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      About the Materials Project

      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.

      supercomputers

      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.

      Database Statistics

      • 131,613

        inorganic compounds
      • 53,950

        bandstructures
      • 49,705

        molecules
      • 530,243

        nanoporous materials
      • 14,071

        elastic tensors
      • 3,411

        piezoelectric tensors
      • 4,730

        intercalation electrodes
      • 16,128

        conversion electrodes

      Director

      Kristin Persson

      Professor, Department of Materials Science and Engineering,
      University of California at Berkeley

      Senior Faculty Scientist, Lawrence Berkeley National Laboratory

      Co-Investigators

      Mark Asta
      Faculty Scientist, LBNL
      Gerbrand Ceder
      Senior Faculty Scientist, LBNL
      Daryl Chrzan
      Faculty Scientist, LBNL
      Daniel Gunter
      Staff Scientist, LBNL
      Geoffroy Hautier
      Asst Professor, UCL Belgium
      Gian-Marco Rignanese
      Professor, UCL Belgium
      Anubhav Jain
      Staff Scientist, LBNL
      Peter Khalifah
      Faculty Scientist, BNL
      Lane Martin
      Faculty Scientist, LBNL
      Jeffrey Neaton
      Senior Faculty Scientist, LBNL
      Shyue Ping Ong
      Asst Professor, UCSD

      In Collaboration With:

      GitHub users with pull requests merged to MP code repositories.

      Partners and Support

      BMR

      Development of the Materials Project is supported by the U.S. Department of Energy (DOE) through its Office of Science, via the Basic Energy Sciences (BES) and Advanced Scientific Computing Research (ASCR) programs, and through its Office of Energy Efficiency and Renewable Energy (EERE), via the Battery Materials Research (BMR, formerly BATT) program. A notable source of support within DOE-BES is the Joint Center for Energy Storage Research (JCESR).

      The Materials Project is also supported by a Laboratory Directed Research and Development grant from LBNL, and by the U.S. National Science Foundation (NSF) via the Data Infrastructure Building Blocks (DIBBS) program. Disseminated science is supported by DOE (BES and BMR), NSF, Gillette, Volkswagen, Umicore, and Bosch.

      Open APIs

      For information about our materials API and pymatgen analysis code, please check our API page and visit the Fireworks page for details about our open source scientific workflow software.

      Get In Touch

      Questions? Feedback? We'd love to hear from you via our discussion forum.

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