Speciation of alkylated dibenzothiophenes through correlation of structure and gas chromatographic retention indexes

Qualitative Analysis of Nitrogen and Sulfur Compounds in Vacuum Gas Oils via Matrix-Assisted Laser Desorption Ionization Time of Flight Mass Spectrometry

Analysis of the heavy fractions in crude oil has been important in petroleum industries. It is well known that heavy fractions such as vacuum gas oils (VGOs) include heteroatoms, of which sulfur and nitrogen are often characterized in many cases. We conducted research regarding the molecular species analysis of VGOs. Further refine processes using VGOs are becoming important when considering carbon recycling. In this work, we attempted to classify compounds within VGOs provided by Kuwait Institute for Scientific Research. Two VGOs were priorly distillated from Kuwait Export crude and Lower Fars crude. Quantitative analysis was performed mainly using matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOFMS). MALDI-TOF-MS has been developed for analyzing high-molecular-weight compounds such as polymer and biopolymers. As matrix selection is one of the most important aspects in MALDI-TOFMS, the careful selection of a matrix was firstly evaluated, followed by analysis using a Kendrick plot with nominal mass series (z*). The objective was to evaluate if this work could provide an effective classification of VGOs compounds. The Kendrick plot is a well-known method for processing mass data. The difference in the Kendrick mass defect (KMD) between CnH2n-14S and CnH2n-20O is only 0.0005 mass units, which makes it difficult in general to distinguish these compounds. However, since the z* value showed effective differences during the classification of these compounds, qualitative analysis could be possible. The analysis using nominal mass series showed the potential to be used as an effective method in analyzing heavy fractions.

Deciphering structure and aggregation in asphaltenes: hypothesis-driven design and development of synthetic model compounds

Asphaltenes comprise the heaviest and least understood fraction of crude petroleum. The asphaltenes are a diverse and complex mixture of organic and organometallic molecules in which most of the molecular constituents are tightly aggregated into more complicated suprastructures. The bulk properties of asphaltenes arise from a broad range of polycyclic aromatics, heteroatoms, and polar functional groups. Despite much analytical effort, the precise molecular architectures of the material remain unresolved. To understand asphaltene characteristics and reactivity, the field has turned to synthetic model compounds that mirror asphaltene structure, aggregation behavior, and thermal chemistry, including the nucleation of coke. Historically, molecular asphaltene modeling was limited to commercial compounds, offering little illumination and few opportunities for hypothesis-driven research. More recently, however, rational molecular design and modern organic synthesis have started to impact this area. This review provides an overview of commercially available model compounds but is principally focused on the design and synthesis of structurally advanced and appropriately functionalized compounds to mimic the physical and chemical behavior of asphaltenes. Efforts to model asphaltene aggregation are briefly discussed, and a prognosis for the field is offered. A referenced tabulation of the synthetic compounds reported to date is provided.

Oil biodesulfurization: A review of applied analytical techniques

The wide use of fossil fuels and their associated environmental concerns, highlighted the importance of affordable and clean energy (goal 7), as adopted by the Sustainable Development Goals of the United Nations for 2030. For years now, the detection of sulfur components in liquid fuels is performed mainly for environmental and health purposes in compliance with the respective legislations. Towards this, the aerobic and anaerobic biodesulfurization (BDS) process, which entails the use of microorganisms to limit the sulfur concentration is followed. To ensure effective BDS, several traditional analytical methods are utilized, although they require bench-top, bulky, costly, and time-consuming instruments along with skilled personnel. The currently employed analytical methods are mostly chromatographic techniques (e.g. liquid and gas) coupled with various detectors. To start with, high-performance liquid chromatography with ultraviolet detector (HPLC-UV), as well as electrospray ionization-LC-mass spectrometry (ESI-LC-MS) were mostly reported. Additionally, many detectors were coupled to gas chromatography (CG) including atomic emission detector (GC-AED), flame ionization detector (GC-FID), flame photometric detector (GC-FPD), sulfur fluorescence detector (GC-SFD), mass selective detector (GC-MS), etc. The solid-phase microextraction (SPME) technique provides extra capabilities when added to the separation techniques. Towards the continuous interest in oil supercomplex synthesis, other atmospheric and surface desorption ionization techniques, as well as the multidimensional 2D chromatographic systems (GC × GC and LC × LC) were also investigated, due to their unsurpassed resolution power. The current review ends with final remarks per applied methodology and the necessity to respect and protect the human environment and life.

Simple, green approach for the synthesis of solid support-embedded PdNPs for ligand exchange

Green approaches have the potential to significantly reduce the costs and environmental impact of chemical syntheses. Here, the authors used green tea (GT) leaf extract to synthesise and anchor palladium nanoparticles (PdNPs) to silica. The synthesised PdNPs in GT extract were characterised by ultraviolet-visible spectroscopy, Fourier-transform infrared spectroscopy, X-ray diffraction, and transmission electron microscopy. PdNPs primarily formed as capped NPs dispersed in GT extract before reduction completed after 24 h. This capped phytochemical solution was employed as a green precursor solution to synthesise PdNP-embedded solid supports. The morphology of PdNPs anchored to silica differed to that of PdNPs in solution. Silica-embedded PdNPs was employed as a new ligand exchanger to isolate trace polycyclic aromatic sulphur heterocycles from a hydrocarbon matrix. The isolation efficiency of the new, greener ligand exchanger was the same as an efficient chemical ligand exchanger and may, therefore, hold promise for future applications.

Retention behavior of isomeric polycyclic aromatic sulfur heterocycles in gas chromatography on stationary phases of different selectivity

Retention indices for 48 polycyclic aromatic sulfur heterocycles (PASHs) were determined using gas chromatography with three different stationary phases: a 50% phenyl phase, a 50% liquid crystalline dimethylpolysiloxane (LC-DMPS) phase, and an ionic liquid (IL) phase. Correlations between the retention behavior on the three stationary phases and PASH geometry (L/B and T, i.e., length-to-breadth ratio and thickness, respectively) were investigated for the following four isomer sets: (1) 4 three-ring molecular mass (MM) 184Da PASHs, (2) 13 four-ring MM 234Da PASHs, (3) 10 five-ring MM 258Da PASHs, and (4) 20 five-ring MM 284Da PASHs. Correlation coefficients for retention on the 50% LC-DMPS vs L/B ranged from r=0.50 (MM 284Da) to r=0.77 (MM 234Da). Correlation coefficients for retention on the IL phase vs L/B ranged from r=0.31 (MM 234Da) to r=0.54 (MM 284Da). Correlation coefficients for retention on the 50% phenyl vs L/B ranged from r=0.14 (MM 258Da) to r=0.59 (MM 284Da). Several correlation trends are discussed in detail for the retention behavior of PASH on the three stationary phases.

Atmospheric pressure chemical ionization Fourier transform ion cyclotron resonance mass spectrometry for complex thiophenic mixture analysis

RATIONALE

Polycyclic aromatic sulfur heterocycles (PASHs) are detrimental species for refining processes in petroleum industry. Current mass spectrometric methods that determine their composition are often preceded by derivatization and dopant addition approaches. Different ionization methods have different impact on the molecular assignment of complex PASHs. The analysis of such species under atmospheric pressure chemical ionization (APCI) is still considered limited due to uncontrolled ion generation with low- and high-mass PASHs.

METHODS

The ionization behavior of a model mixture of five selected PASH standards was investigated using an APCI source with nitrogen as the reagent gas. A complex thiophenic fraction was separated from a vacuum gas oil (VGO) and injected using the same method. The samples were analyzed using Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS).

RESULTS

PASH model analytes were successfully ionized and mainly [M + H](+) ions were produced. The same ionization pattern was observed for the real thiophenic sample. It was found that S1 class species were the major sulfur-containing species found in the VGO sample. These species indicated the presence of alkylated benzothiophenic (BT), dibenzothiophenic (DBT) and benzonaphthothiophenic (BNT) series that were detected by APCI-FTICR MS.

CONCLUSIONS

This study provides an established APCI-FTICR MS method for the analysis of complex PASHs. PASHs were detected without using any derivatization and without fragmentation. The method can be used for the analysis of S-containing crude oil samples.

Heterogeneous photocatalytic reactions of sulfur aromatic compounds

Sulfur aromatic compounds, such as mono-, di-, tri-, and tetraalkyl-substituted thiophene, benzothiophenes, dibenzothiophenes, are the molecular components of many fossils (petroleum, oil shale, tar sands, bitumen). Structural units of natural, cross-linked heteroaromatic polymers present in brown coals, turf, and soil are similar to those of sulfur aromatic compounds. Many sulfur aromatic compounds are found in the streams of petroleum refining and upgrading (naphthas, gas oils) and in the consumer products (gasoline, diesel, jet fuels, heating fuels). Besides fossils, the structural fragments of sulfur aromatic compounds are present in molecules of certain organic semiconductors, pesticides, small molecule drugs, and in certain biomolecules present in human body (pheomelanin pigments). Photocatalysis is the frontier area of physical chemistry that studies chemical reactions initiated by absorption of photons by photocatalysts, that is, upon electronic rather than thermal activation, under "green" ambient conditions. This review provides systematization and critical review of the fundamental chemical and physicochemical information on heterogeneous photocatalysis of sulfur aromatic compounds accumulated in the last 20-30 years. Specifically, the following topics are covered: physicochemical properties of sulfur aromatic compounds, major classes of heterogeneous photocatalysts, mechanisms and reactive intermediates of photocatalytic reactions of sulfur aromatic compounds, and the selectivity of these reactions. Quantum chemical calculations of properties and structures of sulfur aromatic compounds, their reactive intermediates, and the structure of adsorption complexes formed on the surface of the photocatalysts are also discussed.

[Quantitative structure-gas chromatographic retention relationship of polycyclic aromatic sulfur heterocycles using molecular electronegativity-distance vector]

The chemical structures of 114 polycyclic aromatic sulfur heterocycles (PASHs) have been studied by molecular electronegativity-distance vector (MEDV). The linear relationships between gas chromatographic retention index and the MEDV have been established by a multiple linear regression (MLR) model. The results of variable selection by stepwise multiple regression (SMR) and the powerful predictive abilities of the optimization model appraised by leave-one-out cross-validation showed that the optimization model with the correlation coefficient (R) of 0.994 7 and the cross-validated correlation coefficient (Rcv) of 0.994 0 possessed the best statistical quality. Furthermore, when the 114 PASHs compounds were divided into calibration and test sets in the ratio of 2:1, the statistical analysis showed our models possesses almost equal statistical quality, the very similar regression coefficients and the good robustness. The quantitative structure-retention relationship (QSRR) model established may provide a convenient and powerful method for predicting the gas chromatographic retention of PASHs.

Fragmentation pathways of some benzothiophene radical cations formed by atmospheric pressure chemical ionisation

Polycyclic aromatic sulfur-containing compounds (PASHs) are commonly found in fossil fuels and are of considerable importance in environmental studies. This work presents detailed studies on the fragmentation patterns of radical cations formed from four representative PASHs, benzo[b]thiophene, dibenzothiophene, 4-methyldibenzothiophene and 4,6-dimethyldibenzothiophene, using tandem atmospheric pressure chemical ionization mass spectrometry (APCI-MS/MS). Understanding these fragmentation patterns can be a useful aid in the analysis of PASHs employing APCI or electron ionization (EI-MS/MS), either alone or in conjunction with liquid or gas chromatography.

Identification of unknown compounds on the basis of retention index data in comprehensive two-dimensional gas chromatography

The identification of unknown compounds in complex samples is very difficult. Comprehensive two-dimensional gas chromatography (GC x GC) provides very good resolution and improved identification reliability. Mass spectrometry is a powerful identification tool and retention index data are another good approach to this end. In this study, a second-order polynomial was used to calculate retention index data based on n-alkanes beyond the region of the 'isovolatile' curve in GC x GC, and the results in the 2nd dimension were validated by using the same stationary phase column in one-dimensional GC. To test the usefulness of the method, volatile compounds in a tobacco leaf extract fraction were analyzed using GC x GC, and 60 compounds were identified on the basis of their retention indices.

Quantitative structure-(chromatographic) retention relationships

Since the pioneering works of Kaliszan (R. Kaliszan, Quantitative Structure-Chromatographic Retention Relationships, Wiley, New York, 1987; and R. Kaliszan, Structure and Retention in Chromatography. A Chemometric Approach, Harwood Academic, Amsterdam, 1997) no comprehensive summary is available in the field. Present review covers the period of 1996-August 2006. The sources are grouped according to the special properties of kinds of chromatography: Quantitative structure-retention relationship in gas chromatography, in planar chromatography, in column liquid chromatography, in micellar liquid chromatography, affinity chromatography and quantitative structure enantioselective retention relationships. General tendencies, misleading practice and conclusions, validation of the models, suggestions for future works are summarized for each sub-field. Some straightforward applications are emphasized but standard ones. The sources and the model compounds, descriptors, predicted retention data, modeling methods and indicators of their performance, validation of models, and stationary phases are collected in the tables. Some important conclusions are: Not all physicochemical descriptors correlate with the retention data strongly; the heat of formation is not related to the chromatographic retention. It is not appropriate to give the errors of Kovats indices in percentages. The apparently low values (1-3%) can disorient the reviewers and readers. Contemporary mean interlaboratory reproducibility of Kovats indices are about 5-10 i.u. for standard non polar phases and 10-25 i.u. for standard polar phases. The predictive performance of QSRR models deteriorates as the polarity of GC stationary phase increases. The correlation coefficient alone is not a particularly good indicator for the model performance. Residuals are more useful than plots of measured and calculated values. There is no need to give the retention data in a form of an equation if the numbers of compounds are small. The domain of model applicability of models should be given in all cases.