New models for correlating and predicting the solubility of some compounds in supercritical CO₂

详细信息    查看全文

• 作者：Wei Wang ; Xia Gui ; Zhi Yun ; ^{zyun99@hotmail.com" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Molecular connectivity indices ; CO2 ; Solubility ; Correlation ; Prediction
• 刊名：Fluid Phase Equilibria
• 出版年：2016
• 出版时间：25 December 2016
• 年：2016
• 卷：430
• 期：Complete
• 页码：135-142
• 全文大小：536 K

文摘

Two new semi-empirical models were proposed to calculate and predict the solubility data of some compounds in supercritical carbon dioxide (SCCO₂). The new model I was constructed based on the models of Chrastil. Its ability of calculating solubility data was evaluated and compared with the models of Chrastil, Adachi-Lu and de Valle using solubility data of 40 compounds collected from literature published in recent years, and results showed that the new model I is better than other models. However, the new model I as well as other models mentioned above can only be fitted for each solute without the ability of prediction for the unknown solubility data. Meanwhile, the molecular connectivity indices (MCIs) have been widely used as the structure descriptors encoding a large amount of structure information on an entire molecule. Therefore, the new model II was developed by combining the modified MCIs with the new model I to calculate the solubility data of fatty acids, fatty alcohols, fatty acid esters and aromatic compounds in SCCO₂. The relation between the solutes' solubility data and their molecular structures was developed by a one-off correlation of experimental data and then the inductive relation was used in the new model II to predict the solubility data of homogeneous solutes successfully.