CNEG’s research is focused on the theoretical and computational investigation of device science and engineering based on nanoelectronics, spintronics, and advanced materials, with an emphasis on low-power consumption applications and nonvolatile electronic system. The research topics are engaged in a dynamic and multidisciplinary research program requiring (1) fundamental understanding of materials to discover original and unique properties and their affects on carrier, spin and heat transport, and (2) a creative engineering approach to innovate and realize novel devices. The studied devices widely include the electronic, thermoelectric, optoelectronic, electron-optics, magnetic, and spintronic devices. Many of our theoretical predictions have been confirmed by experimental measurements.
The paper "A Surface Potential- and Physics- Based Compact Model for 2D Polycrystalline-MoS2 FET with Resistive Switching Behavior in Neuromorphic Computing" by Lingfei Wang, Lin Wang, Kah-Wee Ang, Aaron Voon-Yew Thean and Gengchiau Liang will be presented in the 2018 IEEE International Electron Devices Meeting in San Francisco.
For the first time, a surface potential- and physics- based compact model for two dimensional (2D) polycrystalline- molybdenum disulfide (MoS2) field effect transistors (FETs) with resistive switching (RS) behavior is developed and verified by experimental data. This model is incorporated with the theories of thermal activation transport, grain boundary (GB) barrier and space charge limited current (SCLC). Based on the GB induced disorders, the grain size, low temperature and high electrical field dependent characteristics are studied. The predicted transfer and output characteristics have excellent quantitative agreement with experimental results. Furthermore, considering the hopping process induced defect- (i.e., sulfur vacancy) redistribution, the GB (e.g., intersecting or bisecting GB) dependent resistive switching behavior is physically investigated. Finally, this model is implemented to simulate the synaptic activity such as short-term/long-term plasticity, which indicates the possibility of using 2D-FETs for neuromorphic computing applications.