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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 1.6k 888

  2. fireworks fireworks Public

    The Fireworks Workflow Management Repo.

    Python 380 186

  3. custodian custodian Public

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

    Python 151 110

  4. atomate2 atomate2 Public

    atomate2 is a library of computational materials science workflows

    Python 203 108

  5. api api Public

    New API client for the Materials Project

    Python 131 49

Repositories

Showing 10 of 52 repositories
  • 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 25 22 8 Updated Apr 1, 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 1,602 888 199 (2 issues need help) 39 Updated Apr 1, 2025
  • emmet Public

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

    materialsproject/emmet’s past year of commit activity
    Python 59 70 42 16 Updated Apr 1, 2025
  • jobflow Public

    jobflow is a library for writing computational workflows.

    materialsproject/jobflow’s past year of commit activity
    Python 102 28 24 17 Updated Apr 1, 2025
  • atomate2 Public

    atomate2 is a library of computational materials science workflows

    materialsproject/atomate2’s past year of commit activity
    Python 203 108 44 33 Updated Apr 1, 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 3 0 10 Updated Mar 31, 2025
  • maggma Public

    Building blocks for scientific data pipelines

    materialsproject/maggma’s past year of commit activity
    Python 39 33 38 7 Updated Mar 31, 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 151 MIT 110 25 3 Updated Mar 31, 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 50 MIT 40 2 3 Updated Mar 31, 2025
  • pyrho Public
    materialsproject/pyrho’s past year of commit activity
    Python 40 9 2 3 Updated Mar 28, 2025