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Diffusional anomaly and network dynamics in liquid silica.

Ruchi Sharma1, Anirban Mudi, Charusita Chakravarty

  • 1Department of Chemistry, Indian Institute of Technology-Delhi, New Delhi 110016, India.

The Journal of Chemical Physics
|September 1, 2006
PubMed
Summary
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Liquid silica exhibits anomalous diffusion linked to network dynamics. Power spectral analysis reveals that changes in local order correlate with increased mobility, explaining the observed anomalies.

Area of Science:

  • Condensed Matter Physics
  • Materials Science
  • Computational Chemistry

Background:

  • Liquid silica displays anomalous diffusion, deviating from typical Fickian behavior.
  • Understanding these anomalies is crucial for materials science and geological processes.
  • The Beest-Kramer-van Santen (BKS) potential is a common model for silica.

Purpose of the Study:

  • To investigate the diffusional anomaly in liquid silica using power spectral analysis.
  • To correlate the anomalous diffusion with the material's structural and dynamic properties.
  • To elucidate the underlying mechanisms of multiple time scale behavior in silica networks.

Main Methods:

  • Molecular-dynamics simulations were employed to model liquid silica.
  • Power spectral analysis of tagged particle potential energy was utilized.

Related Experiment Videos

  • The study focused on the 1/f(alpha) dependence of the power spectrum on frequency (f).

    • Main Results:

    • A characteristic 1/f(alpha) power-law dependence was observed, indicating multiple time scale behavior.
    • The scaling exponent (alpha) directly mirrored variations in particle mobility.
    • Decreased tetrahedral order (with increasing temperature or pressure) correlated with increased coupling of local modes to network reorganizations and higher diffusivity.

    Conclusions:

    • The study establishes a link between structural anomalies (decreased tetrahedral order) and diffusional anomalies in liquid silica.
    • Vibrational couplings, dependent on symmetry, are identified as the key mechanism connecting structure and diffusion.
    • The findings provide insights into the complex dynamics of disordered network materials.