The broader impact/commercial potential of this I-Corps project is the development of a new metal additive manufacturing technique that is designed to print parts in a single process containing multiple metal alloys. These multi-metal parts are called “metal hybrids,” and this system enables the design and manufacturing of metal parts with complex geometries and different metals used in various deposition locations. This is something that no single manufacturing process can achieve today. The metal hybrid parts may be designed to be just as strong but lighter in weight than existing single-metal parts while offering superior thermal, wear, and corrosion resistance. The development of this technology is expected to be disruptive to a wide range of high-temperature applications and systems, increase the efficiency of additive manufacturing processes by reducing technological footprints, reduce manufacturing costs, reduce the need for complex assemblies and joining operations, and reduce part count. This has applications for aerospace, automotive, and energy industries.

This I-Corps project is based on the development of a additive manufacturing technique that allows for the simultaneous deposition and mixing of different metal powders, in thin layers, within a type of additive manufacturing system referred to as powder bed fusion. The deposited multi-metal powder layer is then melted using a laser beam and the process continues layer by layer until the part has been built. In addition, a machine learning algorithm has been developed to determine suitable laser parameters for correctly melting the multi-metal powders with varying composition. This proposed deposition technique and process parameter prediction model will not only introduce a new generation of metal parts to industry, but also will expand the fundamental understanding of the relationship between the manufacturing process parameters and material properties of additively manufactured multi-metal components.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Project Start
Project End
Budget Start
2021-01-01
Budget End
2022-06-30
Support Year
Fiscal Year
2020
Total Cost
$50,000
Indirect Cost
Name
University of Wisconsin Madison
Department
Type
DUNS #
City
Madison
State
WI
Country
United States
Zip Code
53715