Additive manufacturing (AM) of metallic materials has the potential to move from rapid prototyping and manufacturing of a small number of high-value components to full-scale manufacturing of high volume components. With the use of materials characterization and high-performance computing, the path to everyday manufacturing can be greatly sped up compared to the decades development with polymer additive manufacturing.

Metallic additive manufacturing presents many technical challenges related to the nature of the layer-by-layer process. The material experiences thermal cycling and can see repeated solid state and liquid-solid transformations. This leads to complex microstructural textures and grain orientations that are not typically found in conventional manufacturing processes. The resulting component can exhibit increased residual stresses, porosity, and surface roughness that can detrimentally influence the mechanical, corrosion and thermal properties. On the other hand, where additive manufacturing can introduce material complexities that can compromise the performance of the component, the layer-by-layer process can be utilized to engineer material microstructure to enhance the performance beyond what is attainable through conventional processes.

Argonne can speed up the adoption of new alloys by benchmarking the materials and process conditions through materials characterization using X-ray analysis and predictive computer modeling. This would eliminate the need for costly X-ray inspections of all finished parts or the overbuilding of parts to ensure durability at the expense of weight.

Predictive and real-time process control will enable reproducibility of metal parts and the optimization for different applications of material properties, particularly of use in medical, aerospace, automobile, and defense industries.

Lowering the cost of additive manufacturing for common metals, such as aluminum and stainless steal, by increasing product predictability could replace the need for cold stamping manufacturing of common steels for automobiles and appliances and minimize the number of production lines required per manufacturing facility.

To help industry solve challenges with additive manufacturing , Argonne has a unique and world-leading collection of R&D tools to benchmark additive manufacturing alloys and manufacturing processes as well as leading experts in reduced order computation, machine learning, materials science and X-ray characterization.