Cooperative Development of Printable Alloys for Additive Manufacturing Through Metaheuristic Optimization

Additive Manufacturing (AM) is a leading technology in the push toward Industry 4.0, especially for next generation metallic components. However, the microstructure, defect populations, and consequently, the performance of additively manufactured metallic parts are impacted by the topologically dependent, complex thermal histories of AM parts. This complex history can improve the strength and ductility, as in 316 stainless steel, or reduce both strength and ductility through delta phase precipitation in Inconel 718, large prior-beta morphology in Ti-6Al-4V, or hot tearing in 5- and 7-series aluminum alloys. Understanding how the unique conditions of AM impact microstructure formation is critical when designing printable alloys for AM. While many advanced tools exist for predicting the thermodynamics and kinetics of materials, these tools are most effectively utilized in the development of new alloys when those results can be combined with both experimental data for validation and with heuristics that incorporate the intangibles that allow the development of more “printable” alloys. That is, optimize a qualitative or only semi-quantitative metric that captures the expertise of practitioners in a Figure of Merit (FOM). We will present on a generalizable framework for the development of more printable steel and aluminum alloys. While this presentation will include a discussion of the framework itself, it will focus on the process and logic surrounding the iterative development of an appropriate FOM that reasonably captures through empirical relationships, thermodynamics, kinetics, and proxies of the same that either directly calculate or are suspected to correlate to those phenomena that improve the AM processing window. These phenomena include grain-refinement to improve yield through Hall-Petch strengthening, reduction in chemical partitioning and contamination that can lead to grain boundary inclusion formation, and reduction in solidification range (“mushy zone”) that are expected to improve resistance to hot tearing. Combined with traditional physical metallurgy, this optimization approach emphasizes the synergistic roles that advanced, high-throughput materials modeling and experiential insights play when developing alloys optimized for AM.