Volume 64, Issue 5 pp. 1486-1494
Technical Note

Detection and Classification of Ignitable Liquid Residues in the Presence of Matrix Interferences by Using Direct Analysis in Real Time Mass Spectrometry,

Isabella Barnett B.S.

Isabella Barnett B.S.

Forensic Science Program, College of Basic and Applied Sciences, Middle Tennessee State University, Murfreesboro, TN, 37132

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Frank C. Bailey Ph.D.

Frank C. Bailey Ph.D.

Forensic Science Program, College of Basic and Applied Sciences, Middle Tennessee State University, Murfreesboro, TN, 37132

Department of Biology, Middle Tennessee State University, Murfreesboro, TN, 37132

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Mengliang Zhang Ph.D.

Corresponding Author

Mengliang Zhang Ph.D.

Forensic Science Program, College of Basic and Applied Sciences, Middle Tennessee State University, Murfreesboro, TN, 37132

Department of Chemistry, Middle Tennessee State University, Murfreesboro, TN, 37132

Corresponding author: Mengliang Zhang, Ph.D. E-mail: [email protected]Search for more papers by this author
First published: 21 February 2019
Citations: 27
Accepted for presentation at the 71st Annual Scientific Meeting of the American Academy of Forensic Sciences, February 18-23, 2019, in Baltimore, MD.
Supported by startup fund to Mengliang Zhang from Middle Tennessee State University (MTSU). MTSU Undergraduate Research Experience and Creative Activity (URECA) grant is acknowledged for the support to Isabella Barnett.

Abstract

Conventional Gas Chromatography-Mass Spectrometry (GC-MS) methods for the analysis of ignitable liquids (ILs) are usually time-consuming, and the data produced are difficult to interpret. A fast IL screening method using direct analysis in real time mass spectrometry (DART-MS) is proposed in this study. GC-MS, QuickStrip DART-MS, and thermal desorption DART-MS methods were used to analyze neat ILs and thermal desorption DART-MS without extraction was used to analyze ILs on five substrates (e.g., carpet, wood, cloth, sand, and paper). Compared to GC-MS, DART-MS methods generated different spectral profiles for neat ILs with more peaks in the higher mass range and also provided better detection of less volatile compounds. ILs on substrates were successfully classified (98 ± 1%) using partial least squares discriminant analysis (PLS-DA) models based on thermal desorption DART-MS data. This study shows that DART-MS has great potential for the high-throughput screening of ILs on substrates.

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