📝 SummarXiv

Abstract

Neuromorphic computing, inspired by biological intelligence, offers a pathway to revolutionize artificial intelligence (AI) by unifying memory and processing in an energy-efficient, sustainable framework for data-intensive tasks. Ferroelectric (FE) materials have emerged as promising candidates for implementing artificial synapses, yet achieving low-voltage operation in CMOS back-end compatible devices remains a major challenge. In this work, we demonstrate that proper tuning of ferro and antiferroelectric phases in HfO2-ZrO2(HZO) superlattice based capacitors can lead to imprint-free switching with record switchable polarization (2Pr) of 76 micro Coulomb cm-2 under an external field of only 2 MV cm-1. The sizable remanent polarization of the superlattice HZO further enables linear potentiation and depression with an on to off ratio of 20 within a 3 MV cm-1 bias window. Under pulsed operation, the devices show robust endurance, either maintaining polarization with less than 10 per cent degradation up to 10^8 cycles or surviving beyond 10^9 cycles with recoverable fatigue. By elucidating two distinct fatigue mechanisms, this work highlights strategies for optimizing FE devices to meet the stringent demands of neuromorphic training applications.