Plasma Jet Printing and in Situ Reduction of Highly Acidic Graphene Oxide

Miniaturization of electronic devices and the advancement of Internet of Things pose exciting challenges to develop technologies for patterned deposition of functional nanomaterials. Printed and flexible electronic devices and energy storage devices can be embedded onto clothing or other flexible su...

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Bibliographic Details
Published in:ACS nano 2018-06, Vol.12 (6), p.5473-5481
Main Authors: Dey, Avishek, Krishnamurthy, Satheesh, Bowen, James, Nordlund, Dennis, Meyyappan, M, Gandhiraman, Ram P
Format: Article
Language:English
Subjects:
CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY
ENGINEERING
flexible electronics
functionalization
graphene oxide
plasma jet
printing
reduction
surface coating
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Summary:Miniaturization of electronic devices and the advancement of Internet of Things pose exciting challenges to develop technologies for patterned deposition of functional nanomaterials. Printed and flexible electronic devices and energy storage devices can be embedded onto clothing or other flexible surfaces. Graphene oxide (GO) has gained much attention in printed electronics due its solution processability, robustness, and high electrical conductivity in the reduced state. Here, we introduce an approach to print GO films from highly acidic suspensions with in situ reduction using an atmospheric pressure plasma jet. Low-temperature plasma of a He and H2 mixture was used successfully to reduce a highly acidic GO suspension (pH < 2) in situ during deposition. This technique overcomes the multiple intermediate steps required to increase the conductivity of deposited GO. X-ray spectroscopic studies confirmed that the reaction intermediates and the concentration of oxygen functionalities bonded to GO have been reduced significantly by this approach without any additional steps. Moreover, the reduced GO films showed enhanced conductivity. Hence, this technique has a strong potential for printing conducting patterns of GO for a range of large-scale applications.
ISSN:1936-0851
1936-086X
DOI:10.1021/acsnano.8b00903