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A New Library-Search Algorithm for Mixture Analysis Using DART-MS

NCJ Number
Journal of the American Society for Mass Spectrometry Volume: 32 Issue: 7 Dated: June 17, 2021 Pages: 1725-1734
Date Published
June 2021
10 pages

This paper introduces a new library-search algorithm that improves presumptive identifications of mixture components using a series of in-source collision-induced dissociation mass spectra collected through direct analysis in real time mass spectrometry (DART-MS).


The multistage search, titled the Inverted Library-Search Algorithm (ILSA), identifies potential components in a mixture by first searching the lowest fragmentation mass spectrum for target peaks, assuming these peaks are protonated molecules, and then scoring each target peak with possible library matches. As a proof of concept, the ILSA is demonstrated through several example searches of model seized drug mixtures of acetyl fentanyl, benzyl fentanyl, amphetamine, and methamphetamine searched against a small library of select compounds and the freely available NIST DART-MS Forensics Database. Discussion of the search results and several open areas of research to further extend the method are provided. This new approach for presumptive identification provides analysts with refined information about mixture components and will be of immediate importance in forensic analysis using DART-MS. A prototype implementation of the ILSA is available at https://github.com/asm3-nist/DART-MS-DST. (Published abstract provided)

Date Published: June 1, 2021