This work focuses on developing a method for qualifying model Aluminum alloys for the LPBF process using a combination of in-situ monitoring of spatters, thermophysical property measurements of the liquid metal, and determination of the density of built parts. The objective is to identify correlations between alloy composition, melt pool dynamics, and process stability, and resulting densification.

Experiments are conducted on three aluminum powder grades: pure aluminum and two powders grafted with ZrO₂ nanoparticles. The latter are obtained through dry coating with different mixing energies, affecting the adhesion and distribution of the nanoparticles on aluminum grains. Square samples are fabricated on an instrumented LPBF minimachine equipped with high-speed imaging to analyze spatter ejections during the process. Those results are completed with optical microscopy analysis to observe porosity formation. Preliminary analysis of spatters depending on the coating conditions suggests a strong influence of nanoparticle distribution on the melt pool stability. Complementary drop-placed or free-falling droplet experiments will allow determining surface tension and viscosity in order to further interpret the observed instabilities. The combination of in-situ monitoring and forthcoming thermophysical data is expected to provide a comprehensive understanding of the links between powder surface functionalization, melt pool behavior, and alloy processability. More globally, this approach aims to define new design criteria for aluminum alloys optimized for LPBF additive manufacturing.

Keywords: generative design; LPBF; Aluminum