (h-BN), and few-layer graphene. The large electron affinity of SnS2 facilitates a significant reduction in the program voltage of the device by lowering the hole-injection barrier across h-BN. Our floating gate device, as a nonvolatile multilevel electronic memory, exhibits large on/off current ratio (~105), good retention (over 104 s), and robust endurance (over 1000 cycles). Moreover, it can function as an artificial synapse to emulate basic synaptic functions. Further, low energy consumption down to ~7 picojoule (pJ) can be achieved owing to the small program voltage. High linearity (<1) and conductance ratio (~80) in long-term potentiation and depression (LTP/LTD) further contribute to the high pattern recognition accuracy (~90%) in artificial neural network simulation. The proposed device with attentive band engineering can promote the future development of energy-efficient memory and neuromorphic devices. (Figure presented.). © 2021 The Authors. InfoMat published by UESTC and John Wiley & Sons Australia, Ltd.
dc.publisherBlackwell Publishing Ltd
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceScopus OA2021
dc.typeArticle
dc.contributor.departmentPHYSICS
dc.contributor.departmentFOOD SCIENCE & TECHNOLOGY
dc.contributor.departmentCHEMISTRY
dc.contributor.departmentOFFICE OF THE SR DY PRESIDENT & PROVOST
dc.description.doi10.1002/inf2.12230
dc.description.sourcetitleInfoMat
dc.description.volume3
dc.description.issue8
dc.description.page917-928
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