Work

Energy-Efficient VLSI Ferroelectric Elements for Neuromorphic Artificial Intelligence Systems

Year: 2025

Type: conference-paper

Source: IEEE International Conference of Young Professionals in Electron Devices and Materials (EDM)

Authors: Vladimir Popov, Mikhail Tarkov, Valentin Antonov, Fedor Tikhonenko, Andrey Miakonkikh, Konstantin Rudenko

Institutions: Institute of Semiconductor Physics, Kurchatov Institute

Language: English

Topic: Ferroelectric and Negative Capacitance Devices

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: closed

OpenAlex ID: W7084050954

FWCI: 2.32

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Cited by: 1

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