Ahmed, Abdelkadr S.Abdelkadr S.AhmedMüller, SimonSimonMüllerTommasi, ToniaToniaTommasiFraterrigo Garofalo, SilviaSilviaFraterrigo GarofaloSmirnova, IrinaIrinaSmirnova2026-06-232026-06-232026-05-06Journal of Chemical and Engineering Data 71 (6): 2415-2424 (2026)https://hdl.handle.net/11420/63597Deep 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.en1520-51342026624152424American Chemical Society (ACS)Natural Sciences and Mathematics::541: Physical; Theoretical::541.3: Physical ChemistryTechnology::660: Chemistry; Chemical EngineeringTechnology::660: Chemistry; Chemical Engineering::660.6: BiotechnologyReview Article10.1021/acs.jced.5c00865