Recent Advances in Petroleum Analysis by Mass Spectrometry

Collision cross-section measurements of small molecules via transient decay profiles observed in Orbitrap mass analyzers

Collision cross section (CCS) of organic compounds can be measured via Fourier transform-based mass spectrometry (MS) by modeling the decay rate of transient signals in the analyzer. Deriving CCS values of low-mass molecules (mass < 2000 Da and CCS < 500 Å2) with Orbitrap MS is challenging due to their high axial frequencies and small absolute variances in cross-sectional profiles. Here, we acquired mass spectra of progressively more complex low-mass analytes using commercial Orbitrap mass spectrometers. The transient signals were processed using Fast Fourier transform (FFT) and short-time Fourier transform (StFFT) to derive decay constants of multiple select ionic species from a single MS full-scan experiment. Decay constants were translated into CCS values using at least two internal standards in the same mass spectrum. Our results suggest target ionic species should have high S/N in order to derive CCS values with ≤0.5% uncertainty. Limitations in the precision of CCS measurements reflect local space charge effects that disturb ion motion in the analyzer. The derived CCS values of polymer like fragments of Ultramark 1621 and small molecules such as individual protonated amino acids can achieve average ±1% error with selection of internal standards across a wide mass range. Future studies need to optimize the strategy to select internal standards in order to improve the precision and accuracy of CCS measurements for small molecules via Orbitrap MS.

Kinematic viscosity prediction of jet fuels and alternative blending components via comprehensive two-dimensional gas chromatography, partial least squares, and Yeo-Johnson transformation

This work presents an accurate yet simplified partial least squares model to predict the kinematic viscosity of conventional and alternative jet fuels at -20°C using comprehensive two-dimensional gas chromatography coupled to a flame ionization detector (GC × GC/FID). Three different normalization methods (mean-centering, logarithmic, and Yeo-Johnson) were evaluated to identify their impact in the prediction of middle distillates' physical properties. Results using Yeo-Johnson transformation exhibited improved viscosity prediction capabilities over the validation set with a mean absolute percentage error of 5.3%, a root-mean-squared error of 0.23, and a coefficient of determination (R2 ) of 0.9404 using only 10 latent variables. Unlike previously reported correlations, this model allowed the identification of specific hydrocarbon groups and carbon numbers that drive jet fuel viscosity at low temperatures. The presence of even small amounts of large branched-alkanes (C15 -C17 ), dicyclic-alkanes (C10 ), and cycloaromatics (C11 ) have the potential to strongly increase the kinematic viscosity of jet fuels. Contrastingly, light monocycloalkanes and branched-alkanes (≤ C10 ) were associated with lower viscosity values. Novelly, this model suggests the implementation of Yeo-Johnson transformations to predict the physical properties of middle distillates to further improve the performance metrics of partial least squares models based on GC data.

Ion-molecule reactions of mass-selected ions

Gas-phase reactions of mass-selected ions with neutrals covers a very broad area of fundamental and applied mass spectrometry (MS). Oftentimes, ion-molecule reactions (IMR) can serve as a viable alternative to collision-induced dissociation and other ion dissociation techniques when using tandem MS. This review focuses on the literature pertaining applications of IMR since 2013. During the past decade considerable efforts have been made in analytical applications of IMR, including advances in one of the major techniques for characterization of unsaturated fatty acids and lipids, ozone-induced dissociation, and the development of a new technique for sequencing of large ions, hydrogen atom attachment/abstraction dissociation. Many advances have also been made in identifying gas-phase chemistry specific to a functional group in organic and biological compounds, which are useful in structure elucidation of analytes and differentiation of isomers/isobars. With "soft" ionization techniques like electrospray ionization having become mainstream for quite some time now, the efforts in the area of metal ion catalysis have firmly moved into exploring chemistry of ligated metal complexes in their "natural" oxidation states allowing to model individual steps of mechanisms in homogeneous catalysis, especially in combination with high-level DFT calculations. Finally, IMR continue to contribute to the body of knowledge in the area of chemistry of interstellar processes.

Application of Ion Mobility Spectrometry-Mass Spectrometry for Compositional Characterization and Fingerprinting of a Library of Diverse Crude Oil Samples

Exposure characterization of crude oils, especially in time-sensitive circumstances such as spills and disasters, is a well-known analytical chemistry challenge. Gas chromatography-mass spectrometry is commonly used for "fingerprinting" and origin tracing in oil spills; however, this method is both time-consuming and lacks the resolving power to separate co-eluting compounds. Recent advances in methodologies to analyze petroleum substances using high-resolution analytical techniques have demonstrated both improved resolving power and higher throughput. One such method, ion mobility spectrometry-mass spectrometry (IMS-MS), is especially promising because it is both rapid and high-throughput, with the ability to discern among highly homologous hydrocarbon molecules. Previous applications of IMS-MS to crude oil analyses included a limited number of samples and did not provide detailed characterization of chemical constituents. We analyzed a diverse library of 195 crude oil samples using IMS-MS and applied a computational workflow to assign molecular formulas to individual features. The oils were from 12 groups based on geographical and geological origins: non-US (1 group), US onshore (3), and US Gulf of Mexico offshore (8). We hypothesized that information acquired through IMS-MS data would provide a more confident grouping and yield additional fingerprint information. Chemical composition data from IMS-MS was used for unsupervised hierarchical clustering, as well as machine learning-based supervised analysis to predict geographic and source rock categories for each sample; the latter also yielded several novel prospective biomarkers for fingerprinting of crude oils. We found that IMS-MS data have complementary advantages for fingerprinting and characterization of diverse crude oils and that proposed polycyclic aromatic hydrocarbon biomarkers can be used for rapid exposure characterization. Environ Toxicol Chem 2023;42:2336-2349. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Analytical chemistry solutions to hazard evaluation of petroleum refining products

Products of petroleum refining are substances that are both complex and variable. These substances are produced and distributed in high volumes; therefore, they are heavily scrutinized in terms of their potential hazards and risks. Because of inherent compositional complexity and variability, unique challenges exist in terms of their registration and evaluation. Continued dialogue between the industry and the decision-makers has revolved around the most appropriate approach to fill data gaps and ensure safe use of these substances. One of the challenging topics has been the extent of chemical compositional characterization of products of petroleum refining that may be necessary for substance identification and hazard evaluation. There are several novel analytical methods that can be used for comprehensive characterization of petroleum substances and identification of most abundant constituents. However, translation of the advances in analytical chemistry to regulatory decision-making has not been as evident. Therefore, the goal of this review is to bridge the divide between the science of chemical characterization of petroleum and the needs and expectations of the decision-makers. Collectively, mutual appreciation of the regulatory guidance and the realities of what information these new methods can deliver should facilitate the path forward in ensuring safety of the products of petroleum refining.

Next Challenges for the Comprehensive Molecular Characterization of Complex Organic Mixtures in the Field of Sustainable Energy

The conversion of lignocellulosic biomass by pyrolysis or hydrothermal liquefaction gives access to a wide variety of molecules that can be used as fuel or as building blocks in the chemical industry. For such purposes, it is necessary to obtain their detailed chemical composition to adapt the conversion process, including the upgrading steps. Petroleomics has emerged as an integral approach to cover a missing link in the investigation bio-oils and linked products. It relies on ultra-high-resolution mass spectrometry to attempt to unravel the contribution of many compounds in complex samples by a non-targeted approach. The most recent developments in petroleomics partially alter the discriminating nature of the non-targeted analyses. However, a peak referring to one chemical formula possibly hides a forest of isomeric compounds, which may present a large chemical diversity concerning the nature of the chemical functions. This identification of chemical functions is essential in the context of the upgrading of bio-oils. The latest developments dedicated to this analytical challenge will be reviewed and discussed, particularly by integrating ion source features and incorporating new steps in the analytical workflow. The representativeness of the data obtained by the petroleomic approach is still an important issue.

Proton Affinities of Alkanes

Chemical characterization of complex mixtures of large alkanes is critically important for many fields, including petroleomics and the development of renewable transportation fuels. Tandem mass spectrometry is the only analytical method that can be used to characterize such mixtures at the molecular level. Many ionization methods used in mass spectrometry involve proton transfer to the analyte. Unfortunately, very few proton affinity (PA) values are available for alkanes. Indeed, previous research has shown that most protonated alkanes (MH⁺) are not stable but fragment spontaneously via the elimination of a hydrogen molecule to form [M - H]⁺ ions. Here, the PAs of several n-alkanes and alkylcyclohexanes containing 5-8 carbon atoms, n-pentane, n-hexane, n-heptane, n-octane, cyclohexane, methylcyclohexane, and ethylcyclohexane, were determined via bracketing experiments by using a linear quadrupole ion trap mass spectrometer. Monitoring the formation of the [M - H]⁺ ions in reactions between the alkanes and protonated reference bases with known PAs revealed that the PAs of all the alkanes fell into the range 721 ± 20 kJ mol^-1. In order to obtain a more accurate estimate of the relative PAs of different alkanes, two alkanes were introduced simultaneously into the ion trap and allowed to react with the same protonated reference base. Based on these experiments, the longer the alkyl chain in an n-alkane or alkylcyclohexane the greater the PA. Further, when considering alkanes with the same number of carbon atoms, the PAs of those with a cyclohexane ring were found to be greater than those with no such ring.

Recent Advances in Mass Spectrometry-Based Structural Elucidation Techniques

Mass spectrometry (MS) has become the central technique that is extensively used for the analysis of molecular structures of unknown compounds in the gas phase. It manipulates the molecules by converting them into ions using various ionization sources. With high-resolution MS, accurate molecular weights (MW) of the intact molecular ions can be measured so that they can be assigned a molecular formula with high confidence. Furthermore, the application of tandem MS has enabled detailed structural characterization by breaking the intact molecular ions and protonated or deprotonated molecules into key fragment ions. This approach is not only used for the structural elucidation of small molecules (MW < 2000 Da), but also crucial biopolymers such as proteins and polypeptides; therefore, MS has been extensively used in multiomics studies for revealing the structures and functions of important biomolecules and their interactions with each other. The high sensitivity of MS has enabled the analysis of low-level analytes in complex matrices. It is also a versatile technique that can be coupled with separation techniques, including chromatography and ion mobility, and many other analytical instruments such as NMR. In this review, we aim to focus on the technical advances of MS-based structural elucidation methods over the past five years, and provide an overview of their applications in complex mixture analysis. We hope this review can be of interest for a wide range of audiences who may not have extensive experience in MS-based techniques.

In-depth characterization of nitrogen heterocycles of petroleum by liquid chromatography-energy-resolved high resolution tandem mass spectrometry

With the increased attention to processing heavy crude oils, a detailed description of chemical composition is critical for the petroleum refining industry. The current analytical technique such as ultrahigh resolution mass spectrometry has been successfully applied for the molecular level characterization of complex petroleum fractions. But the structural characterization of heavy petroleum feedstock is still a great challenge. In this study, a novel in-depth characterization method of nitrogen heterocycles (N-heterocycles) in heavy petroleum mixtures was proposed by online liquid chromatography coupled with electrospray ionization high resolution energy-resolved mass spectrometry. A series of typical basic aromatic, neutral aromatic and naphtheno-aromatic nitrogen heterocyclic model compounds were synthesized to investigate energy-resolved fragmentation behaviors in high energy collision-induced dissociation at 10-100 eV. Energy-dependent fragmentation pathways were elucidated. Notably, characteristic double bond equivalent (DBE) versus carbon number distributions of N₁ ions and all CH ions were discovered, which were closely related to their core structure. Then a workflow to assign core structures of alkyl-substituted N-heterocycles in petroleum was proposed and validated. The developed method was applied to investigate the structural isomers in feed and product vacuum gas oil (VGO) fractions. Core structural differences in feed VGO and subtle structural variations between feed and product VGOs were recognized. This work can distinguish structural isomers of N-heterocycles with the subtle difference in their core structure in heavy petroleum fractions based on global energy dimensional fragmentation characteristics.

Characterization of Compositional Variability in Petroleum Substances

In the process of registration of substances of Unknown or Variable Composition, Complex Reaction Products or Biological Materials (UVCBs), information sufficient to enable substance identification must be provided. Substance identification for UVCBs formed through petroleum refining is particularly challenging due to their chemical complexity, as well as variability in refining process conditions and composition of the feedstocks. This study aimed to characterize compositional variability of petroleum UVCBs both within and across product categories. We utilized ion mobility spectrometry (IMS)-MS as a technique to evaluate detailed chemical composition of independent production cycle-derived samples of 6 petroleum products from 3 manufacturing categories (heavy aromatic, hydrotreated light paraffinic, and hydrotreated heavy paraffinic). Atmospheric pressure photoionization and drift tube IMS-MS were used to identify structurally related compounds and quantified between- and within-product variability. In addition, we determined both individual molecules and hydrocarbon blocks that were most variable in samples from different production cycles. We found that detailed chemical compositional data on petroleum UVCBs obtained from IMS-MS can provide the information necessary for hazard and risk characterization in terms of quantifying the variability of the products in a manufacturing category, as well as in subsequent production cycles of the same product.

Mass Spectrometry as a Crucial Analytical Basis for Omics Sciences

This review is devoted to the consideration of mass spectrometric platforms as applied to omics sciences. The most significant attention is paid to omics related to life sciences (genomics, proteomics, meta-bolomics, lipidomics, glycomics, plantomics, etc.). Mass spectrometric approaches to solving the problems of petroleomics, polymeromics, foodomics, humeomics, and exosomics, related to inorganic sciences, are also discussed. The review comparatively presents the advantages of various principles of separation and mass spectral techniques, complementary derivatization, used to obtain large arrays of various structural and quantitative information in the mentioned omics sciences.

Atmospheric polycyclic aromatic hydrocarbons (PAHs) at urban settings in Pakistan: Spatial variations, sources and health risks

For the first time, this study presents gaseous and particulate-bound (PM_2.5) polycyclic aromatic hydrocarbons (PAHs) in ambient air samples collected from eight major cities of Pakistan. Diurnal air samples (gaseous and PM_2.5) were collected in summer 2014 on polyurethane foam and quartz fiber filters using high volume-active air sampler. The US-EPA enlisted 16 priority PAHs in particulate and gaseous phase were measured on gas chromatograph equipped with mass spectrometer detector. The total PAHs concentrations ranged between 188 pg m^-3 (in Gilgit), and 2340 pg m^-3 (in Lahore). The decreasing order of PAHs concentrations in various cities was in the following order: Lahore > Rawalpindi > Multan > Faisalabad > Karachgi > Peshawar > Quetta > Gilgit. Phenanthrene showed the highest concentration, accounted 18% of total PAHs followed by fluoranthene (12% of total PAHs). This study showed that the gaseous fractions were predominant in the ambient air. Source apportionment analysis revealed that biomass combustion, vehicular emissions and diesel combustion in power generators were the potential PAHs emissions sources. The lifetime lungs cancer risk (LLCR) was in the range of 8.28 × 10^-7 to 2.09 × 10^-5 depicting mild cancer risk to the residents on exposure to atmospheric PAHs. Therefore, it is recommended to monitor atmospheric PAHs throughout the year and also adopt environmentally friendly fuels to reduce PAHs pollution and health risks in the country.

Data Processing Workflow to Identify Structurally Related Compounds in Petroleum Substances Using Ion Mobility Spectrometry-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 (^DTCCS_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.

Comprehensive Composition, Structure, and Size Characterization for Thiophene Compounds in Petroleum Using Ultrahigh-Resolution Mass Spectrometry and Trapped Ion Mobility Spectrometry

Thiophene compounds are the main concern of petroleum desulfurization, and their chemical composition and molecular configuration have critical impacts on thermodynamic and kinetic processes. In this work, atmospheric pressure chemical ionization (APCI) was employed for effective ionization of thiophene compounds in petroleum with complex matrix, in which carbon disulfide was used for generating predominant [M]^+• ions without the need of derivatization as for electrospray ionization. APCI coupled with ultrahigh-resolution mass spectrometry (UHRMS) was successfully applied to the composition characterization of thiophene compounds in both a low boiling petroleum fraction and a whole crude oil. APCI coupled with trapped ion mobility spectrometry (TIMS) was developed to determine the shape and size of thiophene compounds, providing configuration information that affects the steric hindrance and diffusion behavior of reactants in the desulfurization reaction, which has not been previously reported. Moreover, the comprehensive experimental structural data, expressed as the collision cross section (CCS) of the ions as surrogates of molecules, provided clues to the factors affecting the desulfurization reactivity of thiophene compounds. Further exploration showed that not only qualitative analysis of thiophene compounds can be achieved from the correlation between m/z and CCS, but also molecular size was found to be correlated with CCS that can be used as structural analysis. Overall, the molecular composition and dimension analysis together can provide substantial information for the desulfurization activity of thiophene compounds, facilitating the desulfurization process studies and catalyst design.

Odorant Monitoring in Natural Gas Pipelines Using Ultraviolet-Visible Spectroscopy

The remote, timely and in-field detection of sulfured additives in natural gas pipelines is a challenge for environmental, commercial and safety reasons. Moreover, the constant control of the level of odorants in a pipeline is required by law to prevent explosions and accidents. Currently, the detection of the most common odorants (THT = tetrahydrothiophane; TBM = tertiary butyl mercaptan) added to natural gas streams in pipelines is made in situ by using portable gas chromatography apparatuses. In this study, we report the analysis of the ultraviolet spectra obtained by a customized ultraviolet spectrophotometer, named Spectra, for the in-field detection of thiophane and tertiary butyl mercaptan. Spectra were conceived to accomplish the remote analysis of odorants in the pipelines of the natural gas stream through the adoption of technical solutions aimed to adapt a basic bench ultraviolet spectrophotometer to the in-field analysis of gases. The remotely controlled system acquires spectra continuously, performing the quantitative determination of odorants and catching systemic or accidental variations of the gaseous mixture in different sites of the pipeline. The analysis of the experimental spectra was carried out also through theoretical quantum mechanical approaches aimed to detect and to correctly assign the nature of the intrinsic electronic transitions of the two odorants, thiophane and tertiary butyl mercaptan, that cause the ultraviolet absorptions. So far, these theoretical aspects have never been studied before. The absorption maxima of thiophane and tertiary butyl mercaptan spectra were computationally simulated through the usage of selected molecular models with satisfactory results. The good matches between the experimental and theoretical datasets corroborate the reliability of the collected data. During the tests, unexpected pollutants and accidental malfunctions have been detected and also identified by Spectra, making this instrument suitable for many purposes.

Graph-based machine learning interprets and predicts diagnostic isomer-selective ion-molecule reactions in tandem mass spectrometry

Diagnostic ion-molecule reactions employed in tandem mass spectrometry experiments can frequently be used to differentiate between isomeric compounds unlike the popular collision-activated dissociation methodology. Selected neutral reagents, such as 2-methoxypropene (MOP), are introduced into an ion trap mass spectrometer where they react with protonated analytes to yield product ions that are diagnostic for the functional groups present in the analytes. However, the understanding and interpretation of the mass spectra obtained can be challenging and time-consuming. Here, we introduce the first bootstrapped decision tree model trained on 36 known ion-molecule reactions with MOP. It uses the graph-based connectivity of analytes' functional groups as input to predict whether the protonated analyte will undergo a diagnostic reaction with MOP. A Cohen kappa statistic of 0.70 was achieved with a blind test set, suggesting substantial inter-model reliability on limited training data. Prospective diagnostic product predictions were experimentally tested for 13 previously unpublished analytes. We introduce chemical reactivity flowcharts to facilitate chemical interpretation of the decisions made by the machine learning method that will be useful to understand and interpret the mass spectra for chemical reactivity.

Specification of the nitrogen functional group in a hydrotreated petroleum molecule using hydrogen/deuterium exchange electrospray ionization high-resolution mass spectrometry

Hydrotreatment is extensively used for the production of clean fuel. Attaining an understanding of the structural conversion of the nitrogen species during hydrotreatment is very challenging due to the compositional complexity and the absence of a proper characterization method. In the presented work, we coupled hydrogen/deuterium exchange (HDX) with positive-ion electrospray ionization high-resolution mass spectrometry ((+) ESI HR MS) to investigate the difference between the composition of the nitrogen-containing species and the functional groups before and after hydrotreatment. The solvent and additive were optimized for HDX (+) ESI HRMS through systematic evaluations on model nitrogen-containing compounds. We found that adding deuterated water (D₂O) and deuterated formic acid (DCOOD) significantly increased the degree of HDX and thus facilitated the identification of nitrogen functional groups. After application to the hydrotreated petroleum samples, the compositional variation of intermediate amine compounds during the heavy petroleum hydrotreatment process was clearly revealed.

Petroleomics: Tools, Challenges, and Developments

The detailed molecular characterization of petroleum-related samples by mass spectrometry, often referred to as petroleomics, continues to present significant analytical challenges. As a result, petroleomics continues to be a driving force for the development of new ultrahigh resolution instrumentation, experimental methods, and data analysis procedures. Recent advances in ionization, resolving power, mass accuracy, and the use of separation methods, have allowed for record levels of compositional detail to be obtained for petroleum-related samples. To address the growing size and complexity of the data generated, vital software tools for data processing, analysis, and visualization continue to be developed. The insights gained impact upon the fields of energy and environmental science and the petrochemical industry, among others. In addition to advancing the understanding of one of nature's most complex mixtures, advances in petroleomics methodologies are being adapted for the study of other sample types, resulting in direct benefits to other fields.

Analyzing the solid soot particulates formed in a fuel-rich flame by solvent-free matrix-assisted laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry

RATIONALE

The compositional and structural information of soot particles is essential for a better understanding of the chemistry and mechanism during the combustion. The aim of the present study was to develop a method to analyze such soot particulate samples with high complexity and poor solubility.

METHODS

The solvent-free sample preparation matrix-assisted laser desorption/ionization (MALDI) technique was combined with the ultrahigh-resolution Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS) for the characterization of solid soot particulates. Moreover, a modified iso-abundance plot (Carbon Number vs. Hydrogen Number vs. Abundance) was introduced to visualize the distributions of various chemical species, and to examine the agreement between the hydrogen-abstraction-carbon-addition (HACA) mechanism and the polycyclic aromatic hydrocarbon growth in the investigated flame system.

RESULTS

This solvent-free MALDI method enabled the effective ionization of the solid soot particulates without any dissolving procedure. With the accurate m/z ratios from FTICR-MS, a unique chemical formula was assigned to each of the recorded mass signals. The combustion products were proven to be mainly large polycyclic aromatic hydrocarbons (PAHs), together with a small amount (<5%) of oxidized hydrocarbons.

CONCLUSIONS

The developed method provides a new approach for the molecular characterization of soot particulates like carbonaceous materials. The investigated soot particulates are mainly PAHs with no or very short aliphatic chains. The growth mechanism of PAHs during combustion can be examined against the classic HACA mechanism.