Demystifying the phase diagrams of deep eutectic solvents within an extensive chemical space

Abstract

Abstract Assessing the formation of a deep eutectic solvent (DES) necessitates a solid-liquid equilibrium (SLE) phase diagram. Yet, many studies focusing on DES applications do not include this diagram because of challenges in measurement, leading to misidentified eutectic points. The present study provides a practical approach for estimating the SLE phase diagram of any binary mixture from the structural information, utilizing machine learning and quantum chemical techniques. By pinpointing the eutectic point coordinates within an extensive chemical space, we highlighted the impact of the mole fractions and melting properties on the eutectic temperatures. Our results also showed the potential for misclassifying ideal eutectic mixtures, and even regular solutions, as DESs if one solely observes liquefaction phenomena. Molecular dynamics simulations of selected mixtures at the eutectic points emphasized the pivotal role of hydrogen bonds in dictating mixture behavior. This approach promises to streamline DES design by isolating potential search areas.