Quantification of trace transformation products of rocket fuel unsymmetrical dimethylhydrazine in sand using vacuum-assisted headspace solid-phase microextraction

Validation of the identification reliability of known and assumed UDMH transformation products using gas chromatographic retention indices and machine learning

Thirty two commercially available standards were used to determine chromatographic retention indices for three different stationary phases (non-polar, polar and mid-polar) commonly used in gas chromatography. The selected compounds were nitrogen-containing heterocycles and amides, which are referred to in the literature as unsymmetrical dimethylhydrazine (UDMH) transformation products or its assumed transformation products. UDMH is a highly toxic compound widely used in the space industry. It is a reactive substance that forms a large number of different compounds in the environment. Well-known transformation products may exceed UDMH itself in their toxicity, but most of the products are poorly investigated, while posing a huge environmental threat. Experimental retention indices for the three stationary phases, retention indices from the NIST database, and predicted retention indices are presented in this paper. It is shown that there are virtually no retention indices for UDMH transformation products in the NIST database. In addition, even among those compounds for which retention indices were known, inconsistencies were identified. Adding retention indices to the database and eliminating erroneous data would allow for more reliable identification when standards are not available. The discrepancies identified between experimental retention index values and predicted values will allow for adjustments to the machine learning models that are used for prediction. Previously proposed compounds as possible transformation products without the use of standards and NMR method were confirmed.

Intelligent Workflow and Software for Non-Target Analysis of Complex Samples Using a Mixture of Toxic Transformation Products of Unsymmetrical Dimethylhydrazine as an Example

Unsymmetrical dimethylhydrazine (UDMH) is a widely used rocket propellant. Entering the environment or being stored in uncontrolled conditions, UDMH easily forms an enormous variety (at least many dozens) of transformation products. Environmental pollution by UDMH and its transformation products is a major problem in many countries and across the Arctic region. Unfortunately, previous works often use only electron ionization mass spectrometry with a library search, or they consider only the molecular formula to propose the structures of new products. This is quite an unreliable approach. It was demonstrated that a newly proposed artificial intelligence-based workflow allows for the proposal of structures of UDMH transformation products with a greater degree of certainty. The presented free and open-source software with a convenient graphical user interface facilitates the non-target analysis of industrial samples. It has bundled machine learning models for the prediction of retention indices and mass spectra. A critical analysis of whether a combination of several methods of chromatography and mass spectrometry allows us to elucidate the structure of an unknown UDMH transformation product was provided. It was demonstrated that the use of gas chromatographic retention indices for two stationary phases (polar and non-polar) allows for the rejection of false candidates in many cases when only one retention index is not enough. The structures of five previously unknown UDMH transformation products were proposed, and four previously proposed structures were refined.

Optimization of headspace solid-phase microextraction of volatile organic compounds from dry soil samples by porous coatings using COMSOL Multiphysics

Headspace solid-phase microextraction (HSSPME) is one of the simplest and cost-efficient sample preparation approaches for determination of volatile organic compounds (VOCs) in soil. This study was aimed at the development of the model for numerical optimization of HSSPME of volatile organic compounds from dry soil samples by porous coatings using COMSOL Multiphysics (CMP). ‘Transport of Diluted Species in Porous Medium’ physics was used for modeling. Effect of sample mass, pressure, fiber-headspace and soil-headspace distribution constants on extraction profiles and time of 95% equilibrium has been studied using the developed model. Equilibrium extraction under atmospheric pressure (1 atm) can take up to 97 min, while under vacuum (0.0313 atm) – 2.3 min. Equilibration time under vacuum was 42-43 times lower than under 1 atm at all studied distribution constants and sample masses. The developed model was modified for optimization of pre-incubation time using ‘Transport of Diluted Species’ physics. According to the obtained plots, 95% equilibration time can reach 13.3 min and depends on both sample mass and soil-headspace distribution constant of the analyte. The developed model can be recommended for optimization of pressure, preincubation and extraction time when fiber-headspace and soil-headspace distribution constants, soil porosity and density are known.