Materials 4.0

PN 3 A-4

Project description

Phase diagrams are fundamental to materials development. They provide the conditions for phase stabilities and transformations, and thereby a thorough thermodynamic understanding of materials. However, today’s phase diagrams are often based on scarce experimental input and rely on extrapolations. Ab initio approaches can provide useful complementary information, but they have been limited to zero-Kelvin or low-temperature approximations which are not representative for phase diagrams. Within the Materials 4.0 project, we utilize our unique expertise to develop and apply efficient statistical sampling techniques that are rooted in high-accuracy finite-temperature ab initio methods and are accelerated by machine learning potentials. These techniques facilitate an efficient and accurate determination of Gibbs energies and a wide range of other thermodynamic quantities. In particular the Gibbs energies constitute the fundamental input to the calculation of phase diagrams. With Materials 4.0, we thus provide an important contribution to the design of next-generation materials.

Project information

Project title Materials 4.0
Project leader Blazej Grabowski
Project staff

Jong Hyun Jung, doctoral researcher
Nikolay Zotov, postdoctoral researcher
Project duration January 2021-December 2025
Project number PN 3 A-4

Publications PN 3 A-4

  1. 2024

    1. L.-F. Zhu et al., “Melting properties of the refractory metals V and W and the binary VW alloy fully from first principles,” Physical Review B, vol. 109, Art. no. 9, Mar. 2024, doi: 10.1103/physrevb.109.094110.
    2. G. M. Muralikrishna et al., “Microstructure stability and self-diffusion in the equiatomic HfScTiZr HCP multi-principal element alloy,” Journal of Alloys and Compounds, vol. 976, p. 173196, Mar. 2024, doi: 10.1016/j.jallcom.2023.173196.
    3. N. Zotov, K. Gubaev, J. Wörner, and B. Grabowski, “Moment tensor potential for static and dynamic investigations of screw dislocations in bcc Nb,” Modelling and Simulation in Materials Science and Engineering, vol. 32, Art. no. 3, Mar. 2024, doi: 10.1088/1361-651x/ad2d68.
    4. P. Srinivasan, D. Demuriya, B. Grabowski, and A. Shapeev, “Electronic Moment Tensor Potentials include both electronic and vibrational degrees of freedom,” npj Computational Materials, vol. 10, Art. no. 1, Feb. 2024, doi: 10.1038/s41524-024-01222-9.
    5. S. Sen et al., “Sc diffusion in HCP high entropy alloys,” Scripta Materialia, vol. 242, p. 115917, Mar. 2024, doi: 10.1016/j.scriptamat.2023.115917.

  2. 2023

    1. S. Sen, X. Zhang, L. Rogal, G. Wilde, B. Grabowski, and S. V. Divinski, “Does Zn mimic diffusion of Al in the HCP Al-Sc-Hf-Ti-Zr high entropy alloys?,” Scripta Materialia, vol. 229, p. 115376, May 2023, doi: 10.1016/j.scriptamat.2023.115376.
    2. S. Perween et al., “Topochemical Fluorination of LaBaInO4 to LaBaInO3F2, Their Optical Characterization, and Photocatalytic Activities for Hydrogen Evolution,” Inorganic Chemistry, vol. 62, Art. no. 40, Sep. 2023, doi: 10.1021/acs.inorgchem.3c01682.
    3. S. Sen, X. Zhang, L. Rogal, G. Wilde, B. Grabowski, and S. V. Divinski, “‘Anti-sluggish’ Ti diffusion in HCP high-entropy alloys: Chemical complexity vs. lattice distortions,” Scripta Materialia, vol. 224, p. 115117, Feb. 2023, doi: 10.1016/j.scriptamat.2022.115117.
    4. J. H. Jung, A. Forslund, P. Srinivasan, and B. Grabowski, “Dynamically stabilized phases with full ab initio accuracy: Thermodynamics of Ti, Zr, Hf with a focus on the hcp-bcc transition,” Physical Review B, vol. 108, Art. no. 18, Nov. 2023, doi: 10.1103/physrevb.108.184107.
    5. I. Baker, B. Grabowski, S. V. Divinski, X. Zhang, and Y. Ikeda, “Interstitials in compositionally complex alloys,” MRS Bulletin, vol. 48, Art. no. 7, Jul. 2023, doi: 10.1557/s43577-023-00558-9.
    6. A. Forslund, J. H. Jung, P. Srinivasan, and B. Grabowski, “Thermodynamic properties on the homologous temperature scale from direct upsampling: Understanding electron-vibration coupling and thermal vacancies in bcc refractory metals,” Physical Review B, vol. 107, Art. no. 17, May 2023, doi: 10.1103/physrevb.107.174309.
    7. K. Gubaev, V. Zaverkin, P. Srinivasan, A. I. Duff, J. Kästner, and B. Grabowski, “Performance of two complementary machine-learned potentials in modelling chemically complex systems,” npj Computational Materials, vol. 9, Art. no. 1, Jul. 2023, doi: 10.1038/s41524-023-01073-w.
    8. K. Wissel et al., “Dissolution and Recrystallization Behavior of Li3PS4 in Different Organic Solvents with a Focus on N-Methylformamide,” ACS Applied Energy Materials, vol. 6, Art. no. 15, Jul. 2023, doi: 10.1021/acsaem.2c03278.
    9. J. H. Jung, P. Srinivasan, A. Forslund, and B. Grabowski, “High-accuracy thermodynamic properties to the melting point from ab initio calculations aided by machine-learning potentials,” npj Computational Materials, vol. 9, Art. no. 1, Jan. 2023, doi: 10.1038/s41524-022-00956-8.
    10. P. Srinivasan, A. Shapeev, J. Neugebauer, F. Körmann, and B. Grabowski, “Anharmonicity in bcc refractory elements: A detailed ab initio analysis,” Physical Review B, vol. 107, Art. no. 1, Jan. 2023, doi: 10.1103/physrevb.107.014301.

  3. 2022

    1. A. Dash et al., “Recent Advances in Understanding Diffusion in Multiprincipal Element Systems,” Annual Review of Materials Research, vol. 52, Art. no. 1, 2022, doi: 10.1146/annurev-matsci-081720-092213.
    2. Y. Ikeda, D. P. Estes, and B. Grabowski, “Comprehensive Understanding of H Adsorption on MoO3 from Systematic Ab Initio Simulations,” The Journal of Physical Chemistry C, vol. 126, Art. no. 17, Apr. 2022, doi: 10.1021/acs.jpcc.2c01085.
    3. I. Novikov, B. Grabowski, F. Körmann, and A. Shapeev, “Magnetic Moment Tensor Potentials for collinear spin-polarized materials reproduce different magnetic states of bcc Fe,” npj Computational Materials, vol. 8, Art. no. 1, Jan. 2022, doi: 10.1038/s41524-022-00696-9.
    4. N. Zotov and B. Grabowski, “Entropy of kink pair formation on screw dislocations: an accelerated molecular dynamics study,” Modelling and Simulation in Materials Science and Engineering, vol. 30, Art. no. 6, Jun. 2022, doi: 10.1088/1361-651x/ac7ac9.
    5. Y. Zhou et al., “Thermodynamics up to the melting point in a TaVCrW high entropy alloy: Systematic ab initio study aided by machine learning potentials,” Physical Review B, vol. 105, Art. no. 21, Jun. 2022, doi: 10.1103/physrevb.105.214302.
    6. X. Zhang, S. V. Divinski, and B. Grabowski, “Ab initio prediction of vacancy energetics in HCP Al-Hf-Sc-Ti-Zr high entropy alloys and the subsystems,” Acta Materialia, vol. 227, p. 117677, Apr. 2022, doi: 10.1016/j.actamat.2022.117677.
    7. Y. Ou, Y. Ikeda, O. Clemens, and B. Grabowski, “Dynamic stabilization of perovskites at elevated temperatures: A comparison between cubic BaFeO3 and vacancy-ordered monoclinic BaFeO2.67,” Physical Review B, vol. 106, Art. no. 6, Aug. 2022, doi: 10.1103/physrevb.106.064308.
    8. R. U. Stelzer, Y. Ikeda, P. Srinivasan, T. S. Lehmann, B. Grabowski, and R. Niewa, “Li5Sn, the Most Lithium-Rich Binary Stannide: A Combined Experimental and Computational Study,” Journal of the American Chemical Society, vol. 144, Art. no. 16, Apr. 2022, doi: 10.1021/jacs.1c10640.
    9. J. S. Lee, W.-S. Ko, and B. Grabowski, “Atomistic simulations of the deformation behavior of an Nb nanowire embedded in a NiTi shape memory alloy,” Acta Materialia, vol. 228, p. 117764, Apr. 2022, doi: 10.1016/j.actamat.2022.117764.

  4. 2021

    1. A. Forslund, X. Zhang, B. Grabowski, A. V. Shapeev, and A. V. Ruban, “Ab initio simulations of the surface free energy of TiN(001),” Physical Review B, vol. 103, Art. no. 19, 2021, doi: 10.1103/PhysRevB.103.195428.
    2. K. Gubaev et al., “Finite-temperature interplay of structural stability, chemical complexity, and elastic properties of bcc multicomponent alloys from ab initio trained machine-learning potentials,” Physical Review Materials, vol. 5, Art. no. 7, 2021, doi: 10.1103/PhysRevMaterials.5.073801.
To the top of the page