High-Performance Ferroelectric Field-Effect Transistors Based on Ultrathin Indium Oxide for Neuromorphic Computing.

Journal: ACS nano
Published Date: May 21, 2025

Abstract

The emergence of artificial intelligence has revealed the limitations of traditional von Neumann computing systems in fulfilling the current computational requirements. In-memory computing (IMC) has been generally considered as a promising architecture to break the von Neumann bottleneck, where the FeFET is a strong candidate for developing IMC hardware, but remains challenging. In this work, we demonstrate a complementary metal oxide semiconductor-compatible InO FeFET array for neuromorphic computing. The FeFETs exhibit excellent performance, including an ultrahigh on-off ratio (10), large memory window (>6 V), high endurance (10 cycles), long retention time (>10 years), low cycle-to-cycle variation (1.1%), high uniformity, and highly linear and symmetrical long-term potentiation (LTP)/long-term depression (LTD). Finally, we evaluate the performance of fabricated InO FeFETs for image classification, and a high overall accuracy of 92.5% is achieved. These results suggest the great potential of InO FeFET for constructing IMC hardware for neuromorphic computing.

Authors

  • Jiawen Chen
    Department of Systems and Computational Biology, Albert Einstein College of Medicine, Yeshiva University, 1300 Morris Park Avenue, Bronx, NY, 10461, USA.
  • Jinyu Li
    State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, 100071, China.
  • Qimeng Zhang
    School of Information Science and Technology, Fudan University, Shanghai 200433, People's Republic of China.
  • Shisheng Xiong
    School of Information Science and Technology Micro Nano System Center, Fudan University, Shanghai 200433, China. E-mail: sxiong@fudan.edu.cn.

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