Textiles are important materials that are used in everyday life, with a broad range of applications. Based on the origin of the raw material, textiles can be either natural (e.g. cotton, silk, wool, cashmere, etc.) or synthetic (e.g. acrylics, polyamides, polyesters, etc.). Customers are now more conscious than ever on the correlation between price and quality of the textiles they are buying. However, with increasing prices and the variations of types and quality, counterfeit textile products are becoming more and more common. Whether it is clothes or carpets, people are cheated by being offered material made from synthetics or wool as genuine silk at exaggerated prices.
A simple tool for the rapid test of the correct identity of the textile article of interest would be a significant progress in consumer protection. This tool has to be portable, affordable, and should allow users to analyze their target textiles without destroying their products. Miniaturization of near- infrared (NIR) spectrometers has advanced to the point where handheld instruments could provide reliable and affordable means to serve this purpose. In this application note, we demonstrate the possibility of using NeoSpectra spectral sensors for the analysis of different textiles types.
Mercerization of wool lends the final product a gloss that, for the naked eye, may look very similar to silk. This similarity is exploited by untrustworthy carpet manufacturers to sell such carpets to a credulous customer as a silk product for an unrealistic prize. Figure 1 shows that plotting the NIR spectra corresponding to each type of carpet can easily and quickly discriminate between silk and mercerized wool carpets. This demonstrates that NeoSpectra spectral sensors can be used to discriminate between authentic and counterfeit silk carpets, even by non-experts, with the simple visualization of their corresponding NIR spectra. In more complex situations, material-specific evaluation algorithms can be developed to qualify and/or classify different types of textiles.
Figure 1.
Authentication of a genuine silk carpet and discrimination from a carpet made from mercerized wool:
(a): measurement of the diffuse reflection NIR spectrum of a carpet
(b): authentication of the silk carpet (foreground) by visual comparison to a silk reference spectrum
(c): identification of the mercerized wool carpet (background) by visual comparison to a (non-mercerized)
In order to demonstrate the ability of NeoSpectra spectral sensors to identify and/or classify the different kinds of textiles commonly found in consumer textile-based products, we show how it is used to perform discrimination of nine different classes of natural and synthetic textile materials (cotton, wool/cashmere, silk, Kevlar, Nomex, polyacrylonitrile/acrylics, elasthanes, polyamide 6 (PA6)/polyamide 66 (PA66) and polyethylene terephthalate (PET)) based on their diffuse- reflection NIR spectra.
Sample sets:
The investigations clearly demonstrate that the spectra of the most common textile materials measured with the NeoSpectra spectral sensor provide suitable and rapidly available analytical data for the correct identification of unknown textile test samples. In a first step the PCA applied to the calibration spectra of nine different textile classes yielded a clear separation into clusters and the spectra of test samples were correctly identified. Furthermore, the SIMCA analyses based on the PCAs of all possible textile-class pairs provided a perfect identification of test sample.