Skip to main content
Log in

Strategies for accelerating the adoption of materials informatics

  • Published:
MRS Bulletin Aims and scope Submit manuscript

Abstract

Ongoing, rapid innovations in fields ranging from microelectronics, aerospace, and automotive to defense, energy, and health demand new advanced materials at even greater rates and lower costs. Traditional materials R&D methods offer few paths to achieve both outcomes simultaneously. Materials informatics, while a nascent field, offers such a promise through screening, growing databases of materials for new applications, learning new relationships from existing data resources, and building fast predictive models. We highlight key materials informatics successes from the atomic-scale modeling community, and discuss the ecosystem of open data, software, services, and infrastructure that have led to broad adoption of materials informatics approaches. We then examine emerging opportunities for informatics in materials science and describe an ideal data ecosystem capable of supporting similar widespread adoption of materials informatics, which we believe will enable the faster design of materials.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Figure 1

Similar content being viewed by others

References

  1. J.M. Lutin, A.L. Kornhauser, E. Lerner-Lam, ITE J. 83, 28 (2013).

    Google Scholar 

  2. D.C. Angus, JAMA 314, 767 (2015).

    Google Scholar 

  3. F. Ren, L. Ward, T. Williams, K.J. Laws, C. Wolverton, J. Hattrick-Simpers, A. Mehta, Sci. Adv. 4, eaaq1566 (2018).

  4. S.V. Kalinin, B.G. Sumpter, R.K. Archibald, Nat. Mater. 14, 973 (2015).

    Google Scholar 

  5. R. Ramprasad, R. Batra, G. Pilania, A. Mannodi-Kanakkithodi, C. Kim, NPJ Comput. Mater. 3, 54 (2017).

    Google Scholar 

  6. S. Curtarolo, G.L.W. Hart, M.B. Nardelli, N. Mingo, S. Sanvito, O. Levy, Nat. Mater. 12, 191 (2013).

    Google Scholar 

  7. L. Lin, Mater. Perform. Charact. 4, 148 (2015).

    Google Scholar 

  8. M.F. Ashby, Mater. Sci. Technol. 5, 517 (1989).

    Google Scholar 

  9. H. Smithson, C.A. Marianetti, D. Morgan, A. Van der Ven, A. Predith, G. Ceder, Phys. Rev. B Condens. Matter 66, 144107 (2002).

    Google Scholar 

  10. J. Greeley, T.F. Jaramillo, J. Bonde, I.B. Chorkendorff, J.K. Nørskov, Nat. Mater. 5, 909 (2006).

    Google Scholar 

  11. S. Curtarolo, D. Morgan, G. Ceder, Calphad 29, 163 (2005).

    Google Scholar 

  12. G.K.H. Madsen, J. Am. Chem. Soc. 128, 12140 (2006).

    Google Scholar 

  13. A. Jain, S.P. Ong, G. Hautier, W. Chen, W.D. Richards, S. Dacek, S. Cholia, D. Gunter, D. Skinner, G. Ceder, K.A. Persson, APL Mater. 1, 11002 (2013).

    Google Scholar 

  14. J.E. Saal, S. Kirklin, M. Aykol, B. Meredig, C. Wolverton, JOM 65, 1501 (2013).

    Google Scholar 

  15. S. Kirklin, J.E. Saal, B. Meredig, A. Thompson, J.W. Doak, M. Aykol, S. Rühl, C. Wolverton, NPJ Comput. Mater. 1, 15010 (2015).

    Google Scholar 

  16. 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, O. Levy, Comput. Mater. Sci. 58, 227 (2012).

    Google Scholar 

  17. M. Aykol, S. Kim, V.I. Hegde, D. Snydacker, Z. Lu, S. Hao, S. Kirklin, D. Morgan, C. Wolverton, Nat. Commun. 7, 13779 (2016).

    Google Scholar 

  18. A. Jain, K.A. Persson, G. Ceder, APL Mater. 4, 53102 (2016).

    Google Scholar 

  19. M de Jong, W. Chen, H. Geerlings, M. Asta, K.A. Persson, Sci. Data 2, 1 (2015).

    Google Scholar 

  20. B. Meredig, C. Wolverton, Chem. Mater. 26, 1985 (2014).

    Google Scholar 

  21. A.A. Emery, J.E. Saal, S. Kirklin, V.I. Hegde, C. Wolverton, Chem. Mater. 28, 5621 (2016).

    Google Scholar 

  22. L.M. Ghiringhelli, J. Vybiral, S.V. Levchenko, C. Draxl, M. Scheffler, Phys. Rev. Lett. 114, 105503 (2015).

    Google Scholar 

  23. C.S. Kong, W. Luo, S. Arapan, P. Villars, S. Iwata, R. Ahuja, K. Rajan, J. Chem. Inf. Model. 52, 1812 (2012).

    Google Scholar 

  24. A. Mannodi-Kanakkithodi, T.D. Huan, R. Ramprasad, Chem. Mater. 29, 9001 (2017).

    Google Scholar 

  25. J. Behler, J. Chem. Phys. 145, 170901 (2016).

    Google Scholar 

  26. Z. Li, J.R. Kermode, A. De Vita, Phys. Rev. Lett. 114, 96405 (2015).

    Google Scholar 

  27. M.S. Jørgensen, U.F. Larsen, K.W. Jacobsen, B. Hammer, J. Phys. Chem. A 122, 1504 (2018).

    Google Scholar 

  28. F. Faber, A. Lindmaa, O.A. von Lilienfeld, R. Armiento, Int. J. Quantum Chem. 115, 1094 (2015).

    Google Scholar 

  29. L. Ward, R. Liu, A. Krishna, V.I. Hegde, A. Agrawal, A. Choudhary, C. Wolverton, Phys. Rev. B Condens. Matter 96, 24104 (2017).

    Google Scholar 

  30. G. Hautier, C.C. Fischer, A. Jain, T. Mueller, G. Ceder, Chem. Mater. 22, 3762 (2010).

    Google Scholar 

  31. B. Meredig, A. Agrawal, S. Kirklin, J.E. Saal, J.W. Doak, A. Thompson, K. Zhang, A. Choudhary, C. Wolverton, Phys. Rev. B Condens. Matter 89, 94104 (2014).

    Google Scholar 

  32. F.A. Faber, A. Lindmaa, O.A. von Lilienfeld, R. Armiento, Phys. Rev. Lett. 117, 135502 (2016).

    Google Scholar 

  33. A. Seko, H. Hayashi, H. Kashima, I. Tanaka, Phys. Rev. Mater. 2, 13805 (2018).

    Google Scholar 

  34. A. Seko, T. Maekawa, K. Tsuda, I. Tanaka, Phys. Rev. B Condens. Matter 89, 54303 (2014).

    Google Scholar 

  35. Q.-J. Hong, A. van de Walle, Calphad 52, 88 (2016).

    Google Scholar 

  36. M.L. Hutchinson, E. Antono, B.M. Gibbons, S. Paradiso, J. Ling, B. Meredig, Comput. Sci. Learning (2017), https://arxiv.org/abs/1711.05099.

  37. L. Ward, C. Wolverton, Curr. Opin. Solid State Mater. Sci. 21, 167 (2017).

    Google Scholar 

  38. K. Mathew, J.H. Montoya, A. Faghaninia, S. Dwarakanath, M. Aykol, H. Tang, I. Chu, T. Smidt, B. Bocklund, M. Horton, J. Dagdelen, B. Wood, Z.-K. Liu, J. Neaton, S.P. Ong, K. Persson, A. Jain, Comput. Mater. Sci. 139, 140 (2017).

    Google Scholar 

  39. G. Pizzi, A. Cepellotti, R. Sabatini, N. Marzari, B. Kozinsky, Comput. Mater. Sci. 111, 218 (2016).

    Google Scholar 

  40. T. Mayeshiba, H. Wu, T. Angsten, A. Kaczmarowski, Z. Song, G. Jenness, W. Xie, D. Morgan, Comput. Mater. Sci. 126, 90 (2017).

    Google Scholar 

  41. A. Hjorth Larsen, J. Jørgen Mortensen, J. Blomqvist, I.E. Castelli, R. Christensen, M. Dułak, J. Friis, M.N. Groves, B. Hammer, C. Hargus, E.D. Hermes, P.C. Jennings, P. Bjerre Jensen, J. Kermode, J.R. Kitchin, E. Leonhard Kolsbjerg, J. Kubal, K. Kaasbjerg, S. Lysgaard, J. Bergmann Maronsson, T. Maxson, T. Olsen, L. Pastewka, A. Peterson, C. Rostgaard, J. Schiøtz, O. Schütt, M. Strange, K.S. Thygesen, T. Vegge, L. Vilhelmsen, M. Walter, Z. Zeng, K.W. Jacobsen, J. Phys. Condens. Matter 29, 273002 (2017).

    Google Scholar 

  42. S.P. Ong, W.D. Richards, A. Jain, G. Hautier, M. Kocher, S. Cholia, D. Gunter, V.L. Chevrier, K.A. Persson, G. Ceder, Comput. Mater. Sci. 68, 314 (2013).

    Google Scholar 

  43. http://www.icdd.com/products/pdf4.htmproducts/pdf4.htm.

  44. A. Belsky, M. Hellenbrandt, V.L. Karen, P. Luksch, Acta Crystallogr. B Struct. Sci. 58, 364 (2002).

    Google Scholar 

  45. S. Grazulis, D. Chateigner, R.T. Downs, A.T. Yokochi, M. Quiros, L. Lutterotti, E. Manakova, J. Butkus, P. Moeck, A. Le Bail, J. Appl. Crystallogr. 42, 726 (2009).

    Google Scholar 

  46. S.R. Hall, F.H. Allen, I.D. Brown, Acta Crystallogr. A 47, 655 (1991).

    Google Scholar 

  47. S. Otsuka, I. Kuwajima, J. Hosoya, Y. Xu, M. Yamazaki, 2011 Int. Conf. Emerging Intell. Data. Web Technol. (IEEE, 2011), pp. 22–29.

  48. M. Yamazaki, Y. Xu, in Volume 6: Materials and Fabrication, Parts A and B, ASME 2009 Pressure Vessels and Piping Conference (ASME, 2009), pp. 1561–1568.

  49. https://srdata.nist.gov/gateway/gatewaygateway/gateway.

  50. B.L. DeCost, M.D. Hecht, T. Francis, B.A. Webler, Y.N. Picard, E.A. Holm, Integr. Mater. Manuf. Innov. 6, 197 (2017).

    Google Scholar 

  51. M.W. Gaultois, T.D. Sparks, C.K.H. Borg, R. Seshadri, W.D. Bonificio, D.R. Clarke, Chem. Mater. 25, 2911 (2013).

    Google Scholar 

  52. A. Zunger, Phys. Rev. B Condens. Matter 22, 5839 (1980).

    Google Scholar 

  53. D.G. Pettifor, Mater. Sci. Technol. 4, 675 (1988).

    Google Scholar 

  54. P. Villars, J. Phillips, Phys. Rev. B Condens. Matter 37, 2345 (1988).

    Google Scholar 

  55. H. Lukas, S.G. Fries, B. Sundman, Computational Thermodynamics (Cambridge University Press, Cambridge, UK, 2007).

    Google Scholar 

  56. T.D. Sparks, M.W. Gaultois, A. Oliynyk, J. Brgoch, B. Meredig, Scr. Mater. 111, 10 (2015).

    Google Scholar 

  57. S.K. Suram, J.A. Haber, J. Jin, J.M. Gregoire, ACS Comb. Sci. 17, 224 (2015).

    Google Scholar 

  58. P.V. Balachandran, D. Xue, J. Theiler, J. Hogden, T. Lookman, Sci. Rep. 6, 19660 (2016).

    Google Scholar 

  59. J. Ling, M. Hutchinson, E. Antono, S. Paradiso, B. Meredig, Integr. Mater. Manuf. Innov. 6, 207 (2017).

    Google Scholar 

  60. D. Xue, P.V. Balachandran, J. Hogden, J. Theiler, D. Xue, T. Lookman, Nat. Commun. 7, 11241 (2016).

    Google Scholar 

  61. S.K. Suram, Y. Xue, J. Bai, R. Le Bras, B. Rappazzo, R. Bernstein, J. Bjorck, L. Zhou, R.B. van Dover, C.P. Gomes, J.M. Gregoire, ACS Comb. Sci. 19, 37 (2017).

    Google Scholar 

  62. M.L. Green, C.L. Choi, J.R. Hattrick-Simpers, A.M. Joshi, I. Takeuchi, S.C. Barron, E. Campo, T. Chiang, S. Empedocles, J.M. Gregoire, A.G. Kusne, J. Martin, A. Mehta, K. Persson, Z. Trautt, J. Van Duren, A. Zakutayev, Appl. Phys. Rev. 4, 11105 (2017).

    Google Scholar 

  63. https://www.csiro.au/en/Research/MF/Areas/Chemicals-and-fibres/RAMPen/Research/MF/Areas/Chemicals-and-fibres/RAMP.

  64. X.-G. Lu, Sci. Bull. 60, 1966 (2015).

    Google Scholar 

  65. P. Nikolaev, D. Hooper, F. Webber, R. Rao, K. Decker, M. Krein, J. Poleski, R. Barto, B. Maruyama, NPJ Comput. Mater. 2, 16031 (2016).

    Google Scholar 

  66. A. Dima, S. Bhaskarla, C. Becker, M. Brady, C. Campbell, P. Dessauw, R. Hanisch, U. Kattner, K. Kroenlein, M. Newrock, A. Peskin, R. Plante, S.-Y. Li, P.-F. Rigodiat, G.S. Amaral, Z. Trautt, X. Schmitt, J. Warren, S. Youssef, JOM 68, 2053 (2016).

    Google Scholar 

  67. B. Puchala, G. Tarcea, E.A. Marquis, M. Hedstrom, H.V. Jagadish, J.E. Allison, JOM 68, 2035 (2016).

    Google Scholar 

  68. P. Nguyen, S. Konstanty, T. Nicholson, T. O’Brien, A. Schwartz-Duval, T. Spila, K. Nahrstedt, R.H. Campbell, I. Gupta, M. Chan, K. McHenry, N. Paquin, 2017 17th IEEE/ACM Int. Symp. Cluster, Cloud and Grid Comput. (CCGRID) (IEEE, 2017), pp. 11–20.

  69. E. Kim, K. Huang, A. Tomala, S. Matthews, E. Strubell, A. Saunders, A. McCallum, E. Olivetti, Sci. Data 4, 170127 (2017).

    Google Scholar 

  70. M.C. Swain, J.M. Cole, J. Chem. Inf. Model. 56, 1894 (2016).

    Google Scholar 

  71. R.B. Tchoua, K. Chard, D.J. Audus, L.T. Ward, J. Lequieu, J.J. De Pablo, I.T. Foster, 2017 IEEE 13th Int. Conf. e-Science (e-Science) (IEEE, 2017), pp. 109–118.

  72. P. Beckman, T.J. Skluzacek, K. Chard, I. Foster, Proc. 29th Int. Conf. Scientific Statistical Database Mgmt.—SSDBM ’17 (ACM Press, New York, 2017), https://dl.acm.org/citation.cfm?doid=3085504.3091116.

  73. M.D. Wilkinson, M. Dumontier, Ij.J. Aalbersberg, G. Appleton, M. Axton, A. Baak, N. Blomberg, J.-W. Boiten, L.B. da Silva Santos, P.E. Bourne, J. Bouwman, A.J. Brookes, T. Clark, M. Crosas, I. Dillo, O. Dumon, S. Edmunds, C.T. Evelo, R. Finkers, A. Gonzalez-Beltran, A.J.G. Gray, P. Groth, C. Goble, J.S. Grethe, J. Heringa, P.A. ’t Hoen, R. Hooft, T. Kuhn, R. Kok, J. Kok, S.J. Lusher, M.E. Martone, A. Mons, A.L. Packer, B. Persson, P. Rocca-Serra, M. Roos, R. van Schaik, S.-A. Sansone, E. Schultes, T. Sengstag, T. Slater, G. Strawn, M.A. Swertz, M. Thompson, J. van der Lei, E. van Mulligen, J. Velterop, A. Waagmeester, P. Wittenburg, K. Wolstencroft, J. Zhao, B. Mons, Sci. Data 3, 160018 (2016).

    Google Scholar 

  74. B. Blaiszik, K. Chard, J. Pruyne, R. Ananthakrishnan, S. Tuecke, I. Foster, JOM 68, 2045 (2016).

    Google Scholar 

  75. J. O’Mara, B. Meredig, K. Michel, JOM 68, 2031 (2016).

    Google Scholar 

Download references

Acknowledgments

B.B., I.F., and L.W. were supported by financial assistance Award 70NANB14H012 from the US Department of Commerce, National Institute of Standards and Technology as part of the Center for Hierarchical Material Design (CHiMaD), by the National Science Foundation as part of the Midwest Big Data Hub under NSF Award No. 1636950 “BD Spokes: SPOKE: MIDWEST: Collaborative: Integrative Materials Design (IMaD): Leverage, Innovate, and Disseminate,” and by the US Department of Energy Contract DE-AC02-06CH11357.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Logan Ward.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ward, L., Aykol, M., Blaiszik, B. et al. Strategies for accelerating the adoption of materials informatics. MRS Bulletin 43, 683–689 (2018). https://doi.org/10.1557/mrs.2018.204

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1557/mrs.2018.204

Navigation