COSMO-RS: a novel and efficient method for the a priori prediction of thermophysical data of liquids

By A. Klamt, F. Eckert. 2000

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Sigma-Profile Database for Using COSMO-Based Thermodynamic Methods (2006, methodology): “3,5,6,13,32,33 (2) COSMO - SAC and COSMO - RS predictions are sensitive to variations in sigma profiles; therefore, one should use a consistent procedure or algorithm when generating sigma profiles.”
Ion-specific effects influencing the dissolution of tricalcium silicate (2014, methodology): “In particular, all reaction energies were calculated using a recently developed workflow [20] which is based on density functional theory (DFT) combined with the COSMO-RS model [21,22] in order to account for solvation effects.”
Machine Learning for Fast, Quantum Mechanics-Based Approximation of Drug Lipophilicity (2023, positive): “39 For a range of approved drugs, COSMO-RS calculations based on ReSCoSS-generated conformers showed considerable performance improvement over a single-conformer approach.”
Impact of organic molecular structure on the estimation of atmospherically relevant physicochemical parameters (2021, methodology): “…solvation parameters to estimate partitioning between phases, for instance, COSMOtherm (available from Dassault Systèmes, based on COSMO-RS; Klamt, 1995; Klamt and Eckert, 2000) and SPARC (SPARC Performs Automated Reasoning in Chemistry; available from ARChem, LP; based on Hilal et al., 2004).”