离子液体中有机物溶解度的QSPR模型分析

采用偏最小二乘(PLS)分析方法对84个有机物在四种不同的离子液体中的溶解度进行基于VolSurf参数的定量构性关系(QSPR)研究,取得较好的结果.训练集模型对预测集具有良好的预测能力.参数分析表明有机物具有较大体积的亲水区域,对溶解度有利,且有机物与离子液体之间的相互作用能约为-0.84kJ·mol-1.一定的疏水性对溶解度也是有利因素,当离子液体具有小体积的疏水取代基,有机物具有不对称的局部疏水区域对溶解度有利,当离子液体具有大体积或多个疏水取代基,有机物较高的疏水体积对溶解度有利.多元线性回归(MLR)显示亲水参数W1最重要,表明分子的亲水性是影响有机物在离子液体中溶解的关键因素.     

An Efficient and Simple Approach to Predict Kovat's Indexes of Polychlorinated Naphthalenes in Gas Chromatography

Molecular structures of polychlorinated naphthalenes were numerically described with a simple but efficient encoding method. Correspondingly a set of structural parameters were obtained for these compounds and linearly correlated with their gas chromatography retention indexes. A quantitative structure‐retention relationship Model (M1) was developed by using multiple linear regression (MLR) with correlation coefficient R = 0.9880 between the numeric structural codes and the gas chromatography retention indexes of 62 polychlorinated naphthalenes. If the “leave‐one‐out” cross‐validation procedure was employed to construct QSPR model for all samples, the second model M2 with the correlation coefficient being R = 0.9839 was generated. The structural codes of polychlorinated naphthalenes were tested with MLR for estimation and prediction of the GC RI by models M1 and M2, and the results obtained were satisfactory.     

Application of Density Functional Theoretic Descriptors to Quantitative Structure-Activity Relationships with Temperature Constrained Cascade Correlation Network Models of Nitrobenzene Derivatives

IntroductionNitrobenzene derivatives have been used as organ-ic chemical materials and intermediates for many yearsin the chemical industry. Many of those chemicals arereleased into environment and especially into aquaticsystems, and thus have a high pote…