Rapid multivariate curve resolution applied to identification of explosives by ion mobility spectrometry

被引:47
作者
Buxton, TL [1 ]
Harrington, PD [1 ]
机构
[1] Ohio Univ, Ctr Intelligent Chem Instrumentat, Clippinger Labs, Dept Chem & Biochem, Athens, OH 45701 USA
关键词
ion mobility spectrometry; SIMPLISMA; thermal desorption; PETN; HMX;
D O I
10.1016/S0003-2670(01)00839-X
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Ion mobility spectrometers (IMS) are routinely used by airport personnel to screen for explosive residues on luggage, and law enforcement officials use ion mobility spectrometers to screen samples at crime scenes for drugs of abuse. IMS has several advantages when screening which include high sensitivity, low detection limits, and short analysis times. The Barringer Ionscan (R) 350, coupled to LabVIEW (TM) for data acquisition, can collect 50 spectra per second. These features are very important because of the high throughput demanded for screening luggage. Carry-on luggage in airports undergoes screening for explosive residues by swiping a small filter over the surface. The filter is then inserted into the spectrometer and analyzed. Results of the analysis are available in a matter of seconds. The detection method used must be accurate and rapid because of the large number of samples that must be analyzed in short periods. Unfortunately, IMS spectra can contain interferents because of the sample collection method. Rapid temperature programming coupled with chemometrics has been shown as a useful tool for the separation of analytes from interferents. Pentaerythritol tetranitrate (PETN) and cyclotetramethylene tetranitrate (HMX) are nonvolatile explosives. They decompose rapidly upon heating, making traditional analyses by gas chromatography difficult. In this work, PETN and HMX with interfering compounds were analyzed using rapid temperature programming. The Barringer Ionscan (R) 350, was modified so that the desorber heater could be programmed and the spectra acquired in real-time. Simple-re-use interative self-modeling mixture analysis (SIMPLISMA) was applied to the data to resolve spectral features that vary with respect to temperature. (C) 2001 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:269 / 282
页数:14
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