SERS and Raman imaging as a new tool to monitor dyeing on textile fibres
authors Fateixa, S; Wilhelm, M; Nogueira, HIS; Trindade, T
nationality International
journal JOURNAL OF RAMAN SPECTROSCOPY
author keywords textile nanocomposites; Raman imaging; silver nanoparticles; SERS; methylene blue
keywords SURFACE-ENHANCED RAMAN; MEMBRANE MIMETIC SYSTEMS; SILVER NANOPARTICLES; ANTIMICROBIAL PROPERTIES; SINGLE-MOLECULE; LBL FILMS; SCATTERING; SPECTROSCOPY; GOLD; NANOSTRUCTURES
abstract Textile fibres containing Ag nanoparticles have been widely explored for a number of antimicrobial fabrics. Moreover, it is well-known that textile dyeing is a critical stage in the manufacture thereof. This research shows that surface enhanced Raman scattering (SERS) and Raman imaging can be used with advantage in the monitoring of this process. Using Ag containing linen fibres stained with methylene blue (MB), it was possible to map the local distribution of the MB dye in the fibres by Raman imaging. MB was selected as the SERS molecular probe and as a model dye. Composites of linen fibres and Ag nanoparticles were prepared by distinct methods and used as SERS substrates in order to evaluate the effect of the preparative method on the Raman images. Our results demonstrate that by using Raman imaging associated to the presence of Ag nanoparticles, it is possible to distinguish the local distribution of the dye on the textile surface. This investigation allows to foreseeing the use of this technique in terms of quality control of Ag containing fabrics, which is a market in great expansion. Copyright (c) 2016 John Wiley & Sons, Ltd.
publisher WILEY-BLACKWELL
issn 0377-0486
year published 2016
volume 47
issue 10
beginning page 1239
ending page 1246
digital object identifier (doi) 10.1002/jrs.4947
web of science category Spectroscopy
subject category Spectroscopy
unique article identifier WOS:000386068300009
  ciceco authors
  impact metrics
times cited (wos core): 1
journal impact factor (jcr 2016): 2.969
5 year journal impact factor (jcr 2016): 2.648
category normalized journal impact factor percentile (jcr 2016): 81.707
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