Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-24T15:11:34.995Z Has data issue: false hasContentIssue false

The materials innovation ecosystem: A key enabler for the Materials Genome Initiative

Published online by Cambridge University Press:  06 April 2016

David L. McDowell
Affiliation:
Institute for Materials, Georgia Institute of Technology, USA; [email protected]
Surya R. Kalidindi
Affiliation:
George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, USA; [email protected]
Get access

Abstract

The US Materials Genome Initiative (MGI) has emphasized the need to accelerate the discovery and development of materials to maintain industry competitiveness in new and existing markets. While largely interpreted as an initiative arising from the materials community, it is important to address the coupling of materials with manufacturing and all other relevant aspects of product development in order to maximize its impact. The dual thrusts of Integrated Computational Materials Engineering and the MGI represent a long-term vision of industry, academic, and government stakeholders. The goal is to build a new kind of coupled experimental, computational, and data sciences infrastructure. The emphasis is on high-throughput methods to accelerate historical sequential processes of serendipitous materials discovery and largely empirical materials development by leveraging computation and modern data sciences and analytics. The notion of a materials innovation ecosystem is introduced as the framework in which to pursue acceleration of discovery and development of materials consisting of various elements of data sciences, design optimization, manufacturing scale-up and automation, multiscale modeling, and uncertainty quantification with verification and validation.

Type
Research Article
Copyright
Copyright © Materials Research Society 2016 

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.)

References

References

National Science and Technology Council, Materials Genome Initiative for Global Competitiveness, June 2011, http://www.whitehouse.gov/sites/default/files/microsites/ostp/materials_genome_initiative-final.pdf (accessed November 16, 2015).Google Scholar
National Science and Technology Council, Committee on Technology, Subcommittee on the Materials Genome Initiative, Materials Genome Initiative Strategic Plan, December 2014, https://www.whitehouse.gov/sites/default/files/microsites/ostp/NSTC/mgi_strategic_plan_-_dec_2014.pdf (accessed November 16, 2015).Google 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, 011002 (2013).CrossRefGoogle Scholar
McDowell, D.L., “Rectifying Bottom-Up and Top-Down Uncertainties in Multiscale Modeling: Scientific and Engineering Aspects Relevant to ICME Multilevel Materials Design and Development,” presented at the ICME World Congress, Colorado Springs, CO, June 4, 2015.Google Scholar
Pollock, T.M., Allison, J.E., Committee on Integrated Computational Materials Engineering, National Materials Advisory Board, Division of Engineering and Physical Sciences, National Research Council of the National Academies, Integrated Computational Materials Engineering: A Transformational Discipline for Improved Competitiveness and National Security (National Academies Press, Washington, DC, 2008).Google Scholar
McDowell, D.L., Nature 503, 463 (2013).Google Scholar
Carrete, J., Li, W., Mingo, N., Wang, S., Curtarolo, S., Phys. Rev. X 4 (1), 011019 (2014).Google Scholar
Meredig, B., Agrawal, A., Kirklin, S., Saal, J.E., Doak, J.W., Thompson, A., Wolverton, C., Phys. Rev. B Condens. Matter 89 (9), 094104 (2014).Google Scholar
McDowell, D.L., Panchal, J.H., Choi, H.-J., Seepersad, C.C., Allen, J.K., Mistree, F., Integrated Design of Multiscale, Multifunctional Materials and Products, 1st ed. (Butterworth-Heinemann, Oxford, UK, 2010).Google Scholar
Olson, G.B., Science 277, 1237 (1997).Google Scholar
McDowell, D.L., JOM 59 (9), 21 (2007).Google Scholar
McDowell, D.L., Olson, G.B., Sci. Model. Simul. 15, 207 (2008).Google Scholar
Panchal, J.H., Kalidindi, S.R., McDowell, D.L., Comput. Aided Des. 45 (1), 4 (2013).Google Scholar
McKerns, M., “A Massively-Parallel Heterogeneous Computing Framework for Optimization and Parameter Sensitivity Analysis,” presented at the IPAM Workshop on Optimization, Search and Graph-Theoretical Algorithms for Chemical Compound Space, Los Angeles, April 12, 2011.Google Scholar
Choi, H.-J., “A Robust Design Method for Model and Propagated Uncertainty,” PhD thesis, G.W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta (2005).Google Scholar
Choi, H.-J., McDowell, D.L., Allen, J.K., Mistree, F., Eng. Optim. 40 (4), 287 (2008).CrossRefGoogle Scholar
Taguchi, G., Taguchi on Robust Technology Development: Bringing Quality Engineering Upstream (ASME Press, New York, 1993).CrossRefGoogle Scholar
Seepersad, C.C., “A Robust Topological Preliminary Design Exploration Method with Materials Design Applications,” PhD thesis, G.W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta (2004).Google Scholar
Seepersad, C.C., Kumar, R.S., Allen, J.K., Mistree, F., McDowell, D.L., J. Comput. Aided Mater. Des. 11 (2–3), 163 (2005).CrossRefGoogle Scholar
Seepersad, C.C., Allen, J.K., McDowell, D.L., Mistree, F., J. Mech. Des. 130 (3), 031404-1-13 (2008).Google Scholar
Choi, H.-J., Austin, R., Shepherd, J., Allen, J.K., McDowell, D.L., Mistree, F., Benson, D.J., J. Comput. Aided Mater. Des. 12 (1), 57 (2005).CrossRefGoogle Scholar
Rajan, K., Informatics for Materials Science and Engineering, Data-Driven Discovery for Accelerated Experimentation and Application, 1st ed. (Butterworth-Heinemann, Oxford, UK, 2013).Google Scholar
Rajan, K., Annu. Rev. Mater. Res. 45, 153 (2015).CrossRefGoogle Scholar
Curtarolo, S., Hart, G.L., Nardelli, M.B., Mingo, N., Sanvito, S., Levy, O., Nat. Mater. 12 (3), 191 (2013).CrossRefGoogle Scholar
Ghiringhelli, L.M., Vybiral, J., Levchenko, S.V., Draxl, C., Scheffler, M., Phys. Rev. Lett. 114 (10), 105503 (2015).CrossRefGoogle Scholar
Hall, E.O., Proc. Phys. Soc. Lond. B 64 (9), 742 (1951).CrossRefGoogle Scholar
Petch, N.J., J. Iron Steel Inst. 174, 2528 (1953).Google Scholar
Niezgoda, S.R., Yabansu, Y.C., Kalidindi, S.R., Acta Mater. 59, 6387 (2011).Google Scholar
Niezgoda, S.R., Kanjarla, A.K., Kalidindi, S.R., Integr. Mater. Manuf. Innov. 2, 3 (2013).Google Scholar
Niezgoda, S.R., Turner, D.M., Fullwood, D.T., Kalidindi, S.R., Acta Mater. 58, 4432 (2010).Google Scholar
Kalidindi, S.R., Hierarchical Materials Informatics, 1st ed. (Butterworth-Heinemann, Oxford, UK, 2015).Google Scholar
Kalidindi, S.R., Int. Mater. Rev. 60 (3), 150 (2015).CrossRefGoogle Scholar
Kalidindi, S.R., Niezgoda, S.R., Salem, A.A., JOM 63 (4), 34 (2011).CrossRefGoogle Scholar
Fullwood, D.T., Niezgoda, S.R., Adams, B.L., Kalidindi, S.R., Prog. Mater Sci. 55 (6), 477 (2010).CrossRefGoogle Scholar
Dong, X., McDowell, D.L., Kalidindi, S.R., Jacob, K.I., Polymer 55, 4248 (2014).Google Scholar
Kalidindi, S.R., Gomberg, J.A., Traut, Z.T., Becker, C.A., Nanotechnology 26 (34), 344006 (2015).Google Scholar
Fast, T., Niezgoda, S.R., Kalidindi, S.R., Acta Mater. 59 (2), 699 (2011).CrossRefGoogle Scholar
Yabansu, Y.C., Kalidindi, S.R., Acta Mater. 94, 26 (2015).CrossRefGoogle Scholar
Fast, T., Kalidindi, S.R., Acta Mater. 59, 4595 (2011).Google Scholar
Kalidindi, S.R., Niezgoda, S.R., Landi, G., Vachhani, S., Fast, A., CMC Comput. Mater. Con. 17 (2), 103 (2010).Google Scholar
Al-Harbi, H.F., Landi, G., Kalidindi, S.R., Model. Simul. Mater. Sci. Eng. 20, 055001 (2012).CrossRefGoogle Scholar
Landi, G., Kalidindi, S.R., CMC Comput. Mater. Con. 16 (3), 273 (2010).Google Scholar
Landi, G., Niezgoda, S.R., Kalidindi, S.R., Acta Mater. 58 (7), 2716 (2010).CrossRefGoogle Scholar
Kalidindi, S.R., ISRN Mater. Sci. 2012, 305692 (2012).Google Scholar
Kröner, E., J. Mech. Phys. Solids 25 (2), 137 (1977).CrossRefGoogle Scholar
Kröner, E., in Modelling Small Deformations of Polycrystals, Gittus, J., Zarka, J., Eds. (Elsevier, London, 1986), pp. 229291.CrossRefGoogle Scholar
Volterra, V., Theory of Functionals and Integral and Integro-Differential Equations (Dover, New York, 1959).Google Scholar
Wiener, N., Nonlinear Problems in Random Theory (MIT Press, Cambridge, MA, 1958).Google Scholar
Cherry, J.A., “Distortion Analysis of Weakly Nonlinear Filters Using Volterra Series,” PhD thesis, Ottawa-Carleton Institute for Electrical Engineering, Department of Electronics, Carleton University, Ontario, Canada (1994).Google Scholar
Wray, J., Green, G., Biol. Cybern. 71 (3), 187 (1994).CrossRefGoogle Scholar
Korenberg, M., Hunter, I., Ann. Biomed. Eng. 24 (2), 250 (1996).Google Scholar
Lee, Y.W., Schetzen, M., Int. J. Control 2 (3), 237 (1965).Google Scholar
Agrawal, A., Deshpande, P.D., Cecen, A., Gautham, B.P., Choudhary, A.N., Kalidindi, S.R., Integr. Mater. Manuf. Innov. 3 (8), 2193-9772-3-8 (2014).CrossRefGoogle Scholar
http://www.nnin.org (accessed June 7, 2015).Google Scholar
McDowell, D.L., Ready, W.J., Morgan, D.D., Kuech, T.F., Allison, J.E., Workshop Report: Building an Integrated Materials Genome Initiative Accelerator Network, Atlanta, June 5–6, 2014, http://acceleratornetwork.org/wp-uploads/2014/09/MAN-MGI-REPORT-2015.pdf (accessed November 16, 2015).Google Scholar
Schmitz, G.J., Prahl, U., Integr. Mater. Manuf. Innov. 3 (1), 2 (2014).Google Scholar
Schmitz, G.J., Prahl, U., Integrative Computational Materials Engineering: Concepts and Applications of a Modular Simulation Platform, 1st ed. (Wiley Online Library, 2012), http://dx.doi.org/10.1002/9783527646098.ch2.CrossRefGoogle Scholar
The European Materials Modeling Council, http://emmc.info/index.html (accessed November 17, 2015).Google Scholar
https://nanohub.org (accessed November 16, 2015).Google Scholar

References

http://cams.mse.ufl.edu (accessed June 7, 2015).Google Scholar

References

https://github.com (accessed June 7, 2015).Google Scholar
https://www.dropbox.com (accessed June 7, 2015).Google Scholar
http://figshare.com (accessed June 7, 2015).Google Scholar
https://plot.ly (accessed June 7, 2015).Google Scholar
http://jekyllrb.com (accessed June 7, 2015).Google Scholar
https://disqus.com (accessed June 7, 2015).Google Scholar
https://plus.google.com (accessed June 7, 2015).Google Scholar