On the prediction of critical temperatures of ionic liquids: Model development and evaluation

Abstract

In this study, the Guggenheim equation was used to estimate the critical temperature (T c) of 106 ionic liquids using experimental surface tension data as inputs. A group contribution (GC) and a Quantitative Structure−Property Relationship (QSPR) model were also developed to correlate/predict the T c of ionic liquids. It was shown that a lack of sufficiently large database for T c lead to the development of models with low prediction capability. The model's output as well as the T c values estimated from the surface tension data were compared with the critical temperatures calculated by the Valderrama et al. method. The results showed that the Valderrama et al. method produces different data values compared with the values calculated by the Guggenheim equation. Neither the GC, QSPR, nor Valderrama's method is capable of reliable prediction of the T c of ionic liquids. Consequently, the calculated T c values are not reliable enough to be used in the development of corresponding state models for prediction of other thermophysical properties of ionic liquids. Any usage of critical properties of ionic liquids should be done with a serious caution.

Implementation of CP-PC-SAFT and CS-SAFT-VR-Mie for Predicting the Thermodynamic Properties of C1–C3 Halocarbon Systems. II. Inter-Relation between Solubilities in Ionic Liquids, Their Pressure, Volume, and Temperature, and Critical Constants

“…In this respect, it should be emphasized that the predictions of both models may not reflect their possible true values. As indicated by Sattari et al, the current methods cannot evaluate these data in a reliable manner. Table S1 of the Supporting Information shows that the T c and P c values of the considered ILs estimated thus far by various methods exhibit a particularly large divergence.…”

Estimation of the critical properties of compounds using volume‐based thermodynamics

“…In such cases, reliable methods to indirectly deduce the critical constants from experimental data measured at lower temperatures would be quite welcome considering the importance of these properties in a large variety of thermodynamic models. Following this line of thought, it has been suggested that one could take advantage of the fact that the surface tension vanishes at T c , to estimate its value from experimental surface tension data 7,45‐48 …”

“…The prevailing approaches used for the prediction of critical properties are centered around the group contribution (GC) concept, 1,5 although more computationally intensive methods such as the quantitative structure–property relationship (QSPR) methodology, 6‐9 as well as molecular simulations 10 have also been employed for this purpose. Additionally, numerous studies have made use of two macroscopic properties representing molecular energy and molecular size, in contrast to the QSPR methods where molecular descriptors are utilized, to predict the critical properties with particular focus on homologous series of hydrocarbons and hence with limited generalizability 8,11,12 .…”

The New Method for Correlation and Prediction of Thermophysical Properties of Fluids. Critical Temperature

“…Quantitative structure property relationship (QSPR) − was also an effective approach for prediction of T c . It mainly explores quantitative relations between molecular structure and physicochemical properties of compound accurately using statistic and theoretical calculation.…”

“…These models can predict the properties of unknown compound quickly and help to understand theoretically the differences of substances on the basis of molecular structure, providing guidance for high efficiency synthesizing compounds experimentally. Yao, Godavarthy, Sola, and Kazakov proposed their QSPR models to predict critical parameters of pure substances, and Ramjugernath developed a QSPR model to correlate/predict the T c of ionic liquids. These QSPR models all occupied preferable prediction and enough precision.…”