Programmable ferroelectric rectifier for reliable and efficient neuromorphic crossbar array

The advancement of neuromorphic computing hardware requires energy-efficient operation, scalable device integration, and reliable conduction. These challenges can be effectively addressed by employing functional ferroelectric material as an active layer in memristors, leveraging their electrostatically modulated conduction for reliable switching. In this study, we present memristor devices that achieve a rectifying ratio exceeding 10⁶ and an off-state current below 10⁻¹² A based on epitaxial heterostructures consisting of Pt/Ba<sub>0.2</sub>Bi<sub>0.8</sub>FeO<sub>3</sub> (BBFO)/SrRuO<sub>3</sub>/SrTiO<sub>3</sub> stacks. Substitution of 20% Ba in BiFeO₃ induces a coupled interaction between ferroelectric polarization and oxygen vacancy migration, which under pulsed bias governs vacancy transport and ensures reliable memristive synaptic behavior with near-zero nonlinearity and endurance beyond 10⁷ cycles. Owing to the demonstrated linear synaptic performance and strong memristive rectification, a selector-free crossbar array (CBA) was implemented. By mitigating key CBA challenges such as sneak currents and cell-to-cell variability while maintaining high synaptic performance, BBFO provides a robust material platform for CBA-based neuromorphic systems.

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Publication Details

Journal
Nature Communications
Published
2026-03-17
DOI
https://doi.org/10.1038/s41467-026-70727-2
Primary Topic
Ferroelectric and Negative Capacitance Devices
Type
article
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article

Programmable ferroelectric rectifier for reliable and efficient neuromorphic crossbar array

Jiwoong Yang, Chung Wung Bark, SungJin Choi, Sanghan Lee et al.
Nature Communications
Ferroelectric and Negative Capacitance Devices
article

Programmable ferroelectric rectifier for reliable and efficient neuromorphic crossbar array

Jiwoong Yang, Chung Wung Bark, SungJin Choi, Sanghan Lee, Byungsoo Kim, Youngmin Kim, Min Hyuk Park, Yoon Jung Lee, Dae Hwan Kim, Seung Ju Kim, Jae Young Kim, Haesung Kim, Inhyuk Im, J. Joshua Yang, He Rui, Ho Won Jang, Jaehyun Kim
article en

Abstract

The advancement of neuromorphic computing hardware requires energy-efficient operation, scalable device integration, and reliable conduction. These challenges can be effectively addressed by employing functional ferroelectric material as an active layer in memristors, leveraging their electrostatically modulated conduction for reliable switching. In this study, we present memristor devices that achieve a rectifying ratio exceeding 10⁶ and an off-state current below 10⁻¹² A based on epitaxial heterostructures consisting of Pt/Ba<sub>0.2</sub>Bi<sub>0.8</sub>FeO<sub>3</sub> (BBFO)/SrRuO<sub>3</sub>/SrTiO<sub>3</sub> stacks. Substitution of 20% Ba in BiFeO₃ induces a coupled interaction between ferroelectric polarization and oxygen vacancy migration, which under pulsed bias governs vacancy transport and ensures reliable memristive synaptic behavior with near-zero nonlinearity and endurance beyond 10⁷ cycles. Owing to the demonstrated linear synaptic performance and strong memristive rectification, a selector-free crossbar array (CBA) was implemented. By mitigating key CBA challenges such as sneak currents and cell-to-cell variability while maintaining high synaptic performance, BBFO provides a robust material platform for CBA-based neuromorphic systems.

Nature Communications
Kookmin University (KR), Northwestern University (US), University of Southern California (US), Gachon University (KR), Seoul National University (KR), Gwangju Institute of Science and Technology (KR), National University (SD), Advanced Institute of Convergence Technology (KR), National University College (PR)
Affordable and clean energy
Openalex Percentile: Top 19%
Ferroelectric and Negative Capacitance Devices
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