Predictive methods for the estimation of thermophysical properties of ionic liquids

Abstract

While the design of products and processes involving ionic liquids (ILs) requires knowledge of the thermophysical properties for these compounds, the massive number of possible distinct ILs precludes their detailed experimental characterization. To overcome this limitation, chemists and engineers must rely on predictive models that are able to generate reliable values for these properties, from the knowledge of the structure of the IL. A large body of literature was developed in the last decade for this purpose, aiming at developing predictive models for thermophysical and transport properties of ILs. A critical review of those models is reported here. The modelling approaches are discussed and suggestions relative to the current best methodologies for the prediction of each property are presented. Since most of the these works date from the last 5 years, this field can still be considered to be in its infancy. Consequently, this work also aims at highlighting major gaps in both existing data and modelling approaches, identifying unbeaten tracks and promising paths for further development in this area.

Development of predictive QSAR models for Vibrio fischeri toxicity of ionic liquids and their true external and experimental validation tests

“…To explore the "tuneability" and "designability" features of ILs, predictive QSPR models have to be developed to relate the properties to the chemical structure or other physicochemical properties. 4,9 Such models should also be rigorously validated in order to prove their predictive capacity and applicability to a new set of ILs. Although ILs were originally promoted as green solvents, studies have also shown that ionic liquids, as any organic solvent, may have some degree of toxicity to the various organisms of the ecosystem.…”

“…Therefore, it is necessary to develop mathematical models to predict the various property endpoints of ILs. Quantitative structure-property/activity relationship (QSPR/QSAR) methods [7][8][9] would help to develop quantitative models capable of predicting the properties directly from molecular structure information.…”

Compatibility of Ionic Liquids with Enzymes

“…However, this approach is mainly based on the experimental trial-error means. More recently, many methods including ab initio calculation, molecular simulation, quantum chemistry, and correlation have been successfully applied to calculate and/or predict the physical properties of ionic liquids [123,124]. Not only physical, but also chemical and biological properties of ionic liquids can be predicted by these methods.…”

Método de Contribución de Grupos: una Herramienta Fundamental en cursos Avanzados de Termodinámica y Física de Fluidos para la Estimación de Propiedades de Sustancias

“…Sin embargo, los resultados son similares a los obtenidos con el MCG de Joback-Reid. Esto porque si bien la estructura tiene relevancia en el valor de una determinada propiedad, esta no es la única característica que determina el valor por ejemplo de la temperatura de fusión; y menos en los casos de líquidos iónicos (Coutinho et al, 2012 Tetradecyl-tripentyl-ammoniumbromide 9.0…”