文献类型：期刊文献

英文题名：Prediction of Infinite Dilution Molar Conductivity for Unconventional Ions: A Quantitative Structure-Property Relationship Study

作者：Song, Fan[1];Xiao, Yongjun[1];An, Shuhao[1];Wan, Ren[1];Xu, Yingjie[2];Peng, Changjun[1];Liu, Honglai[1]

机构：[1]East China Univ Sci & Technol, Sch Chem & Mol Engn, Shanghai 200237, Peoples R China;[2]Shaoxing Univ, Dept Chem, Shaoxing 312000, Peoples R China

年份：2021

卷号：60

期号：40

起止页码：14625

外文期刊名：INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

收录：SCI-EXPANDED(收录号：WOS:000709571900020)、、EI(收录号：20214211034848)、Scopus(收录号：2-s2.0-85117099995)、WOS

基金：This research was financially sponsored by the National Natural Science Foundation of China (Grant Nos. 22078086, 21776069, and 21978172).

语种：英文

外文关键词：Ionic liquids - Linear regression - Positive ions

外文摘要：The infinite dilution molar conductivity (lambda(infinity)(B)) that represents the interactions between ions and solvent molecules is an important transfer property for the utilization of ionic liquids (ILs) in electrochemical applications. However, employing the quantitative structure-property relationship (QSPR) model to predict the lambda(infinity)(B) of unconventional ions remains to be explored. In this work, new lambda(infinity)(B)-QSPR models were developed to predict the lambda(infinity)(B) of ions in aqueous solutions by using multiple linear regression (MLR) and stepwise linear regression (SLR) methods based on the molecular descriptors obtained by COSMO-SAC. A total of 132 cations and 158 anions data points at different temperatures were collected and tested. The results showed that the determination coefficients (R-2) of the QSPR model using MLR for cations and anions were 0.9515 and 0.9411, and the average absolute relative deviations (AARD) were 6.79% and 10.42%, respectively, indicating that the proposed lambda(infinity)(B)-QSPR model was excellent at predicting lambda(infinity)(B). Moreover, R-2 of the QSPR model using SLR for cations and anions were 0.9450 and 0.9406, and AARD were 7.10% and 10.19%, respectively, implying that the lambda(infinity)(B)-QSPR model with fewer descriptors could also predict lambda(infinity)(B) satisfactorily. We envisage the established lambda(infinity)(B)-QSPR models provide an available method for obtaining lambda(infinity)(B) of ions in aqueous solutions.