| Abstract Scope |
Additive manufacturing (AM) opens new routes for designing and deploying high-entropy alloys with tailored microstructures and localized functionality. However, AM of multi-principal-element alloys is challenged by microsegregation, non-equilibrium solidification, and defect formation. In this talk, I present recent advances in developing printability maps for HEAs that couple thermodynamic descriptors, CALPHAD-based solidification modeling, and data-driven surrogate models. Using Bayesian calibration and multi-information-source learning, we can efficiently identify processing regimes that minimize cracking, enable desirable phase selection, and promote microstructural stability. Applications to FCC, BCC, and refractory HEAs demonstrate how AM can become a powerful enabler for HEA discovery and deployment. This work opens the door to “3D+” HEA printing—where composition, microstructure, and properties can be tailored in space. |