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|Title:||A Compact Model for 2-D Poly-MoS2 FETs With Resistive Switching in Postsynaptic Simulation||Authors:||Wang, L.
|Issue Date:||2019||Publisher:||IEEE||Citation:||Wang, 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||Abstract:||The 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.||Source Title:||IEEE Transactions on Electron Devices||URI:||https://scholarbank.nus.edu.sg/handle/10635/184400||ISSN:||15579646||DOI:||10.1109/TED.2019.2931069|
|Appears in Collections:||Staff Publications|
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