ArticleJournal of the American Society for Mass Spectrometry2024
Selectivity of Explosives Analysis with Ambient Ionization Single Quadrupole Mass Spectrometry: Implications for Trace Detection.
Article in Journal of the American Society for Mass Spectrometry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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Who cites it
4 citing papers in PubMed.
- Detection and characterization of explosives and explosives residues: a review 2022-2025.Forensic science international. Synergy · 2026Review
- Advancements in Ambient Ionisation Mass Spectrometry in 2024: An Annual Review.Analytical science advances · 2025Review
- Performance Comparison of Ambient Ionization Techniques Using a Single Quadrupole Mass Spectrometer for the Analysis of Amino Acids, Drugs, and Explosives.Journal of the American Society for Mass Spectrometry · 2024Article
- Rapid, Sensitive, and Versatile: A 5-Year Perspective on Applications of Ambient Ionization Mass Spectrometry in Bioanalytical Science.Mass spectrometry reviewsReview
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ambient ionization (AI) is a rapidly growing field in mass spectrometry (MS). It allows for the direct analysis of samples without any sample preparation, making it a promising technique for the detection of explosives. Previous studies have shown that AI can be used to detect a variety of explosives, but the exact gas-phase reactions that occur during ionization are not fully understood. This is further complicated by differences in mass spectrometers and individual experimental set ups between researchers. This study investigated the gas-phase ion reactions of five different explosives using a variety of AI techniques coupled to a Waters QDa mass spectrometer to identify selective ions for explosive detection and identification based on the applied ambient ionization technique. The results showed that the choice of the ion source can have a significant impact on the number of ions observed. This can affect the sensitivity and selectivity of the data produced. The findings of this study provide new insights into the gas-phase ion reactions of explosives and could lead to the development of more sensitive and selective AI-based methods for their detection.
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Registered trials
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