QSPR方法预测阴离子表面活性剂亲水亲油平衡值

Prediction on Hydrophile-Lipophile Balance Values of Anionic Surfactants with QSPR Method

首次使用量子化学描述符,建立了两种阴离子表面活性剂亲水亲油平衡(HLB)值的定量结构性质关系模型(QSPR).最佳模型1包括四类不同结构的烷基硫酸盐和烷基磺酸盐46种阴离子表面活性剂,复相关系数R2=1.000.又建立了包含聚氧乙烯、乙酸、丙酸和碳氟等特殊类型不同结构的73种阴离子表面活性剂的最佳模型2,复相关系数R2=0.993.

The quantitative structure-property relationship （QSPR） models for the hydrophile-lipophile balance （HLB） value of anionic surfactants were established by using the quantum chemical descriptors for the first time. The best multiple linear regression model 1 included 46 anionic surfactants belonging to four series of alkyl sulfates and alkyl sulfonates, with correlation coefficient （R2） being 1.000. The best multiple linear regression model 2 involved 73 structures including polyoxyethylene, acetate, propionate and fluorinated anionic surfactants, with correlation coefficient （R2） being 0.993.