Near infrared neuromorphic computing via upconversion-mediated optogenetics

被引:62
作者
Zhai, Yongbiao [1 ]
Zhou, Ye [2 ]
Yang, Xueqing [3 ]
Wang, Feng [3 ]
Ye, Wenbin [1 ]
Zhu, Xiaojian [1 ,4 ]
She, Donghong [1 ]
Lu, Wei D. [4 ]
Han, Su-Ting [1 ,4 ]
机构
[1] Shenzhen Univ, Coll Elect Sci & Technol, Shenzhen 518060, Guangdong, Peoples R China
[2] Shenzhen Univ, Inst Adv Study, Shenzhen 518060, Guangdong, Peoples R China
[3] City Univ Hong Kong, Dept Mat Sci & Engn, 83 Tat Chee Ave, Hong Kong, Peoples R China
[4] Univ Michigan, Dept Elect Engn & Comp Sci, Ann Arbor, MI 48109 USA
基金
中国国家自然科学基金;
关键词
Optogenetics; Optoelectronics; Neuromorphic computing; Near-infrared light; Long-term potentiation; NANOCRYSTALS;
D O I
10.1016/j.nanoen.2019.104262
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Near infrared (NIR) synaptic devices offer a remote-control approach to implement neuromorphic computing for data safety and artificial retinal system applications. In upconverting nanoparticles (UCNPs)-mediated optogenetics biosystems, NIR regulation of membrane ion channels allows remote and selective control of the Ca2+ flux to modulate synaptic plasticity behaviors. Inspired by the upconversion optogenetics, we proposed a NIR artificial synapse based on a UCNPs-MoS2 floating gate phototransistor in which MoS2 acts as light-sensitive ion channels to reabsorb the visible light emitted from UCNPs under NIR illumination. As a result, the synaptic device exhibits stable persistent photocurrent (PPC) effect up to 353 K and ultrahigh photogain (similar to 10(8) electrons per photon), ensuring the long-term potentiation (LTP) behavior. Simulations using the handwritten digit data sets indicate good recognition accuracy of the light-controlled artificial neuron network. Overall, this design concept combining biology, optics and electronics opens up a new avenue for developing optogenetics-inspired neuromorphic technology in the future.
引用
收藏
页数:9
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