Optimization of Chirality Variation in Carbon Nanotube Field Effect Transistor Spiking Neurons

Abstract

For over half a century, silicon-based Complementary Metal Oxide Semiconductors (CMOS) have been the dominant technology used in the manufacture of nearly all integrated circuits. To fulfill Moore’s Law prediction, CMOS device dimensions were meticulously and carefully reduced to the single-digit nanometer regime. This gradual reduction has led to remarkable exponential performance increases over several decades, ushering in an unparalleled era of computation in human history. However, Short-Channel Effects (SCEs) present many impediments to further improvements in CMOS devices. SCEs occur when the channel length has been scaled down to the same order of magnitude as the depletion-layer widths of the source and drain junctions. To overcome the numerous SCEs caused by the miniaturization of CMOS devices, Carbon Nanotube Field Effect Transistors (CNFETs) aim to serve as their superior successors. CNFETs exhibit exceptional electrical properties, far surpassing those of CMOS, primarily due to their ballistic transport properties and excellent electrostatic scaling. To the best of our knowledge, this paper is the first to investigate chirality variation in CNFETs for spiking neurons. More specifically, chirality variation in CNFETs is used to determine two optimizations: (1) highest-frequency and (2) lowest-energy spiking neurons, using the Penta-Transistor Integrate & Fire (PTIF) architecture to demonstrate these dual mandates. These optimizations separately provide a 6.89x increase in spiking frequency or an 87.43% energy saving.