A Dual Magnetic Tunnel Junction‐Based Neuromorphic Device

Abstract

With the advent of artificial intelligence (AI) in computational devices technology, various synaptic array architectures are proposed for neuromorphic computing applications. Among them, the non‐volatile memory (NVM) architectures are very promising for their small cell size, ultra‐low energy consumption, and capability for large parallel data processing through 3D configurations capable of multilevel signal processing. Herein, the viability of such magnetic tunnel junction (MTJ)‐based synaptic devices via fabrication and characterization of multi‐junction spintronic devices is demonstrated, with the experimental results supported through micromagnetic simulations.

Document Details

Document Type
Pub Defense Publication
Publication Date
Nov 04, 2020
Source ID
10.1002/aisy.202000143

Entities

People

  • Hong Chen
  • Jeffrey Bokor
  • Jeongmin Hong
  • Long You
  • Nuo Xu
  • Sakhrat Khizroev
  • Stefano Cabrini
  • Xin Li

Organizations

  • Air Force Office of Scientific Research
  • Foshan University
  • Huazhong University of Science and Technology
  • Lawrence Berkeley National Laboratory
  • National Natural Science Foundation of China
  • National Science Foundation
  • University of Miami

Tags

Readers

  • Integrated Circuit Design and Technology.
  • Neural Network Machine Learning.
  • Superconducting Magnet Technology

Technology Areas

  • AI & ML
  • Microelectronics