Ferroelectric devices for artificial intelligence chips

作者：Jinshun Bi, Muhammad Faizan, Xuefei Liu, Yue Ma, Xu An Wang, V. R. Stempitsky · 发表于：Chip · 年份：2025 · DOI：10.1016/j.chip.2025.100129 · 被引用次数：6 · 研究领域：Advanced Memory and Neural Computing、Ferroelectric and Negative Capacitance Devices、Semiconductor materials and devices

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 ( ≤ 10 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.