Literature DB >> 35243701

A Fully Solution-Printed Photosynaptic Transistor Array with Ultralow Energy Consumption for Artificial-Vision Neural Networks.

Jialin Shi1, Jiansheng Jie1,2, Wei Deng1, Gan Luo1, Xiaochen Fang1, Yanling Xiao1, Yujian Zhang1, Xiujuan Zhang1, Xiaohong Zhang1.   

Abstract

Photosynaptic organic field-effect transistors (OFETs) represent a viable pathway to develop bionic optoelectronics. However, the high operating voltage and current of traditional photosynaptic OFETs lead to huge energy consumption greater than that of the real biological synapses, hindering their further development in new-generation visual prosthetics and artificial perception systems. Here, a fully solution-printed photosynaptic OFET (FSP-OFET) with substantial energy consumption reduction is reported, where a source Schottky barrier is introduced to regulate charge-carrier injection, and which operates with a fundamentally different mechanism from traditional devices. The FSP-OFET not only significantly lowers the working voltage and current but also provides extraordinary neuromorphic light-perception capabilities. Consequently, the FSP-OFET successfully emulates visual nervous responses to external light stimuli with ultralow energy consumption of 0.07-34 fJ per spike in short-term plasticity and 0.41-19.87 fJ per spike in long-term plasticity, both approaching the energy efficiency of biological synapses (1-100 fJ). Moreover, an artificial optic-neural network made from an 8 × 8 FSP-OFET array on a flexible substrate shows excellent image recognition and reinforcement abilities at a low energy cost. The designed FSP-OFET offers an opportunity to realize photonic neuromorphic functionality with extremely low energy consumption dissipation.
© 2022 Wiley-VCH GmbH.

Entities:  

Keywords:  Schottky barrier; fully solution-printed process; low energy consumption; organic field-effect transistors; photosynaptic devices

Mesh:

Year:  2022        PMID: 35243701     DOI: 10.1002/adma.202200380

Source DB:  PubMed          Journal:  Adv Mater        ISSN: 0935-9648            Impact factor:   30.849


  1 in total

1.  Flexible Artificial Optoelectronic Synapse based on Lead-Free Metal Halide Nanocrystals for Neuromorphic Computing and Color Recognition.

Authors:  Ying Li; Jiahui Wang; Qing Yang; Guozhen Shen
Journal:  Adv Sci (Weinh)       Date:  2022-06-05       Impact factor: 17.521

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.