Prediction of comprehensive two-dimensional gas chromatographic separations

Theoretical modeling and machine learning-based data processing workflows in comprehensive two-dimensional gas chromatography-A review

In recent years, comprehensive two-dimensional gas chromatography (GC × GC) has been gradually gaining prominence as a preferred method for the analysis of complex samples due to its higher peak capacity and resolution power compared to conventional gas chromatography (GC). Nonetheless, to fully benefit from the capabilities of GC × GC, a holistic approach to method development and data processing is essential for a successful and informative analysis. Method development enables the fine-tuning of the chromatographic separation, resulting in high-quality data. While generating such data is pivotal, it does not necessarily guarantee that meaningful information will be extracted from it. To this end, the first part of this manuscript reviews the importance of theoretical modeling in achieving good optimization of the separation conditions, ultimately improving the quality of the chromatographic separation. Multiple theoretical modeling approaches are discussed, with a special focus on thermodynamic-based modeling. The second part of this review highlights the importance of establishing robust data processing workflows, with a special emphasis on the use of advanced data processing tools such as, Machine Learning (ML) algorithms. Three widely used ML algorithms are discussed: Random Forest (RF), Support Vector Machine (SVM), and Partial Least Square-Discriminate Analysis (PLS-DA), highlighting their role in discovery-based analysis.

Comprehensive Thermodynamic Study of Alkyl-Cyclohexanes as Liquid Organic Hydrogen Carriers Motifs

Alkyl-cyclohexanes can be considered as suitable model compounds to understand the thermochemistry of aromatic compounds and their hydrogenated counterparts discussed as Liquid Organic Hydrogen Carrier systems. Thermochemical measurements on these hydrogen-rich compounds are thwarted by complications due to the 99.9 % purity limitation and sample size specific to these methods. However, the data on vaporisation and formation enthalpies are necessary to optimize the hydrogenation/dehydrogenation processes. In this work, various empirical and theoretical methods are described to reliably assess the gas phase enthalpies of formation and vaporization enthalpies of alkyl-substituted cyclohexanes. The empirical and quantum-chemical methods have been validated against reliable literature data and provide reasonable estimates with an accuracy comparable to that of the experimental data. The liquid phase enthalpies of formation of differently shaped alkyl-cyclohexanes were derived and used to estimate the energetics of their dehydrogenation reactions. The influence of alkyl substituents on the reaction enthalpy is discussed. The vapour pressures of typical hydrogen-rich compounds at technically relevant temperatures were calculated and compared to vapour pressures of biodiesel fuels measured in this work using the static method.

Top-Down Approach to Retention Time Prediction in Comprehensive Two-Dimensional Gas Chromatography-Mass Spectrometry

In this contribution, we describe a novel modeling approach to predicting retention times (t_r) in comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC × GC-ToF-MS) with a particular emphasis on the second-dimension (²D) retention time predictions (²t_r). This approach is referred to as a "top-down" approach in that it breaks down the complete GC × GC separation into two independent one-dimensional gas chromatography separations (1D-GC). In this regard, both dimensions, that is, first dimension (¹D) and second dimension (²D) are treated separately, and the cryogenic modulator is simply considered as a second consecutive injection device. Separate 1D-GC t_r predictions are performed on both dimensions using the same flow rate as the one deployed in the conventional GC × GC system. The separate t_r predictions are then combined to account for the two-dimensional separation. This model was applied to 24 analytes from 2 standard mixtures (Grob Test Mix and Fragrance Materials Test Mix) and assessed across 9 GC × GC chromatographic conditions. The experimental and predicted chromatographic retention space occupations were assessed by using the convex hull approach defined by the Delaunay triangulation. The predicted percentage of space occupation corresponded favorably with the experimental values. Furthermore, the top-down approach enabled an accurate prediction of the ²t_r of all investigated analytes, providing an average ²t_r modeling error of 0.26 ± 0.01 s.

Opportunities and challenges for the application of post-consumer plastic waste pyrolysis oils as steam cracker feedstocks: To decontaminate or not to decontaminate?

Thermochemical recycling of plastic waste to base chemicals via pyrolysis followed by a minimal amount of upgrading and steam cracking is expected to be the dominant chemical recycling technology in the coming decade. However, there are substantial safety and operational risks when using plastic waste pyrolysis oils instead of conventional fossil-based feedstocks. This is due to the fact that plastic waste pyrolysis oils contain a vast amount of contaminants which are the main drivers for corrosion, fouling and downstream catalyst poisoning in industrial steam cracking plants. Contaminants are therefore crucial to evaluate the steam cracking feasibility of these alternative feedstocks. Indeed, current plastic waste pyrolysis oils exceed typical feedstock specifications for numerous known contaminants, e.g. nitrogen (∼1650 vs. 100 ppm max.), oxygen (∼1250 vs. 100 ppm max.), chlorine (∼1460vs. 3 ppm max.), iron (∼33 vs. 0.001 ppm max.), sodium (∼0.8 vs. 0.125 ppm max.)and calcium (∼17vs. 0.5 ppm max.). Pyrolysis oils produced from post-consumer plastic waste can only meet the current specifications set for industrial steam cracker feedstocks if they are upgraded, with hydrogen based technologies being the most effective, in combination with an effective pre-treatment of the plastic waste such as dehalogenation. Moreover, steam crackers are reliant on a stable and predictable feedstock quality and quantity representing a challenge with plastic waste being largely influenced by consumer behavior, seasonal changes and local sorting efficiencies. Nevertheless, with standardization of sorting plants this is expected to become less problematic in the coming decade.

Retention-time prediction in comprehensive two-dimensional gas chromatography to aid identification of unknown contaminants

Comprehensive two-dimensional (2D) gas chromatography (GC×GC) coupled to mass spectrometry (MS, GC×GC-MS), which enhances selectivity compared to GC-MS analysis, can be used for non-directed analysis (non-target screening) of environmental samples. Additional tools that aid in identifying unknown compounds are needed to handle the large amount of data generated. These tools include retention indices for characterizing relative retention of compounds and prediction of such. In this study, two quantitative structure–retention relationship (QSRR) approaches for prediction of retention times (¹t_R and ²t_R) and indices (linear retention indices (LRIs) and a new polyethylene glycol–based retention index (PEG-²I)) in GC × GC were explored, and their predictive power compared. In the first method, molecular descriptors combined with partial least squares (PLS) analysis were used to predict times and indices. In the second method, the commercial software package ChromGenius (ACD/Labs), based on a “federation of local models,” was employed. Overall, the PLS approach exhibited better accuracy than the ChromGenius approach. Although average errors for the LRI prediction via ChromGenius were slightly lower, PLS was superior in all other cases. The average deviations between the predicted and the experimental value were 5% and 3% for the ¹t_R and LRI, and 5% and 12% for the ²t_R and PEG-²I, respectively. These results are comparable to or better than those reported in previous studies. Finally, the developed model was successfully applied to an independent dataset and led to the discovery of 12 wrongly assigned compounds. The results of the present work represent the first-ever prediction of the PEG-²I.

Graphical abstract

Comprehensive 2D gas chromatography-time-of-flight mass spectrometry with 2D retention indices for analysis of volatile compounds in frankincense (Boswellia papyrifera)

Frankincense gum resin secreted from Boswellia papyrifera was analysed by comprehensive 2D gas chromatography hyphenated with accurate mass time-of-flight mass spectrometry (GC×GC-accTOFMS). Direct multiple injection experiments with stepwise isothermal temperature programming were then performed to construct isovolatility curves for reference alkane series in GC×GC. This provides access to calculation of second dimensional retention indices (²I). More than 500 peaks were detected and 220 compounds mainly comprising monoterpenes, sesquiterpenes, diterpenes and oxygenated forms of these compounds were identified according to their ¹I, ²I and accurate mass data. The study demonstrates the capability of GC×GC-accTOFMS with retention data on two separate column phases, as an approach for improved component identification. A greater number of identified and/or tentatively identified terpenoids in this traditional Chinese medicine allow for a more comprehensive coverage of the volatile composition of frankincense.

Surface fitting for calculating the second dimension retention index in comprehensive two-dimensional gas chromatography mass spectrometry

Comprehensive two-dimensional gas chromatography mass spectrometry (GC × GC-MS) has been widely used for analysis of volatile compounds. However, the second dimension retention index (I) of each compound is not widely used to aid compound identification owing to the limited accuracy of I calculation. We report a surface fitting approach to the calculation of I using n-alkanes (C7-C30) as references, where the second dimension retention time (2tR) and the second dimension column temperature (2Te) formed the X-Y plane and the I was the Z-axis to form the I surface. Compared to the conventional approach for calculating I using isovolatility curves, the surface fitting approach eliminated the construction of isovolatility curves for the reference compounds and gives better reproducibility. The goodness of the proposed surface fitting achieved R2 = 0.9999 and RMSE = 6.1 retention index units (iu). Ten-fold cross validation demonstrated the surface fitting approach had a good predictability with average R2 = 0.9999 and RMSE = 6.6 iu. The developed method was also applied to calculate the second dimension retention indices of compound standards in two commercial mixtures MegaMix A and MegaMix B. The mean standard deviation of the calculated I was only 1.6 iu for compounds in MegaMix A and 3.4 iu for compounds in MegaMix B. Compared with the literature results, the small value of standard deviation in the calculated retention index using surface fitting method shows that the surface fitting method has less measurement variability than the conventional isovolatility curve approach.

Recent advances in the application of 2-dimensional gas chromatography with soft and hard ionisation time-of-flight mass spectrometry in environmental analysis

Two-dimensional gas chromatography has huge power for separating complex mixtures. The principles of the technique are outlined together with an overview of detection methods applicable to GC × GC column effluent with a focus on selectivity. Applications of GC × GC techniques in the analysis of petroleum-related and airborne particulate matter samples are reviewed. Mass spectrometric detection can be used alongside spectral libraries to identify eluted compounds, but in complex petroleum-related and atmospheric samples, when used conventionally at high ionisation energies, may not allow differentiation of structural isomers. Available low energy ionisation methods are reviewed and an example given of the additional structural information which can be extracted by measuring mass spectra at both low and high ionisation energies, hence greatly enhancing the selectivity of the technique.

Gas Chromatographic Techniques in Metabolomics

High chemical diversity and abundances ranging from trace to millimolar levels still constitute at times insurmountable challenges in the comprehensive analysis of metabolites in biomedical specimens. Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) hyphenated with separation techniques such as liquid chromatography (LC), gas chromatography (GC) and capillary electrophoresis (CE) are the most frequently used techniques for both targeted and discovery‐driven metabolomics. Of the separation techniques, comprehensive two‐dimensional gas chromatography (GC×GC) offers the highest peak resolution and capacity, and in combination with MS lower quantification limits in the submicromolar concentration range are realized. Moreover, electron ionization (EI), the most prominent ionization technique for GC‐MS, is highly reproducible, facilitating the generation of mass spectral libraries for routine metabolite identification. However, GC analysis often requires a derivatization prior to analysis and not all metabolite derivatives are recorded in the libraries available. Consequently, metabolite identification is still a major challenge. To identify unknown metabolite signals, soft ionization techniques in combination with high‐resolution MS are employed to determine the accurate mass of the quasi‐molecular ion. The latter is used to calculate elemental formulae that can be fed into metabolite databases for a putative identification or used for the interpretation of EI spectra.

A method of calculating the second dimension retention index in comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry

A method was developed to calculate the second dimension retention index of comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC/TOF-MS) data using n-alkanes as reference compounds. The retention times of the C(7)-C(31) alkanes acquired during 24 isothermal experiments cover the 0-6s retention time area in the second dimension retention time space, which makes it possible to calculate the retention indices of target compounds from the corresponding retention time values without the extension of the retention space of the reference compounds. An empirical function was proposed to show the relationship among the second dimension retention time, the temperature of the second dimension column, and the carbon number of the n-alkanes. The proposed function is able to extend the second dimension retention time beyond the reference n-alkanes by increasing the carbon number. The extension of carbon numbers in reference n-alkanes up to two more carbon atoms introduces <10 retention index units (iu) of deviation. The effectiveness of using the proposed method was demonstrated by analyzing a mixture of compound standards in temperature programmed experiments using 6 different initial column temperatures. The standard deviation of the calculated retention index values of the compound standards fluctuated from 1 to 12 iu with a mean standard deviation of 5 iu.

Photo-ionisation mass spectrometry as detection method for gas chromatography

Mass spectrometry (MS) with soft ionisation techniques (i.e. ionisation without fragmentation of the analyte molecules) for gaseous samples exhibits interesting analytical properties for direct analysis applications (i.e. direct inlet mass spectrometric on-line monitoring) as well as mass spectrometric detection method for gas chromatography (GC-MS). Commonly either chemical ionisation (CI) or field ionisation (FI) is applied as soft ionisation technology for GC-MS. An interesting alternative to the CI and FI technologies methods are photo-ionisation (PI) methods. PI overcomes some of the limitations of CI and FI and furthermore add some unique analytical properties. The resonance enhanced multi-photon ionisation (REMPI) method uses intense UV-laser pulses (wavelength range approximately 350-193 nm) for highly selective, sensitive and soft ionisation of predominately aromatic compounds. The single photon ionisation (SPI) method utilises VUV light (from lamps or laser sources, wavelengths range approximately 150-110 nm) can be used for a universal soft ionisation of organic molecules. In this article the historical development as well as the current status and concepts of gas chromatography hyphenated to photo-ionisation mass spectrometry are reviewed.

Solid phase microextraction-comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry for the analysis of honey volatiles

Head-space solid phase microextration (SPME), followed by comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GCxGC-TOFMS), has been implemented for the analysis of honey volatiles, with emphasis on the optimal selection of SPME fibre and the first- and second-dimension GC capillaries. From seven SPME fibres investigated, a divinylbenzene/Carboxen/polydimethylsiloxane (DVB/CAR/PDMS) 50/30 microm fibre provided the best sorption capacity and the broadest range of volatiles extracted from the headspace of a mixed honey sample. A combination of DB-5ms x SUPELCOWAX 10 columns enabled the best resolution of sample components compared to the other two tested column configurations. Employing this powerful analytical strategy led to the identification of 164 volatile compounds present in a honey mixture during a 19-min GC run. Combination of this simple and inexpensive SPME-based sampling/concentration technique with the advanced separation/identification approach represented by GCxGC-TOFMS allows a rapid and comprehensive examination of the honey volatiles profile. In this way, the laboratory sample throughput can be increased significantly and, at the same time, the risk of erroneous identification, which cannot be avoided in one-dimensional GC separation, is minimised.

One-dimensional and comprehensive two-dimensional gas chromatography coupled to soft photo ionization time-of-flight mass spectrometry: A two- and three-dimensional separation approach

Soft laser photo-ionization mass spectrometry is presented as a separation dimension hyphenated with gas chromatographic techniques. Single photon ionization (SPI) is a universal soft ionization method which ionizes organic molecules with an ionization potential below 10.5 eV if 118 nm laser radiation is used. The inherently soft ionization of photo ionization techniques can further be utilized together with gas chromatography as a comprehensive two-dimensional separation method (GC x MS), using the GC retention time as first separation dimension and the molecular mass as second separation dimension. Some GC x MS chromatograms of diesel petroleum samples using SPI are presented and discussed. Finally, it is demonstrated that the coupling of soft SPI mass spectrometry with comprehensive two-dimensional gas chromatography (GC x GC) provides a three-dimensional separation technique (GC x GC x SPI-MS).