Chromatographic and spectroscopic analysis of heavy crude oil mixtures with emphasis in nuclear magnetic resonance spectroscopy: A review

Investigation of metal speciation in crude oil contaminated marine environments using a novel DGT technique

Crude oil spills and discharges from refineries, mining, and industrial activities can introduce trace metals into marine environments. Determining trace metal concentrations and speciation in seawater is challenging due to the complex matrix and high salinity. This study developed a novel approach using modified diffusive gradients in thin-films (DGT) to measure labile concentrations and speciation of Co, Ni, Cu, Cd, Pb, and Zn in crude oil-contaminated seawater. Five DGT devices (open pore, restricted pore, 1000 and 3500 MWCO dialysis membranes, and Nafion 112) were tested. Results showed that crude oil impacts the lability and mobility of metals, with Nafion 112 excluding negatively charged complexes. Diffusion coefficients were measured in diffusive hydrogels, dialysis membranes, and Nafion using a diffusion cell. Metal speciation was investigated in synthetic seawater with 1 % and 4 % crude oil/water ratios (OWR). For Co, Ni, Zn, and Pb, similar labile concentrations across DGT devices indicated low molecular weight complexes dominated. Labile Cu decreased significantly with increased oil content, while other metals showed varying degrees of lability. The findings suggest that crude oil influences metal speciation through complexation with organic ligands, affecting their bioavailability in marine environments. Compared to measurements by equilibrium microdialysis, similar concentrations for Pb and Zn suggested their weak complexes with oil-soluble organic chemicals. However, microdialysis measured higher concentrations of Co, Cu, Ni, and Cd, indicating partially non-labile, low molecular weight complexes existed. Nafion 112 diffusion coefficients were 16-38 times lower than those in diffusive gel. Only free metal ions and potentially some positively charged inorganic/small organic complexes are likely to be measured by Nafion-DGT. This work has demonstrated that crude oil level and metal characteristics greatly influence metal speciation, and that small, labile organic complexes play a crucial role in controlling the mobility and availability of metals in oil-contaminated seawater.

A proposed two-level classification approach for forensic detection of diesel adulteration using NMR spectroscopy and machine learning

Adulteration of diesel fuel poses a major concern in most developing countries including Ghana despite the many regulatory schemes adopted. The solvent tracer analysis approach currently used in Ghana has over the years suffered several limitations which affect the overall implementation of the scheme. There is therefore a need for alternative or supplementary tools to help detect adulteration of automotive fuel. Herein we describe a two-level classification method that combines NMR spectroscopy and machine learning algorithms to detect adulteration in diesel fuel. The training sets used in training the machine learning algorithms contained 20-40% w/w adulterant, a level typically found in Ghana. At the first level, a classification model is built to classify diesel samples as neat or adulterated. Adulterated samples are passed on to the second stage where a second classification model identifies the type of adulterant (kerosene, naphtha, or premix) present. Samples were analyzed by 1H NMR spectroscopy and the data obtained were used to build and validate support vector machine (SVM) classification models at both levels. At level 1, the SVM model classified all 200 samples with only 2.5% classification errors after validation. The level 2 classification model developed had no classification errors for kerosene and premix in diesel. However, 2.5% classification error was recorded for samples adulterated with naphtha. Despite the great performance of the proposed schemes, it showed significantly erratic predictions with adulterant levels below 20% w/w as the training sets for both models contained adulterants above 20% w/w. The proposed method, nevertheless, proved to be a potential tool that could serve as an alternative to the marking system in Ghana for the fast detection of adulterants in diesel.

Correlation analysis of modern analytical data - a chemometric dissection of spectral and chromatographic variables

The Standard Practices for Infrared Multivariate Quantitative Analysis (ASTM E1655) provide a guide for determining physicochemical properties of materials using multivariate calibration techniques applied to chemical sources that have high multicollinearity and correlated information. Partial least squares (PLS) is the most widely used multivariate regression method due to its excellent prediction capabilities and easy optimization. Initially applied to chromatographic data, PLS has also shown great results in near-infrared (NIR) and mid-infrared (MIR) spectroscopies. However, complex chemical matrices with low correlation may not be efficiently modeled using PLS or other multivariate analyses limited by grouping similar information (such as latent variables or principal components). Therefore, this study aims to evaluate the multicollinearity of different analytical techniques, such as high-temperature gas chromatography (HTGC), NIR, MIR, hydrogen nuclear magnetic resonance (1H NMR), carbon-13 nuclear magnetic resonance (13C NMR), and Fourier transform ion cyclotron resonance mass spectrometry coupled to the electrospray source in positive and negative ionization modes (ESI(±)FT-ICR). Descriptive statistics (coefficient of determination, R2) and principal component analysis (PCA) were used to identify the distribution of correlated information. Results showed that NIR and MIR spectroscopies exhibited a higher percentage of correlated variables, while 13C NMR and ESI(±)FT-ICR MS had more discrete profiles. Therefore, PLS development may be more effectively applied to NIR, MIR, and 1H NMR data, while 13C NMR and mass spectra may require other algorithms or variable selection methods in combination with PLS.

The contribution of high-resolution GC separations in plastic recycling research

One convenient strategy to reduce environmental impact and pollution involves the reuse and revalorization of waste produced by modern society. Nowadays, global plastic production has reached 367 million tons per year and because of their durable nature, their recycling is fundamental for the achievement of the circular economy objective. In closing the loop of plastics, advanced recycling, i.e., the breakdown of plastics into their building blocks and their transformation into valuable secondary raw materials, is a promising management option for post-consumer plastic waste. The most valuable product from advanced recycling is a fluid hydrocarbon stream (or pyrolysis oil) which represents the feedstock for further refinement and processing into new plastics. In this context, gas chromatography is currently playing an important role since it is being used to study the pyrolysis oils, as well as any organic contaminants, and it can be considered a high-resolution separation technique, able to provide the molecular composition of such complex samples. This information significantly helps to tailor the pyrolysis process to produce high-quality feedstocks. In addition, the detection of contaminants (i.e., heteroatom-containing compounds) is crucial to avoid catalytic deterioration and to implement and design further purification processes. The current review highlights the importance of molecular characterization of waste stream products, and particularly the pyrolysis oils obtained from waste plastics. An overview of relevant applications published recently will be provided, and the potential of comprehensive two-dimensional gas chromatography, which represents the natural evolution of gas chromatography into a higher-resolution technique, will be underlined.

Oil spills: impacts and perspectives of treatment technologies with focus on the use of green surfactants

Oil spills into the oceans cause irreparable damage to marine life and harms the coastal population of the affected areas. The main measures to be taken in response to an oil spill are to reduce the impact on marine life, prevent oil from reaching the shore through its recovery, and accelerate the degradation of unrecovered oil. Any environmental damage can be reduced if the spilled oil is removed from the water quickly and efficiently. Therefore, it is essential to know the treatment strategies for spilled oils. Several technologies are currently available, including booms, skimmers, in situ burning, use of adsorbents, dispersants/surfactants, and bioremediation. The selection of the type of treatment will depend not only on the effectiveness of the technique, but mainly on the type of oil, amount spilled, location, weather, and sea conditions. In this review, the characteristics of oil spills, their origin, destination, and impacts caused, including major accidents around the world, are initially addressed. Then, the main physical, chemical, and biological treatment technologies are presented, describing their advances, advantages, and drawbacks, with a focus on the use of green surfactants. These agents will be described in detail, showing the evolution of research, recent studies, patents, and commercialized products. Finally, the challenges that remain due to spills, the necessary actions, and the prospects for the development of existing treatment technologies are discussed, which must be linked to the use of combined techniques.

Identification and Quantification of Hydrocarbon Functional Groups in Gasoline Using 1H-NMR Spectroscopy for Property Prediction

Gasoline is one of the most important distillate fuels obtained from crude refining; it is mainly used as an automotive fuel to propel spark-ignited (SI) engines. It is a complex hydrocarbon fuel that is known to possess several hundred individual molecules of varying sizes and chemical classes. These large numbers of individual molecules can be assembled into a finite set of molecular moieties or functional groups that can independently represent the chemical composition. Identification and quantification of groups enables the prediction of many fuel properties that otherwise may be difficult and expensive to measure experimentally. In the present work, high resolution ¹H nuclear magnetic resonance (NMR) spectroscopy, an advanced structure elucidation technique, was employed for the molecular characterization of a gasoline sample in order to analyze the functional groups. The chemical composition of the gasoline sample was then expressed using six hydrocarbon functional groups, as follows: paraffinic groups (CH, CH₂ and CH₃), naphthenic CH-CH₂ groups and aromatic C-CH groups. The obtained functional groups were then used to predict a number of fuel properties, including research octane number (RON), motor octane number (MON), derived cetane number (DCN), threshold sooting index (TSI) and yield sooting index (YSI).

NMR relaxometry analysis of molecular degradation in internal combustion engine lubricants

A set of experimental techniques headed by proton fast field-cycling nuclear magnetic resonance (¹ HFFC-NMR) were used to analyze the effects of degradation of lubricant oil used in an internal combustion engine (ICE). Its relaxometric, spectroscopic, and rheological properties were evaluated and interpreted in terms of changes in the chemical structure and the involved molecular dynamics. In order to better understand the relaxometric behavior, chemical changes induced by heat were investigated for selected n-alkanes, as model-systems due to their structural simplicity. Fourier transform infrared (FTIR) spectroscopy, viscosity measurements, and foaming were used to contrast NMR relaxometry experiments. Main observed changes associated with oil degradation can be attributed to molecular oxidation, fragmentation, and ramification. As an outstanding feature of this work, we show that the relaxometric analysis can be done without any special treatment of the sample, allowing results in less than 10 min.

Catalytic Oxidation of Heavy Residual Oil by Pulsed Nuclear Magnetic Resonance

A study on the catalytic oxidation of heavy residual oil (HRO) was carried out. The thermodynamic parameters of components of HRO oxidation products were studied by pulsed nuclear magnetic resonance (NMR). A method for the quantitative assessment of thermodynamic parameters of HRO components and oxidized bitumen using pulsed NMR is presented. The relationship between NMR parameters and the viscosity of HRO and its oxidation products is established. The obtained results prove the possibility of using pulsed NMR as a flow-line method for rapid analysis of intermediates and products of the heavy residual oil oxidation.

Comparison of Thermal and Flow-Based Modulation in Comprehensive Two-Dimensional Gas Chromatography—Time-of-Flight Mass Spectrometry (GC × GC-TOFMS) for the Analysis of Base Oils

Base oils are produced by refining crude oil or through chemical synthesis. They are a key component of engine oils. With an immense range of carbon numbers and boiling points, analyzing such complex mixtures is very difficult. The need to monitor industrial petroleum processing steps, as well as to identify petrochemical environmental pollutants, drives the search for improved characterization methods. Comprehensive two-dimensional gas chromatography (GC × GC) is one of the best tools for that. The modulator used in GC × GC is responsible for trapping/sampling the first dimension (1D) column analytes, then reinjecting them in the form of narrow bands onto the second dimension (2D) column for further separation. Modulators used today generally fall into two categories, thermal and flow ones. Heater-based thermal modulators trap the 1D column effluent at or above ambient temperatures. Flow-based modulators utilize storage loop(s) to collect the 1D effluent, which is subsequently flushed into the second-dimension column for further separation. A single-stage, consumable-free thermal modulator and a reverse fill/flush flow modulator were compared for the characterization of base oils. Both were evaluated on their ability to achieve separation of several conventional and synthetic engine oils components. A reverse column set, polar 1D and nonpolar 2D, allowed group-type analysis of all classes, including linear, branched, and aromatic species. The results show the ability to achieve a comprehensive separation of specific compound classes and the differentiation of engine oil types and manufacturers. Soft ionization assisted in tentative identification of two alkylated diphenylamines in each sample. The advantages and limitations of both thermal and flow modulation are presented.

Analysis of Xinjiang asphaltenes using high precision spectroscopy

Asphaltenes are known for causing flow assurance problems in numerous oil fields. In this study we present a comparative spectroscopic analysis of Xinjiang heavy oil asphaltenes as part of ongoing research for an environmentally friendly and cheap chemical inhibitor. The goal is to predict the internal morphology of these asphaltenes through comparative analysis using high precision spectroscopy. Fourier transform infrared spectroscopy (FTIR), proton-nuclear magnetic resonance (H-NMR) and electrospray ionization Fourier transform ion cyclotron resonance combined with mass spectroscopy were used in this analysis. Several studies have demonstrated the enormous potential of these techniques to characterize hydrocarbons. Here we comparatively apply these techniques to characterize Xinjiang asphaltenes with reference to earlier imaging studies with atomic force and scanning tunneling microscopy to assign a structure to these asphaltenes. Results revealed the nature of the asphaltenes to be polycyclic, aromatic with both heteroatomic and metallic content. Thirteen basic and eleven non-basic/acidic nitrogen compounds fused within the aromatic network were identified. The mass distribution is in the range between 100-800 Da. H-NMR revealed various structural parameters (aromaticity and degree of unsaturation) and together with FTIR various functional groups were identified that include: ethers, sulphides, amides and sulfoxides. The predicted structures are consistent with the "island" and "aryl linked core" models.

Hydrocracking: A Perspective towards Digitalization

In a world of fast technological advancements, it is increasingly important to see how hydrocracking applications can benefit from and adapt to digitalization. A review of hydrocracking processes from the perspective of modeling and characterization methods is presented next to an investigation on digitalization trends. Both physics-based and data-based models are discussed according to their scope of use, needs, and capabilities based on open literature. Discrete and continuous lumping, structure-oriented lumping, and single event micro-kinetic models are reported as well as artificial neural networks, convolutional neural networks, and surrogate models. Infrared, near-infrared, ultra-violet and Raman spectroscopic methods are given with their examples for the characterization of feed or product streams of hydrocracking processes regarding boiling point curve, API, SARA, sulfur, nitrogen and metal content. The critical points to consider while modeling the system and the soft sensor are reported as well as the problems to be addressed. Optimization, control, and diagnostics applications are presented together with suggested future directions of interdisciplinary studies. The links required between the models, soft sensors, optimization, control, and diagnostics are suggested to achieve the automation goals and, therefore, a sustainable operation.

The New Test Procedure for Group-Type Composition of Base Oils of Lubricating Oils, Especially Emitted into the Environment

Mineral base oil, a product of multistep fine refining of the relevant fractions from vacuum distillation of crude oil, is a main component of so-called mineral lubricating oils containing aliphatic and alicyclic substituted aromatic hydrocarbons, i.e., derivatives of benzene and biphenyl. Mineral lubricating oil is composed mostly of mineral base oil and a low amount of enriching additives, most often products of advanced organic chemical technology. The application of mineral lubricating oils in open cutting systems has a very negative impact on environment and on the operator’s health. This work presents a simple, cheap and fast methodology allows identification of the group-type composition of base oil in lubricating oil and to estimate the content or total absence of base oil of mineral and vegetable origin in lubricating oil. The first step of the test is an in-situ screening for fluorescence of petroleum fraction under the 365 nm light. The next is the performance of infrared spectra with Fourier transformation (FT-MIR) to identify and estimate the content of vegetable oil and its derivatives and the performance of UV-Vis spectra to identify and determine the content of aromatic hydrocarbons, as well as dyes present in the lubricating oil. The last stage is normal phase thin layer chromatography (NP-TLC) using different visualization methods to evaluate the group-type composition of lubricating oil. Effectivity of the developed procedure has been confirmed during control of group-type composition evaluation of lubricating oils in cutting systems. The procedure can be also applied with respect to different oil matrices.

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.

Application of low-field, 1H/13C high-field solution and solid state NMR for characterisation of oil fractions responsible for wettability change in sandstones

Asphaltene adsorption on solid surfaces is a standing problem in petroleum industry. It has an adverse effect on reservoir production and development by changing rock wettability, plugging pore throats, and affects oil transport through pipelines. Asphaltene chemistry constitutes important part of the ageing process as part of petrophysical studies and core analysis. The mechanisms and contribution of various oil components to adsorption processes is not fully understood. To investigate the kinetics of the ageing process and address the relative contribution of different oil components, we prepared three sets of sandstone core plugs aged in different oil mixtures over various time intervals. Cores were then re-saturated with decane to evaluate their wetting state using low-field NMR relaxometry by monitoring a change of surface relaxivity. Adsorbed deposits were then extracted from cores for solution-state NMR analysis. Their ¹H and ¹H-¹³C correlation spectra obtained using heteronuclear single quantum coherence (HSQC) technique were matched to spectra of four SARA (saturates, aromatics, resins and asphaltenes) components of oil mixtures to deduce components of deposits and inter-component interactions. We notice that wettability reversal of rock is inversely proportional to initial asphaltene concentration. Analysis of deposits reveals an increase in their aliphatic content over ageing time, which is accompanied by a change of the morphology of the pore space due to cluster aggregates forming a network. Results suggest that the ageing process in respect to the wetting state of rock samples consists of three distinctive stages: (i) an early-time period, when the fraction of most polar asphaltenes creates a discontinuous layer corresponding to mixed-wet state; (ii) an intermediate-time interval, at which the full grain coverage may be achieved (at favourable chemical environment) corresponding to strong oil-wetting; (iii) a late-time stage, where intense macro-aggregates accumulation occurs, changing the pore space integrity. It is likely asphaltene-aliphatic interactions leading to growth of sub-micron size macro-aggregates.

NMR-Spectroscopy Determination of Fragmentary Composition of Bitumen and its Components

This paper represents and discusses the results of quantitative determination for fragmentary composition of road bitumen of grade BND 100/130 and its components (asphaltenes, resins and oils) by NMR spectroscopy method. Group chemical composition of the bitumen has been determined by adsorption chromatography method. It has been identified that the bitumen and its components consist only of aromatic and aliphatic protons, which account for 2.4‒10.2% and 9.8‒97.6% respectively. Availability of olefinic elements in them has not been identified. The most part (79‒81%) of nuclei of carbon atoms relates to quaternary carbon atoms of saturated compounds. Primary carbon atoms at methylene group (CH2) are contained in the least quantity: bitumen ‒ 1.32%; asphaltenes – 0.6%; resins – 3.24% and oils – 2.11%. Primary carbon atoms, linked with CH-group or aromatic nucleus, occupy an intermediate position and are contained in the quantity of 17‒20%.

Study of Surface Wettability Change of Unconsolidated Sand Using Diffuse Reflectance Infrared Fourier Transform Spectroscopy and Thermogravimetric Analysis

The effects exerted by the adsorption of vapors of a non-polar compound (deuterated benzene) and a polar compound (water) on the surface of Ottawa sand and a sample of reservoir sand (Channel), which was previously impregnated with silicon oil or two kinds of surfactants, (2-hydroxyethyl) trimethylammonium oleate (HETAO) and (2-hydroxyethyl)trimethylammonium azelate (HETAA), were studied by diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and thermogravimetric analysis (TGA). The surface chemistry of the sandstone rocks was elucidated by X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM) with energy dispersive X-ray spectroscopy (EDX). Terminal surface groups such as hydroxyls can strongly adsorb molecules that interact with these surface groups (surfactants), resulting in a wettability change. The wettability change effect suffered by the surface after treating it with surfactants was possible to be detected by the DRIFTS technique, wherein it was observed that the surface became more hydrophobic after being treated with silicon oil and HETAO; the surface became more hydrophilic after treating it with HETAA.

Towards unsupervised polyaromatic hydrocarbons structural assignment from SA-TIMS-FTMS data

With the advent of high resolution ion mobility analyzers and their coupling to ultrahigh resolution mass spectrometers, there is a need to further develop a theoretical workflow capable of correlating experimental accurate mass and mobility measurements with tridimensional candidate structures. In the present work, a general workflow is described for unsupervised tridimensional structural assignment based on accurate mass measurements, mobility measurements, in silico 2D-3D structure generation, and theoretical mobility calculations. In particular, the potential of this workflow will be shown for the analysis of polyaromatic hydrocarbons from Coal Tar SRM 1597a using selected accumulation - trapped ion mobility spectrometry (SA-TIMS) coupled to Fourier transform-ion cyclotron resonance mass spectrometry (FT-ICR MS). The proposed workflow can be adapted to different IMS scenarios, can utilize different collisional cross-section calculators and has the potential to include MSⁿ and IMSⁿ measurements for faster and more accurate tridimensional structural assignment.

Asphaltene: structural characterization, molecular functionalization, and application as a low-cost filler in epoxy composites

First comprehensive study focuses on extraction, characterization and functionalization of asphaltene as novel low-cost carbonaceous filler in epoxy resin.

Oil biodegradation. Water droplets in oil are microhabitats for microbial life

Anaerobic microbial degradation of hydrocarbons, typically occurring at the oil-water transition zone, influences the quality of oil reservoirs. In Pitch Lake, Trinidad and Tobago--the world's largest asphalt lake--we found that microorganisms are metabolically active in minuscule water droplets (1 to 3 microliters) entrapped in oil. Pyrotag sequencing of individual droplet microbiomes revealed complex methanogenic microbial communities actively degrading the oil into a diverse range of metabolites, as shown by nuclear magnetic resonance and Fourier transform ion cyclotron resonance mass spectrometry. High salinity and water-stable isotopes of the droplets indicate a deep subsurface origin. The 13.5% water content and the large surface area of the droplets represent an underestimated potential for biodegradation of oil away from the oil-water transition zone.

Molecular evidence of heavy-oil weathering following the M/V Cosco Busan spill: insights from Fourier transform ion cyclotron resonance mass spectrometry

Recent studies have highlighted a critical need to investigate oil weathering beyond the analytical window afforded by conventional gas chromatography (GC). In particular, techniques capable of detecting polar and higher molecular weight (HMW; > 400 Da) components abundant in crude and heavy fuel oils (HFOs) as well as transformation products. Here, we used atmospheric pressure photoionization Fourier transform ion cyclotron resonance mass spectrometry (APPI FT-ICR MS) to identify molecular transformations in oil-residue samples from the 2007 M/V Cosco Busan HFO spill (San Francisco, CA). Over 617 days, the abundance and diversity of oxygen-containing compounds increased relative to the parent HFO, likely from bio- and photodegradation. HMW, highly aromatic, alkylated compounds decreased in relative abundance concurrent with increased relative abundance of less alkylated stable aromatic structures. Combining these results with GC-based data yielded a more comprehensive understanding of oil spill weathering. For example, dealkylation trends and the overall loss of HMW species observed by FT-ICR MS has not previously been documented and is counterintuitive given losses of lower molecular weight species observed by GC. These results suggest a region of relative stability at the interface of these techniques, which provides new indicators for studying long-term weathering and identifying sources.

Prediction of physical-chemical properties of crude oils by 1H NMR analysis of neat samples and chemometrics

In this work, we report the feasibility study to predict the properties of neat crude oil samples from 300-MHz NMR spectral data and partial least squares (PLS) regression models. The study was carried out on 64 crude oil samples obtained from 28 different extraction fields and aims at developing a rapid and reliable method for characterizing the crude oil in a fast and cost-effective way. The main properties generally employed for evaluating crudes' quality and behavior during refining were measured and used for calibration and testing of the PLS models. Among these, the UOP characterization factor K (K(UOP)) used to classify crude oils in terms of composition, density (D), total acidity number (TAN), sulfur content (S), and true boiling point (TBP) distillation yields were investigated. Test set validation with an independent set of data was used to evaluate model performance on the basis of standard error of prediction (SEP) statistics. Model performances are particularly good for K(UOP) factor, TAN, and TPB distillation yields, whose standard error of calibration and SEP values match the analytical method precision, while the results obtained for D and S are less accurate but still useful for predictions. Furthermore, a strategy that reduces spectral data preprocessing and sample preparation procedures has been adopted. The models developed with such an ample crude oil set demonstrate that this methodology can be applied with success to modern refining process requirements.