期刊
ADVANCED MATERIALS
卷 33, 期 52, 页码 -出版社
WILEY-V C H VERLAG GMBH
DOI: 10.1002/adma.202104960
关键词
biomimetic eyes; image learning; MoS; (2); synaptic devices; ultralow power consumption
类别
资金
- National Basic Research Program of China [2019YFB1310200]
- Foundation for Innovative Research Groups of the National Natural Science Foundation of China (NSFC) [51521003]
- Self-Planned Task of State Key Laboratory of Robotics and System (HIT) [SKLRS201801B]
- Newton Mobility Grant through Royal Society [IE161019]
- International Exchange Grant through Royal Society [IEC/NSFC/201078]
- International Exchange Grant through NFSC [IEC/NSFC/201078]
- Newton Mobility Grant through NFSC [IE161019]
In this study, a novel artificial synaptic device is proposed to achieve ultra-low power consumption by increasing channel conductivity and reducing power consumption. The multilayer and polycrystalline MoS2 film demonstrates persistent photoconductivity performance, supporting short-term plasticity and long-term plasticity effectively, with great potential for applications.
Biomimetic eyes, with their excellent imaging functions such as large fields of view and low aberrations, have shown great potentials in the fields of visual prostheses and robotics. However, high power consumption and difficulties in device integration severely restrict their rapid development. In this study, an artificial synaptic device consisting of a molybdenum disulfide (MoS2) film coated with an electron injection enhanced indium (In) layer is proposed to increase the channel conductivity and reduce the power consumption. This artificial synaptic device achieves an ultralow power consumption of 68.9 aJ per spike, which is several hundred times lower than those of the optical artificial synapses reported in literature. Furthermore, the multilayer and polycrystalline MoS2 film shows persistent photoconductivity performance, effectively resulting in short-term plasticity, long-term plasticity, and their transitions between each other. A 5 x 5 In/MoS2 synaptic device array is constructed into a hemispherical electronic retina, demonstrating its impressive image sensing and learning functions. This research provides a new methodology for effective control of artificial synaptic devices, which have great opportunities used in bionic retinas, robots, and visual prostheses.
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