Transconductance analysis of SiGe Nanowire Tunnel FET (NW-TFET) with Artificial Intelligence (AI) for low-power applications

This study employs a 3D Silvaco TCAD tool simulation to develop and enhance a silicon germanium-based transconductance analysis of a SiGe nanowire tunnel field effect transistor. The SiGe Nanowire Tunnel FET has high transconductance, steep subthreshold swing (SS), and ultra-low leakage current because of its superior material features and nanowire structure. Several innovative low-power AI applications are made possible by this device topology when paired with hardware accelerators and artificial intelligence (AI) techniques. The visual specifications for the apparatus performance improvement were channel height, the height of the gate metal, and channel thickness. The gate-metal-NW-TFET that was created has remarkable performance, with 42.8 mV/dec as the subthreshold swing, a threshold voltage of 0.21 V, an Ion of 80.9 A/m, and an Ioff of 1.09 × 10 -12 A/µm. As a result, the proposed logic device has been proven to be an achievable option with AI for low-power applications.