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Institute: search.filters.UBSInstitut.Institut für MaterialwissenschaftInstitute: search.filters.UBSInstitut.Fakultätsübergreifend / Sonstige EinrichtungStart date: 2025End date: 2025Author: search.filters.author.Grabowski, Blazej

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Now showing 1 - 3 of 3
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    Ab initio machine-learning unveils strong anharmonicity in non-Arrhenius self-diffusion of tungsten
    (2025) Zhang, Xi; Divinski, Sergiy V.; Grabowski, Blazej
    The knowledge of diffusion mechanisms in materials is crucial for predicting their high-temperature performance and stability, yet accurately capturing the underlying physics like thermal effects remains challenging. In particular, the origin of the experimentally observed non-Arrhenius diffusion behavior has remained elusive, largely due to the lack of effective computational tools. Here we propose an efficient ab initio framework to compute the Gibbs energy of the transition state in vacancy-mediated diffusion including the relevant thermal excitations at the density-functional-theory level. With the aid of a bespoke machine-learning interatomic potential, the temperature-dependent vacancy formation and migration Gibbs energies of the prototype system body-centered cubic (BCC) tungsten are shown to be strongly affected by anharmonicity. This finding explains the physical origin of the experimentally observed non-Arrhenius behavior of tungsten self-diffusion. A remarkable agreement between the calculated and experimental temperature-dependent self-diffusivity and, in particular, its curvature is revealed. The proposed computational framework is robust and broadly applicable, as evidenced by first tests for a hexagonal close-packed (HCP) multicomponent high-entropy alloy. The successful applications underscore the attainability of an accurate ab initio diffusion database.
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    Free-energy perturbation in the exchange-correlation space accelerated by machine learning : application to silica polymorphs
    (2025) Forslund, Axel; Jung, Jong Hyun; Ikeda, Yuji; Grabowski, Blazej
    We propose a free-energy-perturbation approach accelerated by machine-learning potentials to efficiently compute transition temperatures and entropies for all rungs of Jacob’s ladder. We apply the approach to the dynamically stabilized phases of SiO2, which are characterized by challengingly small transition entropies. All investigated functionals from rungs 1-4 fail to predict an accurate transition temperature by 25-200%. Only by ascending to the fifth rung, within the random phase approximation, an accurate prediction is possible, giving a relative error of 5%. We provide a clear-cut procedure and relevant data to the community for, e.g., developing and evaluating new functionals.
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    Machine learning potentials for hydrogen absorption in TiCr2 Laves phases
    (2025) Kumar, Pranav; Körmann, Fritz; Grabowski, Blazej; Ikeda, Yuji
    The energetics of hydrogen absorption in C15 cubic and C14 hexagonal TiCr2Hx Laves phases is investigated for 0 < x ≤ 6 with density functional theory (DFT) and machine learning interatomic potentials (MLIPs). The MLIPs are trained with configurations generated through a series of active-learning schemes. Basin-hopping Monte Carlo (BHMC) simulations based on the MLIPs predict minimum-energy hydrogen configurations, along with enthalpies of formation and hydrogen orderings. The obtained phase transformations at 0 K agree well with the experiments at low temperatures. The hydrogen solubility limits in the low-concentration 𝛼 phases at 0 K are predicted to be x = 1.0 and x = 1.5 for the C15 and the C14 phases, respectively. At these concentrations, C15 TiCr2H shows the 𝐶𝑐 monoclinic symmetry, while C14 TiCr2H1.5 shows the 𝐴𝑚𝑎2 orthorhombic symmetry, both of which have not been reported for this system. The first and the second hydride phases, i.e., 𝛽 and 𝛽′, at 0 K are found around x = 3 and x = 4, respectively, for both the C15 and the C14 phases. In the second-hydride 𝛽′ phases, C15 TiCr2H4 shows the 𝐼41∕𝑎 tetragonal symmetry, while C14 TiCr2H4 shows the 𝑅̄3𝑐 rhombohedral symmetry. Hydrogen repulsions are found to extend to edge-sharing interstices, affecting the hydrogen ordering. Furthermore, the 6h2 A2B2 interstices are found to be energetically substantially more preferable for C14 TiCr2Hx than the other A2B2 interstices at low hydrogen concentrations, influencing the hydrogen-occupation trend.