Effect of alkyl chain length in cation on thermophysical properties of two homologous series: 1-alkyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imides and 1-alkyl-3-methylimidazolium trifluoromethanesulfonates

Insights into modeling refractive index of ionic liquids using chemical structure-based machine learning methods

Ionic liquids (ILs) have drawn much attention due to their extensive applications and environment-friendly nature. Refractive index prediction is valuable for ILs quality control and property characterization. This paper aims to predict refractive indices of pure ILs and identify factors influencing refractive index changes. Six chemical structure-based machine learning models called eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), Categorical Boosting (CatBoost), Convolutional Neural Network (CNN), Adaptive Boosting-Decision Tree (Ada-DT), and Adaptive Boosting-Support Vector Machine (Ada-SVM) were developed to achieve this goal. An enormous dataset containing 6098 data points of 483 different ILs was exploited to train the machine learning models. Each data point's chemical substructures, temperature, and wavelength were considered for the models' inputs. Including wavelength as input is unprecedented among predictions done by machine learning methods. The results show that the best model was CatBoost, followed by XGBoost, LightGBM, Ada-DT, CNN, and Ada-SVM. The R² and average absolute percent relative error (AAPRE) of the best model were 0.9973 and 0.0545, respectively. Comparing this study's models with the literature shows two advantages regarding the dataset's abundance and prediction accuracy. This study also reveals that the presence of the -F substructure in an ionic liquid has the most influence on its refractive index among all inputs. It was also found that the refractive index of imidazolium-based ILs increases with increasing alkyl chain length. In conclusion, chemical structure-based machine learning methods provide promising insights into predicting the refractive index of ILs in terms of accuracy and comprehensiveness.

Thorough studies of tricyanomethanide-based ionic liquids - the influence of alkyl chain length of the cation

The glassy, supercooled, and normal liquid states of the 1-alkyl-3-methylimidazolium tricyanomethanide series [CnC1im][TCM] (n = 2, 4, 6, 8, and 16) were investigated by dielectric and mechanical (rheological) experiments supplemented by X-ray diffraction. The conductivity relaxation was found to be accompanied by a pronounced secondary relaxation. However, based on ambient and high-pressure results as well as the coupling model, we assumed that the latter one can not be classified as Johari-Goldstein relaxation. Moreover, the studies on the nanoscale organization of ionic liquids indicated that 1-alkyl-3-methylimidazolium tricyanomethanide ILs begin to form nanoscale aggregates when the alkyl chain of the cation has six carbon atoms.