Two-dimensional ferroelectric semiconductor floating-gate transistor with light-tunable field effect for memory and photo-synapse
Ferroelectric field effect transistors (Fe-FETs) offer promising candidates for neuromorphic computing. However, it is still challenging to achieve a light-tunable field effect, which limits the function of photo-synapse. In this work, a ferroelectric semiconductor floating-gate transistor (FSF-FET) is proposed based on MoS2/h-BN/α-In2Se3 van der Waals heterojunctions (vdWHs), in which the two-dimensional ferroelectric semiconducting α-In2Se3 and dielectric h-BN serve as the trapped layer of charges and prevent layer, respectively. The excellent memory performances are exhibited, including a high programming/erasing ratio of over 107, a large memory window ratio of 74.69%, and good non-volatility. Moreover, the FSF-FETs also possess the light-tunable synapse behaviors, including the high paired-pulse facilitation of 236% and an obvious transition from short-term plasticity to long-term plasticity. The high recognition rate of 93.9% is achieved with dual-mode modulation of light and electrical pulses. The ferroelectric semiconductor floating-gate design opens up a strategy to realize the light-tunable field effect of Fe-FETs for photo-synapse.
Authors
- Congxin Xia (ORCID: https://orcid.org/0000-0003-1915-4264)
- Xiaobing Yan (ORCID: https://orcid.org/0000-0002-3266-515X)
- Yuting Peng (ORCID: https://orcid.org/0000-0003-2360-5638)
- Yiduo Shao
- Yurong Jiang (ORCID: https://orcid.org/0000-0001-8022-3965)
- Liangzhi Kou (ORCID: https://orcid.org/0000-0002-3978-117X)
- Xueping Li (ORCID: https://orcid.org/0000-0003-4198-7860)
- Rui Wang (ORCID: https://orcid.org/0000-0002-1964-4776)
- Hongzhi Li (ORCID: https://orcid.org/0009-0002-9962-6814)
Institutions
- Johns Hopkins University (US)
- Queensland University of Technology (AU)
- Hebei University (CN)
- Henan Normal University (CN)
Publication Details
- Journal
- Applied Physics Letters
- Published
- 2024-09-02
- DOI
- https://doi.org/10.1063/5.0197542
- Citations
- 9
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 1.88
Funders
- National Natural Science Foundation of China