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Toward a Realistic Model of Diffusion-Limited Aggregation: Rotation, Size-Dependent Diffusivities, and Settling
Matteo Polimeno1, Changho Kim1, François Blanchette1
1Department of Applied Mathematics, University of California, Merced, California95343, United States.
ACS Omega
|November 21, 2022
Summary
This study simulates particle aggregation using a modified diffusion-limited cluster aggregation (DLCA) model. Including size-dependent diffusion and gravity alters aggregate growth and fractal dimension, impacting cluster formation dynamics.
Area of Science:
- Physics
- Materials Science
- Computational Science
Background:
- Particle aggregation is crucial in various scientific fields.
- Classical diffusion-limited cluster aggregation (DLCA) provides a foundational model.
- Real-world aggregation involves complex factors like particle size, rotation, and external forces.
Purpose of the Study:
- To investigate the impact of size-dependent diffusivities, rotational effects, and gravity on aggregate formation.
- To numerically characterize the growth dynamics and fractal structure of aggregates under these conditions.
- To compare simulation results with the classical DLCA model.
Main Methods:
- Brownian dynamics simulations were employed.
- The study builds upon the established DLCA model.
- Key parameters included size-dependent diffusivities, rotational effects, and gravitational settling.
Main Results:
- Aggregate growth, measured by the radius of gyration (Rg), showed slower dynamics (Rg ~ t^0.71) with size-dependent diffusivity compared to classical DLCA (Rg ~ t^1.02).
- Fractal dimension (d) decreased from ~1.8 (classical DLCA) to ~1.7 with size-dependent rotational diffusion.
- Gravitational settling further reduced fractal dimension to ~1.6, with aggregates exhibiting a slightly smaller vertical extent.
Conclusions:
- Size-dependent diffusion, rotational effects, and gravity significantly influence aggregate growth and structure.
- The fractal dimension of aggregates is reduced under these more realistic conditions.
- Simulation results provide insights into complex aggregation phenomena relevant to various scientific disciplines.
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