Synthesis of hexagonal boron arsenide nanosheets for low-power consumption flexible memristors
Boron arsenide has recently attracted significant attention for its thermal and electronic properties. However, its lengthy growth process and bulk structure limit its application in advanced semiconductor systems. In this study, we introduce a method for synthesizing ultrathin crystalline hexagonal boron arsenide (h-BAs) nanosheets in large quantities via an in-situ chemical reaction of sodium borohydride with elemental arsenic in a low-pressure hydrogen atmosphere. We successfully fabricated h-BAs-based memory devices with ON/OFF current ratios up to 10<sup>9</sup>, low energy consumption of less than 4.65 pJ, and commendable stability. Furthermore, we have developed flexible h-BAs-based memristors with good stability and robustness. This research not only provides a promising avenue for synthesizing h-BAs nanosheets, but also underscores their potential in the development of next-generation electronic devices.
Authors
- You Meng (ORCID: https://orcid.org/0000-0002-5385-4080)
- Johnny Chung Yin Ho (ORCID: https://orcid.org/0000-0003-3000-8794)
- Yi Shen (ORCID: https://orcid.org/0000-0002-0941-8644)
- Dengji Li (ORCID: https://orcid.org/0000-0002-4406-0246)
- Pengshan Xie (ORCID: https://orcid.org/0000-0002-5949-3458)
- Quan Quan (ORCID: https://orcid.org/0000-0001-8216-8998)
- Chenxu Zhang
- Boxiang Gao (ORCID: https://orcid.org/0000-0001-8422-5941)
- Zenghui Wu (ORCID: https://orcid.org/0000-0002-7725-7301)
- Dong Chen (ORCID: https://orcid.org/0000-0002-2133-4697)
- Yuxuan Zhang (ORCID: https://orcid.org/0000-0002-5240-6606)
- Bowen Li (ORCID: https://orcid.org/0000-0001-5133-931X)
- Weijun Wang (ORCID: https://orcid.org/0000-0002-2796-5844)
- Di Yin (ORCID: https://orcid.org/0000-0003-4456-9867)
- SenPo Yip (ORCID: https://orcid.org/0000-0002-6622-3982)
- He Shao
Institutions
- Kyushu University (JP)
- City University of Hong Kong (HK)
- Shenzhen University (CN)
- Kyushu University Hospital (JP)
- City University of Hong Kong, Shenzhen Research Institute (CN)
Publication Details
- Journal
- Nature Communications
- Published
- 2025-05-22
- DOI
- https://doi.org/10.1038/s41467-025-60038-3
- Citations
- 7
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 5.11
Funders
- University Grants Committee