Charge-density based evaluation and prediction of stacking fault energies in Ni alloys from DFT and machine learning

Arora, Gaurav; Manzoor, Anus; Aidhy, Dilpuneet S.

doi:10.1063/5.0122675

Title: Charge-density based evaluation and prediction of stacking fault energies in Ni alloys from DFT and machine learning

Journal Article · Mon Dec 12 00:00:00 EST 2022 · Journal of Applied Physics

DOI:https://doi.org/10.1063/5.0122675· OSTI ID:1905110

^[1]; Manzoor, Anus ^[1];

^[1]

Univ. of Wyoming, Laramie, WY (United States)

A combination of high strength and high ductility has been observed in multi-principal element alloys due to twin formation attributed to low stacking fault energy (SFE). In the pursuit of low SFE alloys, a key bottleneck is the lack of understanding of the composition–SFE correlations that would guide tailoring SFE via alloy composition. Using density functional theory (DFT), we show that dopant radius, which have been postulated as a key descriptor for SFE in dilute alloys, does not fully explain SFE trends across different host metals. Instead, charge density is a much more central descriptor. It allows us to (1) explain contrasting SFE trends in Ni and Cu host metals due to various dopants in dilute concentrations, (2) explain the large SFE variations observed in the literature even within a given alloy composition due to the nearest neighbor environments in “model” concentrated alloys, and (3) develop a machine learning model that can be used to predict SFEs in multi-elemental alloys. Further, this model opens a possibility to use charge density as a descriptor for predicting SFE in alloys.

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Research Organization:: Clemson Univ., SC (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES)

Grant/Contract Number:: SC0023232

OSTI ID:: 1905110

Alternate ID(s):: OSTI ID: 1903030

Journal Information:: Journal of Applied Physics, Vol. 132, Issue 22; ISSN 0021-8979

Publisher:: American Institute of Physics (AIP)Copyright Statement

Country of Publication:: United States

Language:: English

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