Literature DB >> 23905159

Silver colloidal pastes for dye analysis of reference and historical textile fibers using direct, extractionless, non-hydrolysis surface-enhanced Raman spectroscopy.

Ambra Idone1, Monica Gulmini, Anne-Isabelle Henry, Francesca Casadio, Lauren Chang, Lorenzo Appolonia, Richard P Van Duyne, Nilam C Shah.   

Abstract

Surface-enhanced Raman spectroscopy (SERS) is an ideal tool for analyzing dyes on historical textiles because it requires very little sample compared to other available analytical methods and analysis can be done directly on the fiber. This paper reports on the first systematic study of the use of citrate-reduced silver colloidal pastes for the direct, extractionless, non-hydrolysis detection of dyes directly on wool, silk, cotton, and flax fibers. This type of study provides greater insight into the optimal conditions required for accurate analysis of dyes in historical samples. In this work, Ag colloidal pastes were characterized using localized surface plasmon resonance and scanning electron microscopy. The pastes were then employed for SERS analysis of twelve reference samples of different vegetal and animal fibers dyed with cochineal and eleven dyed with brazilwood. Furthermore, six historical textiles from an important collection of Mariano Fortuny (1871-1949) textiles at the Art Institute of Chicago were also examined, to test the efficacy of the paste on aged samples, and to shed light on Fortuny's fascinating production techniques. A mixture of cochineal and brazilwood was detected in some of the historical samples demonstrating, for the first time, simultaneous identification of these colorants used in combination. In addition, the findings give substance to the claim that Fortuny kept using natural dyes at a time when many new and attractive synthetic products became available.

Entities:  

Year:  2013        PMID: 23905159     DOI: 10.1039/c3an00788j

Source DB:  PubMed          Journal:  Analyst        ISSN: 0003-2654            Impact factor:   4.616


  4 in total

1.  Present and Future of Surface-Enhanced Raman Scattering.

Authors:  Judith Langer; Dorleta Jimenez de Aberasturi; Javier Aizpurua; Ramon A Alvarez-Puebla; Baptiste Auguié; Jeremy J Baumberg; Guillermo C Bazan; Steven E J Bell; Anja Boisen; Alexandre G Brolo; Jaebum Choo; Dana Cialla-May; Volker Deckert; Laura Fabris; Karen Faulds; F Javier García de Abajo; Royston Goodacre; Duncan Graham; Amanda J Haes; Christy L Haynes; Christian Huck; Tamitake Itoh; Mikael Käll; Janina Kneipp; Nicholas A Kotov; Hua Kuang; Eric C Le Ru; Hiang Kwee Lee; Jian-Feng Li; Xing Yi Ling; Stefan A Maier; Thomas Mayerhöfer; Martin Moskovits; Kei Murakoshi; Jwa-Min Nam; Shuming Nie; Yukihiro Ozaki; Isabel Pastoriza-Santos; Jorge Perez-Juste; Juergen Popp; Annemarie Pucci; Stephanie Reich; Bin Ren; George C Schatz; Timur Shegai; Sebastian Schlücker; Li-Lin Tay; K George Thomas; Zhong-Qun Tian; Richard P Van Duyne; Tuan Vo-Dinh; Yue Wang; Katherine A Willets; Chuanlai Xu; Hongxing Xu; Yikai Xu; Yuko S Yamamoto; Bing Zhao; Luis M Liz-Marzán
Journal:  ACS Nano       Date:  2019-10-08       Impact factor: 15.881

2.  Compositional and Micro-Morphological Characterisation of Red Colourants in Archaeological Textiles from Pharaonic Egypt.

Authors:  Diego Tamburini; Joanne Dyer; Patrizia Davit; Maurizio Aceto; Valentina Turina; Matilde Borla; Marie Vandenbeusch; Monica Gulmini
Journal:  Molecules       Date:  2019-10-18       Impact factor: 4.411

3.  Plasmonic colloidal pastes for surface-enhanced Raman spectroscopy (SERS) of historical felt-tip pens.

Authors:  Daniela Saviello; Abeer Alyami; Maddalena Trabace; Rodorico Giorgi; Piero Baglioni; Antonio Mirabile; Daniela Iacopino
Journal:  RSC Adv       Date:  2018-02-22       Impact factor: 3.361

4.  Identification of Polish cochineal (Porphyrophora polonica L.) in historical textiles by high-performance liquid chromatography coupled with spectrophotometric and tandem mass spectrometric detection.

Authors:  Katarzyna Lech; Maciej Jarosz
Journal:  Anal Bioanal Chem       Date:  2016-03-02       Impact factor: 4.142

  4 in total

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