DOI QR코드

DOI QR Code

Material Design Using Multi-physics Simulation: Theory and Methodology

다중물리 전산모사를 이용한 물성 최적화 이론 및 시뮬레이션

  • Hyun, Sangil (Nano IT Materials Lab, Advanced Materials Convergence Division, Korea Institute of Ceramic Engineering and Technology)
  • 현상일 (한국세라믹기술원 기초소재융합본부 나노IT소재팀)
  • Received : 2014.10.13
  • Accepted : 2014.11.21
  • Published : 2014.12.01

Abstract

New material design has obtained tremendous attention in material science community as the performance of new materials, especially in nano length scale, could be greatly improved to applied in modern industry. In certain conditions limiting experimental synthesis of these new materials, new approach by computer simulation has been proposed to be applied, being able to save time and cost. Recent development of computer systems with high speed, large memory, and parallel algorithms enables to analyze individual atoms using first principle calculation to predict quantum phenomena. Beyond the quantum level calculations, mesoscopic scale and continuum limit can be addressed either individually or together as a multi-scale approach. In this article, we introduced current endeavors on material design using analytical theory and computer simulations in multi-length scales and on multi-physical properties. Some of the physical phenomena was shown to be interconnected via a cross-link rule called 'cross-property relation'. It is suggested that the computer simulation approach by multi-physics analysis can be efficiently applied to design new materials for multi-functional characteristics.

Keywords

References

  1. S. Torquato, Random Heterogeneous Materials: Microstructure and Macroscopic Properties (Springer-Verlag, New York, 2002).
  2. S. Iijiima, Nature, 354, 56 (1991). https://doi.org/10.1038/354056a0
  3. Y. S. Min, E. J. Bae, U. J. Kim, E. H. Lee, N. J. Park, C. S. Hwang, and W. J. Park, Appl. Phys. Lett., 93, 043113 (2008) https://doi.org/10.1063/1.2965805
  4. A. K. Geim and K. S. Novoselov, Nature, 6, 183 (2007). https://doi.org/10.1038/nmat1849
  5. S. H. Huh and S. I. Hyun, Carbon, 48, 3635 (2010). https://doi.org/10.1016/j.carbon.2010.05.021
  6. M. Allen and D.J. Tildesley, Computer Simulation of Liquids (Clarendon, Oxford, 1987).
  7. S. J. Plimpton, J. Comput. Phys., 117, 1 (1995): LAMMPS (http://lammps.sandia.gov/).
  8. P. A. Thompson and S. M. Troian, Nature, 389, 360 (1997). https://doi.org/10.1038/38686
  9. S. I. Hyun and E. H. Koo, J. Appl. Phys., 113, 074301 (2013). https://doi.org/10.1063/1.4790570
  10. W. Kohn and L. J. Sham, Phys. Rev., 140, A1133 (1965). https://doi.org/10.1103/PhysRev.140.A1133
  11. D. Cohen, Phys. Rev. B, 68, 15 (2003).
  12. Materials Studio, Accelrys Inc.
  13. H. P. Vowles, Isis, 17, 412 (1932). https://doi.org/10.1086/346662
  14. N. Bohr, J. de Physique et le Radium, 2, 361 (1921). https://doi.org/10.1051/jphysrad:01921002012036100
  15. L.S.I. Liyanage, S. Kim, Y. K. Hong, J. H. Park, S. C. Erwin, and S. G. Kim, J. Mag. Mag. Mat., 348, 75 (2013). https://doi.org/10.1016/j.jmmm.2013.08.006
  16. VASP (http://www.vasp.at/).
  17. Z. Hashin and Shtrikman, J. Appl. Phys., 33, 3125 (1962). https://doi.org/10.1063/1.1728579
  18. G. W. Milton, in Homogenization and Effective Moduli of Materials and Media, ed. by J. L. Eriksen, D. Kinderlehrer, R. Kohn, and J. L. Lions (Springer, New York, 1986).
  19. D. J. Bergman, Phys. Rep., 43, 377 (1978) https://doi.org/10.1016/0370-1573(78)90009-1
  20. G. W. Milton, J. Appl. Phys., 52, 5294 (1981). https://doi.org/10.1063/1.329386
  21. S. Vigdergauz, Int. J. Solids Struct., 38, 8593 (2001). https://doi.org/10.1016/S0020-7683(01)00189-5
  22. S. Hyun and S. Torquato, J. Mater. Res., 16, 280 (2001). https://doi.org/10.1557/JMR.2001.0042
  23. A. G. Evans, J. W. Hutchinson, N. A. Fleck, M. F. Ashby, and H.N.G. Wadley, Prog. Mater. Sci., 46, 309 (2001). https://doi.org/10.1016/S0079-6425(00)00016-5
  24. L. V. Gibiansky and S. Torquato, Phys. Rev. Lett., 71, 2927 (1993). https://doi.org/10.1103/PhysRevLett.71.2927
  25. S. Torquato, S. Hyun, and A. Donev, Phys. Rev. Lett., 89, 266601 (2002). https://doi.org/10.1103/PhysRevLett.89.266601
  26. E. B. Tadmor, M. Ortiz, and R. Phillips, Mag. A, 73, 1529 (1996). https://doi.org/10.1080/01418619608243000
  27. J. Q. Broughton, F. F. Abraham, N. Bernstein, and E. Kaxiras, Phys. Rev. B 60, 2391 (1999). https://doi.org/10.1103/PhysRevB.60.2391
  28. B. Q. Luan, S. Hyun, J. F. Molinari, N. Bernstein, and M. Robbins, Phys. Rev. E, 74, 046710 (2006). https://doi.org/10.1103/PhysRevE.74.046710
  29. M. P. Bendsoe and O. Sigmund, Topology Optimization: Theory, Methods, and Applications (Springer, New York, 2003).
  30. COSMOL Inc. (http://www.comsol.com).
  31. ANSYS Inc. (http://www.ansys.com).
  32. DASSAULT Systems (http://www.3ds.com).