ms2: A molecular simulation tool for thermodynamic
properties, release 4.0
Robin Fingerhuta, Gabriela Guevara-Carriona, Isabel Nitzkea, Denis Sarica,
Joshua Marxb, Kai Langenbachb, Sergei Prokopevc, David Celn´yd, Martin
Bernreuthere, Simon Stephanb, Maximilian Kohnsb, Hans Hasseb, Jadran
Vrabeca,∗
aThermodynamics and Process Engineering, Technical University Berlin, 10587 Berlin,
Germany
bLaboratory of Engineering Thermodynamics, University Kaiserslautern, 67653
Kaiserslautern, Germany
cComputational Fluid Dynamics Laboratory, Institute of Continuous Media Mechanics
UB RAS, 614013 Perm, Russia
dNuclear Sciences and Physical Engineering, Czech Technical University in Prague,
11519 Prague, Czech Republic
eHigh Performance Computing Center Stuttgart (HLRS), 70550 Stuttgart, Germany
Abstract
A new version release (4.0) of the molecular simulation tool ms2 (Deublein
et al., 2011; Glass et al., 2014; Rutkai et al., 2017) is presented. Version 4.0
of ms2 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, orien-
tational distribution functions to elucidate mutual configurations of neigh-
boring 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, dielec-
tric constant of non-polarizable fluid models, vapor-liquid equilibria relying
on the second virial coefficient and cluster criteria to identify nucleation.
Keywords: Molecular simulation; Molecular dynamics; Monte Carlo
∗Corresponding author.
E-mail address: vrabec@tu-berlin.de
Preprint submitted to Computer Physics Communications January 25, 2021
Accepted manuscript of: Fingerhut, R., Guevara-Carrion, G., Nitzke, I., Saric, D., Marx, J., Langenbach, K.,
Prokopev, S., Celný, D., Bernreuther, M., Stephan, S., Kohns, M., Hasse, H., & Vrabec, J. (2021). ms2: A
molecular simulation tool for thermodynamic properties, release 4.0. Computer Physics Communications,
262, 107860. https://doi.org/10.1016/j.cpc.2021.107860
© 2021 This manuscript version is made available under the CC-BY-NC-ND 4.0 license
https://creativecommons.org/licenses/by-nc-nd/4.0/
New version programm summary
Program Title: ms2
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 in-
troduced 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 dis-
persive interactions (Mie and Tang-Toennies potential), new properties (Helmholtz
energy, Kirkwood-Buff integrals, thermodynamic factor, thermal diffusion coeffi-
cients, dielectric constant, mean-squared displacement and non-Gaussian param-
eter), 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 esti-
mations, cluster criteria to identify nucleation).
Nature of problem: Calculation of application-oriented thermodynamic proper-
ties: 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 formal-
ism, OPAS method, Smooth-particle mesh Ewald summation
1. Introduction
Significant increases in computing power have led to a broader usage of molec-
ular modeling and simulation, which simultaneously widens the ability to tackle
challenges in physics, chemistry and engineering in a sound and detailed man-
ner. Over the last decades, it has often been shown that these computer-based
methods may predict physical reality very successfully. Thus, the long-standing
2
obstacle of sparse or lacking experimental information on thermophysical data can
be overcome by trustworthy and rapid predictions with massively-parallel high
performance computing (HPC) hardware and scalable codes.
The program ms2 (molecular simulation 2) was developed to compute ther-
mophysical equilibrium properties of pure fluids and mixtures with Monte Carlo
(MC) or molecular dynamics (MD) simulations that are both implemented in a
single source code. Licenses are freely available for all purposes which concern
academic research and teaching under www.ms-2.de together with a substantial
set of molecular force field models [1]. ms2 [2, 3, 4] supports the microcanonical
(NV E), canonical (NV T ), isobaric-isenthalpic (NpH), isobaric-isothermal (NpT )
and grand canonical (µV T) ensembles as well as the simulation of vapor-liquid
equilibria (VLE) with the Grand equilibrium method. Moreover, ms2 facilitates
the sampling of numerous thermodynamic bulk properties, including transport
data, like Maxwell-Stefan (MS) and Fick diffusion coefficients, for molecular mod-
els consisting of Lennard-Jones (LJ) interaction sites, point charges, point dipoles
and point quadrupoles. It allows for the sampling of the chemical potential with
Widom’s particle insertion and thermodynamic integration as well as osmotic pres-
sure, hydrogen bond statistics and other features. Next to these thermophysical
properties, it was focused on an efficient parallelization of ms2 using the message
passing interface (MPI), open multi-processing (OpenMP) and its hybrid form
(MPI+OpenMP).
There is a series of molecular simulation tools, such as CHARMM, DL POLY,
ESPResSo, GIBBS, GROMACS, IMD, LAMMPS, ls1 mardyn, NAMD, TINKER
or Towhee, that is being developed for a range of communities. Both industrial
and academic users are addressed by ms2 with a focus on applications of molecular
modeling and simulation in process and energy engineering. In contrast to most
of the tools listed above, ms2 is limited to rigid force field models which are
appropriate for small molecular species only. However, the implementation of the
internal degrees of freedom into ms2 is underway for some time in an unpublished
version of ms2 [5].
Aiming at high accuracy and short response time, ms2 is characterized by
the large variety of properties that are sampled on the fly. This user-friendly
design was extended by the ability to concurrently sample an arbitrary number
of state points in one program execution. Concurrent sampling was optimized in
the present ms2 version such that communication between ensembles was removed
entirely. Combining this with its dedication to generate large sets of Helmholtz
energy derivative data for the development of equations of state [6], ms2 is very
much suited to be executed on HPC infrastructure.
A more versatile molecular model development was prioritized in this version
release 4.0 such that the traditional LJ 12-6 potential was generalized to the Mie
3
potential and the more complex Tang-Toennies potential [7] was introduced. Con-
sequently, the basis of molecular modeling and simulation may be improved by a
more accurate description of the repulsive and dispersive interactions. Moreover,
ms2 is now able to yield the Fick diffusion coefficient of mixtures constituted by up
to four components due to the concurrent sampling of the MS diffusion coefficient
and Kirkwood-Buff integrals (KBI) [8] that give access to the thermodynamic fac-
tor [9, 10, 11]. Additionally, with this release, more rapid VLE estimations can
be made by carrying out a single NpT ensemble simulation sampling the chemical
potential of the liquid and using the second virial coefficient for the vapor. These
and further new features were implemented in the source code and the toolset
provided at www.ms-2.de. The present work discusses the fourth major release
of ms2 and its most important innovations, which are presented in the following
sections.
2. Mie potential
Addressing repulsive and dispersive interactions in a more versatile way with
ms2, the standard LJ 12-6 potential function was generalized with the Mie po-
tential function [12]. The pairwise interaction between different sites iand jin a
distance rij is modeled by
uij(rij) = n
n−mn
mm/(n−m)·εσ
rij n
−σ
rij m,(1)
where σand εare the Mie size and energy parameters, respectively, and n,mare
the repulsive and dispersive exponents.
In ms2, the interactions between two different Mie sites are described by the
Lorentz-Berthelot combining rules for pure components, while for mixtures the
modified Lorentz-Berthelot rules are applied [2]. The unlike repulsive and disper-
sive exponents are determined according to Lafitte et al. [13] by
kij = 3 + q(ki−3)(kj−3) for k=n, m . (2)
Long-range interactions beyond the cutoff radius rcare considered analytically
with the angle averaging formalism derived for the Mie potential by Lustig [14].
The generalization from LJ 12-6 to Mie was introduced throughout the entire
code so that all properties and functionalities are accessible with it.
3. Tang-Toennies potential
To describe the intermolecular interactions, an additional potential function
based on the work of Tang and Toennies (TT) [7] was introduced into ms2. Con-
4
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