4.6 Article

Water-induced dual ultrahigh mobilities over 400 cm2 V-1 s-1 in 2D MoS2 transistors for ultralow-voltage operation and photoelectric synapse perception

期刊

JOURNAL OF MATERIALS CHEMISTRY C
卷 10, 期 13, 页码 5249-5256

出版社

ROYAL SOC CHEMISTRY
DOI: 10.1039/d1tc06010d

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资金

  1. National Natural Science Foundation of China [52172169]
  2. Central South University Research Fund for Innovation-driven Program [2019CX024]
  3. Fundamental Research Funds for the Central Universities of Central South University [2020zzts046]

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This study proposes a new method to significantly enhance the field-effect mobility of two-dimensional MoS2 in field-effect transistors by capping water molecules on its surface. The method not only achieves low power dissipation and high switching speed, but also successfully realizes intriguing synapse behaviors, and exhibits good light-dependent accuracy.
Two-dimensional (2D) MoS2 is regarded as one of the most promising channel materials for field-effect transistors (FETs) due to its thickness-dependent bandgap and high air-stability. However, current MoS2 FETs generally exhibit high power dissipation and low switching speed because of the general low field-effect mobility (mu approximate to 0.1-20 cm(2) V-1 s(-1)). Here, a facile and effective strategy to significantly enhance the mu over 400 cm(2) V-1 s(-1) is proposed by capping the water molecules on the 2D MoS2 surface of the FET. The device exhibits an ultralow operation voltage of 0.6 V as well as dual ultrahigh mobility behaviors from 409.1 cm(2) V-1 s(-1) to 773.4 cm(2) V-1 s(-1), which can be attributed to the ion-contributed quasi-electric-double-layer effect. More importantly, some intriguing synapse behaviors, such as excitatory/inhibitory postsynaptic current and controllable memory behavior, are successfully realized in our water-induced MoS2 synapse transistors. This artificial synapse can also decode Morse-coded external electrical signals. Most importantly, the light-dependent accuracy of handwritten digit recognition can be found to be as high as 97.2% based on the proposed artificial visual recognition system. These results can open new avenues for the fascinating applications of high-performance photoelectric perception systems in future, such as autonomous vehicles, man-machine interfaces, etc.

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