Unlocking the Versatility of Additive Manufacturing: CALPHAD-Enabled Design for Additive Manufacturing in Resource-Constraint Environments
Abstract: Additive manufacturing (AM) revolutionizes alloy design and prototyping, yet limited feedstock choices hinder its potential. We propose an innovative approach that combines directed energy deposition (DED) as a high-throughput technique with CALPHAD-based ICME modeling for accelerated alloy development and materials discovery based on commercially available alloys in resource-constrained environments. In this talk, I will share some experiences in alloy discovery and design using different DED techniques guided by Integrated Computational Materials Engineering (ICME) supported by the CALPHAD methodology. The talk will present case studies illustrating the advantages of utilizing the CALPHAD-enabled design approach in AM. Moreover, severe challenges in characterization experiments and computational modeling due to the design requirements in AM will be discussed. The case studies will integrate CALPHAD, ICME, machine learning, and high-throughput experiments. They will demonstrate how DED is applied as part of a combined approach to alloy development through compositional screening. In the study of dissimilar steel printing, machine learning is used to facilitate the prediction of the stacking fault energy and thus accelerate the steel composition screening with TRIP/TWIP (TRIP: transformation-induced plasticity; TWIP: twinning-induced plasticity) effects. A new TWIP steel without Mn contribution to modulating the stacking fault energy has been discovered. This steel shows a synergistic effect of high strength and ductility, leading to better mechanical performance than the parent alloys: 316L and high-strength low-alloy (HSLA) steels. While printing stainless steel 316L mixed with Inconel 718, a new high-strength alloy was identified using a mixture of both powders after heat 
treatment design using the CALPHAD-based approach with experimental calibration. Another wire-feed DED printing of copper alloy C18150 with Inconel 625 shows the solution of obtaining a crack-free functionally graded alloy for aerospace applications but also highlights the essential requirement of a fundamental study of phase diagrams. Overall, by leveraging the synergy between CALPHAD-based modeling, high-throughput AM techniques, and machine learning, we can open up new avenues for efficient and cost-effective alloy development, enabling the realization of tailored material properties and functionalities, especially for resource-constrained environments.
Speaker Bio: Prof. Wei Xiong is the William Kepler Whiteford Faculty Fellow at the University of Pittsburgh. He received his Ph.D. in Materials Science from KTH Royal Institute of Technology, Sweden, in 2012. After a year at the University of Wisconsin–Madison performing computational modeling of phase transformations in nuclear materials, he joined Northwestern University as a research associate working on alloy development in the Steels Research Group for three years. He joined the University of Pittsburgh in 2016 and started leading the Physical Metallurgy and Materials Design Laboratory (https://www.pitt.edu/~weixiong/). Using the CALPHAD-based ICME methods, Dr. Xiong works in materials design and process optimization, which covers a wide range of inorganic materials and focuses on phase equilibria and phase transformations. Dr. Wei Xiong has served on the ASM International Alloy Phase Diagrams Committee, TMS Alloy Phases Committee (Past chair), TMS High-Temperature Alloys Committee, and TMS Additive Manufacturing Committee. He has received several academic awards, which include Best Paper Awards of the CALPHAD journal in 2012 and 2013, the TMS FMD Young Leader Professional Development Award 2015, Outstanding Reviewer Award 2020 of Acta Materialia, the CALPHAD Young Leader Award 2020, the TMS Early Career Faculty Fellow Award 2021, APDIC Best Paper Award 2021, and the National Science Foundation CAREER (Faculty Early Career Development Program) Award 2021. Dr. Xiong is an associate editor of the journal, Science and Technology of Advanced Materials. In addition, he serves on the editorial board for the journals: npj Advanced Manufacturing, Materials Characterization, and Journal of Materials Informatics.