Optimization for Device Figure of Merit of Ferroelectric Tunnel FET using Genetic Algorithm

Abstract

A tunnel field effect transistor (TFET) is a gate-controlled, band to band tunneling (BTBT) transport of charge carriers having low subthreshold swing(SS < 60 mV/decade|T = 300K). With TFETs, low-ION is a built-in problem which limits its adaptability to high-speed, low-power uses. To overcome this limitation, a conventional double-gate TFET was constructed having ferroelectric (BaTiO3)/HfO2 gate materials and a source/channel region with Si1-xGex/Si semiconductor channel composition. This design enhances the ION and lowers the subthreshold swing (SS). Analysis using the Silvaco simulator shows improvement in ION current approximately 103 times better than that of conventional DGTFET, without affecting IOFF. Ultimately, a change in ION from 10-8 A/µm to 10-5 A/µ was measured for VDS~0.5 V at room temperature. IOFF of ~10-20 A/µm was measured. In addition to this, a first time genetic algorithm has been used for the optimization of ferroelectric TFET (Fe-TFET) device design parameters like a subthreshold swing (SS), ambipolar current (Iamb), and ION by using device design parameters, doping (NS, ND), dielectric (εOX), and work function (WF). This research shows that Fe-Tunnel can play a leading role for super-low-power applications in advanced VLSI circuits and systems.