Open AccessData Processing Workflow to Identify Structurally Related Compounds in Petroleum Substances Using Ion Mobility Spectrometry–Mass Spectrometry
Author(s) -
Alina T. RomanHubers,
Alexandra C. Cordova,
Noor Aly,
Thomas J. McDonald,
Dillon Lloyd,
Fred A. Wright,
Erin Baker,
Weihsueh A. Chiu,
Ivan Rusyn
Publication year - 2021
Publication title -
energy and fuels
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.861
H-Index - 186
eISSN - 1520-5029
pISSN - 0887-0624
DOI - 10.1021/acs.energyfuels.1c00892
Subject(s) - ion mobility spectrometry , mass spectrometry , chemistry , workflow , gasoline , ion mobility spectrometry–mass spectrometry , chromatography , petroleum , gas chromatography–mass spectrometry , homologous series , analytical chemistry (journal) , database , electrospray ionization , computer science , organic chemistry , sample preparation in mass spectrometry
Ion mobility spectrometry coupled with mass spectrometry (IMS-MS) is a post-ionization separation technique that can be used for rapid multidimensional analyses of complex samples. IMS-MS offers untargeted analysis, including ion-specific conformational data derived as collisional cross section (CCS) values. Here, we combine nitrogen gas drift tube CCS ( DT CCS N2 ) and Kendrick mass defect (KMD) analyses based on CH2 and H functional units to enable compositional analyses of petroleum substances. First, polycyclic aromatic compound standards were analyzed by IMS-MS to demonstrate how CCS assists the identification of isomeric species in homologous series. Next, we used case studies of a gasoline standard previously characterized for paraffin, isoparaffin, aromatic, naphthene, and olefinic (PIANO) compounds, and a crude oil sample to demonstrate the application of the KMD analyses and CCS filtering. Finally, we propose a workflow that enables confident molecular formula assignment to the IMS-MS-derived features in petroleum samples. Collectively, this work demonstrates how rapid untargeted IMS-MS analysis and the proposed data processing workflow can be used to provide confident compositional characterization of hydrocarbon-containing substances.