Chemical forensics has been widely recognized as an important tool to investigate alleged use of chemical weapons and/or to identify the illicit production of chemical warfare agents. This paper describes the use of gas chromatography and mass spectrometry (GC-MS) to determine chemical attribution signatures (CAS) N,N -dimethylphosphoramidic dichloride (DMPADC), a key precursor of tabun, for tracking the production of tabun. Synthetic samples were identified and classified by using GC-MS and chemometrics . Analysis samples (n = 27) were collected from three synthetic DMPADC routes; 20 potential CAS were identified, and the structures of five CAS were assigned. Principal component analysis (PCA) was performed to summarize the distribution trend of the samples and to check for the presence of outliers. A Partial least squares discriminant analysis (PLSDA) model was established to discriminate and classify the synthetic samples. The proposed model in this paper has high predictive ability, and the test set samples can be correctly categorized.
A route determination strategy through non-targeted screening of chemical attribution signatures was developed to identify tabun samples from three different synthetic routes. The CAS profiles of tabun samples were obtained by comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometer (GC×GC-TOFMS). The structures of 109 CAS were identified by NIST library and mass spectrometry fragment analysis. A few identified compounds could be traced to impurities in precursor compounds used in tabun synthesis. Based on the gas chromatography/mass spectrometry peak data of the selected CAS, partial least squares-discriminant analysis (PLS-DA) was used to extract the chemical attribution signatures of the characteristic compounds. The trained PLS-DA model performed well, with the lowest specificity and sensitivity values of 1.000 and 0.882, respectively. The performance of the PLS-DA model was further verified by unknown sample test set. The model demonstrated its ability to differentiate all the unknown tabun samples. The stability of chemical attribution signatures from different time periods was also investigated, and was further evaluated.
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