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Neurofiber Transistors: Dendritic Network Implementable Organic Neurofiber Transistors with Enhanced Memory Cyclic Endurance for Spatiotemporal Iterative Learning (Adv. Mater. 26/2021)
Author(s) -
Kim Soo Jin,
Jeong JaeSeung,
Jang Ho Won,
Yi Hyunjung,
Yang Hoichang,
Ju Hyunsu,
Lim Jung Ah
Publication year - 2021
Publication title -
advanced materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 10.707
H-Index - 527
eISSN - 1521-4095
pISSN - 0935-9648
DOI - 10.1002/adma.202170202
Subject(s) - materials science , neuromorphic engineering , microfiber , artificial neural network , transistor , electrode , nanotechnology , synapse , physical neural network , computer science , optoelectronics , artificial intelligence , electrical engineering , neuroscience , recurrent neural network , voltage , engineering , chemistry , types of artificial neural networks , composite material , biology
Dendritic neural‐network implementable organic neurofiber transistors with enhanced memory cyclic endurance for spatiotemporal iterative learning are developed by Hyunsu Ju, Jung Ah Lim, and co‐workers in article number 2100475. These neurofiber transistors consisting of a double‐stranded assembly of electrode microfibers and an iongel gate insulator enable a multichannel synaptic junction of a neural network via simple physical contact of gate‐electrode microfibers, as the dendritic connections of a biological neuron fiber. This work provides insight into the design of the materials and architecture of organic neuromorphic devices with reliable artificial synaptic functionality for artificial neural network learning.