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Systematic Modeling of Electrostatics, Transport, and Statistical Variability Effects of Interface Traps in End-of-the-Roadmap III–V MOSFETs

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Thanks to their superior transport properties, indium gallium arsenide (InGaAs) metal–oxide–semiconductor field-effect transistors (MOSFETs) constitute an alternative to conventional silicon MOSFETs for digital applications at ultrascaled nodes. The successful integration… Click to show full abstract

Thanks to their superior transport properties, indium gallium arsenide (InGaAs) metal–oxide–semiconductor field-effect transistors (MOSFETs) constitute an alternative to conventional silicon MOSFETs for digital applications at ultrascaled nodes. The successful integration of this technology is challenged mainly by the high defect density in the gate oxide and at the interface with the semiconductor channel, which degrades the electrostatics and could limit the potential benefits over Si. In this work, we: 1) establish a systematic modeling approach to evaluate the performance degradation due to interface traps in terms of electrostatics and transport of InGaAs dual-gate ultrathin body (DG-UTB) FETs and 2) investigate the effects of random interface-trap concentration as another roadblock to the scaling of the technology, due to statistical variability of the threshold voltage. Variability is assessed with a Technology CAD (TCAD) simulator calibrated against multi-subband Monte Carlo (MSMC) simulations. The modeling approach overcomes the TCAD limitations when dealing with ultrathin channels (i.e., below 5 nm) without altering crucial geometrical parameters that would compromise the dependability of the variability analysis. Our results indicate that interface-trap fluctuation becomes comparable with the other variability sources dominating the total variability when shrinking the device dimensions, thus contrasting the trend of reduced variability with scaling. This, in turn, implies that interface and border traps may strongly limit the benefits of InGaAs over Silicon if not effectively reduced by gate process optimization.

Keywords: electrostatics transport; systematic modeling; variability; electrostatics; statistical variability; interface traps

Journal Title: IEEE Transactions on Electron Devices
Year Published: 2020

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