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Neuromorphic Computing with 28nm High-K-Metal Gate Ferroelectric Field Effect Transistors Based Artificial Synapses
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  • Sourav De ,
  • Yannick Raffel ,
  • Sunanda Thunder ,
  • Franz Müller ,
  • Maximilian Lederer ,
  • Thomas Kaempfe ,
  • Masud S K Rana ,
  • Luca Pirro ,
  • Konrad Seidel ,
  • Bhaswar Chakrabarti
Sourav De
CNT, CNT

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Yannick Raffel
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Sunanda Thunder
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Franz Müller
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Maximilian Lederer
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Thomas Kaempfe
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Masud S K Rana
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Luca Pirro
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Konrad Seidel
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Bhaswar Chakrabarti
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Abstract

This paper presents a comprehensive overview of 28 nm high-k-metal gate-based ferroelectric field effect transistor devices for synaptic applications. The device under test was fabricated on 300mm wafers at GlobalFoundries. The fabricated devices demonstrate 103 WRITE-endurance cycles and 104 seconds of data-retention capability at 85°C. We have also assessed the FeFET-based crossbar array’s performance in system-level applications. By simulating the FeFET crossbar array for neuromorphic applications, the system performance was assessed. For datasets from the National Institute of Standards and Technology (MNIST), the crossbar array achieved software-comparable inference accuracy of about 97% using multilayer perceptron (MLP) neural networks.