Fast and Accurate Prediction of Solid–Liquid Equilibria in Type V Eutectic Systems Using openCOSMO-RS

View at publisher
Authors: Abdelkadr S. Ahmed, Simon Müller, Silvia Fraterrigo Garofalo, Tonia Tommasi, Irina Smirnova
Cited by: 1
References: 44

Abstract

Deep eutectic systems (DESs) have attracted growing interest as tunable and environmentally benign alternatives to conventional solvents. However, their practical deployment depends on accurate knowledge of solid–liquid equilibrium (SLE) phase diagrams, the experimental determination of which is time-consuming and resource-intensive. Consequently, reliable and efficient predictive methods for SLE are essential for large-scale DES screening and design. In this work, the performance of the open-source implementation openCOSMO-RS 24a for predicting SLE in type V eutectic systems is evaluated and benchmarked against the commercial COSMO-RS implementation COSMOtherm. A comprehensive data set comprising 157 type V eutectic systems and nearly 2000 experimental data points was compiled from the literature. Several COSMOtherm configurations were examined, including different software versions, levels of theory, and conformer treatments. Model performance was assessed using average absolute deviations (AAD) and average relative deviations (ARD) of melting temperatures. COSMOtherm 25 with multiple conformers yielded the highest accuracy, while openCOSMO-RS 24a achieved comparable predictive performance with only a modest increase in AAD (≈1 K). Notably, openCOSMO-RS performs the calculations several orders of magnitude faster than COSMOtherm. These results demonstrate that openCOSMO-RS offers an attractive balance between accuracy and computational efficiency, making it a powerful tool for high-throughput SLE screening in deep eutectic system design.

Fields of Study & Subjects

Phase Equilibria and Thermodynamics Process Optimization and Integration Chemical and Physical Properties in Aqueous Solutions

Publication details

Journal / source
Journal of Chemical & Engineering Data
Publisher
American Chemical Society (ACS)
Volume
71
Issue
6
Pages
2415–2424
Publication date
6 May 2026
Language
EN