Enhancing Forensic Evidential Value of Fibers via Single-Fiber Detection and Classification of Fluorinated Oil-and-Water-Repellent Fabric Coatings

Abstract

Fibers are a common form of forensic evidence, however, they cannot be attributed to a single source because of the prevalence of fibers with common attributes. Accordingly, fibers are assigned to a class based on their observed characteristics. To strengthen the evidential value of fibers, new fiber characteristics are considered to reduce the size of fiber classes.

Fluorinated oil-and-water-repellent fabric coatings, popular for imparting stain resistance in fabrics, have interested the forensic community to improve fiber classification. These coatings are visually undetectable and are designed to be durable, which is ideal for fiber comparisons. However, due to the thin nature of the coatings and small sample size of a single fiber, detecting the coatings and distinguishing between various coating types have posed significant analytical challenges, hindering the forensic applications of fiber oil-and-water-repellent treatments. To address this shortcoming, we develop a new analytical approach to detect and characterize the fluorinated oil-and-water-repellent coatings at a single fiber level. The technique is then applied to evaluate the diversity of the coatings and their detectability upon aging.

Our studies show that pyrolysis gas chromatography plasma assisted reaction chemical ionization mass spectrometry (py-GC-PARCI-MS) enables facile detection of fluorinated pyrolysates from fibers. We demonstrate detection of fluorinated coatings from 10 mm single fibers, a necessary achievement for implementation in forensic casework. Importantly, py-GC-PARCI-MS also enables discrimination between different fluoropolymer coatings based on pyrogram patterns. To gain insights into the prevalence and diversity of the coatings, py-GC-PARCI-MS is applied to screening nine oil-and-water-repellent garments marketed as stain repellent. Fluorinated pyrolysates are detected on all nine clothing items, demonstrating the prevalence of these coatings. Further, multiple coating types are identified based on pyrogram patterns, enhancing the forensic value of fluoropolymer detection by py-GC-PARCI-MS.

Finally, we show that fiber sampling with adhesives, often used for fiber collection in crime scenes, as well as outdoor aging and laundering of fabrics do not interfere with detection and classification of the fluorinated coatings on single fibers using py-GC-PARCI-MS. These results establish fluoropolymer fabric coatings as robust fiber identifiers for enhanced fiber comparisons and highlight the strengths of elemental detection in forensic analyses.