A Ferroelectric Tunnel Junction-based Integrate-and-Fire Neuron

TL;DR

This paper introduces a hybrid ferroelectric tunnel junction and CMOS-based integrate-and-fire neuron, enabling low-power, tunable neural dynamics for neuromorphic systems in edge computing applications.

Contribution

It presents a novel FTJ-CMOS neuron design that integrates ultra low-power ferroelectric tunnel junctions with CMOS technology for neuromorphic computing.

Findings

Demonstrated electrically tunable neural firing dynamics

Achieved low-power operation suitable for edge computing

Validated the integration of FTJs with CMOS neurons

Abstract

Event-based neuromorphic systems provide a low-power solution by using artificial neurons and synapses to process data asynchronously in the form of spikes. Ferroelectric Tunnel Junctions (FTJs) are ultra low-power memory devices and are well-suited to be integrated in these systems. Here, we present a hybrid FTJ-CMOS Integrate-and-Fire neuron which constitutes a fundamental building block for new-generation neuromorphic networks for edge computing. We demonstrate electrically tunable neural dynamics achievable by tuning the switching of the FTJ device.