Multi-principal element alloys (MPEAs) represent a radical new class of materials that, unlike conventional alloys, are concentrated solid-solutions generally consisting of multiple (≥ 5) principal elements in significant proportions. Certain MPEAs, e.g., Co33W07Al33Nb24Cr03, have exhibited superior hardness and mechanical strength that are unattainable from traditional alloys. These promising properties have encouraged their use as a laser cladded coating material to engineer surfaces of components exposed to severe environments. However, uneven mixing and microstructure evolution of the MPEA melt under rapid cooling have contributed to poor quality and formation of cracks in the coating. Since the dynamics of the molten alloy is fundamentally driven by the diffusion of the elemental species in the MPEA, correlating atomistic properties (e.g. diffusion coefficient) to system-scale processing parameters (e.g. laser power) has posed as a major impediment. In response to this challenge, we are working to establish a predictive framework correlating processing variables to microstructure and material properties by coupling findings from first principles computations of alloy structure and molecular dynamics simulations of the melt together with uncertainty quantification and experimental characterization of additively manufactured MPEAs, geared towards proposing optimal processing parameters to enhance the quality of the laser deposited MPEA clads.
This project was led by Prof. Ganesh Balsubramanian in the Group for Interfacial and Nanoengineering (GIAN) in the Department of Mechanical Engineering & Mechanics at Lehigh. The work is funded by the National Science Foundation.
Read more about this research in Nature Computational Science and Journal of Applied Physics.