Bayesian Alloy Design with Additive Synthesis

To reduce carbon emissions and increase power out, steam powerplants need to increase the operating temperatures and pressures of steam turbines to improve efficiency. This necessitates the development of high temperature alloys with superior strength and stability. This research aims to design a class of solid solution High Entropy Alloys (HEAs) to exceed the high temperature performance of commercial alloys like Haynes 230 while maintaining comparable costs for Advanced Ultra Supercritical (A-USC) steam cycles. This project integrates Bayesian optimization and Calculation of Phase Diagrams (CALPHAD) within an Integrated Computational Materials Engineering (ICME) framework to predict and optimize key material properties: high temperature solid solution strengthening, diffusion coefficients, freezing range, solidification cracking resistance, and pricing. A novel aspect of this work is the use of multi-Wire Arc Additive Manufacturing (mWAAM), enabling high-throughput fabrication of small test coupons with tailored compositions from the same wire stock. Alloys were screened for performance metrics using hot hardness, nanoindentation, metallography with SEM and EDS ensuring a single-phase microstructure. Promising candidates were printed into larger coupons for mechanical testing, including hot tensile tests between 538°C and 871°C and time to 1% creep strain tests at 760°C under various stresses. Cracking during fabrication was identified in optimized alloys containing vanadium, and the nature of this cracking was investigated via EBSD and EDS. Results indicated that unexpected forms of cracking related to grain misorientation, stress concentration at the grain boundaries, and thermal cycling became prominent. This highlights the need to balance performance and printability by optimizing composition and cooling rates to mitigate cracking and ensure printability.