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The characterization of disperse dyes in polyester fibers using DART mass spectrometry

NCJ Number
305233
Journal
Journal of Forensic Sciences Volume: Online Dated: September 2022
Author(s)
Zoe Millbern; Nelson R. Vinueza
Date Published
September 2022
Length
8 pages
Annotation

This study has characterized a collection of commercially available textiles dyes by verifying the chemical structure, collecting reference spectra, and developing a method to analyze dyed fibers via Direct Analysis in Real-Time (DART) mass spectrometry.

 

Abstract

Textile fibers alone are highly prevalent in our environment, and not only are there a wide variety of fibers, but generally, consumer textiles are colored. Given the variety of crime locations where dyes are encountered and the potential circumstances, a rapid, preparation free analysis of samples is highly beneficial. A methodology for direct analysis of pieces of fabric and single thread samples of polyester fibers dyed with disperse dyes was developed in this project. The presence of 31 target dyes on fibers whose structures were previously established via high-resolution mass spectrometry was confirmed. Dyed fabrics containing mixtures of dyes in varying concentrations were also evaluated to determine whether each dye in the composition could be detected. The DART-MS methodology was sensitive and positively characterized disperse dyes in polyester fibers, allowing for blind identification of mixtures with the assistance of a high-resolution mass spectrometry database. A methodology for direct analysis of pieces of fabric and single thread samples of polyester fibers dyed with disperse dyes was developed. The presence of 31 target dyes on fibers whose structures were previously established via high-resolution mass spectrometry was confirmed. Dyed fabrics containing mixtures of dyes in varying concentrations were also evaluated to determine whether each dye in the composition could be detected. The DART-MS methodology was sensitive and positively characterized disperse dyes in polyester fibers, allowing for blind identification of mixtures with the assistance of a high-resolution mass spectrometry database. (Publisher abstract provided)

 

Date Published: September 1, 2022