The Influence of Residual Ion Drift During Programming of Chip‐Integrated Nanoscale HfO <sub>2</sub> ‐Based Memristive Devices

ABSTRACT Filamentary valence change mechanism (VCM)‐type memristive devices based on transition metal oxides offer great potential for the realization of energy‐efficient analog hardware accelerators used in machine learning and neuromorphic computing. To fully exploit this potential, integration of nanostructured memristive devices with complementary metal oxide semiconductor (CMOS) circuits and multi‐level programming are essential prerequisites. In crossbar arrays for in‐memory computing, a transistor in series with the VCM device acts as a selector and limits the current in the SET process, which allows programming of different low‐resistance states (LRS). However, a discrepancy between the programmed LRS value and the measured conductivity value, G LRS , is often observed, even for VCM devices with linear current–voltage characteristics. In this study, we analyze the physical origin of this effect. Therefore, 100 nm × 100 nm‐sized HfO 2 ‐based VCM devices were integrated on foundry‐built 180 nm CMOS wafers. Through transient analysis of the device response during the SET, we show that the conductivity of the VCM cell continuously increases for the duration of the SET pulse. This finding could be understood from physical simulation through thermally assisted ion migration in the filament region. This insight can support the development of devices with improved accuracy under multi‐state programming.

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Publication Details

Journal
Advanced Electronic Materials
Published
2026-05-21
DOI
https://doi.org/10.1002/aelm.202500891
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00

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article

The Influence of Residual Ion Drift During Programming of Chip‐Integrated Nanoscale HfO 2 ‐Based Memristive Devices

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Advanced Electronic Materials
Advanced Memory and Neural Computing
article

The Influence of Residual Ion Drift During Programming of Chip‐Integrated Nanoscale HfO 2 ‐Based Memristive Devices

Felix Cüppers, Susanne Hoffmann‐Eifert, Christopher Bengel, Stefan Wiefels, Xiaohua Liu, Dennis Nielinger, Seokki Son, Yang Chen, Oliver Artner, André Zambanini, Regina Dittmann, Stephan Menzel
article en

Abstract

ABSTRACT Filamentary valence change mechanism (VCM)‐type memristive devices based on transition metal oxides offer great potential for the realization of energy‐efficient analog hardware accelerators used in machine learning and neuromorphic computing. To fully exploit this potential, integration of nanostructured memristive devices with complementary metal oxide semiconductor (CMOS) circuits and multi‐level programming are essential prerequisites. In crossbar arrays for in‐memory computing, a transistor in series with the VCM device acts as a selector and limits the current in the SET process, which allows programming of different low‐resistance states (LRS). However, a discrepancy between the programmed LRS value and the measured conductivity value, G LRS , is often observed, even for VCM devices with linear current–voltage characteristics. In this study, we analyze the physical origin of this effect. Therefore, 100 nm × 100 nm‐sized HfO 2 ‐based VCM devices were integrated on foundry‐built 180 nm CMOS wafers. Through transient analysis of the device response during the SET, we show that the conductivity of the VCM cell continuously increases for the duration of the SET pulse. This finding could be understood from physical simulation through thermally assisted ion migration in the filament region. This insight can support the development of devices with improved accuracy under multi‐state programming.

Advanced Electronic Materials
Forschungszentrum Jülich (DE), Ernst Ruska Centre (DE), Jülich Aachen Research Alliance (DE), RWTH Aachen University (DE)
Deutsche Forschungsgemeinschaft
Affordable and clean energy
Openalex Percentile: Top 9%
Advanced Memory and Neural Computing
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