<i>ls1 mardyn</i>: The Massively Parallel Molecular Dynamics Code for Large Systems

Niethammer, Christoph; Becker, Stefan; Bernreuther, Martin; Buchholz, Martin; Eckhardt, Wolfgang; Heinecke, Alexander; Werth, Stephan; Bungartz, Hans‐Joachim; Glass, Colin W.; Hasse, Hans; Vrabec, Jadran; Horsch, Martin

doi:10.1021/ct500169q

Cited by 121 publications

(80 citation statements)

References 76 publications

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“…The simulations were performed with an extended version of the molecular dy-namics code ls1 mardyn [68,69] in the canonical ensemble with N = 16,000 particles. Further simulation details are given in the Appendix.…”

Section: Simulations With the Mie Potentialmentioning

confidence: 99%

Simultaneous description of bulk and interfacial properties of fluids by the Mie potential

et al. 2016

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The vapor-liquid equilibrium (VLE) of the Mie potential, where the dispersive exponent is constant (m = 6) while the repulsive exponent n is varied between 9 and 48, is systematically investigated by molecular simulation. For systems with planar vapor-liquid interfaces, long-range correction expressions are derived, so that interfacial and bulk properties can be computed accurately. The present simulation results are found to be consistent with the available body of literature on the Mie fluid which is substantially extended. On the basis of correlations for the considered thermodynamic properties, a multicriteria optimization becomes viable. Thereby, users can adjust the three parameters of the Mie potential to the properties of real fluids, weighting different thermodynamic properties according to their importance for a particular application scenario. In the present work, this is demonstrated for carbon dioxide for which different competing objective functions are studied which describe the accuracy of the model for representing the saturated liquid density, the vapor pressure and the surface tension. It is shown that models can be found which describe simultaneously the saturated liquid density and vapor pressure with good accuracy, and it is discussed to what extent this accuracy can be upheld as the model accuracy for the surface tension is further improved.

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Section: Simulations With the Mie Potentialmentioning

confidence: 99%

Simultaneous description of bulk and interfacial properties of fluids by the Mie potential

et al. 2016

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“…It was ensured that the width of the thermostating region at the end of data acquisition was still broad enough (>20). The ls1 mardyn code 38 was used for sampling, which is well suited for massively parallel computation. After an equilibration of 10 6 time steps ∆tσ −1 √ ϵ/m = 0.001 82 at a temperature of T = 0.8, a liquid slab was formed in the center of the simulation volume that was surrounded by vapor.…”

Section: Molecular Model and Simulation Methodsmentioning

confidence: 99%

Communication: Evaporation: Influence of heat transport in the liquid on the interface temperature and the particle flux

Heinen

Vrabec

Fischer³

2016

The Journal of Chemical Physics

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Molecular dynamics simulations are reported for the evaporation of a liquid into vacuum, where a Lennard-Jones type fluid with truncated and shifted potential at 2.5σ is considered. Vacuum is enforced locally by particle deletion and the liquid is thermostated in its bulk so that heat flows to the planar interface driving stationary evaporation. The length of the non-thermostated transition region between the bulk liquid and the interface Ln is under study. First, it is found for the reduced bulk liquid temperature Tl/Tc = 0.74 (Tc is the critical temperature) that by increasing Ln from 5.2σ to 208σ the interface temperature Ti drops by 17% and the evaporation flux decreases by a factor of 4.4. From a series of simulations for increasing values of Ln, an asymptotic value Ti∞ of the interface temperature for Ln → ∞ can be estimated which is 21% lower than the bulk liquid temperature Tl. Second, it is found that the evaporation flux is solely determined by the interface temperature Ti, independent on Tl or Ln. Combining these two findings, the evaporation coefficient α of a liquid thermostated on a macroscopic scale is estimated to be α ≈ 0.14 for Tl/Tc = 0.74.

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“…Choosing the "right" potential functions, this results in much lower computational cost while sufficient accuracy is maintained. In ls1 mardyn, the following effective pair potentials are used [6]:…”

Section: Rigid-body Molecular Dynamicsmentioning

confidence: 99%

“…Tackling the field of process engineering, the simulation code ls1 mardyn [6,36] The development has been inspired by ms2 [37], a mature Fortran code for the molecular simulation of thermodynamic properties. Supporting both classical MD and MC simulation with rich functionality, ms2 focuses on small molecular systems, so the investigation of nucleation or flow processes is hardly possible.…”

Section: Simulation Code Mardynmentioning

confidence: 99%

Molecular Dynamics Simulation

Heinecke¹,

Eckhardt

Horsch

et al. 2015

Supercomputing for Molecular Dynamics Simulations

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This section provides a compact description of the basics of MD simulation. It only covers topics that are required to understand MD simulation in process engineering, i.e. in particular molecular modeling, the computation of potentials and forces, as well as the efficient identification of neighboring molecules. Here focus is put on single-and multi-center interactions based on the Lennard-Jones potential for short-range interactions. These detailed descriptions help to elaborate the differences between MD in process engineering and other fields and motivate the development of a specialized code. Such a code is ls1 mardyn, whose optimizations are discussed in the up-coming chapters. At the end of the section we provide the general layout of the software.Keywords Molecular dynamics simulation · Molecular interactions · Short-range interactions · Linked-cells algorithm · Lennard-Jones potential · Single-center interactions · Multi-center interactions · ls1 mardynIn this section, we give a compact description of the basics of MD simulation and cover only topics required to understand MD simulation in process engineering, i.e., in particular molecular modeling the computation of potentials and forces, as well as the efficient identification of neighboring molecules. This description helps to elaborate the differences between MD in process engineering and other fields, thereby focusing on algorithms, and motivates the development of a specialized code. Such a code is ls1 mardyn which is described at the end of this section. Molecular Models and PotentialsThe development of molecular models is a nontrivial task. Models have to capture the typical behavior of fluids and the geometric shape of a molecule to allow for meaningful simulations. At the same time, models should be as simple as possible to be computationally efficient. In this section, we discuss the design space for molecular models, especially from the point of view of algorithms and implementation. After

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ls1 mardyn: The Massively Parallel Molecular Dynamics Code for Large Systems

Cited by 121 publications

References 76 publications

Simultaneous description of bulk and interfacial properties of fluids by the Mie potential

Simultaneous description of bulk and interfacial properties of fluids by the Mie potential

Communication: Evaporation: Influence of heat transport in the liquid on the interface temperature and the particle flux

Molecular Dynamics Simulation

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