most citedDeciphering Chemical Ordering in High Entropy Materials: A Machine Learning-Accelerated High-throughput Cluster Expansion Approach

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cond-mat.mtrl-sci2024★ 34 cited

Deciphering Chemical Ordering in High Entropy Materials: A Machine Learning-Accelerated High-throughput Cluster Expansion Approach

Guillermo Vazquez, Daniel Sauceda, Raymundo Arróyave

The Cluster Expansion (CE) Method encounters significant computational challenges in multicomponent systems due to the computational expense of generating training data through den…