Hafnia-based neuromorphic devices

The excellent complementary metal-oxide-semiconductor compatibility and rich physicochemical properties of hafnia-based materials, in particular the unique ferroelectricity that surpasses of conventional ferroelectrics, make hafnia-based devices promising candidates for industrial applications. This Perspective examines the fundamental properties of hafnia-based materials relevant to neuromorphic devices, including their dielectric, ferroelectric, antiferroelectric properties, and the associated ultra-high oxygen-ion conductivity. It also reviews neuromorphic devices developed leveraging these properties, such as resistive random-access memories, ferroelectric random-access memories, ferroelectric tunnel junctions, and (anti)ferroelectric field-effect transistors. We also discuss the potential of these devices for mimicking synaptic and neuronal functions and address the challenges and future research directions. Hafnia-based neuromorphic devices promise breakthrough performance improvements through material optimization, such as crystallization engineering and innovative device configuration designs, paving the way for advanced artificial intelligence systems.

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Publication Details

Journal
Applied Physics Letters
Published
2024-10-07
DOI
https://doi.org/10.1063/5.0226206
Citations
5
Primary Topic
Ferroelectric and Negative Capacitance Devices
Type
article
Field-Weighted Citation Impact
1.04

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article

Hafnia-based neuromorphic devices

Kuijuan Jin, Hai Zhong, Chen Ge
5 citations
Applied Physics Letters
Ferroelectric and Negative Capacitance Devices
1.04
article

Hafnia-based neuromorphic devices

Kuijuan Jin, Hai Zhong, Chen Ge
article en
5 citations

Abstract

The excellent complementary metal-oxide-semiconductor compatibility and rich physicochemical properties of hafnia-based materials, in particular the unique ferroelectricity that surpasses of conventional ferroelectrics, make hafnia-based devices promising candidates for industrial applications. This Perspective examines the fundamental properties of hafnia-based materials relevant to neuromorphic devices, including their dielectric, ferroelectric, antiferroelectric properties, and the associated ultra-high oxygen-ion conductivity. It also reviews neuromorphic devices developed leveraging these properties, such as resistive random-access memories, ferroelectric random-access memories, ferroelectric tunnel junctions, and (anti)ferroelectric field-effect transistors. We also discuss the potential of these devices for mimicking synaptic and neuronal functions and address the challenges and future research directions. Hafnia-based neuromorphic devices promise breakthrough performance improvements through material optimization, such as crystallization engineering and innovative device configuration designs, paving the way for advanced artificial intelligence systems.

Applied Physics LettersVol. 125(15)
Ludong University (CN), Chinese Academy of Sciences (CN), FZU ‒ Institute of Physics of the Academy of Sciences of the Czech Republic (CZ), Institute of Physics (CN), University of Chinese Academy of Sciences (CN)
National Natural Science Foundation of China, Youth Innovation Promotion Association of the Chinese Academy of Sciences, Natural Science Foundation of Shandong Province, Youth Innovation Technology Project of Higher School in Shandong Province
Industry, innovation and infrastructure
Openalex Percentile: Top 23%
Ferroelectric and Negative Capacitance Devices
1.04
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