Numerical study on the agglomeration of nanoparticles in aluminum melt

Abstract During the preparation of nanoparticle-reinforced aluminum matrix composites via liquid-state methods, the agglomeration of nanoparticles within the aluminum melt remains a critical challenge. In this study, the Discrete Element Method (DEM) is employed, and a non-contact van der Waals force model based on Hamaker theory was implemented via API, enabling a more realistic representation of long-range attractive interactions and early-stage agglomeration behavior of particles in the melt. Using this approach, the agglomeration processes of two types of nanoparticles—silicon dioxide (SiO₂) and aluminum oxide (Al₂O₃)—in aluminum melt were numerically investigated. It focuses on investigating the influence of particle number density and characteristic material parameters (Hamaker constant) on the morphology and structure of agglomerates, quantified through fractal dimension analysis. The results indicate that the fractal dimension of nanoparticle agglomerates increases significantly with the number of particles, indicating a structural transition from loose chain-like or branchlike formations to a dense, complex network. Nanoparticles with a higher Hamaker constant (SiO₂) form denser agglomerates more readily than those with a lower constant (Al₂O₃), and a synergistic effect exists between particle number and the Hamaker constant. This study provides a numerical basis for understanding the mechanisms of nanoparticle agglomeration and offers significant guidance for optimizing the preparation process of nanoparticle-reinforced aluminum matrix composites.