Progetto di ricerca

EMPHASIS (DFM.AD001.402)

Area tematica

Scienze fisiche e tecnologie della materia

Area progettuale

Sensori multifunzionali e dispositivi elettronici (DFM.AD001)

Struttura responsabile del progetto di ricerca

Istituto per la microelettronica e microsistemi (IMM)

Responsabile di progetto

RAFFAELLA CALARCO
Telefono: 06 4993 4480
E-mail: raffaella.calarco@cnr.it

Abstract

Present-day computers based on the von Neumann architecture are becoming increasingly inadequate for data-centric applications, such as artificial intelligence and machine learning, due to the physical separation of the processing and storage units. Neuromorphic hardware is a revolutionary approach that takes inspiration from the brain for surmounting this drawback: its basic building blocks are "artificial neurons", which can serve both as computing and storage units.
In this joint computational and experimental project, we aim at creating novel prototypes of neuromorphic devices based on chalcogenide heterostructures. The heterostructures will consist of alternating thin layers of phase-change materials (PCMs) and confinement materials (CMs), such as transition-metal dichalcogenides (TMDs). By application of proper electrical pulses, PCMs undergo fast and reversible transitions between multiple states showing resistivity contrast. However, the variability and the temporal drift in resistance of the PCM cells hinder their use in neuromorphic devices. The presence of thin confinement layers has been shown to strongly reduce both cell variability and drift, making these phase-change

Obiettivi

In this project, we aim at designing PCHs with tailored properties for neuromorphic applications. We will also fabricate and characterize prototypes of neuromorphic devices based on the most promising PCH candidates. The project partnership is composed by four units and covers a wide range of facilities, both experimental and theoretical, and recognized expertise in state-of-the-art techniques: molecular dynamics (MD) simulations based on density-functional theory (DFT) and NN "machine-learning" potentials (UNIMIB, Sapienza); crystal growth, electronic and structural characterization (CNR-IMM Roma, UNITOV); high resolution Transmission Electron Microscopy (TEM) and device realization (CNR-IMM Catania); electrical characterization, neuromorphic devices and simulations (CNR-IMM Roma).

Data inizio attività

23/03/2022

Parole chiave

neuromorfica, calcogenuri

Ultimo aggiornamento: 16/04/2024