Synthesis route attribution of sulfur mustard by multivariate data analysis of chemical signatures

Application of chemical attribution in matching OPNAs-exposed biological samples with exposure sources- based on the impurity profiles via GC × GC-TOFMS analysis

Chemical attribution is a vital tool to attribute chemicals or related materials to their origins in chemical forensics via various chemometric methods. Current progress related to organophosphorus nerve agents (OPNAs) has mainly focused on the attribution of chemical sources and synthetic pathways. It has not yet been applied in matching exposed biological samples to their sources. This work used chemical attribution to explore organic impurity profiles in biological samples exposed to various OPNAs. Chemical attribution was first used to identify the exposure source of biological samples based on the full-scan data via comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometer (GC × GC-TOFMS). Taking peak area as the only variable, it can quickly match exposed samples to their sources by applying unsupervised or supervised models, screen difference compounds via one-way ANOVA or t-tests, and then identify valuable impurities that can distinguish different types of exposed samples. To further obtain the impurity profile only applicable to a certain weapon' samples, the irrelevant components were removed via conventional methods. The findings showed there were 53 impurities that can promote distinguishing six groups of OPNA exposed samples, as well as 42 components that can be used as valuable impurities to distinguish class G and class V samples. These were all unique impurities that appear in a certain weapon' samples. The outcomes can be a reference for tracing the source for OPNA-exposed samples, which was beneficial to the further development in source matching of forensic samples. Moreover, the chemical attribution for impurity profiles in biological samples after weapons exposure may inspire research into the characteristics of impurity profile in biological samples as well as practical applications of chemical attribution for OPNA-exposed samples, that may expand potential biomarkers and break the limits of existing markers in the future.

Chemical forensic profiling and attribution signature determination of sarin nerve agent using GC-MS, LC-MS and NMR

Sarin is a highly toxic nerve agent classified by the Chemical Weapon Convention as a Schedule 1 chemical with no use other than to kill or injure. Moreover, in recent times, chemical warfare agents have been deployed against both military and civilian populations. Chemical warfare agents always contain minor impurities that can provide important chemical attribution signatures (CAS) that can aid in forensic investigations. In order to understand the trace molecular composition of sarin, various analytical approaches including GC-MS, LC-MS and NMR were used to determine the chemical markers of a set of sarin samples. Precursor materials were studied and the full characterisation of a synthetic process was undertaken in order to provide new insights into potential chemical attribution signatures for this agent. Several compounds that were identified in the precursor were also found in the sarin samples linking it to its method of preparation. The identification of these CAS contributes critical information about a synthetic route to sarin, and has potential for translation to related nerve agents.

Source Attribution of the Chemical Warfare Agent Soman Using Position-Specific Isotope Analysis by 2H NMR Spectroscopy: From Precursor to Degradation Product

Position-specific isotope analysis (PSIA) by NMR spectroscopy is a technique that provides quantitative isotopic values for every site—a so-called isotopic fingerprint—of a compound of interest. The isotopic fingerprint can be used to link samples with a common origin or to attribute a synthetic chemical to its precursor source. Despite PSIA by NMR being a powerful tool in chemical forensics, it has not yet been applied on chemical warfare agents (CWAs). In this study, different batches of the CWA Soman were synthesized from three distinctive pinacolyl alcohols (PinOHs). Prior to NMR analysis, the Soman samples were hydrolyzed to the less toxic pinacolyl methylphosphonate (PMP), which is a common degradation product. The PinOHs and PMPs were applied to PSIA by ²H NMR experiments to measure the isotopic distribution of naturally abundant ²H within the pinacolyl moiety. By normalizing the ²H NMR peak areas, we show that the different PinOHs have unique intramolecular isotopic distributions. This normalization method makes the study independent of references and sample concentration. We also demonstrate, for the first time, that the isotopic fingerprint retrieved from PSIA by NMR remains stable during the production and degradation of the CWA. By comparing the intramolecular isotopic profiles of the precursor PinOH with the degradation product PMP, it is possible to attribute them to each other.

Forensic signatures of a chemical weapon precursor DMPADC for determination of a synthetic route

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.

Mass spectrometric analysis of adducts of sulfur mustard analogues to human plasma proteins: approach towards chemical provenancing in biomedical samples

The primary aim of this study was to identify biomarkers of exposure to some so-called Schedule 1 sulfur mustard (HD) analogues, in order to facilitate and expedite their retrospective analysis in case of alleged use of such compounds. Since these HD analogues can be regarded as model compounds for possible impurities of HD formed during synthesis processes, the secondary aim was to explore to which extent these biomarkers can be used for chemical provenancing of HD in case biomedical samples are available. While the use of chemical attribution signatures (CAS) for neat chemicals or for environmental samples has been addressed quite frequently, the use of CAS for investigating impurities in biomedical samples has been addressed only scarcely. Human plasma was exposed to each of the five HD analogues. After pronase or proteinase K digestion of precipitated protein and sample work-up, the histidine (His) and tripeptide (CPF) adducts to proteins were analyzed, respectively. Adducts of the analogues could still be unambiguously identified next to the main HD adducts in processed plasma samples after exposure to HD mixed with each of the analogues, at a 1% level relative to HD. In conclusion, we have identified plasma protein adducts of a number of HD analogues, which can be used as biomarkers to assess an exposure to these Schedule 1 chemicals. We have shown that adducts of these analogues can still be analyzed after work-up of plasma samples which had been exposed to these analogues in a mixture with HD, supporting the hypothesis that biomedical sample analysis might be useful for chemical provenancing.

Route Determination of Sulfur Mustard Using Nontargeted Chemical Attribution Signature Screening

Route determination of sulfur mustard was accomplished through comprehensive nontargeted screening of chemical attribution signatures. Sulfur mustard samples prepared via 11 different synthetic routes were analyzed using gas chromatography/high-resolution mass spectrometry. A large number of compounds were detected, and multivariate data analysis of the mass spectrometric results enabled the discovery of route-specific signature profiles. The performance of two supervised machine learning algorithms for retrospective synthetic route attribution, orthogonal partial least squares discriminant analysis (OPLS-DA) and random forest (RF), were compared using external test sets. Complete classification accuracy was achieved for test set samples (2/2 and 9/9) by using classification models to resolve the one-step routes starting from ethylene and the thiodiglycol chlorination methods used in the two-step routes. Retrospective determination of initial thiodiglycol synthesis methods in sulfur mustard samples, following chlorination, was more difficult. Nevertheless, the large number of markers detected using the nontargeted methodology enabled correct assignment of 5/9 test set samples using OPLS-DA and 8/9 using RF. RF was also used to construct an 11-class model with a total classification accuracy of 10/11. The developed methods were further evaluated by classifying sulfur mustard spiked into soil and textile matrix samples. Due to matrix effects and the low spiking level (0.05% w/w), route determination was more challenging in these cases. Nevertheless, acceptable classification performance was achieved during external test set validation: chlorination methods were correctly classified for 12/18 and 11/15 in spiked soil and textile samples, respectively.

Investigating the chemical impurity profiles of fentanyl preparations and precursors to identify chemical attribution signatures for synthetic method attribution

From an analytical chemistry standpoint, determining the chemical attribution signatures (CAS) of synthetic reaction mixtures is an impurity profiling exercise. Identifying and understanding the impurity profile and CAS of these chemical agents would allow them to be exploited for chemical forensic information, such as how a particular chemical agent was synthesised. Being able to determine the synthetic route used to make a chemical agent allows for the possibility of batches of the agent, and individual incidents using that agent, to be forensically linked. This information is of particular benefit to agencies investigating the nefarious and illicit use of chemical agents. One such chemical agent of interest to law enforcement and national security agencies is fentanyl. In this study two acylation methods for the final step of fentanyl production, herein termed the Janssen and Siegfried methods, were investigated by liquid chromatography- high resolution mass spectrometry (LC-HRMS) and multivariate statistical analysis (MVA). From these data, fifty-five chemical impurities were identified. Of these, ten were specific CAS for the Janssen method, and five for the Siegfried method. Additionally, analytical data from four different literature methods for production of the fentanyl precursor 4-anilino-N-phenethylpiperidine (ANPP), were compared to the results obtained from the method of production (Valdez) used in this study. Comparison of the LC-HRMS data for these five methods allowed for four Valdez specific impurities to be identified. These may be useful CAS for the Valdez method of ANPP production.