Ab initio informed yield criterion across body-centered cubic transition metals

Bienvenu, Baptiste; Dézerald, Lucile; Rodney, David; Clouet, Emmanuel

doi:10.1016/j.actamat.2022.118098

Cited by 12 publications

(2 citation statements)

References 79 publications

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“…Indeed, previous ab initio results at 0 K have shown that dislocations have similar core properties in the nonmagnetic and antiferromagnetic phases [5,6], the only notable difference being the generation of magnetic faults by 1 2 111 dislocations at 0 K. Once these magnetic faults have become unstable above T v , magnetism should not have any consequence on Cr plasticity. A plastic behavior similar to other bcc transition metals is therefore expected for Cr [41].…”

Section: Discussionsupporting

confidence: 66%

Interplay between magnetic excitations and plasticity in body-centered cubic chromium

Bienvenu

Clouet

2023

Phys. Rev. B

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The effect of finite-temperature magnetic excitations on the plasticity of body-centered cubic chromium is studied. In chromium, the magnetic order is disrupted by the 1 2 111 Burgers vectors of dislocations, creating magnetic frustrations partially resolved through the generation of magnetic faults. These faults may bear consequences on plasticity, the controlling parameter being their energy. Through the inclusion of finite-temperature magnetic excitations, we show in this work that these faults vanish below the Néel temperature, thus leaving 1 2 111 dislocations free to move. When the faults have disappeared, complex noncollinear magnetic structures are stabilized, surrounding the region sheared by these dislocations, with a negligible excess magnetic energy.

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Section: Discussionsupporting

confidence: 66%

Interplay between magnetic excitations and plasticity in body-centered cubic chromium

Bienvenu

Clouet

2023

Phys. Rev. B

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“…Atomic modeling techniques are employed to establish representative configurations for HEAs and, combined with density functional theory (DFT) calculations, − can effectively explore stable structures. Bai et al .…”

Section: Introductionmentioning

confidence: 99%

VASE: A High-Entropy Alloy Short-Range Order Structural Descriptor for Machine Learning

Liu,

Wang,

Luan

et al. 2024

J. Chem. Theory Comput.

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The short-range order (SRO) structure in high-entropy alloys (HEAs) is closely associated with many properties, which can be studied through density functional theory (DFT) calculations. Atomic-scale modeling and calculations require substantial computational resources, and machine learning can provide rapid estimations of DFT results. To describe SRO information in HEAs, a new descriptor based on Voronoi Analysis and Shannon Entropy (VASE) is proposed. Based on Voronoi analysis, the Shannon entropy is introduced to directly characterize atomic spatial arrangement information except for composition and atomic interactions, which is necessary for describing the disorder atomic occupancy in HEAs. The new descriptor is used for predicting the formation energy of FeCoNiAlTiCu system based on machine learning model, which is more accurate than other descriptors (Coulomb matrices, partial radial distribution functions, and Voronoi analysis). Moreover, the model trained based on VASE descriptors exhibits the best predictive performance for unrelaxed structures (24.06 meV/atom). The introduction of Shannon entropy provides an effective representation of atomic arrangement information in HEAs, which is a powerful tool for investigating the SRO phenomena.

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