摘要
以16种咪唑类四氟硼酸盐和22种咪唑类六氟磷酸盐为研究对象,采用QSAR(quantitative structure-activity relationship)方法和遗传算法对其熔点与结构的定量构效关系进行了研究,以实现对两类咪唑类离子液体熔点的预测.建立的咪唑类四氟硼酸盐三参数模型相关系数R2为0.89,咪唑类六氟磷酸盐四参数模型相关系数R2为0.85;使用留一法对两模型进行内部验证的相关系数R2分别为0.82和0.77,两预测模型具有真实有效性;使用测试集对两模型进行外部验证,所得两模型的平均预测绝对误差分别为11.43和7.78K,优于文献报道水平,可得出结论,两模型均具有较好的熔点预测能力.
Quantitative structure-activity relationship （QSAR） was used to predict the melting points of two kinds of imidazolium ionic liquids. Using a genetic algorithm a three-parameter model with R2 =0.89 was set up for 16 imidazolium tetrafluoroborates and a four-parameter model with R2 =0.85 was developed for 22 imidazolium hexafluorophosphates. Internal reliability validation was performed using a leave-one-out approach with R^2=0.82 for the model of imidazolium tetrafluoroborates and R^2=0.77 for the model of imidazolium hexafluorophosphates. To validate predictive abilities of models an external validation was performed for test sets where the mean absolute deviation were 11.43 and 7.78 K, respectively. These values are better than the values found in the literature. The proposed models can be used to predict melting points of imidazolium ionic liquids.
出处
《物理化学学报》
SCIE
CAS
CSCD
北大核心
2008年第12期2198-2202,共5页
Acta Physico-Chimica Sinica
基金
江苏省自然科学基金(BK2005121)资助项目
关键词
QSAR
咪唑类离子液体
遗传算法
熔点
QSAR
Imidazolium ionic liquids
Genetic algorithm
Melting point
