Nanoparticles-array-air spacer passivated memristor with high on/off ratio and low reset current density
Non-volatile resistive random-access memory (ReRAM) is a promising candidate for next-generation information storage, such as radiation-resistant memory modules and multifunctional memristor for sensing, data storage, and computing. However, ReRAM faces critical challenges in simultaneously achieving high on/off ratios and low reset current density due to conflicting material requirements that demand both high electrical conductivity and low thermal conductivity. Herein, we propose a novel nanoparticles (NPs)-array-air spacer (NAAS) passivated strategy to resolve the inherent electrical-thermal conductivity trade-off in ReRAM design. Specifically, we demonstrated an Al/PMMA/NAAS/ITO memristor featuring the highest on/off ratio (10<sup>7</sup>) and the lowest reset current density (10<sup>−9</sup> A/cm<sup>2 </sup>at 0.02 V read) reported to date. The Au NAAS, formed by monodisperse Au NPs self-assembled on ITO and interstitial air gaps, served as a passivated layer between ITO and suspended PMMA film. Both experimental characterization and electrical/thermal simulations confirm that such unique architecture strategically decouples the conflicting requirements by reducing overall thermal conductivity while enhancing local electrical conductivity, yielding simultaneously a record-high on/off ratio and ultralow reset current density. This spatial passivation strategy transcends conventional single-material approaches, providing a universal design paradigm for reconciling conflicting material requirements in nanoscale resistive switching devices.
Authors
- Bo Zhao (ORCID: https://orcid.org/0000-0002-4452-1735)
- Lin Jiang (ORCID: https://orcid.org/0000-0003-1204-1865)
- Xinpeng Wang (ORCID: https://orcid.org/0009-0005-0041-0135)
- Oleksandr Ivasenko (ORCID: https://orcid.org/0000-0001-9182-3974)
- Habibur Rehman (ORCID: https://orcid.org/0000-0002-8251-654X)
- Weijing Shao (ORCID: https://orcid.org/0009-0006-7342-4121)
- Wanyu Lu (ORCID: https://orcid.org/0000-0003-4478-3724)
- Chang Liu (ORCID: https://orcid.org/0000-0001-6008-7513)
- Yawen Wang (ORCID: https://orcid.org/0000-0003-3749-1416)
- Dong Li (ORCID: https://orcid.org/0000-0002-0823-195X)
- Yu Wang (ORCID: https://orcid.org/0000-0003-2992-7670)
- Yinghui Sun (ORCID: https://orcid.org/0009-0009-1014-4028)
- Yandong Wang (ORCID: https://orcid.org/0009-0005-4068-6689)
Publication Details
- Journal
- Nano Research
- Published
- 2025-09-30
- DOI
- https://doi.org/10.26599/nr.2025.94908111
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Ministry of Science and Technology of the People's Republic of China
- China Postdoctoral Science Foundation
- Ministry of Industry and Information Technology of the People's Republic of China
- Soochow University
- Higher Education Discipline Innovation Project