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  5. Highly Conductive, Scalable, and Machine Washable Graphene‐Based E‐Textiles for Multifunctional Wearable Electronic Applications

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Article
English
2020

Highly Conductive, Scalable, and Machine Washable Graphene‐Based E‐Textiles for Multifunctional Wearable Electronic Applications

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English
2020
Advanced Functional Materials
Vol 30 (23)
DOI: 10.1002/adfm.202000293

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Konstantin ‘kostya’  Novoselov
Konstantin ‘kostya’ Novoselov

The University of Manchester

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Shaila Afroj
Sirui Tan
Amr M. Abdelkader
+2 more

Abstract

Graphene‐based textiles show promise for next‐generation wearable electronic applications due to their advantages over metal‐based technologies. However, current reduced graphene oxide (rGO)‐based electronic textiles (e‐textiles) suffer from poor electrical conductivity and higher power consumption. Here, highly conductive, ultraflexible, and machine washable graphene‐based wearable e‐textiles are reported. A simple and scalable pad−dry−cure method with subsequent roller compression and a fine encapsulation of graphene flakes is used. The graphene‐based wearable e‐textiles thus produced provide lowest sheet resistance (≈11.9 Ω sq −1 ) ever reported on graphene e‐textiles, and highly conductive even after 10 home laundry washing cycles. Moreover, it exhibits extremely high flexibility, bendability, and compressibility as it shows repeatable response in both forward and backward directions before and after home laundry washing cycles. The scalability and multifunctional applications of such highly conductive graphene‐based wearable e‐textiles are demonstrated as ultraflexible supercapacitor and skin‐mounted strain sensors.

How to cite this publication

Shaila Afroj, Sirui Tan, Amr M. Abdelkader, Konstantin ‘kostya’ Novoselov, Nazmul Karim (2020). Highly Conductive, Scalable, and Machine Washable Graphene‐Based E‐Textiles for Multifunctional Wearable Electronic Applications. Advanced Functional Materials, 30(23), DOI: 10.1002/adfm.202000293.

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Publication Details

Type

Article

Year

2020

Authors

5

Datasets

0

Total Files

0

Language

English

Journal

Advanced Functional Materials

DOI

10.1002/adfm.202000293

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