PLEASE NOTE: Due to a planned systems upgrade, purchase orders submitted after 10:00 a.m. ET, Friday, April 23, will not be processed until 8:00 a.m. ET, Monday, April 26. We apologize for the inconvenience.
Your web browser will no longer be supported by Restek.com as of 30 June 2021.
To avoid any interruption in access or functionality, install a current-generation web browser now. Learn more.

Achieving a Near-Theoretical Maximum in Peak Capacity Gain for the Forensic Analysis of Ignitable Liquids Using GC×GC-TOFMS

  • Share:

Author (s): Katie D. Nizio 1, Jack W. Cochran 2, and Shari L. Forbes 1

  1. Centre for Forensic Science, University of Technology Sydney
  2. Restek Corporation

Published By: Separations

Issue: Volume 3, Issue 3

Year of Publication: 2016

Link: 10.3390/separations3030026

Abstract:

At present, gas chromatography–quadrupole mass spectrometry (GC-qMS) is considered the gold standard amongst analytical techniques for fire debris analysis in forensic laboratories worldwide, specifically for the detection and classification of ignitable liquids. Due to the highly complex and unpredictable nature of fire debris, traditional one-dimensional GC-qMS often produces chromatograms that display an unresolved complex mixture containing only trace levels of the ignitable liquid among numerous background pyrolysis products that interfere with pattern recognition necessary to verify the presence and identification of the ignitable liquid. To combat these challenges, this study presents a method optimized to achieve a near-theoretical maximum in peak capacity gain using comprehensive two-dimensional gas chromatography (GC×GC) coupled to time-of-flight mass spectrometry (TOFMS) for the forensic analysis of petroleum-based ignitable liquids. An overall peak capacity gain of ~9.3 was achieved, which is only ~17% below the system’s theoretical maximum of ~11.2. In addition, through the preservation of efficient separation in the first dimension and optimal stationary phase selection in the second dimension, the presented method demonstrated improved resolution, enhanced sensitivity, increased peak detectability and structured chromatograms well-suited for the rapid classification of ignitable liquids. As a result, the method generated extremely detailed fingerprints of petroleum-based ignitable liquids including gasoline, kerosene, mineral spirits and diesel fuel. The resultant data was also shown to be amenable to chromatographic alignment and multivariate statistical analysis for future evaluation of chemometric models for the rapid, objective and automated classification of ignitable liquids in fire debris extracts.

GNOT3357-UNV