Quantitative Prediction of Normal Boiling Points for Organic Compounds Using Gas Chromatographic Retention Times on Two Columns of Different Polarity

Quantitative relationships between normal b.p.s and gas chromatographic retention times of 271 organic compounds of diverse structures was studied using a multivariate regression method and statistical importance evaluation. It was found that satisfactory modelling cannot be obtained using only retention times on a single column. Even dividing the 271 compounds into four groups according to their chemical structures, only hydrocarbons on nonpolar columns gave good results with a linear model. However, if the retention times on two columns of different polarity are used to build the model, a satisfactory two-parameter model can be obtained for the whole data set with a squared correlation coefficient (R ²), standard deviation (s) of the prediction, and probability value (P) of: 0.9456, 16.1K and 1.7×10^?150, respectively. The results also show that the statistical importance of the two-parameter model is much better than that of the one-parameter model.     

基于分子结构预测气相色谱程序升温保留指数

从拓扑指数出发,研究了分子结构与气相色谱程序升温保留指数之间的关系。对所选择的部分分子结构,利用主成分回归(PCR)的相关系数R=0.9998,标准偏差S=9.987,交互检验(leave one out cross-valida-tion)所得标准偏差S=11.17。同时,对同一柱型不同升温速率条件下的保留指数之间的关系、同一升温速率不同柱型条件下保留指数之间的关系进行了初步探讨,建立的模型线性关系明显。     

烷烃同系物气相色谱保留指数的分子拓扑研究

定义了分子中原子的平衡电负性,并用原子的平衡电负性对分子图进行着色,在距离矩阵的基础上结合分子中各原子的支化度构建了一种新的拓扑指数N1,N2和N3。该拓扑指数对分子结构实现惟一性表征,具有优良的结构选择性。将拓扑指数N1,N2和N3与烷烃在固定相角鲨烷(柱温50　℃)及SE-30(柱温80　℃)上的气相色谱保留指数进行多元线性回归,结果表明烷烃的气相色谱保留指数可分别定量描述为I(Squalane)=23.97842N1-3.86562N2+0.787379N3+42.33061,I(SE-30)=23.83937N1-3.5687N2+0.939876N3+22.11952。用上述回归方程对烷烃的气相色谱保留指数进行预测,结果表明预测值与实验值的平均相对误差均为1.31%,预测结果误差在实验误差范围内。     

Simultaneous chromatographic identification of a few components in mixtures based on a correlation between their absolute or relative retention times under different conditions

A correlation was established between the absolute and relative retention parameters of various compounds under different conditions of chromatographic analysis (isothermal and temperature programming conditions in gas chromatography or isocratic and gradient elution in high-performance liquid chromatography). This correlation is described by the linear regression equations t _R (II) = = at _R (I) + b with a high degree of accuracy. This property of chromatographic retention parameters allowed us not only to recalculate the values of these parameters determined under different conditions, but also to propose an algorithm for the simultaneous identification of a few components in complex mixtures with the use of published data on retention parameters found under other conditions (even presented as the drawings of chromatograms).     

Preparation of Titania Monolith Column and Application in Determination of Benzoic Acid by HILIC

The titania monolith column has been synthesized through a template-free sol–gel route, and a simple and reliable method for the determination of benzoic acid by hydrophilic interaction liquid chromatography using the prepared titania monolith has been developed. The influences of acetonitrile, acetate buffer and buffer pH on the retention of benzoic acid were investigated. Benzoic acid in carbonated drinks and fruit beverages samples were determined within 5?min and quantitative analysis was carried out by external standard method with a correlation coefficient (R ²) of 0.9984. The relative standard deviation was 0.91?% and the recovery ranged from 92.5 to 101.3?%. The proposed method is suitable for the analysis of benzoic acid in beverage samples.     

Gas chromatographic retention indices for alkenes on OV-101 and squalane capillary columns

Summary Gas chromatographic retention indices for 47 C₅ to C₈ alkenes on OV-101 dimethylsilicone at 50 and 70 °C were determined within a standard deviation of 0.3i.u. Data obtained on OV-101 are compared with those measured on squalane. The comparison of the retention index and dl/dT values from both columns is presented as linear regression equations with correlation coefficients greater than 0.98.     

Molecular Distance‐Edge Vector (μ) and Chromatographic Retention Index of Alkanes

A new method of quantitative structure‐retention relationship (QSRR) is proposed for estimating and predicting gas chromatographic retention indices of alkanes by using a novel molecular distance‐edge vector, called μ vector, containing 10 elements. The QSRR model (Ml), between the μ vector and chromatographic retention indices of 64 alkanes, was developed by using multiple linear regression (MLR) with the correlation coefficient being R = 0.9992 and the root mean square (RMS) error between the estimated and measured retention indices being RMS = 5.938. In order to explain the equation stability and prediction abilities of the M1 model, it is essential to perform a cross‐validation (CV) procedure. Satisfactory CV results have been obtained by using one external predicted sample every time with the average correlation coefficient being R = 0.9988 and average RMS = 7.128. If 21 compounds, about one third drawn from all 64 alkanes, construct an external prediction set and the 43 remaining construct an internal calibration set, the second QSRR model (M2) can be created by using calibration set data with statistics being R = 0.9993 and RMS = 5.796. The chromatographic retention indices of 21 compounds in the external testing set can be predicted by the M2 model and good prediction results are obtained with R = 0.9988 and RMS = 6.508.