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Monte Carlo Aggregation Code (MCAC) Part 2: Application to soot agglomeration, highlighting the importance of primary
1Normandie Université, INSA Rouen, UNIROUEN, CNRS, CORIA, 76000 Rouen, France.
Particle size significantly impacts soot agglomeration dynamics. Smaller monomers accelerate kinetics and increase fractal dimensions, while larger ones lead to less dense structures, necessitating time-varying regime simulations for accurate modeling.
Area of Science:
- Nanoparticle science
- Chemical engineering
- Computational physics
Background:
- Particle agglomeration simulations often overlook evolving flow and agglomeration regimes.
- These simplifications can significantly affect predicted kinetics, morphology, and size distributions.
Purpose of the Study:
- Investigate the impact of monomer size and polydispersity on soot agglomeration.
- Analyze changes in agglomeration kinetics, homogeneity, and morphology.
- Incorporate varying flow and agglomeration regimes into simulations.
Main Methods:
- Utilized the Monte Carlo Aggregation Code (MCAC).
- Focused on varying particle volume fraction, monomer size, and polydispersity.
- Simulated particle agglomeration under different flow and agglomeration regimes.
Main Results:
- Agglomeration kinetics and homogeneity are highly sensitive to monomer size.
- Smaller monomers enhance kinetics and result in larger fractal dimensions.
- Larger monomers can lead to fractal dimensions as low as 1.67, deviating from classical Diffusion Limited Cluster Agglomeration (DLCA) values.
Conclusions:
- Monomer size is a critical factor influencing soot agglomeration.
- Accurate simulations require considering the time-dependent evolution of flow and agglomeration regimes.
- The findings have implications for predicting nanoparticle behavior in various industrial and environmental applications.
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