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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.

Contributors

The Materials Project thank all users for support and feedback. We are thankful to all our contributors who contribute to our software ecosystem. A complete list of contributors is listed here.

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  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 1.5k 871

  2. fireworks fireworks Public

    The Fireworks Workflow Management Repo.

    Python 367 185

  3. custodian custodian Public

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

    Python 143 110

  4. atomate2 atomate2 Public

    atomate2 is a library of computational materials science workflows

    Python 170 99

  5. api api Public

    New API client for the Materials Project

    Python 119 43

Repositories

Showing 10 of 52 repositories
  • api Public

    New API client for the Materials Project

    materialsproject/api’s past year of commit activity
    Python 119 43 21 2 Updated Dec 21, 2024
  • public-docs Public

    The latest documentation for the Materials Project.

    materialsproject/public-docs’s past year of commit activity
    8 17 0 0 Updated Dec 21, 2024
  • emmet Public

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

    materialsproject/emmet’s past year of commit activity
    Python 55 69 46 8 Updated Dec 21, 2024
  • MPContribs Public

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

    materialsproject/MPContribs’s past year of commit activity
    Jupyter Notebook 37 MIT 23 22 4 Updated Dec 21, 2024
  • jobflow Public

    jobflow is a library for writing computational workflows.

    materialsproject/jobflow’s past year of commit activity
    Python 97 25 23 16 Updated Dec 18, 2024
  • maggma Public

    Building blocks for scientific data pipelines

    materialsproject/maggma’s past year of commit activity
    Python 39 32 38 8 Updated Dec 17, 2024
  • pymatgen-analysis-defects Public

    Defect analysis modules for pymatgen

    materialsproject/pymatgen-analysis-defects’s past year of commit activity
    Python 44 10 1 3 Updated Dec 16, 2024
  • dash-mp-components Public

    Plotly Dash components developed by the Materials Project

    materialsproject/dash-mp-components’s past year of commit activity
    Python 25 3 1 6 Updated Dec 16, 2024
  • pymatgen-io-validation Public

    Comprehensive input/output validator. Made with the purpose of ensuring VASP calculations are compatible with Materials Project data, with possible future expansion to cover other DFT codes.

    materialsproject/pymatgen-io-validation’s past year of commit activity
    Python 12 2 0 10 Updated Dec 16, 2024
  • atomate2 Public

    atomate2 is a library of computational materials science workflows

    materialsproject/atomate2’s past year of commit activity
    Python 170 99 43 28 Updated Dec 16, 2024