A model to predict maximum tolerable temperatures of metal-oxide-supported 1-n-butyl-3-methylimidazolium based ionic liquids. (17th February 2015) - Akçay, Aslı; Babucci, Melike; Balci, Volkan; Uzun, Alper
Abstract: The thermal stability limits of metal-oxide-supported ionic liquids (ILs) with 1- n -butyl-3-methylimidazolium cation, [BMIM] +, on most commonly used metal-oxides, SiO2, TiO2, γ-Al2 O3, and MgO are determined. Data show that stability limits of bulk and metal-oxide-supported ILs linearly increase with increasing acidity of C2 proton on imidazolium ring, controlling the inter-ionic interaction strength. Moreover, data also show that the presence of metal-oxide lowers the stability limits considerably. This effect becomes more significant as the surface acidity of the metal-oxide decreases from SiO2 to MgO. This decrease in stability limits with increasing point of zero charge (PZC) of metal-oxide indicates that the interaction between IL and metal-oxide becomes the dominant factor rather than the inter-ionic interactions. Based on these findings a simple mathematical expression was developed as a function of PZC and inter-ionic interaction strength probed by ν(C2H) to predict the stability limits of [BMIM] + -based ILs immobilized on metal-oxides. Performance of the model was tested on several different ILs supported on different metal-oxides, including Fe2 O3 and CeO2 . Results show that the model successfully predicts the maximum operating or tolerable temperatures of supported-[BMIM] + -based ILs with an average relative error less than 4.3%. We suggest that the model developed here can help to choose proper ILs that can tolerate the operating conditions of systems including ILs immobilized on metal-oxides, such as in solid catalysts with ionic liquid layer (SCILL) or in supported ionic liquid phase (SILP) catalysts. Graphical abstract: Highlights: Maximum tolerable temperatures of [BMIM] + -based ILs on metal-oxides were determined Structural factors controlling stability limits are inter-ionic interactions & surface acidity A simple model was developed to predict maximum tolerable temperatures Model predicts maximum tolerable temperatures within 4.3% average-percent error