ArticleNature communications2026
Universal framework for efficient estimation of stability in multi-principal element alloys.
Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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7 authors.
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Abstract
Predicting the synthetic accessibility of multi-principal element alloys (MPEAs) across the global chemical space remains a challenge. In this study, we show that the synthesizability of MPEAs across broad compositional and structural spaces can be predicted using a physical model that expresses the total energy of any MPEA as a linear combination of energies from lower-dimensional subsystems. The model is validated with a large computational dataset and supported by the experimental synthesis of multiple MPEAs, achieving mean absolute errors near or below 7 meV/atom on a density functional theory dataset of 135,791 MPEAs spanning 28 metals and up to ten components. Its accuracy is comparable to state-of-the-art deep learning models while maintaining interpretability through cluster-expansion theory. Moreover, we show that the stability of high-entropy alloys can be predicted using a linear combination of energies from lower-dimensional systems with low errors, indicating a flatter energy landscape at high compositional complexity.
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