HAL (France)
open access
A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys
High-entropy alloys (HEAs) are highly promising electrocatalysts, but the vastness of their configurational space severely limits traditional screening approaches. To overcome this challenge, this article proposes a conceptual and methodological paradigm shift toward “Inverse Design” (“property-to-m
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