Switching and Charge Trapping in HfO2-based Ferroelectric FETs: An Overview and Potential Applications

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Contributors

  • Halid Mulaosmanovic - , NaMLab - Nanoelectronic materials laboratory gGmbH (Author)
  • Evelyn T. Breyer - , NaMLab - Nanoelectronic materials laboratory gGmbH (Author)
  • Thomas Mikolajick - , Chair of Nanoelectronics, NaMLab - Nanoelectronic materials laboratory gGmbH (Author)
  • Stefan Slesazeck - , NaMLab - Nanoelectronic materials laboratory gGmbH (Author)

Abstract

Ferroelectric field-effect transistor based on ferroelectric hafnium oxide emerges as a promising technology for nonvolatile memory. This work provides an overview on its main switching properties under various pulsing schemes and emphasizes the significant voltage-time trade-off underlying the polarization reversal. A striking difference in switching between the large-and small-area devices is presented. The parasitic charge trapping is pointed out as a severe reliability limitation and a de-trapping method is shown. Finally, possible applications beyond memory are discussed, including neuromorphic, stochastic and logic-in-memory devices.

Details

Original languageEnglish
Title of host publication4th Electron Devices Technology and Manufacturing Conference, EDTM 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISBN (electronic)978-1-7281-2539-8
ISBN (print)978-1-7281-2540-4
Publication statusPublished - Apr 2020
Peer-reviewedYes

Publication series

SeriesIEEE Electron Devices Technology and Manufacturing Conference (EDTM)

Conference

Title4th IEEE Electron Devices Technology and Manufacturing Conference
Abbreviated titleEDTM 2020
Conference number4
Duration6 - 21 April 2020
Website
LocationOnline
CityPenang
CountryMalaysia

External IDs

ORCID /0000-0003-3814-0378/work/142256201

Keywords

Keywords

  • charge trapping, ferroelectric FET, ferroelectric HfO2, neuromorphic computing, nonvolatile memory