Wide-bandgap semiconductor SiC-based memristors fabricated entirely by electron beam evaporation for artificial synapses
The combination of high-performance materials and simplified multilayer fabrication processes can promote the rapid and high-quality development of memristors. In this work, we proposed wide-bandgap semiconductor silicon carbide (SiC)-based memristors fabricated entirely by electron beam evaporation technology. The Cu/SiC/Pt structure was fabricated on a 2-inch intrinsic silicon substrate, which can achieve a transition from volatility to non-volatility. Devices had a low and symmetric switching voltage of ±0.5 V, an endurance of >200 cycles, a retention of >103 s, an ON/OFF ratio of ∼103, and can achieve at least 6 different stable resistance states. The combined effects of traps and Cu conductive filaments caused the current to change abruptly during switching, while also possessing excellent synaptic plasticity and pulse programming ability. Our work demonstrated that wide-bandgap semiconductor SiC is a promising candidate for advanced memristors.
Authors
- Haiming Qin (ORCID: https://orcid.org/0009-0003-2140-1620)
- Nan He (ORCID: https://orcid.org/0000-0002-8885-2907)
- Xinpeng Wang (ORCID: https://orcid.org/0009-0005-0041-0135)
- Youde Hu (ORCID: https://orcid.org/0009-0003-1213-7522)
- Yi Tong (ORCID: https://orcid.org/0000-0001-8146-3549)
- Rui Hu (ORCID: https://orcid.org/0000-0001-7412-8451)
- Pengchao Zhang
- Weijing Shao (ORCID: https://orcid.org/0009-0006-7342-4121)
- Yi Liu (ORCID: https://orcid.org/0000-0002-5333-7163)
- Shuai Chen (ORCID: https://orcid.org/0000-0002-8562-5784)
- Liang Zeng
- Sun Shilei
- Mohamed Saadi (ORCID: https://orcid.org/0000-0001-6818-1678)
- Cong Han
- Hao Zhang (ORCID: https://orcid.org/0009-0001-9987-5186)
- Jiawen Wu (ORCID: https://orcid.org/0000-0002-9160-7304)
Institutions
- Beijing Institute of Technology (CN)
- Soochow University (CN)
- Nanjing University of Posts and Telecommunications (CN)
- Suzhou Research Institute (CN)
Publication Details
- Journal
- Applied Physics Letters
- Published
- 2024-09-30
- DOI
- https://doi.org/10.1063/5.0230471
- Citations
- 7
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 1.46