Please use this identifier to cite or link to this item: https://doi.org/10.1109/TED.2019.2931069
DC FieldValue
dc.titleA Compact Model for 2-D Poly-MoS2 FETs With Resistive Switching in Postsynaptic Simulation
dc.contributor.authorWang, L.
dc.contributor.authorWang, L.
dc.contributor.authorAng, K.-W.
dc.contributor.authorThean, A.V.-Y.
dc.contributor.authorLiang, G.
dc.date.accessioned2020-12-02T01:57:40Z
dc.date.available2020-12-02T01:57:40Z
dc.date.issued2019/08/08
dc.identifier.citationWang, L., Wang, L., Ang, K.-W., Thean, A.V.-Y., Liang, G. (2019/08/08). A Compact Model for 2-D Poly-MoS2 FETs With Resistive Switching in Postsynaptic Simulation. IEEE Transactions on Electron Devices 66 (9) : 4092. ScholarBank@NUS Repository. https://doi.org/10.1109/TED.2019.2931069
dc.identifier.issn15579646
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/184400
dc.description.abstractThe analog resistive switching (RS) characteristics in 2-D polycrystalline (poly-) molybdenum disulfide (MoS 2 ) field-effect transistors (FETs) enable new electronic devices capable of emulating biological synaptic behaviors. In 2-D poly-materials, grain boundary (GB)-induced trap states are of major significance to RS behaviors. However, there is still a lack of appropriate compact models that capture accurate physical mechanisms. Therefore, we developed a surface potential-based compact model, based on the theories of the GB energy barrier and space charge limited current (SCLC). By calibrating to experimental data of MoS 2 , the physical parameters are extracted, and the model explains the scaling behaviors of channel lengths and grain sizes. Due to the electric-field-induced defect redistribution, the energy barrier modulation at a single-GB (e.g., intersecting GB) quantitatively matches the reported experiments. Moreover, the possible SCLC-based RS behavior is also investigated. Furthermore, we have optimized the set/reset process and simulated the postsynaptic current (PSC) with a tunable potentiation (or depression) process, and then the gate voltage dependence and statistical effects on RS and PSC have been investigated. Thus, this model provides important devices physics insights of 2-D poly-materials and it guides device design, fabrication, and material engineering, to meet the requirements of the future neuromorphic computing application.
dc.publisherIEEE
dc.typeArticle
dc.contributor.departmentELECTRICAL AND COMPUTER ENGINEERING
dc.description.doi10.1109/TED.2019.2931069
dc.description.sourcetitleIEEE Transactions on Electron Devices
dc.description.volume66
dc.description.issue9
dc.description.page4092
dc.published.statePublished
dc.grant.idNRF-RSS2015-003
dc.grant.fundingagencyNRF
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