铁电性
电容器
极化(电化学)
材料科学
凝聚态物理
矿物学
光电子学
电介质
物理
化学
物理化学
电压
量子力学
作者
Minjong Lee,Peng Zhou,Heber Hernández-Arriaga,Yong Chan Jung,Jin-Hyun Kim,Naimul Hassan,Wesley H. Brigner,Laura Deremo,Joseph S. Friedman,Jiyoung Kim
出处
期刊:Nano Letters
[American Chemical Society]
日期:2025-01-23
标识
DOI:10.1021/acs.nanolett.4c04771
摘要
Ferroelectric Hf0.5Zr0.5O2 (HZO) capacitors have been extensively explored for in-memory computing (IMC) applications due to their nonvolatility and back-end-of-line (BEOL) compatible process. Several IMC approaches using resistance and capacitance states in ferroelectric HZO have been proposed for vector-matrix multiplication (VMM), but previous approaches suffer from limited accuracy and reliability. In this work, we propose a promising approach centered on the remanent polarization (Pr) switching of binary ferroelectric HZO capacitor synapses. We experimentally demonstrate a simple pattern recognition task showing that the voltage readout of Pr switching provides excellent accuracy due to its high on/off ratio and consequent reliability. We also performed large-scale simulations on a complex inference task, achieving high accuracy and immunity to device variations. We therefore believe that our proposed paradigm is promising for near-term neuromorphic IMC.
科研通智能强力驱动
Strongly Powered by AbleSci AI