Ferroelectric FET Threshold Voltage Optimization for Reliable In-Memory Computing

Om Prakash, Kai Ni, Hussam Amrouch

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Ferroelectric FET (FeFET) emerges as a highly promising candidate for in-memory computing due to its outstanding performance, superior energy efficiency and great scalability. For FeFET, generally the memory window, i.e., the separation between the two threshold voltage (VTH) states, is of interest. The absolute value of the low-VTH and high-VTH states are generally not scrutinized. However, in this work, we demonstrate that a proper engineering of VTH is necessary to ensure correct array operation for in-memory computing applications. We highlight that for all the current-based operations, it is necessary to keep both the VTH states positive to cut off the leakage for grounded unselected cells. To reach that design target, we systematically evaluate various design options for VTH engineering, including the gate metal work function, the body bias, and the buried oxide thickness, in a fully-depleted silicon-on-insulator (FDSOI) FeFET using calibrated TCAD simulations. We establish the design guidelines for VTH engineering to ensure successful operation of in-memory computing applications.

Original languageEnglish
Title of host publication2022 IEEE International Reliability Physics Symposium, IRPS 2022 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages9C31-9C310
ISBN (Electronic)9781665479509
DOIs
StatePublished - 2022
Externally publishedYes
Event2022 IEEE International Reliability Physics Symposium, IRPS 2022 - Dallas, United States
Duration: 27 Mar 202231 Mar 2022

Publication series

NameIEEE International Reliability Physics Symposium Proceedings
Volume2022-March
ISSN (Print)1541-7026

Conference

Conference2022 IEEE International Reliability Physics Symposium, IRPS 2022
Country/TerritoryUnited States
CityDallas
Period27/03/2231/03/22

Keywords

  • FDSOI
  • FeFET
  • In-Memory Computing
  • TCAM

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