4.8 Article

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

期刊

ADVANCED MATERIALS
卷 34, 期 18, 页码 -

出版社

WILEY-V C H VERLAG GMBH
DOI: 10.1002/adma.202200380

关键词

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

资金

  1. National Natural Science Foundation of China [51821002, 91833303, 61904117, 51973147, 52173178]
  2. Suzhou Science and Technology Plan Forward-looking Project [SYG202023]
  3. Suzhou Key Laboratory of Functional Nano & Soft Materials, Collaborative Innovation Center of Suzhou Nano Science Technology
  4. 111 Project

向作者/读者索取更多资源

A solution-printed photosynaptic organic field-effect transistor (OFET) with substantially reduced energy consumption and extraordinary light-perception capabilities is reported. The transistor successfully emulates neural responses to external light stimuli with energy efficiencies approaching those of biological synapses, and can be used in an artificial optic-neural network.
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 x 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.

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