Influence of microstructure on the variability and current percolation paths in ferroelectric hafnium oxide based neuromorphic FeFET synapses

Research output: Contribution to journalConference articleContributedpeer-review

Contributors

  • Maximilian Lederer - , Chair of Experimental Physics / Photophysics, Fraunhofer Institute for Electronic Nano Systems (Author)
  • Franz Müller - , Fraunhofer Institute for Electronic Nano Systems (Author)
  • Anirudh Varanasi - , Fraunhofer Institute for Electronic Nano Systems (Author)
  • Ricardo Olivo - , Fraunhofer Institute for Electronic Nano Systems (Author)
  • Konstantin Mertens - , Fraunhofer Institute for Electronic Nano Systems (Author)
  • David Lehninger - , Fraunhofer Institute for Electronic Nano Systems (Author)
  • Yannick Raffel - , Fraunhofer Institute for Electronic Nano Systems (Author)
  • Raik Hoffmann - , Fraunhofer Institute for Electronic Nano Systems (Author)
  • Tarek Ali - , Fraunhofer Institute for Electronic Nano Systems (Author)
  • Konrad Seidel - , Fraunhofer Institute for Electronic Nano Systems (Author)
  • Thomas Kämpfe - , Fraunhofer Institute for Electronic Nano Systems (Author)
  • Lukas M. Eng - , Chair of Experimental Physics / Photophysics, TUD Dresden University of Technology (Author)

Abstract

Hafnium oxide based ferroelectric FETs (FeFETs) are highly suitable for in-memory computing applications like neuromorphic hardware due to their CMOS compatibility, high dynamic range, low power consumption and good linearity. Device-to-device and die-to-die variability play an important role, especially due to the polycrystalline nature of ferroelectric hafnium oxide. Here, the variability of FeFET based synapses integrated in 300 mm wafers is investigated, showing low drain current variability for up to 32 states per cell. Furthermore, Si doping of HfO2 enables lower voltage amplitudes for learning compared to Zr. Finally, simulation of current percolation paths in these devices reveals more insight in the parameters affecting variability.

Details

Original languageEnglish
Article number63
Journal2021 Silicon Nanoelectronics Workshop, SNW 2021
Publication statusPublished - 2021
Peer-reviewedYes

Conference

Title26th Silicon Nanoelectronics Workshop, SNW 2021
Duration13 June 2021
CityVirtual, Online
CountryJapan

External IDs

ORCID /0000-0002-2484-4158/work/142257577