کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
155846 456913 2012 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
QSPR with extended topochemical atom (ETA) indices: Modeling of critical micelle concentration of non-ionic surfactants
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی مهندسی شیمی (عمومی)
پیش نمایش صفحه اول مقاله
QSPR with extended topochemical atom (ETA) indices: Modeling of critical micelle concentration of non-ionic surfactants
چکیده انگلیسی

In this present study, we have developed predictive quantitative structure–property relationship (QSPR) models with extended topochemical atom (ETA) indices for critical micelle concentration (logCMC) values of 54 non-ionic surfactants. The ETA descriptors have been developed by the present authors’ group and these can be easily calculated from 2D representation of chemical structure without requirement of conformational analysis and alignment steps. Different chemometric tools such as stepwise multiple linear regression (MLR), genetic function approximation (GFA) and partial least squares (PLS) were employed in this study for development of the models. The final PLS models were found to be well validated internally, externally and also by the overall validation technique. From the results, it is clear that the best ETA model shows reliable prediction of the logCMC values and the statistical quality of the model is comparable with the corresponding non-ETA model. It is also observed that the use of ETA descriptors along with the non-ETA ones improved the statistical quality of the models. Thus, it can be inferred that the ETA indices encode important chemical information regarding not only the topological attributes, but also the effect of electronegativity, molecular volume, branching, shape parameter and nature of atoms and bonds, etc. Hence, the ETA descriptors can be satisfactorily employed for modeling the CMC values of non-ionic surfactants.


► The ETA indices have been used for modeling of logCMC values of 54 non-ionic surfactants.
► The ETA indices can be easily calculated from 2D representation of chemical structure.
► The statistical quality of the best ETA model is comparable with the corresponding non-ETA model.
► The use of ETA descriptors along with the non-ETA ones improves the statistical quality of the models.
► The models can be used for prediction of logCMC values of non-ionic surfactants.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chemical Engineering Science - Volume 73, 7 May 2012, Pages 86–98
نویسندگان
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