We show that the magnetic properties of high-entropy alloys (HEAs) can be captured by ab initio calculations within the coherent potential approximation, where the atomic details of the high-entropy mixing are considered as a uniform effective medium. This is demonstrated using the face-centered-cubic ($A1$) phase of $\text{MnFeCoNiCu}$ and the tetragonal ($L{1}_0$) phase of $\text{(MnFeCoNiCu)Pt}$ by comparing the density functional theory (DFT) results with the experimental values. Working within the primitive unit cell of the underlying lattice and its corresponding Brillouin zone, we show that DFT can capture the smooth profile of magnetic properties such as the magnetic moment, the Curie temperature, and the magnetic anisotropy, using only a sparse set of sampling points in the vast compositional space. The smooth profiles given by DFT indeed follow the experimental trend, demonstrating the promising potential of using machine learning to explore the magnetic properties of HEAs, by establishing reasonably large data sets with high-throughput DFT calculations.

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• Magnetic anisotropy
• Magnetism
• Disordered alloys
• Coherent potential approximation
• Density functional theory