Reversible and Controllable Transition Between Filamentary and Interfacial Resistive Switching in HfO <sub>2</sub> ‐Based Memristors

ABSTRACT Reversible weight tuning is critical for edge AI chips, enabling online learning and local inference. Conventionally, the transition from analog interfacial switching to abrupt filamentary switching in memristors is commonly considered irreversible, as high electric fields induce conductive filaments, locking devices in the filamentary state. Here, we report that TiN/HfO 2 /Pt memristors exhibit stable interfacial switching and achieve voltage‐driven, repeatable interfacial‐to‐filamentary‐to‐interfacial (I‐F‐I) transitions. Systematic electrical characterization demonstrates more than 10 stable I‐F‐I transition sequences, controllable I‐F‐I transition yield exceeding 40%, a preserved resistance window, and an ON/OFF ratio of about 30. High bias activates a fast digital filamentary mode, while low bias restores a linearly tunable analog interfacial mode. Two defect migration models—soft filament and Schottky emission—elucidate this phenomenon. This analog‐digital switching could in the future, enable single‐chip training and inference and support reconfigurable logic‐in‐memory architectures, advancing low‐power artificial neural networks as well as neuromorphic computing for edge AI applications.

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Publication Details

Journal
Advanced Electronic Materials
Published
2026-01-05
DOI
https://doi.org/10.1002/aelm.202500644
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00

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article

Reversible and Controllable Transition Between Filamentary and Interfacial Resistive Switching in HfO 2 ‐Based Memristors

Ronald Tetzlaff, Chong Peng, Richard Schroedter, Hampus Åkerman Hoffman et al.
Advanced Electronic Materials
Advanced Memory and Neural Computing
article

Reversible and Controllable Transition Between Filamentary and Interfacial Resistive Switching in HfO 2 ‐Based Memristors

Ronald Tetzlaff, Chong Peng, Richard Schroedter, Hampus Åkerman Hoffman, Stefan Slesazeck, T. Mikolajick, Cuo Wu, Hao Shen, Benjamin Max
article en

Abstract

ABSTRACT Reversible weight tuning is critical for edge AI chips, enabling online learning and local inference. Conventionally, the transition from analog interfacial switching to abrupt filamentary switching in memristors is commonly considered irreversible, as high electric fields induce conductive filaments, locking devices in the filamentary state. Here, we report that TiN/HfO 2 /Pt memristors exhibit stable interfacial switching and achieve voltage‐driven, repeatable interfacial‐to‐filamentary‐to‐interfacial (I‐F‐I) transitions. Systematic electrical characterization demonstrates more than 10 stable I‐F‐I transition sequences, controllable I‐F‐I transition yield exceeding 40%, a preserved resistance window, and an ON/OFF ratio of about 30. High bias activates a fast digital filamentary mode, while low bias restores a linearly tunable analog interfacial mode. Two defect migration models—soft filament and Schottky emission—elucidate this phenomenon. This analog‐digital switching could in the future, enable single‐chip training and inference and support reconfigurable logic‐in‐memory architectures, advancing low‐power artificial neural networks as well as neuromorphic computing for edge AI applications.

Advanced Electronic MaterialsVol. 12(4)
NaMLab (Germany) (DE), Technische Universität Dresden (DE)
Deutsche Forschungsgemeinschaft, Technische Universität Dresden
Openalex Percentile: Top 97%
Advanced Memory and Neural Computing
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