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Cited by 219

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Large-Scale Synthesis and Characterization of Very Long Silver Nanowires via Successive Multistep Growth

Lee, Jin Hwan, Lee, Phillip, Lee, Dongjin, Lee, Seung Seob, Ko, Seung Hwan·2012·Crystal Growth & Design

Abstract

In this research, we developed a novel successive multistep growth method to synthesize very long silver nanowires (AgNWs) over several hundred micrometers (maximum length of 400–500 μm) and performed a systematic parameter study to optimize the dimension of nanowires synthesized at a large scale. It was demonstrated that AgNWs continued to grow through successive multistep growth as long as Ag ion rich conditions were maintained continuously. We successfully attained an extremely high aspect ratio of 1000–3000 with length of over 300 μm and diameter of less than 150 nm. This value demonstrated an order of magnitude length enhancement from previous AgNW synthesis research. Furthermore, we demonstrated that the very long AgNW mesh can be used for a transparent conductor as an alternative to metal oxide conductors. The production of very long metal nanowires at a large scale has significant impact on their potential application in flexible transparent conductors.

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Metadata

Authors
Lee, J. H., Lee, P., Lee, D., Lee, S. S., & Ko, S. H.
Venue
Crystal Growth & Design
Published
2012-10-01
Volume
12
Issue
11
Pages
5598-5605
ISSN
  • 1528-7483 (ISSN-L)
  • 1528-7505
OpenAlex
W2313649460
Cited by
219
References
2
FWCI
11.39
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Large-Scale Synthesis and Characterization of Very Long Silver Nanowires via Successive Multistep Growth. https://app.cochat.ai/papers/10.1021/cg301119d
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Lee, J. H., Lee, P., Lee, D., Lee, S. S., & Ko, S. H. (2012). Large-Scale Synthesis and Characterization of Very Long Silver Nanowires via Successive Multistep Growth. Crystal Growth & Design. https://doi.org/10.1021/cg301119d

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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.