Gate-Tunable Neuromorphic Devices Enabled by Two-Dimensional Materials

Mark C. Hersam*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Neuromorphic (i.e., brain-like) computing aims to circumvent the limitations of von Neumann architectures by spatially co-locating processor and memory blocks or even combining logic and data storage functions within the same device. Neuromorphic devices also have the potential to provide efficient architectures for image recognition, machine learning, and artificial intelligence. With this motivation in mind, this paper will explore how the unique materials properties of two-dimensional (2D) materials enable opportunities for novel gate-tunable neuromorphic devices.

Original languageEnglish (US)
Title of host publication6th IEEE Electron Devices Technology and Manufacturing Conference, EDTM 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages154-156
Number of pages3
ISBN (Electronic)9781665421775
DOIs
StatePublished - 2022
Event6th IEEE Electron Devices Technology and Manufacturing Conference, EDTM 2022 - Virtual, Online, Japan
Duration: Mar 6 2022Mar 9 2022

Publication series

Name6th IEEE Electron Devices Technology and Manufacturing Conference, EDTM 2022

Conference

Conference6th IEEE Electron Devices Technology and Manufacturing Conference, EDTM 2022
Country/TerritoryJapan
CityVirtual, Online
Period3/6/223/9/22

Funding

This research was primarily supported by the National Science Foundation Materials Research Science and Engineering Center at Northwestern University (Grant NSF DMR-1720139). Device fabrication was partially funded by the Laboratory Directed Research and Development Program at Sandia National Laboratories (SNL). SNL is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc. for the U.S. DOE National Nuclear Security Administration under Contract DE-NA0003525. This work describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. DOE or the United States Government. This work also made use of the Northwestern University NUANCE Center and Micro/Nano Fabrication Facility (NUFAB), which has received support from the Soft and Hybrid Nanotechnology Experimental (SHyNE) Resource (Grant NSF ECCS-1542205), the MRSEC program (Grant NSF DMR-1720139) at the Materials Research Center, the International Institute for Nanotechnology (IIN), the Keck Foundation, and the State of Illinois. This research was also supported in part through the computational resources and staff contributions provided by the Quest high performance computing facility at Northwestern University, which is jointly supported by the Office

Keywords

  • (neuromorphic computing
  • 2D materials
  • continuous learning)
  • Gaussian transistors
  • memtransistors
  • van der Waals heterojunctions

ASJC Scopus subject areas

  • Process Chemistry and Technology
  • Hardware and Architecture
  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering
  • Electronic, Optical and Magnetic Materials

Fingerprint

Dive into the research topics of 'Gate-Tunable Neuromorphic Devices Enabled by Two-Dimensional Materials'. Together they form a unique fingerprint.

Cite this