Computational Tools to Understand Inelastic and Quasielastic Neutron Scattering Data

  • Mark R. JohnsonEmail author
  • Miguel A. González
  • Mohamed Zbiri
  • Eric Pellegrini
Part of the Neutron Scattering Applications and Techniques book series (NEUSCATT)


The availability of user-friendly software and affordable multi-processor computers opens the door to the world of simulations to experimentalists, for “advanced data analysis”. Neutron scattering (NS), which explores length and time scales and probes the relative positions and motions of atoms as in simulations, constitutes the ideal partner for atomistic simulations. On the experimental side, the ever-increasing complexity of samples and therefore data requires more elaborate and realistic models. This chapter therefore describes, in practical terms, the simulation methods that can be used to interpret quasielastic and inelastic NS data, namely molecular dynamics and lattice dynamics. Both of these methods are based on the knowledge of inter-atomic interactions and total energy for which density functional theory and classical, force field-based methods are presented as the most viable.


Molecular Dynamic Density Functional Theory Molecular Dynamic Simulation Potential Energy Surface Lattice Dynamic 
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.


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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Mark R. Johnson
    • 1
    Email author
  • Miguel A. González
    • 1
  • Mohamed Zbiri
    • 1
  • Eric Pellegrini
    • 1
  1. 1.Institut Laue LangevinGrenobleFrance

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