Multidimensional Gas Chromatography: Advances in Instrumentation, Chemometrics, and Applications

Exploring accurate mass measurements in pixel-based chemometrics: Advancing coffee classification with GC-HRMS-A proof of concept study

This paper presents a study that assesses the application of chemometrics for classifying coffee samples in a quality control context. High-resolution and accurate mass measurements were utilized as input for pixel-based orthogonal partial least squares discriminant analysis (OPLS-DA) models. The compositional data were acquired through a fully automated workflow combining headspace solid-phase microextraction and gas chromatography-high-resolution mass spectrometry (GC-HRMS) using an FT-Orbitrap® mass analyzer. A workflow centered on accurate mass measurements was successfully utilized for group-type analysis, offering an alternative to methods relying solely on MS similarity searches. The predictive models underwent thorough evaluation, demonstrating robust multivariate classification performance. Five key coffee attributes, bitterness, acidity, body, intensity, and roasting level were successfully predicted using GC-HRMS data. The results revealed strong predictive accuracy across all models, ranging from 88.9 % (bitterness) to 94.4 % (roasting level). This study represents a significant advancement in automating methods for coffee quality control, notably increasing the predictive ability of the models compared to existing literature.

Chemometrics combined with comprehensive two-dimensional gas chromatography-mass spectrometry for the identification of Baijiu vintage

The identification of baijiu vintage is crucial for quality assessment and economic value determination. However, its complex composition and multifaceted influences pose significant technical challenges, necessitating research into its aging mechanisms and the development of related identification methods. This study utilized Chemometrics in conjunction with GC × GC-TOFMS for Baijiu Vintage identification. Data compression achieved a reduction of over 1000-fold without compromising key information, enabling analysis on many samples and get their changing regular in a big matrix by MCR. Subsequently, MCR-ALS facilitated the extraction of physical and chemical meaningful information related to baijiu vintage. Key MCR principal components suitable for qualitative and quantitative assessments were selected using CARS-PLS. The regression model demonstrated errors of less than one year. Furthermore, a PLS-DA model provided 30 MCR principal components as potential markers. The research results provide technical support for baijiu vintage identification and lay the groundwork for studying the changing patterns of flavor compounds in baijiu.

High-efficiency effect-directed analysis (EDA) advancing toxicant identification in aquatic environments: Latest progress and application status

Facing the great threats to ecosystems and human health posed by the continuous release of chemicals into aquatic environments, effect-directed analysis (EDA) has emerged as a powerful tool for identifying causative toxicants. However, traditional EDA shows problems of low-coverage, labor-intensive and low-efficiency. Currently, a number of high-efficiency techniques have been integrated into EDA to improve toxicant identification. In this review, the latest progress and current limitations of high-efficiency EDA, comprising high-coverage effect evaluation, high-resolution fractionation, high-coverage chemical analysis, high-automation causative peak extraction and high-efficiency structure elucidation, are summarized. Specifically, high-resolution fractionation, high-automation data processing algorithms and in silico structure elucidation techniques have been well developed to enhance EDA. While high-coverage effect evaluation and chemical analysis should be further emphasized, especially omics tools and data-independent mass acquisition. For the application status in aquatic environments, high-efficiency EDA is widely applied in surface water and wastewater. Estrogenic, androgenic and aryl hydrocarbon receptor-mediated activities are the most concerning, with causative toxicants showing the typical structural features of steroids and benzenoids. A better understanding of the latest progress and application status of EDA would be beneficial to further advance in the field and greatly support aquatic environment monitoring.

Key Aroma Differences in Volatile Compounds of Aged Feng-Flavored Baijiu Determined Using Sensory Descriptive Analysis and GC×GC-TOFMS

Sensory descriptive analysis of aged feng-flavored Baijiu liquor indicated notable differences in samples of different ages. The samples of freshly distilled Baijiu and those with shorter storage times exhibit bran and fresh green flavors, whereas, with increasing storage time, honey, sweet, and floral fragrances are gradually enhanced. Samples of feng-flavored Baijiu were prepared using headspace solid-phase microextraction, followed by comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry. A total of 496 compounds were identified in all samples, mainly categorized as 14 groups of substances, including esters and aldehydes. Interestingly, 42 of these substances were found in Feng-flavored Baijiu for the first time. Chemometrics was used to analyze the key differential compounds. First, 143 differential compounds closely related to aging were preliminarily screened, and principal component analysis revealed that these compounds were separated by baijiu age. Then, 65 differential compounds were selected by partial least squares discriminant analysis. Furthermore, 43 key differential compounds were selected by combined analysis with variable importance in projection and Pearson correlation coefficients. Partial least squares regression was used to study the correlation between the sensory properties and key differential compounds, and the results indicated that most compounds were closely related to the aging period of the Baijiu. The results of this study provide a theoretical basis and reference for flavor research on feng-flavored Baijiu.

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.

Score Function for the Optimization of the Performance of Forward Fill/Flush Differential Flow Modulation for Comprehensive Two-Dimensional Gas Chromatography

Modulation is the key element of the comprehensive 2D gas chromatography separation. Forward fill/flush flow modulation is cost effective, robust and suitable for analysis of a wide range of samples. Even though this modulation system is well known, studies regarding its optimization are sparse. In this work, based on hundreds of experiments involving multiple column sets and modulation conditions, an approach was proposed that permits to facilitate the choice of the forward fill/flush flow modulation parameters. A score function was developed that allows to predict the forward fill/flush flow modulation process efficiency as judged by the modulated peak shape. The score function was based on the physical rules for optimized and quantitative forward fill/flush flow modulation proposed in our previous work, which state that the sum of the fill and flush modulation distances should be close to the modulation channel length and that the ratio of the flush and fill distances should be sufficiently high for efficient channel flushing. The score function was embedded in a freely available tool in the form of a forward fill/flush flow modulation calculator, which allows the user either to quickly check the relevancy of the modulation operating conditions or to obtain a suggestion for optimal modulation parameters.

Two-dimensional chromatography for the analysis of valorisable biowaste: A review

Various everyday areas such as agriculture, wood industry, and wastewater treatment yield residual biowastes in large amounts that can be utilised for the purpose of sustainability and circular economy. Depending on the type of biowaste, they can be used to extract valuable chemicals or converted into alternative fuels. However, for efficient valorisation, these processes need to be monitored, for which thorough chemical characterisation can be highly beneficial. For this aim, two-dimensional (2D) chromatography can be favourable, as it has a higher peak capacity and sensitivity than one-dimensional (1D) chromatography. Therefore, here we review the studies published since 2010 involving gas chromatography (GC) or liquid chromatography (LC) as one of the dimensions. For the first time, we present the 2D chromatographic characterisation of various biowastes valorised for different purposes (chemical, fuels), together with future prospects and challenges. The aspects related to the 2D chromatographic analysis of polar, poorly volatile, and thermally unstable compounds are highlighted. In addition, it is demonstrated how different 2D setups can be applied for monitoring the biowaste conversion processes.

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 reversed-phase×chiral two-dimensional liquid chromatography coupled to quadrupole-time-of-flight tandem mass spectrometry with post-first dimension flow splitting for untargeted enantioselective amino acid analysis

This work describes a comprehensive achiral × chiral two-dimensional liquid chromatography separation for enantioselective amino acid analysis coupled to electrospray ionization-tandem mass spectrometry detection using data-independent acquisition. Flow splitting after the first and second dimension separation was utilized for volumetric flow reduction and for enabling a multi-detector approach (with ultraviolet, fluorescence, charged aerosol, and MS detection), respectively. Derivatization with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate provided a chromophore, a fluorophore, and an efficient mass tag for efficient ionization in positive electrospray ionization-mass spectrometry. Chiral columns often have limitations in terms of their chemoselectivity, which may be a problem when complex sample mixtures with structurally related compounds need to be separated. It can be alleviated by a reversed-phase×chiral two-dimensional-liquid chromatography setup, in which the first dimension provides the chemoselectivity and a chiral tandem column constituted of quinine-carbamate derived weak anion-exchanger and zwitterionic ion-exchanger in the second dimension separation of D- and L-amino acid enantiomers. The method was used to control the stereointegrity of the therapeutic peptide octreotide. After hydrolysis, all amino acid constituents were detected with the correct configuration and composition. Some options for flow splitting and integration of destructive detectors in the first dimension separation are outlined.

Comprehensive two-dimensional gas chromatography under low-pressure conditions

The analysis of thermally labile and high-boiling point compounds by gas chromatography (GC) can be a challenge. One technique to overcome these challenges is low-pressure GC, which uses the vacuum produced from the mass spectrometer and wide-bore columns to elute compounds at significantly lower temperatures. While GC-MS is a powerful technique, comprehensive two-dimensional gas chromatography (GC × GC), allows for resolution of compounds that would typically coelute using GC. In this study, a pesticide standard mixture (8270 MegaMix Standard) was analyzed using a conventional GC × GC-TOFMS configuration (0.25 mm inner diameter (i.d.) to a 0.18 mm i.d. column) and low-pressure GC × GC-TOFMS configuration (0.53 mm i.d. to a 0.53 mm i.d. column). Elution temperatures, sensitivity, and peak capacity were investigated for both configurations. Compounds eluted an average of 30 °C less on the low-pressure GC × GC-TOFMS configuration compared to the conventional GC × GC-TOFMS configuration. Moreover, the compounds were separated in ∼13 min on the low-pressure GC × GC-TOFMS as opposed to 33 min for conventional GC × GC-TOFMS. However, due to the wide-bore columns and faster runtimes the low-pressure GC × GC-TOFMS had a lower, β corrected 2D peak capacity, nc,β,2D, of 1260 while the conventional GC × GC-TOFMS was 3588. Interestingly, both configurations yielded a similar peak capacity production of 93 peaks/min and 107 peaks/min for low-pressure and conventional GC × GC-TOFMS, respectively. A "real world" sample of diesel fuel was tested on the low-pressure and conventional GC × GC-TOFMS configurations and similar results were obtained compared to the pesticide standard mix except the peak capacity production of the low-pressure GC × GC-TOFMS configuration was higher than that of the conventional GC × GC-TOFMS method.

Aroma correlation assisted volatilome coupled network analysis strategy to unveil main aroma-active volatiles of Rosa roxburghii

To investigate the main aroma-active volatiles out from comprehensive chemical profile, we proposed an aroma correlation assisted volatilome coupled network analysis strategy and applied it to the study of Rosa roxburghii. Based on 475 detected volatiles with GC × GC-TOF/MS analysis, the volatilome was screened with both positive aroma activities and high contents to discover some aliphatic acids, alcohols, aldehydes and esters, terpenoids as well as some alkenes and ketones. Especially, a series of homologous C6- and C8- acids, alcohols, aldehydes, esters as well as some terpenoids like limonene take the predominant contributions to the aromas. Moreover, two aroma-active and aroma-contributing volatile groups including acid-aldehyde-alcohol-ester and terpenoid groups were clustered to integrally be responsible for the major aromas of R. roxburghii with network analysis. Additionally, the accumulation of C6- and C8-family homologous aliphatic volatiles was also elucidated with linoleic and linolenic acid derived pathways. This strategy is practical to investigate the main aroma-active volatiles based on volatilome.

Volatile Composition of Fortification Grape Spirit and Port Wine: Where Do We Stand?

Port wine's prominence worldwide is unequivocal and the grape spirit, which comprises roughly one fifth of the total volume of this fortified wine, is also a contributor to the recognized quality of this beverage. Nonetheless, information about the influence of the grape spirit on the final aroma of Port wine, as well as its volatile composition, is extremely limited. Moreover, the aroma characteristics of Port wines are modulated mainly by their volatile profiles. Hence, this review presents a detailed overview of the volatile composition of the fortification spirit and Port wine, along with the methodologies employed for their characterization. Moreover, it gives a general overview of the Douro Demarcated Region (Portugal) and the relevance of fortification spirit to the production of Port wine. As far as we know, this review contains the most extensive database on the volatile composition of grape spirit and Port wine, corresponding to 23 and 208 compounds, respectively. To conclude, the global outlook and future challenges are addressed, with the position of the analytical coverage of the chemical data on volatile components discussed as crucial for the innovation centered on consumer preferences.

Development and Application of a Novel Multiloop Splitter-Based Non-cryogenic Artificial Trapping Modulation System in Comprehensive Two-Dimensional Gas Chromatography

A multiloop splitter-based non-cryogenic artificial trapping (M-SNAT) modulation technique was established, which applied the first (¹D) nonpolar and the second (²D) polar columns, deactivated fused silica (DFS) columns, a microfluidic Deans switch (DS), and splitters located between the ¹D column outlet and the DS. The splitters were connected into multiple loops with a progressively doubled perimeter of the next loop. This enabled a duplex splitting mechanism within each loop consisting of splitting of analyte pulses, the pulse delay, and their combination which led to equally split peaks of the same analytes with the number of split peaks (n_split) equal to 2^m (m = number of loops). This system resulted in local profiles of artificially split-and-trapped analytes prior to their selective transfers onto the ²D column by means of periodic multiple heart-cuts (H/C). The developed SNAT approach can be successful, providing that the ratio of modulation period to sampling time (P_M/t_samp) is equal to n_split. The approach with n_split = 16 was further developed into a single device platform and applied for the modulation of a wide range of compounds in waste tire pyrolysis samples with the RSD of ≤0.01 and <10% for the one-dimensional modulated peak times and peak areas, respectively (n = 50). The method enabled an artificial modulation mechanism without cryogen consumption and enhanced the ²D peak capacity (²n_c) and ²D separation by use of a longer ²D column.

Comprehensive Two-Dimensional Gas Chromatography as a Bioanalytical Platform for Drug Discovery and Analysis

Over the last decades, comprehensive two-dimensional gas chromatography (GC×GC) has emerged as a significant separation tool for high-resolution analysis of disease-associated metabolites and pharmaceutically relevant molecules. This review highlights recent advances of GC×GC with different detection modalities for drug discovery and analysis, which ideally improve the screening and identification of disease biomarkers, as well as monitoring of therapeutic responses to treatment in complex biological matrixes. Selected recent GC×GC applications that focus on such biomarkers and metabolite profiling of the effects of drug administration are covered. In particular, the technical overview of recent GC×GC implementation with hyphenation to the key mass spectrometry (MS) technologies that provide the benefit of enhanced separation dimension analysis with MS domain differentiation is discussed. We conclude by highlighting the challenges in GC×GC for drug discovery and development with perspectives on future trends.

Comparative Study on the Volatile Organic Compounds and Characteristic Flavor Fingerprints of Five Varieties of Walnut Oil in Northwest China Using Using Headspace Gas Chromatography-Ion Mobility Spectrometry

Odor is an important characteristic of walnut oil; walnut oil aromas from different varieties smell differently. In order to compare the differences of volatile flavor characteristics in different varieties of walnut oil, the volatile organic compounds (VOCs) of walnut oil from five different walnut varieties in Northwest China were detected and analyzed using headspace gas chromatography–ion mobility spectrometry (HS–GC–IMS). The results showed that 41 VOCs in total were identified in walnut oil from five different varieties, including 14 aldehydes, 8 alcohols, 4 ketones, and 2 esters. Walnut oil (WO) extracted from the “Zha343” variety was most abundant in VOCs. The relative odor activity value (ROAV) analysis showed that aldehydes were the main aroma substances of walnut oil; specifically, hexanal, pentanal, and heptanal were the most abundant. Fingerprints and heat map analysis indicated that WO extracted from the “Xin2”, “185”, “Xin’guang”, and “Zha343” varieties, but not from the “Xinfeng” variety, had characteristic markers. The relative content differences of eight key VOCs in WO from five varieties can be directly compared by Kruskal–Wallis tests, among which the distribution four substances, hexanal (M), hexanal (D), pentanal (M), (E)-2-hexanal (M), presented extremely significant differences (P<0.01). According to the results of the principal component analysis (PCA), WO extracted from the “Zha343” variety was distinct from the other four varieties; in addition, WO extracted from the “Xin2” variety exhibited similarity to WO extracted from the “185” variety, and WO extracted from the “Xinfeng” variety showed similarity to WO extracted from the “Xin’guang” variety. These results reveal that there are certain differences in the VOCs extracted from five different WO varieties, making it feasible to distinguish different varieties of walnut oil or to rapidly detect walnut oil quality based on its volatile substances profile.

Evaluation of different getter substrates using two-dimensional gas chromatography with time of flight mass spectrometry

While understanding hydrogen uptake by organic based getters such as 1,4-bis(phenylethynyl)benzene (DEB) combined with a palladium(0)bis(dibenzylideneacetone) (Pd(dba)₂) catalyst is essential, another crucial element to understand is the decomposition of the DEB, Pd(dba)₂, and/or substrate material. The breakdown of these materials may create unwanted volatiles, which may interact with and lead to deterioration of sensitive materials. Moreover, it is critical to understand if different substrates cause the getter and/or catalyst to degrade in different manners. Utilizing comprehensive two-dimensional gas chromatography (GC×GC) with time-of-flight mass spectrometry (TOFMS), the presence of volatiles located in the headspace of various DEB/Pd(dba)₂ getter substrates is examined. These samples include a getter infused silicone foam, a hydrogenated getter infused silicone foam, an activated carbon getter pellet, and a hydrogenated activated carbon getter pellet. Application of Fisher ratio (F-ratio) analyses lead to the identification of several compounds that are generated or consumed through the hydrogenation process. These include benzene derivatives such as bibenzyl, benzaldehyde, and vinyl benzoate in the activated carbon pellets and 1,5-diphenyl-3-pentanone, toluene, styrene, and 1-1'(2-pentene 1,5-diyl)bis benzene in the silicone foams, and alkane/alkene derivatives such undecane, 4-tridecene, and decane in the activated carbon pellets and 2,6-dimethyl undecane in the silicone foams. Further comparison of the different hydrogenated getter substrates (e.g. activated carbon pellet and silicone foam) indicates that the different substrates alter the decomposition products created from the degradation of the DEB and Pd(dba)₂.

Optimization of Parameters for ROI Data Compression for Nontargeted Analyses Using LC-HRMS

Nontargeted analyses of low-concentration analytes in the information-rich data collected by liquid chromatography with high-resolution mass spectrometry detection can be challenging to accomplish in an efficient and comprehensive manner. The aim of this study is to demonstrate a workflow involving targeted parameter optimization for entire chromatograms using region of interest (ROI) data compression uncoupled from a subsequent tile-based Fisher ratio (F-ratio) analysis, a supervised discovery-based method, for the discovery of low-concentration analytes. Soil samples spiked with 18 pesticides at nominal concentrations ranging from 0.1 to 50 ppb for a total of six sample classes served as challenging samples to demonstrate the overall workflow. Optimization of two parameters proved to be the most critical for ROI data compression: the signal threshold parameter and the admissible mass deviation parameter. The parameter optimization method workflow we introduce is based upon spiking known analytes into a representative sample and determining the number of detectable spikes and the Δppm for various combinations of the signal threshold and admissible mass deviation, where Δppm is the absolute value of the difference between the theoretical m/z and the ROI m/z. Once optimal parameters are determined providing the lowest average Δppm and the greatest number of detectable analytes, the optimized parameters can be utilized for the intended analysis. Herein, tile-based F-ratio analysis was performed on the ROI compressed data of all spiked soil samples first by applying ROI parameters recommended in the literature, referred to herein as the initial ROI parameters, and finally by the combination of the two optimized parameters. Using the initial ROI parameters, three pesticides were discovered, whereas all 18 spiked pesticides were discovered by optimizing both ROI parameters.

Comparison of aroma active compounds in cold- and hot-pressed walnut oil by comprehensive two-dimensional gas chromatography-olfactory-mass spectrometry and headspace-gas chromatography-ion mobility spectrometry

Aroma composition of cold-pressed walnut oil (CWO) and hot-pressed walnut oil (HWO) was analyzed by comprehensive two-dimensional gas chromatography-olfactory-mass spectrometry (GC × GC-O-MS) and headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS). A total of 83 and 197 compounds were identified in the CWO and HWO, respectively; among these, 76 and 123 compounds were sniffed exclusively by GC × GC-O-MS, respectively. A total of 36 volatile compounds were detected by HS-GC-IMS, of which 10 in CWO and 32 in HWO. Based on of flavor dilution (FD) factors, odor-activity values (OAVs), and recombination and omission experiments, 1-octen-3-ol, cyclohexanol, and benzaldehyde were found to be the key aroma-active compounds in CWO, while 3-methylbutanal, (E,E)-2,4-nonadienal, nonanal, 1-octen-3-ol, 3-pentanol, 1-octanol, and furfural were the key aroma-active compounds in HWO. Moreover, Maillard reaction and lipid oxidation were found to play an important role in flavor formation in HWO. This study provides a guide to improve the quality of walnut oil based on aroma characteristics.

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.

Analysis of complex drugs by comprehensive two-dimensional gas chromatography and high-resolution mass spectrometry: detailed chemical description of the active pharmaceutical ingredient sodium bituminosulfonate and its process intermediates

The European pharmacopeia provides analytical methods for the chemical characterization of active pharmaceutical ingredients (APIs). However, the complexity of some APIs exceeds the limitations of the currently prevailing physicochemical methods. Sodium bituminosulfonate (SBS) is described by the collection of key parameters of generalizing criteria such as dry matter, sulfur and sodium content, and neutrality, but techniques to unravel the complexity on a molecular level are lacking. We present a study based on online derivatization with tetramethylammonium hydroxide in combination with comprehensive two-dimensional gas chromatography coupled to an electron ionization high-resolution time-of-flight mass spectrometer (GC × GC-HR-ToF–MS) for the chemical description of SBS as well as its process intermediates. The application of GC × GC allowed the comprehensive description of the chemical components in the API and the process intermediates for the first time. Furthermore, it was possible to classify peaks regarding their elemental and structural composition based on accurate mass information, elution behavior, and mass fragmentation pattern. This work demonstrates not only the general applicability, advantages but also limitations of GC × GC for the characterization of APIs for complex drugs.

Graphical Abstract

Multidimensional Gas Chromatography: Benefits and Considerations for Current and Prospective Users

Two-dimensional gas chromatography (GC×GC) offers improved separation power for complex samples containing hundreds to thousands of analytes. However, several considerations must be made to determine whether multidimensional gas chromatography (MDGC) is the logical instrument choice to answer a particular scientific question, including, but not limited to, whether the analysis is targeted or non-targeted, the number of analytes of interest, and the presence of interferences that are coeluted, as well as any potential regulatory or industrial constraints. Currently, MDGC remains daunting for many users because of data complexity and the limited tools commercially available, which are critical for improving the accessibility of MDGC. Herein, we discuss considerations that may assist analysts, laboratory managers, regulatory agents, instrument and software vendors, and those interested in understanding the applicability of 2D-GC for the scientific question being investigated.

Unsymmetrical dimethylhydrazine and related compounds in the environment: Recent updates on pretreatment, analysis, and removal techniques

Unsymmetrical dimethylhydrazine (1,1-Dimethylhydrazine, UDMH) has been widely used as aerospace fuel in many countries. The launch of space vehicles can cause the release and leakage of UDMH into the environment, posing serious threats to ecology system and human population. Even worse, the health risks are also pertinent to its numerous classes of transformation products including N-Nitrosodimethylamine (NDMA), because most of them display carcinogenic and mutagenic properties. Recently, there has been an intense ongoing development of simple, fast, green, and effective techniques for determining and removing these hazardous substances. This review summarizes the latest research progress regarding the sources, fates, pretreatment, analysis, and removal techniques of UDMH and related products in the environment. Sample preparation methods mainly include pressurized liquid extraction, liquid-phase microextraction techniques, solid-phase extraction, headspace-solid-phase microextraction, and supercritical fluid extraction. Detection and identification methods mainly include high-performance liquid chromatography coupled with tandem mass spectrometry (HPLC-MS/MS), gas chromatography coupled with tandem mass spectrometry (GC-MS/MS), and sensors. Removal methods mainly include advanced oxidation processes, adsorption, biodegradation techniques. The advantages/disadvantages, applications, and trends of the proposed approaches are thoroughly discussed to provide a valuable reference for further studies.

A procedure to detect and identify specific chemicals of potential inhalation toxicity concern in aerosols

OBJECTIVE

Understanding the potential inhalation toxicity of poorly characterized aerosols is challenging both because aerosols may contain numerous chemicals and because it is difficult to predict which chemicals may present significant inhalation toxicity concerns at the observed levels. We have developed a novel systematic procedure to address these challenges through non-targeted chemical analysis by two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOFMS) and assessment of the results using publicly available toxicity data to prioritize the tentatively identified detected chemicals according to potential inhalation toxicity.

MATERIALS AND METHODS

The procedure involves non-targeted chemical analysis of aerosol samples utilizing GC × GC-TOFMS, which is selected because it is an effective technique for detecting chemicals in complex samples and assigning tentative identities according to the mass spectra. For data evaluation, existing toxicity data (e.g. from the U.S. Environmental Protection Agency CompTox Chemicals Dashboard) are used to calculate multiple toxicity metrics that can be compared among the tentatively identified chemicals. These metrics include hazard quotient, incremental lifetime cancer risk, and metrics analogous to hazard quotient that we designated as exposure-(toxicology endpoint) ratios.

RESULTS AND DISCUSSION

We demonstrated the utility of our procedure by detecting, identifying, and prioritizing specific chemicals of potential inhalation toxicity concern in the mainstream smoke generated from the machine-smoking of marijuana blunts.

CONCLUSION

By designing a systematic approach for detecting and identifying numerous chemicals in complex aerosol samples and prioritizing the chemicals in relation to different inhalation toxicology endpoints, we have developed an effective approach to elucidate the potential inhalation toxicity of aerosols.

Aroma Clouds of Foods: A Step Forward to Unveil Food Aroma Complexity Using GC × GC

The human senses shape the life in several aspects, namely well-being, socialization, health status, and diet, among others. However, only recently, the understanding of this highly sophisticated sensory neuronal pathway has gained new advances. Also, it is known that each olfactory receptor cell expresses only one type of odorant receptor, and each receptor can detect a limited number of odorant substances. Odorant substances are typically volatile or semi-volatile in nature, exhibit low relative molecular weight, and represent a wide variety of chemical families. These molecules may be released from foods, constituting clouds surrounding them, and are responsible for their aroma properties. A single natural aroma may contain a huge number of volatile components, and some of them are present in trace amounts, which make their study especially difficult. Understanding the components of food aromas has become more important than ever with the transformation of food systems and the increased innovation in the food industry. Two-dimensional gas chromatography and time-of-flight mass spectrometry (GC × GC-ToFMS) seems to be a powerful technique for the analytical coverage of the food aromas. Thus, the main purpose of this review is to critically discuss the potential of the GC × GC–based methodologies, combined with a headspace solvent-free microextraction technique, in tandem with data processing and data analysis, as a useful tool to the analysis of the chemical aroma clouds of foods. Due to the broad and complex nature of the aroma chemistry subject, some concepts and challenges related to the characterization of volatile molecules and the perception of aromas will be presented in advance. All topics covered in this review will be elucidated, as much as possible, with examples reported in recent publications, to make the interpretation of the fascinating world of food aroma chemistry more attractive and perceptive.

Comprehensive two-dimensional gas chromatography with mass spectrometry: an advanced bioanalytical technique for clinical metabolomics studies

This review highlights the current state of knowledge in the development of GC × GC-MS for the analysis of clinical metabolites. Selected applications are described as well as our perspectives on current challenges and potential future directions.

Chromatographic Applications in the Multi-Way Calibration Field

In this review, recent advances and applications using multi-way calibration protocols based on the processing of multi-dimensional chromatographic data are discussed. We first describe the various modes in which multi-way chromatographic data sets can be generated, including some important characteristics that should be taken into account for the selection of an adequate data processing model. We then discuss the different manners in which the collected instrumental data can be arranged, and the most usually applied models and algorithms for the decomposition of the data arrays. The latter activity leads to the estimation of surrogate variables (scores), useful for analyte quantitation in the presence of uncalibrated interferences, achieving the second-order advantage. Recent experimental reports based on multi-way liquid and gas chromatographic data are then reviewed. Finally, analytical figures of merit that should always accompany quantitative calibration reports are described.

Recent forensic applications of enhanced chromatographic separation methods

This study reviews the recent applications of enhanced separation methods employed in forensic analysis utilizing gas chromatography, liquid chromatography, and supercritical fluid chromatography published between 2015 to 2020, except papers previously covered in relevant review articles. Applications of enhanced chromatographic separation methods to arson investigations, environmental forensics, sexual assault investigations, drug analysis, and toxicology are discussed. Future directions for enhanced chromatographic separation methods in forensic science are also explored.

Determination of vacuum ultraviolet detector response factors by hyphenation with two-dimensional comprehensive gas chromatography with flame ionization detection

Two-dimensional comprehensive gas chromatography is an established technique, employed for the characterization of complex samples. Broadband vacuum ultraviolet absorption spectroscopy detection has recently attracted a lot of attention as it is a universal detection technique characterized by good selectivity but also ease of use and amenability to coupling with two-dimensional comprehensive gas chromatography. Vacuum ultraviolet spectroscopy is particularly interesting due to the possibility of performing spectral decomposition for species that coelute in gas chromatography analysis. This detector has quantitative capabilities, however not all species absorb vacuum ultraviolet radiation the same. Unfortunately, vacuum ultraviolet relative response factors for compounds are not always available. Methods to rapidly measure vacuum ultraviolet relative response factors and generate a large database that would allow calibration free quantitative analysis of complex mixtures are therefore of great interest. In this work, a universal methodology that permits rapid measurement of vacuum ultraviolet relative response factors is reported. It involves flow modulated two-dimensional comprehensive gas chromatography with dual vacuum ultraviolet and flame ionization detection. In this set-up, flame ionization detection is employed as a quantitative reference allowing to scale vacuum ultraviolet responses of investigated compounds. This approach was validated by flow measurements and by comparing relative response factors obtained for model compounds with literature data.

Baseline correction method for dynamic pressure gradient modulated comprehensive two-dimensional gas chromatography with flame ionization detection

A baseline correction method is developed for comprehensive two-dimensional (2D) chromatography (GC × GC) with flame-ionization detection (FID) using dynamic pressure gradient modulation (DPGM). The DPGM-GC × GC-FID utilized porous layer open tubular (PLOT) columns in both dimensions to focus on light hydrocarbon separations. Since DPGM is nominally a stop-flow modulation technique, a rhythmic baseline disturbance is observed in the FID signal that cycles with the modulation period (P_M). This baseline disturbance needs to be corrected to optimize trace analysis. The baseline correction method has three steps: collection of a background "blank" chromatogram and multiplying it by an optimized normalization factor, subtraction of the normalization-optimized background chromatogram from a sample chromatogram, and application of Savitzky-Golay smoothing. An alkane standard solution, containing pentane, hexane and heptane was used for method development, producing linear calibration curves (r² > 0.991) over a broad concentration range (7.8 ppm - 4000 ppm). Further, the limit-of-detection (LOD) and limit-of-quantification (LOQ) were determined for pentane (LOD = 2.5 ppm, LOQ = 8.2 ppm), hexane (LOD = 0.9 ppm, LOQ = 3.0 ppm), and heptane (LOD = 1.9 ppm, LOQ = 6.4 ppm). A natural gas sample separation illustrated method applicability, whereby the DPGM produced a signal enhancement (SE) of 30 for isopentane, where SE is defined as the height of the tallest ²D peak in the modulated chromatogram for the analyte divided by the height of the unmodulated ¹D peak. The 30-fold SE resulted in about a 10-fold improvement in the signal-to-noise ratio (S/N) for isopentane. Additional versatility of the baseline correction method for more complicated samples was demonstrated for an unleaded gasoline sample, which enabled the detection (and visual appearance) of trace components.

Determination of the Signal-To-Noise Ratio Enhancement in Comprehensive Three-Dimensional Gas Chromatography

We investigate the extent to which comprehensive three-dimensional gas chromatography (GC³) provides a signal enhancement (SE) and a signal-to-noise ratio enhancement (S/N_Rel) relative to one-dimensional (1D)-GC. Specifically, the SE is defined as the ratio of the tallest ³D peak height from the GC³ separation to the 1D peak height from the unmodulated 1D-GC separation. A model is proposed which allows the analyst to predict the theoretically attainable SE (SE_T) based upon the peak width and sampling density inputs. The model is validated via comparison of the SE_T to the experimentally measured SE (SE_M) obtained using total-transfer GC³ (100% duty cycle for both modulators) with time-of-flight mass spectrometry detection. Two experimental conditions were studied using the same GC³ column set, differing principally in the modulation period from the ¹D to ²D columns: 4 s versus 8 s. Under the first set of conditions, the average SE_M was 97 (±22), in excellent agreement with the SE_T of 97 (±18). The second set of conditions improved the average SE_M to 181 (±27), also in agreement with the average SE_T of 176 (±26). The average S/N_Rel following correction for the mass spectrum acquisition frequency was 38.8 (±11.2) and 59.0 (±27.2) for the two sets of conditions. The enhancement in S/N is largely attributed to moving the signal to a higher frequency domain where the impact of "low frequency" noise is less detrimental. The findings here provide strong evidence that GC³ separations can provide enhanced detectability relative to 1D-GC and comprehensive two-dimensional gas chromatography (GC×GC) separations.

Multivariate statistics for summarizing diesel feeds for flammability attributes using comprehensive two-dimensional gas chromatography

Comprehensive 2D gas chromatography has been utilized for analyzing complex mixtures of hydrocarbons of diesel feeds. Here, we evaluated 19 diesel feeds for their paraffinic, naphthenic, and aromatic group compositions dictating their flammability properties. Compositional ranges of feeds were as follows: paraffins: 9.6-57.8%, naphthenes: 7.9-38.5%, and aromatics: 10.5-82.3%. Diesel's flammability performance is estimated by thermodynamic conditions and rates of radical formation of hydrocarbon type in actual engine condition, limiting cetane number. However, limitations are overcome by understanding the relative compositional variations of feeds by simple ranking of feeds based on C15-16 compositions. Due to the multidimensional variability of feeds, a principal component analysis was adopted later for its distinguishing capability. Paraffinic, naphthenic, and aromatic group's principal component analysis clustered up feeds based on the higher concentration of individual hydrocarbon group. We explored hierarchical cluster analysis to organize feeds into classes of mixed C9 to C26 paraffin's composition in the diesel range. Further, for discriminating C15-C16 enriched and depleted feeds in total paraffin composition, a row dendrogram with heat map was drawn. The above multivariate methods have led to a fair distinction of nonadditive feed compositions influencing flammability properties by radical formation rate.

Modeling approaches for temperature-programmed gas chromatographic retention times under vacuum outlet conditions

This contribution evaluates the performance of two predictive approaches in calculating temperature-programmed gas chromatographic retention times under vacuum outlet conditions. In the first approach, the predictions are performed according to a thermodynamic-based model, while in the second approach the predictions are conducted by using the temperature-programmed retention time equation. These modeling approaches were evaluated on 47 test compounds belonging to different chemical classes, under different experimental conditions, namely, two modes of gas flow regulation (i.e., constant inlet pressure and constant flow rate), and different temperature programs (i.e., 7 °C/min, 5 °C/min, and 3 °C/min). Both modeling approaches gave satisfactory results and were able to accurately predict the elution profiles of the studied test compounds. The thermodynamic-based model provided more satisfying results under constant flow rate mode, with average modeling errors of 0.43%, 0.33%, and 0.15% across all the studied temperature programs. Nevertheless, under constant inlet pressure mode, lower modeling errors were achieved when using the temperature-programmed retention time equation, with average modeling errors of 0.18%, 0.18%, and 0.31% across the used temperature programs.

Data handling and data analysis in metabolomic studies of essential oils using GC-MS

Gas chromatography electron impact ionization mass spectrometry (GC-EI-MS) has been, and remains, the most widely applied analytical technique for metabolomic studies of essential oils. GC-EI-MS analysis of complex samples, such as essential oils, creates a large volume of data. Creating predictive models for such samples and observing patterns within complex data sets presents a significant challenge and requires application of robust data handling and data analysis methods. Accordingly, a wide variety of software and algorithms has been investigated and developed for this purpose over the years. This review provides an overview and summary of that research effort, and attempts to classify and compare different data handling and data analysis procedures that have been reported to-date in the metabolomic study of essential oils using GC-EI-MS.

A multi-location peak parking approach for calculation of second dimensional retention indices for improved volatile compound identification with cryogen-free comprehensive heart-cut two-dimensional gas chromatography

Comprehensive heart-cut multidimensional gas chromatography (CH/C MDGC) without a cryogenic trapping device was developed with an established approach for calculation of first and second dimensional retention indices (¹I and ²I) for improved compound identification. A first dimensional (¹D) DB-1MS column (60 m) and a second dimensional (²D) DB-WAX column (60 m) were applied with a Deans switch (DS) using a constant H/C window of 0.2 min and a periodic multiple heartcut strategy comprising 225H/C throughout the CH/C. ¹I was calculated based on comparison of the middle of the heartcut time with the alkane retention times on the ¹D column. A multi-location peak parking approach using sixteen sets of automated injections of alkane references was also established with the least square curve fitting method for construction of the alkane isovolatility curves which were applied for ²I calculation. The untargeted compound analysis of a perfume sample was then performed according to comparison with the libraries of mass spectra, ¹I and ²I. The CH/C MDGC system with a 25 h analysis time showed a peak capacity (n_c) of 9198 and 128 separated peaks with 71 compounds successfully identified according to MS, ¹I and ²I library match under the established error approximation criteria. Furthermore, relationship between the analysis time and number of separated peaks was proposed based on the set of 84 identifiable compounds. With the compensation of lower separation performance and greater I errors, the analysis time could be reduced by applying a 2.5 min H/C window with a total analysis time of 2 h and n_c of 1134.

Strategies towards simpler configuration and higher peak capacity with comprehensive multidimensional gas chromatography

Experimental and data analysis approaches in multidimensional gas chromatography (MDGC) comprising comprehensive multiple heart-cut (H/C) and comprehensive two dimensional GC (GC × GC) were developed with an example application illustrated for analysis of a technical glycol precursor sample. The GC × GC system employed a long ¹D (30 m) and a short ²D (5 m) column with a flow modulator and a Deans switch (DS) as a splitter; meanwhile. The H/C system was applied solely as a DS located between long ¹D (30 m) and ²D (60 m) columns without use of cryogenic trapping devices. The effects of injection time and ²D column flow in GC × GC and the impacts of H/C window and number of injections (total analysis time) in H/C analysis were investigated. The analysis performance for each condition was evaluated according to peak capacity and number of separated compounds. The continuum between the two techniques was then established via the relationship between analysis time and analysis performance. The separation performances were improved with longer analysis time so that the suitable condition was selected within this compromise. Under the selected conditions, volatile compounds in the technical glycol precursor sample were identified according to the match between the experimental MS spectra and first dimensional retention indices (¹I) with that from the NIST2014 database and literature. An hour analysis with GC × GC resulted in a total peak capacity of 798, number of separated peaks of 61 and average MS match score of 887 ± 35; meanwhile, the corresponding numbers were improved to be 9198, 107 and 898 ± 24, respectively, with the 25 h comprehensive H/C analysis.

Experimental and data analysis approaches in MDGC comprising comprehensive H/C and GC × GC were developed with an example application illustrated for analysis of a technical glycol precursor sample.

Perylene Imide-Based Optical Chemosensors for Vapor Detection

Perylene imide (PI) molecules and materials have been extensively studied for optical chemical sensors, particularly those based on fluorescence and colorimetric mode, taking advantage of the unique features of PIs such as structure tunability, good thermal, optical and chemical stability, strong electron affinity, strong visible light absorption and high fluorescence quantum yield. PI-based optical chemosensors have now found broad applications in gas phase detection of chemicals, including explosives, biomarkers of some food and diseases (such as organic amines (alkylamines and aromatic amines)), benzene homologs, organic peroxides, phenols and nitroaromatics, etc. In this review, the recent research on PI-based fluorometric and colorimetric sensors, as well as array technology incorporating multiple sensors, is reviewed along with the discussion of potential applications in environment, health and public safety areas. Specifically, we discuss the molecular design and aggregate architecture of PIs in correlation with the corresponding sensor performances (including sensitivity, selectivity, response time, recovery time, reversibility, etc.). We also provide a perspective summary highlighting the great potential for future development of PIs optical chemosensors, especially in the sensor array format that will largely enhance the detection specificity in complexed environments.

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.