共查询到20条相似文献,搜索用时 23 毫秒
1.
2.
3.
4.
5.
6.
Chunlei Wang Michael J. Skibic Richard E. Higgs Ian A. Watson Hai Bui Jibo Wang Jose M. Cintron 《Journal of chromatography. A》2009,1216(25):5030-5038
7.
拓扑-量子指数醛酮气相色谱保留指数及沸点的定量构效关系 总被引:3,自引:0,他引:3
通过对醛酮化合物分子结构特征及其气相色谱保留指数(RI)和沸点与分子结构间关系的研究,提出了分子极化效应指数(MPEI)、奇偶指数(OEI)、立体效应指数(SVij)、顶点度-距离指数(VDI)及键连接矩阵特征根(∑X1CH)等拓扑-量子结构参数,用多元线性回归(MLR)方法获得了醛酮类化合物的沸点及其在不同极性色谱柱上的气相色谱保留指数与这些拓扑-量子指数间良好的定量结构-性质相关(QSPR)模型,相关系数均大于0.99。5个分子结构参数具有明确的物理化学意义且易于计算和运用。与文献研究的比较结果表明:由上述分子结构参数得出的模型方程适用于各类醛酮化合物的气相色谱保留指数及沸点的预测且具有较好的稳定性和准确性。 相似文献
8.
9.
10.
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. 相似文献
11.
12.
13.
14.
15.
16.
17.
18.
19.