Advertisement

Atomistic Methods for Structure-Property Correlations

  • Sidney Yip

Abstract

There is a general belief that physical properties of crystals can be classified, to a first approximation, according to its structure. The basis of this thinking is that there is close correlation between structure and the chemical bonding between atoms which in turn controls the properties [1]. Although it is not guaranteed to be always successful, this can be a good starting point toward the understanding of materials properties and behavior. In this section we discuss the use of atomistic techniques to study interfaces, primarily grain boundaries, in the context of structure-property correlation. As we will see, these methods are a subset of the multiscale techniques treated extensively in Chapters 1–4. Using grain boundary as a prototypical crystal defect, we examine how atomistic simulation techniques can be brought together to determine the physical properties of crystalline materials with well-characterized defect microstructure. This section also serves as an introduction to the subsequent sections which are concerned, in one way or another, with probing the structure and associated properties of grain boundaries.

Keywords

Monte Carlo Property Correlation Intergranular Fracture Interface Plane Mean Square Displacement 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    C. Kittel, Introduction to Solid State Physics, 3rd edn., John Wiley & Sons, New York, 1966.Google Scholar
  2. [2]
    S. Yip and D. Wolf, “Atomistic concepts for simulation of grain boundary fracture”, Mater. Sci. Forum, 46, 77–168, 1989.CrossRefGoogle Scholar
  3. [3]
    J.F. Lutsko, D. Wolf, S. Yip, S.R. Phillpot, and T. Nguyen, “Molecular-dynamics method for the simulation of bulk-solid interfaces at high temperatures”, Phys. Rev. B, 38, 11572–11581, 1988.CrossRefADSGoogle Scholar
  4. [4]
    J.R. Beeler, In: H. Herman (ed.), Advances in Materials Research, 5, Wiley, New York, p. 295, 1970.Google Scholar
  5. [5]
    A.A. Maradudin, E.W. Montroll, G.H. Weiss, and I. Ipatova, Theory of Lattice Dynamics in the Harmonic Approximation, Academic, New York, 1971.Google Scholar
  6. [6]
    D.C. Wallace, Thermodynamics of Crystals, Wiley, New York, 1972.Google Scholar
  7. [7]
    M.P. Allen and D.J. Tildesley, Computer Simulation of Liquids, Clarendon, Oxford, 1987.MATHGoogle Scholar
  8. [8]
    M. Parrinello and A. Rahman, “Polymorphic transitions in single crystals: a new molecular dynamics method”, J. Appl. Phys., 52, 7182–7190, 1981.CrossRefADSGoogle Scholar
  9. [9]
    S.R. Phillpot, D. Wolf, and S. Yip, “Effects of atomic-level disorder at solid interfaces”, MRS Bull., XV, pp. 38–45, 1990.Google Scholar
  10. [10]
    G.H. Bishop, R.J. Harrison, T. Kwok, and S. Yip, “Simulation of grain boundaries at elevated temperature by computer molecular dynamics”, In: J.W. Christian, P. Haasen, T.B. Massalski (eds.), Progress in Materials Science, Chalmers Anniversary Volume, Pergamon, Oxford, pp. 49–95, 1981.Google Scholar
  11. [11]
    R. Najafabadi and S. Yip, Scripta Metall., 18, 159, 1984.CrossRefGoogle Scholar
  12. [12]
    R.W. Balluffi, Metall. Trans. B, 13, 527, 1982, L. Peterson, Int. Metall. Rev., 28, 66, 1983.CrossRefADSGoogle Scholar
  13. [13]
    G. Ciccotti, M. Guillope, and V. Pontikis, Phys. Rev. B, 27, 5576, 1983.CrossRefADSGoogle Scholar
  14. [14]
    C. Nitta, “Computer simulation study of grain boundary diffusion in aluminum and aluminum-copper systems”, PhD Thesis, MIT, 1986.Google Scholar
  15. [15]
    T. Kwok, P.S. Ho, and S. Yip, “Molecular-dynamics studies of grain-boundary diffusion, II. Vacancy migration, diffusion mechanism, and kinetics”, Phys. Rev. B, 29, 5363–5371, 1984.CrossRefADSGoogle Scholar
  16. [16]
    M.P. Seah, J. Phys., F10, 1043, 1985.ADSGoogle Scholar
  17. [17]
    J. Ray, “Elastic constants and statistical ensembles in molecular dynamics”, Comput. Phys. Rep., 8, 109–151, 1988.CrossRefADSGoogle Scholar
  18. [18]
    S. Foiles, Phys. Rev. B, 32, 7685, 1985.CrossRefADSGoogle Scholar
  19. [19]
    S. Foiles and D. Seidman, “Solute-atom segregation at internal interfaces”, MRS Bull., XV, pp. 51–57, 1990.Google Scholar
  20. [20]
    M.C. Flemings and S. Suresh, “Materials education for the new century”, MRS Bull., November, 918–924, 2001.Google Scholar
  21. [21]
    W.G. Hoover and B.J. Alder, “Studies in molecular dynamics. IV The pressure, collision rate, and their number dependence for hard disks”, J. Chem. Phys., 46, 686–691, 1967.CrossRefADSGoogle Scholar
  22. [22]
    H. Gleiter and B. Chalmers, Progr. Mater. Sci., 16, 77, 1972.CrossRefGoogle Scholar
  23. [23]
    K. Binder, Applications of the Monte Carlo Methods in Statistical Phys. (Springer Verlag, Berlin, 1979).Google Scholar

Copyright information

© Springer 2005

Authors and Affiliations

  • Sidney Yip
    • 1
  1. 1.Department of Nuclear Science and EngineeringMassachusetts Institute of TechnologyCambridgeUSA

Personalised recommendations