MLR Data-Driven for the Prediction of Infinite Dilution Activity Coefficient of Water in Ionic Liquids (ILs) Using QSPR-Based COSMO Descriptors

To predict the partial
molar excess enthalpy, entropy
at infinite
dilution, and phase equilibria, the availability of an infinite dilution
activity coefficient is vital. The “quantitative structure-activity/property
relationship” (QSAR/QSPR) approach has been used for the prediction
of infinite dilution activity coefficient of water in ionic liquids
using an extensive data set. The data set comprised 380 data points
including 68 unique ILs at a wide range of temperatures, which is
more extensive than previously published data sets. Moreover, new
predictive QSAR/QSPR models including novel molecular descriptors,
called “COSMO-RS descriptors”, have been developed.
Using two different techniques of external validation, the data set
was divided to the training set for the development of models and
to the validation set for external validation. Unlike former available
models, internal validation using leave one/multi out-cross validations
(LOO–CV/LMO–CV) and Y-scrambling methods were performed
on the models using statistical parameters for further assessment.
According to the obtained results of statistical parameters (R2 = 0.99 and Q2LOO–CV = 0.99), the predictive capability of the developed
QSPR model was excellent for training set. Regarding the external
validation, other statistical parameters such as AAD = 0.283 and AARD
% = 30 were also satisfactory for the validation set. While the values
of γH2O∞ increase or decrease with increasing
temperature, the QSAR/QSPR models based on the van’t Hoff equation
takes into account the negative and positive effects of temperature
on the γH2O∞ in ILs well, depending on the
nature of ILs. It was also shown that γH2O∞ in
some new ILs which had not been experimentally studied before can
be predicted using the QSPR model.