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  4. Spike-Time Dependent Plasticity in HfO-Based Ferroelectric FET Synapses
 
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2024
Conference Paper
Title

Spike-Time Dependent Plasticity in HfO-Based Ferroelectric FET Synapses

Abstract
This paper reports a study on spike-timing-dependent plasticity (STDP) in high-k metal gate (HKMG) based ferroelectric Field effect transistors (FeFET). FeFET devices have been fairly well exploited in the context of in-memory computing due to their excellent non-volatile storage characteristics and analog conductance tunability. However, applications of FeFET devices in Spiking Neural Networks (SNN) are yet to be explored properly. This work reports the potential of HfO<inf>2</inf> based HKMG-FeFET synapses for SNN hardware by demonstrating energy-efficient STDP learning.
Author(s)
Masud Rana, Sk
Indian Institute of Technology Madras
Roy, Sourodeep
Indian Institute of Technology Madras
Lederer, Maximilian
Fraunhofer-Institut für Photonische Mikrosysteme IPMS  
Raffel, Yannick
Fraunhofer-Institut für Photonische Mikrosysteme IPMS  
Pirro, Luca
Global Foundries, Germany
Chohan, Talha
Global Foundries, Germany
Seidel, Konrad  
Fraunhofer-Institut für Photonische Mikrosysteme IPMS  
De, Sourav
Fraunhofer-Institut für Photonische Mikrosysteme IPMS  
Chakrabarti, Bhaswar
Indian Institute of Technology Madras
Mainwork
IEEE Electron Devices Technology and Manufacturing Conference Strengthening the Globalization in Semiconductors Edtm 2024
Funder
Freistaat Sachsen  
Conference
8th IEEE Electron Devices Technology and Manufacturing Conference, EDTM 2024
DOI
10.1109/EDTM58488.2024.10512154
Language
English
Fraunhofer-Institut für Photonische Mikrosysteme IPMS  
Keyword(s)
  • and SNNs

  • FeFET

  • HfO

  • STDP

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