The identification of polyester fibers dyed with disperse dyes for forensic purposes
Daria Śmigiel-Kamińska , Jan Pośpiech , Joanna Makowska , Piotr Stepnowski , Jolanta Wąs-Gubała , Jolanta Kumirska
AbstractIn forensic laboratories, the most commonly analyzed microtraces are microscopic fragments of single fibers. One of the main goals of the examination of fragments of fibers a few millimeters long is to determine their characteristic physicochemical properties and compare them with fibers originating from a known source (e.g., a suspect’s clothes). The color and dyes of fiber microtraces play an important role in their research and evaluation, being analyzed by means of microscopic, spectroscopic, and chromatographic methods. The results of examinations conducted with the use of spectroscopic techniques might be ambiguous due to overlapping bands of absorption and the transmission and dispersion of electromagnetic radiation corresponding to the specific chemical structure of the fibers and their dyes. For this reason, it is very important to improve currently available spectroscopic methods and/or to propose new ones that allow evidential materials to be analyzed in a much more reliable way. In this review, the possibility of the use of chromatographic techniques with different detection systems for such analyses is underlined. This review covers the different analytical methods used in the forensic analysis of polyester fibers dyed with disperse dyes. Polyester fibers occupy the first position among synthetic fibers in their use for a variety of purposes, and disperse dyes are commonly applied for dyeing them.
|Journal series||Molecules, ISSN 1420-3049, (A 30 pkt)|
|Keywords in English||polyester fibers, dyed fibers, disperse dyes, forensic analysis, chromatographic methods, spectroscopic methods|
|License||Journal (articles only); published final; ; with publication|
|Score|| = 30.0, 04-04-2019, ArticleFromJournal|
= 30.0, 04-04-2019, ArticleFromJournal
|Publication indicators||= 0; : 2017 = 1.146; : 2017 = 3.098 (2) - 2017=3.268 (5)|
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