QSPR Study on the Melting Points of a Diverse Set of Potential Ionic Liquids by Projection Pursuit Regression

Abstract

A Quantitative Structure -Property Relationship (QSPR) study was carried out to model the melting points for a diverse set of 288 potential Ionic Liquids (ILs) including pyridinium bromides, imidazolium bromides, benzimidazolium bromides, and 1-substituted 4-amino-1,2,4-triazolium bromides. Based on the calculated descriptors by CODESSA program, a Principal Component Analysis (PCA) was performed on the whole data to detect the homogeneities in the dataset and to assist the separation of the data into representative training and test sets. Heuristic Method (HM) and Projection Pursuit Regression (PPR) were used to develop linear and nonlinear models between the descriptors and the melting points. The PPR model gave a high predictive correlation coefficient (R 2 ) of 0.810 and an Average of Absolute Relative Deviation (AARD) of 17.75%, which are better than those by HM model (R 2 ¼ 0.712, AARD ¼ 24.33%) indicating that PPR is better for the prediction of the melting points. In addition, the descriptors selected by HM can give some insight into factors that can affect the melting points, i.e., benzene ring structure, rotatable bonds, branching, symmetry, and intramolecular electronic effects. This information would be very useful in the design of the potential ILs with desired melting points.

Thermal Behaviour of Pure Ionic Liquids

“…According to the authors, the most significant descriptors were, the indices reflecting the coordination ability of the cation, the average nucleophilic reactivity index for the N atom related to electrostatic intermolecular interactions and the total entropy per atom related to the difference in conformational and rotational degrees of freedom in solid and liquid phases. Many other models [22][23][24][25][26][27][28][29] have been developed for several families of ILs (Table 2), most of them for imidazoliumbased ILs with the same anion; consequently, their range of application is quite limited.…”

Predictive methods for the estimation of thermophysical properties of ionic liquids

“…Another correlation for various families of bromide ILs (including pyridinium, imidazolium, benzimidazolium, and 1-substituted 4-amino-1,2,4-triazolium) was proposed by Ren et al 172 Using the CODESSA descriptors and a PCA analysis, the best correlation reported (an eight-descriptor non linear model) has R 2 = 0.804 and an AARD (%) of 18. 39 174 Here the authors used multiple approaches to perform QSPR modelling of the melting point of a structurally diverse data set of 717 bromides of nitrogencontaining organic cations.…”

Use of advanced statistical learning methods and principal component analysis in quantitative structure–genotoxicity relationship study of amines

“…Amongst them, Duplex seems to be the best way to select representative training and test sets in a validation context and its principle as well as the treating procedure are described in literature 34 . In addition to above approaches, PCA was another very useful method proved by our previous works to assist the data splitting 35,36 . Design of the training set is performed with respect to the PCs by selecting a subset of substances that are most efficient in spanning the substance (or PCA model) space.…”