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Copper Nanoparticles for Printed Electronics: Routes Towards Achieving Oxidation Stability

Open access
Magdassi, Shlomo, Grouchko, Michael, Kamyshny, Alexander·2010·Materials

Abstract

In the past few years, the synthesis of Cu nanoparticles has attracted much attention because of its huge potential for replacing expensive nano silver inks utilized in conductive printing. A major problem in utilizing these copper nanoparticles is their inherent tendency to oxidize in ambient conditions. Recently, there have been several reports presenting various approaches which demonstrate that copper nanoparticles can resist oxidation under ambient conditions, if they are coated by a proper protective layer. This layer may consist of an organic polymer, alkene chains, amorphous carbon or graphenes, or inorganic materials such as silica, or an inert metal. Such coated copper nanoparticles enable achieving high conductivities by direct printing of conductive patterns. These approaches open new possibilities in printed electronics, for example by using copper based inkjet inks to form various devices such as solar cells, Radio Frequency Identification (RFID) tags, and electroluminescence devices. This paper provides a review on the synthesis of copper nanoparticles, mainly by wet chemistry routes, and their utilization in printed electronics.

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Metadata

Authors
Magdassi, S., Grouchko, M., & Kamyshny, A.
Venue
Materials
Publisher
MDPI AG
Published
2010-09-08
Volume
3
Issue
9
Pages
4626-4638
ISSN
1996-1944 (ISSN-L)
OpenAlex
W2108234203
Cited by
429
References
0
FWCI
10.22
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Copper Nanoparticles for Printed Electronics: Routes Towards Achieving Oxidation Stability. https://app.cochat.ai/papers/10.3390/ma3094626
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Magdassi, S., Grouchko, M., & Kamyshny, A. (2010). Copper Nanoparticles for Printed Electronics: Routes Towards Achieving Oxidation Stability. Materials. https://doi.org/10.3390/ma3094626

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.