2D electric-double-layer phototransistor for photoelectronic and spatiotemporal hybrid neuromorphic integration

被引:228
|
作者
Jiang, Jie [1 ]
Hu, Wennan [1 ]
Xie, Dingdong [1 ]
Yang, Junliang [1 ]
He, Jun [1 ]
Gao, Yongli [1 ,4 ]
Wan, Qing [2 ,3 ]
机构
[1] Cent S Univ, Sch Phys & Elect, Hunan Key Lab Super Microstruct & Ultrafast Proc, Changsha 410083, Hunan, Peoples R China
[2] Nanjing Univ, Sch Elect Sci & Engn, Nanjing 210093, Jiangsu, Peoples R China
[3] Nanjing Univ, Collaborat Innovat Ctr Adv Microstruct, Nanjing 210093, Jiangsu, Peoples R China
[4] Univ Rochester, Dept Phys & Astron, Rochester, NY 14627 USA
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
MOS2; PLASTICITY; MONOLAYER; MECHANISMS; NETWORK; FILMS;
D O I
10.1039/c8nr07133k
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The hardware implementation of neuromorphic computing has attracted growing interest as a promising candidate for confronting the bottleneck of traditional von Neumann computers. However, most previous reports are focusd on emulating the synaptic behaviors by a mono-mode using an electric-driving or photo-driving approach, resulting in a big challenge to synchronously handle the natural photoelectric information. Herein, we report a multifunctional photoelectronic hybrid-integrated synaptic device based on the electric-double-layer (EDL) MoS2 phototransistor. Interestingly, the electric MoS2 synapse exhibits a potentiation filtering effect, while the photonic counterpart can implement both potentiation and depression filtering effects. Most importantly, for the first time, photoelectronic and spatio-temporal four-dimensional (4D) hybrid integration was successfully demonstrated by the synergic interplay between photonic and electric stimuli within a single MoS2 synapse. An energy band model is proposed to further understand such a photoelectronic and spatio-temporal 4D hybrid coupling mechanism. These results might provide an alternative solution for the size-scaling and intellectualization campaign of the post-Moore era, and for more sophisticated photoelectronic hybrid computing in the emerging neuromorphic nanoelectronics.
引用
收藏
页码:1360 / 1369
页数:10
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