A Self-Consistent Scheme for Understanding Particle Impact and Adhesion in the Aerosol Deposition Process

Aerosol deposition (AD) is a thick-film deposition process that can produce films tens to hundreds of micrometers thick with densities greater than 95% of the bulk at room temperature. However, the precise mechanisms of bonding and densification are still under debate. To better understand and predict deposition, a self-consistent approach is employed that combines computational fluid dynamics (CFD), finite element (FE) modeling, and experimental observation of particle impact to improve the understanding of particle flight, impact, and adhesion in the AD process. First, deposition is performed with a trial material to form a film. The process parameters are fed into a CFD model that refines the particle flow and impact velocity for a range of sizes. These values are in turn used to inform the FE parameters to model the fracture and adhesion of the particle on the substrate. The results of FE modeling are compared to SEM images of fractured particles to complete a self-consistent numerical and experimental understanding of the AD process. Additional FE and CFD simulations are used to study how process parameters, materials, and particle parameters affect the deposition process and how the developed tools can be used to optimize deposition efficiency.

Automated summary

By combining CFD simulation, FE modeling, and experimental observation, a self-consistent numerical and experimental understanding of particle flight, impact, and adhesion in the AD process can be achieved to optimize deposition efficiency.