Classifying single fibers based on fluorinated surface treatments
Fibers are an important form of forensic evidence, but their evidential value can be severely limited when the identified characteristics of the fibers are common, such as blue cotton. Detecting chemical fiber treatments offers an avenue to further classify fibers and to improve their evidential value. In this report, we investigate the potential of fluoropolymer fiber coatings, used to impart oil and water-repellent properties in fabrics, for differentiating between fibers. The thin nature of these fiber surface modifications creates an analytical challenge for their detection on a single fiber, a typical sample size for forensic evidence. Specifically, pyrolysis-gas chromatography-mass spectrometry (py-GC-MS) has shown promising selectivity but the sensitivity of the method is not adequate for single-fiber analysis of fluorinated coatings. To overcome this challenge, we utilize a newly developed elemental ionization source, plasma-assisted reaction chemical ionization (PARCI). The high sensitivity of py-GC-PARCI-MS for elemental fluorine analysis offers selective and sensitive detection of fluorinated pyrolysates among the non-fluorinated pyrolysates of the fiber core. As a result, fluoropolymer coatings are detected from 10-mm single-fiber samples. The technique is applied for classification of 22 fiber types, resulting in 4 distinct groups via hierarchical cluster analysis based on similarity of fluorine pyrograms. These results present the first study to classify fibers based on fluorinated coatings, and highlight the potential of py-GC-PARCI-MS for forensic analyses.
KeywordsElemental mass spectrometry Forensic Fiber coating Fluorine
We thank PerkinElmer Inc. for providing the GC, the microwave plasma generator, and the MS used in these studies. We would also like to thank Testfabrics, Huntsman, Pulcra, Sears, JOANN, Cornerstone Technology, Daikin, Rudolf Venture, and Zara Hall for providing coating emulsions, coated fibers, and sprays. We are grateful to Eldana Tadesse for the assistance in data collection for some of the samples.
This project was supported by Award No. 2017-R2-CX-0007, awarded by the National Institute of Justice, Office of Justice Programs, U.S. Department of Justice. The opinions, findings, and conclusions or recommendations expressed in this publication/program/exhibition are those of the author(s) and do not necessarily reflect those of the Department of Justice. Major instrumentation was provided by PerkinElmer Inc.
Compliance with ethical standards
Conflict of interest
Kaveh Jorabchi is an inventor of PARCI (US patent 9966243). All other authors declare no conflict of interest.
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