The ADF COSMO-RS (COnductor like Screening MOdel for Realistic Solvents) program is a program that can be used for calculating thermodynamic properties of (mixed) fluids. The COSMO-RS method was developed by Klamt and coworkers [1-3]. On the basis of the framework of COSMO-RS, Lin and Sandler  suggested a variation, the COSMO-SAC (where SAC denotes segment activity coefficient) model. There are different implementations of COSMO-RS and COSMO-SAC or derivatives, and different parametrizations. The implementation of COSMO-RS in ADF is described in Ref. , which is based on the COSMO-RS method developed by Klamt et al. . The implementation of COSMO-SAC 2013-ADF in ADF is based on the COSMO-SAC model developed by Xiong et al. . The implementation of COSMO-SAC 2016-ADF in ADF is based on the COSMO-SAC model developed by Hsieh et al. , but the parameters in COSMO-SAC 2016-ADF were optimized by Chen et al., like in , for use with ADF.
With COSMO-RS it is possible to use a thermodynamically consistent combinatorial contribution to the chemical potential as is used in Ref. , and a temperature dependent hydrogen bond interaction, also described in Ref. . The parameters in the paper  were reparametrized for ADF, see Ref.  for details.
The COSMO-SAC 2013-ADF parameters in Ref.  were optimized for use with ADF COSMO result files. COSMO-SAC 2013-ADF is an improved COSMO-SAC method compatible to ADF and different than previous COSMO-SAC methods. The main difference that the COSMO-SAC 2013 model includes a dispersion contribution in the mixture interaction. The COSMO-SAC 2016-ADF parameters were optimized by Chen et al. for use with ADF, like was done in Ref.  for different QM packages. Previous COSMO-SAC methods are described in Refs. [6,7].
The ADF COSMO-RS (and COSMO-SAC) command line program is called crs. The main authors of this program are Cory Pye (Saint Mary’s University, Halifax NS Canada) and Jaap Louwen (Albemarle Corporation). COSMO-SAC 2013-ADF was implemented in collaboration with R. Xiong and R.I. Burnett (Sandler group, University of Delaware, Newark, USA). Previous COSMO-SAC methods were implemented by Erin McGarrity (TU Delft, the Netherlands). The COSMO-RS GUI ADFcrs contains an input builder for COSMO-RS and can visualize results, see the COSMO-RS GUI tutorials and the COSMO-RS GUI reference manual.
COSMO-RS (and COSMO-SAC) use the intermediate results from quantum mechanical (QM) calculations on individual molecules to predict thermodynamic properties of mixtures of these molecules, for example, solubility. There are a fair number of reports of accurate prediction by COSMO-RS of thermodynamic properties in general in the literature. Many of these have been written by Klamt and co-workers, see Ref.  and references therein.
There are also empirical methods like UNIFAC that can predict thermodynamic properties (including the activity coefficients). These methods contain group specific parameters and are parametrized against a large data base. They will often do better than COSMO-RS or COSMO-SAC methods (especially, of course, if the system of interest was part of the data base used for parameter estimation). However, these methods cannot handle every type of molecule. In particular when unusual combinations of functional groups occur (such as in drug molecules), no parametrization is available. COSMO-RS and COSMO-SAC methods, on the other hand, only feature general parameters not specific to chemical groups or functionalities. All that is required is that a quantum mechanical calculation can be done on the molecule. Therefore, COSMO-RS or COSMO-SAC can be a valuable tool for the prediction of chemical engineering thermodynamical properties, like, for example, partial vapor pressures, solubilities, and partition coefficients. An additional advantage of COSMO-RS and COSMO-SAC over empirical methods is that the molecules dissolved may in fact be transition states of a chemical reaction. This follows from the fact that all that is required is that one can do a QM calculation on the solute and QM on a transition state has become standard in the last two decades. This affords a unique opportunity to predict the thermodynamics of a reaction including, for instance, the balance between kinetically and thermodynamically favored reaction pathways as a function of the solvent used.