Gas Chromatographic Retention Indices Research Articles

6-Hydroxyisocaryophyllene and Isocaryophyllenic Acid from Birch Vegetative Buds

The new isocaryophyllene derivatives: 6-hydroxyisocaryophyllene [(1R,4Z,6R,9S)-8-methylene-11,11-dimethylbicyclo[7.2.0]undec-4-ene-6-ol], epoxide of 6-hydroxyisocaryophyllene [(6R)-hydroxy-(4R,5S)-epoxyisocaryophyllene [(1R,4R,5S,6R,9S)-4.5-epoxy-8-methylene-11,11-dimethylbicyclo[7.2.0]undeco-6-ol], (6R)-acetoxyisocaryophyllene [(6R)-acetoxy-(1R,4Z,9S)-8-methylene-11,11-dimethylbicyclo[7.2.0]undec-4-ene], isocaryphyllenic acid [(1R,4E,9S)4-carboxy-8-methylene-11,11-dimethylbicyclo[7.2.0]undec-4-ene] were first detected in the birch vegetative buds. 6-Hydroxyisocaryophyllene and epoxide of 6-hydroxyisocaryophyllene are isolated by from the Betula pendula Roth. birch buds etheric extract by chromatography on silica gel. (6R)-Acetoxyisocaryophyllene was synthesized. The structure of 6-hydroxyisocaryophyllene and epoxide of 6-hydroxyisocaryophyllene isolated from the buds were determined by NMR spectroscopy. Caryophyllenic acids are isolated from the ether extract with an aqueous solution of alkali. Caryophyllenic acids are separated by chromatography on silica gel. The structures of caryophyllenic acid and isocaryphyllenic acid isolated from the Betula grandifolia Litv., B. albo-sinensis Burk., B. fusca Pall.ex Georg, B. obscura A. Kotula, B. litwinowii Doluch., B. hallii Howell, B. grandifolia Litv. birch buds were determined by X-ray diffraction analysis. The physico-chemical characteristics and NMR data of 6-hydroxyisocaryophyllene, epoxide of 6-hydroxyisocaryophyllene and all the isolated acids are given. The obtained mixtures of compounds were analyzed by gas chromatography–mass spectrometry (GC-MS). The gas chromatographic retention indices of all identified compounds were determined.

Unusual Regularity in GC Retention of Simple Amino Acid Derivatives.

Application of simple regularities and general principles along with direct use of reference gas chromatography retention index data for reliable structure determination of compounds can be enhanced by determination of new regularities that are specific to certain structural elements. Revelation and interpretation of an anomaly in the elution order of alkyl esters of alkoxycarbonyl derivatives of glycine and alanine on standard and semi-standard non-polar phases. Preliminary derivatization of amino acids to alkyl esters of N-alkoxycarbonyl analogs and interpretation of their gas chromatographic characteristics. Alkyl esters of N-alkoxycarbonyl derivatives of alanine (Alkyl = C2H5, n- and iso-C3H7) elute prior to the same derivatives of glycine, despite the presence of an additional methyl group at C(2) in the molecule. Elution order is reversed for methyl esters of N-methoxycarbonyl derivatives. It is established that the peculiar behavior of alkyl esters of N-alkoxycarbonyl derivatives of glycine and alanine agrees with the concepts of gas chromatography and the known retention index regularities of organic compounds. A decrease of retention index values is a result of an introduction of an additional methyl group to a carbon atom connected to two polar fragments in a molecule like CH2XY. The dependence of the difference of retention index values for homologs of the types of CH3-CHXY and CH2XY vs. the total mass of fragments (X + Y) is similar to those for other sub-groups of analytes.

A deep convolutional neural network for the estimation of gas chromatographic retention indices

A deep convolutional neural network was used for the estimation of gas chromatographic retention indices on non-polar (polydimethylsiloxane and polydimethyl(5%-phenyl) siloxane) stationary phases. The neural network can be used for candidate ranking while searching a mass spectral database. A linear representation (SMILES notation) of the molecule structure was used as an input for the model. The input line was converted to a one-hot matrix and then directly processed by the neural network. The calculation of any common molecular descriptors is avoided, following the modern tendency in machine learning: to allow the neural network to find the most preferable features by itself instead of using hard-coded features. The model has two 1D-convolutional layers with 120 neurons each followed by a pooling layer and a fully-connected layer with 200 hidden neurons. The model was compared with state-of-the-art models for prediction of gas chromatographic indices based on molecular descriptors and on functional groups contributions. On different data sets better accuracy is shown together with greater versatility. The applicability to diverse sets of flavors and fragrances, essential oils, metabolites is shown. The possibility of using the model for improvement of mass spectral identification (without reference retention index) is demonstrated. The median absolute error and the median percentage error are in the range of 17.3 (0.93%) to 38.1 (2.15%) depending on used test data set. Ready-to-use neural network parameters are provided.

Comparative gas chromatographic/mass spectrometric characterization of di- and trialkyl phosphites.

Homologous series of alkyl esters of phosphorus-containing acids, namely, dialkyl phosphonates (synonym: dialkyl phosphites) and trialkyl phosphites, were characterized by electron ionization (EI) mass spectra and gas chromatographic retention indices (GC RI) on semi-standard non-polar stationary phases. It is confirmed that GC/MS characterization of any sets of homologues should not be restricted to independent registration of these analytical parameters. Their joint processing in the form of so-called homologous increments of GC RIs means, firstly, a novel way of evaluating the chromatographic polarity of analytes and, secondly, a new algorithm for the prediction of their molecular weights if no peaks of molecular ions are registered in the mass spectra. A standard GC/MS technique, including determination of GC RIs on semi-standard nonpolar stationary phases in temperature-programmed regime and electron ionization (EI) mass spectra was used. A total of 31 dialkyl phosphonate homologues and 37 trialkyl phosphite homologues were characterized by EI mass spectra and GC RIs for the first time. Joint processing of these analytical parameters allows the calculation of so-called homologous increments of GC RIs, which are useful parameters for evaluating the chromatographic polarity of analytes and predicting their molecular weights. GC/MS characterization of any sets of homologues should not be restricted to independent registration of the mass spectra and chromatographic retention parameters. Their joint processing in the form of so-called homologous increments of GC retention indices means, firstly, a novel way of evaluating the chromatographic polarity of analytes and, secondly, a new algorithm for predicting their molecular weights.

Front Cover: A new approach for predicting gas chromatography retention indices of polycyclic aromatic sulfur heterocycles

Front Cover: A new approach for predicting gas chromatography retention indices of polycyclic aromatic sulfur heterocycles

A new approach for predicting gas chromatography retention indices of polycyclic aromatic sulfur heterocycles

AbstractHere we present a novel and simple approach for predicting retention indices of polycyclic aromatic sulfur heterocycles on (5%‐Phenyl)‐methylpolysiloxane stationary phase using a new set of structural descriptors based on substituent positions. The prediction method modeled correlations between retention indices and structural parameters for alkyl substituted benzothiophenes and dibenzothiophenes. Five models were created: two for uni‐ and di‐ substituted benzothiophenes homologous series, and three for the following non‐homologous series: (i) uni‐ to tri‐ substituted benzothiophenes; (ii) uni‐ to tetra‐substituted dibenzothiophenes and (iii) isomers of benzo[b]naphtha[2,1‐d]thiophene and benzo[b]naphtha[1,2‐d]thiophene. Retention was highly correlated with structural parameters, and all models had high correlation coefficients, low root mean‐squared errors, and low mean absolute percentage errors for the homologous series. For non‐homologous models, R‐values were 0.998 for dibenzothiophenes, 0.995 for benzothiophenes, and 0.991 for benzo[b]naphtha[2,1‐d]thiophene and benzo[b]naphtha[1,2‐d]thiophene, lower than for homologous series. Our approach represents a simple strategy for the prediction of experimental retention indices values without the need for state‐of‐the‐art technology.

Homologous Increments of Gas Chromatographic Retention Indices as Characteristic of Organic Compounds Polarity

Properties of homologous increments of gas chromatographic retention indices have been examined, iRI = RI − 100int(M/14), where M is molecular weight and RI is retention index. Comparing to the characteristics of other organic substances (normal boiling points, permittivity, dipole moments, retention indices and their differences for standard polar and nonpolar phases, indices of boiling points, molecular masses, molar refractions, and their differences), it has been shown that the iRI value can be used as an additional characteristic of polarity.

Comparative study of chemical composition of essential oils for two species of Asteriscus genus from Western Algeria

ABSTRACTComparative study between the chemical composition of the essential oils of Asteriscus maritimus and Asteriscus spinosus from Western Algeria have been investigated. Chemical variability of the essential oils of both species was reported for the first time using gas chromatography/retention indices (GC/RI) and GC-mass spectrometry (GC/MS). A total of 86 compounds were identified in A. maritimus collective essential oil and 76 compounds in A. spinosus collective essential oil. Intra-species variations of the chemical compositions of essential oil from eighteen Algerian samples of various locations of both species were also investigated using statistical analysis. A. maritimus essential oils were characterized by T-cadinol (34.2–16.1%), p-cymene (30–15.1%), α-pinene (13.9–2.8%), bornyl acetate (8.7–5.3%) and Z-phytol (7.8–2.4%), as the major compounds. The main compounds of A. spinosus were α-cadinol (19.8–7.3%), β-pinene (17.6–12.9%), hexadecanoic acid (13.4–4.1%), T-cadinol (10.3–3.5%) and δ-cadinene (8.2–3.9%).

Identification of alkylpyrazines by gas chromatography mass spectrometry (GC-MS)

Pyrazines are an important group of natural products widely used as food additives and fragrants. Gas chromatography-mass spectrometry (GCMS) is the most widely applied analytical technique for characterization of alkylpyrazines. However, mass spectra of many positional isomers of alkylpyrazines are very similar. Consequently, an unambiguous identification of each positional isomer by spectral interpretation or database search protocols is practically unfeasible. In fact, there are many misidentifications in literature. To identify alkylpyrazines, chemists often resort to gas chromatographic retention indices (RIs). Although there are many compilations of retention indices of alkylpyrazines, these databases are often incomplete and the values reported are sometimes inconsistent. Herein, we present retention indices of fifty-six alkylpyrazines recorded on DB-1, ZB-5MS, DB-624, and ZB-WAXplus stationary phases, and compare them with those available in the NIST-2017 MS-RI database. Furthermore, we demonstrate how RI values can be used, together with mass spectral interpretations, to identify certain alkylpyrazines unambiguously.

Identification features of volatile impurities in ethyl alcohol using gas chromatographic retention indices

The restrictions of the commonly used determination algorithm of gas chro­matographic retention indices ( RI ) for the volatile impurities identification of ethyl alcohol being eluted prior to the principal constituent on the standard polar stationary phases (polyethylene glycols) are confirmed. The main reason of the­se restrictions seems to be the interfering n -alkanes С 6 – С 9 reference with the most of impurities. Due to this reason the identification of ethanol impurities to date preferably is based on comparing the profiles of chromatograms of target samples and those of model mixtures. It is shown that RI calculation in similar cases can be based on the data for the non-alkane reference constituents with known RI values that are always contained in the samples, namely acetone (RI 819 ± 6) and methanol (819 ± 6), in combination with the hold-up time value. Just the RI calculation permits us to reveal few groups of difficult to separate constituents as well as to identify some constituents previously not mentioned among ethanol impurities such as formaldehyde diethyl acetal (RI 860 ± 7) and ethyl vinyl ether (667 ± 10). The identification of ethyl vinyl ether is also confirmed by the analysis of the sample enriched with this ether in the result of the treatment of ethanol, containing small amounts of water, by calci­um carbide. In addition, the presence of ethyl vinyl ether is suggested in the sample of absolute ethanol prepared according to the known laboratory method by boiling with anhydrous cal­cium oxide. The evaluation of quantitative content of impurities is fulfilled using the internal standard method with acetone and methanol as standards. Keywords: Ethyl alcohol, impurities, gas chromatographic analysis, identification, vinyl ethyl ether, formaldehyde diethyl acetal (Russian) DOI: http://dx.doi.org/10.15826/analitika.2019.23.4.013 1 Alena I. Desyatova, 2 Nina G. Kovaleva, 3 Dmitrii A. Ponomarev, 1 Igor G. Zenkevich 1 St. Petersburg State University, Institute for Chemistry, Universitetskii prosp., 26, St. Petersburg 198504, Russian Federation 2 «Ekroskhim», Evpatoriiskii by-str., 7A, St. Petersburg 194044, Russia т Federation 3 St. Petersburg State Forest Technical University, Institutskii by-str., 5, St. Petersburg 194021, Russian Federation

Алгоритмы определения газохроматографических индексов удерживания. Сравнительная характеристика

Алгоритмы определения газохроматографических индексов удерживания. Сравнительная характеристика

Use of Molecular Weight and Elemental Composition as an Additional Constraint in Library Search

Identification of organic compounds based only on searching against electron ionization mass spectral libraries is tentative. To increase the reliability of the identification, additional information should be used. Gas chromatographic retention indices, in addition to mass spectra, are most often used. Molecular weight and elemental composition is less frequently used, because additional experiments are required to determine these characteristics. In the present paper, we examined the influence of the molecular weight, elements present in a molecule and molecular formula on the results of the library search. It is shown that, determination of the nominal mass or molecular formula slightly increases efficiency of the library search (for example, probability that the correct compound occupies the first position in the list of possible candidates increases by only 2.8 and 3.0% respectively). On the other hand, use of additional constraints in the library search can significantly reduce the number of possible candidates and simplify predicting the absence of compound in the database.

Special Features of the Interaction between Asymmetric Dimethylhydrazine and Thiocontaining Schungite

The interaction between asymmetric dimethylhydrazine and thiocontaining mineral schungite-III has been studied. Chromatography–mass spectrometry has been used to identify alkyl polysulfides as the products of desorption of asymmetric dimethylhydrazine from schungite surface. The interaction of asymmetric dimethylhydrazine with crystalline sulfur has been investigated in a model system. Dimethyl polysulfides, CH3SnCH3; (dimethylamino)methyl polysulfides, (CH3)2NSnCH3; and bis(dimethylamino) polysulfides, (CH3)2NSnN(CH3)2, with 2 ≤ n ≤ 4 have been detected. Gas-chromatographic retention indices have been determined for the products of the interaction of asymmetric dimethylhydrazine with sulfur and the schungite material.

Atom-Type-Based AI Topological Indices for Artificial Neural Network Modeling of Retention Indices of Monomethylalkanes.

In this work, a combination of Xu and atom-type-based AI topological indices (TIs) were employed for quantitative structure-retention relationship (QSRR) study of monomethylalkanes (MMAs). A total of 196 temperature-programmed gas chromatographic retention indices corresponding to all C4-C30 MMAs on OV-1 stationary phase have been used in QSRR modeling. Results of the study showed that an artificial neural network (ANN) with 4-9-1 topology and Levenberg-Marquardt training algorithm can predict the retention indices with high degree of accuracy. The statistics of root-mean-square error for the training, validation and test sets were 0.200, 0.316 and 0.215, respectively. The proposed model resulted in a maximum relative error of 0.24% suggesting the TIs as excellent alternative for estimating retention indices of MMAs. According to the obtained results, relative importance of the TIs decreased in the order of AI(-CH3)> AI(-CH2-)> AI(>CH-)> Xu showing significant role of molecular branching, steric factor and molecular size as effective structural features on retention indices of MMAs.

Regression algorithm for calculating second-dimension retention indices in comprehensive two-dimensional gas chromatography

Gas chromatography-mass spectrometry (GC–MS) is one of the most accurate, well developed, and reliable analytical tools for the analysis of volatile and semivolatile compounds. The GC–MS data have been extensively improved by enhancing the separation capacity via comprehensive two-dimensional gas chromatography (GC × GC). The reliability of the identification of the analytes in GC × GC–MS can be notably improved by applying the second-dimension retention index (2I) as additional analytical parameter along with the commonly used first dimension retention index (1I) and mass spectrum. A novel approach for calculating second-dimension retention indices (2I) for semivolatile organic compounds is proposed. It is noteworthy that the standards used in calculations are the same compounds recommended as internal standards by US EPA 8270 Method for analysis of semivolatile organic compounds. The new algorithm takes into account the analyte retention time and its retention temperature at the secondary column, (2tR) and (2TR), respectively. The experimental data collected with different primary oven temperature ramp rates and carrier gas flow rates have shown that the calculated by the proposed approach 2I values remain the same for each evaluated compound, drifting in a very narrow range. The proposed approach was tested using 100 organic compounds from various chemical classes including alkanes, phenols, nitrobenzenes, chlorinated hydrocarbons, anilines, polycyclic aromatic hydrocarbons (PAHs), phthalates, etc. The important advantage of the proposed 2I values for compounds of the same chemical origin (reference standards and analytes) involves applicability of well-known Lee’s indices for non-polar phases. Therefore, the proposed approach can be used in targeted and non-targeted analysis of a wide range of organic compounds. The reduced version of the second dimension retention indices provides a valuable mapping of the homologues series of organic compounds, making their detection and identification easy and reliable.

Novel Atom-Type-Based Topological Descriptors for Simultaneous Prediction of Gas Chromatographic Retention Indices of Saturated Alcohols on Different Stationary Phases

In this work, novel atom-type-based topological indices, named AT indices, were presented as descriptors to encode structural information of a molecule at the atomic level. The descriptors were successfully used for simultaneous quantitative structure-retention relationship (QSRR) modeling of saturated alcohols on different stationary phases (SE-30, OV-3, OV-7, OV-11, OV-17 and OV-25). At first, multiple linear regression models for Kovats retention index (RI) of alcohols on each stationary phase were separately developed using AT and Randic’s first-order molecular connectivity (1χ) indices. Adjusted correlation coefficient (R2adj) and standard error (SE) for the models were in the range of 0.994-0.999 and 4.40-8.90, respectively. Statistical validity of the models were verified by leave-one-out cross validation (R2cv > 0.99). In the next step, whole RI values on the stationary phases were combined to generate a new data set. Then, a unified model, added McReynolds polarity term as a descriptor, was developed for the new data set and the results were satisfactory (R2adj=0.995 and SE=8.55). External validation of the model resulted in the average values of 8.29 and 8.69 for standard errors of calibration and prediction, respectively. The topological indices well covered the molecular properties known to be relevant for retention indices of the model compounds.

6-Hydroxyisocaryophyllene and isocaryophyllenic acid from birches vegetative buds

The new isocaryophyllene derivatives were first detected in the birch vegetative buds. The structure of 6-hydroxyisocaryophyllene [(1R,4Z, 6R, 9S)-8-methylene-11,11-dimethylbicyclo[7.2.0]undec-4-ene-6-ol] isolated from the Betula pendula Roth. birch buds was determined by NMR spectroscopy. The structures of caryophyllenic acid and isocaryphyllenic acid isolated from the Betula grandifolia Litv., B. albo-sinensis Burk., B. fusca Pall.ex Georg, B. obscura A. Kotula, B. litwinowii Doluch., B. hallii Howell, B. grandifolia Litv. birch buds was determined by X-ray diffraction analysis. The physico-chemical characteristics and NMR data of 6-hydroxyisocaryophyllene, epoxide of 6-hydroxyisocaryophyllene and all the isolated acids are given. The gas chromatographic retention indices of all identified compounds were determined.

Methodological Approaches to the Calculation and Prediction of Retention Indices in Capillary Gas Chromatography

The scientific achievements in the field of calculation and prediction of gas chromatographic indices of retention of organic compounds on standard nonpolar polydimethylsiloxane stationary phases of capillary chromatographic columns are analyzed. Approaches based on the study of correlation dependences with the use of physicochemical, fragment, and quantum-chemical descriptors, topological indices, and various additive models are described.

QSPR in forensic analysis – The prediction of retention time of pesticide residues based on the Monte Carlo method

A method for the prediction of retention indices of pesticides using the Monte Carlo method and with optimal molecular descriptors based on local graph invariants and the SMILES notation of studied compounds has been presented. Quite satisfactory results were obtained with the proposed method, since a robust model with good statistical quality was developed. The predictive potential of the applied approach was tested and the robustness of the model was proven with different methods. The best calculated QSPR model had following statistical parameters: r2 = 0.9182 for the training set and r2 = 0.8939 for the test set. Structural indicators defined as molecular fragments responsible for the increases and decreases of gas chromatographic retention indices activity were calculated.

QSRR prediction of gas chromatography retention indices of essential oil components

A comprehensive and largest (to the best of our knowledge) database of 791 essential oil components (EOCs) with corresponding gas chromatographic retention properties has been built. With this data set, Quantitative structure–retention relationship (QSRR) models for the prediction of the Kovats retention indices (RIs) on the non-polar DB-5 stationary phase have been built using the DRAGON molecular descriptors and the regression methods: multiple linear regression (MLR) and artificial neural networks (ANN). The obtained models demonstrate good performance, evidenced by the satisfactory statistical parameters for the best MLR (R 2 = 96.75% and $$Q_{\text{ext}}^{2}$$ = 98.0%) and ANN (R 2 = 97.18% and $$Q_{\text{ext}}^{2}$$ = 98.4%) models, respectively. In addition, the built models provide information on the factors that influence the retention of EOCs over the DB-5 stationary phase. Comparisons of the statistical parameters for the QSRR models in the present study with those reported in the literature demonstrate comparable to superior performance for the former. The obtained models constitute valuable tools for the prediction of RIs for new EOCs whose experimental data are undetermined.