Advertisement

The Penn State-Georgia Tech CCMD: ushering in the ICME Era

  • Zi-Kui Liu
  • David L McDowellEmail author
Case study

Abstract

This case study paper presents the origins, philosophy, organization, development, and contributions of the joint Penn State-Georgia Tech Center for Computational Materials Design (CCMD), a NSF Industry/University Cooperative Research Center (I/UCRC) founded in 2005. As a predecessor of and catalyst for Integrated Computational Materials Engineering (ICME), the CCMD served as a basis for coupling industry, academia, and government in advancing the state of computational materials science and mechanics across a portfolio of process-structure-property-performance relations, with emphasis on education and training of the future workforce in computational materials design.

Keywords

ICME MGI CCMD NSF I/UCRC Materials design Computational materials science 

Notes

Acknowledgements

The authors are grateful for the long-term support of the NSF Industry/University Cooperative Research Center for Computational Materials Design (CCMD), including dues contributions of CCMD members, through grants IIP-0433033 (Penn State), IIP-0541674 (Penn State) and IIP-541678 (Georgia Tech) from 2005–2010, and IIP-1034965 (Penn State) and IIP-1034968 (Georgia Tech) from 2010 to 2013. The authors would like to thank our collaborators at Penn State and Georgia Tech for their enthusiastic and innovative contributions to CCMD projects and meetings over the years, including Co-PIs of the CCMD planning, phase I, and phase II proposals (Long-Qing Chen, Qiang Du, James Kubicki, Evangelos Manias, Padma Raghavan, and Jorge Sofo at Penn State, and Hamid Garmestani, Farrokh Mistree, Richard Neu, and Min Zhou at Georgia Tech), various additional Penn State and Georgia Tech faculty involved in CCMD proposals and projects, and students who conducted research with CCMD support. ZKL also acknowledges Penn State for further reduced overhead rate and Penn State MRI (Materials Research Institute) that provided partial support of the CCMD administrative staff. DLM also acknowledges the support of the Carter N. Paden, Jr. Distinguished Chair in Metals Processing. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the NSF, Penn State, or Georgia Tech.

Supplementary material

40192_2014_28_MOESM1_ESM.gif (26 kb)
Authors’ original file for figure 1
40192_2014_28_MOESM2_ESM.gif (54 kb)
Authors’ original file for figure 2
40192_2014_28_MOESM3_ESM.gif (13 kb)
Authors’ original file for figure 3
40192_2014_28_MOESM4_ESM.gif (31 kb)
Authors’ original file for figure 4
40192_2014_28_MOESM5_ESM.gif (74 kb)
Authors’ original file for figure 5
40192_2014_28_MOESM6_ESM.gif (70 kb)
Authors’ original file for figure 6
40192_2014_28_MOESM7_ESM.gif (33 kb)
Authors’ original file for figure 7
40192_2014_28_MOESM8_ESM.gif (87 kb)
Authors’ original file for figure 8
40192_2014_28_MOESM9_ESM.gif (39 kb)
Authors’ original file for figure 9

References

  1. 1.
    Pollock TM, Allison JE, Backman DG, Boyce MC, Gersh M, Holm EA, LeSar R, Long M, Powell AC IV, Schirra JJ, Whitis DD, Woodward C (2008) Integrated computational materials engineering: a transformational discipline for improved competitiveness and national security. National Materials Advisory Board, NAE, National Academies Press, Washington, DC, ISBN-10: 0–309–11999–5Google Scholar
  2. 2.
    Olson GB: Computational design of hierarchically structured materials. Science 1997, 277: 1237–1242. 10.1126/science.277.5330.1237CrossRefGoogle Scholar
  3. 3.
    McDowell DL, Story TL (1998) New directions in materials design science and engineering (MDS&E). Report of a NSF DMR-sponsored workshop held at Georgia Tech, October 19–21, , accessed December 2, 2014 http://www.me.gatech.edu/paden/material-design/md_se.pdf
  4. 4.
    Liu ZK, Chen LQ, Spear KE, Pollard C (2003) An integrated education program on computational thermodynamics, kinetics, and materials design, an article from the Dec. 2003 JOM-e, a Web-Only Supplement to JOM, TMS. . Accessed December 2, 2014 http://www.tms.org/pubs/journals/JOM/0312/LiuII/LiuII-0312.html
  5. 5.
    Liu ZK, Chen LQ, Raghavan P, Du Q, Sofo JO, Langer SA, Wolverton C: An integrated framework for multi-scale materials simulation and design. J Comput Aided Mater Des 2004, 11(2–3):183–199. 10.1007/s10820-005-3173-2CrossRefGoogle Scholar
  6. 6.
    Liu ZK: First principles calculations and Calphad modeling of thermodynamics. J Phase Equilib Diffus 2009, 30: 517–534. 10.1007/s11669-009-9570-6CrossRefGoogle Scholar
  7. 7.
    Liu ZK: A materials research paradigm driven by computation. JOM 2009, 61(10):18–20. 10.1007/s11837-009-0143-2CrossRefGoogle Scholar
  8. 8.
    McDowell DL: Simulation-assisted materials design for the concurrent design of materials and products. JOM 2007, 59: 21–25. 10.1007/s11837-007-0111-7CrossRefGoogle Scholar
  9. 9.
    McDowell DL, Olson GB: Concurrent design of hierarchical materials and structures. Sci Model Simul 2008, 15: 207–240. 10.1007/s10820-008-9100-6CrossRefGoogle Scholar
  10. 10.
    McDowell DL, Panchal JH, Choi HJ, Seepersad CC, Allen JK, Mistree F: Integrated design of multiscale, multifunctional materials and products. 1st edition. Elsevier, Oxford; 2009.Google Scholar
  11. 11.
    Apelian D, Alleyne A, Handwerker CA, Hopkins D, Isaacs JA, Olson GB, Vidyanathan R, Wolf SD (2004) Accelerating technology transition: bridging the valley of death for materials and processes in defense systems. National Materials Advisory Board, NAE, National Academies Press, Washington, DC, ISBN-10: 0–309–09317–1Google Scholar
  12. 12.
    Allison J, Backman D, Christodoulou L: Integrated computational materials engineering: a new paradigm for the global materials profession. JOM 2006, 58: 25–27. 10.1007/s11837-006-0223-5CrossRefGoogle Scholar
  13. 13.
    McDowell DL, Backman D: Simulation-assisted design and accelerated insertion of materials, Ch. 19. In Computational methods for microstructure-property relationships. Edited by: Ghosh S, Dimiduk D. Springer, New York; 2010.Google Scholar
  14. 14.
    (2011) The materials genome initiative for global competitiveness, office of science and technology policy. National Science and Technology Council, , accessed December 2, 2014 http://www.whitehouse.gov/sites/default/files/microsites/ostp/materials_genome_initiative-final.pdf
  15. 15.
    Liu ZK, McDowell DL: Center for computational materials design (CCMD) and its education vision. TMS MS&T, Cincinnati, OH; 2006.Google Scholar
  16. 16.
    McDowell DL: Simulation and robust design of materials. TMS MS&T, Cincinnati, OH; 2006.Google Scholar
  17. 17.
    McDowell DL, Mistree F, Allen JK: Prospects and challenges for materials design. Mechanics and materials modeling and materials design methodologies, symposium in honor of Dr. Craig Hartley's 40 years of contributions to the field of mechanics and materials science. TMS Annual Meeting & Exhibition, Orlando, FL; 2007.Google Scholar
  18. 18.
    Liu ZK (2007) Integrating forward simulation and inverse design of materials. TMS webcast, http://iweb.tms.org/forum/messageview.aspx?catid=97%threadid=1094%enterthread=y
  19. 19.
    Liu ZK: Properties of individual phases by first-principles calculations and CALPHAD modeling. Eastern New York ASM/TMS Annual Symposium. Computational Materials Design, GE Global Research Center, Niskayuna, NY; 2007.Google Scholar
  20. 20.
    McDowell DL: Multiscale modeling and materials design. TMS 2008 9th Global Innovations Symposium on Trends in ICME, New Orleans, LA; 2008.Google Scholar
  21. 21.
    McDowell DL (2008) Multiscale modeling in multilevel materials design. Kickoff lecture, symposium on computational materials design via multiscale modeling. Session on New Approaches Toward Multiscale Materials Design, MRS Fall Meeting, Boston, MAMcDowell DL (2010) Robust materials design and multiscale simulation: distinct but complementary pursuits. Tools, models, databases and simulation tools developed and needed to realize the vision of ICME: material model and simulation tools, part II. MS&T, Houston, TXGoogle Scholar
  22. 22.
    McDowell DL: Some comments on materials design education. MS&T, Pittsburgh, OH; 2009.Google Scholar
  23. 23.
    Liu ZK, McDowell DL: Materials research paradigm driven by computation. MS&T, Pittsburgh, OH; 2009.CrossRefGoogle Scholar
  24. 24.
    McDowell DL (2010) Robust materials design and multiscale simulation: distinct but complementary pursuits. Tools, models, databases and simulation tools developed and needed to realize the vision of ICME: material model and simulation tools, part II. MS&T, Houston, TXGoogle Scholar
  25. 25.
    McDowell DL (2011) Critical path issues in ICME. Models, databases, and simulation tools needed for the realization of integrated computational materials engineering, Proc. Symposium held at MS&T 2010, Houston, Tx, S.M. Arnold and T.T. Wong, eds., ASM International, 31-37Google Scholar
  26. 26.
    Liu ZK: Materials genome: building blocks of materials. TMS Annual Meeting, Orlando, FL; 2012.Google Scholar
  27. 27.
    McDowell DL: Simulation-based strategies to support alloy design for fatigue resistance. Symposium on Integrative Materials Design: Performance and Sustainability. TMS Annual Meeting, Orlando, FL; 2012.Google Scholar
  28. 28.
    McDowell DL: Modeling inelastic behavior of metals at multiple scales to support materials design. MS&T ’13, Montreal, Quebec, Canada; 2013.Google Scholar
  29. 29.
    Panchal JH, Kalidindi SR, McDowell DL: Key computational modeling issues in ICME. Comput Aided Des 2013, 45(1):4–25. 10.1016/j.cad.2012.06.006CrossRefGoogle Scholar
  30. 30.
    Liu ZK: Perspective on Materials Genome®. Chin Sci Bull 2014, 59(15):1619–1623. 10.1007/s11434-013-0072-xCrossRefGoogle Scholar
  31. 31.
    Campbell EC, Kattner RU, Liu ZK: The development of phase-based property data using the CALPHAD method and infrastructure needs. Integrating Materials and Manufacturing Innovation 2014, 3: 12. 10.1186/2193-9772-3-12CrossRefGoogle Scholar
  32. 32.
    Shang SL, Wang Y, Liu ZK (2010) ESPEI: extensible, self-optimizing phase equilibrium infrastructure for magnesium alloys. In: Agnew SR, Neelameggham NR, Nyberg EA, Sillekens WH (eds) Magnesium technology 2010, Seattle. WA, Minerals, Metals and Materials Society/AIME, 184 Thorn Hill Road, Warrendale, PA, pp 617–622Google Scholar

Copyright information

© Liu and McDowell; licensee Springer. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0), which permits use, duplication, adaptation, distribution, and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.Department of Materials Science and EngineeringThe Pennsylvania State University, University ParkPennsylvaniaUSA
  2. 2.Woodruff School of Mechanical EngineeringSchool of Materials Science and Engineering, Georgia Institute of TechnologyAtlantaUSA

Personalised recommendations