A High Throughput CALPHAD Development Method for the Design of (Fe_xNi_y)_80Cr_10(Al,Si,Ti)_10 Single Phase Alloys: Enabling the Exploration of Light-weighting Elements' as Passivators in Co-Free FCC Alloys

RIP2025-00058: The emergence of compositionally-complex alloys (CCAs) as a new frontier of corrosion-resistant alloy design has opened doors for advanced optimization of the usage of low-density, corrosion-resistant elements for promoting enhanced passivation and self-healing while lowering overall alloy density. However, researchers must contend with an enormous design space with many compositional and microstructural possibilities. In this work, the lightweighting elements (LWE) with appreciable solubility in an austenitic phase (Al, Si, Ti) were evaluated for their individual and combinatorial effects on the passivation of austenitic alloys containing a subcritical (xCr = 10 at%) chromium concentration based on binary Fe-Cr alloys. A novel FCC “platform” consisting of a non-equiatomic (NixFeyCr10)90(LWE)10 alloy set was designed using a novel high-throughput CALPHAD methodology to maximize the probability of full 10 at% solubility of any combination of LWE. LWE were utilized in binary pairs, with all combinations of 10:0, 7:3, 5:5, 3:7 and 0:10 between each LWE. Each alloy’s degree of protectiveness, self-healing and long-term passive growth behavior in sulfuric acid were electrochemically characterized using potentiodynamic, potentiostatic, and AC impedance-based methods. Oxide species’ identities and oxidation states were characterized using X-ray photoelectron spectroscopy (XPS) to connect oxide composition to performance. Furthermore, the fate of each element during passivation/corrosion and its role as passivator, facilitator and phase stabilizer were determined through atomic emission spectro-electrochemistry (AESEC). Results point toward a greater understanding of third- and fourth-elemental effects on subcritical Cr passivation towards optimizing alloy chemistry for enhanced self-healing corrosion capabilities in such novel low-density alloys. Further, the use of unsupervised learning methods has yielded initial data-driven design rules for the design of alloys with superior passivation behavior. Such early-stage design rules will be further expanded and generalized utilizing other similar alloy platforms in future work. Resulting performance and oxide chemistry trends are also correlated to facilely calculable thermodynamic parameters, allowing for the prediction of corrosion resistance of alloys of a given composition, facilitating further alloy development by allowing for a robust filtering step before alloy fabrication and testing.