Ultrafast reconfigurable direct charge trapping devices based on few-layer MoS<sub>2</sub>
Abstract Charge trapping devices incorporating 2D materials and high- κ dielectrics have emerged as promising candidates for compact, multifunctional memory devices compatible with silicon-based manufacturing processes. However, traditional charge trapping devices encounter bottlenecks including complex device structure and low operation speed. Here, we demonstrate an ultrafast reconfigurable direct charge trapping device utilizing only a 30 nm-thick Al 2 O 3 trapping layer with a MoS 2 channel, where charge traps reside within the Al 2 O 3 bulk confirmed by transfer curves with different gate-voltage sweeping rates and photoluminescence (PL) spectra. The direct charging tapping device shows exceptional memory performance in both three-terminal and two-terminal operation modes characterized by ultrafast three-terminal operation speed (∼300 ns), an extremely low OFF current of 10 −14 A, a high ON/OFF current ratio of up to 10 7 , and stable retention and endurance properties. Furthermore, the device with a simple symmetrical structure exhibits V D polarity-dependent reverse rectification behavior in the high resistance state (HRS), with a rectification ratio of 10 5 . Additionally, utilizing the synergistic modulation of the conductance of the MoS 2 channel by V D and V G , it achieves gate-tunable reverse rectifier and ternary logic capabilities.
Authors
- Ching‐Ming Wei (ORCID: https://orcid.org/0000-0003-3984-4422)
- Lihong Bao (ORCID: https://orcid.org/0000-0002-2942-892X)
- Peng Song (ORCID: https://orcid.org/0000-0002-6029-945X)
- Hui Gao (ORCID: https://orcid.org/0000-0002-8736-4485)
- Haitao Yang (ORCID: https://orcid.org/0000-0003-4304-9835)
- Hong‐Jun Gao (ORCID: https://orcid.org/0000-0002-6766-0623)
- Nuertai Jiazila
- Jian Sun (ORCID: https://orcid.org/0000-0002-4085-6167)
- Kang Wu (ORCID: https://orcid.org/0009-0005-6151-1132)
- Hui Guo (ORCID: https://orcid.org/0009-0007-6542-5148)
- Xuanye Liu
Institutions
- Hefei University (CN)
- Institute of Physics (CN)
- University of Chinese Academy of Sciences (CN)
Publication Details
- Journal
- Chinese Physics B
- Published
- 2024-11-05
- DOI
- https://doi.org/10.1088/1674-1056/ad8ecd
- Citations
- 1
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.21