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Abstract We present results from a stochastic cellular automata (CA) model developed and employed for examining the oxidation kinetics of NiAl and NiAl+Hf alloys. The rules of the CA model are grounded in diffusion probabilities and basic principles of alloy oxidation. Using this approach, we can model the oxide scale thickness and morphology, specific mass change and oxidation kinetics as well as an approximate estimate of the stress and strains in the oxide scale. Furthermore, we also incorporate Hf in the grain boundaries and observe the “reactive element effect”, where doping with Hf results in a drastic reduction in the oxidation kinetics concomitant with the formation of thin, planar oxide scales. Interestingly, although we find that grain boundaries result in rapid oxidation of the undoped NiAl, they result in a slower-growing oxide and a planar oxide/metal interface when doped with Hf.

Together with the thermodynamics and kinetics, the complex microstructure of high-entropy alloys (HEAs) exerts a significant influence on the associated oxidation mechanisms in these concentrated solid solutions. To describe the surface oxidation in AlCoCrFeNi HEA, we employed a stochastic cellular automata model that replicates the mesoscale structures that form. The model benefits from diffusion coefficients of the principal elements through the native oxides predicted by using molecular simulations. Through our examination of the oxidation behavior as a function of the alloy composition, we corroborated that the oxide scale growth is a function of the complex chemistry and resultant microstructures. The effect of heat treatment on these alloys is also simulated by using reconstructed experimental micrographs. When they are in a single-crystal structure, no segregation is noted for α-Al2O3 and Cr2O3, which are the primary scale-forming oxides. However, a coexistent separation between Al2O3 and Cr2O3 oxide scales with the Al-Ni- and Cr-Fe-rich regions is predicted when phase-separated microstructures are incorporated into the model.