Ferroelectric devices for artificial intelligence chips

Abstract

The identification of ferroelectricity in oxides such as hafnium oxide, which are compatible with the contemporary semiconductor fabrication techniques, has contributed to a resurgence of ferroelectric devices in cutting-edge microelectronics. In a transistor structure, ferroelectric devices play the role of connecting a ferroelectric material to a semiconductor, which combines memory and logic operations at the level of a single device, thus meeting some of the most essential hardware requirements for new paradigms for artificial intelligence (A.I) chips. In this review, we addressed the issues associated with high-volume fabrication at advanced technology nodes ($\le 10\mathrm{nm})$ at the material and device level. Moreover, we also reviewed the advancement of A.I chips such as neuro-inspired computer chips. For neuro-inspired A.I chips based on nonvolatile memory, four important metrics are suggested for benchmarking: computing density, energy efficiency, learning capability, and computing accuracy. It is inferred that ferroelectric devices can be a major hardware element in the design of future A.I chips, which will leads to an innovative approach to electronics that is termed ferroelectronics.