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This study simulates a binary Voronoi mixture, revealing that its complex many-body interactions do not significantly alter structural relaxation dynamics compared to simpler liquid models. Mode-coupling theory accurately predicts key dynamic properties using only static structural data.

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Area of Science:

  • Computational physics and chemistry
  • Soft matter physics
  • Statistical mechanics

Background:

  • The binary Voronoi mixture is a novel fluid model featuring local, many-body interactions derived from Voronoi-Laguerre tessellation.
  • Understanding the dynamics of supercooled liquids is crucial for materials science and condensed matter physics.

Purpose of the Study:

  • To investigate the structural relaxation dynamics of a weakly polydisperse, additive binary Voronoi mixture in the supercooled-liquid regime.
  • To compare simulation results with first-principles-based idealized mode-coupling theory (MCT) for validation and predictive power assessment.

Main Methods:

  • Performed molecular-dynamics (MD) simulations of the binary Voronoi mixture.
  • Calculated time- and temperature-dependent coherent and incoherent scattering functions and mean-square displacements.
  • Compared MD results with MCT using two approaches: fitting asymptotic predictions and using static-structure-factor input for parameter-free calculations.

Main Results:

  • Many-body interactions in the Voronoi mixture showed no strong qualitative differences in dynamics compared to simple liquids with pair-wise interactions.
  • Fitted exponent parameter (λ ≈ 0.746) and Kohlrausch relaxation time behavior were consistent with literature for similar systems.
  • Mode-coupling theory (MCT) calculations based on static input showed a modest overestimation of the critical temperature (factor of ~1.2).

Conclusions:

  • The study demonstrates that many-body interactions in the Voronoi mixture do not qualitatively alter supercooled-liquid dynamics.
  • There is strong agreement between MD simulations and MCT, suggesting predictive capabilities of MCT based solely on static correlations.
  • This highlights the potential to predict microscopic dynamic properties of complex fluids using static structural information, even with inherent many-body interactions.