{
    "identifier": "5D00D811BC74B453E0531A570681BC861875",
    "accessLevel": "public",
    "contactPoint": {
        "hasEmail": "mailto:[email protected]",
        "fn": "Harold Hatch"
    },
    "programCode": [
        "006:045"
    ],
    "landingPage": "https:\/\/pages.nist.gov\/feasst",
    "title": "FEASST: Free Energy and Advanced Sampling Simulation Toolkit",
    "description": "The Free Energy and Advanced Sampling Simulation Toolkit (FEASST) is a free, open-source, modular program to conduct molecular and particle-based simulations with flat-histogram Monte Carlo and molecular dynamics methods. It is a software written in C++ and python which is made publicly available to aid in reproducibility. It is also provided as a service to the scientific community in which there are few , if any, Monte Carlo programs that support flat histogram methods and advanced sampling algorithms. This software is expected to be updated frequently with new methods.",
    "language": [
        "en"
    ],
    "distribution": [
        {
            "accessURL": "https:\/\/github.com\/usnistgov\/feasst",
            "format": "A GitHub repository",
            "description": "A git repository containing the C++ and python source code for the FEASST software. This software can be downloaded from GitHub.",
            "title": "feasst"
        },
        {
            "accessURL": "https:\/\/doi.org\/10.18434\/M3S095"
        }
    ],
    "bureauCode": [
        "006:55"
    ],
    "modified": "2017-11-02",
    "publisher": {
        "@type": "org:Organization",
        "name": "National Institute of Standards and Technology"
    },
    "theme": [
        "Physics: Thermodynamics",
        "Mathematics and Statistics: Numerical methods and software",
        "Materials : Modeling and computational material science",
        "Chemistry: Theoretical chemistry and modeling",
        "Chemistry: Chemical thermodynamics and chemical properties",
        "Manufacturing: Biomanufacturing",
        "Mathematics and Statistics: Modeling and simulation research",
        "Nanotechnology: Nanomaterials",
        "Physics: Biological physics"
    ],
    "keyword": [
        "Monte Carlo",
        "molecular simulation",
        "free energy",
        "flat histogram",
        "C++",
        "python"
    ]
}