Gas Chromatographic Retention Research Articles

Hologram quantitative structure-activity relationship on the gas chromatographic retention index of plant essential oil constituents

The gas chromatography retention index (RI) is an important parameter for the identification of different types of compounds in the field of chromatographic analysis; however, the experimental collection of RI values is a extremely cumbersome process. Thus, there is an urgent need for the establishment of a simple, efficient, and accurate model for the prediction of the RI values of compounds. In this study, first, the experimental RI values for 60 plant essential oil constituents were obtained. Next, a model describing the hologram quantitative structure-activity relationship (HQSAR) between the structural properties of the essential oil constituents and their RI values was investigated and constructed. The optimal HQSAR model was established by setting the model parameters "fragment size", "fragment distinction", "hologram length" and "principal components" to "1-4", "C, Ch", "199", and "4", respectively. Finally, the predictive ability of the model was verified using external test set validation and leave-one-out cross-validation (LOO-CV). The experimental results were as follows, the root mean square error of prediction (RMSEP), predictive determination coefficient ([Formula: see text]), concordance correlation coefficient (CCC), and mean relative error (MRE) for external test set validation were 40.45, 0.984, 0.968, and 2.20%, respectively. Meanwhile, the root mean square error of cross validation (RMSECV) and MRE for LOO-CV were 72.56 and 4.17%, respectively. These findings demonstrate that the established HQSAR model has a good predictive ability and can accurately predict the RI values of plant essential oil constituents. In addition, the molecular contribution maps of the HQSAR model revealed that the RI values of aromatic compounds increase when hydroxyl groups are connected to their alkyl chains. Aliphatic compounds feature long chain alkyl groups, which can lead to an increase in RI values. The above phenomena highlight the promising application prospects of HQSAR for studying the RI values of plant essential oil constituents. Therefore, this study provides a reliable theoretical basis for predicting the RI values of other essential oil constituents.

Mutual interference between 3,6-dichlorinated carbazole and p,p'-dichlorodiphenyltrichloroethane in gas chromatography mass spectrometry analysis.

The widespread contamination of the environment by polyhalogenated carbazoles (PHCZs) has been increasingly observed during the past decade. Among numerous PHCZ congeners, 3,6-dichlorocarbazole (36-CCZ) is often among the most frequently detected at higher concentrations. Although the environmental level of the legacy pesticide p,p'-dichlorodiphenyltrichloroethane (p,p'-DDT) has been declining, it continues to be ubiquitously detected. These two compounds were found to interfere with each other during analyses using gas chromatography (GC) coupled with single- or triple-quadrupole low-resolution mass spectrometry (MS or MS/MS). The base peak in the mass spectra was that of m/z 235 for both compounds. In MS/MS with multiple reaction monitoring (MRM), the same transitions (235 → 200 and 235 → 165) were often used. Under the same GC operating conditions, the SH-I-5MS capillary column used in this work did not resolve the two compounds at baseline. Pre-treatment using cleanup column chromatography can fractionate the sample extract, with the two compounds separated in different fractions before instrumental analyses. Reversed-phase HPLC columns also work for resolving 36-CCZ and p,p'-DDT. Possible overlaps in GC retention and similarity in MS spectra might have caused data inaccuracy for 36-CCZ as well as p,p'-DDT in some studies published to date, and steps to avoid the interference should be taken into quality control protocols in future research and environmental monitoring.

The effect of the assigned descriptors for phthalate esters on the characterization of their separation properties using the solvation parameter model

Revised descriptors are determined for fifteen phthalate esters for use in the solvation parameter model and form part of the Wayne State University (WSU) compound descriptor database. For thirteen phthalate esters a comparison is made with the same compounds in the Abraham descriptor database. Gas chromatographic retention factors on poly(methyloctylsiloxane), SPB-Octyl, and poly(cyanopropylphenyldimethylsiloxane), DB-225, stationary phases are used to facilitate an assessment of the contribution of cavity formation and dispersion interactions, L descriptor, and dipole-type interactions, S descriptor, to the experimental retention factors (log k) for the phthalate esters with minimum interference from competing intermolecular interactions. The results indicate a systematic overprediction of the cavity and dispersion interaction term and underprediction of dipole-type interactions for the Abraham descriptors compared with the WSU descriptors for the phthalate esters. The average absolute deviation (AAD) for 13 phthalate esters on SPB-Octyl is 0.039 (WSU descriptors) compared with 0.252 (Abraham descriptors) and for 9 phthalate esters on DB-225 0.030 (WSU descriptors) compared with 0.167 (Abraham descriptors). The results for dipole-type interactions are confirmed and extended to include the hydrogen-bond basicity of the phthalate esters, B descriptor, by evaluation of partition constants in aqueous biphasic systems and the n-heptane-2,2,2-trifluoroethanol biphasic system. Differences in the contribution of the hydrogen-bond basicity of the phthalate esters to the experimental partition constants are largely random with respect to database selection but important for the accurate prediction of the partition constants. The AAD for the partition constant for 15 phthalate esters is 0.063 (WSU descriptors) compared with 0.320 (Abraham descriptors) for the heptane-2,2,2-trifluoroethanol biphasic system and 0.13 (WSU descriptors) compared with 0.25 (Abraham descriptors) for 9 phthalate esters in the octanol-water biphasic system. The WSU descriptors for the phthalate esters exhibit a better fit with the experimental data for separation systems and are free of the extreme values predicted for the Abraham descriptors for several phthalate esters.

On the challenge of unambiguous identification of fentanyl analogs: Exploring measurement diversity using standard reference mass spectral libraries.

Fentanyl analogs are a class of designer drugs that are particularly challenging to unambiguously identify due to the mass spectral and retention time similarities of unique compounds. In this paper, we use agglomerative hierarchical clustering to explore the measurement diversity of fentanyl analogs and better understand the challenge of unambiguous identifications using analytical techniques traditionally available to drug chemists. We consider four measurements in particular: gas chromatography retention indices, electron ionization mass spectra, electrospray ionization tandem mass spectra, and direct analysis in real time mass spectra. Our analysis demonstrates how simultaneously considering data from multiple measurement techniques increases the observable measurement diversity of fentanyl analogs, which can reduce identification ambiguity. This paper further supports the use of multiple analytical techniques to identify fentanyl analogs (among other substances), as is recommended by the Scientific Working Group for the Analysis of Seized Drugs (SWGDRUG).

Detailed Comparison of Xenon APPI (9.6/8.4 eV), Krypton APPI (10.6/10.0 eV), APCI, and APLI (266 nm) for Gas Chromatography High Resolution Mass Spectrometry of Standards and Complex Mixtures.

Photoionization schemes for mass spectrometry, either by laser or discharge lamps, have been widely examined and deployed. In this work, the ionization characteristics of a xenon discharge lamp (Xe-APPI, 9.6/8.4 eV) have been studied and compared to established ionization schemes, such as atmospheric pressure chemical ionization, atmospheric pressure photoionization with a krypton discharge lamp (Kr-APPI, 10.6/10 eV) and atmospheric pressure laser ionization (266 nm). Addressing the gas-phase ionization behavior has been realized by gas chromatography coupled to high-resolution mass spectrometry without the usage of a dopant. For standard substances, it has been found that Xe-APPI is able to ionize a broad range of polycyclic aromatic hydrocarbons as well as their heteroatom-containing and alkylated derivatives. However, thiol and ester compounds could not be detected. Moreover, Xe-APPI revealed a high tendency to generate oxygenated artifacts, most likely due to a VUV absorption band of oxygen at 148 nm. Beneficially, almost no chemical background, commonly caused by APCI or Kr-APPI due to column blood, plasticizers or impurities, is observed. This advantage is noteworthy for evolved gas analysis without preseparation or for chromatographic coelution. For the complex mixtures, Xe-APPI revealed the predominant generation of radical cations via direct photoionization with a high selectivity toward aromatic core structures with low alkylation. Interestingly, both Xe-APPI and Kr-APPI could sensitively detect sterane cycloalkanes, validated by gas chromatographic retention. The narrowly ionized chemical space could let Xe-APPI find niche applications, e.g., for strongly contaminated samples to reduce the background.

Linear Correlations of the Gas Chromatographic Retention Indices of Compounds from Various Taxonomic Groups

Linear Correlations of the Gas Chromatographic Retention Indices of Compounds from Various Taxonomic Groups

Intelligent Workflow and Software for Non-Target Analysis of Complex Samples Using a Mixture of Toxic Transformation Products of Unsymmetrical Dimethylhydrazine as an Example.

Unsymmetrical dimethylhydrazine (UDMH) is a widely used rocket propellant. Entering the environment or being stored in uncontrolled conditions, UDMH easily forms an enormous variety (at least many dozens) of transformation products. Environmental pollution by UDMH and its transformation products is a major problem in many countries and across the Arctic region. Unfortunately, previous works often use only electron ionization mass spectrometry with a library search, or they consider only the molecular formula to propose the structures of new products. This is quite an unreliable approach. It was demonstrated that a newly proposed artificial intelligence-based workflow allows for the proposal of structures of UDMH transformation products with a greater degree of certainty. The presented free and open-source software with a convenient graphical user interface facilitates the non-target analysis of industrial samples. It has bundled machine learning models for the prediction of retention indices and mass spectra. A critical analysis of whether a combination of several methods of chromatography and mass spectrometry allows us to elucidate the structure of an unknown UDMH transformation product was provided. It was demonstrated that the use of gas chromatographic retention indices for two stationary phases (polar and non-polar) allows for the rejection of false candidates in many cases when only one retention index is not enough. The structures of five previously unknown UDMH transformation products were proposed, and four previously proposed structures were refined.

Using Thermodynamics and Simulations to Understand Selectivity and Retention in Gas Chromatography

Retention and selectivity in gas chromatography (GC) occur because of the thermodynamics of the phase transition from the vapor phase following sample injection to the solution phase of being dissolved in the stationary phase. Analytes then move along the column because the vapor phase is flowing. In this installment, we quickly review the basic thermodynamics underlying separation in GC, and we see how this impacts selectivity and retention. Last month, we saw how seemingly large differences in column polarity may still generate little, or even the opposite, effect on retention and generate confusion and difficulty in method development. This month, we explore this challenge more in-depth using thermodynamics and a freely available online GC simulator.

Determination of Abraham Model Solute Descriptors for 62 Additional C10 through C13 Methyl- and Ethyl-Branched Alkanes

Abraham model solute descriptors are reported for the first time for 62 additional C10 through C13 methyl- and ethyl-branched alkanes. The numerical values were determined using published gas chromatographic retention Kováts retention indices for 157 alkane solutes eluted from a squalane stationary phase column. The 95 alkane solutes that have known descriptor values were used to construct the Abraham model KRI versus L-solute descriptor correlation needed in our calculations. The calculated solute descriptors can be used in conjunction with previously published Abraham model correlations to predict a wide range of important physico-chemical and biological properties. The predictive computations are illustrated by estimating the air-to-polydimethylsiloxane partition coefficient for each of the 157 alkane solutes.

Construction of Chemical Libraries of Volatile Compounds by Combinatorial Synthesis of Homologous Mixtures: Alk-4-en-1-ols, Alk-4-enals and Methyl Alk-4-enoates.

A compound library of sixty six linear compounds, eleven representatives of six molecular families: (E)- and (Z)-isomers of alk-4-en-1-ols, alk-4-enals, and methyl alk-4-enoates, was prepared by combinatorial syntheses to allow the creation of a mass spectral database directly usable for their identification in GC/MS analyses. We demonstrate here that compound libraries can be prepared by combinatorial syntheses using long linear synthetic sequences, i. e., eight step in the case of 4-enals. The resulting mixtures of homologues are still perfectly exploitable to deliver the requested information such as clean mass spectra and good gas chromatographic retention indices.

Comparison of Gas-Chromatographic Retention Parameters of Aliphatic Enyne Alcohols with the Data for Their Structural Analogues

Comparison of Gas-Chromatographic Retention Parameters of Aliphatic Enyne Alcohols with the Data for Their Structural Analogues

Volatiles of the Apicomplexan Alga Chromera velia and Associated Bacteria.

Volatiles released by the apicomplexan alga Chromera velia CCAP1602/1 and their associated bacteria have been investigated. A metagenome analysis allowed the identification of the most abundant heterotrophic bacteria of the phycosphere, but the isolation of additional strains showed that metagenomics underestimated the complexity of the algal microbiome, However, a culture-independent approach revealed the presence of a planctomycete that likely represents a novel bacterial family. We analysed algal and bacterial volatiles by open-system-stripping analysis (OSSA) on Tenax TA desorption tubes, followed by thermodesorption, cryofocusing and GC-MS-analysis. The analyses of the alga and the abundant bacterial strains Sphingopyxis litoris A01A-101, Algihabitans albus A01A-324, "Coraliitalea coralii" A01A-333 and Litoreibacter sp. A01A-347 revealed sulfur- and nitrogen-containing compounds, ketones, alcohols, aldehydes, aromatic compounds, amides and one lactone, as well as the typical algal products, apocarotenoids. The compounds were identified by gas chromatographic retention indices, comparison of mass spectra and syntheses of reference compounds. A major algal metabolite was 3,4,4-trimethylcyclopent-2-en-1-one, an apocarotenoid indicating the presence of carotenoids related to capsanthin, not reported from algae so far. A low overlap in volatiles bouquets between C. velia and the bacteria was found, and the xenic algal culture almost exclusively released algal components.

Study on Gas Chromatography Retention Time Variation of Acetic Acid Combined with Quantum Chemical Calculation

Study on Gas Chromatography Retention Time Variation of Acetic Acid Combined with Quantum Chemical Calculation

Volatility and Nonspecific van der Waals Interaction Properties of Per- and Polyfluoroalkyl Substances (PFAS): Evaluation Using Hexadecane/Air Partition Coefficients.

Per- and polyfluoroalkyl substances (PFAS) form weak van der Waals (vdW) interactions, which render this class of chemicals more volatile than nonfluorinated analogues. Here, the hexadecane/air partition coefficient (KHxd/air) values at 25 °C, as an index of vdW interaction strength and volatility, were determined for 64 neutral PFAS using the variable phase ratio headspace and gas chromatographic retention methods. Log KHxd/air values increased linearly with increasing number of CF2 units, and the increase in log KHxd/air value per CF2 was smaller than that per CH2. Comparison of PFAS sharing the same perfluoroalkyl chain length but with different functional groups demonstrated that KHxd/air was highest for the N-alkyl perfluoroalkanesulfonamidethanols and lowest for the perfluoroalkanes and that the size of the nonfluorinated structure determines the difference in KHxd/air between PFAS groups. Two models, the quantum chemistry-based COSMOtherm model and an iterative fragment selection quantitative structure-property relationship (IFS-QSPR) model, accurately predicted the log KHxd/air values of the PFAS with root-mean-square errors of 0.55 and 0.35, respectively. COSMOtherm showed minor systematic errors for all PFAS, whereas IFS-QSPR exhibited large errors for a few PFAS groups that were outside the model applicability domain. The present data set will be useful as a benchmark of the volatilities of the various PFAS and for predicting other partition coefficient values of PFAS.

Comparative Prediction of Gas Chromatographic Retention Indices for GC/MS Identification of Chemicals Related to Chemical Weapons Convention by Incremental and Machine Learning Methods

During on-site verification activities conducted by the Technical Secretariat of Organization for the Prohibition of Chemical Weapons, identification by gas chromatography retention indices (RI) data, in addition to mass spectrometry data, increase the reliability of factual findings. However, reference RIs do not cover all the possible chemical structures. That is why it is important to have models to predict RIs. Applicable only for narrow data sets of chemicals with a fixed scaffold (G- and V-series gases as example), the non-learning incremental method demonstrated predictive median absolute and percentage errors of 2–4 units and 0.1–0.2%; these are comparable with the experimental bias in RI measurements in the same laboratory with the same GC conditions. It outperforms the accuracy of two reported machine learning methods–median absolute and percentage errors of 11–52 units and 0.5–2.8%. However, for the whole Chemical Weapons Convention (CWC) data set of chemicals, when a fixed scaffold is absent, the incremental method is not applicable; essential machine learning methods achieved accuracy: median absolute and percentage errors of 29–33 units and 0.5–2.2%, depending on the machine learning method. In addition, we have developed a homology tree approach as a convenient method for the visualization of the CWC chemical space. We conclude that non-learning incremental methods may be more accurate than the state-of-the-art machine learning techniques in particular cases, such as predicting the RIs of homologues and isomers of chemicals related to CWC.

A simple method for predicting the gas-chromatographic retention indices of phenolic derivatives

A simple method for predicting the gas-chromatographic retention indices of phenolic derivatives

QSRR modelling for the investigation of gas chromatography retention indices of flavour and fragrance compounds on Carbowax 20 ​M glass capillary column with the index of ideality of correlation and the consensus modelling

The goal of the present study was to use a quantitative structure-retention relationship (QSRR) for the retention indices of 1179 flavour and fragrance organic compounds using the Monte Carlo algorithm of CORAL software. All the organic compounds were represented by SMILES notation for computation of descriptor of correlation weight (DCW). The dataset of 1179 flavour and fragrance organic compounds was used to make nine splits, each of which was further segmented into four sets: training, invisible training, calibration, and validation. The task of the index of ideality correlation (IIC) was analysed in-depth and it was found that the QSRR models generated by the use of IIC were more robust and significant. Two target functions i.e. TFA (IICweight=0.0), TFB (IICweight=0.2) were applied to build 18 QSRR models. The established QSRR model with TFB having Rvalidation2=0.9015 for split 6 was considered as the prime model. The reliability and robustness of the prime model was also confirmed by the numerical value of Qvalidation2=0.9000 and Qcalibration2=0.8919. The common promoters of increase and decrease of endpoint were also extracted from three splits 5, 6 and 9. Moreover, consensus modelling employing the split 6 layout of dataset distribution improves the prediction performance by enhancing the numerical value of Rvalidation2 from 0.9015 to 0.9241.

Characteristics of the Anomalous Temperature Dependence of Gas Chromatographic Retention Indices of Polar Compounds on Packed Columns with a Nonpolar Phase

Characteristics of the Anomalous Temperature Dependence of Gas Chromatographic Retention Indices of Polar Compounds on Packed Columns with a Nonpolar Phase

Descriptors for some compounds with pharmacological activity; calculation of properties

Abraham model solute descriptors have been determined for nisoldipine, nizatidine, loratadine, zonisamide, oxaprozin, rebamipide, domperidone, temozolomide, ‘florfenicol’, florfenicol A, dapsone, chrysin, benorilate, β-lapachone, and Ipriflavone based on published partition coefficients, molar solubilities and gas chromatographic retention indices. The calculated solute descriptors, combined with our previously published Abraham model correlations, are used to predict several important physicochemical and biological properties, such as air–water, air-blood, air-lung, air-fat, air-skin, water–lipid, water-membrane and water-skin partition coefficients, as well as permeation from water through skin.

Analytical aspects of organic compounds retention indices dependence in reversed phase HPLC on the content of methanol in eluent

As a result of the determination of retention indices (RI) of 11 organic compounds of various polarity in reversed phase (RP) HPLC using methanol as organic solvent in elu­ent, the coefficients of the dependence of RI vs. content of methanol, dRI/dС were de­ter­mi­ned. Formally, these parameters are equivalent to the temperature coefficients of gas chromatographic retention indices, b = dRI/dT. It is shown that the ranges of variations of these coefficients are rather large (from -2.0 up to +4.6 in the current work), which requires re­ve­­a­ling the factors influencing their signs and absolute values. The correlations of coeffi­ci­­ents dRI/dC with retention indices themselves, as well as with hydrophobicity factors, logP (the logarithms of partition coefficients in the system 1-octanol/water) seem to be negligible. The best correlations of dRI/dC were observed with such polarity mea­su­res of organic compounds as homologous increments of hydrophobicity factors (ilogP), and re­ten­tion indices (iRI). Such transformations of pro­perties A as their homologous increments characterize different homologues despite of their locations within the homologous series. Thus, the parameters ilogP and iRI appeared to be the measures of the polarity of the corres­pon­­ding series. This approach per­mits us to reveal that the dependence of retention indices in RP HPLC on the content of me­tha­nol in eluent is determined just by the analytes¢ po­la­rity and their hydrophobic – hydrophilic proper­ties. The ratio dRI/dC > 0 is typi­cal for non-polar analytes, while for polar compo­unds the negative signs of these coeffi­ci­ents are typical, dRI/dC < 0. Hence, deter­mining even the sign of this coefficient provi­des the important information on the chemical origin of analytes.