Projects per year
Abstract
Swabs taken from the surface of a suspicious object are a standard method of identifying a concealed explosive device in security-conscious locations like airports. In this paper we demonstrate a sensitive method to collect and detect trace explosive residues from improvised explosive devices using swabs and an optical sensor element. Swabs coated with a commercial fluoropolymer are used to collect material and are subsequently heated to thermally desorb the explosives, causing the quenching of light emission from a thin film luminescent sensor. We report the sorption and desorption characteristics of swabs loaded with 2,4-DNT tested with Super Yellow fluorescence sensors in a laboratory setting, with detection that is up to three orders of magnitude more sensitive than standard colorimetric tests. The method was then applied in field tests with raw military-grade explosives TNT, PETN and RDX, on various objects containing the explosives, and post-blast craters. We show for the first time results using organic semiconductors to detect sub-milligram amounts of explosive sorbed onto a substrate from real explosives in the field, giving a promising new approach for IED detection.
Original language | English |
---|---|
Number of pages | 8 |
Journal | Analyst |
Early online date | 5 Oct 2020 |
DOIs | |
Publication status | E-pub ahead of print - 5 Oct 2020 |
Keywords
- Nitroaromatic
- Organic semiconductor
- Luminescence quenching
- Fluoropolymer
- Optical sensing
- Super Yellow
Fingerprint
Dive into the research topics of 'Explosives detection by swabbing for improvised explosive devices'. Together they form a unique fingerprint.Projects
- 1 Finished
-
EPSRC IAA 2017-2020 G Turnbull: Adaptation of Landmine Detection research for Counter-IED applications; engagement with C-IED stakeholders
Turnbull, G. (PI) & Gillanders, R. (CoI)
1/10/17 → 30/11/19
Project: Standard
Datasets
-
Explosives Detection by Swabbing for Improvised Explosive Devices (dataset)
Gillanders, R. (Creator) & Glackin, J. M. E. (Creator), University of St Andrews, 5 Oct 2020
DOI: 10.17630/995a56e4-d61e-4d27-b192-e73db61c7818
Dataset
File