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arXiv · 2607.18099

Study of ordering in (MoCrTi)$_{100-x}$Al$_x$ refractory high-entropy alloys using machine learning interatomic potential

Jiyao Zhang·Klemens Lechner·Markus Maßwohl·Petra Spoerk-Erdely·David Holec
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Abstract

Refractory high-entropy alloys are promising candidates for high-temperature applications, yet the effects of composition on their chemical-ordering pathways and mechanical properties remain insufficiently understood. Here, a universal MLIP combined with MC and MD simulations is employed to investigate the temperature-dependent thermodynamic and mechanical behavior of (MoCrTi)(100-x)Alx alloys. Atomic configurations, sublattice occupations, and simulated diffraction intensities reveal pronounced B2-type chemical ordering at low temperatures, with Mo and Al occupying one sublattice and Cr and Ti occupying the other. The configurational heat capacities and SRO parameters further reveal a strong composition dependence of the ordering pathway. The Mo25Cr25Ti25Al25 and Mo32Cr32Ti32Al4 alloys exhibit a single dominant ordering stage involving cooperative changes in multiple B2-type pair correlations. By contrast, Mo28Cr28Ti28Al16 and Mo30Cr30Ti30Al10 exhibit two distinct ordering stages. Their low-temperature features are associated primarily with changes in the Mo-Al and Al-Al correlations, respectively, whereas their high-temperature features involve collective changes in the remaining B2-type pair correlations. Chemical ordering also fundamentally alters the composition dependence of mechanical stiffness. Whereas the elastic constants of disordered configurations increase approximately monotonically with decreasing Al content, those of the ordered configurations exhibit a non-monotonic dependence and reach a maximum in Mo30Cr30Ti30Al10. This anomalous enhancement originates from a SRO induced redistribution of atomic pairs, particularly Mo-Cr pairs. These results establish a direct atomistic connection among alloy composition, multistage chemical ordering, and mechanical stiffness, providing guidance for tuning the mechanical behavior of RHEAs through compositional control.

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Jiyao Zhang, Klemens Lechner, Markus Maßwohl, Petra Spoerk-Erdely, David Holec. 2026-07-20. Study of ordering in (MoCrTi)$_{100-x}$Al$_x$ refractory high-entropy alloys using machine learning interatomic potential. https://arxiv.org/abs/2607.18099

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