Advertisement

JOM

, Volume 70, Issue 9, pp 1652–1658 | Cite as

Evolution of a Materials Data Infrastructure

  • James A. Warren
  • Charles H. Ward
ICME - 10 Years Later: Success and Challenges
  • 289 Downloads

Abstract

The field of materials science and engineering is writing a new chapter in its evolution, one of digitally empowered materials discovery, development, and deployment. The 2008 Integrated Computational Materials Engineering (ICME) study report helped usher in this paradigm shift, making a compelling case and strong recommendations for an infrastructure supporting ICME that would enable access to precompetitive materials data for both scientific and engineering applications. With the launch of the Materials Genome Initiative in 2011, which drew substantial inspiration from the ICME study, digital data was highlighted as a core component of a Materials Innovation Infrastructure, along with experimental and computational tools. Over the past 10 years, our understanding of what it takes to provide accessible materials data has matured and rapid progress has been made in establishing a Materials Data Infrastructure (MDI). We are learning that the MDI is essential to eliminating the seams between experiment and computation by providing a means for them to connect effortlessly. Additionally, the MDI is becoming an enabler, allowing materials engineering to tie into a much broader model-based engineering enterprise for product design.

References

  1. 1.
    J.H. Westbrook and J.R. Rumble Jr, Computerized Materials Data Systems (Fairfield Glades: National Bureau of Standards, 1983).Google Scholar
  2. 2.
    J.S. Glassman and J.R. Rumble, eds., Computerization and Networking of Materials Data Bases, ASTM STP 1017 (Philadelphia: American Society for Testing and Materials, 1989).Google Scholar
  3. 3.
    National Research Council, Materials Research to Meet 21st-Century Defense Needs (Washington: The National Academies Press, 2003).  https://doi.org/10.17226/10631.Google Scholar
  4. 4.
    National Research Council, Accelerating Technology Transition: Bridging the Valley of Death for Materials and Processes in Defense Systems (Washington: The National Academies Press, 2003).  https://doi.org/10.17226/11108.Google Scholar
  5. 5.
    International Assessment of Research and Development in Simulation-Based Engineering and Science (Baltimore, MD: World Technology Evaluation Center, Inc., 2009. http://www.wtec.org/sbes/SBES-GlobalFinalReport_BW.pdf.
  6. 6.
    National Research Council, Integrated Computational Materials Engineering: A Transformational Discipline for Improved Competitiveness and National Security (Washington, DC: The National Academies Press, 2008).  https://doi.org/10.17226/12199.Google Scholar
  7. 7.
    Materials Genome Initiative Strategic Plan, The White House, Washington, DC (2014) https://obamawhitehouse.archives.gov/sites/default/files/microsites/ostp/NSTC/mgi_strategic_plan_-_dec_2014.pdf
  8. 8.
    S.R. Kalidindi, Int. Mater. Rev. 60, 150 (2015).  https://doi.org/10.1179/1743280414Y.0000000043.CrossRefGoogle Scholar
  9. 9.
    S.R. Kalidindi and M. de Graef, Annu. Rev. Mater. Res. 45, 171 (2015).  https://doi.org/10.1146/annurev-matsci-070214-020844.CrossRefGoogle Scholar
  10. 10.
    J. Hill, A. Mannodi-Kanakkithodi, R. Ramprasad, B. Meredig, Computational Materials System Design, eds. D. Shin, J. Saal (New York, NY: Springer, 2018).  https://doi.org/10.1007/978-3-319-68280-8_9
  11. 11.
    C.H. Ward, J.A. Warren, and R.A. Hanisch, Integr. Mater. Manuf. Innov. 3, 22 (2014).  https://doi.org/10.1186/s40192-014-0022-8.CrossRefGoogle Scholar
  12. 12.
    J.P. Holdren, Increasing Access to the Results of Federally Funded Scientific Research (Washington, DC: The White House, 2013). https://obamawhitehouse.archives.gov/sites/default/files/microsites/ostp/ostp_public_access_memo_2013.pdf
  13. 13.
    Open Science Collaboration, Science 349, 6251 (2015).  https://doi.org/10.1126/science.aac4716.CrossRefGoogle Scholar
  14. 14.
    C.G. Begley and L.M. Ellis, Nature 483, 531 (2012).  https://doi.org/10.1038/483531a.CrossRefGoogle Scholar
  15. 15.
    M. Baker, Nature 533, 452 (2016).  https://doi.org/10.1038/533452a.CrossRefGoogle Scholar
  16. 16.
    M.D. Wilkinson, et al., Sci. Data 3, 160018 (2016).  https://doi.org/10.1038/sdata.2016.18.CrossRefGoogle Scholar
  17. 17.
    Building a Materials Data Infrastructure (Pittsburgh, PA: The Minerals, Metals & Materials Society, 2017).  https://doi.org/10.7449/mdistudy_1
  18. 18.
    R.T. Fielding (Ph.D. dissertation, University of California, Irvine, 2000).Google Scholar
  19. 19.
    A. Dima, S. Bhaskarla, and C. Becker, et al., JOM 68, 2053 (2016).  https://doi.org/10.1007/s11837-016-2000-4.CrossRefGoogle Scholar
  20. 20.
    B. Blaiszik, K. Chard, J. Pruyne, R. Ananthakrishnan, S. Tuecke, and I. Foster, JOM 68, 2045 (2016).  https://doi.org/10.1007/s11837-016-2001-3.CrossRefGoogle Scholar
  21. 21.
    B. Puchala, G. Tarcea, E.A. Marquis, M. Hedstrom, H.V. Jagadish, and J.E. Allison, JOM 68, 2035 (2016).  https://doi.org/10.1007/s11837-016-1998-7.CrossRefGoogle Scholar
  22. 22.
    J. O’Mara, B. Meredig, and K. Michel, JOM 68, 2031 (2016).  https://doi.org/10.1007/s11837-016-1984-0.CrossRefGoogle Scholar
  23. 23.
    A. Jain, S.P. Ong, G. Hautier, W. Chen, W.D. Richards, S. Dacek, S. Cholia, D. Gunter, D. Skinner, G. Ceder, and K.A. Persson, APL Mater. 1, 011002 (2013).  https://doi.org/10.1063/1.4812323.CrossRefGoogle Scholar
  24. 24.
    S. Curtarolo, W. Setyawan, S. Wang, J. Xue, K. Yang, R.H. Taylor, L.J. Nelson, G.L.W. Hart, S. Sanvito, M. Buongiorno-Nardelli, N. Mingo, and O. Levy, Comput. Mater. Sci. 58, 227 (2012).  https://doi.org/10.1016/j.commatsci.2012.02.002.CrossRefGoogle Scholar
  25. 25.
    S. Curtarolo, W. Setyawan, G.L.W. Hart, M. Jahnatek, R.V. Chepulskii, R.H. Taylor, S. Wang, J. Xue, K. Yang, O. Levy, M. Mehl, H.T. Stokes, D.O. Demchenko, and D. Morgan, Comput. Mater. Sci. 58, 218 (2012).  https://doi.org/10.1016/j.commatsci.2012.02.005.CrossRefGoogle Scholar
  26. 26.
    J.E. Saal, S. Kirklin, M. Aykol, B. Meredig, and C. Wolverton, JOM 65, 1501 (2013).  https://doi.org/10.1007/s11837-013-0755-4.CrossRefGoogle Scholar
  27. 27.
    The NIST Materials Resource Registry. https://mgi.nist.gov/materials-resource-registry/
  28. 28.
    S.R. Hall, F.H. Allen, and I.D. Brown, Acta Cryst. A47, 655 (1991).CrossRefGoogle Scholar
  29. 29.
    K.J. Michel and B. Meredig, MRS Bull. 41, 617 (2016).  https://doi.org/10.1557/mrs.2016.166.CrossRefGoogle Scholar
  30. 30.
    The Materials Data Curation System. https://mgi.nist.gov/materials-data-curation-system/
  31. 31.
    J. Rumble, E-Materials Data. ASTM International. Standardization News (2014). http://www.astm.org/standardization-news/perspective/ematerials-data-ma14.html.
  32. 32.
    T. Austin, C. Bullough, D. Gagliardi, D. Leal, and M. Loveday, Int. J. Digit Curation 8, 5 (2013).  https://doi.org/10.2218/ijdc.v8i1.245.CrossRefGoogle Scholar
  33. 33.
    M.D. Jacobsen, J.R. Fourman, K.M. Porter, E.A. Wirrig, M.D. Benedict, B.J. Foster, and C.H. Ward, Integr. Mater Manuf. Innov. 5, 12 (2016).  https://doi.org/10.1186/s40192-016-0055-2.CrossRefGoogle Scholar
  34. 34.
    N.S. Carey, T. Budavri, N. Daphalapurkar, and K.T. Ramesh, Integr. Mater. Manuf. Innov. 5, 7 (2016).  https://doi.org/10.1186/s40192-016-0049-0.CrossRefGoogle Scholar
  35. 35.
    M.W. Gaultois, T.D. Sparks, C.K.H. Borg, R. Seshadri, W.D. Bonificio, and D.R. Clarke, Chem. Mater. 25, 2911 (2013).  https://doi.org/10.1021/cm400893e.CrossRefGoogle Scholar
  36. 36.
    J.H. Martin, B.D. Yahata, J.M. Hundley, J.A. Mayer, T.A. Schaedler, and T.M. Pollock, Nature 549, 365 (2017).  https://doi.org/10.1038/nature23894.CrossRefGoogle Scholar
  37. 37.
    E. Popova, T.M. Rodgers, and X. Gong, et al., Integr. Mater. Manuf. Innov. 6, 54 (2017).  https://doi.org/10.1007/s40192-017-0088-1.CrossRefGoogle Scholar
  38. 38.
    P. Nikolaev, D. Hooper, F. Webber, R. Rao, K. Decker, M. Krein, J. Poleski, R. Barto, B. Maruyama, and N.P.J. Comput, Mater. 2, 16031 (2016).  https://doi.org/10.1038/npjcompumats.2016.31.Google Scholar
  39. 39.
    D.U. Furrer, D.M. Dimiduk, J.D. Cotton, and C.H. Ward, Integr. Mater. Manuf. Innov. 6, 249 (2017).  https://doi.org/10.1007/s40192-017-0102-7.CrossRefGoogle Scholar

Copyright information

© This is a U.S. government work and its text is not subject to copyright protection in the United States; however, its text may be subject to foreign copyright protection 2018

Authors and Affiliations

  1. 1.Material Measurement LaboratoryNational Institute of Standards and TechnologyGaithersburgUSA
  2. 2.Materials and Manufacturing DirectorateAir Force Research LaboratoryWright-Patterson AFBUSA

Personalised recommendations