Advertisement

Abstract

A working definition of molecular dynamics (MD) simulation is technique by which one generates the atomic trajectories of a system of N particles by numerical integration of Newton’s equation of motion, for a specific interatomic potential, with certain initial condition (IC) and boundary condition (BC).

Keywords

Global Error Unit System Jones Potential Local Truncation Error Symplectic Integrator 
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]
    M. Allen and D. Tildesley, Computer Simulation of Liquids, Clarendon Press, New York, 1987.MATHGoogle Scholar
  2. [2]
    J. Li, L. Porter, and S. Yip, “Atomistic modeling of finite-temperature properties of crystalline beta-SiC — II. Thermal conductivity and effects of point defects,” J. Nucl. Mater., 255, 139–152, 1998.CrossRefADSGoogle Scholar
  3. [3]
    J. Li, “AtomEye: an efficient atomistic configuration viewer,” Model. Simul. Mater. Sci. Eng., 11, 173–177, 2003.MATHCrossRefADSGoogle Scholar
  4. [4]
    D. Chandler, Introduction to Modern Statistical Mechanics, Oxford University Press, New York, 1987.Google Scholar
  5. [5]
    M. Born and K. Huang, Dynamical Theory of Crystal Lattices, 2nd edn., Clarendon Press, Oxford, 1954.MATHGoogle Scholar
  6. [6]
    R. Parr and W. Yang, Density-functional Theory of Atoms and Molecules, Clarendon Press, Oxford, 1989.Google Scholar
  7. [7]
    S.D. Ivanov, A.P. Lyubartsev, and A. Laaksonen, “Bead-Fourier path integral molec-ular dynamics,” Phys. Rev. E, 67, art. no.-066710, 2003.Google Scholar
  8. [8]
    T. Schlick, Molecular Modeling and Simulation, Springer, Berlin, 2002.MATHGoogle Scholar
  9. [9]
    W. Press, B. Flannery, S. Teukolsky, and W. Vetterling, Numerical Recipes in C: the Art of Scientific Computing, 2nd edn., Cambridge University Press, Cambridge, 1992.Google Scholar
  10. [10]
    C. Gear, Numerical Initial Value Problems in Ordinary Differential Equation, Prentice-Hall, Englewood Cliffs, NJ 1971.Google Scholar
  11. [11]
    M.E. Tuckerman and G.J. Martyna, “Understanding modern molecular dynamics: techniques and applications,” J. Phys. Chem. B, 104, 159–178, 2000.CrossRefGoogle Scholar
  12. [12]
    S. Nose, “A unified formulation of the constant temperature molecular dynamics methods,” J. Chem. Phys., 81, 511–519, 1984.CrossRefADSGoogle Scholar
  13. [13]
    W.G. Hoover, “Canonical dynamics — equilibrium phase-space distributions,” Phys. Rev. A, 31, 1695–1697, 1985.CrossRefADSGoogle Scholar
  14. [14]
    D. Beeman, “Some multistep methods for use in molecular-dynamics calculations,” J. Comput. Phys., 20, 130–139, 1976.CrossRefADSGoogle Scholar
  15. [15]
    L. Verlet, “Computer “experiments” on classical fluids. I. Thermodynamical proper-ties of Lennard-Jones molecules,” Phys. Rev., 159, 98–103, 1967.CrossRefADSGoogle Scholar
  16. [16]
    H. Yoshida, “Construction of higher-order symplectic integrators,” Phys. Lett. A, 150, 262–268, 1990.CrossRefMathSciNetADSGoogle Scholar
  17. [17]
    J. Sanz-Serna and M. Calvo, Numerical Hamiltonian Problems, Chapman & Hall, London, 1994.MATHGoogle Scholar
  18. [18]
    S. Plimpton, “Fast parallel algorithms for short-range molecular-dynamics,” J. Com-put. Phys., 117, 1–19, 1995.MATHCrossRefADSGoogle Scholar
  19. [19]
    W. Smith and T.R. Forester, “DL_POLY_2.0: a general-purpose parallel molecular dynamics simulation package,” J. Mol. Graph., 14, 136–141, 1996.CrossRefGoogle Scholar
  20. [20]
    W. Smith, C.W. Yong, and P.M. Rodger, “DL_POLY: application to molecular simu-lation,” Mol. Simul., 28, 385–471, 2002.MATHCrossRefGoogle Scholar
  21. [21]
    K. Refson, “Moldy: a portable molecular dynamics simulation program for serial and parallel computers,” Comput. Phys. Commun., 126, 310–329, 2000.MATHCrossRefADSGoogle Scholar
  22. [22]
    M.T. Nelson, W. Humphrey, A. Gursoy, A. Dalke, L.V. Kale, R.D. Skeel, and K. Schulten, “NAMD: a parallel, object oriented molecular dynamics program,” Int. J. Supercomput. Appl. High Perform. Comput, 10, 251–268, 1996.CrossRefGoogle Scholar
  23. [23]
    L. Kale, R. Skeel, M. Bhandarkar, R. Brunner, A. Gursoy, N. Krawetz, J. Phillips, A. Shinozaki, K. Varadarajan, and K. Schulten, “NAMD2: Greater scalability for parallel molecular dynamics,” J. Comput. Phys., 151, 283–312, 1999.MATHCrossRefADSGoogle Scholar
  24. [24]
    H.J.C. Berendsen, D. Vanderspoel, and R. Vandrunen, “Gromacs — a message-passing parallel molecular-dynamics implementation,” Comput. Phys. Commun., 91, 43–56, 1995.CrossRefADSGoogle Scholar
  25. [25]
    E. Lindahl, B. Hess, and D. van der Spoel, “GROMACS 3.0: apackage for molecular simulation and trajectory analysis,” J. Mol. Model., 7, 306–317, 2001.Google Scholar
  26. [26]
    B.R. Brooks, R.E. Bruccoleri, B.D. Olafson, D.J. States, S. Swaminathan, and M. Karplus, “Charmm — a program for macromolecular energy, minimization, and dynamics calculations,” J. Comput. Chem., 4, 187–217, 1983.CrossRefGoogle Scholar
  27. [27]
    D.A. Pearlman, D.A. Case, J.W. Caldwell, W.S. Ross, T.E. Cheatham, S. Debolt, D. Ferguson, G. Seibel, and P. Kollman, “Amber, a package of computer-programs for applying molecular mechanics, normal-mode analysis, molecular-dynamics and freeenergy calculations to simulate the structural and energetic properties of molecules,” Comput. Phys. Commun., 91, 1–41, 1995.MATHCrossRefADSGoogle Scholar

Copyright information

© Springer 2005

Authors and Affiliations

  • Ju Li
    • 1
  1. 1.Department of Materials Science and EngineeringOhio State UniversityColumbusUSA

Personalised recommendations