Research & Development World

  • Home Page
  • Topics
    • Aerospace
    • Archeology
    • Automotive
    • Biotech
    • Chemistry
    • COVID-19
    • Environment
    • Energy
    • Life Science
    • Material Science
    • R&D Market Pulse
    • R&D Management
    • Physics
  • Technology
    • 3D Printing
    • A.I./Robotics
    • Battery Technology
    • Controlled Environments
      • Cleanrooms
      • Graphene
      • Lasers
      • Regulations/Standards
      • Sensors
    • Imaging
    • Nanotechnology
    • Scientific Computing
      • Big Data
      • HPC/Supercomputing
      • Informatics
      • Security
      • Software
    • Semiconductors
  • 2021 R&D 100 Award Winners
    • R&D 100 Awards
    • 2020 Winners
    • Winner Archive
  • Resources
    • Digital Issues
    • Podcasts
    • Subscribe
  • Global Funding Forecast
  • Webinars

New Memristor Boosts Accuracy and Efficiency for Neural Networks on an Atomic Scale

By American Institute of Physics | October 17, 2018

Hardware that mimics the neural circuitry of the brain requires building blocks that can adjust how they synapse. One such approach, called memristors, uses current resistance to store this information. New work looks to overcome reliability issues in these devices by scaling memristors to the atomic level. Researchers demonstrated a new type of compound synapse that can achieve synaptic weight programming and conduct vector-matrix multiplication with significant advances over the current state of the art. They discuss their work in this week’s Journal of Applied Physics. This image shows a conceptual schematic of the 3D implementation of compound synapses constructed with boron nitride oxide (BNOx) binary memristors, and the crossbar array with compound BNOx synapses for neuromorphic computing applications. Credit: Ivan Sanchez Esqueda

Related Articles Read More >

COMSOL announces event series introducing Multiphysics Version 6.0
Look who’s turning 25: Z machine celebrates its colorful history at Sandia
Scientists create world’s thinnest magnet
LaserNetUS High-Power Laser Consortium, including Berkeley Lab, receives $18M from the U.S. DOE
2021 R&D Global Funding Forecast

Need R&D World news in a minute?

We Deliver!
R&D World Enewsletters get you caught up on all the mission critical news you need in research and development. Sign up today.
Enews Signup

R&D World Digital Issues

February 2020 issue

Browse the most current issue of R&D World and back issues in an easy to use high quality format. Clip, share and download with the leading R& magazine today.

Research & Development World
  • Subscribe to R&D World Magazine
  • Enews Sign Up
  • Contact Us
  • About Us
  • Drug Discovery & Development
  • Pharmaceutical Processing
  • 2021 Global Funding Forecast

Copyright © 2022 WTWH Media LLC. All Rights Reserved. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of WTWH Media
Privacy Policy | Advertising | About Us

Search R&D World

  • Home Page
  • Topics
    • Aerospace
    • Archeology
    • Automotive
    • Biotech
    • Chemistry
    • COVID-19
    • Environment
    • Energy
    • Life Science
    • Material Science
    • R&D Market Pulse
    • R&D Management
    • Physics
  • Technology
    • 3D Printing
    • A.I./Robotics
    • Battery Technology
    • Controlled Environments
      • Cleanrooms
      • Graphene
      • Lasers
      • Regulations/Standards
      • Sensors
    • Imaging
    • Nanotechnology
    • Scientific Computing
      • Big Data
      • HPC/Supercomputing
      • Informatics
      • Security
      • Software
    • Semiconductors
  • 2021 R&D 100 Award Winners
    • R&D 100 Awards
    • 2020 Winners
    • Winner Archive
  • Resources
    • Digital Issues
    • Podcasts
    • Subscribe
  • Global Funding Forecast
  • Webinars