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Ferroelectric field-effect transistors and their applications in spiking neuron circuits

Keil, Haddou
(2022)

Files

Keil_77941400_2022.pdf
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  • 7.34 MB
Keil_77941400_2022_APPENDIX1.zip
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Keil_77941400_2022_APPENDIX2.zip
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Details

Supervisors
Flandre, Denis ; Raskin, Jean-Pierre
Faculty
Ecole polytechnique de Louvain
Degree label
Master [120] : ingénieur civil électricien, à finalité spécialisée
Abstract
The emergence of ferroelectric gate stack Field-Effect Transistors (FETs) provides new compact building blocks for circuits. The ability of these devices to retain programmable conductance states opens up many versatile applications. Among these applications that would benefit from the novelty are Spiking Neural Networks (SNNs) which are the future for machine learning Application Specific Integrated Circuits (ASICs). In this work, the Ferroelectric Field-Effect Transistor (FeFET) will be described and its properties analysed in the aim of creating a compact model. Meanwhile two contenders for spiking neuron circuits will be analysed for their Figures of Merit (FOM) and their ability to integrate the FeFET technology as well as the subsequent benefits of the integration.