Data Processing Workflow to Identify Structurally Related Compounds in Petroleum Substances Using Ion Mobility
Alina T Roman-Hubers1, Alexandra C Cordova1, Noor A Aly1
1Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, Texas 77843, United States.
Energy & Fuels : an American Chemical Society Journal
|August 9, 2021
Summary
Ion mobility spectrometry coupled with mass spectrometry (IMS-MS) provides rapid, untargeted analysis of complex samples. Combining collisional cross section (CCS) and Kendrick mass defect (KMD) analyses enables confident molecular formula assignment for petroleum substances.
Area of Science:
- Analytical Chemistry
- Petroleum Geochemistry
- Spectrometry
Background:
- Ion mobility spectrometry coupled with mass spectrometry (IMS-MS) is a powerful post-ionization separation technique for multidimensional analysis.
- IMS-MS provides untargeted analysis, yielding ion-specific conformational data as collisional cross section (CCS) values.
- Characterizing complex hydrocarbon mixtures like petroleum requires advanced analytical methods.
Purpose of the Study:
- To combine nitrogen gas drift tube CCS (DTCCSN2) and Kendrick mass defect (KMD) analyses for compositional analysis of petroleum.
- To demonstrate the utility of CCS in identifying isomeric species within homologous series using polycyclic aromatic compound standards.
- To propose a workflow for confident molecular formula assignment in IMS-MS data of petroleum samples.
Main Methods:
- Utilized IMS-MS for rapid, multidimensional analysis of complex samples.
- Employed DTCCSN2 and KMD analyses, focusing on CH2 and H functional units.
- Applied CCS filtering and KMD analysis to gasoline and crude oil samples.
Main Results:
- Demonstrated that CCS aids in identifying isomeric species in homologous series.
- Successfully applied KMD analyses and CCS filtering to characterize a gasoline standard and a crude oil sample.
- Developed a workflow for confident molecular formula assignment to IMS-MS features.
Conclusions:
- The integration of DTCCSN2 and KMD analyses offers enhanced compositional characterization of petroleum.
- The proposed workflow enables confident molecular formula assignment for untargeted IMS-MS data.
- Rapid untargeted IMS-MS analysis combined with advanced data processing provides robust characterization of hydrocarbon substances.
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