Prediction of Infinite Dilution Molar Conductivity for Unconventional Ions: A Quantitative Structure–Property Relationship Study

The infinite dilution molar conductivity (λ_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 λ_B^∞ of unconventional ions remains to be explored. In this work, new λ_B^∞-QSPR models were developed to predict the λ_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 (R²) 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 λ_B^∞-QSPR model was excellent at predicting λ_B^∞. Moreover, R² 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 λ_B^∞-QSPR model with fewer descriptors could also predict λ_B^∞ satisfactorily. We envisage the established λ_B^∞-QSPR models provide an available method for obtaining λ_B^∞ of ions in aqueous solutions.