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Nanofiber Channel Organic Electrochemical Transistors for Low‐Power Neuromorphic Computing and Wide‐Bandwidth Sensing Platforms

Authors :
Youngran Jung
Seung Hyun Oh
Jeong-Yun Sun
Young Woon Cho
Young-Chang Joo
Sol-Kyu Lee
Sangbum Kim
Jong-Sung Lee
Source :
Advanced Science, Vol 8, Iss 10, Pp n/a-n/a (2021), Advanced Science
Publication Year :
2021
Publisher :
Wiley, 2021.

Abstract

Organic neuromorphic computing/sensing platforms are a promising concept for local monitoring and processing of biological signals in real time. Neuromorphic devices and sensors with low conductance for low power consumption and high conductance for low‐impedance sensing are desired. However, it has been a struggle to find materials and fabrication methods that satisfy both of these properties simultaneously in a single substrate. Here, nanofiber channels with a self‐formed ion‐blocking layer are fabricated to create organic electrochemical transistors (OECTs) that can be tailored to achieve low‐power neuromorphic computing and fast‐response sensing by transferring different amounts of electrospun nanofibers to each device. With their nanofiber architecture, the OECTs exhibit a low switching energy of 113 fJ and operate within a wide bandwidth (cut‐off frequency of 13.5 kHz), opening a new paradigm for energy‐efficient neuromorphic computing/sensing platforms in a biological environment without the leakage of personal information.<br />Concepts of organic neuromorphic computing/sensing platforms for local monitoring and processing of biological signals in real time are presented. With a nanofiber architecture as a channel of a transistor, low‐power neuromorphic devices and wide‐bandwidth sensors are fabricated together on a single substrate without changing the materials, structures, and fabrication processes, demonstrating the future applications for neuromorphic computing/sensing platforms.

Details

Language :
English
ISSN :
21983844
Volume :
8
Issue :
10
Database :
OpenAIRE
Journal :
Advanced Science
Accession number :
edsair.doi.dedup.....2a9137de4434d270c2389f659aaee6f9