Prediction of Structures of Compounds Encountered in Complex Organic Matter with Highly Flexible Alkyl Chains Using Ion Mobility-Mass Spectrometry.
Johann Le MaîtreJulien Florent MaillardMarie Hubert-RouxCarlos AfonsoPierre GiustiPublished in: Journal of the American Society for Mass Spectrometry (2022)
The chemical structure of an organic molecule has a direct influence on its three-dimensional conformation. One way to obtain information on this conformation is to use ion mobility spectrometry. This technique allows the separation of different isomers according to their collision cross section (CCS) with an inert gas. Smaller or more compact molecules will have lower collision cross section values than larger molecules. The CCS is an intrinsic ion parameter for a specific gas and is thus predictable. Today, calculations of rigid molecules are commonly performed to obtain additional structural information on an ion. However, calculations are more complex with very flexible molecules. In particular, molecules presenting long alkyl chains can yield a high number of conformers. Each conformer is then associated with a CCS value that is specific to it. We report, here, a methodology to predict CCS of flexible molecules. The used approach is based on automatic conformers research followed by geometry optimization and CCS calculations. Determination of theoretical and experimental CCS values for a rigid polycyclic aromatic hydrocarbons (PAHs) standard was used to calibrate the Mobcal software. Then, 13 standard molecules ranging from 4 to 19 carbon alkyl chains, including three long alkyl chain isomers of C 22 H 38 , were analyzed on a TWIMS-ToF and calculated using our methodology. CCS deviations between experimental and theoretical values were found to be less than 1.5% over the whole studied CCS range. This method was finally applied for structural analysis of petroleum compounds refractory to the hydro-denitrogenation process.
Keyphrases
- polycyclic aromatic hydrocarbons
- mass spectrometry
- molecular dynamics simulations
- ionic liquid
- density functional theory
- molecular dynamics
- high resolution
- organic matter
- liquid chromatography
- healthcare
- machine learning
- ms ms
- room temperature
- solid phase extraction
- health information
- case report
- solid state
- climate change
- neural network