摘要
利用AM1法全优化计算了一系列硅烷类化合物,并将获得的8种量化参数与其在阿皮松M上的气相(GC)Kovats指数进行多元线性回归(MLR),成功建立了QSRR模型,该模型的预测值与实验值基本吻合.
A quantitative structure retention relationship （QSRR） model has been developed for the chromatographic （GC） Kovsts indices of silane derivatives on Apiezon M stationary phase. AM1 method was employed to calculate a set of molecular descriptors of silane derivatives. Using multi ple linear regression （MLR）, we obtained the empirical functions with high correlation coefficient between Kovkts indices and quantum-chemical descriptor. The results indicated that the QSRR models proposed were satisfactory.
出处
《华中师范大学学报（自然科学版）》
CAS
CSCD
北大核心
2010年第3期448-454,共7页
Journal of Central China Normal University：Natural Sciences
基金
the National Natural Science Foundation of China(20405011)
Science Foundation of Jiangsu Province Education Department of China(04KJD1 50038)
Chemical Materials and Engineering Laboratory Center of Anhui Province,The Natural Science Foundation of Anhui Province Education Department (KJ2010A246)
the Natural Science Foundation of Chizhou College(XK0901)
关键词
定量结构-保留关系
多元线性回归
硅烷衍生物
人工神经网络
quantitative structure-retention relationship
multiple linear regression
silane deriva- tives
artificial neural networks
