CAREER: Integration and Tailoring of Thermal Energy Sources to Enable Defect-Free High Deposition Rate Metal Additive Manufacturing

Metal additive manufacturing has revolutionized various industries by providing sustainable and unparalleled customization in part production. However, to become compatible with mainstream manufacturing processes like casting and forging, the material deposition rate needs to be significantly enhanced. Currently, a substantial amount of thermal energy is concentrated from a single source to melt a large volume of metal powders, which often results in defects and undesirable material properties in the printed components. This Faculty Early Career Development (CAREER) award supports research that aims to address this challenge by reducing the thermal gradient in the laser energy input and integrating efficient and cost-effective energy sources, such as induction heat and ultrasonic vibration. By achieving a balanced thermal environment within the process zone, a defect-free high deposition additive manufacturing process becomes possible. If successful, research enabled by this award may transform large-scale manufacturing industries. By providing hands-on exploration and igniting intrinsic motivation, the award is expected to support the workforce development for the nation’s sustainable future in advanced manufacturing. This CAREER project aims to investigate and control the metallurgical transformation of deposited material during high-deposition rate additive manufacturing processes. Thermal energies from multiple sources, such as laser with beam shaping, induction heating, and ultrasonic vibration, are simultaneously employed onto the melt pool. However, current knowledge in integrating multifaceted thermal inputs to metal additive manufacturing is limited. A critical challenge of additive manufacturing lies in energy delivery to the processing zone, which powers thermodynamic forces, drives metallurgical transformation, and governs the formation of microstructures. These microstructures, in turn, determine the quality of printed parts. The research tasks include: (1) Establishing dynamic control of energy inputs to achieve favorable thermal distribution at the process zone by integrating laser (with beam shaping), induction heating, and ultrasound. (2) Increasing material deposition by preheating the substrate and on-the-fly powders using induction heating. (3) Minimizing residual stress in the part through in-situ induction heat treatment. (4) Developing an AI-based prediction model for microstructure and defect control. The outcomes may facilitate the establishment of a convergent research and education platform on additive manufacturing research and innovation. 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.