Gas Chromatographic Retention Indices Research Articles

Gas chromatographic retention indices for N-substituted amino s-triazines on capillary columns. Part V. Temperature dependence of the retention index

The temperature dependence of the retention index was studied for N-substituted amino s-triazines on DB-1, DB-5 and DB-WAX capillary columns within the temperature range 190?230 ?C. Two linear equations with the column temperature and its reciprocal as variables were studied. The first one shows a slightly better precision for 2,4-bis(alky lamino)-6-chloro-s-triazines and 2-alkylamino-4,6-dichloro-s-triazines while the second one shows a better precision for 2,4-bis(cycloalkylamino)-6-chloro-s-triazines.

Gas-Chromatographic Identification of the Products of the Thermal Degradation of a Tetrafluoroethylene and Perfluoro(Propyl Vinyl Ether) Copolymer

The volatile products of the thermal degradation of a tetrafluoroethylene and perfluoro(propyl vinyl ether) were identified based on a priori chemical information on the nature of samples (only perfluorinated compounds can be present) and on reference gas-chromatographic retention indices on a Silipore 600 polar inorganic adsorbent in combination with calculated values of these parameters. All of the major degradation products exhibited the general formula CnF2n and belonged to the perfluorocycloalkene (tetrafluoroethylene and hexafluoropropylene were predominant) and perfluorocycloalkane (primarily, perfluorocyclobutane) series. Many minor components were represented by 1- and 2-perfluoroalkenes (n ≤ 6) and perfluorocycloalkanes (n ≤ 7).

The prediction for gas chromatographic retention index of disulfides on stationary phases of different polarity

Quantitative structure–retention relationship (QSRR) models for the gas chromatographic (GC) Kaváts indices of disulfides on four different polarity stationary phase have been developed. Semi-empirical quantum chemical method (AM1) implemented in hyperchem 4.0 was employed to calculate a set of molecular descriptors of 50 disulfides. The four stationary phases in the research were: Apiezon M, OV-17 , Triton X-305 and PEG-1000 . By using multiple linear regression (MLR), we obtained four empirical functions with high correlation coefficient ( R 1=0.995, R 2=0.994, R 3=0.990, R 4=0.976). At the same time, using Thin Plat Spline the Radial Basis Function neural networks models were obtained with root mean squared error (RMS) of training set (RMS T1=0.013351, RMS T2=0.012973, RMS T3=0.023228, RMS T4=0.020755) and RMS of validation set (RMS V1=0.007626, RMS V2=0.005897, RMS V3=0.005109, RMS V4=0.007377) and RMS of testing set (RMS X1=0.016676, RMS X2=0.016704, RMS X3=0.017162, RMS X4=0.014755). The results indicated that the QSRR models proposed were very satisfactory.

Correlation relationships between physico-chemical properties and gas chromatographic retention index of polychlorinated-dibenzofurans.

Correlation relationships between physico-chemical properties including vapor pressures (P), water solubilities (S), Henry's law constants (H(c)), n-octanol-water partition coefficients (K(ow)), sediment-water partition coefficient (K(pw)) and biotic lipid-water partition coefficient (K(bw), bioconcentration factor) of polychlorinated-dibenzofurans (PCDFs) and their gas chromatographic retention indices (GC-RIs) were established. A model equation between GC-RIs (= RI) and these physico-chemical properties (K) of PCDFs was in a form of log K = aRI2 + bRI + c with correlation coefficients (R2) greater than 0.94, except H(c). These equations were derived from six experimental data (five experimental data for log K(bw)) in each physico-chemical properties of PCDFs reported previously. The values of log P, log S, log H(c), log K(ow), log K(pw) and log K(bw) of PCDFs predicted by these equations based on their GC-RIs in the present study derviated from those calculated by the solubility parameters for fate analysis method in a previous study by 0.49, 0.32, 0.11, 0.34, 0.14 and 0.22 log units, respectively.

Aroma characterization and antioxidant activity of supercritical carbon dioxide extracts from Terminalia catappa leaves

The green, yellow fallen, and red fallen leaves of Terminalia catappa were extracted using supercritical carbon dioxide at 2000, 3000 or 4000 psi and 40 °C. The volatile components of the extracts were identified using gas chromatographic retention indices, mass spectra, and authentic compounds. Gas chromatography/olfactometry (GC/O) was employed for the analysis of aroma characteristics. Antioxidant activities of the extracts were also determined. A total of 18 compounds were identified in the leaf extracts. Among them, three highest amounts of compounds were ethyl acetate, 6,10,14-trimethyl-2-pentadecanone and phytol. Although ( E, E)-2,4-decadienal with oily odour was not high in content, it was odour significant due to its odour value of 18,572–31,714. β-Ionone with the highest odour value of 82,857–44,5715 was described as a fruity, floral aroma. With respect to the antioxidant activity by the 1,3-diethyl-2-thiobarbituric acid method, the extracts from yellow fallen and red fallen leaves exhibited higher inhibition of peroxidation than those from green leaves. Supercritical carbon dioxide extraction at 2000 psi and 40 °C resulted in the extracts with better antioxidant activity whereas lower inhibition of peroxidation was observed with the extracts prepared from the extraction at 4000 psi and 40 °C.

The prediction for gas chromatographic retention indices of saturated esters on stationary phases of different polarity

A quantitative structure-retention relationship (QSRR) model has been developed for the gas chromatographic Kováts indices of 98 saturated esters on seven different polar stationary phases by multiple linear regression analysis (MLR). The seven stationary phases are: SE-30, OV-7, DC-710, OV-25, 100% phenyl, DC-230 and DC-530. Chemical descriptors were calculated from the molecular structures by PM3 of Hyperchem 4.0. Principal component analysis (PCA) was applied to extract the data structure. Multiple linear regression was made in forward stepwise manner to select suitable variables in the model. The proposed model had a high multiple square correlation coefficient R 2 and low standard error S.E. The result proved the strong predictive power of the model.

Characterization and analysis ofSemen Cuscutae by capillary gas chromatography and gas chromatography-mass spectrometry

Chloroform extracts of the Chinese herbal medicine Semen Cuscutae were analyzed by capillary gas chromatography (GC) and gas chromatography–mass spectrometry (GC–MS), and the pharmaceutically active component (+)-Sesamin was identified and determined in this plant for the first time. Several n-alkanes, (+)-sesamin, and some compounds, identified by GC–MS and GC retention index, were chosen to characterize different samples of Semen Cuscutae. Fingerprints were obtained of the extracts of Semen Cuscutae from six sources. In addition, it was shown that some fatty acids are present in the seed oils (petroleum ether extracts) of Semen Cuscutae.

Prediction of gas chromatographic retention indices by the use of radial basis function neural networks

A new method for the prediction of retention indices for a diverse set of compounds from their physicochemical parameters has been proposed. The two used input parameters for representing molecular properties are boiling point and molar volume. Models relating relationships between physicochemical parameters and retention indices of compounds are constructed by means of radial basis function neural networks. To get the best prediction results, some strategies are also employed to optimize the topology and learning parameters of the RBFNNs. For the test set, a predictive correlation coefficient R=0.9910 and root mean squared error of 14.1 are obtained. Results show that radial basis function networks can give satisfactory prediction ability and its optimization is less-time consuming and easy to implement.

Gas chromatographic and IR spectroscopic characteristics of tri- and tetramethylcyclohexenyl butenyl ketones

Infrared spectroscopic characteristics and gas chromatographic retention indices of tri- and tetramethylcyclohexenyl butenyl ketones were determined at different temperatures of analysis. Thermodynamic characteristics of sorption on the apolar stationary phase were calculated. The sorption characteristics of tri- and tetramethylcyclohexenyl butenyl ketones show that under conditions of capillary gas chromatography these compounds are retained due to the dispersive energy. It was shown by FTIR spectroscopy that the formation of conjugation systems of double bonds is responsible for the higher retention of the β-isomers compared with that of the α-isomers. The shortening of the distance between the carbonyl and trimethylcyclohexenyl groups was found to be accompanied by a decrease in the retention of the isomeric compounds.

Optimum Analytical Parameters for the Chromatographic Characterization of Pesticides

Correlation coefficients were considered for various combinations of analytical parameters for a series of 20 most widely used pesticides. These parameters included gas-chromatographic retention indices (RIs) on standard nonpolar polydimethylsiloxane stationary phases, RIs in reversed-phase HPLC, data on out-of-column phase equilibria (distribution constants Kpin heterophase solvent systems), UV-spectroscopic characteristics, and the most important mass-spectrometric characteristics. A combination of RIs with the relative absorbance Arel= A(254)/A(220) and distribution constants in the hexane–acetonitrile system was found to be most informative for the HPLC identification of compounds from this class.

Improving the accuracy of Kováts’ retention indices in isothermal gas chromatography

Isothermal Kováts’ retention indices are currently reported as whole numbers, and are frequently deduced from a linear least mean squares fitting of the logarithms of adjusted retention times of a number of n-alkanes versus carbon number, following an iterative method that minimises errors. The currently accepted accuracy is about one retention index unit for apolar stationary phases, and lower for polar stationary phases. This paper presents results that show how the accuracy of the retention index may be safely reported to one-tenth of a retention index unit by the use of a non-linear equation, with present day gas chromatographs without electronic flow controllers. Results are presented that prove the correctness of the retention indices found for several substances on one particular capillary column. Hints on the minimum retention times needed to achieve the 0.1 retention index accuracy are mentioned, for retention times recorded in minutes and in seconds. According to results of this paper, two chromatograms, run under the appropriate conditions, are sufficient to obtain the desired accuracy. The method proposed in this paper does not require knowledge of the hold-up time of the chromatogram.

Mathematical relationships between vapor pressure, water solubility, Henry's law constant, n-octanol/water partition coefficent and gas chromatographic retention index of polychlorinated-dibenzo-dioxins

Mathematical relationships between vapor pressures ( P), water solubilities ( S), Henry's law constants (Hc), n-octanol/water partition coefficients ( K ow) and gas chromatograph retention indices (GC-RIs) of polychlorinated-dibenzo-dioxins (PCDDs) were established. A model equation was established between GC-RIs (=RI) and other physico-chemical parameters ( K) of PCDDs in the form of log K= aRI 2+ bRI+ c with correlation coefficients ( R 2) greater than 0.97, except Hc. These equations were derived from 56 experimental data of PCDDs reported previously. The values of P, S, Hc and K ow of PCDDs predicted by these equations based on their GC-RIs in the present study deviated from those calculated by the SOFA method in a previous study by only 0.19, 0.13, 0.18 and 0.096 log units, respectively.

Application of Wavelet Neural Network to the Prediction of Gas Chromatographic Retention Indices of Alkanes

AbstractA wavelet neural network (WNN) is employed to create a quantitative structure‐retention index relationship, which correlates the novel molecular distance edge vector (MDEV)‐consisting of ten elements to Gas Chromatographic retention indexes (RIGC) of Alkanes. The RIGC has been calculated by the WNN from the molecular topological descriptors of examined alkanes. In this work, the RIGC estimated and predicted by conventional neural networks (say back propagation neural networks, BP) has also been provided. The excellent predicted results with a correlation of 0.9996 and standard deviation of 5.0598 suggest that the WNN technique is a powerful tool in QSAR/QSPR modeling and superior to the BP neural networks.

Partition coefficients of alkyl aromatic hydrocarbons and esters in a hexane–acetonitrile system

Partition coefficients ( K p) in a heterogeneous system consisting of two immiscible organic solvents can be successfully used for a supplementary identification parameter in qualitative GC and GC–MS analysis of organic compounds. For rapid addition to database of K p values, calculation methods based on the well-known ‘retention–structure relationships’ approach can be used. This paper reports the experimentally determined and calculated K p values for 252 compounds including alkyl aromatic hydrocarbons and esters. It is shown that for group identification of components it is desirable to use not the K p values themselves but the parameter j which is a combination of K p and gas chromatographic retention indices: j= kI−log K p.

Linear and non-linear modeling for the investigation of gas chromatography retention indices of alkylbenzenes on Cit.A-4, SE-30 and Carbowax 20M

Models for theoretical prediction of gas chromatographic retention indices of alkylbenzenes on different polar stationary phases at different temperatures were established by linear and non-linear methods. The linear model is multivariable linear regression. The non-linear models include artificial neural networks (ANNs) and multivariable polynomial regression. The performances of different models were compared. The result of ANN is superior over other methods. The 170 data belong to 46 alkylbenzenes at different temperatures on three different stationary phases. In order to describe the structure of alkylbenzenes, we proposed a new method to describe them. Each alkylbenzene was uniquely represented by a simple set of six numeric codes. Three different stationary phases are Cit.A-4, SE-30 and Carbowax 20M, their polarity were characterized by McReynolds’ constant. The eight input parameters included a set of six numeric codes, McReynolds’ constant of the different stationary phases, and temperature. The output parameter is retention index. The neural networks’ architecture and the learning times were optimized. The optimum ANN could give excellent prediction results.

Chemometrics to chemical modeling: Structural coding in hydrocarbons and retention indices of gas chromatography

Systematic studies were performed on an application of chemometrics to molecular modeling and the regularity of the retention index (RI ) of gas chromatography (GC). Molecular structures of hydrocarbons in straight-run gasoline were numerically coded. A set of structural parameters was accordingly obtained for the hydrocarbons and found correlate to their GC retention indices. A quantitative structure-retention relationship (QSRR) model (M1), with a correlation coefficient of R = 0.9901 and a standard deviation (SD) error of SD = 20.24, between the numeric structural codes and GC retention indices of 150 hydrocarbons was developed using multiple linear regression (MLR). If a “leave-one-out” cross-validation procedure was employed to construct a QSRR model for all samples, a second model (M2) with R = 0.9874 and SD = 22.87 was generated. The structural codes of hydrocarbons were tested with MLR for estimation and prediction of the GC RI by models M1 and M2, and the results obtained proved to be satisfactory.

Interpretation of quantitative structure-property and -activity relationships.

The potential utility of data reduction methods (e.g. principal component analysis) for the analysis of matrices assembled from the related properties of large sets of compounds is discussed by reference to results obtained from solvent polarity scales, ongoing work on solubilities and sweetness properties, and proposed general treatments of toxicities and gas chromatographic retention indices.

Molar Refractivity and Connectivity Index Correlations for Henry's Law Virial Coefficients of Odorous Sulfur Compounds on Carbon and for Gas-Chromatographic Retention Indices

Gas–solid chromatography was used to obtain values of the second gas–solid virial coefficient, B2s, in the temperature range from 392 to 511 K for 10 volatile, malodorous organic sulfur compounds; ethanethiol, 1-propanethiol, methyl sulfide, 2-propanethiol, 1-methyl-1-propanethiol, 2-methyl-1-propanethiol, 2-methyl-2-propanethiol, ethyl sulfide, ethyl methyl sulfide, and tert-butyl methyl sulfide. Carbopack C (Supelco Inc.), a graphitized carbon black powder, was used as the adsorbent. Beginning with a theoretical equation for the second gas–solid virial coefficient, it was shown how a quantitative structure–retention relation (QSRR) could be developed to correlate ln B2s and hence chromatographic retention times with calculated molar refractivity and connectivity index values for the thiols and thioethers. It was found that both the gas–solid interaction energies and the ln B2s values could be correlated with calculated adsorbate molar refractivity (r2=0.951) and (r2=0.961), respectively. Connectivity index and molar refractivity together provide a r2=0.989 correlation of the ten ln B2s values at 403 K. A set of 373 organic compounds with retention indices taken from the literature was used to further test our approach. The 373 molecules were divided into 10 structural subgroups and molar refractivities and connectivity indices were calculated and used to correlate their retention index values. An overall correlation of r2=0.982 for the retention indices of the 373 molecules was found.

Interpretation of Retention Indices in Gas Chromatography for Establishing Structures of Isomeric Products of Alkylarenes Radical Chlorination

By an example of previously uncharacterized products obtained by alkylarenes radical chlorinationwas demonstrated that combination of various interpretation methods applied to the retention indices (RI) inthe gas chromatography on the standard nonpolar phases (comparison of RI of products, initialcompounds, characteristics of succession of the chromatographic elution of the structural isomers with theuse of estimation of molecular dynamic parameters, application of the additive schemes to RI calculation, and using of structural analogy CH3↔Cl for testing the results obtained) permitted unambiguous identification of the structure even without data of mass spectrometry.

Comparison of the Topological and Dynamic Characteristics of Molecules for Calculating Retention Indices of Organic Compounds

This paper reports on a comparative analysis of the linear correlation equations relating the gas-chromatographic retention indices (RI) of several groups of isomeric organic compounds to the topological (Wiener and Hosoya indices) and dynamic (intramolecular energies estimated by molecular dynamic methods and the vibrational components of this energy estimated with simple models) parameters of molecules. It is shown that the choice of one of these parameters does not ensure the best approximation to RI, since the results depend on the chemical nature of substances. Correlations between all of the above quantities have been established. The correlations serve as a basis for physicochemical interpretation of the topological parameters of molecules as quantities proportional to the intramolecular vibrational and rotation energies.