Hostname: page-component-7dd5485656-zlgnt Total loading time: 0 Render date: 2025-10-31T09:13:57.357Z Has data issue: false hasContentIssue false
  • English
  • Français

Strategies for accelerating the adoption of materials informatics

Published online by Cambridge University Press:  10 September 2018

Logan Ward ,
Muratahan Aykol ,
Ben Blaiszik ,
Ian Foster ,
Bryce Meredig ,
James Saal  and
Santosh Suram
Logan Ward
Affiliation:
The University of Chicago, and Data Science and Learning Division, Argonne National Laboratory, USA; loganw@uchicago.edu
Muratahan Aykol
Affiliation:
Toyota Research Institute, USA; murat.aykol@tri.global
Ben Blaiszik
Affiliation:
The University of Chicago, and Data Science and Learning Division, Argonne National Laboratory, USA; blaiszik@uchicago.edu
Ian Foster
Affiliation:
Department of Computer Science, The University of Chicago, and Data Science and Learning Division, Argonne National Laboratory, USA; foster@anl.gov
Bryce Meredig
Affiliation:
Citrine Informatics, USA; bryce@citrine.io
James Saal
Affiliation:
QuesTek InnovationsLLC, USA; jsaal@questek.com
Santosh Suram
Affiliation:
Toyota Research Institute, USA; santosh.suram@tri.global
Get access

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.

Keywords

combinatorial synthesiscrystallographic structuresimulation

Information

Type
Data-Centric Science for Materials Innovation
Information
MRS Bulletin , Volume 43 , Issue 9: Data-Centric Science for Materials Innovation , September 2018 , pp. 683 - 689
Copyright
Copyright © Materials Research Society 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Lutin, J.M., Kornhauser, A.L., Lerner-Lam, E., ITE J. 83, 28 (2013).Google Scholar
Angus, D.C., JAMA 314, 767 (2015).CrossRefGoogle Scholar
Ren, F., Ward, L., Williams, T., Laws, K.J., Wolverton, C., Hattrick-Simpers, J., Mehta, A., Sci. Adv. 4, eaaq1566 (2018).CrossRefGoogle Scholar
Kalinin, S.V., Sumpter, B.G., Archibald, R.K., Nat. Mater. 14, 973 (2015).CrossRefGoogle Scholar
Ramprasad, R., Batra, R., Pilania, G., Mannodi-Kanakkithodi, A., Kim, C., NPJ Comput. Mater. 3, 54 (2017).CrossRefGoogle Scholar
Curtarolo, S., Hart, G.L.W., Nardelli, M.B., Mingo, N., Sanvito, S., Levy, O., Nat. Mater. 12, 191 (2013).CrossRefGoogle Scholar
Lin, L., Mater. Perform. Charact. 4, 148 (2015).Google Scholar
Ashby, M.F., Mater. Sci. Technol. 5, 517 (1989).CrossRefGoogle Scholar
Smithson, H., Marianetti, C.A., Morgan, D., Van der Ven, A., Predith, A., Ceder, G., Phys. Rev. B Condens. Matter 66, 144107 (2002).CrossRefGoogle Scholar
Greeley, J., Jaramillo, T.F., Bonde, J., Chorkendorff, I.B., Nørskov, J.K., Nat. Mater. 5, 909 (2006).CrossRefGoogle Scholar
Curtarolo, S., Morgan, D., Ceder, G., Calphad 29, 163 (2005).CrossRefGoogle Scholar
Madsen, G.K.H., J. Am. Chem. Soc. 128, 12140 (2006).CrossRefGoogle Scholar
Jain, A., Ong, S.P., Hautier, G., Chen, W., Richards, W.D., Dacek, S., Cholia, S., Gunter, D., Skinner, D., Ceder, G., Persson, K.A., APL Mater. 1, 11002 (2013).CrossRefGoogle Scholar
Saal, J.E., Kirklin, S., Aykol, M., Meredig, B., Wolverton, C., JOM 65, 1501 (2013).CrossRefGoogle Scholar
Kirklin, S., Saal, J.E., Meredig, B., Thompson, A., Doak, J.W., Aykol, M., Rühl, S., Wolverton, C., NPJ Comput. Mater. 1, 15010 (2015).CrossRefGoogle Scholar
Curtarolo, S., Setyawan, W., Wang, S., Xue, J., Yang, K., Taylor, R.H., Nelson, L.J., Hart, G.L.W., Sanvito, S., Buongiorno-Nardelli, M., Mingo, N., Levy, O., Comput. Mater. Sci. 58, 227 (2012).CrossRefGoogle Scholar
Aykol, M., Kim, S., Hegde, V.I., Snydacker, D., Lu, Z., Hao, S., Kirklin, S., Morgan, D., Wolverton, C., Nat. Commun. 7, 13779 (2016).CrossRefGoogle Scholar
Jain, A., Persson, K.A., Ceder, G., APL Mater. 4, 53102 (2016).CrossRefGoogle Scholar
de Jong, M, Chen, W., Geerlings, H., Asta, M., Persson, K.A., Sci. Data 2, 1 (2015).Google Scholar
Meredig, B., Wolverton, C., Chem. Mater. 26, 1985 (2014).CrossRefGoogle Scholar
Emery, A.A., Saal, J.E., Kirklin, S., Hegde, V.I., Wolverton, C., Chem. Mater. 28, 5621 (2016).CrossRefGoogle Scholar
Ghiringhelli, L.M., Vybiral, J., Levchenko, S.V., Draxl, C., Scheffler, M., Phys. Rev. Lett. 114, 105503 (2015).CrossRefGoogle Scholar
Kong, C.S., Luo, W., Arapan, S., Villars, P., Iwata, S., Ahuja, R., Rajan, K., J. Chem. Inf. Model. 52, 1812 (2012).CrossRefGoogle Scholar
Mannodi-Kanakkithodi, A., Huan, T.D., Ramprasad, R., Chem. Mater. 29, 9001 (2017).CrossRefGoogle Scholar
Behler, J., J. Chem. Phys. 145, 170901 (2016).CrossRefGoogle ScholarPubMed
Li, Z., Kermode, J.R., De Vita, A., Phys. Rev. Lett. 114, 96405 (2015).CrossRefGoogle Scholar
Jørgensen, M.S., Larsen, U.F., Jacobsen, K.W., Hammer, B., J. Phys. Chem. A 122, 1504 (2018).CrossRefGoogle Scholar
Faber, F., Lindmaa, A., von Lilienfeld, O.A., Armiento, R., Int. J. Quantum Chem. 115, 1094 (2015).CrossRefGoogle Scholar
Ward, L., Liu, R., Krishna, A., Hegde, V.I., Agrawal, A., Choudhary, A., Wolverton, C., Phys. Rev. B Condens. Matter 96, 24104 (2017).CrossRefGoogle Scholar
Hautier, G., Fischer, C.C., Jain, A., Mueller, T., Ceder, G., Chem. Mater. 22, 3762 (2010).CrossRefGoogle Scholar
Meredig, B., Agrawal, A., Kirklin, S., Saal, J.E., Doak, J.W., Thompson, A., Zhang, K., Choudhary, A., Wolverton, C., Phys. Rev. B Condens. Matter 89, 94104 (2014).CrossRefGoogle Scholar
Faber, F.A., Lindmaa, A., von Lilienfeld, O.A., Armiento, R., Phys. Rev. Lett. 117, 135502 (2016).CrossRefGoogle Scholar
Seko, A., Hayashi, H., Kashima, H., Tanaka, I., Phys. Rev. Mater. 2, 13805 (2018).CrossRefGoogle Scholar
Seko, A., Maekawa, T., Tsuda, K., Tanaka, I., Phys. Rev. B Condens. Matter 89, 54303 (2014).CrossRefGoogle Scholar
Hong, Q.-J., van de Walle, A., Calphad 52, 88 (2016).CrossRefGoogle Scholar
Hutchinson, M.L., Antono, E., Gibbons, B.M., Paradiso, S., Ling, J., Meredig, B., Comput. Sci. Learning (2017), https://arxiv.org/abs/1711.05099.Google Scholar
Ward, L., Wolverton, C., Curr. Opin. Solid State Mater. Sci. 21, 167 (2017).CrossRefGoogle Scholar
Mathew, K., Montoya, J.H., Faghaninia, A., Dwarakanath, S., Aykol, M., Tang, H., Chu, I., Smidt, T., Bocklund, B., Horton, M., Dagdelen, J., Wood, B., Liu, Z.-K., Neaton, J., Ong, S.P., Persson, K., Jain, A., Comput. Mater. Sci. 139, 140 (2017).CrossRefGoogle Scholar
Pizzi, G., Cepellotti, A., Sabatini, R., Marzari, N., Kozinsky, B., Comput. Mater. Sci. 111, 218 (2016).CrossRefGoogle Scholar
Mayeshiba, T., Wu, H., Angsten, T., Kaczmarowski, A., Song, Z., Jenness, G., Xie, W., Morgan, D., Comput. Mater. Sci. 126, 90 (2017).CrossRefGoogle Scholar
Hjorth Larsen, A., Jørgen Mortensen, J., Blomqvist, J., Castelli, I.E., Christensen, R., Dułak, M., Friis, J., Groves, M.N., Hammer, B., Hargus, C., Hermes, E.D., Jennings, P.C., Bjerre Jensen, P., Kermode, J., Kitchin, J.R., Leonhard Kolsbjerg, E., Kubal, J., Kaasbjerg, K., Lysgaard, S., Bergmann Maronsson, J., Maxson, T., Olsen, T., Pastewka, L., Peterson, A., Rostgaard, C., Schiøtz, J., Schütt, O., Strange, M., Thygesen, K.S., Vegge, T., Vilhelmsen, L., Walter, M., Zeng, Z., Jacobsen, K.W., J. Phys. Condens. Matter 29, 273002 (2017).CrossRefGoogle Scholar
Ong, S.P., Richards, W.D., Jain, A., Hautier, G., Kocher, M., Cholia, S., Gunter, D., Chevrier, V.L., Persson, K.A., Ceder, G., Comput. Mater. Sci. 68, 314 (2013).CrossRefGoogle Scholar
http://www.icdd.com/products/pdf4.htm.Google Scholar
Belsky, A., Hellenbrandt, M., Karen, V.L., Luksch, P., Acta Crystallogr. B Struct. Sci. 58, 364 (2002).CrossRefGoogle Scholar
Grazulis, S., Chateigner, D., Downs, R.T., Yokochi, A.T., Quiros, M., Lutterotti, L., Manakova, E., Butkus, J., Moeck, P., Le Bail, A., J. Appl. Crystallogr. 42, 726 (2009).CrossRefGoogle Scholar
Hall, S.R., Allen, F.H., Brown, I.D., Acta Crystallogr. A 47, 655 (1991).CrossRefGoogle Scholar
Otsuka, S., Kuwajima, I., Hosoya, J., Xu, Y., Yamazaki, M., 2011 Int. Conf. Emerging Intell. Data. Web Technol. (IEEE, 2011), pp. 22–29.CrossRefGoogle Scholar
Yamazaki, M., Xu, Y., in Volume 6: Materials and Fabrication, Parts A and B, ASME 2009 Pressure Vessels and Piping Conference (ASME, 2009), pp. 1561–1568.Google Scholar
https://srdata.nist.gov/gateway/gateway.Google Scholar
DeCost, B.L., Hecht, M.D., Francis, T., Webler, B.A., Picard, Y.N., Holm, E.A., Integr. Mater. Manuf. Innov. 6, 197 (2017).CrossRefGoogle Scholar
Gaultois, M.W., Sparks, T.D., Borg, C.K.H., Seshadri, R., Bonificio, W.D., Clarke, D.R., Chem. Mater. 25, 2911 (2013).CrossRefGoogle Scholar
Zunger, A., Phys. Rev. B Condens. Matter 22, 5839 (1980).CrossRefGoogle Scholar
Pettifor, D.G., Mater. Sci. Technol. 4, 675 (1988).CrossRefGoogle Scholar
Villars, P., Phillips, J., Phys. Rev. B Condens. Matter 37, 2345 (1988).CrossRefGoogle Scholar
Lukas, H., Fries, S.G., Sundman, B., Computational Thermodynamics (Cambridge University Press, Cambridge, UK, 2007).CrossRefGoogle Scholar
Sparks, T.D., Gaultois, M.W., Oliynyk, A., Brgoch, J., Meredig, B., Scr. Mater. 111, 10 (2015).CrossRefGoogle Scholar
Suram, S.K., Haber, J.A., Jin, J., Gregoire, J.M., ACS Comb. Sci. 17, 224 (2015).CrossRefGoogle Scholar
Balachandran, P.V., Xue, D., Theiler, J., Hogden, J., Lookman, T., Sci. Rep. 6, 19660 (2016).CrossRefGoogle Scholar
Ling, J., Hutchinson, M., Antono, E., Paradiso, S., Meredig, B., Integr. Mater. Manuf. Innov. 6, 207 (2017).CrossRefGoogle Scholar
Xue, D., Balachandran, P.V., Hogden, J., Theiler, J., Xue, D., Lookman, T., Nat. Commun. 7, 11241 (2016).CrossRefGoogle Scholar
Suram, S.K., Xue, Y., Bai, J., Le Bras, R., Rappazzo, B., Bernstein, R., Bjorck, J., Zhou, L., van Dover, R.B., Gomes, C.P., Gregoire, J.M., ACS Comb. Sci. 19, 37 (2017).CrossRefGoogle Scholar
Green, M.L., Choi, C.L., Hattrick-Simpers, J.R., Joshi, A.M., Takeuchi, I., Barron, S.C., Campo, E., Chiang, T., Empedocles, S., Gregoire, J.M., Kusne, A.G., Martin, J., Mehta, A., Persson, K., Trautt, Z., Van Duren, J., Zakutayev, A., Appl. Phys. Rev. 4, 11105 (2017).CrossRefGoogle Scholar
https://www.csiro.au/en/Research/MF/Areas/Chemicals-and-fibres/RAMP.Google Scholar
Lu, X.-G., Sci. Bull. 60, 1966 (2015).CrossRefGoogle Scholar
Nikolaev, P., Hooper, D., Webber, F., Rao, R., Decker, K., Krein, M., Poleski, J., Barto, R., Maruyama, B., NPJ Comput. Mater. 2, 16031 (2016).CrossRefGoogle Scholar
Dima, A., Bhaskarla, S., Becker, C., Brady, M., Campbell, C., Dessauw, P., Hanisch, R., Kattner, U., Kroenlein, K., Newrock, M., Peskin, A., Plante, R., Li, S.-Y., Rigodiat, P.-F., Amaral, G.S., Trautt, Z., Schmitt, X., Warren, J., Youssef, S., JOM 68, 2053 (2016).CrossRefGoogle Scholar
Puchala, B., Tarcea, G., Marquis, E.A., Hedstrom, M., Jagadish, H.V., Allison, J.E., JOM 68, 2035 (2016).CrossRefGoogle Scholar
Nguyen, P., Konstanty, S., Nicholson, T., O’Brien, T., Schwartz-Duval, A., Spila, T., Nahrstedt, K., Campbell, R.H., Gupta, I., Chan, M., McHenry, K., Paquin, N., 2017 17th IEEE/ACM Int. Symp. Cluster, Cloud and Grid Comput. (CCGRID) (IEEE, 2017), pp. 11–20.CrossRefGoogle Scholar
Kim, E., Huang, K., Tomala, A., Matthews, S., Strubell, E., Saunders, A., McCallum, A., Olivetti, E., Sci. Data 4, 170127 (2017).CrossRefGoogle Scholar
Swain, M.C., Cole, J.M., J. Chem. Inf. Model. 56, 1894 (2016).CrossRefGoogle Scholar
Tchoua, R.B., Chard, K., Audus, D.J., Ward, L.T., Lequieu, J., De Pablo, J.J., Foster, I.T., 2017 IEEE 13th Int. Conf. e-Science (e-Science) (IEEE, 2017), pp. 109–118.CrossRefGoogle Scholar
Beckman, P., Skluzacek, T.J., Chard, K., Foster, I., Proc. 29th Int. Conf. Scientific Statistical Database Mgmt.—SSDBM ’17 (ACM Press, New York, 2017), https://dl.acm.org/citation.cfm?doid=3085504.3091116.Google Scholar
Wilkinson, M.D., Dumontier, M., Aalbersberg, Ij.J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J.-W., da Silva Santos, L.B., Bourne, P.E., Bouwman, J., Brookes, A.J., Clark, T., Crosas, M., Dillo, I., Dumon, O., Edmunds, S., Evelo, C.T., Finkers, R., Gonzalez-Beltran, A., Gray, A.J.G., Groth, P., Goble, C., Grethe, J.S., Heringa, J., ’t Hoen, P.A., Hooft, R., Kuhn, T., Kok, R., Kok, J., Lusher, S.J., Martone, M.E., Mons, A., Packer, A.L., Persson, B., Rocca-Serra, P., Roos, M., van Schaik, R., Sansone, S.-A., Schultes, E., Sengstag, T., Slater, T., Strawn, G., Swertz, M.A., Thompson, M., van der Lei, J., van Mulligen, E., Velterop, J., Waagmeester, A., Wittenburg, P., Wolstencroft, K., Zhao, J., Mons, B., Sci. Data 3, 160018 (2016).CrossRefGoogle ScholarPubMed
Blaiszik, B., Chard, K., Pruyne, J., Ananthakrishnan, R., Tuecke, S., Foster, I., JOM 68, 2045 (2016).CrossRefGoogle Scholar
O’Mara, J., Meredig, B., Michel, K., JOM 68, 2031 (2016).CrossRefGoogle Scholar