Journal Article

FZJ-2026-02636

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png The Influence of Residual Ion Drift During Programming of Chip‐Integrated Nanoscale HfO 2 ‐Based Memristive Devices

Artner, O. (Corresponding author) ; Cüppers, F. ; Son, S.FZJ* ; Chen, Y.FZJ* ; Liu, X.FZJ* ; Bengel, C. ; Nielinger, D.FZJ* ; Zambanini, A.FZJ* ; Wiefels, S.FZJ* ; Menzel, S. (Corresponding author)FZJ* ; Dittmann, R.FZJ* ; Hoffmann-Eifert, S. (Corresponding author)FZJ*

2026
Wiley-VCH Verlag GmbH & Co. KG Weinheim

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Please use a persistent id in citations: doi:10.1002/aelm.202500891

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 HfO2-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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Contributing Institute(s):

1. Elektronische Materialien (PGI-7)
2. JARA-FIT (JARA-FIT)
3. Integrated Computing Architectures (PGI-4)

Research Program(s):

1. 5233 - Memristive Materials and Devices (POF4-523) (POF4-523)
2. DFG project G:(GEPRIS)528378584 - TRR 404: Zukunftsweisende Elektronik durch aktive Bauelemente in drei Dimensionen (Active-3D) (528378584) (528378584)
3. BMBF 16ME0398K - Verbundprojekt: Neuro-inspirierte Technologien der künstlichen Intelligenz für die Elektronik der Zukunft - NEUROTEC II - (BMBF-16ME0398K) (BMBF-16ME0398K)
4. BMFTR 03ZU2106AB - NeuroSys: KI-anwendungsspezifische Technologiereifung memristiver Bauteile (Projekt A) - Teilvorhaben B (03ZU2106AB) (03ZU2106AB)

Appears in the scientific report 2026

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