Data-driven electron-diffraction approach reveals local short-range ordering in CrCoNi with ordering effects

Haw-Wen Hsiao, Rui Feng, Haoyang Ni, Ke An, Jonathan D. Poplawsky, Peter K. Liaw and Jian-Min Zuo ()
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Haw-Wen Hsiao: University of Illinois Urbana-Champaign
Rui Feng: Oak Ridge National Laboratory
Haoyang Ni: University of Illinois Urbana-Champaign
Ke An: Oak Ridge National Laboratory
Jonathan D. Poplawsky: Oak Ridge National Laboratory
Peter K. Liaw: The University of Tennessee Knoxville
Jian-Min Zuo: University of Illinois Urbana-Champaign

Nature Communications, 2022, vol. 13, issue 1, 1-9

Abstract: Abstract The exceptional mechanical strength of medium/high-entropy alloys has been attributed to hardening in random solid solutions. Here, we evidence non-random chemical mixing in a CrCoNi alloy, resulting from short-range ordering. A data-mining approach of electron nanodiffraction enabled the study, which is assisted by neutron scattering, atom probe tomography, and diffraction simulation using first-principles theory models. Two samples, one homogenized and one heat-treated, are observed. In both samples, results reveal two types of short-range-order inside nanoclusters that minimize the Cr–Cr nearest neighbors (L12) or segregate Cr on alternating close-packed planes (L11). The L11 is predominant in the homogenized sample, while the L12 formation is promoted by heat-treatment, with the latter being accompanied by a dramatic change in dislocation-slip behavior. These findings uncover short-range order and the resulted chemical heterogeneities behind the mechanical strength in CrCoNi, providing general opportunities for atomistic-structure study in concentrated alloys for the design of strong and ductile materials.

Date: 2022
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DOI: 10.1038/s41467-022-34335-0

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