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.

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.

The identification of chemical attribution signatures of stored VX nerve agents using NMR, GC-MS, and LC-HRMS.

The organophosphorous nerve agent VX is classified by the Chemical Warfare Convention (CWC) as a Schedule 1 chemical; namely a substance that is highly toxic with no use that is of benefit to society. Even with this classification, the nefarious use of the Schedule 1 chemical VX has been observed, as demonstrated in 2017 in Malaysia. Therefore, undertaking chemical analysis on samples of VX to identify chemical attribution signatures (CAS) for chemical forensics is required. To further understand the chemical profile of VX, and to aid in the identification of potential CAS, three in house synthesised stocks of VX were investigated. The three VX stocks analysed were synthesised in 2014, 2017 and 2018 using the same method, allowing for a comparison of data between each of the stocks at different stages of storage. As opposed to a majority of literature reports, these agent stocks were not stabilised, nor were they subjected to forced degradation. Using NMR, high resolution (HR) LC-HRMS, GC-(EI)MS and GC-(CI)MS to gain a full insight into the CAS profile, a total of 44 compounds were identified. Of these compounds, 30 were readily identified through accurate mass measurement and NIST library matches. A further seven were identified through extensive LC-HRMS/MS studies, with seven remaining unresolved. Several compounds, identified in minor amounts, were able to be traced back to impurities in the precursor compounds used in the synthesis of VX, and hence may be useful as CAS for source attribution.

Multidimensional gas chromatography of oxidative degradation products in algae-derived fuel oil samples using narrow heartcuts and rapid cycle times.

To characterize a fuel's thermal and storage stability an understanding of the process of oxidation and oxidation pathways is essential. Oxidation pathways commence with hydroperoxides which quickly decompose to form a range of alcohols, acids and other oxygen-containing species. In the presence of significant levels of hydrocarbon-based matrix, analysis of these heteroatomic species is difficult. Applying multidimensional gas chromatography with very narrow heart-cut windows (0.20 min) minimizes the number of compounds transferred to the second dimension (2D) column during each heart-cut. Successive heart-cuts every 2.00 min are taken throughout the analytical run, since each heart-cut has a maximum retention on 2D of <2.00 min on the fast elution 2D column. Subsequent analyses involve incrementing or offsetting the heart-cut windows by 0.20 min, so after 10 analyses, a complete coverage of the sample components can be obtained. On the polar 1D and non-polar 2D phase column arrangement, non-polar matrix compounds elute last on the 2D column, and this determines the largest (2t)R; i.e., (2t)R < P(M) to ensure retained components on 2D will not overlap with subsequent heart-cuts. Heartcutting is supported by cryotrapping at the start of the 2D column in order to provide significantly better resolution. Good quality MS library match data generally demonstrate the high resolution separation of oxygenates achieved. Whilst 1D GC-MS was unsuccessful in identifying any of the oxygen-containing compounds reported here, good correlation of MS data (with average MS library similarity data) for acids (903), alcohols (909), ketones (941) and aldehydes (938) in the sample is obtained. The method requires ten sequential runs, and this can be accomplished automatically once the events table is set up. However if fewer target compounds are to be transferred, a reduced number of sequential runs can be implemented.