Please use this identifier to cite or link to this item:
https://doi.org/10.1002/inf2.12230
DC Field | Value | |
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dc.title | Band-tailored van der Waals heterostructure for multilevel memory and artificial synapse | |
dc.contributor.author | Wang, Yanan | |
dc.contributor.author | Zheng, Yue | |
dc.contributor.author | Gao, Jing | |
dc.contributor.author | Jin, Tengyu | |
dc.contributor.author | Li, Enlong | |
dc.contributor.author | Lian, Xu | |
dc.contributor.author | Pan, Xuan | |
dc.contributor.author | Han, Cheng | |
dc.contributor.author | Chen, Huipeng | |
dc.contributor.author | Chen, Wei | |
dc.date.accessioned | 2022-10-13T07:35:15Z | |
dc.date.available | 2022-10-13T07:35:15Z | |
dc.date.issued | 2021-07-13 | |
dc.identifier.citation | Wang, 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.issn | 2567-3165 | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/233153 | |
dc.description.abstract | Two-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.publisher | Blackwell Publishing Ltd | |
dc.rights | Attribution 4.0 International | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.source | Scopus OA2021 | |
dc.type | Article | |
dc.contributor.department | PHYSICS | |
dc.contributor.department | FOOD SCIENCE & TECHNOLOGY | |
dc.contributor.department | CHEMISTRY | |
dc.contributor.department | OFFICE OF THE SR DY PRESIDENT & PROVOST | |
dc.description.doi | 10.1002/inf2.12230 | |
dc.description.sourcetitle | InfoMat | |
dc.description.volume | 3 | |
dc.description.issue | 8 | |
dc.description.page | 917-928 | |
Appears in Collections: | Elements Staff Publications |
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