A Novel Split-Gate Ferroelectric FET for a Compact and Energy Efficient Neuron

Abstract

Neuromorphic computing—brain-inspired computing—is considered a next-generation computing architecture that can overcome problems caused by the high computing cost of modern data science. Ferroelectric FETs (FeFETs) are one of the promising candidates for hardware implementation of bio-inspired neurons. However, the conventional FeFET-based neurons require a considerable number of device components for the realization of inhibitory operation, or they need negative supply voltage, leading to high routing costs. In this letter, a novel device, named a Split-Gate (SG) FeFET, is proposed for a bio-inspired neuron. Harnessing the capacitance difference between two gates, both excitatory and inhibitory operations can be simply implemented on a single device. Furthermore, adding a “current stopper” to the SG FeFET enables energy-efficient operation of the neuron by eliminating the remanent current of the FeFET, which has been a significant drawback of conventional FeFET-based leaky integration-and-firing (LIF) emulation.