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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.
Hide All1.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).2.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).3.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).4.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, 2015.5.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).6.McDowell, D.L., Nature 503, 463 (2013).7.http://www.materials.gatech.edu (accessed February 8, 2016).8.https://www.hdfgroup.org/HDF5/doc/H5.intro.html (accessed November 17, 2015).9.Carrete, J., Li, W., Mingo, N., Wang, S., Curtarolo, S., Phys. Rev. X 4 (1), 011019 (2014).10.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).11.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).12.Olson, G.B., Science 277, 1237 (1997).13.McDowell, D.L., JOM 59 (9), 21 (2007).14.McDowell, D.L., Olson, G.B., Sci. Model. Simul. 15, 207 (2008).15.Panchal, J.H., Kalidindi, S.R., McDowell, D.L., Comput. Aided Des. 45 (1), 4 (2013).16.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, 2011.17.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).18.Choi, H.-J., McDowell, D.L., Allen, J.K., Mistree, F., Eng. Optim. 40 (4), 287 (2008).19.Taguchi, G., Taguchi on Robust Technology Development: Bringing Quality Engineering Upstream (ASME Press, New York, 1993).20.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).21.Seepersad, C.C., Kumar, R.S., Allen, J.K., Mistree, F., McDowell, D.L., J. Comput. Aided Mater. Des. 11 (2–3), 163 (2005).22.Seepersad, C.C., Allen, J.K., McDowell, D.L., Mistree, F., J. Mech. Des. 130 (3), 031404-1-13 (2008).23.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).24.Rajan, K., Informatics for Materials Science and Engineering, Data-Driven Discovery for Accelerated Experimentation and Application, 1st ed. (Butterworth-Heinemann, Oxford, UK, 2013).25.Rajan, K., Annu. Rev. Mater. Res. 45, 153 (2015).26.Curtarolo, S., Hart, G.L., Nardelli, M.B., Mingo, N., Sanvito, S., Levy, O., Nat. Mater. 12 (3), 191 (2013).27.Ghiringhelli, L.M., Vybiral, J., Levchenko, S.V., Draxl, C., Scheffler, M., Phys. Rev. Lett. 114 (10), 105503 (2015).28.Hall, E.O., Proc. Phys. Soc. Lond. B 64 (9), 742 (1951).29.Petch, N.J., J. Iron Steel Inst. 174, 25–28 (1953).30.Niezgoda, S.R., Yabansu, Y.C., Kalidindi, S.R., Acta Mater. 59, 6387 (2011).31.Niezgoda, S.R., Kanjarla, A.K., Kalidindi, S.R., Integr. Mater. Manuf. Innov. 2, 3 (2013).32.Niezgoda, S.R., Turner, D.M., Fullwood, D.T., Kalidindi, S.R., Acta Mater. 58, 4432 (2010).33.Kalidindi, S.R., Hierarchical Materials Informatics, 1st ed. (Butterworth-Heinemann, Oxford, UK, 2015).34.Kalidindi, S.R., Int. Mater. Rev. 60 (3), 150 (2015).35.Kalidindi, S.R., Niezgoda, S.R., Salem, A.A., JOM 63 (4), 34 (2011).36.Fullwood, D.T., Niezgoda, S.R., Adams, B.L., Kalidindi, S.R., Prog. Mater Sci. 55 (6), 477 (2010).37.Dong, X., McDowell, D.L., Kalidindi, S.R., Jacob, K.I., Polymer 55, 4248 (2014).38.Kalidindi, S.R., Gomberg, J.A., Traut, Z.T., Becker, C.A., Nanotechnology 26 (34), 344006 (2015).39.Fast, T., Niezgoda, S.R., Kalidindi, S.R., Acta Mater. 59 (2), 699 (2011).40.Yabansu, Y.C., Kalidindi, S.R., Acta Mater. 94, 26 (2015).41.Fast, T., Kalidindi, S.R., Acta Mater. 59, 4595 (2011).42.Kalidindi, S.R., Niezgoda, S.R., Landi, G., Vachhani, S., Fast, A., CMC Comput. Mater. Con. 17 (2), 103 (2010).43.Al-Harbi, H.F., Landi, G., Kalidindi, S.R., Model. Simul. Mater. Sci. Eng. 20, 055001 (2012).44.Landi, G., Kalidindi, S.R., CMC Comput. Mater. Con. 16 (3), 273 (2010).45.Landi, G., Niezgoda, S.R., Kalidindi, S.R., Acta Mater. 58 (7), 2716 (2010).46.Kalidindi, S.R., ISRN Mater. Sci. 2012, 305692 (2012).47.Kröner, E., J. Mech. Phys. Solids 25 (2), 137 (1977).48.Kröner, E., in Modelling Small Deformations of Polycrystals, Gittus, J., Zarka, J., Eds. (Elsevier, London, 1986), pp. 229–291.49.Volterra, V., Theory of Functionals and Integral and Integro-Differential Equations (Dover, New York, 1959).50.Wiener, N., Nonlinear Problems in Random Theory (MIT Press, Cambridge, MA, 1958).51.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).52.Wray, J., Green, G., Biol. Cybern. 71 (3), 187 (1994).53.Korenberg, M., Hunter, I., Ann. Biomed. Eng. 24 (2), 250 (1996).54.Lee, Y.W., Schetzen, M., Int. J. Control 2 (3), 237 (1965).55.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).56.http://www.nnin.org (accessed June 7, 2015).57.http://acceleratornetwork.org (accessed June 7, 2015).58.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).59.Schmitz, G.J., Prahl, U., Integr. Mater. Manuf. Innov. 3 (1), 2 (2014).60.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.ch2.61.The European Materials Modeling Council, http://emmc.info/index.html (accessed November 17, 2015).62.https://www.materialsproject.org (accessed June 7, 2015).63.https://openkim.org/about (accessed June 7, 2015).64.http://chimad.northwestern.edu (accessed June 7, 2015).65.http://prisms.engin.umich.edu/#/prisms (accessed June 7, 2015).66.https://materialsdata.nist.gov/dspace/xmlui (accessed November 16, 2015).67.http://www.citrine.io/#citrineinformatics (accessed November 16, 2015).68.https://nanohub.org (accessed November 16, 2015).69.http://www.nationaldataservice.org/projects/mdf.html (accessed November 16, 2015).70.http://nomad-repository.eu/cms/index.php?page=other-repositories (accessed November 16, 2015).71.http://www.nims.go.jp/eng/infrastructure/materials-data/index.html (accessed November 16, 2015).1.http://www.icams.de/content/master-course-mss (accessed June 7, 2015).2.https://icme.hpc.msstate.edu/mediawiki/index.php/Mississippi_State_University (accessed June 7, 2015).3.http://www.mccormick.northwestern.edu/materials-science/documents/graduate/icme-brochure.pdf (accessed November 16, 2015).4.http://www.flamel.gatech.edu (accessed June 7, 2015).5.http://engineering.tamu.edu/news/2015/08/03/texas-am-hosts-fourth-iimec-summer-school-on-computational-materials-science-across-scales (accessed November 16, 2015).6.http://icmed.engin.umich.edu (accessed June 7, 2015).7.https://www-pls.llnl.gov/?url=jobs_and_internships-internships-ccms (accessed June 7, 2015).8.http://cams.mse.ufl.edu (accessed June 7, 2015).1.http://www.flamel.gatech.edu (accessed June 7, 2015).2.https://github.com (accessed June 7, 2015).3.https://www.dropbox.com (accessed June 7, 2015).4.https://www.sharelatex.com (accessed June 7, 2015).5.https://www.authorea.com (accessed June 7, 2015).6.http://figshare.com (accessed June 7, 2015).7.https://plot.ly (accessed June 7, 2015).8.http://jekyllrb.com (accessed June 7, 2015).9.https://disqus.com (accessed June 7, 2015).10.https://plus.google.com (accessed June 7, 2015).11.https://www.linkedin.com/nhome (accessed June 7, 2015).12.http://materials-informatics-class-fall2014.github.io (accessed February 8, 2016).
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