|Campbell, Carelyn E.
|Lass, Eric Andrew
|Levine, Lyle Edward
|Stoudt, Mark R.
Additive manufacturing (AM) of metallic alloys produces extreme heating and cooling cycles that result in unexpected microstructures and phases. This research will integrate a variety of modeling tools across multiple time and length scales to predict the microstructure evolution during the AM build process and post build thermal-mechanical processing. Some of these modeling tools include density functional theory (DFT), CALPHAD-based models, phase-field models, and finite-element models (FEM) to predict as-built microsegregation, post-processing homogenization, precipitation, and stress-relaxation. DFT simulations will be used to provide inputs needed for precipitation simulations. This modeling will rely on a range of characterization techniques to determine processing-structure-property relations that occur during processing, including scanning and transmission electron microscopy, thermal analysis, and x-ray diffraction techniques. Developed models will be used to optimize processing and conventional alloy compositions for additive manufacturing.
T. Keller, G. Lindwall, S. Ghosh, L. Ma, B.M. Lane, F. Zhang, U.R. Kattner, E.A. Lass, J.C. Heigel, Y. Idell, M.E. Williams, A.J. Allen, J.E. Guyer, L.E. Levine, Acta Mater., 139 (2017) 244-253.
Additive manufacturing; Metals; Phase transformations; CALPHAD; DFT; Computational thermodynamics; Multicomponent diffusion; Solidification; Microscopy; Diffraction; Alloy Optimization