Determination and Estimation of Some Important Properties of Ammonium and Phosphonium Salt-Based Deep Eutectic Solvents

Abstract

Due to similar properties, Deep Eutectic Solvents (DESs) are analogous to ionic liquids (ILs). Due to the simple preparation steps and environmentally benign nature, DESs have gained much attention from researchers. The promising applications of DESs at an industrial scale include a variety of fields like extraction and separation, nanotechnology, bio-catalysis, reaction media, membrane technology, lubricants, metal processing, electrochemistry, and other applications. One of the reasons hindering the use of DESs for large industrial-scale applications is the scarce thermophysical properties database. In this regard, 45 DESs were synthesized based on varying molar ratios of hydrogen bond acceptors (choline chloride, methyl triphenylphosphonium bromide, and tetra-n-butyl ammonium bromide) and hydrogen bond donors (glycerol, ethylene glycol, and diethylene glycol). The thermophysical properties are essential for process design and extending the laboratory scale applications of DESs to large scale. The thermophysical properties like density, viscosity, conductivity, and surface tension were experimentally determined for a wide range of temperatures. The heat capacity database of 17-DESs as a function of temperature was collected from open literature. The main objective of the work was an experimental measurement and study of some fundamental thermophysical properties (density, viscosity, conductivity, heat capacity, and surface tension) of DESs. Also, to establish the correlation between the basic input parameters and these thermophysical properties by regressing the experimental data. Since the decade, the prediction of vital thermophysical properties has been aroused due to the urgent requirement to reduce the cost and time to experimental determination for DESs. Various empirical models were classified and studied over DESs based on the input requirements. The models were categorized as component-specific regression coefficient-based and molecular structure-based models. The molecular structure-based models were further classified as group contribution, critical properties, and mass connectivity index. The input parameters like average molecular weight, critical properties, acentric factor, and mass connectivity index were calculated. The empirical models were modified, employed, evaluated, and recommended based on prediction/estimation capabilities. Density, surface tension, and heat capacity showed linear drop in behavior with increasing temperature whereas, viscosity and conductivity showed an exponential trend with increasing temperature. The calculated errors were higher in predicting exponential behavior of viscosity and conductivities than density, surface tension, and heat capacities. The recommended generalized models were trained using 75% overall data points, and the 25% data points were used for testing purposes. The schematic view of the approach of the present work is shown in the graphical abstract. Keywords: DES, thermophysical properties, empirical models