P. Kumar, F. Körmann, B. Grabowski, and Y. Ikeda. Dataset, (2025)Related to: P. Kumar, F. Körmann, B. Grabowski, Y. Ikeda, Machine learning potentials for hydrogen absorption in TiCr2 Laves phases, Acta Materialia (2025) 121319. doi: 10.1016/j.actamat.2025.121319.
M. Sung, T. Jang, S. Song, G. Lee, K. Ryou, S. Oh, B. Lee, P. Choi, J. Neugebauer, B. Grabowski and 4 other author(s). Journal of Materials Science & Technology, (August 2025)
L. Scholz, Y. Ou, B. Grabowski, and F. Fritzen. Dataset, (2025)Related to: L. Scholz, Y. Ou, B. Grabowski and F. Fritzen. A collapsed interface approach to resolve grain boundaries in finite element simulations of polycrystalline diffusion, Computational Materials Science 260 (2025), 114172. doi: 10.1016/j.commatsci.2025.114172.
X. Zhang, X. Xu, F. Körmann, S. Divinski, and B. Grabowski. Dataset, (2025)Related to: J. Zhang et al., "Lattice distortions and non-sluggish diffusion in BCC refractory high entropy alloys", Acta Materialia 297 (2025), 121283. doi: 10.1016/j.actamat.2025.121283.
Y. Ikeda, and F. Körmann. Dataset, (2025)Related to: Y. Ikeda and F. Körmann, Impact of N on the Stacking Fault Energy and Phase Stability of FCC CrMnFeCoNi: An Ab Initio Study, J. Phase Equilib. Diff. 42, 551 (2021). doi: 10.1007/s11669-021-00877-x.
A. Forslund, J. Jung, Y. Ikeda, and B. Grabowski. Dataset, (2025)Related to: A. Forslund, J. H. Jung, Y. Ikeda, and B. Grabowski, Free-energy perturbation in the exchange-correlation space accelerated by machine learning: Application to silica polymorphs, npj Comput. Mater. (2025). doi: 10.1038/s41524-025-01874-1.
G. Muralikrishna, S. Sen, S. Ayyappan, S. Sankaran, K. Guruvidyathri, J. Schell, L. Rogal, X. Zhang, J. Mayer, B. Grabowski and 2 other author(s). Journal of alloys and compounds, (2024)
L. Zhu, P. Srinivasan, Y. Gong, T. Hickel, B. Grabowski, F. Körmann, and J. Neugebauer. Physical review. B, Condensed matter and materials physics, 109 (9):
094110(2024)
P. Srinivasan, D. Demuriya, B. Grabowski, and A. Shapeev. Dataset, (2024)Related to: Srinivasan, P., Demuriya, D., Grabowski, B. et al. Electronic Moment Tensor Potentials include both electronic and vibrational degrees of freedom. npj Comput Mater 10, 41 (2024). doi: 10.1038/s41524-024-01222-9.
X. Zhang. Dataset, (2024)Related to: Zhang, X., Divinski, S.V. & Grabowski, B. Ab initio machine-learning unveils strong anharmonicity in non-Arrhenius self-diffusion of tungsten. Nat Commun 16, 394 (2025). doi: 10.1038/s41467-024-55759-w.
Y. Ou, Y. Ikeda, L. Scholz, S. Divinski, F. Fritzen, and B. Grabowski. Dataset, (2024)Related to: Yongliang Ou, Yuji Ikeda, Lena Scholz, Sergiy Divinski, Felix Fritzen, Blazej Grabowski (2024). Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials. arXiv: 2407.04126.
