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Energy-efficient Artificial Synapses based on Innovative Ferroelectric Transisto...

Energy-efficient Artificial Synapses based on Innovative Ferroelectric Transistors The exponential growth of demand for data processing requires increasingly large computational resources and, consequently, prohibitively high energy consumption. To sustain this evolution, a paradigm switch from conventional comp... ver más

31/10/2025

UNIUD

173K€

Presupuesto del proyecto: 173K€

Líder del proyecto

UNIVERSITA DEGLI STUDI DI UDINE No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2023-05-03

HORIZON-MSCA-2022-PF-01-01: MSCA Postdoctoral Fellowships 2022 ExpectedOutcome:

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1 Participantes

UNIUD

172.75K€ | Lider

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Duración del proyecto: 29 meses Fecha Inicio: 2023-05-03
Fecha Fin: 2025-10-31

Líder del proyecto

UNIVERSITA DEGLI STUDI DI UDINE No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 173K€

Descripción del proyecto The exponential growth of demand for data processing requires increasingly large computational resources and, consequently, prohibitively high energy consumption. To sustain this evolution, a paradigm switch from conventional computing architectures to data-centric platforms is needed. Neuromorphic computing aims at reaching this goal by realizing brain-inspired circuits based on artificial neurons and synapses, which are extremely energy efficient. The objective of this project is to explore a novel type of artificial synapse to be employed in neuromorphic chips. Among the technological options for solid state synapses, memories based on ferroelectric field-effect transistors (FeFET) are considered very promising due to their energy efficiency and to their compatibility with a Back-End-Of-Line implementation and thus a 3D integration. A FeFET is a field-effect transistors that employs a ferroelectric (FE) material as gate oxide. FE materials have a spontaneous electric polarization that can be reversed by the application of an electric field, and in conventional FeFETs this is used to modulate the threshold voltage and thus resistance in the channel region. This project will address an alternative physical mechanism to obtain a synaptic behavior in FeFET, namely a polarization-induced tuning of the resistance at source/drain Schottky contacts. In the Ferroelectric Schottky barrier FETs (Fe-SBFETs), the FE material overlaps the Schottky contact region, hence in this region the FE material is placed between two metals resulting in an effective and low voltage ferroelectric switching. For this reason, Fe-SBFETs are expected to operate as low energy synaptic devices. In this project, Fe-SBFETs will be extensively studied and modeled, by means of TCAD simulations. A design-space for optimal synaptic operation will be derived. Finally, a compact model for SPICE simulations of neuromorphic circuits based on Fe-SBFETs will be developed.

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