Leaky-integrate-fire neuron based on vertically extended drain Si[formula omitted]Ge[formula omitted] source TFET: Ultra-energy-efficient and high speed design

Abstract

This article investigates the performance of a vertically extended drain double gate Si1−x Gex source tunnel field effect transistor (VD-DG-Si1−x Gex S-TFET) as a leaky integrate-and-fire (LIF) neuron. The proposed VD-DG-Si1−x Gex S-TFET structure has been designed and optimized by deploying the commercially available Silvaco TCAD. The LIF neuron using VD-DG-Si1−x Gex S-TFET requires a low spiking threshold voltage (i.e. 0.20 V) which is 5x, 3x, 5x, 1.3x, 1.55x, 7.5x, and 1.44x times less in comparison to MOSFET, Bulk FinFET, phase change device, SOI MOSFET, DG-JLFET, silicon nanowire, and DL-TFET silicon neuron. The proposed device based neuron demonstrates the least spiking energy (177 ZJ) reported to date which is 18192 times less as compared to BTBT based PDSOI MOSFET neuron. The threshold value of current is achieved at 0.20 V drain voltage which is 15x, 14x, 10x, and 1.5x less as compared to FinFET, PD-SOI MOSFET, LBIMOS, and DL-TFET, respectively. Moreover, the effects of gate metal work function, germanium mole fraction, and temperature on the spike current variations have also been investigated. Here, impact ionization is a key method for generating a neuron spike due to holes accumulated in the potential well of VD-DG-Si1−xGex S-TFET. In addition, a LIF neuron based on VD-DG-Si0.5Ge0.5 S-TFET device exhibits a 9 THz spiking frequency which is approximately 12 times higher than real nerves present in the human body. This work shows a remarkable reduction in the power consumption and the proposed device neuron is a potential start-up solution for a large scale spiking neural networks (SNN) implementation because of its better performance and compact circuitry.