کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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1180144 | 1491522 | 2016 | 7 صفحه PDF | دانلود رایگان |
In this study, a new approach based on group-interaction contribution (GIC) is proposed for predicting the thermal decomposition temperature (Td) of ionic liquids (ILs). It was developed using a large database which consisted of 639 experimental data points associated with a wide variety of cations and anions. The whole dataset was split randomly into a training set having 499 data points and a validation set with 140 data points. From average absolute relative deviation (%AARD) and correlation coefficient (R2) values calculated as 4.22% and 0.866 respectively, it was concluded that the model was accurate enough for reliable predictions. More importantly, the new model accounts for isomers distinguishing, which represents an advantage over the conventional group contribution methods reported in the literature.
Journal: Chemometrics and Intelligent Laboratory Systems - Volume 157, 15 October 2016, Pages 189–195