Solution‐Processed Ultralow Voltage Organic Transistors With Sharp Switching for Adaptive Visual Perception

Author:

Duan Shuming12,Zhang Xianghong3,Xi Yue1,Liu Di3,Zhang Xiaotao1,Li Chunlei4,Jiang Lang4,Li Liqiang12,Chen Huipeng3,Ren Xiaochen1ORCID,Hu Wenping12

Affiliation:

1. Key Laboratory of Organic Integrated Circuits Ministry of Education Tianjin Key Laboratory of Molecular Optoelectronic Sciences Department of Chemistry School of Science Tianjin University and Collaborative Innovation Center of Chemical Science and Engineering (Tianjin) Tianjin 300072 China

2. Joint School of National University of Singapore and Tianjin University International Campus of Tianjin University Binhai New City Fuzhou 350207 China

3. Institute of Optoelectronic Display National & Local United Engineering Lab of Flat Panel Display Technology Fuzhou University Fuzhou 350002 China

4. Beijing National Laboratory for Molecular Sciences Key Laboratory of Organic Solids Institute of Chemistry Chinese Academy of Sciences Beijing 100190 China

Abstract

AbstractNeuromorphic visual systems can emulate biological retinal systems to perceive visual information under different levels of illumination, making them have considerable potential for future intelligent vehicles and vision automation. However, the complex circuits and high operating voltages of conventional artificial vision systems present great challenges for device integration and power consumption. Here, bioinspired synaptic transistors based on organic single crystal phototransistors are reported, which exhibit excitation and inhibition synaptic plasticity with time‐varying. By manipulating the charge dynamics of the trapping centers of organic crystal–electret vertical stacks, organic transistors can operate below 1 V with record high on/off ratios close to 108 and sharp switching with a subthreshold swing of 59.8 mV dec−1. Moreover, the approach offers visual adaptation with highly localized modulation and over 98.2% recognition accuracy under different illumination levels. These bioinspired visual adaptation transistors offer great potential for simplifying the circuitry of artificial vision systems and will contribute to the development of machine vision applications.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Fujian Province

Ministry of Science and Technology of the People's Republic of China

Publisher

Wiley

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