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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.

Pinned Loading

  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 1.6k 876

  2. fireworks fireworks Public

    The Fireworks Workflow Management Repo.

    Python 372 187

  3. custodian custodian Public

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

    Python 147 111

  4. atomate2 atomate2 Public

    atomate2 is a library of computational materials science workflows

    Python 184 103

  5. api api Public

    New API client for the Materials Project

    Python 127 45

Repositories

Showing 10 of 52 repositories
  • reaction-network Public

    Reaction Network is a Python package for predicting likely inorganic chemical reaction pathways using graph theoretical methods. Project led by @mattmcdermott (formerly at Berkeley Lab).

    materialsproject/reaction-network’s past year of commit activity
    Python 97 19 3 0 Updated Feb 4, 2025
  • jobflow Public

    jobflow is a library for writing computational workflows.

    materialsproject/jobflow’s past year of commit activity
    Python 99 27 23 16 Updated Feb 3, 2025
  • custodian Public

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

    materialsproject/custodian’s past year of commit activity
    Python 147 MIT 111 20 5 Updated Feb 3, 2025
  • pymatgen-analysis-defects Public

    Defect analysis modules for pymatgen

    materialsproject/pymatgen-analysis-defects’s past year of commit activity
    Python 45 11 1 1 Updated Feb 3, 2025
  • pymatgen-db Public

    Pymatgen-db provides an addon to the Python Materials Genomics (pymatgen) library (https://pypi.python.org/pypi/pymatgen) that allows the creation of Materials Project-style databases for management of materials data.

    materialsproject/pymatgen-db’s past year of commit activity
    Python 49 MIT 39 2 3 Updated Feb 3, 2025
  • 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.

    materialsproject/pymatgen’s past year of commit activity
    Python 1,562 876 190 (2 issues need help) 41 Updated Feb 3, 2025
  • emmet Public

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

    materialsproject/emmet’s past year of commit activity
    Python 56 69 45 14 Updated Feb 3, 2025
  • 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 24 22 8 Updated Feb 3, 2025
  • 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 13 2 0 10 Updated Feb 3, 2025
  • maggma Public

    Building blocks for scientific data pipelines

    materialsproject/maggma’s past year of commit activity
    Python 39 32 39 8 Updated Feb 3, 2025