Monolayer hydrophilic MoS2 with strong charge trapping for atomically thin neuromorphic vision systems

Hu, Yunxia, Dai, Mingjin, Fang, Wei, Zhang, Xin, Zhang, Shichao, Tan, Biying, Shang, Huiming, Fu, Yong Qing and Hu, PingAn (2020) Monolayer hydrophilic MoS2 with strong charge trapping for atomically thin neuromorphic vision systems. Materials Horizon, 7 (12). pp. 3316-3324. ISSN 2051-6347

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Effective control of electrical and optoelectronic properties of two-dimensional layered materials, one of the key requirements for applications in advanced optoelectronics with multiple functions, has been hindered by the difficulty of elemental doping, which is commonly utilized in Si technology. In this study, we proposed a new method to synthesize hydrophilic MoS2 monolayers through covalently introducing hydroxyl groups during their growth process. These hydroxyl groups exhibit a strong capability of charge trapping, and thus the hydrophilic MoS2 monolayers achieve excellent electrical, optical, and memory properties. Optical memory transistors, made from a single component of monolayer hydrophilic MoS2, exhibit not only excellent light-dependent and time-dependent photoelectric performance, but also good photo-responsive memory characteristics with over multi-bit storage and more than 104 switching ratios. Atomically thin neuromorphic vision systems (with a concept of proof of 10 × 10 neuromorphic visual image) are manufactured from arrays of hydrophilic MoS2 optical memory transistors, showing high quality image sensing and memory functions with a high color resolution. These results proved our new concepts to realize image memorization and simplify the pixel matrix preparation process, which is a significant step toward the development of future artificial visual systems.

Item Type: Article
Additional Information: Funding information: This work is supported by National Basic Research Program of China (2019YFB1310200), Foundation for Innovative Research Groups of the National Natural Science Foundation of China (no. 51521003), Self-Planned Task of State Key Laboratory of Robotics and System (HIT) (no. SKLRS201801B), Engineering Physics and Science Research Council of UK (EPSRC EP/P018998/1) and Newton Mobility Grant (IE161019) through Royal Society and Natural Science Foundation of China.
Subjects: F300 Physics
H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: John Coen
Date Deposited: 27 Oct 2020 10:06
Last Modified: 02 Nov 2021 10:45

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