Ex Situ Doping of Oxygen Vacancies for Improved ZnO Resistance Switching Devices

Oxygen vacancies (V<sub>O</sub>s) are fundamental for oxide resistance switching (RS) devices, while the introduction of V<sub>O</sub>s in oxides during the fabrication processes has generally generated unfavorable defects which have limited the improvements in RS performance. Herein, a novel strategy, called ex situ V<sub>O</sub>s doping, has been proposed to increase the concentration of V<sub>O</sub>s to fabricate improved ZnO RS devices. The ex situ V<sub>O</sub>s doping process is similar to modulation doping of heterojunctions, where V<sub>O</sub>s are intentionally incorporated in a separate oxide material and then migrated toward the target materials. Specifically, HfO<sub>2</sub>/ZnO architecture with a thin oxygen-deficient HfO<sub>2</sub> capping layer is prepared, where V<sub>O</sub>s in the HfO<sub>2</sub> layer facilely migrated toward the underlying ZnO under applying bias. Theoretical calculations and atomic binding energy analysis have verified the effective ex situ V<sub>O</sub>s doping of ZnO in the HfO<sub>2</sub>/ZnO architecture. Benefiting from the dominant migration of V<sub>O</sub>s along grain boundaries, the accumulated V<sub>O</sub>s around grain boundaries at HfO<sub>2</sub>/ZnO interface provided preferential nucleation sites for deterministic formation of conductive filaments. Accordingly, improved ZnO RS devices have been demonstrated in terms of increased RS window and enhanced uniformity, stability, and endurance. The ex situ doping of V<sub>O</sub>s using a heterojunction architecture enables multi-dimensional regulation of the formation of conductive filaments, which will find potential applications in achieving improved oxide RS devices in the future.

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Publication Details

Journal
Small Methods
Published
2025-12-26
DOI
https://doi.org/10.1002/smtd.202501295
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00

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article

Ex Situ Doping of Oxygen Vacancies for Improved ZnO Resistance Switching Devices

Dawei Cao, Mingming Chen, youchao Kong, Xinyu Ni et al.
Small Methods
Advanced Memory and Neural Computing
article

Ex Situ Doping of Oxygen Vacancies for Improved ZnO Resistance Switching Devices

Dawei Cao, Mingming Chen, youchao Kong, Xinyu Ni, Zhicheng Lv
article en

Abstract

Oxygen vacancies (V<sub>O</sub>s) are fundamental for oxide resistance switching (RS) devices, while the introduction of V<sub>O</sub>s in oxides during the fabrication processes has generally generated unfavorable defects which have limited the improvements in RS performance. Herein, a novel strategy, called ex situ V<sub>O</sub>s doping, has been proposed to increase the concentration of V<sub>O</sub>s to fabricate improved ZnO RS devices. The ex situ V<sub>O</sub>s doping process is similar to modulation doping of heterojunctions, where V<sub>O</sub>s are intentionally incorporated in a separate oxide material and then migrated toward the target materials. Specifically, HfO<sub>2</sub>/ZnO architecture with a thin oxygen-deficient HfO<sub>2</sub> capping layer is prepared, where V<sub>O</sub>s in the HfO<sub>2</sub> layer facilely migrated toward the underlying ZnO under applying bias. Theoretical calculations and atomic binding energy analysis have verified the effective ex situ V<sub>O</sub>s doping of ZnO in the HfO<sub>2</sub>/ZnO architecture. Benefiting from the dominant migration of V<sub>O</sub>s along grain boundaries, the accumulated V<sub>O</sub>s around grain boundaries at HfO<sub>2</sub>/ZnO interface provided preferential nucleation sites for deterministic formation of conductive filaments. Accordingly, improved ZnO RS devices have been demonstrated in terms of increased RS window and enhanced uniformity, stability, and endurance. The ex situ doping of V<sub>O</sub>s using a heterojunction architecture enables multi-dimensional regulation of the formation of conductive filaments, which will find potential applications in achieving improved oxide RS devices in the future.

Small MethodsVol. 10(3)
Jiangsu University (CN), Yancheng Teachers University (CN)
Jiangsu University, Government of Jiangsu Province, Natural Science Foundation of Jiangsu Province
Affordable and clean energy
Openalex Percentile: Top 42%
Advanced Memory and Neural Computing
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