2D electric-double-layer phototransistor for photoelectronic and spatiotemporal hybrid neuromorphic integration. Issue 3 (3rd January 2019)

• Record Type: Journal Article
• Authors: Jiang, Jie; Hu, Wennan; Xie, Dingdong; Yang, Junliang; He, Jun; Gao, Yongli; Wan, Qing
• Is Part Of: Nanoscale. Volume 11:Issue 3(2019)
• Page Start: 1360
• Page End: 1369
• Publication Date: 2019-01-03
• Subjects: Nanoscience -- Periodicals; Nanotechnology -- Periodicals; 620.505
• DOI: 10.1039/c8nr07133k
• Languages: English
• ISSNs: 2040-3364

Abstract

Abstract : A novel photo-electronic hybrid-integrated synaptic device based on a 2D MoS2 phototransistor gated by the electric-double-layer biopolymer electrolyte (sodium alginate) is proposed. Abstract : 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.