Methodology for deriving quantitative structure-retention relationships in gas chromatography

Mekenyan, Ovanes G.; Dimov, N.; Enchev, Venelin

doi:10.1016/0003-2670(92)80128-t

Cited by 23 publications

(5 citation statements)

References 12 publications

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“…Mekenyan et al derived linear quantitative retention-structure models in gas chromatography for 41 alkylbenzenes: boiling point, two geometric indexes, and two electronic structure descriptors in their best equation (Table : no. 1) . Jurs and his group correlated the observed Kovats retention indexes of sulfur vesicants by multiple linear regression techniques using 9 descriptors (topological, electronic, and geometrical) in the models for different stationary phases (Table : no.…”

mentioning

confidence: 99%

QSPR Correlation and Predictions of GC Retention Indexes for Methyl-Branched Hydrocarbons Produced by Insects

et al. 1999

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A successful interpretation of the complex manner by which the GC retention indexes of methylalkanes produced by insects are related to chemical structure was achieved using the quantitative structure-property relationship (QSPR) method. A general QSPR model including mainly topological descriptors was obtained for 178 data points. The error of the model is similar to the experimental error. The model was supported by (i) leave-one-out cross validation and (ii) division into three sets and prediction of each set from the other two. As a further test of the utility of the model, retention indexes were successfully predicted for an external set of 30 methyl-branched hydrocarbons not involved in the deduction of the correction equation from the main data set. General trends of the structural variation of compounds in any given range of retention index are discussed. The average error was 4.6 overall and 4.3 for the 165 compounds remaining after leaving out small monomethyl alkanes.

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confidence: 99%

QSPR Correlation and Predictions of GC Retention Indexes for Methyl-Branched Hydrocarbons Produced by Insects

et al. 1999

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“…The selection of this set of physicochemical parameters was motivated by the fact that they previously found application in QSRR studies. Thus, M-RE for the assessment of the relationship between structure and retention of solutes on polybutadiene-coated alumina stationary phase, 21 for the study of the impact of lipophilicity and polarity parameters in HPLC, 22 and diverse electronic and steric parameters for QSRR studies in both GC, 23,24 and HPLC. 25 The number of accepted independent variables was not limited, the limit of acceptance was set to 95 % significance level.…”

Section: Stepwise Regression Analysismentioning

confidence: 99%

Simultaneous Effect of Organic Modifier and Physicochemical Parameters of Barbiturates on their Retention on a Narrow-Bore PGC Column. Part 2

Cserháti¹,

Szőgyi²

2011

Croat. Chem. Acta

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Abstract. The retention time of 23 barbituric acid derivatives was determined on an narrow-bore porous graphitized carbon (PGC) column employing water-dioxane mixtures as mobile phases. The retention factor (k), theoretical plate number (N), and asymmetry factor (AF) were computed for each analyte in each mobile phase. Quantitative structure-retention relationship (QSRR) calculations using stepwise regression analysis (SRA) demonstrated the binding of analytes to the surface of PGC stationary phase is influenced by electrostatic interaction and sterical correspondence between the stationary phase and the various substructures of barbituric acid derivatives.

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“…For example, Dimov and Osman used QSRRs to relate the chromatographic retention of 38 isoalkanes to their molecular structure features [14]. Mekenyan et al have derived a linear quantitative retention structure model in GC for 41 alkylbenzenes [15]. Also, Karitzky et al has used QSRR techniques for prediction of GC retention indices of methyl-branched hydrocarbons produced by insects [16].…”

Section: Introductionmentioning

confidence: 98%

Prediction of supercritical fluid chromatographic retention factors at different percents of organic modifiers in mobile phase

Fatemi

Malekzadeh

Shamseddin

2009

J of Separation Science

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In this work quantitative structure-retention relationship models were developed to predict the solute retention factors in supercritical fluid chromatography (SFC) in various organic modifiers. Data set contains the retention data of 35 various organic compounds in 0, 2, 4 and 6% of methanol in mobile phase. The obtained 140 data points were divided into training, internal and external test sets which have 93, 23 and 24 retention data. The diversity validation test was performed on data the set to ensure that the structure of the training and/or test sets can represent those of the whole ones. Descriptors which were selected by stepwise multiple linear regression (MLR) methods are: the percent of organic modifier in mobile phase, salvation connectivity index chi-2, salvation connectivity index chi-5, H attached to heteroatom, the 2(nd) structural information content and polarity parameter. These descriptors were used as features in generation of linear and non-linear models using MLR and artificial neural network (ANN) methods, respectively. The root mean square error of MLR model are 0.116, 0.138 and 0.260 for training, internal and external test sets, respectively, while these values are 0.036, 0.097 and 0.244 for ANN model, respectively. Comparison between these values and other statistical parameters obtained from these two models reveals the credibility of ANN in prediction of solute retention factors in SFC.

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Methodology for deriving quantitative structure-retention relationships in gas chromatography

Cited by 23 publications

References 12 publications

QSPR Correlation and Predictions of GC Retention Indexes for Methyl-Branched Hydrocarbons Produced by Insects

QSPR Correlation and Predictions of GC Retention Indexes for Methyl-Branched Hydrocarbons Produced by Insects

Simultaneous Effect of Organic Modifier and Physicochemical Parameters of Barbiturates on their Retention on a Narrow-Bore PGC Column. Part 2

Prediction of supercritical fluid chromatographic retention factors at different percents of organic modifiers in mobile phase

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