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A new version release (3.0) of the molecular simulation tool ms 2 (Deublein et al., 2011; Glass et al. 2014) is presented. Version 3.0 of ms 2 features two additional ensembles, i.e. microcanonical ( N V E ) and isobaric–isoenthalpic ( N p H ), various Helmholtz energy derivatives in the N V E ensemble, thermodynamic integration as a method for calculating the chemical potential, the osmotic pressure for calculating the activity of solvents, the six Maxwell–Stefan diffusion coefficients of quaternary mixtures, statistics for sampling hydrogen bonds, smooth-particle mesh Ewald summation as well as the ability to carry out molecular dynamics runs for an arbitrary number of state points in a single program execution. New version program summary Program Title: m s 2 Program Files doi: http://dx.doi.org/10.17632/9rcrykvkyh.1 Licensing provisions: CC by NC 3.0 Programming language: Fortran95 Supplementary material: A detailed description of the parameter setup for thermodynamic integration and hydrogen bonding is given in the supplementary material. Furthermore, all molecular force field models developed by our group are provided Journal reference of previous versions: Deublein et al., Comput. Phys. Commun. 182 (2011) 2350 and Glass et al., Comput. Phys. Commun. 185 (2014) 3302 Does the new version supersede the previous version?: Yes Reasons for the new version: Introduction of new features as well as enhancement of computational efficiency Summary of revisions: Two new ensembles ( N V E and N p H ), new properties (Helmholtz energy derivatives, chemical potential via thermodynamic integration, activity coefficients via osmotic pressure, Maxwell–Stefan diffusion coefficients of quaternary mixtures), new functionalities (detection and statistics of hydrogen bonding, smooth-particle mesh Ewald summation, ability to carry out molecular dynamics runs for an arbitrary number of state points in a single program execution). Nature of problem: Calculation of application oriented thermodynamic properties: vapor–liquid equilibria of pure fluids and multi-component mixtures, thermal, caloric and entropic data as well as transport properties and data on microscopic structure Solution method: Molecular dynamics, Monte Carlo, various ensembles, Grand Equilibrium method, Green–Kubo formalism, Lustig formalism, OPAS method, smooth-particle mesh Ewald summation Restrictions: Typical problems addressed by m s 2 are solved by simulating systems containing 1000 to 5000 molecules that are modeled as rigid bodies. Additional comments: Documentation is available at http://www.ms-2.de [ABSTRACT FROM AUTHOR]

A new version release (4.0) of the molecular simulation tool ms 2 (Deublein et al. 2011; Glass et al. 2014; Rutkai et al. 2017) is presented. Version 4.0 of ms 2 features two additional potential functions to address the repulsive and dispersive interactions in a more versatile way, i.e. the Mie potential and the Tang–Toennies potential. This version further introduces Kirkwood–Buff integrals based on radial distribution functions, which allow the sampling of the thermodynamic factor of mixtures with up to four components, orientational distribution functions to elucidate mutual configurations of neighboring molecules, thermal diffusion coefficients of binary mixtures for heat, mass as well as coupled heat and mass transport, Einstein relations to sample transport properties with an alternative to the Green–Kubo formalism, dielectric constant of non-polarizable fluid models, vapor–liquid equilibria relying on the second virial coefficient and cluster criteria to identify nucleation. Program Title: ms 2 Program Files doi: http://dx.doi.org/10.17632/nsfj67wydx.3 Licensing provisions: CC by NC 3.0 Programming language: Fortran95 Supplemental material: A detailed description of the parameter setup for the introduced methods, properties, functionalities etc. is given in the supplemental material. Furthermore, all molecular force field models developed by our group are provided by the MolMod Database: Stephan et al. , Mol. Sim. 45 (2019) 806 Journal reference of previous version: Deublein et al. , Comput. Phys. Commun. 182 (2011) 2350 and Glass et al. , Comput. Phys. Commun. 185 (2014) 3302 and Rutkai et al. , Comput. Phys. Commun. 221 (2017) 343 Does the new version supersede the previous version?: Yes Reasons for the new version: Introduction of new features as well as enhancement of computational efficiency Summary of revisions: Two new potential functions to address repulsive and dispersive interactions (Mie and Tang–Toennies potential), new properties (Helmholtz energy, Kirkwood–Buff integrals, thermodynamic factor, thermal diffusion coefficients, dielectric constant, mean squared displacement and non-Gaussian parameter), new functionalities (Kirkwood–Buff integration with extrapolation to the thermodynamic limit, van der Vegt correction for the radial distribution function, orientational distribution function, Einstein relations, vapor–liquid equilibria estimations, cluster criteria to identify nucleation). Nature of problem: Calculation of application-oriented thermodynamic properties: vapor–liquid equilibria of pure fluids and multi-component mixtures, thermal, caloric and entropic data as well as transport properties and data on microscopic structure Solution method: Molecular dynamics, Monte Carlo, various ensembles, Grand equilibrium method, Green–Kubo formalism, Einstein formalism, Lustig formalism, OPAS method, smooth-particle mesh Ewald summation. [ABSTRACT FROM AUTHOR]