Prediction Of Gas Chromatographic Retention Times Research Articles

Prediction of GC Retention Times of PBDE Congeners Based on QSRR

Support vector machine (SVM) algorithm was applied to predict the gas chromatographic (GC) relative retention times (RRTs) for 126 polybrominated diphenyl ether (PBDE) congeners on 7 stationary phases. A total of 151 topological and connectivity indices descriptors were derived from E-dragon software. Genetic algorithm (GA) coupled with multiple linear regression (MLR) was used to select optimal subsets from large-size molecular descriptors. Overall support vector regression predicting training sets correlation coefficients R2 are greater than 0.996, except for the CP-Sil19 column, in which Q2loo (correlation coefficient of leave-one-out cross validation) and test sets correlation coefficients R2 are larger than 0.992. The excellent statistical parameters reveal that the models are robust and have high internal and external predictive capability.

Prediction of Thermodynamic Parameters in Gas Chromatography from Molecular Structure: Hydrocarbons.

Theoretical prediction of gas-chromatographic retention times could be used as an additional method for a more accurate identification of organic compounds during GC/MS analysis. Two separate quantitative structure−property relationship models were introduced for the calculation of thermodynamic values (ΔH°, ΔS°) for aliphatic and aromatic hydrocarbons. These values are required for the calculation of retention times in temperature programmed gas chromatography. Seven-descriptor and five-descriptor MLR models were selected for the calculation of ΔH° and ΔS° values, respectively, based on the best cross-validation abilities. The final prediction capabilities of the models were evaluated by a test set procedure. RMS errors calculated from the test set were 207 cal mol-1 and 0.58 cal mol-1 K-1 for ΔH° and ΔS° prediction models, respectively. To evaluate the error of the models represented in the time scale, several chromatograms were simulated using experimental Pro ezGC and theoretically calculated thermody...

Prediction of thermodynamic parameters in gas chromatography from molecular structure: hydrocarbons.

Theoretical prediction of gas-chromatographic retention times could be used as an additional method for a more accurate identification of organic compounds during GC/MS analysis. Two separate quantitative structure-property relationship models were introduced for the calculation of thermodynamic values (DeltaH degrees, DeltaS degrees) for aliphatic and aromatic hydrocarbons. These values are required for the calculation of retention times in temperature programmed gas chromatography. Seven-descriptor and five-descriptor MLR models were selected for the calculation of DeltaH degrees and DeltaS degrees values, respectively, based on the best cross-validation abilities. The final prediction capabilities of the models were evaluated by a test set procedure. RMS errors calculated from the test set were 207 cal mol(-1) and 0.58 cal mol(-1) K(-1) for DeltaH degrees and DeltaS degrees prediction models, respectively. To evaluate the error of the models represented in the time scale, several chromatograms were simulated using experimental Pro ezGC and theoretically calculated thermodynamic data. Afterward a standard deviation of retention time residuals was calculated. It was found out that, although the standard deviation varies from one chromatographic condition to another, the ratio between the standard deviation and the maximum available separation space for the particular set of organic compounds remains constant and was around 5% of the maximum separation space available at selected chromatographic conditions. Our prediction model was able to accurately differentiate between the retention times of the consecutive compounds in the n-alkanes, 1-alkenes, and 2-alkenes homological series.