Machine learning approaches over ion mobility spectra for the discrimination of ignitable liquids residues from interfering substrates
In arson fires, ignitable liquids (ILs) are frequently used to start combustion. For this reason, detecting IL residues (ILRs) at the fire scene is a key factor in fire investigation to determine whether a crime has been committed as well as to establish the modus operandi of the perpetrator. In the...
Main Authors: | José Luis P. Calle, Barbara Falatová, María José Aliaño-González, Marta Ferreiro-González, Miguel Palma |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2022-12-01
|
Series: | Talanta Open |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2666831922000431 |
Similar Items
-
Discrimination of Ignitable Liquid Residues in Burned Petroleum-Derived Substrates by Using HS-MS eNose and Chemometrics
by: Barbara Falatová, et al.
Published: (2021-01-01) -
Effects of Fire Suppression Agents and Weathering in the Analysis of Fire Debris by HS-MS eNose
by: Barbara Falatová, et al.
Published: (2018-06-01) -
Characterization of Biodegraded Ignitable Liquids by Headspace–Ion Mobility Spectrometry
by: José Luis P. Calle, et al.
Published: (2020-10-01) -
Detection and Characterization of Ignitable Liquid Residues in Forensic Fire Debris Samples by Comprehensive Two-Dimensional Gas Chromatography
by: Andjoe A. S. Sampat, et al.
Published: (2018-08-01) -
A Novel Method Based on Headspace-Ion Mobility Spectrometry for the Detection and Discrimination of Different Petroleum Derived Products in Seawater
by: Lucas Jaén-González, et al.
Published: (2021-03-01)