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‐material”) by intro...