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Engineering atomic-level complexity in high-entropy and complex concentrated alloys

Hyun Seok Oh, Sang Jun Kim, Khorgolkhuu Odbadrakh, Wook Ha Ryu, Kook Noh Yoon, Sai Mu, Fritz Körmann, Yuji Ikeda, Cemal Cem Tasan, Dierk Raabe (), Takeshi Egami () and Eun Soo Park ()
Additional contact information
Hyun Seok Oh: Seoul National University
Sang Jun Kim: Seoul National University
Khorgolkhuu Odbadrakh: University of Tennessee and Oak Ridge National Laboratory
Wook Ha Ryu: Seoul National University
Kook Noh Yoon: Seoul National University
Sai Mu: Oak Ridge National Laboratory
Fritz Körmann: Max-Planck-Institut für Eisenforschung
Yuji Ikeda: Max-Planck-Institut für Eisenforschung
Cemal Cem Tasan: Massachusetts Institute of Technology
Dierk Raabe: Max-Planck-Institut für Eisenforschung
Takeshi Egami: Oak Ridge National Laboratory
Eun Soo Park: Seoul National University

Nature Communications, 2019, vol. 10, issue 1, 1-8

Abstract: Abstract Quantitative and well-targeted design of modern alloys is extremely challenging due to their immense compositional space. When considering only 50 elements for compositional blending the number of possible alloys is practically infinite, as is the associated unexplored property realm. In this paper, we present a simple property-targeted quantitative design approach for atomic-level complexity in complex concentrated and high-entropy alloys, based on quantum-mechanically derived atomic-level pressure approximation. It allows identification of the best suited element mix for high solid-solution strengthening using the simple electronegativity difference among the constituent elements. This approach can be used for designing alloys with customized properties, such as a simple binary NiV solid solution whose yield strength exceeds that of the Cantor high-entropy alloy by nearly a factor of two. This study provides general design rules that enable effective utilization of atomic level information to reduce the immense degrees of freedom in compositional space without sacrificing physics-related plausibility.

Date: 2019
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DOI: 10.1038/s41467-019-10012-7

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