测定了23种酚的臭氧氧化速率，分别采用遗传算法（ GA）结合偏最小二乘法（ PLS）、遗传算法结合人工神经网络（ ANN）建立了酚类物质臭氧氧化速率的定量构效关系（ QSAR）模型．研究表明，臭氧氧化酚的速率可用伪一级反应速率模型描述，苯环上取代基得失电子的能力对酚的氧化速率影响较大．基于GA?PLS算法建立的QSAR模型为lgk＝3．439－0．206lgP（辛醇?水分配系数对数值）＋0．122×pKa（解离常数）＋0．3464χpc （四阶路径／簇分子连接性指数）－0．0236qC－（碳原子所带最大负电荷）．基于GA?ANN算法建立的QSAR模型含有参数lgP、4χpc、pKa 和α（平均分子极化率）．留一法交叉验证结果表明，基于GA?ANN算法建立的模型比基于GA?PLS算法建立的模型具有更好的稳健性．QSAR研究表明，酚的臭氧氧化速率与电子云分布以及苯环上取代基的性质密切相关，另外，水的溶剂化作用对酚的氧化速率也有显著影响．
Ozonation rates of twenty?three phenols were measured. Their Quantitative Structure Activity Relationship ( QSAR ) models were developed by the method of genetic algorithm ( GA ) combining with Partial Least Squares (PLS) and Artificial Neural Networks (ANN), respectively. The degradation rate of phenols can be described by the pseudo?first?order reaction rate model. The capacity of releasing or taking electron of the substitution group in the ring has obvious effect on the ozonation rate of the phenols. The QSAR model developed by GA?PLS is lgk=3.439-0.206lgP ( the logarithm of octanol?water partition coefficients)+0.122×pKa(dissociation constant)-0.3464χpc(four order path/cluster molecular connectivity index )-0. 0236qC-( the maximum negative charge of carbon atom). The QSAR model developed by GA?ANN model has the descriptors of lgP,4χpc, pKa and α ( molecular average polarizability) . Based on leave?one?out cross validation, the QSAR model constructed by GA?ANN has better robustness than that by GA?PLS. The study of QSAR shows that the ozonation rate of phenols has a close relationship with electron cloud distribution and the properties of substitution groups in benzene ring. It also shows that the solvent effect of water obviously influences the ozonation rate of phenols.
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