Near‐Infrared‐Irradiation‐Mediated Synaptic Behavior from Tunable Charge‐Trapping Dynamics. (13th November 2019)

• Record Type: Journal Article
• Authors: Wang, Yan; Yang, Jing; Ye, Wenbin; She, Donghong; Chen, Jinrui; Lv, Ziyu; Roy, Vellaisamy A. L.; Li, Huilin; Zhou, Kui; Yang, Qing; Zhou, Ye; Han, Su‐Ting
• Is Part Of: Advanced Electronic Materials. Volume 6:Number 2(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-11-13
• Subjects: charge trapping -- heterostructures -- pattern recognition -- photonic neuromorphic computing -- synaptic transistors; Materials -- Electric properties -- Periodicals; Materials science -- Periodicals; Magnetic materials -- Periodicals; Electronic apparatus and appliances -- Periodicals; 537
• DOI: 10.1002/aelm.201900765
• Languages: English
• ISSNs: 2199-160X

Abstract

Abstract: Parallel information storage coupled with storage density is a major focus for non‐volatile memory devices to achieve neuromorphic computing that can work at low power. In this regard, a photoactive charge‐trapping medium consisting of inorganic heteronanosheets for the fabrication of a synaptic transistor is demonstrated. This synaptic device senses and responds to near‐infrared (NIR) light signals and mimics the memorization and dynamic forgetting process due to the reversible nature of photogenerated charge interaction. Device‐level synaptic evolutions from short‐term plasticity to long‐term plasticity, paired pulse facilitation, and paired pulse depression are realized with light modulation on the weight update terminal. To understand the underlying mechanism of the synaptic behavior under NIR signals, systematic analysis is carried out using in situ atomic force microscopy based electrical techniques. With its photoactive architecture, this information processing analogue is validated for visual object recognition, which paves the way for implementing NIR‐controlled neuromorphic computing. Abstract : A near‐infrared (NIR‐) irradiation‐gated synaptic device based on an organic–inorganic heterostructure is demonstrated to emulate important neuroplasticities including short‐term memory, long‐term memory, neural facilitation, and the important functions of learning and forgetting processes in the brain, which set the stage for biorealistic implementation of NIR computing.