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Metallic Nanoislands on Graphene as Highly Sensitive Transducers of Mechanical, Biological, and Optical Signals.

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Date
2016-02-10
Authors
Zaretski, Aliaksandr V
Root, Samuel E
Savchenko, Alex
Molokanova, Elena
Printz, Adam D
Jibril, Liban
Arya, Gaurav
Mercola, Mark
Lipomi, Darren J
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Abstract
This article describes an effect based on the wetting transparency of graphene; the morphology of a metallic film (≤20 nm) when deposited on graphene by evaporation depends strongly on the identity of the substrate supporting the graphene. This control permits the formation of a range of geometries, such as tightly packed nanospheres, nanocrystals, and island-like formations with controllable gaps down to 3 nm. These graphene-supported structures can be transferred to any surface and function as ultrasensitive mechanical signal transducers with high sensitivity and range (at least 4 orders of magnitude of strain) for applications in structural health monitoring, electronic skin, measurement of the contractions of cardiomyocytes, and substrates for surface-enhanced Raman scattering (SERS, including on the tips of optical fibers). These composite films can thus be treated as a platform technology for multimodal sensing. Moreover, they are low profile, mechanically robust, semitransparent and have the potential for reproducible manufacturing over large areas.
Type
Journal article
Subject
Graphene
SERS
cardiomyocyte
strain sensor
wearable sensor
wetting transparency
Biosensing Techniques
Graphite
Humans
Mechanical Phenomena
Metal Nanoparticles
Myocytes, Cardiac
Nanoparticles
Nanospheres
Spectrum Analysis, Raman
Surface Properties
Permalink
https://hdl.handle.net/10161/15626
Published Version (Please cite this version)
10.1021/acs.nanolett.5b04821
Publication Info
Zaretski, Aliaksandr V; Root, Samuel E; Savchenko, Alex; Molokanova, Elena; Printz, Adam D; Jibril, Liban; ... Lipomi, Darren J (2016). Metallic Nanoislands on Graphene as Highly Sensitive Transducers of Mechanical, Biological, and Optical Signals. Nano Lett, 16(2). pp. 1375-1380. 10.1021/acs.nanolett.5b04821. Retrieved from https://hdl.handle.net/10161/15626.
This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.
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Scholars@Duke

Arya

Gaurav Arya

Professor in the Thomas Lord Department of Mechanical Engineering and Materials Science
My research laboratory uses physics-based computational tools to provide fundamental, molecular-level understanding of a diverse range of biological and soft-material systems, with the aim of discovering new phenomena and developing new technologies. The methods we use or develop are largely based on statistical mechanics, molecular modeling and simulations, stochastic dynamics, coarse-graining, bioinformatics, machine learning, and polymer/colloidal physics. Our current resear
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