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@materialsproject

Materials Project

The Materials Project is a multi-institution, multi-national effort to compute the properties of all inorganic materials and provide the data and associated analysis algorithms for every materials researcher free of charge. The ultimate goal of the initiative is to drastically reduce the time needed to invent new materials by focusing costly and time-consuming experiments on compounds that show the most promise computationally.

Software

By computing properties of all known materials, the Materials Project aims to remove guesswork from materials design in a variety of applications. Experimental research can be targeted to the most promising compounds from computational data sets. Researchers will be able to data-mine scientific trends in materials properties. By providing materials researchers with the information they need to design better, the Materials Project aims to accelerate innovation in materials research.

Supercomputing

Supercomputing clusters at national laboratories provide the infrastructure that enables our computations, data, and algorithms to run at unparalleled speed. We principally use the Lawrence Berkeley National Laboratory's NERSC Scientific Computing Center and Computational Research Division, but we are also active with Oak Ridge's OLCF Argonne's ALCF and San Diego's SDSC

Screening

Computational materials science is now powerful enough that it can predict many properties of materials before those materials are ever synthesized in the lab. By scaling materials computations over supercomputing clusters, we have predicted several new battery materials which were made and tested in the lab. Recently, we have also identified new transparent conducting oxides and thermoelectric materials using this approach.

Pinned

  1. pymatgen pymatgen Public

    Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials …

    Python 1.2k 775

  2. fireworks fireworks Public

    The Fireworks Workflow Management Repo.

    Python 298 171

  3. custodian custodian Public

    A simple, robust and flexible just-in-time job management framework in Python.

    Python 117 98

  4. atomate2 atomate2 Public

    atomate2 is a library of computational materials science workflows

    Python 101 52

  5. api api Public

    New API client for the Materials Project

    Python 82 31

Repositories

Showing 10 of 51 repositories
  • pymatgen Public

    Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.

    Python 1,191 775 95 30 Updated Dec 1, 2023
  • pymatgen-io-validation Public

    Comprehensive input/output validator. Made with the initial purpose of ensuring VASP calculations in the MP Database are compatible, with possible future expansion to cover other codes.

    Python 6 0 0 2 Updated Dec 1, 2023
  • MPContribs Public

    Platform for materials scientists to contribute and disseminate their materials data through Materials Project

    Python 32 MIT 21 20 5 Updated Nov 29, 2023
  • atomate2 Public

    atomate2 is a library of computational materials science workflows

    Python 101 52 31 17 Updated Nov 29, 2023
  • maggma Public

    MongoDB aggregation machine

    Python 31 30 35 6 Updated Nov 29, 2023
  • emmet Public

    Be a master builder of databases of material properties. Avoid the Kragle.

    Python 40 57 42 10 Updated Nov 28, 2023
  • jobflow Public

    jobflow is a library for writing computational workflows.

    Python 58 17 13 6 Updated Nov 28, 2023
  • pyrho Public
    Python 29 6 1 1 Updated Nov 28, 2023
  • api Public

    New API client for the Materials Project

    Python 82 31 53 16 Updated Nov 27, 2023
  • pymatgen-analysis-defects Public

    Defect analysis modules for pymatgen

    Python 25 9 2 4 Updated Nov 27, 2023