Abstract:

Researches on ionic liquids (ILs）are attractive due to ILs’ unique characteristics, while an important drawback in the application of ILs is the scarcity of their thermodynamic data.The number of potential ILs is so enormous, some say as many as 10¹² to 10¹⁸, that it is impossible to determine all these data by experimental methods.Many attempts, including group-contribution and connectivity index have had some success to develop methods to estimate the physical properties of unknown ILs in order to facilitate the design of new modifications and reduce the need for experimental work.A new concept named mass connectivity index to encode bond contributions and to allow quantifying the extent of branching in a molecule, especially in ILs, was proposed in 2010.The preliminary study showed that there was a close but complicated relationship between mass connectivity index and the melting point of ILs, implying that it was hard to predict the melting point only by mass connectivity index without the available information supplied by the other models.In this paper, a new group-contribution model combined with mass connectivity index was proposed for the prediction of the melting point of imidazolium-based ionic liquids, which adopted successful group-contribution parameters and distinguished structure characteristics of ILs by mass connectivity index considering the influence of structure on melting points.It was the first attempt to introduce the concept of mass connectivity index to group-contribution method to estimate melting point. In the model, 23 basic group contribution parameters of ILs and 3 structure characteristic factors were defined except for mass connectivity index and all the constants needed were determined by regression analysis of 62 typical data points obtained from available experimental data in the literatures.The melting points of other 59 ILs not used for determining the parameters of the equation were predicted by the new method and all the 121 data points were collected and compared with both experimental data and those predicted by single group-contribution method to check the predictive capabilities of the model.The average derivation for both correlation and prediction of melting temperature of 121 ILs was 5.15%, R² and RMSD were 0.8686 and 20.75 K respectively.The statistical parameters supported the conclusion that the value of melting points could be estimated with good accuracy by the proposed model.