Molecular dynamics on the diffusive time scale

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Molecular dynamics on the diffusive time scale

  • Date: Dec 14, 2018
  • Time: 15:00 - 16:30
  • Speaker: Prof. Michael Ortiz
  • Frank and Ora-Lee Marble Professor of Aeronautics and Mechanical Engineering California Institute of Technology
  • Location: Max-Planck-Institut für Eisenforschung GmbH
  • Room: Seminarraum 1
  • Host: Prof. Dierk Raabe
We formulate a theory of non-equilibrium statistical thermodynamics for ensembles of atoms or molecules. The theory is an application of Jayne's maximum entropy principle, which allows the statistical treatment of systems away from equilibrium. In particular, neither temperature nor atomic fractions are required to be uniform but instead are allowed to take different values from particle to particle. In addition, following the Coleman-Noll method of continuum thermodynamics we derive a dissipation inequality expressed in terms of discrete thermodynamic fluxes and forces. This discrete dissipation inequality effectively sets the structure for discrete kinetic potentials that couple the microscopic field rates to the corresponding driving forces, thus resulting in a closed set of equations governing the evolution of the system. We complement the general theory with a variational meanfield theory that provides a basis for the formulation of computationally tractable approximations. We present several validation cases, concerned with equilibrium properties of alloys, heat conduction in silicon nanowires, hydrogen desorption from palladium thin films and segregation/precipitation in alloys, that demonstrate the range and scope of the method and assess its fidelity and predictiveness. These validation cases are characterized by the need or desirability to account for atomic-level properties while simultaneously entailing time scales much longer than those accessible to direct molecular dynamics. The ability of simple meanfield models and discrete kinetic laws to reproduce equilibrium properties and long-term behavior of complex systems is remarkable.
 
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