The Vibrational Stiffness of an Atomic Lattice

Abstract

A static atomic model is described, which may be employed to evaluate the characteristic vibrational stiffness of an atomic lattice, given the pairwise potential of the constituent atom. Because the vibrational stiffness is directly related to the resultant vibrational frequency spectrum of the lattice, the method may be used to infer the behavior of the characteristic lattice frequency as a function of lattice spacing. The characteristic frequency behavior is sufficient to determine the Grueneisen function, an important thermodynamic parameter relating to thermal behavior of a crystal lattice. The current method computes and utilizes several spring constants derived from a static lattice in order to infer the characteristic vibrational behavior. No atomic dynamics calculations involving either the equations of motion or modal (vibrational) analysis are required. As such, the method generally requires mere seconds of computation on today's generation of desktop workstations. Results indicate that the vibrational stiffness of the lattice is qualitatively distinct from the volumetric stiffness of the lattice, and, furthermore, that the resulting lattice behavior can be described, over a wide region of lattice spacing, by an analytical equation of state in terms of lattice frequency.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1998
Accession Number
ADA353163

Entities

People

  • Steven B. Segletes

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Weapons Technologies

DTIC Thesaurus Topics

  • Crystal Lattice Vibrations
  • Crystal Lattices
  • Crystal Structure
  • Crystals
  • Cubic Lattices
  • Dynamics
  • Equations
  • Equations Of Motion
  • Frequency
  • Jet Propulsion
  • Materials
  • Materials Science
  • Mechanical Engineering
  • Physics
  • Physics Laboratories
  • Spectra
  • Vibrational Spectra

Fields of Study

  • Engineering

Readers

  • Computational Modeling and Simulation
  • Materials Science and Engineering.
  • Structural Dynamics.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Space