Ductility mechanisms in complex concentrated refractory alloys from atomistic fracture simulations

Abstract The striking variation in damage tolerance among refractory complex concentrated alloys is examined through the analysis of atomistic fracture simulations, contrasting behavior in elemental Nb with that in brittle NbMoTaW and ductile Nb 45 Ta 25 Ti 15 Hf 15 . We employ machine-learning interatomic potentials (MLIPs), including a new MLIP developed for NbTaTiHf, in atomistic simulations of crack tip extension mechanisms based on analyses of atomistic fracture resistance curves. While the initial behavior of sharp cracks shows good correspondence with the Rice theory, fracture resistance curves reveal marked changes in fracture modes for the complex alloys as crack extension proceeds. In NbMoTaW, compositional complexity appears to promote dislocation nucleation relative to pure Nb, despite theoretical predictions that the alloy should be relatively more brittle. In Nb 45 Ta 25 Ti 15 Hf 15 , alloying alters the fracture mode compared to elemental Nb, promoting crack tip blunting and enhancing resistance to crack propagation.

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Publication Details

Journal
npj Computational Materials
Published
2025-11-14
DOI
https://doi.org/10.1038/s41524-025-01810-3
Citations
4
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
2.07

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article

Ductility mechanisms in complex concentrated refractory alloys from atomistic fracture simulations

Diana Farkas, David H. Cook, Robert O. Ritchie, Mark Asta et al.
4 citations
npj Computational Materials
Machine Learning in Materials Science
2.07
article

Ductility mechanisms in complex concentrated refractory alloys from atomistic fracture simulations

Diana Farkas, David H. Cook, Robert O. Ritchie, Mark Asta, Buyu Zhang, Flynn Walsh, Pedro P. P. O. Borges, Punit Kumar, W.L. Wang
article en
4 citations

Abstract

Abstract The striking variation in damage tolerance among refractory complex concentrated alloys is examined through the analysis of atomistic fracture simulations, contrasting behavior in elemental Nb with that in brittle NbMoTaW and ductile Nb 45 Ta 25 Ti 15 Hf 15 . We employ machine-learning interatomic potentials (MLIPs), including a new MLIP developed for NbTaTiHf, in atomistic simulations of crack tip extension mechanisms based on analyses of atomistic fracture resistance curves. While the initial behavior of sharp cracks shows good correspondence with the Rice theory, fracture resistance curves reveal marked changes in fracture modes for the complex alloys as crack extension proceeds. In NbMoTaW, compositional complexity appears to promote dislocation nucleation relative to pure Nb, despite theoretical predictions that the alloy should be relatively more brittle. In Nb 45 Ta 25 Ti 15 Hf 15 , alloying alters the fracture mode compared to elemental Nb, promoting crack tip blunting and enhancing resistance to crack propagation.

npj Computational MaterialsVol. 11(1)
Lawrence Berkeley National Laboratory (US), Virginia Tech (US), University of California, Berkeley (US)
U.S. Department of Energy, National Energy Research Scientific Computing Center, Office of Science, Basic Energy Sciences, Lawrence Berkeley National Laboratory
Openalex Percentile: Top 12%
Machine Learning in Materials Science
2.07
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