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Random sequential adsorption of cuboids.

Michał Cieśla1, Piotr Kubala1

  • 1M. Smoluchowski Institute of Physics, Department of Statistical Physics, Jagiellonian University, Łojasiewicza 11, 30-348 Kraków, Poland.

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This study investigated cuboid shapes for optimal packing. The research found that cuboids with axes ratios near 0.75:1:1.30 achieve the highest packing fraction, a key metric in materials science.

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Area of Science:

  • Materials Science
  • Statistical Mechanics
  • Computational Physics

Background:

  • Random sequential adsorption is a fundamental process in materials science.
  • Understanding the packing fraction of anisotropic particles is crucial for designing new materials.
  • Previous studies have focused on simpler shapes, leaving the optimal packing of cuboids largely unexplored.

Purpose of the Study:

  • To determine the optimal axis length ratios of cuboids for achieving the maximum packing fraction.
  • To investigate the kinetics of random sequential adsorption for cuboids.
  • To analyze the microstructural properties, including density correlations and orientational ordering, of the resulting cuboid packings.

Main Methods:

  • Simulations of random sequential adsorption of cuboids with varying axis length ratios (a:1:b, where a ∈ [0.3, 1.0] and b ∈ [1.0, 2.0]).
  • Calculation of packing fraction and analysis of its dependence on cuboid shape.
  • Kinetic analysis using power-law characterization.
  • Microstructural analysis employing density correlation functions and orientational ordering propagation.

Main Results:

  • The highest packing fraction achieved was 0.40187 ± 0.00097.
  • This maximum packing density was observed for cuboids with axis ratios close to 0.75:1:1.30.
  • The kinetics of packing growth followed a power-law, independent of the number of cuboid degrees of freedom.

Conclusions:

  • Cuboid shape significantly influences packing efficiency, with specific ratios yielding optimal density.
  • The findings provide insights into the fundamental principles governing the assembly of anisotropic particles.
  • This research contributes to the development of predictive models for material properties based on particle geometry.