Data Processing Workflow to Identify Structurally Related Compounds in Petroleum Substances Using Ion Mobility Spectrometry–Mass Spectrometry

Abstract

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 (DTCCSN2) 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.

The Next Frontier of Environmental Unknowns: Substances of Unknown or Variable Composition, Complex Reaction Products, or Biological Materials (UVCBs)

“…Additionally, certain UVCBs such as petroleum substances that contain mostly hydrocarbons may be less challenging to characterize compared to UVCBs containing multiple chemical classes such as essential oils. Overall, petroleum substances appear to be the most extensively characterized UVCBs: constituent identification commonly by gas chromatography–mass spectrometry (GC–MS) and ion mobility spectrometry–mass spectrometry, and relative quantification by GC­(xGC) flame ionization detection. − Essential-oil UVCBs were characterized using low resolution GC–MS aided by available library spectra and reference standards of constituents. − Among high resolution mass spectrometry methods, one example used five different techniques to characterize a polyhalogenated flame retardant UVCB, concluding that it is “dominated by C 18 carbon chain lengths, substituted with 3–7 chlorine atoms and 1–3 bromine atoms on an alkane chain” . Unambiguous structural identification is often not feasible for many UVCBs such as these, as “no individual or mixed standards for [polyhalogenated (bromo-chloro) n -alkanes] exist” .…”

Uncovering PFAS and Other Xenobiotics in the Dark Metabolome Using Ion Mobility Spectrometry, Mass Defect Analysis, and Machine Learning

“…The numerous resulting species therefore require progressively more sophisticated techniques to detect their presence, enable structural characterization, and evaluate their temporal evolution and distribution. Since many of these xenobiotic classes have characteristic molecular and structural traits such as PFAS, all sharing the presence of C–F bonds and PCBs having chlorinated biphenyl moieties, these can be exploited to increase detection specificity . For example, Kendrick mass defect (KMD) analysis has been important for distinguishing different molecular classes as it can probe repetitive patterns in complex datasets by normalization to specific atomic or functional group components.…”

“…Since many of these xenobiotic classes have characteristic molecular and structural traits such as PFAS, all sharing the presence of C−F bonds and PCBs having chlorinated biphenyl moieties, these can be exploited to increase detection specificity. 29 For example, Kendrick mass defect (KMD) analysis has been important for distinguishing different molecular classes as it can probe repetitive patterns in complex datasets by normalization to specific atomic or functional group components. In the case of PFAS, KMD analysis with a CF 2 repeating unit pinpoints molecules with and without CF 2 functional groups.…”

Oil Irradiation Experiments Document Changes in Oil Properties, Molecular Composition, and Dispersant Effectiveness Associated with Oil Photo-Oxidation

“…Sample analysis was performed with a 6560A Ion Mobility Q-TOF MS instrument (Agilent Technologies, Santa Clara, CA) using an atmospheric pressure photoionization source in positive ion mode (APPI + ), facilitating the detection of aromatic compounds . IMS-MS raw files were processed for feature identification and molecular formula assignment (see the SI for details) as detailed elsewhere …”

“…21 IMS-MS raw files were processed for feature identification and molecular formula assignment (see the SI for details) as detailed elsewhere. 22 Dispersant Effectiveness. Dispersibilities of fresh and experimental oil residues with and without Corexit EC9500A and Corexit EC9500B (Corexit Environmental Solutions LLC; Sugar Land, TX) were determined using the Baffled Flask Test.…”