Development of a Methodology for Predicting Thermophysical and Physicochemical Properties of a Novel Deep Eutectic Solvent (DES)

Abstract

This work proposes methodologies for estimating thermophysical and physicochemical properties of a new DES, specifically, L-arginine/glycerol (1:6). Due to the lack of experimental data available in the literature for this system, critical and scalar properties were predicted using group contribution methods and Lee–Kesler mixing rules. Temperature-dependent properties were estimated using correlations developed for DES from the literature and adjusted to models compatible with the simulator, including IK-CAPE polynomials for heat capacity and molar volume of the liquid (density), Andrade's equation for viscosity, and DIPPR correlation for surface tension. The methodology was indirectly validated by applying the same procedure to the Choline Chloride/Urea DES (1:2), obtaining acceptable deviations from experimental data. The results allow for an initial thermodynamic modeling of the solvent and enable preliminary simulations of deep eutectic solvents in CO₂ capture processes, highlighting the need for future experimental measurements to refine the estimates.