Tailoring the resistive switching performance of niobium oxide memristors for neuromorphic computing through nitrogen doping
Memristors, which integrate storage and computing in a single device, are promising for neuromorphic computing. In this study, NbOx and nitrogen doped NbOxNy films were prepared by pulsed laser deposition in mixed oxygen nitrogen atmospheres. XPS and EDS confirmd successful and uniform nitrogen incorporation. Pt/NbOxNy/Cu devices exhibited a switching ratio of 3 × 105, which is two orders of magnitude higher than Pt/NbOx/Cu, and stable resistance states exceeding 30,000s in both HRS and LRS. The NbOxNy devices showed only minor performance degradation, with the switching ratio decreasing from 105 to 104 between 20 and 70 °C and the SET voltage rising from 0.5 to 1 V under 35–90 % RH. Atomic-scale force-field simulations revealed a strong interaction (−1.238 eV) between oxygen vacancies and nitrogen dopants, favoring Vo–N complex formation. These complexes repel adjacent Nb5+ ions, generating relaxed Nb–Nb regions that facilitate Cu2+migration and confine conductive filament growth. As a result, nitrogen doping improves stability and shifts the HRS conduction mechanism from space-charge-limited current to hopping transport, while preserving Ohmic conduction in the LRS. These enhancements expand the dynamic range of synaptic weights, supporting high-precision weight mapping and reliable long-term learning, making NbOxNy memristors strong candidates for energy-efficient neuromorphic computing.
Authors
- Rui Xiong (ORCID: https://orcid.org/0000-0003-0468-6014)
- Xu Jing (ORCID: https://orcid.org/0000-0001-8692-6581)
- Hongjun Wang
- Meng Chen (ORCID: https://orcid.org/0000-0002-0279-8381)
- Yadong Yang (ORCID: https://orcid.org/0000-0002-2403-8244)
- Yuanyuan Zhu (ORCID: https://orcid.org/0000-0002-2795-3333)
- Xiumei Xu
- Yong Liu (ORCID: https://orcid.org/0000-0001-6095-6926)
Publication Details
- Journal
- Journal of Materials Research and Technology
- Published
- 2025-11-01
- DOI
- https://doi.org/10.1016/j.jmrt.2025.11.130
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00