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Functionally graded materials enable the spatial tailoring of properties through controlling compositions and phases that appear as a function of position within a component. The present study investigates the ability to reduce the coefficient of thermal expansion (CTE) of an aluminum alloy, Al 2219, through additions of Ti-6Al-4V. Thermodynamic simulations were used for phase predictions, and homogenization methods were used for CTE predictions of the bulk CTE of samples spanning compositions between 100 wt% Al 2219 and 70 wt% Al 2219 (balance Ti-6Al-4V) in 10 wt% increments. The samples were fabricated using directed energy deposition (DED) additive manufacturing (AM). Al2Cu and fcc phases were experimentally identified in all samples, and aluminides were shown to form in the samples containing Ti-6Al-4V. Thermomechanical analysis was used to measure the CTE of the samples, which agreed with the predicted CTE values from homogenization methods. The present study demonstrates the ability to tailor the CTEs of samples through compositional modification, thermodynamic calculations, and homogenization methods for property predictions. 

A database for the Cr-Ni-V system was constructed by modeling the binary Cr-V and ternary Cr-Ni-V systems using the CALPHAD approach aided by density functional theory (DFT)-based first-principles calculations and ab initio molecular dynamics (AIMD) simulations. To validate this new database, a functionally graded material (FGM) using Ni-20Cr and V was fabricated using directed energy deposition additive manufacturing (DED AM) and experimentally characterized. The deposited Ni-20Cr was pure fcc phase, while increasing V content across the gradient resulted in sigma phase formation, followed by bcc phase formation. The experimentally measured phases were compared with CALPHAD computations made using a Cr-Ni-V thermodynamic database from the literature and the database developed in the present work. The newly developed database was shown to better predict the experimentally observed phases due to its accurate modeling of binary systems within the database and the ternary liquid phase, which is critical for accurate Scheil calculations.