期刊
TALANTA
卷 186, 期 -, 页码 615-621出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.talanta.2018.02.100
关键词
Chemical forensics; Multivariate data analysis; Sulfur mustard; Synthesis method attribution
资金
- Swedish Civil Contingencies Agency, Sweden [2014-5170]
- Department of Homeland Security, Science and Technology Directorate, Chemical Biological Division, United States [HSHQPM-16-X-00102]
- U.S. Department of Energy, National Nuclear Security Administration [DE-AC52-07NA27344]
A multivariate model was developed to attribute samples to a synthetic method used in the production of sulfur mustard (HD). Eleven synthetic methods were used to produce 66 samples for model construction. Three chemists working in both participating laboratories took part in the production, with the aim to introduce variability while reducing the influence of laboratory or chemist specific impurities in multivariate analysis. A gas chromatographic/mass spectrometric data set of peak areas for 103 compounds was subjected to orthogonal partial least squares - discriminant analysis to extract chemical attribution signature profiles and to construct multivariate models for classification of samples. For one-and two-step routes, model quality allowed the classification of an external test set (16/16 samples) according to synthesis conditions in the reaction yielding sulfur mustard. Classification of.samples according to first-step methodology was considerably more difficult, given the high purity and uniform quality of the intermediate thiodiglycol produced in the study. Model performance in classification of aged samples was also investigated.
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