Campus Units

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

Document Type

Article

Publication Version

Submitted Manuscript

Publication Date

2020

Journal or Book Title

arXiv

Abstract

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.

Comments

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.

Copyright Owner

The Author(s)

Language

en

File Format

application/pdf

Published Version

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