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Materials Science and Engineering, Chemical and Biological Engineering, Physics and Astronomy, Ames Laboratory, Mechanical Engineering

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With huge design spaces for unique chemical and mechanical properties, we remove a roadblock to computational design of {high-entropy alloys} using a metaheuristic hybrid Cuckoo Search (CS) for "on-the-fly" construction of Super-Cell Random APproximates (SCRAPs) having targeted atomic site and pair probabilities on arbitrary crystal lattices. Our hybrid-CS schema overcomes large, discrete combinatorial optimization by ultrafast global solutions that scale linearly in system size and strongly in parallel, e.g. a 4-element, 128-atom model [a 1073+ space] is found in seconds -- a reduction of 13,000+ over current strategies. With model-generation eliminated as a bottleneck, computational alloy design can be performed that is currently impossible or impractical. We showcase the method for real alloys with varying short-range order. Being problem-agnostic, our hybrid-CS schema offers numerous applications in diverse fields.


This is a pre-print of the article Singh, Rahul, Aayush Sharma, Prashant Singh, Ganesh Balasubramanian, and Duane D. Johnson. "Accelerating computational modeling and design of high-entropy alloys." arXiv preprint arXiv:2010.12107 (2020). Posted with permission.

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