Structural analysis of petroporphyrins from asphaltene by trapped ion mobility coupled with Fourier transform ion cyclotron resonance mass spectrometry.

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Normandie Université, COBRA, UMR 6014 et FR 3038, Université de Rouen, INSA de Rouen-Normandie, CNRS, IRCOF, Mont Saint Aignan Cedex, France. and TOTAL Refining & Chemicals, Total Research & Technology Gonfreville, BP 27, 76700 Harfleur, France and International Joint Laboratory - iC2MC: Complex Matrices Molecular Characterization, TRTG, BP 27, 76700 Harfleur, France.

Published: June 2021

Molecular characterization of compounds present in highly complex mixtures such as petroleum is proving to be one of the main analytical challenges. Heavy fractions, such as asphaltenes, exhibit immense molecular and isomeric complexity. Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) with its unequalled resolving power, mass accuracy and dynamic range can address the isobaric complexity. Nevertheless, isomers remain largely inaccessible. Therefore, another dimension of separation is required. Recently, ion mobility mass spectrometry has revealed great potential for isomer description. In this study, the combination of trapped ion mobility and Fourier transform ion cyclotron resonance mass spectrometry (TIMS-FTICR) is used to obtain information on the structural features and isomeric diversity of vanadium petroporphyrins present in heavy petroleum fractions. The ion mobility spectra provided information on the isomeric diversity of the different classes of porphyrins. The determination of the collision cross section (CCS) from the peak apex allows us to hypothesize about the structural aspects of the petroleum molecules. In addition, the ion mobility signal full width at half maximum (FWHM) was used as a measure for isomeric diversity. Finally, theoretical CCS determinations were conducted first on core structures and then on alkylated petroporphyrins taking advantage of the linear correlation between the CCS and the alkylation level. This allowed the proposal of putative structures in agreement with the experimental results. The authors believe that the presented workflow will be useful for the structural prediction of real unknowns in highly complex mixtures.

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http://dx.doi.org/10.1039/d1an00140jDOI Listing

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