journal article·2026-04Open access

Study of Resistive Switching Dynamics and Memory States Equilibria in Analog Filamentary Conductive‐Metal‐Oxide/HfO x ReRAM via Compact Modeling

Matteo Galetta, Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Stephan Menzel, Antonio La Porta, Tommaso Stecconi, Folkert Horst, Bert Jan Offrein, Valeria Bragaglia

Advanced Electronic Materials· Volume 12· Issue 7

Abstract

Abstract Resistive Random Access Memory (ReRAM) devices offer a promising solution for next‐generation non‐volatile memory and neuromorphic computing systems. Yet, existing compact models fail to capture analog resistive switching behavior of ReRAM devices. This work presents an advanced physics‐based compact model for analog filamentary Conductive‐Metal‐Oxide (CMO)/HfO x ReRAM, capable of reproducing switching characteristics over a broad range of operating conditions. Compared to the state‐of‐the‐art, the model extends the dynamic interplay between ion migration and electron hopping, while also accounting for parasitic resistive elements. Simulations of various voltage inputs are tested to reproduce quasi‐static I–V curves, SET switching kinetics under single‐pulse programming conditions, and analog accumulative conductance modulation upon bipolar identical pulse streams. Additional simulations reveal the physical criterion underlying the stabilization of the CMO/HfO x ‐based ReRAM memory state around the equilibrium point, namely symmetry point, under pulsing conditions when a fading memory mechanism emerges. Building upon the evidence of such equilibrium stabilization under pulsing and quasi‐static conditions, a procedure is established to visualize and map equilibrium memory states across different input domains. The physical model supports design optimization of switching behavior for analog neuromorphic systems and non‐volatile memory architectures. It also enables accurate integrated circuit simulations with CMO/HfO x ‐based ReRAM technology.
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Research context

OpenAlex topics: Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices · Neuroscience and Neural Engineering

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Science of Quantum and Information Technology IBM Research Europe‐Zürich Rüschlikon CH‐8803 Switzerland

Peter Grünberg Institute‐7, Forschungszentrum Jülich DE‐52425 Jülich Germany

Funding

Horizon 2020 Framework Programme · Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung · Bundesministerium für Bildung und Forschung

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