Building Success: The Role of Particle Size (and Shape) in the Additive Manufacturing of Metallic Components
Particle size and shape analysis are key in additive manufacturing of metals. Using Dynamic Image Analysis (DIA), this study highlights the importance of selecting proper measurement parameters, developing predictive models for particle size distribution, and understanding the effects of Laser Powder Bed Fusion, sieving, and ball milling on powder properties.
Additive manufacturing (AM) has revolutionized the production of complex metallic components, offering unparalleled design flexibility and efficiency. Among AM techniques, Laser Powder Bed Fusion (LPBF) excels in producing high-performance parts with intricate geometries. This makes it a promising method for fabricating metallic catalysts, essential for numerous industrial processes due to their excellent thermal stability and catalytic activity.
The efficiency of metallic catalysts is significantly influenced by their porosity and surface area. A higher surface area provides more active sites for catalytic reactions, enhancing overall performance. Optimizing the LPBF process for metallic catalysts to obtain ideal surface area and porosity relies heavily on the powder feedstock. Particle size, shape, and tapped density impact powder flowability and the manufactured part's mechanical properties. Therefore, precise characterization of these parameters is crucial for process optimization and quality control.
This report focuses on the importance of determining the particle size, shape, and tapped density in the LPBF production of nickel aluminum (NiAl) metallic catalysts. Ni-based catalysts are widely used in industries such as:
• Steam reforming for hydrogen production (1);
• Carbon monoxide methanation for synthetic natural gas production (2);
• Chemical synthesis for fine chemicals and biomass conversion to biofuels and bio-based chemicals (3).
The following sections detail particle characterization methodologies, the impact of particle properties on the LPBF process, and how these insights contribute to improved process optimization and quality control for NiAl catalyst production.
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