Enabling Quantum‐Compatible Nonvolatile Memory: Cryogenic Evaluation of 1T1R HfO <sub>2</sub> ‐Based RRAM From 300 to 1.5 K

ABSTRACT To enable compact quantum computing systems, cryogenically compatible CMOS‐based non‐volatile memories are required. In this work, we investigate 1‐transistor–1‐resistor (1T1R) resistive random‐access memory (RRAM) devices over an extended temperature range, including previously unexplored cryogenic regimes. To enhance storage density, we explore a multilevel‐cell approach via multilevel programming. As temperature decreases, the low‐resistance state (LRS) effective conductance increases, improving state separation but also leading to higher LRS currents and increased reset voltages required for reliable switching to the high‐resistance state (HRS), resulting in incomplete filament rupture and a broader HRS distribution. Through independent characterization of the access nMOS transistor, we identify transistor temperature dependence as the dominant factor governing LRS evolution, while extraction of the intrinsic metal–insulator–metal (MIM) behavior reveals an opposite trend, with decreasing conductivity at lower temperatures. Based on these insights, we implement an optimized programming strategy for cryogenic operation by tuning the nMOS gate bias during set, reducing LRS currents, particularly in intermediate and high conductance states, while preserving state separation, narrowing the HRS distribution, and lowering reset voltages. Overall, this work establishes a robust and scalable approach for reliable 1T1R operation at cryogenic temperatures and provides a key step toward nonvolatile memory integration in quantum computing architectures.

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Publication Details

Journal
Advanced Electronic Materials
Published
2026-08-13
DOI
https://doi.org/10.1002/aelm.202500798
Primary Topic
Advanced Memory and Neural Computing
Type
article
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article

Enabling Quantum‐Compatible Nonvolatile Memory: Cryogenic Evaluation of 1T1R HfO 2 ‐Based RRAM From 300 to 1.5 K

S. Dueñas, Emilio Pérez-Bosch Quesada, Oliver Skibitzki, J.B. Roldán et al.
Advanced Electronic Materials
Advanced Memory and Neural Computing
article

Enabling Quantum‐Compatible Nonvolatile Memory: Cryogenic Evaluation of 1T1R HfO 2 ‐Based RRAM From 300 to 1.5 K

S. Dueñas, Emilio Pérez-Bosch Quesada, Oliver Skibitzki, J.B. Roldán, Eduardo Pérez, Markus Fritscher, Keerthi Dorai Swamy Reddy, Felix Reichmann, Helena Castán, Christian Wenger, Ruolan Jia, Alberto Mistroni
article en

Abstract

ABSTRACT To enable compact quantum computing systems, cryogenically compatible CMOS‐based non‐volatile memories are required. In this work, we investigate 1‐transistor–1‐resistor (1T1R) resistive random‐access memory (RRAM) devices over an extended temperature range, including previously unexplored cryogenic regimes. To enhance storage density, we explore a multilevel‐cell approach via multilevel programming. As temperature decreases, the low‐resistance state (LRS) effective conductance increases, improving state separation but also leading to higher LRS currents and increased reset voltages required for reliable switching to the high‐resistance state (HRS), resulting in incomplete filament rupture and a broader HRS distribution. Through independent characterization of the access nMOS transistor, we identify transistor temperature dependence as the dominant factor governing LRS evolution, while extraction of the intrinsic metal–insulator–metal (MIM) behavior reveals an opposite trend, with decreasing conductivity at lower temperatures. Based on these insights, we implement an optimized programming strategy for cryogenic operation by tuning the nMOS gate bias during set, reducing LRS currents, particularly in intermediate and high conductance states, while preserving state separation, narrowing the HRS distribution, and lowering reset voltages. Overall, this work establishes a robust and scalable approach for reliable 1T1R operation at cryogenic temperatures and provides a key step toward nonvolatile memory integration in quantum computing architectures.

Advanced Electronic Materials
Universidad de Valladolid (ES), Universidad de Granada (ES), Nanosystems Initiative Munich (DE), Brandenburg University of Technology Cottbus-Senftenberg (DE), Leibniz Institute for High Performance Microelectronics (DE)
Affordable and clean energy
Openalex Percentile: Top 17%
Advanced Memory and Neural Computing
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