Recent Research for HZO-Based Ferroelectric Memory towards In-Memory Computing Applications

  • Jaewook Yoo
  • , Hyeonjun Song
  • , Hongseung Lee
  • , Seongbin Lim
  • , Soyeon Kim
  • , Keun Heo*
  • , Hagyoul Bae*
  • *Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

Abstract

The AI and IoT era requires software and hardware capable of efficiently processing massive amounts data quickly and at a low cost. However, there are bottlenecks in existing Von Neumann structures, including the difference in the operating speed of current-generation DRAM and Flash memory systems, the large voltage required to erase the charge of nonvolatile memory cells, and the limitations of scaled-down systems. Ferroelectric materials are one exciting means of breaking away from this structure, as Hf-based ferroelectric materials have a low operating voltage, excellent data retention qualities, and show fast switching speed, and can be used as non-volatile memory (NVM) if polarization characteristics are utilized. Moreover, adjusting their conductance enables diverse computing architectures, such as neuromorphic computing with analog characteristics or ‘logic-in-memory’ computing with digital characteristics, through high integration. Several types of ferroelectric memories, including two-terminal-based FTJs, three-terminal-based FeFETs using electric field effect, and FeRAMs using ferroelectric materials as capacitors, are currently being studied. In this review paper, we include these devices, as well as a Fe-diode with high on/off ratio properties, which has a similar structure to the FTJs but operate with the Schottky barrier modulation. After reviewing the operating principles and features of each structure, we conclude with a summary of recent applications that have incorporated them.

Original languageEnglish
Article number2297
JournalElectronics (Switzerland)
Volume12
Issue number10
DOIs
StatePublished - 2023.05

Keywords

  • Fe-diode
  • FeFET
  • FeRAM
  • ferroelectric memory device
  • FTJ
  • HZO
  • in-memory computing
  • neuromorphic
  • NVM

Quacquarelli Symonds(QS) Subject Topics

  • Computer Science & Information Systems
  • Engineering - Electrical & Electronic
  • Engineering - Petroleum
  • Data Science

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