Metallic Nanoislands on Graphene as Highly Sensitive Transducers of Mechanical, Biological, and Optical Signals.
Date
2016-02-10
Journal Title
Journal ISSN
Volume Title
Repository Usage Stats
views
downloads
Citation Stats
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
Department
Description
Provenance
Citation
Permalink
Published Version (Please cite this version)
Publication Info
Zaretski, Aliaksandr V, Samuel E Root, Alex Savchenko, Elena Molokanova, Adam D Printz, Liban Jibril, Gaurav Arya, Mark Mercola, et al. (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.
Collections
Scholars@Duke
Gaurav Arya
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 research interests fall within four main themes: genome organization and regulation; polymer-nanoparticle composites; viral-DNA-packaging; and DNA nanotechnology. Please visit our website for more details about each of these research projects.
Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.