Forensic Analysis of Polymeric Carpet Fibers Using Direct Analysis in Real Time Coupled to an AccuTOF™ Mass Spectrometer

Polymeric fibers are encountered in numerous forensic circumstances. This study focused on polymeric carpet fibers most encountered at a crime scene, which are nylons, polyesters and olefins. Analysis of the multiple polymer types was done using Direct Analysis in Real Time (DART™) coupled to an Accurate time-of-flight (AccuTOF™) mass spectrometer (MS). A DART gas temperature of 275 °C was determined as optimal. Twelve olefin, polyester, and nylon polymer standards were used for parameter optimization for the carpet fiber analysis. A successful identification and differentiation of all twelve polymer standards was completed using the DART-AccuTOF™. Thirty-two carpet samples of both known and unknown fiber composition were collected and subsequently analyzed. All samples with known fiber compositions were correctly identified by class. All of the remaining carpet samples with no known composition information were correctly identified by confirmation using Fourier-transform infrared spectroscopy (FTIR). The method was also capable of identifying sub-classes of nylon carpet fibers. The results exhibit the capability of DART-AccuTOF™ being applied as an addition to the sequence of tests conducted to analyze carpet fibers in a forensic laboratory.

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Accurate Mass Measurements With a Reflectron Time-of-Flight Mass Spectrometer and the Direct Analysis in Real Time (DART) Interface for the Identification of Unknown Compounds below Masses of 500 DA

Liquid Chromatography Time-of-Flight Mass Spectrometry ◽

10.1002/9780470429969.ch13 ◽

2008 ◽

pp. 229-245 ◽

Cited By ~ 2

Author(s):

O. David Sparkman ◽

Patrick R. Jones ◽

Matthew Curtis

Keyword(s):

Real Time ◽

Mass Spectrometer ◽

Time Of Flight ◽

Direct Analysis ◽

Accurate Mass ◽

Mass Measurements ◽

Flight Mass Spectrometer ◽

Accurate Mass Measurements ◽

Identification Of Unknown Compounds

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Timber species identification from chemical fingerprints using direct analysis in real time (DART) coupled to Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS): comparison of wood samples subjected to different treatments

Holzforschung ◽

10.1515/hf-2018-0304 ◽

2019 ◽

Vol 73 (11) ◽

pp. 975-985 ◽

Cited By ~ 2

Author(s):

Maomao Zhang ◽

Guangjie Zhao ◽

Juan Guo ◽

Alex C. Wiedenhoeft ◽

Charles C. Liu ◽

...

Keyword(s):

Mass Spectrometry ◽

Fourier Transform ◽

Statistical Analysis ◽

Real Time ◽

Cyclotron Resonance ◽

Direct Analysis ◽

Species Level ◽

Ion Cyclotron Resonance ◽

Timber Species ◽

Fticr Ms

Abstract Timber genus identification based on the anatomical features of wood is well established in botany. However, species-level wood identification is not always possible based on traditional wood morphology techniques alone. To compensate for the deficiencies of traditional methods, direct analysis in real time coupled to Fourier transform ion cyclotron resonance mass spectrometry (DART-FTICR-MS) was used to obtain the mass spectral fingerprints of different timber species. Using heartwood samples of two morphologically similar species, Pterocarpus santalinus and Pterocarpus tinctorius, subjected to different treatments, i.e. solvent extractions and powdered samples as well as air-dried samples and samples dried at low and high temperatures, we observed distinct chemical signatures for the wood samples from the two species, enabling rapid species-level identification when multivariate statistical analysis was adopted. The supervised orthogonal partial least squares discriminant analysis (OPLS-DA) models for samples subjected to different treatments all exhibited accurate differentiation performance of the explained fraction of variance of classes (R2Y = 0.936–0.987) and the cross-validated fraction of variance of classes (Q2 = 0.857–0.949). Compared with solvent types and the physical form of the sample, the drying treatment method had a greater impact on the chemical fingerprint from DART-FTICR-MS. Air-dried wood chips were the optimal samples for the DART-FTICR-MS method coupled with statistical analysis.

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