<div class="csl-bib-body">
<div class="csl-entry">Lin, S., Holec, D., Sangiovanni, D. G., Leiner, T., Hultman, L., Mayrhofer, P. H., & Koutna, N. (2025). Shear-activated phase transformations of diborides via machine-learning potential molecular dynamics. <i>Acta Materialia</i>, <i>301</i>, Article 121606. https://doi.org/10.1016/j.actamat.2025.121606</div>
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dc.identifier.issn
1359-6454
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/225458
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dc.description.abstract
The layered character of transition metal diborides (TMB₂:s)—with three structure polymorphs representing different stackings of the metallic sublattice—evokes the possibility of activating phase-transformation plasticity via mechanical shear strain. This is critical to overcome the most severe limitation of TMB2:s: their brittleness. To understand finite-temperature mechanical response of the α,ω, and ᵞ polymorphs at the atomic scale, we train machine-learning interatomic potentials (MLIPs) for TMB₂:s, TM = (Ti, Ta, W, Re). Validation against ab initio data set supports the MLIPs’ capability to predict structural and elastic properties, as well as shear-induced slipping and phase transformations. Nanoscale molecular dynamics simulations (>10⁴ atoms; ≈ 5³ nm³
) allow evaluating theoretical shear strengths attainable in single-crystal TMB
:s and their temperature evolution from 300 up to 1200 K. Quantitative structural analysis via angular and bond-order Steinhardt parameter descriptors shows that (0001)[1210] and (0001)[1010] shearing activates transformations between the (energetically) metastable and the preferred phase of TiB₂, TaB₂, and WB₂. These transformations can be promoted by additional tensile or compressive strain along the [0001] axis. The preferred phase of ReB₂ shows negative thermal expansion and an unprecedented shear-induced plasticity mechanism: metallic/boron layer interpenetration and uniform lattice rotation.
en
dc.language.iso
en
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dc.publisher
PERGAMON-ELSEVIER SCIENCE LTD
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dc.relation.ispartof
Acta Materialia
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dc.subject
Machine learning
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dc.subject
interatomic potentials
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dc.subject
Molecular dynamics
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dc.subject
Diborides Shearing
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dc.subject
Phase transformation
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dc.title
Shear-activated phase transformations of diborides via machine-learning potential molecular dynamics