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Reflectance FT-IR Spectroscopy As a Viable Option for Textile Fiber

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Reflectance FT-IR Spectroscopy As a Viable Option for Textile Fiber Peets et al. Herit Sci (2019) 7:93 https://doi.org/10.1186/s40494-019-0337-z RESEARCH ARTICLE Open Access Refectance FT-IR spectroscopy as a viable option for textile fber identifcation Pilleriin Peets* , Karl Kaupmees, Signe Vahur and Ivo Leito Abstract In this study, the refectance-FT-IR (r-FT-IR) spectroscopy is demonstrated to be a suitable option for non-invasive identifcation of textile fbers. A collection of known textile fbers, 61 single-component textiles from 16 diferent types, were analyzed, resulting in more than 4000 individual spectra. The r-FT-IR method was compared with ATR-FT-IR spectroscopy using two instrumental approaches: FT-IR-microspectrometer with ATR mode (mATR-FT-IR) and ATR- FT-IR spectrometer (ATR-FT-IR). Advantages and drawbacks of these methods were discussed. Principal component based discriminant analysis and random forest classifcation methods were created for the identifcation of textile fb- ers in case-study samples. It was concluded that in general, the performance of r-FT-IR is comparable with ATR-FT-IR. In particular, r-FT-IR is more successful than ATR-FT-IR in diferentiating between the amide-based fbers wool, silk and polyamide. As an additional result of this work, a collection of r-FT-IR spectra of diferent textile fbers was compiled and made available for the scientifc community. Keywords: Refectance-FT-IR, ATR-FT-IR, Textile analysis, Non-invasive, Classifcation Introduction Te easiest and most used way to identify fbers is Textile fbers are by their chemical composition complex probably using optical microscopy. Tis method is well materials, commonly classifed by their origin as natural suitable to detect the presence of natural fbers like wool, (e.g. cotton, linen, silk, wool), regenerated (e.g. viscose, cotton, linen. Unfortunately, most of the modern fb- cellulose acetate) and synthetic (e.g. polyester, polyam- ers (regenerated and synthetic) are almost identical in ide, polyacrylic) [1, 2]. Textile fbers can be used in mak- their morphology and thus cannot be identifed reliably ing items like clothes, carpets, furniture, ropes and bags. with microscopic visualization [2, 6]. For fast analysis of Te identifcation of textile fbers is of great importance textile fbers, often in (almost) non-destructive way, dif- as textiles are a major international commodities, form a ferent vibrational spectroscopy approaches—Raman, signifcant part of cultural heritage and can be an impor- near-infrared spectroscopy (NIR) and mid-infrared spec- tant physical evidence in forensics [3–5]. Due to the wide troscopy (IR)—have been used [1, 4, 5, 7–11]. Raman variety of fbers used to make textiles, analysis and iden- spectroscopy, while being widely used method in cul- tifcation of the fbers is often challenging [1]. In many tural heritage, [4, 12, 13] has a serious limitation when cases in forensics and cultural heritage, the samples are it comes to the identifcation of textile fbers. Te main unique and/or highly valuable. Tus, either non-invasive obstacles are the textile dyes. Several studies [4, 9, 14] approaches or extremely small samples have to be used have shown that most of the Raman bands come from the for the analysis. Otherwise the analyzed object would be dyes and represent only a small part of textile fbers. Due damaged. Also, the time needed to perform the analysis to a fact that cloths are usually dyed, this signifcantly might be an important factor. Tus, it is often desirable to hinders the use of Raman spectroscopy in identifcation use express methods. of textile fbers. When it comes to the analysis of textile fbers, Fourier *Correspondence: [email protected] transform infrared (FT-IR) spectroscopy in the attenu- Institute of Chemistry, University of Tartu, 14a Ravila Str, 50411 Tartu, ated total refectance (ATR) mode is the most acknowl- Estonia edged analytical technique [1, 8, 15–20]. Te main © The Author(s) 2019. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creat iveco mmons .org/licen ses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/ publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Peets et al. Herit Sci (2019) 7:93 Page 2 of 10 drawback of ATR-FT-IR is the need to apply signifcant the parameter that indicates how much sample is needed pressure to the textile, which in cases of e.g. unique arti- to identify real-life samples. Problems with very small facts can be unacceptable as they can break under ATR sample sizes are discussed more thoroughly in “Results pressure. FT-IR analysis of textiles can be performed in and discussion” section. a contactless non-invasive way when refectance mode is Case-study samples in this work were small textile used instead of ATR. Using refectance FT-IR (r-FT-IR) pieces or threads that were analyzed directly without cut- with a microspectrometer [21, 22] enables analysis of ting or altering the sample. miniature objects or small parts of larger objects with- out sample removal, i.e. local analysis. Tis is possible because of the small measurement area and accurate con- Analysis with FT‑IR‑microspectrometer using refectance trol of the position from where the spectra are measured. and ATR modes Tus, it becomes possible to collect a number of spectra Termo Scientifc Nicolet iN10 MX integrated FT-IR across the surface for spectral mapping, e.g. for assessing microscope (FT-IR microspectrometer) was used in the homogeneity of the sample. Despite these advantages, refectance and ATR modes. Measurements were done r-FT-IR has previously been overlooked for fber identif- using MCT detector cooled with liquid nitrogen, spec- cation as it is classically considered suitable only for fat tral range 600–4000 cm−1, resolution 4 cm−1 and 64 surfaces [23, 24]. number of scans. For refectance mode, sample was Te aim of this work was to evaluate the ability of placed on the gold plate, which was also used as back- refectance-FT-IR to identify textile fbers using FT-IR ground. In the ATR mode, the slide-on ATR objective microspectrometer in refectance mode. In this study with a conical germanium crystal (Slide-On MicroTip Ge comparison between r-FT-IR and ATR-FT-IR spectra ATR crystal) was used with 60–75% pressure strength. of textile fbers was made and the main advantages and For all the samples, multiple spectra from diferent limitations of these techniques have been highlighted. parts of each sample piece were recorded. Te micro- Diferent data science tools were used for data analysis ATR tip allows analyzing samples as small as 3 microns. and classifying textile fbers. Additionally, a collection of In the refectance mode measurement area is adjust- r-FT-IR spectra of diferent textile fbers was composed able: in most cases aperture 150 × 150 μm was used. and made available for the scientifc community [25]. For smaller sample pieces aperture down to 25 × 25 μm was used. With FT-IR microspectrometer using ATR Experimental mode (mATR-FT-IR) 2068 spectra and using refectance Analyzed textile samples mode 1677 spectra were recorded altogether. Te data For the analysis, 61 single-component textile fbers from were collected and processed using Termo Electron’s 16 diferent types were used: wool, silk, cotton, linen, OMNIC PICTA software. jute, sisal, viscose, cellulose acetate (acetate), Tencel™ (lyocell), fberglass, polyester, polyamide, polyacrylic, Analysis with ATR‑FT‑IR spectroscopy elastane, polyethylene and polypropylene. For classifca- tion analysis 59, single-component textile samples were Termo Scientifc Nicolet 6700 FT-IR spectrometer used (two Tencel™ samples were excluded). Real-life tex- with Smart Orbit micro-ATR accessory was used. Te tile samples (fabrics from fabric manufacturers, cloth- instrument has DLaTGS detector, Vectra Aluminium ing items, shopping bags, etc.) were used, obtained from interferometer and sealed and desiccated optical bench diferent companies from Estonia (Kreenholm Manu- with CsI optics. Smart Orbit is a single-bounce dia- faktuur OÜ, Estonian National Opera), fabric stores (AS mond crystal ATR accessory with a refractive index of Abakhan Fabrics Estonia) and private collections. Most 2.4, active sample area diameter 1.5 mm. Parameters 1 of the standard samples were pieces with a size of few used in measurements were: resolution 4 cm− , spec- 1 cm2, cut of from the fabric, clothing items or bags. Oth- tral range 225–4000− , zero flling factor 0, apodization ers were yarns or threads. Sample of standards were sig- window was Happ-Genzel and number of scans 128. nifcantly larger than needed, in order to be able to map Termo Electron’s OMNIC 9 software was used to col- larger area for our reference spectral collection. Obtained lect and process the IR spectra. ATR-FT-IR spectra were standard spectra were afterwards used for creating classi- recorded directly from the textile piece, textile fber or fcation models. Tis approach was also needed to verify clothing. Sample was placed on the ATR crystal, pressure that the standard samples are homogeneous and do not was applied, and the ATR-FT-IR spectrum was scanned. contain any other fber types or additives. Te measure- Together with the spectra acquired in this work our col- ment area (sampling area) of the specifc sampling tech- lection of ATR-FT-IR spectra contains now altogether niques (see next section of spectrometers’ parameters) is 614 spectra of diferent samples. Peets et al. Herit Sci (2019) 7:93 Page 3 of 10 Classifcation 5 random spectra from each class.
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