Monte Carlo molecular simulations with FEASST version 0.25.1

FEASST is an open-source Monte Carlo software package for particle-based simulations. This software, which was released in 2017, has been used to study phase equilibrium, self-assembly, aggregation or gelation in biological materials, colloids, polymers, ionic liquids, and adsorption in porous networks. We highlight some of the unique features available in FEASST, such as flat-histogram grand canonical ensemble, Gibbs ensemble, and Mayer-sampling simulations with support for anisotropic models and parallelization with flat-histogram and prefetching. We also discuss how the challenges of supporting a variety of Monte Carlo algorithms were overcome by an object-oriented design. This also allows others to extend classes, which improves software interoperability, as inspired by LAMMPS classes and user packages. This article describes version 0.25.1 with benchmarks, compilation instructions, and introductory tutorials for running, restarting, and testing simulations, user guidelines, software design strategies, alternative interfaces, and the test-driven development strategy.

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Publication Details

Journal
The Journal of Chemical Physics
Published
2024-09-05
DOI
https://doi.org/10.1063/5.0224283
Citations
10
Primary Topic
Phase Equilibria and Thermodynamics
Type
article
Field-Weighted Citation Impact
1.84
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article

Monte Carlo molecular simulations with FEASST version 0.25.1

Harold W. Hatch, Daniel W. Siderius, Vincent K. Shen
10 citations
The Journal of Chemical Physics
Phase Equilibria and Thermodynamics
1.84
article

Monte Carlo molecular simulations with FEASST version 0.25.1

Harold W. Hatch, Daniel W. Siderius, Vincent K. Shen
article en
10 citations

Abstract

FEASST is an open-source Monte Carlo software package for particle-based simulations. This software, which was released in 2017, has been used to study phase equilibrium, self-assembly, aggregation or gelation in biological materials, colloids, polymers, ionic liquids, and adsorption in porous networks. We highlight some of the unique features available in FEASST, such as flat-histogram grand canonical ensemble, Gibbs ensemble, and Mayer-sampling simulations with support for anisotropic models and parallelization with flat-histogram and prefetching. We also discuss how the challenges of supporting a variety of Monte Carlo algorithms were overcome by an object-oriented design. This also allows others to extend classes, which improves software interoperability, as inspired by LAMMPS classes and user packages. This article describes version 0.25.1 with benchmarks, compilation instructions, and introductory tutorials for running, restarting, and testing simulations, user guidelines, software design strategies, alternative interfaces, and the test-driven development strategy.

The Journal of Chemical PhysicsVol. 161(9)
National Institute of Standards and Technology (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 15%
Phase Equilibria and Thermodynamics
1.84
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